diff --git a/.cproject b/.cproject index efdaf0c8a..df6fdc5f5 100644 --- a/.cproject +++ b/.cproject @@ -35,10 +35,6 @@ @@ -285,6 +281,8 @@ + + @@ -439,156 +437,18 @@ true true - + make - -j2 - check + -j5 + testPoseRTV.run true true true - + make - -j2 - testGaussianFactorGraph.run - true - true - true - - - make - -j2 - testGaussianISAM.run - true - true - true - - - make - testGraph.run - true - false - true - - - make - -j2 - testIterative.run - true - true - true - - - make - -j2 - testNonlinearEquality.run - true - true - true - - - make - -j2 - testNonlinearFactor.run - true - true - true - - - make - -j2 - testNonlinearFactorGraph.run - true - true - true - - - make - -j2 - testNonlinearOptimizer.run - true - true - true - - - make - -j2 - testSubgraphPreconditioner.run - true - true - true - - - make - -j2 - testTupleConfig.run - true - true - true - - - make - -j2 - timeGaussianFactorGraph.run - true - true - true - - - make - testInference.run - true - false - true - - - make - testGaussianFactor.run - true - false - true - - - make - testJunctionTree.run - true - false - true - - - make - testSymbolicBayesNet.run - true - false - true - - - make - testSymbolicFactorGraph.run - true - false - true - - - make - -j2 - clean - true - true - true - - - make - -j2 - testGaussianJunctionTree - true - true - true - - - make - -j2 - testSerialization.run + -j5 + testIMUSystem.run true true true @@ -745,34 +605,82 @@ true true - + make - -j2 - tests/testGeneralSFMFactor.run + -j5 + testGeneralSFMFactor.run true true true - + make - -j2 - tests/testPlanarSLAM.run + -j5 + testPlanarSLAM.run true true true - + make - -j2 - tests/testPose2SLAM.run + -j5 + testPose2SLAM.run true true true - + make - -j2 - tests/testPose3SLAM.run + -j5 + testPose3SLAM.run + true + true + true + + + make + -j5 + testSimulated2D.run + true + true + true + + + make + -j5 + testSimulated2DOriented.run + true + true + true + + + make + -j5 + testVisualSLAM.run + true + true + true + + + make + -j5 + testProjectionFactor.run + true + true + true + + + make + -j5 + testSerializationSLAM.run + true + true + true + + + make + -j5 + testGeneralSFMFactor_Cal3Bundler.run true true true @@ -793,6 +701,14 @@ true true + + make + -j5 + testKey.run + true + true + true + make -j5 @@ -865,6 +781,30 @@ true true + + make + -j5 + testInvDepthFactor3.run + true + true + true + + + make + -j5 + testPoseTranslationPrior.run + true + true + true + + + make + -j5 + testPoseRotationPrior.run + true + true + true + make -j5 @@ -873,6 +813,22 @@ true true + + make + -j5 + testDiscreteMarginals.run + true + true + true + + + make + -j5 + testInference.run + true + true + true + make -j2 @@ -881,6 +837,14 @@ true true + + make + -j5 + testInvDepthCamera3.run + true + true + true + make -j2 @@ -897,22 +861,6 @@ true true - - make - -j2 - testGaussianJunctionTree.run - true - true - true - - - make - -j2 - testGaussianFactorGraph.run - true - true - true - make -j2 @@ -921,42 +869,26 @@ true true - + make - -j2 - testTupleConfig.run + -j5 + testMarginals.run true true true - + make - -j2 - testSerialization.run + -j5 + testGaussianISAM2.run true true true - + make - -j2 - testInference.run - true - true - true - - - make - -j2 - testGaussianISAM.run - true - true - true - - - make - -j2 - testSymbolicFactorGraph.run + -j5 + testSymbolicFactorGraphB.run true true true @@ -969,10 +901,10 @@ true true - + make - -j2 - testNonlinearFactorGraph.run + -j5 + testGradientDescentOptimizer.run true true true @@ -985,14 +917,6 @@ true true - - make - -j2 - testPose2SLAMwSPCG.run - true - true - true - make -j2 @@ -1017,14 +941,6 @@ true true - - make - -j5 - tests.testBoundingConstraint.run - true - true - true - make -j2 @@ -1049,6 +965,118 @@ true true + + make + -j5 + testNonlinearFactor.run + true + true + true + + + make + -j5 + clean + true + true + true + + + make + -j5 + testGaussianJunctionTreeB.run + true + true + true + + + make + + testGraph.run + true + false + true + + + make + + testJunctionTree.run + true + false + true + + + make + + testSymbolicBayesNetB.run + true + false + true + + + make + -j5 + testGaussianISAM.run + true + true + true + + + make + -j5 + testDoglegOptimizer.run + true + true + true + + + make + -j5 + testNonlinearFactorGraph.run + true + true + true + + + make + -j5 + testIterative.run + true + true + true + + + make + -j5 + testSubgraphSolver.run + true + true + true + + + make + -j5 + testGaussianFactorGraphB.run + true + true + true + + + make + -j5 + clean + true + true + true + + + make + -j5 + all + true + true + true + make -j2 @@ -1185,6 +1213,14 @@ true true + + make + -j5 + testLinearContainerFactor.run + true + true + true + make -j2 @@ -1513,6 +1549,14 @@ true true + + make + -j5 + testSimpleCamera.run + true + true + true + make -j2 @@ -1742,18 +1786,18 @@ true true - + make - -j2 - CameraResectioning + -j5 + CameraResectioning.run true true true - + make - -j2 - PlanarSLAMExample_easy.run + -j5 + PlanarSLAMExample.run true true true @@ -1782,26 +1826,10 @@ true true - + make - -j2 - PlanarSLAMSelfContained_advanced.run - true - true - true - - - make - -j2 - Pose2SLAMExample_advanced.run - true - true - true - - - make - -j2 - Pose2SLAMExample_easy.run + -j5 + Pose2SLAMExample.run true true true @@ -1822,6 +1850,22 @@ true true + + make + -j5 + LocalizationExample.run + true + true + true + + + make + -j5 + OdometryExample.run + true + true + true + make -j2 @@ -1855,10 +1899,10 @@ make - -j2 + -j1 install true - true + false true @@ -1869,12 +1913,12 @@ true true - + make - -j5 + -j1 check true - true + false true @@ -2092,6 +2136,126 @@ true true + + make + -j5 + check.discrete_unstable + true + true + true + + + make + -j5 + check.base_unstable + true + true + true + + + make + -j5 + check.dynamics_unstable + true + true + true + + + make + -j5 + check.slam_unstable + true + true + true + + + make + -j5 + check.unstable + true + true + true + + + make + -j5 + wrap_gtsam_build + true + true + true + + + make + -j5 + wrap_gtsam_unstable_build + true + true + true + + + make + -j5 + wrap_gtsam_unstable + true + true + true + + + make + -j5 + wrap + true + true + true + + + make + -j5 + check.nonlinear_unstable + true + true + true + + + make + -j5 + wrap_gtsam_distclean + true + true + true + + + make + -j5 + wrap_gtsam_unstable_distclean + true + true + true + + + make + -j5 + doc + true + true + true + + + make + -j5 + doc_clean + true + true + true + + + make + -j5 + check + true + true + true + make -j2 @@ -2227,18 +2391,18 @@ false true - + make -j5 - wrap.testSpirit.run + testSpirit.run true true true - + make -j5 - wrap.testWrap.run + testWrap.run true true true @@ -2251,14 +2415,6 @@ true true - - make - -j5 - wrap_gtsam - true - true - true - make -j5 diff --git a/.settings/org.eclipse.cdt.core.prefs b/.settings/org.eclipse.cdt.core.prefs deleted file mode 100644 index a915be654..000000000 --- a/.settings/org.eclipse.cdt.core.prefs +++ /dev/null @@ -1,6 +0,0 @@ -#Wed Oct 06 11:57:41 EDT 2010 -eclipse.preferences.version=1 -environment/project/cdt.managedbuild.toolchain.gnu.macosx.base.1359703544.1441575890/append=true -environment/project/cdt.managedbuild.toolchain.gnu.macosx.base.1359703544.1441575890/appendContributed=true -environment/project/cdt.managedbuild.toolchain.gnu.macosx.base.1359703544/append=true -environment/project/cdt.managedbuild.toolchain.gnu.macosx.base.1359703544/appendContributed=true diff --git a/CMakeLists.txt b/CMakeLists.txt index e6c9bc422..6b7ce4599 100644 --- a/CMakeLists.txt +++ b/CMakeLists.txt @@ -1,16 +1,26 @@ + project(GTSAM CXX C) cmake_minimum_required(VERSION 2.6) # Set the version number for the library set (GTSAM_VERSION_MAJOR 2) -set (GTSAM_VERSION_MINOR 0) +set (GTSAM_VERSION_MINOR 1) set (GTSAM_VERSION_PATCH 0) # Set the default install path to home #set (CMAKE_INSTALL_PREFIX ${HOME} CACHE PATH "Install prefix for library") +set(CMAKE_MODULE_PATH "${CMAKE_MODULE_PATH}" "${CMAKE_CURRENT_SOURCE_DIR}/cmake") +include(GtsamMakeConfigFile) + +# Record the root dir for gtsam - needed during external builds, e.g., ROS +set(GTSAM_SOURCE_ROOT_DIR ${CMAKE_CURRENT_SOURCE_DIR}) +message(STATUS "GTSAM_SOURCE_ROOT_DIR: [${GTSAM_SOURCE_ROOT_DIR}]") + +# Load build type flags and default to Debug mode +include(GtsamBuildTypes) + # Use macros for creating tests/timing scripts -set(CMAKE_MODULE_PATH "${CMAKE_MODULE_PATH}" "${PROJECT_SOURCE_DIR}/cmake") include(GtsamTesting) include(GtsamPrinting) @@ -26,40 +36,46 @@ else() set(GTSAM_UNSTABLE_AVAILABLE 0) endif() -# Load build type flags and default to Debug mode -include(GtsamBuildTypes) - -# Check build types -if(${CMAKE_MAJOR_VERSION}.${CMAKE_MINOR_VERSION} VERSION_GREATER 2.8 OR ${CMAKE_MAJOR_VERSION}.${CMAKE_MINOR_VERSION} VERSION_EQUAL 2.8) - set_property(CACHE CMAKE_BUILD_TYPE PROPERTY STRINGS None Debug Release Timing Profiling RelWithDebInfo MinSizeRel) -endif() -string(TOLOWER "${CMAKE_BUILD_TYPE}" cmake_build_type_tolower) -if( NOT cmake_build_type_tolower STREQUAL "" - AND NOT cmake_build_type_tolower STREQUAL "none" - AND NOT cmake_build_type_tolower STREQUAL "debug" - AND NOT cmake_build_type_tolower STREQUAL "release" - AND NOT cmake_build_type_tolower STREQUAL "timing" - AND NOT cmake_build_type_tolower STREQUAL "profiling" - AND NOT cmake_build_type_tolower STREQUAL "relwithdebinfo") - message(FATAL_ERROR "Unknown build type \"${CMAKE_BUILD_TYPE}\". Allowed values are None, Debug, Release, Timing, Profiling, RelWithDebInfo (case-insensitive).") -endif() - # Configurable Options option(GTSAM_BUILD_TESTS "Enable/Disable building of tests" ON) -option(GTSAM_BUILD_TIMING "Enable/Disable building of timing scripts" ON) +#option(GTSAM_BUILD_TIMING "Enable/Disable building of timing scripts" ON) # These do not currently work option(GTSAM_BUILD_EXAMPLES "Enable/Disable building of examples" ON) if(GTSAM_UNSTABLE_AVAILABLE) - option(GTSAM_BUILD_UNSTABLE "Enable/Disable libgtsam_unstable" OFF) + option(GTSAM_BUILD_UNSTABLE "Enable/Disable libgtsam_unstable" ON) +endif() +if(NOT MSVC) + option(GTSAM_BUILD_SHARED_LIBRARY "Enable/Disable building of a shared version of gtsam" ON) + option(GTSAM_BUILD_STATIC_LIBRARY "Enable/Disable building of a static version of gtsam" ON) +else() + set(GTSAM_BUILD_STATIC_LIBRARY ON) endif() -option(GTSAM_BUILD_WRAP "Enable/Disable building of matlab wrap utility (necessary for matlab interface)" ON) -option(GTSAM_BUILD_SHARED_LIBRARY "Enable/Disable building of a shared version of gtsam" ON) -option(GTSAM_BUILD_STATIC_LIBRARY "Enable/Disable building of a static version of gtsam" ON) option(GTSAM_USE_QUATERNIONS "Enable/Disable using an internal Quaternion representation for rotations instead of rotation matrices" OFF) -option(GTSAM_BUILD_CONVENIENCE_LIBRARIES "Enable/Disable use of convenience libraries for faster development rebuilds, but slower install" ON) -option(GTSAM_INSTALL_MATLAB_TOOLBOX "Enable/Disable installation of matlab toolbox" ON) -option(GTSAM_INSTALL_MATLAB_EXAMPLES "Enable/Disable installation of matlab examples" ON) -option(GTSAM_INSTALL_MATLAB_TESTS "Enable/Disable installation of matlab tests" ON) -option(GTSAM_INSTALL_WRAP "Enable/Disable installation of wrap utility" ON) +if(NOT MSVC) + option(GTSAM_BUILD_CONVENIENCE_LIBRARIES "Enable/Disable use of convenience libraries for faster development rebuilds, but slower install" ON) +endif() + + +# Options relating to MATLAB wrapper +# TODO: Check for matlab mex binary before handling building of binaries +option(GTSAM_INSTALL_MATLAB_TOOLBOX "Enable/Disable installation of matlab toolbox" OFF) +option(GTSAM_BUILD_WRAP "Enable/Disable building of matlab wrap utility (necessary for matlab interface)" ON) +option(GTSAM_INSTALL_WRAP "Enable/Disable installation of wrap utility for wrapping other libraries" ON) +set(GTSAM_TOOLBOX_INSTALL_PATH "" CACHE PATH "Matlab toolbox destination, blank defaults to CMAKE_INSTALL_PREFIX/borg/toolbox") +set(GTSAM_BUILD_MEX_BINARY_FLAGS "" CACHE STRING "Extra flags for running Matlab MEX compilation") +set(MEX_COMMAND "mex" CACHE FILEPATH "Command to use for executing mex (if on path, 'mex' will work)") + +# Check / set dependent variables for MATLAB wrapper +set(GTSAM_WRAP_HEADER_PATH "${PROJECT_SOURCE_DIR}/wrap") +if(GTSAM_INSTALL_MATLAB_TOOLBOX AND NOT GTSAM_BUILD_WRAP) + message(FATAL_ERROR "GTSAM_INSTALL_MATLAB_TOOLBOX is enabled, please also enable GTSAM_BUILD_WRAP") +endif() +if(GTSAM_INSTALL_WRAP AND NOT GTSAM_BUILD_WRAP) + message(FATAL_ERROR "GTSAM_INSTALL_WRAP is enabled, please also enable GTSAM_BUILD_WRAP") +endif() +if(NOT GTSAM_TOOLBOX_INSTALL_PATH) + set(GTSAM_TOOLBOX_INSTALL_PATH "${CMAKE_INSTALL_PREFIX}/borg/toolbox") +endif() + # Flags for choosing default packaging tools set(CPACK_SOURCE_GENERATOR "TGZ" CACHE STRING "CPack Default Source Generator") @@ -72,18 +88,14 @@ endif() # Add the Quaternion Build Flag if requested if (GTSAM_USE_QUATERNIONS) - set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -DGTSAM_DEFAULT_QUATERNIONS") - set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -DGTSAM_DEFAULT_QUATERNIONS") + set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -DGTSAM_DEFAULT_QUATERNIONS") + set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -DGTSAM_DEFAULT_QUATERNIONS") endif(GTSAM_USE_QUATERNIONS) -# Avoid building non-installed exes and unit tests when installing -# FIXME: breaks generation and install of matlab toolbox -# FIXME: can't add install dependencies, so libraries never get built -#set(CMAKE_SKIP_INSTALL_ALL_DEPENDENCY TRUE) - -# Alternative version to keep tests from building during make install -# Use the EXCLUDE_FROM_ALL property on test executables -option(GTSAM_ENABLE_INSTALL_TEST_FIX "Enable/Disable fix to remove dependency of tests on 'all' target" ON) +# Flags to determine whether tests and examples are build during 'make install' +# Note that these remove the targets from the 'all' +option(GTSAM_DISABLE_TESTS_ON_INSTALL "Disables building tests during install" ON) +option(GTSAM_DISABLE_EXAMPLES_ON_INSTALL "Disables building examples during install" OFF) # Pull in infrastructure if (GTSAM_BUILD_TESTS) @@ -93,7 +105,11 @@ if (GTSAM_BUILD_TESTS) endif() # Find boost -find_package(Boost 1.40 COMPONENTS serialization REQUIRED) +if(CYGWIN OR MSVC OR WIN32) + set(Boost_USE_STATIC_LIBS 1) +endif() +find_package(Boost 1.43 COMPONENTS serialization system filesystem thread date_time regex REQUIRED) +set(GTSAM_BOOST_LIBRARIES ${Boost_SERIALIZATION_LIBRARY} ${Boost_SYSTEM_LIBRARY} ${Boost_FILESYSTEM_LIBRARY}) # General build settings include_directories( @@ -107,28 +123,45 @@ link_directories(${Boost_LIBRARY_DIRS}) # Build CppUnitLite add_subdirectory(CppUnitLite) +# Build wrap +if (GTSAM_BUILD_WRAP) + add_subdirectory(wrap) +endif(GTSAM_BUILD_WRAP) + # Build GTSAM library add_subdirectory(gtsam) # Build Tests add_subdirectory(tests) -# Build wrap -if (GTSAM_BUILD_WRAP) - add_subdirectory(wrap) -endif(GTSAM_BUILD_WRAP) - # Build examples if (GTSAM_BUILD_EXAMPLES) add_subdirectory(examples) endif(GTSAM_BUILD_EXAMPLES) +# Matlab toolbox +if (GTSAM_INSTALL_MATLAB_TOOLBOX) + add_subdirectory(matlab) +endif() + # Build gtsam_unstable if (GTSAM_BUILD_UNSTABLE) add_subdirectory(gtsam_unstable) endif(GTSAM_BUILD_UNSTABLE) -# Set up CPack +# Install config and export files +GtsamMakeConfigFile(GTSAM) +export(TARGETS ${GTSAM_EXPORTED_TARGETS} FILE GTSAM-exports.cmake) + +# Check for doxygen availability - optional dependency +find_package(Doxygen) + +# Doxygen documentation - enabling options in subfolder +if (DOXYGEN_FOUND) + add_subdirectory(doc) +endif() + +## Set up CPack set(CPACK_PACKAGE_DESCRIPTION_SUMMARY "GTSAM") set(CPACK_PACKAGE_VENDOR "Frank Dellaert, Georgia Institute of Technology") set(CPACK_PACKAGE_CONTACT "Frank Dellaert, dellaert@cc.gatech.edu") @@ -138,30 +171,39 @@ set(CPACK_PACKAGE_VERSION_MAJOR ${GTSAM_VERSION_MAJOR}) set(CPACK_PACKAGE_VERSION_MINOR ${GTSAM_VERSION_MINOR}) set(CPACK_PACKAGE_VERSION_PATCH ${GTSAM_VERSION_PATCH}) set(CPACK_PACKAGE_INSTALL_DIRECTORY "CMake ${CMake_VERSION_MAJOR}.${CMake_VERSION_MINOR}") -set(CPACK_INSTALLED_DIRECTORIES "doc;.") # Include doc directory -set(CPACK_SOURCE_IGNORE_FILES "/build;/\\\\.;/makedoc.sh$;/gtsam_unstable/") +#set(CPACK_INSTALLED_DIRECTORIES "doc;.") # Include doc directory +#set(CPACK_INSTALLED_DIRECTORIES ".") # FIXME: throws error +set(CPACK_SOURCE_IGNORE_FILES "/build*;/\\\\.;/makestats.sh$") +set(CPACK_SOURCE_IGNORE_FILES "${CPACK_SOURCE_IGNORE_FILES}" "/gtsam_unstable/") +set(CPACK_SOURCE_IGNORE_FILES "${CPACK_SOURCE_IGNORE_FILES}" "/package_scripts/") set(CPACK_SOURCE_PACKAGE_FILE_NAME "gtsam-${GTSAM_VERSION_MAJOR}.${GTSAM_VERSION_MINOR}.${GTSAM_VERSION_PATCH}") #set(CPACK_SOURCE_PACKAGE_FILE_NAME "gtsam-aspn${GTSAM_VERSION_PATCH}") # Used for creating ASPN tarballs -# Record the root dir for gtsam - needed during external builds, e.g., ROS -set(GTSAM_SOURCE_ROOT_DIR ${CMAKE_CURRENT_SOURCE_DIR}) -message(STATUS "GTSAM_SOURCE_ROOT_DIR: [${GTSAM_SOURCE_ROOT_DIR}]") +# Deb-package specific cpack +set(CPACK_DEBIAN_PACKAGE_NAME "libgtsam-dev") +set(CPACK_DEBIAN_PACKAGE_DEPENDS "libboost-dev (>= 1.43)") #Example: "libc6 (>= 2.3.1-6), libgcc1 (>= 1:3.4.2-12)") # print configuration variables message(STATUS "===============================================================") message(STATUS "================ Configuration Options ======================") message(STATUS "Build flags ") -print_config_flag(${GTSAM_BUILD_TIMING} "Build Timing scripts ") +#print_config_flag(${GTSAM_BUILD_TIMING} "Build Timing scripts ") print_config_flag(${GTSAM_BUILD_EXAMPLES} "Build Examples ") print_config_flag(${GTSAM_BUILD_TESTS} "Build Tests ") -print_config_flag(${GTSAM_BUILD_WRAP} "Build Wrap ") -print_config_flag(${GTSAM_BUILD_SHARED_LIBRARY} "Build shared GTSAM Library ") -print_config_flag(${GTSAM_BUILD_STATIC_LIBRARY} "Build static GTSAM Library ") -print_config_flag(${GTSAM_BUILD_CONVENIENCE_LIBRARIES} "Build Convenience Libraries ") -if(GTSAM_UNSTABLE_AVAILABLE) - print_config_flag(${GTSAM_BUILD_UNSTABLE} "Build libgtsam_unstable ") +if (DOXYGEN_FOUND) + print_config_flag(${GTSAM_BUILD_DOCS} "Build Docs ") endif() -print_config_flag(${GTSAM_ENABLE_INSTALL_TEST_FIX} "Tests excluded from all target ") +if(NOT MSVC) + print_config_flag(${GTSAM_BUILD_SHARED_LIBRARY} "Build shared GTSAM Library ") + print_config_flag(${GTSAM_BUILD_STATIC_LIBRARY} "Build static GTSAM Library ") + print_config_flag(${GTSAM_BUILD_CONVENIENCE_LIBRARIES} "Build Convenience Libraries ") +endif() +print_config_flag(${GTSAM_BUILD_TYPE_POSTFIXES} "Put build-type in library name ") +if(GTSAM_UNSTABLE_AVAILABLE) + print_config_flag(${GTSAM_BUILD_UNSTABLE} "Build libgtsam_unstable ") +endif() +print_config_flag(${GTSAM_DISABLE_TESTS_ON_INSTALL} "Tests excluded from all/install target ") +print_config_flag(${GTSAM_DISABLE_EXAMPLES_ON_INSTALL} "Examples excluded from all/install target ") string(TOUPPER "${CMAKE_BUILD_TYPE}" cmake_build_type_toupper) message(STATUS " Build type : ${CMAKE_BUILD_TYPE}") message(STATUS " C compilation flags : ${CMAKE_C_FLAGS} ${CMAKE_C_FLAGS_${cmake_build_type_toupper}}") @@ -176,8 +218,7 @@ print_config_flag(${GTSAM_USE_QUATERNIONS} "Quaternions as default R message(STATUS "MATLAB toolbox flags ") print_config_flag(${GTSAM_INSTALL_MATLAB_TOOLBOX} "Install matlab toolbox ") -print_config_flag(${GTSAM_INSTALL_MATLAB_EXAMPLES} "Install matlab examples ") -print_config_flag(${GTSAM_INSTALL_MATLAB_TESTS} "Install matlab tests ") +print_config_flag(${GTSAM_BUILD_WRAP} "Build Wrap ") print_config_flag(${GTSAM_INSTALL_WRAP} "Install wrap utility ") message(STATUS "===============================================================") diff --git a/CppUnitLite/CMakeLists.txt b/CppUnitLite/CMakeLists.txt index 642e8e462..35ecd71f8 100644 --- a/CppUnitLite/CMakeLists.txt +++ b/CppUnitLite/CMakeLists.txt @@ -3,10 +3,14 @@ file(GLOB cppunitlite_headers "*.h") file(GLOB cppunitlite_src "*.cpp") -add_library(CppUnitLite STATIC ${cppunitlite_src}) +add_library(CppUnitLite STATIC ${cppunitlite_src} ${cppunitlite_headers}) +list(APPEND GTSAM_EXPORTED_TARGETS CppUnitLite) +set(GTSAM_EXPORTED_TARGETS "${GTSAM_EXPORTED_TARGETS}" PARENT_SCOPE) + +gtsam_assign_source_folders("${cppunitlite_headers};${cppunitlite_src}") # MSVC project structure option(GTSAM_INSTALL_CPPUNITLITE "Enable/Disable installation of CppUnitLite library" ON) if (GTSAM_INSTALL_CPPUNITLITE) install(FILES ${cppunitlite_headers} DESTINATION include/CppUnitLite) - install(TARGETS CppUnitLite ARCHIVE DESTINATION lib) + install(TARGETS CppUnitLite EXPORT GTSAM-exports ARCHIVE DESTINATION lib) endif(GTSAM_INSTALL_CPPUNITLITE) diff --git a/CppUnitLite/Failure.cpp b/CppUnitLite/Failure.cpp deleted file mode 100644 index d0c919165..000000000 --- a/CppUnitLite/Failure.cpp +++ /dev/null @@ -1,71 +0,0 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) - - * See LICENSE for the license information - - * -------------------------------------------------------------------------- */ - - - -#include "Failure.h" - -#include -#include - - -Failure::Failure (const SimpleString& theTestName, - const SimpleString& theFileName, - long theLineNumber, - const SimpleString& theCondition) -: message (theCondition), - testName (theTestName), - fileName (theFileName), - lineNumber (theLineNumber) -{ -} - -Failure::Failure (const SimpleString& theTestName, - const SimpleString& theFileName, - const SimpleString& theCondition) -: message (theCondition), - testName (theTestName), - fileName (theFileName), - lineNumber (-1) -{ -} - - -Failure::Failure (const SimpleString& theTestName, - const SimpleString& theFileName, - long theLineNumber, - const SimpleString& expected, - const SimpleString& actual) -: testName (theTestName), - fileName (theFileName), - lineNumber (theLineNumber) -{ - const char *part1 = "expected "; - const char *part3 = " but was: "; - - char *stage = new char [strlen (part1) - + expected.size () - + strlen (part3) - + actual.size () - + 1]; - - sprintf(stage, "%s%s%s%s", - part1, - expected.asCharString(), - part3, - actual.asCharString()); - - message = SimpleString(stage); - - delete stage; -} - - diff --git a/CppUnitLite/Failure.h b/CppUnitLite/Failure.h index 1f898f08c..93c99df12 100644 --- a/CppUnitLite/Failure.h +++ b/CppUnitLite/Failure.h @@ -21,37 +21,50 @@ /////////////////////////////////////////////////////////////////////////////// -#ifndef FAILURE_H -#define FAILURE_H - -#include "SimpleString.h" +#pragma once +#include class Failure { public: - Failure (const SimpleString& theTestName, - const SimpleString& theFileName, - long theLineNumber, - const SimpleString& theCondition); + Failure (const std::string& theTestName, + const std::string& theFileName, + long theLineNumber, + const std::string& theCondition) + : message (theCondition), + testName (theTestName), + fileName (theFileName), + lineNumber (theLineNumber) + { + } - Failure (const SimpleString& theTestName, - const SimpleString& theFileName, - long theLineNumber, - const SimpleString& expected, - const SimpleString& actual); - - Failure (const SimpleString& theTestName, - const SimpleString& theFileName, - const SimpleString& theCondition); + Failure (const std::string& theTestName, + const std::string& theFileName, + const std::string& theCondition) + : message (theCondition), + testName (theTestName), + fileName (theFileName), + lineNumber (-1) + { + } - SimpleString message; - SimpleString testName; - SimpleString fileName; + Failure (const std::string& theTestName, + const std::string& theFileName, + long theLineNumber, + const std::string& expected, + const std::string& actual) + : message("expected " + expected + " but was: " + actual), + testName (theTestName), + fileName (theFileName), + lineNumber (theLineNumber) + { + } + + std::string message; + std::string testName; + std::string fileName; long lineNumber; }; - - -#endif diff --git a/CppUnitLite/SimpleString.cpp b/CppUnitLite/SimpleString.cpp deleted file mode 100644 index 19dc7f258..000000000 --- a/CppUnitLite/SimpleString.cpp +++ /dev/null @@ -1,115 +0,0 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) - - * See LICENSE for the license information - - * -------------------------------------------------------------------------- */ - - - -#include "SimpleString.h" -#include -#include -#include - - -static const int DEFAULT_SIZE = 20; - -SimpleString::SimpleString () -: buffer_(new char [1]) -{ - buffer_ [0] = '\0'; -} - - -SimpleString::SimpleString (const char *otherBuffer) -: buffer_ (new char [strlen (otherBuffer) + 1]) -{ - strcpy (buffer_, otherBuffer); -} - -SimpleString::SimpleString (const SimpleString& other) -{ - buffer_ = new char [other.size() + 1]; - strcpy(buffer_, other.buffer_); -} - - -SimpleString SimpleString::operator= (const SimpleString& other) -{ - delete buffer_; - buffer_ = new char [other.size() + 1]; - strcpy(buffer_, other.buffer_); - return *this; -} - -SimpleString SimpleString::operator+ (const SimpleString& other) -{ - SimpleString ret; - delete ret.buffer_; - ret.buffer_ = new char [size() + other.size() - 1]; - strcpy(ret.buffer_, buffer_); - strcat(ret.buffer_, other.buffer_); - return ret; -} - -char *SimpleString::asCharString () const -{ - return buffer_; -} - -int SimpleString::size() const -{ - return strlen (buffer_); -} - -SimpleString::~SimpleString () -{ - delete [] buffer_; -} - - -bool operator== (const SimpleString& left, const SimpleString& right) -{ - return !strcmp (left.asCharString (), right.asCharString ()); -} - - -SimpleString StringFrom (bool value) -{ - char buffer [sizeof ("false") + 1]; - sprintf (buffer, "%s", value ? "true" : "false"); - return SimpleString(buffer); -} - -SimpleString StringFrom (const char *value) -{ - return SimpleString(value); -} - -SimpleString StringFrom (long value) -{ - char buffer [DEFAULT_SIZE]; - sprintf (buffer, "%ld", value); - - return SimpleString(buffer); -} - -SimpleString StringFrom (double value) -{ - char buffer [DEFAULT_SIZE]; - sprintf (buffer, "%lg", value); - - return SimpleString(buffer); -} - -SimpleString StringFrom (const SimpleString& value) -{ - return SimpleString(value); -} - - diff --git a/CppUnitLite/SimpleString.h b/CppUnitLite/SimpleString.h deleted file mode 100644 index c454e5571..000000000 --- a/CppUnitLite/SimpleString.h +++ /dev/null @@ -1,57 +0,0 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) - - * See LICENSE for the license information - - * -------------------------------------------------------------------------- */ - - -/////////////////////////////////////////////////////////////////////////////// -// -// SIMPLESTRING.H -// -// One of the design goals of CppUnitLite is to compilation with very old C++ -// compilers. For that reason, I've added a simple string class that provides -// only the operations needed in CppUnitLite. -// -/////////////////////////////////////////////////////////////////////////////// - -#ifndef SIMPLE_STRING -#define SIMPLE_STRING - - - -class SimpleString -{ - friend bool operator== (const SimpleString& left, const SimpleString& right); - -public: - SimpleString (); - SimpleString (const char *value); - SimpleString (const SimpleString& other); - ~SimpleString (); - - SimpleString operator= (const SimpleString& other); - SimpleString operator+ (const SimpleString& other); - - char *asCharString () const; - int size() const; - -private: - char *buffer_; -}; - - - -SimpleString StringFrom (bool value); -SimpleString StringFrom (const char *value); -SimpleString StringFrom (long value); -SimpleString StringFrom (double value); -SimpleString StringFrom (const SimpleString& other); - - -#endif diff --git a/CppUnitLite/Test.cpp b/CppUnitLite/Test.cpp index 1d9902b37..e6a2ad51f 100644 --- a/CppUnitLite/Test.cpp +++ b/CppUnitLite/Test.cpp @@ -10,21 +10,21 @@ * -------------------------------------------------------------------------- */ - #include "Test.h" #include "TestRegistry.h" #include "TestResult.h" #include "Failure.h" +#include -Test::Test (const SimpleString& testName) - : name_ (testName) +Test::Test (const std::string& testName) + : name_ (testName), next_(0), lineNumber_(-1), safeCheck_(true) { TestRegistry::addTest (this); } -Test::Test (const SimpleString& testName, const SimpleString& filename, long lineNumber, bool safeCheck = true) - : name_(testName), filename_(filename), lineNumber_(lineNumber), safeCheck_(safeCheck) +Test::Test (const std::string& testName, const std::string& filename, long lineNumber, bool safeCheck) + : name_(testName), next_(0), filename_(filename), lineNumber_(lineNumber), safeCheck_(safeCheck) { TestRegistry::addTest (this); } @@ -40,31 +40,31 @@ void Test::setNext(Test *test) next_ = test; } -bool Test::check(long expected, long actual, TestResult& result, const SimpleString& fileName, long lineNumber) +bool Test::check(long expected, long actual, TestResult& result, const std::string& fileName, long lineNumber) { if (expected == actual) return true; result.addFailure ( Failure ( name_, - StringFrom (__FILE__), + boost::lexical_cast (__FILE__), __LINE__, - StringFrom (expected), - StringFrom (actual))); + boost::lexical_cast (expected), + boost::lexical_cast (actual))); return false; } -bool Test::check(const SimpleString& expected, const SimpleString& actual, TestResult& result, const SimpleString& fileName, long lineNumber) +bool Test::check(const std::string& expected, const std::string& actual, TestResult& result, const std::string& fileName, long lineNumber) { if (expected == actual) return true; result.addFailure ( Failure ( name_, - StringFrom (__FILE__), + boost::lexical_cast (__FILE__), __LINE__, expected, actual)); diff --git a/CppUnitLite/Test.h b/CppUnitLite/Test.h index 22566131e..820ed48cf 100644 --- a/CppUnitLite/Test.h +++ b/CppUnitLite/Test.h @@ -23,17 +23,15 @@ #include -#include "SimpleString.h" +#include class TestResult; - - class Test { public: - Test (const SimpleString& testName); - Test (const SimpleString& testName, const SimpleString& filename, long lineNumber, bool safeCheck); + Test (const std::string& testName); + Test (const std::string& testName, const std::string& filename, long lineNumber, bool safeCheck); virtual ~Test() {}; virtual void run (TestResult& result) = 0; @@ -41,19 +39,19 @@ public: void setNext(Test *test); Test *getNext () const; - SimpleString getName() const {return name_;} - SimpleString getFilename() const {return filename_;} + std::string getName() const {return name_;} + std::string getFilename() const {return filename_;} long getLineNumber() const {return lineNumber_;} bool safe() const {return safeCheck_;} protected: - bool check (long expected, long actual, TestResult& result, const SimpleString& fileName, long lineNumber); - bool check (const SimpleString& expected, const SimpleString& actual, TestResult& result, const SimpleString& fileName, long lineNumber); + bool check (long expected, long actual, TestResult& result, const std::string& fileName, long lineNumber); + bool check (const std::string& expected, const std::string& actual, TestResult& result, const std::string& fileName, long lineNumber); - SimpleString name_; + std::string name_; Test *next_; - SimpleString filename_; + std::string filename_; long lineNumber_; /// This is the line line number of the test, rather than the a single check bool safeCheck_; @@ -102,17 +100,17 @@ protected: #define THROWS_EXCEPTION(condition)\ { try { condition; \ - result_.addFailure (Failure (name_, __FILE__,__LINE__, SimpleString("Didn't throw: ") + StringFrom(#condition))); \ + result_.addFailure (Failure (name_, __FILE__,__LINE__, std::string("Didn't throw: ") + boost::lexical_cast(#condition))); \ return; } \ catch (...) {} } #define CHECK_EXCEPTION(condition, exception_name)\ { try { condition; \ - result_.addFailure (Failure (name_, __FILE__,__LINE__, SimpleString("Didn't throw: ") + StringFrom(#condition))); \ + result_.addFailure (Failure (name_, __FILE__,__LINE__, std::string("Didn't throw: ") + boost::lexical_cast(#condition))); \ return; } \ - catch (exception_name& e) {} \ + catch (exception_name&) {} \ catch (...) { \ - result_.addFailure (Failure (name_, __FILE__,__LINE__, SimpleString("Wrong exception: ") + StringFrom(#condition) + StringFrom(", expected: ") + StringFrom(#exception_name))); \ + result_.addFailure (Failure (name_, __FILE__,__LINE__, std::string("Wrong exception: ") + boost::lexical_cast(#condition) + boost::lexical_cast(", expected: ") + boost::lexical_cast(#exception_name))); \ return; } } #define EQUALITY(expected,actual)\ @@ -120,21 +118,21 @@ protected: result_.addFailure(Failure(name_, __FILE__, __LINE__, #expected, #actual)); } #define CHECK_EQUAL(expected,actual)\ -{ if ((expected) == (actual)) return; result_.addFailure(Failure(name_, __FILE__, __LINE__, StringFrom(expected), StringFrom(actual))); } +{ if ((expected) == (actual)) return; result_.addFailure(Failure(name_, __FILE__, __LINE__, boost::lexical_cast(expected), boost::lexical_cast(actual))); } #define LONGS_EQUAL(expected,actual)\ { long actualTemp = actual; \ long expectedTemp = expected; \ if ((expectedTemp) != (actualTemp)) \ -{ result_.addFailure (Failure (name_, __FILE__, __LINE__, StringFrom(expectedTemp), \ -StringFrom(actualTemp))); return; } } +{ result_.addFailure (Failure (name_, __FILE__, __LINE__, boost::lexical_cast(expectedTemp), \ +boost::lexical_cast(actualTemp))); return; } } #define DOUBLES_EQUAL(expected,actual,threshold)\ { double actualTemp = actual; \ double expectedTemp = expected; \ if (fabs ((expectedTemp)-(actualTemp)) > threshold) \ { result_.addFailure (Failure (name_, __FILE__, __LINE__, \ -StringFrom((double)expectedTemp), StringFrom((double)actualTemp))); return; } } +boost::lexical_cast((double)expectedTemp), boost::lexical_cast((double)actualTemp))); return; } } /* EXPECTs: tests will continue running after a failure */ @@ -146,15 +144,15 @@ StringFrom((double)expectedTemp), StringFrom((double)actualTemp))); return; } } { long actualTemp = actual; \ long expectedTemp = expected; \ if ((expectedTemp) != (actualTemp)) \ -{ result_.addFailure (Failure (name_, __FILE__, __LINE__, StringFrom(expectedTemp), \ -StringFrom(actualTemp))); } } +{ result_.addFailure (Failure (name_, __FILE__, __LINE__, boost::lexical_cast(expectedTemp), \ +boost::lexical_cast(actualTemp))); } } #define EXPECT_DOUBLES_EQUAL(expected,actual,threshold)\ { double actualTemp = actual; \ double expectedTemp = expected; \ if (fabs ((expectedTemp)-(actualTemp)) > threshold) \ { result_.addFailure (Failure (name_, __FILE__, __LINE__, \ -StringFrom((double)expectedTemp), StringFrom((double)actualTemp))); } } +boost::lexical_cast((double)expectedTemp), boost::lexical_cast((double)actualTemp))); } } #define FAIL(text) \ diff --git a/CppUnitLite/TestRegistry.cpp b/CppUnitLite/TestRegistry.cpp index fa5295229..1d06b225c 100644 --- a/CppUnitLite/TestRegistry.cpp +++ b/CppUnitLite/TestRegistry.cpp @@ -17,7 +17,6 @@ #include "Failure.h" #include "TestResult.h" #include "TestRegistry.h" -#include "SimpleString.h" void TestRegistry::addTest (Test *test) { @@ -65,12 +64,12 @@ int TestRegistry::run (TestResult& result) // catch standard exceptions and derivatives result.addFailure( Failure(test->getName(), test->getFilename(), test->getLineNumber(), - SimpleString("Exception: ") + SimpleString(e.what()))); + std::string("Exception: ") + std::string(e.what()))); } catch (...) { // catch all other exceptions result.addFailure( Failure(test->getName(), test->getFilename(), test->getLineNumber(), - SimpleString("ExceptionThrown!"))); + "ExceptionThrown!")); } } else { diff --git a/CppUnitLite/TestResult.cpp b/CppUnitLite/TestResult.cpp index 3bc8a8ad5..a9e599989 100644 --- a/CppUnitLite/TestResult.cpp +++ b/CppUnitLite/TestResult.cpp @@ -32,16 +32,16 @@ void TestResult::addFailure (const Failure& failure) if (failure.lineNumber < 0) // allow for no line number fprintf (stdout, "%s%s%s%s\n", "Failure: \"", - failure.message.asCharString (), + failure.message.c_str (), "\" in ", - failure.fileName.asCharString ()); + failure.fileName.c_str ()); else fprintf (stdout, "%s%s%ld%s%s%s\n", - failure.fileName.asCharString(), // Format matches Eclipse error flagging + failure.fileName.c_str(), // Format matches Eclipse error flagging ":", failure.lineNumber, ": Failure: \"", - failure.message.asCharString(), + failure.message.c_str(), "\" "); failureCount++; diff --git a/README b/README index 8ec8a99f8..d7486c8b8 100644 --- a/README +++ b/README @@ -37,7 +37,7 @@ of licensing in LICENSE and as follows: - CCOLAMD 2.73: Tim Davis' constrained column approximate minimum degree ordering library - http://www.cise.ufl.edu/research/sparse - Licenced under LGPL v2.1, provided in gtsam/3rdparty/CCOLAMD/Doc/lesser.txt - - Eigen 3.0.5: General C++ matrix and linear algebra library + - Eigen 3.1: General C++ matrix and linear algebra library - Licenced under LGPL v3, provided in gtsam/3rdparty/Eigen/COPYING.LGPL @@ -51,17 +51,20 @@ Important Installation Notes 1) GTSAM requires the following libraries to be installed on your system: - - BOOST version 1.40 or greater (install through Linux repositories or MacPorts) + - BOOST version 1.43 or greater (install through Linux repositories or MacPorts) - Cmake version 2.6 or higher + - Support for XCode 4.3 command line tools on Mac requires CMake 2.8.8 or higher Tested compilers - GCC 4.2-4.7 - Clang 2.9-3.2 - OSX GCC 4.2 + - MSVC 2010, 2012 Tested systems: - Ubuntu 11.04, 11.10, 12.04 - MacOS 10.6, 10.7 + - Windows 7 2) GTSAM makes extensive use of debug assertions, and we highly recommend you work @@ -71,8 +74,8 @@ will run up to 10x faster in Release mode! See the end of this document for additional debugging tips. 3) -GTSAM has Doxygen documentation. To generate, run the the script -makedoc.sh. +GTSAM has Doxygen documentation. To generate, run 'make doc' from your +build directory. 4) The instructions below install the library to the default system install path and @@ -147,6 +150,12 @@ just the geometry tests, run "make check.geometry". Individual tests can be run appending ".run" to the name of the test, for example, to run testMatrix, run "make testMatrix.run". +MEX_COMMAND: Path to the mex compiler. Defaults to assume the path is included in your +shell's PATH environment variable. mex is installed with matlab at +$MATLABROOT/bin/mex + +$MATLABROOT can be found by executing the command 'matlabroot' in MATLAB + Debugging tips: Another useful debugging symbol is _GLIBCXX_DEBUG, which enables debug checks diff --git a/doc/CMakeLists.txt b/doc/CMakeLists.txt new file mode 100644 index 000000000..4cb6d4a40 --- /dev/null +++ b/doc/CMakeLists.txt @@ -0,0 +1,79 @@ +# Doxygen documentation configuration +option(GTSAM_BUILD_DOCS "Enable/Disable building of doxygen docs" ON) + +# configure doxygen +option(GTSAM_BUILD_DOC_HTML "Enable/Disable doxygen HTML output" ON) +option(GTSAM_BUILD_DOC_LATEX "Enable/Disable doxygen LaTeX output" OFF) + +# add a target to generate API documentation with Doxygen +if (GTSAM_BUILD_DOCS) + # Convert configuration to YES/NO variables + if (GTSAM_BUILD_DOC_HTML) + set(GTSAM_BUILD_DOC_HTML_YN "YES") + else() + set(GTSAM_BUILD_DOC_HTML_YN "NO") + endif() + + if (GTSAM_BUILD_DOC_LATEX) + set(GTSAM_BUILD_DOC_LATEX_YN "YES") + else() + set(GTSAM_BUILD_DOC_LATEX_YN "NO") + endif() + + # GTSAM core subfolders + set(gtsam_doc_subdirs + gtsam/base + gtsam/geometry + gtsam/inference + gtsam/discrete + gtsam/linear + gtsam/nonlinear + gtsam/slam + gtsam + ) + + # Optional GTSAM_UNSTABLE subfolders + set(gtsam_unstable_doc_subdirs + gtsam_unstable/base + gtsam_unstable/discrete + gtsam_unstable/linear + gtsam_unstable/nonlinear + gtsam_unstable/slam + gtsam_unstable/dynamics + gtsam_unstable + ) + + # Build a list of folders to include depending on build options + set(doc_subdirs ${gtsam_doc_subdirs}) + if (GTSAM_BUILD_UNSTABLE) + list(APPEND doc_subdirs ${gtsam_unstable_doc_subdirs}) + endif() + if (GTSAM_BUILD_EXAMPLES) + list(APPEND doc_subdirs examples) + endif() + + # From subfolders, build a list with whitespace separation of paths + set(GTSAM_DOXYGEN_INPUT_PATHS "") + foreach(dir ${doc_subdirs}) + set(GTSAM_DOXYGEN_INPUT_PATHS "${GTSAM_DOXYGEN_INPUT_PATHS} ${PROJECT_SOURCE_DIR}/${dir}") + endforeach() + + # Generate Doxyfile + configure_file(${CMAKE_CURRENT_SOURCE_DIR}/Doxyfile.in ${CMAKE_CURRENT_BINARY_DIR}/Doxyfile @ONLY) + + # Add target to actually build documentation as configured + add_custom_target(doc + ${DOXYGEN_EXECUTABLE} ${CMAKE_CURRENT_BINARY_DIR}/Doxyfile + WORKING_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR} + COMMENT "Generating API documentation with Doxygen" VERBATIM + ) + + # Clean target + add_custom_target(doc_clean + COMMAND + cmake -E remove_directory ${CMAKE_CURRENT_SOURCE_DIR}/latex + COMMAND + cmake -E remove_directory ${CMAKE_CURRENT_SOURCE_DIR}/html + COMMENT "Removing Doxygen documentation" + ) +endif() diff --git a/Doxyfile b/doc/Doxyfile.in similarity index 99% rename from Doxyfile rename to doc/Doxyfile.in index d7dd6adff..f12e12217 100644 --- a/Doxyfile +++ b/doc/Doxyfile.in @@ -32,7 +32,7 @@ PROJECT_NAME = gtsam # This could be handy for archiving the generated documentation or # if some version control system is used. -PROJECT_NUMBER = 2.0.0 +PROJECT_NUMBER = @GTSAM_VERSION_MAJOR@.@GTSAM_VERSION_MINOR@.@GTSAM_VERSION_PATCH@ # Using the PROJECT_BRIEF tag one can provide an optional one line description # for a project that appears at the top of each page and should give viewer @@ -52,7 +52,7 @@ PROJECT_LOGO = # If a relative path is entered, it will be relative to the location # where doxygen was started. If left blank the current directory will be used. -OUTPUT_DIRECTORY = doc +OUTPUT_DIRECTORY = . # If the CREATE_SUBDIRS tag is set to YES, then doxygen will create # 4096 sub-directories (in 2 levels) under the output directory of each output @@ -597,7 +597,7 @@ WARNINGS = YES # for undocumented members. If EXTRACT_ALL is set to YES then this flag will # automatically be disabled. -WARN_IF_UNDOCUMENTED = YES +WARN_IF_UNDOCUMENTED = NO # If WARN_IF_DOC_ERROR is set to YES, doxygen will generate warnings for # potential errors in the documentation, such as not documenting some @@ -638,19 +638,7 @@ WARN_LOGFILE = # directories like "/usr/src/myproject". Separate the files or directories # with spaces. -INPUT = gtsam/base \ - gtsam/geometry \ - gtsam/inference \ - gtsam/discrete \ - gtsam/linear \ - gtsam/nonlinear \ - gtsam -# gtsam/slam \ -# gtsam_unstable/slam \ -# gtsam_unstable/base \ -# gtsam_unstable/geometry \ -# gtsam_unstable/dynamics \ -# gtsam_unstable +INPUT = @GTSAM_DOXYGEN_INPUT_PATHS@ # This tag can be used to specify the character encoding of the source files # that doxygen parses. Internally doxygen uses the UTF-8 encoding, which is @@ -880,7 +868,7 @@ IGNORE_PREFIX = # If the GENERATE_HTML tag is set to YES (the default) Doxygen will # generate HTML output. -GENERATE_HTML = YES +GENERATE_HTML = @GTSAM_BUILD_DOC_HTML_YN@ # The HTML_OUTPUT tag is used to specify where the HTML docs will be put. # If a relative path is entered the value of OUTPUT_DIRECTORY will be @@ -1234,7 +1222,7 @@ SERVER_BASED_SEARCH = NO # If the GENERATE_LATEX tag is set to YES (the default) Doxygen will # generate Latex output. -GENERATE_LATEX = NO +GENERATE_LATEX = @GTSAM_BUILD_DOC_LATEX_YN@ # The LATEX_OUTPUT tag is used to specify where the LaTeX docs will be put. # If a relative path is entered the value of OUTPUT_DIRECTORY will be diff --git a/DoxygenLayout.xml b/doc/DoxygenLayout.xml similarity index 100% rename from DoxygenLayout.xml rename to doc/DoxygenLayout.xml diff --git a/doc/LieGroups.lyx b/doc/LieGroups.lyx new file mode 100644 index 000000000..03116dbc9 --- /dev/null +++ b/doc/LieGroups.lyx @@ -0,0 +1,4065 @@ +#LyX 2.0 created this file. For more info see http://www.lyx.org/ +\lyxformat 413 +\begin_document +\begin_header +\textclass article +\use_default_options false +\begin_modules +theorems-std +\end_modules +\maintain_unincluded_children false +\language english +\language_package default +\inputencoding auto +\fontencoding global +\font_roman times +\font_sans default +\font_typewriter default +\font_default_family rmdefault +\use_non_tex_fonts false +\font_sc false +\font_osf false +\font_sf_scale 100 +\font_tt_scale 100 + +\graphics default +\default_output_format default +\output_sync 0 +\bibtex_command default +\index_command default +\paperfontsize 12 +\spacing single +\use_hyperref false +\papersize default +\use_geometry true +\use_amsmath 1 +\use_esint 0 +\use_mhchem 1 +\use_mathdots 1 +\cite_engine basic +\use_bibtopic false +\use_indices false +\paperorientation portrait +\suppress_date false +\use_refstyle 0 +\index Index +\shortcut idx +\color #008000 +\end_index +\leftmargin 1in +\topmargin 1in +\rightmargin 1in +\bottommargin 1in +\secnumdepth 3 +\tocdepth 3 +\paragraph_separation indent +\paragraph_indentation default +\quotes_language english +\papercolumns 1 +\papersides 1 +\paperpagestyle default +\tracking_changes false +\output_changes false +\html_math_output 0 +\html_css_as_file 0 +\html_be_strict false +\end_header + +\begin_body + +\begin_layout Title +Lie Groups for Beginners +\end_layout + +\begin_layout Author +Frank Dellaert +\end_layout + +\begin_layout Standard +\begin_inset Note Comment +status open + +\begin_layout Plain Layout +Derivatives +\end_layout + +\end_inset + + +\end_layout + +\begin_layout Standard +\begin_inset FormulaMacro +\newcommand{\deriv}[2]{\frac{\partial#1}{\partial#2}} +{\frac{\partial#1}{\partial#2}} +\end_inset + + +\begin_inset FormulaMacro +\newcommand{\at}[2]{#1\biggr\rvert_{#2}} +{#1\biggr\rvert_{#2}} +\end_inset + + +\begin_inset FormulaMacro +\newcommand{\Jac}[3]{ \at{\deriv{#1}{#2}} {#3} } +{\at{\deriv{#1}{#2}}{#3}} +\end_inset + + +\end_layout + +\begin_layout Standard +\begin_inset Note Comment +status open + +\begin_layout Plain Layout +Lie Groups +\end_layout + +\end_inset + + +\end_layout + +\begin_layout Standard +\begin_inset FormulaMacro +\newcommand{\xhat}{\hat{x}} +{\hat{x}} +\end_inset + + +\begin_inset FormulaMacro +\newcommand{\yhat}{\hat{y}} +{\hat{y}} +\end_inset + + +\begin_inset FormulaMacro +\newcommand{\Ad}[1]{Ad_{#1}} +{Ad_{#1}} +\end_inset + + +\begin_inset FormulaMacro +\newcommand{\AAdd}[1]{\mathbf{\mathop{Ad}}{}_{#1}} +{\mathbf{\mathop{Ad}}{}_{#1}} +\end_inset + + +\end_layout + +\begin_layout Standard +\begin_inset FormulaMacro +\newcommand{\define}{\stackrel{\Delta}{=}} +{\stackrel{\Delta}{=}} +\end_inset + + +\begin_inset FormulaMacro +\newcommand{\gg}{\mathfrak{g}} +{\mathfrak{g}} +\end_inset + + +\begin_inset FormulaMacro +\newcommand{\Rn}{\mathbb{R}^{n}} +{\mathbb{R}^{n}} +\end_inset + + +\end_layout + +\begin_layout Standard +\begin_inset Note Comment +status open + +\begin_layout Plain Layout +SO(2), 1 +\end_layout + +\end_inset + + +\end_layout + +\begin_layout Standard +\begin_inset FormulaMacro +\newcommand{\Rtwo}{\mathfrak{\mathbb{R}^{2}}} +{\mathfrak{\mathbb{R}^{2}}} +\end_inset + + +\begin_inset FormulaMacro +\newcommand{\SOtwo}{SO(2)} +{SO(2)} +\end_inset + + +\begin_inset FormulaMacro +\newcommand{\sotwo}{\mathfrak{so(2)}} +{\mathfrak{so(2)}} +\end_inset + + +\begin_inset FormulaMacro +\newcommand{\that}{\hat{\theta}} +{\hat{\theta}} +\end_inset + + +\begin_inset FormulaMacro +\newcommand{\skew}[1]{[#1]_{+}} +{[#1]_{+}} +\end_inset + + +\end_layout + +\begin_layout Standard +\begin_inset Note Comment +status open + +\begin_layout Plain Layout +SE(2), 3 +\end_layout + +\end_inset + + +\end_layout + +\begin_layout Standard +\begin_inset FormulaMacro +\newcommand{\SEtwo}{SE(2)} +{SE(2)} +\end_inset + + +\begin_inset FormulaMacro +\newcommand{\setwo}{\mathfrak{se(2)}} +{\mathfrak{se(2)}} +\end_inset + + +\begin_inset FormulaMacro +\newcommand{\Skew}[1]{[#1]_{\times}} +{[#1]_{\times}} +\end_inset + + +\end_layout + +\begin_layout Standard +\begin_inset Note Comment +status open + +\begin_layout Plain Layout +SO(3), 3 +\end_layout + +\end_inset + + +\end_layout + +\begin_layout Standard +\begin_inset FormulaMacro +\newcommand{\Rthree}{\mathfrak{\mathbb{R}^{3}}} +{\mathfrak{\mathbb{R}^{3}}} +\end_inset + + +\begin_inset FormulaMacro +\newcommand{\SOthree}{SO(3)} +{SO(3)} +\end_inset + + +\begin_inset FormulaMacro +\newcommand{\sothree}{\mathfrak{so(3)}} +{\mathfrak{so(3)}} +\end_inset + + +\begin_inset FormulaMacro +\newcommand{\what}{\hat{\omega}} +{\hat{\omega}} +\end_inset + + +\end_layout + +\begin_layout Standard +\begin_inset Note Comment +status open + +\begin_layout Plain Layout +SE(3),6 +\end_layout + +\end_inset + + +\end_layout + +\begin_layout Standard +\begin_inset FormulaMacro +\newcommand{\Rsix}{\mathfrak{\mathbb{R}^{6}}} +{\mathfrak{\mathbb{R}^{6}}} +\end_inset + + +\begin_inset FormulaMacro +\newcommand{\SEthree}{SE(3)} +{SE(3)} +\end_inset + + +\begin_inset FormulaMacro +\newcommand{\sethree}{\mathfrak{se(3)}} +{\mathfrak{se(3)}} +\end_inset + + +\begin_inset FormulaMacro +\newcommand{\xihat}{\hat{\xi}} +{\hat{\xi}} +\end_inset + + +\end_layout + +\begin_layout Standard +\begin_inset Note Comment +status open + +\begin_layout Plain Layout +Aff(2),6 +\end_layout + +\end_inset + + +\end_layout + +\begin_layout Standard +\begin_inset FormulaMacro +\newcommand{\Afftwo}{Aff(2)} +{Aff(2)} +\end_inset + + +\begin_inset FormulaMacro +\newcommand{\afftwo}{\mathfrak{aff(2)}} +{\mathfrak{aff(2)}} +\end_inset + + +\begin_inset FormulaMacro +\newcommand{\aa}{a} +{a} +\end_inset + + +\begin_inset FormulaMacro +\newcommand{\ahat}{\hat{a}} +{\hat{a}} +\end_inset + + +\end_layout + +\begin_layout Standard +\begin_inset Note Comment +status collapsed + +\begin_layout Plain Layout +SL(3),8 +\end_layout + +\end_inset + + +\end_layout + +\begin_layout Standard +\begin_inset FormulaMacro +\newcommand{\SLthree}{SL(3)} +{SL(3)} +\end_inset + + +\begin_inset FormulaMacro +\newcommand{\slthree}{\mathfrak{sl(3)}} +{\mathfrak{sl(3)}} +\end_inset + + +\begin_inset FormulaMacro +\newcommand{\hh}{h} +{h} +\end_inset + + +\begin_inset FormulaMacro +\newcommand{\hhat}{\hat{h}} +{\hat{h}} +\end_inset + + +\end_layout + +\begin_layout Section +Motivation: Rigid Motions in the Plane +\end_layout + +\begin_layout Standard +We will start with a small example of a robot moving in a plane, parameterized + by a +\emph on +2D pose +\emph default + +\begin_inset Formula $(x,\, y,\,\theta)$ +\end_inset + +. + When we give it a small forward velocity +\begin_inset Formula $v_{x}$ +\end_inset + +, we know that the location changes as +\begin_inset Formula +\[ +\dot{x}=v_{x} +\] + +\end_inset + +The solution to this trivial differential equation is, with +\begin_inset Formula $x_{0}$ +\end_inset + + the initial +\begin_inset Formula $x$ +\end_inset + +-position of the robot, +\begin_inset Formula +\[ +x_{t}=x_{0}+v_{x}t +\] + +\end_inset + +A similar story holds for translation in the +\begin_inset Formula $y$ +\end_inset + + direction, and in fact for translations in general: +\begin_inset Formula +\[ +(x_{t},\, y_{t},\,\theta_{t})=(x_{0}+v_{x}t,\, y_{0}+v_{y}t,\,\theta_{0}) +\] + +\end_inset + +Similarly for rotation we have +\begin_inset Formula +\[ +(x_{t},\, y_{t},\,\theta_{t})=(x_{0},\, y_{0},\,\theta_{0}+\omega t) +\] + +\end_inset + +where +\begin_inset Formula $\omega$ +\end_inset + + is angular velocity, measured in +\begin_inset Formula $rad/s$ +\end_inset + + in counterclockwise direction. + +\end_layout + +\begin_layout Standard +\begin_inset Float figure +placement h +wide false +sideways false +status collapsed + +\begin_layout Plain Layout +\align center +\begin_inset Graphics + filename images/circular.pdf + +\end_inset + + +\begin_inset Caption + +\begin_layout Plain Layout +Robot moving along a circular trajectory. +\end_layout + +\end_inset + + +\end_layout + +\end_inset + + +\end_layout + +\begin_layout Standard +However, if we combine translation and rotation, the story breaks down! + We cannot write +\begin_inset Formula +\[ +(x_{t},\, y_{t},\,\theta_{t})=(x_{0}+v_{x}t,\, y_{0}+v_{y}t,\,\theta_{0}+\omega t) +\] + +\end_inset + +The reason is that, if we move the robot a tiny bit according to the velocity + vector +\begin_inset Formula $(v_{x},\, v_{y},\,\omega)$ +\end_inset + +, we have (to first order) +\begin_inset Formula +\[ +(x_{\delta},\, y_{\delta},\,\theta_{\delta})=(x_{0}+v_{x}\delta,\, y_{0}+v_{y}\delta,\,\theta_{0}+\omega\delta) +\] + +\end_inset + +but now the robot has rotated, and for the next incremental change, the + velocity vector would have to be rotated before it can be applied. + In fact, the robot will move on a +\emph on +circular +\emph default + trajectory. + +\end_layout + +\begin_layout Standard +The reason is that +\emph on +translation and rotation do not commute +\emph default +: if we rotate and then move we will end up in a different place than if + we moved first, then rotated. + In fact, someone once said (I forget who, kudos for who can track down + the exact quote): +\end_layout + +\begin_layout Quote +If rotation and translation commuted, we could do all rotations before leaving + home. +\end_layout + +\begin_layout Standard +\begin_inset Float figure +placement h +wide false +sideways false +status open + +\begin_layout Plain Layout +\align center +\begin_inset Graphics + filename images/n-steps.pdf + +\end_inset + + +\begin_inset Caption + +\begin_layout Plain Layout +\begin_inset CommandInset label +LatexCommand label +name "fig:n-step-program" + +\end_inset + +Approximating a circular trajectory with +\begin_inset Formula $n$ +\end_inset + + steps. +\end_layout + +\end_inset + + +\end_layout + +\end_inset + +To make progress, we have to be more precise about how the robot behaves. + Specifically, let us define composition of two poses +\begin_inset Formula $T_{1}$ +\end_inset + + and +\begin_inset Formula $T_{2}$ +\end_inset + + as +\begin_inset Formula +\[ +T_{1}T_{2}=(x_{1},\, y_{1},\,\theta_{1})(x_{2},\, y_{2},\,\theta_{2})=(x_{1}+\cos\theta_{1}x_{2}-\sin\theta y_{2},\, y_{1}+\sin\theta_{1}x_{2}+\cos\theta_{1}y_{2},\,\theta_{1}+\theta_{2}) +\] + +\end_inset + +This is a bit clumsy, so we resort to a trick: embed the 2D poses in the + space of +\begin_inset Formula $3\times3$ +\end_inset + + matrices, so we can define composition as matrix multiplication: +\begin_inset Formula +\[ +T_{1}T_{2}=\left[\begin{array}{cc} +R_{1} & t_{1}\\ +0 & 1 +\end{array}\right]\left[\begin{array}{cc} +R_{2} & t_{2}\\ +0 & 1 +\end{array}\right]=\left[\begin{array}{cc} +R_{1}R_{2} & R_{1}t_{2}+t_{1}\\ +0 & 1 +\end{array}\right] +\] + +\end_inset + +where the matrices +\begin_inset Formula $R$ +\end_inset + + are 2D rotation matrices defined as +\begin_inset Formula +\[ +R=\left[\begin{array}{cc} +\cos\theta & -\sin\theta\\ +\sin\theta & \cos\theta +\end{array}\right] +\] + +\end_inset + +Now a +\begin_inset Quotes eld +\end_inset + +tiny +\begin_inset Quotes erd +\end_inset + + motion of the robot can be written as +\begin_inset Formula +\[ +T(\delta)=\left[\begin{array}{ccc} +\cos\omega\delta & -\sin\omega\delta & v_{x}\delta\\ +\sin\omega\delta & \cos\omega\delta & v_{y}\delta\\ +0 & 0 & 1 +\end{array}\right]\approx\left[\begin{array}{ccc} +1 & -\omega\delta & v_{x}\delta\\ +\omega\delta & 1 & v_{y}\delta\\ +0 & 0 & 1 +\end{array}\right]=I+\delta\left[\begin{array}{ccc} +0 & -\omega & v_{x}\\ +\omega & 0 & v_{y}\\ +0 & 0 & 0 +\end{array}\right] +\] + +\end_inset + +Let us define the +\emph on +2D twist +\emph default + vector +\begin_inset Formula $\xi=(v,\omega)$ +\end_inset + +, and the matrix above as +\begin_inset Formula +\[ +\xihat\define\left[\begin{array}{ccc} +0 & -\omega & v_{x}\\ +\omega & 0 & v_{y}\\ +0 & 0 & 0 +\end{array}\right] +\] + +\end_inset + +If we wanted +\begin_inset Formula $t$ +\end_inset + + to be large, we could split up +\begin_inset Formula $t$ +\end_inset + + into smaller timesteps, say +\begin_inset Formula $n$ +\end_inset + + of them, and compose them as follows: +\begin_inset Formula +\[ +T(t)\approx\left(I+\frac{t}{n}\xihat\right)\ldots\mbox{n times}\ldots\left(I+\frac{t}{n}\xihat\right)=\left(I+\frac{t}{n}\xihat\right)^{n} +\] + +\end_inset + +The result is shown in Figure +\begin_inset CommandInset ref +LatexCommand ref +reference "fig:n-step-program" + +\end_inset + +. +\end_layout + +\begin_layout Standard +Of course, the perfect solution would be obtained if we take +\begin_inset Formula $n$ +\end_inset + + to infinity: +\begin_inset Formula +\[ +T(t)=\lim_{n\rightarrow\infty}\left(I+\frac{t}{n}\xihat\right)^{n} +\] + +\end_inset + +For real numbers, this series is familiar and is actually a way to compute + the exponential function: +\begin_inset Formula +\[ +e^{x}=\lim_{n\rightarrow\infty}\left(1+\frac{x}{n}\right)^{n}=\sum_{k=0}^{\infty}\frac{x^{k}}{k!} +\] + +\end_inset + +The series can be similarly defined for square matrices, and the final result + is that we can write the motion of a robot along a circular trajectory, + resulting from the 2D twist +\begin_inset Formula $\xi=(v,\omega)$ +\end_inset + + +\begin_inset Formula $ $ +\end_inset + + as the +\emph on +matrix exponential +\emph default + of +\begin_inset Formula $\xihat$ +\end_inset + +: +\begin_inset Formula +\[ +T(t)=e^{t\xihat}\define\lim_{n\rightarrow\infty}\left(I+\frac{t}{n}\xihat\right)^{n}=\sum_{k=0}^{\infty}\frac{t^{k}}{k!}\xihat^{k} +\] + +\end_inset + +We call this mapping from 2D twists matrices +\begin_inset Formula $\xihat$ +\end_inset + + to 2D rigid transformations the +\emph on +exponential map. +\end_layout + +\begin_layout Standard +The above has all elements of Lie group theory. + We call the space of 2D rigid transformations, along with the composition + operation, the +\emph on +special Euclidean group +\emph default + +\begin_inset Formula $\SEtwo$ +\end_inset + +. + It is called a Lie group because it is simultaneously a topological group + and a manifold, which implies that the multiplication and the inversion + operations are smooth. + The space of 2D twists, together with a special binary operation to be + defined below, is called the Lie algebra +\begin_inset Formula $\setwo$ +\end_inset + + associated with +\begin_inset Formula $\SEtwo$ +\end_inset + +. + +\end_layout + +\begin_layout Standard +\begin_inset Newpage pagebreak +\end_inset + + +\end_layout + +\begin_layout Section +Basic Lie Group Concepts +\end_layout + +\begin_layout Standard +We now define the concepts illustrated above, introduce some notation, and + see what we can say in general. + After this we then introduce the most commonly used Lie groups and their + Lie algebras. +\end_layout + +\begin_layout Subsection +A Manifold and a Group +\end_layout + +\begin_layout Standard +A +\series bold +Lie group +\series default + +\begin_inset Formula $G$ +\end_inset + + is both a group +\emph on +and +\emph default + a manifold that possesses a smooth group operation. + Associated with it is a +\series bold +Lie Algebra +\series default + +\begin_inset Formula $\gg$ +\end_inset + + which, loosely speaking, can be identified with the tangent space at the + identity and completely defines how the groups behaves around the identity. + There is a mapping from +\begin_inset Formula $\gg$ +\end_inset + + back to +\begin_inset Formula $G$ +\end_inset + +, called the +\series bold +exponential map +\series default + +\begin_inset Formula +\[ +\exp:\gg\rightarrow G +\] + +\end_inset + +which is typically a many-to-one mapping. + The corresponding inverse can be define locally around the origin and hence + is a +\begin_inset Quotes eld +\end_inset + +logarithm +\begin_inset Quotes erd +\end_inset + + +\begin_inset Formula +\[ +\log:G\rightarrow\gg +\] + +\end_inset + +that maps elements in a neighborhood of +\begin_inset Formula $id$ +\end_inset + + in G to an element in +\begin_inset Formula $\gg$ +\end_inset + +. +\end_layout + +\begin_layout Standard +An important family of Lie groups are the matrix Lie groups, whose elements + are +\begin_inset Formula $n\times n$ +\end_inset + + invertible matrices. + The set of all such matrices, together with the matrix multiplication, + is called the general linear group +\begin_inset Formula $GL(n)$ +\end_inset + + of dimension +\begin_inset Formula $n$ +\end_inset + +, and any closed subgroup of it is a +\series bold + matrix Lie group +\series default +. + Most if not all Lie groups we are interested in will be matrix Lie groups. +\end_layout + +\begin_layout Subsection +Lie Algebra +\end_layout + +\begin_layout Standard +The Lie Algebra +\begin_inset Formula $\gg$ +\end_inset + + is called an algebra because it is endowed with a binary operation, the + +\series bold +Lie bracket +\series default + +\begin_inset Formula $[X,Y]$ +\end_inset + +, the properties of which are closely related to the group operation of + +\begin_inset Formula $G$ +\end_inset + +. + For example, for algebras associated with matrix Lie groups, the Lie bracket + is given by +\begin_inset Formula $[A,B]\define AB-BA$ +\end_inset + +. +\end_layout + +\begin_layout Standard +The relationship of the Lie bracket to the group operation is as follows: + for commutative Lie groups vector addition +\begin_inset Formula $X+Y$ +\end_inset + + in +\begin_inset Formula $\gg$ +\end_inset + + mimicks the group operation. + For example, if we have +\begin_inset Formula $Z=X+Y$ +\end_inset + + in +\begin_inset Formula $\gg$ +\end_inset + +, when mapped backed to +\begin_inset Formula $G$ +\end_inset + + via the exponential map we obtain +\begin_inset Formula +\[ +e^{Z}=e^{X+Y}=e^{X}e^{Y} +\] + +\end_inset + +However, this does +\emph on +not +\emph default + hold for non-commutative Lie groups: +\begin_inset Formula +\[ +Z=\log(e^{X}e^{Y})\neq X+Y +\] + +\end_inset + +Instead, +\begin_inset Formula $Z$ +\end_inset + + can be calculated using the Baker-Campbell-Hausdorff (BCH) formula +\begin_inset CommandInset citation +LatexCommand cite +key "Hall00book" + +\end_inset + + +\begin_inset Note Note +status collapsed + +\begin_layout Plain Layout +http://en.wikipedia.org/wiki/Baker–Campbell–Hausdorff_formula +\end_layout + +\end_inset + +: +\begin_inset Formula +\[ +Z=X+Y+[X,Y]/2+[X-Y,[X,Y]]/12-[Y,[X,[X,Y]]]/24+\ldots +\] + +\end_inset + +For commutative groups the bracket is zero and we recover +\begin_inset Formula $Z=X+Y$ +\end_inset + +. + For non-commutative groups we can use the BCH formula to approximate it. +\end_layout + +\begin_layout Subsection +Exponential Coordinates +\end_layout + +\begin_layout Standard +For +\begin_inset Formula $n$ +\end_inset + +-dimensional matrix Lie groups, as a vector space the Lie algebra +\begin_inset Formula $\gg$ +\end_inset + + is isomorphic to +\begin_inset Formula $\mathbb{R}^{n}$ +\end_inset + +, and we can define the hat operator +\begin_inset CommandInset citation +LatexCommand cite +after "page 41" +key "Murray94book" + +\end_inset + +, +\begin_inset Formula +\[ +\hat{}:x\in\mathbb{R}^{n}\rightarrow\xhat\in\gg +\] + +\end_inset + +which maps +\begin_inset Formula $n$ +\end_inset + +-vectors +\begin_inset Formula $x\in\mathbb{R}^{n}$ +\end_inset + + to elements of +\begin_inset Formula $\gg$ +\end_inset + +. + In the case of matrix Lie groups, the elements +\begin_inset Formula $\xhat$ +\end_inset + + of +\begin_inset Formula $\gg$ +\end_inset + + are also +\begin_inset Formula $n\times n$ +\end_inset + + matrices, and the map is given by +\begin_inset Formula +\begin{equation} +\xhat=\sum_{i=1}^{n}x_{i}G^{i}\label{eq:generators} +\end{equation} + +\end_inset + +where the +\begin_inset Formula $G^{i}$ +\end_inset + + are +\begin_inset Formula $n\times n$ +\end_inset + + matrices known as Lie group generators. + The meaning of the map +\begin_inset Formula $x\rightarrow\xhat$ +\end_inset + + will depend on the group +\begin_inset Formula $G$ +\end_inset + + and will generally have an intuitive interpretation. +\end_layout + +\begin_layout Subsection +Actions +\end_layout + +\begin_layout Standard +An important concept is that of a group element acting on an element of + a manifold +\begin_inset Formula $M$ +\end_inset + +. + For example, 2D rotations act on 2D points, 3D rotations act on 3D points, + etc. + In particular, a +\series bold +left action +\series default + of +\begin_inset Formula $G$ +\end_inset + + on +\begin_inset Formula $M$ +\end_inset + + is defined as a smooth map +\begin_inset Formula $\Phi:G\times M\rightarrow M$ +\end_inset + + such that +\begin_inset CommandInset citation +LatexCommand cite +after "Appendix A" +key "Murray94book" + +\end_inset + +: +\end_layout + +\begin_layout Enumerate +The identity element +\begin_inset Formula $e$ +\end_inset + + has no effect, i.e., +\begin_inset Formula $\Phi(e,p)=p$ +\end_inset + + +\end_layout + +\begin_layout Enumerate +Composing two actions can be combined into one action: +\begin_inset Formula $\Phi(g,\Phi(h,p))=\Phi(gh,p)$ +\end_inset + + +\end_layout + +\begin_layout Standard +The (usual) action of an +\begin_inset Formula $n$ +\end_inset + +-dimensional matrix group +\begin_inset Formula $G$ +\end_inset + + is matrix-vector multiplication on +\begin_inset Formula $\mathbb{R}^{n}$ +\end_inset + +, +\begin_inset Formula +\[ +q=Ap +\] + +\end_inset + +with +\begin_inset Formula $p,q\in\mathbb{R}^{n}$ +\end_inset + + and +\begin_inset Formula $A\in G\subseteq GL(n)$ +\end_inset + +. + +\end_layout + +\begin_layout Subsection +The Adjoint Map and Adjoint Representation +\end_layout + +\begin_layout Standard +Suppose a point +\begin_inset Formula $p$ +\end_inset + + is specified as +\begin_inset Formula $p'$ +\end_inset + + in the frame +\begin_inset Formula $T$ +\end_inset + +, i.e., +\begin_inset Formula $p'=Tp$ +\end_inset + +, where +\begin_inset Formula $T$ +\end_inset + + transforms from the global coordinates +\begin_inset Formula $p$ +\end_inset + + to the local frame +\begin_inset Formula $p'$ +\end_inset + +. + To apply an action +\begin_inset Formula $A$ +\end_inset + + we first need to undo +\begin_inset Formula $T$ +\end_inset + +, then apply +\begin_inset Formula $A$ +\end_inset + +, and then transform the result back to +\begin_inset Formula $T$ +\end_inset + +: +\begin_inset Formula +\[ +q'=TAT^{-1}p' +\] + +\end_inset + +The matrix +\begin_inset Formula $TAT^{-1}$ +\end_inset + + is said to be conjugate to +\begin_inset Formula $A$ +\end_inset + +, and this is a central element of group theory. +\end_layout + +\begin_layout Standard +In general, the +\series bold +adjoint map +\series default + +\begin_inset Formula $\AAdd g$ +\end_inset + + maps a group element +\begin_inset Formula $a\in G$ +\end_inset + + to its +\series bold +conjugate +\series default + +\begin_inset Formula $gag^{-1}$ +\end_inset + + by +\begin_inset Formula $g$ +\end_inset + +. + This map captures conjugacy in the group +\begin_inset Formula $G$ +\end_inset + +, but there is an equivalent notion in the Lie algebra +\begin_inset Formula $\mathfrak{\gg}$ +\end_inset + +, +\begin_inset Note Note +status open + +\begin_layout Plain Layout +http://en.wikipedia.org/wiki/Exponential_map +\end_layout + +\end_inset + + +\begin_inset Formula +\[ +\AAdd ge^{\xhat}=g\exp\left(\xhat\right)g^{-1}=\exp(\Ad g{\xhat}) +\] + +\end_inset + +where +\begin_inset Formula $\Ad g:\gg\rightarrow\mathfrak{\gg}$ +\end_inset + + is a map parameterized by a group element +\begin_inset Formula $g$ +\end_inset + +, and is called the +\emph on +adjoint representation +\emph default +. + The intuitive explanation is that a change +\begin_inset Formula $\exp\left(\xhat\right)$ +\end_inset + + defined around the origin, but applied at the group element +\begin_inset Formula $g$ +\end_inset + +, can be written in one step by taking the adjoint +\begin_inset Formula $\Ad g{\xhat}$ +\end_inset + + of +\begin_inset Formula $\xhat$ +\end_inset + +. + +\end_layout + +\begin_layout Standard +In the special case of matrix Lie groups the adjoint can be written as +\begin_inset Note Note +status collapsed + +\begin_layout Plain Layout +http://en.wikipedia.org/wiki/Adjoint_representation_of_a_Lie_group +\end_layout + +\end_inset + + +\begin_inset Formula +\[ +\Ad T{\xhat}\define T\xhat T^{-1} +\] + +\end_inset + +and hence we have +\end_layout + +\begin_layout Standard +\begin_inset Formula +\begin{equation} +Te^{\xhat}T^{-1}=e^{T\xhat T^{-1}}\label{eq:matrixAdjoint} +\end{equation} + +\end_inset + +where both +\begin_inset Formula $T\in G$ +\end_inset + + and +\begin_inset Formula $\xhat\in\gg$ +\end_inset + + are +\begin_inset Formula $n\times n$ +\end_inset + + matrices for an +\begin_inset Formula $n$ +\end_inset + +-dimensional Lie group. +\end_layout + +\begin_layout Standard +\begin_inset Newpage pagebreak +\end_inset + + +\end_layout + +\begin_layout Section +2D Rotations +\end_layout + +\begin_layout Standard +We first look at a very simple group, the 2D rotations. +\end_layout + +\begin_layout Subsection +Basics +\end_layout + +\begin_layout Standard +The Lie group +\begin_inset Formula $\SOtwo$ +\end_inset + + is a subgroup of the general linear group +\begin_inset Formula $GL(2)$ +\end_inset + + of +\begin_inset Formula $2\times2$ +\end_inset + + invertible matrices. + Its Lie algebra +\begin_inset Formula $\sotwo$ +\end_inset + + is the vector space of +\begin_inset Formula $2\times2$ +\end_inset + + skew-symmetric matrices. + Since +\begin_inset Formula $\SOtwo$ +\end_inset + + is a one-dimensional manifold, +\begin_inset Formula $\sotwo$ +\end_inset + + is isomorphic to +\begin_inset Formula $\mathbb{R}$ +\end_inset + + and we define +\begin_inset Formula +\[ +\hat{}:\mathbb{R}\rightarrow\sotwo +\] + +\end_inset + + +\begin_inset Formula +\[ +\hat{}:\omega\rightarrow\what=\skew{\omega} +\] + +\end_inset + +which maps the angle +\begin_inset Formula $\omega$ +\end_inset + + to the +\begin_inset Formula $2\times2$ +\end_inset + + skew-symmetric matrix +\family roman +\series medium +\shape up +\size normal +\emph off +\bar no +\noun off +\color none + +\begin_inset Formula $\skew{\omega}$ +\end_inset + +: +\family default +\series default +\shape default +\size default +\emph default +\bar default +\noun default +\color inherit + +\begin_inset Formula +\[ +\skew{\omega}=\left[\begin{array}{cc} +0 & -\omega\\ +\omega & 0 +\end{array}\right] +\] + +\end_inset + +The exponential map can be computed in closed form as +\begin_inset Formula +\[ +e^{\skew{\omega}}=\left[\begin{array}{cc} +\cos\omega & -\sin\omega\\ +\sin\omega & \cos\omega +\end{array}\right] +\] + +\end_inset + + +\end_layout + +\begin_layout Subsection +\begin_inset CommandInset label +LatexCommand label +name "sub:Diagonalized2D" + +\end_inset + +Diagonalized Form +\end_layout + +\begin_layout Standard +The matrix +\begin_inset Formula $\skew 1$ +\end_inset + + can be diagonalized (see +\begin_inset CommandInset citation +LatexCommand cite +key "Hall00book" + +\end_inset + +) with eigenvalues +\begin_inset Formula $-i$ +\end_inset + + and +\begin_inset Formula $i$ +\end_inset + + , and eigenvectors +\begin_inset Formula $\left[\begin{array}{c} +1\\ +i +\end{array}\right]$ +\end_inset + + and +\begin_inset Formula $\left[\begin{array}{c} +i\\ +1 +\end{array}\right]$ +\end_inset + + . + Readers familiar with projective geometry will recognize these as the circular + points when promoted to homogeneous coordinates. + In particular: +\begin_inset Formula +\[ +\skew{\omega}=\left[\begin{array}{cc} +0 & -\omega\\ +\omega & 0 +\end{array}\right]=\left[\begin{array}{cc} +1 & i\\ +i & 1 +\end{array}\right]\left[\begin{array}{cc} +-i\omega & 0\\ +0 & i\omega +\end{array}\right]\left[\begin{array}{cc} +1 & i\\ +i & 1 +\end{array}\right]^{-1} +\] + +\end_inset + +and hence +\begin_inset Formula +\[ +e^{\skew{\omega}}=\frac{1}{2}\left[\begin{array}{cc} +1 & i\\ +i & 1 +\end{array}\right]\left[\begin{array}{cc} +e^{-i\omega} & 0\\ +0 & e^{i\omega} +\end{array}\right]\left[\begin{array}{cc} +1 & -i\\ +-i & 1 +\end{array}\right]=\left[\begin{array}{cc} +\cos\omega & -\sin\omega\\ +\sin\omega & \cos\omega +\end{array}\right] +\] + +\end_inset + +where the latter can be shown using +\begin_inset Formula $e^{i\omega}=\cos\omega+i\sin\omega$ +\end_inset + +. +\end_layout + +\begin_layout Subsection +Adjoint +\end_layout + +\begin_layout Standard +The adjoint for +\begin_inset Formula $\sotwo$ +\end_inset + + is trivially equal to the identity, as is the case for +\emph on +all +\emph default + commutative groups: +\begin_inset Formula +\begin{eqnarray*} +\Ad R\what & = & \left[\begin{array}{cc} +\cos\theta & -\sin\theta\\ +\sin\theta & \cos\theta +\end{array}\right]\left[\begin{array}{cc} +0 & -\omega\\ +\omega & 0 +\end{array}\right]\left[\begin{array}{cc} +\cos\theta & -\sin\theta\\ +\sin\theta & \cos\theta +\end{array}\right]^{T}\\ + & = & \omega\left[\begin{array}{cc} +-\sin\theta & -\cos\theta\\ +\cos\theta & -\sin\theta +\end{array}\right]\left[\begin{array}{cc} +\cos\theta & \sin\theta\\ +-\sin\theta & \cos\theta +\end{array}\right]=\left[\begin{array}{cc} +0 & -\omega\\ +\omega & 0 +\end{array}\right] +\end{eqnarray*} + +\end_inset + +i.e., +\begin_inset Formula +\[ +\Ad R\what=\what +\] + +\end_inset + + +\end_layout + +\begin_layout Subsection +Actions +\end_layout + +\begin_layout Standard +In the case of +\begin_inset Formula $\SOtwo$ +\end_inset + + the vector space is +\begin_inset Formula $\Rtwo$ +\end_inset + +, and the group action corresponds to rotating a point +\begin_inset Formula +\[ +q=Rp +\] + +\end_inset + +We would now like to know what an incremental rotation parameterized by + +\begin_inset Formula $\omega$ +\end_inset + + would do: +\begin_inset Formula +\[ +q(\text{\omega})=Re^{\skew{\omega}}p +\] + +\end_inset + +For small angles +\begin_inset Formula $\omega$ +\end_inset + + we have +\begin_inset Formula +\[ +e^{\skew{\omega}}\approx\skew{\omega}=\omega\skew 1 +\] + +\end_inset + +where +\begin_inset Formula $\skew 1$ +\end_inset + + acts like a restricted +\begin_inset Quotes eld +\end_inset + +cross product +\begin_inset Quotes erd +\end_inset + + in the plane on points: +\begin_inset Formula +\begin{equation} +\skew 1\left[\begin{array}{c} +x\\ +y +\end{array}\right]=R_{\pi/2}\left[\begin{array}{c} +x\\ +y +\end{array}\right]=\left[\begin{array}{c} +-y\\ +x +\end{array}\right]\label{eq:RestrictedCross} +\end{equation} + +\end_inset + +Hence the derivative of the action is given as +\begin_inset Formula +\[ +\deriv{q(\omega)}{\omega}=R\deriv{}{\omega}\left(e^{\skew{\omega}}p\right)=R\deriv{}{\omega}\left(\omega\skew 1p\right)=RH_{p} +\] + +\end_inset + +where +\begin_inset Formula $H_{p}$ +\end_inset + + is a +\begin_inset Formula $2\times1$ +\end_inset + + matrix that depends on +\begin_inset Formula $p$ +\end_inset + +: +\begin_inset Formula +\[ +H_{p}\define\skew 1p=\left[\begin{array}{c} +-p_{y}\\ +p_{x} +\end{array}\right] +\] + +\end_inset + + +\end_layout + +\begin_layout Standard +\begin_inset Newpage pagebreak +\end_inset + + +\end_layout + +\begin_layout Section +2D Rigid Transformations +\end_layout + +\begin_layout Subsection +Basics +\end_layout + +\begin_layout Standard +The Lie group +\begin_inset Formula $\SEtwo$ +\end_inset + + is a subgroup of the general linear group +\begin_inset Formula $GL(3)$ +\end_inset + + of +\begin_inset Formula $3\times3$ +\end_inset + + invertible matrices of the form +\begin_inset Formula +\[ +T\define\left[\begin{array}{cc} +R & t\\ +0 & 1 +\end{array}\right] +\] + +\end_inset + +where +\begin_inset Formula $R\in\SOtwo$ +\end_inset + + is a rotation matrix and +\begin_inset Formula $t\in\Rtwo$ +\end_inset + + is a translation vector. + +\begin_inset Formula $\SEtwo$ +\end_inset + + is the +\emph on +semi-direct product +\emph default + of +\begin_inset Formula $\Rtwo$ +\end_inset + + by +\begin_inset Formula $SO(2)$ +\end_inset + +, written as +\begin_inset Formula $\SEtwo=\Rtwo\rtimes\SOtwo$ +\end_inset + +. + In particular, any element +\begin_inset Formula $T$ +\end_inset + + of +\begin_inset Formula $\SEtwo$ +\end_inset + + can be written as +\begin_inset Formula +\[ +T=\left[\begin{array}{cc} +0 & t\\ +0 & 1 +\end{array}\right]\left[\begin{array}{cc} +R & 0\\ +0 & 1 +\end{array}\right] +\] + +\end_inset + +and they compose as +\begin_inset Formula +\[ +T_{1}T_{2}=\left[\begin{array}{cc} +R_{1} & t_{1}\\ +0 & 1 +\end{array}\right]\left[\begin{array}{cc} +R_{2} & t_{2}\\ +0 & 1 +\end{array}\right]=\left[\begin{array}{cc} +R_{1}R_{2} & R_{1}t_{2}+t_{1}\\ +0 & 1 +\end{array}\right] +\] + +\end_inset + +Hence, an alternative way of writing down elements of +\begin_inset Formula $\SEtwo$ +\end_inset + + is as the ordered pair +\begin_inset Formula $(R,\, t)$ +\end_inset + +, with composition defined a +\begin_inset Formula +\[ +(R_{1},\, t_{1})(R_{2},\, t_{2})=(R_{1}R_{2},\, R{}_{1}t_{2}+t_{1}) +\] + +\end_inset + + +\end_layout + +\begin_layout Standard +The corresponding Lie algebra +\begin_inset Formula $\setwo$ +\end_inset + + is the vector space of +\begin_inset Formula $3\times3$ +\end_inset + + twists +\begin_inset Formula $\xihat$ +\end_inset + + parameterized by the +\emph on +twist coordinates +\emph default + +\begin_inset Formula $\xi\in\Rthree$ +\end_inset + +, with the mapping +\begin_inset Formula +\[ +\xi\define\left[\begin{array}{c} +v\\ +\omega +\end{array}\right]\rightarrow\xihat\define\left[\begin{array}{cc} +\skew{\omega} & v\\ +0 & 0 +\end{array}\right] +\] + +\end_inset + +Note we think of robots as having a pose +\begin_inset Formula $(x,y,\theta)$ +\end_inset + + and hence I reserved the first two components for translation and the last + for rotation. + +\family roman +\series medium +\shape up +\size normal +\emph off +\bar no +\noun off +\color none +The corresponding Lie group generators are +\begin_inset Formula +\[ +G^{x}=\left[\begin{array}{ccc} +0 & 0 & 1\\ +0 & 0 & 0\\ +0 & 0 & 0 +\end{array}\right]\mbox{ }G^{y}=\left[\begin{array}{ccc} +0 & 0 & 0\\ +0 & 0 & 1\\ +0 & 0 & 0 +\end{array}\right]\mbox{ }G^{\theta}=\left[\begin{array}{ccc} +0 & -1 & 0\\ +1 & 0 & 0\\ +0 & 0 & 0 +\end{array}\right] +\] + +\end_inset + + +\family default +\series default +\shape default +\size default +\emph default +\bar default +\noun default +\color inherit +Applying the exponential map to a twist +\begin_inset Formula $\xi$ +\end_inset + + yields a screw motion yielding an element in +\begin_inset Formula $\SEtwo$ +\end_inset + +: +\begin_inset Formula +\[ +T=e^{\xihat}=\left(e^{\skew{\omega}},(I-e^{\skew{\omega}})\frac{v^{\perp}}{\omega}\right) +\] + +\end_inset + + +\end_layout + +\begin_layout Subsection +The Adjoint Map +\end_layout + +\begin_layout Standard +The adjoint is +\begin_inset Formula +\begin{eqnarray} +\Ad T{\xihat} & = & T\xihat T^{-1}\nonumber \\ + & = & \left[\begin{array}{cc} +R & t\\ +0 & 1 +\end{array}\right]\left[\begin{array}{cc} +\skew{\omega} & v\\ +0 & 0 +\end{array}\right]\left[\begin{array}{cc} +R^{T} & -R^{T}t\\ +0 & 1 +\end{array}\right]\nonumber \\ + & = & \left[\begin{array}{cc} +\skew{\omega} & -\skew{\omega}t+Rv\\ +0 & 0 +\end{array}\right]\nonumber \\ + & = & \left[\begin{array}{cc} +\skew{\omega} & Rv-\omega R_{\pi/2}t\\ +0 & 0 +\end{array}\right]\label{eq:adjointSE2} +\end{eqnarray} + +\end_inset + +From this we can express the Adjoint map in terms of plane twist coordinates: +\begin_inset Formula +\[ +\left[\begin{array}{c} +v'\\ +\omega' +\end{array}\right]=\left[\begin{array}{cc} +R & -R_{\pi/2}t\\ +0 & 1 +\end{array}\right]\left[\begin{array}{c} +v\\ +\omega +\end{array}\right] +\] + +\end_inset + + +\end_layout + +\begin_layout Subsection +Actions +\end_layout + +\begin_layout Standard +The action of +\begin_inset Formula $\SEtwo$ +\end_inset + + on 2D points is done by embedding the points in +\begin_inset Formula $\mathbb{R}^{3}$ +\end_inset + + by using homogeneous coordinates +\begin_inset Formula +\[ +\hat{q}=\left[\begin{array}{c} +q\\ +1 +\end{array}\right]=\left[\begin{array}{cc} +R & t\\ +0 & 1 +\end{array}\right]\left[\begin{array}{c} +p\\ +1 +\end{array}\right]=T\hat{p} +\] + +\end_inset + +Analoguous to +\begin_inset Formula $\SEthree$ +\end_inset + +, we can compute a velocity +\begin_inset Formula $\xihat\hat{p}$ +\end_inset + + in the local +\begin_inset Formula $T$ +\end_inset + + frame: +\begin_inset Formula +\[ +\xihat\hat{p}=\left[\begin{array}{cc} +\skew{\omega} & v\\ +0 & 0 +\end{array}\right]\left[\begin{array}{c} +p\\ +1 +\end{array}\right]=\left[\begin{array}{c} +\skew{\omega}p+v\\ +0 +\end{array}\right] +\] + +\end_inset + +By only taking the top two rows, we can write this as a velocity in +\begin_inset Formula $\Rtwo$ +\end_inset + +, as the product of a +\begin_inset Formula $2\times3$ +\end_inset + + matrix +\begin_inset Formula $H_{p}$ +\end_inset + + that acts upon the exponential coordinates +\begin_inset Formula $\xi$ +\end_inset + + directly: +\begin_inset Formula +\[ +\skew{\omega}p+v=v+R_{\pi/2}p\omega=\left[\begin{array}{cc} +I_{2} & R_{\pi/2}p\end{array}\right]\left[\begin{array}{c} +v\\ +\omega +\end{array}\right]=H_{p}\xi +\] + +\end_inset + + +\end_layout + +\begin_layout Standard +\begin_inset Newpage pagebreak +\end_inset + + +\end_layout + +\begin_layout Section +3D Rotations +\end_layout + +\begin_layout Subsection +Basics +\end_layout + +\begin_layout Standard +The Lie group +\begin_inset Formula $\SOthree$ +\end_inset + + is a subgroup of the general linear group +\begin_inset Formula $GL(3)$ +\end_inset + + of +\begin_inset Formula $3\times3$ +\end_inset + + invertible matrices. + Its Lie algebra +\begin_inset Formula $\sothree$ +\end_inset + + is the vector space of +\begin_inset Formula $3\times3$ +\end_inset + + skew-symmetric matrices +\begin_inset Formula $\what$ +\end_inset + +. + Since +\begin_inset Formula $\SOthree$ +\end_inset + + is a three-dimensional manifold, +\begin_inset Formula $\sothree$ +\end_inset + + is isomorphic to +\begin_inset Formula $\Rthree$ +\end_inset + + and we define the map +\begin_inset Formula +\[ +\hat{}:\Rthree\rightarrow\sothree +\] + +\end_inset + + +\begin_inset Formula +\[ +\hat{}:\omega\rightarrow\what=\Skew{\omega} +\] + +\end_inset + +which maps 3-vectors +\begin_inset Formula $\omega$ +\end_inset + + to skew-symmetric matrices +\begin_inset Formula $\Skew{\omega}$ +\end_inset + + : +\begin_inset Formula +\[ +\Skew{\omega}=\left[\begin{array}{ccc} +0 & -\omega_{z} & \omega_{y}\\ +\omega_{z} & 0 & -\omega_{x}\\ +-\omega_{y} & \omega_{x} & 0 +\end{array}\right]=\omega_{x}G^{x}+\omega_{y}G^{y}+\omega_{z}G^{z} +\] + +\end_inset + +Here the matrices +\begin_inset Formula $G^{i}$ +\end_inset + + are the generators for +\begin_inset Formula $\SOthree$ +\end_inset + +, +\begin_inset Formula +\[ +G^{x}=\left(\begin{array}{ccc} +0 & 0 & 0\\ +0 & 0 & -1\\ +0 & 1 & 0 +\end{array}\right)\mbox{}G^{y}=\left(\begin{array}{ccc} +0 & 0 & 1\\ +0 & 0 & 0\\ +-1 & 0 & 0 +\end{array}\right)\mbox{ }G^{z}=\left(\begin{array}{ccc} +0 & -1 & 0\\ +1 & 0 & 0\\ +0 & 0 & 0 +\end{array}\right) +\] + +\end_inset + +corresponding to a rotation around +\begin_inset Formula $X$ +\end_inset + +, +\begin_inset Formula $Y$ +\end_inset + +, and +\begin_inset Formula $Z$ +\end_inset + +, respectively. + The Lie bracket +\begin_inset Formula $[x,y]$ +\end_inset + + in +\begin_inset Formula $\sothree$ +\end_inset + + corresponds to the cross product +\begin_inset Formula $x\times y$ +\end_inset + + in +\begin_inset Formula $\Rthree$ +\end_inset + +. +\end_layout + +\begin_layout Standard +Hence, for every +\begin_inset Formula $3$ +\end_inset + +-vector +\begin_inset Formula $\omega$ +\end_inset + + there is a corresponding rotation matrix +\begin_inset Formula +\[ +R=e^{\Skew{\omega}} +\] + +\end_inset + +which defines a canonical parameterization of +\begin_inset Formula $\SOthree$ +\end_inset + +, with +\begin_inset Formula $\omega$ +\end_inset + + known as the canonical or exponential coordinates. + It is equivalent to the axis-angle representation for rotations, where + the unit vector +\begin_inset Formula $\omega/\theta$ +\end_inset + + defines the rotation axis, and its magnitude the amount of rotation +\begin_inset Formula $\theta$ +\end_inset + +. + +\end_layout + +\begin_layout Standard +The exponential map can be computed in closed form using +\series bold +Rodrigues' formula +\series default + +\begin_inset CommandInset citation +LatexCommand cite +after "page 28" +key "Murray94book" + +\end_inset + +: +\end_layout + +\begin_layout Standard +\begin_inset Formula +\begin{equation} +e^{\what}=I+\frac{\sin\theta}{\theta}\what+\frac{1\text{−}\cos\theta}{\theta^{2}}\what^{2}\label{eq:Rodrigues} +\end{equation} + +\end_inset + +where +\begin_inset Formula $\what^{2}=\omega\omega^{T}-I$ +\end_inset + +, with +\begin_inset Formula $\omega\omega^{T}$ +\end_inset + + the outer product of +\begin_inset Formula $\omega$ +\end_inset + +. + Hence, a slightly more efficient variant is +\begin_inset Formula +\begin{equation} +e^{\what}=\left(\cos\theta\right)I+\frac{\sin\theta}{\theta}\what+\frac{1\text{−}cos\theta}{\theta^{2}}\omega\omega^{T}\label{eq:Rodrigues2} +\end{equation} + +\end_inset + + +\end_layout + +\begin_layout Subsection +Diagonalized Form +\end_layout + +\begin_layout Standard +Because a 3D rotation +\begin_inset Formula $R$ +\end_inset + + leaves the axis +\begin_inset Formula $\omega$ +\end_inset + + unchanged, +\begin_inset Formula $R$ +\end_inset + + can be diagonalized as +\begin_inset Formula +\[ +R=C\left(\begin{array}{ccc} +e^{-i\theta} & 0 & 0\\ +0 & e^{i\theta} & 0\\ +0 & 0 & 1 +\end{array}\right)C^{-1} +\] + +\end_inset + +with +\begin_inset Formula $C=\left(\begin{array}{ccc} +c_{1} & c_{2} & \omega/\theta\end{array}\right)$ +\end_inset + +, where +\begin_inset Formula $c_{1}$ +\end_inset + + and +\begin_inset Formula $c_{2}$ +\end_inset + + are the complex eigenvectors corresponding to the 2D rotation around +\begin_inset Formula $\omega$ +\end_inset + +. + This also means that, by +\begin_inset CommandInset ref +LatexCommand eqref +reference "eq:matrixAdjoint" + +\end_inset + +, +\begin_inset Formula +\[ +\hat{\omega}=C\left(\begin{array}{ccc} +-i\theta & 0 & 0\\ +0 & i\theta & 0\\ +0 & 0 & 0 +\end{array}\right)C^{-1} +\] + +\end_inset + +In this case, +\begin_inset Formula $C$ +\end_inset + + has complex columns, but we also have +\begin_inset Formula +\begin{equation} +\hat{\omega}=B\left(\begin{array}{ccc} +0 & -\theta & 0\\ +\theta & 0 & 0\\ +0 & 0 & 0 +\end{array}\right)B^{T}\label{eq:OmegaDecomposed} +\end{equation} + +\end_inset + +with +\begin_inset Formula $B=\left(\begin{array}{ccc} +b_{1} & b_{2} & \omega/\theta\end{array}\right)$ +\end_inset + +, where +\begin_inset Formula $b_{1}$ +\end_inset + + and +\begin_inset Formula $b_{2}$ +\end_inset + + form a basis for the 2D plane through the origin and perpendicular to +\begin_inset Formula $\omega$ +\end_inset + +. + Clearly, from Section +\begin_inset CommandInset ref +LatexCommand ref +reference "sub:Diagonalized2D" + +\end_inset + +, we have +\begin_inset Formula +\[ +c_{1}=B\left(\begin{array}{c} +1\\ +i\\ +0 +\end{array}\right)\mbox{\,\,\,\ and\,\,\,\,\,}c_{2}=B\left(\begin{array}{c} +i\\ +1\\ +0 +\end{array}\right) +\] + +\end_inset + +and when we exponentiate +\begin_inset CommandInset ref +LatexCommand eqref +reference "eq:OmegaDecomposed" + +\end_inset + + we expose the 2D rotation around the axis +\begin_inset Formula $\omega/\theta$ +\end_inset + + with magnitude +\begin_inset Formula $\theta$ +\end_inset + +: +\begin_inset Formula +\[ +R=B\left(\begin{array}{ccc} +\cos\theta & -\sin\theta & 0\\ +\sin\theta & \cos\theta & 0\\ +0 & 0 & 1 +\end{array}\right)B^{T} +\] + +\end_inset + +The latter form for +\begin_inset Formula $R$ +\end_inset + + can be used to prove Rodrigues' formula. + Expanding the above, we get +\begin_inset Formula +\[ +R=\left(\cos\theta\right)\left(b_{1}b_{1}^{T}+b_{2}b_{2}^{T}\right)+\left(\sin\theta\right)\left(b_{2}b_{1}^{T}-b_{1}b_{2}^{T}\right)+\omega\omega^{T}/\theta^{2} +\] + +\end_inset + + +\family roman +\series medium +\shape up +\size normal +\emph off +\bar no +\strikeout off +\uuline off +\uwave off +\noun off +\color none + +\begin_inset Note Note +status collapsed + +\begin_layout Plain Layout + +\family roman +\series medium +\shape up +\size normal +\emph off +\bar no +\strikeout off +\uuline off +\uwave off +\noun off +\color none +\begin_inset Formula +\begin{eqnarray*} +R & = & \left(\begin{array}{ccc} +b_{1} & b_{2} & \omega/\theta\end{array}\right)\left(\begin{array}{ccc} +\cos\theta & -\sin\theta & 0\\ +\sin\theta & \cos\theta & 0\\ +0 & 0 & 1 +\end{array}\right)\left(\begin{array}{c} +b_{1}^{T}\\ +b_{2}^{T}\\ +\omega^{T}/\theta +\end{array}\right)\\ + & = & \left(\begin{array}{ccc} +b_{1} & b_{2} & \omega/\theta\end{array}\right)\left(\begin{array}{c} +b_{1}^{T}\cos\theta-b_{2}^{T}\sin\theta\\ +b_{1}^{T}\sin\theta+b_{2}^{T}\cos\theta\\ +\omega^{T}/\theta +\end{array}\right)\\ + & = & b_{1}b_{1}^{T}\cos\theta-b_{1}b_{2}^{T}\sin\theta+b_{2}b_{1}^{T}\sin\theta+b_{2}b_{2}^{T}\cos\theta+\omega\omega^{T}/\theta^{2} +\end{eqnarray*} + +\end_inset + + +\end_layout + +\end_inset + +Because +\begin_inset Formula $B$ +\end_inset + + is a rotation matrix, we have +\begin_inset Formula $BB^{T}=b_{1}b_{1}^{T}+b_{2}b_{2}^{T}+\omega\omega^{T}/\theta^{2}=I$ +\end_inset + +, and using +\begin_inset CommandInset ref +LatexCommand eqref +reference "eq:OmegaDecomposed" + +\end_inset + + it is easy to show that +\begin_inset Formula $b_{2}b_{1}^{T}-b_{1}b_{2}^{T}=\hat{\omega}/\theta$ +\end_inset + +, hence +\family default +\series default +\shape default +\size default +\emph default +\bar default +\strikeout default +\uuline default +\uwave default +\noun default +\color inherit + +\begin_inset Formula +\[ +R=\left(\cos\theta\right)(I-\omega\omega^{T}/\theta^{2})+\left(\sin\theta\right)\left(\hat{\omega}/\theta\right)+\omega\omega^{T}/\theta^{2} +\] + +\end_inset + +which is equivalent to +\begin_inset CommandInset ref +LatexCommand eqref +reference "eq:Rodrigues2" + +\end_inset + +. +\end_layout + +\begin_layout Subsection +The Adjoint Map +\end_layout + +\begin_layout Standard +For rotation matrices +\begin_inset Formula $R$ +\end_inset + + we can prove the following identity (see +\begin_inset CommandInset ref +LatexCommand vref +reference "proof1" + +\end_inset + +): +\begin_inset Formula +\begin{equation} +R\Skew{\omega}R^{T}=\Skew{R\omega}\label{eq:property1} +\end{equation} + +\end_inset + +Hence, given property +\begin_inset CommandInset ref +LatexCommand eqref +reference "eq:property1" + +\end_inset + +, the adjoint map for +\begin_inset Formula $\sothree$ +\end_inset + + simplifies to +\begin_inset Formula +\[ +\Ad R{\Skew{\omega}}=R\Skew{\omega}R^{T}=\Skew{R\omega} +\] + +\end_inset + +and this can be expressed in exponential coordinates simply by rotating + the axis +\begin_inset Formula $\omega$ +\end_inset + + to +\begin_inset Formula $R\omega$ +\end_inset + +. + +\end_layout + +\begin_layout Standard +As an example, to apply an axis-angle rotation +\begin_inset Formula $\omega$ +\end_inset + + to a point +\begin_inset Formula $p$ +\end_inset + + in the frame +\begin_inset Formula $R$ +\end_inset + +, we could: +\end_layout + +\begin_layout Enumerate +First transform +\begin_inset Formula $p$ +\end_inset + + back to the world frame, apply +\begin_inset Formula $\omega$ +\end_inset + +, and then rotate back: +\begin_inset Formula +\[ +q=Re^{\Skew{\omega}}R^{T} +\] + +\end_inset + + +\end_layout + +\begin_layout Enumerate +Immediately apply the transformed axis-angle transformation +\begin_inset Formula $\Ad R{\Skew{\omega}}=\Skew{R\omega}$ +\end_inset + +: +\begin_inset Formula +\[ +q=e^{\Skew{R\omega}}p +\] + +\end_inset + + +\end_layout + +\begin_layout Subsection +Actions +\end_layout + +\begin_layout Standard +In the case of +\begin_inset Formula $\SOthree$ +\end_inset + + the vector space is +\begin_inset Formula $\Rthree$ +\end_inset + +, and the group action corresponds to rotating a point +\begin_inset Formula +\[ +q=Rp +\] + +\end_inset + +We would now like to know what an incremental rotation parameterized by + +\begin_inset Formula $\omega$ +\end_inset + + would do: +\begin_inset Formula +\[ +q(\omega)=Re^{\Skew{\omega}}p +\] + +\end_inset + +hence the derivative is: +\begin_inset Formula +\[ +\deriv{q(\omega)}{\omega}=R\deriv{}{\omega}\left(e^{\Skew{\omega}}p\right)=R\deriv{}{\omega}\left(\Skew{\omega}p\right)=R\Skew{-p} +\] + +\end_inset + +To show the last equality note that +\begin_inset Formula +\[ +\Skew{\omega}p=\omega\times p=-p\times\omega=\Skew{-p}\omega +\] + +\end_inset + + +\end_layout + +\begin_layout Standard +\begin_inset Newpage pagebreak +\end_inset + + +\end_layout + +\begin_layout Section +3D Rigid Transformations +\end_layout + +\begin_layout Standard +The Lie group +\begin_inset Formula $\SEthree$ +\end_inset + + is a subgroup of the general linear group +\begin_inset Formula $GL(4)$ +\end_inset + + of +\begin_inset Formula $4\times4$ +\end_inset + + invertible matrices of the form +\begin_inset Formula +\[ +T\define\left[\begin{array}{cc} +R & t\\ +0 & 1 +\end{array}\right] +\] + +\end_inset + +where +\begin_inset Formula $R\in\SOthree$ +\end_inset + + is a rotation matrix and +\begin_inset Formula $t\in\Rthree$ +\end_inset + + is a translation vector. + An alternative way of writing down elements of +\begin_inset Formula $\SEthree$ +\end_inset + + is as the ordered pair +\begin_inset Formula $(R,\, t)$ +\end_inset + +, with composition defined as +\begin_inset Formula +\[ +(R_{1},\, t_{1})(R_{2},\, t_{2})=(R_{1}R_{2},\, R{}_{1}t_{2}+t_{1}) +\] + +\end_inset + + Its Lie algebra +\begin_inset Formula $\sethree$ +\end_inset + + is the vector space of +\begin_inset Formula $4\times4$ +\end_inset + + twists +\begin_inset Formula $\xihat$ +\end_inset + + parameterized by the +\emph on +twist coordinates +\emph default + +\begin_inset Formula $\xi\in\Rsix$ +\end_inset + +, with the mapping +\begin_inset CommandInset citation +LatexCommand cite +key "Murray94book" + +\end_inset + + +\begin_inset Formula +\[ +\xi\define\left[\begin{array}{c} +\omega\\ +v +\end{array}\right]\rightarrow\xihat\define\left[\begin{array}{cc} +\Skew{\omega} & v\\ +0 & 0 +\end{array}\right] +\] + +\end_inset + +Note we follow Frank Park's convention and reserve the first three components + for rotation, and the last three for translation. + Hence, with this parameterization, the generators for +\begin_inset Formula $\SEthree$ +\end_inset + + are +\begin_inset Formula +\[ +G^{1}=\left(\begin{array}{cccc} +0 & 0 & 0 & 0\\ +0 & 0 & -1 & 0\\ +0 & 1 & 0 & 0\\ +0 & 0 & 0 & 0 +\end{array}\right)\mbox{}G^{2}=\left(\begin{array}{cccc} +0 & 0 & 1 & 0\\ +0 & 0 & 0 & 0\\ +-1 & 0 & 0 & 0\\ +0 & 0 & 0 & 0 +\end{array}\right)\mbox{ }G^{3}=\left(\begin{array}{cccc} +0 & -1 & 0 & 0\\ +1 & 0 & 0 & 0\\ +0 & 0 & 0 & 0\\ +0 & 0 & 0 & 0 +\end{array}\right) +\] + +\end_inset + + +\begin_inset Formula +\[ +G^{4}=\left(\begin{array}{cccc} +0 & 0 & 0 & 1\\ +0 & 0 & 0 & 0\\ +0 & 0 & 0 & 0\\ +0 & 0 & 0 & 0 +\end{array}\right)\mbox{}G^{5}=\left(\begin{array}{cccc} +0 & 0 & 0 & 0\\ +0 & 0 & 0 & 1\\ +0 & 0 & 0 & 0\\ +0 & 0 & 0 & 0 +\end{array}\right)\mbox{ }G^{6}=\left(\begin{array}{cccc} +0 & 0 & 0 & 0\\ +0 & 0 & 0 & 0\\ +0 & 0 & 0 & 1\\ +0 & 0 & 0 & 0 +\end{array}\right) +\] + +\end_inset + +Applying the exponential map to a twist +\begin_inset Formula $\xi$ +\end_inset + + yields a screw motion yielding an element in +\begin_inset Formula $\SEthree$ +\end_inset + +: +\begin_inset Formula +\[ +T=\exp\xihat +\] + +\end_inset + +A closed form solution for the exponential map is given in +\begin_inset CommandInset citation +LatexCommand cite +after "page 42" +key "Murray94book" + +\end_inset + +. +\end_layout + +\begin_layout Standard + +\family roman +\series medium +\shape up +\size normal +\emph off +\bar no +\noun off +\color none +\begin_inset Formula +\[ +\exp\left(\left[\begin{array}{c} +\omega\\ +v +\end{array}\right]t\right)=\left[\begin{array}{cc} +e^{\Skew{\omega}t} & (I-e^{\Skew{\omega}t})\left(\omega\times v\right)+\omega\omega^{T}vt\\ +0 & 1 +\end{array}\right] +\] + +\end_inset + + +\end_layout + +\begin_layout Subsection +The Adjoint Map +\end_layout + +\begin_layout Standard +The adjoint is +\begin_inset Formula +\begin{eqnarray*} +\Ad T{\xihat} & = & T\xihat T^{-1}\\ + & = & \left[\begin{array}{cc} +R & t\\ +0 & 1 +\end{array}\right]\left[\begin{array}{cc} +\Skew{\omega} & v\\ +0 & 0 +\end{array}\right]\left[\begin{array}{cc} +R^{T} & -R^{T}t\\ +0 & 1 +\end{array}\right]\\ + & = & \left[\begin{array}{cc} +\Skew{R\omega} & -\Skew{R\omega}t+Rv\\ +0 & 0 +\end{array}\right]\\ + & = & \left[\begin{array}{cc} +\Skew{R\omega} & t\times R\omega+Rv\\ +0 & 0 +\end{array}\right] +\end{eqnarray*} + +\end_inset + +From this we can express the Adjoint map in terms of twist coordinates (see + also +\begin_inset CommandInset citation +LatexCommand cite +key "Murray94book" + +\end_inset + + and FP): +\begin_inset Formula +\[ +\left[\begin{array}{c} +\omega'\\ +v' +\end{array}\right]=\left[\begin{array}{cc} +R & 0\\ +\Skew tR & R +\end{array}\right]\left[\begin{array}{c} +\omega\\ +v +\end{array}\right] +\] + +\end_inset + + +\end_layout + +\begin_layout Subsection +Actions +\end_layout + +\begin_layout Standard +The action of +\begin_inset Formula $\SEthree$ +\end_inset + + on 3D points is done by embedding the points in +\begin_inset Formula $\mathbb{R}^{4}$ +\end_inset + + by using homogeneous coordinates +\begin_inset Formula +\[ +\hat{q}=\left[\begin{array}{c} +q\\ +1 +\end{array}\right]=\left[\begin{array}{c} +Rp+t\\ +1 +\end{array}\right]=\left[\begin{array}{cc} +R & t\\ +0 & 1 +\end{array}\right]\left[\begin{array}{c} +p\\ +1 +\end{array}\right]=T\hat{p} +\] + +\end_inset + +We would now like to know what an incremental rotation parameterized by + +\begin_inset Formula $\xi$ +\end_inset + + would do: +\begin_inset Formula +\[ +\hat{q}(\xi)=Te^{\xihat}\hat{p} +\] + +\end_inset + +hence the derivative is +\begin_inset Formula +\[ +\deriv{\hat{q}(\xi)}{\xi}=T\deriv{}{\xi}\left(\xihat\hat{p}\right) +\] + +\end_inset + +where +\begin_inset Formula $\xihat\hat{p}$ +\end_inset + + corresponds to a velocity in +\begin_inset Formula $\mathbb{R}^{4}$ +\end_inset + + (in the local +\begin_inset Formula $T$ +\end_inset + + frame): +\begin_inset Formula +\[ +\xihat\hat{p}=\left[\begin{array}{cc} +\Skew{\omega} & v\\ +0 & 0 +\end{array}\right]\left[\begin{array}{c} +p\\ +1 +\end{array}\right]=\left[\begin{array}{c} +\omega\times p+v\\ +0 +\end{array}\right] +\] + +\end_inset + +Notice how velocities are analogous to points at infinity in projective + geometry: they correspond to free vectors indicating a direction and magnitude + of change. +\end_layout + +\begin_layout Standard +By only taking the top three rows, we can write this as a velocity in +\begin_inset Formula $\Rthree$ +\end_inset + +, as the product of a +\begin_inset Formula $3\times6$ +\end_inset + + matrix +\begin_inset Formula $H_{p}$ +\end_inset + + that acts upon the exponential coordinates +\begin_inset Formula $\xi$ +\end_inset + + directly: +\begin_inset Formula +\[ +\omega\times p+v=-p\times\omega+v=\left[\begin{array}{cc} +-\Skew p & I_{3}\end{array}\right]\left[\begin{array}{c} +\omega\\ +v +\end{array}\right] +\] + +\end_inset + +The inverse action +\begin_inset Formula $T^{-1}p$ +\end_inset + + is +\begin_inset Formula +\[ +\hat{q}=\left[\begin{array}{c} +q\\ +1 +\end{array}\right]=\left[\begin{array}{c} +R^{T}(p-t)\\ +1 +\end{array}\right]=\left[\begin{array}{cc} +R^{T} & -R^{T}t\\ +0 & 1 +\end{array}\right]\left[\begin{array}{c} +p\\ +1 +\end{array}\right]=T^{-1}\hat{p} +\] + +\end_inset + + +\end_layout + +\begin_layout Standard +\begin_inset Newpage pagebreak +\end_inset + + +\end_layout + +\begin_layout Section +2D Affine Transformations +\end_layout + +\begin_layout Standard +The Lie group +\begin_inset Formula $Aff(2)$ +\end_inset + + is a subgroup of the general linear group +\begin_inset Formula $GL(3)$ +\end_inset + + of +\begin_inset Formula $3\times3$ +\end_inset + + invertible matrices that maps the line infinity to itself, and hence preserves + paralellism. + The affine transformation matrices +\begin_inset Formula $A$ +\end_inset + + can be written as +\begin_inset CommandInset citation +LatexCommand cite +key "Mei08tro" + +\end_inset + + +\family roman +\series medium +\shape up +\size normal +\emph off +\bar no +\noun off +\color none + +\begin_inset Formula +\[ +\left[\begin{array}{ccc} +m_{11} & m_{12} & t_{1}\\ +m_{21} & m_{22} & t_{2}\\ +0 & 0 & k +\end{array}\right] +\] + +\end_inset + +with +\begin_inset Formula $M\in GL(2)$ +\end_inset + +, +\begin_inset Formula $t\in\Rtwo$ +\end_inset + +, and +\begin_inset Formula $k$ +\end_inset + + a scalar chosen such that +\begin_inset Formula $det(A)=1$ +\end_inset + +. + +\family default +\series default +\shape default +\size default +\emph default +\bar default +\noun default +\color inherit +Note that just as +\begin_inset Formula $\SEtwo$ +\end_inset + + is a semi-direct product, so too is +\begin_inset Formula $Aff(2)=\Rtwo\rtimes GL(2)$ +\end_inset + +. + In particular, any affine transformation +\begin_inset Formula $A$ +\end_inset + + can be written as +\begin_inset Formula +\[ +A=\left[\begin{array}{cc} +0 & t\\ +0 & 1 +\end{array}\right]\left[\begin{array}{cc} +M & 0\\ +0 & k +\end{array}\right] +\] + +\end_inset + +and they compose as +\begin_inset Formula +\[ +A_{1}A_{2}=\left[\begin{array}{cc} +M_{1} & t_{1}\\ +0 & k_{1} +\end{array}\right]\left[\begin{array}{cc} +M_{2} & t_{2}\\ +0 & k_{2} +\end{array}\right]=\left[\begin{array}{cc} +M_{1}M_{2} & M_{2}t_{2}+k_{2}t_{1}\\ +0 & k_{1}k_{2} +\end{array}\right] +\] + +\end_inset + +From this it can be gleaned that the groups +\begin_inset Formula $\SOtwo$ +\end_inset + + and +\begin_inset Formula $\SEtwo$ +\end_inset + + are both subgroups, with +\begin_inset Formula $\SOtwo\subset\SEtwo\subset\Afftwo$ +\end_inset + +. + +\family roman +\series medium +\shape up +\size normal +\emph off +\bar no +\noun off +\color none +By choosing the generators carefully we maintain this hierarchy among the + associated Lie algebras. + In particular, +\begin_inset Formula $\setwo$ +\end_inset + + +\begin_inset Formula +\[ +G^{1}=\left[\begin{array}{ccc} +0 & 0 & 1\\ +0 & 0 & 0\\ +0 & 0 & 0 +\end{array}\right]\mbox{ }G^{2}=\left[\begin{array}{ccc} +0 & 0 & 0\\ +0 & 0 & 1\\ +0 & 0 & 0 +\end{array}\right]\mbox{ }G^{3}=\left[\begin{array}{ccc} +0 & -1 & 0\\ +1 & 0 & 0\\ +0 & 0 & 0 +\end{array}\right] +\] + +\end_inset + +can be extended to the +\family default +\series default +\shape default +\size default +\emph default +\bar default +\noun default +\color inherit +Lie algebra +\family roman +\series medium +\shape up +\size normal +\emph off +\bar no +\noun off +\color none + +\begin_inset Formula $\afftwo$ +\end_inset + + using the three additional generators +\begin_inset Formula +\[ +G^{4}=\left[\begin{array}{ccc} +0 & 1 & 0\\ +1 & 0 & 0\\ +0 & 0 & 0 +\end{array}\right]\mbox{ }G^{5}=\left[\begin{array}{ccc} +1 & 0 & 0\\ +0 & -1 & 0\\ +0 & 0 & 0 +\end{array}\right]\mbox{ }G^{6}=\left[\begin{array}{ccc} +0 & 0 & 0\\ +0 & -1 & 0\\ +0 & 0 & 1 +\end{array}\right] +\] + +\end_inset + + +\family default +\series default +\shape default +\size default +\emph default +\bar default +\noun default +\color inherit +Hence, the Lie algebra +\begin_inset Formula $\afftwo$ +\end_inset + + is the vector space of +\begin_inset Formula $3\times3$ +\end_inset + + incremental affine transformations +\begin_inset Formula $\ahat$ +\end_inset + + parameterized by 6 parameters +\begin_inset Formula $\aa\in\mathbb{R}^{6}$ +\end_inset + +, with the mapping +\begin_inset Formula +\[ +\aa\rightarrow\ahat\define\left[\begin{array}{ccc} +a_{5} & a_{4}-a_{3} & a_{1}\\ +a_{4}+a_{3} & -a_{5}-a_{6} & a_{2}\\ +0 & 0 & a_{6} +\end{array}\right] +\] + +\end_inset + +Note that +\begin_inset Formula $G_{5}$ +\end_inset + + and +\begin_inset Formula $G_{6}$ +\end_inset + + change the relative scale of +\begin_inset Formula $x$ +\end_inset + + and +\begin_inset Formula $y$ +\end_inset + + but without changing the determinant: +\begin_inset Formula +\[ +e^{xG_{5}}=\exp\left[\begin{array}{ccc} +x & 0 & 0\\ +0 & -x & 0\\ +0 & 0 & 0 +\end{array}\right]=\left[\begin{array}{ccc} +e^{x} & 0 & 0\\ +0 & 1/e^{x} & 0\\ +0 & 0 & 1 +\end{array}\right] +\] + +\end_inset + + +\begin_inset Formula +\[ +e^{xG_{6}}=\exp\left[\begin{array}{ccc} +0 & 0 & 0\\ +0 & -x & 0\\ +0 & 0 & x +\end{array}\right]=\left[\begin{array}{ccc} +1 & 0 & 0\\ +0 & 1/e^{x} & 0\\ +0 & 0 & e^{x} +\end{array}\right] +\] + +\end_inset + +It might be nicer to have the correspondence with scaling +\begin_inset Formula $x$ +\end_inset + + and +\begin_inset Formula $y$ +\end_inset + + more direct, by choosing +\family roman +\series medium +\shape up +\size normal +\emph off +\bar no +\noun off +\color none + +\begin_inset Formula +\[ +\mbox{ }G^{5}=\left[\begin{array}{ccc} +1 & 0 & 0\\ +0 & 0 & 0\\ +0 & 0 & -1 +\end{array}\right]\mbox{ }G^{6}=\left[\begin{array}{ccc} +0 & 0 & 0\\ +0 & 1 & 0\\ +0 & 0 & -1 +\end{array}\right] +\] + +\end_inset + +and hence +\family default +\series default +\shape default +\size default +\emph default +\bar default +\noun default +\color inherit + +\begin_inset Formula +\[ +e^{xG_{5}}=\exp\left[\begin{array}{ccc} +x & 0 & 0\\ +0 & 0 & 0\\ +0 & 0 & -x +\end{array}\right]=\left[\begin{array}{ccc} +e^{x} & 0 & 0\\ +0 & 1 & 0\\ +0 & 0 & 1/e^{x} +\end{array}\right] +\] + +\end_inset + + +\begin_inset Formula +\[ +e^{xG_{6}}=\exp\left[\begin{array}{ccc} +0 & 0 & 0\\ +0 & x & 0\\ +0 & 0 & -x +\end{array}\right]=\left[\begin{array}{ccc} +1 & 0 & 0\\ +0 & e^{x} & 0\\ +0 & 0 & 1/e^{x} +\end{array}\right] +\] + +\end_inset + + +\end_layout + +\begin_layout Section +2D Homographies +\end_layout + +\begin_layout Standard +When viewed as operations on images, represented by 2D projective space + +\begin_inset Formula $\mathcal{P}^{3}$ +\end_inset + +, 3D rotations are a special case of 2D homographies. + These are now treated, loosely based on the exposition in +\begin_inset CommandInset citation +LatexCommand cite +key "Mei06iros,Mei08tro" + +\end_inset + +. +\end_layout + +\begin_layout Subsection +Basics +\end_layout + +\begin_layout Standard +The Lie group +\begin_inset Formula $\SLthree$ +\end_inset + + is a subgroup of the general linear group +\begin_inset Formula $GL(3)$ +\end_inset + + of +\begin_inset Formula $3\times3$ +\end_inset + + invertible matrices with determinant +\begin_inset Formula $1$ +\end_inset + +. + The homographies generalize transformations of the 2D projective space, + and +\begin_inset Formula $\Afftwo\subset\SLthree$ +\end_inset + +. + +\end_layout + +\begin_layout Standard + +\family roman +\series medium +\shape up +\size normal +\emph off +\bar no +\noun off +\color none +We can extend +\begin_inset Formula $\afftwo$ +\end_inset + + to the Lie algebra +\begin_inset Formula $\slthree$ +\end_inset + + by adding two generators +\begin_inset Formula +\[ +G^{7}=\left[\begin{array}{ccc} +0 & 0 & 0\\ +0 & 0 & 0\\ +1 & 0 & 0 +\end{array}\right]\mbox{ }G^{8}=\left[\begin{array}{ccc} +0 & 0 & 0\\ +0 & 0 & 0\\ +0 & 1 & 0 +\end{array}\right] +\] + +\end_inset + + +\family default +\series default +\shape default +\size default +\emph default +\bar default +\noun default +\color inherit +obtaining the vector space of +\begin_inset Formula $3\times3$ +\end_inset + + incremental homographies +\begin_inset Formula $\hhat$ +\end_inset + + parameterized by 8 parameters +\begin_inset Formula $\hh\in\mathbb{R}^{8}$ +\end_inset + +, with the mapping +\begin_inset Formula +\[ +h\rightarrow\hhat\define\left[\begin{array}{ccc} +h_{5} & h_{4}-h_{3} & h_{1}\\ +h_{4}+h_{3} & -h_{5}-h_{6} & h_{2}\\ +h_{7} & h_{8} & h_{6} +\end{array}\right] +\] + +\end_inset + + +\end_layout + +\begin_layout Subsection +Tensor Notation +\end_layout + +\begin_layout Itemize +A homography between 2D projective spaces +\begin_inset Formula $A$ +\end_inset + + and +\begin_inset Formula $B$ +\end_inset + + can be written in tensor notation +\begin_inset Formula $H_{A}^{B}$ +\end_inset + + +\end_layout + +\begin_layout Itemize +Applying a homography is then a tensor contraction +\begin_inset Formula $x^{B}=H_{A}^{B}x^{A}$ +\end_inset + +, mapping points in +\begin_inset Formula $A$ +\end_inset + + to points in +\begin_inset Formula $B$ +\end_inset + +. +\end_layout + +\begin_layout Standard +\begin_inset Note Note +status collapsed + +\begin_layout Plain Layout +The inverse of a homography can be found by contracting with two permutation + tensors: +\begin_inset Formula +\[ +H_{B}^{A}=H_{A_{1}}^{B_{1}}H_{A_{2}}^{B_{2}}\epsilon_{B_{1}B_{2}B}\epsilon^{A_{1}A_{2}A} +\] + +\end_inset + + +\end_layout + +\end_inset + + +\begin_inset Note Note +status collapsed + +\begin_layout Subsection +The Adjoint Map +\end_layout + +\begin_layout Plain Layout +The adjoint can be done using tensor notation. + Denoting an incremental homography in space +\begin_inset Formula $A$ +\end_inset + + as +\begin_inset Formula $\hhat_{A_{1}}^{A_{2}}$ +\end_inset + +, we have, for example for +\begin_inset Formula $G_{1}$ +\end_inset + + +\begin_inset Formula +\begin{eqnarray*} +\hhat_{B_{1}}^{B_{2}}=\Ad{H_{A}^{B}}{\hhat_{A_{1}}^{A_{2}}} & = & H_{A_{2}}^{B_{2}}\hhat_{A_{1}}^{A_{2}}H_{B_{1}}^{A_{1}}\\ + & = & H_{A_{2}}^{B_{2}}\left[\begin{array}{ccc} +0 & 0 & 1\\ +0 & 0 & 0\\ +0 & 0 & 0 +\end{array}\right]H_{A_{2}}^{B_{2}}H_{A_{3}}^{B_{3}}\epsilon_{B_{1}B_{2}B_{3}}\epsilon^{A_{1}A_{2}A_{3}}\\ + & = & H_{1}^{B_{2}}H_{A_{2}}^{B_{2}}H_{A_{3}}^{B_{3}}\epsilon_{B_{1}B_{2}B_{3}}\epsilon^{3A_{2}A_{3}} +\end{eqnarray*} + +\end_inset + +This does not seem to help. +\end_layout + +\end_inset + + +\end_layout + +\begin_layout Standard +\begin_inset Newpage pagebreak +\end_inset + + +\end_layout + +\begin_layout Section* +Appendix: Proof of Property +\begin_inset CommandInset ref +LatexCommand ref +reference "proof1" + +\end_inset + + +\end_layout + +\begin_layout Standard +We can prove the following identity for rotation matrices +\begin_inset Formula $R$ +\end_inset + +, +\begin_inset Formula +\begin{eqnarray} +R\Skew{\omega}R^{T} & = & R\Skew{\omega}\left[\begin{array}{ccc} +a_{1} & a_{2} & a_{3}\end{array}\right]\nonumber \\ + & = & R\left[\begin{array}{ccc} +\omega\times a_{1} & \omega\times a_{2} & \omega\times a_{3}\end{array}\right]\nonumber \\ + & = & \left[\begin{array}{ccc} +a_{1}(\omega\times a_{1}) & a_{1}(\omega\times a_{2}) & a_{1}(\omega\times a_{3})\\ +a_{2}(\omega\times a_{1}) & a_{2}(\omega\times a_{2}) & a_{2}(\omega\times a_{3})\\ +a_{3}(\omega\times a_{1}) & a_{3}(\omega\times a_{2}) & a_{3}(\omega\times a_{3}) +\end{array}\right]\nonumber \\ + & = & \left[\begin{array}{ccc} +\omega(a_{1}\times a_{1}) & \omega(a_{2}\times a_{1}) & \omega(a_{3}\times a_{1})\\ +\omega(a_{1}\times a_{2}) & \omega(a_{2}\times a_{2}) & \omega(a_{3}\times a_{2})\\ +\omega(a_{1}\times a_{3}) & \omega(a_{2}\times a_{3}) & \omega(a_{3}\times a_{3}) +\end{array}\right]\nonumber \\ + & = & \left[\begin{array}{ccc} +0 & -\omega a_{3} & \omega a_{2}\\ +\omega a_{3} & 0 & -\omega a_{1}\\ +-\omega a_{2} & \omega a_{1} & 0 +\end{array}\right]\nonumber \\ + & = & \Skew{R\omega}\label{proof1} +\end{eqnarray} + +\end_inset + +where +\begin_inset Formula $a_{1}$ +\end_inset + +, +\begin_inset Formula $a_{2}$ +\end_inset + +, and +\begin_inset Formula $a_{3}$ +\end_inset + + are the +\emph on +rows +\emph default + of +\begin_inset Formula $R$ +\end_inset + +. + Above we made use of the orthogonality of rotation matrices and the triple + product rule: +\begin_inset Formula +\[ +a(b\times c)=b(c\times a)=c(a\times b) +\] + +\end_inset + +Similarly, without proof +\begin_inset CommandInset citation +LatexCommand cite +after "Lemma 2.3" +key "Murray94book" + +\end_inset + +: +\begin_inset Formula +\[ +R(a\times b)=Ra\times Rb +\] + +\end_inset + + +\end_layout + +\begin_layout Section* +Appendix: Alternative Generators for +\begin_inset Formula $\slthree$ +\end_inset + + +\end_layout + +\begin_layout Standard +\begin_inset CommandInset citation +LatexCommand cite +key "Mei06iros" + +\end_inset + + uses the following generators for +\begin_inset Formula $\slthree$ +\end_inset + +: +\family roman +\series medium +\shape up +\size normal +\emph off +\bar no +\noun off +\color none + +\begin_inset Formula +\[ +G^{1}=\left[\begin{array}{ccc} +0 & 0 & 1\\ +0 & 0 & 0\\ +0 & 0 & 0 +\end{array}\right]\mbox{ }G^{2}=\left[\begin{array}{ccc} +0 & 0 & 0\\ +0 & 0 & 1\\ +0 & 0 & 0 +\end{array}\right]\mbox{ }G^{3}=\left[\begin{array}{ccc} +0 & 1 & 0\\ +0 & 0 & 0\\ +0 & 0 & 0 +\end{array}\right] +\] + +\end_inset + + +\begin_inset Formula +\[ +G^{4}=\left[\begin{array}{ccc} +0 & 0 & 0\\ +1 & 0 & 0\\ +0 & 0 & 0 +\end{array}\right]\mbox{ }G^{5}=\left[\begin{array}{ccc} +1 & 0 & 0\\ +0 & -1 & 0\\ +0 & 0 & 0 +\end{array}\right]\mbox{ }G^{6}=\left[\begin{array}{ccc} +0 & 0 & 0\\ +0 & -1 & 0\\ +0 & 0 & 1 +\end{array}\right] +\] + +\end_inset + + +\begin_inset Formula +\[ +G^{7}=\left[\begin{array}{ccc} +0 & 0 & 0\\ +0 & 0 & 0\\ +1 & 0 & 0 +\end{array}\right]\mbox{ }G^{8}=\left[\begin{array}{ccc} +0 & 0 & 0\\ +0 & 0 & 0\\ +0 & 1 & 0 +\end{array}\right] +\] + +\end_inset + + +\family default +\series default +\shape default +\size default +\emph default +\bar default +\noun default +\color inherit +We choose to use a different linear combination as the basis. +\end_layout + +\begin_layout Standard +\begin_inset CommandInset bibtex +LatexCommand bibtex +bibfiles "../../../papers/refs" +options "plain" + +\end_inset + + +\end_layout + +\end_body +\end_document diff --git a/doc/LieGroups.pdf b/doc/LieGroups.pdf new file mode 100644 index 000000000..f271f35c0 Binary files /dev/null and b/doc/LieGroups.pdf differ diff --git a/doc/cholesky.lyx b/doc/cholesky.lyx new file mode 100644 index 000000000..99157fadc --- /dev/null +++ b/doc/cholesky.lyx @@ -0,0 +1,170 @@ +#LyX 1.6.7 created this file. For more info see http://www.lyx.org/ +\lyxformat 345 +\begin_document +\begin_header +\textclass article +\use_default_options true +\language english +\inputencoding auto +\font_roman default +\font_sans default +\font_typewriter default +\font_default_family default +\font_sc false +\font_osf false +\font_sf_scale 100 +\font_tt_scale 100 + +\graphics default +\paperfontsize default +\use_hyperref false +\papersize default +\use_geometry false +\use_amsmath 1 +\use_esint 1 +\cite_engine basic +\use_bibtopic false +\paperorientation portrait +\secnumdepth 3 +\tocdepth 3 +\paragraph_separation indent +\defskip medskip +\quotes_language english +\papercolumns 1 +\papersides 1 +\paperpagestyle default +\tracking_changes false +\output_changes false +\author "" +\author "" +\end_header + +\begin_body + +\begin_layout Section +Basic solving with Cholesky +\end_layout + +\begin_layout Standard +Solving a linear least-squares system: +\begin_inset Formula \[ +\arg\min_{x}\left\Vert Ax-b\right\Vert ^{2}\] + +\end_inset + +Set derivative equal to zero: +\begin_inset Formula \begin{align*} +0 & =2A^{T}\left(Ax-b\right)\\ +0 & =A^{T}Ax-A^{T}b\end{align*} + +\end_inset + +For comparison, with QR we do +\begin_inset Formula \begin{align*} +0 & =R^{T}Q^{T}QRx-R^{T}Qb\\ + & =R^{T}Rx-R^{T}Qb\\ +Rx & =Qb\\ +x & =R^{-1}Qb\end{align*} + +\end_inset + +But with Cholesky we do +\begin_inset Formula \begin{align*} +0 & =R^{T}RR^{T}Rx-R^{T}Rb\\ + & =R^{T}Rx-b\\ + & =Rx-R^{-T}b\\ +x & =R^{-1}R^{-T}b\end{align*} + +\end_inset + + +\end_layout + +\begin_layout Section +Frontal (rank-deficient) solving with Cholesky +\end_layout + +\begin_layout Standard +To do multi-frontal elimination, we decompose into rank-deficient conditionals. + +\begin_inset Formula \[ +\left[\begin{array}{cccccc} +\cdot & \cdot & \cdot & \cdot & \cdot & \cdot\\ +\cdot & \cdot & \cdot & \cdot & \cdot & \cdot\\ +\cdot & \cdot & \cdot & \cdot & \cdot & \cdot\end{array}\right]\to\] + +\end_inset + + +\end_layout + +\begin_layout Standard +\begin_inset Formula \[ +\left[\begin{array}{cc} +R^{T} & 0\\ +S^{T} & C^{T}\end{array}\right]\left[\begin{array}{cc} +R & S\\ +0 & C\end{array}\right]=\left[\begin{array}{cc} +F^{T}F & F^{T}G\\ +G^{T}F & G^{T}G\end{array}\right]\] + +\end_inset + + +\end_layout + +\begin_layout Standard +\begin_inset space ~ +\end_inset + + +\end_layout + +\begin_layout Standard +\begin_inset Formula \[ +R^{T}R=F^{T}F\] + +\end_inset + + +\end_layout + +\begin_layout Standard +\begin_inset space ~ +\end_inset + + +\end_layout + +\begin_layout Standard +\begin_inset Formula \begin{align*} +R^{T}S & =F^{T}G\\ +S & =R^{-T}F^{T}G\end{align*} + +\end_inset + + +\end_layout + +\begin_layout Standard +\begin_inset space ~ +\end_inset + + +\end_layout + +\begin_layout Standard +\begin_inset Formula \begin{align*} +S^{T}S+C^{T}C & =G^{T}G\\ +G^{T}FR^{-1}R^{-T}F^{T}G+C^{T}C & =G^{T}G\\ +G^{T}QRR^{-1}R^{-T}R^{T}Q^{T}G+C^{T}C & =G^{T}G\\ +\textbf{if }R\textbf{ is invertible, }G^{T}G+C^{T}C & =G^{T}G\\ +C^{T}C & =0\end{align*} + +\end_inset + + +\end_layout + +\end_body +\end_document diff --git a/doc/images/circular.pdf b/doc/images/circular.pdf new file mode 100644 index 000000000..b0f43f649 Binary files /dev/null and b/doc/images/circular.pdf differ diff --git a/doc/images/circular.png b/doc/images/circular.png new file mode 100644 index 000000000..71c346a8e Binary files /dev/null and b/doc/images/circular.png differ diff --git a/doc/images/gtsam-structure.graffle b/doc/images/gtsam-structure.graffle new file mode 100644 index 000000000..22eb72dc3 --- /dev/null +++ b/doc/images/gtsam-structure.graffle @@ -0,0 +1,1302 @@ + + + + + ActiveLayerIndex + 0 + ApplicationVersion + + com.omnigroup.OmniGraffle + 138.14.0.129428 + + AutoAdjust + + BackgroundGraphic + + Bounds + {{0, 0}, {559.29, 782.89}} + Class + SolidGraphic + ID + 2 + Style + + fill + + GradientColor + + w + 0.666667 + + + shadow + + Draws + NO + + stroke + + Draws + NO + + + + 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Layout +\begin_inset FormulaMacro +\newcommand{\deriv}[2]{\frac{\partial#1}{\partial#2}} +{\frac{\partial#1}{\partial#2}} +\end_inset + + +\begin_inset FormulaMacro +\newcommand{\at}[2]{#1\biggr\rvert_{#2}} +{#1\biggr\rvert_{#2}} +\end_inset + + +\begin_inset FormulaMacro +\newcommand{\Jac}[3]{ \at{\deriv{#1}{#2}} {#3} } +{\at{\deriv{#1}{#2}}{#3}} +\end_inset + + +\end_layout + +\begin_layout Plain Layout +\begin_inset Note Comment +status open + +\begin_layout Plain Layout +Lie Groups +\end_layout + +\end_inset + + +\end_layout + +\begin_layout Plain Layout +\begin_inset FormulaMacro +\newcommand{\xhat}{\hat{x}} +{\hat{x}} +\end_inset + + +\begin_inset FormulaMacro +\newcommand{\yhat}{\hat{y}} +{\hat{y}} +\end_inset + + +\begin_inset FormulaMacro +\newcommand{\Ad}[1]{Ad_{#1}} +{Ad_{#1}} +\end_inset + + +\end_layout + +\begin_layout Plain Layout +\begin_inset FormulaMacro +\newcommand{\define}{\stackrel{\Delta}{=}} +{\stackrel{\Delta}{=}} +\end_inset + + +\begin_inset FormulaMacro +\newcommand{\gg}{\mathfrak{g}} +{\mathfrak{g}} +\end_inset + + +\begin_inset FormulaMacro +\newcommand{\Rn}{\mathbb{R}^{n}} +{\mathbb{R}^{n}} +\end_inset + + +\end_layout + +\begin_layout Plain Layout +\begin_inset Note Comment +status open + +\begin_layout Plain Layout +SO(2) +\end_layout + +\end_inset + + +\end_layout + +\begin_layout Plain Layout +\begin_inset FormulaMacro +\newcommand{\Rtwo}{\mathbb{R}^{2}} +{\mathbb{R}^{2}} +\end_inset + + +\begin_inset FormulaMacro +\newcommand{\SOtwo}{SO(2)} +{SO(2)} +\end_inset + + +\begin_inset FormulaMacro +\newcommand{\sotwo}{\mathfrak{so(2)}} +{\mathfrak{so(2)}} +\end_inset + + +\begin_inset FormulaMacro +\newcommand{\that}{\hat{\theta}} +{\hat{\theta}} +\end_inset + + +\begin_inset FormulaMacro +\newcommand{\skew}[1]{[#1]_{+}} +{[#1]_{+}} +\end_inset + + +\end_layout + +\begin_layout Plain Layout +\begin_inset Note Comment +status open + +\begin_layout Plain Layout +SE(2) +\end_layout + +\end_inset + + +\end_layout + +\begin_layout Plain Layout +\begin_inset FormulaMacro +\newcommand{\SEtwo}{SE(2)} +{SE(2)} +\end_inset + + +\begin_inset FormulaMacro +\newcommand{\setwo}{\mathfrak{se(2)}} +{\mathfrak{se(2)}} +\end_inset + + +\end_layout + +\begin_layout Plain Layout +\begin_inset Note Comment +status open + +\begin_layout Plain Layout +SO(3) +\end_layout + +\end_inset + + +\end_layout + +\begin_layout Plain Layout +\begin_inset FormulaMacro +\newcommand{\Rthree}{\mathbb{R}^{3}} +{\mathbb{R}^{3}} +\end_inset + + +\begin_inset FormulaMacro +\newcommand{\SOthree}{SO(3)} +{SO(3)} +\end_inset + + +\begin_inset FormulaMacro +\newcommand{\sothree}{\mathfrak{so(3)}} +{\mathfrak{so(3)}} +\end_inset + + +\begin_inset FormulaMacro +\newcommand{\what}{\hat{\omega}} +{\hat{\omega}} +\end_inset + + +\begin_inset FormulaMacro +\newcommand{\Skew}[1]{[#1]_{\times}} +{[#1]_{\times}} +\end_inset + + +\end_layout + +\begin_layout Plain Layout +\begin_inset Note Comment +status open + +\begin_layout Plain Layout +SE(3) +\end_layout + +\end_inset + + +\end_layout + +\begin_layout Plain Layout +\begin_inset FormulaMacro +\newcommand{\Rsix}{\mathbb{R}^{6}} +{\mathbb{R}^{6}} +\end_inset + + +\begin_inset FormulaMacro +\newcommand{\SEthree}{SE(3)} +{SE(3)} +\end_inset + + +\begin_inset FormulaMacro +\newcommand{\sethree}{\mathfrak{se(3)}} +{\mathfrak{se(3)}} +\end_inset + + +\begin_inset FormulaMacro +\newcommand{\xihat}{\hat{\xi}} +{\hat{\xi}} +\end_inset + + +\end_layout + +\end_inset + + +\end_layout + +\begin_layout Part +Theory +\end_layout + +\begin_layout Section +Optimization +\end_layout + +\begin_layout Standard +We will be concerned with minimizing a non-linear least squares objective + of the form +\begin_inset Formula +\begin{equation} +x^{*}=\arg\min_{x}\SqrMah{h(x)}z{\Sigma}\label{eq:objective} +\end{equation} + +\end_inset + +where +\begin_inset Formula $x\in\Man$ +\end_inset + + is a point on an +\begin_inset Formula $n$ +\end_inset + +-dimensional manifold (which could be +\begin_inset Formula $\Reals n$ +\end_inset + +, an n-dimensional Lie group +\begin_inset Formula $G$ +\end_inset + +, or a general manifold +\begin_inset Formula $\Man)$ +\end_inset + +, +\begin_inset Formula $z\in\Reals m$ +\end_inset + + is an observed measurement, +\begin_inset Formula $h:\Man\rightarrow\Reals m$ +\end_inset + + is a measurement function that predicts +\begin_inset Formula $z$ +\end_inset + + from +\begin_inset Formula $x$ +\end_inset + +, and +\begin_inset Formula $\SqrZMah e{\Sigma}\define e^{T}\Sigma^{-1}e$ +\end_inset + + is the squared Mahalanobis distance with covariance +\begin_inset Formula $\Sigma$ +\end_inset + +. + +\end_layout + +\begin_layout Standard +To minimize +\begin_inset CommandInset ref +LatexCommand eqref +reference "eq:objective" + +\end_inset + + we need a notion of how the non-linear measurement function +\begin_inset Formula $h(x)$ +\end_inset + + behaves in the neighborhood of a linearization point +\begin_inset Formula $a$ +\end_inset + +. + Loosely speaking, we would like to define an +\begin_inset Formula $m\times n$ +\end_inset + + Jacobian matrix +\begin_inset Formula $H_{a}$ +\end_inset + + such that +\begin_inset Formula +\begin{equation} +h(a\oplus\xi)\approx h(a)+H_{a}\xi\label{eq:LocalBehavior} +\end{equation} + +\end_inset + +with +\begin_inset Formula $\xi\in\Reals n$ +\end_inset + +, and the operation +\begin_inset Formula $\oplus$ +\end_inset + + +\begin_inset Quotes eld +\end_inset + +increments +\begin_inset Quotes erd +\end_inset + + +\begin_inset Formula $a\in\Man$ +\end_inset + +. + Below we more formally develop this notion, first for functions from +\begin_inset Formula $\Multi nm$ +\end_inset + +, then for Lie groups, and finally for manifolds. +\end_layout + +\begin_layout Standard +Once equipped with the approximation +\begin_inset CommandInset ref +LatexCommand eqref +reference "eq:LocalBehavior" + +\end_inset + +, we can minimize the objective function +\begin_inset CommandInset ref +LatexCommand eqref +reference "eq:objective" + +\end_inset + + with respect to +\begin_inset Formula $\delta x$ +\end_inset + + instead: +\begin_inset Formula +\begin{equation} +\xi^{*}=\arg\min_{\xi}\SqrMah{h(a)+H_{a}\xi}z{\Sigma}\label{eq:ApproximateObjective} +\end{equation} + +\end_inset + +This can be done by setting the derivative of +\begin_inset CommandInset ref +LatexCommand eqref +reference "eq:ApproximateObjective" + +\end_inset + + to zero, +\begin_inset Note Note +status collapsed + +\begin_layout Plain Layout + +\begin_inset Formula +\[ +\frac{1}{2}H_{a}^{T}(h(a)+H_{a}\xi-z)=0 +\] + +\end_inset + + +\end_layout + +\end_inset + + yielding the +\series bold +normal equations +\series default +, +\begin_inset Formula +\[ +H_{a}^{T}H_{a}\xi=H_{a}^{T}\left(z-h(a)\right) +\] + +\end_inset + +which can be solved using Cholesky factorization. + Of course, we might have to iterate this multiple times, and use a trust-region + method to bound +\begin_inset Formula $\xi$ +\end_inset + + when the approximation +\begin_inset CommandInset ref +LatexCommand eqref +reference "eq:LocalBehavior" + +\end_inset + + is not good. +\end_layout + +\begin_layout Section +Multivariate Differentiation +\end_layout + +\begin_layout Subsection +Derivatives +\end_layout + +\begin_layout Standard +For a vector space +\begin_inset Formula $\Reals n$ +\end_inset + +, the notion of an increment is just done by vector addition +\begin_inset Formula +\[ +a\oplus\xi\define a+\xi +\] + +\end_inset + +and for the approximation +\begin_inset CommandInset ref +LatexCommand ref +reference "eq:LocalBehavior" + +\end_inset + + we will use a Taylor expansion using multivariate differentiation. + However, loosely following +\begin_inset CommandInset citation +LatexCommand cite +key "Spivak65book" + +\end_inset + +, we use a perhaps unfamiliar way to define derivatives: +\end_layout + +\begin_layout Definition +\begin_inset CommandInset label +LatexCommand label +name "def:differentiable" + +\end_inset + +We define a function +\begin_inset Formula $f:\Multi nm$ +\end_inset + + to be +\series bold +differentiable +\series default + at +\begin_inset Formula $a$ +\end_inset + + if there exists a matrix +\begin_inset Formula $f'(a)\in\Reals{m\times n}$ +\end_inset + + such that +\begin_inset Formula +\[ +\lim_{\delta x\rightarrow0}\frac{\left|f(a)+f'(a)\xi-f(a+\xi)\right|}{\left|\xi\right|}=0 +\] + +\end_inset + +where +\begin_inset Formula $\left|e\right|\define\sqrt{e^{T}e}$ +\end_inset + + is the usual norm. + If +\begin_inset Formula $f$ +\end_inset + + is differentiable, then the matrix +\begin_inset Formula $f'(a)$ +\end_inset + + is called the +\series bold +Jacobian matrix +\series default + of +\begin_inset Formula $f$ +\end_inset + + at +\begin_inset Formula $a$ +\end_inset + +, and the linear map +\begin_inset Formula $Df_{a}:\xi\mapsto f'(a)\xi$ +\end_inset + + is called the +\series bold +derivative +\series default + of +\begin_inset Formula $f$ +\end_inset + + at +\begin_inset Formula $a$ +\end_inset + +. + When no confusion is likely, we use the notation +\begin_inset Formula $F_{a}\define f'(a)$ +\end_inset + + to stress that +\begin_inset Formula $f'(a)$ +\end_inset + + is a matrix. +\end_layout + +\begin_layout Standard +The benefit of using this definition is that it generalizes the notion of + a scalar derivative +\begin_inset Formula $f'(a):\Rone\rightarrow\Rone$ +\end_inset + + to multivariate functions from +\begin_inset Formula $\Multi nm$ +\end_inset + +. + In particular, the derivative +\begin_inset Formula $Df_{a}$ +\end_inset + + maps vector increments +\begin_inset Formula $\xi$ +\end_inset + + on +\begin_inset Formula $a$ +\end_inset + + to increments +\begin_inset Formula $f'(a)\xi$ +\end_inset + + on +\begin_inset Formula $f(a)$ +\end_inset + +, such that this linear map locally approximates +\begin_inset Formula $f$ +\end_inset + +: +\begin_inset Formula +\[ +f(a+\xi)\approx f(a)+f'(a)\xi +\] + +\end_inset + + +\end_layout + +\begin_layout Example +\begin_inset CommandInset label +LatexCommand label +name "ex:projection" + +\end_inset + +The function +\begin_inset Formula $\pi:(x,y,z)\mapsto(x/z,y/z)$ +\end_inset + + projects a 3D point +\begin_inset Formula $(x,y,z)$ +\end_inset + + to the image plane, and has the Jacobian matrix +\begin_inset Formula +\[ +\pi'(x,y,z)=\frac{1}{z}\left[\begin{array}{ccc} +1 & 0 & -x/z\\ +0 & 1 & -y/z +\end{array}\right] +\] + +\end_inset + + +\end_layout + +\begin_layout Subsection +Properties of Derivatives +\end_layout + +\begin_layout Standard +This notion of a multivariate derivative obeys the usual rules: +\end_layout + +\begin_layout Theorem +(Chain rule) If +\begin_inset Formula $f:\Multi np$ +\end_inset + + is differentiable at +\begin_inset Formula $a$ +\end_inset + + and +\begin_inset Formula $g:\Multi pm$ +\end_inset + + is differentiable at +\begin_inset Formula $f(a)$ +\end_inset + +, +\begin_inset Note Note +status collapsed + +\begin_layout Plain Layout + +\family roman +\series medium +\shape up +\size normal +\emph off +\bar no +\strikeout off +\uuline off +\uwave off +\noun off +\color none + then +\begin_inset Formula $D(g\circ f)_{a}=Dg_{f(a)}\circ Df_{a}$ +\end_inset + + and +\end_layout + +\end_inset + + then the Jacobian matrix +\begin_inset Formula $H_{a}$ +\end_inset + + of +\begin_inset Formula $h=g\circ f$ +\end_inset + + at +\begin_inset Formula $a$ +\end_inset + + is the +\begin_inset Formula $m\times n$ +\end_inset + + matrix product +\begin_inset Formula +\[ +H_{a}=G_{f(a)}F_{a} +\] + +\end_inset + + +\end_layout + +\begin_layout Proof +See +\begin_inset CommandInset citation +LatexCommand cite +key "Spivak65book" + +\end_inset + + +\end_layout + +\begin_layout Example +\begin_inset CommandInset label +LatexCommand label +name "ex:chain-rule" + +\end_inset + +If we follow the projection +\begin_inset Formula $\pi$ +\end_inset + + by a calibration step +\begin_inset Formula $\gamma:(x,y)\mapsto(u_{0}+fx,u_{0}+fy)$ +\end_inset + +, with +\begin_inset Formula +\[ +\gamma'(x,y)=\left[\begin{array}{cc} +f & 0\\ +0 & f +\end{array}\right] +\] + +\end_inset + +then the combined function +\begin_inset Formula $\gamma\circ\pi$ +\end_inset + + has the Jacobian matrix +\begin_inset Formula +\[ +(\gamma\circ\pi)'(x,y)=\frac{f}{z}\left[\begin{array}{ccc} +1 & 0 & -x/z\\ +0 & 1 & -y/z +\end{array}\right] +\] + +\end_inset + + +\end_layout + +\begin_layout Theorem +(Inverse) If +\begin_inset Formula $f:\Multi nn$ +\end_inset + + is differentiable and has a differentiable inverse +\begin_inset Formula $g\define f^{-1}$ +\end_inset + +, then its Jacobian matrix +\begin_inset Formula $G_{a}$ +\end_inset + + at +\begin_inset Formula $a$ +\end_inset + + is just the inverse of that of +\begin_inset Formula $f$ +\end_inset + +, evaluated at +\begin_inset Formula $g(a)$ +\end_inset + +: +\begin_inset Formula +\[ +G_{a}=\left[F_{g(a)}\right]^{-1} +\] + +\end_inset + + +\end_layout + +\begin_layout Proof +See +\begin_inset CommandInset citation +LatexCommand cite +key "Spivak65book" + +\end_inset + + +\end_layout + +\begin_layout Example +\begin_inset CommandInset label +LatexCommand label +name "ex:inverse" + +\end_inset + +The function +\begin_inset Formula $f:(x,y)\mapsto(x^{2},xy)$ +\end_inset + + has the Jacobian matrix +\end_layout + +\begin_layout Example +\begin_inset Formula +\[ +F_{(x,y)}=\left[\begin{array}{cc} +2x & 0\\ +y & x +\end{array}\right] +\] + +\end_inset + +and, for +\begin_inset Formula $x\geq0$ +\end_inset + +, its inverse is the function +\begin_inset Formula $g:(x,y)\mapsto(x^{1/2},x^{-1/2}y)$ +\end_inset + + with the Jacobian matrix +\begin_inset Formula +\[ +G_{(x,y)}=\frac{1}{2}\left[\begin{array}{cc} +x^{-1/2} & 0\\ +-x^{-3/2}y & 2x^{-1/2} +\end{array}\right] +\] + +\end_inset + +It is easily verified that +\begin_inset Formula +\[ +g'(a,b)f'(a^{1/2},a^{-1/2}b)=\frac{1}{2}\left[\begin{array}{cc} +a^{-1/2} & 0\\ +-a^{-3/2}b & 2a^{-1/2} +\end{array}\right]\left[\begin{array}{cc} +2a^{1/2} & 0\\ +a^{-1/2}b & a^{1/2} +\end{array}\right]=\left[\begin{array}{cc} +1 & 0\\ +0 & 1 +\end{array}\right] +\] + +\end_inset + + +\end_layout + +\begin_layout Problem +Verify the above for +\begin_inset Formula $(a,b)=(4,6)$ +\end_inset + +. + Sketch the situation graphically to get insight. +\end_layout + +\begin_layout Subsection +Computing Multivariate Derivatives +\end_layout + +\begin_layout Standard +Computing derivatives is made easy by defining the concept of a partial + derivative: +\end_layout + +\begin_layout Definition +For +\begin_inset Formula $f:\OneD n$ +\end_inset + +, the +\series bold +partial derivative +\series default + of +\begin_inset Formula $f$ +\end_inset + + at +\begin_inset Formula $a$ +\end_inset + +, +\series bold + +\series default + +\begin_inset Formula +\[ +D_{j}f(a)\define\lim_{h\rightarrow0}\frac{f\left(a^{1},\ldots,a^{j}+h,\ldots,a^{n}\right)-f\left(a^{1},\ldots,a^{n}\right)}{h} +\] + +\end_inset + +which is the ordinary derivative of the scalar function +\begin_inset Formula $g(x)\define f\left(a^{1},\ldots,x,\ldots,a^{n}\right)$ +\end_inset + +. + +\end_layout + +\begin_layout Standard +Using this definition, one can show that the Jacobian matrix +\begin_inset Formula $F_{a}$ +\end_inset + + of a differentiable +\emph on +multivariate +\emph default + function +\begin_inset Formula $f:\Multi nm$ +\end_inset + + consists simply of the +\begin_inset Formula $m\times n$ +\end_inset + + partial derivatives +\begin_inset Formula $D_{j}f^{i}(a)$ +\end_inset + +, evaluated at +\begin_inset Formula $a\in\Reals n$ +\end_inset + +: +\begin_inset Formula +\[ +F_{a}=\left[\begin{array}{ccc} +D_{1}f^{1}(a) & \cdots & D_{n}f^{1}(a)\\ +\vdots & \ddots & \vdots\\ +D_{1}f^{m}(a) & \ldots & D_{n}f^{m}(a) +\end{array}\right] +\] + +\end_inset + + +\end_layout + +\begin_layout Problem +Verify the derivatives in Examples +\begin_inset CommandInset ref +LatexCommand ref +reference "ex:projection" + +\end_inset + + to +\begin_inset CommandInset ref +LatexCommand ref +reference "ex:inverse" + +\end_inset + +. +\end_layout + +\begin_layout Standard +\begin_inset Newpage pagebreak +\end_inset + + +\end_layout + +\begin_layout Section +Multivariate Functions on Lie Groups +\end_layout + +\begin_layout Subsection +Lie Groups +\end_layout + +\begin_layout Standard +Lie groups are not as easy to treat as the vector space +\begin_inset Formula $\Reals n$ +\end_inset + + but nevertheless have a lot of structure. + To generalize the concept of the total derivative above we just need to + replace +\begin_inset Formula $a\oplus\xi$ +\end_inset + + in +\begin_inset CommandInset ref +LatexCommand eqref +reference "eq:ApproximateObjective" + +\end_inset + + with a suitable operation in the Lie group +\begin_inset Formula $G$ +\end_inset + +. + In particular, the notion of an exponential map allows us to define an + incremental transformation as tracing out a geodesic curve on the group + manifold along a certain +\series bold +tangent vector +\series default + +\begin_inset Formula $\xi$ +\end_inset + +, +\begin_inset Formula +\[ +a\oplus\xi\define a\exp\left(\hat{\xi}\right) +\] + +\end_inset + +with +\begin_inset Formula $\xi\in\Reals n$ +\end_inset + + for an +\begin_inset Formula $n$ +\end_inset + +-dimensional Lie group, +\begin_inset Formula $\hat{\xi}\in\mathfrak{g}$ +\end_inset + + the Lie algebra element corresponding to the vector +\begin_inset Formula $\xi$ +\end_inset + +, and +\begin_inset Formula $\exp\hat{\xi}$ +\end_inset + + the exponential map. + Note that if +\begin_inset Formula $G$ +\end_inset + + is equal to +\begin_inset Formula $\Reals n$ +\end_inset + + then composing with the exponential map +\begin_inset Formula $ae^{\xihat}$ +\end_inset + + is just vector addition +\begin_inset Formula $a+\xi$ +\end_inset + +. +\end_layout + +\begin_layout Example +For the Lie group +\begin_inset Formula $\SOthree$ +\end_inset + + of 3D rotations the vector +\begin_inset Formula $\xi$ +\end_inset + + is denoted as +\begin_inset Formula $\omega$ +\end_inset + + and represents an angular displacement. + The Lie algebra element +\begin_inset Formula $\xihat$ +\end_inset + + is a skew symmetric matrix denoted as +\begin_inset Formula $\Skew{\omega}\in\sothree$ +\end_inset + +, and is given by +\begin_inset Formula +\[ +\Skew{\omega}=\left[\begin{array}{ccc} +0 & -\omega_{z} & \omega_{y}\\ +\omega_{z} & 0 & -\omega_{x}\\ +-\omega_{y} & \omega_{x} & 0 +\end{array}\right] +\] + +\end_inset + +Finally, the increment +\begin_inset Formula $a\oplus\xi=ae^{\xihat}$ +\end_inset + + corresponds to an incremental rotation +\begin_inset Formula $R\oplus\omega=Re^{\Skew{\omega}}$ +\end_inset + +. +\end_layout + +\begin_layout Subsection +Derivatives +\end_layout + +\begin_layout Standard +We can generalize Definition +\begin_inset CommandInset ref +LatexCommand ref +reference "def:differentiable" + +\end_inset + + to map exponential coordinates +\begin_inset Formula $\xi$ +\end_inset + + to increments +\begin_inset Formula $f'(a)\xi$ +\end_inset + + on +\begin_inset Formula $f(a)$ +\end_inset + +, such that the linear map +\begin_inset Formula $Df_{a}$ +\end_inset + + locally approximates a function +\begin_inset Formula $f$ +\end_inset + + from +\begin_inset Formula $G$ +\end_inset + + to +\begin_inset Formula $\Reals m$ +\end_inset + +: +\begin_inset Formula +\[ +f(ae^{\xihat})\approx f(a)+f'(a)\xi +\] + +\end_inset + + +\end_layout + +\begin_layout Definition +We define a function +\begin_inset Formula $f:G\rightarrow\Reals m$ +\end_inset + + to be +\series bold +differentiable +\series default + at +\begin_inset Formula $a\in G$ +\end_inset + + if there exists a matrix +\begin_inset Formula $f'(a)\in\Reals{m\times n}$ +\end_inset + + such that +\begin_inset Formula +\[ +\lim_{\xi\rightarrow0}\frac{\left|f(a)+f'(a)\xi-f(ae^{\hat{\xi}})\right|}{\left|\xi\right|}=0 +\] + +\end_inset + +If +\begin_inset Formula $f$ +\end_inset + + is differentiable, then the matrix +\begin_inset Formula $f'(a)$ +\end_inset + + is called the +\series bold +Jacobian matrix +\series default + of +\begin_inset Formula $f$ +\end_inset + + at +\begin_inset Formula $a$ +\end_inset + +, and the linear map +\begin_inset Formula $Df_{a}:\xi\mapsto f'(a)\xi$ +\end_inset + + is called the +\series bold +derivative +\series default + of +\begin_inset Formula $f$ +\end_inset + + at +\begin_inset Formula $a$ +\end_inset + +. +\end_layout + +\begin_layout Standard +Note that the vectors +\begin_inset Formula $\xi$ +\end_inset + + can be viewed as lying in the tangent space to +\begin_inset Formula $G$ +\end_inset + + at +\begin_inset Formula $a$ +\end_inset + +, but defining this rigorously would take us on a longer tour of differential + geometry. + Informally, +\begin_inset Formula $\xi$ +\end_inset + + is simply the direction, in a local coordinate frame, that is locally tangent + at +\begin_inset Formula $a$ +\end_inset + + to a geodesic curve +\begin_inset Formula $\gamma:t\mapsto ae^{\widehat{t\xi}}$ +\end_inset + + traced out by the exponential map, with +\begin_inset Formula $\gamma(0)=a$ +\end_inset + +. +\end_layout + +\begin_layout Subsection +Derivative of an Action +\begin_inset CommandInset label +LatexCommand label +name "sec:Derivatives-of-Actions" + +\end_inset + + +\end_layout + +\begin_layout Standard +The (usual) action of an +\begin_inset Formula $n$ +\end_inset + +-dimensional matrix group +\begin_inset Formula $G$ +\end_inset + + is matrix-vector multiplication on +\begin_inset Formula $\mathbb{R}^{n}$ +\end_inset + +, i.e., +\begin_inset Formula $f:G\times\Reals n\rightarrow\Reals n$ +\end_inset + + with +\begin_inset Formula +\[ +f(T,p)=Tp +\] + +\end_inset + +Since this is a function defined on the product +\begin_inset Formula $G\times\Reals n$ +\end_inset + + the derivative is a linear transformation +\begin_inset Formula $Df:\Multi{2n}n$ +\end_inset + + with +\begin_inset Formula +\[ +Df_{(T,p)}\left(\xi,\delta p\right)=D_{1}f_{(T,p)}\left(\xi\right)+D_{2}f_{(T,p)}\left(\delta p\right) +\] + +\end_inset + + +\end_layout + +\begin_layout Theorem +\begin_inset CommandInset label +LatexCommand label +name "th:Action" + +\end_inset + +The Jacobian matrix of the group action +\begin_inset Formula $f(T,P)=Tp$ +\end_inset + + at +\begin_inset Formula $(T,p)$ +\end_inset + + is given by +\begin_inset Formula +\[ +F_{(T,p)}=\left[\begin{array}{cc} +TH(p) & T\end{array}\right]=T\left[\begin{array}{cc} +H(p) & I_{n}\end{array}\right] +\] + +\end_inset + +with +\begin_inset Formula $H:\Reals n\rightarrow\Reals{n\times n}$ +\end_inset + + a linear mapping that depends on +\begin_inset Formula $p$ +\end_inset + +, and +\begin_inset Formula $I_{n}$ +\end_inset + + the +\begin_inset Formula $n\times n$ +\end_inset + + identity matrix. +\end_layout + +\begin_layout Proof +First, the derivative +\begin_inset Formula $D_{2}f$ +\end_inset + + with respect to in +\begin_inset Formula $p$ +\end_inset + + is easy, as its matrix is simply T: +\begin_inset Formula +\[ +f(T,p+\delta p)=T(p+\delta p)=Tp+T\delta p=f(T,p)+D_{2}f(\delta p) +\] + +\end_inset + +For the derivative +\begin_inset Formula $D_{1}f$ +\end_inset + + with respect to a change in the first argument +\begin_inset Formula $T$ +\end_inset + +, we want +\end_layout + +\begin_layout Proof + +\family roman +\series medium +\shape up +\size normal +\emph off +\bar no +\strikeout off +\uuline off +\uwave off +\noun off +\color none +\begin_inset Formula +\[ +f(Te^{\hat{\xi}},p)=Te^{\hat{\xi}}p\approx Tp+D_{1}f(\xi) +\] + +\end_inset + + +\family default +\series default +\shape default +\size default +\emph default +\bar default +\strikeout default +\uuline default +\uwave default +\noun default +\color inherit +Since the matrix exponential is given by the series +\begin_inset Formula $e^{A}=I+A+\frac{A^{2}}{2!}+\frac{A^{3}}{3!}+\ldots$ +\end_inset + + we have, to first order +\begin_inset Formula +\[ +Te^{\hat{\xi}}p\approx T(I+\hat{\xi})p=Tp+T\hat{\xi}p +\] + +\end_inset + + +\begin_inset Note Note +status collapsed + +\begin_layout Plain Layout +Note also that +\begin_inset Formula +\[ +T\hat{\xi}p=\left(T\hat{\xi}T^{-1}\right)Tp=\left(\Ad T\xihat\right)\left(Tp\right) +\] + +\end_inset + + +\end_layout + +\end_inset + +Hence, we need to show that +\begin_inset Formula +\begin{equation} +\xihat p=H(p)\xi\label{eq:Hp} +\end{equation} + +\end_inset + +with +\begin_inset Formula $H(p)$ +\end_inset + + an +\begin_inset Formula $n\times n$ +\end_inset + + matrix that depends on +\begin_inset Formula $p$ +\end_inset + +. + Expressing the map +\begin_inset Formula $\xi\rightarrow\hat{\xi}$ +\end_inset + + in terms of the Lie algebra generators +\begin_inset Formula $G^{i}$ +\end_inset + +, using tensors and Einstein summation, we have +\begin_inset Formula $\hat{\xi}_{j}^{i}=G_{jk}^{i}\xi^{k}$ +\end_inset + + allowing us to calculate +\family roman +\series medium +\shape up +\size normal +\emph off +\bar no +\noun off +\color none + +\begin_inset Formula $\hat{\xi}p$ +\end_inset + + +\family default +\series default +\shape default +\size default +\emph default +\bar default +\noun default +\color inherit + as +\begin_inset Formula +\[ +\left(\hat{\xi}p\right)^{i}=\hat{\xi}_{j}^{i}p^{j}=G_{jk}^{i}\xi^{k}p^{j}=\left(G_{jk}^{i}p^{j}\right)\xi^{k}=H_{k}^{i}(p)\xi^{k} +\] + +\end_inset + + +\end_layout + +\begin_layout Example +For 3D rotations +\begin_inset Formula $R\in\SOthree$ +\end_inset + +, we have +\begin_inset Formula $\hat{\omega}=\Skew{\omega}$ +\end_inset + + and +\begin_inset Formula +\[ +G_{k=1}:\left(\begin{array}{ccc} +0 & 0 & 0\\ +0 & 0 & -1\\ +0 & 1 & 0 +\end{array}\right)\mbox{}G_{k=2}:\left(\begin{array}{ccc} +0 & 0 & 1\\ +0 & 0 & 0\\ +-1 & 0 & 0 +\end{array}\right)\mbox{ }G_{k=3}:\left(\begin{array}{ccc} +0 & -1 & 0\\ +1 & 0 & 0\\ +0 & 0 & 0 +\end{array}\right) +\] + +\end_inset + + +\family roman +\series medium +\shape up +\size normal +\emph off +\bar no +\noun off +\color none +The matrices +\begin_inset Formula $\left(G_{k}^{i}\right)_{j}$ +\end_inset + + are obtained by assembling the +\begin_inset Formula $j^{th}$ +\end_inset + + columns of the generators above, yielding +\begin_inset Formula $H(p)$ +\end_inset + + equal to: +\begin_inset Formula +\[ +\left(\begin{array}{ccc} +0 & 0 & 0\\ +0 & 0 & 1\\ +0 & -1 & 0 +\end{array}\right)p^{1}+\left(\begin{array}{ccc} +0 & 0 & -1\\ +0 & 0 & 0\\ +1 & 0 & 0 +\end{array}\right)p^{2}+\left(\begin{array}{ccc} +0 & 1 & 0\\ +-1 & 0 & 0\\ +0 & 0 & 0 +\end{array}\right)p^{3}=\left(\begin{array}{ccc} +0 & p^{3} & -p^{2}\\ +-p^{3} & 0 & p^{1}\\ +p^{2} & -p^{1} & 0 +\end{array}\right)=\Skew{-p} +\] + +\end_inset + + +\family default +\series default +\shape default +\size default +\emph default +\bar default +\noun default +\color inherit +Hence, the Jacobian matrix of +\begin_inset Formula $f(R,p)=Rp$ +\end_inset + + is given by +\begin_inset Formula +\[ +F_{(R,p)}=R\left(\begin{array}{cc} +\Skew{-p} & I_{3}\end{array}\right) +\] + +\end_inset + + +\end_layout + +\begin_layout Subsection +Derivative of an Inverse Action +\end_layout + +\begin_layout Standard +Applying the action by the inverse of +\begin_inset Formula $T\in G$ +\end_inset + + yields a function +\begin_inset Formula $g:G\times\Reals n\rightarrow\Reals n$ +\end_inset + + defined by +\begin_inset Formula +\[ +g(T,p)=T^{-1}p +\] + +\end_inset + + +\end_layout + +\begin_layout Theorem +\begin_inset CommandInset label +LatexCommand label +name "Th:InverseAction" + +\end_inset + +The Jacobian matrix of the inverse group action +\begin_inset Formula $g(T,p)=T^{-1}p$ +\end_inset + + is given by +\begin_inset Formula +\[ +G_{(T,p)}=\left[\begin{array}{cc} +-H(T^{-1}p) & T^{-1}\end{array}\right] +\] + +\end_inset + +where +\begin_inset Formula $H:\Reals n\rightarrow\Reals{n\times n}$ +\end_inset + + is the same mapping as before. +\end_layout + +\begin_layout Proof +Again, the derivative +\begin_inset Formula $D_{2}g$ +\end_inset + + with respect to in +\begin_inset Formula $p$ +\end_inset + + is easy, the matrix of which is simply +\begin_inset Formula $T^{-1}$ +\end_inset + +: +\begin_inset Formula +\[ +g(T,p+\delta p)=T^{-1}(p+\delta p)=T^{-1}p+T^{-1}\delta p=g(T,p)+D_{2}g(\delta p) +\] + +\end_inset + +Conversely, a change in +\begin_inset Formula $T$ +\end_inset + + yields +\begin_inset Formula +\[ +g(Te^{\xihat},p)=\left(Te^{\xihat}\right)^{-1}p=e^{-\xihat}T^{-1}p +\] + +\end_inset + +Similar to before, if we expand the matrix exponential we get +\begin_inset Formula +\[ +e^{-A}=I-A+\frac{A^{2}}{2!}-\frac{A^{3}}{3!}+\ldots +\] + +\end_inset + +so +\begin_inset Formula +\[ +e^{-\xihat}T^{-1}p\approx(I-\xihat)T^{-1}p=g(T,p)-\xihat\left(T^{-1}p\right) +\] + +\end_inset + + +\end_layout + +\begin_layout Example +For 3D rotations +\begin_inset Formula $R\in\SOthree$ +\end_inset + + we have +\begin_inset Formula $R^{-1}=R^{T}$ +\end_inset + +, +\begin_inset Formula $H(p)=-\Skew p$ +\end_inset + +, and hence the Jacobian matrix of +\begin_inset Formula $g(R,p)=R^{T}p$ +\end_inset + + is given by +\begin_inset Formula +\[ +G_{(R,p)}=\left(\begin{array}{cc} +\Skew{R^{T}p} & R^{T}\end{array}\right) +\] + +\end_inset + + +\end_layout + +\begin_layout Standard +\begin_inset Note Note +status collapsed + +\begin_layout Plain Layout +My earlier attempt: because the wedge operator is linear, we have +\end_layout + +\begin_layout Plain Layout +\begin_inset Formula +\begin{eqnarray*} +f(\xi+x) & = & \exp\widehat{\left(\xi+x\right)}\\ + & = & \exp\left(\xihat+\hat{x}\right) +\end{eqnarray*} + +\end_inset + +However, except for commutative Lie groups, it is not true that +\begin_inset Formula $\exp\left(\xihat+\hat{x}\right)=\exp\xihat\exp\hat{x}$ +\end_inset + +. + However, if we expand the matrix exponential to second order and assume + +\begin_inset Formula $x\rightarrow0$ +\end_inset + + we do have +\begin_inset Formula +\[ +\exp\left(\xihat+\hat{x}\right)\approx I+\xihat+\hat{x}+\frac{1}{2}\xihat^{2}+\xhat\xihat +\] + +\end_inset + +Now, if we ask what +\begin_inset Formula $\hat{y}$ +\end_inset + + would effect the same change: +\begin_inset Formula +\begin{eqnarray*} +\exp\xihat\exp\yhat & = & I+\xihat+\hat{x}+\frac{1}{2}\xihat^{2}+\xhat\xihat\\ +\exp\xihat(I+\yhat) & = & I+\xihat+\hat{x}+\frac{1}{2}\xihat^{2}+\xhat\xihat\\ +\left(\exp\xihat\right)\yhat & = & \xhat+\xhat\xihat +\end{eqnarray*} + +\end_inset + + +\end_layout + +\end_inset + + +\end_layout + +\begin_layout Section +Instantaneous Velocity +\end_layout + +\begin_layout Standard +For matrix Lie groups, if we have a matrix +\begin_inset Formula $T_{b}^{n}(t)$ +\end_inset + + that depends on a parameter +\begin_inset Formula $t$ +\end_inset + +, i.e., +\begin_inset Formula $T_{b}^{n}(t)$ +\end_inset + + follows a curve on the manifold, then it would be of interest to find the + velocity of a point +\begin_inset Formula $q^{n}(t)=T_{b}^{n}(t)p^{b}$ +\end_inset + + acted upon by +\begin_inset Formula $T_{b}^{n}(t)$ +\end_inset + +. + We can express the velocity of +\begin_inset Formula $q(t)$ +\end_inset + + in both the n-frame and b-frame: +\begin_inset Formula +\[ +\dot{q}^{n}=\dot{T}_{b}^{n}p^{b}=\dot{T}_{b}^{n}\left(T_{b}^{n}\right)^{-1}p^{n}\mbox{\,\,\,\,\ and\,\,\,\,}\dot{q}^{b}=\left(T_{b}^{n}\right)^{-1}\dot{q}^{n}=\left(T_{b}^{n}\right)^{-1}\dot{T}_{b}^{n}p^{b} +\] + +\end_inset + +Both the matrices +\begin_inset Formula $\xihat_{nb}^{n}\define\dot{T}_{b}^{n}\left(T_{b}^{n}\right)^{-1}$ +\end_inset + + and +\begin_inset Formula $\xihat_{nb}^{b}\define\left(T_{b}^{n}\right)^{-1}\dot{T}_{b}^{n}$ +\end_inset + + are skew-symmetric Lie algebra elements that describe the +\series bold +instantaneous velocity +\series default + +\begin_inset CommandInset citation +LatexCommand cite +after "page 51 for rotations, page 419 for SE(3)" +key "Murray94book" + +\end_inset + +. + We will revisit this for both rotations and rigid 3D transformations. +\end_layout + +\begin_layout Section +Differentials: Smooth Mapping between Lie Groups +\end_layout + +\begin_layout Subsection +Motivation and Definition +\end_layout + +\begin_layout Standard +The above shows how to compute the derivative of a function +\begin_inset Formula $f:G\rightarrow\Reals m$ +\end_inset + +. + However, what if the argument to +\begin_inset Formula $f$ +\end_inset + + is itself the result of a mapping between Lie groups? In other words, +\begin_inset Formula $f=g\circ\varphi$ +\end_inset + +, with +\begin_inset Formula $g:G\rightarrow\Reals m$ +\end_inset + + and where +\begin_inset Formula $\varphi:H\rightarrow G$ +\end_inset + + is a smooth mapping from the +\begin_inset Formula $n$ +\end_inset + +-dimensional Lie group +\begin_inset Formula $H$ +\end_inset + + to the +\begin_inset Formula $p$ +\end_inset + +-dimensional Lie group +\begin_inset Formula $G$ +\end_inset + +. + In this case, one would expect that we can arrive at +\begin_inset Formula $Df_{a}$ +\end_inset + + by composing linear maps, as follows: +\begin_inset Formula +\[ +f'(a)=(g\circ\varphi)'(a)=G_{\varphi(a)}\varphi'(a) +\] + +\end_inset + +where +\begin_inset Formula $\varphi'(a)$ +\end_inset + + is an +\begin_inset Formula $n\times p$ +\end_inset + + matrix that is the best linear approximation to the map +\family roman +\series medium +\shape up +\size normal +\emph off +\bar no +\strikeout off +\uuline off +\uwave off +\noun off +\color none + +\begin_inset Formula $\varphi:H\rightarrow G$ +\end_inset + +. + The corresponding linear map +\begin_inset Formula $D\varphi_{a}$ +\end_inset + + is called the +\family default +\series bold +\shape default +\size default +\emph default +\bar default +\strikeout default +\uuline default +\uwave default +\noun default +\color inherit +differential +\family roman +\series medium +\shape up +\size normal +\emph off +\bar no +\strikeout off +\uuline off +\uwave off +\noun off +\color none + +\family default +\series default +\shape default +\size default +\emph default +\bar default +\strikeout default +\uuline default +\uwave default +\noun default +\color inherit +or +\series bold +pushforward +\family roman +\series medium +\shape up +\size normal +\emph off +\bar no +\strikeout off +\uuline off +\uwave off +\noun off +\color none + of +\begin_inset Formula $ $ +\end_inset + +the mapping +\begin_inset Formula $\varphi$ +\end_inset + + at +\begin_inset Formula $a$ +\end_inset + +. + +\end_layout + +\begin_layout Standard + +\family roman +\series medium +\shape up +\size normal +\emph off +\bar no +\strikeout off +\uuline off +\uwave off +\noun off +\color none +Because a rigorous definition will lead us too far astray, here we only + informally define the pushforward of +\begin_inset Formula $\varphi$ +\end_inset + + at +\begin_inset Formula $a$ +\end_inset + + as the linear map +\begin_inset Formula $D\varphi_{a}:\Multi np$ +\end_inset + + such that +\begin_inset Formula $D\varphi_{a}\left(\xi\right)\define\varphi'(a)\xi$ +\end_inset + + and +\family default +\series default +\shape default +\size default +\emph default +\bar default +\strikeout default +\uuline default +\uwave default +\noun default +\color inherit + +\begin_inset Formula +\begin{equation} +\varphi\left(ae^{\xihat}\right)\approx\varphi\left(a\right)\exp\left(\widehat{\varphi'(a)\xi}\right)\label{eq:pushforward} +\end{equation} + +\end_inset + +with equality for +\begin_inset Formula $\xi\rightarrow0$ +\end_inset + +. + We call +\begin_inset Formula $\varphi'(a)$ +\end_inset + + the +\series bold +Jacobian matrix +\series default + of the map +\begin_inset Formula $\varphi$ +\end_inset + + at +\begin_inset Formula $a$ +\end_inset + +. + Below we show that even with this informal definition we can deduce the + pushforward in a number of useful cases. +\end_layout + +\begin_layout Subsection +Left Multiplication with a Constant +\end_layout + +\begin_layout Theorem +Suppose +\begin_inset Formula $G$ +\end_inset + + is an +\begin_inset Formula $n$ +\end_inset + +-dimensional Lie group, and +\begin_inset Formula $\varphi:G\rightarrow G$ +\end_inset + + is defined as +\begin_inset Formula $\varphi(g)=hg$ +\end_inset + +, with +\begin_inset Formula $h\in G$ +\end_inset + + a constant. + Then +\begin_inset Formula $D\varphi_{a}$ +\end_inset + + is the identity mapping and +\begin_inset Formula +\[ +\varphi'(a)=I_{n} +\] + +\end_inset + + +\end_layout + +\begin_layout Proof +Defining +\begin_inset Formula $y=D\varphi_{a}x$ +\end_inset + + as in +\begin_inset CommandInset ref +LatexCommand eqref +reference "eq:pushforward" + +\end_inset + +, we have +\begin_inset Formula +\begin{eqnarray*} +\varphi(a)e^{\yhat} & = & \varphi(ae^{\xhat})\\ +hae^{\yhat} & = & hae^{\xhat}\\ +y & = & x +\end{eqnarray*} + +\end_inset + + +\end_layout + +\begin_layout Subsection +Pushforward of the Inverse Mapping +\end_layout + +\begin_layout Standard +A well known property of Lie groups is the the fact that applying an incremental + change +\begin_inset Formula $\xihat$ +\end_inset + + in a different frame +\begin_inset Formula $g$ +\end_inset + + can be applied in a single step by applying the change +\begin_inset Formula $Ad_{g}\xihat$ +\end_inset + + in the original frame, +\begin_inset Formula +\begin{equation} +ge^{\xihat}g^{-1}=\exp\left(Ad_{g}\xihat\right)\label{eq:Adjoint2} +\end{equation} + +\end_inset + +where +\begin_inset Formula $Ad_{g}:\mathfrak{g}\rightarrow\mathfrak{g}$ +\end_inset + + is the +\series bold +adjoint representation +\series default +. + This comes in handy in the following: +\end_layout + +\begin_layout Theorem +Suppose that +\begin_inset Formula $\varphi:G\rightarrow G$ +\end_inset + + is defined as the mapping from an element +\begin_inset Formula $g$ +\end_inset + + to its +\series bold +inverse +\series default + +\begin_inset Formula $g^{-1}$ +\end_inset + +, i.e., +\begin_inset Formula $\varphi(g)=g^{-1}$ +\end_inset + +, then the pushforward +\begin_inset Formula $D\varphi_{a}$ +\end_inset + + satisfies +\begin_inset Formula +\begin{align} +\left(D\varphi_{a}x\right)\hat{} & =-Ad_{a}\xhat\label{eq:Dinverse} +\end{align} + +\end_inset + + +\end_layout + +\begin_layout Standard +\begin_inset ERT +status open + +\begin_layout Plain Layout + + +\backslash +noindent +\end_layout + +\end_inset + + In other words, and this is intuitive in hindsight, approximating the inverse + is accomplished by negation of +\begin_inset Formula $\xihat$ +\end_inset + +, along with an adjoint to make sure it is applied in the right frame. + +\begin_inset ERT +status open + +\begin_layout Plain Layout + + +\backslash +noindent +\end_layout + +\end_inset + + Note, however, that +\begin_inset CommandInset ref +LatexCommand eqref +reference "eq:Dinverse" + +\end_inset + + does not immediately yield a useful expression for the Jacobian matrix + +\begin_inset Formula $\varphi'(a)$ +\end_inset + +, but in many important cases this will turn out to be easy. + +\end_layout + +\begin_layout Proof +Defining +\begin_inset Formula $y=D\varphi_{a}x$ +\end_inset + + as in +\begin_inset CommandInset ref +LatexCommand eqref +reference "eq:pushforward" + +\end_inset + +, we have +\begin_inset Formula +\begin{eqnarray*} +\varphi(a)e^{\yhat} & = & \varphi(ae^{\xhat})\\ +a^{-1}e^{\yhat} & = & \left(ae^{\xhat}\right)^{-1}\\ +e^{\yhat} & = & -ae^{\xhat}a^{-1}\\ +\yhat & = & -\Ad a\xhat +\end{eqnarray*} + +\end_inset + + +\end_layout + +\begin_layout Example +For 3D rotations +\begin_inset Formula $R\in\SOthree$ +\end_inset + + we have +\begin_inset Formula +\[ +Ad_{g}(\hat{\omega})=R\hat{\omega}R^{T}=\Skew{R\omega} +\] + +\end_inset + +and hence the pushforward for the inverse mapping +\begin_inset Formula $\varphi(R)=R^{T}$ +\end_inset + + has the matrix +\begin_inset Formula $\varphi'(R)=-R$ +\end_inset + +. +\end_layout + +\begin_layout Subsection +Right Multiplication with a Constant +\end_layout + +\begin_layout Theorem +Suppose +\begin_inset Formula $\varphi:G\rightarrow G$ +\end_inset + + is defined as +\begin_inset Formula $\varphi(g)=gh$ +\end_inset + +, with +\begin_inset Formula $h\in G$ +\end_inset + + a constant. + Then +\begin_inset Formula $D\varphi_{a}$ +\end_inset + + satisfies +\begin_inset Formula +\[ +\left(D\varphi_{a}x\right)\hat{}=\Ad{h^{-1}}\xhat +\] + +\end_inset + + +\end_layout + +\begin_layout Proof +Defining +\begin_inset Formula $y=D\varphi_{a}x$ +\end_inset + + as in +\begin_inset CommandInset ref +LatexCommand eqref +reference "eq:pushforward" + +\end_inset + +, we have +\begin_inset Formula +\begin{align*} +\varphi(a)e^{\yhat} & =\varphi(ae^{\xhat})\\ +ahe & =ae^{\xhat}h\\ +e^{\yhat} & =h^{-1}e^{\xhat}h=\exp\left(\Ad{h^{-1}}\xhat\right)\\ +\yhat & =\Ad{h^{-1}}\xhat +\end{align*} + +\end_inset + + +\end_layout + +\begin_layout Example +In the case of 3D rotations, right multiplication with a constant rotation + +\begin_inset Formula $R$ +\end_inset + + is done through the mapping +\begin_inset Formula $\varphi(A)=AR$ +\end_inset + +, and satisfies +\begin_inset Formula +\[ +\Skew{D\varphi_{A}x}=\Ad{R^{T}}\Skew x +\] + +\end_inset + +For 3D rotations +\begin_inset Formula $R\in\SOthree$ +\end_inset + + we have +\begin_inset Formula +\[ +Ad_{R^{T}}(\hat{\omega})=R^{T}\hat{\omega}R=\Skew{R^{T}\omega} +\] + +\end_inset + +and hence the Jacobian matrix of +\begin_inset Formula $\varphi$ +\end_inset + + at +\begin_inset Formula $A$ +\end_inset + + is +\begin_inset Formula $\varphi'(A)=R^{T}$ +\end_inset + +. +\end_layout + +\begin_layout Subsection +Pushforward of Compose +\end_layout + +\begin_layout Theorem +If we define the mapping +\begin_inset Formula $\varphi:G\times G\rightarrow G$ +\end_inset + + as the product of two group elements +\begin_inset Formula $g,h\in G$ +\end_inset + +, i.e., +\begin_inset Formula $\varphi(g,h)=gh$ +\end_inset + +, then the pushforward will satisfy +\begin_inset Formula +\[ +D\varphi_{(a,b)}(x,y)=D_{1}\varphi_{(a,b)}x+D_{2}\varphi_{(a,b)}y +\] + +\end_inset + +with +\begin_inset Formula +\[ +\left(D_{1}\varphi_{(a,b)}x\right)\hat{}=\Ad{b^{-1}}\xhat\mbox{\;\ and\;}D_{2}\varphi_{(a,b)}y=y +\] + +\end_inset + + +\end_layout + +\begin_layout Proof +Looking at the first argument, the proof is very similar to right multiplication + with a constant +\begin_inset Formula $b$ +\end_inset + +. + Indeed, defining +\begin_inset Formula $y=D\varphi_{a}x$ +\end_inset + + as in +\begin_inset CommandInset ref +LatexCommand eqref +reference "eq:pushforward" + +\end_inset + +, we have +\begin_inset Formula +\begin{align} +\varphi(a,b)e^{\yhat} & =\varphi(ae^{\xhat},b)\nonumber \\ +abe^{\yhat} & =ae^{\xhat}b\nonumber \\ +e^{\yhat} & =b^{-1}e^{\xhat}b=\exp\left(\Ad{b^{-1}}\xhat\right)\nonumber \\ +\yhat & =\Ad{b^{-1}}\xhat\label{eq:Dcompose1} +\end{align} + +\end_inset + +In other words, to apply an incremental change +\begin_inset Formula $\xhat$ +\end_inset + + to +\begin_inset Formula $a$ +\end_inset + + we first need to undo +\begin_inset Formula $b$ +\end_inset + +, then apply +\begin_inset Formula $\xhat$ +\end_inset + +, and then apply +\begin_inset Formula $b$ +\end_inset + + again. + Using +\begin_inset CommandInset ref +LatexCommand eqref +reference "eq:Adjoint2" + +\end_inset + + this can be done in one step by simply applying +\begin_inset Formula $\Ad{b^{-1}}\xhat$ +\end_inset + +. + +\end_layout + +\begin_layout Proof +The second argument is quite a bit easier and simply yields the identity + mapping: +\begin_inset Formula +\begin{align} +\varphi(a,b)e^{\yhat} & =\varphi(a,be^{\xhat})\nonumber \\ +abe^{\yhat} & =abe^{\xhat}\nonumber \\ +y & =x\label{eq:Dcompose2} +\end{align} + +\end_inset + + +\end_layout + +\begin_layout Standard +\begin_inset Note Note +status open + +\begin_layout Plain Layout +In summary, the Jacobian matrix of +\begin_inset Formula $\varphi(g,h)=gh$ +\end_inset + + at +\begin_inset Formula $(a,b)\in G\times G$ +\end_inset + + is given by +\begin_inset Formula +\[ +\varphi'(a,b)=? +\] + +\end_inset + + +\end_layout + +\end_inset + + +\end_layout + +\begin_layout Example +For 3D rotations +\begin_inset Formula $A,B\in\SOthree$ +\end_inset + + we have +\begin_inset Formula $\varphi(A,B)=AB$ +\end_inset + +, and +\begin_inset Formula $\Ad{B^{T}}\Skew{\omega}=\Skew{B^{T}\omega}$ +\end_inset + +, hence the Jacobian matrix +\begin_inset Formula $\varphi'(A,B)$ +\end_inset + + of composing two rotations is given by +\begin_inset Formula +\[ +\varphi'(A,B)=\left[\begin{array}{cc} +B^{T} & I_{3}\end{array}\right] +\] + +\end_inset + + +\end_layout + +\begin_layout Subsection +Pushforward of Between +\end_layout + +\begin_layout Standard +Finally, let us find the pushforward of +\series bold +between +\series default +, defined as +\begin_inset Formula $\varphi(g,h)=g^{-1}h$ +\end_inset + +. + For the first argument we reason as: +\begin_inset Formula +\begin{align} +\varphi(g,h)e^{\yhat} & =\varphi(ge^{\xhat},h)\nonumber \\ +g^{-1}he^{\yhat} & =\left(ge^{\xhat}\right)^{-1}h=-e^{\xhat}g^{-1}h\nonumber \\ +e^{\yhat} & =-\left(h^{-1}g\right)e^{\xhat}\left(h^{-1}g\right)^{-1}=-\exp\Ad{\left(h^{-1}g\right)}\xhat\nonumber \\ +\yhat & =-\Ad{\left(h^{-1}g\right)}\xhat=-\Ad{\varphi\left(h,g\right)}\xhat\label{eq:Dbetween1} +\end{align} + +\end_inset + +The second argument yields the identity mapping. +\end_layout + +\begin_layout Example +For 3D rotations +\begin_inset Formula $A,B\in\SOthree$ +\end_inset + + we have +\begin_inset Formula $\varphi(A,B)=A^{T}B$ +\end_inset + +, and +\begin_inset Formula $\Ad{B^{T}A}\Skew{-\omega}=\Skew{-B^{T}A\omega}$ +\end_inset + +, hence the Jacobian matrix +\begin_inset Formula $\varphi'(A,B)$ +\end_inset + + of between is given by +\begin_inset Formula +\[ +\varphi'(A,B)=\left[\begin{array}{cc} +\left(-B^{T}A\right) & I_{3}\end{array}\right] +\] + +\end_inset + + +\end_layout + +\begin_layout Subsection +Numerical PushForward +\end_layout + +\begin_layout Standard +Let's examine +\begin_inset Formula +\[ +f\left(g\right)e^{\yhat}=f\left(ge^{\xhat}\right) +\] + +\end_inset + +and multiply with +\begin_inset Formula $f(g)^{-1}$ +\end_inset + + on both sides: +\begin_inset Formula +\[ +e^{\yhat}=f\left(g\right)^{-1}f\left(ge^{\xhat}\right) +\] + +\end_inset + +We then take the log (which in our case returns +\begin_inset Formula $y$ +\end_inset + +, not +\begin_inset Formula $\yhat$ +\end_inset + +): +\begin_inset Formula +\[ +y(x)=\log\left[f\left(g\right)^{-1}f\left(ge^{\xhat}\right)\right] +\] + +\end_inset + +Let us look at +\begin_inset Formula $x=0$ +\end_inset + +, and perturb in direction +\begin_inset Formula $i$ +\end_inset + +, +\begin_inset Formula $e_{i}=[0,0,1,0,0]$ +\end_inset + +. + Then take derivative, +\begin_inset Formula +\[ +\deriv{y(d)}d\define\lim_{d\rightarrow0}\frac{y(d)-y(0)}{d}=\lim_{d\rightarrow0}\frac{1}{d}\log\left[f\left(g\right)^{-1}f\left(ge^{\widehat{de_{i}}}\right)\right] +\] + +\end_inset + +which is the basis for a numerical derivative scheme. +\begin_inset Note Note +status collapsed + +\begin_layout Plain Layout +Not understood yet: Let us also look at a chain rule. + If we know the behavior at the origin +\begin_inset Formula $I$ +\end_inset + +, we can extrapolate +\begin_inset Formula +\[ +f(ge^{\xhat})=f(ge^{\xhat}g^{-1}g)=f(e^{\Ad g\xhat}g) +\] + +\end_inset + + +\end_layout + +\end_inset + + +\end_layout + +\begin_layout Subsection +Derivative of the Exponential and Logarithm Map +\end_layout + +\begin_layout Theorem +\begin_inset CommandInset label +LatexCommand label +name "D-exp" + +\end_inset + +The derivative of the function +\begin_inset Formula $f:\Reals n\rightarrow G$ +\end_inset + + that applies the wedge operator followed by the exponential map, i.e., +\begin_inset Formula $f(\xi)=\exp\xihat$ +\end_inset + +, is the identity map for +\begin_inset Formula $\xi=0$ +\end_inset + +. +\end_layout + +\begin_layout Proof +For +\begin_inset Formula $\xi=0$ +\end_inset + +, we have +\begin_inset Formula +\begin{eqnarray*} +f(\xi)e^{\yhat} & = & f(\xi+x)\\ +f(0)e^{\yhat} & = & f(0+x)\\ +e^{\yhat} & = & e^{\xhat} +\end{eqnarray*} + +\end_inset + + +\end_layout + +\begin_layout Corollary +The derivative of the inverse +\begin_inset Formula $f^{-1}$ +\end_inset + + is the identity as well, i.e., for +\begin_inset Formula $T=e$ +\end_inset + +, the identity element in +\begin_inset Formula $G$ +\end_inset + +. +\end_layout + +\begin_layout Standard +For +\begin_inset Formula $\xi\neq0$ +\end_inset + +, things are not simple, see . + +\begin_inset Flex URL +status collapsed + +\begin_layout Plain Layout + +http://deltaepsilons.wordpress.com/2009/11/06/helgasons-formula-for-the-differenti +al-of-the-exponential/ +\end_layout + +\end_inset + +. +\end_layout + +\begin_layout Standard +\begin_inset Newpage pagebreak +\end_inset + + +\end_layout + +\begin_layout Section +General Manifolds +\end_layout + +\begin_layout Subsection +Retractions +\end_layout + +\begin_layout Standard +\begin_inset FormulaMacro +\newcommand{\retract}{\mathcal{R}} +{\mathcal{R}} +\end_inset + + +\end_layout + +\begin_layout Standard +General manifolds that are not Lie groups do not have an exponential map, + but can still be handled by defining a +\series bold +retraction +\series default + +\begin_inset Formula $\retract:\Man\times\Reals n\rightarrow\Man$ +\end_inset + +, such that +\begin_inset Formula +\[ +a\oplus\xi\define\retract_{a}\left(\xi\right) +\] + +\end_inset + +A retraction +\begin_inset CommandInset citation +LatexCommand cite +key "Absil07book" + +\end_inset + + is required to be tangent to geodesics on the manifold +\begin_inset Formula $\Man$ +\end_inset + + at +\begin_inset Formula $a$ +\end_inset + +. + We can define many retractions for a manifold +\begin_inset Formula $\Man$ +\end_inset + +, even for those with more structure. + For the vector space +\begin_inset Formula $\Reals n$ +\end_inset + + the retraction is just vector addition, and for Lie groups the obvious + retraction is simply the exponential map, i.e., +\begin_inset Formula $\retract_{a}(\xi)=a\cdot\exp\xihat$ +\end_inset + +. + However, one can choose other, possibly computationally attractive retractions, + as long as around a they agree with the geodesic induced by the exponential + map, i.e., +\begin_inset Formula +\[ +\lim_{\xi\rightarrow0}\frac{\left|a\cdot\exp\xihat-\retract_{a}\left(\xi\right)\right|}{\left|\xi\right|}=0 +\] + +\end_inset + + +\end_layout + +\begin_layout Example +For +\begin_inset Formula $\SEthree$ +\end_inset + +, instead of using the true exponential map it is computationally more efficient + to define the retraction, which uses a first order approximation of the + translation update +\begin_inset Formula +\[ +\retract_{T}\left(\left[\begin{array}{c} +\omega\\ +v +\end{array}\right]\right)=\left[\begin{array}{cc} +R & t\\ +0 & 1 +\end{array}\right]\left[\begin{array}{cc} +e^{\Skew{\omega}} & v\\ +0 & 1 +\end{array}\right]=\left[\begin{array}{cc} +Re^{\Skew{\omega}} & t+Rv\\ +0 & 1 +\end{array}\right] +\] + +\end_inset + + +\end_layout + +\begin_layout Subsection +Derivatives +\end_layout + +\begin_layout Standard +Equipped with a retraction, then, we can generalize the notion of a derivative + for functions +\begin_inset Formula $f$ +\end_inset + + from general a manifold +\begin_inset Formula $\Man$ +\end_inset + + to +\begin_inset Formula $\Reals m$ +\end_inset + +: +\end_layout + +\begin_layout Definition +We define a function +\begin_inset Formula $f:\Man\rightarrow\Reals m$ +\end_inset + + to be +\series bold +differentiable +\series default + at +\begin_inset Formula $a\in\Man$ +\end_inset + + if there exists a matrix +\begin_inset Formula $f'(a)$ +\end_inset + + such that +\begin_inset Formula +\[ +\lim_{\xi\rightarrow0}\frac{\left|f(a)+f'(a)\xi-f\left(\retract_{a}(\xi)\right)\right|}{\left|\xi\right|}=0 +\] + +\end_inset + +with +\begin_inset Formula $\xi\in\Reals n$ +\end_inset + + for an +\begin_inset Formula $n$ +\end_inset + +-dimensional manifold, and +\begin_inset Formula $\retract_{a}:\Reals n\rightarrow\Man$ +\end_inset + + a retraction +\begin_inset Formula $\retract$ +\end_inset + + at +\begin_inset Formula $a$ +\end_inset + +. + If +\begin_inset Formula $f$ +\end_inset + + is differentiable, then +\begin_inset Formula $f'(a)$ +\end_inset + + is called the +\series bold +Jacobian matrix +\series default + of +\begin_inset Formula $f$ +\end_inset + + at +\begin_inset Formula $a$ +\end_inset + +, and the linear transformation +\begin_inset Formula $Df_{a}:\xi\mapsto f'(a)\xi$ +\end_inset + + is called the +\series bold +derivative +\series default + of +\begin_inset Formula $f$ +\end_inset + + at +\begin_inset Formula $a$ +\end_inset + +. +\end_layout + +\begin_layout Definition +For manifolds that are also Lie groups, the derivative of any function +\begin_inset Formula $f:G\rightarrow\Reals m$ +\end_inset + + will agree no matter what retraction +\begin_inset Formula $\retract$ +\end_inset + + is used. +\end_layout + +\begin_layout Standard +\begin_inset Newpage pagebreak +\end_inset + + +\end_layout + +\begin_layout Part +Practice +\end_layout + +\begin_layout Standard +Below we apply the results derived in the theory part to the geometric objects + we use in GTSAM. + Above we preferred the modern notation +\begin_inset Formula $D_{1}f$ +\end_inset + + for the partial derivative. + Below (because this was written earlier) we use the more classical notation + +\begin_inset Formula +\[ +\deriv{f(x,y)}x +\] + +\end_inset + +In addition, for Lie groups we will abuse the notation and take +\begin_inset Formula +\[ +\at{\deriv{\varphi(g)}{\xi}}a +\] + +\end_inset + +to be the Jacobian matrix +\begin_inset Formula $\varphi'($ +\end_inset + +a) of the mapping +\begin_inset Formula $\varphi$ +\end_inset + + at +\begin_inset Formula $a\in G$ +\end_inset + +, associated with the pushforward +\begin_inset Formula $D\varphi_{a}$ +\end_inset + +. +\end_layout + +\begin_layout Section +SLAM Example +\end_layout + +\begin_layout Standard +Let us examine a visual SLAM example. + We have 2D measurements +\begin_inset Formula $z_{ij}$ +\end_inset + +, where each measurement is predicted by +\begin_inset Formula +\[ +z_{ij}=h(T_{i},p_{j})=\pi(T_{i}^{-1}p_{j}) +\] + +\end_inset + +where +\begin_inset Formula $T_{i}$ +\end_inset + + is the 3D pose of the +\begin_inset Formula $i^{th}$ +\end_inset + + camera, +\begin_inset Formula $p_{j}$ +\end_inset + + is the location of the +\begin_inset Formula $j^{th}$ +\end_inset + + point, and +\begin_inset Formula $\pi:(x,y,z)\mapsto(x/z,y/z)$ +\end_inset + + is the camera projection function from Example +\begin_inset CommandInset ref +LatexCommand ref +reference "ex:projection" + +\end_inset + +. +\end_layout + +\begin_layout Section +BetweenFactor +\end_layout + +\begin_layout Standard +BetweenFactor is often used to summarize +\end_layout + +\begin_layout Standard +Theorem +\begin_inset CommandInset ref +LatexCommand ref +reference "D-exp" + +\end_inset + + about the derivative of the exponential map +\begin_inset Formula $f:\xi\mapsto\exp\xihat$ +\end_inset + + being identity only at +\begin_inset Formula $\xi=0$ +\end_inset + + has implications for GTSAM. + Given two elements +\begin_inset Formula $T_{1}$ +\end_inset + + and +\begin_inset Formula $T_{2}$ +\end_inset + +, BetweenFactor evaluates +\begin_inset Formula +\[ +g(T_{1},T_{2};Z)=f^{-1}\left(\mathop{between}(Z,\mathop{between}(T_{1},T_{2})\right)=f^{-1}\left(Z^{-1}\left(T_{1}^{-1}T_{2}\right)\right) +\] + +\end_inset + +but because it is assumed that +\begin_inset Formula $Z\approx T_{1}^{-1}T_{2}$ +\end_inset + +, and hence we have +\begin_inset Formula $Z^{-1}T_{1}^{-1}T_{2}\approx e$ +\end_inset + + and the derivative should be good there. + Note that the derivative of +\emph on +between +\emph default + is identity in its second argument. +\end_layout + +\begin_layout Section +Point3 +\end_layout + +\begin_layout Standard +A cross product +\begin_inset Formula $a\times b$ +\end_inset + + can be written as a matrix multiplication +\begin_inset Formula +\[ +a\times b=\Skew ab +\] + +\end_inset + +where +\begin_inset Formula $\Skew a$ +\end_inset + + is a skew-symmetric matrix defined as +\begin_inset Formula +\[ +\Skew{x,y,z}=\left[\begin{array}{ccc} +0 & -z & y\\ +z & 0 & -x\\ +-y & x & 0 +\end{array}\right] +\] + +\end_inset + +We also have +\begin_inset Formula +\[ +a^{T}\Skew b=-(\Skew ba)^{T}=-(a\times b)^{T} +\] + +\end_inset + +The derivative of a cross product +\begin_inset Formula +\begin{equation} +\frac{\partial(a\times b)}{\partial a}=\Skew{-b}\label{eq:Dcross1} +\end{equation} + +\end_inset + + +\begin_inset Formula +\begin{equation} +\frac{\partial(a\times b)}{\partial b}=\Skew a\label{eq:Dcross2} +\end{equation} + +\end_inset + + +\end_layout + +\begin_layout Standard +\begin_inset Newpage pagebreak +\end_inset + + +\end_layout + +\begin_layout Section +2D Rotations +\end_layout + +\begin_layout Subsection +Rot2 in GTSAM +\end_layout + +\begin_layout Standard +A rotation is stored as +\begin_inset Formula $(\cos\theta,\sin\theta)$ +\end_inset + +. + An incremental rotation is applied using the trigonometric sum rule: +\begin_inset Formula +\[ +\cos\theta'=\cos\theta\cos\delta-\sin\theta\sin\delta +\] + +\end_inset + + +\begin_inset Formula +\[ +\sin\theta'=\sin\theta\cos\delta+\cos\theta\sin\delta +\] + +\end_inset + +where +\begin_inset Formula $\delta$ +\end_inset + + is an incremental rotation angle. +\end_layout + +\begin_layout Subsection +Derivatives of Actions +\end_layout + +\begin_layout Standard +In the case of +\begin_inset Formula $\SOtwo$ +\end_inset + + the vector space is +\begin_inset Formula $\Rtwo$ +\end_inset + +, and the group action +\begin_inset Formula $f(R,p)$ +\end_inset + + corresponds to rotating the 2D point +\begin_inset Formula $p$ +\end_inset + + +\begin_inset Formula +\[ +f(R,p)=Rp +\] + +\end_inset + +According to Theorem +\begin_inset CommandInset ref +LatexCommand ref +reference "th:Action" + +\end_inset + +, the Jacobian matrix of +\begin_inset Formula $f$ +\end_inset + + is given by +\begin_inset Formula +\[ +f'(R,p)=\left[\begin{array}{cc} +RH(p) & R\end{array}\right] +\] + +\end_inset + +with +\begin_inset Formula $H:\Reals 2\rightarrow\Reals{2\times2}$ +\end_inset + + a linear mapping that depends on +\begin_inset Formula $p$ +\end_inset + +. + In the case of +\begin_inset Formula $\SOtwo$ +\end_inset + +, we can find +\begin_inset Formula $H(p)$ +\end_inset + + by equating (as in Equation +\begin_inset CommandInset ref +LatexCommand ref +reference "eq:Hp" + +\end_inset + +): +\begin_inset Formula +\[ +\skew wp=\left[\begin{array}{cc} +0 & -\omega\\ +\omega & 0 +\end{array}\right]\left[\begin{array}{c} +x\\ +y +\end{array}\right]=\left[\begin{array}{c} +-y\\ +x +\end{array}\right]\omega=H(p)\omega +\] + +\end_inset + +Note that +\family roman +\series medium +\shape up +\size normal +\emph off +\bar no +\strikeout off +\uuline off +\uwave off +\noun off +\color none + +\begin_inset Formula +\[ +H(p)=\left[\begin{array}{c} +-y\\ +x +\end{array}\right]=\left[\begin{array}{cc} +0 & -1\\ +1 & 0 +\end{array}\right]\left[\begin{array}{c} +x\\ +y +\end{array}\right]=R_{\pi/2}p +\] + +\end_inset + +and since 2D rotations commute, we also have, with +\begin_inset Formula $q=Rp$ +\end_inset + + +\family default +\series default +\shape default +\size default +\emph default +\bar default +\strikeout default +\uuline default +\uwave default +\noun default +\color inherit +: +\begin_inset Formula +\[ +f'(R,p)=\left[\begin{array}{cc} +R\left(R_{\pi/2}p\right) & R\end{array}\right]=\left[\begin{array}{cc} +R_{\pi/2}q & R\end{array}\right] +\] + +\end_inset + + +\end_layout + +\begin_layout Subsection +Pushforwards of Mappings +\end_layout + +\begin_layout Standard +Since +\begin_inset Formula $\Ad R\skew{\omega}=\skew{\omega}$ +\end_inset + +, we have the derivative of +\series bold +inverse +\series default +, +\begin_inset Formula +\[ +\frac{\partial R^{T}}{\partial\omega}=-\Ad R=-1\mbox{ } +\] + +\end_inset + + +\series bold +compose, +\series default + +\begin_inset Formula +\[ +\frac{\partial\left(R_{1}R_{2}\right)}{\partial\omega_{1}}=\Ad{R_{2}^{T}}=1\mbox{ and }\frac{\partial\left(R_{1}R_{2}\right)}{\partial\omega_{2}}=1 +\] + +\end_inset + +and +\series bold +between: +\series default + +\begin_inset Formula +\[ +\frac{\partial\left(R_{1}^{T}R_{2}\right)}{\partial\omega_{1}}=-\Ad{R_{2}^{T}R_{1}}=-1\mbox{ and }\frac{\partial\left(R_{1}^{T}R_{2}\right)}{\partial\omega_{2}}=1 +\] + +\end_inset + + +\end_layout + +\begin_layout Standard +\begin_inset Newpage pagebreak +\end_inset + + +\end_layout + +\begin_layout Section +2D Rigid Transformations +\end_layout + +\begin_layout Subsection +The derivatives of Actions +\end_layout + +\begin_layout Standard +The action of +\begin_inset Formula $\SEtwo$ +\end_inset + + on 2D points is done by embedding the points in +\begin_inset Formula $\mathbb{R}^{3}$ +\end_inset + + by using homogeneous coordinates +\begin_inset Formula +\[ +f(T,p)=\hat{q}=\left[\begin{array}{c} +q\\ +1 +\end{array}\right]=\left[\begin{array}{cc} +R & t\\ +0 & 1 +\end{array}\right]\left[\begin{array}{c} +p\\ +1 +\end{array}\right]=T\hat{p} +\] + +\end_inset + +To find the derivative, we write the quantity +\begin_inset Formula $\xihat\hat{p}$ +\end_inset + + as the product of the +\begin_inset Formula $3\times3$ +\end_inset + + matrix +\begin_inset Formula $H(p)$ +\end_inset + + with +\begin_inset Formula $\xi$ +\end_inset + +: +\begin_inset Formula +\begin{equation} +\xihat\hat{p}=\left[\begin{array}{cc} +\skew{\omega} & v\\ +0 & 0 +\end{array}\right]\left[\begin{array}{c} +p\\ +1 +\end{array}\right]=\left[\begin{array}{c} +\skew{\omega}p+v\\ +0 +\end{array}\right]=\left[\begin{array}{cc} +I_{2} & R_{\pi/2}p\\ +0 & 0 +\end{array}\right]\left[\begin{array}{c} +v\\ +\omega +\end{array}\right]=H(p)\xi\label{eq:HpSE2} +\end{equation} + +\end_inset + +Hence, by Theorem +\begin_inset CommandInset ref +LatexCommand ref +reference "th:Action" + +\end_inset + + we have +\begin_inset Formula +\begin{equation} +\deriv{\left(T\hat{p}\right)}{\xi}=TH(p)=\left[\begin{array}{cc} +R & t\\ +0 & 1 +\end{array}\right]\left[\begin{array}{cc} +I_{2} & R_{\pi/2}p\\ +0 & 0 +\end{array}\right]=\left[\begin{array}{cc} +R & RR_{\pi/2}p\\ +0 & 0 +\end{array}\right]=\left[\begin{array}{cc} +R & R_{\pi/2}q\\ +0 & 0 +\end{array}\right]\label{eq:SE2Action} +\end{equation} + +\end_inset + +Note that, looking only at the top rows of +\begin_inset CommandInset ref +LatexCommand eqref +reference "eq:HpSE2" + +\end_inset + + and +\begin_inset CommandInset ref +LatexCommand eqref +reference "eq:SE2Action" + +\end_inset + +, we can recognize the quantity +\begin_inset Formula $\skew{\omega}p+v=v+\omega\left(R_{\pi/2}p\right)$ +\end_inset + + as the velocity of +\begin_inset Formula $p$ +\end_inset + + in +\begin_inset Formula $\Rtwo$ +\end_inset + +, and +\begin_inset Formula $\left[\begin{array}{cc} +R & R_{\pi/2}q\end{array}\right]$ +\end_inset + + is the derivative of the action on +\begin_inset Formula $\Rtwo$ +\end_inset + +. + +\end_layout + +\begin_layout Standard +The derivative of the inverse action +\begin_inset Formula $g(T,p)=T^{-1}\hat{p}$ +\end_inset + + is given by Theorem +\begin_inset CommandInset ref +LatexCommand ref +reference "Th:InverseAction" + +\end_inset + + specialized to +\begin_inset Formula $\SEtwo$ +\end_inset + +: +\end_layout + +\begin_layout Standard +\begin_inset Formula +\[ +\deriv{\left(T^{-1}\hat{p}\right)}{\xi}=-H(T^{-1}p)=\left[\begin{array}{cc} +-I_{2} & -R_{\pi/2}\left(T^{-1}p\right)\\ +0 & 0 +\end{array}\right] +\] + +\end_inset + + +\end_layout + +\begin_layout Subsection +Pushforwards of Mappings +\end_layout + +\begin_layout Standard +We can just define all derivatives in terms of the adjoint map, which in + the case of +\begin_inset Formula $\SEtwo$ +\end_inset + +, in twist coordinates, is the linear mapping +\begin_inset Formula +\[ +\Ad T\xi=\left[\begin{array}{cc} +R & -R_{\pi/2}t\\ +0 & 1 +\end{array}\right]\left[\begin{array}{c} +v\\ +\omega +\end{array}\right] +\] + +\end_inset + +and we have +\begin_inset Formula +\begin{eqnarray*} +\frac{\partial T^{^{-1}}}{\partial\xi} & = & -\Ad T +\end{eqnarray*} + +\end_inset + + +\begin_inset Formula +\begin{eqnarray*} +\frac{\partial\left(T_{1}T_{2}\right)}{\partial\xi_{1}} & = & \Ad{T_{2}^{^{-1}}}\mbox{ and }\frac{\partial\left(T_{1}T_{2}\right)}{\partial\xi_{2}}=I_{3} +\end{eqnarray*} + +\end_inset + + +\begin_inset Formula +\begin{eqnarray*} +\frac{\partial\left(T_{1}^{-1}T_{2}\right)}{\partial\xi_{1}} & = & -\Ad{T_{2}^{^{-1}}T_{1}}=-\Ad{between(T_{2},T_{1})}\mbox{ and }\frac{\partial\left(T_{1}^{-1}T_{2}\right)}{\partial\xi_{2}}=I_{3} +\end{eqnarray*} + +\end_inset + + +\end_layout + +\begin_layout Standard +\begin_inset Newpage pagebreak +\end_inset + + +\end_layout + +\begin_layout Section +3D Rotations +\end_layout + +\begin_layout Subsection +Derivatives of Actions +\end_layout + +\begin_layout Standard +In the case of +\begin_inset Formula $\SOthree$ +\end_inset + + the vector space is +\begin_inset Formula $\Rthree$ +\end_inset + +, and the group action +\begin_inset Formula $f(R,p)$ +\end_inset + + corresponds to rotating a point +\begin_inset Formula +\[ +q=f(R,p)=Rp +\] + +\end_inset + +To calculate +\begin_inset Formula $H(p)$ +\end_inset + + for use in Theorem +\begin_inset CommandInset ref +LatexCommand eqref +reference "th:Action" + +\end_inset + + we make use of +\begin_inset Formula +\[ +\Skew{\omega}p=\omega\times p=-p\times\omega=\Skew{-p}\omega +\] + +\end_inset + +so +\begin_inset Formula $H(p)\define\Skew{-p}$ +\end_inset + +. + Hence, the final derivative of an action in its first argument is +\begin_inset Formula +\[ +\deriv{\left(Rp\right)}{\omega}=RH(p)=-R\Skew p +\] + +\end_inset + +Likewise, according to Theorem +\begin_inset CommandInset ref +LatexCommand ref +reference "Th:InverseAction" + +\end_inset + +, the derivative of the inverse action is given by +\end_layout + +\begin_layout Standard +\begin_inset Formula +\[ +\deriv{\left(R^{T}p\right)}{\omega}=-H(R^{T}p)=\Skew{R^{T}p} +\] + +\end_inset + + +\end_layout + +\begin_layout Subsection +\begin_inset CommandInset label +LatexCommand label +name "sub:3DAngularVelocities" + +\end_inset + +Instantaneous Velocity +\end_layout + +\begin_layout Standard +For 3D rotations +\begin_inset Formula $R_{b}^{n}$ +\end_inset + + from a body frame +\begin_inset Formula $b$ +\end_inset + + to a navigation frame +\begin_inset Formula $n$ +\end_inset + + we have the spatial angular velocity +\begin_inset Formula $\omega_{nb}^{n}$ +\end_inset + + measured in the navigation frame, +\begin_inset Formula +\[ +\Skew{\omega_{nb}^{n}}\define\dot{R}_{b}^{n}\left(R_{b}^{n}\right)^{T}=\dot{R}_{b}^{n}R_{n}^{b} +\] + +\end_inset + +and the body angular velocity +\begin_inset Formula $\omega_{nb}^{b}$ +\end_inset + + measured in the body frame: +\begin_inset Formula +\[ +\Skew{\omega_{nb}^{b}}\define\left(R_{b}^{n}\right)^{T}\dot{R}_{b}^{n}=R_{n}^{b}\dot{R}_{b}^{n} +\] + +\end_inset + +These quantities can be used to derive the velocity of a point +\begin_inset Formula $p$ +\end_inset + +, and we choose between spatial or body angular velocity depending on the + frame in which we choose to represent +\begin_inset Formula $p$ +\end_inset + +: +\begin_inset Formula +\[ +v^{n}=\Skew{\omega_{nb}^{n}}p^{n}=\omega_{nb}^{n}\times p^{n} +\] + +\end_inset + + +\begin_inset Formula +\[ +v^{b}=\Skew{\omega_{nb}^{b}}p^{b}=\omega_{nb}^{b}\times p^{b} +\] + +\end_inset + +We can transform these skew-symmetric matrices from navigation to body frame + by conjugating, +\begin_inset Formula +\[ +\Skew{\omega_{nb}^{b}}=R_{n}^{b}\Skew{\omega_{nb}^{n}}R_{b}^{n} +\] + +\end_inset + +but because the adjoint representation satisfies +\begin_inset Formula +\[ +Ad_{R}\Skew{\omega}\define R\Skew{\omega}R^{T}=\Skew{R\omega} +\] + +\end_inset + +we can even more easily transform between spatial and body angular velocities + as 3-vectors: +\begin_inset Formula +\[ +\omega_{nb}^{b}=R_{n}^{b}\omega_{nb}^{n} +\] + +\end_inset + + +\end_layout + +\begin_layout Subsection +Pushforwards of Mappings +\end_layout + +\begin_layout Standard +For +\begin_inset Formula $\SOthree$ +\end_inset + + we have +\begin_inset Formula $\Ad R\Skew{\omega}=\Skew{R\omega}$ +\end_inset + + and, in terms of angular velocities: +\begin_inset Formula $\Ad R\omega=R\omega$ +\end_inset + +. + Hence, the Jacobian matrix of the +\series bold +inverse +\series default + mapping is (see Equation +\begin_inset CommandInset ref +LatexCommand ref +reference "eq:Dinverse" + +\end_inset + +) +\begin_inset Formula +\[ +\frac{\partial R^{T}}{\partial\omega}=-\Ad R=-R +\] + +\end_inset + +for +\series bold +compose +\series default + we have (Equations +\begin_inset CommandInset ref +LatexCommand ref +reference "eq:Dcompose1" + +\end_inset + + and +\begin_inset CommandInset ref +LatexCommand ref +reference "eq:Dcompose2" + +\end_inset + +): +\begin_inset Formula +\[ +\frac{\partial\left(R_{1}R_{2}\right)}{\partial\omega_{1}}=R_{2}^{T}\mbox{ and }\frac{\partial\left(R_{1}R_{2}\right)}{\partial\omega_{2}}=I_{3} +\] + +\end_inset + +and +\series bold +between +\series default + (Equation +\begin_inset CommandInset ref +LatexCommand ref +reference "eq:Dbetween1" + +\end_inset + +): +\begin_inset Formula +\[ +\frac{\partial\left(R_{1}^{T}R_{2}\right)}{\partial\omega_{1}}=-R_{2}^{T}R_{1}=-between(R_{2},R_{1})\mbox{ and }\frac{\partial\left(R_{1}R_{2}\right)}{\partial\omega_{2}}=I_{3} +\] + +\end_inset + + +\end_layout + +\begin_layout Subsection +Retractions +\end_layout + +\begin_layout Standard +Absil +\begin_inset CommandInset citation +LatexCommand cite +after "page 58" +key "Absil07book" + +\end_inset + + discusses two possible retractions for +\begin_inset Formula $\SOthree$ +\end_inset + + based on the QR decomposition or the polar decomposition of the matrix + +\begin_inset Formula $R\Skew{\omega}$ +\end_inset + +, but they are expensive. + Another retraction is based on the Cayley transform +\begin_inset Formula $\mathcal{C}:\sothree\rightarrow\SOthree$ +\end_inset + +, a mapping from the skew-symmetric matrices to rotation matrices: +\begin_inset Formula +\[ +Q=\mathcal{C}(\Omega)=(I-\Omega)(I+\Omega)^{-1} +\] + +\end_inset + +Interestingly, the inverse Cayley transform +\begin_inset Formula $\mathcal{C}^{-1}:\SOthree\rightarrow\sothree$ +\end_inset + + has the same form: +\begin_inset Formula +\[ +\Omega=\mathcal{C}^{-1}(Q)=(I-Q)(I+Q)^{-1} +\] + +\end_inset + +The retraction needs a factor +\begin_inset Formula $-\frac{1}{2}$ +\end_inset + + however, to make it locally align with a geodesic: +\begin_inset Formula +\[ +R'=\retract_{R}(\omega)=R\mathcal{C}(-\frac{1}{2}\Skew{\omega}) +\] + +\end_inset + +Note that given +\begin_inset Formula $\omega=(x,y,z)$ +\end_inset + + this has the closed-form expression below +\begin_inset Formula +\[ +\frac{1}{4+x^{2}+y^{2}+z^{2}}\left[\begin{array}{ccc} +4+x^{2}-y^{2}-z^{2} & 2xy-4z & 2xz+4y\\ +2xy+4z & 4-x^{2}+y^{2}-z^{2} & 2yz-4x\\ +2xz-4y & 2yz+4x & 4-x^{2}-y^{2}+z^{2} +\end{array}\right] +\] + +\end_inset + + +\begin_inset Formula +\[ +=\frac{1}{4+x^{2}+y^{2}+z^{2}}\left\{ 4(I+\Skew{\omega})+\left[\begin{array}{ccc} +x^{2}-y^{2}-z^{2} & 2xy & 2xz\\ +2xy & -x^{2}+y^{2}-z^{2} & 2yz\\ +2xz & 2yz & -x^{2}-y^{2}+z^{2} +\end{array}\right]\right\} +\] + +\end_inset + +so it can be seen to be a second-order correction on +\begin_inset Formula $(I+\Skew{\omega})$ +\end_inset + +. + The corresponding approximation to the logarithmic map is: +\begin_inset Formula +\[ +\Skew{\omega}=\retract_{R}^{-1}(R')=-2\mathcal{C}^{-1}\left(R^{T}R'\right) +\] + +\end_inset + + +\end_layout + +\begin_layout Section +3D Rigid Transformations +\end_layout + +\begin_layout Subsection +The derivatives of Actions +\end_layout + +\begin_layout Standard +The action of +\begin_inset Formula $\SEthree$ +\end_inset + + on 3D points is done by embedding the points in +\begin_inset Formula $\mathbb{R}^{4}$ +\end_inset + + by using homogeneous coordinates +\begin_inset Formula +\[ +\hat{q}=\left[\begin{array}{c} +q\\ +1 +\end{array}\right]=f(T,p)=\left[\begin{array}{cc} +R & t\\ +0 & 1 +\end{array}\right]\left[\begin{array}{c} +p\\ +1 +\end{array}\right]=T\hat{p} +\] + +\end_inset + +The quantity +\begin_inset Formula $\xihat\hat{p}$ +\end_inset + + corresponds to a velocity in +\begin_inset Formula $\mathbb{R}^{4}$ +\end_inset + + (in the local +\begin_inset Formula $T$ +\end_inset + + frame), and equating it to +\begin_inset Formula $H(p)\xi$ +\end_inset + + as in Equation +\begin_inset CommandInset ref +LatexCommand ref +reference "eq:Hp" + +\end_inset + + yields the +\begin_inset Formula $4\times6$ +\end_inset + + matrix +\begin_inset Formula $H(p)$ +\end_inset + + +\begin_inset Foot +status collapsed + +\begin_layout Plain Layout +\begin_inset Formula $H(p)$ +\end_inset + + can also be obtained by taking the +\begin_inset Formula $j^{th}$ +\end_inset + + column of each of the 6 generators to multiply with components of +\begin_inset Formula $\hat{p}$ +\end_inset + + +\end_layout + +\end_inset + +: +\begin_inset Formula +\[ +\xihat\hat{p}=\left[\begin{array}{cc} +\Skew{\omega} & v\\ +0 & 0 +\end{array}\right]\left[\begin{array}{c} +p\\ +1 +\end{array}\right]=\left[\begin{array}{c} +\omega\times p+v\\ +0 +\end{array}\right]=\left[\begin{array}{cc} +\Skew{-p} & I_{3}\\ +0 & 0 +\end{array}\right]\left[\begin{array}{c} +\omega\\ +v +\end{array}\right]=H(p)\xi +\] + +\end_inset + +Note how velocities are analogous to points at infinity in projective geometry: + they correspond to free vectors indicating a direction and magnitude of + change. + According to Theorem +\begin_inset CommandInset ref +LatexCommand ref +reference "th:Action" + +\end_inset + +, the derivative of the group action is then +\begin_inset Formula +\[ +\deriv{\left(T\hat{p}\right)}{\xi}=TH(p)=\left[\begin{array}{cc} +R & t\\ +0 & 1 +\end{array}\right]\left[\begin{array}{cc} +\Skew{-p} & I_{3}\\ +0 & 0 +\end{array}\right]=\left[\begin{array}{cc} +R\Skew{-p} & R\\ +0 & 0 +\end{array}\right] +\] + +\end_inset + + +\begin_inset Formula +\[ +\deriv{\left(T\hat{p}\right)}{\hat{p}}=\left[\begin{array}{cc} +R & t\\ +0 & 1 +\end{array}\right] +\] + +\end_inset + +in homogenous coordinates. + In +\begin_inset Formula $\Rthree$ +\end_inset + + this becomes +\begin_inset Formula $R\left[\begin{array}{cc} +-\Skew p & I_{3}\end{array}\right]$ +\end_inset + +. +\end_layout + +\begin_layout Standard +The derivative of the inverse action +\begin_inset Formula $T^{-1}p$ +\end_inset + + is given by Theorem +\begin_inset CommandInset ref +LatexCommand ref +reference "Th:InverseAction" + +\end_inset + +: +\end_layout + +\begin_layout Standard + +\family roman +\series medium +\shape up +\size normal +\emph off +\bar no +\noun off +\color none +\begin_inset Formula +\[ +\deriv{\left(T^{-1}\hat{p}\right)}{\xi}=-H\left(T^{-1}\hat{p}\right)=\left[\begin{array}{cc} +\Skew{T^{-1}\hat{p}} & -I_{3}\end{array}\right] +\] + +\end_inset + + +\begin_inset Formula +\[ +\deriv{\left(T^{-1}\hat{p}\right)}{\hat{p}}=\left[\begin{array}{cc} +R^{T} & -R^{T}t\\ +0 & 1 +\end{array}\right] +\] + +\end_inset + + +\end_layout + +\begin_layout Example +Let us examine a visual SLAM example. + We have 2D measurements +\begin_inset Formula $z_{ij}$ +\end_inset + +, where each measurement is predicted by +\begin_inset Formula +\[ +z_{ij}=h(T_{i},p_{j})=\pi(T_{i}^{-1}p_{j})=\pi(q) +\] + +\end_inset + +where +\begin_inset Formula $T_{i}$ +\end_inset + + is the 3D pose of the +\begin_inset Formula $i^{th}$ +\end_inset + + camera, +\begin_inset Formula $p_{j}$ +\end_inset + + is the location of the +\begin_inset Formula $j^{th}$ +\end_inset + + point, +\begin_inset Formula $q=(x',y',z')=T^{-1}p$ +\end_inset + + is the point in camera coordinates, and +\begin_inset Formula $\pi:(x,y,z)\mapsto(x/z,y/z)$ +\end_inset + + is the camera projection function from Example +\begin_inset CommandInset ref +LatexCommand ref +reference "ex:projection" + +\end_inset + +. + By the chain rule, we then have +\begin_inset Formula +\[ +\deriv{h(T,p)}{\xi}=\deriv{\pi(q)}q\deriv{(T^{-1}p)}{\xi}=\frac{1}{z'}\left[\begin{array}{ccc} +1 & 0 & -x'/z'\\ +0 & 1 & -y'/z' +\end{array}\right]\left[\begin{array}{cc} +\Skew q & -I_{3}\end{array}\right]=\left[\begin{array}{cc} +\pi'(q)\Skew q & -\pi'(q)\end{array}\right] +\] + +\end_inset + + +\begin_inset Formula +\[ +\deriv{h(T,p)}p=\pi'(q)R^{T} +\] + +\end_inset + + +\end_layout + +\begin_layout Subsection +Instantaneous Velocity +\end_layout + +\begin_layout Standard +For rigid 3D transformations +\begin_inset Formula $T_{b}^{n}$ +\end_inset + + from a body frame +\begin_inset Formula $b$ +\end_inset + + to a navigation frame +\begin_inset Formula $n$ +\end_inset + + we have the instantaneous spatial twist +\begin_inset Formula $\xi_{nb}^{n}$ +\end_inset + + measured in the navigation frame, +\begin_inset Formula +\[ +\hat{\xi}_{nb}^{n}\define\dot{T}_{b}^{n}\left(T_{b}^{n}\right)^{-1} +\] + +\end_inset + +and the instantaneous body twist +\begin_inset Formula $\xi_{nb}^{b}$ +\end_inset + + measured in the body frame: +\begin_inset Formula +\[ +\hat{\xi}_{nb}^{b}\define\left(T_{b}^{n}\right)^{T}\dot{T}_{b}^{n} +\] + +\end_inset + + +\end_layout + +\begin_layout Subsection +Pushforwards of Mappings +\end_layout + +\begin_layout Standard +As we can express the Adjoint representation in terms of twist coordinates, + we have +\begin_inset Formula +\[ +\left[\begin{array}{c} +\omega'\\ +v' +\end{array}\right]=\left[\begin{array}{cc} +R & 0\\ +\Skew tR & R +\end{array}\right]\left[\begin{array}{c} +\omega\\ +v +\end{array}\right] +\] + +\end_inset + +Hence, as with +\begin_inset Formula $\SOthree$ +\end_inset + +, we are now in a position to simply posit the derivative of +\series bold +inverse +\series default +, +\begin_inset Formula +\[ +\frac{\partial T^{-1}}{\partial\xi}=\Ad T=-\left[\begin{array}{cc} +R & 0\\ +\Skew tR & R +\end{array}\right] +\] + +\end_inset + + +\series bold +compose +\series default + in its first argument, +\begin_inset Formula +\[ +\frac{\partial\left(T_{1}T_{2}\right)}{\partial\xi_{1}}=\Ad{T_{2}^{-1}} +\] + +\end_inset + + in its second argument, +\begin_inset Formula +\[ +\frac{\partial\left(T_{1}T_{2}\right)}{\partial\xi_{2}}=I_{6} +\] + +\end_inset + + +\series bold +between +\series default + in its first argument, +\begin_inset Formula +\[ +\frac{\partial\left(T_{1}^{^{-1}}T_{2}\right)}{\partial\xi_{1}}=\Ad{T_{2}^{^{-1}}T_{1}} +\] + +\end_inset + +and in its second argument, +\begin_inset Formula +\begin{eqnarray*} +\frac{\partial\left(T_{1}^{^{-1}}T_{2}\right)}{\partial\xi_{1}} & = & I_{6} +\end{eqnarray*} + +\end_inset + + +\end_layout + +\begin_layout Subsection +Retractions +\end_layout + +\begin_layout Standard +For +\begin_inset Formula $\SEthree$ +\end_inset + +, instead of using the true exponential map it is computationally more efficient + to design other retractions. + A first-order approximation to the exponential map does not quite cut it, + as it yields a +\begin_inset Formula $4\times4$ +\end_inset + + matrix which is not in +\begin_inset Formula $\SEthree$ +\end_inset + +: +\begin_inset Formula +\begin{eqnarray*} +T\exp\xihat & \approx & T(I+\xihat)\\ + & = & T\left(I_{4}+\left[\begin{array}{cc} +\Skew{\omega} & v\\ +0 & 0 +\end{array}\right]\right)\\ + & = & \left[\begin{array}{cc} +R & t\\ +0 & 1 +\end{array}\right]\left[\begin{array}{cc} +I_{3}+\Skew{\omega} & v\\ +0 & 1 +\end{array}\right]\\ + & = & \left[\begin{array}{cc} +R\left(I_{3}+\Skew{\omega}\right) & t+Rv\\ +0 & 1 +\end{array}\right] +\end{eqnarray*} + +\end_inset + +However, we can make it into a retraction by using any retraction defined + for +\begin_inset Formula $\SOthree$ +\end_inset + +, including, as below, using the exponential map +\begin_inset Formula $Re^{\Skew{\omega}}$ +\end_inset + +: +\begin_inset Formula +\[ +\retract_{T}\left(\left[\begin{array}{c} +\omega\\ +v +\end{array}\right]\right)=\left[\begin{array}{cc} +R & t\\ +0 & 1 +\end{array}\right]\left[\begin{array}{cc} +e^{\Skew{\omega}} & v\\ +0 & 1 +\end{array}\right]=\left[\begin{array}{cc} +Re^{\Skew{\omega}} & t+Rv\\ +0 & 1 +\end{array}\right] +\] + +\end_inset + +Similarly, for a second order approximation we have +\begin_inset Formula +\begin{eqnarray*} +T\exp\xihat & \approx & T(I+\xihat+\frac{\xihat^{2}}{2})\\ + & = & T\left(I_{4}+\left[\begin{array}{cc} +\Skew{\omega} & v\\ +0 & 0 +\end{array}\right]+\frac{1}{2}\left[\begin{array}{cc} +\Skew{\omega} & v\\ +0 & 0 +\end{array}\right]\left[\begin{array}{cc} +\Skew{\omega} & v\\ +0 & 0 +\end{array}\right]\right)\\ + & = & \left[\begin{array}{cc} +R & t\\ +0 & 1 +\end{array}\right]\left(\left[\begin{array}{cc} +I_{3}+\Skew{\omega}+\frac{1}{2}\Skew{\omega}^{2} & v+\frac{1}{2}\Skew{\omega}v\\ +0 & 1 +\end{array}\right]\right)\\ + & = & \left[\begin{array}{cc} +R\left(I_{3}+\Skew{\omega}+\frac{1}{2}\Skew{\omega}^{2}\right) & t+R\left[v+\left(\omega\times v\right)/2\right]\\ +0 & 1 +\end{array}\right] +\end{eqnarray*} + +\end_inset + +inspiring the retraction +\begin_inset Formula +\[ +\retract_{T}\left(\left[\begin{array}{c} +\omega\\ +v +\end{array}\right]\right)=\left[\begin{array}{cc} +R & t\\ +0 & 1 +\end{array}\right]\left[\begin{array}{cc} +e^{\Skew{\omega}} & v+\left(\omega\times v\right)/2\\ +0 & 1 +\end{array}\right]=\left[\begin{array}{cc} +Re^{\Skew{\omega}} & t+R\left[v+\left(\omega\times v\right)/2\right]\\ +0 & 1 +\end{array}\right] +\] + +\end_inset + + +\end_layout + +\begin_layout Standard +\begin_inset Newpage pagebreak +\end_inset + + +\end_layout + +\begin_layout Section +2D Line Segments (Ocaml) +\end_layout + +\begin_layout Standard +The error between an infinite line +\begin_inset Formula $(a,b,c)$ +\end_inset + + and a 2D line segment +\begin_inset Formula $((x1,y1),(x2,y2))$ +\end_inset + + is defined in Line3.ml. +\end_layout + +\begin_layout Section +Line3vd (Ocaml) +\end_layout + +\begin_layout Standard +One representation of a line is through 2 vectors +\begin_inset Formula $(v,d)$ +\end_inset + +, where +\begin_inset Formula $v$ +\end_inset + + is the direction and the vector +\begin_inset Formula $d$ +\end_inset + + points from the orgin to the closest point on the line. +\end_layout + +\begin_layout Standard +In this representation, transforming a 3D line from a world coordinate frame + to a camera at +\begin_inset Formula $(R_{w}^{c},t^{w})$ +\end_inset + + is done by +\begin_inset Formula +\[ +v^{c}=R_{w}^{c}v^{w} +\] + +\end_inset + + +\begin_inset Formula +\[ +d^{c}=R_{w}^{c}\left(d^{w}+(t^{w}v^{w})v^{w}-t^{w}\right) +\] + +\end_inset + + +\end_layout + +\begin_layout Section +Line3 (Ocaml) +\end_layout + +\begin_layout Standard +For 3D lines, we use a parameterization due to C.J. + Taylor, using a rotation matrix +\begin_inset Formula $R$ +\end_inset + + and 2 scalars +\begin_inset Formula $a$ +\end_inset + + and +\begin_inset Formula $b$ +\end_inset + +. + The line direction +\begin_inset Formula $v$ +\end_inset + + is simply the Z-axis of the rotated frame, i.e., +\begin_inset Formula $v=R_{3}$ +\end_inset + +, while the vector +\begin_inset Formula $d$ +\end_inset + + is given by +\begin_inset Formula $d=aR_{1}+bR_{2}$ +\end_inset + +. +\end_layout + +\begin_layout Standard +Now, we will +\emph on +not +\emph default + use the incremental rotation scheme we used for rotations: because the + matrix R translates from the line coordinate frame to the world frame, + we need to apply the incremental rotation on the right-side: +\begin_inset Formula +\[ +R'=R(I+\Omega) +\] + +\end_inset + +Projecting a line to 2D can be done easily, as both +\begin_inset Formula $v$ +\end_inset + + and +\begin_inset Formula $d$ +\end_inset + + are also the 2D homogenous coordinates of two points on the projected line, + and hence we have +\begin_inset Formula +\begin{eqnarray*} +l & = & v\times d\\ + & = & R_{3}\times\left(aR_{1}+bR_{2}\right)\\ + & = & a\left(R_{3}\times R_{1}\right)+b\left(R_{3}\times R_{2}\right)\\ + & = & aR_{2}-bR_{1} +\end{eqnarray*} + +\end_inset + +This can be written as a rotation of a point, +\begin_inset Formula +\[ +l=R\left(\begin{array}{c} +-b\\ +a\\ +0 +\end{array}\right) +\] + +\end_inset + +but because the incremental rotation is now done on the right, we need to + figure out the derivatives again: +\begin_inset Formula +\begin{equation} +\frac{\partial(R(I+\Omega)x)}{\partial\omega}=\frac{\partial(R\Omega x)}{\partial\omega}=R\frac{\partial(\Omega x)}{\partial\omega}=R\Skew{-x}\label{eq:rotateRight} +\end{equation} + +\end_inset + +and hence the derivative of the projection +\begin_inset Formula $l$ +\end_inset + + with respect to the rotation matrix +\begin_inset Formula $R$ +\end_inset + +of the 3D line is +\begin_inset Formula +\begin{equation} +\frac{\partial(l)}{\partial\omega}=R\Skew{\left(\begin{array}{c} +b\\ +-a\\ +0 +\end{array}\right)}=\left[\begin{array}{ccc} +aR_{3} & bR_{3} & -(aR_{1}+bR_{2})\end{array}\right] +\end{equation} + +\end_inset + +or the +\begin_inset Formula $a,b$ +\end_inset + + scalars: +\begin_inset Formula +\[ +\frac{\partial(l)}{\partial a}=R_{2} +\] + +\end_inset + + +\begin_inset Formula +\[ +\frac{\partial(l)}{\partial b}=-R_{1} +\] + +\end_inset + + +\end_layout + +\begin_layout Standard +Transforming a 3D line +\begin_inset Formula $(R,(a,b))$ +\end_inset + + from a world coordinate frame to a camera frame +\begin_inset Formula $(R_{w}^{c},t^{w})$ +\end_inset + + is done by +\end_layout + +\begin_layout Standard +\begin_inset Formula +\[ +R'=R_{w}^{c}R +\] + +\end_inset + + +\begin_inset Formula +\[ +a'=a-R_{1}^{T}t^{w} +\] + +\end_inset + + +\begin_inset Formula +\[ +b'=b-R_{2}^{T}t^{w} +\] + +\end_inset + +Again, we need to redo the derivatives, as R is incremented from the right. + The first argument is incremented from the left, but the result is incremented + on the right: +\begin_inset Formula +\begin{eqnarray*} +R'(I+\Omega')=(AB)(I+\Omega') & = & (I+\Skew{S\omega})AB\\ +I+\Omega' & = & (AB)^{T}(I+\Skew{S\omega})(AB)\\ +\Omega' & = & R'^{T}\Skew{S\omega}R'\\ +\Omega' & = & \Skew{R'^{T}S\omega}\\ +\omega' & = & R'^{T}S\omega +\end{eqnarray*} + +\end_inset + +For the second argument +\begin_inset Formula $R$ +\end_inset + + we now simply have: +\begin_inset Formula +\begin{eqnarray*} +AB(I+\Omega') & = & AB(I+\Omega)\\ +\Omega' & = & \Omega\\ +\omega' & = & \omega +\end{eqnarray*} + +\end_inset + +The scalar derivatives can be found by realizing that +\begin_inset Formula +\[ +\left(\begin{array}{c} +a'\\ +b'\\ +... +\end{array}\right)=\left(\begin{array}{c} +a\\ +b\\ +0 +\end{array}\right)-R^{T}t^{w} +\] + +\end_inset + +where we don't care about the third row. + Hence +\begin_inset Formula +\[ +\frac{\partial(\left(R(I+\Omega_{2})\right)^{T}t^{w})}{\partial\omega}=-\frac{\partial(\Omega_{2}R^{T}t^{w})}{\partial\omega}=-\Skew{R^{T}t^{w}}=\left[\begin{array}{ccc} +0 & R_{3}^{T}t^{w} & -R_{2}^{T}t^{w}\\ +-R_{3}^{T}t^{w} & 0 & R_{1}^{T}t^{w}\\ +... & ... & 0 +\end{array}\right] +\] + +\end_inset + + +\end_layout + +\begin_layout Section + +\series bold +Aligning 3D Scans +\end_layout + +\begin_layout Standard +Below is the explanaition underlying Pose3.align, i.e. + aligning two point clouds using SVD. + Inspired but modified from CVOnline... +\end_layout + +\begin_layout Standard + +\emph on +Our +\emph default + model is +\begin_inset Formula +\[ +p^{c}=R\left(p^{w}-t\right) +\] + +\end_inset + +i.e., +\begin_inset Formula $R$ +\end_inset + + is from camera to world, and +\begin_inset Formula $t$ +\end_inset + + is the camera location in world coordinates. + The objective function is +\begin_inset Formula +\begin{equation} +\frac{1}{2}\sum\left(p^{c}-R(p^{w}-t)\right)^{2}=\frac{1}{2}\sum\left(p^{c}-Rp^{w}+Rt\right)^{2}=\frac{1}{2}\sum\left(p^{c}-Rp^{w}-t'\right)^{2}\label{eq:J} +\end{equation} + +\end_inset + +where +\begin_inset Formula $t'=-Rt$ +\end_inset + + is the location of the origin in the camera frame. + Taking the derivative with respect to +\begin_inset Formula $t'$ +\end_inset + + and setting to zero we have +\begin_inset Formula +\[ +\sum\left(p^{c}-Rp^{w}-t'\right)=0 +\] + +\end_inset + +or +\begin_inset Formula +\begin{equation} +t'=\frac{1}{n}\sum\left(p^{c}-Rp^{w}\right)=\bar{p}^{c}-R\bar{p}^{w}\label{eq:t} +\end{equation} + +\end_inset + +here +\begin_inset Formula $\bar{p}^{c}$ +\end_inset + + and +\begin_inset Formula $\bar{p}^{w}$ +\end_inset + + are the point cloud centroids. + Substituting back into +\begin_inset CommandInset ref +LatexCommand eqref +reference "eq:J" + +\end_inset + +, we get +\begin_inset Formula +\[ +\frac{1}{2}\sum\left(p^{c}-R(p^{w}-t)\right)^{2}=\frac{1}{2}\sum\left(\left(p^{c}-\bar{p}^{c}\right)-R\left(p^{w}-\bar{p}^{w}\right)\right)^{2}=\frac{1}{2}\sum\left(\hat{p}^{c}-R\hat{p}^{w}\right)^{2} +\] + +\end_inset + +Now, to minimize the above it suffices to maximize (see CVOnline) +\begin_inset Formula +\[ +\mathop{trace}\left(R^{T}C\right) +\] + +\end_inset + +where +\begin_inset Formula $C=\sum\hat{p}^{c}\left(\hat{p}^{w}\right)^{T}$ +\end_inset + + is the correlation matrix. + Intuitively, the cloud of points is rotated to align with the principal + axes. + This can be achieved by SVD decomposition on +\begin_inset Formula $C$ +\end_inset + + +\begin_inset Formula +\[ +C=USV^{T} +\] + +\end_inset + +and setting +\begin_inset Formula +\[ +R=UV^{T} +\] + +\end_inset + +Clearly, from +\begin_inset CommandInset ref +LatexCommand eqref +reference "eq:t" + +\end_inset + + we then also recover the optimal +\begin_inset Formula $t$ +\end_inset + + as +\begin_inset Formula +\[ +t=\bar{p}^{w}-R^{T}\bar{p}^{c} +\] + +\end_inset + + +\end_layout + +\begin_layout Section* +Appendix +\end_layout + +\begin_layout Subsection* +Differentiation Rules +\end_layout + +\begin_layout Standard +Spivak +\begin_inset CommandInset citation +LatexCommand cite +key "Spivak65book" + +\end_inset + + also notes some multivariate derivative rules defined component-wise, but + they are not that useful in practice: +\end_layout + +\begin_layout Itemize +Since +\begin_inset Formula $f:\Multi nm$ +\end_inset + + is defined in terms of +\begin_inset Formula $m$ +\end_inset + + component functions +\begin_inset Formula $f^{i}$ +\end_inset + +, then +\begin_inset Formula $f$ +\end_inset + + is differentiable at +\begin_inset Formula $a$ +\end_inset + + iff each +\begin_inset Formula $f^{i}$ +\end_inset + + is, and the Jacobian matrix +\begin_inset Formula $F_{a}$ +\end_inset + + is the +\begin_inset Formula $m\times n$ +\end_inset + + matrix whose +\begin_inset Formula $i^{th}$ +\end_inset + + row is +\begin_inset Formula $\left(f^{i}\right)'(a)$ +\end_inset + +: +\begin_inset Formula +\[ +F_{a}\define f'(a)=\left[\begin{array}{c} +\left(f^{1}\right)'(a)\\ +\vdots\\ +\left(f^{m}\right)'(a) +\end{array}\right] +\] + +\end_inset + + +\end_layout + +\begin_layout Itemize +Scalar differentiation rules: if +\begin_inset Formula $f,g:\OneD n$ +\end_inset + + are differentiable at +\begin_inset Formula $a$ +\end_inset + +, then +\begin_inset Formula +\[ +(f+g)'(a)=F_{a}+G_{a} +\] + +\end_inset + + +\begin_inset Formula +\[ +(f\cdot g)'(a)=g(a)F_{a}+f(a)G_{a} +\] + +\end_inset + + +\begin_inset Formula +\[ +(f/g)'(a)=\frac{1}{g(a)^{2}}\left[g(a)F_{a}-f(a)G_{a}\right] +\] + +\end_inset + + +\end_layout + +\begin_layout Subsection* +Tangent Spaces and the Tangent Bundle +\end_layout + +\begin_layout Standard +The following is adapted from Appendix A in +\begin_inset CommandInset citation +LatexCommand cite +key "Murray94book" + +\end_inset + +. +\end_layout + +\begin_layout Standard +The +\series bold +tangent space +\series default + +\begin_inset Formula $T_{p}M$ +\end_inset + + of a manifold +\begin_inset Formula $M$ +\end_inset + + at a point +\begin_inset Formula $p\in M$ +\end_inset + + is the vector space of +\series bold +tangent vectors +\series default + at +\begin_inset Formula $p$ +\end_inset + +. + The +\series bold +tangent bundle +\series default + +\begin_inset Formula $TM$ +\end_inset + + is the set of all tangent vectors +\begin_inset Formula +\[ +TM\define\bigcup_{p\in M}T_{p}M +\] + +\end_inset + +A +\series bold +vector field +\series default + +\begin_inset Formula $X:M\rightarrow TM$ +\end_inset + + assigns a single tangent vector +\begin_inset Formula $x\in T_{p}M$ +\end_inset + + to each point +\begin_inset Formula $p$ +\end_inset + +. +\end_layout + +\begin_layout Standard +If +\begin_inset Formula $F:M\rightarrow N$ +\end_inset + + is a smooth map from a manifold +\begin_inset Formula $M$ +\end_inset + + to a manifold +\begin_inset Formula $N$ +\end_inset + +, then we can define the +\series bold + tangent map +\series default + of +\begin_inset Formula $F$ +\end_inset + + at +\begin_inset Formula $p$ +\end_inset + + as the linear map +\begin_inset Formula $F_{*p}:T_{p}M\rightarrow T_{F(p)}N$ +\end_inset + + that maps tangent vectors in +\begin_inset Formula $T_{p}M$ +\end_inset + + at +\begin_inset Formula $p$ +\end_inset + + to tangent vectors in +\begin_inset Formula $T_{F(p)}N$ +\end_inset + + at the image +\begin_inset Formula $F(p)$ +\end_inset + +. +\end_layout + +\begin_layout Subsection* +Homomorphisms +\end_layout + +\begin_layout Standard +The following +\emph on +might be +\emph default + relevant +\begin_inset CommandInset citation +LatexCommand cite +after "page 45" +key "Hall00book" + +\end_inset + +: suppose that +\begin_inset Formula $\Phi:G\rightarrow H$ +\end_inset + + is a mapping (Lie group homomorphism). + Then there exists a unique linear map +\begin_inset Formula $\phi:\gg\rightarrow\mathfrak{h}$ +\end_inset + + +\begin_inset Formula +\[ +\phi(\xhat)\define\lim_{t\rightarrow0}\frac{d}{dt}\Phi\left(e^{t\xhat}\right) +\] + +\end_inset + +such that +\end_layout + +\begin_layout Enumerate +\begin_inset Formula $\Phi\left(e^{\xhat}\right)=e^{\phi\left(\xhat\right)}$ +\end_inset + + +\end_layout + +\begin_layout Enumerate +\begin_inset Formula $\phi\left(T\xhat T^{-1}\right)=\Phi(T)\phi(\xhat)\Phi(T^{-1})$ +\end_inset + + +\end_layout + +\begin_layout Enumerate +\begin_inset Formula $\phi\left([\xhat,\yhat]\right)=\left[\phi(\xhat),\phi(\yhat)\right]$ +\end_inset + + +\end_layout + +\begin_layout Standard +In other words, the map +\begin_inset Formula $\phi$ +\end_inset + + is the derivative of +\begin_inset Formula $\Phi$ +\end_inset + + at the identity. + As an example, suppose +\begin_inset Formula $\Phi(g)=g^{-1}$ +\end_inset + +, then the corresponding derivative +\emph on +at the identity +\emph default +is +\begin_inset Formula +\[ +\phi(\xhat)\define\lim_{t\rightarrow0}\frac{d}{dt}\left(e^{t\xhat}\right)^{-1}=\lim_{t\rightarrow0}\frac{d}{dt}e^{-t\xhat}=-\xhat\lim_{t\rightarrow0}e^{-t\xhat}=-\xhat +\] + +\end_inset + +In general it suffices to compute +\begin_inset Formula $\phi$ +\end_inset + + for a basis of +\begin_inset Formula $\gg$ +\end_inset + +. +\end_layout + +\begin_layout Standard +\begin_inset Note Note +status collapsed + +\begin_layout Plain Layout +Undercooked: What if we want the derivative of +\begin_inset Formula $\Phi$ +\end_inset + + at some other element +\begin_inset Formula $g$ +\end_inset + +? In other words, if we apply +\begin_inset Formula $\Phi$ +\end_inset + + at +\begin_inset Formula $g$ +\end_inset + + incremented by some Lie algebra element +\begin_inset Formula $e^{\xhat}$ +\end_inset + +, then we are looking for a +\begin_inset Formula $\yhat\in\gg$ +\end_inset + + will yield the same result: +\begin_inset Formula +\[ +\Phi\left(g\right)\lim_{t\rightarrow0}\frac{d}{dt}e^{t\yhat}=\lim_{t\rightarrow0}\frac{d}{dt}\Phi\left(ge^{t\xhat}\right) +\] + +\end_inset + + +\begin_inset Formula +\[ +\lim_{t\rightarrow0}\frac{d}{dt}e^{t\yhat}=\Phi\left(g\right)^{-1}\lim_{t\rightarrow0}\frac{d}{dt}\Phi\left(ge^{t\xhat}\right) +\] + +\end_inset + + +\end_layout + +\end_inset + + +\end_layout + +\begin_layout Standard +\begin_inset Note Note +status collapsed + +\begin_layout Plain Layout +Let us define two mappings +\begin_inset Formula +\[ +\Phi_{1}(A)=AB\mbox{ and }\Phi_{2}(B)=AB +\] + +\end_inset + +Then +\begin_inset Formula +\[ +\phi_{1}(\xhat)=\lim_{t\rightarrow0}\frac{d}{dt}\Phi_{1}\left(e^{t\xhat}B\right)= +\] + +\end_inset + + +\end_layout + +\end_inset + + +\end_layout + +\begin_layout Standard +\begin_inset CommandInset bibtex +LatexCommand bibtex +bibfiles "/Users/dellaert/papers/refs" +options "plain" + +\end_inset + + +\end_layout + +\end_body +\end_document diff --git a/doc/math.pdf b/doc/math.pdf new file mode 100644 index 000000000..ee50857ce Binary files /dev/null and b/doc/math.pdf differ diff --git a/examples/CMakeLists.txt b/examples/CMakeLists.txt index 55f2db60b..9f799d294 100644 --- a/examples/CMakeLists.txt +++ b/examples/CMakeLists.txt @@ -1,4 +1,6 @@ -add_custom_target(examples) +if(NOT MSVC) + add_custom_target(examples) +endif() # Build example executables FILE(GLOB example_srcs "*.cpp") @@ -6,10 +8,25 @@ foreach(example_src ${example_srcs} ) get_filename_component(example_base ${example_src} NAME_WE) set( example_bin ${example_base} ) message(STATUS "Adding Example ${example_bin}") - add_dependencies(examples ${example_bin}) + if(NOT MSVC) + add_dependencies(examples ${example_bin}) + endif() add_executable(${example_bin} ${example_src}) + + # Disable building during make all/install + if (GTSAM_DISABLE_EXAMPLES_ON_INSTALL) + set_target_properties(${example_bin} PROPERTIES EXCLUDE_FROM_ALL ON) + endif() + target_link_libraries(${example_bin} gtsam-static) - add_custom_target(${example_bin}.run ${EXECUTABLE_OUTPUT_PATH}${example_bin} ${ARGN}) + if(NOT MSVC) + add_custom_target(${example_bin}.run ${EXECUTABLE_OUTPUT_PATH}${example_bin} ${ARGN}) + endif() + + # Set up Visual Studio folder + if(MSVC) + set_property(TARGET ${example_bin} PROPERTY FOLDER "Examples") + endif() + endforeach(example_src) -add_subdirectory(vSLAMexample) diff --git a/examples/CameraResectioning.cpp b/examples/CameraResectioning.cpp index 7d0e37e7f..4133d1e1e 100644 --- a/examples/CameraResectioning.cpp +++ b/examples/CameraResectioning.cpp @@ -17,86 +17,82 @@ */ #include -#include -#include -#include -#include -#include #include +#include +#include using namespace gtsam; +using namespace gtsam::noiseModel; +using symbol_shorthand::X; /** - * Unary factor for the pose. + * Unary factor on the unknown pose, resulting from meauring the projection of + * a known 3D point in the image */ class ResectioningFactor: public NoiseModelFactor1 { - typedef NoiseModelFactor1 Base; + typedef NoiseModelFactor1 Base; - shared_ptrK K_; // camera's intrinsic parameters - Point3 P_; // 3D point on the calibration rig - Point2 p_; // 2D measurement of the 3D point + shared_ptrK K_; // camera's intrinsic parameters + Point3 P_; // 3D point on the calibration rig + Point2 p_; // 2D measurement of the 3D point public: - ResectioningFactor(const SharedNoiseModel& model, const Symbol& key, - const shared_ptrK& calib, const Point2& p, const Point3& P) : - Base(model, key), K_(calib), P_(P), p_(p) { - } - virtual ~ResectioningFactor() {} + /// Construct factor given known point P and its projection p + ResectioningFactor(const SharedNoiseModel& model, const Key& key, + const shared_ptrK& calib, const Point2& p, const Point3& P) : + Base(model, key), K_(calib), P_(P), p_(p) { + } - virtual Vector evaluateError(const Pose3& X, boost::optional H = boost::none) const { - SimpleCamera camera(*K_, X); - Point2 reprojectionError(camera.project(P_, H) - p_); - return reprojectionError.vector(); - } + /// evaluate the error + virtual Vector evaluateError(const Pose3& pose, boost::optional H = + boost::none) const { + SimpleCamera camera(pose, *K_); + Point2 reprojectionError(camera.project(P_, H) - p_); + return reprojectionError.vector(); + } }; -/*******************************************************************************/ -/** - * Camera: f = 1.0, Image: 100x100, center: 50.0, 50.0 +/******************************************************************************* + * Camera: f = 1, Image: 100x100, center: 50, 50.0 * Pose (ground truth): (Xw, -Yw, -Zw, [0,0,2.0]') * Known landmarks: * 3D Points: (10,10,0) (-10,10,0) (-10,-10,0) (10,-10,0) * Perfect measurements: * 2D Point: (55,45) (45,45) (45,55) (55,55) - */ + *******************************************************************************/ int main(int argc, char* argv[]) { - /* read camera intrinsic parameters */ - shared_ptrK calib(new Cal3_S2(1.0, 1.0, 0, 50.0, 50.0)); + /* read camera intrinsic parameters */ + shared_ptrK calib(new Cal3_S2(1, 1, 0, 50, 50)); - /* create keys for variables */ - // we have only 1 variable to solve: the camera pose - Symbol X('x',1); + /* 1. create graph */ + NonlinearFactorGraph graph; - /* 1. create graph */ - NonlinearFactorGraph graph; + /* 2. add factors to the graph */ + // add measurement factors + SharedDiagonal measurementNoise = Diagonal::Sigmas(Vector_(2, 0.5, 0.5)); + boost::shared_ptr factor; + graph.push_back( + boost::make_shared(measurementNoise, X(1), calib, + Point2(55, 45), Point3(10, 10, 0))); + graph.push_back( + boost::make_shared(measurementNoise, X(1), calib, + Point2(45, 45), Point3(-10, 10, 0))); + graph.push_back( + boost::make_shared(measurementNoise, X(1), calib, + Point2(45, 55), Point3(-10, -10, 0))); + graph.push_back( + boost::make_shared(measurementNoise, X(1), calib, + Point2(55, 55), Point3(10, -10, 0))); - /* 2. add factors to the graph */ - // add measurement factors - SharedDiagonal measurementNoise = sharedSigmas(Vector_(2, 0.5, 0.5)); - boost::shared_ptr factor; - factor = boost::shared_ptr(new ResectioningFactor( - measurementNoise, X, calib, Point2(55.0, 45.0), Point3(10.0, 10.0, 0.0))); - graph.push_back(factor); - factor = boost::shared_ptr(new ResectioningFactor( - measurementNoise, X, calib, Point2(45.0, 45.0), Point3(-10.0, 10.0, 0.0))); - graph.push_back(factor); - factor = boost::shared_ptr(new ResectioningFactor( - measurementNoise, X, calib, Point2(45.0, 55.0), Point3(-10.0, -10.0, 0.0))); - graph.push_back(factor); - factor = boost::shared_ptr(new ResectioningFactor( - measurementNoise, X, calib, Point2(55.0, 55.0), Point3(10.0, -10.0, 0.0))); - graph.push_back(factor); + /* 3. Create an initial estimate for the camera pose */ + Values initial; + initial.insert(X(1), + Pose3(Rot3(1, 0, 0, 0, -1, 0, 0, 0, -1), Point3(0, 0, 2))); - /* 3. Create an initial estimate for the camera pose */ - Values initial; - initial.insert(X, Pose3(Rot3(1.,0.,0., - 0.,-1.,0., - 0.,0.,-1.), Point3(0.,0.,2.0))); + /* 4. Optimize the graph using Levenberg-Marquardt*/ + Values result = LevenbergMarquardtOptimizer(graph, initial).optimize(); + result.print("Final result:\n"); - /* 4. Optimize the graph using Levenberg-Marquardt*/ - Values result = LevenbergMarquardtOptimizer(graph, initial).optimize(); - result.print("Final result: "); - - return 0; + return 0; } diff --git a/examples/Data/Balbianello/BalbianelloMedium-1.jpg b/examples/Data/Balbianello/BalbianelloMedium-1.jpg new file mode 100644 index 000000000..0e75c8725 Binary files /dev/null and b/examples/Data/Balbianello/BalbianelloMedium-1.jpg differ diff --git a/examples/Data/Balbianello/BalbianelloMedium-1.key.gz b/examples/Data/Balbianello/BalbianelloMedium-1.key.gz new file mode 100644 index 000000000..fdbdc4188 Binary files /dev/null and b/examples/Data/Balbianello/BalbianelloMedium-1.key.gz differ diff --git a/examples/Data/Balbianello/BalbianelloMedium-2.jpg b/examples/Data/Balbianello/BalbianelloMedium-2.jpg new file mode 100644 index 000000000..5e51ee16e Binary files /dev/null and b/examples/Data/Balbianello/BalbianelloMedium-2.jpg differ diff --git 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differ diff --git a/examples/Data/Balbianello/BalbianelloMedium-4.key.gz b/examples/Data/Balbianello/BalbianelloMedium-4.key.gz new file mode 100644 index 000000000..efc9cf008 Binary files /dev/null and b/examples/Data/Balbianello/BalbianelloMedium-4.key.gz differ diff --git a/examples/Data/Balbianello/BalbianelloMedium-5.jpg b/examples/Data/Balbianello/BalbianelloMedium-5.jpg new file mode 100644 index 000000000..4f4dd16c8 Binary files /dev/null and b/examples/Data/Balbianello/BalbianelloMedium-5.jpg differ diff --git a/examples/Data/Balbianello/BalbianelloMedium-5.key.gz b/examples/Data/Balbianello/BalbianelloMedium-5.key.gz new file mode 100644 index 000000000..f299c5cb4 Binary files /dev/null and b/examples/Data/Balbianello/BalbianelloMedium-5.key.gz differ diff --git a/examples/Data/VO_calibration.txt b/examples/Data/VO_calibration.txt new file mode 100644 index 000000000..138eb3646 --- /dev/null +++ b/examples/Data/VO_calibration.txt @@ -0,0 +1 @@ +721.5377 721.5377 0.0 609.5593 172.854 0.537150588 \ No newline at end of file diff --git a/examples/Data/VO_camera_poses_large.txt b/examples/Data/VO_camera_poses_large.txt new file mode 100644 index 000000000..879d091b6 --- /dev/null +++ b/examples/Data/VO_camera_poses_large.txt @@ -0,0 +1,26 @@ +1 1 0 0 0 0 1 0 0 -0 0 1 0 0 0 0 1 +2 0.999997 -0.00240146 0.00061075 0.00314304 0.0024019 0.999997 -0.00071977 0.00414596 -0.00060902 0.000721235 1 0.95998 0 0 0 1 +3 0.999993 -0.00371801 0.000595621 0.00280572 0.00371612 0.999988 0.00314729 0.00981461 -0.000607315 -0.00314506 0.999995 1.91967 0 0 0 1 +4 0.999981 -0.00619252 -0.000161076 0.00419847 0.00619374 0.999939 0.00918605 0.0120306 0.000104181 -0.00918687 0.999958 2.87292 0 0 0 1 +5 0.999948 -0.0100179 -0.00177824 0.00741887 0.010034 0.999907 0.00925915 0.0175144 0.00168532 -0.00927651 0.999956 3.8158 0 0 0 1 +6 0.999913 -0.0128105 -0.00298253 0.00649213 0.0128298 0.999896 0.00655406 0.0221085 0.00289826 -0.00659176 0.999974 4.75923 0 0 0 1 +7 0.999901 -0.0135442 -0.00393541 0.00202365 0.0135567 0.999903 0.00315259 0.0274932 0.00389233 -0.00320563 0.999987 5.69454 0 0 0 1 +8 0.999901 -0.0131232 -0.00504356 -0.00337588 0.0131365 0.99991 0.00261558 0.0312754 0.00500879 -0.00268157 0.999984 6.62905 0 0 0 1 +9 0.999898 -0.0127525 -0.00649016 -0.00834529 0.0127815 0.999908 0.00443934 0.0363095 0.00643296 -0.00452184 0.999969 7.56509 0 0 0 1 +10 0.999891 -0.0126057 -0.0076649 -0.0140367 0.012663 0.999892 0.00747804 0.0406566 0.00756981 -0.00757428 0.999943 8.50119 0 0 0 1 +11 0.99988 -0.012916 -0.00853732 -0.0314704 0.0129905 0.999878 0.00872879 0.0502508 0.00842353 -0.00883865 0.999925 9.44031 0 0 0 1 +12 0.999851 -0.0144077 -0.00947329 -0.0383227 0.0144958 0.999852 0.00930193 0.0627772 0.00933787 -0.00943787 0.999912 10.3736 0 0 0 1 +13 0.999838 -0.0146038 -0.0105024 -0.0473225 0.0147016 0.999849 0.00930217 0.0696137 0.010365 -0.00945507 0.999902 11.2945 0 0 0 1 +14 0.999827 -0.0148804 -0.0111878 -0.0611688 0.0149688 0.999857 0.00785918 0.0760175 0.0110692 -0.00802528 0.999907 12.2087 0 0 0 1 +15 0.999804 -0.015194 -0.0126986 -0.0750261 0.0152691 0.999866 0.0058357 0.0827557 0.0126082 -0.00602846 0.999902 13.1154 0 0 0 1 +16 0.999759 -0.0166787 -0.0142956 -0.0893963 0.0167446 0.99985 0.00450347 0.0886196 0.0142183 -0.00474176 0.999888 14.0218 0 0 0 1 +17 0.999738 -0.0164046 -0.0159548 -0.110797 0.0164665 0.999857 0.00375294 0.0939735 0.0158909 -0.00401468 0.999866 14.9288 0 0 0 1 +18 0.999731 -0.0152362 -0.0175058 -0.134602 0.0152899 0.999879 0.00293826 0.0949048 0.0174589 -0.00320513 0.999842 15.8347 0 0 0 1 +19 0.999721 -0.013717 -0.0192196 -0.158411 0.0137759 0.999901 0.00293494 0.0977547 0.0191774 -0.00319889 0.999811 16.7344 0 0 0 1 +20 0.999683 -0.0142193 -0.0207555 -0.182009 0.0142987 0.999891 0.00368405 0.101695 0.0207008 -0.00397966 0.999778 17.6352 0 0 0 1 +21 0.999659 -0.0137778 -0.0221853 -0.207494 0.01389 0.999891 0.00491306 0.105966 0.0221152 -0.00521954 0.999742 18.5239 0 0 0 1 +22 0.999637 -0.013439 -0.0233607 -0.237562 0.0135682 0.999893 0.0053802 0.112022 0.023286 -0.00569521 0.999713 19.408 0 0 0 1 +23 0.999585 -0.0146657 -0.0247774 -0.266515 0.0147976 0.999877 0.00515018 0.116865 0.0246988 -0.00551469 0.99968 20.2912 0 0 0 1 +24 0.999541 -0.0147341 -0.0264658 -0.293414 0.0148605 0.999879 0.00458559 0.12245 0.0263951 -0.00497678 0.999639 21.1689 0 0 0 1 +25 0.999508 -0.0146117 -0.0277547 -0.320586 0.0147561 0.999879 0.00500356 0.126076 0.0276782 -0.00541065 0.999602 22.0409 0 0 0 1 +26 0.999474 -0.0145772 -0.0289811 -0.347714 0.0147851 0.999866 0.00697181 0.131533 0.0288756 -0.00739663 0.999556 22.9037 0 0 0 1 diff --git a/examples/Data/VO_stereo_factors_large.txt b/examples/Data/VO_stereo_factors_large.txt new file mode 100644 index 000000000..a2451cf75 --- /dev/null +++ b/examples/Data/VO_stereo_factors_large.txt @@ -0,0 +1,8189 @@ +1 3 209.979 185.87 61.5418 -8.90263 -2.48003 16.0758 +2 3 183.871 158.526 58.5288 -9.02175 -2.42293 15.2918 +3 3 154.533 127.498 45.2523 -9.04073 -2.53526 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1109.31 1085.46 129.523 11.2524 -0.97564 16.2461 +5 1890 983.973 962.989 151.623 9.58411 -0.54346 18.4697 +6 1890 1004.51 983.166 151.523 9.93848 -0.536773 18.1566 +7 1890 1027.68 1004.62 152.642 9.74353 -0.471013 16.8143 +8 1890 1054.26 1029.21 152.323 9.53553 -0.440247 15.4716 +5 1894 1023.93 1002.39 145.984 10.3319 -0.669982 17.9908 +6 1894 1047.49 1025.2 145.294 10.5559 -0.664322 17.3922 +7 1894 1072.67 1049.91 144.754 10.9291 -0.663142 17.0276 +5 1916 179.961 128.39 306.289 -4.47461 1.38983 7.51538 +6 1916 120.666 64.0623 328.474 -4.63944 1.47678 6.84716 +5 1917 241.346 195.5 317.66 -4.31414 1.69661 8.45383 +6 1917 197.335 145.683 339.27 -4.28693 1.73065 7.50363 +7 1917 140.195 80.2428 365.806 -4.20536 1.72879 6.46476 +5 1947 629.004 588.391 293.483 0.257175 1.59546 9.54315 +6 1947 632.232 587.914 309.398 0.2748 1.65499 8.74544 +5 1950 813.808 773.088 283.537 2.69429 1.46004 9.51797 +6 1950 837.336 791.955 297.303 2.69606 1.47303 8.54042 +7 1950 866.492 815.279 315.245 2.69485 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0 25 +EDGE3 1841 1842 4.61225 -0.179533 -0.271756 -0.0149073 0.114372 -0.0772276 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1792 1842 -0.0715469 -3.11082 -0.306459 0.0653106 -0.00790786 0.037411 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1842 1843 4.76378 -0.377619 -0.214941 0.00412791 0.0865911 -0.0728148 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1793 1843 0.0518907 -2.91562 -0.122442 0.043295 0.00439581 -0.086833 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1843 1844 4.75419 -0.359341 -0.170499 -0.00531465 0.0949683 -0.118355 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1794 1844 -0.0159708 -3.12139 -0.0824815 0.0623852 -0.00142231 -0.0483063 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1844 1845 4.68768 -0.252698 -0.156315 -0.00677702 0.100201 -0.209675 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1795 1845 0.120579 -3.15235 0.146184 0.0437515 0.0034017 -0.0390961 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1845 1846 4.72071 -0.0861133 -0.295451 9.50973e-05 0.100831 -0.0547042 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1796 1846 0.123159 -3.01997 -0.253439 0.0580113 0.00828285 0.0588462 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1846 1847 4.5354 -0.407092 -0.101975 -0.00891557 0.0920906 -0.0191004 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1797 1847 0.144637 -3.16179 -0.265119 0.0764653 -0.00658368 0.0460853 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1847 1848 4.60801 -0.126293 -0.244688 -0.0052939 0.103868 -0.094666 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1798 1848 -0.12162 -2.98479 -0.154439 0.0671829 0.0324719 -0.00283929 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1848 1849 4.61804 -0.109776 0.0579462 0.00955842 0.100207 -0.0700888 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1799 1849 0.132477 -3.03471 -0.145067 0.0609105 0.01149 -0.0127041 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1849 1850 4.77603 -0.15837 -0.10548 0.000827253 0.103943 -0.0752349 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1800 1850 -0.108137 -2.87796 -0.224581 0.0708447 0.000116664 0.00372955 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1850 1851 4.63142 -0.272999 -0.128289 0.00536304 0.0791685 -0.108227 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1801 1851 0.042069 -2.80394 -0.18803 0.0621952 -0.0043172 -0.0157536 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1851 1852 4.68181 -0.0973537 -0.151376 -0.00658094 0.0990499 -0.0917664 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1802 1852 -0.0877699 -3.17664 -0.0572846 0.0479959 0.00962734 0.100438 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1852 1853 4.6503 -0.320069 -0.331807 -0.00976131 0.100877 -0.13558 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1803 1853 -0.0742592 -2.90932 0.0189127 0.0721261 -0.0165091 -0.036432 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1853 1854 4.69398 -0.193299 0.0197714 -0.0176067 0.0909729 -0.0080528 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1804 1854 -0.0383705 -3.16786 -0.0654075 0.0584352 0.0208323 -0.00536037 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1854 1855 4.6655 -0.267701 -0.190265 -0.00211648 0.0865708 -0.0278417 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1805 1855 -0.00902558 -2.92915 -0.120399 0.0591487 -0.00488917 -0.0315146 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1855 1856 4.42177 -0.256342 -0.205254 -0.016843 0.0949576 -0.0944535 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1806 1856 -0.0765701 -3.12898 -0.090606 0.0768918 0.011933 0.0750656 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1856 1857 4.71076 -0.367691 -0.227541 -0.0133918 0.113067 0.000679603 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1807 1857 0.14094 -3.05249 -0.343382 0.0792538 -0.0139568 -0.0145973 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1857 1858 4.50405 -0.294668 -0.26997 -0.0185135 0.101194 -0.0647436 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1808 1858 -0.0761782 -3.09231 -0.0246564 0.072825 -0.0149646 0.0251462 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1858 1859 4.55554 -0.148973 -0.182055 0.00290392 0.0906017 0.0354924 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1809 1859 -0.188033 -2.9272 -0.113857 0.0612109 0.00747083 0.0431749 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1859 1860 4.64651 -0.277451 -0.359388 -0.00926957 0.107963 -0.0562575 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1810 1860 -0.090876 -3.05835 -0.290709 0.0765461 0.00631462 -0.0388976 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1860 1861 4.56676 -0.36899 -0.164651 0.00580102 0.084293 -0.0688952 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1811 1861 0.0526861 -3.07877 -0.169244 0.059532 -0.00797233 -0.0827041 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1861 1862 4.50337 -0.230667 -0.177172 0.0030579 0.0919689 -0.111539 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1812 1862 0.116739 -2.98034 -0.217091 0.0702648 -0.00609367 0.0199529 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1862 1863 4.64065 -0.300941 -0.158616 -0.010913 0.0907156 -0.0926637 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1813 1863 -0.13546 -3.11522 -0.0917262 0.0692889 -0.0125472 0.0151566 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1863 1864 4.59642 -0.254075 -0.0463375 0.017004 0.0800944 -0.149026 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1814 1864 -0.0866169 -3.00286 -0.293697 0.0728429 0.00244369 0.00365238 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1864 1865 4.63337 -0.209633 -0.260197 -0.0123506 0.0894912 -0.0123663 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1815 1865 -0.169136 -3.01777 -0.0343924 0.0739501 -0.0276018 0.0202029 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1865 1866 4.42479 -0.240782 -0.264261 -0.00605098 0.102242 -0.0886238 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1816 1866 0.10855 -3.03261 -0.123647 0.0590287 0.006759 -0.0136211 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1866 1867 4.55391 -0.261659 -0.358861 -0.00253605 0.0808509 -0.0814289 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1817 1867 0.1199 -3.1384 -0.247879 0.0475286 0.00597141 0.031673 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1867 1868 4.55404 -0.030304 -0.261655 0.0110733 0.087561 -0.123222 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1818 1868 0.101038 -3.15884 -0.0424015 0.0570756 0.0125934 0.124163 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1868 1869 4.59594 -0.359304 -0.28261 -0.00562722 0.0929925 -0.0350109 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1819 1869 0.0952807 -2.85621 0.124586 0.0332439 -0.0103211 -0.00109132 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1869 1870 4.78738 -0.167502 -0.151601 0.00195706 0.0897277 -0.10005 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1820 1870 -0.0168166 -3.04721 -0.239359 0.0431807 0.0042476 -0.0155395 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1870 1871 4.56802 -0.129037 -0.20308 0.00238513 0.098059 -0.111834 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1821 1871 0.0803017 -3.02661 -0.191708 0.0635411 0.0149503 -0.0343494 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1871 1872 4.48885 -0.0342608 -0.0181551 0.0193062 0.0753743 -0.0586859 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1822 1872 0.0739379 -2.96847 0.00569321 0.0682755 0.00374356 0.0332516 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1872 1873 4.3311 -0.264852 -0.186083 -0.0110717 0.104062 -0.132561 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1823 1873 -0.0143154 -3.23242 -0.0257429 0.0622019 0.00240997 -0.0137481 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1873 1874 4.49719 -0.261598 0.0532623 0.00122266 0.0922871 -0.093952 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1824 1874 0.0613559 -2.92594 -0.312506 0.0596012 -0.00863976 -0.052485 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1874 1875 4.58532 -0.23031 -0.192696 -0.00494584 0.101564 -0.10779 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1825 1875 0.00772411 -3.10499 -0.0477326 0.0679275 -0.000813983 -0.0185891 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1875 1876 4.35546 -0.339718 -0.169654 -0.0109987 0.0809854 -0.0920165 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1826 1876 0.161524 -3.2491 -0.114827 0.0804324 0.00224102 -0.0176379 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1876 1877 4.54031 -0.244959 -0.267222 0.00241677 0.0762422 -0.0662324 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1827 1877 0.186278 -3.11028 -0.0133621 0.052274 -0.00292716 0.0280542 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1877 1878 4.60547 -0.309716 -0.251823 -0.00599094 0.0954587 -0.179015 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1828 1878 0.0531775 -3.08589 -0.112001 0.0405242 -0.0064053 0.00917279 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1878 1879 4.54325 -0.115893 -0.140441 -0.0146982 0.0978564 -0.0836896 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1829 1879 -0.020543 -3.27013 -0.212735 0.0564147 0.0128103 -0.0760244 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1879 1880 4.52617 -0.302251 -0.37575 -0.00183563 0.108235 -0.158284 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1830 1880 -0.00259814 -3.14464 -0.087878 0.0695936 -0.00956796 -0.0445708 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1880 1881 4.54856 -0.158533 -0.254646 0.00205262 0.0994201 -0.100491 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1831 1881 -0.0893566 -3.07893 -0.18693 0.0610658 0.00073669 0.0440814 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1881 1882 4.35954 -0.288155 -0.211167 0.00745067 0.0837914 -0.0691687 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1832 1882 0.116092 -2.92028 -0.0442224 0.0677234 -0.00204854 0.0439028 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1882 1883 4.56887 -0.0929468 -0.311223 0.000460255 0.0872684 -0.178205 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1833 1883 0.0758564 -3.18104 -0.226805 0.0709626 0.0129886 0.00358545 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1883 1884 4.46033 -0.294934 -0.219197 0.00569462 0.102623 -0.0999751 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1834 1884 -0.084759 -3.22165 0.0114432 0.0499421 -0.0148616 0.00918912 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1884 1885 4.38959 -0.196717 -0.208776 0.00624706 0.0935683 -0.108966 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1835 1885 0.0548894 -2.99025 -0.144123 0.0655518 -0.00423922 -0.0542006 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1885 1886 4.43024 -0.160032 -0.239509 -0.0349875 0.090498 -0.123335 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1836 1886 0.0885277 -3.14703 -0.0265822 0.0579084 0.0137227 0.00905663 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1886 1887 4.50574 -0.253492 -0.131022 -0.00630733 0.0910965 -0.0538159 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1837 1887 0.0218338 -3.13588 -0.113553 0.0668271 0.00372304 -0.0991861 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1887 1888 4.51343 -0.429701 -0.287934 -0.000209637 0.108305 -0.149976 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1838 1888 -0.00821434 -3.17133 0.00805733 0.0666172 -0.00824035 -0.0363585 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1888 1889 4.47962 -0.37622 -0.272483 -0.00789119 0.0813587 -0.06964 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1839 1889 -0.0509058 -2.91188 -0.212373 0.067461 -0.0205428 -0.000182639 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1889 1890 4.34179 -0.0240087 -0.241593 0.00726602 0.0975707 -0.0839039 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1840 1890 -0.0505836 -2.91351 -0.250506 0.08337 -0.00630299 -0.0501471 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1890 1891 4.35205 -0.16348 -0.20882 -0.0123174 0.087271 -0.0518578 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1841 1891 -0.129239 -3.18183 -0.230686 0.0538964 -0.000225464 -0.0838791 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1891 1892 4.30193 -0.281841 -0.088496 -0.00954845 0.0929985 -0.157635 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1842 1892 -0.0535983 -2.92779 -0.0518271 0.0799358 0.0142019 -0.00681962 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1892 1893 4.21476 -0.111473 -0.192084 -0.0180358 0.0735265 -0.0606514 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1843 1893 0.0324093 -3.19663 -0.0408329 0.0612652 -0.00871208 -0.04819 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1893 1894 4.4421 -0.337322 -0.22283 -0.000882865 0.0823614 -0.0208079 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1844 1894 -0.0770178 -3.16532 -0.0640183 0.0707633 -0.00977542 -0.0208785 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1894 1895 4.38043 -0.385174 -0.169445 0.00567405 0.101163 -0.0937427 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1845 1895 -0.0234045 -3.15978 -0.0221831 0.0646353 -0.0128911 0.0948391 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1895 1896 4.31434 -0.270794 -0.282302 0.00240869 0.0900273 -0.0768036 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1846 1896 -0.0843723 -3.00494 0.000423335 0.0531676 -0.0111417 -0.0622419 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1896 1897 4.44356 -0.29539 -0.240215 -0.0141811 0.0836801 -0.0817204 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1847 1897 0.191385 -2.92016 -0.208971 0.0585519 0.00772875 0.0571633 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1897 1898 4.46323 -0.226667 -0.147095 0.0140399 0.0697035 -0.121016 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1848 1898 0.202927 -3.05126 -0.142374 0.0555069 0.0103147 -0.011735 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1898 1899 4.31549 -0.306274 -0.332723 0.0109474 0.0945646 -0.0817513 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1849 1899 0.0403644 -3.03129 -0.0179074 0.0614092 -0.00291469 0.028469 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1899 1900 4.18451 -0.150939 -0.40337 -0.00138186 0.0876948 -0.0471816 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1850 1900 0.0957077 -3.01279 -0.044987 0.0506446 -0.000660243 -0.019608 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1900 1901 4.3209 -0.0123597 -0.102028 9.83534e-05 0.0922107 -0.051044 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1851 1901 -0.174056 -3.04715 -0.111642 0.0621035 -0.00755424 0.0135644 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1901 1902 4.319 -0.192356 -0.0337542 -0.0182751 0.0833723 -0.0809759 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1852 1902 0.0680705 -3.14048 -0.178702 0.0607085 0.0135957 -0.00229303 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1902 1903 4.41828 -0.0962022 -0.211985 -0.00995988 0.0744657 -0.110466 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1853 1903 0.00378761 -3.16236 -0.141362 0.0591533 0.00509642 -0.0140452 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1903 1904 4.25658 -0.12072 -0.0793969 0.00515729 0.0963357 -0.00792459 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1854 1904 0.095026 -2.88379 -0.278144 0.0622662 0.00417311 0.0479794 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1904 1905 4.25253 -0.242802 -0.268575 0.0113678 0.0943997 -0.0600259 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1855 1905 -0.32096 -3.21696 -0.1433 0.0553023 0.0075246 -0.00153905 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1905 1906 4.49917 -0.266086 -0.377066 -0.0152041 0.0946548 -0.193306 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1856 1906 -0.0141632 -2.94756 -0.266488 0.0727217 0.00277965 -0.0160306 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1906 1907 4.31382 -0.267079 -0.208264 -0.000243839 0.0892815 -0.114627 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1857 1907 0.123448 -3.11809 -0.0386667 0.0618456 0.0068748 -0.0346133 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1907 1908 4.45144 -0.365909 -0.312542 -0.013901 0.0890966 -0.112512 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1858 1908 0.175612 -3.00971 0.0343817 0.0670299 -0.000263977 0.0405356 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1908 1909 4.26669 -0.274093 -0.135733 -0.0133767 0.0888738 -0.0922154 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1859 1909 -0.0143492 -3.03281 -0.191016 0.0633778 0.0168929 0.048693 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1909 1910 4.24691 -0.11138 -0.14229 0.000229511 0.0858012 -0.0592783 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1860 1910 -0.0958643 -3.07388 0.0497909 0.0470989 0.00508015 -0.0126608 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1910 1911 4.22629 -0.253439 -0.157639 0.00267606 0.0815736 -0.075993 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1861 1911 -0.0332655 -2.95962 0.0264198 0.0576656 -0.00461829 0.00380271 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1911 1912 4.2983 -0.148176 -0.101345 -0.00615889 0.0695333 -0.11309 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1862 1912 -0.0801627 -3.03279 -0.126231 0.066146 -0.000662345 0.0254509 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1912 1913 4.29847 -0.247014 -0.216417 0.00466853 0.0894955 -0.167794 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1863 1913 -0.0067682 -2.99896 -0.114812 0.0652925 -0.00769526 -0.0398806 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1913 1914 4.28744 -0.190456 -0.1246 -0.00523147 0.0884533 -0.132183 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1864 1914 -0.0875273 -3.18437 0.008422 0.0670764 -0.0098103 0.0340302 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1914 1915 4.26013 -0.293275 -0.118631 0.00162434 0.0840828 -0.0931572 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1865 1915 0.110046 -2.95598 -0.203223 0.0707307 0.0097679 -0.00974171 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1915 1916 4.29278 -0.211865 -0.419779 -0.00516219 0.0925443 -0.104693 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1866 1916 0.165809 -2.92397 -0.0639948 0.0704789 0.00142009 0.0184804 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1916 1917 4.43892 -0.212728 -0.157385 -0.00128075 0.0870124 -0.177047 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1867 1917 -0.25459 -2.94055 -0.067981 0.0766394 0.00910864 -0.0155151 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1917 1918 4.24089 -0.232276 -0.177805 -0.01324 0.0511016 -0.120929 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1868 1918 0.0744493 -3.18284 -0.0596563 0.0497036 -0.0110359 -0.0138372 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1918 1919 4.16527 -0.25614 -0.129577 -0.00676019 0.0739457 -0.0449676 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1869 1919 0.0474249 -3.14388 -0.120452 0.0523094 -0.000940022 0.0649863 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1919 1920 4.2376 -0.208001 -0.244516 0.0025855 0.0658397 -0.128578 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1870 1920 -0.131812 -2.99875 -0.0187358 0.0535419 -0.00572999 -0.0170683 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1920 1921 4.26588 -0.244314 -0.138584 0.0169447 0.0923461 -0.129302 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1871 1921 0.172469 -3.1663 -0.203053 0.057713 0.00698398 -0.00323928 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1921 1922 4.29202 -0.326796 -0.249091 0.00999889 0.0881306 -0.0893554 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1872 1922 -0.100465 -3.18693 -0.118614 0.0761284 0.0021087 -0.0232732 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1922 1923 4.17805 -0.216368 -0.262239 -0.0106656 0.0997709 -0.046544 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1873 1923 -0.0256783 -3.09551 -0.206493 0.0508551 0.00287114 -0.0136379 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1923 1924 4.27869 -0.319575 -0.233288 -0.0235943 0.0785207 -0.0909385 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1874 1924 0.153733 -3.12105 -0.0643246 0.0435506 -0.00758778 -0.00679884 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1924 1925 4.29058 -0.376121 -0.384833 -0.00123667 0.0939581 -0.112237 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1875 1925 -0.0190031 -3.11941 -0.0322153 0.0538352 2.90802e-05 0.0887264 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1925 1926 4.39244 -0.23956 0.0539397 -0.01035 0.0845915 -0.127842 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1876 1926 0.0236955 -2.959 -0.096646 0.0505093 -0.0271878 0.000431228 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1926 1927 4.19606 -0.34414 -0.142735 -0.00773727 0.0841039 -0.0667369 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1877 1927 0.173492 -3.00229 -0.127557 0.0588094 -0.000669096 0.0608391 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1927 1928 4.30325 -0.266877 -0.14374 -0.0123015 0.0828402 -0.0535617 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1878 1928 -0.162028 -3.22612 -0.195156 0.0718848 -0.00182541 0.0323809 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1928 1929 4.19134 -0.324255 -0.178556 -0.0162972 0.0883525 -0.0796562 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1879 1929 -0.0358555 -3.01209 -0.053434 0.0657251 0.00166911 -0.0196347 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1929 1930 4.09887 -0.297373 -0.32448 0.00265376 0.0759434 -0.0684646 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1880 1930 0.157879 -3.04929 -0.0713773 0.0655567 0.00327823 0.0290589 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1930 1931 4.23549 -0.303304 -0.379125 0.00468234 0.0774373 -0.0812882 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1881 1931 0.0286061 -3.12105 0.0517603 0.0694921 -0.0056283 0.0145916 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1931 1932 4.08328 -0.391529 -0.19426 -0.0121089 0.0722206 -0.0945631 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1882 1932 -0.0399439 -2.92277 -0.0809829 0.0527822 -0.0069721 0.0710042 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1932 1933 4.06086 -0.167069 -0.0924443 -0.0182719 0.0867986 -0.0859814 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1883 1933 -0.052735 -2.93029 -0.147111 0.0653108 -0.00151232 0.00249172 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1933 1934 4.15542 -0.178941 -0.0754697 -0.0181083 0.0880364 -0.119904 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1884 1934 -0.0664556 -2.95549 -0.0643582 0.0736804 -0.0074965 -0.00673016 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1934 1935 4.28579 -0.482084 -0.197275 -0.000602183 0.0745662 -0.0762575 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1885 1935 -0.120315 -3.15726 -0.190176 0.0599016 0.00897308 -0.025345 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1935 1936 4.3514 -0.266014 -0.196074 -0.0118994 0.0771209 -0.0921799 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1886 1936 0.154242 -3.04692 -0.0974953 0.0547337 -0.000535011 0.0662167 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1936 1937 4.12983 -0.285903 -0.183014 0.0179957 0.0561641 -0.0796293 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1887 1937 -0.0863398 -3.22479 -0.161658 0.0534412 0.00288308 0.0673637 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1937 1938 4.21764 -0.27165 -0.0621017 -0.00391806 0.0844955 -0.142137 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1888 1938 -0.0734187 -3.02007 0.0673569 0.0676042 0.0134512 -0.0555018 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1938 1939 4.08981 -0.344466 -0.0921311 -0.0263845 0.0760042 -0.0575004 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1889 1939 0.0840464 -3.17894 -0.0339765 0.0519333 -0.0111514 0.0558327 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1939 1940 3.9116 -0.223302 -0.244041 -0.00472284 0.0642214 -0.0360385 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1890 1940 0.0570372 -2.8924 -0.0610536 0.0479607 -0.00817971 -0.0361353 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1940 1941 4.26428 -0.17288 -0.229269 0.00422024 0.103071 -0.115945 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1891 1941 0.131844 -3.0645 -0.232504 0.0791449 -0.00380398 0.0389546 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1941 1942 4.15675 -0.219201 -0.266267 -0.000560014 0.0727546 -0.135641 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1892 1942 0.0777617 -3.04831 -0.0535451 0.0631704 0.00942701 -0.0371857 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1942 1943 4.14824 -0.308997 -0.252387 -0.000623447 0.0904886 -0.0854588 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1893 1943 -0.128108 -2.88505 -0.155163 0.0588831 0.00675514 -0.0422598 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1943 1944 4.25728 -0.188387 -0.156685 -0.0101019 0.0732098 -0.112368 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1894 1944 0.153072 -3.01143 -0.0797814 0.0677367 -0.00878229 -0.007482 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1944 1945 4.02996 -0.35726 -0.0912853 0.00188491 0.0954209 -0.132888 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1895 1945 0.164682 -2.9473 -0.119452 0.0611001 -0.000673267 -0.0181416 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1945 1946 4.12195 -0.337303 -0.280472 -0.00303241 0.0869872 -0.0903253 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1896 1946 -0.023264 -3.04771 -0.152045 0.0619894 -0.00634507 0.0392784 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1946 1947 4.06167 -0.23868 -0.11998 0.00265271 0.0892516 -0.0327593 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1897 1947 0.00547007 -3.09013 -0.0511763 0.0619846 0.0226482 -0.0110786 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1947 1948 4.0425 -0.258 -0.250096 -0.0115353 0.0709673 -0.101372 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1898 1948 0.121128 -3.11473 -0.121931 0.0492621 0.0190299 -0.0223325 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1948 1949 3.97484 -0.296761 -0.193436 -0.0193701 0.0916655 -0.0781071 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1899 1949 0.151909 -2.89019 0.101183 0.0594345 -0.00383205 -0.0576626 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1949 1950 4.20071 -0.309989 -0.326205 0.00498975 0.0794809 -0.0219681 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1900 1950 -0.0558459 -3.05886 -0.00808693 0.0555724 -0.00178108 -0.00258199 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1950 1951 3.98914 -0.377714 -0.146508 -0.00503001 0.0779264 -0.0456139 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1901 1951 0.020223 -3.10738 -0.0417297 0.058371 -0.00154075 -0.00161483 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1951 1952 4.15649 -0.474466 -0.205463 0.013224 0.0776772 -0.149838 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1902 1952 -0.030244 -3.05845 -0.136567 0.073076 0.0222177 -0.0470917 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1952 1953 4.07392 -0.131107 -0.159059 -0.0101704 0.0816373 -0.020526 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1903 1953 0.0557011 -2.99479 -0.102065 0.0675648 -0.00381538 -0.0271069 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1953 1954 4.12942 -0.238501 -0.193384 -0.0172608 0.0778085 -0.0947855 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1904 1954 -0.216131 -3.03897 -0.0433695 0.0675301 0.0177496 -0.115951 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1954 1955 4.02161 -0.230868 -0.153143 -0.0050373 0.0722148 -0.164973 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1905 1955 -0.0897988 -2.97752 -0.10118 0.0403913 0.010461 0.0133102 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1955 1956 4.0127 -0.332368 -0.219003 -0.00789817 0.0838446 -0.0571936 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1906 1956 -0.14467 -3.05528 -0.312279 0.0916964 -0.00669889 -0.007295 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1956 1957 4.03161 -0.142439 -0.102149 -0.0106457 0.0602491 -0.0406136 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1907 1957 -0.00123278 -2.90526 -0.26953 0.0627806 -0.0049433 0.045618 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1957 1958 4.12457 -0.027463 -0.204845 -0.00720539 0.0870151 -0.0582056 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1908 1958 -0.0813435 -3.02588 -0.157532 0.0655548 -0.00357006 0.0378483 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1958 1959 4.1822 -0.196563 -0.382705 0.0133169 0.063573 -0.0505472 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1909 1959 -0.0978837 -2.90575 0.093453 0.0612773 -0.0101771 -0.0149189 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1959 1960 4.01098 -0.16293 -0.205224 0.000690703 0.0683197 -0.125481 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1910 1960 0.0592711 -3.1138 -0.247364 0.042871 0.0105628 0.0428797 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1960 1961 4.15577 -0.195198 -0.143934 -0.0131374 0.0808275 -0.0620354 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1911 1961 -0.150285 -2.98368 -0.165131 0.055658 0.0171125 -0.0177415 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1961 1962 4.09018 -0.436098 -0.185573 0.00168603 0.0734392 -0.0857874 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1912 1962 -0.0789751 -3.01499 -0.00610366 0.0720518 -0.0216005 -0.0843853 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1962 1963 4.23886 -0.278578 -0.0758427 -0.015394 0.0964312 -0.0925962 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1913 1963 -0.0355763 -3.07105 -0.0748421 0.065682 0.00753022 0.0274502 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1963 1964 3.98134 -0.180001 -0.190638 -0.0111859 0.0981133 -0.124912 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1914 1964 0.0190411 -2.94673 -0.0715748 0.0608257 0.00820011 -0.0121434 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1964 1965 4.0293 -0.29605 -0.192949 -0.0197484 0.0819707 -0.0836343 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1915 1965 -0.0626555 -2.99931 -0.241992 0.0651594 -0.0174585 0.0097151 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1965 1966 4.05788 -0.0722964 -0.149412 -0.0178659 0.0895746 -0.0876653 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1916 1966 -0.0834555 -3.04717 -0.145403 0.0560101 0.00345291 0.0225831 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1966 1967 4.0752 -0.299522 -0.203021 0.00613674 0.0771903 -0.0641583 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1917 1967 -0.0617324 -3.03557 -0.0924446 0.0617031 -0.00550161 0.0236195 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1967 1968 4.04603 -0.198135 -0.355313 -0.00646143 0.0831503 -0.0733695 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1918 1968 0.108933 -3.15224 -0.290402 0.0598904 0.0105879 -0.00255137 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1968 1969 3.97505 -0.193533 -0.0404268 0.000963879 0.0850782 -0.0726859 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1919 1969 -0.113101 -3.01724 -0.00961383 0.0669725 0.00283789 -0.0347312 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1969 1970 3.85677 -0.19319 -0.0938565 -0.0142197 0.083613 -0.0351686 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1920 1970 -0.197512 -3.11572 -0.157018 0.0708744 -0.00664834 0.0273647 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1970 1971 3.93538 -0.192721 -0.100265 -0.00327336 0.0778942 -0.0921695 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1921 1971 -0.179218 -3.18095 -0.0896117 0.0861331 -0.000132903 0.081152 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1971 1972 3.87697 -0.23189 -0.142868 -0.00194415 0.0649033 -0.0405224 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1922 1972 -0.0476279 -3.02727 -0.0677929 0.0620293 0.0183332 -0.0468609 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1972 1973 3.93295 -0.351428 -0.0692229 0.00157272 0.0777122 -0.0645434 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1923 1973 -0.18019 -3.1274 -0.215239 0.0605612 -0.000547583 -0.0478365 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1973 1974 4.08117 -0.325844 -0.143426 0.011943 0.0773388 -0.0861566 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1924 1974 0.0718273 -3.10457 -0.177574 0.0561563 0.00150109 -0.0534509 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1974 1975 3.96931 -0.200514 -0.227838 -0.0135039 0.0838421 -0.0910143 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1925 1975 -0.0852625 -2.9934 0.0333761 0.0691608 -0.000100165 0.0396848 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1975 1976 3.95499 -0.126193 -0.182623 0.0101559 0.0757382 -0.0414272 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1926 1976 -0.0549844 -2.95415 0.0503509 0.074622 0.00286758 -0.0197989 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1976 1977 3.93775 -0.105977 -0.299612 0.00251116 0.0748473 -0.0919241 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1927 1977 0.0499105 -3.05122 -0.122024 0.0615881 0.0182797 0.00690448 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1977 1978 3.9011 -0.365612 -0.104658 -0.00881255 0.073347 -0.031555 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1928 1978 0.0773659 -3.07539 -0.0405432 0.0525861 0.000438271 -0.0102741 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1978 1979 4.11376 -0.298042 -0.179663 -0.00309183 0.0877969 -0.0708691 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1929 1979 0.107398 -3.25687 0.0176977 0.0494088 -0.0221734 0.00732095 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1979 1980 3.83187 -0.257301 -0.171019 -0.000184932 0.0918396 -0.251722 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1930 1980 -0.11863 -3.04041 -0.122991 0.0487717 0.0118078 -0.0144252 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1980 1981 3.88607 -0.285043 -0.264392 -0.00570068 0.0822052 -0.0919888 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1931 1981 0.0186651 -3.18181 -0.139696 0.0557855 0.00998612 -0.0106596 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1981 1982 3.92373 -0.232823 -0.117316 0.00108363 0.0721919 -0.112173 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1932 1982 -0.0241102 -2.99522 -0.167005 0.0753525 -0.0178488 -0.0100052 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1982 1983 3.89774 -0.399653 -0.203818 -0.00998694 0.0693313 -0.143321 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1933 1983 0.135014 -2.82967 -0.252255 0.0644094 0.00820984 0.052871 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1983 1984 3.7314 -0.326964 -0.249638 -0.00458387 0.0856673 -0.149648 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1934 1984 0.044808 -3.12939 -0.0859541 0.0857895 -0.0104472 -0.0701079 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1984 1985 3.89 -0.181903 -0.283264 -0.00275248 0.0796951 -0.146341 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1935 1985 0.0236924 -3.08302 -0.0928126 0.0673263 -0.00174586 -0.0534962 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1985 1986 3.83248 -0.409762 -0.239389 -0.0139169 0.0736887 -0.0531359 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1936 1986 -0.00505125 -3.11936 -0.122213 0.0690315 -0.00639175 0.0574055 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1986 1987 4.06696 -0.272481 -0.22723 0.0143956 0.0983608 -0.0790062 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1937 1987 0.0263322 -2.97505 -0.133867 0.0476881 -0.0104861 0.0182313 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1987 1988 3.94074 -0.166553 -0.203753 -0.00466307 0.095582 -0.143967 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1938 1988 0.0091196 -3.11688 -0.178431 0.0461039 0.00581804 0.00249168 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1988 1989 3.99065 -0.304642 -0.162138 -0.00807173 0.0894635 -0.000532056 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1939 1989 -0.00433661 -3.26607 0.0314002 0.0449051 0.00750661 -0.0135727 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1989 1990 3.71339 -0.218157 -0.0834343 -0.00850129 0.0599762 0.00411139 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1940 1990 -0.0190984 -3.22341 -0.0442282 0.0567095 0.014596 -0.0250566 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1990 1991 3.93 -0.204349 -0.129851 -0.000377474 0.0711486 -0.0579703 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1941 1991 0.0897336 -2.94896 -0.0238168 0.0333184 0.0052942 -0.0727295 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1991 1992 3.92079 -0.288127 -0.269137 -0.00950973 0.0779951 -0.0870242 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1942 1992 -0.107628 -3.15056 0.040788 0.0350415 0.00204729 0.0227784 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1992 1993 3.85097 -0.408908 -0.198446 -0.00653542 0.0911453 -0.160269 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1943 1993 0.0377913 -2.97537 -0.00858782 0.0473134 0.00133275 -0.00761058 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1993 1994 3.83342 -0.209282 -0.107311 -0.00523756 0.0760703 -0.129525 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1944 1994 -0.200275 -3.02643 -0.145734 0.0553561 0.0124984 0.0833295 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1994 1995 3.84574 -0.097062 -0.189343 -0.0141308 0.0815852 -0.189678 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1945 1995 0.0516165 -2.97591 -0.0560244 0.0752554 -0.0060587 -0.0421071 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1995 1996 3.80267 -0.249033 -0.0632055 -0.0248118 0.07084 -0.091551 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1946 1996 0.121357 -3.04053 -0.200719 0.0611263 -0.00402293 0.0575747 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1996 1997 4.05999 -0.348409 -0.0678961 0.00148827 0.0813297 -0.0731714 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1947 1997 -0.0308405 -3.04748 0.0571645 0.0523132 -0.00572717 0.0819391 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1997 1998 3.58636 -0.259717 -0.0849707 -0.00130152 0.0771543 -0.0938153 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1948 1998 0.0536134 -3.12658 -0.320196 0.0687956 0.0098049 0.0385344 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1998 1999 3.75228 -0.132566 -0.0826785 0.00855786 0.0810907 -0.0815025 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1949 1999 0.030286 -3.07141 -0.0710082 0.0662994 -0.0132673 -0.0325276 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1999 2000 3.7061 -0.277007 -0.229495 -0.00764001 0.0678636 -0.0723049 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1950 2000 0.0148607 -3.13423 -0.138566 0.0633798 -0.00206171 0.0100648 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2000 2001 3.94372 -0.364221 -0.182918 0.00645856 0.0502168 -0.103713 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1951 2001 0.0521878 -3.03471 0.0377428 0.0596219 -0.00708902 0.0657467 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2001 2002 3.76193 -0.355789 -0.222014 -0.00300618 0.0753516 -0.0479499 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1952 2002 0.0312852 -3.05352 -0.188157 0.0675008 0.0202726 -0.043469 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2002 2003 3.67902 -0.213382 -0.214829 0.00701115 0.0853371 -0.112833 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1953 2003 -0.138849 -3.01898 -0.0750788 0.0611615 -0.00905312 0.0224817 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2003 2004 3.91755 -0.164977 -0.10725 0.0131947 0.0648788 -0.0717277 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1954 2004 -0.00099052 -3.14651 -0.0146388 0.0769402 -0.0157311 -0.00425177 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2004 2005 3.77653 -0.391448 -0.0360583 -0.010608 0.0958135 -0.0435752 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1955 2005 0.0925024 -3.09935 -0.0978751 0.0809205 -0.00698252 0.0460514 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2005 2006 3.80116 -0.310168 -0.138617 -0.00192078 0.0832512 -0.0808566 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1956 2006 -0.194563 -3.01287 0.0205387 0.0600865 0.00446102 0.0305715 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2006 2007 3.73529 -0.459481 -0.231161 -0.00750538 0.0695369 -0.0437146 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1957 2007 0.105266 -2.96184 -0.111297 0.0575965 -0.00939636 0.0651021 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2007 2008 3.73511 -0.347834 -0.158496 -0.0096189 0.0724432 -0.0660995 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1958 2008 -0.108838 -2.9883 -0.0176286 0.0661488 0.0109523 -0.0218325 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2008 2009 3.80865 -0.0847682 0.0484325 -0.00860126 0.0841538 -0.0958081 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1959 2009 0.0198086 -2.87677 -0.0693471 0.0462626 0.0101029 -0.0620391 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2009 2010 3.64592 -0.348139 -0.205187 -0.0144 0.0734242 -0.0908535 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1960 2010 0.0620823 -2.86315 -0.146143 0.0516219 -0.0059276 0.0166504 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2010 2011 3.83458 -0.176115 -0.0552606 0.00770637 0.0693927 -0.100231 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1961 2011 -0.104128 -3.09505 -0.0121927 0.0663289 0.00195369 0.0209419 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2011 2012 3.76957 -0.220653 -0.136653 -0.0111087 0.0662607 -0.0385169 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1962 2012 -0.0382338 -3.00643 -0.0654127 0.0568282 -0.00939105 -0.0513172 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2012 2013 3.6968 -0.260408 -0.306459 0.00809763 0.0715436 -0.0774 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1963 2013 -0.103737 -3.12396 -0.270104 0.0610715 -0.016514 0.0787495 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2013 2014 3.57015 -0.217549 -0.237674 0.00505963 0.068742 -0.0933335 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1964 2014 -0.0410864 -3.12942 -0.121939 0.0671667 -0.0188968 0.023357 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2014 2015 3.69388 -0.331596 -0.0171443 0.0141729 0.0550964 -0.158971 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1965 2015 -0.00394692 -3.12284 -0.120259 0.0468607 -0.003365 -0.0812927 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2015 2016 3.75549 -0.324537 -0.270617 0.00843679 0.0762542 -0.109485 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1966 2016 0.035538 -3.01311 -0.167803 0.0735814 -0.0187464 0.0506743 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2016 2017 3.66044 -0.416423 -0.151793 -0.00953658 0.0575649 -0.0875991 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1967 2017 0.00160172 -3.00319 -0.289741 0.0381222 0.00950498 0.0147429 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2017 2018 3.77146 -0.2592 -0.0438973 0.00856138 0.0676355 -0.152065 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1968 2018 0.0183999 -2.92201 0.0329823 0.0560734 -0.00541229 0.0589358 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2018 2019 3.69838 -0.318102 0.0969819 -0.00353239 0.058472 -0.0906684 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1969 2019 0.0269479 -3.06412 -0.134239 0.041109 0.00631797 -0.0485567 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2019 2020 3.62488 -0.229052 -0.194989 -0.00431024 0.0724754 -0.0967823 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1970 2020 -0.000304255 -3.18856 -0.112986 0.0627602 0.0078902 0.0385972 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2020 2021 3.67628 -0.359818 -0.0531481 0.00291086 0.0821518 -0.0514497 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1971 2021 0.0243198 -2.98738 -0.23178 0.0793911 -0.00397448 0.0673275 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2021 2022 3.70208 -0.00211951 0.035242 0.00466816 0.0752083 -0.143919 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1972 2022 0.0411305 -2.97061 -0.0454571 0.0803237 -0.0024945 -0.0109802 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2022 2023 3.70533 -0.343122 -0.21916 -0.011092 0.062428 -0.064884 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1973 2023 0.110846 -3.00954 -0.0460256 0.0523123 -0.00651303 -0.0717703 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2023 2024 3.57595 -0.130087 -0.182328 -0.00763289 0.0828123 -0.0692883 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1974 2024 -0.0597523 -3.03427 -0.0776605 0.0415787 0.00119917 0.0597269 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2024 2025 3.63867 -0.362192 -0.232067 6.71021e-06 0.0872261 -0.0926256 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1975 2025 -0.0932133 -3.05779 -0.152591 0.0573443 -0.00508391 0.0396799 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2025 2026 3.51279 -0.292839 -0.289881 -0.0342383 0.061289 -0.11843 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1976 2026 0.00357393 -3.23914 -0.161052 0.068616 -0.00646015 0.052866 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2026 2027 3.70234 -0.387619 -0.269292 0.00404123 0.077507 -0.153865 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1977 2027 -0.180899 -3.16128 -0.147999 0.084729 0.00248696 0.0222292 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2027 2028 3.56233 -0.372679 -0.200957 -0.00550305 0.0669253 -0.0339962 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1978 2028 -0.13379 -3.24197 -0.172663 0.0556349 -0.00512141 -0.0460592 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2028 2029 3.49367 -0.276565 -0.111897 0.00872853 0.0698488 -0.0909876 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1979 2029 0.157572 -3.08483 -0.015791 0.0561958 0.00428978 -0.00142322 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2029 2030 3.55546 -0.347194 -0.147411 0.00792586 0.0812436 -0.0735982 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1980 2030 0.0558258 -3.01001 -0.158652 0.0705229 -0.0357807 0.0155148 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2030 2031 3.59624 -0.121327 -0.182388 -0.00717412 0.0676787 -0.140362 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1981 2031 0.0523394 -3.16742 -0.19736 0.0479983 0.00712977 0.0050826 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2031 2032 3.67612 -0.369524 -0.125767 -0.0154269 0.0631136 -0.133743 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1982 2032 -0.21673 -2.86464 -0.162463 0.0627936 0.00608695 -0.0030869 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2032 2033 3.55253 -0.266153 -0.0398371 0.00205329 0.0751987 -0.109453 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1983 2033 -0.144195 -3.13249 0.00132992 0.0703013 -0.00318527 0.00140536 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2033 2034 3.58934 -0.307994 -0.207852 0.00107559 0.0675295 -0.0862884 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1984 2034 -0.0670177 -2.888 0.237676 0.056287 -0.0128674 0.0711759 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2034 2035 3.60535 -0.133341 -0.248406 0.0114793 0.0632323 -0.0995834 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1985 2035 -0.0209647 -3.17551 -0.267033 0.0536729 0.0104624 0.031267 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2035 2036 3.66779 -0.178988 -0.130556 -0.00301086 0.0635599 -0.0946509 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1986 2036 -0.0238239 -2.8232 -0.0525839 0.0708069 -0.00836265 0.0468911 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2036 2037 3.57846 -0.118432 -0.179432 0.00629884 0.0835163 -0.100247 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1987 2037 -0.0504269 -3.11407 -0.185938 0.0526284 -0.00551218 -0.0259865 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2037 2038 3.52523 -0.244794 -0.0520923 -0.0198477 0.0611237 -0.127133 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1988 2038 -0.0189585 -3.07027 -0.0683004 0.0748082 -0.00908523 -0.0230099 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2038 2039 3.7194 -0.243581 -0.219514 -0.00127801 0.0899491 -0.118238 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1989 2039 0.0147197 -3.09238 -0.208605 0.056931 0.00255577 0.0326083 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2039 2040 3.43304 -0.130643 -0.142288 0.00439302 0.0684212 -0.05758 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1990 2040 0.032072 -3.24973 -0.0696703 0.0679527 0.0135707 0.0290668 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2040 2041 3.4791 -0.198703 -0.126062 0.0121599 0.0839251 -0.138899 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1991 2041 -0.0359589 -3.21296 -0.0623838 0.0742012 0.0253433 -0.0125126 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2041 2042 3.64315 -0.226554 -0.315696 0.00271988 0.0742986 -0.151842 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1992 2042 -0.0774013 -3.063 -0.0814995 0.0774075 0.00164421 0.0314242 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2042 2043 3.50459 -0.266466 -0.173174 -0.0162543 0.0742343 -0.0756713 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1993 2043 -0.0160024 -2.94983 0.0273565 0.0683551 -0.0176981 0.0241458 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2043 2044 3.5959 -0.1959 -0.181279 -0.0141972 0.060515 -0.0838814 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1994 2044 0.0384637 -3.16603 -0.0156016 0.0636765 -0.0178174 0.0431538 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2044 2045 3.55489 -0.303045 -0.0642663 0.00604594 0.0725077 -0.0732478 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1995 2045 0.010927 -3.03111 0.0104183 0.0546198 0.000893637 0.0111643 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2045 2046 3.57822 -0.142312 0.105578 0.00886738 0.0837704 -0.130746 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1996 2046 0.097244 -2.99099 0.048626 0.0500272 -6.90939e-05 0.0213143 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2046 2047 3.42728 -0.356409 -0.161725 0.0110012 0.0698618 -0.0957525 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1997 2047 -0.0624482 -3.01433 -0.0802096 0.0718351 0.000960346 -0.00992014 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2047 2048 3.55289 -0.156051 -0.331846 0.0071787 0.067836 -0.072484 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1998 2048 -0.00224381 -3.00439 0.0464199 0.0498342 -0.011921 -0.000426229 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2048 2049 3.55217 -0.271874 -0.0598408 0.0101431 0.0856169 -0.089823 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1999 2049 -0.0144345 -3.06316 -0.175608 0.0514101 -0.00300242 -0.00371854 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2049 2050 3.60147 -0.114269 0.0564121 -0.00201539 0.0626433 -0.0877492 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2000 2050 -0.0643962 -3.18008 -0.166869 0.0550361 0.00769411 -0.0584173 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2050 2051 3.57746 -0.0468281 -0.0789584 -0.00395663 0.0705354 -0.157622 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2001 2051 0.0371151 -3.14533 -0.0838149 0.0651258 0.00222369 -0.0292995 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2051 2052 3.63038 -0.270854 -0.0144253 -0.00874243 0.0625857 -0.0683319 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2002 2052 0.0835603 -3.07361 -0.0633718 0.0528567 -0.000765593 -0.0420744 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2052 2053 3.31559 -0.181155 -0.304759 0.00772557 0.077911 -0.0912202 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2003 2053 0.115243 -3.09724 -0.138628 0.0673004 -0.00177217 -0.000381095 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2053 2054 3.30556 -0.217723 -0.168323 -0.00390401 0.0572114 -0.0469201 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2004 2054 -0.0706894 -3.09164 0.00896299 0.0608617 0.0206609 0.0190265 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2054 2055 3.58314 -0.265036 0.0422537 0.0208767 0.0656358 -0.0571548 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2005 2055 -0.0874422 -3.10329 -0.0692837 0.058226 -0.012659 -0.0150131 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2055 2056 3.48936 -0.432252 -0.0716867 -0.013267 0.0675975 -0.128845 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2006 2056 -0.0634775 -2.90446 0.0393535 0.0932889 -0.0030456 0.057481 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2056 2057 3.36455 -0.26077 -0.096088 0.00434994 0.0675728 -0.140037 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2007 2057 -0.00118421 -3.20395 -0.0703197 0.0534714 0.0168948 0.03099 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2057 2058 3.59821 -0.233977 0.0142636 -0.0033452 0.039423 -0.115332 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2008 2058 0.089576 -3.17679 -0.0790087 0.0410658 -0.000153665 -0.0114374 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2058 2059 3.57646 -0.124742 0.00405078 -0.00884704 0.0842831 -0.10149 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2009 2059 0.154141 -3.27799 -0.190217 0.0696598 0.000463073 -0.00592491 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2059 2060 3.42214 -0.19946 -0.141362 0.0143252 0.0747396 -0.181241 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2010 2060 0.0586031 -3.08102 -0.193086 0.0573666 -0.00436353 0.00348661 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2060 2061 3.3802 -0.21902 -0.0964095 -0.0120444 0.0632004 -0.0349306 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2011 2061 -0.0205971 -2.98712 -0.255829 0.0667232 -0.0128329 -0.0306593 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2061 2062 3.48935 -0.332609 -0.0179532 0.00416518 0.0673758 -0.109937 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2012 2062 0.0452902 -2.97497 -0.245561 0.0504328 0.00205029 0.0135809 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2062 2063 3.70822 -0.389152 -0.0994019 -0.0108951 0.0681705 -0.130221 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2013 2063 -0.00247814 -3.00499 -0.19276 0.0671112 0.00306903 0.0167438 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2063 2064 3.39377 -0.307898 -0.0105911 0.000943008 0.0661764 -0.166664 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2014 2064 0.123495 -3.09005 -0.223313 0.0691352 0.00565192 0.0205554 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2064 2065 3.32351 -0.306747 -0.247074 0.0154149 0.073912 -0.0140332 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2015 2065 -0.00684393 -3.1065 0.0218204 0.053722 -0.00422538 0.0804196 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2065 2066 3.37625 -0.265736 -0.0512975 -0.00918942 0.0594238 -0.142239 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2016 2066 0.00874849 -2.94551 -0.0028244 0.0602759 -0.0214517 -0.0407197 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2066 2067 3.34244 -0.109624 -0.375367 0.0222302 0.0717789 -0.115241 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2017 2067 0.0724536 -3.15653 -0.241265 0.0772802 0.000322605 -0.0134154 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2067 2068 3.36437 -0.170279 -0.144049 -0.00182204 0.0616702 -0.0830319 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2018 2068 -0.146806 -3.01057 -0.121051 0.0515932 0.012459 -0.00615419 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2068 2069 3.34494 -0.302038 -0.0238283 -0.0074607 0.0591736 -0.0889325 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2019 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100 0 0 100 0 25 +EDGE3 1780 1830 1.21041e-11 -3.05972 -0.0937068 0.0612327 2.54463e-13 -1.93179e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1830 1831 4.74617 -0.25594 -0.226429 -0.00269134 0.0951671 -0.0821889 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1781 1831 1.20934e-11 -3.05972 -0.0937068 0.0612327 2.54463e-13 -1.93623e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1831 1832 4.74115 -0.256011 -0.225951 -0.00269274 0.0950665 -0.0823053 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1782 1832 1.20757e-11 -3.05972 -0.0937068 0.0612327 2.54019e-13 -1.93623e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1832 1833 4.73613 -0.256081 -0.225473 -0.00269412 0.0949657 -0.0824216 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1783 1833 1.20579e-11 -3.05972 -0.0937068 0.0612327 2.54019e-13 -1.94067e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1833 1834 4.7311 -0.25615 -0.224995 -0.00269547 0.0948648 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4.71091 -0.256413 -0.223082 -0.00270066 0.0944598 -0.0830013 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1788 1838 1.1998e-11 -3.05972 -0.0937068 0.0612327 2.52687e-13 -1.95399e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1838 1839 4.70585 -0.256476 -0.222603 -0.00270189 0.0943582 -0.0831169 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1789 1839 1.19851e-11 -3.05972 -0.0937068 0.0612327 2.52243e-13 -1.95843e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1839 1840 4.70078 -0.256538 -0.222125 -0.00270311 0.0942565 -0.0832323 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1790 1840 1.19726e-11 -3.05972 -0.0937068 0.0612327 2.52243e-13 -1.96287e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1840 1841 4.6957 -0.256598 -0.221646 -0.0027043 0.0941546 -0.0833476 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1791 1841 1.19584e-11 -3.05972 -0.0937068 0.0612327 2.51799e-13 -1.96287e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1841 1842 4.69061 -0.256658 -0.221166 -0.00270547 0.0940526 -0.0834628 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1792 1842 1.19478e-11 -3.05972 -0.0937068 0.0612327 2.51799e-13 -1.96732e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1842 1843 4.68552 -0.256716 -0.220687 -0.00270661 0.0939504 -0.0835779 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1793 1843 1.19371e-11 -3.05972 -0.0937068 0.0612327 2.51354e-13 -1.97176e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1843 1844 4.68042 -0.256773 -0.220208 -0.00270773 0.0938481 -0.0836928 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1794 1844 1.19229e-11 -3.05972 -0.0937068 0.0612327 2.51354e-13 -1.9762e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1844 1845 4.67531 -0.256829 -0.219728 -0.00270882 0.0937456 -0.0838076 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1795 1845 1.19051e-11 -3.05972 -0.0937068 0.0612327 2.5091e-13 -1.9762e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1845 1846 4.6702 -0.256883 -0.219248 -0.00270989 0.0936431 -0.0839223 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1796 1846 1.18927e-11 -3.05972 -0.0937068 0.0612327 2.50466e-13 -1.98064e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1846 1847 4.66508 -0.256937 -0.218768 -0.00271094 0.0935403 -0.0840368 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1797 1847 1.18821e-11 -3.05972 -0.0937068 0.0612327 2.50466e-13 -1.98508e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1847 1848 4.65995 -0.256989 -0.218288 -0.00271197 0.0934375 -0.0841513 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1798 1848 1.18696e-11 -3.05972 -0.0937068 0.0612327 2.50022e-13 -1.98508e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1848 1849 4.65482 -0.25704 -0.217808 -0.00271297 0.0933345 -0.0842656 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1799 1849 1.18563e-11 -3.05972 -0.0937068 0.0612327 2.50022e-13 -1.98952e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1849 1850 4.64967 -0.25709 -0.217328 -0.00271395 0.0932313 -0.0843797 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1800 1850 1.18423e-11 -3.05972 -0.0937068 0.0612327 2.49578e-13 -1.99396e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1850 1851 4.64453 -0.257139 -0.216848 -0.0027149 0.093128 -0.0844938 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1801 1851 1.18296e-11 -3.05972 -0.0937068 0.0612327 2.49578e-13 -1.99396e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1851 1852 4.63937 -0.257187 -0.216367 -0.00271583 0.0930246 -0.0846077 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1802 1852 1.18181e-11 -3.05972 -0.0937068 0.0612327 2.49134e-13 -1.9984e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1852 1853 4.63421 -0.257233 -0.215887 -0.00271674 0.0929211 -0.0847214 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1803 1853 1.18039e-11 -3.05972 -0.0937068 0.0612327 2.49134e-13 -2.00284e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1853 1854 4.62904 -0.257278 -0.215406 -0.00271762 0.0928174 -0.0848351 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1804 1854 1.17932e-11 -3.05972 -0.0937068 0.0612327 2.4869e-13 -2.00728e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1854 1855 4.62386 -0.257323 -0.214925 -0.00271848 0.0927135 -0.0849486 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1805 1855 1.17737e-11 -3.05972 -0.0937068 0.0612327 2.4869e-13 -2.00728e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1855 1856 4.61868 -0.257365 -0.214444 -0.00271931 0.0926095 -0.085062 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1806 1856 1.17595e-11 -3.05972 -0.0937068 0.0612327 2.48246e-13 -2.01172e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1856 1857 4.61349 -0.257407 -0.213963 -0.00272013 0.0925054 -0.0851753 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1807 1857 1.17524e-11 -3.05972 -0.0937068 0.0612327 2.48246e-13 -2.01617e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1857 1858 4.60829 -0.257448 -0.213482 -0.00272091 0.0924012 -0.0852884 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1808 1858 1.17346e-11 -3.05972 -0.0937068 0.0612327 2.47802e-13 -2.01617e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1858 1859 4.60309 -0.257487 -0.213001 -0.00272168 0.0922968 -0.0854014 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1809 1859 1.17222e-11 -3.05972 -0.0937068 0.0612327 2.47358e-13 -2.02061e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1859 1860 4.59787 -0.257525 -0.212519 -0.00272242 0.0921923 -0.0855143 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1810 1860 1.17115e-11 -3.05972 -0.0937068 0.0612327 2.47358e-13 -2.02505e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1860 1861 4.59266 -0.257562 -0.212038 -0.00272314 0.0920876 -0.085627 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1811 1861 1.16964e-11 -3.05972 -0.0937068 0.0612327 2.46914e-13 -2.02505e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1861 1862 4.58743 -0.257598 -0.211556 -0.00272383 0.0919828 -0.0857397 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1812 1862 1.16835e-11 -3.05972 -0.0937068 0.0612327 2.46914e-13 -2.02949e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1862 1863 4.5822 -0.257633 -0.211075 -0.0027245 0.0918778 -0.0858521 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1813 1863 1.16693e-11 -3.05972 -0.0937068 0.0612327 2.4647e-13 -2.03393e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1863 1864 4.57696 -0.257666 -0.210593 -0.00272514 0.0917728 -0.0859645 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1814 1864 1.16565e-11 -3.05972 -0.0937068 0.0612327 2.4647e-13 -2.03393e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1864 1865 4.57172 -0.257698 -0.210111 -0.00272577 0.0916676 -0.0860767 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1815 1865 1.16422e-11 -3.05972 -0.0937068 0.0612327 2.46025e-13 -2.03837e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1865 1866 4.56646 -0.25773 -0.20963 -0.00272636 0.0915622 -0.0861888 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1816 1866 1.1628e-11 -3.05972 -0.0937068 0.0612327 2.45581e-13 -2.04281e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1866 1867 4.5612 -0.25776 -0.209148 -0.00272694 0.0914567 -0.0863008 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1817 1867 1.16174e-11 -3.05972 -0.0937068 0.0612327 2.45581e-13 -2.04281e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1867 1868 4.55594 -0.257788 -0.208666 -0.00272749 0.0913511 -0.0864126 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1818 1868 1.16032e-11 -3.05972 -0.0937068 0.0612327 2.45581e-13 -2.04725e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1868 1869 4.55067 -0.257816 -0.208184 -0.00272802 0.0912453 -0.0865243 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1819 1869 1.15854e-11 -3.05972 -0.0937068 0.0612327 2.45137e-13 -2.05169e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1869 1870 4.54539 -0.257842 -0.207702 -0.00272852 0.0911394 -0.0866359 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1820 1870 1.15783e-11 -3.05972 -0.0937068 0.0612327 2.44693e-13 -2.05169e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1870 1871 4.5401 -0.257867 -0.207219 -0.002729 0.0910334 -0.0867473 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1821 1871 1.15623e-11 -3.05972 -0.0937068 0.0612327 2.44693e-13 -2.05613e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1871 1872 4.53481 -0.257891 -0.206737 -0.00272946 0.0909272 -0.0868586 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1822 1872 1.15481e-11 -3.05972 -0.0937068 0.0612327 2.44249e-13 -2.06057e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1872 1873 4.52951 -0.257914 -0.206255 -0.00272989 0.0908209 -0.0869698 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1823 1873 1.15339e-11 -3.05972 -0.0937068 0.0612327 2.43805e-13 -2.06057e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1873 1874 4.5242 -0.257936 -0.205772 -0.0027303 0.0907145 -0.0870808 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1824 1874 1.15223e-11 -3.05972 -0.0937068 0.0612327 2.43805e-13 -2.06501e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1874 1875 4.51888 -0.257956 -0.20529 -0.00273068 0.0906079 -0.0871918 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1825 1875 1.15085e-11 -3.05972 -0.0937068 0.0612327 2.43361e-13 -2.06946e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1875 1876 4.51356 -0.257976 -0.204808 -0.00273104 0.0905012 -0.0873025 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1826 1876 1.14948e-11 -3.05972 -0.0937068 0.0612327 2.43361e-13 -2.06946e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1876 1877 4.50824 -0.257994 -0.204325 -0.00273138 0.0903943 -0.0874132 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1827 1877 1.14824e-11 -3.05972 -0.0937068 0.0612327 2.42917e-13 -2.0739e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1877 1878 4.5029 -0.258011 -0.203843 -0.00273169 0.0902874 -0.0875237 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1828 1878 1.14699e-11 -3.05972 -0.0937068 0.0612327 2.42917e-13 -2.07834e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1878 1879 4.49756 -0.258027 -0.20336 -0.00273198 0.0901802 -0.0876341 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1829 1879 1.14557e-11 -3.05972 -0.0937068 0.0612327 2.42473e-13 -2.07834e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1879 1880 4.49221 -0.258041 -0.202877 -0.00273225 0.090073 -0.0877443 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1830 1880 1.14433e-11 -3.05972 -0.0937068 0.0612327 2.42029e-13 -2.08278e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1880 1881 4.48686 -0.258054 -0.202395 -0.00273249 0.0899656 -0.0878544 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1831 1881 1.14255e-11 -3.05972 -0.0937068 0.0612327 2.42029e-13 -2.08722e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1881 1882 4.4815 -0.258067 -0.201912 -0.00273271 0.0898581 -0.0879644 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1832 1882 1.14184e-11 -3.05972 -0.0937068 0.0612327 2.41585e-13 -2.08722e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1882 1883 4.47613 -0.258078 -0.201429 -0.00273291 0.0897504 -0.0880743 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1833 1883 1.14007e-11 -3.05972 -0.0937068 0.0612327 2.41585e-13 -2.09166e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1883 1884 4.47076 -0.258088 -0.200947 -0.00273308 0.0896426 -0.088184 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1834 1884 1.13847e-11 -3.05972 -0.0937068 0.0612327 2.4114e-13 -2.0961e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1884 1885 4.46538 -0.258096 -0.200464 -0.00273322 0.0895347 -0.0882936 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1835 1885 1.13722e-11 -3.05972 -0.0937068 0.0612327 2.4114e-13 -2.0961e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1885 1886 4.45999 -0.258104 -0.199981 -0.00273335 0.0894267 -0.088403 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1836 1886 1.1358e-11 -3.05972 -0.0937068 0.0612327 2.40696e-13 -2.10054e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1886 1887 4.45459 -0.25811 -0.199498 -0.00273345 0.0893185 -0.0885123 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1837 1887 1.13438e-11 -3.05972 -0.0937068 0.0612327 2.40252e-13 -2.10498e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1887 1888 4.44919 -0.258115 -0.199015 -0.00273352 0.0892101 -0.0886215 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1838 1888 1.13305e-11 -3.05972 -0.0937068 0.0612327 2.40252e-13 -2.10498e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1888 1889 4.44378 -0.258119 -0.198533 -0.00273358 0.0891017 -0.0887306 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1839 1889 1.13189e-11 -3.05972 -0.0937068 0.0612327 2.39808e-13 -2.10942e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1889 1890 4.43837 -0.258122 -0.19805 -0.00273361 0.0889931 -0.0888395 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1840 1890 1.1303e-11 -3.05972 -0.0937068 0.0612327 2.39808e-13 -2.11386e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1890 1891 4.43295 -0.258123 -0.197567 -0.00273361 0.0888844 -0.0889482 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1841 1891 1.12941e-11 -3.05972 -0.0937068 0.0612327 2.39364e-13 -2.11386e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1891 1892 4.42752 -0.258124 -0.197084 -0.00273359 0.0887755 -0.0890569 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1842 1892 1.12763e-11 -3.05972 -0.0937068 0.0612327 2.39364e-13 -2.11831e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1892 1893 4.42209 -0.258123 -0.196601 -0.00273355 0.0886665 -0.0891654 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1843 1893 1.12621e-11 -3.05972 -0.0937068 0.0612327 2.3892e-13 -2.12275e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1893 1894 4.41664 -0.258121 -0.196118 -0.00273348 0.0885574 -0.0892738 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1844 1894 1.12443e-11 -3.05972 -0.0937068 0.0612327 2.38476e-13 -2.12275e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1894 1895 4.4112 -0.258118 -0.195636 -0.00273339 0.0884482 -0.089382 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1845 1895 1.12372e-11 -3.05972 -0.0937068 0.0612327 2.38476e-13 -2.12719e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1895 1896 4.40574 -0.258113 -0.195153 -0.00273328 0.0883388 -0.0894901 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1846 1896 1.12177e-11 -3.05972 -0.0937068 0.0612327 2.38032e-13 -2.13163e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1896 1897 4.40028 -0.258108 -0.19467 -0.00273314 0.0882293 -0.0895981 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1847 1897 1.12035e-11 -3.05972 -0.0937068 0.0612327 2.38032e-13 -2.13163e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1897 1898 4.39481 -0.258101 -0.194187 -0.00273298 0.0881196 -0.0897059 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1848 1898 1.1191e-11 -3.05972 -0.0937068 0.0612327 2.37588e-13 -2.13607e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1898 1899 4.38934 -0.258093 -0.193704 -0.00273279 0.0880099 -0.0898136 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1849 1899 1.11795e-11 -3.05972 -0.0937068 0.0612327 2.37144e-13 -2.14051e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1899 1900 4.38386 -0.258084 -0.193222 -0.00273259 0.0878999 -0.0899211 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1850 1900 1.11639e-11 -3.05972 -0.0937068 0.0612327 2.37144e-13 -2.14051e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1900 1901 4.37837 -0.258074 -0.192739 -0.00273235 0.0877899 -0.0900286 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1851 1901 1.11502e-11 -3.05972 -0.0937068 0.0612327 2.367e-13 -2.14495e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1901 1902 4.37288 -0.258062 -0.192256 -0.0027321 0.0876797 -0.0901359 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1852 1902 1.11342e-11 -3.05972 -0.0937068 0.0612327 2.367e-13 -2.14939e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1902 1903 4.36738 -0.25805 -0.191774 -0.00273182 0.0875694 -0.090243 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1853 1903 1.11218e-11 -3.05972 -0.0937068 0.0612327 2.36255e-13 -2.14939e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1903 1904 4.36187 -0.258036 -0.191291 -0.00273151 0.087459 -0.09035 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1854 1904 1.11058e-11 -3.05972 -0.0937068 0.0612327 2.36255e-13 -2.15383e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1904 1905 4.35636 -0.258021 -0.190808 -0.00273119 0.0873484 -0.0904569 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1855 1905 1.10951e-11 -3.05972 -0.0937068 0.0612327 2.35811e-13 -2.15827e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1905 1906 4.35084 -0.258005 -0.190326 -0.00273084 0.0872378 -0.0905636 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1856 1906 1.10809e-11 -3.05972 -0.0937068 0.0612327 2.35367e-13 -2.15827e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1906 1907 4.34531 -0.257988 -0.189843 -0.00273046 0.0871269 -0.0906702 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1857 1907 1.10632e-11 -3.05972 -0.0937068 0.0612327 2.35367e-13 -2.16271e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1907 1908 4.33978 -0.257969 -0.189361 -0.00273006 0.087016 -0.0907767 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1858 1908 1.10507e-11 -3.05972 -0.0937068 0.0612327 2.34923e-13 -2.16716e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1908 1909 4.33424 -0.257949 -0.188878 -0.00272964 0.0869049 -0.090883 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1859 1909 1.10401e-11 -3.05972 -0.0937068 0.0612327 2.34479e-13 -2.16716e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1909 1910 4.32869 -0.257928 -0.188396 -0.00272919 0.0867937 -0.0909892 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1860 1910 1.10205e-11 -3.05972 -0.0937068 0.0612327 2.34479e-13 -2.1716e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1910 1911 4.32314 -0.257906 -0.187914 -0.00272872 0.0866823 -0.0910953 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1861 1911 1.1009e-11 -3.05972 -0.0937068 0.0612327 2.34035e-13 -2.17604e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1911 1912 4.31758 -0.257883 -0.187431 -0.00272823 0.0865709 -0.0912012 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1862 1912 1.09948e-11 -3.05972 -0.0937068 0.0612327 2.34035e-13 -2.17604e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1912 1913 4.31201 -0.257859 -0.186949 -0.00272771 0.0864593 -0.0913069 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1863 1913 1.09805e-11 -3.05972 -0.0937068 0.0612327 2.33591e-13 -2.18048e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1913 1914 4.30644 -0.257833 -0.186467 -0.00272717 0.0863475 -0.0914126 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1864 1914 1.09663e-11 -3.05972 -0.0937068 0.0612327 2.33147e-13 -2.18048e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1914 1915 4.30086 -0.257806 -0.185985 -0.00272661 0.0862357 -0.0915181 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1865 1915 1.0953e-11 -3.05972 -0.0937068 0.0612327 2.33147e-13 -2.18492e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1915 1916 4.29528 -0.257778 -0.185503 -0.00272602 0.0861237 -0.0916234 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1866 1916 1.09353e-11 -3.05972 -0.0937068 0.0612327 2.32703e-13 -2.18936e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1916 1917 4.28969 -0.257749 -0.185021 -0.00272541 0.0860116 -0.0917287 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1867 1917 1.09228e-11 -3.05972 -0.0937068 0.0612327 2.32703e-13 -2.18936e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1917 1918 4.28409 -0.257719 -0.184539 -0.00272477 0.0858993 -0.0918337 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1868 1918 1.09139e-11 -3.05972 -0.0937068 0.0612327 2.32259e-13 -2.1938e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1918 1919 4.27849 -0.257687 -0.184057 -0.00272411 0.085787 -0.0919387 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1869 1919 1.08962e-11 -3.05972 -0.0937068 0.0612327 2.31815e-13 -2.19824e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1919 1920 4.27287 -0.257654 -0.183575 -0.00272343 0.0856745 -0.0920435 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1870 1920 1.08749e-11 -3.05972 -0.0937068 0.0612327 2.31815e-13 -2.19824e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1920 1921 4.26726 -0.257621 -0.183094 -0.00272272 0.0855618 -0.0921481 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1871 1921 1.08678e-11 -3.05972 -0.0937068 0.0612327 2.3137e-13 -2.20268e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1921 1922 4.26163 -0.257585 -0.182612 -0.00272199 0.0854491 -0.0922527 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1872 1922 1.08535e-11 -3.05972 -0.0937068 0.0612327 2.30926e-13 -2.20268e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1922 1923 4.256 -0.257549 -0.182131 -0.00272124 0.0853362 -0.0923571 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1873 1923 1.08411e-11 -3.05972 -0.0937068 0.0612327 2.30926e-13 -2.20712e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1923 1924 4.25037 -0.257512 -0.181649 -0.00272046 0.0852232 -0.0924613 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1874 1924 1.08225e-11 -3.05972 -0.0937068 0.0612327 2.30482e-13 -2.21156e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1924 1925 4.24472 -0.257473 -0.181168 -0.00271966 0.0851101 -0.0925654 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1875 1925 1.08089e-11 -3.05972 -0.0937068 0.0612327 2.30482e-13 -2.21156e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1925 1926 4.23908 -0.257433 -0.180687 -0.00271884 0.0849968 -0.0926694 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1876 1926 1.07949e-11 -3.05972 -0.0937068 0.0612327 2.30038e-13 -2.21601e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1926 1927 4.23342 -0.257392 -0.180206 -0.00271799 0.0848834 -0.0927732 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1877 1927 1.07789e-11 -3.05972 -0.0937068 0.0612327 2.30038e-13 -2.22045e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1927 1928 4.22776 -0.25735 -0.179725 -0.00271712 0.0847699 -0.0928769 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1878 1928 1.07647e-11 -3.05972 -0.0937068 0.0612327 2.29594e-13 -2.22045e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1928 1929 4.22209 -0.257307 -0.179244 -0.00271622 0.0846563 -0.0929804 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1879 1929 1.07487e-11 -3.05972 -0.0937068 0.0612327 2.2915e-13 -2.22489e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1929 1930 4.21642 -0.257263 -0.178763 -0.0027153 0.0845425 -0.0930838 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1880 1930 1.07363e-11 -3.05972 -0.0937068 0.0612327 2.2915e-13 -2.22933e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1930 1931 4.21074 -0.257217 -0.178282 -0.00271436 0.0844286 -0.0931871 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1881 1931 1.07256e-11 -3.05972 -0.0937068 0.0612327 2.28706e-13 -2.22933e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1931 1932 4.20505 -0.25717 -0.177802 -0.00271339 0.0843146 -0.0932902 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1882 1932 1.07043e-11 -3.05972 -0.0937068 0.0612327 2.28262e-13 -2.23377e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1932 1933 4.19936 -0.257122 -0.177321 -0.0027124 0.0842004 -0.0933932 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1883 1933 1.06972e-11 -3.05972 -0.0937068 0.0612327 2.28262e-13 -2.23821e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1933 1934 4.19366 -0.257073 -0.176841 -0.00271139 0.0840862 -0.093496 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1884 1934 1.06777e-11 -3.05972 -0.0937068 0.0612327 2.27818e-13 -2.23821e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1934 1935 4.18795 -0.257022 -0.176361 -0.00271035 0.0839718 -0.0935987 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1885 1935 1.06635e-11 -3.05972 -0.0937068 0.0612327 2.27818e-13 -2.24265e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1935 1936 4.18224 -0.256971 -0.175881 -0.00270929 0.0838572 -0.0937013 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1886 1936 1.06484e-11 -3.05972 -0.0937068 0.0612327 2.27374e-13 -2.24265e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1936 1937 4.17652 -0.256918 -0.175401 -0.0027082 0.0837426 -0.0938037 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1887 1937 1.0635e-11 -3.05972 -0.0937068 0.0612327 2.2693e-13 -2.24709e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1937 1938 4.17079 -0.256864 -0.174921 -0.0027071 0.0836278 -0.093906 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1888 1938 1.06204e-11 -3.05972 -0.0937068 0.0612327 2.2693e-13 -2.25153e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1938 1939 4.16506 -0.256809 -0.174441 -0.00270597 0.0835129 -0.0940081 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1889 1939 1.0604e-11 -3.05972 -0.0937068 0.0612327 2.26485e-13 -2.25153e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1939 1940 4.15933 -0.256753 -0.173962 -0.00270481 0.0833979 -0.0941101 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1890 1940 1.05924e-11 -3.05972 -0.0937068 0.0612327 2.26485e-13 -2.25597e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1940 1941 4.15358 -0.256695 -0.173482 -0.00270363 0.0832828 -0.0942119 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1891 1941 1.05747e-11 -3.05972 -0.0937068 0.0612327 2.26041e-13 -2.25597e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1941 1942 4.14783 -0.256637 -0.173003 -0.00270243 0.0831675 -0.0943136 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1892 1942 1.05587e-11 -3.05972 -0.0937068 0.0612327 2.25597e-13 -2.26041e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1942 1943 4.14208 -0.256577 -0.172524 -0.0027012 0.0830521 -0.0944152 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1893 1943 1.05409e-11 -3.05972 -0.0937068 0.0612327 2.25597e-13 -2.26485e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1943 1944 4.13632 -0.256516 -0.172045 -0.00269995 0.0829366 -0.0945166 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1894 1944 1.05373e-11 -3.05972 -0.0937068 0.0612327 2.25153e-13 -2.26485e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1944 1945 4.13055 -0.256454 -0.171566 -0.00269868 0.082821 -0.0946179 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1895 1945 1.05143e-11 -3.05972 -0.0937068 0.0612327 2.24709e-13 -2.2693e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1945 1946 4.12477 -0.256391 -0.171088 -0.00269739 0.0827052 -0.094719 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1896 1946 1.05054e-11 -3.05972 -0.0937068 0.0612327 2.24709e-13 -2.27374e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1946 1947 4.11899 -0.256326 -0.170609 -0.00269607 0.0825893 -0.09482 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1897 1947 1.04894e-11 -3.05972 -0.0937068 0.0612327 2.24265e-13 -2.27374e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1947 1948 4.1132 -0.256261 -0.170131 -0.00269472 0.0824733 -0.0949209 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1898 1948 1.04716e-11 -3.05972 -0.0937068 0.0612327 2.23821e-13 -2.27818e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1948 1949 4.10741 -0.256194 -0.169652 -0.00269336 0.0823572 -0.0950216 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1899 1949 1.04583e-11 -3.05972 -0.0937068 0.0612327 2.23821e-13 -2.27818e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1949 1950 4.10161 -0.256126 -0.169174 -0.00269197 0.0822409 -0.0951221 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1900 1950 1.04437e-11 -3.05972 -0.0937068 0.0612327 2.23377e-13 -2.28262e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1950 1951 4.09581 -0.256057 -0.168697 -0.00269055 0.0821245 -0.0952226 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1901 1951 1.0429e-11 -3.05972 -0.0937068 0.0612327 2.23377e-13 -2.28706e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1951 1952 4.09 -0.255986 -0.168219 -0.00268912 0.082008 -0.0953228 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1902 1952 1.04157e-11 -3.05972 -0.0937068 0.0612327 2.22933e-13 -2.28706e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1952 1953 4.08418 -0.255915 -0.167741 -0.00268766 0.0818914 -0.095423 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1903 1953 1.0397e-11 -3.05972 -0.0937068 0.0612327 2.22933e-13 -2.2915e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1953 1954 4.07835 -0.255842 -0.167264 -0.00268617 0.0817747 -0.0955229 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1904 1954 1.03881e-11 -3.05972 -0.0937068 0.0612327 2.22489e-13 -2.29594e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1954 1955 4.07252 -0.255768 -0.166787 -0.00268466 0.0816578 -0.0956228 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1905 1955 1.03668e-11 -3.05972 -0.0937068 0.0612327 2.22045e-13 -2.29594e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1955 1956 4.06669 -0.255693 -0.16631 -0.00268313 0.0815408 -0.0957225 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1906 1956 1.03562e-11 -3.05972 -0.0937068 0.0612327 2.22045e-13 -2.30038e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1956 1957 4.06085 -0.255617 -0.165833 -0.00268158 0.0814237 -0.095822 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1907 1957 1.03419e-11 -3.05972 -0.0937068 0.0612327 2.21601e-13 -2.30038e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1957 1958 4.055 -0.25554 -0.165356 -0.00268 0.0813065 -0.0959214 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1908 1958 1.03242e-11 -3.05972 -0.0937068 0.0612327 2.21156e-13 -2.30482e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1958 1959 4.04914 -0.255461 -0.16488 -0.0026784 0.0811891 -0.0960207 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1909 1959 1.031e-11 -3.05972 -0.0937068 0.0612327 2.21156e-13 -2.30926e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1959 1960 4.04328 -0.255382 -0.164404 -0.00267678 0.0810716 -0.0961198 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1910 1960 1.02958e-11 -3.05972 -0.0937068 0.0612327 2.20712e-13 -2.30926e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1960 1961 4.03742 -0.255301 -0.163928 -0.00267513 0.0809541 -0.0962188 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1911 1961 1.02807e-11 -3.05972 -0.0937068 0.0612327 2.20268e-13 -2.3137e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1961 1962 4.03154 -0.255219 -0.163452 -0.00267346 0.0808363 -0.0963176 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1912 1962 1.02642e-11 -3.05972 -0.0937068 0.0612327 2.20268e-13 -2.3137e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1962 1963 4.02567 -0.255136 -0.162976 -0.00267176 0.0807185 -0.0964163 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1913 1963 1.025e-11 -3.05972 -0.0937068 0.0612327 2.19824e-13 -2.31815e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1963 1964 4.01978 -0.255051 -0.162501 -0.00267005 0.0806006 -0.0965148 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1914 1964 1.02354e-11 -3.05972 -0.0937068 0.0612327 2.1938e-13 -2.32259e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1964 1965 4.01389 -0.254966 -0.162026 -0.0026683 0.0804825 -0.0966132 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1915 1965 1.02212e-11 -3.05972 -0.0937068 0.0612327 2.1938e-13 -2.32259e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1965 1966 4.00799 -0.254879 -0.161551 -0.00266654 0.0803643 -0.0967115 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1916 1966 1.02069e-11 -3.05972 -0.0937068 0.0612327 2.18936e-13 -2.32703e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1966 1967 4.00209 -0.254791 -0.161076 -0.00266475 0.080246 -0.0968095 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1917 1967 1.01874e-11 -3.05972 -0.0937068 0.0612327 2.18492e-13 -2.32703e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1967 1968 3.99618 -0.254702 -0.160601 -0.00266294 0.0801275 -0.0969075 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1918 1968 1.0175e-11 -3.05972 -0.0937068 0.0612327 2.18492e-13 -2.33147e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1968 1969 3.99027 -0.254612 -0.160127 -0.00266111 0.080009 -0.0970053 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1919 1969 1.01625e-11 -3.05972 -0.0937068 0.0612327 2.18048e-13 -2.33591e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1969 1970 3.98435 -0.254521 -0.159653 -0.00265925 0.0798903 -0.097103 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1920 1970 1.0143e-11 -3.05972 -0.0937068 0.0612327 2.18048e-13 -2.33591e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1970 1971 3.97842 -0.254428 -0.159179 -0.00265737 0.0797715 -0.0972005 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1921 1971 1.01306e-11 -3.05972 -0.0937068 0.0612327 2.17604e-13 -2.34035e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1971 1972 3.97249 -0.254335 -0.158705 -0.00265547 0.0796526 -0.0972978 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1922 1972 1.01128e-11 -3.05972 -0.0937068 0.0612327 2.1716e-13 -2.34479e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1972 1973 3.96655 -0.25424 -0.158232 -0.00265354 0.0795336 -0.0973951 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1923 1973 1.00959e-11 -3.05972 -0.0937068 0.0612327 2.1716e-13 -2.34479e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1973 1974 3.96061 -0.254144 -0.157759 -0.00265159 0.0794144 -0.0974921 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1924 1974 1.00857e-11 -3.05972 -0.0937068 0.0612327 2.16716e-13 -2.34923e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1974 1975 3.95466 -0.254047 -0.157286 -0.00264962 0.0792952 -0.0975891 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1925 1975 1.00687e-11 -3.05972 -0.0937068 0.0612327 2.16271e-13 -2.34923e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1975 1976 3.9487 -0.253949 -0.156813 -0.00264762 0.0791758 -0.0976858 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1926 1976 1.00528e-11 -3.05972 -0.0937068 0.0612327 2.16271e-13 -2.35367e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1976 1977 3.94274 -0.253849 -0.156341 -0.0026456 0.0790563 -0.0977825 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1927 1977 1.00409e-11 -3.05972 -0.0937068 0.0612327 2.15827e-13 -2.35367e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1977 1978 3.93677 -0.253749 -0.155868 -0.00264356 0.0789367 -0.0978789 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1928 1978 1.0024e-11 -3.05972 -0.0937068 0.0612327 2.15383e-13 -2.35811e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1978 1979 3.93079 -0.253647 -0.155396 -0.00264149 0.0788169 -0.0979753 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1929 1979 1.00098e-11 -3.05972 -0.0937068 0.0612327 2.15383e-13 -2.36255e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1979 1980 3.92481 -0.253544 -0.154925 -0.0026394 0.0786971 -0.0980715 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1930 1980 9.98845e-12 -3.05972 -0.0937068 0.0612327 2.14939e-13 -2.36255e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1980 1981 3.91883 -0.25344 -0.154453 -0.00263729 0.0785771 -0.0981675 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1931 1981 9.9778e-12 -3.05972 -0.0937068 0.0612327 2.14939e-13 -2.367e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1981 1982 3.91284 -0.253335 -0.153982 -0.00263515 0.078457 -0.0982634 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1932 1982 9.96359e-12 -3.05972 -0.0937068 0.0612327 2.14495e-13 -2.367e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1982 1983 3.90684 -0.253228 -0.153511 -0.00263299 0.0783368 -0.0983591 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1933 1983 9.94937e-12 -3.05972 -0.0937068 0.0612327 2.14051e-13 -2.37144e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1983 1984 3.90084 -0.253121 -0.15304 -0.00263081 0.0782165 -0.0984547 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1934 1984 9.93161e-12 -3.05972 -0.0937068 0.0612327 2.14051e-13 -2.37588e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1984 1985 3.89483 -0.253012 -0.15257 -0.00262861 0.0780961 -0.0985502 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1935 1985 9.91562e-12 -3.05972 -0.0937068 0.0612327 2.13607e-13 -2.37588e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1985 1986 3.88881 -0.252902 -0.152099 -0.00262638 0.0779755 -0.0986455 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1936 1986 9.90141e-12 -3.05972 -0.0937068 0.0612327 2.13163e-13 -2.38032e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1986 1987 3.88279 -0.252791 -0.15163 -0.00262413 0.0778549 -0.0987406 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1937 1987 9.8852e-12 -3.05972 -0.0937068 0.0612327 2.13163e-13 -2.38032e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1987 1988 3.87676 -0.252679 -0.15116 -0.00262186 0.0777341 -0.0988356 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1938 1988 9.86988e-12 -3.05972 -0.0937068 0.0612327 2.12719e-13 -2.38476e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1988 1989 3.87073 -0.252566 -0.150691 -0.00261956 0.0776132 -0.0989305 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1939 1989 9.85523e-12 -3.05972 -0.0937068 0.0612327 2.12275e-13 -2.3892e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1989 1990 3.86469 -0.252452 -0.150221 -0.00261724 0.0774922 -0.0990252 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1940 1990 9.84102e-12 -3.05972 -0.0937068 0.0612327 2.12275e-13 -2.3892e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1990 1991 3.85865 -0.252336 -0.149753 -0.0026149 0.077371 -0.0991197 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1941 1991 9.82503e-12 -3.05972 -0.0937068 0.0612327 2.11831e-13 -2.39364e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1991 1992 3.8526 -0.252219 -0.149284 -0.00261253 0.0772498 -0.0992141 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1942 1992 9.81082e-12 -3.05972 -0.0937068 0.0612327 2.11386e-13 -2.39364e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1992 1993 3.84654 -0.252101 -0.148816 -0.00261014 0.0771284 -0.0993084 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1943 1993 9.79838e-12 -3.05972 -0.0937068 0.0612327 2.11386e-13 -2.39808e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1993 1994 3.84048 -0.251982 -0.148348 -0.00260773 0.0770069 -0.0994025 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1944 1994 9.77529e-12 -3.05972 -0.0937068 0.0612327 2.10942e-13 -2.39808e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1994 1995 3.83441 -0.251862 -0.14788 -0.0026053 0.0768853 -0.0994964 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1945 1995 9.76108e-12 -3.05972 -0.0937068 0.0612327 2.10498e-13 -2.40252e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1995 1996 3.82834 -0.251741 -0.147413 -0.00260284 0.0767636 -0.0995902 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1946 1996 9.74687e-12 -3.05972 -0.0937068 0.0612327 2.10498e-13 -2.40696e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1996 1997 3.82226 -0.251619 -0.146946 -0.00260036 0.0766418 -0.0996839 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1947 1997 9.73266e-12 -3.05972 -0.0937068 0.0612327 2.10054e-13 -2.40696e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1997 1998 3.81618 -0.251495 -0.146479 -0.00259785 0.0765199 -0.0997774 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1948 1998 9.71667e-12 -3.05972 -0.0937068 0.0612327 2.0961e-13 -2.4114e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1998 1999 3.81009 -0.25137 -0.146013 -0.00259533 0.0763978 -0.0998707 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1949 1999 9.6998e-12 -3.05972 -0.0937068 0.0612327 2.0961e-13 -2.4114e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1999 2000 3.80399 -0.251244 -0.145547 -0.00259278 0.0762757 -0.0999639 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1950 2000 9.68433e-12 -3.05972 -0.0937068 0.0612327 2.09166e-13 -2.41585e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2000 2001 3.79789 -0.251117 -0.145081 -0.00259021 0.0761534 -0.100057 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1951 2001 9.66782e-12 -3.05972 -0.0937068 0.0612327 2.08722e-13 -2.41585e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2001 2002 3.79178 -0.250989 -0.144615 -0.00258761 0.076031 -0.10015 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1952 2002 9.65272e-12 -3.05972 -0.0937068 0.0612327 2.08722e-13 -2.42029e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2002 2003 3.78567 -0.25086 -0.14415 -0.00258499 0.0759085 -0.100243 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1953 2003 9.63674e-12 -3.05972 -0.0937068 0.0612327 2.08278e-13 -2.42473e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2003 2004 3.77955 -0.25073 -0.143685 -0.00258235 0.0757859 -0.100335 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1954 2004 9.62252e-12 -3.05972 -0.0937068 0.0612327 2.07834e-13 -2.42473e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2004 2005 3.77343 -0.250598 -0.143221 -0.00257969 0.0756632 -0.100428 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1955 2005 9.60476e-12 -3.05972 -0.0937068 0.0612327 2.0739e-13 -2.42917e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2005 2006 3.7673 -0.250465 -0.142756 -0.00257701 0.0755403 -0.10052 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1956 2006 9.5941e-12 -3.05972 -0.0937068 0.0612327 2.0739e-13 -2.42917e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2006 2007 3.76116 -0.250331 -0.142292 -0.0025743 0.0754174 -0.100612 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1957 2007 9.57634e-12 -3.05972 -0.0937068 0.0612327 2.06946e-13 -2.43361e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2007 2008 3.75502 -0.250196 -0.141829 -0.00257157 0.0752943 -0.100704 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1958 2008 9.5568e-12 -3.05972 -0.0937068 0.0612327 2.06946e-13 -2.43361e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2008 2009 3.74887 -0.25006 -0.141366 -0.00256881 0.0751712 -0.100796 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1959 2009 9.54081e-12 -3.05972 -0.0937068 0.0612327 2.06501e-13 -2.43805e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2009 2010 3.74272 -0.249923 -0.140903 -0.00256604 0.0750479 -0.100888 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1960 2010 9.5266e-12 -3.05972 -0.0937068 0.0612327 2.06057e-13 -2.44249e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2010 2011 3.73656 -0.249785 -0.14044 -0.00256324 0.0749245 -0.100979 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1961 2011 9.51239e-12 -3.05972 -0.0937068 0.0612327 2.06057e-13 -2.44249e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2011 2012 3.7304 -0.249645 -0.139978 -0.00256041 0.074801 -0.101071 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1962 2012 9.4964e-12 -3.05972 -0.0937068 0.0612327 2.05613e-13 -2.44693e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2012 2013 3.72423 -0.249504 -0.139516 -0.00255757 0.0746773 -0.101162 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1963 2013 9.48108e-12 -3.05972 -0.0937068 0.0612327 2.05169e-13 -2.44693e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2013 2014 3.71805 -0.249363 -0.139054 -0.0025547 0.0745536 -0.101253 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1964 2014 9.46532e-12 -3.05972 -0.0937068 0.0612327 2.04725e-13 -2.45137e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2014 2015 3.71187 -0.24922 -0.138593 -0.00255181 0.0744298 -0.101344 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1965 2015 9.45022e-12 -3.05972 -0.0937068 0.0612327 2.04725e-13 -2.45137e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2015 2016 3.70569 -0.249076 -0.138132 -0.0025489 0.0743058 -0.101435 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1966 2016 9.43423e-12 -3.05972 -0.0937068 0.0612327 2.04281e-13 -2.45581e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2016 2017 3.69949 -0.248931 -0.137672 -0.00254597 0.0741817 -0.101525 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1967 2017 9.41824e-12 -3.05972 -0.0937068 0.0612327 2.04281e-13 -2.46025e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2017 2018 3.6933 -0.248784 -0.137212 -0.00254301 0.0740576 -0.101616 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1968 2018 9.40226e-12 -3.05972 -0.0937068 0.0612327 2.03837e-13 -2.46025e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2018 2019 3.68709 -0.248637 -0.136752 -0.00254003 0.0739333 -0.101706 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1969 2019 9.38449e-12 -3.05972 -0.0937068 0.0612327 2.03393e-13 -2.4647e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2019 2020 3.68089 -0.248488 -0.136292 -0.00253703 0.0738089 -0.101796 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1970 2020 9.37206e-12 -3.05972 -0.0937068 0.0612327 2.02949e-13 -2.4647e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2020 2021 3.67467 -0.248339 -0.135833 -0.002534 0.0736844 -0.101886 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1971 2021 9.3543e-12 -3.05972 -0.0937068 0.0612327 2.02949e-13 -2.46914e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2021 2022 3.66845 -0.248188 -0.135375 -0.00253095 0.0735598 -0.101976 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1972 2022 9.34008e-12 -3.05972 -0.0937068 0.0612327 2.02505e-13 -2.46914e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2022 2023 3.66223 -0.248036 -0.134916 -0.00252788 0.073435 -0.102066 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1973 2023 9.32321e-12 -3.05972 -0.0937068 0.0612327 2.02061e-13 -2.47358e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2023 2024 3.656 -0.247883 -0.134458 -0.00252479 0.0733102 -0.102155 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1974 2024 9.30589e-12 -3.05972 -0.0937068 0.0612327 2.02061e-13 -2.47802e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2024 2025 3.64976 -0.247729 -0.134001 -0.00252168 0.0731853 -0.102245 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1975 2025 9.29086e-12 -3.05972 -0.0937068 0.0612327 2.01617e-13 -2.47802e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2025 2026 3.64352 -0.247573 -0.133544 -0.00251854 0.0730602 -0.102334 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1976 2026 9.27525e-12 -3.05972 -0.0937068 0.0612327 2.01172e-13 -2.48246e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2026 2027 3.63727 -0.247417 -0.133087 -0.00251538 0.0729351 -0.102423 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1977 2027 9.25748e-12 -3.05972 -0.0937068 0.0612327 2.01172e-13 -2.48246e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2027 2028 3.63102 -0.24726 -0.13263 -0.0025122 0.0728098 -0.102512 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1978 2028 9.24061e-12 -3.05972 -0.0937068 0.0612327 2.00728e-13 -2.4869e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2028 2029 3.62476 -0.247101 -0.132174 -0.002509 0.0726844 -0.102601 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1979 2029 9.2264e-12 -3.05972 -0.0937068 0.0612327 2.00284e-13 -2.4869e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2029 2030 3.6185 -0.246941 -0.131719 -0.00250577 0.0725589 -0.102689 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1980 2030 9.21752e-12 -3.05972 -0.0937068 0.0612327 2.00284e-13 -2.49134e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2030 2031 3.61223 -0.24678 -0.131264 -0.00250252 0.0724333 -0.102778 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1981 2031 9.19265e-12 -3.05972 -0.0937068 0.0612327 1.9984e-13 -2.49134e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2031 2032 3.60596 -0.246618 -0.130809 -0.00249925 0.0723076 -0.102866 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1982 2032 9.17666e-12 -3.05972 -0.0937068 0.0612327 1.99396e-13 -2.49578e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2032 2033 3.59968 -0.246455 -0.130354 -0.00249596 0.0721818 -0.102954 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1983 2033 9.16067e-12 -3.05972 -0.0937068 0.0612327 1.98952e-13 -2.49578e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2033 2034 3.59339 -0.246291 -0.1299 -0.00249264 0.0720559 -0.103042 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1984 2034 9.14646e-12 -3.05972 -0.0937068 0.0612327 1.98952e-13 -2.50022e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2034 2035 3.5871 -0.246126 -0.129447 -0.0024893 0.0719299 -0.10313 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1985 2035 9.13225e-12 -3.05972 -0.0937068 0.0612327 1.98508e-13 -2.50466e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2035 2036 3.58081 -0.245959 -0.128993 -0.00248594 0.0718038 -0.103218 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1986 2036 9.11538e-12 -3.05972 -0.0937068 0.0612327 1.98064e-13 -2.50466e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2036 2037 3.57451 -0.245792 -0.12854 -0.00248256 0.0716775 -0.103305 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1987 2037 9.09872e-12 -3.05972 -0.0937068 0.0612327 1.98064e-13 -2.5091e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2037 2038 3.5682 -0.245623 -0.128088 -0.00247916 0.0715512 -0.103393 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1988 2038 9.08296e-12 -3.05972 -0.0937068 0.0612327 1.9762e-13 -2.5091e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2038 2039 3.56189 -0.245453 -0.127636 -0.00247573 0.0714247 -0.10348 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1989 2039 9.06653e-12 -3.05972 -0.0937068 0.0612327 1.97176e-13 -2.51354e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2039 2040 3.55557 -0.245282 -0.127184 -0.00247228 0.0712982 -0.103567 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1990 2040 9.04876e-12 -3.05972 -0.0937068 0.0612327 1.97176e-13 -2.51354e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2040 2041 3.54925 -0.245111 -0.126733 -0.00246881 0.0711715 -0.103654 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1991 2041 9.03277e-12 -3.05972 -0.0937068 0.0612327 1.96732e-13 -2.51799e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2041 2042 3.54292 -0.244937 -0.126282 -0.00246532 0.0710448 -0.103741 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1992 2042 9.02212e-12 -3.05972 -0.0937068 0.0612327 1.96287e-13 -2.52243e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2042 2043 3.53659 -0.244763 -0.125832 -0.0024618 0.0709179 -0.103827 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1993 2043 9.00258e-12 -3.05972 -0.0937068 0.0612327 1.96287e-13 -2.52243e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2043 2044 3.53025 -0.244588 -0.125382 -0.00245827 0.0707909 -0.103914 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1994 2044 8.98659e-12 -3.05972 -0.0937068 0.0612327 1.95843e-13 -2.52243e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2044 2045 3.52391 -0.244412 -0.124933 -0.00245471 0.0706638 -0.104 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1995 2045 8.96883e-12 -3.05972 -0.0937068 0.0612327 1.95399e-13 -2.52687e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2045 2046 3.51756 -0.244234 -0.124484 -0.00245113 0.0705366 -0.104086 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1996 2046 8.95284e-12 -3.05972 -0.0937068 0.0612327 1.95399e-13 -2.53131e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2046 2047 3.51121 -0.244056 -0.124035 -0.00244753 0.0704094 -0.104172 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1997 2047 8.93685e-12 -3.05972 -0.0937068 0.0612327 1.94955e-13 -2.53131e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2047 2048 3.50485 -0.243876 -0.123587 -0.0024439 0.070282 -0.104258 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1998 2048 8.92264e-12 -3.05972 -0.0937068 0.0612327 1.94511e-13 -2.53575e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2048 2049 3.49848 -0.243695 -0.123139 -0.00244026 0.0701545 -0.104344 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 1999 2049 8.90443e-12 -3.05972 -0.0937068 0.0612327 1.94067e-13 -2.53575e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2049 2050 3.49211 -0.243513 -0.122692 -0.00243659 0.0700269 -0.104429 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2000 2050 8.88867e-12 -3.05972 -0.0937068 0.0612327 1.94067e-13 -2.54019e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2050 2051 3.48574 -0.24333 -0.122245 -0.0024329 0.0698991 -0.104515 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2001 2051 8.8729e-12 -3.05972 -0.0937068 0.0612327 1.93623e-13 -2.54019e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2051 2052 3.47936 -0.243146 -0.121799 -0.00242919 0.0697713 -0.1046 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2002 2052 8.85514e-12 -3.05972 -0.0937068 0.0612327 1.93179e-13 -2.54463e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2052 2053 3.47297 -0.242961 -0.121353 -0.00242545 0.0696434 -0.104685 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2003 2053 8.8427e-12 -3.05972 -0.0937068 0.0612327 1.93179e-13 -2.54907e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2053 2054 3.46658 -0.242775 -0.120907 -0.0024217 0.0695154 -0.10477 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2004 2054 8.82139e-12 -3.05972 -0.0937068 0.0612327 1.92735e-13 -2.54907e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2054 2055 3.46018 -0.242587 -0.120462 -0.00241792 0.0693873 -0.104854 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2005 2055 8.81073e-12 -3.05972 -0.0937068 0.0612327 1.92291e-13 -2.54907e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2055 2056 3.45378 -0.242399 -0.120018 -0.00241412 0.069259 -0.104939 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2006 2056 8.78586e-12 -3.05972 -0.0937068 0.0612327 1.92291e-13 -2.55351e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2056 2057 3.44738 -0.24221 -0.119574 -0.0024103 0.0691307 -0.105023 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2007 2057 8.7752e-12 -3.05972 -0.0937068 0.0612327 1.91847e-13 -2.55351e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2057 2058 3.44097 -0.242019 -0.11913 -0.00240646 0.0690023 -0.105108 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2008 2058 8.75922e-12 -3.05972 -0.0937068 0.0612327 1.91402e-13 -2.55795e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2058 2059 3.43455 -0.241827 -0.118687 -0.00240259 0.0688737 -0.105192 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2009 2059 8.745e-12 -3.05972 -0.0937068 0.0612327 1.90958e-13 -2.55795e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2059 2060 3.42813 -0.241634 -0.118244 -0.00239871 0.0687451 -0.105276 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2010 2060 8.72724e-12 -3.05972 -0.0937068 0.0612327 1.90958e-13 -2.56239e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2060 2061 3.4217 -0.241441 -0.117802 -0.0023948 0.0686164 -0.105359 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2011 2061 8.70859e-12 -3.05972 -0.0937068 0.0612327 1.90514e-13 -2.56684e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2061 2062 3.41527 -0.241246 -0.11736 -0.00239087 0.0684875 -0.105443 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2012 2062 8.69282e-12 -3.05972 -0.0937068 0.0612327 1.9007e-13 -2.56684e-13 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2062 2063 3.40883 -0.24105 -0.116919 -0.00238692 0.0683586 -0.105526 10 0 0 0 0 0 10 0 0 0 0 10 0 0 0 100 0 0 100 0 25 +EDGE3 2013 2063 8.67595e-12 -3.05972 -0.0937068 0.0612327 1.9007e-13 -2.57128e-13 10 0 0 0 0 0 10 0 0 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6.6863 -0.107225 -0.0174115 0.0219284 0.149327 +EDGE3 1908 1909 -0.529598 6.57438 -0.165611 0.037633 0.0251834 0.122439 +EDGE3 1909 1910 -0.550003 6.49588 -0.131708 0.0347732 0.00820918 0.146815 +EDGE3 1910 1911 -0.604966 6.55066 -0.0576862 -0.0300207 0.00607614 0.0536557 +EDGE3 1911 1912 -0.519194 6.48382 -0.000380502 0.022061 0.00674755 0.176131 +EDGE3 1912 1913 -0.58462 6.54622 0.112154 0.0235749 0.0118063 0.139007 +EDGE3 1913 1914 -0.617625 6.49059 -0.148337 0.00535814 -0.00172524 0.129453 +EDGE3 1914 1915 -0.479683 6.62715 -0.080135 -0.0178309 -0.00365513 0.0875597 +EDGE3 1915 1916 -0.58749 6.70822 0.0847443 -0.0305741 0.00754548 0.129222 +EDGE3 1916 1917 -0.451042 6.48218 -0.0207604 0.018108 0.0189387 0.117504 +EDGE3 1917 1918 -0.391254 6.60939 -0.173592 0.0496346 0.0202329 0.0947357 +EDGE3 1918 1919 -0.392004 6.42854 -0.047911 0.00284509 -0.0178553 0.12102 +EDGE3 1919 1920 -0.3076 6.52029 -0.00805391 0.00960978 -0.00877807 0.111829 +EDGE3 1920 1921 -0.482137 6.50725 0.0133788 0.0128875 -0.0255452 0.145842 +EDGE3 1921 1922 -0.422145 6.36038 -0.146317 -0.0380725 -0.00340331 0.128358 +EDGE3 1922 1923 -0.628684 6.32894 -0.155959 -0.000589319 -0.00927705 0.090458 +EDGE3 1923 1924 -0.489771 6.38105 -0.0216703 -0.0315264 0.00371578 0.140759 +EDGE3 1924 1925 -0.472106 6.34225 -0.20346 0.00230964 0.018118 0.1366 +EDGE3 1925 1926 -0.516094 6.42739 -0.129203 0.0551955 -0.0316826 0.125383 +EDGE3 1926 1927 -0.313683 6.38208 -0.050251 -0.0169743 0.0259984 0.0812736 +EDGE3 1927 1928 -0.477272 6.2889 -0.0326432 0.00185164 0.0239854 0.148875 +EDGE3 1928 1929 -0.457734 6.37111 -0.0477562 -0.0254784 -0.0154525 0.11644 +EDGE3 1929 1930 -0.50595 6.45736 -0.0867234 -0.0517454 -0.0307942 0.157101 +EDGE3 1930 1931 -0.647519 6.18865 -0.167554 0.0337091 0.00535225 0.131821 +EDGE3 1931 1932 -0.417839 6.3653 -0.191163 -0.0250263 0.0148571 0.131897 +EDGE3 1932 1933 -0.368519 6.39371 0.0628883 0.00944716 0.00232136 0.136309 +EDGE3 1933 1934 -0.407855 6.22758 -0.208137 -0.00569539 -0.00339384 0.152747 +EDGE3 1934 1935 -0.522082 6.06436 -0.00142494 -0.029872 -0.0185306 0.158903 +EDGE3 1935 1936 -0.549863 6.27677 -0.156211 -0.00563626 -0.0254933 0.143366 +EDGE3 1936 1937 -0.620376 6.10427 0.0152066 -0.00857525 -0.0180701 0.130078 +EDGE3 1937 1938 -0.470794 6.18691 0.0259853 0.00828865 0.0259791 0.130076 +EDGE3 1938 1939 -0.656877 6.23153 -0.100291 0.026037 0.0110495 0.0894652 +EDGE3 1939 1940 -0.635102 6.26215 -0.1812 0.0141179 0.00524722 0.124909 +EDGE3 1940 1941 -0.29092 6.22965 -0.0967064 -0.00883403 -0.019549 0.106338 +EDGE3 1941 1942 -0.589252 6.19792 0.0795378 0.00113142 0.00466372 0.159739 +EDGE3 1942 1943 -0.494553 6.07509 0.125068 0.0333908 0.0240146 0.068152 +EDGE3 1943 1944 -0.523077 6.14972 0.0384974 0.0279524 -0.0172954 0.119458 +EDGE3 1944 1945 -0.611566 6.08104 -0.037546 0.00407767 -0.0236275 0.11156 +EDGE3 1945 1946 -0.429217 6.02741 -0.180638 0.0141882 -0.00131638 0.181681 +EDGE3 1946 1947 -0.546358 6.22259 -0.0712174 -0.0239666 0.011451 0.115811 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1923 -5.58129 -6.40258 -3.31529 0.0039288 -0.00182464 -0.127105 +EDGE3 1875 1925 -5.31893 -0.00955089 -3.36933 0.000646228 -0.0049979 0.00289322 +EDGE3 1874 1925 -5.80502 6.40053 -3.42968 0.00225727 -0.00166103 0.136251 +EDGE3 1875 1924 -5.60889 -6.40082 -3.28398 0.0068033 -0.0114332 -0.117295 +EDGE3 1876 1926 -5.29092 0.00384964 -3.35334 0.00352746 -0.00260534 -0.00171604 +EDGE3 1875 1926 -5.81785 6.36343 -3.43491 0.0104818 0.00745003 0.127596 +EDGE3 1877 1927 -5.31817 -0.00701177 -3.34764 -0.00654147 0.00101238 -0.00180559 +EDGE3 1876 1925 -5.61908 -6.38953 -3.2925 0.0079494 -0.00333023 -0.134583 +EDGE3 1876 1927 -5.80711 6.35809 -3.41266 0.00314591 0.00213415 0.124744 +EDGE3 1877 1926 -5.60443 -6.36522 -3.28619 0.000509374 -0.0141503 -0.125705 +EDGE3 1878 1928 -5.32146 0.00114493 -3.36044 0.00471224 -0.000932439 -0.00253407 +EDGE3 1877 1928 -5.81012 6.34433 -3.41912 0.000429312 -0.00331361 0.131045 +EDGE3 1878 1927 -5.62879 -6.33611 -3.2787 0.00194759 -0.00608617 -0.124952 +EDGE3 1879 1929 -5.30061 0.00434193 -3.34086 -0.00311293 0.00926704 0.00398527 +EDGE3 1878 1929 -5.83173 6.31906 -3.38828 0.00133753 0.00265985 0.119534 +EDGE3 1879 1928 -5.6017 -6.34623 -3.26147 -0.00601599 -0.0056844 -0.122325 +EDGE3 1880 1930 -5.33595 0.00510348 -3.33204 -0.00615293 -0.00363009 -0.00124265 +EDGE3 1879 1930 -5.8464 6.3125 -3.39884 -0.00748567 -0.00479524 0.122864 +EDGE3 1880 1929 -5.6204 -6.322 -3.29004 -0.00737452 0.000543084 -0.127591 +EDGE3 1881 1931 -5.32376 0.0188107 -3.32871 0.00226888 0.00114298 -0.000860421 +EDGE3 1880 1931 -5.84215 6.28429 -3.38561 -0.00635031 0.000640743 0.123886 +EDGE3 1881 1930 -5.60928 -6.31502 -3.26762 0.00474297 0.00362334 -0.12711 +EDGE3 1882 1932 -5.34941 -0.0145751 -3.32067 -0.00551713 -0.00506063 -0.00713923 +EDGE3 1881 1932 -5.83336 6.28296 -3.40341 0.00217309 -0.0117383 0.118477 +EDGE3 1882 1931 -5.62262 -6.31396 -3.26203 0.000644942 -0.000389022 -0.116143 +EDGE3 1883 1933 -5.33678 -0.00176256 -3.30723 -0.008553 -0.000814676 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0.0015159 -0.12711 +EDGE3 1892 1942 -5.36357 0.00160392 -3.27006 -0.00708724 0.00393476 -0.00414916 +EDGE3 1891 1942 -5.87015 6.16503 -3.30907 0.0018498 0.000423082 0.127875 +EDGE3 1892 1941 -5.6386 -6.1559 -3.18604 0.00219947 -0.00485354 -0.119984 +EDGE3 1893 1943 -5.35773 -0.0038269 -3.25575 -0.00235348 0.000834121 0.00152251 +EDGE3 1892 1943 -5.87439 6.13316 -3.30729 -0.000247705 -0.000988456 0.125336 +EDGE3 1893 1942 -5.64967 -6.16036 -3.19567 0.00188488 0.000852968 -0.125223 +EDGE3 1894 1944 -5.37145 -0.0092327 -3.24162 0.000189917 0.00433797 0.00365577 +EDGE3 1893 1944 -5.8763 6.11825 -3.30746 -0.000117102 0.00196663 0.130015 +EDGE3 1894 1943 -5.66446 -6.14086 -3.16173 -0.00212123 0.000973495 -0.129907 +EDGE3 1895 1945 -5.38967 0.0037349 -3.22818 0.0116071 0.000677882 -0.00259782 +EDGE3 1894 1945 -5.88192 6.11668 -3.28301 -0.00144359 0.00372206 0.121672 +EDGE3 1895 1944 -5.6635 -6.10784 -3.16296 0.00731365 0.0017216 -0.12533 +EDGE3 1896 1946 -5.39573 0.00657945 -3.22439 0.000317883 -0.00183642 0.000368526 +EDGE3 1895 1946 -5.86667 6.09899 -3.29684 -0.000263134 -0.0015017 0.12179 +EDGE3 1896 1945 -5.67412 -6.08366 -3.16545 0.0052457 0.00250773 -0.121947 +EDGE3 1897 1947 -5.39357 0.00283829 -3.24237 -0.00228744 0.000173388 -0.00512873 +EDGE3 1896 1947 -5.87511 6.08954 -3.29632 0.00478532 0.00304064 0.135981 +EDGE3 1897 1946 -5.65847 -6.08136 -3.16787 0.000409056 0.00413764 -0.125668 +EDGE3 1898 1948 -5.3819 0.00821504 -3.18909 -0.000252837 0.00906003 -0.000641906 +EDGE3 1897 1948 -5.88923 6.05664 -3.2788 -0.00104689 -0.0095697 0.12056 +EDGE3 1898 1947 -5.65132 -6.06553 -3.15595 -0.0055003 -0.000760796 -0.12838 +EDGE3 1898 1949 -5.8924 6.0315 -3.28629 0.00283168 0.00015285 0.127207 +EDGE3 1899 1949 -5.41409 0.004899 -3.18113 -0.0128026 0.00242451 -0.00301246 +EDGE3 1900 1950 -5.40555 0.00449769 -3.19031 -0.000773293 0.0085803 -0.000855349 +EDGE3 1899 1948 -5.69256 -6.07514 -3.13826 -0.00385793 4.38254e-06 -0.126257 +EDGE3 1899 1950 -5.88508 6.03227 -3.26025 0.0021558 -0.000973312 0.122006 +EDGE3 1900 1949 -5.66991 -6.05268 -3.13665 0.000980291 0.000524749 -0.115893 +EDGE3 1901 1951 -5.41686 -0.00564788 -3.20732 -0.00363837 -0.00610922 -0.000700343 +EDGE3 1900 1951 -5.89034 6.02068 -3.25921 0.00998144 0.0066982 0.119863 +EDGE3 1901 1950 -5.68476 -6.04687 -3.11809 -0.00232885 -0.00152281 -0.118596 +EDGE3 1902 1952 -5.43038 -0.00833196 -3.19583 -0.00703495 -0.00572986 0.00186532 +EDGE3 1901 1952 -5.88789 6.01479 -3.23085 -0.00535047 -0.0103298 0.121357 +EDGE3 1902 1951 -5.6708 -6.03229 -3.11827 -0.000596574 -0.00443279 -0.134258 +EDGE3 1903 1953 -5.42626 0.00738079 -3.17987 0.00709033 0.00365837 -0.00206977 +EDGE3 1902 1953 -5.89223 5.98688 -3.25339 -0.00229023 0.00156955 0.128186 +EDGE3 1903 1952 -5.68034 -6.02174 -3.1325 0.00753471 -0.000517762 -0.126598 +EDGE3 1904 1954 -5.42408 0.0199544 -3.16109 -0.00149456 -0.00244919 0.00214676 +EDGE3 1903 1954 -5.90704 5.9817 -3.2394 -0.0106598 0.00431322 0.125747 +EDGE3 1904 1953 -5.70119 -5.98925 -3.11563 -0.00611544 -0.0017025 -0.127205 +EDGE3 1905 1955 -5.4262 -0.00225865 -3.17554 -0.00220082 0.00670061 -0.00840319 +EDGE3 1904 1955 -5.9073 5.96329 -3.24276 -0.00635743 -0.00742364 0.121181 +EDGE3 1905 1954 -5.67821 -5.98115 -3.11112 -0.00418176 0.00724216 -0.123352 +EDGE3 1906 1956 -5.43128 0.00871152 -3.15222 -0.0045412 -0.0023397 0.00332764 +EDGE3 1905 1956 -5.90631 5.94665 -3.23051 -0.00299968 -0.00395425 0.123487 +EDGE3 1906 1955 -5.69797 -5.96699 -3.09568 -0.00650241 -0.00756336 -0.131506 +EDGE3 1907 1957 -5.41931 -0.00557384 -3.1389 -0.0127214 0.00485097 -0.00732458 +EDGE3 1906 1957 -5.91347 5.95343 -3.22571 0.00138954 -0.00508784 0.122327 +EDGE3 1907 1956 -5.69957 -5.9499 -3.07238 0.0050695 -0.0027827 -0.134899 +EDGE3 1908 1958 -5.45633 0.0119737 -3.16457 0.0181138 0.00275565 -0.0032894 +EDGE3 1907 1958 -5.91871 5.92302 -3.20011 -0.00220222 -0.000995355 0.128028 +EDGE3 1908 1957 -5.70374 -5.93753 -3.09047 0.00433953 0.00191999 -0.112961 +EDGE3 1909 1959 -5.43794 0.00255173 -3.12671 0.00169914 0.00327618 0.00143381 +EDGE3 1908 1959 -5.91487 5.90552 -3.21657 -0.0019754 0.00129584 0.129298 +EDGE3 1909 1958 -5.70787 -5.93481 -3.07223 0.00896748 -0.00820647 -0.13072 +EDGE3 1910 1960 -5.45253 0.00299423 -3.12474 0.00722001 0.00176273 -0.00083542 +EDGE3 1909 1960 -5.92128 5.90153 -3.21425 0.00767992 -0.00274562 0.128302 +EDGE3 1910 1959 -5.70742 -5.91613 -3.06455 0.00616479 -0.00631238 -0.12793 +EDGE3 1911 1961 -5.44458 -0.00107663 -3.142 -0.00786885 0.00688707 0.00658756 +EDGE3 1910 1961 -5.93376 5.88349 -3.17342 0.0111102 0.00311372 0.12621 +EDGE3 1911 1960 -5.72226 -5.90948 -3.06114 0.0110804 -0.000140461 -0.123374 +EDGE3 1912 1962 -5.45094 -0.00970238 -3.12651 -0.011332 -0.00322675 -0.00543351 +EDGE3 1911 1962 -5.90333 5.87903 -3.17783 0.00807875 0.0014455 0.133496 +EDGE3 1912 1961 -5.7152 -5.90113 -3.05341 -0.000771196 0.00342868 -0.127841 +EDGE3 1913 1963 -5.45458 -0.0108798 -3.11279 -0.00207864 0.0010523 0.00111623 +EDGE3 1912 1963 -5.92005 5.85179 -3.18131 -0.000944133 -0.000473549 0.1245 +EDGE3 1913 1962 -5.71749 -5.87549 -3.04925 0.0152772 -0.00274506 -0.126617 +EDGE3 1914 1964 -5.45486 0.0139235 -3.09703 0.00791159 -0.00682328 -0.00499117 +EDGE3 1913 1964 -5.92801 5.84591 -3.16384 -0.0028415 0.00221034 0.122493 +EDGE3 1914 1963 -5.7099 -5.86629 -3.03149 -0.00664256 -0.00755185 -0.124237 +EDGE3 1915 1965 -5.45465 -0.00518927 -3.09157 0.00402723 0.00513008 0.000818003 +EDGE3 1914 1965 -5.9486 5.81957 -3.16872 0.00816466 -0.000146956 0.12543 +EDGE3 1915 1964 -5.73817 -5.84353 -3.04801 0.00321765 0.00421407 -0.126767 +EDGE3 1916 1966 -5.46059 -0.00275226 -3.07958 -0.0134542 0.00801459 -0.0060315 +EDGE3 1915 1966 -5.93285 5.83272 -3.14942 0.0107932 0.00480811 0.121129 +EDGE3 1916 1965 -5.7283 -5.83024 -3.0416 -0.00678177 0.000375403 -0.123407 +EDGE3 1917 1967 -5.47525 0.00102524 -3.08743 0.00147318 8.50273e-05 0.00990075 +EDGE3 1916 1967 -5.95191 5.80714 -3.15122 -0.00863514 0.00559517 0.138128 +EDGE3 1917 1966 -5.73631 -5.82201 -3.01779 0.00481043 -0.0105813 -0.138089 +EDGE3 1918 1968 -5.46687 0.0129975 -3.0764 0.00112787 0.00416425 -0.00597787 +EDGE3 1917 1968 -5.93639 5.79409 -3.12968 0.000345783 0.0037258 0.12408 +EDGE3 1918 1967 -5.7103 -5.81196 -3.0143 0.0013524 -0.00193262 -0.133577 +EDGE3 1919 1969 -5.47851 0.00531679 -3.08727 -0.00115575 0.00299742 -0.00741325 +EDGE3 1918 1969 -5.94807 5.79671 -3.12893 0.00132322 0.00553222 0.119934 +EDGE3 1919 1968 -5.75164 -5.78267 -3.00684 -0.00500797 0.00385851 -0.128026 +EDGE3 1920 1970 -5.51027 0.00290657 -3.06881 0.00177696 -0.00481297 -0.00188406 +EDGE3 1919 1970 -5.95473 5.75885 -3.10824 -0.00776289 0.00768938 0.130911 +EDGE3 1920 1969 -5.74765 -5.78063 -3.00592 0.000494625 0.00218535 -0.118755 +EDGE3 1921 1971 -5.48623 0.0127142 -3.05473 -0.000712989 0.00595857 0.00520224 +EDGE3 1920 1971 -5.96173 5.74132 -3.12812 0.00672913 0.00156664 0.126894 +EDGE3 1921 1970 -5.74785 -5.75423 -2.9902 -0.00442636 0.00591841 -0.124254 +EDGE3 1922 1972 -5.47486 -0.00957271 -3.03015 0.00575038 0.00956175 0.00901711 +EDGE3 1921 1972 -5.96861 5.7276 -3.10775 0.00677739 -0.00107328 0.119132 +EDGE3 1922 1971 -5.75517 -5.75839 -2.99568 -0.00219476 0.00199698 -0.127549 +EDGE3 1923 1973 -5.505 -0.00324469 -3.04968 0.00360502 -0.00987679 -0.00702848 +EDGE3 1922 1973 -5.96631 5.73624 -3.10643 -0.0020861 -0.00207337 0.132013 +EDGE3 1923 1972 -5.74023 -5.71548 -2.99698 0.00335579 0.00137074 -0.124558 +EDGE3 1924 1974 -5.51265 0.00504605 -3.03273 0.00297301 0.000267571 -0.00238564 +EDGE3 1923 1974 -5.96351 5.71065 -3.11396 0.00538354 -0.00737199 0.124121 +EDGE3 1924 1973 -5.7536 -5.71326 -2.96847 0.00353678 0.0102409 -0.129999 +EDGE3 1925 1975 -5.49935 0.00976312 -3.04737 -3.64189e-05 0.00117017 -0.000540121 +EDGE3 1924 1975 -5.97896 5.67893 -3.09727 -0.0037038 0.00462302 0.124485 +EDGE3 1925 1974 -5.7542 -5.70214 -2.96842 0.0102969 0.00325885 -0.125939 +EDGE3 1926 1976 -5.51296 0.0058147 -3.02713 0.000238775 -0.000365179 -0.00342774 +EDGE3 1925 1976 -5.96709 5.67253 -3.08881 -0.00493901 -0.0139938 0.129311 +EDGE3 1926 1975 -5.73122 -5.6896 -2.97701 0.00409519 0.000105824 -0.134319 +EDGE3 1927 1977 -5.53409 0.00925834 -3.01108 -0.00234978 -0.00809264 -0.00670391 +EDGE3 1926 1977 -5.98768 5.66112 -3.07957 0.00207868 -0.00428169 0.118597 +EDGE3 1927 1976 -5.76025 -5.66852 -2.9705 0.00425601 -0.00519793 -0.124708 +EDGE3 1928 1978 -5.49545 -0.0113442 -2.97665 0.00347308 0.000693838 -0.00418668 +EDGE3 1927 1978 -5.95456 5.6351 -3.06152 -0.00627341 0.000832713 0.130825 +EDGE3 1928 1977 -5.74925 -5.6621 -2.93415 -0.00152813 -0.00691283 -0.122927 +EDGE3 1929 1979 -5.52943 0.0037856 -3.00264 -0.0031097 -0.00164873 -0.000470783 +EDGE3 1928 1979 -5.99905 5.64829 -3.0759 -0.0013635 0.00264902 0.112056 +EDGE3 1929 1978 -5.7643 -5.63266 -2.94203 0.00087833 0.00022573 -0.128858 +EDGE3 1930 1980 -5.52834 0.00646121 -2.99251 -0.00105196 -0.00491989 0.00375517 +EDGE3 1929 1980 -5.98436 5.61263 -3.06471 -0.00595355 -0.00497491 0.133621 +EDGE3 1930 1979 -5.77351 -5.65358 -2.94399 0.011942 0.00784394 -0.12568 +EDGE3 1931 1981 -5.53466 0.0108668 -2.98951 0.00335638 -0.00151867 0.00626584 +EDGE3 1930 1981 -5.97143 5.61538 -3.05299 -0.00268779 0.00806028 0.12164 +EDGE3 1931 1980 -5.76763 -5.60878 -2.92867 -0.000692859 0.00759049 -0.130414 +EDGE3 1932 1982 -5.54389 0.0158913 -2.97691 -0.00275903 -0.0020458 0.00791519 +EDGE3 1931 1982 -5.98414 5.61229 -3.04283 -0.00778799 0.0019244 0.126726 +EDGE3 1932 1981 -5.7656 -5.60498 -2.90806 -0.00058178 -7.96522e-05 -0.117146 +EDGE3 1933 1983 -5.52911 0.00249384 -2.9692 0.00255532 0.00426569 0.0105989 +EDGE3 1932 1983 -5.99046 5.57183 -3.04143 0.0114317 0.00166349 0.12025 +EDGE3 1933 1982 -5.78678 -5.60859 -2.91803 -0.00619448 0.000866437 -0.118936 +EDGE3 1934 1984 -5.5434 0.0080529 -2.96469 -0.00153978 0.00478685 -0.00970984 +EDGE3 1933 1984 -6.0028 5.56902 -3.02333 -0.0102068 0.00696758 0.12744 +EDGE3 1934 1983 -5.77199 -5.58286 -2.91125 -0.00257946 0.00054549 -0.126268 +EDGE3 1935 1985 -5.55857 -0.00577557 -2.96556 0.00483907 -0.00353712 -0.000410494 +EDGE3 1934 1985 -6.00934 5.53947 -3.01819 -0.00800605 0.00262047 0.128033 +EDGE3 1935 1984 -5.79441 -5.57675 -2.90252 -0.00133558 -0.000237224 -0.131593 +EDGE3 1936 1986 -5.54686 0.0023144 -2.94801 0.00597871 3.93326e-05 0.00112469 +EDGE3 1935 1986 -6.0051 5.54155 -3.00839 -0.00116882 -0.00665964 0.130864 +EDGE3 1936 1985 -5.78159 -5.54734 -2.89328 0.00478137 -0.00117958 -0.130937 +EDGE3 1937 1987 -5.54665 -0.011941 -2.92994 -0.00724633 -0.00108401 -0.0052027 +EDGE3 1936 1987 -6.01735 5.52662 -3.00387 0.00842214 0.00210134 0.116253 +EDGE3 1937 1986 -5.77099 -5.53528 -2.8886 0.000346885 0.00526133 -0.124321 +EDGE3 1938 1988 -5.56683 -0.00291494 -2.9358 -0.000712875 -0.00129538 -0.000686411 +EDGE3 1937 1988 -6.01441 5.51297 -3.00172 0.00520635 0.00497543 0.129399 +EDGE3 1938 1987 -5.79441 -5.50623 -2.88102 -0.0047978 -0.00417152 -0.134286 +EDGE3 1939 1989 -5.55124 -0.0158818 -2.93374 0.000801164 -0.00105943 -0.00579888 +EDGE3 1938 1989 -6.0063 5.50203 -2.98735 -0.0063503 0.00427412 0.114408 +EDGE3 1939 1988 -5.79818 -5.52221 -2.88128 0.00701604 -0.00536374 -0.112867 +EDGE3 1940 1990 -5.57132 0.0116076 -2.92598 0.00380591 -0.00131419 0.00322591 +EDGE3 1939 1990 -6.00843 5.47458 -2.98888 -0.000492734 0.00235777 0.126978 +EDGE3 1940 1989 -5.78457 -5.49092 -2.88974 0.000228448 0.00680623 -0.126548 +EDGE3 1941 1991 -5.56991 -0.00558997 -2.89809 0.00242658 0.00931747 0.00204082 +EDGE3 1940 1991 -5.99684 5.45655 -2.98526 -0.00137462 -0.00527492 0.131652 +EDGE3 1941 1990 -5.79629 -5.47263 -2.85105 0.00595228 -0.00142078 -0.12293 +EDGE3 1942 1992 -5.59152 -0.0212325 -2.90127 -0.00540962 0.00597246 0.00312764 +EDGE3 1941 1992 -6.02367 5.44705 -2.98275 0.00135644 0.00170721 0.122284 +EDGE3 1942 1991 -5.79717 -5.44616 -2.8524 0.00486424 0.00873439 -0.1335 +EDGE3 1943 1993 -5.5772 -0.010063 -2.88379 -0.00103114 -0.00478939 -0.00587242 +EDGE3 1942 1993 -6.01119 5.43886 -2.97587 -0.00725017 -0.00319134 0.126522 +EDGE3 1943 1992 -5.79927 -5.47078 -2.83014 0.00352528 0.00413822 -0.125509 +EDGE3 1944 1994 -5.57365 0.000848455 -2.88549 -0.001073 0.00572914 -0.0008407 +EDGE3 1943 1994 -6.02653 5.41374 -2.9452 -0.000383602 -0.00795551 0.12434 +EDGE3 1944 1993 -5.80088 -5.41726 -2.85127 0.0114619 -0.00490873 -0.125047 +EDGE3 1945 1995 -5.58552 0.00101109 -2.90024 -0.00814831 0.0039062 -0.00378408 +EDGE3 1944 1995 -6.01961 5.40448 -2.95355 0.00527659 0.00264058 0.13221 +EDGE3 1945 1994 -5.7977 -5.4279 -2.85378 -0.0101286 0.00276164 -0.123742 +EDGE3 1946 1996 -5.57451 -0.00145722 -2.8682 0.00169367 -0.0146546 -0.00380074 +EDGE3 1945 1996 -6.03607 5.38742 -2.9358 0.00149363 -0.00246134 0.129947 +EDGE3 1946 1995 -5.80325 -5.41852 -2.81974 0.0107271 -0.00925749 -0.122772 +EDGE3 1947 1997 -5.59283 -0.0117238 -2.87841 -0.000609928 -0.00221692 0.00111616 +EDGE3 1946 1997 -6.03117 5.36613 -2.93584 0.00889473 0.00301499 0.122241 +EDGE3 1947 1996 -5.80672 -5.37803 -2.83131 -0.0062877 -0.0032303 -0.126607 +EDGE3 1948 1998 -5.58457 -0.00119354 -2.87158 -0.00559931 -0.00844645 -0.00423722 +EDGE3 1947 1998 -6.03402 5.37986 -2.93836 -0.00682208 -0.00144857 0.11827 +EDGE3 1948 1997 -5.82088 -5.38313 -2.80311 0.000691188 0.00215266 -0.122895 +EDGE3 1949 1999 -5.59071 0.00667578 -2.86478 8.55629e-05 0.00595285 -0.0049736 +EDGE3 1948 1999 -6.02021 5.33921 -2.92573 -0.00142202 -0.00573423 0.127055 +EDGE3 1949 1998 -5.81159 -5.35273 -2.80336 0.000684082 0.0035971 -0.121843 +EDGE3 1950 2000 -5.59575 -0.00419579 -2.86647 -0.00277985 0.0104589 -0.00212302 +EDGE3 1949 2000 -6.0742 5.32421 -2.89755 0.0123511 0.00706643 0.125618 +EDGE3 1950 1999 -5.81671 -5.34966 -2.79616 0.00230823 -0.00228506 -0.126171 +EDGE3 1951 2001 -5.60296 -0.00817804 -2.8594 0.000276944 -0.000886763 0.0110153 +EDGE3 1950 2001 -6.05539 5.32921 -2.90149 -0.00189942 -0.00572901 0.119612 +EDGE3 1951 2000 -5.81911 -5.34241 -2.79742 -0.000302118 0.00617901 -0.122047 +EDGE3 1952 2002 -5.61285 0.00273397 -2.85226 -0.00131322 0.00654866 0.00451317 +EDGE3 1951 2002 -6.04454 5.31233 -2.90912 -0.00676358 -0.00176541 0.123367 +EDGE3 1952 2001 -5.81987 -5.29939 -2.7974 0.00237527 0.0029512 -0.127436 +EDGE3 1953 2003 -5.61281 0.0173624 -2.83283 -0.00821729 0.00231243 -0.00198992 +EDGE3 1952 2003 -6.0442 5.28225 -2.88559 0.00479039 -0.00290219 0.12475 +EDGE3 1953 2002 -5.84024 -5.31216 -2.76189 0.00841298 -0.00132699 -0.12934 +EDGE3 1954 2004 -5.60898 -0.00274502 -2.8168 -0.00367854 -0.00114419 0.00228453 +EDGE3 1953 2004 -6.04515 5.27668 -2.88639 0.00377854 -0.00605849 0.118488 +EDGE3 1954 2003 -5.81976 -5.29148 -2.78273 0.00333521 -0.000956545 -0.131773 +EDGE3 1955 2005 -5.61379 0.00407275 -2.82358 -0.00383064 0.00663643 -0.00336601 +EDGE3 1954 2005 -6.06558 5.26941 -2.8788 0.00720361 -0.00582111 0.123006 +EDGE3 1955 2004 -5.82779 -5.2801 -2.76155 -0.000260862 0.00568802 -0.137603 +EDGE3 1956 2006 -5.6295 -0.00297196 -2.80581 -0.00538486 0.00249065 0.00309432 +EDGE3 1955 2006 -6.0489 5.24933 -2.85136 0.00451571 -0.00804957 0.120522 +EDGE3 1956 2005 -5.83137 -5.26182 -2.75858 -0.00344215 -0.00685491 -0.121845 +EDGE3 1957 2007 -5.61548 0.00536062 -2.80103 0.00297612 -0.00503937 0.00470988 +EDGE3 1956 2007 -6.06453 5.24294 -2.8512 -0.000956403 -0.00108455 0.131191 +EDGE3 1957 2006 -5.85078 -5.26019 -2.75804 -0.00825878 -0.00388195 -0.131439 +EDGE3 1958 2008 -5.62227 0.0155275 -2.79241 0.000697699 -0.000490867 0.00176388 +EDGE3 1957 2008 -6.05818 5.22696 -2.86052 0.00365555 -0.000990128 0.124371 +EDGE3 1958 2007 -5.83188 -5.21839 -2.74016 -0.00317899 0.00187072 -0.12843 +EDGE3 1959 2009 -5.6453 0.00740263 -2.78745 0.00713127 0.00674665 0.00755264 +EDGE3 1958 2009 -6.06069 5.20371 -2.84382 0.00427806 -0.00211225 0.120322 +EDGE3 1959 2008 -5.82827 -5.22266 -2.74746 0.00499369 0.00577802 -0.115161 +EDGE3 1960 2010 -5.64157 0.0181014 -2.78037 -0.00184412 -0.00143602 -0.00150876 +EDGE3 1959 2010 -6.07768 5.19253 -2.83891 -0.00825649 -0.00219315 0.130249 +EDGE3 1960 2009 -5.84075 -5.21011 -2.71681 0.00608648 0.00230065 -0.13551 +EDGE3 1961 2011 -5.62202 0.00423525 -2.7681 0.00262469 -0.00404198 0.0140314 +EDGE3 1960 2011 -6.07257 5.18361 -2.82335 0.00486628 0.0103289 0.123439 +EDGE3 1961 2010 -5.85159 -5.20161 -2.70799 0.00840214 2.97394e-05 -0.139751 +EDGE3 1962 2012 -5.63987 0.00177652 -2.77025 0.00348143 -0.00461863 0.00311556 +EDGE3 1961 2012 -6.0871 5.15877 -2.80454 -0.000799931 0.00151283 0.128089 +EDGE3 1962 2011 -5.84812 -5.17487 -2.72569 -0.00881248 -0.0052736 -0.120447 +EDGE3 1963 2013 -5.63908 0.00053293 -2.75841 0.000588165 0.00402461 0.00584897 +EDGE3 1962 2013 -6.0823 5.15393 -2.81107 -0.00543668 0.00423426 0.127617 +EDGE3 1963 2012 -5.85326 -5.15448 -2.6814 0.00442265 -0.00197515 -0.129062 +EDGE3 1964 2014 -5.65934 0.00807446 -2.75546 -0.00137949 0.00875705 0.00398367 +EDGE3 1963 2014 -6.08205 5.12148 -2.8239 -0.000365711 -0.000260473 0.136815 +EDGE3 1965 2015 -5.65678 -0.0146728 -2.73639 -0.00254799 -0.0048732 0.00479912 +EDGE3 1964 2013 -5.85473 -5.14415 -2.70807 0.00722985 0.00339841 -0.123566 +EDGE3 1964 2015 -6.07785 5.12658 -2.79758 -0.00139057 -0.0034229 0.12108 +EDGE3 1965 2014 -5.85575 -5.12004 -2.68467 -0.0164985 0.0066618 -0.1217 +EDGE3 1966 2016 -5.65072 0.0169404 -2.72819 -0.00259626 0.00257382 0.00128452 +EDGE3 1965 2016 -6.08283 5.10486 -2.80138 -8.07433e-05 -0.00398571 0.128943 +EDGE3 1966 2015 -5.85844 -5.11895 -2.70445 0.00431656 0.00286175 -0.137684 +EDGE3 1967 2017 -5.64567 -0.00431639 -2.72747 -0.00299496 0.0081383 -0.00585009 +EDGE3 1966 2017 -6.08822 5.07109 -2.79196 0.00349544 0.00207464 0.134647 +EDGE3 1967 2016 -5.86688 -5.11326 -2.6985 0.00429477 -0.00591933 -0.128054 +EDGE3 1968 2018 -5.65801 0.0206301 -2.73953 -0.00527999 -0.000269626 -0.00189452 +EDGE3 1967 2018 -6.10321 5.06804 -2.78564 -0.000658319 0.00024317 0.123474 +EDGE3 1968 2017 -5.84895 -5.06092 -2.67389 0.00612391 0.000819214 -0.112843 +EDGE3 1969 2019 -5.65846 0.00559005 -2.70045 0.000417581 0.00408351 -0.0006966 +EDGE3 1968 2019 -6.08899 5.06229 -2.78422 0.00282868 0.00121901 0.130076 +EDGE3 1969 2018 -5.86343 -5.06675 -2.6634 -0.00217478 0.0044978 -0.121873 +EDGE3 1970 2020 -5.67546 0.0152022 -2.71622 -0.00808119 -0.00293761 0.00241239 +EDGE3 1969 2020 -6.10034 5.03042 -2.77528 0.00139948 0.0018802 0.125519 +EDGE3 1970 2019 -5.88227 -5.06667 -2.66501 0.00243645 -0.0024782 -0.124427 +EDGE3 1971 2021 -5.66792 -0.00371838 -2.70377 -0.00293968 -0.000444173 0.00155232 +EDGE3 1970 2021 -6.09984 5.04601 -2.76069 -0.00472765 0.00851885 0.119881 +EDGE3 1971 2020 -5.8707 -5.05888 -2.64735 -0.0049322 0.00401403 -0.123807 +EDGE3 1972 2022 -5.66352 -0.00179885 -2.70368 0.00346185 -9.73194e-05 -0.00571407 +EDGE3 1971 2022 -6.09477 5.03497 -2.76518 0.00128165 -0.00177571 0.118167 +EDGE3 1972 2021 -5.87806 -5.05371 -2.62816 0.00381303 0.00369958 -0.118824 +EDGE3 1973 2023 -5.67573 -0.0167079 -2.70349 0.00113967 0.00291716 -0.00290714 +EDGE3 1972 2023 -6.11164 5.01021 -2.7475 -0.00477598 -0.00138039 0.12133 +EDGE3 1973 2022 -5.87426 -5.02266 -2.65041 0.00765128 0.00101388 -0.129682 +EDGE3 1974 2024 -5.67797 -0.00440572 -2.68056 0.0069377 0.00706319 -0.00331808 +EDGE3 1973 2024 -6.11386 4.98268 -2.72325 0.00356497 0.00103656 0.134316 +EDGE3 1974 2023 -5.86791 -5.00645 -2.63004 0.00499318 0.00397367 -0.123661 +EDGE3 1975 2025 -5.69194 -0.00939471 -2.66728 -0.00371873 0.00491463 -0.00290824 +EDGE3 1974 2025 -6.10495 4.98567 -2.72957 -0.00874588 0.00174585 0.127264 +EDGE3 1975 2024 -5.87097 -4.97912 -2.62542 0.00586282 0.00449985 -0.122856 +EDGE3 1976 2026 -5.69275 0.00175766 -2.64297 -0.00659111 -0.00304246 -0.00342775 +EDGE3 1975 2026 -6.11354 4.98457 -2.69983 -0.011482 -0.00538869 0.128734 +EDGE3 1976 2025 -5.88145 -4.99451 -2.6125 -0.00802617 -0.000498878 -0.126156 +EDGE3 1977 2027 -5.68552 -0.00259463 -2.65417 -0.000895117 -0.00917468 0.00466201 +EDGE3 1976 2027 -6.10601 4.94769 -2.71653 0.000402919 0.00629842 0.12919 +EDGE3 1977 2026 -5.88762 -4.97776 -2.60792 -0.00789496 0.00442893 -0.127865 +EDGE3 1978 2028 -5.68832 -0.0120616 -2.66402 -0.00253004 0.000279988 0.00390043 +EDGE3 1977 2028 -6.12622 4.93498 -2.71018 0.00480295 0.00156111 0.126563 +EDGE3 1978 2027 -5.87971 -4.97422 -2.60538 -0.00113797 0.00451869 -0.122012 +EDGE3 1979 2029 -5.68937 -0.00483494 -2.65422 0.0019051 0.00022987 0.000628138 +EDGE3 1978 2029 -6.0981 4.92902 -2.71323 0.00349942 -0.00319367 0.122731 +EDGE3 1979 2028 -5.89997 -4.95356 -2.60002 0.00104094 -0.0029203 -0.122893 +EDGE3 1980 2030 -5.70644 0.00981718 -2.63796 -0.000810061 0.000815083 0.00394178 +EDGE3 1979 2030 -6.11012 4.91604 -2.68577 0.000373158 -0.00146418 0.12864 +EDGE3 1980 2029 -5.89608 -4.91491 -2.58249 0.00716838 0.000627993 -0.126979 +EDGE3 1981 2031 -5.70029 0.0103036 -2.61469 -0.00812967 -0.0105987 0.000201646 +EDGE3 1980 2031 -6.12635 4.89014 -2.69433 0.00496996 0.00453455 0.129435 +EDGE3 1981 2030 -5.90683 -4.90595 -2.58374 -0.00883008 0.00295164 -0.128402 +EDGE3 1982 2032 -5.71383 -0.00508804 -2.61098 -0.00172683 -0.00616701 -0.00188828 +EDGE3 1981 2032 -6.12548 4.87477 -2.66559 -0.0019092 -0.0121391 0.123419 +EDGE3 1982 2031 -5.87399 -4.87441 -2.56641 0.000194926 -0.00365293 -0.12622 +EDGE3 1983 2033 -5.70435 -4.68006e-05 -2.61322 -0.00119224 -0.00427238 -0.000459402 +EDGE3 1982 2033 -6.14499 4.86172 -2.69185 0.00258962 0.00167336 0.119678 +EDGE3 1983 2032 -5.88933 -4.87997 -2.57352 0.0136186 -0.00053469 -0.113947 +EDGE3 1984 2034 -5.70866 0.00740743 -2.6169 0.0070403 -0.00740498 -0.00426495 +EDGE3 1983 2034 -6.12992 4.8486 -2.67041 0.000613673 -0.00484777 0.123082 +EDGE3 1984 2033 -5.89246 -4.8649 -2.55875 -0.00150449 -0.000601549 -0.118692 +EDGE3 1985 2035 -5.72381 0.00196836 -2.6104 0.00474132 0.00369973 -0.00928139 +EDGE3 1984 2035 -6.14261 4.82665 -2.65943 -0.00386675 0.000172735 0.117963 +EDGE3 1985 2034 -5.91073 -4.84735 -2.54636 -0.00497801 0.00234227 -0.12809 +EDGE3 1985 2036 -6.11982 4.80201 -2.66184 -0.00324819 0.00863909 0.12945 +EDGE3 1986 2036 -5.72677 0.00382911 -2.59004 0.00980639 0.0010069 0.0089004 +EDGE3 1987 2037 -5.729 0.0125778 -2.60432 -0.00461108 -0.000919019 -0.00405932 +EDGE3 1986 2035 -5.91921 -4.82525 -2.55333 -0.0037187 0.00610245 -0.123571 +EDGE3 1986 2037 -6.14308 4.79213 -2.6394 -0.00708418 0.000286545 0.127403 +EDGE3 1987 2036 -5.90948 -4.81843 -2.53106 -0.00374852 0.0136236 -0.130216 +EDGE3 1988 2038 -5.72723 -0.012184 -2.58184 0.00280776 -0.00303138 0.00678438 +EDGE3 1987 2038 -6.13312 4.7865 -2.65133 -0.00370447 0.000732884 0.125371 +EDGE3 1988 2037 -5.88902 -4.80056 -2.54457 -0.000314103 0.00249991 -0.126326 +EDGE3 1989 2039 -5.71025 -0.00967135 -2.5907 0.00537582 1.53546e-05 -0.00146584 +EDGE3 1988 2039 -6.153 4.76545 -2.65028 0.0117102 0.00144592 0.128812 +EDGE3 1989 2038 -5.8993 -4.80011 -2.5341 0.00288866 0.0063646 -0.119684 +EDGE3 1990 2040 -5.73889 -0.00119034 -2.56429 -0.00109989 -0.00315108 0.00031357 +EDGE3 1989 2040 -6.15324 4.77179 -2.64271 -0.001378 -0.00117353 0.124713 +EDGE3 1990 2039 -5.92804 -4.7756 -2.51318 -0.000644632 0.00395925 -0.125373 +EDGE3 1991 2041 -5.71671 4.96791e-05 -2.56081 -0.00240224 0.00493047 -0.000233993 +EDGE3 1990 2041 -6.13659 4.7519 -2.61667 -0.00117809 -0.00589109 0.124796 +EDGE3 1991 2040 -5.91479 -4.76916 -2.52589 -0.00522813 -1.21103e-05 -0.123421 +EDGE3 1992 2042 -5.741 0.0163824 -2.53424 -0.00332111 0.00513903 -0.00328601 +EDGE3 1991 2042 -6.14323 4.72251 -2.59834 -0.012849 0.00702589 0.1204 +EDGE3 1992 2041 -5.91697 -4.74255 -2.49408 0.00197826 0.00233048 -0.135124 +EDGE3 1993 2043 -5.74865 0.00741669 -2.53799 -0.00231165 -0.00337837 0.00893604 +EDGE3 1992 2043 -6.15616 4.70534 -2.60166 -0.0062415 0.00222547 0.127571 +EDGE3 1993 2042 -5.9251 -4.72891 -2.48772 -0.000202461 0.00309071 -0.127355 +EDGE3 1994 2044 -5.73641 -0.00432517 -2.55032 -0.00244914 -0.00071224 -0.00606833 +EDGE3 1993 2044 -6.14334 4.6887 -2.58314 -0.00048312 0.00916664 0.136056 +EDGE3 1994 2043 -5.93669 -4.72724 -2.49448 -0.00379939 -0.00258039 -0.125835 +EDGE3 1995 2045 -5.76333 -0.00576178 -2.53612 0.0034264 0.00257061 -0.00514583 +EDGE3 1994 2045 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2048 -5.94408 -4.65923 -2.45192 0.000883096 0.00140328 -0.123139 +EDGE3 2000 2050 -5.74839 -0.00734357 -2.49863 0.000311057 -0.00142417 -0.00377704 +EDGE3 1999 2050 -6.15495 4.61349 -2.5414 -0.000181217 -0.00203306 0.129037 +EDGE3 2000 2049 -5.9317 -4.64752 -2.44503 0.00901745 0.0017234 -0.118038 +EDGE3 2001 2051 -5.75976 -0.00171117 -2.47989 -0.00792534 -0.00413709 -0.00781739 +EDGE3 2000 2051 -6.18659 4.58175 -2.54779 -0.0049066 0.00259802 0.132815 +EDGE3 2001 2050 -5.9428 -4.61092 -2.4395 -0.00525132 -0.000677051 -0.127397 +EDGE3 2002 2052 -5.76636 -0.00599688 -2.48583 -0.00468483 0.00396651 -0.0103127 +EDGE3 2001 2052 -6.17512 4.57127 -2.52633 -0.00953566 -0.00267424 0.127105 +EDGE3 2002 2051 -5.94168 -4.59943 -2.4424 0.0128335 -0.00304354 -0.120298 +EDGE3 2003 2053 -5.79252 0.00870577 -2.47847 0.00523746 0.00536477 -0.00327143 +EDGE3 2002 2053 -6.17521 4.5837 -2.53395 0.00523524 -0.00324907 0.121779 +EDGE3 2003 2052 -5.96882 -4.58883 -2.41945 -0.00478965 -0.00231544 -0.123808 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1876 1875 -0.966863 -0.0535332 1.55642 1 0 1 1 0 0 +EDGE2 1876 1475 -1.10331 -0.0587764 1.57769 1 0 1 1 0 0 +EDGE2 1876 1675 -0.957235 0.0319771 1.55186 1 0 1 1 0 0 +EDGE2 1876 1695 -0.97638 0.00613395 -1.56403 1 0 1 1 0 0 +EDGE2 1876 1676 0.00526169 0.0217062 0.00583998 1 0 1 1 0 0 +EDGE2 1876 1476 0.0647258 -0.0254436 -0.0231493 1 0 1 1 0 0 +EDGE2 1876 1677 1.00854 -0.057791 -0.0063746 1 0 1 1 0 0 +EDGE2 1876 1477 1.00635 0.0573916 0.0515605 1 0 1 1 0 0 +EDGE2 1877 1676 -0.960549 -0.013006 -0.0189578 1 0 1 1 0 0 +EDGE2 1877 1876 -0.977749 0.158078 -0.0022528 1 0 1 1 0 0 +EDGE2 1877 1476 -0.998178 0.0307309 0.00421687 1 0 1 1 0 0 +EDGE2 1877 1677 -0.0145258 0.0287662 -0.0262434 1 0 1 1 0 0 +EDGE2 1877 1477 0.0242115 0.0078866 0.00393758 1 0 1 1 0 0 +EDGE2 1877 1678 1.06878 -0.0020559 0.0298236 1 0 1 1 0 0 +EDGE2 1877 1478 0.999434 -0.0181454 0.00560009 1 0 1 1 0 0 +EDGE2 1878 1677 -1.02022 -0.0262144 0.00144612 1 0 1 1 0 0 +EDGE2 1878 1877 -1.02961 0.0330304 0.0262339 1 0 1 1 0 0 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1881 1880 -0.9177 -0.00373364 -1.54682 1 0 1 1 0 0 +EDGE2 1881 1500 -1.05822 0.0576166 1.53312 1 0 1 1 0 0 +EDGE2 1881 1680 -0.989456 -0.00578804 -1.60825 1 0 1 1 0 0 +EDGE2 1881 1480 -0.95734 -0.0196621 -1.57474 1 0 1 1 0 0 +EDGE2 1881 1340 -0.989292 0.0141358 1.56483 1 0 1 1 0 0 +EDGE2 1882 1681 -1.00796 -0.0193165 -0.0435438 1 0 1 1 0 0 +EDGE2 1882 1682 0.055367 0.0359405 -0.00141953 1 0 1 1 0 0 +EDGE2 1882 1683 0.989582 0.0296149 0.0208108 1 0 1 1 0 0 +EDGE2 1882 1881 -0.968428 0.0302511 0.00371931 1 0 1 1 0 0 +EDGE2 1883 1684 0.927021 -0.0832617 -0.00884942 1 0 1 1 0 0 +EDGE2 1883 1682 -0.937216 0.0151095 0.00763666 1 0 1 1 0 0 +EDGE2 1883 1882 -1.01848 -0.0636796 0.00560133 1 0 1 1 0 0 +EDGE2 1883 1683 -0.0587378 -0.0227073 0.0232806 1 0 1 1 0 0 +EDGE2 1884 1883 -0.962154 -0.0246764 0.0165284 1 0 1 1 0 0 +EDGE2 1884 1685 1.01773 -0.0105938 -0.0272677 1 0 1 1 0 0 +EDGE2 1884 1684 0.0681752 -0.0881443 0.00452822 1 0 1 1 0 0 +EDGE2 1884 1683 -1.00934 0.035925 0.0044444 1 0 1 1 0 0 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0 1 1 0 0 +EDGE2 1919 1880 1.03919 0.0639893 -3.13778 1 0 1 1 0 0 +EDGE2 1919 1900 1.06863 0.0507684 -3.15105 1 0 1 1 0 0 +EDGE2 1919 1500 0.998729 -0.0115194 -0.00364977 1 0 1 1 0 0 +EDGE2 1919 1680 0.968992 0.0251194 -3.14835 1 0 1 1 0 0 +EDGE2 1919 1480 0.957597 -0.0786979 -3.15853 1 0 1 1 0 0 +EDGE2 1919 1340 1.02076 -0.0263488 0.00543907 1 0 1 1 0 0 +EDGE2 1919 1359 -0.00283972 -0.0566118 2.05473e-05 1 0 1 1 0 0 +EDGE2 1919 1499 -0.0284414 -0.0362667 -0.00701144 1 0 1 1 0 0 +EDGE2 1919 1339 -0.0186725 -0.0675883 0.02824 1 0 1 1 0 0 +EDGE2 1919 1358 -1.10436 -0.0240285 0.0143308 1 0 1 1 0 0 +EDGE2 1919 1498 -0.989168 0.0308876 -0.0223436 1 0 1 1 0 0 +EDGE2 1919 1918 -0.961076 0.00920183 -0.00655415 1 0 1 1 0 0 +EDGE2 1919 1338 -0.978904 0.10946 -0.0185478 1 0 1 1 0 0 +EDGE2 1920 1360 -0.0613266 0.000643278 -0.00327164 1 0 1 1 0 0 +EDGE2 1920 1679 0.989564 0.0010716 -3.14924 1 0 1 1 0 0 +EDGE2 1920 1879 1.02614 0.0489042 -3.14796 1 0 1 1 0 0 +EDGE2 1920 1899 1.00436 -0.0153875 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1 0 0 +EDGE2 1920 1339 -0.983896 -0.0212069 -0.0114655 1 0 1 1 0 0 +EDGE2 1921 1360 -0.944673 0.00326866 -1.57341 1 0 1 1 0 0 +EDGE2 1921 1880 -1.06789 -0.0530023 1.57779 1 0 1 1 0 0 +EDGE2 1921 1920 -1.0448 -0.0248486 -1.57104 1 0 1 1 0 0 +EDGE2 1921 1900 -0.97041 0.0094995 1.57816 1 0 1 1 0 0 +EDGE2 1921 1500 -1.02298 0.00116022 -1.59026 1 0 1 1 0 0 +EDGE2 1921 1680 -1.06942 -0.0328709 1.57143 1 0 1 1 0 0 +EDGE2 1921 1480 -0.945856 -0.0021635 1.59449 1 0 1 1 0 0 +EDGE2 1921 1502 1.00871 -0.00588035 0.0347317 1 0 1 1 0 0 +EDGE2 1921 1481 -0.0323927 0.0551046 0.0253285 1 0 1 1 0 0 +EDGE2 1921 1901 -0.101486 0.0495563 0.00495831 1 0 1 1 0 0 +EDGE2 1921 1340 -1.07468 -0.0462988 -1.57833 1 0 1 1 0 0 +EDGE2 1921 1501 -0.00929866 0.0158611 0.0125594 1 0 1 1 0 0 +EDGE2 1921 1341 0.0374267 0.0452721 -0.00685207 1 0 1 1 0 0 +EDGE2 1921 1361 -0.0977258 -0.00820433 0.033922 1 0 1 1 0 0 +EDGE2 1921 1902 1.02242 -0.0202983 0.00218177 1 0 1 1 0 0 +EDGE2 1921 1342 0.9394 -0.0109797 -0.0313308 1 0 1 1 0 0 +EDGE2 1921 1362 1.02489 0.0480309 0.00472705 1 0 1 1 0 0 +EDGE2 1921 1482 1.04872 -0.0454935 0.0123623 1 0 1 1 0 0 +EDGE2 1922 1502 -0.0126479 -0.0415579 0.00351958 1 0 1 1 0 0 +EDGE2 1922 1481 -1.02582 0.0295552 -0.0134238 1 0 1 1 0 0 +EDGE2 1922 1901 -0.994026 0.0549693 0.00907988 1 0 1 1 0 0 +EDGE2 1922 1921 -1.03108 -0.0069971 0.00521013 1 0 1 1 0 0 +EDGE2 1922 1501 -1.01479 0.012016 0.0360223 1 0 1 1 0 0 +EDGE2 1922 1341 -1.02524 0.0751513 -0.0232293 1 0 1 1 0 0 +EDGE2 1922 1361 -1.002 0.0256568 0.0317156 1 0 1 1 0 0 +EDGE2 1922 1902 -0.0563773 0.0111879 0.0212718 1 0 1 1 0 0 +EDGE2 1922 1903 0.959043 -0.0580862 -0.00563584 1 0 1 1 0 0 +EDGE2 1922 1342 0.0566429 -0.0199478 0.0140852 1 0 1 1 0 0 +EDGE2 1922 1362 0.0694748 -0.0346404 -0.0213263 1 0 1 1 0 0 +EDGE2 1922 1482 -0.0663108 0.014695 0.0295498 1 0 1 1 0 0 +EDGE2 1922 1363 0.986255 -0.00268518 -0.0198081 1 0 1 1 0 0 +EDGE2 1922 1483 0.947245 0.0804325 0.013132 1 0 1 1 0 0 +EDGE2 1922 1503 1.05569 -0.0439387 0.0239189 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1925 1485 0.0883881 -0.0331715 0.0187473 1 0 1 1 0 0 +EDGE2 1925 1505 -0.101371 0.0543886 -0.00931636 1 0 1 1 0 0 +EDGE2 1925 1365 0.0231411 -0.0291304 0.0191285 1 0 1 1 0 0 +EDGE2 1925 1325 0.0632302 -0.0647082 -3.14489 1 0 1 1 0 0 +EDGE2 1925 1524 1.03742 -0.0036676 -3.15437 1 0 1 1 0 0 +EDGE2 1925 1644 1.02195 -0.111937 -3.13973 1 0 1 1 0 0 +EDGE2 1925 1324 0.930818 0.015278 -3.15928 1 0 1 1 0 0 +EDGE2 1925 1486 0.0479892 1.03951 1.55823 1 0 1 1 0 0 +EDGE2 1925 1906 0.0962932 0.999711 1.598 1 0 1 1 0 0 +EDGE2 1925 1326 0.0216972 1.0644 1.56615 1 0 1 1 0 0 +EDGE2 1925 1346 0.00186423 0.908698 1.59737 1 0 1 1 0 0 +EDGE2 1926 1345 -0.946023 -0.00889775 1.55853 1 0 1 1 0 0 +EDGE2 1926 1526 0.0408744 0.0533576 -0.00516767 1 0 1 1 0 0 +EDGE2 1926 1507 1.03979 -0.00757356 0.0361578 1 0 1 1 0 0 +EDGE2 1926 1527 0.969525 -0.0253599 0.0063938 1 0 1 1 0 0 +EDGE2 1926 1647 1.05649 0.0912232 0.001141 1 0 1 1 0 0 +EDGE2 1926 1367 0.993554 -0.00732757 0.020302 1 0 1 1 0 0 +EDGE2 1926 1646 -0.0221794 -0.00820338 0.0127201 1 0 1 1 0 0 +EDGE2 1926 1366 0.0563478 0.0806374 -0.00116458 1 0 1 1 0 0 +EDGE2 1926 1506 -0.0201741 -0.071916 -0.0266853 1 0 1 1 0 0 +EDGE2 1926 1525 -1.00512 0.000783238 -1.56324 1 0 1 1 0 0 +EDGE2 1926 1905 -1.0474 -0.0469627 1.55661 1 0 1 1 0 0 +EDGE2 1926 1925 -1.03516 0.0162233 1.57937 1 0 1 1 0 0 +EDGE2 1926 1645 -0.982266 0.0316559 -1.54752 1 0 1 1 0 0 +EDGE2 1926 1485 -1.0502 -0.00804113 1.57054 1 0 1 1 0 0 +EDGE2 1926 1505 -1.10973 0.0393432 1.59489 1 0 1 1 0 0 +EDGE2 1926 1365 -1.04683 -0.0131508 1.60852 1 0 1 1 0 0 +EDGE2 1926 1325 -0.960531 -0.0214905 -1.60925 1 0 1 1 0 0 +EDGE2 1927 1648 0.933731 -0.115913 -0.00350672 1 0 1 1 0 0 +EDGE2 1927 1368 0.981671 0.0701361 0.00680852 1 0 1 1 0 0 +EDGE2 1927 1508 1.03955 -0.0107658 -0.00107903 1 0 1 1 0 0 +EDGE2 1927 1528 1.03518 0.00876097 -0.00235397 1 0 1 1 0 0 +EDGE2 1927 1526 -1.04918 -0.0274085 -0.0166483 1 0 1 1 0 0 +EDGE2 1927 1507 0.0149452 0.0915524 -0.0447211 1 0 1 1 0 0 +EDGE2 1927 1527 0.0398536 -0.000940338 -0.00592045 1 0 1 1 0 0 +EDGE2 1927 1647 0.0693633 0.0275918 -0.0392715 1 0 1 1 0 0 +EDGE2 1927 1367 0.0471152 0.0105449 0.00829287 1 0 1 1 0 0 +EDGE2 1927 1926 -0.936487 -0.0180098 -0.00895083 1 0 1 1 0 0 +EDGE2 1927 1646 -1.10923 0.0700709 0.0419977 1 0 1 1 0 0 +EDGE2 1927 1366 -1.02572 -0.00134996 -0.0125451 1 0 1 1 0 0 +EDGE2 1927 1506 -1.02771 -0.0147067 -0.015888 1 0 1 1 0 0 +EDGE2 1928 1509 0.984241 -0.0313617 0.00251376 1 0 1 1 0 0 +EDGE2 1928 1649 0.909234 0.12653 0.00215458 1 0 1 1 0 0 +EDGE2 1928 1529 1.04818 -0.0652808 -0.00384624 1 0 1 1 0 0 +EDGE2 1928 1369 0.935847 0.0175466 0.0317745 1 0 1 1 0 0 +EDGE2 1928 1648 0.0142586 0.0301668 0.0424222 1 0 1 1 0 0 +EDGE2 1928 1368 -0.031812 -0.0466325 0.0496814 1 0 1 1 0 0 +EDGE2 1928 1508 -0.0454259 -0.0132046 0.0133768 1 0 1 1 0 0 +EDGE2 1928 1528 -0.000614644 0.010382 0.0237269 1 0 1 1 0 0 +EDGE2 1928 1507 -1.0129 -0.0483348 -0.0171306 1 0 1 1 0 0 +EDGE2 1928 1527 -1.0421 0.0509869 0.00266875 1 0 1 1 0 0 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0 1 1 0 0 +EDGE2 1929 1368 -1.04349 0.000440483 0.0103178 1 0 1 1 0 0 +EDGE2 1929 1508 -0.92013 0.0566838 0.0042127 1 0 1 1 0 0 +EDGE2 1929 1528 -1.02711 0.0617186 -0.00139552 1 0 1 1 0 0 +EDGE2 1930 1669 0.992208 0.101793 -3.1262 1 0 1 1 0 0 +EDGE2 1930 1709 1.01752 0.0242608 -3.13054 1 0 1 1 0 0 +EDGE2 1930 1869 1.00505 0.0228497 -3.14726 1 0 1 1 0 0 +EDGE2 1930 1469 1.00587 -0.0942514 -3.13441 1 0 1 1 0 0 +EDGE2 1930 1671 0.0371668 -1.08918 -1.57361 1 0 1 1 0 0 +EDGE2 1930 1711 0.039076 -0.973308 -1.56802 1 0 1 1 0 0 +EDGE2 1930 1871 -0.0121484 -0.852154 -1.58939 1 0 1 1 0 0 +EDGE2 1930 1471 0.0109775 -1.02089 -1.56046 1 0 1 1 0 0 +EDGE2 1930 1650 -0.0694669 -0.0118536 0.0236796 1 0 1 1 0 0 +EDGE2 1930 1710 0.00334032 -0.0875787 -3.1329 1 0 1 1 0 0 +EDGE2 1930 1870 0.0489006 0.0129886 -3.15228 1 0 1 1 0 0 +EDGE2 1930 1670 0.00640147 0.113393 -3.13018 1 0 1 1 0 0 +EDGE2 1930 1470 0.0731746 -0.00974561 -3.14225 1 0 1 1 0 0 +EDGE2 1930 1510 -0.0254346 -0.00512014 -0.00610561 1 0 1 1 0 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1749 1.02771 0.0236449 -0.0156386 1 0 1 1 0 0 +EDGE2 1948 1729 1.01239 -0.0155394 -0.00113215 1 0 1 1 0 0 +EDGE2 1948 1727 -0.970799 0.0225408 -0.00876162 1 0 1 1 0 0 +EDGE2 1948 1947 -1.0536 0.0564209 -0.011933 1 0 1 1 0 0 +EDGE2 1948 1728 0.0341724 -0.0465192 -0.00217459 1 0 1 1 0 0 +EDGE2 1948 1748 0.0449377 -0.0240675 -0.00680101 1 0 1 1 0 0 +EDGE2 1948 1747 -1.01795 0.047013 0.0549715 1 0 1 1 0 0 +EDGE2 1949 1948 -1.04201 0.0193283 0.00806039 1 0 1 1 0 0 +EDGE2 1949 1750 0.996837 0.0317135 0.00892525 1 0 1 1 0 0 +EDGE2 1949 1730 1.00664 0.00569943 0.00483779 1 0 1 1 0 0 +EDGE2 1949 1749 -0.0433132 -0.00669647 -0.0312158 1 0 1 1 0 0 +EDGE2 1949 1729 0.062398 0.0163671 -0.00208004 1 0 1 1 0 0 +EDGE2 1949 1728 -1.00679 0.0210522 0.0148563 1 0 1 1 0 0 +EDGE2 1949 1748 -1.03802 -0.0473024 -0.0150728 1 0 1 1 0 0 +EDGE2 1950 1750 -0.00459823 0.0406054 -0.0255372 1 0 1 1 0 0 +EDGE2 1950 1949 -1.00524 0.00857809 -0.0138023 1 0 1 1 0 0 +EDGE2 1950 1730 -0.101284 0.137102 0.0288636 1 0 1 1 0 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1962 1961 -1.05809 -0.0414948 0.0105518 1 0 1 1 0 0 +EDGE2 1963 1962 -0.993888 -0.0589607 -0.0370754 1 0 1 1 0 0 +EDGE2 1964 1963 -0.966421 -0.0306585 -0.0240633 1 0 1 1 0 0 +EDGE2 1965 1964 -0.994873 -0.00466666 0.0224142 1 0 1 1 0 0 +EDGE2 1966 1965 -1.0033 0.00377487 -1.58998 1 0 1 1 0 0 +EDGE2 1967 1966 -0.971765 0.0319893 -0.00646729 1 0 1 1 0 0 +EDGE2 1968 1967 -0.946994 0.00991469 -0.00483266 1 0 1 1 0 0 +EDGE2 1969 1968 -0.93351 0.0334612 0.00776193 1 0 1 1 0 0 +EDGE2 1970 1969 -0.915027 -0.00921922 0.0389372 1 0 1 1 0 0 +EDGE2 1971 1970 -1.04248 -0.0188794 -1.5627 1 0 1 1 0 0 +EDGE2 1972 1971 -0.988714 0.0426255 -0.00833797 1 0 1 1 0 0 +EDGE2 1973 1972 -0.923307 -0.00502572 0.0160189 1 0 1 1 0 0 +EDGE2 1974 1973 -0.96362 0.0269859 0.0183691 1 0 1 1 0 0 +EDGE2 1974 1955 0.98267 -0.0587952 -3.16323 1 0 1 1 0 0 +EDGE2 1975 1954 1.06649 0.0363914 -3.16319 1 0 1 1 0 0 +EDGE2 1975 1974 -0.96762 -0.001388 0.00169247 1 0 1 1 0 0 +EDGE2 1975 1955 0.0431246 -0.024315 -3.13667 1 0 1 1 0 0 +EDGE2 1975 1956 -0.0451835 0.994651 1.61509 1 0 1 1 0 0 +EDGE2 1976 1975 -0.986738 -0.0104457 -1.55557 1 0 1 1 0 0 +EDGE2 1976 1955 -0.978853 0.0634217 1.61061 1 0 1 1 0 0 +EDGE2 1976 1956 -0.00423246 -0.050154 -0.0162084 1 0 1 1 0 0 +EDGE2 1976 1957 0.992492 0.044839 0.000239347 1 0 1 1 0 0 +EDGE2 1977 1956 -0.996629 -0.108151 -0.0454251 1 0 1 1 0 0 +EDGE2 1977 1976 -1.04692 -0.0243873 -0.00703196 1 0 1 1 0 0 +EDGE2 1977 1957 -0.0144798 -0.00277489 0.0273135 1 0 1 1 0 0 +EDGE2 1977 1958 0.967213 -0.0691074 -0.00575115 1 0 1 1 0 0 +EDGE2 1978 1977 -1.08013 0.0333463 0.0102876 1 0 1 1 0 0 +EDGE2 1978 1957 -0.987933 -0.0058788 -0.0171579 1 0 1 1 0 0 +EDGE2 1978 1958 0.0444829 0.0833283 -0.0577801 1 0 1 1 0 0 +EDGE2 1978 1959 0.966877 0.0235905 0.00500637 1 0 1 1 0 0 +EDGE2 1979 1978 -0.952346 -0.0401466 0.0123793 1 0 1 1 0 0 +EDGE2 1979 1958 -1.01589 0.0054175 -0.0215536 1 0 1 1 0 0 +EDGE2 1979 1959 -0.0389842 -0.0862518 -0.0169288 1 0 1 1 0 0 +EDGE2 1979 1960 0.975895 -0.0495453 0.0197864 1 0 1 1 0 0 +EDGE2 1980 1979 -1.00598 0.0532653 0.0216999 1 0 1 1 0 0 +EDGE2 1980 1959 -1.02501 0.0344823 -0.0127801 1 0 1 1 0 0 +EDGE2 1980 1960 -0.0471652 0.0863481 0.0062378 1 0 1 1 0 0 +EDGE2 1980 1961 0.00901442 1.03347 1.57827 1 0 1 1 0 0 +EDGE2 1981 1962 0.940742 0.00341825 0.0168041 1 0 1 1 0 0 +EDGE2 1981 1960 -1.00015 0.0438103 -1.53363 1 0 1 1 0 0 +EDGE2 1981 1980 -0.958201 0.02756 -1.58033 1 0 1 1 0 0 +EDGE2 1981 1961 0.0170745 0.0725172 -0.00124512 1 0 1 1 0 0 +EDGE2 1982 1981 -1.01578 -0.0214548 0.0311474 1 0 1 1 0 0 +EDGE2 1982 1963 1.05768 -0.0226734 0.017436 1 0 1 1 0 0 +EDGE2 1982 1962 -0.0532055 0.045735 -0.028132 1 0 1 1 0 0 +EDGE2 1982 1961 -1.03548 -0.0648484 -0.0257451 1 0 1 1 0 0 +EDGE2 1983 1964 1.00276 -0.00835625 -0.0055426 1 0 1 1 0 0 +EDGE2 1983 1982 -0.969956 -0.0322649 -0.00018619 1 0 1 1 0 0 +EDGE2 1983 1963 0.0564916 0.0369334 0.00443873 1 0 1 1 0 0 +EDGE2 1983 1962 -0.985286 0.0122176 -0.0124195 1 0 1 1 0 0 +EDGE2 1984 1964 0.0717805 0.000804701 0.000489767 1 0 1 1 0 0 +EDGE2 1984 1965 0.895167 0.0815251 -0.009058 1 0 1 1 0 0 +EDGE2 1984 1963 -0.982849 -0.0757825 -0.0479688 1 0 1 1 0 0 +EDGE2 1984 1983 -1.05478 -0.0364054 -0.0194313 1 0 1 1 0 0 +EDGE2 1985 1964 -0.999001 0.0168539 0.00163576 1 0 1 1 0 0 +EDGE2 1985 1965 -0.0197151 -0.048047 -0.0300131 1 0 1 1 0 0 +EDGE2 1985 1966 0.031442 0.977049 1.60526 1 0 1 1 0 0 +EDGE2 1985 1984 -0.949048 -0.0212716 -0.0366859 1 0 1 1 0 0 +EDGE2 1986 1967 0.937513 0.0493326 0.0199668 1 0 1 1 0 0 +EDGE2 1986 1965 -0.913676 0.02738 -1.57373 1 0 1 1 0 0 +EDGE2 1986 1985 -1.00978 0.0450655 -1.53487 1 0 1 1 0 0 +EDGE2 1986 1966 0.0626167 0.0246417 0.0179191 1 0 1 1 0 0 +EDGE2 1987 1968 0.971278 -0.0317633 0.02737 1 0 1 1 0 0 +EDGE2 1987 1986 -1.07877 -0.0756139 -0.0266188 1 0 1 1 0 0 +EDGE2 1987 1967 0.0208396 -0.0404893 -0.0377407 1 0 1 1 0 0 +EDGE2 1987 1966 -0.969448 -0.0362498 0.00101759 1 0 1 1 0 0 +EDGE2 1988 1969 1.01257 -0.0335056 0.0145992 1 0 1 1 0 0 +EDGE2 1988 1968 -0.0622395 -0.0165413 -0.00719098 1 0 1 1 0 0 +EDGE2 1988 1967 -0.993366 -0.0737222 -0.0367186 1 0 1 1 0 0 +EDGE2 1988 1987 -0.963401 0.0261517 -0.00716377 1 0 1 1 0 0 +EDGE2 1989 1970 0.948275 -0.0146619 0.0318573 1 0 1 1 0 0 +EDGE2 1989 1969 -0.0171098 -0.0273623 0.00880636 1 0 1 1 0 0 +EDGE2 1989 1968 -0.979076 -0.0709008 0.00710372 1 0 1 1 0 0 +EDGE2 1989 1988 -1.04271 -0.0833517 0.0264933 1 0 1 1 0 0 +EDGE2 1990 1970 -0.00689206 0.0189439 -0.00670274 1 0 1 1 0 0 +EDGE2 1990 1971 -0.0331747 1.01305 1.61178 1 0 1 1 0 0 +EDGE2 1990 1969 -1.03999 -0.0194879 -0.0191377 1 0 1 1 0 0 +EDGE2 1990 1989 -0.970665 -0.0273407 0.00485176 1 0 1 1 0 0 +EDGE2 1991 1970 -0.986906 0.0371399 1.55516 1 0 1 1 0 0 +EDGE2 1991 1990 -1.0075 0.030087 1.60491 1 0 1 1 0 0 +EDGE2 1992 1991 -0.889089 0.00876667 -0.0115424 1 0 1 1 0 0 +EDGE2 1993 1992 -0.979778 -0.0577887 -0.0228168 1 0 1 1 0 0 +EDGE2 1994 1993 -1.003 -0.0523314 -0.0176558 1 0 1 1 0 0 +EDGE2 1995 1994 -1.0749 -0.00669704 0.00311574 1 0 1 1 0 0 +EDGE2 1996 1995 -1.07875 0.0332414 -1.55955 1 0 1 1 0 0 +EDGE2 1997 1996 -0.973014 -0.0101613 -0.00368584 1 0 1 1 0 0 +EDGE2 1998 1997 -0.994255 -0.0436559 -0.00811794 1 0 1 1 0 0 +EDGE2 1999 1998 -0.999811 0.0197544 0.0182535 1 0 1 1 0 0 +EDGE2 2000 1999 -0.947696 -0.0869239 0.0102297 1 0 1 1 0 0 +EDGE2 2001 2000 -0.973752 0.0691682 -1.60947 1 0 1 1 0 0 +EDGE2 2002 2001 -1.05464 0.123964 0.0183274 1 0 1 1 0 0 +EDGE2 2003 2002 -1.0143 0.0423181 -0.00525544 1 0 1 1 0 0 +EDGE2 2004 2003 -1.09083 -0.0351689 0.00792952 1 0 1 1 0 0 +EDGE2 2005 2004 -0.908782 -0.0254165 -0.0143975 1 0 1 1 0 0 +EDGE2 2006 2005 -1.01976 -0.0331941 1.56854 1 0 1 1 0 0 +EDGE2 2007 2006 -1.0568 0.0397136 0.0251142 1 0 1 1 0 0 +EDGE2 2008 2007 -0.958366 0.00878078 -0.0209455 1 0 1 1 0 0 +EDGE2 2009 2008 -0.965193 0.01105 -0.00803488 1 0 1 1 0 0 +EDGE2 2010 2009 -0.976531 0.0809394 0.00656133 1 0 1 1 0 0 +EDGE2 2011 2010 -1.07244 0.0756217 -1.58931 1 0 1 1 0 0 +EDGE2 2012 2011 -0.953108 0.0135975 0.0299713 1 0 1 1 0 0 +EDGE2 2013 2012 -1.08004 0.0101901 -0.0191886 1 0 1 1 0 0 +EDGE2 2014 2013 -0.896443 0.0700767 -0.0157352 1 0 1 1 0 0 +EDGE2 2015 2014 -1.01383 0.00596184 -0.00901969 1 0 1 1 0 0 +EDGE2 2016 2015 -1.05566 -0.0720228 1.57461 1 0 1 1 0 0 +EDGE2 2017 2016 -0.996657 -0.0580298 0.0212475 1 0 1 1 0 0 +EDGE2 2018 2017 -1.02126 -0.0525167 -0.00246928 1 0 1 1 0 0 +EDGE2 2019 2018 -1.07095 0.00424662 -0.000571737 1 0 1 1 0 0 +EDGE2 2020 2019 -0.974978 0.0683737 0.0115495 1 0 1 1 0 0 +EDGE2 2021 2020 -1.0224 0.00545924 -1.55022 1 0 1 1 0 0 +EDGE2 2022 2021 -0.93369 -0.0720647 -0.0111007 1 0 1 1 0 0 +EDGE2 2023 2022 -0.891795 0.0678456 -0.0134894 1 0 1 1 0 0 +EDGE2 2024 2023 -0.92219 0.0205852 0.0148953 1 0 1 1 0 0 +EDGE2 2025 2024 -0.989427 -0.0474381 -0.0113209 1 0 1 1 0 0 +EDGE2 2026 2025 -1.06307 0.00217862 -1.58854 1 0 1 1 0 0 +EDGE2 2027 2026 -1.03087 0.0852776 0.0164415 1 0 1 1 0 0 +EDGE2 2028 2027 -1.04948 -0.0192385 0.0214181 1 0 1 1 0 0 +EDGE2 2029 2028 -1.07877 -0.0576971 -0.00977899 1 0 1 1 0 0 +EDGE2 2029 1770 0.967999 0.068146 -3.1459 1 0 1 1 0 0 +EDGE2 2030 2029 -1.0711 0.0793798 0.00827537 1 0 1 1 0 0 +EDGE2 2030 1770 -0.123098 0.0633544 -3.16166 1 0 1 1 0 0 +EDGE2 2030 1771 0.0515934 -1.04544 -1.55233 1 0 1 1 0 0 +EDGE2 2030 1769 1.04109 -0.0316559 -3.13415 1 0 1 1 0 0 +EDGE2 2031 1770 -1.07055 -0.0662899 -1.5828 1 0 1 1 0 0 +EDGE2 2031 2030 -0.995306 0.0415322 1.56804 1 0 1 1 0 0 +EDGE2 2031 1771 -0.00946214 -0.0364417 0.0106513 1 0 1 1 0 0 +EDGE2 2031 1772 1.06457 0.0331958 0.00722261 1 0 1 1 0 0 +EDGE2 2032 2031 -1.1349 -0.0164872 0.00476837 1 0 1 1 0 0 +EDGE2 2032 1771 -1.06965 -0.0186978 -0.00491418 1 0 1 1 0 0 +EDGE2 2032 1772 -0.0388556 0.0117188 0.0207303 1 0 1 1 0 0 +EDGE2 2032 1773 1.05593 -0.0637715 0.00746517 1 0 1 1 0 0 +EDGE2 2033 2032 -0.874984 0.0170643 0.0221874 1 0 1 1 0 0 +EDGE2 2033 1772 -1.02996 -0.0163435 -0.0235294 1 0 1 1 0 0 +EDGE2 2033 1773 -0.0274608 -0.00322703 0.0251846 1 0 1 1 0 0 +EDGE2 2033 1774 0.980111 -0.0052702 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Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file DiscreteBayesNet_FG.cpp + * @brief Discrete Bayes Net example using Factor Graphs + * @author Abhijit + * @date Jun 4, 2012 + * + * We use the famous Rain/Cloudy/Sprinkler Example of [Russell & Norvig, 2009, p529] + * You may be familiar with other graphical model packages like BNT (available + * at http://bnt.googlecode.com/svn/trunk/docs/usage.html) where this is used as an + * example. The following demo is same as that in the above link, except that + * everything is using GTSAM. + */ + +#include +#include +#include + +using namespace std; +using namespace gtsam; + +int main(int argc, char **argv) { + + // We assume binary state variables + // we have 0 == "False" and 1 == "True" + const size_t nrStates = 2; + + // define variables + DiscreteKey Cloudy(1, nrStates), Sprinkler(2, nrStates), Rain(3, nrStates), + WetGrass(4, nrStates); + + // create Factor Graph of the bayes net + DiscreteFactorGraph graph; + + // add factors + graph.add(Cloudy, "0.5 0.5"); //P(Cloudy) + graph.add(Cloudy & Sprinkler, "0.5 0.5 0.9 0.1"); //P(Sprinkler | Cloudy) + graph.add(Cloudy & Rain, "0.8 0.2 0.2 0.8"); //P(Rain | Cloudy) + graph.add(Sprinkler & Rain & WetGrass, + "1 0 0.1 0.9 0.1 0.9 0.001 0.99"); //P(WetGrass | Sprinkler, Rain) + + // Alternatively we can also create a DiscreteBayesNet, add DiscreteConditional + // factors and create a FactorGraph from it. (See testDiscreteBayesNet.cpp) + + // Since this is a relatively small distribution, we can as well print + // the whole distribution.. + cout << "Distribution of Example: " << endl; + cout << setw(11) << "Cloudy(C)" << setw(14) << "Sprinkler(S)" << setw(10) + << "Rain(R)" << setw(14) << "WetGrass(W)" << setw(15) << "P(C,S,R,W)" + << endl; + for (size_t a = 0; a < nrStates; a++) + for (size_t m = 0; m < nrStates; m++) + for (size_t h = 0; h < nrStates; h++) + for (size_t c = 0; c < nrStates; c++) { + DiscreteFactor::Values values; + values[Cloudy.first] = c; + values[Sprinkler.first] = h; + values[Rain.first] = m; + values[WetGrass.first] = a; + double prodPot = graph(values); + cout << boolalpha << setw(8) << (bool) c << setw(14) + << (bool) h << setw(12) << (bool) m << setw(13) + << (bool) a << setw(16) << prodPot << endl; + } + + + // "Most Probable Explanation", i.e., configuration with largest value + DiscreteSequentialSolver solver(graph); + DiscreteFactor::sharedValues optimalDecoding = solver.optimize(); + cout <<"\nMost Probable Explanation (MPE):" << endl; + cout << boolalpha << "Cloudy = " << (bool)(*optimalDecoding)[Cloudy.first] + << " Sprinkler = " << (bool)(*optimalDecoding)[Sprinkler.first] + << " Rain = " << boolalpha << (bool)(*optimalDecoding)[Rain.first] + << " WetGrass = " << (bool)(*optimalDecoding)[WetGrass.first]<< endl; + + + // "Inference" We show an inference query like: probability that the Sprinkler was on; + // given that the grass is wet i.e. P( S | W=1) =? + cout << "\nInference Query: Probability of Sprinkler being on given Grass is Wet" << endl; + + // Method 1: we can compute the joint marginal P(S,W) and from that we can compute + // P(S | W=1) = P(S,W=1)/P(W=1) We do this in following three steps.. + + //Step1: Compute P(S,W) + DiscreteFactorGraph jointFG; + jointFG = *solver.jointFactorGraph(DiscreteKeys(Sprinkler & WetGrass).indices()); + DecisionTreeFactor probSW = jointFG.product(); + + //Step2: Compute P(W) + DiscreteFactor::shared_ptr probW = solver.marginalFactor(WetGrass.first); + + //Step3: Computer P(S | W=1) = P(S,W=1)/P(W=1) + DiscreteFactor::Values values; + values[WetGrass.first] = 1; + + //print P(S=0|W=1) + values[Sprinkler.first] = 0; + cout << "P(S=0|W=1) = " << probSW(values)/(*probW)(values) << endl; + + //print P(S=1|W=1) + values[Sprinkler.first] = 1; + cout << "P(S=1|W=1) = " << probSW(values)/(*probW)(values) << endl; + + // TODO: Method 2 : One way is to modify the factor graph to + // incorporate the evidence node and compute the marginal + // TODO: graph.addEvidence(Cloudy,0); + + return 0; +} diff --git a/examples/LocalizationExample.cpp b/examples/LocalizationExample.cpp new file mode 100644 index 000000000..dfe3d1e99 --- /dev/null +++ b/examples/LocalizationExample.cpp @@ -0,0 +1,159 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file LocalizationExample.cpp + * @brief Simple robot localization example, with three "GPS-like" measurements + * @author Frank Dellaert + */ + +/** + * A simple 2D pose slam example with "GPS" measurements + * - The robot moves forward 2 meter each iteration + * - The robot initially faces along the X axis (horizontal, to the right in 2D) + * - We have full odometry between pose + * - We have "GPS-like" measurements implemented with a custom factor + */ + +// We will use Pose2 variables (x, y, theta) to represent the robot positions +#include + +// We will use simple integer Keys to refer to the robot poses. +#include + +// As in OdometryExample.cpp, we use a BetweenFactor to model odometry measurements. +#include + +// We add all facors to a Nonlinear Factor Graph, as our factors are nonlinear. +#include + +// The nonlinear solvers within GTSAM are iterative solvers, meaning they linearize the +// nonlinear functions around an initial linearization point, then solve the linear system +// to update the linearization point. This happens repeatedly until the solver converges +// to a consistent set of variable values. This requires us to specify an initial guess +// for each variable, held in a Values container. +#include + +// Finally, once all of the factors have been added to our factor graph, we will want to +// solve/optimize to graph to find the best (Maximum A Posteriori) set of variable values. +// GTSAM includes several nonlinear optimizers to perform this step. Here we will use the +// standard Levenberg-Marquardt solver +#include + +// Once the optimized values have been calculated, we can also calculate the marginal covariance +// of desired variables +#include + +using namespace std; +using namespace gtsam; + +// Before we begin the example, we must create a custom unary factor to implement a +// "GPS-like" functionality. Because standard GPS measurements provide information +// only on the position, and not on the orientation, we cannot use a simple prior to +// properly model this measurement. +// +// The factor will be a unary factor, affect only a single system variable. It will +// also use a standard Gaussian noise model. Hence, we will derive our new factor from +// the NoiseModelFactor1. +#include + +class UnaryFactor: public NoiseModelFactor1 { + + // The factor will hold a measurement consisting of an (X,Y) location + // We could this with a Point2 but here we just use two doubles + double mx_, my_; + +public: + /// shorthand for a smart pointer to a factor + typedef boost::shared_ptr shared_ptr; + + // The constructor requires the variable key, the (X, Y) measurement value, and the noise model + UnaryFactor(Key j, double x, double y, const SharedNoiseModel& model): + NoiseModelFactor1(model, j), mx_(x), my_(y) {} + + virtual ~UnaryFactor() {} + + // Using the NoiseModelFactor1 base class there are two functions that must be overridden. + // The first is the 'evaluateError' function. This function implements the desired measurement + // function, returning a vector of errors when evaluated at the provided variable value. It + // must also calculate the Jacobians for this measurement function, if requested. + Vector evaluateError(const Pose2& q, boost::optional H = boost::none) const + { + // The measurement function for a GPS-like measurement is simple: + // error_x = pose.x - measurement.x + // error_y = pose.y - measurement.y + // Consequently, the Jacobians are: + // [ derror_x/dx derror_x/dy derror_x/dtheta ] = [1 0 0] + // [ derror_y/dx derror_y/dy derror_y/dtheta ] = [0 1 0] + if (H) (*H) = Matrix_(2,3, 1.0,0.0,0.0, 0.0,1.0,0.0); + return Vector_(2, q.x() - mx_, q.y() - my_); + } + + // The second is a 'clone' function that allows the factor to be copied. Under most + // circumstances, the following code that employs the default copy constructor should + // work fine. + virtual gtsam::NonlinearFactor::shared_ptr clone() const { + return boost::static_pointer_cast( + gtsam::NonlinearFactor::shared_ptr(new UnaryFactor(*this))); } + + // Additionally, we encourage you the use of unit testing your custom factors, + // (as all GTSAM factors are), in which you would need an equals and print, to satisfy the + // GTSAM_CONCEPT_TESTABLE_INST(T) defined in Testable.h, but these are not needed below. + +}; // UnaryFactor + + +int main(int argc, char** argv) { + + // 1. Create a factor graph container and add factors to it + NonlinearFactorGraph graph; + + // 2a. Add odometry factors + // For simplicity, we will use the same noise model for each odometry factor + noiseModel::Diagonal::shared_ptr odometryNoise = noiseModel::Diagonal::Sigmas(Vector_(3, 0.2, 0.2, 0.1)); + // Create odometry (Between) factors between consecutive poses + graph.add(BetweenFactor(1, 2, Pose2(2.0, 0.0, 0.0), odometryNoise)); + graph.add(BetweenFactor(2, 3, Pose2(2.0, 0.0, 0.0), odometryNoise)); + + // 2b. Add "GPS-like" measurements + // We will use our custom UnaryFactor for this. + noiseModel::Diagonal::shared_ptr unaryNoise = noiseModel::Diagonal::Sigmas(Vector_(2, 0.1, 0.1)); // 10cm std on x,y + graph.push_back(boost::make_shared(1, 0.0, 0.0, unaryNoise)); + graph.push_back(boost::make_shared(2, 2.0, 0.0, unaryNoise)); + graph.push_back(boost::make_shared(3, 4.0, 0.0, unaryNoise)); + graph.print("\nFactor Graph:\n"); // print + + // 3. Create the data structure to hold the initialEstimate estimate to the solution + // For illustrative purposes, these have been deliberately set to incorrect values + Values initialEstimate; + initialEstimate.insert(1, Pose2(0.5, 0.0, 0.2)); + initialEstimate.insert(2, Pose2(2.3, 0.1, -0.2)); + initialEstimate.insert(3, Pose2(4.1, 0.1, 0.1)); + initialEstimate.print("\nInitial Estimate:\n"); // print + + // 4. Optimize using Levenberg-Marquardt optimization. The optimizer + // accepts an optional set of configuration parameters, controlling + // things like convergence criteria, the type of linear system solver + // to use, and the amount of information displayed during optimization. + // Here we will use the default set of parameters. See the + // documentation for the full set of parameters. + LevenbergMarquardtOptimizer optimizer(graph, initialEstimate); + Values result = optimizer.optimize(); + result.print("Final Result:\n"); + + // 5. Calculate and print marginal covariances for all variables + Marginals marginals(graph, result); + cout << "x1 covariance:\n" << marginals.marginalCovariance(1) << endl; + cout << "x2 covariance:\n" << marginals.marginalCovariance(2) << endl; + cout << "x3 covariance:\n" << marginals.marginalCovariance(3) << endl; + + return 0; +} diff --git a/examples/OdometryExample.cpp b/examples/OdometryExample.cpp new file mode 100644 index 000000000..d556798f0 --- /dev/null +++ b/examples/OdometryExample.cpp @@ -0,0 +1,99 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file OdometryExample.cpp + * @brief Simple robot motion example, with prior and two odometry measurements + * @author Frank Dellaert + */ + +/** + * Example of a simple 2D localization example + * - Robot poses are facing along the X axis (horizontal, to the right in 2D) + * - The robot moves 2 meters each step + * - We have full odometry between poses + */ + +// We will use Pose2 variables (x, y, theta) to represent the robot positions +#include + +// In GTSAM, measurement functions are represented as 'factors'. Several common factors +// have been provided with the library for solving robotics/SLAM/Bundle Adjustment problems. +// Here we will use Between factors for the relative motion described by odometry measurements. +// Also, we will initialize the robot at the origin using a Prior factor. +#include +#include + +// When the factors are created, we will add them to a Factor Graph. As the factors we are using +// are nonlinear factors, we will need a Nonlinear Factor Graph. +#include + +// Finally, once all of the factors have been added to our factor graph, we will want to +// solve/optimize to graph to find the best (Maximum A Posteriori) set of variable values. +// GTSAM includes several nonlinear optimizers to perform this step. Here we will use the +// Levenberg-Marquardt solver +#include + +// Once the optimized values have been calculated, we can also calculate the marginal covariance +// of desired variables +#include + +// The nonlinear solvers within GTSAM are iterative solvers, meaning they linearize the +// nonlinear functions around an initial linearization point, then solve the linear system +// to update the linearization point. This happens repeatedly until the solver converges +// to a consistent set of variable values. This requires us to specify an initial guess +// for each variable, held in a Values container. +#include + +using namespace std; +using namespace gtsam; + +int main(int argc, char** argv) { + + // Create an empty nonlinear factor graph + NonlinearFactorGraph graph; + + // Add a prior on the first pose, setting it to the origin + // A prior factor consists of a mean and a noise model (covariance matrix) + Pose2 priorMean(0.0, 0.0, 0.0); // prior at origin + noiseModel::Diagonal::shared_ptr priorNoise = noiseModel::Diagonal::Sigmas(Vector_(3, 0.3, 0.3, 0.1)); + graph.add(PriorFactor(1, priorMean, priorNoise)); + + // Add odometry factors + Pose2 odometry(2.0, 0.0, 0.0); + // For simplicity, we will use the same noise model for each odometry factor + noiseModel::Diagonal::shared_ptr odometryNoise = noiseModel::Diagonal::Sigmas(Vector_(3, 0.2, 0.2, 0.1)); + // Create odometry (Between) factors between consecutive poses + graph.add(BetweenFactor(1, 2, odometry, odometryNoise)); + graph.add(BetweenFactor(2, 3, odometry, odometryNoise)); + graph.print("\nFactor Graph:\n"); // print + + // Create the data structure to hold the initialEstimate estimate to the solution + // For illustrative purposes, these have been deliberately set to incorrect values + Values initial; + initial.insert(1, Pose2(0.5, 0.0, 0.2)); + initial.insert(2, Pose2(2.3, 0.1, -0.2)); + initial.insert(3, Pose2(4.1, 0.1, 0.1)); + initial.print("\nInitial Estimate:\n"); // print + + // optimize using Levenberg-Marquardt optimization + Values result = LevenbergMarquardtOptimizer(graph, initial).optimize(); + result.print("Final Result:\n"); + + // Calculate and print marginal covariances for all variables + cout.precision(2); + Marginals marginals(graph, result); + cout << "x1 covariance:\n" << marginals.marginalCovariance(1) << endl; + cout << "x2 covariance:\n" << marginals.marginalCovariance(2) << endl; + cout << "x3 covariance:\n" << marginals.marginalCovariance(3) << endl; + + return 0; +} diff --git a/examples/PlanarSLAMExample.cpp b/examples/PlanarSLAMExample.cpp new file mode 100644 index 000000000..c6f6b636f --- /dev/null +++ b/examples/PlanarSLAMExample.cpp @@ -0,0 +1,142 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file PlanarSLAMExample.cpp + * @brief Simple robotics example using odometry measurements and bearing-range (laser) measurements + * @author Alex Cunningham + */ + +/** + * A simple 2D planar slam example with landmarks + * - The robot and landmarks are on a 2 meter grid + * - Robot poses are facing along the X axis (horizontal, to the right in 2D) + * - The robot moves 2 meters each step + * - We have full odometry between poses + * - We have bearing and range information for measurements + * - Landmarks are 2 meters away from the robot trajectory + */ + +// As this is a planar SLAM example, we will use Pose2 variables (x, y, theta) to represent +// the robot positions and Point2 variables (x, y) to represent the landmark coordinates. +#include +#include + +// Each variable in the system (poses and landmarks) must be identified with a unique key. +// We can either use simple integer keys (1, 2, 3, ...) or symbols (X1, X2, L1). +// Here we will use Symbols +#include + +// In GTSAM, measurement functions are represented as 'factors'. Several common factors +// have been provided with the library for solving robotics/SLAM/Bundle Adjustment problems. +// Here we will use a RangeBearing factor for the range-bearing measurements to identified +// landmarks, and Between factors for the relative motion described by odometry measurements. +// Also, we will initialize the robot at the origin using a Prior factor. +#include +#include +#include + +// When the factors are created, we will add them to a Factor Graph. As the factors we are using +// are nonlinear factors, we will need a Nonlinear Factor Graph. +#include + +// Finally, once all of the factors have been added to our factor graph, we will want to +// solve/optimize to graph to find the best (Maximum A Posteriori) set of variable values. +// GTSAM includes several nonlinear optimizers to perform this step. Here we will use the +// common Levenberg-Marquardt solver +#include + +// Once the optimized values have been calculated, we can also calculate the marginal covariance +// of desired variables +#include + +// The nonlinear solvers within GTSAM are iterative solvers, meaning they linearize the +// nonlinear functions around an initial linearization point, then solve the linear system +// to update the linearization point. This happens repeatedly until the solver converges +// to a consistent set of variable values. This requires us to specify an initial guess +// for each variable, held in a Values container. +#include + + +using namespace std; +using namespace gtsam; + +int main(int argc, char** argv) { + + // Create a factor graph + NonlinearFactorGraph graph; + + // Create the keys we need for this simple example + static Symbol x1('x',1), x2('x',2), x3('x',3); + static Symbol l1('l',1), l2('l',2); + + // Add a prior on pose x1 at the origin. A prior factor consists of a mean and a noise model (covariance matrix) + Pose2 prior(0.0, 0.0, 0.0); // prior mean is at origin + noiseModel::Diagonal::shared_ptr priorNoise = noiseModel::Diagonal::Sigmas(Vector_(3, 0.3, 0.3, 0.1)); // 30cm std on x,y, 0.1 rad on theta + graph.add(PriorFactor(x1, prior, priorNoise)); // add directly to graph + + // Add two odometry factors + Pose2 odometry(2.0, 0.0, 0.0); // create a measurement for both factors (the same in this case) + noiseModel::Diagonal::shared_ptr odometryNoise = noiseModel::Diagonal::Sigmas(Vector_(3, 0.2, 0.2, 0.1)); // 20cm std on x,y, 0.1 rad on theta + graph.add(BetweenFactor(x1, x2, odometry, odometryNoise)); + graph.add(BetweenFactor(x2, x3, odometry, odometryNoise)); + + // Add Range-Bearing measurements to two different landmarks + // create a noise model for the landmark measurements + noiseModel::Diagonal::shared_ptr measurementNoise = noiseModel::Diagonal::Sigmas(Vector_(2, 0.1, 0.2)); // 0.1 rad std on bearing, 20cm on range + // create the measurement values - indices are (pose id, landmark id) + Rot2 bearing11 = Rot2::fromDegrees(45), + bearing21 = Rot2::fromDegrees(90), + bearing32 = Rot2::fromDegrees(90); + double range11 = std::sqrt(4.0+4.0), + range21 = 2.0, + range32 = 2.0; + + // Add Bearing-Range factors + graph.add(BearingRangeFactor(x1, l1, bearing11, range11, measurementNoise)); + graph.add(BearingRangeFactor(x2, l1, bearing21, range21, measurementNoise)); + graph.add(BearingRangeFactor(x3, l2, bearing32, range32, measurementNoise)); + + // Print + graph.print("Factor Graph:\n"); + + // Create (deliberately inaccurate) initial estimate + Values initialEstimate; + initialEstimate.insert(x1, Pose2(0.5, 0.0, 0.2)); + initialEstimate.insert(x2, Pose2(2.3, 0.1,-0.2)); + initialEstimate.insert(x3, Pose2(4.1, 0.1, 0.1)); + initialEstimate.insert(l1, Point2(1.8, 2.1)); + initialEstimate.insert(l2, Point2(4.1, 1.8)); + + // Print + initialEstimate.print("Initial Estimate:\n"); + + // Optimize using Levenberg-Marquardt optimization. The optimizer + // accepts an optional set of configuration parameters, controlling + // things like convergence criteria, the type of linear system solver + // to use, and the amount of information displayed during optimization. + // Here we will use the default set of parameters. See the + // documentation for the full set of parameters. + LevenbergMarquardtOptimizer optimizer(graph, initialEstimate); + Values result = optimizer.optimize(); + result.print("Final Result:\n"); + + // Calculate and print marginal covariances for all variables + Marginals marginals(graph, result); + print(marginals.marginalCovariance(x1), "x1 covariance"); + print(marginals.marginalCovariance(x2), "x2 covariance"); + print(marginals.marginalCovariance(x3), "x3 covariance"); + print(marginals.marginalCovariance(l1), "l1 covariance"); + print(marginals.marginalCovariance(l2), "l2 covariance"); + + return 0; +} + diff --git a/examples/PlanarSLAMExample_easy.cpp b/examples/PlanarSLAMExample_easy.cpp deleted file mode 100644 index 912589080..000000000 --- a/examples/PlanarSLAMExample_easy.cpp +++ /dev/null @@ -1,91 +0,0 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) - - * See LICENSE for the license information - - * -------------------------------------------------------------------------- */ - -/** - * @file PlanarSLAMExample.cpp - * @brief Simple robotics example using the pre-built planar SLAM domain - * @author Alex Cunningham - */ - -#include -#include - -// pull in the planar SLAM domain with all typedefs and helper functions defined -#include -#include - -using namespace std; -using namespace gtsam; -using namespace planarSLAM; - -/** - * In this version of the system we make the following assumptions: - * - All values are axis aligned - * - Robot poses are facing along the X axis (horizontal, to the right in images) - * - We have bearing and range information for measurements - * - We have full odometry for measurements - * - The robot and landmarks are on a grid, moving 2 meters each step - * - Landmarks are 2 meters away from the robot trajectory - */ -int main(int argc, char** argv) { - - // create graph container and add factors to it - Graph graph; - - /* add prior */ - // gaussian for prior - SharedDiagonal prior_model = noiseModel::Diagonal::Sigmas(Vector_(3, 0.3, 0.3, 0.1)); - Pose2 prior_measurement(0.0, 0.0, 0.0); // prior at origin - graph.addPrior(1, prior_measurement, prior_model); // add directly to graph - - /* add odometry */ - // general noisemodel for odometry - SharedDiagonal odom_model = noiseModel::Diagonal::Sigmas(Vector_(3, 0.2, 0.2, 0.1)); - Pose2 odom_measurement(2.0, 0.0, 0.0); // create a measurement for both factors (the same in this case) - graph.addOdometry(1, 2, odom_measurement, odom_model); - graph.addOdometry(2, 3, odom_measurement, odom_model); - - /* add measurements */ - // general noisemodel for measurements - SharedDiagonal meas_model = noiseModel::Diagonal::Sigmas(Vector_(2, 0.1, 0.2)); - - // create the measurement values - indices are (pose id, landmark id) - Rot2 bearing11 = Rot2::fromDegrees(45), - bearing21 = Rot2::fromDegrees(90), - bearing32 = Rot2::fromDegrees(90); - double range11 = sqrt(4+4), - range21 = 2.0, - range32 = 2.0; - - // create bearing/range factors and add them - graph.addBearingRange(1, 1, bearing11, range11, meas_model); - graph.addBearingRange(2, 1, bearing21, range21, meas_model); - graph.addBearingRange(3, 2, bearing32, range32, meas_model); - - graph.print("full graph"); - - // initialize to noisy points - planarSLAM::Values initialEstimate; - initialEstimate.insertPose(1, Pose2(0.5, 0.0, 0.2)); - initialEstimate.insertPose(2, Pose2(2.3, 0.1,-0.2)); - initialEstimate.insertPose(3, Pose2(4.1, 0.1, 0.1)); - initialEstimate.insertPoint(1, Point2(1.8, 2.1)); - initialEstimate.insertPoint(2, Point2(4.1, 1.8)); - - initialEstimate.print("initial estimate"); - - // optimize using Levenberg-Marquardt optimization with an ordering from colamd - planarSLAM::Values result = LevenbergMarquardtOptimizer(graph, initialEstimate).optimize(); - result.print("final result"); - - return 0; -} - diff --git a/examples/PlanarSLAMSelfContained_advanced.cpp b/examples/PlanarSLAMSelfContained_advanced.cpp deleted file mode 100644 index bd5c5295a..000000000 --- a/examples/PlanarSLAMSelfContained_advanced.cpp +++ /dev/null @@ -1,137 +0,0 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) - - * See LICENSE for the license information - - * -------------------------------------------------------------------------- */ - -/** - * @file PlanarSLAMSelfContained_advanced.cpp - * @brief Simple robotics example with all typedefs internal to this script. - * @author Alex Cunningham - */ - -#include -#include - -// for all nonlinear keys -#include - -// for points and poses -#include -#include - -// for modeling measurement uncertainty - all models included here -#include - -// add in headers for specific factors -#include -#include -#include - -// implementations for structures - needed if self-contained, and these should be included last -#include -#include -#include - -using namespace std; -using namespace gtsam; - -/** - * In this version of the system we make the following assumptions: - * - All values are axis aligned - * - Robot poses are facing along the X axis (horizontal, to the right in images) - * - We have bearing and range information for measurements - * - We have full odometry for measurements - * - The robot and landmarks are on a grid, moving 2 meters each step - * - Landmarks are 2 meters away from the robot trajectory - */ -int main(int argc, char** argv) { - // create keys for variables - Symbol x1('x',1), x2('x',2), x3('x',3); - Symbol l1('l',1), l2('l',2); - - // create graph container and add factors to it - NonlinearFactorGraph graph; - - /* add prior */ - // gaussian for prior - SharedDiagonal prior_model = noiseModel::Diagonal::Sigmas(Vector_(3, 0.3, 0.3, 0.1)); - Pose2 prior_measurement(0.0, 0.0, 0.0); // prior at origin - PriorFactor posePrior(x1, prior_measurement, prior_model); // create the factor - graph.add(posePrior); // add the factor to the graph - - /* add odometry */ - // general noisemodel for odometry - SharedDiagonal odom_model = noiseModel::Diagonal::Sigmas(Vector_(3, 0.2, 0.2, 0.1)); - Pose2 odom_measurement(2.0, 0.0, 0.0); // create a measurement for both factors (the same in this case) - // create between factors to represent odometry - BetweenFactor odom12(x1, x2, odom_measurement, odom_model); - BetweenFactor odom23(x2, x3, odom_measurement, odom_model); - graph.add(odom12); // add both to graph - graph.add(odom23); - - /* add measurements */ - // general noisemodel for measurements - SharedDiagonal meas_model = noiseModel::Diagonal::Sigmas(Vector_(2, 0.1, 0.2)); - - // create the measurement values - indices are (pose id, landmark id) - Rot2 bearing11 = Rot2::fromDegrees(45), - bearing21 = Rot2::fromDegrees(90), - bearing32 = Rot2::fromDegrees(90); - double range11 = sqrt(4+4), - range21 = 2.0, - range32 = 2.0; - - // create bearing/range factors - BearingRangeFactor meas11(x1, l1, bearing11, range11, meas_model); - BearingRangeFactor meas21(x2, l1, bearing21, range21, meas_model); - BearingRangeFactor meas32(x3, l2, bearing32, range32, meas_model); - - // add the factors - graph.add(meas11); - graph.add(meas21); - graph.add(meas32); - - graph.print("Full Graph"); - - // initialize to noisy points - Values initial; - initial.insert(x1, Pose2(0.5, 0.0, 0.2)); - initial.insert(x2, Pose2(2.3, 0.1,-0.2)); - initial.insert(x3, Pose2(4.1, 0.1, 0.1)); - initial.insert(l1, Point2(1.8, 2.1)); - initial.insert(l2, Point2(4.1, 1.8)); - - initial.print("initial estimate"); - - // optimize using Levenberg-Marquardt optimization with an ordering from colamd - - // first using sequential elimination - LevenbergMarquardtParams lmParams; - lmParams.elimination = LevenbergMarquardtParams::SEQUENTIAL; - Values resultSequential = LevenbergMarquardtOptimizer(graph, initial, lmParams).optimize(); - resultSequential.print("final result (solved with a sequential solver)"); - - // then using multifrontal, advanced interface - // Note that we keep the original optimizer object so we can use the COLAMD - // ordering it computes. - LevenbergMarquardtOptimizer optimizer(graph, initial); - Values resultMultifrontal = optimizer.optimize(); - resultMultifrontal.print("final result (solved with a multifrontal solver)"); - - // Print marginals covariances for all variables - Marginals marginals(graph, resultMultifrontal, Marginals::CHOLESKY); - print(marginals.marginalCovariance(x1), "x1 covariance"); - print(marginals.marginalCovariance(x2), "x2 covariance"); - print(marginals.marginalCovariance(x3), "x3 covariance"); - print(marginals.marginalCovariance(l1), "l1 covariance"); - print(marginals.marginalCovariance(l2), "l2 covariance"); - - return 0; -} - diff --git a/examples/Pose2SLAMExample.cpp b/examples/Pose2SLAMExample.cpp new file mode 100644 index 000000000..4885e72c8 --- /dev/null +++ b/examples/Pose2SLAMExample.cpp @@ -0,0 +1,130 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file Pose2SLAMExample.cpp + * @brief A 2D Pose SLAM example + * @date Oct 21, 2010 + * @author Yong Dian Jian + */ + +/** + * A simple 2D pose slam example + * - The robot moves in a 2 meter square + * - The robot moves 2 meters each step, turning 90 degrees after each step + * - The robot initially faces along the X axis (horizontal, to the right in 2D) + * - We have full odometry between pose + * - We have a loop closure constraint when the robot returns to the first position + */ + +// In planar SLAM example we use Pose2 variables (x, y, theta) to represent the robot poses +#include + +// We will use simple integer Keys to refer to the robot poses. +#include + +// In GTSAM, measurement functions are represented as 'factors'. Several common factors +// have been provided with the library for solving robotics/SLAM/Bundle Adjustment problems. +// Here we will use Between factors for the relative motion described by odometry measurements. +// We will also use a Between Factor to encode the loop closure constraint +// Also, we will initialize the robot at the origin using a Prior factor. +#include +#include + +// When the factors are created, we will add them to a Factor Graph. As the factors we are using +// are nonlinear factors, we will need a Nonlinear Factor Graph. +#include + +// Finally, once all of the factors have been added to our factor graph, we will want to +// solve/optimize to graph to find the best (Maximum A Posteriori) set of variable values. +// GTSAM includes several nonlinear optimizers to perform this step. Here we will use the +// a Gauss-Newton solver +#include + +// Once the optimized values have been calculated, we can also calculate the marginal covariance +// of desired variables +#include + +// The nonlinear solvers within GTSAM are iterative solvers, meaning they linearize the +// nonlinear functions around an initial linearization point, then solve the linear system +// to update the linearization point. This happens repeatedly until the solver converges +// to a consistent set of variable values. This requires us to specify an initial guess +// for each variable, held in a Values container. +#include + + +using namespace std; +using namespace gtsam; + +int main(int argc, char** argv) { + + // 1. Create a factor graph container and add factors to it + NonlinearFactorGraph graph; + + // 2a. Add a prior on the first pose, setting it to the origin + // A prior factor consists of a mean and a noise model (covariance matrix) + noiseModel::Diagonal::shared_ptr priorNoise = noiseModel::Diagonal::Sigmas(Vector_(3, 0.3, 0.3, 0.1)); + graph.add(PriorFactor(1, Pose2(0, 0, 0), priorNoise)); + + // For simplicity, we will use the same noise model for odometry and loop closures + noiseModel::Diagonal::shared_ptr model = noiseModel::Diagonal::Sigmas(Vector_(3, 0.2, 0.2, 0.1)); + + // 2b. Add odometry factors + // Create odometry (Between) factors between consecutive poses + graph.add(BetweenFactor(1, 2, Pose2(2, 0, 0 ), model)); + graph.add(BetweenFactor(2, 3, Pose2(2, 0, M_PI_2), model)); + graph.add(BetweenFactor(3, 4, Pose2(2, 0, M_PI_2), model)); + graph.add(BetweenFactor(4, 5, Pose2(2, 0, M_PI_2), model)); + + // 2c. Add the loop closure constraint + // This factor encodes the fact that we have returned to the same pose. In real systems, + // these constraints may be identified in many ways, such as appearance-based techniques + // with camera images. We will use another Between Factor to enforce this constraint: + graph.add(BetweenFactor(5, 2, Pose2(2, 0, M_PI_2), model)); + graph.print("\nFactor Graph:\n"); // print + + // 3. Create the data structure to hold the initialEstimate estimate to the solution + // For illustrative purposes, these have been deliberately set to incorrect values + Values initialEstimate; + initialEstimate.insert(1, Pose2(0.5, 0.0, 0.2 )); + initialEstimate.insert(2, Pose2(2.3, 0.1, -0.2 )); + initialEstimate.insert(3, Pose2(4.1, 0.1, M_PI_2)); + initialEstimate.insert(4, Pose2(4.0, 2.0, M_PI )); + initialEstimate.insert(5, Pose2(2.1, 2.1, -M_PI_2)); + initialEstimate.print("\nInitial Estimate:\n"); // print + + // 4. Optimize the initial values using a Gauss-Newton nonlinear optimizer + // The optimizer accepts an optional set of configuration parameters, + // controlling things like convergence criteria, the type of linear + // system solver to use, and the amount of information displayed during + // optimization. We will set a few parameters as a demonstration. + GaussNewtonParams parameters; + // Stop iterating once the change in error between steps is less than this value + parameters.relativeErrorTol = 1e-5; + // Do not perform more than N iteration steps + parameters.maxIterations = 100; + // Create the optimizer ... + GaussNewtonOptimizer optimizer(graph, initialEstimate, parameters); + // ... and optimize + Values result = optimizer.optimize(); + result.print("Final Result:\n"); + + // 5. Calculate and print marginal covariances for all variables + cout.precision(3); + Marginals marginals(graph, result); + cout << "x1 covariance:\n" << marginals.marginalCovariance(1) << endl; + cout << "x2 covariance:\n" << marginals.marginalCovariance(2) << endl; + cout << "x3 covariance:\n" << marginals.marginalCovariance(3) << endl; + cout << "x4 covariance:\n" << marginals.marginalCovariance(4) << endl; + cout << "x5 covariance:\n" << marginals.marginalCovariance(5) << endl; + + return 0; +} diff --git a/examples/Pose2SLAMExample_advanced.cpp b/examples/Pose2SLAMExample_advanced.cpp deleted file mode 100644 index 29d8c58cf..000000000 --- a/examples/Pose2SLAMExample_advanced.cpp +++ /dev/null @@ -1,88 +0,0 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) - - * See LICENSE for the license information - - * -------------------------------------------------------------------------- */ - -/** - * @file Pose2SLAMExample_advanced.cpp - * @brief Simple Pose2SLAM Example using - * pre-built pose2SLAM domain - * @author Chris Beall - */ - -#include -#include -#include - -// pull in the Pose2 SLAM domain with all typedefs and helper functions defined -#include -#include -#include - -#include -#include - -using namespace std; -using namespace gtsam; -using namespace boost; -using namespace pose2SLAM; - -int main(int argc, char** argv) { - /* 1. create graph container and add factors to it */ - Graph graph; - - /* 2.a add prior */ - // gaussian for prior - SharedDiagonal prior_model = noiseModel::Diagonal::Sigmas(Vector_(3, 0.3, 0.3, 0.1)); - Pose2 prior_measurement(0.0, 0.0, 0.0); // prior at origin - graph.addPrior(1, prior_measurement, prior_model); // add directly to graph - - /* 2.b add odometry */ - // general noisemodel for odometry - SharedDiagonal odom_model = noiseModel::Diagonal::Sigmas(Vector_(3, 0.2, 0.2, 0.1)); - - /* Pose2 measurements take (x,y,theta), where theta is taken from the positive x-axis*/ - Pose2 odom_measurement(2.0, 0.0, 0.0); // create a measurement for both factors (the same in this case) - graph.addOdometry(1, 2, odom_measurement, odom_model); - graph.addOdometry(2, 3, odom_measurement, odom_model); - graph.print("full graph"); - - /* 3. Create the data structure to hold the initial estimate to the solution - * initialize to noisy points */ - pose2SLAM::Values initial; - initial.insertPose(1, Pose2(0.5, 0.0, 0.2)); - initial.insertPose(2, Pose2(2.3, 0.1,-0.2)); - initial.insertPose(3, Pose2(4.1, 0.1, 0.1)); - initial.print("initial estimate"); - - /* 4.2.1 Alternatively, you can go through the process step by step - * Choose an ordering */ - Ordering ordering = *graph.orderingCOLAMD(initial); - - /* 4.2.2 set up solver and optimize */ - LevenbergMarquardtParams params; - params.absoluteErrorTol = 1e-15; - params.relativeErrorTol = 1e-15; - params.ordering = ordering; - LevenbergMarquardtOptimizer optimizer(graph, initial, params); - - pose2SLAM::Values result = optimizer.optimize(); - result.print("final result"); - - /* Get covariances */ - Marginals marginals(graph, result, Marginals::CHOLESKY); - Matrix covariance1 = marginals.marginalCovariance(PoseKey(1)); - Matrix covariance2 = marginals.marginalCovariance(PoseKey(2)); - - print(covariance1, "Covariance1"); - print(covariance2, "Covariance2"); - - return 0; -} - diff --git a/examples/Pose2SLAMExample_easy.cpp b/examples/Pose2SLAMExample_easy.cpp deleted file mode 100644 index 18a756aba..000000000 --- a/examples/Pose2SLAMExample_easy.cpp +++ /dev/null @@ -1,69 +0,0 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) - - * See LICENSE for the license information - - * -------------------------------------------------------------------------- */ - -/** - * @file Pose2SLAMExample_easy.cpp - * - * A 2D Pose SLAM example using the predefined typedefs in gtsam/slam/pose2SLAM.h - * - * @date Oct 21, 2010 - * @author ydjian - */ - -#include -#include -#include - -// pull in the Pose2 SLAM domain with all typedefs and helper functions defined -#include -#include - -using namespace std; -using namespace gtsam; -using namespace pose2SLAM; - -int main(int argc, char** argv) { - - /* 1. create graph container and add factors to it */ - Graph graph ; - - /* 2.a add prior */ - // gaussian for prior - SharedDiagonal prior_model = noiseModel::Diagonal::Sigmas(Vector_(3, 0.3, 0.3, 0.1)); - Pose2 prior_measurement(0.0, 0.0, 0.0); // prior at origin - graph.addPrior(1, prior_measurement, prior_model); // add directly to graph - - /* 2.b add odometry */ - // general noisemodel for odometry - SharedDiagonal odom_model = noiseModel::Diagonal::Sigmas(Vector_(3, 0.2, 0.2, 0.1)); - - /* Pose2 measurements take (x,y,theta), where theta is taken from the positive x-axis*/ - Pose2 odom_measurement(2.0, 0.0, 0.0); // create a measurement for both factors (the same in this case) - graph.addOdometry(1, 2, odom_measurement, odom_model); - graph.addOdometry(2, 3, odom_measurement, odom_model); - graph.print("full graph"); - - /* 3. Create the data structure to hold the initial estinmate to the solution - * initialize to noisy points */ - pose2SLAM::Values initial; - initial.insertPose(1, Pose2(0.5, 0.0, 0.2)); - initial.insertPose(2, Pose2(2.3, 0.1,-0.2)); - initial.insertPose(3, Pose2(4.1, 0.1, 0.1)); - initial.print("initial estimate"); - - /* 4 Single Step Optimization - * optimize using Levenberg-Marquardt optimization with an ordering from colamd */ - pose2SLAM::Values result = graph.optimize(initial); - result.print("final result"); - - - return 0; -} diff --git a/examples/Pose2SLAMExample_graph.cpp b/examples/Pose2SLAMExample_graph.cpp new file mode 100644 index 000000000..cc873eb08 --- /dev/null +++ b/examples/Pose2SLAMExample_graph.cpp @@ -0,0 +1,57 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file Pose2SLAMExample_graph->cpp + * @brief Read graph from file and perform GraphSLAM + * @date June 3, 2012 + * @author Frank Dellaert + */ + +#include +#include +#include +#include +#include +#include +#include +#include +#include + +using namespace std; +using namespace gtsam; + +int main(int argc, char** argv) { + + // Read File and create graph and initial estimate + // we are in build/examples, data is in examples/Data + NonlinearFactorGraph::shared_ptr graph ; + Values::shared_ptr initial; + SharedDiagonal model = noiseModel::Diagonal::Sigmas(Vector_(3, 0.05, 0.05, 5.0*M_PI/180.0)); + boost::tie(graph,initial) = load2D("../../examples/Data/w100-odom.graph",model); + initial->print("Initial estimate:\n"); + + // Add a Gaussian prior on first poses + Pose2 priorMean(0.0, 0.0, 0.0); // prior at origin + SharedDiagonal priorNoise = noiseModel::Diagonal::Sigmas(Vector_(3, 0.01, 0.01, 0.01)); + graph->add(PriorFactor(0, priorMean, priorNoise)); + + // Single Step Optimization using Levenberg-Marquardt + Values result = LevenbergMarquardtOptimizer(*graph, *initial).optimize(); + result.print("\nFinal result:\n"); + + // Plot the covariance of the last pose + Marginals marginals(*graph, result); + cout.precision(2); + cout << "\nP3:\n" << marginals.marginalCovariance(99) << endl; + +return 0; +} diff --git a/examples/Pose2SLAMwSPCG.cpp b/examples/Pose2SLAMwSPCG.cpp new file mode 100644 index 000000000..36f2552a1 --- /dev/null +++ b/examples/Pose2SLAMwSPCG.cpp @@ -0,0 +1,118 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file Pose2SLAMwSPCG.cpp + * @brief A 2D Pose SLAM example using the SimpleSPCGSolver. + * @author Yong-Dian Jian + * @date June 2, 2012 + */ + +/** + * A simple 2D pose slam example solved using a Conjugate-Gradient method + * - The robot moves in a 2 meter square + * - The robot moves 2 meters each step, turning 90 degrees after each step + * - The robot initially faces along the X axis (horizontal, to the right in 2D) + * - We have full odometry between pose + * - We have a loop closure constraint when the robot returns to the first position + */ + +// As this is a planar SLAM example, we will use Pose2 variables (x, y, theta) to represent +// the robot positions +#include +#include + +// Each variable in the system (poses) must be identified with a unique key. +// We can either use simple integer keys (1, 2, 3, ...) or symbols (X1, X2, L1). +// Here we will use simple integer keys +#include + +// In GTSAM, measurement functions are represented as 'factors'. Several common factors +// have been provided with the library for solving robotics/SLAM/Bundle Adjustment problems. +// Here we will use Between factors for the relative motion described by odometry measurements. +// We will also use a Between Factor to encode the loop closure constraint +// Also, we will initialize the robot at the origin using a Prior factor. +#include +#include + +// When the factors are created, we will add them to a Factor Graph. As the factors we are using +// are nonlinear factors, we will need a Nonlinear Factor Graph. +#include + +// The nonlinear solvers within GTSAM are iterative solvers, meaning they linearize the +// nonlinear functions around an initial linearization point, then solve the linear system +// to update the linearization point. This happens repeatedly until the solver converges +// to a consistent set of variable values. This requires us to specify an initial guess +// for each variable, held in a Values container. +#include + +#include +#include + +using namespace std; +using namespace gtsam; + +int main(int argc, char** argv) { + + // 1. Create a factor graph container and add factors to it + NonlinearFactorGraph graph; + + // 2a. Add a prior on the first pose, setting it to the origin + // A prior factor consists of a mean and a noise model (covariance matrix) + Pose2 prior(0.0, 0.0, 0.0); // prior at origin + noiseModel::Diagonal::shared_ptr priorNoise = noiseModel::Diagonal::Sigmas(Vector_(3, 0.3, 0.3, 0.1)); + graph.add(PriorFactor(1, prior, priorNoise)); + + // 2b. Add odometry factors + // For simplicity, we will use the same noise model for each odometry factor + noiseModel::Diagonal::shared_ptr odometryNoise = noiseModel::Diagonal::Sigmas(Vector_(3, 0.2, 0.2, 0.1)); + // Create odometry (Between) factors between consecutive poses + graph.add(BetweenFactor(1, 2, Pose2(2.0, 0.0, M_PI_2), odometryNoise)); + graph.add(BetweenFactor(2, 3, Pose2(2.0, 0.0, M_PI_2), odometryNoise)); + graph.add(BetweenFactor(3, 4, Pose2(2.0, 0.0, M_PI_2), odometryNoise)); + graph.add(BetweenFactor(4, 5, Pose2(2.0, 0.0, M_PI_2), odometryNoise)); + + // 2c. Add the loop closure constraint + // This factor encodes the fact that we have returned to the same pose. In real systems, + // these constraints may be identified in many ways, such as appearance-based techniques + // with camera images. + // We will use another Between Factor to enforce this constraint, with the distance set to zero, + noiseModel::Diagonal::shared_ptr model = noiseModel::Diagonal::Sigmas(Vector_(3, 0.2, 0.2, 0.1)); + graph.add(BetweenFactor(5, 1, Pose2(0.0, 0.0, 0.0), model)); + graph.print("\nFactor Graph:\n"); // print + + + // 3. Create the data structure to hold the initialEstimate estimate to the solution + // For illustrative purposes, these have been deliberately set to incorrect values + Values initialEstimate; + initialEstimate.insert(1, Pose2(0.5, 0.0, 0.2)); + initialEstimate.insert(2, Pose2(2.3, 0.1, 1.1)); + initialEstimate.insert(3, Pose2(2.1, 1.9, 2.8)); + initialEstimate.insert(4, Pose2(-.3, 2.5, 4.2)); + initialEstimate.insert(5, Pose2(0.1,-0.7, 5.8)); + initialEstimate.print("\nInitial Estimate:\n"); // print + + // 4. Single Step Optimization using Levenberg-Marquardt + LevenbergMarquardtParams parameters; + parameters.verbosity = NonlinearOptimizerParams::ERROR; + parameters.verbosityLM = LevenbergMarquardtParams::LAMBDA; + parameters.linearSolverType = SuccessiveLinearizationParams::CONJUGATE_GRADIENT; + + { + parameters.iterativeParams = boost::make_shared(); + LevenbergMarquardtOptimizer optimizer(graph, initialEstimate, parameters); + Values result = optimizer.optimize(); + result.print("Final Result:\n"); + cout << "subgraph solver final error = " << graph.error(result) << endl; + } + + return 0; +} diff --git a/examples/Pose2SLAMwSPCG_advanced.cpp b/examples/Pose2SLAMwSPCG_advanced.cpp deleted file mode 100644 index 12d17a6e9..000000000 --- a/examples/Pose2SLAMwSPCG_advanced.cpp +++ /dev/null @@ -1,109 +0,0 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) - - * See LICENSE for the license information - - * -------------------------------------------------------------------------- */ - -/* - * @file Pose2SLAMwSPCG_advanced.cpp - * @brief Solve a simple 3 by 3 grid of Pose2 SLAM problem by using advanced SPCG interface - * @author Yong Dian - * Created October 21, 2010 - */ - -#include - -#if ENABLE_SPCG - -#include - -#include -#include -#include - -using namespace std; -using namespace gtsam; -using namespace pose2SLAM; - -typedef boost::shared_ptr sharedGraph ; -typedef boost::shared_ptr sharedValue ; -//typedef NonlinearOptimizer > SPCGOptimizer; - - -typedef SubgraphSolver Solver; -typedef boost::shared_ptr sharedSolver ; -typedef NonlinearOptimizer SPCGOptimizer; - -sharedGraph graph; -sharedValue initial; -Values result; - -/* ************************************************************************* */ -int main(void) { - - /* generate synthetic data */ - const SharedNoiseModel sigma(noiseModel::Unit::Create(0.1)); - Key x1(1), x2(2), x3(3), x4(4), x5(5), x6(6), x7(7), x8(8), x9(9); - - graph = boost::make_shared() ; - initial = boost::make_shared() ; - - // create a 3 by 3 grid - // x3 x6 x9 - // x2 x5 x8 - // x1 x4 x7 - graph->addConstraint(x1,x2,Pose2(0,2,0),sigma) ; - graph->addConstraint(x2,x3,Pose2(0,2,0),sigma) ; - graph->addConstraint(x4,x5,Pose2(0,2,0),sigma) ; - graph->addConstraint(x5,x6,Pose2(0,2,0),sigma) ; - graph->addConstraint(x7,x8,Pose2(0,2,0),sigma) ; - graph->addConstraint(x8,x9,Pose2(0,2,0),sigma) ; - graph->addConstraint(x1,x4,Pose2(2,0,0),sigma) ; - graph->addConstraint(x4,x7,Pose2(2,0,0),sigma) ; - graph->addConstraint(x2,x5,Pose2(2,0,0),sigma) ; - graph->addConstraint(x5,x8,Pose2(2,0,0),sigma) ; - graph->addConstraint(x3,x6,Pose2(2,0,0),sigma) ; - graph->addConstraint(x6,x9,Pose2(2,0,0),sigma) ; - graph->addPrior(x1, Pose2(0,0,0), sigma) ; - - initial->insert(x1, Pose2( 0, 0, 0)); - initial->insert(x2, Pose2( 0, 2.1, 0.01)); - initial->insert(x3, Pose2( 0, 3.9,-0.01)); - initial->insert(x4, Pose2(2.1,-0.1, 0)); - initial->insert(x5, Pose2(1.9, 2.1, 0.02)); - initial->insert(x6, Pose2(2.0, 3.9,-0.02)); - initial->insert(x7, Pose2(4.0, 0.1, 0.03 )); - initial->insert(x8, Pose2(3.9, 2.1, 0.01)); - initial->insert(x9, Pose2(4.1, 3.9,-0.01)); - /* done with generating data */ - - - graph->print("full graph") ; - initial->print("initial estimate") ; - - sharedSolver solver(new Solver(*graph, *initial)) ; - SPCGOptimizer optimizer(graph, initial, solver->ordering(), solver) ; - - cout << "before optimization, sum of error is " << optimizer.error() << endl; - SPCGOptimizer optimizer2 = optimizer.levenbergMarquardt(); - cout << "after optimization, sum of error is " << optimizer2.error() << endl; - - result = *optimizer2.values() ; - result.print("final result") ; - - return 0 ; -} - -#else - -int main() { - std::cout << "SPCG is currently disabled" << std::endl; - return 0; -} - -#endif diff --git a/examples/Pose2SLAMwSPCG_easy.cpp b/examples/Pose2SLAMwSPCG_easy.cpp deleted file mode 100644 index e610d327c..000000000 --- a/examples/Pose2SLAMwSPCG_easy.cpp +++ /dev/null @@ -1,87 +0,0 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) - - * See LICENSE for the license information - - * -------------------------------------------------------------------------- */ - -/* - * @file Pose2SLAMwSPCG_easy.cpp - * @brief Solve a simple 3 by 3 grid of Pose2 SLAM problem by using easy SPCG interface - * @author Yong Dian - * Created October 21, 2010 - */ - -#include - -#if ENABLE_SPCG - -#include - -#include -#include - - -using namespace std; -using namespace gtsam; -using namespace pose2SLAM; - -Graph graph; -Values initial, result; - -/* ************************************************************************* */ -int main(void) { - - /* generate synthetic data */ - const SharedNoiseModel sigma(noiseModel::Unit::Create(0.1)); - Key x1(1), x2(2), x3(3), x4(4), x5(5), x6(6), x7(7), x8(8), x9(9); - - // create a 3 by 3 grid - // x3 x6 x9 - // x2 x5 x8 - // x1 x4 x7 - graph.addConstraint(x1,x2,Pose2(0,2,0),sigma) ; - graph.addConstraint(x2,x3,Pose2(0,2,0),sigma) ; - graph.addConstraint(x4,x5,Pose2(0,2,0),sigma) ; - graph.addConstraint(x5,x6,Pose2(0,2,0),sigma) ; - graph.addConstraint(x7,x8,Pose2(0,2,0),sigma) ; - graph.addConstraint(x8,x9,Pose2(0,2,0),sigma) ; - graph.addConstraint(x1,x4,Pose2(2,0,0),sigma) ; - graph.addConstraint(x4,x7,Pose2(2,0,0),sigma) ; - graph.addConstraint(x2,x5,Pose2(2,0,0),sigma) ; - graph.addConstraint(x5,x8,Pose2(2,0,0),sigma) ; - graph.addConstraint(x3,x6,Pose2(2,0,0),sigma) ; - graph.addConstraint(x6,x9,Pose2(2,0,0),sigma) ; - graph.addPrior(x1, Pose2(0,0,0), sigma) ; - - initial.insert(x1, Pose2( 0, 0, 0)); - initial.insert(x2, Pose2( 0, 2.1, 0.01)); - initial.insert(x3, Pose2( 0, 3.9,-0.01)); - initial.insert(x4, Pose2(2.1,-0.1, 0)); - initial.insert(x5, Pose2(1.9, 2.1, 0.02)); - initial.insert(x6, Pose2(2.0, 3.9,-0.02)); - initial.insert(x7, Pose2(4.0, 0.1, 0.03 )); - initial.insert(x8, Pose2(3.9, 2.1, 0.01)); - initial.insert(x9, Pose2(4.1, 3.9,-0.01)); - /* done */ - - - graph.print("full graph") ; - initial.print("initial estimate"); - result = optimizeSPCG(graph, initial); - result.print("final result") ; - return 0 ; -} - -#else - -int main() { - std::cout << "SPCG is currently disabled" << std::endl; - return 0; -} - -#endif diff --git a/examples/README b/examples/README index d7706a0b8..2a54459f3 100644 --- a/examples/README +++ b/examples/README @@ -1,4 +1,4 @@ -This directory contains a number of exapmples that illustrate the use of GTSAM: +This directory contains a number of examples that illustrate the use of GTSAM: SimpleRotation: a super-simple example of optimizing a single rotation according to a single prior @@ -11,18 +11,20 @@ errorStateKalmanFilter: simple 1D example of a moving target measured by a accel 2D Pose SLAM ============ -Pose2SLAMExample_easy: A 2D Pose SLAM example using the predefined typedefs in gtsam/slam/pose2SLAM.h +LocalizationExample.cpp: modeling robot motion +LocalizationExample2.cpp: example with GPS like measurements +Pose2SLAMExample: A 2D Pose SLAM example using the predefined typedefs in gtsam/slam/pose2SLAM.h Pose2SLAMExample_advanced: same, but uses an Optimizer object -Pose2SLAMwSPCG_easy: solve a simple 3 by 3 grid of Pose2 SLAM problem by using easy SPCG interface -Pose2SLAMwSPCG_advanced: solve a simple 3 by 3 grid of Pose2 SLAM problem by using advanced SPCG interface +Pose2SLAMwSPCG: solve a simple 3 by 3 grid of Pose2 SLAM problem by using easy SPCG interface Planar SLAM with landmarks ========================== PlanarSLAMExample: simple robotics example using the pre-built planar SLAM domain -PlanarSLAMSelfContained_advanced: simple robotics example with all typedefs internal to this script. +PlanarSLAMExample_selfcontained: simple robotics example with all typedefs internal to this script. Visual SLAM =========== +CameraResectioning.cpp: An example of gtsam for solving the camera resectioning problem The directory vSLAMexample includes 2 simple examples using GTSAM: - vSFMexample using visualSLAM in for structure-from-motion (SFM), and - vISAMexample using visualSLAM and ISAM for incremental SLAM updates diff --git a/examples/SimpleRotation.cpp b/examples/SimpleRotation.cpp index 603d345bf..cff9d754e 100644 --- a/examples/SimpleRotation.cpp +++ b/examples/SimpleRotation.cpp @@ -17,20 +17,41 @@ * @author Alex Cunningham */ -#include -#include -#include + /** + * This example will perform a relatively trivial optimization on + * a single variable with a single factor. + */ + +// In this example, a 2D rotation will be used as the variable of interest #include -#include + +// Each variable in the system (poses) must be identified with a unique key. +// We can either use simple integer keys (1, 2, 3, ...) or symbols (X1, X2, L1). +// Here we will use symbols #include + +// In GTSAM, measurement functions are represented as 'factors'. Several common factors +// have been provided with the library for solving robotics/SLAM/Bundle Adjustment problems. +// We will apply a simple prior on the rotation +#include + +// When the factors are created, we will add them to a Factor Graph. As the factors we are using +// are nonlinear factors, we will need a Nonlinear Factor Graph. #include + +// The nonlinear solvers within GTSAM are iterative solvers, meaning they linearize the +// nonlinear functions around an initial linearization point, then solve the linear system +// to update the linearization point. This happens repeatedly until the solver converges +// to a consistent set of variable values. This requires us to specify an initial guess +// for each variable, held in a Values container. +#include + +// Finally, once all of the factors have been added to our factor graph, we will want to +// solve/optimize to graph to find the best (Maximum A Posteriori) set of variable values. +// GTSAM includes several nonlinear optimizers to perform this step. Here we will use the +// standard Levenberg-Marquardt solver #include -/* - * TODO: make factors independent of RotValues - * TODO: make toplevel documentation - * TODO: Clean up nonlinear optimization API - */ using namespace std; using namespace gtsam; @@ -40,12 +61,7 @@ const double degree = M_PI / 180; int main() { /** - * This example will perform a relatively trivial optimization on - * a single variable with a single factor. - */ - - /** - * Step 1: create a factor on to express a unary constraint + * Step 1: Create a factor to express a unary constraint * The "prior" in this case is the measurement from a sensor, * with a model of the noise on the measurement. * @@ -60,12 +76,12 @@ int main() { */ Rot2 prior = Rot2::fromAngle(30 * degree); prior.print("goal angle"); - SharedDiagonal model = noiseModel::Isotropic::Sigma(1, 1 * degree); + noiseModel::Isotropic::shared_ptr model = noiseModel::Isotropic::Sigma(1, 1 * degree); Symbol key('x',1); PriorFactor factor(key, prior, model); /** - * Step 2: create a graph container and add the factor to it + * Step 2: Create a graph container and add the factor to it * Before optimizing, all factors need to be added to a Graph container, * which provides the necessary top-level functionality for defining a * system of constraints. @@ -78,7 +94,7 @@ int main() { graph.print("full graph"); /** - * Step 3: create an initial estimate + * Step 3: Create an initial estimate * An initial estimate of the solution for the system is necessary to * start optimization. This system state is the "RotValues" structure, * which is similar in structure to a STL map, in that it maps @@ -98,7 +114,7 @@ int main() { initial.print("initial estimate"); /** - * Step 4: optimize + * Step 4: Optimize * After formulating the problem with a graph of constraints * and an initial estimate, executing optimization is as simple * as calling a general optimization function with the graph and diff --git a/examples/UGM_chain.cpp b/examples/UGM_chain.cpp new file mode 100644 index 000000000..56dbd4726 --- /dev/null +++ b/examples/UGM_chain.cpp @@ -0,0 +1,114 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file small.cpp + * @brief UGM (undirected graphical model) examples: chain + * @author Frank Dellaert + * @author Abhijit Kundu + * + * See http://www.di.ens.fr/~mschmidt/Software/UGM/chain.html + * for more explanation. This code demos the same example using GTSAM. + */ + +#include +#include +#include +#include + +#include + +using namespace std; +using namespace gtsam; + +int main(int argc, char** argv) { + + // Set Number of Nodes in the Graph + const int nrNodes = 60; + + // Each node takes 1 of 7 possible states denoted by 0-6 in following order: + // ["VideoGames" "Industry" "GradSchool" "VideoGames(with PhD)" + // "Industry(with PhD)" "Academia" "Deceased"] + const size_t nrStates = 7; + + // define variables + vector nodes; + for (int i = 0; i < nrNodes; i++){ + DiscreteKey dk(i, nrStates); + nodes.push_back(dk); + } + + // create graph + DiscreteFactorGraph graph; + + // add node potentials + graph.add(nodes[0], ".3 .6 .1 0 0 0 0"); + for (int i = 1; i < nrNodes; i++) + graph.add(nodes[i], "1 1 1 1 1 1 1"); + + const std::string edgePotential = ".08 .9 .01 0 0 0 .01 " + ".03 .95 .01 0 0 0 .01 " + ".06 .06 .75 .05 .05 .02 .01 " + "0 0 0 .3 .6 .09 .01 " + "0 0 0 .02 .95 .02 .01 " + "0 0 0 .01 .01 .97 .01 " + "0 0 0 0 0 0 1"; + + // add edge potentials + for (int i = 0; i < nrNodes - 1; i++) + graph.add(nodes[i] & nodes[i + 1], edgePotential); + + cout << "Created Factor Graph with " << nrNodes << " variable nodes and " + << graph.size() << " factors (Unary+Edge)."; + + // "Decoding", i.e., configuration with largest value + // We use sequential variable elimination + DiscreteSequentialSolver solver(graph); + DiscreteFactor::sharedValues optimalDecoding = solver.optimize(); + optimalDecoding->print("\nMost Probable Explanation (optimalDecoding)\n"); + + // "Inference" Computing marginals for each node + + + cout << "\nComputing Node Marginals ..(Sequential Elimination)" << endl; + tic_(1, "Sequential"); + for (vector::iterator itr = nodes.begin(); itr != nodes.end(); + ++itr) { + //Compute the marginal + Vector margProbs = solver.marginalProbabilities(*itr); + + //Print the marginals + cout << "Node#" << setw(4) << itr->first << " : "; + print(margProbs); + } + toc_(1, "Sequential"); + + // Here we'll make use of DiscreteMarginals class, which makes use of + // bayes-tree based shortcut evaluation of marginals + DiscreteMarginals marginals(graph); + + cout << "\nComputing Node Marginals ..(BayesTree based)" << endl; + tic_(2, "Multifrontal"); + for (vector::iterator itr = nodes.begin(); itr != nodes.end(); + ++itr) { + //Compute the marginal + Vector margProbs = marginals.marginalProbabilities(*itr); + + //Print the marginals + cout << "Node#" << setw(4) << itr->first << " : "; + print(margProbs); + } + toc_(2, "Multifrontal"); + + tictoc_print_(); + return 0; +} + diff --git a/examples/UGM_small.cpp b/examples/UGM_small.cpp index a4655d2ad..e9424d369 100644 --- a/examples/UGM_small.cpp +++ b/examples/UGM_small.cpp @@ -49,26 +49,38 @@ int main(int argc, char** argv) { // Print the UGM distribution cout << "\nUGM distribution:" << endl; - for (size_t a = 0; a < nrStates; a++) - for (size_t m = 0; m < nrStates; m++) - for (size_t h = 0; h < nrStates; h++) - for (size_t c = 0; c < nrStates; c++) { - DiscreteFactor::Values values; - values[1] = c; - values[2] = h; - values[3] = m; - values[4] = a; - double prodPot = graph(values); - cout << c << " " << h << " " << m << " " << a << " :\t" - << prodPot << "\t" << prodPot/3790 << endl; - } + vector allPosbValues = cartesianProduct( + Cathy & Heather & Mark & Allison); + for (size_t i = 0; i < allPosbValues.size(); ++i) { + DiscreteFactor::Values values = allPosbValues[i]; + double prodPot = graph(values); + cout << values[Cathy.first] << " " << values[Heather.first] << " " + << values[Mark.first] << " " << values[Allison.first] << " :\t" + << prodPot << "\t" << prodPot / 3790 << endl; + } - // "Decoding", i.e., configuration with largest value + // "Decoding", i.e., configuration with largest value (MPE) // We use sequential variable elimination DiscreteSequentialSolver solver(graph); DiscreteFactor::sharedValues optimalDecoding = solver.optimize(); optimalDecoding->print("\noptimalDecoding"); + // "Inference" Computing marginals + cout << "\nComputing Node Marginals .." << endl; + Vector margProbs; + + margProbs = solver.marginalProbabilities(Cathy); + print(margProbs, "Cathy's Node Marginal:"); + + margProbs = solver.marginalProbabilities(Heather); + print(margProbs, "Heather's Node Marginal"); + + margProbs = solver.marginalProbabilities(Mark); + print(margProbs, "Mark's Node Marginal"); + + margProbs = solver.marginalProbabilities(Allison); + print(margProbs, "Allison's Node Marginal"); + return 0; } diff --git a/examples/VisualISAM2Example.cpp b/examples/VisualISAM2Example.cpp new file mode 100644 index 000000000..1485da1e4 --- /dev/null +++ b/examples/VisualISAM2Example.cpp @@ -0,0 +1,159 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file VisualISAM2Example.cpp + * @brief A visualSLAM example for the structure-from-motion problem on a simulated dataset + * This version uses iSAM2 to solve the problem incrementally + * @author Duy-Nguyen Ta + */ + +/** + * A structure-from-motion example with landmarks + * - The landmarks form a 10 meter cube + * - The robot rotates around the landmarks, always facing towards the cube + */ + +// As this is a full 3D problem, we will use Pose3 variables to represent the camera +// positions and Point3 variables (x, y, z) to represent the landmark coordinates. +// Camera observations of landmarks (i.e. pixel coordinates) will be stored as Point2 (x, y). +// We will also need a camera object to hold calibration information and perform projections. +#include +#include +#include +#include + +// Each variable in the system (poses and landmarks) must be identified with a unique key. +// We can either use simple integer keys (1, 2, 3, ...) or symbols (X1, X2, L1). +// Here we will use Symbols +#include + +// In GTSAM, measurement functions are represented as 'factors'. Several common factors +// have been provided with the library for solving robotics/SLAM/Bundle Adjustment problems. +// Here we will use Projection factors to model the camera's landmark observations. +// Also, we will initialize the robot at some location using a Prior factor. +#include +#include + +// We want to use iSAM2 to solve the structure-from-motion problem incrementally, so +// include iSAM2 here +#include + +// iSAM2 requires as input a set set of new factors to be added stored in a factor graph, +// and initial guesses for any new variables used in the added factors +#include +#include + +#include + +using namespace std; +using namespace gtsam; + +/* ************************************************************************* */ +int main(int argc, char* argv[]) { + + // Define the camera calibration parameters + Cal3_S2::shared_ptr K(new Cal3_S2(50.0, 50.0, 0.0, 50.0, 50.0)); + + // Define the camera observation noise model + noiseModel::Isotropic::shared_ptr measurementNoise = noiseModel::Isotropic::Sigma(2, 1.0); // one pixel in u and v + + // Create the set of ground-truth landmarks + std::vector points; + points.push_back(gtsam::Point3(10.0,10.0,10.0)); + points.push_back(gtsam::Point3(-10.0,10.0,10.0)); + points.push_back(gtsam::Point3(-10.0,-10.0,10.0)); + points.push_back(gtsam::Point3(10.0,-10.0,10.0)); + points.push_back(gtsam::Point3(10.0,10.0,-10.0)); + points.push_back(gtsam::Point3(-10.0,10.0,-10.0)); + points.push_back(gtsam::Point3(-10.0,-10.0,-10.0)); + points.push_back(gtsam::Point3(10.0,-10.0,-10.0)); + + // Create the set of ground-truth poses + std::vector poses; + double radius = 30.0; + int i = 0; + double theta = 0.0; + gtsam::Point3 up(0,0,1); + gtsam::Point3 target(0,0,0); + for(; i < 8; ++i, theta += 2*M_PI/8) { + gtsam::Point3 position = Point3(radius*cos(theta), radius*sin(theta), 0.0); + gtsam::SimpleCamera camera = SimpleCamera::Lookat(position, target, up); + poses.push_back(camera.pose()); + } + + // Create an iSAM2 object. Unlike iSAM1, which performs periodic batch steps to maintain proper linearization + // and efficient variable ordering, iSAM2 performs partial relinearization/reordering at each step. A parameter + // structure is available that allows the user to set various properties, such as the relinearization threshold + // and type of linear solver. For this example, we we set the relinearization threshold small so the iSAM2 result + // will approach the batch result. + ISAM2Params parameters; + parameters.relinearizeThreshold = 0.01; + parameters.relinearizeSkip = 1; + ISAM2 isam(parameters); + + // Create a Factor Graph and Values to hold the new data + NonlinearFactorGraph graph; + Values initialEstimate; + + // Loop over the different poses, adding the observations to iSAM incrementally + for (size_t i = 0; i < poses.size(); ++i) { + + // Add factors for each landmark observation + for (size_t j = 0; j < points.size(); ++j) { + SimpleCamera camera(poses[i], *K); + Point2 measurement = camera.project(points[j]); + graph.add(GenericProjectionFactor(measurement, measurementNoise, Symbol('x', i), Symbol('l', j), K)); + } + + // Add an initial guess for the current pose + // Intentionally initialize the variables off from the ground truth + initialEstimate.insert(Symbol('x', i), poses[i].compose(Pose3(Rot3::rodriguez(-0.1, 0.2, 0.25), Point3(0.05, -0.10, 0.20)))); + + // If this is the first iteration, add a prior on the first pose to set the coordinate frame + // and a prior on the first landmark to set the scale + // Also, as iSAM solves incrementally, we must wait until each is observed at least twice before + // adding it to iSAM. + if( i == 0) { + // Add a prior on pose x0 + noiseModel::Diagonal::shared_ptr poseNoise = noiseModel::Diagonal::Sigmas(Vector_(6, 0.3, 0.3, 0.3, 0.1, 0.1, 0.1)); // 30cm std on x,y,z 0.1 rad on roll,pitch,yaw + graph.add(PriorFactor(Symbol('x', 0), poses[0], poseNoise)); + + // Add a prior on landmark l0 + noiseModel::Isotropic::shared_ptr pointNoise = noiseModel::Isotropic::Sigma(3, 0.1); + graph.add(PriorFactor(Symbol('l', 0), points[0], pointNoise)); // add directly to graph + + // Add initial guesses to all observed landmarks + // Intentionally initialize the variables off from the ground truth + for (size_t j = 0; j < points.size(); ++j) + initialEstimate.insert(Symbol('l', j), points[j].compose(Point3(-0.25, 0.20, 0.15))); + + } else { + // Update iSAM with the new factors + isam.update(graph, initialEstimate); + // Each call to iSAM2 update(*) performs one iteration of the iterative nonlinear solver. + // If accuracy is desired at the expense of time, update(*) can be called additional times + // to perform multiple optimizer iterations every step. + isam.update(); + Values currentEstimate = isam.calculateEstimate(); + cout << "****************************************************" << endl; + cout << "Frame " << i << ": " << endl; + currentEstimate.print("Current estimate: "); + + // Clear the factor graph and values for the next iteration + graph.resize(0); + initialEstimate.clear(); + } + } + + return 0; +} +/* ************************************************************************* */ diff --git a/examples/VisualISAMExample.cpp b/examples/VisualISAMExample.cpp new file mode 100644 index 000000000..832a2ab83 --- /dev/null +++ b/examples/VisualISAMExample.cpp @@ -0,0 +1,149 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file VisualISAMExample.cpp + * @brief A visualSLAM example for the structure-from-motion problem on a simulated dataset + * This version uses iSAM to solve the problem incrementally + * @author Duy-Nguyen Ta + */ + +/** + * A structure-from-motion example with landmarks + * - The landmarks form a 10 meter cube + * - The robot rotates around the landmarks, always facing towards the cube + */ + +// As this is a full 3D problem, we will use Pose3 variables to represent the camera +// positions and Point3 variables (x, y, z) to represent the landmark coordinates. +// Camera observations of landmarks (i.e. pixel coordinates) will be stored as Point2 (x, y). +// We will also need a camera object to hold calibration information and perform projections. +#include +#include +#include +#include + +// Each variable in the system (poses and landmarks) must be identified with a unique key. +// We can either use simple integer keys (1, 2, 3, ...) or symbols (X1, X2, L1). +// Here we will use Symbols +#include + +// In GTSAM, measurement functions are represented as 'factors'. Several common factors +// have been provided with the library for solving robotics/SLAM/Bundle Adjustment problems. +// Here we will use Projection factors to model the camera's landmark observations. +// Also, we will initialize the robot at some location using a Prior factor. +#include +#include + +// We want to use iSAM to solve the structure-from-motion problem incrementally, so +// include iSAM here +#include + +// iSAM requires as input a set set of new factors to be added stored in a factor graph, +// and initial guesses for any new variables used in the added factors +#include +#include + +#include + +using namespace std; +using namespace gtsam; + +/* ************************************************************************* */ +int main(int argc, char* argv[]) { + + // Define the camera calibration parameters + Cal3_S2::shared_ptr K(new Cal3_S2(50.0, 50.0, 0.0, 50.0, 50.0)); + + // Define the camera observation noise model + noiseModel::Isotropic::shared_ptr measurementNoise = noiseModel::Isotropic::Sigma(2, 1.0); // one pixel in u and v + + // Create the set of ground-truth landmarks + std::vector points; + points.push_back(gtsam::Point3(10.0,10.0,10.0)); + points.push_back(gtsam::Point3(-10.0,10.0,10.0)); + points.push_back(gtsam::Point3(-10.0,-10.0,10.0)); + points.push_back(gtsam::Point3(10.0,-10.0,10.0)); + points.push_back(gtsam::Point3(10.0,10.0,-10.0)); + points.push_back(gtsam::Point3(-10.0,10.0,-10.0)); + points.push_back(gtsam::Point3(-10.0,-10.0,-10.0)); + points.push_back(gtsam::Point3(10.0,-10.0,-10.0)); + + // Create the set of ground-truth poses + std::vector poses; + double radius = 30.0; + int i = 0; + double theta = 0.0; + gtsam::Point3 up(0,0,1); + gtsam::Point3 target(0,0,0); + for(; i < 8; ++i, theta += 2*M_PI/8) { + gtsam::Point3 position = Point3(radius*cos(theta), radius*sin(theta), 0.0); + gtsam::SimpleCamera camera = SimpleCamera::Lookat(position, target, up); + poses.push_back(camera.pose()); + } + + // Create a NonlinearISAM object which will relinearize and reorder the variables every "relinearizeInterval" updates + int relinearizeInterval = 3; + NonlinearISAM isam(relinearizeInterval); + + // Create a Factor Graph and Values to hold the new data + NonlinearFactorGraph graph; + Values initialEstimate; + + // Loop over the different poses, adding the observations to iSAM incrementally + for (size_t i = 0; i < poses.size(); ++i) { + + // Add factors for each landmark observation + for (size_t j = 0; j < points.size(); ++j) { + SimpleCamera camera(poses[i], *K); + Point2 measurement = camera.project(points[j]); + graph.add(GenericProjectionFactor(measurement, measurementNoise, Symbol('x', i), Symbol('l', j), K)); + } + + // Add an initial guess for the current pose + // Intentionally initialize the variables off from the ground truth + initialEstimate.insert(Symbol('x', i), poses[i].compose(Pose3(Rot3::rodriguez(-0.1, 0.2, 0.25), Point3(0.05, -0.10, 0.20)))); + + // If this is the first iteration, add a prior on the first pose to set the coordinate frame + // and a prior on the first landmark to set the scale + // Also, as iSAM solves incrementally, we must wait until each is observed at least twice before + // adding it to iSAM. + if( i == 0) { + // Add a prior on pose x0 + noiseModel::Diagonal::shared_ptr poseNoise = noiseModel::Diagonal::Sigmas(Vector_(6, 0.3, 0.3, 0.3, 0.1, 0.1, 0.1)); // 30cm std on x,y,z 0.1 rad on roll,pitch,yaw + graph.add(PriorFactor(Symbol('x', 0), poses[0], poseNoise)); + + // Add a prior on landmark l0 + noiseModel::Isotropic::shared_ptr pointNoise = noiseModel::Isotropic::Sigma(3, 0.1); + graph.add(PriorFactor(Symbol('l', 0), points[0], pointNoise)); // add directly to graph + + // Add initial guesses to all observed landmarks + // Intentionally initialize the variables off from the ground truth + for (size_t j = 0; j < points.size(); ++j) + initialEstimate.insert(Symbol('l', j), points[j].compose(Point3(-0.25, 0.20, 0.15))); + + } else { + // Update iSAM with the new factors + isam.update(graph, initialEstimate); + Values currentEstimate = isam.estimate(); + cout << "****************************************************" << endl; + cout << "Frame " << i << ": " << endl; + currentEstimate.print("Current estimate: "); + + // Clear the factor graph and values for the next iteration + graph.resize(0); + initialEstimate.clear(); + } + } + + return 0; +} +/* ************************************************************************* */ diff --git a/examples/VisualSLAMExample.cpp b/examples/VisualSLAMExample.cpp new file mode 100644 index 000000000..8aed051eb --- /dev/null +++ b/examples/VisualSLAMExample.cpp @@ -0,0 +1,139 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file VisualSLAMExample.cpp + * @brief A visualSLAM example for the structure-from-motion problem on a simulated dataset + * @author Duy-Nguyen Ta + */ + +/** + * A structure-from-motion example with landmarks + * - The landmarks form a 10 meter cube + * - The robot rotates around the landmarks, always facing towards the cube + */ + +// As this is a full 3D problem, we will use Pose3 variables to represent the camera +// positions and Point3 variables (x, y, z) to represent the landmark coordinates. +// Camera observations of landmarks (i.e. pixel coordinates) will be stored as Point2 (x, y). +// We will also need a camera object to hold calibration information and perform projections. +#include +#include +#include +#include + +// Each variable in the system (poses and landmarks) must be identified with a unique key. +// We can either use simple integer keys (1, 2, 3, ...) or symbols (X1, X2, L1). +// Here we will use Symbols +#include + +// In GTSAM, measurement functions are represented as 'factors'. Several common factors +// have been provided with the library for solving robotics/SLAM/Bundle Adjustment problems. +// Here we will use Projection factors to model the camera's landmark observations. +// Also, we will initialize the robot at some location using a Prior factor. +#include +#include + +// When the factors are created, we will add them to a Factor Graph. As the factors we are using +// are nonlinear factors, we will need a Nonlinear Factor Graph. +#include + +// Finally, once all of the factors have been added to our factor graph, we will want to +// solve/optimize to graph to find the best (Maximum A Posteriori) set of variable values. +// GTSAM includes several nonlinear optimizers to perform this step. Here we will use a +// trust-region method known as Powell's Degleg +#include + +// The nonlinear solvers within GTSAM are iterative solvers, meaning they linearize the +// nonlinear functions around an initial linearization point, then solve the linear system +// to update the linearization point. This happens repeatedly until the solver converges +// to a consistent set of variable values. This requires us to specify an initial guess +// for each variable, held in a Values container. +#include + +#include + +using namespace std; +using namespace gtsam; + +/* ************************************************************************* */ +int main(int argc, char* argv[]) { + + // Define the camera calibration parameters + Cal3_S2::shared_ptr K(new Cal3_S2(50.0, 50.0, 0.0, 50.0, 50.0)); + + // Define the camera observation noise model + noiseModel::Isotropic::shared_ptr measurementNoise = noiseModel::Isotropic::Sigma(2, 1.0); // one pixel in u and v + + // Create the set of ground-truth landmarks + std::vector points; + points.push_back(gtsam::Point3(10.0,10.0,10.0)); + points.push_back(gtsam::Point3(-10.0,10.0,10.0)); + points.push_back(gtsam::Point3(-10.0,-10.0,10.0)); + points.push_back(gtsam::Point3(10.0,-10.0,10.0)); + points.push_back(gtsam::Point3(10.0,10.0,-10.0)); + points.push_back(gtsam::Point3(-10.0,10.0,-10.0)); + points.push_back(gtsam::Point3(-10.0,-10.0,-10.0)); + points.push_back(gtsam::Point3(10.0,-10.0,-10.0)); + + // Create the set of ground-truth poses + std::vector poses; + double radius = 30.0; + int i = 0; + double theta = 0.0; + gtsam::Point3 up(0,0,1); + gtsam::Point3 target(0,0,0); + for(; i < 8; ++i, theta += 2*M_PI/8) { + gtsam::Point3 position = Point3(radius*cos(theta), radius*sin(theta), 0.0); + gtsam::SimpleCamera camera = SimpleCamera::Lookat(position, target, up); + poses.push_back(camera.pose()); + } + + // Create a factor graph + NonlinearFactorGraph graph; + + // Add a prior on pose x1. This indirectly specifies where the origin is. + noiseModel::Diagonal::shared_ptr poseNoise = noiseModel::Diagonal::Sigmas(Vector_(6, 0.3, 0.3, 0.3, 0.1, 0.1, 0.1)); // 30cm std on x,y,z 0.1 rad on roll,pitch,yaw + graph.add(PriorFactor(Symbol('x', 0), poses[0], poseNoise)); // add directly to graph + + // Simulated measurements from each camera pose, adding them to the factor graph + for (size_t i = 0; i < poses.size(); ++i) { + for (size_t j = 0; j < points.size(); ++j) { + SimpleCamera camera(poses[i], *K); + Point2 measurement = camera.project(points[j]); + graph.add(GenericProjectionFactor(measurement, measurementNoise, Symbol('x', i), Symbol('l', j), K)); + } + } + + // Because the structure-from-motion problem has a scale ambiguity, the problem is still under-constrained + // Here we add a prior on the position of the first landmark. This fixes the scale by indicating the distance + // between the first camera and the first landmark. All other landmark positions are interpreted using this scale. + noiseModel::Isotropic::shared_ptr pointNoise = noiseModel::Isotropic::Sigma(3, 0.1); + graph.add(PriorFactor(Symbol('l', 0), points[0], pointNoise)); // add directly to graph + graph.print("Factor Graph:\n"); + + // Create the data structure to hold the initialEstimate estimate to the solution + // Intentionally initialize the variables off from the ground truth + Values initialEstimate; + for (size_t i = 0; i < poses.size(); ++i) + initialEstimate.insert(Symbol('x', i), poses[i].compose(Pose3(Rot3::rodriguez(-0.1, 0.2, 0.25), Point3(0.05, -0.10, 0.20)))); + for (size_t j = 0; j < points.size(); ++j) + initialEstimate.insert(Symbol('l', j), points[j].compose(Point3(-0.25, 0.20, 0.15))); + initialEstimate.print("Initial Estimates:\n"); + + /* Optimize the graph and print results */ + Values result = DoglegOptimizer(graph, initialEstimate).optimize(); + result.print("Final results:\n"); + + return 0; +} +/* ************************************************************************* */ + diff --git a/examples/easyPoint2KalmanFilter.cpp b/examples/easyPoint2KalmanFilter.cpp index b13058a07..6d75e9149 100644 --- a/examples/easyPoint2KalmanFilter.cpp +++ b/examples/easyPoint2KalmanFilter.cpp @@ -21,7 +21,8 @@ * @author Stephen Williams */ -#include +#include +#include #include #include #include diff --git a/examples/matlab/PlanarSLAMExample_easy.m b/examples/matlab/PlanarSLAMExample_easy.m deleted file mode 100644 index 54462732b..000000000 --- a/examples/matlab/PlanarSLAMExample_easy.m +++ /dev/null @@ -1,75 +0,0 @@ -%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% -% GTSAM Copyright 2010, Georgia Tech Research Corporation, -% Atlanta, Georgia 30332-0415 -% All Rights Reserved -% Authors: Frank Dellaert, et al. (see THANKS for the full author list) -% -% See LICENSE for the license information -% -% @brief Simple robotics example using the pre-built planar SLAM domain -% @author Alex Cunningham -% @author Frank Dellaert -%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% - -%% Assumptions -% - All values are axis aligned -% - Robot poses are facing along the X axis (horizontal, to the right in images) -% - We have bearing and range information for measurements -% - We have full odometry for measurements -% - The robot and landmarks are on a grid, moving 2 meters each step -% - Landmarks are 2 meters away from the robot trajectory - -%% Create keys for variables -x1 = 1; x2 = 2; x3 = 3; -l1 = 1; l2 = 2; - -%% Create graph container and add factors to it -graph = planarSLAMGraph; - -%% Add prior -% gaussian for prior -prior_model = gtsamSharedNoiseModel_Sigmas([0.3; 0.3; 0.1]); -prior_measurement = gtsamPose2(0.0, 0.0, 0.0); % prior at origin -graph.addPrior(x1, prior_measurement, prior_model); % add directly to graph - -%% Add odometry -% general noisemodel for odometry -odom_model = gtsamSharedNoiseModel_Sigmas([0.2; 0.2; 0.1]); -odom_measurement = gtsamPose2(2.0, 0.0, 0.0); % create a measurement for both factors (the same in this case) -graph.addOdometry(x1, x2, odom_measurement, odom_model); -graph.addOdometry(x2, x3, odom_measurement, odom_model); - -%% Add measurements -% general noisemodel for measurements -meas_model = gtsamSharedNoiseModel_Sigmas([0.1; 0.2]); - -% create the measurement values - indices are (pose id, landmark id) -degrees = pi/180; -bearing11 = gtsamRot2(45*degrees); -bearing21 = gtsamRot2(90*degrees); -bearing32 = gtsamRot2(90*degrees); -range11 = sqrt(4+4); -range21 = 2.0; -range32 = 2.0; - -% % create bearing/range factors and add them -graph.addBearingRange(x1, l1, bearing11, range11, meas_model); -graph.addBearingRange(x2, l1, bearing21, range21, meas_model); -graph.addBearingRange(x3, l2, bearing32, range32, meas_model); - -% print -graph.print('full graph'); - -%% Initialize to noisy points -initialEstimate = planarSLAMValues; -initialEstimate.insertPose(x1, gtsamPose2(0.5, 0.0, 0.2)); -initialEstimate.insertPose(x2, gtsamPose2(2.3, 0.1,-0.2)); -initialEstimate.insertPose(x3, gtsamPose2(4.1, 0.1, 0.1)); -initialEstimate.insertPoint(l1, gtsamPoint2(1.8, 2.1)); -initialEstimate.insertPoint(l2, gtsamPoint2(4.1, 1.8)); - -initialEstimate.print('initial estimate'); - -%% Optimize using Levenberg-Marquardt optimization with an ordering from colamd -result = graph.optimize(initialEstimate); -result.print('final result'); diff --git a/examples/matlab/Pose2SLAMExample_easy.m b/examples/matlab/Pose2SLAMExample_easy.m deleted file mode 100644 index 6c359f314..000000000 --- a/examples/matlab/Pose2SLAMExample_easy.m +++ /dev/null @@ -1,57 +0,0 @@ -%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% -% GTSAM Copyright 2010, Georgia Tech Research Corporation, -% Atlanta, Georgia 30332-0415 -% All Rights Reserved -% Authors: Frank Dellaert, et al. (see THANKS for the full author list) -% -% See LICENSE for the license information -% -% @brief Simple robotics example using the pre-built planar SLAM domain -% @author Alex Cunningham -% @author Frank Dellaert -% @author Chris Beall -%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% - -%% Assumptions -% - All values are axis aligned -% - Robot poses are facing along the X axis (horizontal, to the right in images) -% - We have full odometry for measurements -% - The robot is on a grid, moving 2 meters each step - -%% Create keys for variables -x1 = 1; x2 = 2; x3 = 3; - -%% Create graph container and add factors to it -graph = pose2SLAMGraph; - -%% Add prior -% gaussian for prior -prior_model = gtsamSharedNoiseModel_Sigmas([0.3; 0.3; 0.1]); -prior_measurement = gtsamPose2(0.0, 0.0, 0.0); % prior at origin -graph.addPrior(x1, prior_measurement, prior_model); % add directly to graph - -%% Add odometry -% general noisemodel for odometry -odom_model = gtsamSharedNoiseModel_Sigmas([0.2; 0.2; 0.1]); -odom_measurement = gtsamPose2(2.0, 0.0, 0.0); % create a measurement for both factors (the same in this case) -graph.addOdometry(x1, x2, odom_measurement, odom_model); -graph.addOdometry(x2, x3, odom_measurement, odom_model); - -%% Add measurements -% general noisemodel for measurements -meas_model = gtsamSharedNoiseModel_Sigmas([0.1; 0.2]); - -% print -graph.print('full graph'); - -%% Initialize to noisy points -initialEstimate = pose2SLAMValues; -initialEstimate.insertPose(x1, gtsamPose2(0.5, 0.0, 0.2)); -initialEstimate.insertPose(x2, gtsamPose2(2.3, 0.1,-0.2)); -initialEstimate.insertPose(x3, gtsamPose2(4.1, 0.1, 0.1)); - -initialEstimate.print('initial estimate'); - -%% Optimize using Levenberg-Marquardt optimization with an ordering from colamd -result = graph.optimize(initialEstimate); -result.print('final result'); diff --git a/examples/vSLAMexample/CMakeLists.txt b/examples/vSLAMexample/CMakeLists.txt deleted file mode 100644 index 57fd6bf6d..000000000 --- a/examples/vSLAMexample/CMakeLists.txt +++ /dev/null @@ -1,14 +0,0 @@ -# Build vSLAMexample - -message(STATUS "Adding Example vISAMexample") -add_executable(vISAMexample vISAMexample.cpp vSLAMutils.cpp) -target_link_libraries(vISAMexample gtsam-static) -add_dependencies(examples vISAMexample) - -message(STATUS "Adding Example vSFMexample") -add_executable(vSFMexample vSFMexample.cpp vSLAMutils.cpp) -target_link_libraries(vSFMexample gtsam-static) -add_dependencies(examples vSFMexample) - - - diff --git a/examples/vSLAMexample/Feature2D.h b/examples/vSLAMexample/Feature2D.h deleted file mode 100644 index aca5f9e4b..000000000 --- a/examples/vSLAMexample/Feature2D.h +++ /dev/null @@ -1,41 +0,0 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) - - * See LICENSE for the license information - - * -------------------------------------------------------------------------- */ - -/** - * @file Feature2D.h - * @brief - * @author Duy-Nguyen Ta - */ - -#pragma once - -#include "gtsam/geometry/Point2.h" -#include - -struct Feature2D -{ - - gtsam::Point2 m_p; - int m_idCamera; // id of the camera pose that makes this measurement - int m_idLandmark; // id of the 3D landmark that it is associated with - - Feature2D(int idCamera, int idLandmark, gtsam::Point2 p) : - m_p(p), - m_idCamera(idCamera), - m_idLandmark(idLandmark) {} - - void print(const std::string& s = "") const { - std::cout << s << std::endl; - std::cout << "Pose id: " << m_idCamera << " -- Landmark id: " << m_idLandmark << std::endl; - m_p.print("\tMeasurement: "); - } - -}; diff --git a/examples/vSLAMexample/README b/examples/vSLAMexample/README deleted file mode 100644 index 99b10608c..000000000 --- a/examples/vSLAMexample/README +++ /dev/null @@ -1,101 +0,0 @@ -README - vSLAMexample ------------------------------------------------------- - - vSLAMexample includes 2 simple examples using GTSAM: - - vSFMexample using visualSLAM in for structure-from-motion (SFM), and - - vISAMexample using visualSLAM and ISAM for incremental SLAM updates - - The two examples use the same visual SLAM graph structure which nodes are 6d camera poses (SE3) and 3d point landmarks. Measurement factors are 2D features detected on each image, connecting its camera-pose node and the corresponding landmark nodes. There are also prior factors on each pose nodes. - -Synthesized data generation ---------------------------- -The data are generated by using Panda3D graphics engine to render a sequence of virtual scene with 7 colorful small 3d patches viewing by camera moving around. The patches' coordinates are given in "landmarks.txt" file. Centroids of those colorful features in the rendered images are detected and stored in "ttpy*.feat" files. - -Files "ttpy*.pose" contain the poses of the virtual camera that renders the scene. A *VERY IMPORTANT* note is that the values in these "ttpy*.pose" files follow Panda3D's convention for camera frame coordinate system: "z up, y view", where as in our code, we follow OpenGL's convention: "y up, -z view". Thus, we have to change it to match with our convention. Essentially, the z- and y- axes are swapped, then the z-axis is negated to stick to the right-hand rule. Please see the function "gtsam::Pose3 readPose(const char* Fn)" in "vSLAMutils.cpp" for more information. - -File "calib.txt" contains intrinsic parameters of the virtual camera. The signs are correctly adjusted to match with our projection coordinate system's convention. - -Files "measurements.txt" and "poses.txt" simulate typical input data for a structure-from-motion problem. Similarly, "measurementsISAM.txt" and "posesISAM.txt" simulate the data used in SLAM context with incremental-update using ISAM. - -Note that for SFM, the whole graph is solved as a whole batch problem, so the camera_id's corresponding to the feature files and pose files need to be specified in "measurements.txt" and "poses.txt", but they are not necessarily in order. - -On the other hand, for ISAM, we sequentially add the camera poses and features and update after every frame; so the pose files and features files in "measurementsISAM.txt" and "posesISAM.txt" need to be specified in order (time order), even though the camera id's are not necessary. - - - -Data file format ------------------------------ - -"calib.txt": ------------- -image_width image_height fx fy ox oy - - -"landmarks.txt" ------------- -N #number of landmarks -landmark_id1 x1 y1 z1 -landmark_id2 x2 y2 z2 -... -landmark_idN xN yN zN - - -"ttpy*.feat" ------------- -N #number of features -corresponding_landmark_id1 x1 y1 -corresponding_landmark_id2 x2 y2 -... -corresponding_landmark_idN xN yN - - -"ttpy*.pose" ------------- -0.939693 0.34202 0 0 --0.241845 0.664463 -0.707107 0 --0.241845 0.664463 0.707107 0 -34.202 -93.9693 100 1 - -The camera pose matrix in column order. Note that these values follows Panda3D's convention for camera coordinate frame. We have to change it to match with our convention used in the code, which follows OpenGL system. See previous section for more details. - - -Data For SFM: - -"measurements.txt" ------------- -N #number of cameras -camera_id1 featureFile1 -camera_id2 featureFile2 -... -camera_id3 featureFile3 - -"poses.txt" ------------- -N #number of cameras -camera_id1 poseFile1 -camera_id2 poseFile2 -... -camera_id3 poseFile3 - - -Data For ISAM: - -"measurementsISAM.txt" ------------- -N #number of cameras -featureFile1 -featureFile2 -... -featureFile3 - -"posesISAM.txt" ------------- -N #number of cameras -poseFile1 -poseFile2 -... -poseFile3 - - - - diff --git a/examples/vSLAMexample/vISAMexample.cpp b/examples/vSLAMexample/vISAMexample.cpp deleted file mode 100644 index edd745676..000000000 --- a/examples/vSLAMexample/vISAMexample.cpp +++ /dev/null @@ -1,147 +0,0 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) - - * See LICENSE for the license information - - * -------------------------------------------------------------------------- */ - -/** - * @file vISAMexample.cpp - * @brief An ISAM example for synthesis sequence - * single camera - * @author Duy-Nguyen Ta - */ - -#include -#include -using namespace boost; - -#include -#include -#include -#include -#include - -#include "vSLAMutils.h" -#include "Feature2D.h" - -using namespace std; -using namespace gtsam; -using namespace visualSLAM; -using namespace boost; - -/* ************************************************************************* */ -#define CALIB_FILE "calib.txt" -#define LANDMARKS_FILE "landmarks.txt" -#define POSES_FILE "poses.txt" -#define MEASUREMENTS_FILE "measurements.txt" - -// Base data folder -string g_dataFolder; - -// Store groundtruth values, read from files -shared_ptrK g_calib; -map g_landmarks; // map: -map g_poses; // map: -std::map > g_measurements; // feature sets detected at each frame - -// Noise models -SharedNoiseModel measurementSigma(noiseModel::Isotropic::Sigma(2, 5.0f)); -SharedNoiseModel poseSigma(noiseModel::Unit::Create(1)); - - -/* ************************************************************************* */ -/** - * Read all data: calibration file, landmarks, poses, and all features measurements - * Data is stored in global variables, which are used later to simulate incremental updates. - */ -void readAllDataISAM() { - g_calib = readCalibData(g_dataFolder + CALIB_FILE); - - // Read groundtruth landmarks' positions. These will be used later as intial estimates and priors for landmark nodes. - g_landmarks = readLandMarks(g_dataFolder + LANDMARKS_FILE); - - // Read groundtruth camera poses. These will be used later as intial estimates for pose nodes. - g_poses = readPoses(g_dataFolder, POSES_FILE); - - // Read all 2d measurements. Those will become factors linking their associating pose and the corresponding landmark. - g_measurements = readAllMeasurementsISAM(g_dataFolder, MEASUREMENTS_FILE); -} - -/* ************************************************************************* */ -/** - * Setup newFactors and initialValues for each new pose and set of measurements at each frame. - */ -void createNewFactors(shared_ptr& newFactors, boost::shared_ptr& initialValues, - const Values& currentEstimate, int pose_id, const Pose3& pose, - const std::vector& measurements, SharedNoiseModel measurementSigma, shared_ptrK calib) { - - // Create a graph of newFactors with new measurements - newFactors = shared_ptr (new Graph()); - for (size_t i = 0; i < measurements.size(); i++) { - newFactors->addMeasurement( - measurements[i].m_p, - measurementSigma, - pose_id, - measurements[i].m_idLandmark, - calib); - } - - // Add prior on the first pose - if(pose_id == 0) - newFactors->addPosePrior(pose_id, Pose3(), poseSigma); - - // Create initial values for all new variables and add priors on new landmarks - initialValues = shared_ptr (new Values()); - initialValues->insert(PoseKey(pose_id), pose); - for (size_t i = 0; i < measurements.size(); i++) { - if(!currentEstimate.exists(PointKey(measurements[i].m_idLandmark))) { - initialValues->insert(PointKey(measurements[i].m_idLandmark), g_landmarks[measurements[i].m_idLandmark]); - newFactors->addPointPrior(measurements[i].m_idLandmark, g_landmarks[measurements[i].m_idLandmark]); - } - } -} - -/* ************************************************************************* */ -int main(int argc, char* argv[]) { - if (argc < 2) { - cout << "Usage: vISAMexample " << endl << endl; - cout << "\tPlease specify , which contains calibration file, initial\n" - "\tlandmarks, initial poses, and feature data." << endl; - cout << "\tSample folder is in $gtsam_source_folder$/examples/Data/" << endl << endl; - cout << "Example usage: vISAMexample '$gtsam_source_folder$/examples/Data/'" << endl; - exit(0); - } - - g_dataFolder = string(argv[1]) + "/"; - readAllDataISAM(); - - // Create a NonlinearISAM which will be relinearized and reordered after every "relinearizeInterval" updates - int relinearizeInterval = 3; - NonlinearISAM<> isam(relinearizeInterval); - - // At each frame (poseId) with new camera pose and set of associated measurements, - // create a graph of new factors and update ISAM - typedef std::map > FeatureMap; - Values currentEstimate = isam.estimate(); - BOOST_FOREACH(const FeatureMap::value_type& features, g_measurements) { - const int poseId = features.first; - shared_ptr newFactors; - shared_ptr initialValues; - createNewFactors(newFactors, initialValues, currentEstimate, poseId, g_poses[poseId], - features.second, measurementSigma, g_calib); - - isam.update(*newFactors, *initialValues); - currentEstimate = isam.estimate(); - cout << "****************************************************" << endl; - currentEstimate.print("Current estimate: "); - } - - return 1; -} -/* ************************************************************************* */ - diff --git a/examples/vSLAMexample/vSFMexample.cpp b/examples/vSLAMexample/vSFMexample.cpp deleted file mode 100644 index 8774b79f3..000000000 --- a/examples/vSLAMexample/vSFMexample.cpp +++ /dev/null @@ -1,157 +0,0 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) - - * See LICENSE for the license information - - * -------------------------------------------------------------------------- */ - -/** - * @file vSFMexample.cpp - * @brief An vSFM example for synthesis sequence - * single camera - * @author Duy-Nguyen Ta - */ - -#include -using namespace boost; - -#include -#include -#include -#include - -#include "vSLAMutils.h" -#include "Feature2D.h" - -using namespace std; -using namespace gtsam; -using namespace visualSLAM; -using namespace boost; - -/* ************************************************************************* */ -#define CALIB_FILE "calib.txt" -#define LANDMARKS_FILE "landmarks.txt" -#define POSES_FILE "poses.txt" -#define MEASUREMENTS_FILE "measurements.txt" - -// Base data folder -string g_dataFolder; - -// Store groundtruth values, read from files -shared_ptrK g_calib; -map g_landmarks; // map: -map g_poses; // map: -std::vector g_measurements; // Feature2D: {camera_id, landmark_id, 2d feature_position} - -// Noise models -SharedNoiseModel measurementSigma(noiseModel::Isotropic::Sigma(2, 5.0f)); - -/* ************************************************************************* */ -/** - * Read all data: calibration file, landmarks, poses, and all features measurements - * Data is stored in global variables. - */ -void readAllData() { - - g_calib = readCalibData(g_dataFolder + "/" + CALIB_FILE); - - // Read groundtruth landmarks' positions. These will be used later as intial estimates for landmark nodes. - g_landmarks = readLandMarks(g_dataFolder + "/" + LANDMARKS_FILE); - - // Read groundtruth camera poses. These will be used later as intial estimates for pose nodes. - g_poses = readPoses(g_dataFolder, POSES_FILE); - - // Read all 2d measurements. Those will become factors linking their associating pose and the corresponding landmark. - g_measurements = readAllMeasurements(g_dataFolder, MEASUREMENTS_FILE); -} - -/* ************************************************************************* */ -/** - * Setup vSLAM graph - * by adding and linking 2D features (measurements) detected in each captured image - * with their corresponding landmarks. - */ -Graph setupGraph(std::vector& measurements, SharedNoiseModel measurementSigma, shared_ptrK calib) { - - Graph g; - - cout << "Built graph: " << endl; - for (size_t i = 0; i < measurements.size(); i++) { - measurements[i].print(); - - g.addMeasurement( - measurements[i].m_p, - measurementSigma, - measurements[i].m_idCamera, - measurements[i].m_idLandmark, - calib); - } - - return g; -} - -/* ************************************************************************* */ -/** - * Create a structure of initial estimates for all nodes (landmarks and poses) in the graph. - * The returned Values structure contains all initial values for all nodes. - */ -Values initialize(std::map landmarks, std::map poses) { - - Values initValues; - - // Initialize landmarks 3D positions. - for (map::iterator lmit = landmarks.begin(); lmit != landmarks.end(); lmit++) - initValues.insert(PointKey(lmit->first), lmit->second); - - // Initialize camera poses. - for (map::iterator poseit = poses.begin(); poseit != poses.end(); poseit++) - initValues.insert(PoseKey(poseit->first), poseit->second); - - return initValues; -} - -/* ************************************************************************* */ -int main(int argc, char* argv[]) { - if (argc < 2) { - cout << "Usage: vSFMexample " << endl << endl; - cout << "\tPlease specify , which contains calibration file, initial\n" - "\tlandmarks, initial poses, and feature data." << endl; - cout << "\tSample folder is in $gtsam_source_folder$/examples/Data" << endl << endl; - cout << "Example usage: vSFMexample '$gtsam_source_folder$/examples/Data'" << endl; - exit(0); - } - - g_dataFolder = string(argv[1]) + "/"; - readAllData(); - - // Create a graph using the 2D measurements (features) and the calibration data - Graph graph(setupGraph(g_measurements, measurementSigma, g_calib)); - - // Create an initial Values structure using groundtruth values as the initial estimates - Values initialEstimates(initialize(g_landmarks, g_poses)); - cout << "*******************************************************" << endl; - initialEstimates.print("INITIAL ESTIMATES: "); - - // Add prior factor for all poses in the graph - map::iterator poseit = g_poses.begin(); - for (; poseit != g_poses.end(); poseit++) - graph.addPosePrior(poseit->first, poseit->second, noiseModel::Unit::Create(1)); - - // Optimize the graph - cout << "*******************************************************" << endl; - LevenbergMarquardtParams params; - params.verbosityLM = LevenbergMarquardtParams::DAMPED; - visualSLAM::Values result = LevenbergMarquardtOptimizer(graph, initialEstimates, params).optimize(); - - // Print final results - cout << "*******************************************************" << endl; - result.print("FINAL RESULTS: "); - - return 0; -} -/* ************************************************************************* */ - diff --git a/examples/vSLAMexample/vSLAMutils.cpp b/examples/vSLAMexample/vSLAMutils.cpp deleted file mode 100644 index 1c3912f2d..000000000 --- a/examples/vSLAMexample/vSLAMutils.cpp +++ /dev/null @@ -1,176 +0,0 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) - - * See LICENSE for the license information - - * -------------------------------------------------------------------------- */ - -/** - * @file VSLAMutils.cpp - * @brief - * @author Duy-Nguyen Ta - */ - -#include "vSLAMutils.h" -#include -#include - -using namespace gtsam; -using namespace std; - -/* ************************************************************************* */ -std::map readLandMarks(const std::string& landmarkFile) { - ifstream file(landmarkFile.c_str()); - if (!file) { - cout << "Cannot read landmark file: " << landmarkFile << endl; - exit(0); - } - - int num; - file >> num; - std::map landmarks; - landmarks.clear(); - for (int i = 0; i> color_id >> x >> y >> z; - landmarks[color_id] = Point3(x, y, z); - } - - file.close(); - return landmarks; -} - -/* ************************************************************************* */ -gtsam::Pose3 readPose(const char* Fn) { - ifstream poseFile(Fn); - if (!poseFile) { - cout << "Cannot read pose file: " << Fn << endl; - exit(0); - } - - double v[16]; - for (int i = 0; i<16; i++) - poseFile >> v[i]; - poseFile.close(); - - Matrix T = Matrix_(4,4, v); // row order !!! - - Pose3 pose(T); - return pose; -} -/* ************************************************************************* */ -std::map readPoses(const std::string& baseFolder, const std::string& posesFn) { - ifstream posesFile((baseFolder+posesFn).c_str()); - if (!posesFile) { - cout << "Cannot read all pose file: " << posesFn << endl; - exit(0); - } - int numPoses; - posesFile >> numPoses; - map poses; - for (int i = 0; i> poseId; - - string poseFileName; - posesFile >> poseFileName; - - Pose3 pose = readPose((baseFolder+poseFileName).c_str()); - poses[poseId] = pose; - } - - return poses; -} - -/* ************************************************************************* */ -gtsam::shared_ptrK readCalibData(const std::string& calibFn) { - ifstream calibFile(calibFn.c_str()); - if (!calibFile) { - cout << "Cannot read calib file: " << calibFn << endl; - exit(0); - } - int imX, imY; - float fx, fy, ox, oy; - calibFile >> imX >> imY >> fx >> fy >> ox >> oy; - calibFile.close(); - - return shared_ptrK(new Cal3_S2(fx, fy, 0, ox, oy)); // skew factor = 0 -} - -/* ************************************************************************* */ -std::vector readFeatures(int pose_id, const char* filename) { - ifstream file(filename); - if (!file) { - cout << "Cannot read feature file: " << filename<< endl; - exit(0); - } - - int numFeatures; - file >> numFeatures ; - - std::vector vFeatures_; - for (int i = 0; i < numFeatures; i++) { - int landmark_id; double x, y; - file >> landmark_id >> x >> y; - vFeatures_.push_back(Feature2D(pose_id, landmark_id, Point2(x, y))); - } - - file.close(); - return vFeatures_; -} - -/* ************************************************************************* */ -std::vector readAllMeasurements(const std::string& baseFolder, const std::string& measurementsFn) { - ifstream measurementsFile((baseFolder+measurementsFn).c_str()); - if (!measurementsFile) { - cout << "Cannot read all pose file: " << baseFolder+measurementsFn << endl; - exit(0); - } - int numPoses; - measurementsFile >> numPoses; - - vector allFeatures; - allFeatures.clear(); - - for (int i = 0; i> poseId; - - string featureFileName; - measurementsFile >> featureFileName; - vector features = readFeatures(poseId, (baseFolder+featureFileName).c_str()); - allFeatures.insert( allFeatures.end(), features.begin(), features.end() ); - } - - return allFeatures; -} - -/* ************************************************************************* */ -std::map > readAllMeasurementsISAM(const std::string& baseFolder, const std::string& measurementsFn) { - ifstream measurementsFile((baseFolder+measurementsFn).c_str()); - if (!measurementsFile) { - cout << "Cannot read all pose file: " << baseFolder+measurementsFn << endl; - exit(0); - } - int numPoses; - measurementsFile >> numPoses; - - std::map > allFeatures; - - for (int i = 0; i> poseId; - - string featureFileName; - measurementsFile >> featureFileName; - vector features = readFeatures(poseId, (baseFolder+featureFileName).c_str()); - allFeatures[poseId] = features; - } - - return allFeatures; -} diff --git a/examples/vSLAMexample/vSLAMutils.h b/examples/vSLAMexample/vSLAMutils.h deleted file mode 100644 index 52d492224..000000000 --- a/examples/vSLAMexample/vSLAMutils.h +++ /dev/null @@ -1,37 +0,0 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) - - * See LICENSE for the license information - - * -------------------------------------------------------------------------- */ - -/** - * @file Feature2D.cpp - * @brief - * @author Duy-Nguyen Ta - */ - -#pragma once - -#include -#include -#include "Feature2D.h" -#include "gtsam/geometry/Pose3.h" -#include "gtsam/geometry/Point3.h" -#include "gtsam/geometry/Cal3_S2.h" - - -std::map readLandMarks(const std::string& landmarkFile); - -gtsam::Pose3 readPose(const char* poseFn); -std::map readPoses(const std::string& baseFolder, const std::string& posesFN); - -gtsam::shared_ptrK readCalibData(const std::string& calibFn); - -std::vector readFeatureFile(const char* filename); -std::vector readAllMeasurements(const std::string& baseFolder, const std::string& measurementsFn); -std::map > readAllMeasurementsISAM(const std::string& baseFolder, const std::string& measurementsFn); diff --git a/gtsam.h b/gtsam.h index 18c8921cb..88efe7618 100644 --- a/gtsam.h +++ b/gtsam.h @@ -6,285 +6,1045 @@ * * Requirements: * Classes must start with an uppercase letter - * Only one Method/Constructor per line + * - Can wrap a typedef + * Only one Method/Constructor per line, though methods/constructors can extend across multiple lines * Methods can return * - Eigen types: Matrix, Vector - * - C/C++ basic types: string, bool, size_t, int, double, char + * - C/C++ basic types: string, bool, size_t, size_t, double, char, unsigned char * - void * - Any class with which be copied with boost::make_shared() * - boost::shared_ptr of any object type - * Limitations on methods - * - Parsing does not support overloading - * - There can only be one method with a given name + * Constructors + * - Overloads are supported + * - A class with no constructors can be returned from other functions but not allocated directly in MATLAB + * Methods + * - Constness has no effect + * - Specify by-value (not reference) return types, even if C++ method returns reference + * - Must start with a lowercase letter + * - Overloads are supported + * Static methods + * - Must start with a letter (upper or lowercase) and use the "static" keyword + * - The first letter will be made uppercase in the generated MATLAB interface + * - Overloads are supported * Arguments to functions any of * - Eigen types: Matrix, Vector * - Eigen types and classes as an optionally const reference - * - C/C++ basic types: string, bool, size_t, int, double + * - C/C++ basic types: string, bool, size_t, size_t, double, char, unsigned char * - Any class with which be copied with boost::make_shared() (except Eigen) * - boost::shared_ptr of any object type (except Eigen) * Comments can use either C++ or C style, with multiple lines * Namespace definitions * - Names of namespaces must start with a lowercase letter * - start a namespace with "namespace {" - * - end a namespace with exactly "}///\namespace [namespace_name]", optionally adding the name of the namespace - * - This ending is not C++ standard, and must contain "}///\namespace" to parse + * - end a namespace with exactly "}" * - Namespaces can be nested * Namespace usage * - Namespaces can be specified for classes in arguments and return values * - In each case, the namespace must be fully specified, e.g., "namespace1::namespace2::ClassName" - * Using namespace - * - To use a namespace (e.g., generate a "using namespace x" line in cpp files), add "using namespace x;" - * - This declaration applies to all classes *after* the declaration, regardless of brackets - * Methods must start with a lowercase letter - * Static methods must start with a letter (upper or lowercase) and use the "static" keyword * Includes in C++ wrappers - * - By default, the include will be <[classname].h> - * - All namespaces must have angle brackets: - * - To override, add a full include statement just before the class statement - * - An override include can be added for a namespace by placing it just before the namespace statement - * - Both classes and namespace accept exactly one namespace - * Overriding type dependency checks + * - All includes will be collected and added in a single file + * - All namespaces must have angle brackets: + * - No default includes will be added + * Global/Namespace functions + * - Functions specified outside of a class are global + * - Can be overloaded with different arguments + * - Can have multiple functions of the same name in different namespaces + * Using classes defined in other modules * - If you are using a class 'OtherClass' not wrapped in this definition file, add "class OtherClass;" to avoid a dependency error - * - Limitation: this only works if the class does not need a namespace specification + * Virtual inheritance + * - Specify fully-qualified base classes, i.e. "virtual class Derived : module::Base {" + * - Mark with 'virtual' keyword, e.g. "virtual class Base {", and also "virtual class Derived : module::Base {" + * - Forward declarations must also be marked virtual, e.g. "virtual class module::Base;" and + * also "virtual class module::Derived;" + * - Pure virtual (abstract) classes should list no constructors in this interface file + * - Virtual classes must have a clone() function in C++ (though it does not have to be included + * in the MATLAB interface). clone() will be called whenever an object copy is needed, instead + * of using the copy constructor (which is used for non-virtual objects). + * Templates + * - Basic templates are supported either with an explicit list of types to instantiate, + * e.g. template class Class1 { ... }; + * or with typedefs, e.g. + * template class Class2 { ... }; + * typedef Class2 MyInstantiatedClass; + * - In the class definition, appearances of the template argument(s) will be replaced with their + * instantiated types, e.g. 'void setValue(const T& value);'. + * - To refer to the instantiation of the template class itself, use 'This', i.e. 'static This Create();' + * - To create new instantiations in other modules, you must copy-and-paste the whole class definition + * into the new module, but use only your new instantiation types. + * - When forward-declaring template instantiations, use the generated/typedefed name, e.g. + * class gtsam::Class1Pose2; + * class gtsam::MyInstantiatedClass; */ /** * Status: - * - TODO: global functions * - TODO: default values for arguments - * - TODO: overloaded functions - * - TODO: signatures for constructors can be ambiguous if two types have the same first letter * - TODO: Handle gtsam::Rot3M conversions to quaternions */ -// Everything is in the gtsam namespace, so we avoid copying everything in -//using namespace gtsam; +/*namespace std { + template + //Module.cpp needs to be changed to allow lowercase classnames + class vector + { + //Capcaity + size_t size() const; + size_t max_size() const; + void resize(size_t sz, T c = T()); + size_t capacity() const; + bool empty() const; + void reserve(size_t n); + + //Element acces + T& at(size_t n); + const T& at(size_t n) const; + T& front(); + const T& front() const; + T& back(); + const T& back() const; + + //Modifiers + void assign(size_t n, const T& u); + void push_back(const T& x); + void pop_back(); + }; +}*/ namespace gtsam { +//typedef std::vector IndexVector; + //************************************************************************* // base //************************************************************************* +/** gtsam namespace functions */ +bool linear_independent(Matrix A, Matrix B, double tol); + +virtual class Value { + // No constructors because this is an abstract class + + // Testable + void print(string s) const; + + // Manifold + size_t dim() const; +}; + +#include +virtual class LieScalar : gtsam::Value { + // Standard constructors + LieScalar(); + LieScalar(double d); + + // Standard interface + double value() const; + + // Testable + void print(string s) const; + bool equals(const gtsam::LieScalar& expected, double tol) const; + + // Group + static gtsam::LieScalar identity(); + gtsam::LieScalar inverse() const; + gtsam::LieScalar compose(const gtsam::LieScalar& p) const; + gtsam::LieScalar between(const gtsam::LieScalar& l2) const; + + // Manifold + size_t dim() const; + gtsam::LieScalar retract(Vector v) const; + Vector localCoordinates(const gtsam::LieScalar& t2) const; + + // Lie group + static gtsam::LieScalar Expmap(Vector v); + static Vector Logmap(const gtsam::LieScalar& p); +}; + +#include +virtual class LieVector : gtsam::Value { + // Standard constructors + LieVector(); + LieVector(Vector v); + + // Standard interface + Vector vector() const; + + // Testable + void print(string s) const; + bool equals(const gtsam::LieVector& expected, double tol) const; + + // Group + static gtsam::LieVector identity(); + gtsam::LieVector inverse() const; + gtsam::LieVector compose(const gtsam::LieVector& p) const; + gtsam::LieVector between(const gtsam::LieVector& l2) const; + + // Manifold + size_t dim() const; + gtsam::LieVector retract(Vector v) const; + Vector localCoordinates(const gtsam::LieVector& t2) const; + + // Lie group + static gtsam::LieVector Expmap(Vector v); + static Vector Logmap(const gtsam::LieVector& p); +}; + +#include +virtual class LieMatrix : gtsam::Value { + // Standard constructors + LieMatrix(); + LieMatrix(Matrix v); + + // Standard interface + Matrix matrix() const; + + // Testable + void print(string s) const; + bool equals(const gtsam::LieMatrix& expected, double tol) const; + + // Group + static gtsam::LieMatrix identity(); + gtsam::LieMatrix inverse() const; + gtsam::LieMatrix compose(const gtsam::LieMatrix& p) const; + gtsam::LieMatrix between(const gtsam::LieMatrix& l2) const; + + // Manifold + size_t dim() const; + gtsam::LieMatrix retract(Vector v) const; + Vector localCoordinates(const gtsam::LieMatrix & t2) const; + + // Lie group + static gtsam::LieMatrix Expmap(Vector v); + static Vector Logmap(const gtsam::LieMatrix& p); +}; + //************************************************************************* // geometry //************************************************************************* -class Point2 { - Point2(); - Point2(double x, double y); +virtual class Point2 : gtsam::Value { + // Standard Constructors + Point2(); + Point2(double x, double y); + Point2(Vector v); + + // Testable + void print(string s) const; + bool equals(const gtsam::Point2& pose, double tol) const; + + // Group + static gtsam::Point2 identity(); + gtsam::Point2 inverse() const; + gtsam::Point2 compose(const gtsam::Point2& p2) const; + gtsam::Point2 between(const gtsam::Point2& p2) const; + + // Manifold + static size_t Dim(); + size_t dim() const; + gtsam::Point2 retract(Vector v) const; + Vector localCoordinates(const gtsam::Point2& p) const; + + // Lie Group static gtsam::Point2 Expmap(Vector v); - static Vector Logmap(const gtsam::Point2& p); - void print(string s) const; - double x(); - double y(); - Vector localCoordinates(const gtsam::Point2& p); - gtsam::Point2 compose(const gtsam::Point2& p2); - gtsam::Point2 between(const gtsam::Point2& p2); - gtsam::Point2 retract(Vector v); + static Vector Logmap(const gtsam::Point2& p); + + // Standard Interface + double x() const; + double y() const; + Vector vector() const; + double dist(const gtsam::Point2& p2) const; }; -class Point3 { +virtual class StereoPoint2 : gtsam::Value { + // Standard Constructors + StereoPoint2(); + StereoPoint2(double uL, double uR, double v); + + // Testable + void print(string s) const; + bool equals(const gtsam::StereoPoint2& point, double tol) const; + + // Group + static gtsam::StereoPoint2 identity(); + gtsam::StereoPoint2 inverse() const; + gtsam::StereoPoint2 compose(const gtsam::StereoPoint2& p2) const; + gtsam::StereoPoint2 between(const gtsam::StereoPoint2& p2) const; + + // Manifold + static size_t Dim(); + size_t dim() const; + gtsam::StereoPoint2 retract(Vector v) const; + Vector localCoordinates(const gtsam::StereoPoint2& p) const; + + // Lie Group + static gtsam::StereoPoint2 Expmap(Vector v); + static Vector Logmap(const gtsam::StereoPoint2& p); + + // Standard Interface + Vector vector() const; +}; + +virtual class Point3 : gtsam::Value { + // Standard Constructors Point3(); Point3(double x, double y, double z); Point3(Vector v); - static gtsam::Point3 Expmap(Vector v); + + // Testable + void print(string s) const; + bool equals(const gtsam::Point3& p, double tol) const; + + // Group + static gtsam::Point3 identity(); + gtsam::Point3 inverse() const; + gtsam::Point3 compose(const gtsam::Point3& p2) const; + gtsam::Point3 between(const gtsam::Point3& p2) const; + + // Manifold + static size_t Dim(); + size_t dim() const; + gtsam::Point3 retract(Vector v) const; + Vector localCoordinates(const gtsam::Point3& p) const; + + // Lie Group + static gtsam::Point3 Expmap(Vector v); static Vector Logmap(const gtsam::Point3& p); - void print(string s) const; - bool equals(const gtsam::Point3& p, double tol); + + // Standard Interface Vector vector() const; - double x(); - double y(); - double z(); - Vector localCoordinates(const gtsam::Point3& p); - gtsam::Point3 retract(Vector v); - gtsam::Point3 compose(const gtsam::Point3& p2); - gtsam::Point3 between(const gtsam::Point3& p2); + double x() const; + double y() const; + double z() const; }; -class Rot2 { +virtual class Rot2 : gtsam::Value { + // Standard Constructors and Named Constructors Rot2(); Rot2(double theta); - static gtsam::Rot2 Expmap(Vector v); + static gtsam::Rot2 fromAngle(double theta); + static gtsam::Rot2 fromDegrees(double theta); + static gtsam::Rot2 fromCosSin(double c, double s); + + // Testable + void print(string s) const; + bool equals(const gtsam::Rot2& rot, double tol) const; + + // Group + static gtsam::Rot2 identity(); + gtsam::Rot2 inverse(); + gtsam::Rot2 compose(const gtsam::Rot2& p2) const; + gtsam::Rot2 between(const gtsam::Rot2& p2) const; + + // Manifold + static size_t Dim(); + size_t dim() const; + gtsam::Rot2 retract(Vector v) const; + Vector localCoordinates(const gtsam::Rot2& p) const; + + // Lie Group + static gtsam::Rot2 Expmap(Vector v); static Vector Logmap(const gtsam::Rot2& p); - static gtsam::Rot2 fromAngle(double theta); - static gtsam::Rot2 fromDegrees(double theta); - static gtsam::Rot2 fromCosSin(double c, double s); + + // Group Action on Point2 + gtsam::Point2 rotate(const gtsam::Point2& point) const; + gtsam::Point2 unrotate(const gtsam::Point2& point) const; + + // Standard Interface static gtsam::Rot2 relativeBearing(const gtsam::Point2& d); // Ignoring derivative static gtsam::Rot2 atan2(double y, double x); - void print(string s) const; - bool equals(const gtsam::Rot2& rot, double tol) const; double theta() const; double degrees() const; double c() const; double s() const; - Vector localCoordinates(const gtsam::Rot2& p); - gtsam::Rot2 retract(Vector v); - gtsam::Rot2 compose(const gtsam::Rot2& p2); - gtsam::Rot2 between(const gtsam::Rot2& p2); + Matrix matrix() const; }; -class Rot3 { +virtual class Rot3 : gtsam::Value { + // Standard Constructors and Named Constructors Rot3(); Rot3(Matrix R); - static gtsam::Rot3 Rx(double t); - static gtsam::Rot3 Ry(double t); - static gtsam::Rot3 Rz(double t); -// static gtsam::Rot3 RzRyRx(double x, double y, double z); // FIXME: overloaded functions don't work yet - static gtsam::Rot3 RzRyRx(Vector xyz); - static gtsam::Rot3 yaw (double t); // positive yaw is to right (as in aircraft heading) - static gtsam::Rot3 pitch(double t); // positive pitch is up (increasing aircraft altitude) - static gtsam::Rot3 roll (double t); // positive roll is to right (increasing yaw in aircraft) - static gtsam::Rot3 ypr(double y, double p, double r); - static gtsam::Rot3 quaternion(double w, double x, double y, double z); - static gtsam::Rot3 rodriguez(Vector v); + static gtsam::Rot3 Rx(double t); + static gtsam::Rot3 Ry(double t); + static gtsam::Rot3 Rz(double t); + static gtsam::Rot3 RzRyRx(double x, double y, double z); // FIXME: overloaded functions don't work yet + static gtsam::Rot3 RzRyRx(Vector xyz); + static gtsam::Rot3 yaw(double t); // positive yaw is to right (as in aircraft heading) + static gtsam::Rot3 pitch(double t); // positive pitch is up (increasing aircraft altitude) + static gtsam::Rot3 roll(double t); // positive roll is to right (increasing yaw in aircraft) + static gtsam::Rot3 ypr(double y, double p, double r); + static gtsam::Rot3 quaternion(double w, double x, double y, double z); + static gtsam::Rot3 rodriguez(Vector v); + + // Testable void print(string s) const; bool equals(const gtsam::Rot3& rot, double tol) const; - static gtsam::Rot3 identity(); - gtsam::Rot3 compose(const gtsam::Rot3& p2) const; + + // Group + static gtsam::Rot3 identity(); gtsam::Rot3 inverse() const; + gtsam::Rot3 compose(const gtsam::Rot3& p2) const; gtsam::Rot3 between(const gtsam::Rot3& p2) const; + + // Manifold + static size_t Dim(); + size_t dim() const; + gtsam::Rot3 retractCayley(Vector v) const; // FIXME, does not exist in both Matrix and Quaternion options + gtsam::Rot3 retract(Vector v) const; + Vector localCoordinates(const gtsam::Rot3& p) const; + + // Group Action on Point3 gtsam::Point3 rotate(const gtsam::Point3& p) const; gtsam::Point3 unrotate(const gtsam::Point3& p) const; - gtsam::Rot3 retractCayley(Vector v) const; - gtsam::Rot3 retract(Vector v) const; - Vector localCoordinates(const gtsam::Rot3& p) const; + + // Standard Interface static gtsam::Rot3 Expmap(Vector v); static Vector Logmap(const gtsam::Rot3& p); Matrix matrix() const; Matrix transpose() const; - gtsam::Point3 column(int index) const; + gtsam::Point3 column(size_t index) const; Vector xyz() const; Vector ypr() const; Vector rpy() const; - double roll() const; - double pitch() const; - double yaw() const; + double roll() const; + double pitch() const; + double yaw() const; // Vector toQuaternion() const; // FIXME: Can't cast to Vector properly }; -class Pose2 { +virtual class Pose2 : gtsam::Value { + // Standard Constructor Pose2(); Pose2(double x, double y, double theta); Pose2(double theta, const gtsam::Point2& t); Pose2(const gtsam::Rot2& r, const gtsam::Point2& t); Pose2(Vector v); + + // Testable + void print(string s) const; + bool equals(const gtsam::Pose2& pose, double tol) const; + + // Group + static gtsam::Pose2 identity(); + gtsam::Pose2 inverse() const; + gtsam::Pose2 compose(const gtsam::Pose2& p2) const; + gtsam::Pose2 between(const gtsam::Pose2& p2) const; + + // Manifold + static size_t Dim(); + size_t dim() const; + gtsam::Pose2 retract(Vector v) const; + Vector localCoordinates(const gtsam::Pose2& p) const; + + // Lie Group static gtsam::Pose2 Expmap(Vector v); static Vector Logmap(const gtsam::Pose2& p); - void print(string s) const; - bool equals(const gtsam::Pose2& pose, double tol) const; + Matrix adjointMap() const; + Vector adjoint(const Vector& xi) const; + static Matrix wedge(double vx, double vy, double w); + + // Group Actions on Point2 + gtsam::Point2 transform_from(const gtsam::Point2& p) const; + gtsam::Point2 transform_to(const gtsam::Point2& p) const; + + // Standard Interface double x() const; double y() const; double theta() const; - int dim() const; - Vector localCoordinates(const gtsam::Pose2& p); - gtsam::Pose2 retract(Vector v); - gtsam::Pose2 compose(const gtsam::Pose2& p2); - gtsam::Pose2 between(const gtsam::Pose2& p2); - gtsam::Rot2 bearing(const gtsam::Point2& point); - double range(const gtsam::Point2& point); + gtsam::Rot2 bearing(const gtsam::Point2& point) const; + double range(const gtsam::Point2& point) const; gtsam::Point2 translation() const; gtsam::Rot2 rotation() const; + Matrix matrix() const; }; -class Pose3 { +virtual class Pose3 : gtsam::Value { + // Standard Constructors Pose3(); + Pose3(const gtsam::Pose3& pose); Pose3(const gtsam::Rot3& r, const gtsam::Point3& t); + Pose3(const gtsam::Pose2& pose2); // FIXME: shadows Pose3(Pose3 pose) Pose3(Matrix t); - Pose3(const gtsam::Pose2& pose2); - static gtsam::Pose3 Expmap(Vector v); - static Vector Logmap(const gtsam::Pose3& p); + + // Testable void print(string s) const; bool equals(const gtsam::Pose3& pose, double tol) const; + + // Group + static gtsam::Pose3 identity(); + gtsam::Pose3 inverse() const; + gtsam::Pose3 compose(const gtsam::Pose3& p2) const; + gtsam::Pose3 between(const gtsam::Pose3& p2) const; + + // Manifold + static size_t Dim(); + size_t dim() const; + gtsam::Pose3 retract(Vector v) const; + gtsam::Pose3 retractFirstOrder(Vector v) const; + Vector localCoordinates(const gtsam::Pose3& T2) const; + + // Lie Group + static gtsam::Pose3 Expmap(Vector v); + static Vector Logmap(const gtsam::Pose3& p); + Matrix adjointMap() const; + Vector adjoint(const Vector& xi) const; + static Matrix wedge(double wx, double wy, double wz, double vx, double vy, double vz); + + // Group Action on Point3 + gtsam::Point3 transform_from(const gtsam::Point3& p) const; + gtsam::Point3 transform_to(const gtsam::Point3& p) const; + + // Standard Interface + gtsam::Rot3 rotation() const; + gtsam::Point3 translation() const; double x() const; double y() const; double z() const; Matrix matrix() const; - Matrix adjointMap() const; - gtsam::Pose3 compose(const gtsam::Pose3& p2); - gtsam::Pose3 between(const gtsam::Pose3& p2); - gtsam::Pose3 retract(Vector v); - gtsam::Pose3 retractFirstOrder(Vector v); - Vector localCoordinates(const gtsam::Pose3& T2) const; - gtsam::Point3 translation() const; - gtsam::Rot3 rotation() const; + gtsam::Pose3 transform_to(const gtsam::Pose3& pose) const; // FIXME: shadows other transform_to() + double range(const gtsam::Point3& point); + double range(const gtsam::Pose3& pose); }; -class CalibratedCamera { - - CalibratedCamera(); - CalibratedCamera(const gtsam::Pose3& pose); - CalibratedCamera(const Vector& v); +virtual class Cal3_S2 : gtsam::Value { + // Standard Constructors + Cal3_S2(); + Cal3_S2(double fx, double fy, double s, double u0, double v0); + Cal3_S2(Vector v); + Cal3_S2(double fov, int w, int h); - void print(string s) const; - bool equals(const gtsam::CalibratedCamera& camera, double tol) const; + // Testable + void print(string s) const; + bool equals(const gtsam::Cal3_S2& rhs, double tol) const; - gtsam::Pose3 pose() const; + // Manifold + static size_t Dim(); + size_t dim() const; + gtsam::Cal3_S2 retract(Vector v) const; + Vector localCoordinates(const gtsam::Cal3_S2& c) const; - gtsam::CalibratedCamera compose(const gtsam::CalibratedCamera& c) const; - gtsam::CalibratedCamera inverse() const; - gtsam::CalibratedCamera level(const gtsam::Pose2& pose2, double height); - gtsam::CalibratedCamera retract(const Vector& d) const; - Vector localCoordinates(const gtsam::CalibratedCamera& T2) const; + // Action on Point2 + gtsam::Point2 calibrate(const gtsam::Point2& p) const; + gtsam::Point2 uncalibrate(const gtsam::Point2& p) const; - gtsam::Point2 project(const gtsam::Point3& point) const; - static gtsam::Point2 project_to_camera(const gtsam::Point3& cameraPoint); + // Standard Interface + double fx() const; + double fy() const; + double skew() const; + double px() const; + double py() const; + gtsam::Point2 principalPoint() const; + Vector vector() const; + Matrix matrix() const; + Matrix matrix_inverse() const; }; +#include +virtual class Cal3DS2 : gtsam::Value { + // Standard Constructors + Cal3DS2(); + Cal3DS2(double fx, double fy, double s, double u0, double v0, double k1, double k2, double k3, double k4); + Cal3DS2(Vector v); + + // Testable + void print(string s) const; + bool equals(const gtsam::Cal3DS2& rhs, double tol) const; + + // Manifold + static size_t Dim(); + size_t dim() const; + gtsam::Cal3DS2 retract(Vector v) const; + Vector localCoordinates(const gtsam::Cal3DS2& c) const; + + // Action on Point2 + gtsam::Point2 uncalibrate(const gtsam::Point2& p) const; + // TODO: D2d functions that start with an uppercase letter + + // Standard Interface + double fx() const; + double fy() const; + double skew() const; + double px() const; + double py() const; + Vector vector() const; + Vector k() const; + //Matrix K() const; //FIXME: Uppercase +}; + +class Cal3_S2Stereo { + // Standard Constructors + Cal3_S2Stereo(); + Cal3_S2Stereo(double fx, double fy, double s, double u0, double v0, double b); + + // Testable + void print(string s) const; + bool equals(const gtsam::Cal3_S2Stereo& pose, double tol) const; + + // Standard Interface + double fx() const; + double fy() const; + double skew() const; + double px() const; + double py() const; + gtsam::Point2 principalPoint() const; + double baseline() const; +}; + +virtual class CalibratedCamera : gtsam::Value { + // Standard Constructors and Named Constructors + CalibratedCamera(); + CalibratedCamera(const gtsam::Pose3& pose); + CalibratedCamera(const Vector& v); + static gtsam::CalibratedCamera Level(const gtsam::Pose2& pose2, double height); + + // Testable + void print(string s) const; + bool equals(const gtsam::CalibratedCamera& camera, double tol) const; + + // Manifold + static size_t Dim(); + size_t dim() const; + gtsam::CalibratedCamera retract(const Vector& d) const; + Vector localCoordinates(const gtsam::CalibratedCamera& T2) const; + + // Group + gtsam::CalibratedCamera compose(const gtsam::CalibratedCamera& c) const; + gtsam::CalibratedCamera inverse() const; + + // Action on Point3 + gtsam::Point2 project(const gtsam::Point3& point) const; + static gtsam::Point2 project_to_camera(const gtsam::Point3& cameraPoint); + + // Standard Interface + gtsam::Pose3 pose() const; + double range(const gtsam::Point3& p) const; // TODO: Other overloaded range methods +}; + +virtual class SimpleCamera : gtsam::Value { + // Standard Constructors and Named Constructors + SimpleCamera(); + SimpleCamera(const gtsam::Pose3& pose); + SimpleCamera(const gtsam::Pose3& pose, const gtsam::Cal3_S2& K); + static gtsam::SimpleCamera Level(const gtsam::Cal3_S2& K, + const gtsam::Pose2& pose, double height); + static gtsam::SimpleCamera Level(const gtsam::Pose2& pose, double height); // FIXME overload + static gtsam::SimpleCamera Lookat(const gtsam::Point3& eye, + const gtsam::Point3& target, const gtsam::Point3& upVector, + const gtsam::Cal3_S2& K); + + // Testable + void print(string s) const; + bool equals(const gtsam::SimpleCamera& camera, double tol) const; + + // Standard Interface + gtsam::Pose3 pose() const; + gtsam::Cal3_S2 calibration(); + + // Manifold + gtsam::SimpleCamera retract(const Vector& d) const; + Vector localCoordinates(const gtsam::SimpleCamera& T2) const; + size_t dim() const; + static size_t Dim(); + + // Transformations and measurement functions + static gtsam::Point2 project_to_camera(const gtsam::Point3& cameraPoint); + pair projectSafe(const gtsam::Point3& pw) const; + gtsam::Point2 project(const gtsam::Point3& point); + gtsam::Point3 backproject(const gtsam::Point2& p, double depth) const; + double range(const gtsam::Point3& point); + double range(const gtsam::Pose3& point); // FIXME, overload +}; + +// TODO: Add this back in when Cal3DS2 has a calibrate function +//template +//virtual class PinholeCamera : gtsam::Value { +// // Standard Constructors and Named Constructors +// PinholeCamera(); +// PinholeCamera(const gtsam::Pose3& pose); +// PinholeCamera(const gtsam::Pose3& pose, const gtsam::Cal3DS2& K); +// static This Level(const gtsam::Cal3DS2& K, +// const gtsam::Pose2& pose, double height); +// static This Level(const gtsam::Pose2& pose, double height); // FIXME overload +// static This Lookat(const gtsam::Point3& eye, +// const gtsam::Point3& target, const gtsam::Point3& upVector, +// const gtsam::Cal3DS2& K); +// +// // Testable +// void print(string s) const; +// bool equals(const This& camera, double tol) const; +// +// // Standard Interface +// gtsam::Pose3 pose() const; +// CALIBRATION calibration() const; +// +// // Manifold +// This retract(const Vector& d) const; +// Vector localCoordinates(const This& T2) const; +// size_t dim() const; +// static size_t Dim(); +// +// // Transformations and measurement functions +// static gtsam::Point2 project_to_camera(const gtsam::Point3& cameraPoint); +// pair projectSafe(const gtsam::Point3& pw) const; +// gtsam::Point2 project(const gtsam::Point3& point); +// gtsam::Point3 backproject(const gtsam::Point2& p, double depth) const; +// double range(const gtsam::Point3& point); +// double range(const gtsam::Pose3& point); // FIXME, overload +//}; //************************************************************************* // inference //************************************************************************* +#include +class Permutation { + // Standard Constructors and Named Constructors + Permutation(); + Permutation(size_t nVars); + static gtsam::Permutation Identity(size_t nVars); + // Testable + void print(string s) const; + bool equals(const gtsam::Permutation& rhs, double tol) const; + // Standard interface + size_t at(size_t variable) const; + size_t size() const; + bool empty() const; + void resize(size_t newSize); + gtsam::Permutation* permute(const gtsam::Permutation& permutation) const; + gtsam::Permutation* inverse() const; + // FIXME: Cannot currently wrap std::vector + //static gtsam::Permutation PullToFront(const vector& toFront, size_t size, bool filterDuplicates); + //static gtsam::Permutation PushToBack(const vector& toBack, size_t size, bool filterDuplicates = false); + gtsam::Permutation* partialPermutation(const gtsam::Permutation& selector, const gtsam::Permutation& partialPermutation) const; +}; + +class IndexFactor { + // Standard Constructors and Named Constructors + IndexFactor(const gtsam::IndexFactor& f); + IndexFactor(const gtsam::IndexConditional& c); + IndexFactor(); + IndexFactor(size_t j); + IndexFactor(size_t j1, size_t j2); + IndexFactor(size_t j1, size_t j2, size_t j3); + IndexFactor(size_t j1, size_t j2, size_t j3, size_t j4); + IndexFactor(size_t j1, size_t j2, size_t j3, size_t j4, size_t j5); + IndexFactor(size_t j1, size_t j2, size_t j3, size_t j4, size_t j5, size_t j6); + // FIXME: Must wrap std::set for this to work + //IndexFactor(const std::set& js); + void permuteWithInverse(const gtsam::Permutation& inversePermutation); + + // From Factor + size_t size() const; + void print(string s) const; + bool equals(const gtsam::IndexFactor& other, double tol) const; + // FIXME: Need to wrap std::vector + //std::vector& keys(); +}; + +class IndexConditional { + // Standard Constructors and Named Constructors + IndexConditional(); + IndexConditional(size_t key); + IndexConditional(size_t key, size_t parent); + IndexConditional(size_t key, size_t parent1, size_t parent2); + IndexConditional(size_t key, size_t parent1, size_t parent2, size_t parent3); + // FIXME: Must wrap std::vector for this to work + //IndexFactor(size_t key, const std::vector& parents); + //IndexConditional(const std::vector& keys, size_t nrFrontals); + //template static shared_ptr FromKeys(const KEYS& keys, size_t nrFrontals); + + // Testable + void print(string s) const; + bool equals(const gtsam::IndexConditional& other, double tol) const; + + // Standard interface + size_t nrFrontals() const; + size_t nrParents() const; + gtsam::IndexFactor* toFactor() const; + + //Advanced interface + bool permuteSeparatorWithInverse(const gtsam::Permutation& inversePermutation); + void permuteWithInverse(const gtsam::Permutation& inversePermutation); +}; + +#include +class SymbolicBayesNet { + // Standard Constructors and Named Constructors + SymbolicBayesNet(); + SymbolicBayesNet(const gtsam::SymbolicBayesNet& bn); + SymbolicBayesNet(const gtsam::IndexConditional* conditional); + + // Testable + void print(string s) const; + bool equals(const gtsam::SymbolicBayesNet& other, double tol) const; + + // Standard interface + size_t size() const; + void push_back(const gtsam::IndexConditional* conditional); + //TODO:Throws parse error + //void push_back(const gtsam::SymbolicBayesNet bn); + void push_front(const gtsam::IndexConditional* conditional); + //TODO:Throws parse error + //void push_front(const gtsam::SymbolicBayesNet bn); + + //Advanced Interface + gtsam::IndexConditional* front() const; + gtsam::IndexConditional* back() const; + void pop_front(); + void permuteWithInverse(const gtsam::Permutation& inversePermutation); + bool permuteSeparatorWithInverse(const gtsam::Permutation& inversePermutation); +}; + +#include +class SymbolicBayesTree { + // Standard Constructors and Named Constructors + SymbolicBayesTree(); + SymbolicBayesTree(const gtsam::SymbolicBayesNet& bn); + SymbolicBayesTree(const gtsam::SymbolicBayesTree& other); + // FIXME: wrap needs to understand std::list + //SymbolicBayesTree(const gtsam::SymbolicBayesNet& bayesNet, std::list subtrees); + + // Testable + void print(string s) const; + bool equals(const gtsam::SymbolicBayesTree& other, double tol) const; + + // Standard interface + size_t findParentClique(const gtsam::IndexConditional& parents) const; + size_t size() const; + void saveGraph(string s) const; + void clear(); + // TODO: There are many other BayesTree member functions which might be of use +}; + +class SymbolicFactorGraph { + // Standard Constructors and Named Constructors + SymbolicFactorGraph(); + SymbolicFactorGraph(const gtsam::SymbolicBayesNet& bayesNet); + SymbolicFactorGraph(const gtsam::SymbolicBayesTree& bayesTree); + + // From FactorGraph + void push_back(gtsam::IndexFactor* factor); + void print(string s) const; + bool equals(const gtsam::SymbolicFactorGraph& rhs, double tol) const; + size_t size() const; + + // Standard interface + // FIXME: Must wrap FastSet for this to work + //FastSet keys() const; + + //Advanced Interface + void push_factor(size_t key); + void push_factor(size_t key1, size_t key2); + void push_factor(size_t key1, size_t key2, size_t key3); + void push_factor(size_t key1, size_t key2, size_t key3, size_t key4); + + pair eliminateFrontals(size_t nFrontals) const; +}; + +#include +class SymbolicSequentialSolver { + // Standard Constructors and Named Constructors + SymbolicSequentialSolver(const gtsam::SymbolicFactorGraph& factorGraph); + SymbolicSequentialSolver(const gtsam::SymbolicFactorGraph* factorGraph, const gtsam::VariableIndex* variableIndex); + + // Testable + void print(string s) const; + bool equals(const gtsam::SymbolicSequentialSolver& rhs, double tol) const; + + // Standard interface + gtsam::SymbolicBayesNet* eliminate() const; + gtsam::IndexFactor* marginalFactor(size_t j) const; +}; + +#include +class SymbolicMultifrontalSolver { + // Standard Constructors and Named Constructors + SymbolicMultifrontalSolver(const gtsam::SymbolicFactorGraph& factorGraph); + SymbolicMultifrontalSolver(const gtsam::SymbolicFactorGraph* factorGraph, const gtsam::VariableIndex* variableIndex); + + // Testable + void print(string s) const; + bool equals(const gtsam::SymbolicMultifrontalSolver& rhs, double tol) const; + + // Standard interface + gtsam::SymbolicBayesTree* eliminate() const; + gtsam::IndexFactor* marginalFactor(size_t j) const; +}; + +#include +class VariableIndex { + // Standard Constructors and Named Constructors + VariableIndex(); + // TODO: Templetize constructor when wrap supports it + //template + //VariableIndex(const T& factorGraph, size_t nVariables); + //VariableIndex(const T& factorGraph); + VariableIndex(const gtsam::SymbolicFactorGraph& factorGraph); + VariableIndex(const gtsam::SymbolicFactorGraph& factorGraph, size_t nVariables); + VariableIndex(const gtsam::GaussianFactorGraph& factorGraph); + VariableIndex(const gtsam::GaussianFactorGraph& factorGraph, size_t nVariables); + VariableIndex(const gtsam::NonlinearFactorGraph& factorGraph); + VariableIndex(const gtsam::NonlinearFactorGraph& factorGraph, size_t nVariables); + VariableIndex(const gtsam::VariableIndex& other); + + // Testable + bool equals(const gtsam::VariableIndex& other, double tol) const; + void print(string s) const; + + // Standard interface + size_t size() const; + size_t nFactors() const; + size_t nEntries() const; + void permuteInPlace(const gtsam::Permutation& permutation); +}; + +#include +template +virtual class BayesTree { + + //Constructors + BayesTree(); + + //Standard Interface + bool equals(const This& other, double tol) const; + void print(string s); + //size_t findParentClique(const gtsam::IndexVector& parents) const; + size_t size(); + CLIQUE* root() const; + void clear(); + void insert(const CLIQUE* subtree); +}; + +typedef gtsam::BayesTree ISAM2BayesTree; //************************************************************************* // linear //************************************************************************* -class SharedGaussian { - SharedGaussian(Matrix covariance); +namespace noiseModel { +#include +virtual class Base { +}; + +virtual class Gaussian : gtsam::noiseModel::Base { + static gtsam::noiseModel::Gaussian* SqrtInformation(Matrix R); + static gtsam::noiseModel::Gaussian* Covariance(Matrix R); + //Matrix R() const; // FIXME: cannot parse!!! + bool equals(gtsam::noiseModel::Base& expected, double tol); void print(string s) const; }; -class SharedDiagonal { - SharedDiagonal(Vector sigmas); +virtual class Diagonal : gtsam::noiseModel::Gaussian { + static gtsam::noiseModel::Diagonal* Sigmas(Vector sigmas); + static gtsam::noiseModel::Diagonal* Variances(Vector variances); + static gtsam::noiseModel::Diagonal* Precisions(Vector precisions); +// Matrix R() const; // FIXME: cannot parse!!! void print(string s) const; - Vector sample() const; }; -class SharedNoiseModel { - static gtsam::SharedNoiseModel Sigmas(Vector sigmas); - static gtsam::SharedNoiseModel Sigma(size_t dim, double sigma); - static gtsam::SharedNoiseModel Precisions(Vector precisions); - static gtsam::SharedNoiseModel Precision(size_t dim, double precision); - static gtsam::SharedNoiseModel Unit(size_t dim); - static gtsam::SharedNoiseModel SqrtInformation(Matrix R); - static gtsam::SharedNoiseModel Covariance(Matrix covariance); +virtual class Constrained : gtsam::noiseModel::Diagonal { + static gtsam::noiseModel::Constrained* MixedSigmas(const Vector& mu, const Vector& sigmas); + static gtsam::noiseModel::Constrained* MixedSigmas(double m, const Vector& sigmas); + static gtsam::noiseModel::Constrained* MixedVariances(const Vector& mu, const Vector& variances); + static gtsam::noiseModel::Constrained* MixedVariances(const Vector& variances); + static gtsam::noiseModel::Constrained* MixedPrecisions(const Vector& mu, const Vector& precisions); + static gtsam::noiseModel::Constrained* MixedPrecisions(const Vector& precisions); + + static gtsam::noiseModel::Constrained* All(size_t dim); + static gtsam::noiseModel::Constrained* All(size_t dim, double m); + + gtsam::noiseModel::Constrained* unit() const; +}; + +virtual class Isotropic : gtsam::noiseModel::Diagonal { + static gtsam::noiseModel::Isotropic* Sigma(size_t dim, double sigma); + static gtsam::noiseModel::Isotropic* Variance(size_t dim, double varianace); + static gtsam::noiseModel::Isotropic* Precision(size_t dim, double precision); void print(string s) const; }; +virtual class Unit : gtsam::noiseModel::Isotropic { + static gtsam::noiseModel::Unit* Create(size_t dim); + void print(string s) const; +}; +}///\namespace noiseModel + +#include +class Sampler { + //Constructors + Sampler(gtsam::noiseModel::Diagonal* model, int seed); + Sampler(Vector sigmas, int seed); + Sampler(int seed); + + //Standard Interface + size_t dim() const; + Vector sigmas() const; + gtsam::noiseModel::Diagonal* model() const; + Vector sample(); + Vector sampleNewModel(gtsam::noiseModel::Diagonal* model); +}; + class VectorValues { + //Constructors VectorValues(); - VectorValues(int nVars, int varDim); + VectorValues(const gtsam::VectorValues& other); + VectorValues(size_t nVars, size_t varDim); + + //Named Constructors + static gtsam::VectorValues Zero(const gtsam::VectorValues& model); + static gtsam::VectorValues Zero(size_t nVars, size_t varDim); + static gtsam::VectorValues SameStructure(const gtsam::VectorValues& other); + + //Standard Interface + size_t size() const; + size_t dim(size_t j) const; + size_t dim() const; + bool exists(size_t j) const; void print(string s) const; bool equals(const gtsam::VectorValues& expected, double tol) const; - int size() const; - void insert(int j, Vector value); + void insert(size_t j, Vector value); + Vector vector() const; + Vector at(size_t j) const; + + //Advanced Interface + void resizeLike(const gtsam::VectorValues& other); + void resize(size_t nVars, size_t varDim); + void setZero(); + + //FIXME: Parse errors with vector() + //const Vector& vector() const; + //Vector& vector(); + bool hasSameStructure(const gtsam::VectorValues& other) const; + double dot(const gtsam::VectorValues& V) const; + double norm() const; }; class GaussianConditional { - GaussianConditional(int key, Vector d, Matrix R, Vector sigmas); - GaussianConditional(int key, Vector d, Matrix R, int name1, Matrix S, + //Constructors + GaussianConditional(size_t key, Vector d, Matrix R, Vector sigmas); + GaussianConditional(size_t key, Vector d, Matrix R, size_t name1, Matrix S, Vector sigmas); - GaussianConditional(int key, Vector d, Matrix R, int name1, Matrix S, - int name2, Matrix T, Vector sigmas); + GaussianConditional(size_t key, Vector d, Matrix R, size_t name1, Matrix S, + size_t name2, Matrix T, Vector sigmas); + + //Standard Interface void print(string s) const; bool equals(const gtsam::GaussianConditional &cg, double tol) const; + size_t dim() const; + + //Advanced Interface + Matrix computeInformation() const; + gtsam::JacobianFactor* toFactor() const; + void solveInPlace(gtsam::VectorValues& x) const; + void solveTransposeInPlace(gtsam::VectorValues& gy) const; + void scaleFrontalsBySigma(gtsam::VectorValues& gy) const; }; class GaussianDensity { - GaussianDensity(int key, Vector d, Matrix R, Vector sigmas); + //Constructors + GaussianDensity(size_t key, Vector d, Matrix R, Vector sigmas); + + //Standard Interface void print(string s) const; Vector mean() const; Matrix information() const; @@ -292,401 +1052,856 @@ class GaussianDensity { }; class GaussianBayesNet { + //Constructors GaussianBayesNet(); + + //Standard Interface void print(string s) const; bool equals(const gtsam::GaussianBayesNet& cbn, double tol) const; void push_back(gtsam::GaussianConditional* conditional); void push_front(gtsam::GaussianConditional* conditional); }; -class GaussianFactor { +//Non-Class methods found in GaussianBayesNet.h +//FIXME: No MATLAB documentation for these functions! +/*gtsam::GaussianBayesNet scalarGaussian(size_t key, double mu, double sigma); +gtsam::GaussianBayesNet simpleGaussian(size_t key, const Vector& mu, double sigma); +void push_front(gtsam::GaussianBayesNet& bn, size_t key, Vector d, Matrix R, size_t name1, Matrix S, Vector sigmas); +void push_front(gtsam::GaussianBayesNet& bn, size_t key, Vector d, Matrix R, size_t name1, Matrix S, size_t name2, Matrix T, Vector sigmas); +gtsam::VectorValues* allocateVectorValues(const gtsam::GaussianBayesNet& bn); +gtsam::VectorValues optimize(const gtsam::GaussianBayesNet& bn); +void optimizeInPlace(const gtsam::GaussianBayesNet& bn, gtsam::VectorValues& x); +gtsam::VectorValues optimizeGradientSearch(const gtsam::GaussianBayesNet& bn); +void optimizeGradientSearchInPlace(const gtsam::GaussianBayesNet& bn, gtsam::VectorValues& grad); +gtsam::VectorValues backSubstitute(const gtsam::GaussianBayesNet& bn, const gtsam::VectorValues& gx); +gtsam::VectorValues backSubstituteTranspose(const gtsam::GaussianBayesNet& bn, const gtsam::VectorValues& gx); +pair matrix(const gtsam::GaussianBayesNet& bn); +double determinant(const gtsam::GaussianBayesNet& bayesNet); +gtsam::VectorValues gradient(const gtsam::GaussianBayesNet& bayesNet, const gtsam::VectorValues& x0); +void gradientAtZero(const gtsam::GaussianBayesNet& bayesNet, const gtsam::VectorValues& g);*/ + +virtual class GaussianFactor { void print(string s) const; bool equals(const gtsam::GaussianFactor& lf, double tol) const; double error(const gtsam::VectorValues& c) const; + gtsam::GaussianFactor* negate() const; + size_t size() const; }; -class JacobianFactor { +virtual class JacobianFactor : gtsam::GaussianFactor { + //Constructors JacobianFactor(); JacobianFactor(Vector b_in); - JacobianFactor(int i1, Matrix A1, Vector b, const gtsam::SharedDiagonal& model); - JacobianFactor(int i1, Matrix A1, int i2, Matrix A2, Vector b, - const gtsam::SharedDiagonal& model); - JacobianFactor(int i1, Matrix A1, int i2, Matrix A2, int i3, Matrix A3, - Vector b, const gtsam::SharedDiagonal& model); + JacobianFactor(size_t i1, Matrix A1, Vector b, + const gtsam::noiseModel::Diagonal* model); + JacobianFactor(size_t i1, Matrix A1, size_t i2, Matrix A2, Vector b, + const gtsam::noiseModel::Diagonal* model); + JacobianFactor(size_t i1, Matrix A1, size_t i2, Matrix A2, size_t i3, Matrix A3, + Vector b, const gtsam::noiseModel::Diagonal* model); + JacobianFactor(const gtsam::GaussianFactor& factor); + + //Testable void print(string s) const; + void printKeys(string s) const; bool equals(const gtsam::GaussianFactor& lf, double tol) const; - bool empty() const; - Vector getb() const; + size_t size() const; + Vector unweighted_error(const gtsam::VectorValues& c) const; + Vector error_vector(const gtsam::VectorValues& c) const; double error(const gtsam::VectorValues& c) const; - gtsam::GaussianConditional* eliminateFirst(); + + //Standard Interface + gtsam::GaussianFactor* negate() const; + bool empty() const; + Matrix getA() const; + Vector getb() const; + size_t rows() const; + size_t cols() const; + size_t numberOfRows() const; + bool isConstrained() const; + pair matrix() const; + Matrix matrix_augmented() const; + + gtsam::GaussianConditional* eliminateFirst(); + gtsam::GaussianConditional* eliminate(size_t nrFrontals); + gtsam::GaussianFactor* negate() const; + Matrix computeInformation() const; + void transposeMultiplyAdd(double alpha, const Vector& e, gtsam::VectorValues& x) const; + gtsam::JacobianFactor whiten() const; + gtsam::GaussianConditional* eliminateFirst(); + gtsam::GaussianConditional* eliminate(size_t nFrontals); + gtsam::GaussianConditional* splitConditional(size_t nFrontals); + + void setModel(bool anyConstrained, const Vector& sigmas); + void assertInvariants() const; + + //gtsam::SharedDiagonal& get_model(); }; -class HessianFactor { +virtual class HessianFactor : gtsam::GaussianFactor { + //Constructors HessianFactor(const gtsam::HessianFactor& gf); HessianFactor(); - HessianFactor(int j, Matrix G, Vector g, double f); - HessianFactor(int j, Vector mu, Matrix Sigma); - HessianFactor(int j1, int j2, Matrix G11, Matrix G12, Vector g1, Matrix G22, + HessianFactor(size_t j, Matrix G, Vector g, double f); + HessianFactor(size_t j, Vector mu, Matrix Sigma); + HessianFactor(size_t j1, size_t j2, Matrix G11, Matrix G12, Vector g1, Matrix G22, Vector g2, double f); - HessianFactor(int j1, int j2, int j3, Matrix G11, Matrix G12, Matrix G13, + HessianFactor(size_t j1, size_t j2, size_t j3, Matrix G11, Matrix G12, Matrix G13, Vector g1, Matrix G22, Matrix G23, Vector g2, Matrix G33, Vector g3, double f); HessianFactor(const gtsam::GaussianConditional& cg); HessianFactor(const gtsam::GaussianFactor& factor); - void print(string s) const; - bool equals(const gtsam::GaussianFactor& lf, double tol) const; - double error(const gtsam::VectorValues& c) const; + + //Testable + size_t size() const; + void print(string s) const; + void printKeys(string s) const; + bool equals(const gtsam::GaussianFactor& lf, double tol) const; + double error(const gtsam::VectorValues& c) const; + + //Standard Interface + size_t rows() const; + gtsam::GaussianFactor* negate() const; + Matrix info() const; + double constantTerm() const; + Vector linearTerm() const; + Matrix computeInformation() const; + + //Advanced Interface + void partialCholesky(size_t nrFrontals); + gtsam::GaussianConditional* splitEliminatedFactor(size_t nrFrontals); + void assertInvariants() const; }; class GaussianFactorGraph { GaussianFactorGraph(); - GaussianFactorGraph(const gtsam::GaussianBayesNet& CBN); + GaussianFactorGraph(const gtsam::GaussianBayesNet& CBN); - // From FactorGraph - void push_back(gtsam::GaussianFactor* factor); + // From FactorGraph void print(string s) const; bool equals(const gtsam::GaussianFactorGraph& lfgraph, double tol) const; - int size() const; + size_t size() const; + gtsam::GaussianFactor* at(size_t idx) const; + + // Inference + pair eliminateFrontals(size_t nFrontals) const; // Building the graph - void add(gtsam::JacobianFactor* factor); + void push_back(gtsam::GaussianFactor* factor); + void add(const gtsam::GaussianFactor& factor); void add(Vector b); - void add(int key1, Matrix A1, Vector b, const gtsam::SharedDiagonal& model); - void add(int key1, Matrix A1, int key2, Matrix A2, Vector b, - const gtsam::SharedDiagonal& model); - void add(int key1, Matrix A1, int key2, Matrix A2, int key3, Matrix A3, - Vector b, const gtsam::SharedDiagonal& model); - void add(gtsam::HessianFactor* factor); + void add(size_t key1, Matrix A1, Vector b, const gtsam::noiseModel::Diagonal* model); + void add(size_t key1, Matrix A1, size_t key2, Matrix A2, Vector b, + const gtsam::noiseModel::Diagonal* model); + void add(size_t key1, Matrix A1, size_t key2, Matrix A2, size_t key3, Matrix A3, + Vector b, const gtsam::noiseModel::Diagonal* model); + + //Permutations + void permuteWithInverse(const gtsam::Permutation& inversePermutation); // error and probability double error(const gtsam::VectorValues& c) const; double probPrime(const gtsam::VectorValues& c) const; // combining - static gtsam::GaussianFactorGraph combine2(const gtsam::GaussianFactorGraph& lfg1, - const gtsam::GaussianFactorGraph& lfg2); + static gtsam::GaussianFactorGraph combine2( + const gtsam::GaussianFactorGraph& lfg1, + const gtsam::GaussianFactorGraph& lfg2); void combine(const gtsam::GaussianFactorGraph& lfg); // Conversion to matrices Matrix sparseJacobian_() const; - Matrix denseJacobian() const; - Matrix denseHessian() const; + Matrix augmentedJacobian() const; + pair jacobian() const; + Matrix augmentedHessian() const; + pair hessian() const; }; +//Non-Class functions in GaussianFactorGraph.h +/*void multiplyInPlace(const gtsam::GaussianFactorGraph& fg, const gtsam::VectorValues& x, gtsam::Errors& e); +gtsam::VectorValues gradient(const gtsam::GaussianFactorGraph& fg, const gtsam::VectorValues& x0); +void gradientAtZero(const gtsam::GaussianFactorGraph& fg, gtsam::VectorValues& g); +void residual(const gtsam::GaussianFactorGraph& fg, const gtsam::VectorValues& x, gtsam::VectorValues& r); +void multiply(const gtsam::GaussianFactorGraph& fg, const gtsam::VectorValues& x, gtsam::VectorValues& r); +void transposeMultiply(const gtsam::GaussianFactorGraph& fg, const gtsam::VectorValues& x, gtsam::VectorValues& r);*/ + +class Errors { + //Constructors + Errors(); + Errors(const gtsam::VectorValues& V); + + //Testable + void print(string s); + bool equals(const gtsam::Errors& expected, double tol) const; +}; + +//Non-Class functions for Errors +//double dot(const gtsam::Errors& A, const gtsam::Errors& b); + +class GaussianISAM { + //Constructor + GaussianISAM(); + + //Standard Interface + void saveGraph(string s) const; + gtsam::GaussianFactor* marginalFactor(size_t j) const; + gtsam::GaussianBayesNet* marginalBayesNet(size_t key) const; + Matrix marginalCovariance(size_t key) const; + gtsam::GaussianBayesNet* jointBayesNet(size_t key1, size_t key2) const; + void clear(); +}; + +#include class GaussianSequentialSolver { - GaussianSequentialSolver(const gtsam::GaussianFactorGraph& graph, bool useQR); - gtsam::GaussianBayesNet* eliminate() const; - gtsam::VectorValues* optimize() const; - gtsam::GaussianFactor* marginalFactor(int j) const; - Matrix marginalCovariance(int j) const; + //Constructors + GaussianSequentialSolver(const gtsam::GaussianFactorGraph& graph, + bool useQR); + + //Standard Interface + void replaceFactors(const gtsam::GaussianFactorGraph* factorGraph); + gtsam::GaussianBayesNet* eliminate() const; + gtsam::VectorValues* optimize() const; + gtsam::GaussianFactor* marginalFactor(size_t j) const; + Matrix marginalCovariance(size_t j) const; }; +#include +virtual class IterativeOptimizationParameters { + string getKernel() const ; + string getVerbosity() const; + void setKernel(string s) ; + void setVerbosity(string s) ; + void print() const; +}; + +//virtual class IterativeSolver { +// IterativeSolver(); +// gtsam::VectorValues optimize (); +//}; + +#include +virtual class ConjugateGradientParameters : gtsam::IterativeOptimizationParameters { + ConjugateGradientParameters(); + size_t getMinIterations() const ; + size_t getMaxIterations() const ; + size_t getReset() const; + double getEpsilon_rel() const; + double getEpsilon_abs() const; + + void setMinIterations(size_t value); + void setMaxIterations(size_t value); + void setReset(size_t value); + void setEpsilon_rel(double value); + void setEpsilon_abs(double value); + void print(string s); +}; + +#include +virtual class SubgraphSolverParameters : gtsam::ConjugateGradientParameters { + SubgraphSolverParameters(); + void print(string s) const; +}; + +class SubgraphSolver { + SubgraphSolver(const gtsam::GaussianFactorGraph &A, const gtsam::SubgraphSolverParameters ¶meters); + SubgraphSolver(const gtsam::GaussianFactorGraph &Ab1, const gtsam::GaussianFactorGraph &Ab2, const gtsam::SubgraphSolverParameters ¶meters); + gtsam::VectorValues optimize() const; +}; + +#include class KalmanFilter { KalmanFilter(size_t n); - gtsam::GaussianDensity* init(Vector x0, const gtsam::SharedDiagonal& P0); + // gtsam::GaussianDensity* init(Vector x0, const gtsam::SharedDiagonal& P0); gtsam::GaussianDensity* init(Vector x0, Matrix P0); void print(string s) const; - static int step(gtsam::GaussianDensity* p); - gtsam::GaussianDensity* predict(gtsam::GaussianDensity* p, Matrix F, Matrix B, Vector u, - const gtsam::SharedDiagonal& modelQ); - gtsam::GaussianDensity* predictQ(gtsam::GaussianDensity* p, Matrix F, Matrix B, Vector u, - Matrix Q); - gtsam::GaussianDensity* predict2(gtsam::GaussianDensity* p, Matrix A0, Matrix A1, Vector b, - const gtsam::SharedDiagonal& model); - gtsam::GaussianDensity* update(gtsam::GaussianDensity* p, Matrix H, Vector z, - const gtsam::SharedDiagonal& model); - gtsam::GaussianDensity* updateQ(gtsam::GaussianDensity* p, Matrix H, Vector z, - Matrix Q); + static size_t step(gtsam::GaussianDensity* p); + gtsam::GaussianDensity* predict(gtsam::GaussianDensity* p, Matrix F, + Matrix B, Vector u, const gtsam::noiseModel::Diagonal* modelQ); + gtsam::GaussianDensity* predictQ(gtsam::GaussianDensity* p, Matrix F, + Matrix B, Vector u, Matrix Q); + gtsam::GaussianDensity* predict2(gtsam::GaussianDensity* p, Matrix A0, + Matrix A1, Vector b, const gtsam::noiseModel::Diagonal* model); + gtsam::GaussianDensity* update(gtsam::GaussianDensity* p, Matrix H, + Vector z, const gtsam::noiseModel::Diagonal* model); + gtsam::GaussianDensity* updateQ(gtsam::GaussianDensity* p, Matrix H, + Vector z, Matrix Q); }; //************************************************************************* // nonlinear //************************************************************************* +#include +size_t symbol(char chr, size_t index); +char symbolChr(size_t key); +size_t symbolIndex(size_t key); + +#include class Ordering { - Ordering(); + // Standard Constructors and Named Constructors + Ordering(); + + // Testable void print(string s) const; bool equals(const gtsam::Ordering& ord, double tol) const; - void push_back(size_t key); + + // Standard interface + size_t nVars() const; + size_t size() const; + size_t at(size_t key) const; + bool exists(size_t key) const; + void insert(size_t key, size_t order); + void push_back(size_t key); + void permuteWithInverse(const gtsam::Permutation& inversePermutation); + gtsam::InvertedOrdering invert() const; }; -}///\namespace gtsam +class InvertedOrdering { + InvertedOrdering(); -//************************************************************************* -// planarSLAM -//************************************************************************* + // FIXME: add bracket operator overload -#include -namespace planarSLAM { + bool empty() const; + size_t size() const; + bool count(size_t index) const; // Use as a boolean function with implicit cast -class Values { - Values(); - void print(string s) const; - gtsam::Pose2 pose(int key) const; - gtsam::Point2 point(int key) const; - void insertPose(int key, const gtsam::Pose2& pose); - void insertPoint(int key, const gtsam::Point2& point); + void clear(); }; -class Graph { - Graph(); +class NonlinearFactorGraph { + NonlinearFactorGraph(); + NonlinearFactorGraph(const gtsam::NonlinearFactorGraph& graph); + // FactorGraph void print(string s) const; + bool equals(const gtsam::NonlinearFactorGraph& fg, double tol) const; + size_t size() const; + bool empty() const; + void remove(size_t i); + size_t nrFactors() const; + gtsam::NonlinearFactor* at(size_t i) const; + void push_back(const gtsam::NonlinearFactorGraph& factors); - double error(const planarSLAM::Values& values) const; - gtsam::Ordering* orderingCOLAMD(const planarSLAM::Values& values) const; - gtsam::GaussianFactorGraph* linearize(const planarSLAM::Values& values, + // NonlinearFactorGraph + double error(const gtsam::Values& values) const; + double probPrime(const gtsam::Values& values) const; + void add(const gtsam::NonlinearFactor* factor); + gtsam::Ordering* orderingCOLAMD(const gtsam::Values& values) const; + // Ordering* orderingCOLAMDConstrained(const gtsam::Values& c, const std::map& constraints) const; + gtsam::GaussianFactorGraph* linearize(const gtsam::Values& values, const gtsam::Ordering& ordering) const; - - void addPrior(int key, const gtsam::Pose2& pose, const gtsam::SharedNoiseModel& noiseModel); - void addPoseConstraint(int key, const gtsam::Pose2& pose); - void addOdometry(int key1, int key2, const gtsam::Pose2& odometry, const gtsam::SharedNoiseModel& noiseModel); - void addBearing(int poseKey, int pointKey, const gtsam::Rot2& bearing, const gtsam::SharedNoiseModel& noiseModel); - void addRange(int poseKey, int pointKey, double range, const gtsam::SharedNoiseModel& noiseModel); - void addBearingRange(int poseKey, int pointKey, const gtsam::Rot2& bearing, double range, - const gtsam::SharedNoiseModel& noiseModel); - planarSLAM::Values optimize(const planarSLAM::Values& initialEstimate); + gtsam::SymbolicFactorGraph* symbolic(const gtsam::Ordering& ordering) const; + gtsam::NonlinearFactorGraph clone() const; }; -class Odometry { - Odometry(int key1, int key2, const gtsam::Pose2& measured, - const gtsam::SharedNoiseModel& model); +virtual class NonlinearFactor { void print(string s) const; - gtsam::GaussianFactor* linearize(const planarSLAM::Values& center, const gtsam::Ordering& ordering) const; + void printKeys(string s) const; + void equals(const gtsam::NonlinearFactor& other, double tol) const; + gtsam::KeyVector keys() const; + size_t size() const; + size_t dim() const; + double error(const gtsam::Values& c) const; + bool active(const gtsam::Values& c) const; + gtsam::GaussianFactor* linearize(const gtsam::Values& c, const gtsam::Ordering& ordering) const; + gtsam::NonlinearFactor* clone() const; + // gtsam::NonlinearFactor* rekey(const gtsam::KeyVector& newKeys) const; //FIXME: Conversion from KeyVector to std::vector does not happen }; -}///\namespace planarSLAM - -//************************************************************************* -// gtsam::Pose2SLAM -//************************************************************************* - -#include -namespace pose2SLAM { - -class Values { - Values(); - void print(string s) const; - void insertPose(int key, const gtsam::Pose2& pose); - gtsam::Pose2 pose(int i); -}; - -class Graph { - Graph(); - - void print(string s) const; - - double error(const pose2SLAM::Values& values) const; - gtsam::Ordering* orderingCOLAMD(const pose2SLAM::Values& values) const; - gtsam::GaussianFactorGraph* linearize(const pose2SLAM::Values& values, - const gtsam::Ordering& ordering) const; - - void addPrior(int key, const gtsam::Pose2& pose, const gtsam::SharedNoiseModel& noiseModel); - void addPoseConstraint(int key, const gtsam::Pose2& pose); - void addOdometry(int key1, int key2, const gtsam::Pose2& odometry, const gtsam::SharedNoiseModel& noiseModel); - pose2SLAM::Values optimize(const pose2SLAM::Values& initialEstimate); -}; - -}///\namespace pose2SLAM - -//************************************************************************* -// Simulated2D -//************************************************************************* - -#include -namespace simulated2D { - +#include class Values { Values(); - void insertPose(int i, const gtsam::Point2& p); - void insertPoint(int j, const gtsam::Point2& p); - int nrPoses() const; - int nrPoints() const; - gtsam::Point2 pose(int i); - gtsam::Point2 point(int j); + Values(const gtsam::Values& other); + + size_t size() const; + bool empty() const; + void clear(); + size_t dim() const; + + void print(string s) const; + bool equals(const gtsam::Values& other, double tol) const; + + void insert(size_t j, const gtsam::Value& value); + void insert(const gtsam::Values& values); + void update(size_t j, const gtsam::Value& val); + void update(const gtsam::Values& values); + void erase(size_t j); + void swap(gtsam::Values& values); + + bool exists(size_t j) const; + gtsam::Value at(size_t j) const; + gtsam::KeyList keys() const; + + gtsam::VectorValues zeroVectors(const gtsam::Ordering& ordering) const; + gtsam::Ordering* orderingArbitrary(size_t firstVar) const; + + gtsam::Values retract(const gtsam::VectorValues& delta, const gtsam::Ordering& ordering) const; + gtsam::VectorValues localCoordinates(const gtsam::Values& cp, const gtsam::Ordering& ordering) const; + void localCoordinates(const gtsam::Values& cp, const gtsam::Ordering& ordering, gtsam::VectorValues& delta) const; }; -class Graph { - Graph(); +// Actually a FastList +#include +class KeyList { + KeyList(); + KeyList(const gtsam::KeyList& other); + + // Note: no print function + + // common STL methods + size_t size() const; + bool empty() const; + void clear(); + + // structure specific methods + size_t front() const; + size_t back() const; + void push_back(size_t key); + void push_front(size_t key); + void sort(); + void remove(size_t key); }; -// TODO: add factors, etc. +// Actually a FastSet +#include +class KeySet { + KeySet(); + KeySet(const gtsam::KeySet& other); -}///\namespace simulated2D + // Testable + void print(string s) const; + bool equals(const gtsam::KeySet& other) const; -// Simulated2DOriented Example Domain -#include -namespace simulated2DOriented { + // common STL methods + size_t size() const; + bool empty() const; + void clear(); -class Values { - Values(); - void insertPose(int i, const gtsam::Pose2& p); - void insertPoint(int j, const gtsam::Point2& p); - int nrPoses() const; - int nrPoints() const; - gtsam::Pose2 pose(int i); - gtsam::Point2 point(int j); + // structure specific methods + void insert(size_t key); + bool erase(size_t key); // returns true if value was removed + bool count(size_t key) const; // returns true if value exists }; -class Graph { - Graph(); +// Actually a FastVector +#include +class KeyVector { + KeyVector(); + KeyVector(const gtsam::KeyVector& other); + KeyVector(const gtsam::KeySet& other); + KeyVector(const gtsam::KeyList& other); + + // Note: no print function + + // common STL methods + size_t size() const; + bool empty() const; + void clear(); + + // structure specific methods + size_t at(size_t i) const; + size_t front() const; + size_t back() const; + void push_back(size_t key) const; }; -// TODO: add factors, etc. +#include +class Marginals { + Marginals(const gtsam::NonlinearFactorGraph& graph, + const gtsam::Values& solution); + void print(string s) const; + Matrix marginalCovariance(size_t variable) const; + Matrix marginalInformation(size_t variable) const; + gtsam::JointMarginal jointMarginalCovariance(const gtsam::KeyVector& variables) const; + gtsam::JointMarginal jointMarginalInformation(const gtsam::KeyVector& variables) const; +}; -}///\namespace simulated2DOriented +class JointMarginal { + Matrix at(size_t iVariable, size_t jVariable) const; + Matrix fullMatrix() const; + void print(string s) const; + void print() const; +}; + +//************************************************************************* +// Nonlinear optimizers +//************************************************************************* + +#include +virtual class NonlinearOptimizerParams { + NonlinearOptimizerParams(); + void print(string s) const; + + size_t getMaxIterations() const; + double getRelativeErrorTol() const; + double getAbsoluteErrorTol() const; + double getErrorTol() const; + string getVerbosity() const; + + void setMaxIterations(size_t value); + void setRelativeErrorTol(double value); + void setAbsoluteErrorTol(double value); + void setErrorTol(double value); + void setVerbosity(string s); +}; + +#include +virtual class SuccessiveLinearizationParams : gtsam::NonlinearOptimizerParams { + SuccessiveLinearizationParams(); + + string getLinearSolverType() const; + + void setLinearSolverType(string solver); + void setOrdering(const gtsam::Ordering& ordering); + void setIterativeParams(const gtsam::SubgraphSolverParameters ¶ms); + + bool isMultifrontal() const; + bool isSequential() const; + bool isCholmod() const; + bool isCG() const; +}; + +#include +virtual class GaussNewtonParams : gtsam::SuccessiveLinearizationParams { + GaussNewtonParams(); +}; + +#include +virtual class LevenbergMarquardtParams : gtsam::SuccessiveLinearizationParams { + LevenbergMarquardtParams(); + + double getlambdaInitial() const; + double getlambdaFactor() const; + double getlambdaUpperBound() const; + string getVerbosityLM() const; + + void setlambdaInitial(double value); + void setlambdaFactor(double value); + void setlambdaUpperBound(double value); + void setVerbosityLM(string s); +}; + +#include +virtual class DoglegParams : gtsam::SuccessiveLinearizationParams { + DoglegParams(); + + double getDeltaInitial() const; + string getVerbosityDL() const; + + void setDeltaInitial(double deltaInitial) const; + void setVerbosityDL(string verbosityDL) const; +}; + +virtual class NonlinearOptimizer { + gtsam::Values optimize(); + gtsam::Values optimizeSafely(); + double error() const; + int iterations() const; + gtsam::Values values() const; + void iterate() const; +}; + +virtual class GaussNewtonOptimizer : gtsam::NonlinearOptimizer { + GaussNewtonOptimizer(const gtsam::NonlinearFactorGraph& graph, const gtsam::Values& initialValues); + GaussNewtonOptimizer(const gtsam::NonlinearFactorGraph& graph, const gtsam::Values& initialValues, const gtsam::GaussNewtonParams& params); +}; + +virtual class DoglegOptimizer : gtsam::NonlinearOptimizer { + DoglegOptimizer(const gtsam::NonlinearFactorGraph& graph, const gtsam::Values& initialValues); + DoglegOptimizer(const gtsam::NonlinearFactorGraph& graph, const gtsam::Values& initialValues, const gtsam::DoglegParams& params); + double getDelta() const; +}; + +virtual class LevenbergMarquardtOptimizer : gtsam::NonlinearOptimizer { + LevenbergMarquardtOptimizer(const gtsam::NonlinearFactorGraph& graph, const gtsam::Values& initialValues); + LevenbergMarquardtOptimizer(const gtsam::NonlinearFactorGraph& graph, const gtsam::Values& initialValues, const gtsam::LevenbergMarquardtParams& params); + double lambda() const; + void print(string str) const; +}; + +#include +class ISAM2GaussNewtonParams { + ISAM2GaussNewtonParams(); + + void print(string str) const; + + /** Getters and Setters for all properties */ + double getWildfireThreshold() const; + void setWildfireThreshold(double wildfireThreshold); +}; + +class ISAM2DoglegParams { + ISAM2DoglegParams(); + + void print(string str) const; + + /** Getters and Setters for all properties */ + double getWildfireThreshold() const; + void setWildfireThreshold(double wildfireThreshold); + double getInitialDelta() const; + void setInitialDelta(double initialDelta); + string getAdaptationMode() const; + void setAdaptationMode(string adaptationMode); + bool isVerbose() const; + void setVerbose(bool verbose); +}; + +class ISAM2ThresholdMapValue { + ISAM2ThresholdMapValue(char c, Vector thresholds); + ISAM2ThresholdMapValue(const gtsam::ISAM2ThresholdMapValue& other); +}; + +class ISAM2ThresholdMap { + ISAM2ThresholdMap(); + ISAM2ThresholdMap(const gtsam::ISAM2ThresholdMap& other); + + // Note: no print function + + // common STL methods + size_t size() const; + bool empty() const; + void clear(); + + // structure specific methods + void insert(const gtsam::ISAM2ThresholdMapValue& value) const; +}; + +class ISAM2Params { + ISAM2Params(); + + void print(string str) const; + + /** Getters and Setters for all properties */ + void setOptimizationParams(const gtsam::ISAM2GaussNewtonParams& params); + void setOptimizationParams(const gtsam::ISAM2DoglegParams& params); + void setRelinearizeThreshold(double relinearizeThreshold); + void setRelinearizeThreshold(const gtsam::ISAM2ThresholdMap& relinearizeThreshold); + int getRelinearizeSkip() const; + void setRelinearizeSkip(int relinearizeSkip); + bool isEnableRelinearization() const; + void setEnableRelinearization(bool enableRelinearization); + bool isEvaluateNonlinearError() const; + void setEvaluateNonlinearError(bool evaluateNonlinearError); + string getFactorization() const; + void setFactorization(string factorization); + bool isCacheLinearizedFactors() const; + void setCacheLinearizedFactors(bool cacheLinearizedFactors); + bool isEnableDetailedResults() const; + void setEnableDetailedResults(bool enableDetailedResults); + bool isEnablePartialRelinearizationCheck() const; + void setEnablePartialRelinearizationCheck(bool enablePartialRelinearizationCheck); +}; + +virtual class ISAM2Clique { + + //Constructors + ISAM2Clique(const gtsam::GaussianConditional* conditional); + + //Standard Interface + Vector gradientContribution() const; + gtsam::ISAM2Clique* clone() const; + void print(string s); + + void permuteWithInverse(const gtsam::Permutation& inversePermutation); + bool permuteSeparatorWithInverse(const gtsam::Permutation& inversePermutation); +}; + +class ISAM2Result { + ISAM2Result(); + + void print(string str) const; + + /** Getters and Setters for all properties */ + size_t getVariablesRelinearized() const; + size_t getVariablesReeliminated() const; + size_t getCliques() const; +}; + +virtual class ISAM2 : gtsam::ISAM2BayesTree { + ISAM2(); + ISAM2(const gtsam::ISAM2Params& params); + + bool equals(const gtsam::ISAM2& other, double tol) const; + void print(string s) const; + void printStats() const; + void saveGraph(string s) const; + + gtsam::ISAM2Result update(); + gtsam::ISAM2Result update(const gtsam::NonlinearFactorGraph& newFactors, const gtsam::Values& newTheta); + gtsam::ISAM2Result update(const gtsam::NonlinearFactorGraph& newFactors, const gtsam::Values& newTheta, const gtsam::KeyVector& removeFactorIndices); + // TODO: wrap the full version of update + //void update(const gtsam::NonlinearFactorGraph& newFactors, const gtsam::Values& newTheta, const gtsam::KeyVector& removeFactorIndices, FastMap& constrainedKeys); + //void update(const gtsam::NonlinearFactorGraph& newFactors, const gtsam::Values& newTheta, const gtsam::KeyVector& removeFactorIndices, FastMap& constrainedKeys, bool force_relinearize); + + gtsam::Values getLinearizationPoint() const; + gtsam::Values calculateEstimate() const; + gtsam::Values calculateBestEstimate() const; + gtsam::VectorValues getDelta() const; + gtsam::NonlinearFactorGraph getFactorsUnsafe() const; + gtsam::Ordering getOrdering() const; + gtsam::VariableIndex getVariableIndex() const; + gtsam::ISAM2Params params() const; +}; + +#include +class NonlinearISAM { + NonlinearISAM(); + NonlinearISAM(int reorderInterval); + void print(string s) const; + void printStats() const; + void saveGraph(string s) const; + gtsam::Values estimate() const; + Matrix marginalCovariance(size_t key) const; + int reorderInterval() const; + int reorderCounter() const; + void update(const gtsam::NonlinearFactorGraph& newFactors, const gtsam::Values& initialValues); + void reorder_relinearize(); + void addKey(size_t key); + void setOrdering(const gtsam::Ordering& new_ordering); + + // These might be expensive as instead of a reference the wrapper will make a copy + gtsam::GaussianISAM bayesTree() const; + gtsam::Values getLinearizationPoint() const; + gtsam::Ordering getOrdering() const; + gtsam::NonlinearFactorGraph getFactorsUnsafe() const; +}; + +//************************************************************************* +// Nonlinear factor types +//************************************************************************* +#include +#include +#include +#include +#include +#include + +#include +template +virtual class PriorFactor : gtsam::NonlinearFactor { + PriorFactor(size_t key, const T& prior, const gtsam::noiseModel::Base* noiseModel); +}; -//// These are considered to be broken and will be added back as they start working -//// It's assumed that there have been interface changes that might break this -// -//class Ordering{ -// Ordering(string key); -// void print(string s) const; -// bool equals(const Ordering& ord, double tol) const; -// Ordering subtract(const Ordering& keys) const; -// void unique (); -// void reverse (); -// void push_back(string s); -//}; -// -//class GaussianFactorSet { -// GaussianFactorSet(); -// void push_back(GaussianFactor* factor); -//}; -// -//class Simulated2DPosePrior { -// Simulated2DPosePrior(Point2& mu, const SharedDiagonal& model, int i); -// void print(string s) const; -// double error(const Simulated2DValues& c) const; -//}; -// -//class Simulated2DOrientedPosePrior { -// Simulated2DOrientedPosePrior(Pose2& mu, const SharedDiagonal& model, int i); -// void print(string s) const; -// double error(const Simulated2DOrientedValues& c) const; -//}; -// -//class Simulated2DPointPrior { -// Simulated2DPointPrior(Point2& mu, const SharedDiagonal& model, int i); -// void print(string s) const; -// double error(const Simulated2DValues& c) const; -//}; -// -//class Simulated2DOdometry { -// Simulated2DOdometry(Point2& mu, const SharedDiagonal& model, int i1, int i2); -// void print(string s) const; -// double error(const Simulated2DValues& c) const; -//}; -// -//class Simulated2DOrientedOdometry { -// Simulated2DOrientedOdometry(Pose2& mu, const SharedDiagonal& model, int i1, int i2); -// void print(string s) const; -// double error(const Simulated2DOrientedValues& c) const; -//}; -// -//class Simulated2DMeasurement { -// Simulated2DMeasurement(Point2& mu, const SharedDiagonal& model, int i, int j); -// void print(string s) const; -// double error(const Simulated2DValues& c) const; -//}; -// -//class GaussianFactor { -// GaussianFactor(string key1, -// Matrix A1, -// Vector b_in, -// const SharedDiagonal& model); -// GaussianFactor(string key1, -// Matrix A1, -// string key2, -// Matrix A2, -// Vector b_in, -// const SharedDiagonal& model); -// GaussianFactor(string key1, -// Matrix A1, -// string key2, -// Matrix A2, -// string key3, -// Matrix A3, -// Vector b_in, -// const SharedDiagonal& model); -// bool involves(string key) const; -// Matrix getA(string key) const; -// pair matrix(const Ordering& ordering) const; -// pair eliminate(string key) const; -//}; -// -//class GaussianFactorGraph { -// GaussianConditional* eliminateOne(string key); -// GaussianBayesNet* eliminate_(const Ordering& ordering); -// VectorValues* optimize_(const Ordering& ordering); -// pair matrix(const Ordering& ordering) const; -// VectorValues* steepestDescent_(const VectorValues& x0) const; -// VectorValues* conjugateGradientDescent_(const VectorValues& x0) const; -//}; -// -//class gtsam::Pose2Values{ -// Pose2Values(); -// Pose2 get(string key) const; -// void insert(string name, const gtsam::Pose2& val); -// void print(string s) const; -// void clear(); -// int size(); -//}; -// -//class gtsam::Pose2Factor { -// Pose2Factor(string key1, string key2, -// const gtsam::Pose2& measured, Matrix measurement_covariance); -// void print(string name) const; -// double error(const gtsam::Pose2Values& c) const; -// size_t size() const; -// GaussianFactor* linearize(const gtsam::Pose2Values& config) const; -//}; -// -//class gtsam::pose2SLAM::Graph{ -// pose2SLAM::Graph(); -// void print(string s) const; -// GaussianFactorGraph* linearize_(const gtsam::Pose2Values& config) const; -// void push_back(Pose2Factor* factor); -//}; -// -//class SymbolicFactor{ -// SymbolicFactor(const Ordering& keys); -// void print(string s) const; -//}; -// -//class Simulated2DPosePrior { -// GaussianFactor* linearize(const Simulated2DValues& config) const; -//}; -// -//class Simulated2DOrientedPosePrior { -// GaussianFactor* linearize(const Simulated2DOrientedValues& config) const; -//}; -// -//class Simulated2DPointPrior { -// GaussianFactor* linearize(const Simulated2DValues& config) const; -//}; -// -//class Simulated2DOdometry { -// GaussianFactor* linearize(const Simulated2DValues& config) const; -//}; -// -//class Simulated2DOrientedOdometry { -// GaussianFactor* linearize(const Simulated2DOrientedValues& config) const; -//}; -// -//class Simulated2DMeasurement { -// GaussianFactor* linearize(const Simulated2DValues& config) const; -//}; -// -//class gtsam::Pose2SLAMOptimizer { -// Pose2SLAMOptimizer(string dataset_name); -// void print(string s) const; -// void update(Vector x) const; -// Vector optimize() const; -// double error() const; -// Matrix a1() const; -// Matrix a2() const; -// Vector b1() const; -// Vector b2() const; -//}; +#include +template +virtual class BetweenFactor : gtsam::NonlinearFactor { + BetweenFactor(size_t key1, size_t key2, const T& relativePose, const gtsam::noiseModel::Base* noiseModel); +}; + + +#include +template +virtual class NonlinearEquality : gtsam::NonlinearFactor { + // Constructor - forces exact evaluation + NonlinearEquality(size_t j, const T& feasible); + // Constructor - allows inexact evaluation + NonlinearEquality(size_t j, const T& feasible, double error_gain); +}; + + +#include +template +virtual class RangeFactor : gtsam::NonlinearFactor { + RangeFactor(size_t key1, size_t key2, double measured, const gtsam::noiseModel::Base* noiseModel); +}; + +typedef gtsam::RangeFactor RangeFactorPosePoint2; +typedef gtsam::RangeFactor RangeFactorPosePoint3; +typedef gtsam::RangeFactor RangeFactorPose2; +typedef gtsam::RangeFactor RangeFactorPose3; +typedef gtsam::RangeFactor RangeFactorCalibratedCameraPoint; +typedef gtsam::RangeFactor RangeFactorSimpleCameraPoint; +typedef gtsam::RangeFactor RangeFactorCalibratedCamera; +typedef gtsam::RangeFactor RangeFactorSimpleCamera; + + +#include +template +virtual class BearingFactor : gtsam::NonlinearFactor { + BearingFactor(size_t key1, size_t key2, const ROTATION& measured, const gtsam::noiseModel::Base* noiseModel); +}; + +typedef gtsam::BearingFactor BearingFactor2D; + + +#include +template +virtual class BearingRangeFactor : gtsam::NonlinearFactor { + BearingRangeFactor(size_t poseKey, size_t pointKey, const ROTATION& measuredBearing, double measuredRange, const gtsam::noiseModel::Base* noiseModel); +}; + +typedef gtsam::BearingRangeFactor BearingRangeFactor2D; + + +#include +template +virtual class GenericProjectionFactor : gtsam::NonlinearFactor { + GenericProjectionFactor(const gtsam::Point2& measured, const gtsam::noiseModel::Base* noiseModel, + size_t poseKey, size_t pointKey, const CALIBRATION* k); + gtsam::Point2 measured() const; + CALIBRATION* calibration() const; +}; +typedef gtsam::GenericProjectionFactor GenericProjectionFactorCal3_S2; +// FIXME: Add Cal3DS2 when it has a 'calibrate' function +//typedef gtsam::GenericProjectionFactor GenericProjectionFactorCal3DS2; + + +#include +template +virtual class GeneralSFMFactor : gtsam::NonlinearFactor { + GeneralSFMFactor(const gtsam::Point2& measured, const gtsam::noiseModel::Base* model, size_t cameraKey, size_t landmarkKey); + gtsam::Point2 measured() const; +}; +typedef gtsam::GeneralSFMFactor GeneralSFMFactorCal3_S2; +// FIXME: Add Cal3DS2 when it has a 'calibrate' function +//typedef gtsam::GeneralSFMFactor GeneralSFMFactorCal3DS2; + +// FIXME: Add Cal3DS2 when it has a 'calibrate' function +template +virtual class GeneralSFMFactor2 : gtsam::NonlinearFactor { + GeneralSFMFactor2(const gtsam::Point2& measured, const gtsam::noiseModel::Base* model, size_t poseKey, size_t landmarkKey, size_t calibKey); + gtsam::Point2 measured() const; +}; + + +#include +template +virtual class GenericStereoFactor : gtsam::NonlinearFactor { + GenericStereoFactor(const gtsam::StereoPoint2& measured, const gtsam::noiseModel::Base* noiseModel, + size_t poseKey, size_t landmarkKey, const gtsam::Cal3_S2Stereo* K); + gtsam::StereoPoint2 measured() const; + gtsam::Cal3_S2Stereo* calibration() const; +}; +typedef gtsam::GenericStereoFactor GenericStereoFactor3D; + +#include +pair load2D(string filename, + gtsam::noiseModel::Diagonal* model, int maxID, bool addNoise, bool smart); +pair load2D(string filename, + gtsam::noiseModel::Diagonal* model, int maxID, bool addNoise); +pair load2D(string filename, + gtsam::noiseModel::Diagonal* model, int maxID); +pair load2D(string filename, + gtsam::noiseModel::Diagonal* model); + + +//************************************************************************* +// Utilities +//************************************************************************* + +namespace utilities { + + #include + Matrix extractPoint2(const gtsam::Values& values); + Matrix extractPoint3(const gtsam::Values& values); + Matrix extractPose2(const gtsam::Values& values); + Matrix extractPose3(const gtsam::Values& values); + void perturbPoint2(gtsam::Values& values, double sigma, int seed); + void perturbPoint3(gtsam::Values& values, double sigma, int seed); + void insertBackprojections(gtsam::Values& values, const gtsam::SimpleCamera& c, Vector J, Matrix Z, double depth); + void insertProjectionFactors(gtsam::NonlinearFactorGraph& graph, size_t i, Vector J, Matrix Z, const gtsam::noiseModel::Base* model, const gtsam::Cal3_S2* K); + Matrix reprojectionErrors(const gtsam::NonlinearFactorGraph& graph, const gtsam::Values& values); + +} //\namespace utilities + +} diff --git a/gtsam/3rdparty/Eigen/CMakeLists.txt b/gtsam/3rdparty/Eigen/CMakeLists.txt index 4a6a849e9..3ba310a27 100644 --- a/gtsam/3rdparty/Eigen/CMakeLists.txt +++ b/gtsam/3rdparty/Eigen/CMakeLists.txt @@ -64,6 +64,10 @@ set(CMAKE_MODULE_PATH ${PROJECT_SOURCE_DIR}/cmake) find_package(StandardMathLibrary) + +set(EIGEN_TEST_CUSTOM_LINKER_FLAGS "" CACHE STRING "Additional linker flags when linking unit tests.") +set(EIGEN_TEST_CUSTOM_CXX_FLAGS "" CACHE STRING "Additional compiler flags when compiling unit tests.") + set(EIGEN_STANDARD_LIBRARIES_TO_LINK_TO "") if(NOT STANDARD_MATH_LIBRARY_FOUND) @@ -103,6 +107,8 @@ endif() add_definitions("-DEIGEN_PERMANENTLY_DISABLE_STUPID_WARNINGS") +set(EIGEN_TEST_MAX_SIZE "320" CACHE STRING "Maximal matrix/vector size, default is 320") + if(CMAKE_COMPILER_IS_GNUCXX) set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -Wnon-virtual-dtor -Wno-long-long -ansi -Wundef -Wcast-align -Wchar-subscripts -Wall -W -Wpointer-arith -Wwrite-strings -Wformat-security -fexceptions -fno-check-new -fno-common -fstrict-aliasing") set(CMAKE_CXX_FLAGS_DEBUG "-g3") @@ -158,7 +164,7 @@ if(CMAKE_COMPILER_IS_GNUCXX) option(EIGEN_TEST_NEON "Enable/Disable Neon in tests/examples" OFF) if(EIGEN_TEST_NEON) - set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mfloat-abi=softfp -mfpu=neon -mcpu=cortex-a8") + set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mfpu=neon -mcpu=cortex-a8") message(STATUS "Enabling NEON in tests/examples") endif() @@ -301,44 +307,9 @@ add_subdirectory(Eigen) add_subdirectory(doc EXCLUDE_FROM_ALL) -add_custom_target(buildtests) -add_custom_target(check COMMAND "ctest") -add_dependencies(check buildtests) - -# CMake/Ctest does not allow us to change the build command, -# so we have to workaround by directly editing the generated DartConfiguration.tcl file -# save CMAKE_MAKE_PROGRAM -set(CMAKE_MAKE_PROGRAM_SAVE ${CMAKE_MAKE_PROGRAM}) -# and set a fake one -set(CMAKE_MAKE_PROGRAM "@EIGEN_MAKECOMMAND_PLACEHOLDER@") - -include(CTest) +include(EigenConfigureTesting) +# fixme, not sure this line is still needed: enable_testing() # must be called from the root CMakeLists, see man page -include(EigenTesting) -ei_init_testing() - -# overwrite default DartConfiguration.tcl -# The worarounds are different for each version of the MSVC IDE -if(MSVC_IDE) - if(MSVC_VERSION EQUAL 1600) # MSVC 2010 - set(EIGEN_MAKECOMMAND_PLACEHOLDER "${CMAKE_MAKE_PROGRAM_SAVE} buildtests.vcxproj /p:Configuration=\${CTEST_CONFIGURATION_TYPE} \n # ") - else() # MSVC 2008 (TODO check MSVC 2005) - set(EIGEN_MAKECOMMAND_PLACEHOLDER "${CMAKE_MAKE_PROGRAM_SAVE} /project buildtests") - endif() -else() - # for make and nmake - set(EIGEN_MAKECOMMAND_PLACEHOLDER "${CMAKE_MAKE_PROGRAM_SAVE} buildtests") -endif() - -configure_file(${CMAKE_BINARY_DIR}/DartConfiguration.tcl ${CMAKE_BINARY_DIR}/DartConfiguration.tcl) -# restore default CMAKE_MAKE_PROGRAM -set(CMAKE_MAKE_PROGRAM ${CMAKE_MAKE_PROGRAM_SAVE}) -# un-set temporary variables so that it is like they never existed. -# CMake 2.6.3 introduces the more logical unset() syntax for this. -set(CMAKE_MAKE_PROGRAM_SAVE) -set(EIGEN_MAKECOMMAND_PLACEHOLDER) - -configure_file(${CMAKE_SOURCE_DIR}/CTestCustom.cmake.in ${CMAKE_BINARY_DIR}/CTestCustom.cmake) if(EIGEN_LEAVE_TEST_IN_ALL_TARGET) @@ -347,15 +318,13 @@ else() add_subdirectory(test EXCLUDE_FROM_ALL) endif() -if(NOT MSVC) - if(EIGEN_LEAVE_TEST_IN_ALL_TARGET) - add_subdirectory(blas) - add_subdirectory(lapack) - else() - add_subdirectory(blas EXCLUDE_FROM_ALL) - add_subdirectory(lapack EXCLUDE_FROM_ALL) - endif() -endif(NOT MSVC) +if(EIGEN_LEAVE_TEST_IN_ALL_TARGET) + add_subdirectory(blas) + add_subdirectory(lapack) +else() + add_subdirectory(blas EXCLUDE_FROM_ALL) + add_subdirectory(lapack EXCLUDE_FROM_ALL) +endif() add_subdirectory(unsupported) @@ -369,6 +338,10 @@ if(EIGEN_BUILD_BTL) add_subdirectory(bench/btl EXCLUDE_FROM_ALL) endif(EIGEN_BUILD_BTL) +if(NOT WIN32) + add_subdirectory(bench/spbench EXCLUDE_FROM_ALL) +endif(NOT WIN32) + ei_testing_print_summary() message(STATUS "") diff --git a/gtsam/3rdparty/Eigen/COPYING.BSD b/gtsam/3rdparty/Eigen/COPYING.BSD new file mode 100644 index 000000000..11971ffe2 --- /dev/null +++ b/gtsam/3rdparty/Eigen/COPYING.BSD @@ -0,0 +1,26 @@ +/* + Copyright (c) 2011, Intel Corporation. All rights reserved. + + Redistribution and use in source and binary forms, with or without modification, + are permitted provided that the following conditions are met: + + * Redistributions of source code must retain the above copyright notice, this + list of conditions and the following disclaimer. + * Redistributions in binary form must reproduce the above copyright notice, + this list of conditions and the following disclaimer in the documentation + and/or other materials provided with the distribution. + * Neither the name of Intel Corporation nor the names of its contributors may + be used to endorse or promote products derived from this software without + specific prior written permission. + + THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND + ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED + WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE + DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR + ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES + (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; + LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON + ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS + SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. +*/ \ No newline at end of file diff --git a/gtsam/3rdparty/Eigen/CTestConfig.cmake b/gtsam/3rdparty/Eigen/CTestConfig.cmake index 7edc9d48d..a5a4eb012 100644 --- a/gtsam/3rdparty/Eigen/CTestConfig.cmake +++ b/gtsam/3rdparty/Eigen/CTestConfig.cmake @@ -8,6 +8,6 @@ set(CTEST_PROJECT_NAME "Eigen") set(CTEST_NIGHTLY_START_TIME "00:00:00 UTC") set(CTEST_DROP_METHOD "http") -set(CTEST_DROP_SITE "eigen.tuxfamily.org") +set(CTEST_DROP_SITE "manao.inria.fr") set(CTEST_DROP_LOCATION "/CDash/submit.php?project=Eigen") set(CTEST_DROP_SITE_CDASH TRUE) diff --git a/gtsam/3rdparty/Eigen/Eigen/Cholesky b/gtsam/3rdparty/Eigen/Eigen/Cholesky index 53f7bf911..f727f5d89 100644 --- a/gtsam/3rdparty/Eigen/Eigen/Cholesky +++ b/gtsam/3rdparty/Eigen/Eigen/Cholesky @@ -5,8 +5,6 @@ #include "src/Core/util/DisableStupidWarnings.h" -namespace Eigen { - /** \defgroup Cholesky_Module Cholesky module * * @@ -24,8 +22,9 @@ namespace Eigen { #include "src/misc/Solve.h" #include "src/Cholesky/LLT.h" #include "src/Cholesky/LDLT.h" - -} // namespace Eigen +#ifdef EIGEN_USE_LAPACKE +#include "src/Cholesky/LLT_MKL.h" +#endif #include "src/Core/util/ReenableStupidWarnings.h" diff --git a/gtsam/3rdparty/Eigen/Eigen/CholmodSupport b/gtsam/3rdparty/Eigen/Eigen/CholmodSupport new file mode 100644 index 000000000..745b884e7 --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/CholmodSupport @@ -0,0 +1,45 @@ +#ifndef EIGEN_CHOLMODSUPPORT_MODULE_H +#define EIGEN_CHOLMODSUPPORT_MODULE_H + +#include "SparseCore" + +#include "src/Core/util/DisableStupidWarnings.h" + +extern "C" { + #include +} + +/** \ingroup Support_modules + * \defgroup CholmodSupport_Module CholmodSupport module + * + * This module provides an interface to the Cholmod library which is part of the suitesparse package. + * It provides the two following main factorization classes: + * - class CholmodSupernodalLLT: a supernodal LLT Cholesky factorization. + * - class CholmodDecomposiiton: a general L(D)LT Cholesky factorization with automatic or explicit runtime selection of the underlying factorization method (supernodal or simplicial). + * + * For the sake of completeness, this module also propose the two following classes: + * - class CholmodSimplicialLLT + * - class CholmodSimplicialLDLT + * Note that these classes does not bring any particular advantage compared to the built-in + * SimplicialLLT and SimplicialLDLT factorization classes. + * + * \code + * #include + * \endcode + * + * In order to use this module, the cholmod headers must be accessible from the include paths, and your binary must be linked to the cholmod library and its dependencies. + * The dependencies depend on how cholmod has been compiled. + * For a cmake based project, you can use our FindCholmod.cmake module to help you in this task. + * + */ + +#include "src/misc/Solve.h" +#include "src/misc/SparseSolve.h" + +#include "src/CholmodSupport/CholmodSupport.h" + + +#include "src/Core/util/ReenableStupidWarnings.h" + +#endif // EIGEN_CHOLMODSUPPORT_MODULE_H + diff --git a/gtsam/3rdparty/Eigen/Eigen/Core b/gtsam/3rdparty/Eigen/Eigen/Core index a5025e37e..0cf101636 100644 --- a/gtsam/3rdparty/Eigen/Eigen/Core +++ b/gtsam/3rdparty/Eigen/Eigen/Core @@ -34,6 +34,12 @@ // defined e.g. EIGEN_DONT_ALIGN) so it needs to be done before we do anything with vectorization. #include "src/Core/util/Macros.h" +#include + +// this include file manages BLAS and MKL related macros +// and inclusion of their respective header files +#include "src/Core/util/MKL_support.h" + // if alignment is disabled, then disable vectorization. Note: EIGEN_ALIGN is the proper check, it takes into // account both the user's will (EIGEN_DONT_ALIGN) and our own platform checks #if !EIGEN_ALIGN @@ -136,7 +142,7 @@ #endif // MSVC for windows mobile does not have the errno.h file -#if !(defined(_MSC_VER) && defined(_WIN32_WCE)) +#if !(defined(_MSC_VER) && defined(_WIN32_WCE)) && !defined(__ARMCC_VERSION) #define EIGEN_HAS_ERRNO #endif @@ -146,7 +152,6 @@ #include #include #include -#include #include #include #include @@ -175,9 +180,6 @@ #include #endif -// defined in bits/termios.h -#undef B0 - /** \brief Namespace containing all symbols from the %Eigen library. */ namespace Eigen { @@ -201,6 +203,8 @@ inline static const char *SimdInstructionSetsInUse(void) { #endif } +} // end namespace Eigen + #define STAGE10_FULL_EIGEN2_API 10 #define STAGE20_RESOLVE_API_CONFLICTS 20 #define STAGE30_FULL_EIGEN3_API 30 @@ -247,6 +251,10 @@ using std::ptrdiff_t; * \endcode */ +/** \defgroup Support_modules Support modules [category] + * Category of modules which add support for external libraries. + */ + #include "src/Core/util/Constants.h" #include "src/Core/util/ForwardDeclarations.h" #include "src/Core/util/Meta.h" @@ -318,15 +326,15 @@ using std::ptrdiff_t; #include "src/Core/CommaInitializer.h" #include "src/Core/Flagged.h" #include "src/Core/ProductBase.h" -#include "src/Core/Product.h" +#include "src/Core/GeneralProduct.h" #include "src/Core/TriangularMatrix.h" #include "src/Core/SelfAdjointView.h" -#include "src/Core/SolveTriangular.h" +#include "src/Core/products/GeneralBlockPanelKernel.h" #include "src/Core/products/Parallelizer.h" #include "src/Core/products/CoeffBasedProduct.h" -#include "src/Core/products/GeneralBlockPanelKernel.h" #include "src/Core/products/GeneralMatrixVector.h" #include "src/Core/products/GeneralMatrixMatrix.h" +#include "src/Core/SolveTriangular.h" #include "src/Core/products/GeneralMatrixMatrixTriangular.h" #include "src/Core/products/SelfadjointMatrixVector.h" #include "src/Core/products/SelfadjointMatrixMatrix.h" @@ -347,7 +355,20 @@ using std::ptrdiff_t; #include "src/Core/ArrayBase.h" #include "src/Core/ArrayWrapper.h" -} // namespace Eigen +#ifdef EIGEN_USE_BLAS +#include "src/Core/products/GeneralMatrixMatrix_MKL.h" +#include "src/Core/products/GeneralMatrixVector_MKL.h" +#include "src/Core/products/GeneralMatrixMatrixTriangular_MKL.h" +#include "src/Core/products/SelfadjointMatrixMatrix_MKL.h" +#include "src/Core/products/SelfadjointMatrixVector_MKL.h" +#include "src/Core/products/TriangularMatrixMatrix_MKL.h" +#include "src/Core/products/TriangularMatrixVector_MKL.h" +#include "src/Core/products/TriangularSolverMatrix_MKL.h" +#endif // EIGEN_USE_BLAS + +#ifdef EIGEN_USE_MKL_VML +#include "src/Core/Assign_MKL.h" +#endif #include "src/Core/GlobalFunctions.h" diff --git a/gtsam/3rdparty/Eigen/Eigen/Eigen2Support b/gtsam/3rdparty/Eigen/Eigen/Eigen2Support index d96592a8d..c2aa2f618 100644 --- a/gtsam/3rdparty/Eigen/Eigen/Eigen2Support +++ b/gtsam/3rdparty/Eigen/Eigen/Eigen2Support @@ -31,9 +31,8 @@ #include "src/Core/util/DisableStupidWarnings.h" -namespace Eigen { - -/** \defgroup Eigen2Support_Module Eigen2 support module +/** \ingroup Support_modules + * \defgroup Eigen2Support_Module Eigen2 support module * This module provides a couple of deprecated functions improving the compatibility with Eigen2. * * To use it, define EIGEN2_SUPPORT before including any Eigen header @@ -56,13 +55,29 @@ namespace Eigen { #include "src/Eigen2Support/MathFunctions.h" -} // namespace Eigen - #include "src/Core/util/ReenableStupidWarnings.h" // Eigen2 used to include iostream #include +#define EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, SizeSuffix) \ +using Eigen::Matrix##SizeSuffix##TypeSuffix; \ +using Eigen::Vector##SizeSuffix##TypeSuffix; \ +using Eigen::RowVector##SizeSuffix##TypeSuffix; + +#define EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(TypeSuffix) \ +EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, 2) \ +EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, 3) \ +EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, 4) \ +EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, X) \ + +#define EIGEN_USING_MATRIX_TYPEDEFS \ +EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(i) \ +EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(f) \ +EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(d) \ +EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(cf) \ +EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(cd) + #define USING_PART_OF_NAMESPACE_EIGEN \ EIGEN_USING_MATRIX_TYPEDEFS \ using Eigen::Matrix; \ diff --git a/gtsam/3rdparty/Eigen/Eigen/Eigenvalues b/gtsam/3rdparty/Eigen/Eigen/Eigenvalues index 250c0f466..af99ccd1f 100644 --- a/gtsam/3rdparty/Eigen/Eigen/Eigenvalues +++ b/gtsam/3rdparty/Eigen/Eigen/Eigenvalues @@ -9,8 +9,7 @@ #include "Jacobi" #include "Householder" #include "LU" - -namespace Eigen { +#include "Geometry" /** \defgroup Eigenvalues_Module Eigenvalues module * @@ -35,8 +34,11 @@ namespace Eigen { #include "src/Eigenvalues/ComplexSchur.h" #include "src/Eigenvalues/ComplexEigenSolver.h" #include "src/Eigenvalues/MatrixBaseEigenvalues.h" - -} // namespace Eigen +#ifdef EIGEN_USE_LAPACKE +#include "src/Eigenvalues/RealSchur_MKL.h" +#include "src/Eigenvalues/ComplexSchur_MKL.h" +#include "src/Eigenvalues/SelfAdjointEigenSolver_MKL.h" +#endif #include "src/Core/util/ReenableStupidWarnings.h" diff --git a/gtsam/3rdparty/Eigen/Eigen/Geometry b/gtsam/3rdparty/Eigen/Eigen/Geometry index 78277c0c5..efd9d4504 100644 --- a/gtsam/3rdparty/Eigen/Eigen/Geometry +++ b/gtsam/3rdparty/Eigen/Eigen/Geometry @@ -13,8 +13,6 @@ #define M_PI 3.14159265358979323846 #endif -namespace Eigen { - /** \defgroup Geometry_Module Geometry module * * @@ -58,8 +56,6 @@ namespace Eigen { #include "src/Eigen2Support/Geometry/All.h" #endif -} // namespace Eigen - #include "src/Core/util/ReenableStupidWarnings.h" #endif // EIGEN_GEOMETRY_MODULE_H diff --git a/gtsam/3rdparty/Eigen/Eigen/Householder b/gtsam/3rdparty/Eigen/Eigen/Householder index 6b86cf65c..6e348db5c 100644 --- a/gtsam/3rdparty/Eigen/Eigen/Householder +++ b/gtsam/3rdparty/Eigen/Eigen/Householder @@ -5,8 +5,6 @@ #include "src/Core/util/DisableStupidWarnings.h" -namespace Eigen { - /** \defgroup Householder_Module Householder module * This module provides Householder transformations. * @@ -19,8 +17,6 @@ namespace Eigen { #include "src/Householder/HouseholderSequence.h" #include "src/Householder/BlockHouseholder.h" -} // namespace Eigen - #include "src/Core/util/ReenableStupidWarnings.h" #endif // EIGEN_HOUSEHOLDER_MODULE_H diff --git a/gtsam/3rdparty/Eigen/Eigen/IterativeLinearSolvers b/gtsam/3rdparty/Eigen/Eigen/IterativeLinearSolvers new file mode 100644 index 000000000..315c2dd1e --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/IterativeLinearSolvers @@ -0,0 +1,40 @@ +#ifndef EIGEN_ITERATIVELINEARSOLVERS_MODULE_H +#define EIGEN_ITERATIVELINEARSOLVERS_MODULE_H + +#include "SparseCore" +#include "OrderingMethods" + +#include "src/Core/util/DisableStupidWarnings.h" + +/** \ingroup Sparse_modules + * \defgroup IterativeLinearSolvers_Module IterativeLinearSolvers module + * + * This module currently provides iterative methods to solve problems of the form \c A \c x = \c b, where \c A is a squared matrix, usually very large and sparse. + * Those solvers are accessible via the following classes: + * - ConjugateGradient for selfadjoint (hermitian) matrices, + * - BiCGSTAB for general square matrices. + * + * These iterative solvers are associated with some preconditioners: + * - IdentityPreconditioner - not really useful + * - DiagonalPreconditioner - also called JAcobi preconditioner, work very well on diagonal dominant matrices. + * - IncompleteILUT - incomplete LU factorization with dual thresholding + * + * Such problems can also be solved using the direct sparse decomposition modules: SparseCholesky, CholmodSupport, UmfPackSupport, SuperLUSupport. + * + * \code + * #include + * \endcode + */ + +#include "src/misc/Solve.h" +#include "src/misc/SparseSolve.h" + +#include "src/IterativeLinearSolvers/IterativeSolverBase.h" +#include "src/IterativeLinearSolvers/BasicPreconditioners.h" +#include "src/IterativeLinearSolvers/ConjugateGradient.h" +#include "src/IterativeLinearSolvers/BiCGSTAB.h" +#include "src/IterativeLinearSolvers/IncompleteLUT.h" + +#include "src/Core/util/ReenableStupidWarnings.h" + +#endif // EIGEN_ITERATIVELINEARSOLVERS_MODULE_H diff --git a/gtsam/3rdparty/Eigen/Eigen/Jacobi b/gtsam/3rdparty/Eigen/Eigen/Jacobi index afa676813..ba8a4dc36 100644 --- a/gtsam/3rdparty/Eigen/Eigen/Jacobi +++ b/gtsam/3rdparty/Eigen/Eigen/Jacobi @@ -5,8 +5,6 @@ #include "src/Core/util/DisableStupidWarnings.h" -namespace Eigen { - /** \defgroup Jacobi_Module Jacobi module * This module provides Jacobi and Givens rotations. * @@ -21,8 +19,6 @@ namespace Eigen { #include "src/Jacobi/Jacobi.h" -} // namespace Eigen - #include "src/Core/util/ReenableStupidWarnings.h" #endif // EIGEN_JACOBI_MODULE_H diff --git a/gtsam/3rdparty/Eigen/Eigen/LU b/gtsam/3rdparty/Eigen/Eigen/LU index 226f88ca3..db5795504 100644 --- a/gtsam/3rdparty/Eigen/Eigen/LU +++ b/gtsam/3rdparty/Eigen/Eigen/LU @@ -5,8 +5,6 @@ #include "src/Core/util/DisableStupidWarnings.h" -namespace Eigen { - /** \defgroup LU_Module LU module * This module includes %LU decomposition and related notions such as matrix inversion and determinant. * This module defines the following MatrixBase methods: @@ -23,6 +21,9 @@ namespace Eigen { #include "src/misc/Image.h" #include "src/LU/FullPivLU.h" #include "src/LU/PartialPivLU.h" +#ifdef EIGEN_USE_LAPACKE +#include "src/LU/PartialPivLU_MKL.h" +#endif #include "src/LU/Determinant.h" #include "src/LU/Inverse.h" @@ -34,8 +35,6 @@ namespace Eigen { #include "src/Eigen2Support/LU.h" #endif -} // namespace Eigen - #include "src/Core/util/ReenableStupidWarnings.h" #endif // EIGEN_LU_MODULE_H diff --git a/gtsam/3rdparty/Eigen/Eigen/LeastSquares b/gtsam/3rdparty/Eigen/Eigen/LeastSquares index 93a6302dc..35137c25d 100644 --- a/gtsam/3rdparty/Eigen/Eigen/LeastSquares +++ b/gtsam/3rdparty/Eigen/Eigen/LeastSquares @@ -15,8 +15,6 @@ #include "Eigenvalues" #include "Geometry" -namespace Eigen { - /** \defgroup LeastSquares_Module LeastSquares module * This module provides linear regression and related features. * @@ -27,8 +25,6 @@ namespace Eigen { #include "src/Eigen2Support/LeastSquares.h" -} // namespace Eigen - #include "src/Core/util/ReenableStupidWarnings.h" #endif // EIGEN2_SUPPORT diff --git a/gtsam/3rdparty/Eigen/Eigen/OrderingMethods b/gtsam/3rdparty/Eigen/Eigen/OrderingMethods new file mode 100644 index 000000000..1e2d87452 --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/OrderingMethods @@ -0,0 +1,23 @@ +#ifndef EIGEN_ORDERINGMETHODS_MODULE_H +#define EIGEN_ORDERINGMETHODS_MODULE_H + +#include "SparseCore" + +#include "src/Core/util/DisableStupidWarnings.h" + +/** \ingroup Sparse_modules + * \defgroup OrderingMethods_Module OrderingMethods module + * + * This module is currently for internal use only. + * + * + * \code + * #include + * \endcode + */ + +#include "src/OrderingMethods/Amd.h" + +#include "src/Core/util/ReenableStupidWarnings.h" + +#endif // EIGEN_ORDERINGMETHODS_MODULE_H diff --git a/gtsam/3rdparty/Eigen/Eigen/PaStiXSupport b/gtsam/3rdparty/Eigen/Eigen/PaStiXSupport new file mode 100644 index 000000000..7c616ee5e --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/PaStiXSupport @@ -0,0 +1,46 @@ +#ifndef EIGEN_PASTIXSUPPORT_MODULE_H +#define EIGEN_PASTIXSUPPORT_MODULE_H + +#include "SparseCore" + +#include "src/Core/util/DisableStupidWarnings.h" + +#include +extern "C" { +#include +#include +} + +#ifdef complex +#undef complex +#endif + +/** \ingroup Support_modules + * \defgroup PaStiXSupport_Module PaStiXSupport module + * + * This module provides an interface to the PaSTiX library. + * PaSTiX is a general \b supernodal, \b parallel and \b opensource sparse solver. + * It provides the two following main factorization classes: + * - class PastixLLT : a supernodal, parallel LLt Cholesky factorization. + * - class PastixLDLT: a supernodal, parallel LDLt Cholesky factorization. + * - class PastixLU : a supernodal, parallel LU factorization (optimized for a symmetric pattern). + * + * \code + * #include + * \endcode + * + * In order to use this module, the PaSTiX headers must be accessible from the include paths, and your binary must be linked to the PaSTiX library and its dependencies. + * The dependencies depend on how PaSTiX has been compiled. + * For a cmake based project, you can use our FindPaSTiX.cmake module to help you in this task. + * + */ + +#include "src/misc/Solve.h" +#include "src/misc/SparseSolve.h" + +#include "src/PaStiXSupport/PaStiXSupport.h" + + +#include "src/Core/util/ReenableStupidWarnings.h" + +#endif // EIGEN_PASTIXSUPPORT_MODULE_H diff --git a/gtsam/3rdparty/Eigen/Eigen/PardisoSupport b/gtsam/3rdparty/Eigen/Eigen/PardisoSupport new file mode 100644 index 000000000..99330ce7a --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/PardisoSupport @@ -0,0 +1,30 @@ +#ifndef EIGEN_PARDISOSUPPORT_MODULE_H +#define EIGEN_PARDISOSUPPORT_MODULE_H + +#include "SparseCore" + +#include "src/Core/util/DisableStupidWarnings.h" + +#include + +#include + +/** \ingroup Support_modules + * \defgroup PardisoSupport_Module PardisoSupport module + * + * This module brings support for the Intel(R) MKL PARDISO direct sparse solvers. + * + * \code + * #include + * \endcode + * + * In order to use this module, the MKL headers must be accessible from the include paths, and your binary must be linked to the MKL library and its dependencies. + * See this \ref TopicUsingIntelMKL "page" for more information on MKL-Eigen integration. + * + */ + +#include "src/PardisoSupport/PardisoSupport.h" + +#include "src/Core/util/ReenableStupidWarnings.h" + +#endif // EIGEN_PARDISOSUPPORT_MODULE_H diff --git a/gtsam/3rdparty/Eigen/Eigen/QR b/gtsam/3rdparty/Eigen/Eigen/QR index 97c1788ee..ac5b02693 100644 --- a/gtsam/3rdparty/Eigen/Eigen/QR +++ b/gtsam/3rdparty/Eigen/Eigen/QR @@ -9,8 +9,6 @@ #include "Jacobi" #include "Householder" -namespace Eigen { - /** \defgroup QR_Module QR module * * @@ -28,13 +26,15 @@ namespace Eigen { #include "src/QR/HouseholderQR.h" #include "src/QR/FullPivHouseholderQR.h" #include "src/QR/ColPivHouseholderQR.h" +#ifdef EIGEN_USE_LAPACKE +#include "src/QR/HouseholderQR_MKL.h" +#include "src/QR/ColPivHouseholderQR_MKL.h" +#endif #ifdef EIGEN2_SUPPORT #include "src/Eigen2Support/QR.h" #endif -} // namespace Eigen - #include "src/Core/util/ReenableStupidWarnings.h" #ifdef EIGEN2_SUPPORT diff --git a/gtsam/3rdparty/Eigen/Eigen/SVD b/gtsam/3rdparty/Eigen/Eigen/SVD index 7c987a9dd..fd310017a 100644 --- a/gtsam/3rdparty/Eigen/Eigen/SVD +++ b/gtsam/3rdparty/Eigen/Eigen/SVD @@ -7,8 +7,6 @@ #include "src/Core/util/DisableStupidWarnings.h" -namespace Eigen { - /** \defgroup SVD_Module SVD module * * @@ -24,14 +22,15 @@ namespace Eigen { #include "src/misc/Solve.h" #include "src/SVD/JacobiSVD.h" +#if defined(EIGEN_USE_LAPACKE) && !defined(EIGEN_USE_LAPACKE_STRICT) +#include "src/SVD/JacobiSVD_MKL.h" +#endif #include "src/SVD/UpperBidiagonalization.h" #ifdef EIGEN2_SUPPORT #include "src/Eigen2Support/SVD.h" #endif -} // namespace Eigen - #include "src/Core/util/ReenableStupidWarnings.h" #endif // EIGEN_SVD_MODULE_H diff --git a/gtsam/3rdparty/Eigen/Eigen/Sparse b/gtsam/3rdparty/Eigen/Eigen/Sparse index 7425b3a41..2d1757172 100644 --- a/gtsam/3rdparty/Eigen/Eigen/Sparse +++ b/gtsam/3rdparty/Eigen/Eigen/Sparse @@ -1,69 +1,23 @@ #ifndef EIGEN_SPARSE_MODULE_H #define EIGEN_SPARSE_MODULE_H -#include "Core" - -#include "src/Core/util/DisableStupidWarnings.h" - -#include -#include -#include -#include -#include - -#ifdef EIGEN2_SUPPORT -#define EIGEN_YES_I_KNOW_SPARSE_MODULE_IS_NOT_STABLE_YET -#endif - -#ifndef EIGEN_YES_I_KNOW_SPARSE_MODULE_IS_NOT_STABLE_YET -#error The sparse module API is not stable yet. To use it anyway, please define the EIGEN_YES_I_KNOW_SPARSE_MODULE_IS_NOT_STABLE_YET preprocessor token. -#endif - -namespace Eigen { - -/** \defgroup Sparse_Module Sparse module +/** \defgroup Sparse_modules Sparse modules * - * - * - * See the \ref TutorialSparse "Sparse tutorial" + * Meta-module including all related modules: + * - SparseCore + * - OrderingMethods + * - SparseCholesky + * - IterativeLinearSolvers * * \code * #include * \endcode */ -/** The type used to identify a general sparse storage. */ -struct Sparse {}; - -#include "src/Sparse/SparseUtil.h" -#include "src/Sparse/SparseMatrixBase.h" -#include "src/Sparse/CompressedStorage.h" -#include "src/Sparse/AmbiVector.h" -#include "src/Sparse/SparseMatrix.h" -#include "src/Sparse/DynamicSparseMatrix.h" -#include "src/Sparse/MappedSparseMatrix.h" -#include "src/Sparse/SparseVector.h" -#include "src/Sparse/CoreIterators.h" -#include "src/Sparse/SparseBlock.h" -#include "src/Sparse/SparseTranspose.h" -#include "src/Sparse/SparseCwiseUnaryOp.h" -#include "src/Sparse/SparseCwiseBinaryOp.h" -#include "src/Sparse/SparseDot.h" -#include "src/Sparse/SparseAssign.h" -#include "src/Sparse/SparseRedux.h" -#include "src/Sparse/SparseFuzzy.h" -#include "src/Sparse/SparseProduct.h" -#include "src/Sparse/SparseSparseProduct.h" -#include "src/Sparse/SparseDenseProduct.h" -#include "src/Sparse/SparseDiagonalProduct.h" -#include "src/Sparse/SparseTriangularView.h" -#include "src/Sparse/SparseSelfAdjointView.h" -#include "src/Sparse/TriangularSolver.h" -#include "src/Sparse/SparseView.h" - -} // namespace Eigen - -#include "src/Core/util/ReenableStupidWarnings.h" +#include "SparseCore" +#include "OrderingMethods" +#include "SparseCholesky" +#include "IterativeLinearSolvers" #endif // EIGEN_SPARSE_MODULE_H diff --git a/gtsam/3rdparty/Eigen/Eigen/SparseCholesky b/gtsam/3rdparty/Eigen/Eigen/SparseCholesky new file mode 100644 index 000000000..5f82742f7 --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/SparseCholesky @@ -0,0 +1,30 @@ +#ifndef EIGEN_SPARSECHOLESKY_MODULE_H +#define EIGEN_SPARSECHOLESKY_MODULE_H + +#include "SparseCore" + +#include "src/Core/util/DisableStupidWarnings.h" + +/** \ingroup Sparse_modules + * \defgroup SparseCholesky_Module SparseCholesky module + * + * This module currently provides two variants of the direct sparse Cholesky decomposition for selfadjoint (hermitian) matrices. + * Those decompositions are accessible via the following classes: + * - SimplicialLLt, + * - SimplicialLDLt + * + * Such problems can also be solved using the ConjugateGradient solver from the IterativeLinearSolvers module. + * + * \code + * #include + * \endcode + */ + +#include "src/misc/Solve.h" +#include "src/misc/SparseSolve.h" + +#include "src/SparseCholesky/SimplicialCholesky.h" + +#include "src/Core/util/ReenableStupidWarnings.h" + +#endif // EIGEN_SPARSECHOLESKY_MODULE_H diff --git a/gtsam/3rdparty/Eigen/Eigen/SparseCore b/gtsam/3rdparty/Eigen/Eigen/SparseCore new file mode 100644 index 000000000..41d28c928 --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/SparseCore @@ -0,0 +1,66 @@ +#ifndef EIGEN_SPARSECORE_MODULE_H +#define EIGEN_SPARSECORE_MODULE_H + +#include "Core" + +#include "src/Core/util/DisableStupidWarnings.h" + +#include +#include +#include +#include +#include + +/** \ingroup Sparse_modules + * \defgroup SparseCore_Module SparseCore module + * + * This module provides a sparse matrix representation, and basic associatd matrix manipulations + * and operations. + * + * See the \ref TutorialSparse "Sparse tutorial" + * + * \code + * #include + * \endcode + * + * This module depends on: Core. + */ + +namespace Eigen { + +/** The type used to identify a general sparse storage. */ +struct Sparse {}; + +} + +#include "src/SparseCore/SparseUtil.h" +#include "src/SparseCore/SparseMatrixBase.h" +#include "src/SparseCore/CompressedStorage.h" +#include "src/SparseCore/AmbiVector.h" +#include "src/SparseCore/SparseMatrix.h" +#include "src/SparseCore/MappedSparseMatrix.h" +#include "src/SparseCore/SparseVector.h" +#include "src/SparseCore/CoreIterators.h" +#include "src/SparseCore/SparseBlock.h" +#include "src/SparseCore/SparseTranspose.h" +#include "src/SparseCore/SparseCwiseUnaryOp.h" +#include "src/SparseCore/SparseCwiseBinaryOp.h" +#include "src/SparseCore/SparseDot.h" +#include "src/SparseCore/SparsePermutation.h" +#include "src/SparseCore/SparseAssign.h" +#include "src/SparseCore/SparseRedux.h" +#include "src/SparseCore/SparseFuzzy.h" +#include "src/SparseCore/ConservativeSparseSparseProduct.h" +#include "src/SparseCore/SparseSparseProductWithPruning.h" +#include "src/SparseCore/SparseProduct.h" +#include "src/SparseCore/SparseDenseProduct.h" +#include "src/SparseCore/SparseDiagonalProduct.h" +#include "src/SparseCore/SparseTriangularView.h" +#include "src/SparseCore/SparseSelfAdjointView.h" +#include "src/SparseCore/TriangularSolver.h" +#include "src/SparseCore/SparseView.h" + +#include "src/Core/util/ReenableStupidWarnings.h" + +#endif // EIGEN_SPARSECORE_MODULE_H + diff --git a/gtsam/3rdparty/Eigen/Eigen/SuperLUSupport b/gtsam/3rdparty/Eigen/Eigen/SuperLUSupport new file mode 100644 index 000000000..575e14fbc --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/SuperLUSupport @@ -0,0 +1,59 @@ +#ifndef EIGEN_SUPERLUSUPPORT_MODULE_H +#define EIGEN_SUPERLUSUPPORT_MODULE_H + +#include "SparseCore" + +#include "src/Core/util/DisableStupidWarnings.h" + +#ifdef EMPTY +#define EIGEN_EMPTY_WAS_ALREADY_DEFINED +#endif + +typedef int int_t; +#include +#include +#include + +// slu_util.h defines a preprocessor token named EMPTY which is really polluting, +// so we remove it in favor of a SUPERLU_EMPTY token. +// If EMPTY was already defined then we don't undef it. + +#if defined(EIGEN_EMPTY_WAS_ALREADY_DEFINED) +# undef EIGEN_EMPTY_WAS_ALREADY_DEFINED +#elif defined(EMPTY) +# undef EMPTY +#endif + +#define SUPERLU_EMPTY (-1) + +namespace Eigen { struct SluMatrix; } + +/** \ingroup Support_modules + * \defgroup SuperLUSupport_Module SuperLUSupport module + * + * This module provides an interface to the SuperLU library. + * It provides the following factorization class: + * - class SuperLU: a supernodal sequential LU factorization. + * - class SuperILU: a supernodal sequential incomplete LU factorization (to be used as a preconditioner for iterative methods). + * + * \warning When including this module, you have to use SUPERLU_EMPTY instead of EMPTY which is no longer defined because it is too polluting. + * + * \code + * #include + * \endcode + * + * In order to use this module, the superlu headers must be accessible from the include paths, and your binary must be linked to the superlu library and its dependencies. + * The dependencies depend on how superlu has been compiled. + * For a cmake based project, you can use our FindSuperLU.cmake module to help you in this task. + * + */ + +#include "src/misc/Solve.h" +#include "src/misc/SparseSolve.h" + +#include "src/SuperLUSupport/SuperLUSupport.h" + + +#include "src/Core/util/ReenableStupidWarnings.h" + +#endif // EIGEN_SUPERLUSUPPORT_MODULE_H diff --git a/gtsam/3rdparty/Eigen/Eigen/UmfPackSupport b/gtsam/3rdparty/Eigen/Eigen/UmfPackSupport new file mode 100644 index 000000000..984f64a84 --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/UmfPackSupport @@ -0,0 +1,36 @@ +#ifndef EIGEN_UMFPACKSUPPORT_MODULE_H +#define EIGEN_UMFPACKSUPPORT_MODULE_H + +#include "SparseCore" + +#include "src/Core/util/DisableStupidWarnings.h" + +extern "C" { +#include +} + +/** \ingroup Support_modules + * \defgroup UmfPackSupport_Module UmfPackSupport module + * + * This module provides an interface to the UmfPack library which is part of the suitesparse package. + * It provides the following factorization class: + * - class UmfPackLU: a multifrontal sequential LU factorization. + * + * \code + * #include + * \endcode + * + * In order to use this module, the umfpack headers must be accessible from the include paths, and your binary must be linked to the umfpack library and its dependencies. + * The dependencies depend on how umfpack has been compiled. + * For a cmake based project, you can use our FindUmfPack.cmake module to help you in this task. + * + */ + +#include "src/misc/Solve.h" +#include "src/misc/SparseSolve.h" + +#include "src/UmfPackSupport/UmfPackSupport.h" + +#include "src/Core/util/ReenableStupidWarnings.h" + +#endif // EIGEN_UMFPACKSUPPORT_MODULE_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Cholesky/LDLT.h b/gtsam/3rdparty/Eigen/Eigen/src/Cholesky/LDLT.h index f47b2ea56..a5e3d5469 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Cholesky/LDLT.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Cholesky/LDLT.h @@ -1,9 +1,10 @@ // This file is part of Eigen, a lightweight C++ template library // for linear algebra. // -// Copyright (C) 2008-2010 Gael Guennebaud +// Copyright (C) 2008-2011 Gael Guennebaud // Copyright (C) 2009 Keir Mierle // Copyright (C) 2009 Benoit Jacob +// Copyright (C) 2011 Timothy E. Holy // // Eigen is free software; you can redistribute it and/or // modify it under the terms of the GNU Lesser General Public @@ -27,17 +28,21 @@ #ifndef EIGEN_LDLT_H #define EIGEN_LDLT_H +namespace Eigen { + namespace internal { template struct LDLT_Traits; } -/** \ingroup cholesky_Module +/** \ingroup Cholesky_Module * * \class LDLT * * \brief Robust Cholesky decomposition of a matrix with pivoting * * \param MatrixType the type of the matrix of which to compute the LDL^T Cholesky decomposition + * \param UpLo the triangular part that will be used for the decompositon: Lower (default) or Upper. + * The other triangular part won't be read. * * Perform a robust Cholesky decomposition of a positive semidefinite or negative semidefinite * matrix \f$ A \f$ such that \f$ A = P^TLDL^*P \f$, where P is a permutation matrix, L @@ -48,14 +53,10 @@ template struct LDLT_Traits; * on D also stabilizes the computation. * * Remember that Cholesky decompositions are not rank-revealing. Also, do not use a Cholesky - * decomposition to determine whether a system of equations has a solution. + * decomposition to determine whether a system of equations has a solution. * * \sa MatrixBase::ldlt(), class LLT */ - /* THIS PART OF THE DOX IS CURRENTLY DISABLED BECAUSE INACCURATE BECAUSE OF BUG IN THE DECOMPOSITION CODE - * Note that during the decomposition, only the upper triangular part of A is considered. Therefore, - * the strict lower part does not have to store correct values. - */ template class LDLT { public: @@ -98,6 +99,11 @@ template class LDLT m_isInitialized(false) {} + /** \brief Constructor with decomposition + * + * This calculates the decomposition for the input \a matrix. + * \sa LDLT(Index size) + */ LDLT(const MatrixType& matrix) : m_matrix(matrix.rows(), matrix.cols()), m_transpositions(matrix.rows()), @@ -107,6 +113,14 @@ template class LDLT compute(matrix); } + /** Clear any existing decomposition + * \sa rankUpdate(w,sigma) + */ + void setZero() + { + m_isInitialized = false; + } + /** \returns a view of the upper triangular matrix U */ inline typename Traits::MatrixU matrixU() const { @@ -130,14 +144,14 @@ template class LDLT } /** \returns the coefficients of the diagonal matrix D */ - inline Diagonal vectorD(void) const + inline Diagonal vectorD() const { eigen_assert(m_isInitialized && "LDLT is not initialized."); return m_matrix.diagonal(); } /** \returns true if the matrix is positive (semidefinite) */ - inline bool isPositive(void) const + inline bool isPositive() const { eigen_assert(m_isInitialized && "LDLT is not initialized."); return m_sign == 1; @@ -196,6 +210,9 @@ template class LDLT LDLT& compute(const MatrixType& matrix); + template + LDLT& rankUpdate(const MatrixBase& w,RealScalar alpha=1); + /** \returns the internal LDLT decomposition matrix * * TODO: document the storage layout @@ -211,6 +228,17 @@ template class LDLT inline Index rows() const { return m_matrix.rows(); } inline Index cols() const { return m_matrix.cols(); } + /** \brief Reports whether previous computation was successful. + * + * \returns \c Success if computation was succesful, + * \c NumericalIssue if the matrix.appears to be negative. + */ + ComputationInfo info() const + { + eigen_assert(m_isInitialized && "LDLT is not initialized."); + return Success; + } + protected: /** \internal @@ -249,7 +277,7 @@ template<> struct ldlt_inplace return true; } - RealScalar cutoff = 0, biggest_in_corner; + RealScalar cutoff(0), biggest_in_corner; for (Index k = 0; k < size; ++k) { @@ -317,6 +345,61 @@ template<> struct ldlt_inplace return true; } + + // Reference for the algorithm: Davis and Hager, "Multiple Rank + // Modifications of a Sparse Cholesky Factorization" (Algorithm 1) + // Trivial rearrangements of their computations (Timothy E. Holy) + // allow their algorithm to work for rank-1 updates even if the + // original matrix is not of full rank. + // Here only rank-1 updates are implemented, to reduce the + // requirement for intermediate storage and improve accuracy + template + static bool updateInPlace(MatrixType& mat, MatrixBase& w, typename MatrixType::RealScalar sigma=1) + { + using internal::isfinite; + typedef typename MatrixType::Scalar Scalar; + typedef typename MatrixType::RealScalar RealScalar; + typedef typename MatrixType::Index Index; + + const Index size = mat.rows(); + eigen_assert(mat.cols() == size && w.size()==size); + + RealScalar alpha = 1; + + // Apply the update + for (Index j = 0; j < size; j++) + { + // Check for termination due to an original decomposition of low-rank + if (!isfinite(alpha)) + break; + + // Update the diagonal terms + RealScalar dj = real(mat.coeff(j,j)); + Scalar wj = w.coeff(j); + RealScalar swj2 = sigma*abs2(wj); + RealScalar gamma = dj*alpha + swj2; + + mat.coeffRef(j,j) += swj2/alpha; + alpha += swj2/dj; + + + // Update the terms of L + Index rs = size-j-1; + w.tail(rs) -= wj * mat.col(j).tail(rs); + if(gamma != 0) + mat.col(j).tail(rs) += (sigma*conj(wj)/gamma)*w.tail(rs); + } + return true; + } + + template + static bool update(MatrixType& mat, const TranspositionType& transpositions, Workspace& tmp, const WType& w, typename MatrixType::RealScalar sigma=1) + { + // Apply the permutation to the input w + tmp = transpositions * w; + + return ldlt_inplace::updateInPlace(mat,tmp,sigma); + } }; template<> struct ldlt_inplace @@ -327,22 +410,29 @@ template<> struct ldlt_inplace Transpose matt(mat); return ldlt_inplace::unblocked(matt, transpositions, temp, sign); } + + template + static EIGEN_STRONG_INLINE bool update(MatrixType& mat, TranspositionType& transpositions, Workspace& tmp, WType& w, typename MatrixType::RealScalar sigma=1) + { + Transpose matt(mat); + return ldlt_inplace::update(matt, transpositions, tmp, w.conjugate(), sigma); + } }; template struct LDLT_Traits { - typedef TriangularView MatrixL; - typedef TriangularView MatrixU; - inline static MatrixL getL(const MatrixType& m) { return m; } - inline static MatrixU getU(const MatrixType& m) { return m.adjoint(); } + typedef const TriangularView MatrixL; + typedef const TriangularView MatrixU; + static inline MatrixL getL(const MatrixType& m) { return m; } + static inline MatrixU getU(const MatrixType& m) { return m.adjoint(); } }; template struct LDLT_Traits { - typedef TriangularView MatrixL; - typedef TriangularView MatrixU; - inline static MatrixL getL(const MatrixType& m) { return m.adjoint(); } - inline static MatrixU getU(const MatrixType& m) { return m; } + typedef const TriangularView MatrixL; + typedef const TriangularView MatrixU; + static inline MatrixL getL(const MatrixType& m) { return m.adjoint(); } + static inline MatrixU getU(const MatrixType& m) { return m; } }; } // end namespace internal @@ -367,6 +457,37 @@ LDLT& LDLT::compute(const MatrixType& a) return *this; } +/** Update the LDLT decomposition: given A = L D L^T, efficiently compute the decomposition of A + sigma w w^T. + * \param w a vector to be incorporated into the decomposition. + * \param sigma a scalar, +1 for updates and -1 for "downdates," which correspond to removing previously-added column vectors. Optional; default value is +1. + * \sa setZero() + */ +template +template +LDLT& LDLT::rankUpdate(const MatrixBase& w,typename NumTraits::Real sigma) +{ + const Index size = w.rows(); + if (m_isInitialized) + { + eigen_assert(m_matrix.rows()==size); + } + else + { + m_matrix.resize(size,size); + m_matrix.setZero(); + m_transpositions.resize(size); + for (Index i = 0; i < size; i++) + m_transpositions.coeffRef(i) = i; + m_temporary.resize(size); + m_sign = sigma>=0 ? 1 : -1; + m_isInitialized = true; + } + + internal::ldlt_inplace::update(m_matrix, m_transpositions, m_temporary, w, sigma); + + return *this; +} + namespace internal { template struct solve_retval, Rhs> @@ -481,4 +602,6 @@ MatrixBase::ldlt() const return LDLT(derived()); } +} // end namespace Eigen + #endif // EIGEN_LDLT_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Cholesky/LLT.h b/gtsam/3rdparty/Eigen/Eigen/src/Cholesky/LLT.h index a4ee5b11c..17c6d6b8d 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Cholesky/LLT.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Cholesky/LLT.h @@ -25,17 +25,21 @@ #ifndef EIGEN_LLT_H #define EIGEN_LLT_H +namespace Eigen { + namespace internal{ template struct LLT_Traits; } -/** \ingroup cholesky_Module +/** \ingroup Cholesky_Module * * \class LLT * * \brief Standard Cholesky decomposition (LL^T) of a matrix and associated features * * \param MatrixType the type of the matrix of which we are computing the LL^T Cholesky decomposition + * \param UpLo the triangular part that will be used for the decompositon: Lower (default) or Upper. + * The other triangular part won't be read. * * This class performs a LL^T Cholesky decomposition of a symmetric, positive definite * matrix A such that A = LL^* = U^*U, where L is lower triangular. @@ -49,6 +53,9 @@ template struct LLT_Traits; * use LDLT instead for the semidefinite case. Also, do not use a Cholesky decomposition to determine whether a system of equations * has a solution. * + * Example: \include LLT_example.cpp + * Output: \verbinclude LLT_example.out + * * \sa MatrixBase::llt(), class LDLT */ /* HEY THIS DOX IS DISABLED BECAUSE THERE's A BUG EITHER HERE OR IN LDLT ABOUT THAT (OR BOTH) @@ -178,6 +185,9 @@ template class LLT inline Index rows() const { return m_matrix.rows(); } inline Index cols() const { return m_matrix.cols(); } + template + LLT rankUpdate(const VectorType& vec, const RealScalar& sigma = 1); + protected: /** \internal * Used to compute and store L @@ -190,16 +200,85 @@ template class LLT namespace internal { -template struct llt_inplace; +template struct llt_inplace; -template<> struct llt_inplace +template +static typename MatrixType::Index llt_rank_update_lower(MatrixType& mat, const VectorType& vec, const typename MatrixType::RealScalar& sigma) { + typedef typename MatrixType::Scalar Scalar; + typedef typename MatrixType::RealScalar RealScalar; + typedef typename MatrixType::Index Index; + typedef typename MatrixType::ColXpr ColXpr; + typedef typename internal::remove_all::type ColXprCleaned; + typedef typename ColXprCleaned::SegmentReturnType ColXprSegment; + typedef Matrix TempVectorType; + typedef typename TempVectorType::SegmentReturnType TempVecSegment; + + int n = mat.cols(); + eigen_assert(mat.rows()==n && vec.size()==n); + + TempVectorType temp; + + if(sigma>0) + { + // This version is based on Givens rotations. + // It is faster than the other one below, but only works for updates, + // i.e., for sigma > 0 + temp = sqrt(sigma) * vec; + + for(int i=0; i g; + g.makeGivens(mat(i,i), -temp(i), &mat(i,i)); + + int rs = n-i-1; + if(rs>0) + { + ColXprSegment x(mat.col(i).tail(rs)); + TempVecSegment y(temp.tail(rs)); + apply_rotation_in_the_plane(x, y, g); + } + } + } + else + { + temp = vec; + RealScalar beta = 1; + for(int j=0; j struct llt_inplace +{ + typedef typename NumTraits::Real RealScalar; template static typename MatrixType::Index unblocked(MatrixType& mat) { typedef typename MatrixType::Index Index; - typedef typename MatrixType::Scalar Scalar; - typedef typename MatrixType::RealScalar RealScalar; eigen_assert(mat.rows()==mat.cols()); const Index size = mat.rows(); @@ -254,55 +333,71 @@ template<> struct llt_inplace } return -1; } -}; -template<> struct llt_inplace + template + static typename MatrixType::Index rankUpdate(MatrixType& mat, const VectorType& vec, const RealScalar& sigma) + { + return Eigen::internal::llt_rank_update_lower(mat, vec, sigma); + } +}; + +template struct llt_inplace { + typedef typename NumTraits::Real RealScalar; + template static EIGEN_STRONG_INLINE typename MatrixType::Index unblocked(MatrixType& mat) { Transpose matt(mat); - return llt_inplace::unblocked(matt); + return llt_inplace::unblocked(matt); } template static EIGEN_STRONG_INLINE typename MatrixType::Index blocked(MatrixType& mat) { Transpose matt(mat); - return llt_inplace::blocked(matt); + return llt_inplace::blocked(matt); + } + template + static typename MatrixType::Index rankUpdate(MatrixType& mat, const VectorType& vec, const RealScalar& sigma) + { + Transpose matt(mat); + return llt_inplace::rankUpdate(matt, vec.conjugate(), sigma); } }; template struct LLT_Traits { - typedef TriangularView MatrixL; - typedef TriangularView MatrixU; - inline static MatrixL getL(const MatrixType& m) { return m; } - inline static MatrixU getU(const MatrixType& m) { return m.adjoint(); } + typedef const TriangularView MatrixL; + typedef const TriangularView MatrixU; + static inline MatrixL getL(const MatrixType& m) { return m; } + static inline MatrixU getU(const MatrixType& m) { return m.adjoint(); } static bool inplace_decomposition(MatrixType& m) - { return llt_inplace::blocked(m)==-1; } + { return llt_inplace::blocked(m)==-1; } }; template struct LLT_Traits { - typedef TriangularView MatrixL; - typedef TriangularView MatrixU; - inline static MatrixL getL(const MatrixType& m) { return m.adjoint(); } - inline static MatrixU getU(const MatrixType& m) { return m; } + typedef const TriangularView MatrixL; + typedef const TriangularView MatrixU; + static inline MatrixL getL(const MatrixType& m) { return m.adjoint(); } + static inline MatrixU getU(const MatrixType& m) { return m; } static bool inplace_decomposition(MatrixType& m) - { return llt_inplace::blocked(m)==-1; } + { return llt_inplace::blocked(m)==-1; } }; } // end namespace internal /** Computes / recomputes the Cholesky decomposition A = LL^* = U^*U of \a matrix - * * * \returns a reference to *this + * + * Example: \include TutorialLinAlgComputeTwice.cpp + * Output: \verbinclude TutorialLinAlgComputeTwice.out */ template LLT& LLT::compute(const MatrixType& a) { - assert(a.rows()==a.cols()); + eigen_assert(a.rows()==a.cols()); const Index size = a.rows(); m_matrix.resize(size, size); m_matrix = a; @@ -314,6 +409,26 @@ LLT& LLT::compute(const MatrixType& a) return *this; } +/** Performs a rank one update (or dowdate) of the current decomposition. + * If A = LL^* before the rank one update, + * then after it we have LL^* = A + sigma * v v^* where \a v must be a vector + * of same dimension. + */ +template +template +LLT<_MatrixType,_UpLo> LLT<_MatrixType,_UpLo>::rankUpdate(const VectorType& v, const RealScalar& sigma) +{ + EIGEN_STATIC_ASSERT_VECTOR_ONLY(VectorType); + eigen_assert(v.size()==m_matrix.cols()); + eigen_assert(m_isInitialized); + if(internal::llt_inplace::rankUpdate(m_matrix,v,sigma)>=0) + m_info = NumericalIssue; + else + m_info = Success; + + return *this; +} + namespace internal { template struct solve_retval, Rhs> @@ -383,4 +498,6 @@ SelfAdjointView::llt() const return LLT(m_matrix); } +} // end namespace Eigen + #endif // EIGEN_LLT_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Cholesky/LLT_MKL.h b/gtsam/3rdparty/Eigen/Eigen/src/Cholesky/LLT_MKL.h new file mode 100644 index 000000000..64daa445c --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/src/Cholesky/LLT_MKL.h @@ -0,0 +1,102 @@ +/* + Copyright (c) 2011, Intel Corporation. All rights reserved. + + Redistribution and use in source and binary forms, with or without modification, + are permitted provided that the following conditions are met: + + * Redistributions of source code must retain the above copyright notice, this + list of conditions and the following disclaimer. + * Redistributions in binary form must reproduce the above copyright notice, + this list of conditions and the following disclaimer in the documentation + and/or other materials provided with the distribution. + * Neither the name of Intel Corporation nor the names of its contributors may + be used to endorse or promote products derived from this software without + specific prior written permission. + + THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND + ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED + WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE + DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR + ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES + (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; + LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON + ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS + SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + + ******************************************************************************** + * Content : Eigen bindings to Intel(R) MKL + * LLt decomposition based on LAPACKE_?potrf function. + ******************************************************************************** +*/ + +#ifndef EIGEN_LLT_MKL_H +#define EIGEN_LLT_MKL_H + +#include "Eigen/src/Core/util/MKL_support.h" +#include + +namespace Eigen { + +namespace internal { + +template struct mkl_llt; + +#define EIGEN_MKL_LLT(EIGTYPE, MKLTYPE, MKLPREFIX) \ +template<> struct mkl_llt \ +{ \ + template \ + static inline typename MatrixType::Index potrf(MatrixType& m, char uplo) \ + { \ + lapack_int matrix_order; \ + lapack_int size, lda, info, StorageOrder; \ + EIGTYPE* a; \ + eigen_assert(m.rows()==m.cols()); \ + /* Set up parameters for ?potrf */ \ + size = m.rows(); \ + StorageOrder = MatrixType::Flags&RowMajorBit?RowMajor:ColMajor; \ + matrix_order = StorageOrder==RowMajor ? LAPACK_ROW_MAJOR : LAPACK_COL_MAJOR; \ + a = &(m.coeffRef(0,0)); \ + lda = m.outerStride(); \ +\ + info = LAPACKE_##MKLPREFIX##potrf( matrix_order, uplo, size, (MKLTYPE*)a, lda ); \ + info = (info==0) ? Success : NumericalIssue; \ + return info; \ + } \ +}; \ +template<> struct llt_inplace \ +{ \ + template \ + static typename MatrixType::Index blocked(MatrixType& m) \ + { \ + return mkl_llt::potrf(m, 'L'); \ + } \ + template \ + static typename MatrixType::Index rankUpdate(MatrixType& mat, const VectorType& vec, const typename MatrixType::RealScalar& sigma) \ + { return Eigen::internal::llt_rank_update_lower(mat, vec, sigma); } \ +}; \ +template<> struct llt_inplace \ +{ \ + template \ + static typename MatrixType::Index blocked(MatrixType& m) \ + { \ + return mkl_llt::potrf(m, 'U'); \ + } \ + template \ + static typename MatrixType::Index rankUpdate(MatrixType& mat, const VectorType& vec, const typename MatrixType::RealScalar& sigma) \ + { \ + Transpose matt(mat); \ + return llt_inplace::rankUpdate(matt, vec.conjugate(), sigma); \ + } \ +}; + +EIGEN_MKL_LLT(double, double, d) +EIGEN_MKL_LLT(float, float, s) +EIGEN_MKL_LLT(dcomplex, MKL_Complex16, z) +EIGEN_MKL_LLT(scomplex, MKL_Complex8, c) + +} // end namespace internal + +} // end namespace Eigen + +#endif // EIGEN_LLT_MKL_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/CholmodSupport/CMakeLists.txt b/gtsam/3rdparty/Eigen/Eigen/src/CholmodSupport/CMakeLists.txt new file mode 100644 index 000000000..814dfa613 --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/src/CholmodSupport/CMakeLists.txt @@ -0,0 +1,6 @@ +FILE(GLOB Eigen_CholmodSupport_SRCS "*.h") + +INSTALL(FILES + ${Eigen_CholmodSupport_SRCS} + DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/CholmodSupport COMPONENT Devel + ) diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/SparseExtra/CholmodSupport.h b/gtsam/3rdparty/Eigen/Eigen/src/CholmodSupport/CholmodSupport.h similarity index 60% rename from gtsam/3rdparty/Eigen/unsupported/Eigen/src/SparseExtra/CholmodSupport.h rename to gtsam/3rdparty/Eigen/Eigen/src/CholmodSupport/CholmodSupport.h index 3e502c0aa..a06c429f0 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/SparseExtra/CholmodSupport.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/CholmodSupport/CholmodSupport.h @@ -25,6 +25,8 @@ #ifndef EIGEN_CHOLMODSUPPORT_H #define EIGEN_CHOLMODSUPPORT_H +namespace Eigen { + namespace internal { template @@ -69,11 +71,20 @@ cholmod_sparse viewAsCholmod(SparseMatrix<_Scalar,_Options,_Index>& mat) res.nzmax = mat.nonZeros(); res.nrow = mat.rows();; res.ncol = mat.cols(); - res.p = mat._outerIndexPtr(); - res.i = mat._innerIndexPtr(); - res.x = mat._valuePtr(); + res.p = mat.outerIndexPtr(); + res.i = mat.innerIndexPtr(); + res.x = mat.valuePtr(); res.sorted = 1; - res.packed = 1; + if(mat.isCompressed()) + { + res.packed = 1; + } + else + { + res.packed = 0; + res.nz = mat.innerNonZeroPtr(); + } + res.dtype = 0; res.stype = -1; @@ -149,19 +160,14 @@ enum CholmodMode { CholmodAuto, CholmodSimplicialLLt, CholmodSupernodalLLt, CholmodLDLt }; -/** \brief A Cholesky factorization and solver based on Cholmod - * - * This class allows to solve for A.X = B sparse linear problems via a LL^T or LDL^T Cholesky factorization - * using the Cholmod library. The sparse matrix A must be selfajoint and positive definite. The vectors or matrices - * X and B can be either dense or sparse. - * - * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<> - * \tparam _UpLo the triangular part that will be used for the computations. It can be Lower - * or Upper. Default is Lower. - * + +/** \ingroup CholmodSupport_Module + * \class CholmodBase + * \brief The base class for the direct Cholesky factorization of Cholmod + * \sa class CholmodSupernodalLLT, class CholmodSimplicialLDLT, class CholmodSimplicialLLT */ -template -class CholmodDecomposition +template +class CholmodBase : internal::noncopyable { public: typedef _MatrixType MatrixType; @@ -173,21 +179,20 @@ class CholmodDecomposition public: - CholmodDecomposition() + CholmodBase() : m_cholmodFactor(0), m_info(Success), m_isInitialized(false) { cholmod_start(&m_cholmod); - setMode(CholmodLDLt); } - CholmodDecomposition(const MatrixType& matrix) + CholmodBase(const MatrixType& matrix) : m_cholmodFactor(0), m_info(Success), m_isInitialized(false) { cholmod_start(&m_cholmod); compute(matrix); } - ~CholmodDecomposition() + ~CholmodBase() { if(m_cholmodFactor) cholmod_free_factor(&m_cholmodFactor, &m_cholmod); @@ -197,31 +202,8 @@ class CholmodDecomposition inline Index cols() const { return m_cholmodFactor->n; } inline Index rows() const { return m_cholmodFactor->n; } - void setMode(CholmodMode mode) - { - switch(mode) - { - case CholmodAuto: - m_cholmod.final_asis = 1; - m_cholmod.supernodal = CHOLMOD_AUTO; - break; - case CholmodSimplicialLLt: - m_cholmod.final_asis = 0; - m_cholmod.supernodal = CHOLMOD_SIMPLICIAL; - m_cholmod.final_ll = 1; - break; - case CholmodSupernodalLLt: - m_cholmod.final_asis = 1; - m_cholmod.supernodal = CHOLMOD_SUPERNODAL; - break; - case CholmodLDLt: - m_cholmod.final_asis = 1; - m_cholmod.supernodal = CHOLMOD_SIMPLICIAL; - break; - default: - break; - } - } + Derived& derived() { return *static_cast(this); } + const Derived& derived() const { return *static_cast(this); } /** \brief Reports whether previous computation was successful. * @@ -235,10 +217,11 @@ class CholmodDecomposition } /** Computes the sparse Cholesky decomposition of \a matrix */ - void compute(const MatrixType& matrix) + Derived& compute(const MatrixType& matrix) { analyzePattern(matrix); factorize(matrix); + return derived(); } /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A. @@ -246,13 +229,13 @@ class CholmodDecomposition * \sa compute() */ template - inline const internal::solve_retval + inline const internal::solve_retval solve(const MatrixBase& b) const { eigen_assert(m_isInitialized && "LLT is not initialized."); eigen_assert(rows()==b.rows() && "CholmodDecomposition::solve(): invalid number of rows of the right hand side matrix b"); - return internal::solve_retval(*this, b.derived()); + return internal::solve_retval(*this, b.derived()); } /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A. @@ -260,13 +243,13 @@ class CholmodDecomposition * \sa compute() */ template - inline const internal::sparse_solve_retval + inline const internal::sparse_solve_retval solve(const SparseMatrixBase& b) const { eigen_assert(m_isInitialized && "LLT is not initialized."); eigen_assert(rows()==b.rows() && "CholmodDecomposition::solve(): invalid number of rows of the right hand side matrix b"); - return internal::sparse_solve_retval(*this, b.derived()); + return internal::sparse_solve_retval(*this, b.derived()); } /** Performs a symbolic decomposition on the sparcity of \a matrix. @@ -356,7 +339,7 @@ class CholmodDecomposition template void dumpMemory(Stream& s) {} - + protected: mutable cholmod_common m_cholmod; cholmod_factor* m_cholmodFactor; @@ -366,13 +349,223 @@ class CholmodDecomposition int m_analysisIsOk; }; +/** \ingroup CholmodSupport_Module + * \class CholmodSimplicialLLT + * \brief A simplicial direct Cholesky (LLT) factorization and solver based on Cholmod + * + * This class allows to solve for A.X = B sparse linear problems via a simplicial LL^T Cholesky factorization + * using the Cholmod library. + * This simplicial variant is equivalent to Eigen's built-in SimplicialLLT class. Thefore, it has little practical interest. + * The sparse matrix A must be selfajoint and positive definite. The vectors or matrices + * X and B can be either dense or sparse. + * + * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<> + * \tparam _UpLo the triangular part that will be used for the computations. It can be Lower + * or Upper. Default is Lower. + * + * This class supports all kind of SparseMatrix<>: row or column major; upper, lower, or both; compressed or non compressed. + * + * \sa \ref TutorialSparseDirectSolvers, class CholmodSupernodalLLT, class SimplicialLLT + */ +template +class CholmodSimplicialLLT : public CholmodBase<_MatrixType, _UpLo, CholmodSimplicialLLT<_MatrixType, _UpLo> > +{ + typedef CholmodBase<_MatrixType, _UpLo, CholmodSimplicialLLT> Base; + using Base::m_cholmod; + + public: + + typedef _MatrixType MatrixType; + + CholmodSimplicialLLT() : Base() { init(); } + + CholmodSimplicialLLT(const MatrixType& matrix) : Base() + { + init(); + compute(matrix); + } + + ~CholmodSimplicialLLT() {} + protected: + void init() + { + m_cholmod.final_asis = 0; + m_cholmod.supernodal = CHOLMOD_SIMPLICIAL; + m_cholmod.final_ll = 1; + } +}; + + +/** \ingroup CholmodSupport_Module + * \class CholmodSimplicialLDLT + * \brief A simplicial direct Cholesky (LDLT) factorization and solver based on Cholmod + * + * This class allows to solve for A.X = B sparse linear problems via a simplicial LDL^T Cholesky factorization + * using the Cholmod library. + * This simplicial variant is equivalent to Eigen's built-in SimplicialLDLT class. Thefore, it has little practical interest. + * The sparse matrix A must be selfajoint and positive definite. The vectors or matrices + * X and B can be either dense or sparse. + * + * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<> + * \tparam _UpLo the triangular part that will be used for the computations. It can be Lower + * or Upper. Default is Lower. + * + * This class supports all kind of SparseMatrix<>: row or column major; upper, lower, or both; compressed or non compressed. + * + * \sa \ref TutorialSparseDirectSolvers, class CholmodSupernodalLLT, class SimplicialLDLT + */ +template +class CholmodSimplicialLDLT : public CholmodBase<_MatrixType, _UpLo, CholmodSimplicialLDLT<_MatrixType, _UpLo> > +{ + typedef CholmodBase<_MatrixType, _UpLo, CholmodSimplicialLDLT> Base; + using Base::m_cholmod; + + public: + + typedef _MatrixType MatrixType; + + CholmodSimplicialLDLT() : Base() { init(); } + + CholmodSimplicialLDLT(const MatrixType& matrix) : Base() + { + init(); + compute(matrix); + } + + ~CholmodSimplicialLDLT() {} + protected: + void init() + { + m_cholmod.final_asis = 1; + m_cholmod.supernodal = CHOLMOD_SIMPLICIAL; + } +}; + +/** \ingroup CholmodSupport_Module + * \class CholmodSupernodalLLT + * \brief A supernodal Cholesky (LLT) factorization and solver based on Cholmod + * + * This class allows to solve for A.X = B sparse linear problems via a supernodal LL^T Cholesky factorization + * using the Cholmod library. + * This supernodal variant performs best on dense enough problems, e.g., 3D FEM, or very high order 2D FEM. + * The sparse matrix A must be selfajoint and positive definite. The vectors or matrices + * X and B can be either dense or sparse. + * + * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<> + * \tparam _UpLo the triangular part that will be used for the computations. It can be Lower + * or Upper. Default is Lower. + * + * This class supports all kind of SparseMatrix<>: row or column major; upper, lower, or both; compressed or non compressed. + * + * \sa \ref TutorialSparseDirectSolvers + */ +template +class CholmodSupernodalLLT : public CholmodBase<_MatrixType, _UpLo, CholmodSupernodalLLT<_MatrixType, _UpLo> > +{ + typedef CholmodBase<_MatrixType, _UpLo, CholmodSupernodalLLT> Base; + using Base::m_cholmod; + + public: + + typedef _MatrixType MatrixType; + + CholmodSupernodalLLT() : Base() { init(); } + + CholmodSupernodalLLT(const MatrixType& matrix) : Base() + { + init(); + compute(matrix); + } + + ~CholmodSupernodalLLT() {} + protected: + void init() + { + m_cholmod.final_asis = 1; + m_cholmod.supernodal = CHOLMOD_SUPERNODAL; + } +}; + +/** \ingroup CholmodSupport_Module + * \class CholmodDecomposition + * \brief A general Cholesky factorization and solver based on Cholmod + * + * This class allows to solve for A.X = B sparse linear problems via a LL^T or LDL^T Cholesky factorization + * using the Cholmod library. The sparse matrix A must be selfajoint and positive definite. The vectors or matrices + * X and B can be either dense or sparse. + * + * This variant permits to change the underlying Cholesky method at runtime. + * On the other hand, it does not provide access to the result of the factorization. + * The default is to let Cholmod automatically choose between a simplicial and supernodal factorization. + * + * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<> + * \tparam _UpLo the triangular part that will be used for the computations. It can be Lower + * or Upper. Default is Lower. + * + * This class supports all kind of SparseMatrix<>: row or column major; upper, lower, or both; compressed or non compressed. + * + * \sa \ref TutorialSparseDirectSolvers + */ +template +class CholmodDecomposition : public CholmodBase<_MatrixType, _UpLo, CholmodDecomposition<_MatrixType, _UpLo> > +{ + typedef CholmodBase<_MatrixType, _UpLo, CholmodDecomposition> Base; + using Base::m_cholmod; + + public: + + typedef _MatrixType MatrixType; + + CholmodDecomposition() : Base() { init(); } + + CholmodDecomposition(const MatrixType& matrix) : Base() + { + init(); + compute(matrix); + } + + ~CholmodDecomposition() {} + + void setMode(CholmodMode mode) + { + switch(mode) + { + case CholmodAuto: + m_cholmod.final_asis = 1; + m_cholmod.supernodal = CHOLMOD_AUTO; + break; + case CholmodSimplicialLLt: + m_cholmod.final_asis = 0; + m_cholmod.supernodal = CHOLMOD_SIMPLICIAL; + m_cholmod.final_ll = 1; + break; + case CholmodSupernodalLLt: + m_cholmod.final_asis = 1; + m_cholmod.supernodal = CHOLMOD_SUPERNODAL; + break; + case CholmodLDLt: + m_cholmod.final_asis = 1; + m_cholmod.supernodal = CHOLMOD_SIMPLICIAL; + break; + default: + break; + } + } + protected: + void init() + { + m_cholmod.final_asis = 1; + m_cholmod.supernodal = CHOLMOD_AUTO; + } +}; + namespace internal { -template -struct solve_retval, Rhs> - : solve_retval_base, Rhs> +template +struct solve_retval, Rhs> + : solve_retval_base, Rhs> { - typedef CholmodDecomposition<_MatrixType,_UpLo> Dec; + typedef CholmodBase<_MatrixType,_UpLo,Derived> Dec; EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs) template void evalTo(Dest& dst) const @@ -381,11 +574,11 @@ struct solve_retval, Rhs> } }; -template -struct sparse_solve_retval, Rhs> - : sparse_solve_retval_base, Rhs> +template +struct sparse_solve_retval, Rhs> + : sparse_solve_retval_base, Rhs> { - typedef CholmodDecomposition<_MatrixType,_UpLo> Dec; + typedef CholmodBase<_MatrixType,_UpLo,Derived> Dec; EIGEN_MAKE_SPARSE_SOLVE_HELPERS(Dec,Rhs) template void evalTo(Dest& dst) const @@ -394,6 +587,8 @@ struct sparse_solve_retval, Rhs> } }; -} +} // end namespace internal + +} // end namespace Eigen #endif // EIGEN_CHOLMODSUPPORT_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/Array.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/Array.h index a11fb1b53..4762933d7 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/Array.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/Array.h @@ -25,6 +25,8 @@ #ifndef EIGEN_ARRAY_H #define EIGEN_ARRAY_H +namespace Eigen { + /** \class Array * \ingroup Core_Module * @@ -316,5 +318,6 @@ EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(d) \ EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(cf) \ EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(cd) +} // end namespace Eigen #endif // EIGEN_ARRAY_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/ArrayBase.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/ArrayBase.h index 9399ac3d1..ec3a4be43 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/ArrayBase.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/ArrayBase.h @@ -25,6 +25,8 @@ #ifndef EIGEN_ARRAYBASE_H #define EIGEN_ARRAYBASE_H +namespace Eigen { + template class MatrixWrapper; /** \class ArrayBase @@ -159,7 +161,7 @@ template class ArrayBase /** \returns an \link MatrixBase Matrix \endlink expression of this array * \sa MatrixBase::array() */ MatrixWrapper matrix() { return derived(); } - const MatrixWrapper matrix() const { return derived(); } + const MatrixWrapper matrix() const { return derived(); } // template // inline void evalTo(Dest& dst) const { dst = matrix(); } @@ -174,10 +176,10 @@ template class ArrayBase protected: // mixing arrays and matrices is not legal template Derived& operator+=(const MatrixBase& ) - {EIGEN_STATIC_ASSERT(sizeof(typename OtherDerived::Scalar)==-1,YOU_CANNOT_MIX_ARRAYS_AND_MATRICES);} + {EIGEN_STATIC_ASSERT(std::ptrdiff_t(sizeof(typename OtherDerived::Scalar))==-1,YOU_CANNOT_MIX_ARRAYS_AND_MATRICES); return *this;} // mixing arrays and matrices is not legal template Derived& operator-=(const MatrixBase& ) - {EIGEN_STATIC_ASSERT(sizeof(typename OtherDerived::Scalar)==-1,YOU_CANNOT_MIX_ARRAYS_AND_MATRICES);} + {EIGEN_STATIC_ASSERT(std::ptrdiff_t(sizeof(typename OtherDerived::Scalar))==-1,YOU_CANNOT_MIX_ARRAYS_AND_MATRICES); return *this;} }; /** replaces \c *this by \c *this - \a other. @@ -236,4 +238,6 @@ ArrayBase::operator/=(const ArrayBase& other) return derived(); } +} // end namespace Eigen + #endif // EIGEN_ARRAYBASE_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/ArrayWrapper.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/ArrayWrapper.h index 07f082e1e..f8a442cee 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/ArrayWrapper.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/ArrayWrapper.h @@ -25,6 +25,8 @@ #ifndef EIGEN_ARRAYWRAPPER_H #define EIGEN_ARRAYWRAPPER_H +namespace Eigen { + /** \class ArrayWrapper * \ingroup Core_Module * @@ -61,7 +63,7 @@ class ArrayWrapper : public ArrayBase > typedef typename internal::nested::type NestedExpressionType; - inline ArrayWrapper(const ExpressionType& matrix) : m_expression(matrix) {} + inline ArrayWrapper(ExpressionType& matrix) : m_expression(matrix) {} inline Index rows() const { return m_expression.rows(); } inline Index cols() const { return m_expression.cols(); } @@ -71,7 +73,7 @@ class ArrayWrapper : public ArrayBase > inline ScalarWithConstIfNotLvalue* data() { return m_expression.data(); } inline const Scalar* data() const { return m_expression.data(); } - inline const CoeffReturnType coeff(Index row, Index col) const + inline CoeffReturnType coeff(Index row, Index col) const { return m_expression.coeff(row, col); } @@ -86,7 +88,7 @@ class ArrayWrapper : public ArrayBase > return m_expression.const_cast_derived().coeffRef(row, col); } - inline const CoeffReturnType coeff(Index index) const + inline CoeffReturnType coeff(Index index) const { return m_expression.coeff(index); } @@ -128,8 +130,14 @@ class ArrayWrapper : public ArrayBase > template inline void evalTo(Dest& dst) const { dst = m_expression; } + const typename internal::remove_all::type& + nestedExpression() const + { + return m_expression; + } + protected: - const NestedExpressionType m_expression; + NestedExpressionType m_expression; }; /** \class MatrixWrapper @@ -168,7 +176,7 @@ class MatrixWrapper : public MatrixBase > typedef typename internal::nested::type NestedExpressionType; - inline MatrixWrapper(const ExpressionType& matrix) : m_expression(matrix) {} + inline MatrixWrapper(ExpressionType& matrix) : m_expression(matrix) {} inline Index rows() const { return m_expression.rows(); } inline Index cols() const { return m_expression.cols(); } @@ -178,7 +186,7 @@ class MatrixWrapper : public MatrixBase > inline ScalarWithConstIfNotLvalue* data() { return m_expression.data(); } inline const Scalar* data() const { return m_expression.data(); } - inline const CoeffReturnType coeff(Index row, Index col) const + inline CoeffReturnType coeff(Index row, Index col) const { return m_expression.coeff(row, col); } @@ -193,7 +201,7 @@ class MatrixWrapper : public MatrixBase > return m_expression.derived().coeffRef(row, col); } - inline const CoeffReturnType coeff(Index index) const + inline CoeffReturnType coeff(Index index) const { return m_expression.coeff(index); } @@ -232,8 +240,16 @@ class MatrixWrapper : public MatrixBase > m_expression.const_cast_derived().template writePacket(index, x); } + const typename internal::remove_all::type& + nestedExpression() const + { + return m_expression; + } + protected: - const NestedExpressionType m_expression; + NestedExpressionType m_expression; }; +} // end namespace Eigen + #endif // EIGEN_ARRAYWRAPPER_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/Assign.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/Assign.h index 3a17152f0..75390acf3 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/Assign.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/Assign.h @@ -27,6 +27,8 @@ #ifndef EIGEN_ASSIGN_H #define EIGEN_ASSIGN_H +namespace Eigen { + namespace internal { /*************************************************************************** @@ -152,7 +154,7 @@ struct assign_DefaultTraversal_CompleteUnrolling inner = Index % Derived1::InnerSizeAtCompileTime }; - EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src) + static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src) { dst.copyCoeffByOuterInner(outer, inner, src); assign_DefaultTraversal_CompleteUnrolling::run(dst, src); @@ -162,13 +164,13 @@ struct assign_DefaultTraversal_CompleteUnrolling template struct assign_DefaultTraversal_CompleteUnrolling { - EIGEN_STRONG_INLINE static void run(Derived1 &, const Derived2 &) {} + static EIGEN_STRONG_INLINE void run(Derived1 &, const Derived2 &) {} }; template struct assign_DefaultTraversal_InnerUnrolling { - EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src, int outer) + static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src, int outer) { dst.copyCoeffByOuterInner(outer, Index, src); assign_DefaultTraversal_InnerUnrolling::run(dst, src, outer); @@ -178,7 +180,7 @@ struct assign_DefaultTraversal_InnerUnrolling template struct assign_DefaultTraversal_InnerUnrolling { - EIGEN_STRONG_INLINE static void run(Derived1 &, const Derived2 &, int) {} + static EIGEN_STRONG_INLINE void run(Derived1 &, const Derived2 &, int) {} }; /*********************** @@ -188,7 +190,7 @@ struct assign_DefaultTraversal_InnerUnrolling template struct assign_LinearTraversal_CompleteUnrolling { - EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src) + static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src) { dst.copyCoeff(Index, src); assign_LinearTraversal_CompleteUnrolling::run(dst, src); @@ -198,7 +200,7 @@ struct assign_LinearTraversal_CompleteUnrolling template struct assign_LinearTraversal_CompleteUnrolling { - EIGEN_STRONG_INLINE static void run(Derived1 &, const Derived2 &) {} + static EIGEN_STRONG_INLINE void run(Derived1 &, const Derived2 &) {} }; /************************** @@ -214,7 +216,7 @@ struct assign_innervec_CompleteUnrolling JointAlignment = assign_traits::JointAlignment }; - EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src) + static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src) { dst.template copyPacketByOuterInner(outer, inner, src); assign_innervec_CompleteUnrolling struct assign_innervec_CompleteUnrolling { - EIGEN_STRONG_INLINE static void run(Derived1 &, const Derived2 &) {} + static EIGEN_STRONG_INLINE void run(Derived1 &, const Derived2 &) {} }; template struct assign_innervec_InnerUnrolling { - EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src, int outer) + static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src, int outer) { dst.template copyPacketByOuterInner(outer, Index, src); assign_innervec_InnerUnrolling struct assign_innervec_InnerUnrolling { - EIGEN_STRONG_INLINE static void run(Derived1 &, const Derived2 &, int) {} + static EIGEN_STRONG_INLINE void run(Derived1 &, const Derived2 &, int) {} }; /*************************************************************************** @@ -251,24 +253,25 @@ struct assign_innervec_InnerUnrolling template::Traversal, - int Unrolling = assign_traits::Unrolling> + int Unrolling = assign_traits::Unrolling, + int Version = Specialized> struct assign_impl; /************************ *** Default traversal *** ************************/ -template -struct assign_impl +template +struct assign_impl { - inline static void run(Derived1 &, const Derived2 &) { } + static inline void run(Derived1 &, const Derived2 &) { } }; -template -struct assign_impl +template +struct assign_impl { typedef typename Derived1::Index Index; - inline static void run(Derived1 &dst, const Derived2 &src) + static inline void run(Derived1 &dst, const Derived2 &src) { const Index innerSize = dst.innerSize(); const Index outerSize = dst.outerSize(); @@ -278,21 +281,21 @@ struct assign_impl } }; -template -struct assign_impl +template +struct assign_impl { - EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src) + static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src) { assign_DefaultTraversal_CompleteUnrolling ::run(dst, src); } }; -template -struct assign_impl +template +struct assign_impl { typedef typename Derived1::Index Index; - EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src) + static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src) { const Index outerSize = dst.outerSize(); for(Index outer = 0; outer < outerSize; ++outer) @@ -305,11 +308,11 @@ struct assign_impl *** Linear traversal *** ***********************/ -template -struct assign_impl +template +struct assign_impl { typedef typename Derived1::Index Index; - inline static void run(Derived1 &dst, const Derived2 &src) + static inline void run(Derived1 &dst, const Derived2 &src) { const Index size = dst.size(); for(Index i = 0; i < size; ++i) @@ -317,10 +320,10 @@ struct assign_impl } }; -template -struct assign_impl +template +struct assign_impl { - EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src) + static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src) { assign_LinearTraversal_CompleteUnrolling ::run(dst, src); @@ -331,11 +334,11 @@ struct assign_impl *** Inner vectorization *** **************************/ -template -struct assign_impl +template +struct assign_impl { typedef typename Derived1::Index Index; - inline static void run(Derived1 &dst, const Derived2 &src) + static inline void run(Derived1 &dst, const Derived2 &src) { const Index innerSize = dst.innerSize(); const Index outerSize = dst.outerSize(); @@ -346,21 +349,21 @@ struct assign_impl } }; -template -struct assign_impl +template +struct assign_impl { - EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src) + static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src) { assign_innervec_CompleteUnrolling ::run(dst, src); } }; -template -struct assign_impl +template +struct assign_impl { typedef typename Derived1::Index Index; - EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src) + static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src) { const Index outerSize = dst.outerSize(); for(Index outer = 0; outer < outerSize; ++outer) @@ -398,11 +401,11 @@ struct unaligned_assign_impl } }; -template -struct assign_impl +template +struct assign_impl { typedef typename Derived1::Index Index; - EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src) + static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src) { const Index size = dst.size(); typedef packet_traits PacketTraits; @@ -412,7 +415,7 @@ struct assign_impl srcAlignment = assign_traits::JointAlignment }; const Index alignedStart = assign_traits::DstIsAligned ? 0 - : first_aligned(&dst.coeffRef(0), size); + : internal::first_aligned(&dst.coeffRef(0), size); const Index alignedEnd = alignedStart + ((size-alignedStart)/packetSize)*packetSize; unaligned_assign_impl::DstIsAligned!=0>::run(src,dst,0,alignedStart); @@ -426,11 +429,11 @@ struct assign_impl } }; -template -struct assign_impl +template +struct assign_impl { typedef typename Derived1::Index Index; - EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src) + static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src) { enum { size = Derived1::SizeAtCompileTime, packetSize = packet_traits::size, @@ -445,11 +448,11 @@ struct assign_impl -struct assign_impl +template +struct assign_impl { typedef typename Derived1::Index Index; - inline static void run(Derived1 &dst, const Derived2 &src) + static inline void run(Derived1 &dst, const Derived2 &src) { typedef packet_traits PacketTraits; enum { @@ -463,7 +466,7 @@ struct assign_impl const Index outerSize = dst.outerSize(); const Index alignedStep = alignable ? (packetSize - dst.outerStride() % packetSize) & packetAlignedMask : 0; Index alignedStart = ((!alignable) || assign_traits::DstIsAligned) ? 0 - : first_aligned(&dst.coeffRef(0,0), innerSize); + : internal::first_aligned(&dst.coeffRef(0,0), innerSize); for(Index outer = 0; outer < outerSize; ++outer) { @@ -531,19 +534,19 @@ struct assign_selector; template struct assign_selector { - EIGEN_STRONG_INLINE static Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.derived()); } + static EIGEN_STRONG_INLINE Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.derived()); } }; template struct assign_selector { - EIGEN_STRONG_INLINE static Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.eval()); } + static EIGEN_STRONG_INLINE Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.eval()); } }; template struct assign_selector { - EIGEN_STRONG_INLINE static Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.transpose()); } + static EIGEN_STRONG_INLINE Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.transpose()); } }; template struct assign_selector { - EIGEN_STRONG_INLINE static Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.transpose().eval()); } + static EIGEN_STRONG_INLINE Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.transpose().eval()); } }; } // end namespace internal @@ -590,4 +593,6 @@ EIGEN_STRONG_INLINE Derived& MatrixBase::operator=(const ReturnByValue< return derived(); } +} // end namespace Eigen + #endif // EIGEN_ASSIGN_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/Assign_MKL.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/Assign_MKL.h new file mode 100644 index 000000000..428c6367b --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/Assign_MKL.h @@ -0,0 +1,224 @@ +/* + Copyright (c) 2011, Intel Corporation. All rights reserved. + + Redistribution and use in source and binary forms, with or without modification, + are permitted provided that the following conditions are met: + + * Redistributions of source code must retain the above copyright notice, this + list of conditions and the following disclaimer. + * Redistributions in binary form must reproduce the above copyright notice, + this list of conditions and the following disclaimer in the documentation + and/or other materials provided with the distribution. + * Neither the name of Intel Corporation nor the names of its contributors may + be used to endorse or promote products derived from this software without + specific prior written permission. + + THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND + ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED + WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE + DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR + ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES + (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; + LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON + ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS + SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + + ******************************************************************************** + * Content : Eigen bindings to Intel(R) MKL + * MKL VML support for coefficient-wise unary Eigen expressions like a=b.sin() + ******************************************************************************** +*/ + +#ifndef EIGEN_ASSIGN_VML_H +#define EIGEN_ASSIGN_VML_H + +namespace Eigen { + +namespace internal { + +template struct vml_call +{ enum { IsSupported = 0 }; }; + +template +class vml_assign_traits +{ + private: + enum { + DstHasDirectAccess = Dst::Flags & DirectAccessBit, + SrcHasDirectAccess = Src::Flags & DirectAccessBit, + + StorageOrdersAgree = (int(Dst::IsRowMajor) == int(Src::IsRowMajor)), + InnerSize = int(Dst::IsVectorAtCompileTime) ? int(Dst::SizeAtCompileTime) + : int(Dst::Flags)&RowMajorBit ? int(Dst::ColsAtCompileTime) + : int(Dst::RowsAtCompileTime), + InnerMaxSize = int(Dst::IsVectorAtCompileTime) ? int(Dst::MaxSizeAtCompileTime) + : int(Dst::Flags)&RowMajorBit ? int(Dst::MaxColsAtCompileTime) + : int(Dst::MaxRowsAtCompileTime), + MaxSizeAtCompileTime = Dst::SizeAtCompileTime, + + MightEnableVml = vml_call::IsSupported && StorageOrdersAgree && DstHasDirectAccess && SrcHasDirectAccess + && Src::InnerStrideAtCompileTime==1 && Dst::InnerStrideAtCompileTime==1, + MightLinearize = MightEnableVml && (int(Dst::Flags) & int(Src::Flags) & LinearAccessBit), + VmlSize = MightLinearize ? MaxSizeAtCompileTime : InnerMaxSize, + LargeEnough = VmlSize==Dynamic || VmlSize>=EIGEN_MKL_VML_THRESHOLD, + MayEnableVml = MightEnableVml && LargeEnough, + MayLinearize = MayEnableVml && MightLinearize + }; + public: + enum { + Traversal = MayLinearize ? LinearVectorizedTraversal + : MayEnableVml ? InnerVectorizedTraversal + : DefaultTraversal + }; +}; + +template::Traversal > +struct vml_assign_impl + : assign_impl,Traversal,Unrolling,BuiltIn> +{ +}; + +template +struct vml_assign_impl +{ + typedef typename Derived1::Scalar Scalar; + typedef typename Derived1::Index Index; + static inline void run(Derived1& dst, const CwiseUnaryOp& src) + { + // in case we want to (or have to) skip VML at runtime we can call: + // assign_impl,Traversal,Unrolling,BuiltIn>::run(dst,src); + const Index innerSize = dst.innerSize(); + const Index outerSize = dst.outerSize(); + for(Index outer = 0; outer < outerSize; ++outer) { + const Scalar *src_ptr = src.IsRowMajor ? &(src.nestedExpression().coeffRef(outer,0)) : + &(src.nestedExpression().coeffRef(0, outer)); + Scalar *dst_ptr = dst.IsRowMajor ? &(dst.coeffRef(outer,0)) : &(dst.coeffRef(0, outer)); + vml_call::run(src.functor(), innerSize, src_ptr, dst_ptr ); + } + } +}; + +template +struct vml_assign_impl +{ + static inline void run(Derived1& dst, const CwiseUnaryOp& src) + { + // in case we want to (or have to) skip VML at runtime we can call: + // assign_impl,Traversal,Unrolling,BuiltIn>::run(dst,src); + vml_call::run(src.functor(), dst.size(), src.nestedExpression().data(), dst.data() ); + } +}; + +// Macroses + +#define EIGEN_MKL_VML_SPECIALIZE_ASSIGN(TRAVERSAL,UNROLLING) \ + template \ + struct assign_impl, TRAVERSAL, UNROLLING, Specialized> { \ + static inline void run(Derived1 &dst, const Eigen::CwiseUnaryOp &src) { \ + vml_assign_impl::run(dst, src); \ + } \ + }; + +EIGEN_MKL_VML_SPECIALIZE_ASSIGN(DefaultTraversal,NoUnrolling) +EIGEN_MKL_VML_SPECIALIZE_ASSIGN(DefaultTraversal,CompleteUnrolling) +EIGEN_MKL_VML_SPECIALIZE_ASSIGN(DefaultTraversal,InnerUnrolling) +EIGEN_MKL_VML_SPECIALIZE_ASSIGN(LinearTraversal,NoUnrolling) +EIGEN_MKL_VML_SPECIALIZE_ASSIGN(LinearTraversal,CompleteUnrolling) +EIGEN_MKL_VML_SPECIALIZE_ASSIGN(InnerVectorizedTraversal,NoUnrolling) +EIGEN_MKL_VML_SPECIALIZE_ASSIGN(InnerVectorizedTraversal,CompleteUnrolling) +EIGEN_MKL_VML_SPECIALIZE_ASSIGN(InnerVectorizedTraversal,InnerUnrolling) +EIGEN_MKL_VML_SPECIALIZE_ASSIGN(LinearVectorizedTraversal,CompleteUnrolling) +EIGEN_MKL_VML_SPECIALIZE_ASSIGN(LinearVectorizedTraversal,NoUnrolling) +EIGEN_MKL_VML_SPECIALIZE_ASSIGN(SliceVectorizedTraversal,NoUnrolling) + + +#if !defined (EIGEN_FAST_MATH) || (EIGEN_FAST_MATH != 1) +#define EIGEN_MKL_VML_MODE VML_HA +#else +#define EIGEN_MKL_VML_MODE VML_LA +#endif + +#define EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, VMLOP, EIGENTYPE, VMLTYPE) \ + template<> struct vml_call< scalar_##EIGENOP##_op > { \ + enum { IsSupported = 1 }; \ + static inline void run( const scalar_##EIGENOP##_op& /*func*/, \ + int size, const EIGENTYPE* src, EIGENTYPE* dst) { \ + VMLOP(size, (const VMLTYPE*)src, (VMLTYPE*)dst); \ + } \ + }; + +#define EIGEN_MKL_VML_DECLARE_UNARY_CALL_LA(EIGENOP, VMLOP, EIGENTYPE, VMLTYPE) \ + template<> struct vml_call< scalar_##EIGENOP##_op > { \ + enum { IsSupported = 1 }; \ + static inline void run( const scalar_##EIGENOP##_op& /*func*/, \ + int size, const EIGENTYPE* src, EIGENTYPE* dst) { \ + MKL_INT64 vmlMode = EIGEN_MKL_VML_MODE; \ + VMLOP(size, (const VMLTYPE*)src, (VMLTYPE*)dst, vmlMode); \ + } \ + }; + +#define EIGEN_MKL_VML_DECLARE_POW_CALL(EIGENOP, VMLOP, EIGENTYPE, VMLTYPE) \ + template<> struct vml_call< scalar_##EIGENOP##_op > { \ + enum { IsSupported = 1 }; \ + static inline void run( const scalar_##EIGENOP##_op& func, \ + int size, const EIGENTYPE* src, EIGENTYPE* dst) { \ + EIGENTYPE exponent = func.m_exponent; \ + MKL_INT64 vmlMode = EIGEN_MKL_VML_MODE; \ + VMLOP(&size, (const VMLTYPE*)src, (const VMLTYPE*)&exponent, \ + (VMLTYPE*)dst, &vmlMode); \ + } \ + }; + +#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(EIGENOP, VMLOP) \ + EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, vs##VMLOP, float, float) \ + EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, vd##VMLOP, double, double) + +#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_COMPLEX(EIGENOP, VMLOP) \ + EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, vc##VMLOP, scomplex, MKL_Complex8) \ + EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, vz##VMLOP, dcomplex, MKL_Complex16) + +#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS(EIGENOP, VMLOP) \ + EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(EIGENOP, VMLOP) \ + EIGEN_MKL_VML_DECLARE_UNARY_CALLS_COMPLEX(EIGENOP, VMLOP) + + +#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL_LA(EIGENOP, VMLOP) \ + EIGEN_MKL_VML_DECLARE_UNARY_CALL_LA(EIGENOP, vms##VMLOP, float, float) \ + EIGEN_MKL_VML_DECLARE_UNARY_CALL_LA(EIGENOP, vmd##VMLOP, double, double) + +#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_COMPLEX_LA(EIGENOP, VMLOP) \ + EIGEN_MKL_VML_DECLARE_UNARY_CALL_LA(EIGENOP, vmc##VMLOP, scomplex, MKL_Complex8) \ + EIGEN_MKL_VML_DECLARE_UNARY_CALL_LA(EIGENOP, vmz##VMLOP, dcomplex, MKL_Complex16) + +#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(EIGENOP, VMLOP) \ + EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL_LA(EIGENOP, VMLOP) \ + EIGEN_MKL_VML_DECLARE_UNARY_CALLS_COMPLEX_LA(EIGENOP, VMLOP) + + +EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(sin, Sin) +EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(asin, Asin) +EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(cos, Cos) +EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(acos, Acos) +EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(tan, Tan) +//EIGEN_MKL_VML_DECLARE_UNARY_CALLS(abs, Abs) +EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(exp, Exp) +EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(log, Ln) +EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(sqrt, Sqrt) + +EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(square, Sqr) + +// The vm*powx functions are not avaibale in the windows version of MKL. +#ifdef _WIN32 +EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmspowx_, float, float) +EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmdpowx_, double, double) +EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmcpowx_, scomplex, MKL_Complex8) +EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmzpowx_, dcomplex, MKL_Complex16) +#endif + +} // end namespace internal + +} // end namespace Eigen + +#endif // EIGEN_ASSIGN_VML_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/BandMatrix.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/BandMatrix.h index 2570d7b55..8ef917de1 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/BandMatrix.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/BandMatrix.h @@ -25,8 +25,9 @@ #ifndef EIGEN_BANDMATRIX_H #define EIGEN_BANDMATRIX_H -namespace internal { +namespace Eigen { +namespace internal { template class BandMatrixBase : public EigenBase @@ -343,4 +344,6 @@ class TridiagonalMatrix : public BandMatrix::type& nestedExpression() const + { + return m_xpr; + } + + Index startRow() const + { + return m_startRow.value(); + } + + Index startCol() const + { + return m_startCol.value(); + } + protected: const typename XprType::Nested m_xpr; @@ -304,6 +321,11 @@ class Block init(); } + const typename internal::remove_all::type& nestedExpression() const + { + return m_xpr; + } + /** \sa MapBase::innerStride() */ inline Index innerStride() const { @@ -341,9 +363,10 @@ class Block : m_xpr.innerStride(); } - const typename XprType::Nested m_xpr; - int m_outerStride; + typename XprType::Nested m_xpr; + Index m_outerStride; }; +} // end namespace Eigen #endif // EIGEN_BLOCK_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/BooleanRedux.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/BooleanRedux.h index 5c3444a57..2c554a57d 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/BooleanRedux.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/BooleanRedux.h @@ -25,6 +25,8 @@ #ifndef EIGEN_ALLANDANY_H #define EIGEN_ALLANDANY_H +namespace Eigen { + namespace internal { template @@ -35,7 +37,7 @@ struct all_unroller row = (UnrollCount-1) % Derived::RowsAtCompileTime }; - inline static bool run(const Derived &mat) + static inline bool run(const Derived &mat) { return all_unroller::run(mat) && mat.coeff(row, col); } @@ -44,13 +46,13 @@ struct all_unroller template struct all_unroller { - inline static bool run(const Derived &mat) { return mat.coeff(0, 0); } + static inline bool run(const Derived &mat) { return mat.coeff(0, 0); } }; template struct all_unroller { - inline static bool run(const Derived &) { return false; } + static inline bool run(const Derived &) { return false; } }; template @@ -61,7 +63,7 @@ struct any_unroller row = (UnrollCount-1) % Derived::RowsAtCompileTime }; - inline static bool run(const Derived &mat) + static inline bool run(const Derived &mat) { return any_unroller::run(mat) || mat.coeff(row, col); } @@ -70,13 +72,13 @@ struct any_unroller template struct any_unroller { - inline static bool run(const Derived &mat) { return mat.coeff(0, 0); } + static inline bool run(const Derived &mat) { return mat.coeff(0, 0); } }; template struct any_unroller { - inline static bool run(const Derived &) { return false; } + static inline bool run(const Derived &) { return false; } }; } // end namespace internal @@ -146,4 +148,6 @@ inline typename DenseBase::Index DenseBase::count() const return derived().template cast().template cast().sum(); } +} // end namespace Eigen + #endif // EIGEN_ALLANDANY_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/CommaInitializer.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/CommaInitializer.h index 92422bf2f..f9ec1d587 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/CommaInitializer.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/CommaInitializer.h @@ -26,6 +26,8 @@ #ifndef EIGEN_COMMAINITIALIZER_H #define EIGEN_COMMAINITIALIZER_H +namespace Eigen { + /** \class CommaInitializer * \ingroup Core_Module * @@ -147,4 +149,6 @@ DenseBase::operator<<(const DenseBase& other) return CommaInitializer(*static_cast(this), other); } +} // end namespace Eigen + #endif // EIGEN_COMMAINITIALIZER_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/CwiseBinaryOp.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/CwiseBinaryOp.h index 7386b2e18..32599a7d9 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/CwiseBinaryOp.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/CwiseBinaryOp.h @@ -26,6 +26,8 @@ #ifndef EIGEN_CWISE_BINARY_OP_H #define EIGEN_CWISE_BINARY_OP_H +namespace Eigen { + /** \class CwiseBinaryOp * \ingroup Core_Module * @@ -167,8 +169,8 @@ class CwiseBinaryOp : internal::no_assignment_operator, const BinaryOp& functor() const { return m_functor; } protected: - const LhsNested m_lhs; - const RhsNested m_rhs; + LhsNested m_lhs; + RhsNested m_rhs; const BinaryOp m_functor; }; @@ -237,4 +239,6 @@ MatrixBase::operator+=(const MatrixBase& other) return derived(); } +} // end namespace Eigen + #endif // EIGEN_CWISE_BINARY_OP_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/CwiseNullaryOp.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/CwiseNullaryOp.h index c616e7ae1..a6d5e0934 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/CwiseNullaryOp.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/CwiseNullaryOp.h @@ -25,6 +25,8 @@ #ifndef EIGEN_CWISE_NULLARY_OP_H #define EIGEN_CWISE_NULLARY_OP_H +namespace Eigen { + /** \class CwiseNullaryOp * \ingroup Core_Module * @@ -101,6 +103,9 @@ class CwiseNullaryOp : internal::no_assignment_operator, return m_functor.packetOp(index); } + /** \returns the functor representing the nullary operation */ + const NullaryOp& functor() const { return m_functor; } + protected: const internal::variable_if_dynamic m_rows; const internal::variable_if_dynamic m_cols; @@ -238,6 +243,8 @@ DenseBase::Constant(const Scalar& value) * assumed to be a(0), a(1), ..., a(size). This assumption allows for better vectorization * and yields faster code than the random access version. * + * When size is set to 1, a vector of length 1 containing 'high' is returned. + * * \only_for_vectors * * Example: \include DenseBase_LinSpaced_seq.cpp @@ -270,6 +277,7 @@ DenseBase::LinSpaced(Sequential_t, const Scalar& low, const Scalar& hig * \brief Sets a linearly space vector. * * The function generates 'size' equally spaced values in the closed interval [low,high]. + * When size is set to 1, a vector of length 1 containing 'high' is returned. * * \only_for_vectors * @@ -381,6 +389,7 @@ PlainObjectBase::setConstant(Index rows, Index cols, const Scalar& valu * \brief Sets a linearly space vector. * * The function generates 'size' equally spaced values in the closed interval [low,high]. + * When size is set to 1, a vector of length 1 containing 'high' is returned. * * \only_for_vectors * @@ -396,6 +405,23 @@ EIGEN_STRONG_INLINE Derived& DenseBase::setLinSpaced(Index size, const return derived() = Derived::NullaryExpr(size, internal::linspaced_op(low,high,size)); } +/** + * \brief Sets a linearly space vector. + * + * The function fill *this with equally spaced values in the closed interval [low,high]. + * When size is set to 1, a vector of length 1 containing 'high' is returned. + * + * \only_for_vectors + * + * \sa setLinSpaced(Index, const Scalar&, const Scalar&), CwiseNullaryOp + */ +template +EIGEN_STRONG_INLINE Derived& DenseBase::setLinSpaced(const Scalar& low, const Scalar& high) +{ + EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived) + return setLinSpaced(size(), low, high); +} + // zero: /** \returns an expression of a zero matrix. @@ -848,4 +874,6 @@ template EIGEN_STRONG_INLINE const typename MatrixBase::BasisReturnType MatrixBase::UnitW() { return Derived::Unit(3); } +} // end namespace Eigen + #endif // EIGEN_CWISE_NULLARY_OP_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/CwiseUnaryOp.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/CwiseUnaryOp.h index 958571d64..9110c9800 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/CwiseUnaryOp.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/CwiseUnaryOp.h @@ -26,6 +26,8 @@ #ifndef EIGEN_CWISE_UNARY_OP_H #define EIGEN_CWISE_UNARY_OP_H +namespace Eigen { + /** \class CwiseUnaryOp * \ingroup Core_Module * @@ -95,7 +97,7 @@ class CwiseUnaryOp : internal::no_assignment_operator, nestedExpression() { return m_xpr.const_cast_derived(); } protected: - const typename XprType::Nested m_xpr; + typename XprType::Nested m_xpr; const UnaryOp m_functor; }; @@ -134,4 +136,6 @@ class CwiseUnaryOpImpl } }; +} // end namespace Eigen + #endif // EIGEN_CWISE_UNARY_OP_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/CwiseUnaryView.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/CwiseUnaryView.h index d24ef0373..bf16243d5 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/CwiseUnaryView.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/CwiseUnaryView.h @@ -25,6 +25,8 @@ #ifndef EIGEN_CWISE_UNARY_VIEW_H #define EIGEN_CWISE_UNARY_VIEW_H +namespace Eigen { + /** \class CwiseUnaryView * \ingroup Core_Module * @@ -97,7 +99,7 @@ class CwiseUnaryView : internal::no_assignment_operator, protected: // FIXME changed from MatrixType::Nested because of a weird compilation error with sun CC - const typename internal::nested::type m_matrix; + typename internal::nested::type m_matrix; ViewOp m_functor; }; @@ -143,6 +145,6 @@ class CwiseUnaryViewImpl } }; - +} // end namespace Eigen #endif // EIGEN_CWISE_UNARY_VIEW_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/DenseBase.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/DenseBase.h index 838fa4030..1882dcca4 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/DenseBase.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/DenseBase.h @@ -26,6 +26,8 @@ #ifndef EIGEN_DENSEBASE_H #define EIGEN_DENSEBASE_H +namespace Eigen { + /** \class DenseBase * \ingroup Core_Module * @@ -169,8 +171,8 @@ template class DenseBase IsRowMajor = int(Flags) & RowMajorBit, /**< True if this expression has row-major storage order. */ - InnerSizeAtCompileTime = int(IsVectorAtCompileTime) ? SizeAtCompileTime - : int(IsRowMajor) ? ColsAtCompileTime : RowsAtCompileTime, + InnerSizeAtCompileTime = int(IsVectorAtCompileTime) ? int(SizeAtCompileTime) + : int(IsRowMajor) ? int(ColsAtCompileTime) : int(RowsAtCompileTime), CoeffReadCost = internal::traits::CoeffReadCost, /**< This is a rough measure of how expensive it is to read one coefficient from @@ -376,12 +378,13 @@ template class DenseBase inline Derived& operator*=(const Scalar& other); inline Derived& operator/=(const Scalar& other); + typedef typename internal::add_const_on_value_type::type>::type EvalReturnType; /** \returns the matrix or vector obtained by evaluating this expression. * * Notice that in the case of a plain matrix or vector (not an expression) this function just returns * a const reference, in order to avoid a useless copy. */ - EIGEN_STRONG_INLINE const typename internal::eval::type eval() const + EIGEN_STRONG_INLINE EvalReturnType eval() const { // Even though MSVC does not honor strong inlining when the return type // is a dynamic matrix, we desperately need strong inlining for fixed @@ -540,4 +543,6 @@ template class DenseBase template explicit DenseBase(const DenseBase&); }; +} // end namespace Eigen + #endif // EIGEN_DENSEBASE_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/DenseCoeffsBase.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/DenseCoeffsBase.h index e45238fb5..e1aa1a5f8 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/DenseCoeffsBase.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/DenseCoeffsBase.h @@ -25,6 +25,8 @@ #ifndef EIGEN_DENSECOEFFSBASE_H #define EIGEN_DENSECOEFFSBASE_H +namespace Eigen { + namespace internal { template struct add_const_on_value_type_if_arithmetic { @@ -710,16 +712,16 @@ namespace internal { template struct first_aligned_impl { - inline static typename Derived::Index run(const Derived&) + static inline typename Derived::Index run(const Derived&) { return 0; } }; template struct first_aligned_impl { - inline static typename Derived::Index run(const Derived& m) + static inline typename Derived::Index run(const Derived& m) { - return first_aligned(&m.const_cast_derived().coeffRef(0,0), m.size()); + return internal::first_aligned(&m.const_cast_derived().coeffRef(0,0), m.size()); } }; @@ -729,7 +731,7 @@ struct first_aligned_impl * documentation. */ template -inline static typename Derived::Index first_aligned(const Derived& m) +static inline typename Derived::Index first_aligned(const Derived& m) { return first_aligned_impl @@ -762,4 +764,6 @@ struct outer_stride_at_compile_time } // end namespace internal +} // end namespace Eigen + #endif // EIGEN_DENSECOEFFSBASE_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/DenseStorage.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/DenseStorage.h index 813053b00..0ea05bc90 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/DenseStorage.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/DenseStorage.h @@ -33,6 +33,8 @@ #define EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN #endif +namespace Eigen { + namespace internal { struct constructor_without_unaligned_array_assert {}; @@ -104,8 +106,8 @@ template class DenseSt : m_data(internal::constructor_without_unaligned_array_assert()) {} inline DenseStorage(DenseIndex,DenseIndex,DenseIndex) {} inline void swap(DenseStorage& other) { std::swap(m_data,other.m_data); } - inline static DenseIndex rows(void) {return _Rows;} - inline static DenseIndex cols(void) {return _Cols;} + static inline DenseIndex rows(void) {return _Rows;} + static inline DenseIndex cols(void) {return _Cols;} inline void conservativeResize(DenseIndex,DenseIndex,DenseIndex) {} inline void resize(DenseIndex,DenseIndex,DenseIndex) {} inline const T *data() const { return m_data.array; } @@ -120,14 +122,24 @@ template class DenseStorage class DenseStorage +: public DenseStorage { }; + +template class DenseStorage +: public DenseStorage { }; + +template class DenseStorage +: public DenseStorage { }; + // dynamic-size matrix with fixed-size storage template class DenseStorage { @@ -241,7 +253,7 @@ template class DenseStorage(m_data, _Rows*m_cols); } inline void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_cols,other.m_cols); } - inline static DenseIndex rows(void) {return _Rows;} + static inline DenseIndex rows(void) {return _Rows;} inline DenseIndex cols(void) const {return m_cols;} inline void conservativeResize(DenseIndex size, DenseIndex, DenseIndex cols) { @@ -278,7 +290,7 @@ template class DenseStorage(m_data, _Cols*m_rows); } inline void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); } inline DenseIndex rows(void) const {return m_rows;} - inline static DenseIndex cols(void) {return _Cols;} + static inline DenseIndex cols(void) {return _Cols;} inline void conservativeResize(DenseIndex size, DenseIndex rows, DenseIndex) { m_data = internal::conditional_aligned_realloc_new_auto(m_data, size, m_rows*_Cols); @@ -301,4 +313,6 @@ template class DenseStorage +// Copyright (C) 2009-2010 Gael Guennebaud // // Eigen is free software; you can redistribute it and/or // modify it under the terms of the GNU Lesser General Public @@ -25,6 +26,8 @@ #ifndef EIGEN_DIAGONAL_H #define EIGEN_DIAGONAL_H +namespace Eigen { + /** \class Diagonal * \ingroup Core_Module * @@ -101,6 +104,15 @@ template class Diagonal return 0; } + typedef typename internal::conditional< + internal::is_lvalue::value, + Scalar, + const Scalar + >::type ScalarWithConstIfNotLvalue; + + inline ScalarWithConstIfNotLvalue* data() { return &(m_matrix.const_cast_derived().coeffRef(rowOffset(), colOffset())); } + inline const Scalar* data() const { return &(m_matrix.const_cast_derived().coeffRef(rowOffset(), colOffset())); } + inline Scalar& coeffRef(Index row, Index) { EIGEN_STATIC_ASSERT_LVALUE(MatrixType) @@ -133,8 +145,19 @@ template class Diagonal return m_matrix.coeff(index+rowOffset(), index+colOffset()); } + const typename internal::remove_all::type& + nestedExpression() const + { + return m_matrix; + } + + int index() const + { + return m_index.value(); + } + protected: - const typename MatrixType::Nested m_matrix; + typename MatrixType::Nested m_matrix; const internal::variable_if_dynamic m_index; private: @@ -224,4 +247,6 @@ MatrixBase::diagonal() const return derived(); } +} // end namespace Eigen + #endif // EIGEN_DIAGONAL_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/DiagonalMatrix.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/DiagonalMatrix.h index f41a74bfa..844f9864b 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/DiagonalMatrix.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/DiagonalMatrix.h @@ -26,6 +26,8 @@ #ifndef EIGEN_DIAGONALMATRIX_H #define EIGEN_DIAGONALMATRIX_H +namespace Eigen { + #ifndef EIGEN_PARSED_BY_DOXYGEN template class DiagonalBase : public EigenBase @@ -72,7 +74,7 @@ class DiagonalBase : public EigenBase const DiagonalProduct operator*(const MatrixBase &matrix) const; - inline const DiagonalWrapper, const DiagonalVectorType> > + inline const DiagonalWrapper, const DiagonalVectorType> > inverse() const { return diagonal().cwiseInverse(); @@ -251,13 +253,13 @@ class DiagonalWrapper #endif /** Constructor from expression of diagonal coefficients to wrap. */ - inline DiagonalWrapper(const DiagonalVectorType& diagonal) : m_diagonal(diagonal) {} + inline DiagonalWrapper(DiagonalVectorType& diagonal) : m_diagonal(diagonal) {} /** \returns a const reference to the wrapped expression of diagonal coefficients. */ const DiagonalVectorType& diagonal() const { return m_diagonal; } protected: - const typename DiagonalVectorType::Nested m_diagonal; + typename DiagonalVectorType::Nested m_diagonal; }; /** \returns a pseudo-expression of a diagonal matrix with *this as vector of diagonal coefficients @@ -303,4 +305,6 @@ bool MatrixBase::isDiagonal(RealScalar prec) const return true; } +} // end namespace Eigen + #endif // EIGEN_DIAGONALMATRIX_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/DiagonalProduct.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/DiagonalProduct.h index de0c6ed11..9f6a99895 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/DiagonalProduct.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/DiagonalProduct.h @@ -26,6 +26,8 @@ #ifndef EIGEN_DIAGONALPRODUCT_H #define EIGEN_DIAGONALPRODUCT_H +namespace Eigen { + namespace internal { template struct traits > @@ -107,8 +109,8 @@ class DiagonalProduct : internal::no_assignment_operator, m_diagonal.diagonal().template packet(id)); } - const typename MatrixType::Nested m_matrix; - const typename DiagonalType::Nested m_diagonal; + typename MatrixType::Nested m_matrix; + typename DiagonalType::Nested m_diagonal; }; /** \returns the diagonal matrix product of \c *this by the diagonal matrix \a diagonal. @@ -131,5 +133,6 @@ DiagonalBase::operator*(const MatrixBase &matrix return DiagonalProduct(matrix.derived(), derived()); } +} // end namespace Eigen #endif // EIGEN_DIAGONALPRODUCT_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/Dot.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/Dot.h index 42da78498..67dbbf8ba 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/Dot.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/Dot.h @@ -25,6 +25,8 @@ #ifndef EIGEN_DOT_H #define EIGEN_DOT_H +namespace Eigen { + namespace internal { // helper function for dot(). The problem is that if we put that in the body of dot(), then upon calling dot @@ -176,7 +178,7 @@ template struct lpNorm_selector { typedef typename NumTraits::Scalar>::Real RealScalar; - inline static RealScalar run(const MatrixBase& m) + static inline RealScalar run(const MatrixBase& m) { return pow(m.cwiseAbs().array().pow(p).sum(), RealScalar(1)/p); } @@ -185,7 +187,7 @@ struct lpNorm_selector template struct lpNorm_selector { - inline static typename NumTraits::Scalar>::Real run(const MatrixBase& m) + static inline typename NumTraits::Scalar>::Real run(const MatrixBase& m) { return m.cwiseAbs().sum(); } @@ -194,7 +196,7 @@ struct lpNorm_selector template struct lpNorm_selector { - inline static typename NumTraits::Scalar>::Real run(const MatrixBase& m) + static inline typename NumTraits::Scalar>::Real run(const MatrixBase& m) { return m.norm(); } @@ -203,7 +205,7 @@ struct lpNorm_selector template struct lpNorm_selector { - inline static typename NumTraits::Scalar>::Real run(const MatrixBase& m) + static inline typename NumTraits::Scalar>::Real run(const MatrixBase& m) { return m.cwiseAbs().maxCoeff(); } @@ -269,4 +271,6 @@ bool MatrixBase::isUnitary(RealScalar prec) const return true; } +} // end namespace Eigen + #endif // EIGEN_DOT_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/EigenBase.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/EigenBase.h index 0472539af..77d4c25d5 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/EigenBase.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/EigenBase.h @@ -26,6 +26,7 @@ #ifndef EIGEN_EIGENBASE_H #define EIGEN_EIGENBASE_H +namespace Eigen { /** Common base class for all classes T such that MatrixBase has an operator=(T) and a constructor MatrixBase(T). * @@ -169,4 +170,6 @@ inline void MatrixBase::applyOnTheLeft(const EigenBase &o other.derived().applyThisOnTheLeft(derived()); } +} // end namespace Eigen + #endif // EIGEN_EIGENBASE_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/Flagged.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/Flagged.h index 458213ab5..47f411b05 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/Flagged.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/Flagged.h @@ -25,6 +25,8 @@ #ifndef EIGEN_FLAGGED_H #define EIGEN_FLAGGED_H +namespace Eigen { + /** \class Flagged * \ingroup Core_Module * @@ -148,4 +150,6 @@ DenseBase::flagged() const return derived(); } +} // end namespace Eigen + #endif // EIGEN_FLAGGED_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/ForceAlignedAccess.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/ForceAlignedAccess.h index 11c1f8f70..238b7b770 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/ForceAlignedAccess.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/ForceAlignedAccess.h @@ -25,6 +25,8 @@ #ifndef EIGEN_FORCEALIGNEDACCESS_H #define EIGEN_FORCEALIGNEDACCESS_H +namespace Eigen { + /** \class ForceAlignedAccess * \ingroup Core_Module * @@ -154,4 +156,6 @@ MatrixBase::forceAlignedAccessIf() return derived(); } +} // end namespace Eigen + #endif // EIGEN_FORCEALIGNEDACCESS_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/Functors.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/Functors.h index 54636e0d4..f33f636bb 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/Functors.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/Functors.h @@ -25,6 +25,8 @@ #ifndef EIGEN_FUNCTORS_H #define EIGEN_FUNCTORS_H +namespace Eigen { + namespace internal { // associative functors: @@ -178,6 +180,18 @@ struct functor_traits > { enum { Cost = 5 * NumTraits::MulCost, PacketAccess=0 }; }; +/** \internal + * \brief Template functor to compute the pow of two scalars + */ +template struct scalar_binary_pow_op { + EIGEN_EMPTY_STRUCT_CTOR(scalar_binary_pow_op) + inline Scalar operator() (const Scalar& a, const OtherScalar& b) const { return internal::pow(a, b); } +}; +template +struct functor_traits > { + enum { Cost = 5 * NumTraits::MulCost, PacketAccess = false }; +}; + // other binary functors: /** \internal @@ -220,6 +234,38 @@ struct functor_traits > { }; }; +/** \internal + * \brief Template functor to compute the and of two booleans + * + * \sa class CwiseBinaryOp, ArrayBase::operator&& + */ +struct scalar_boolean_and_op { + EIGEN_EMPTY_STRUCT_CTOR(scalar_boolean_and_op) + EIGEN_STRONG_INLINE bool operator() (const bool& a, const bool& b) const { return a && b; } +}; +template<> struct functor_traits { + enum { + Cost = NumTraits::AddCost, + PacketAccess = false + }; +}; + +/** \internal + * \brief Template functor to compute the or of two booleans + * + * \sa class CwiseBinaryOp, ArrayBase::operator|| + */ +struct scalar_boolean_or_op { + EIGEN_EMPTY_STRUCT_CTOR(scalar_boolean_or_op) + EIGEN_STRONG_INLINE bool operator() (const bool& a, const bool& b) const { return a || b; } +}; +template<> struct functor_traits { + enum { + Cost = NumTraits::AddCost, + PacketAccess = false + }; +}; + // unary functors: /** \internal @@ -249,7 +295,7 @@ struct functor_traits > template struct scalar_abs_op { EIGEN_EMPTY_STRUCT_CTOR(scalar_abs_op) typedef typename NumTraits::Real result_type; - EIGEN_STRONG_INLINE const result_type operator() (const Scalar& a) const { return abs(a); } + EIGEN_STRONG_INLINE const result_type operator() (const Scalar& a) const { return internal::abs(a); } template EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const { return internal::pabs(a); } @@ -271,7 +317,7 @@ struct functor_traits > template struct scalar_abs2_op { EIGEN_EMPTY_STRUCT_CTOR(scalar_abs2_op) typedef typename NumTraits::Real result_type; - EIGEN_STRONG_INLINE const result_type operator() (const Scalar& a) const { return abs2(a); } + EIGEN_STRONG_INLINE const result_type operator() (const Scalar& a) const { return internal::abs2(a); } template EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const { return internal::pmul(a,a); } @@ -287,7 +333,7 @@ struct functor_traits > */ template struct scalar_conjugate_op { EIGEN_EMPTY_STRUCT_CTOR(scalar_conjugate_op) - EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a) const { return conj(a); } + EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a) const { return internal::conj(a); } template EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const { return internal::pconj(a); } }; @@ -324,7 +370,7 @@ template struct scalar_real_op { EIGEN_EMPTY_STRUCT_CTOR(scalar_real_op) typedef typename NumTraits::Real result_type; - EIGEN_STRONG_INLINE result_type operator() (const Scalar& a) const { return real(a); } + EIGEN_STRONG_INLINE result_type operator() (const Scalar& a) const { return internal::real(a); } }; template struct functor_traits > @@ -339,7 +385,7 @@ template struct scalar_imag_op { EIGEN_EMPTY_STRUCT_CTOR(scalar_imag_op) typedef typename NumTraits::Real result_type; - EIGEN_STRONG_INLINE result_type operator() (const Scalar& a) const { return imag(a); } + EIGEN_STRONG_INLINE result_type operator() (const Scalar& a) const { return internal::imag(a); } }; template struct functor_traits > @@ -354,7 +400,7 @@ template struct scalar_real_ref_op { EIGEN_EMPTY_STRUCT_CTOR(scalar_real_ref_op) typedef typename NumTraits::Real result_type; - EIGEN_STRONG_INLINE result_type& operator() (const Scalar& a) const { return real_ref(*const_cast(&a)); } + EIGEN_STRONG_INLINE result_type& operator() (const Scalar& a) const { return internal::real_ref(*const_cast(&a)); } }; template struct functor_traits > @@ -369,7 +415,7 @@ template struct scalar_imag_ref_op { EIGEN_EMPTY_STRUCT_CTOR(scalar_imag_ref_op) typedef typename NumTraits::Real result_type; - EIGEN_STRONG_INLINE result_type& operator() (const Scalar& a) const { return imag_ref(*const_cast(&a)); } + EIGEN_STRONG_INLINE result_type& operator() (const Scalar& a) const { return internal::imag_ref(*const_cast(&a)); } }; template struct functor_traits > @@ -383,7 +429,7 @@ struct functor_traits > */ template struct scalar_exp_op { EIGEN_EMPTY_STRUCT_CTOR(scalar_exp_op) - inline const Scalar operator() (const Scalar& a) const { return exp(a); } + inline const Scalar operator() (const Scalar& a) const { return internal::exp(a); } typedef typename packet_traits::type Packet; inline Packet packetOp(const Packet& a) const { return internal::pexp(a); } }; @@ -399,7 +445,7 @@ struct functor_traits > */ template struct scalar_log_op { EIGEN_EMPTY_STRUCT_CTOR(scalar_log_op) - inline const Scalar operator() (const Scalar& a) const { return log(a); } + inline const Scalar operator() (const Scalar& a) const { return internal::log(a); } typedef typename packet_traits::type Packet; inline Packet packetOp(const Packet& a) const { return internal::plog(a); } }; @@ -584,7 +630,7 @@ template struct functor_traits< linspaced_o template struct linspaced_op { typedef typename packet_traits::type Packet; - linspaced_op(Scalar low, Scalar high, int num_steps) : impl(low, (high-low)/(num_steps-1)) {} + linspaced_op(Scalar low, Scalar high, int num_steps) : impl((num_steps==1 ? high : low), (num_steps==1 ? Scalar() : (high-low)/(num_steps-1))) {} template EIGEN_STRONG_INLINE const Scalar operator() (Index i) const { return impl(i); } @@ -657,7 +703,7 @@ struct functor_traits > */ template struct scalar_sqrt_op { EIGEN_EMPTY_STRUCT_CTOR(scalar_sqrt_op) - inline const Scalar operator() (const Scalar& a) const { return sqrt(a); } + inline const Scalar operator() (const Scalar& a) const { return internal::sqrt(a); } typedef typename packet_traits::type Packet; inline Packet packetOp(const Packet& a) const { return internal::psqrt(a); } }; @@ -675,7 +721,7 @@ struct functor_traits > */ template struct scalar_cos_op { EIGEN_EMPTY_STRUCT_CTOR(scalar_cos_op) - inline Scalar operator() (const Scalar& a) const { return cos(a); } + inline Scalar operator() (const Scalar& a) const { return internal::cos(a); } typedef typename packet_traits::type Packet; inline Packet packetOp(const Packet& a) const { return internal::pcos(a); } }; @@ -694,7 +740,7 @@ struct functor_traits > */ template struct scalar_sin_op { EIGEN_EMPTY_STRUCT_CTOR(scalar_sin_op) - inline const Scalar operator() (const Scalar& a) const { return sin(a); } + inline const Scalar operator() (const Scalar& a) const { return internal::sin(a); } typedef typename packet_traits::type Packet; inline Packet packetOp(const Packet& a) const { return internal::psin(a); } }; @@ -714,7 +760,7 @@ struct functor_traits > */ template struct scalar_tan_op { EIGEN_EMPTY_STRUCT_CTOR(scalar_tan_op) - inline const Scalar operator() (const Scalar& a) const { return tan(a); } + inline const Scalar operator() (const Scalar& a) const { return internal::tan(a); } typedef typename packet_traits::type Packet; inline Packet packetOp(const Packet& a) const { return internal::ptan(a); } }; @@ -733,7 +779,7 @@ struct functor_traits > */ template struct scalar_acos_op { EIGEN_EMPTY_STRUCT_CTOR(scalar_acos_op) - inline const Scalar operator() (const Scalar& a) const { return acos(a); } + inline const Scalar operator() (const Scalar& a) const { return internal::acos(a); } typedef typename packet_traits::type Packet; inline Packet packetOp(const Packet& a) const { return internal::pacos(a); } }; @@ -752,7 +798,7 @@ struct functor_traits > */ template struct scalar_asin_op { EIGEN_EMPTY_STRUCT_CTOR(scalar_asin_op) - inline const Scalar operator() (const Scalar& a) const { return asin(a); } + inline const Scalar operator() (const Scalar& a) const { return internal::asin(a); } typedef typename packet_traits::type Packet; inline Packet packetOp(const Packet& a) const { return internal::pasin(a); } }; @@ -781,6 +827,20 @@ template struct functor_traits > { enum { Cost = 5 * NumTraits::MulCost, PacketAccess = false }; }; +/** \internal + * \brief Template functor to compute the quotient between a scalar and array entries. + * \sa class CwiseUnaryOp, Cwise::inverse() + */ +template +struct scalar_inverse_mult_op { + scalar_inverse_mult_op(const Scalar& other) : m_other(other) {} + inline Scalar operator() (const Scalar& a) const { return m_other / a; } + template + inline const Packet packetOp(const Packet& a) const + { return internal::pdiv(pset1(m_other),a); } + Scalar m_other; +}; + /** \internal * \brief Template functor to compute the inverse of a scalar * \sa class CwiseUnaryOp, Cwise::inverse() @@ -939,4 +999,6 @@ struct functor_traits > } // end namespace internal +} // end namespace Eigen + #endif // EIGEN_FUNCTORS_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/Fuzzy.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/Fuzzy.h index d266eed0a..887641163 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/Fuzzy.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/Fuzzy.h @@ -26,6 +26,8 @@ #ifndef EIGEN_FUZZY_H #define EIGEN_FUZZY_H +namespace Eigen { + namespace internal { @@ -35,8 +37,8 @@ struct isApprox_selector static bool run(const Derived& x, const OtherDerived& y, typename Derived::RealScalar prec) { using std::min; - const typename internal::nested::type nested(x); - const typename internal::nested::type otherNested(y); + typename internal::nested::type nested(x); + typename internal::nested::type otherNested(y); return (nested - otherNested).cwiseAbs2().sum() <= prec * prec * (min)(nested.cwiseAbs2().sum(), otherNested.cwiseAbs2().sum()); } }; @@ -158,4 +160,6 @@ bool DenseBase::isMuchSmallerThan( return internal::isMuchSmallerThan_object_selector::run(derived(), other.derived(), prec); } +} // end namespace Eigen + #endif // EIGEN_FUZZY_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/GeneralProduct.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/GeneralProduct.h new file mode 100644 index 000000000..4fbe1f14b --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/GeneralProduct.h @@ -0,0 +1,628 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2006-2008 Benoit Jacob +// Copyright (C) 2008-2011 Gael Guennebaud +// +// Eigen is free software; you can redistribute it and/or +// modify it under the terms of the GNU Lesser General Public +// License as published by the Free Software Foundation; either +// version 3 of the License, or (at your option) any later version. +// +// Alternatively, you can redistribute it and/or +// modify it under the terms of the GNU General Public License as +// published by the Free Software Foundation; either version 2 of +// the License, or (at your option) any later version. +// +// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY +// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the +// GNU General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public +// License and a copy of the GNU General Public License along with +// Eigen. If not, see . + +#ifndef EIGEN_GENERAL_PRODUCT_H +#define EIGEN_GENERAL_PRODUCT_H + +namespace Eigen { + +/** \class GeneralProduct + * \ingroup Core_Module + * + * \brief Expression of the product of two general matrices or vectors + * + * \param LhsNested the type used to store the left-hand side + * \param RhsNested the type used to store the right-hand side + * \param ProductMode the type of the product + * + * This class represents an expression of the product of two general matrices. + * We call a general matrix, a dense matrix with full storage. For instance, + * This excludes triangular, selfadjoint, and sparse matrices. + * It is the return type of the operator* between general matrices. Its template + * arguments are determined automatically by ProductReturnType. Therefore, + * GeneralProduct should never be used direclty. To determine the result type of a + * function which involves a matrix product, use ProductReturnType::Type. + * + * \sa ProductReturnType, MatrixBase::operator*(const MatrixBase&) + */ +template::value> +class GeneralProduct; + +enum { + Large = 2, + Small = 3 +}; + +namespace internal { + +template struct product_type_selector; + +template struct product_size_category +{ + enum { is_large = MaxSize == Dynamic || + Size >= EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD, + value = is_large ? Large + : Size == 1 ? 1 + : Small + }; +}; + +template struct product_type +{ + typedef typename remove_all::type _Lhs; + typedef typename remove_all::type _Rhs; + enum { + MaxRows = _Lhs::MaxRowsAtCompileTime, + Rows = _Lhs::RowsAtCompileTime, + MaxCols = _Rhs::MaxColsAtCompileTime, + Cols = _Rhs::ColsAtCompileTime, + MaxDepth = EIGEN_SIZE_MIN_PREFER_FIXED(_Lhs::MaxColsAtCompileTime, + _Rhs::MaxRowsAtCompileTime), + Depth = EIGEN_SIZE_MIN_PREFER_FIXED(_Lhs::ColsAtCompileTime, + _Rhs::RowsAtCompileTime), + LargeThreshold = EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD + }; + + // the splitting into different lines of code here, introducing the _select enums and the typedef below, + // is to work around an internal compiler error with gcc 4.1 and 4.2. +private: + enum { + rows_select = product_size_category::value, + cols_select = product_size_category::value, + depth_select = product_size_category::value + }; + typedef product_type_selector selector; + +public: + enum { + value = selector::ret + }; +#ifdef EIGEN_DEBUG_PRODUCT + static void debug() + { + EIGEN_DEBUG_VAR(Rows); + EIGEN_DEBUG_VAR(Cols); + EIGEN_DEBUG_VAR(Depth); + EIGEN_DEBUG_VAR(rows_select); + EIGEN_DEBUG_VAR(cols_select); + EIGEN_DEBUG_VAR(depth_select); + EIGEN_DEBUG_VAR(value); + } +#endif +}; + + +/* The following allows to select the kind of product at compile time + * based on the three dimensions of the product. + * This is a compile time mapping from {1,Small,Large}^3 -> {product types} */ +// FIXME I'm not sure the current mapping is the ideal one. +template struct product_type_selector { enum { ret = OuterProduct }; }; +template struct product_type_selector<1, 1, Depth> { enum { ret = InnerProduct }; }; +template<> struct product_type_selector<1, 1, 1> { enum { ret = InnerProduct }; }; +template<> struct product_type_selector { enum { ret = CoeffBasedProductMode }; }; +template<> struct product_type_selector<1, Small,Small> { enum { ret = CoeffBasedProductMode }; }; +template<> struct product_type_selector { enum { ret = CoeffBasedProductMode }; }; +template<> struct product_type_selector { enum { ret = LazyCoeffBasedProductMode }; }; +template<> struct product_type_selector { enum { ret = LazyCoeffBasedProductMode }; }; +template<> struct product_type_selector { enum { ret = LazyCoeffBasedProductMode }; }; +template<> struct product_type_selector<1, Large,Small> { enum { ret = CoeffBasedProductMode }; }; +template<> struct product_type_selector<1, Large,Large> { enum { ret = GemvProduct }; }; +template<> struct product_type_selector<1, Small,Large> { enum { ret = CoeffBasedProductMode }; }; +template<> struct product_type_selector { enum { ret = CoeffBasedProductMode }; }; +template<> struct product_type_selector { enum { ret = GemvProduct }; }; +template<> struct product_type_selector { enum { ret = CoeffBasedProductMode }; }; +template<> struct product_type_selector { enum { ret = GemmProduct }; }; +template<> struct product_type_selector { enum { ret = GemmProduct }; }; +template<> struct product_type_selector { enum { ret = GemmProduct }; }; +template<> struct product_type_selector { enum { ret = GemmProduct }; }; +template<> struct product_type_selector { enum { ret = GemmProduct }; }; +template<> struct product_type_selector { enum { ret = GemmProduct }; }; +template<> struct product_type_selector { enum { ret = GemmProduct }; }; + +} // end namespace internal + +/** \class ProductReturnType + * \ingroup Core_Module + * + * \brief Helper class to get the correct and optimized returned type of operator* + * + * \param Lhs the type of the left-hand side + * \param Rhs the type of the right-hand side + * \param ProductMode the type of the product (determined automatically by internal::product_mode) + * + * This class defines the typename Type representing the optimized product expression + * between two matrix expressions. In practice, using ProductReturnType::Type + * is the recommended way to define the result type of a function returning an expression + * which involve a matrix product. The class Product should never be + * used directly. + * + * \sa class Product, MatrixBase::operator*(const MatrixBase&) + */ +template +struct ProductReturnType +{ + // TODO use the nested type to reduce instanciations ???? +// typedef typename internal::nested::type LhsNested; +// typedef typename internal::nested::type RhsNested; + + typedef GeneralProduct Type; +}; + +template +struct ProductReturnType +{ + typedef typename internal::nested::type >::type LhsNested; + typedef typename internal::nested::type >::type RhsNested; + typedef CoeffBasedProduct Type; +}; + +template +struct ProductReturnType +{ + typedef typename internal::nested::type >::type LhsNested; + typedef typename internal::nested::type >::type RhsNested; + typedef CoeffBasedProduct Type; +}; + +// this is a workaround for sun CC +template +struct LazyProductReturnType : public ProductReturnType +{}; + +/*********************************************************************** +* Implementation of Inner Vector Vector Product +***********************************************************************/ + +// FIXME : maybe the "inner product" could return a Scalar +// instead of a 1x1 matrix ?? +// Pro: more natural for the user +// Cons: this could be a problem if in a meta unrolled algorithm a matrix-matrix +// product ends up to a row-vector times col-vector product... To tackle this use +// case, we could have a specialization for Block with: operator=(Scalar x); + +namespace internal { + +template +struct traits > + : traits::ReturnType,1,1> > +{}; + +} + +template +class GeneralProduct + : internal::no_assignment_operator, + public Matrix::ReturnType,1,1> +{ + typedef Matrix::ReturnType,1,1> Base; + public: + GeneralProduct(const Lhs& lhs, const Rhs& rhs) + { + EIGEN_STATIC_ASSERT((internal::is_same::value), + YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY) + + Base::coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); + } + + /** Convertion to scalar */ + operator const typename Base::Scalar() const { + return Base::coeff(0,0); + } +}; + +/*********************************************************************** +* Implementation of Outer Vector Vector Product +***********************************************************************/ + +namespace internal { +template struct outer_product_selector; + +template +struct traits > + : traits, Lhs, Rhs> > +{}; + +} + +template +class GeneralProduct + : public ProductBase, Lhs, Rhs> +{ + public: + EIGEN_PRODUCT_PUBLIC_INTERFACE(GeneralProduct) + + GeneralProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs) + { + EIGEN_STATIC_ASSERT((internal::is_same::value), + YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY) + } + + template void scaleAndAddTo(Dest& dest, Scalar alpha) const + { + internal::outer_product_selector<(int(Dest::Flags)&RowMajorBit) ? RowMajor : ColMajor>::run(*this, dest, alpha); + } +}; + +namespace internal { + +template<> struct outer_product_selector { + template + static EIGEN_DONT_INLINE void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha) { + typedef typename Dest::Index Index; + // FIXME make sure lhs is sequentially stored + // FIXME not very good if rhs is real and lhs complex while alpha is real too + const Index cols = dest.cols(); + for (Index j=0; j struct outer_product_selector { + template + static EIGEN_DONT_INLINE void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha) { + typedef typename Dest::Index Index; + // FIXME make sure rhs is sequentially stored + // FIXME not very good if lhs is real and rhs complex while alpha is real too + const Index rows = dest.rows(); + for (Index i=0; i call fast BLAS-like colmajor routine + * 2 - the matrix is row-major, BLAS compatible and N is large => call fast BLAS-like rowmajor routine + * 3 - all other cases are handled using a simple loop along the outer-storage direction. + * Therefore we need a lower level meta selector. + * Furthermore, if the matrix is the rhs, then the product has to be transposed. + */ +namespace internal { + +template +struct traits > + : traits, Lhs, Rhs> > +{}; + +template +struct gemv_selector; + +} // end namespace internal + +template +class GeneralProduct + : public ProductBase, Lhs, Rhs> +{ + public: + EIGEN_PRODUCT_PUBLIC_INTERFACE(GeneralProduct) + + typedef typename Lhs::Scalar LhsScalar; + typedef typename Rhs::Scalar RhsScalar; + + GeneralProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs) + { +// EIGEN_STATIC_ASSERT((internal::is_same::value), +// YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY) + } + + enum { Side = Lhs::IsVectorAtCompileTime ? OnTheLeft : OnTheRight }; + typedef typename internal::conditional::type MatrixType; + + template void scaleAndAddTo(Dest& dst, Scalar alpha) const + { + eigen_assert(m_lhs.rows() == dst.rows() && m_rhs.cols() == dst.cols()); + internal::gemv_selector::HasUsableDirectAccess)>::run(*this, dst, alpha); + } +}; + +namespace internal { + +// The vector is on the left => transposition +template +struct gemv_selector +{ + template + static void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha) + { + Transpose destT(dest); + enum { OtherStorageOrder = StorageOrder == RowMajor ? ColMajor : RowMajor }; + gemv_selector + ::run(GeneralProduct,Transpose, GemvProduct> + (prod.rhs().transpose(), prod.lhs().transpose()), destT, alpha); + } +}; + +template struct gemv_static_vector_if; + +template +struct gemv_static_vector_if +{ + EIGEN_STRONG_INLINE Scalar* data() { eigen_internal_assert(false && "should never be called"); return 0; } +}; + +template +struct gemv_static_vector_if +{ + EIGEN_STRONG_INLINE Scalar* data() { return 0; } +}; + +template +struct gemv_static_vector_if +{ + #if EIGEN_ALIGN_STATICALLY + internal::plain_array m_data; + EIGEN_STRONG_INLINE Scalar* data() { return m_data.array; } + #else + // Some architectures cannot align on the stack, + // => let's manually enforce alignment by allocating more data and return the address of the first aligned element. + enum { + ForceAlignment = internal::packet_traits::Vectorizable, + PacketSize = internal::packet_traits::size + }; + internal::plain_array m_data; + EIGEN_STRONG_INLINE Scalar* data() { + return ForceAlignment + ? reinterpret_cast((reinterpret_cast(m_data.array) & ~(size_t(15))) + 16) + : m_data.array; + } + #endif +}; + +template<> struct gemv_selector +{ + template + static inline void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha) + { + typedef typename ProductType::Index Index; + typedef typename ProductType::LhsScalar LhsScalar; + typedef typename ProductType::RhsScalar RhsScalar; + typedef typename ProductType::Scalar ResScalar; + typedef typename ProductType::RealScalar RealScalar; + typedef typename ProductType::ActualLhsType ActualLhsType; + typedef typename ProductType::ActualRhsType ActualRhsType; + typedef typename ProductType::LhsBlasTraits LhsBlasTraits; + typedef typename ProductType::RhsBlasTraits RhsBlasTraits; + typedef Map, Aligned> MappedDest; + + ActualLhsType actualLhs = LhsBlasTraits::extract(prod.lhs()); + ActualRhsType actualRhs = RhsBlasTraits::extract(prod.rhs()); + + ResScalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(prod.lhs()) + * RhsBlasTraits::extractScalarFactor(prod.rhs()); + + enum { + // FIXME find a way to allow an inner stride on the result if packet_traits::size==1 + // on, the other hand it is good for the cache to pack the vector anyways... + EvalToDestAtCompileTime = Dest::InnerStrideAtCompileTime==1, + ComplexByReal = (NumTraits::IsComplex) && (!NumTraits::IsComplex), + MightCannotUseDest = (Dest::InnerStrideAtCompileTime!=1) || ComplexByReal + }; + + gemv_static_vector_if static_dest; + + bool alphaIsCompatible = (!ComplexByReal) || (imag(actualAlpha)==RealScalar(0)); + bool evalToDest = EvalToDestAtCompileTime && alphaIsCompatible; + + RhsScalar compatibleAlpha = get_factor::run(actualAlpha); + + ei_declare_aligned_stack_constructed_variable(ResScalar,actualDestPtr,dest.size(), + evalToDest ? dest.data() : static_dest.data()); + + if(!evalToDest) + { + #ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN + int size = dest.size(); + EIGEN_DENSE_STORAGE_CTOR_PLUGIN + #endif + if(!alphaIsCompatible) + { + MappedDest(actualDestPtr, dest.size()).setZero(); + compatibleAlpha = RhsScalar(1); + } + else + MappedDest(actualDestPtr, dest.size()) = dest; + } + + general_matrix_vector_product + ::run( + actualLhs.rows(), actualLhs.cols(), + actualLhs.data(), actualLhs.outerStride(), + actualRhs.data(), actualRhs.innerStride(), + actualDestPtr, 1, + compatibleAlpha); + + if (!evalToDest) + { + if(!alphaIsCompatible) + dest += actualAlpha * MappedDest(actualDestPtr, dest.size()); + else + dest = MappedDest(actualDestPtr, dest.size()); + } + } +}; + +template<> struct gemv_selector +{ + template + static void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha) + { + typedef typename ProductType::LhsScalar LhsScalar; + typedef typename ProductType::RhsScalar RhsScalar; + typedef typename ProductType::Scalar ResScalar; + typedef typename ProductType::Index Index; + typedef typename ProductType::ActualLhsType ActualLhsType; + typedef typename ProductType::ActualRhsType ActualRhsType; + typedef typename ProductType::_ActualRhsType _ActualRhsType; + typedef typename ProductType::LhsBlasTraits LhsBlasTraits; + typedef typename ProductType::RhsBlasTraits RhsBlasTraits; + + typename add_const::type actualLhs = LhsBlasTraits::extract(prod.lhs()); + typename add_const::type actualRhs = RhsBlasTraits::extract(prod.rhs()); + + ResScalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(prod.lhs()) + * RhsBlasTraits::extractScalarFactor(prod.rhs()); + + enum { + // FIXME find a way to allow an inner stride on the result if packet_traits::size==1 + // on, the other hand it is good for the cache to pack the vector anyways... + DirectlyUseRhs = _ActualRhsType::InnerStrideAtCompileTime==1 + }; + + gemv_static_vector_if static_rhs; + + ei_declare_aligned_stack_constructed_variable(RhsScalar,actualRhsPtr,actualRhs.size(), + DirectlyUseRhs ? const_cast(actualRhs.data()) : static_rhs.data()); + + if(!DirectlyUseRhs) + { + #ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN + int size = actualRhs.size(); + EIGEN_DENSE_STORAGE_CTOR_PLUGIN + #endif + Map(actualRhsPtr, actualRhs.size()) = actualRhs; + } + + general_matrix_vector_product + ::run( + actualLhs.rows(), actualLhs.cols(), + actualLhs.data(), actualLhs.outerStride(), + actualRhsPtr, 1, + dest.data(), dest.innerStride(), + actualAlpha); + } +}; + +template<> struct gemv_selector +{ + template + static void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha) + { + typedef typename Dest::Index Index; + // TODO makes sure dest is sequentially stored in memory, otherwise use a temp + const Index size = prod.rhs().rows(); + for(Index k=0; k struct gemv_selector +{ + template + static void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha) + { + typedef typename Dest::Index Index; + // TODO makes sure rhs is sequentially stored in memory, otherwise use a temp + const Index rows = prod.rows(); + for(Index i=0; i +template +inline const typename ProductReturnType::Type +MatrixBase::operator*(const MatrixBase &other) const +{ + // A note regarding the function declaration: In MSVC, this function will sometimes + // not be inlined since DenseStorage is an unwindable object for dynamic + // matrices and product types are holding a member to store the result. + // Thus it does not help tagging this function with EIGEN_STRONG_INLINE. + enum { + ProductIsValid = Derived::ColsAtCompileTime==Dynamic + || OtherDerived::RowsAtCompileTime==Dynamic + || int(Derived::ColsAtCompileTime)==int(OtherDerived::RowsAtCompileTime), + AreVectors = Derived::IsVectorAtCompileTime && OtherDerived::IsVectorAtCompileTime, + SameSizes = EIGEN_PREDICATE_SAME_MATRIX_SIZE(Derived,OtherDerived) + }; + // note to the lost user: + // * for a dot product use: v1.dot(v2) + // * for a coeff-wise product use: v1.cwiseProduct(v2) + EIGEN_STATIC_ASSERT(ProductIsValid || !(AreVectors && SameSizes), + INVALID_VECTOR_VECTOR_PRODUCT__IF_YOU_WANTED_A_DOT_OR_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTIONS) + EIGEN_STATIC_ASSERT(ProductIsValid || !(SameSizes && !AreVectors), + INVALID_MATRIX_PRODUCT__IF_YOU_WANTED_A_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTION) + EIGEN_STATIC_ASSERT(ProductIsValid || SameSizes, INVALID_MATRIX_PRODUCT) +#ifdef EIGEN_DEBUG_PRODUCT + internal::product_type::debug(); +#endif + return typename ProductReturnType::Type(derived(), other.derived()); +} + +/** \returns an expression of the matrix product of \c *this and \a other without implicit evaluation. + * + * The returned product will behave like any other expressions: the coefficients of the product will be + * computed once at a time as requested. This might be useful in some extremely rare cases when only + * a small and no coherent fraction of the result's coefficients have to be computed. + * + * \warning This version of the matrix product can be much much slower. So use it only if you know + * what you are doing and that you measured a true speed improvement. + * + * \sa operator*(const MatrixBase&) + */ +template +template +const typename LazyProductReturnType::Type +MatrixBase::lazyProduct(const MatrixBase &other) const +{ + enum { + ProductIsValid = Derived::ColsAtCompileTime==Dynamic + || OtherDerived::RowsAtCompileTime==Dynamic + || int(Derived::ColsAtCompileTime)==int(OtherDerived::RowsAtCompileTime), + AreVectors = Derived::IsVectorAtCompileTime && OtherDerived::IsVectorAtCompileTime, + SameSizes = EIGEN_PREDICATE_SAME_MATRIX_SIZE(Derived,OtherDerived) + }; + // note to the lost user: + // * for a dot product use: v1.dot(v2) + // * for a coeff-wise product use: v1.cwiseProduct(v2) + EIGEN_STATIC_ASSERT(ProductIsValid || !(AreVectors && SameSizes), + INVALID_VECTOR_VECTOR_PRODUCT__IF_YOU_WANTED_A_DOT_OR_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTIONS) + EIGEN_STATIC_ASSERT(ProductIsValid || !(SameSizes && !AreVectors), + INVALID_MATRIX_PRODUCT__IF_YOU_WANTED_A_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTION) + EIGEN_STATIC_ASSERT(ProductIsValid || SameSizes, INVALID_MATRIX_PRODUCT) + + return typename LazyProductReturnType::Type(derived(), other.derived()); +} + +} // end namespace Eigen + +#endif // EIGEN_PRODUCT_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/GenericPacketMath.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/GenericPacketMath.h index 8ed835327..d92ac9529 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/GenericPacketMath.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/GenericPacketMath.h @@ -26,6 +26,8 @@ #ifndef EIGEN_GENERIC_PACKET_MATH_H #define EIGEN_GENERIC_PACKET_MATH_H +namespace Eigen { + namespace internal { /** \internal @@ -312,7 +314,7 @@ template struct palign_impl { // by default data are aligned, so there is nothing to be done :) - inline static void run(PacketType&, const PacketType&) {} + static inline void run(PacketType&, const PacketType&) {} }; /** \internal update \a first using the concatenation of the \a Offset last elements @@ -335,5 +337,7 @@ template<> inline std::complex pmul(const std::complex& a, const } // end namespace internal +} // end namespace Eigen + #endif // EIGEN_GENERIC_PACKET_MATH_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/GlobalFunctions.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/GlobalFunctions.h index 144145a95..94605252d 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/GlobalFunctions.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/GlobalFunctions.h @@ -66,13 +66,36 @@ namespace std template inline const Eigen::CwiseUnaryOp, const Derived> - pow(const Eigen::ArrayBase& x, const typename Derived::Scalar& exponent) { \ - return x.derived().pow(exponent); \ + pow(const Eigen::ArrayBase& x, const typename Derived::Scalar& exponent) { + return x.derived().pow(exponent); + } + + template + inline const Eigen::CwiseBinaryOp, const Derived, const Derived> + pow(const Eigen::ArrayBase& x, const Eigen::ArrayBase& exponents) + { + return Eigen::CwiseBinaryOp, const Derived, const Derived>( + x.derived(), + exponents.derived() + ); } } namespace Eigen { + /** + * \brief Component-wise division of a scalar by array elements. + **/ + template + inline const Eigen::CwiseUnaryOp, const Derived> + operator/(typename Derived::Scalar s, const Eigen::ArrayBase& a) + { + return Eigen::CwiseUnaryOp, const Derived>( + a.derived(), + Eigen::internal::scalar_inverse_mult_op(s) + ); + } + namespace internal { EIGEN_ARRAY_DECLARE_GLOBAL_EIGEN_UNARY(real,scalar_real_op) diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/IO.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/IO.h index f3cfcdbf4..2f1906f2a 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/IO.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/IO.h @@ -26,6 +26,8 @@ #ifndef EIGEN_IO_H #define EIGEN_IO_H +namespace Eigen { + enum { DontAlignCols = 1 }; enum { StreamPrecision = -1, FullPrecision = -2 }; @@ -171,7 +173,7 @@ std::ostream & print_matrix(std::ostream & s, const Derived& _m, const IOFormat& return s; } - const typename Derived::Nested m = _m; + typename Derived::Nested m = _m; typedef typename Derived::Scalar Scalar; typedef typename Derived::Index Index; @@ -257,4 +259,6 @@ std::ostream & operator << return internal::print_matrix(s, m.eval(), EIGEN_DEFAULT_IO_FORMAT); } +} // end namespace Eigen + #endif // EIGEN_IO_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/Map.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/Map.h index 2bf80b3af..360a2280e 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/Map.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/Map.h @@ -26,6 +26,8 @@ #ifndef EIGEN_MAP_H #define EIGEN_MAP_H +namespace Eigen { + /** \class Map * \ingroup Core_Module * @@ -200,4 +202,6 @@ inline Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> this->_set_noalias(Eigen::Map(data)); } +} // end namespace Eigen + #endif // EIGEN_MAP_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/MapBase.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/MapBase.h index 9426e2d24..2b736cb74 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/MapBase.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/MapBase.h @@ -30,6 +30,7 @@ EIGEN_STATIC_ASSERT((int(internal::traits::Flags) & LinearAccessBit) || Derived::IsVectorAtCompileTime, \ YOU_ARE_TRYING_TO_USE_AN_INDEX_BASED_ACCESSOR_ON_AN_EXPRESSION_THAT_DOES_NOT_SUPPORT_THAT) +namespace Eigen { /** \class MapBase * \ingroup Core_Module @@ -251,5 +252,6 @@ template class MapBase using Base::Base::operator=; }; +} // end namespace Eigen #endif // EIGEN_MAPBASE_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/MathFunctions.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/MathFunctions.h index 2b454db21..ab153c1eb 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/MathFunctions.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/MathFunctions.h @@ -25,6 +25,8 @@ #ifndef EIGEN_MATHFUNCTIONS_H #define EIGEN_MATHFUNCTIONS_H +namespace Eigen { + namespace internal { /** \internal \struct global_math_functions_filtering_base @@ -309,8 +311,7 @@ struct abs2_impl > { static inline RealScalar run(const std::complex& x) { - using std::norm; - return norm(x); + return real(x)*real(x) + imag(x)*imag(x); } }; @@ -553,7 +554,7 @@ struct pow_default_impl { static inline Scalar run(Scalar x, Scalar y) { - Scalar res = 1; + Scalar res(1); eigen_assert(!NumTraits::IsSigned || y >= 0); if(y & 1) res *= x; y >>= 1; @@ -838,6 +839,19 @@ template<> struct scalar_fuzzy_impl }; +/**************************************************************************** +* Special functions * +****************************************************************************/ + +// std::isfinite is non standard, so let's define our own version, +// even though it is not very efficient. +template bool isfinite(const T& x) +{ + return x::highest() && x>NumTraits::lowest(); +} + } // end namespace internal +} // end namespace Eigen + #endif // EIGEN_MATHFUNCTIONS_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/Matrix.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/Matrix.h index 982c9256a..8742a0130 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/Matrix.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/Matrix.h @@ -26,6 +26,8 @@ #ifndef EIGEN_MATRIX_H #define EIGEN_MATRIX_H +namespace Eigen { + /** \class Matrix * \ingroup Core_Module * @@ -411,25 +413,8 @@ EIGEN_MAKE_TYPEDEFS_ALL_SIZES(std::complex, cd) #undef EIGEN_MAKE_TYPEDEFS_ALL_SIZES #undef EIGEN_MAKE_TYPEDEFS +#undef EIGEN_MAKE_FIXED_TYPEDEFS -#undef EIGEN_MAKE_TYPEDEFS_LARGE - -#define EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, SizeSuffix) \ -using Eigen::Matrix##SizeSuffix##TypeSuffix; \ -using Eigen::Vector##SizeSuffix##TypeSuffix; \ -using Eigen::RowVector##SizeSuffix##TypeSuffix; - -#define EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(TypeSuffix) \ -EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, 2) \ -EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, 3) \ -EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, 4) \ -EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, X) \ - -#define EIGEN_USING_MATRIX_TYPEDEFS \ -EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(i) \ -EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(f) \ -EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(d) \ -EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(cf) \ -EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(cd) +} // end namespace Eigen #endif // EIGEN_MATRIX_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/MatrixBase.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/MatrixBase.h index 62877bce0..5a744c5ec 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/MatrixBase.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/MatrixBase.h @@ -26,6 +26,8 @@ #ifndef EIGEN_MATRIXBASE_H #define EIGEN_MATRIXBASE_H +namespace Eigen { + /** \class MatrixBase * \ingroup Core_Module * @@ -250,8 +252,7 @@ template class MatrixBase // huuuge hack. make Eigen2's matrix.part() work in eigen3. Problem: Diagonal is now a class template instead // of an integer constant. Solution: overload the part() method template wrt template parameters list. - // Note: replacing next line by "template class U>" produces a mysterious error C2082 in MSVC. - template class U> + template class U> const DiagonalWrapper part() const { return diagonal().asDiagonal(); } #endif // EIGEN2_SUPPORT @@ -331,7 +332,7 @@ template class MatrixBase /** \returns an \link ArrayBase Array \endlink expression of this matrix * \sa ArrayBase::matrix() */ ArrayWrapper array() { return derived(); } - const ArrayWrapper array() const { return derived(); } + const ArrayWrapper array() const { return derived(); } /////////// LU module /////////// @@ -466,6 +467,8 @@ template class MatrixBase const MatrixFunctionReturnValue sinh() const; const MatrixFunctionReturnValue cos() const; const MatrixFunctionReturnValue sin() const; + const MatrixSquareRootReturnValue sqrt() const; + const MatrixLogarithmReturnValue log() const; #ifdef EIGEN2_SUPPORT template @@ -512,10 +515,12 @@ template class MatrixBase protected: // mixing arrays and matrices is not legal template Derived& operator+=(const ArrayBase& ) - {EIGEN_STATIC_ASSERT(sizeof(typename OtherDerived::Scalar)==-1,YOU_CANNOT_MIX_ARRAYS_AND_MATRICES);} + {EIGEN_STATIC_ASSERT(std::ptrdiff_t(sizeof(typename OtherDerived::Scalar))==-1,YOU_CANNOT_MIX_ARRAYS_AND_MATRICES); return *this;} // mixing arrays and matrices is not legal template Derived& operator-=(const ArrayBase& ) - {EIGEN_STATIC_ASSERT(sizeof(typename OtherDerived::Scalar)==-1,YOU_CANNOT_MIX_ARRAYS_AND_MATRICES);} + {EIGEN_STATIC_ASSERT(std::ptrdiff_t(sizeof(typename OtherDerived::Scalar))==-1,YOU_CANNOT_MIX_ARRAYS_AND_MATRICES); return *this;} }; +} // end namespace Eigen + #endif // EIGEN_MATRIXBASE_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/NestByValue.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/NestByValue.h index a6104d2a4..cfe3e7990 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/NestByValue.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/NestByValue.h @@ -26,6 +26,8 @@ #ifndef EIGEN_NESTBYVALUE_H #define EIGEN_NESTBYVALUE_H +namespace Eigen { + /** \class NestByValue * \ingroup Core_Module * @@ -119,4 +121,6 @@ DenseBase::nestByValue() const return NestByValue(derived()); } +} // end namespace Eigen + #endif // EIGEN_NESTBYVALUE_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/NoAlias.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/NoAlias.h index da64affcf..5278cfb73 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/NoAlias.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/NoAlias.h @@ -25,6 +25,8 @@ #ifndef EIGEN_NOALIAS_H #define EIGEN_NOALIAS_H +namespace Eigen { + /** \class NoAlias * \ingroup Core_Module * @@ -133,4 +135,6 @@ NoAlias MatrixBase::noalias() return derived(); } +} // end namespace Eigen + #endif // EIGEN_NOALIAS_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/NumTraits.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/NumTraits.h index 73ef05dfe..e8867235e 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/NumTraits.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/NumTraits.h @@ -25,6 +25,8 @@ #ifndef EIGEN_NUMTRAITS_H #define EIGEN_NUMTRAITS_H +namespace Eigen { + /** \class NumTraits * \ingroup Core_Module * @@ -81,14 +83,14 @@ template struct GenericNumTraits >::type NonInteger; typedef T Nested; - inline static Real epsilon() { return std::numeric_limits::epsilon(); } - inline static Real dummy_precision() + static inline Real epsilon() { return std::numeric_limits::epsilon(); } + static inline Real dummy_precision() { // make sure to override this for floating-point types return Real(0); } - inline static T highest() { return (std::numeric_limits::max)(); } - inline static T lowest() { return IsInteger ? (std::numeric_limits::min)() : (-(std::numeric_limits::max)()); } + static inline T highest() { return (std::numeric_limits::max)(); } + static inline T lowest() { return IsInteger ? (std::numeric_limits::min)() : (-(std::numeric_limits::max)()); } #ifdef EIGEN2_SUPPORT enum { @@ -104,12 +106,12 @@ template struct NumTraits : GenericNumTraits template<> struct NumTraits : GenericNumTraits { - inline static float dummy_precision() { return 1e-5f; } + static inline float dummy_precision() { return 1e-5f; } }; template<> struct NumTraits : GenericNumTraits { - inline static double dummy_precision() { return 1e-12; } + static inline double dummy_precision() { return 1e-12; } }; template<> struct NumTraits @@ -130,8 +132,8 @@ template struct NumTraits > MulCost = 4 * NumTraits::MulCost + 2 * NumTraits::AddCost }; - inline static Real epsilon() { return NumTraits::epsilon(); } - inline static Real dummy_precision() { return NumTraits::dummy_precision(); } + static inline Real epsilon() { return NumTraits::epsilon(); } + static inline Real dummy_precision() { return NumTraits::dummy_precision(); } }; template @@ -155,6 +157,6 @@ struct NumTraits > }; }; - +} // end namespace Eigen #endif // EIGEN_NUMTRAITS_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/PermutationMatrix.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/PermutationMatrix.h index a064e053e..e0d618dfb 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/PermutationMatrix.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/PermutationMatrix.h @@ -26,6 +26,8 @@ #ifndef EIGEN_PERMUTATIONMATRIX_H #define EIGEN_PERMUTATIONMATRIX_H +namespace Eigen { + template class PermutedImpl; /** \class PermutationBase @@ -56,6 +58,8 @@ namespace internal { template struct permut_matrix_product_retval; +template +struct permut_sparsematrix_product_retval; enum PermPermProduct_t {PermPermProduct}; } // end namespace internal @@ -511,7 +515,7 @@ class PermutationWrapper : public PermutationBase MatrixBase::asPermutation() con return derived(); } +} // end namespace Eigen + #endif // EIGEN_PERMUTATIONMATRIX_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/PlainObjectBase.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/PlainObjectBase.h index 612254e9d..f9c432732 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/PlainObjectBase.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/PlainObjectBase.h @@ -32,6 +32,8 @@ # define EIGEN_INITIALIZE_BY_ZERO_IF_THAT_OPTION_IS_ENABLED #endif +namespace Eigen { + namespace internal { template @@ -47,13 +49,13 @@ EIGEN_ALWAYS_INLINE void check_rows_cols_for_overflow(Index rows, Index cols) throw_std_bad_alloc(); } -template (Derived::IsVectorAtCompileTime)> struct conservative_resize_like_impl; +template struct conservative_resize_like_impl; template struct matrix_swap_impl; } // end namespace internal -/** +/** \class PlainObjectBase * \brief %Dense storage base class for matrices and arrays. * * This class can be extended with the help of the plugin mechanism described on the page @@ -61,8 +63,29 @@ template struct m * * \sa \ref TopicClassHierarchy */ +#ifdef EIGEN_PARSED_BY_DOXYGEN +namespace internal { + +// this is a warkaround to doxygen not being able to understand the inheritence logic +// when it is hidden by the dense_xpr_base helper struct. +template struct dense_xpr_base_dispatcher_for_doxygen;// : public MatrixBase {}; +/** This class is just a workaround for Doxygen and it does not not actually exist. */ +template +struct dense_xpr_base_dispatcher_for_doxygen > + : public MatrixBase > {}; +/** This class is just a workaround for Doxygen and it does not not actually exist. */ +template +struct dense_xpr_base_dispatcher_for_doxygen > + : public ArrayBase > {}; + +} // namespace internal + +template +class PlainObjectBase : public internal::dense_xpr_base_dispatcher_for_doxygen +#else template class PlainObjectBase : public internal::dense_xpr_base::type +#endif { public: enum { Options = internal::traits::Options }; @@ -443,68 +466,68 @@ class PlainObjectBase : public internal::dense_xpr_base::type * \see class Map */ //@{ - inline static ConstMapType Map(const Scalar* data) + static inline ConstMapType Map(const Scalar* data) { return ConstMapType(data); } - inline static MapType Map(Scalar* data) + static inline MapType Map(Scalar* data) { return MapType(data); } - inline static ConstMapType Map(const Scalar* data, Index size) + static inline ConstMapType Map(const Scalar* data, Index size) { return ConstMapType(data, size); } - inline static MapType Map(Scalar* data, Index size) + static inline MapType Map(Scalar* data, Index size) { return MapType(data, size); } - inline static ConstMapType Map(const Scalar* data, Index rows, Index cols) + static inline ConstMapType Map(const Scalar* data, Index rows, Index cols) { return ConstMapType(data, rows, cols); } - inline static MapType Map(Scalar* data, Index rows, Index cols) + static inline MapType Map(Scalar* data, Index rows, Index cols) { return MapType(data, rows, cols); } - inline static ConstAlignedMapType MapAligned(const Scalar* data) + static inline ConstAlignedMapType MapAligned(const Scalar* data) { return ConstAlignedMapType(data); } - inline static AlignedMapType MapAligned(Scalar* data) + static inline AlignedMapType MapAligned(Scalar* data) { return AlignedMapType(data); } - inline static ConstAlignedMapType MapAligned(const Scalar* data, Index size) + static inline ConstAlignedMapType MapAligned(const Scalar* data, Index size) { return ConstAlignedMapType(data, size); } - inline static AlignedMapType MapAligned(Scalar* data, Index size) + static inline AlignedMapType MapAligned(Scalar* data, Index size) { return AlignedMapType(data, size); } - inline static ConstAlignedMapType MapAligned(const Scalar* data, Index rows, Index cols) + static inline ConstAlignedMapType MapAligned(const Scalar* data, Index rows, Index cols) { return ConstAlignedMapType(data, rows, cols); } - inline static AlignedMapType MapAligned(Scalar* data, Index rows, Index cols) + static inline AlignedMapType MapAligned(Scalar* data, Index rows, Index cols) { return AlignedMapType(data, rows, cols); } template - inline static typename StridedConstMapType >::type Map(const Scalar* data, const Stride& stride) + static inline typename StridedConstMapType >::type Map(const Scalar* data, const Stride& stride) { return typename StridedConstMapType >::type(data, stride); } template - inline static typename StridedMapType >::type Map(Scalar* data, const Stride& stride) + static inline typename StridedMapType >::type Map(Scalar* data, const Stride& stride) { return typename StridedMapType >::type(data, stride); } template - inline static typename StridedConstMapType >::type Map(const Scalar* data, Index size, const Stride& stride) + static inline typename StridedConstMapType >::type Map(const Scalar* data, Index size, const Stride& stride) { return typename StridedConstMapType >::type(data, size, stride); } template - inline static typename StridedMapType >::type Map(Scalar* data, Index size, const Stride& stride) + static inline typename StridedMapType >::type Map(Scalar* data, Index size, const Stride& stride) { return typename StridedMapType >::type(data, size, stride); } template - inline static typename StridedConstMapType >::type Map(const Scalar* data, Index rows, Index cols, const Stride& stride) + static inline typename StridedConstMapType >::type Map(const Scalar* data, Index rows, Index cols, const Stride& stride) { return typename StridedConstMapType >::type(data, rows, cols, stride); } template - inline static typename StridedMapType >::type Map(Scalar* data, Index rows, Index cols, const Stride& stride) + static inline typename StridedMapType >::type Map(Scalar* data, Index rows, Index cols, const Stride& stride) { return typename StridedMapType >::type(data, rows, cols, stride); } template - inline static typename StridedConstAlignedMapType >::type MapAligned(const Scalar* data, const Stride& stride) + static inline typename StridedConstAlignedMapType >::type MapAligned(const Scalar* data, const Stride& stride) { return typename StridedConstAlignedMapType >::type(data, stride); } template - inline static typename StridedAlignedMapType >::type MapAligned(Scalar* data, const Stride& stride) + static inline typename StridedAlignedMapType >::type MapAligned(Scalar* data, const Stride& stride) { return typename StridedAlignedMapType >::type(data, stride); } template - inline static typename StridedConstAlignedMapType >::type MapAligned(const Scalar* data, Index size, const Stride& stride) + static inline typename StridedConstAlignedMapType >::type MapAligned(const Scalar* data, Index size, const Stride& stride) { return typename StridedConstAlignedMapType >::type(data, size, stride); } template - inline static typename StridedAlignedMapType >::type MapAligned(Scalar* data, Index size, const Stride& stride) + static inline typename StridedAlignedMapType >::type MapAligned(Scalar* data, Index size, const Stride& stride) { return typename StridedAlignedMapType >::type(data, size, stride); } template - inline static typename StridedConstAlignedMapType >::type MapAligned(const Scalar* data, Index rows, Index cols, const Stride& stride) + static inline typename StridedConstAlignedMapType >::type MapAligned(const Scalar* data, Index rows, Index cols, const Stride& stride) { return typename StridedConstAlignedMapType >::type(data, rows, cols, stride); } template - inline static typename StridedAlignedMapType >::type MapAligned(Scalar* data, Index rows, Index cols, const Stride& stride) + static inline typename StridedAlignedMapType >::type MapAligned(Scalar* data, Index rows, Index cols, const Stride& stride) { return typename StridedAlignedMapType >::type(data, rows, cols, stride); } //@} @@ -594,6 +617,9 @@ class PlainObjectBase : public internal::dense_xpr_base::type template EIGEN_STRONG_INLINE void _init2(Index rows, Index cols, typename internal::enable_if::type* = 0) { + EIGEN_STATIC_ASSERT(bool(NumTraits::IsInteger) && + bool(NumTraits::IsInteger), + FLOATING_POINT_ARGUMENT_PASSED__INTEGER_WAS_EXPECTED) eigen_assert(rows >= 0 && (RowsAtCompileTime == Dynamic || RowsAtCompileTime == rows) && cols >= 0 && (ColsAtCompileTime == Dynamic || ColsAtCompileTime == cols)); internal::check_rows_cols_for_overflow(rows, cols); @@ -623,7 +649,7 @@ class PlainObjectBase : public internal::dense_xpr_base::type public: #ifndef EIGEN_PARSED_BY_DOXYGEN - EIGEN_STRONG_INLINE static void _check_template_params() + static EIGEN_STRONG_INLINE void _check_template_params() { EIGEN_STATIC_ASSERT((EIGEN_IMPLIES(MaxRowsAtCompileTime==1 && MaxColsAtCompileTime!=1, (Options&RowMajor)==RowMajor) && EIGEN_IMPLIES(MaxColsAtCompileTime==1 && MaxRowsAtCompileTime!=1, (Options&RowMajor)==0) @@ -751,4 +777,6 @@ struct matrix_swap_impl } // end namespace internal +} // end namespace Eigen + #endif // EIGEN_DENSESTORAGEBASE_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/Product.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/Product.h index e2035b242..53eb0fbae 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/Product.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/Product.h @@ -1,8 +1,7 @@ // This file is part of Eigen, a lightweight C++ template library // for linear algebra. // -// Copyright (C) 2006-2008 Benoit Jacob -// Copyright (C) 2008 Gael Guennebaud +// Copyright (C) 2008-2011 Gael Guennebaud // // Eigen is free software; you can redistribute it and/or // modify it under the terms of the GNU Lesser General Public @@ -26,600 +25,89 @@ #ifndef EIGEN_PRODUCT_H #define EIGEN_PRODUCT_H -/** \class GeneralProduct +template class Product; +template class ProductImpl; + +/** \class Product * \ingroup Core_Module * - * \brief Expression of the product of two general matrices or vectors + * \brief Expression of the product of two arbitrary matrices or vectors * - * \param LhsNested the type used to store the left-hand side - * \param RhsNested the type used to store the right-hand side - * \param ProductMode the type of the product + * \param Lhs the type of the left-hand side expression + * \param Rhs the type of the right-hand side expression * - * This class represents an expression of the product of two general matrices. - * We call a general matrix, a dense matrix with full storage. For instance, - * This excludes triangular, selfadjoint, and sparse matrices. - * It is the return type of the operator* between general matrices. Its template - * arguments are determined automatically by ProductReturnType. Therefore, - * GeneralProduct should never be used direclty. To determine the result type of a - * function which involves a matrix product, use ProductReturnType::Type. + * This class represents an expression of the product of two arbitrary matrices. * - * \sa ProductReturnType, MatrixBase::operator*(const MatrixBase&) */ -template::value> -class GeneralProduct; - -enum { - Large = 2, - Small = 3 -}; namespace internal { - -template struct product_type_selector; - -template struct product_size_category +template +struct traits > { - enum { is_large = MaxSize == Dynamic || - Size >= EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD, - value = is_large ? Large - : Size == 1 ? 1 - : Small + typedef MatrixXpr XprKind; + typedef typename remove_all::type LhsCleaned; + typedef typename remove_all::type RhsCleaned; + typedef typename scalar_product_traits::Scalar, typename traits::Scalar>::ReturnType Scalar; + typedef typename promote_storage_type::StorageKind, + typename traits::StorageKind>::ret StorageKind; + typedef typename promote_index_type::Index, + typename traits::Index>::type Index; + enum { + RowsAtCompileTime = LhsCleaned::RowsAtCompileTime, + ColsAtCompileTime = RhsCleaned::ColsAtCompileTime, + MaxRowsAtCompileTime = LhsCleaned::MaxRowsAtCompileTime, + MaxColsAtCompileTime = RhsCleaned::MaxColsAtCompileTime, + Flags = (MaxRowsAtCompileTime==1 ? RowMajorBit : 0), // TODO should be no storage order + CoeffReadCost = 0 // TODO CoeffReadCost should not be part of the expression traits }; }; - -template struct product_type -{ - typedef typename remove_all::type _Lhs; - typedef typename remove_all::type _Rhs; - enum { - MaxRows = _Lhs::MaxRowsAtCompileTime, - Rows = _Lhs::RowsAtCompileTime, - MaxCols = _Rhs::MaxColsAtCompileTime, - Cols = _Rhs::ColsAtCompileTime, - MaxDepth = EIGEN_SIZE_MIN_PREFER_FIXED(_Lhs::MaxColsAtCompileTime, - _Rhs::MaxRowsAtCompileTime), - Depth = EIGEN_SIZE_MIN_PREFER_FIXED(_Lhs::ColsAtCompileTime, - _Rhs::RowsAtCompileTime), - LargeThreshold = EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD - }; - - // the splitting into different lines of code here, introducing the _select enums and the typedef below, - // is to work around an internal compiler error with gcc 4.1 and 4.2. -private: - enum { - rows_select = product_size_category::value, - cols_select = product_size_category::value, - depth_select = product_size_category::value - }; - typedef product_type_selector selector; - -public: - enum { - value = selector::ret - }; -#ifdef EIGEN_DEBUG_PRODUCT - static void debug() - { - EIGEN_DEBUG_VAR(Rows); - EIGEN_DEBUG_VAR(Cols); - EIGEN_DEBUG_VAR(Depth); - EIGEN_DEBUG_VAR(rows_select); - EIGEN_DEBUG_VAR(cols_select); - EIGEN_DEBUG_VAR(depth_select); - EIGEN_DEBUG_VAR(value); - } -#endif -}; - - -/* The following allows to select the kind of product at compile time - * based on the three dimensions of the product. - * This is a compile time mapping from {1,Small,Large}^3 -> {product types} */ -// FIXME I'm not sure the current mapping is the ideal one. -template struct product_type_selector { enum { ret = OuterProduct }; }; -template struct product_type_selector<1, 1, Depth> { enum { ret = InnerProduct }; }; -template<> struct product_type_selector<1, 1, 1> { enum { ret = InnerProduct }; }; -template<> struct product_type_selector { enum { ret = CoeffBasedProductMode }; }; -template<> struct product_type_selector<1, Small,Small> { enum { ret = CoeffBasedProductMode }; }; -template<> struct product_type_selector { enum { ret = CoeffBasedProductMode }; }; -template<> struct product_type_selector { enum { ret = LazyCoeffBasedProductMode }; }; -template<> struct product_type_selector { enum { ret = LazyCoeffBasedProductMode }; }; -template<> struct product_type_selector { enum { ret = LazyCoeffBasedProductMode }; }; -template<> struct product_type_selector<1, Large,Small> { enum { ret = CoeffBasedProductMode }; }; -template<> struct product_type_selector<1, Large,Large> { enum { ret = GemvProduct }; }; -template<> struct product_type_selector<1, Small,Large> { enum { ret = CoeffBasedProductMode }; }; -template<> struct product_type_selector { enum { ret = CoeffBasedProductMode }; }; -template<> struct product_type_selector { enum { ret = GemvProduct }; }; -template<> struct product_type_selector { enum { ret = CoeffBasedProductMode }; }; -template<> struct product_type_selector { enum { ret = GemmProduct }; }; -template<> struct product_type_selector { enum { ret = GemmProduct }; }; -template<> struct product_type_selector { enum { ret = GemmProduct }; }; -template<> struct product_type_selector { enum { ret = GemmProduct }; }; -template<> struct product_type_selector { enum { ret = GemmProduct }; }; -template<> struct product_type_selector { enum { ret = GemmProduct }; }; -template<> struct product_type_selector { enum { ret = GemmProduct }; }; - } // end namespace internal -/** \class ProductReturnType - * \ingroup Core_Module - * - * \brief Helper class to get the correct and optimized returned type of operator* - * - * \param Lhs the type of the left-hand side - * \param Rhs the type of the right-hand side - * \param ProductMode the type of the product (determined automatically by internal::product_mode) - * - * This class defines the typename Type representing the optimized product expression - * between two matrix expressions. In practice, using ProductReturnType::Type - * is the recommended way to define the result type of a function returning an expression - * which involve a matrix product. The class Product should never be - * used directly. - * - * \sa class Product, MatrixBase::operator*(const MatrixBase&) - */ -template -struct ProductReturnType -{ - // TODO use the nested type to reduce instanciations ???? -// typedef typename internal::nested::type LhsNested; -// typedef typename internal::nested::type RhsNested; - - typedef GeneralProduct Type; -}; template -struct ProductReturnType -{ - typedef typename internal::nested::type >::type LhsNested; - typedef typename internal::nested::type >::type RhsNested; - typedef CoeffBasedProduct Type; -}; - -template -struct ProductReturnType -{ - typedef typename internal::nested::type >::type LhsNested; - typedef typename internal::nested::type >::type RhsNested; - typedef CoeffBasedProduct Type; -}; - -// this is a workaround for sun CC -template -struct LazyProductReturnType : public ProductReturnType -{}; - -/*********************************************************************** -* Implementation of Inner Vector Vector Product -***********************************************************************/ - -// FIXME : maybe the "inner product" could return a Scalar -// instead of a 1x1 matrix ?? -// Pro: more natural for the user -// Cons: this could be a problem if in a meta unrolled algorithm a matrix-matrix -// product ends up to a row-vector times col-vector product... To tackle this use -// case, we could have a specialization for Block with: operator=(Scalar x); - -namespace internal { - -template -struct traits > - : traits::ReturnType,1,1> > -{}; - -} - -template -class GeneralProduct - : internal::no_assignment_operator, - public Matrix::ReturnType,1,1> -{ - typedef Matrix::ReturnType,1,1> Base; - public: - GeneralProduct(const Lhs& lhs, const Rhs& rhs) - { - EIGEN_STATIC_ASSERT((internal::is_same::value), - YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY) - - Base::coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); - } - - /** Convertion to scalar */ - operator const typename Base::Scalar() const { - return Base::coeff(0,0); - } -}; - -/*********************************************************************** -* Implementation of Outer Vector Vector Product -***********************************************************************/ - -namespace internal { -template struct outer_product_selector; - -template -struct traits > - : traits, Lhs, Rhs> > -{}; - -} - -template -class GeneralProduct - : public ProductBase, Lhs, Rhs> +class Product : public ProductImpl::StorageKind, + typename internal::traits::StorageKind>::ret> { public: - EIGEN_PRODUCT_PUBLIC_INTERFACE(GeneralProduct) - - GeneralProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs) - { - EIGEN_STATIC_ASSERT((internal::is_same::value), - YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY) - } - - template void scaleAndAddTo(Dest& dest, Scalar alpha) const - { - internal::outer_product_selector<(int(Dest::Flags)&RowMajorBit) ? RowMajor : ColMajor>::run(*this, dest, alpha); - } -}; - -namespace internal { - -template<> struct outer_product_selector { - template - static EIGEN_DONT_INLINE void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha) { - typedef typename Dest::Index Index; - // FIXME make sure lhs is sequentially stored - // FIXME not very good if rhs is real and lhs complex while alpha is real too - const Index cols = dest.cols(); - for (Index j=0; j struct outer_product_selector { - template - static EIGEN_DONT_INLINE void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha) { - typedef typename Dest::Index Index; - // FIXME make sure rhs is sequentially stored - // FIXME not very good if lhs is real and rhs complex while alpha is real too - const Index rows = dest.rows(); - for (Index i=0; i call fast BLAS-like colmajor routine - * 2 - the matrix is row-major, BLAS compatible and N is large => call fast BLAS-like rowmajor routine - * 3 - all other cases are handled using a simple loop along the outer-storage direction. - * Therefore we need a lower level meta selector. - * Furthermore, if the matrix is the rhs, then the product has to be transposed. - */ -namespace internal { - -template -struct traits > - : traits, Lhs, Rhs> > -{}; - -template -struct gemv_selector; - -} // end namespace internal - -template -class GeneralProduct - : public ProductBase, Lhs, Rhs> -{ - public: - EIGEN_PRODUCT_PUBLIC_INTERFACE(GeneralProduct) - - typedef typename Lhs::Scalar LhsScalar; - typedef typename Rhs::Scalar RhsScalar; - - GeneralProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs) - { -// EIGEN_STATIC_ASSERT((internal::is_same::value), -// YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY) - } - - enum { Side = Lhs::IsVectorAtCompileTime ? OnTheLeft : OnTheRight }; - typedef typename internal::conditional::type MatrixType; - - template void scaleAndAddTo(Dest& dst, Scalar alpha) const - { - eigen_assert(m_lhs.rows() == dst.rows() && m_rhs.cols() == dst.cols()); - internal::gemv_selector::HasUsableDirectAccess)>::run(*this, dst, alpha); - } -}; - -namespace internal { - -// The vector is on the left => transposition -template -struct gemv_selector -{ - template - static void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha) - { - Transpose destT(dest); - enum { OtherStorageOrder = StorageOrder == RowMajor ? ColMajor : RowMajor }; - gemv_selector - ::run(GeneralProduct,Transpose, GemvProduct> - (prod.rhs().transpose(), prod.lhs().transpose()), destT, alpha); - } -}; - -template struct gemv_static_vector_if; - -template -struct gemv_static_vector_if -{ - EIGEN_STRONG_INLINE Scalar* data() { eigen_internal_assert(false && "should never be called"); return 0; } -}; - -template -struct gemv_static_vector_if -{ - EIGEN_STRONG_INLINE Scalar* data() { return 0; } -}; - -template -struct gemv_static_vector_if -{ - #if EIGEN_ALIGN_STATICALLY - internal::plain_array m_data; - EIGEN_STRONG_INLINE Scalar* data() { return m_data.array; } - #else - // Some architectures cannot align on the stack, - // => let's manually enforce alignment by allocating more data and return the address of the first aligned element. - enum { - ForceAlignment = internal::packet_traits::Vectorizable, - PacketSize = internal::packet_traits::size - }; - internal::plain_array m_data; - EIGEN_STRONG_INLINE Scalar* data() { - return ForceAlignment - ? reinterpret_cast((reinterpret_cast(m_data.array) & ~(size_t(15))) + 16) - : m_data.array; - } - #endif -}; - -template<> struct gemv_selector -{ - template - static inline void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha) - { - typedef typename ProductType::Index Index; - typedef typename ProductType::LhsScalar LhsScalar; - typedef typename ProductType::RhsScalar RhsScalar; - typedef typename ProductType::Scalar ResScalar; - typedef typename ProductType::RealScalar RealScalar; - typedef typename ProductType::ActualLhsType ActualLhsType; - typedef typename ProductType::ActualRhsType ActualRhsType; - typedef typename ProductType::LhsBlasTraits LhsBlasTraits; - typedef typename ProductType::RhsBlasTraits RhsBlasTraits; - typedef Map, Aligned> MappedDest; - - const ActualLhsType actualLhs = LhsBlasTraits::extract(prod.lhs()); - const ActualRhsType actualRhs = RhsBlasTraits::extract(prod.rhs()); - - ResScalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(prod.lhs()) - * RhsBlasTraits::extractScalarFactor(prod.rhs()); - - enum { - // FIXME find a way to allow an inner stride on the result if packet_traits::size==1 - // on, the other hand it is good for the cache to pack the vector anyways... - EvalToDestAtCompileTime = Dest::InnerStrideAtCompileTime==1, - ComplexByReal = (NumTraits::IsComplex) && (!NumTraits::IsComplex), - MightCannotUseDest = (Dest::InnerStrideAtCompileTime!=1) || ComplexByReal - }; - - gemv_static_vector_if static_dest; - - // this is written like this (i.e., with a ?:) to workaround an ICE with ICC 12 - bool alphaIsCompatible = (!ComplexByReal) ? true : (imag(actualAlpha)==RealScalar(0)); - bool evalToDest = EvalToDestAtCompileTime && alphaIsCompatible; - RhsScalar compatibleAlpha = get_factor::run(actualAlpha); + typedef typename ProductImpl< + Lhs, Rhs, + typename internal::promote_storage_type::ret>::Base Base; + EIGEN_GENERIC_PUBLIC_INTERFACE(Product) - ei_declare_aligned_stack_constructed_variable(ResScalar,actualDestPtr,dest.size(), - evalToDest ? dest.data() : static_dest.data()); - - if(!evalToDest) + typedef typename Lhs::Nested LhsNested; + typedef typename Rhs::Nested RhsNested; + typedef typename internal::remove_all::type LhsNestedCleaned; + typedef typename internal::remove_all::type RhsNestedCleaned; + + Product(const Lhs& lhs, const Rhs& rhs) : m_lhs(lhs), m_rhs(rhs) { - #ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN - int size = dest.size(); - EIGEN_DENSE_STORAGE_CTOR_PLUGIN - #endif - if(!alphaIsCompatible) - { - MappedDest(actualDestPtr, dest.size()).setZero(); - compatibleAlpha = RhsScalar(1); - } - else - MappedDest(actualDestPtr, dest.size()) = dest; + eigen_assert(lhs.cols() == rhs.rows() + && "invalid matrix product" + && "if you wanted a coeff-wise or a dot product use the respective explicit functions"); } - general_matrix_vector_product - ::run( - actualLhs.rows(), actualLhs.cols(), - &actualLhs.coeffRef(0,0), actualLhs.outerStride(), - actualRhs.data(), actualRhs.innerStride(), - actualDestPtr, 1, - compatibleAlpha); + inline Index rows() const { return m_lhs.rows(); } + inline Index cols() const { return m_rhs.cols(); } - if (!evalToDest) - { - if(!alphaIsCompatible) - dest += actualAlpha * MappedDest(actualDestPtr, dest.size()); - else - dest = MappedDest(actualDestPtr, dest.size()); - } - } + const LhsNestedCleaned& lhs() const { return m_lhs; } + const RhsNestedCleaned& rhs() const { return m_rhs; } + + protected: + + const LhsNested m_lhs; + const RhsNested m_rhs; }; -template<> struct gemv_selector +template +class ProductImpl : public internal::dense_xpr_base >::type { - template - static void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha) - { - typedef typename ProductType::LhsScalar LhsScalar; - typedef typename ProductType::RhsScalar RhsScalar; - typedef typename ProductType::Scalar ResScalar; - typedef typename ProductType::Index Index; - typedef typename ProductType::ActualLhsType ActualLhsType; - typedef typename ProductType::ActualRhsType ActualRhsType; - typedef typename ProductType::_ActualRhsType _ActualRhsType; - typedef typename ProductType::LhsBlasTraits LhsBlasTraits; - typedef typename ProductType::RhsBlasTraits RhsBlasTraits; + typedef Product Derived; + public: - typename add_const::type actualLhs = LhsBlasTraits::extract(prod.lhs()); - typename add_const::type actualRhs = RhsBlasTraits::extract(prod.rhs()); - - ResScalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(prod.lhs()) - * RhsBlasTraits::extractScalarFactor(prod.rhs()); - - enum { - // FIXME find a way to allow an inner stride on the result if packet_traits::size==1 - // on, the other hand it is good for the cache to pack the vector anyways... - DirectlyUseRhs = _ActualRhsType::InnerStrideAtCompileTime==1 - }; - - gemv_static_vector_if static_rhs; - - ei_declare_aligned_stack_constructed_variable(RhsScalar,actualRhsPtr,actualRhs.size(), - DirectlyUseRhs ? const_cast(actualRhs.data()) : static_rhs.data()); - - if(!DirectlyUseRhs) - { - #ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN - int size = actualRhs.size(); - EIGEN_DENSE_STORAGE_CTOR_PLUGIN - #endif - Map(actualRhsPtr, actualRhs.size()) = actualRhs; - } - - general_matrix_vector_product - ::run( - actualLhs.rows(), actualLhs.cols(), - &actualLhs.coeffRef(0,0), actualLhs.outerStride(), - actualRhsPtr, 1, - &dest.coeffRef(0,0), dest.innerStride(), - actualAlpha); - } + typedef typename internal::dense_xpr_base >::type Base; + EIGEN_DENSE_PUBLIC_INTERFACE(Derived) }; -template<> struct gemv_selector -{ - template - static void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha) - { - typedef typename Dest::Index Index; - // TODO makes sure dest is sequentially stored in memory, otherwise use a temp - const Index size = prod.rhs().rows(); - for(Index k=0; k struct gemv_selector -{ - template - static void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha) - { - typedef typename Dest::Index Index; - // TODO makes sure rhs is sequentially stored in memory, otherwise use a temp - const Index rows = prod.rows(); - for(Index i=0; i -template -inline const typename ProductReturnType::Type -MatrixBase::operator*(const MatrixBase &other) const -{ - // A note regarding the function declaration: In MSVC, this function will sometimes - // not be inlined since DenseStorage is an unwindable object for dynamic - // matrices and product types are holding a member to store the result. - // Thus it does not help tagging this function with EIGEN_STRONG_INLINE. - enum { - ProductIsValid = Derived::ColsAtCompileTime==Dynamic - || OtherDerived::RowsAtCompileTime==Dynamic - || int(Derived::ColsAtCompileTime)==int(OtherDerived::RowsAtCompileTime), - AreVectors = Derived::IsVectorAtCompileTime && OtherDerived::IsVectorAtCompileTime, - SameSizes = EIGEN_PREDICATE_SAME_MATRIX_SIZE(Derived,OtherDerived) - }; - // note to the lost user: - // * for a dot product use: v1.dot(v2) - // * for a coeff-wise product use: v1.cwiseProduct(v2) - EIGEN_STATIC_ASSERT(ProductIsValid || !(AreVectors && SameSizes), - INVALID_VECTOR_VECTOR_PRODUCT__IF_YOU_WANTED_A_DOT_OR_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTIONS) - EIGEN_STATIC_ASSERT(ProductIsValid || !(SameSizes && !AreVectors), - INVALID_MATRIX_PRODUCT__IF_YOU_WANTED_A_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTION) - EIGEN_STATIC_ASSERT(ProductIsValid || SameSizes, INVALID_MATRIX_PRODUCT) -#ifdef EIGEN_DEBUG_PRODUCT - internal::product_type::debug(); -#endif - return typename ProductReturnType::Type(derived(), other.derived()); -} - -/** \returns an expression of the matrix product of \c *this and \a other without implicit evaluation. - * - * The returned product will behave like any other expressions: the coefficients of the product will be - * computed once at a time as requested. This might be useful in some extremely rare cases when only - * a small and no coherent fraction of the result's coefficients have to be computed. - * - * \warning This version of the matrix product can be much much slower. So use it only if you know - * what you are doing and that you measured a true speed improvement. - * - * \sa operator*(const MatrixBase&) - */ -template -template -const typename LazyProductReturnType::Type -MatrixBase::lazyProduct(const MatrixBase &other) const -{ - enum { - ProductIsValid = Derived::ColsAtCompileTime==Dynamic - || OtherDerived::RowsAtCompileTime==Dynamic - || int(Derived::ColsAtCompileTime)==int(OtherDerived::RowsAtCompileTime), - AreVectors = Derived::IsVectorAtCompileTime && OtherDerived::IsVectorAtCompileTime, - SameSizes = EIGEN_PREDICATE_SAME_MATRIX_SIZE(Derived,OtherDerived) - }; - // note to the lost user: - // * for a dot product use: v1.dot(v2) - // * for a coeff-wise product use: v1.cwiseProduct(v2) - EIGEN_STATIC_ASSERT(ProductIsValid || !(AreVectors && SameSizes), - INVALID_VECTOR_VECTOR_PRODUCT__IF_YOU_WANTED_A_DOT_OR_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTIONS) - EIGEN_STATIC_ASSERT(ProductIsValid || !(SameSizes && !AreVectors), - INVALID_MATRIX_PRODUCT__IF_YOU_WANTED_A_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTION) - EIGEN_STATIC_ASSERT(ProductIsValid || SameSizes, INVALID_MATRIX_PRODUCT) - - return typename LazyProductReturnType::Type(derived(), other.derived()); -} - #endif // EIGEN_PRODUCT_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/ProductBase.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/ProductBase.h index 233ed6467..6cf02a649 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/ProductBase.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/ProductBase.h @@ -25,6 +25,8 @@ #ifndef EIGEN_PRODUCTBASE_H #define EIGEN_PRODUCTBASE_H +namespace Eigen { + /** \class ProductBase * \ingroup Core_Module * @@ -115,10 +117,10 @@ class ProductBase : public MatrixBase inline void evalTo(Dest& dst) const { dst.setZero(); scaleAndAddTo(dst,Scalar(1)); } template - inline void addTo(Dest& dst) const { scaleAndAddTo(dst,1); } + inline void addTo(Dest& dst) const { scaleAndAddTo(dst,Scalar(1)); } template - inline void subTo(Dest& dst) const { scaleAndAddTo(dst,-1); } + inline void subTo(Dest& dst) const { scaleAndAddTo(dst,Scalar(-1)); } template inline void scaleAndAddTo(Dest& dst,Scalar alpha) const { derived().scaleAndAddTo(dst,alpha); } @@ -152,7 +154,8 @@ class ProductBase : public MatrixBase #else EIGEN_STATIC_ASSERT_SIZE_1x1(Derived) eigen_assert(this->rows() == 1 && this->cols() == 1); - return derived().coeff(row,col); + Matrix result = *this; + return result.coeff(row,col); #endif } @@ -160,7 +163,8 @@ class ProductBase : public MatrixBase { EIGEN_STATIC_ASSERT_SIZE_1x1(Derived) eigen_assert(this->rows() == 1 && this->cols() == 1); - return derived().coeff(i); + Matrix result = *this; + return result.coeff(i); } const Scalar& coeffRef(Index row, Index col) const @@ -179,8 +183,8 @@ class ProductBase : public MatrixBase protected: - const LhsNested m_lhs; - const RhsNested m_rhs; + LhsNested m_lhs; + RhsNested m_rhs; mutable PlainObject m_result; }; @@ -284,5 +288,6 @@ Derived& MatrixBase::lazyAssign(const ProductBase struct scalar_random_op { @@ -160,4 +162,6 @@ PlainObjectBase::setRandom(Index rows, Index cols) return setRandom(); } +} // end namespace Eigen + #endif // EIGEN_RANDOM_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/Redux.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/Redux.h index f9f5a95d5..d66ff00c1 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/Redux.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/Redux.h @@ -26,6 +26,8 @@ #ifndef EIGEN_REDUX_H #define EIGEN_REDUX_H +namespace Eigen { + namespace internal { // TODO @@ -95,7 +97,7 @@ struct redux_novec_unroller typedef typename Derived::Scalar Scalar; - EIGEN_STRONG_INLINE static Scalar run(const Derived &mat, const Func& func) + static EIGEN_STRONG_INLINE Scalar run(const Derived &mat, const Func& func) { return func(redux_novec_unroller::run(mat,func), redux_novec_unroller::run(mat,func)); @@ -112,7 +114,7 @@ struct redux_novec_unroller typedef typename Derived::Scalar Scalar; - EIGEN_STRONG_INLINE static Scalar run(const Derived &mat, const Func&) + static EIGEN_STRONG_INLINE Scalar run(const Derived &mat, const Func&) { return mat.coeffByOuterInner(outer, inner); } @@ -125,7 +127,7 @@ template struct redux_novec_unroller { typedef typename Derived::Scalar Scalar; - EIGEN_STRONG_INLINE static Scalar run(const Derived&, const Func&) { return Scalar(); } + static EIGEN_STRONG_INLINE Scalar run(const Derived&, const Func&) { return Scalar(); } }; /*** vectorization ***/ @@ -141,7 +143,7 @@ struct redux_vec_unroller typedef typename Derived::Scalar Scalar; typedef typename packet_traits::type PacketScalar; - EIGEN_STRONG_INLINE static PacketScalar run(const Derived &mat, const Func& func) + static EIGEN_STRONG_INLINE PacketScalar run(const Derived &mat, const Func& func) { return func.packetOp( redux_vec_unroller::run(mat,func), @@ -162,7 +164,7 @@ struct redux_vec_unroller typedef typename Derived::Scalar Scalar; typedef typename packet_traits::type PacketScalar; - EIGEN_STRONG_INLINE static PacketScalar run(const Derived &mat, const Func&) + static EIGEN_STRONG_INLINE PacketScalar run(const Derived &mat, const Func&) { return mat.template packetByOuterInner(outer, inner); } @@ -214,20 +216,33 @@ struct redux_impl const Index size = mat.size(); eigen_assert(size && "you are using an empty matrix"); const Index packetSize = packet_traits::size; - const Index alignedStart = first_aligned(mat); + const Index alignedStart = internal::first_aligned(mat); enum { alignment = bool(Derived::Flags & DirectAccessBit) || bool(Derived::Flags & AlignedBit) ? Aligned : Unaligned }; - const Index alignedSize = ((size-alignedStart)/packetSize)*packetSize; - const Index alignedEnd = alignedStart + alignedSize; + const Index alignedSize2 = ((size-alignedStart)/(2*packetSize))*(2*packetSize); + const Index alignedSize = ((size-alignedStart)/(packetSize))*(packetSize); + const Index alignedEnd2 = alignedStart + alignedSize2; + const Index alignedEnd = alignedStart + alignedSize; Scalar res; if(alignedSize) { - PacketScalar packet_res = mat.template packet(alignedStart); - for(Index index = alignedStart + packetSize; index < alignedEnd; index += packetSize) - packet_res = func.packetOp(packet_res, mat.template packet(index)); - res = func.predux(packet_res); + PacketScalar packet_res0 = mat.template packet(alignedStart); + if(alignedSize>packetSize) // we have at least two packets to partly unroll the loop + { + PacketScalar packet_res1 = mat.template packet(alignedStart+packetSize); + for(Index index = alignedStart + 2*packetSize; index < alignedEnd2; index += 2*packetSize) + { + packet_res0 = func.packetOp(packet_res0, mat.template packet(index)); + packet_res1 = func.packetOp(packet_res1, mat.template packet(index+packetSize)); + } + + packet_res0 = func.packetOp(packet_res0,packet_res1); + if(alignedEnd>alignedEnd2) + packet_res0 = func.packetOp(packet_res0, mat.template packet(alignedEnd2)); + } + res = func.predux(packet_res0); for(Index index = 0; index < alignedStart; ++index) res = func(res,mat.coeff(index)); @@ -296,7 +311,7 @@ struct redux_impl Size = Derived::SizeAtCompileTime, VectorizedSize = (Size / PacketSize) * PacketSize }; - EIGEN_STRONG_INLINE static Scalar run(const Derived& mat, const Func& func) + static EIGEN_STRONG_INLINE Scalar run(const Derived& mat, const Func& func) { eigen_assert(mat.rows()>0 && mat.cols()>0 && "you are using an empty matrix"); Scalar res = func.predux(redux_vec_unroller::run(mat,func)); @@ -401,4 +416,6 @@ MatrixBase::trace() const return derived().diagonal().sum(); } +} // end namespace Eigen + #endif // EIGEN_REDUX_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/Replicate.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/Replicate.h index d2f9712db..79e3578df 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/Replicate.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/Replicate.h @@ -25,6 +25,8 @@ #ifndef EIGEN_REPLICATE_H #define EIGEN_REPLICATE_H +namespace Eigen { + /** * \class Replicate * \ingroup Core_Module @@ -48,7 +50,10 @@ struct traits > typedef typename MatrixType::Scalar Scalar; typedef typename traits::StorageKind StorageKind; typedef typename traits::XprKind XprKind; - typedef typename nested::type MatrixTypeNested; + enum { + Factor = (RowFactor==Dynamic || ColFactor==Dynamic) ? Dynamic : RowFactor*ColFactor + }; + typedef typename nested::type MatrixTypeNested; typedef typename remove_reference::type _MatrixTypeNested; enum { RowsAtCompileTime = RowFactor==Dynamic || int(MatrixType::RowsAtCompileTime)==Dynamic @@ -72,6 +77,8 @@ struct traits > template class Replicate : public internal::dense_xpr_base< Replicate >::type { + typedef typename internal::traits::MatrixTypeNested MatrixTypeNested; + typedef typename internal::traits::_MatrixTypeNested _MatrixTypeNested; public: typedef typename internal::dense_xpr_base::type Base; @@ -87,7 +94,7 @@ template class Replicate } template - inline Replicate(const OriginalMatrixType& matrix, int rowFactor, int colFactor) + inline Replicate(const OriginalMatrixType& matrix, Index rowFactor, Index colFactor) : m_matrix(matrix), m_rowFactor(rowFactor), m_colFactor(colFactor) { EIGEN_STATIC_ASSERT((internal::is_same::type,OriginalMatrixType>::value), @@ -122,9 +129,13 @@ template class Replicate return m_matrix.template packet(actual_row, actual_col); } + const _MatrixTypeNested& nestedExpression() const + { + return m_matrix; + } protected: - const typename MatrixType::Nested m_matrix; + MatrixTypeNested m_matrix; const internal::variable_if_dynamic m_rowFactor; const internal::variable_if_dynamic m_colFactor; }; @@ -176,4 +187,6 @@ VectorwiseOp::replicate(Index factor) const (_expression(),Direction==Vertical?factor:1,Direction==Horizontal?factor:1); } +} // end namespace Eigen + #endif // EIGEN_REPLICATE_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/ReturnByValue.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/ReturnByValue.h index 24c5a4e21..24b6a3f6a 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/ReturnByValue.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/ReturnByValue.h @@ -26,6 +26,8 @@ #ifndef EIGEN_RETURNBYVALUE_H #define EIGEN_RETURNBYVALUE_H +namespace Eigen { + /** \class ReturnByValue * \ingroup Core_Module * @@ -96,4 +98,6 @@ Derived& DenseBase::operator=(const ReturnByValue& other) return derived(); } +} // end namespace Eigen + #endif // EIGEN_RETURNBYVALUE_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/Reverse.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/Reverse.h index 600744ae7..9e4e8a2bc 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/Reverse.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/Reverse.h @@ -27,6 +27,8 @@ #ifndef EIGEN_REVERSE_H #define EIGEN_REVERSE_H +namespace Eigen { + /** \class Reverse * \ingroup Core_Module * @@ -183,8 +185,14 @@ template class Reverse m_matrix.const_cast_derived().template writePacket(m_matrix.size() - index - PacketSize, internal::preverse(x)); } + const typename internal::remove_all::type& + nestedExpression() const + { + return m_matrix; + } + protected: - const typename MatrixType::Nested m_matrix; + typename MatrixType::Nested m_matrix; }; /** \returns an expression of the reverse of *this. @@ -226,5 +234,6 @@ inline void DenseBase::reverseInPlace() derived() = derived().reverse().eval(); } +} // end namespace Eigen #endif // EIGEN_REVERSE_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/Select.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/Select.h index d0cd66a26..92508a168 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/Select.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/Select.h @@ -25,6 +25,8 @@ #ifndef EIGEN_SELECT_H #define EIGEN_SELECT_H +namespace Eigen { + /** \class Select * \ingroup Core_Module * @@ -101,10 +103,25 @@ class Select : internal::no_assignment_operator, return m_else.coeff(i); } + const ConditionMatrixType& conditionMatrix() const + { + return m_condition; + } + + const ThenMatrixType& thenMatrix() const + { + return m_then; + } + + const ElseMatrixType& elseMatrix() const + { + return m_else; + } + protected: - const typename ConditionMatrixType::Nested m_condition; - const typename ThenMatrixType::Nested m_then; - const typename ElseMatrixType::Nested m_else; + typename ConditionMatrixType::Nested m_condition; + typename ThenMatrixType::Nested m_then; + typename ElseMatrixType::Nested m_else; }; @@ -155,4 +172,6 @@ DenseBase::select(typename ElseDerived::Scalar thenScalar, derived(), ElseDerived::Constant(rows(),cols(),thenScalar), elseMatrix.derived()); } +} // end namespace Eigen + #endif // EIGEN_SELECT_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/SelfAdjointView.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/SelfAdjointView.h index 4bb68755e..086f05c49 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/SelfAdjointView.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/SelfAdjointView.h @@ -25,6 +25,8 @@ #ifndef EIGEN_SELFADJOINTMATRIX_H #define EIGEN_SELFADJOINTMATRIX_H +namespace Eigen { + /** \class SelfAdjointView * \ingroup Core_Module * @@ -82,7 +84,7 @@ template class SelfAdjointView }; typedef typename MatrixType::PlainObject PlainObject; - inline SelfAdjointView(const MatrixType& matrix) : m_matrix(matrix) + inline SelfAdjointView(MatrixType& matrix) : m_matrix(matrix) {} inline Index rows() const { return m_matrix.rows(); } @@ -199,7 +201,7 @@ template class SelfAdjointView #endif protected: - const MatrixTypeNested m_matrix; + MatrixTypeNested m_matrix; }; @@ -222,7 +224,7 @@ struct triangular_assignment_selector::run(dst, src); @@ -236,7 +238,7 @@ struct triangular_assignment_selector struct triangular_assignment_selector { - inline static void run(Derived1 &, const Derived2 &) {} + static inline void run(Derived1 &, const Derived2 &) {} }; template @@ -247,7 +249,7 @@ struct triangular_assignment_selector::run(dst, src); @@ -261,14 +263,14 @@ struct triangular_assignment_selector struct triangular_assignment_selector { - inline static void run(Derived1 &, const Derived2 &) {} + static inline void run(Derived1 &, const Derived2 &) {} }; template struct triangular_assignment_selector { typedef typename Derived1::Index Index; - inline static void run(Derived1 &dst, const Derived2 &src) + static inline void run(Derived1 &dst, const Derived2 &src) { for(Index j = 0; j < dst.cols(); ++j) { @@ -285,7 +287,7 @@ struct triangular_assignment_selector struct triangular_assignment_selector { - inline static void run(Derived1 &dst, const Derived2 &src) + static inline void run(Derived1 &dst, const Derived2 &src) { typedef typename Derived1::Index Index; for(Index i = 0; i < dst.rows(); ++i) @@ -322,4 +324,6 @@ MatrixBase::selfadjointView() return derived(); } +} // end namespace Eigen + #endif // EIGEN_SELFADJOINTMATRIX_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/SelfCwiseBinaryOp.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/SelfCwiseBinaryOp.h index 4e9ca8874..99389d7e2 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/SelfCwiseBinaryOp.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/SelfCwiseBinaryOp.h @@ -25,6 +25,8 @@ #ifndef EIGEN_SELFCWISEBINARYOP_H #define EIGEN_SELFCWISEBINARYOP_H +namespace Eigen { + /** \class SelfCwiseBinaryOp * \ingroup Core_Module * @@ -163,6 +165,16 @@ template class SelfCwiseBinaryOp return Base::operator=(rhs); } + Lhs& expression() const + { + return m_matrix; + } + + const BinaryOp& functor() const + { + return m_functor; + } + protected: Lhs& m_matrix; const BinaryOp& m_functor; @@ -192,4 +204,6 @@ inline Derived& DenseBase::operator/=(const Scalar& other) return derived(); } +} // end namespace Eigen + #endif // EIGEN_SELFCWISEBINARYOP_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/SolveTriangular.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/SolveTriangular.h index a23014a34..ef09226a4 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/SolveTriangular.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/SolveTriangular.h @@ -25,6 +25,8 @@ #ifndef EIGEN_SOLVETRIANGULAR_H #define EIGEN_SOLVETRIANGULAR_H +namespace Eigen { + namespace internal { // Forward declarations: @@ -98,12 +100,22 @@ struct triangular_solver_selector typedef typename Rhs::Index Index; typedef blas_traits LhsProductTraits; typedef typename LhsProductTraits::DirectLinearAccessType ActualLhsType; + static void run(const Lhs& lhs, Rhs& rhs) { - const ActualLhsType actualLhs = LhsProductTraits::extract(lhs); + typename internal::add_const_on_value_type::type actualLhs = LhsProductTraits::extract(lhs); + + const Index size = lhs.rows(); + const Index othersize = Side==OnTheLeft? rhs.cols() : rhs.rows(); + + typedef internal::gemm_blocking_space<(Rhs::Flags&RowMajorBit) ? RowMajor : ColMajor,Scalar,Scalar, + Rhs::MaxRowsAtCompileTime, Rhs::MaxColsAtCompileTime, Lhs::MaxRowsAtCompileTime,4> BlockingType; + + BlockingType blocking(rhs.rows(), rhs.cols(), size); + triangular_solve_matrix - ::run(lhs.rows(), Side==OnTheLeft? rhs.cols() : rhs.rows(), &actualLhs.coeffRef(0,0), actualLhs.outerStride(), &rhs.coeffRef(0,0), rhs.outerStride()); + ::run(size, othersize, &actualLhs.coeffRef(0,0), actualLhs.outerStride(), &rhs.coeffRef(0,0), rhs.outerStride(), blocking); } }; @@ -177,10 +189,8 @@ template void TriangularView::solveInPlace(const MatrixBase& _other) const { OtherDerived& other = _other.const_cast_derived(); - eigen_assert(cols() == rows()); - eigen_assert( (Side==OnTheLeft && cols() == other.rows()) || (Side==OnTheRight && cols() == other.cols()) ); - eigen_assert(!(Mode & ZeroDiag)); - eigen_assert((Mode & (Upper|Lower)) != 0); + eigen_assert( cols() == rows() && ((Side==OnTheLeft && cols() == other.rows()) || (Side==OnTheRight && cols() == other.cols())) ); + eigen_assert((!(Mode & ZeroDiag)) && bool(Mode & (Upper|Lower))); enum { copy = internal::traits::Flags & RowMajorBit && OtherDerived::IsVectorAtCompileTime }; typedef typename internal::conditional struct triangular_solv protected: const TriangularType& m_triangularMatrix; - const typename Rhs::Nested m_rhs; + typename Rhs::Nested m_rhs; }; } // namespace internal +} // end namespace Eigen + #endif // EIGEN_SOLVETRIANGULAR_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/StableNorm.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/StableNorm.h index f667272e4..16514c86a 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/StableNorm.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/StableNorm.h @@ -25,6 +25,8 @@ #ifndef EIGEN_STABLENORM_H #define EIGEN_STABLENORM_H +namespace Eigen { + namespace internal { template inline void stable_norm_kernel(const ExpressionType& bl, Scalar& ssq, Scalar& scale, Scalar& invScale) @@ -58,9 +60,9 @@ MatrixBase::stableNorm() const { using std::min; const Index blockSize = 4096; - RealScalar scale = 0; - RealScalar invScale = 1; - RealScalar ssq = 0; // sum of square + RealScalar scale(0); + RealScalar invScale(1); + RealScalar ssq(0); // sum of square enum { Alignment = (int(Flags)&DirectAccessBit) || (int(Flags)&AlignedBit) ? 1 : 0 }; @@ -187,4 +189,6 @@ MatrixBase::hypotNorm() const return this->cwiseAbs().redux(internal::scalar_hypot_op()); } +} // end namespace Eigen + #endif // EIGEN_STABLENORM_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/Stride.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/Stride.h index 0430f1116..73c54e6bf 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/Stride.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/Stride.h @@ -25,6 +25,8 @@ #ifndef EIGEN_STRIDE_H #define EIGEN_STRIDE_H +namespace Eigen { + /** \class Stride * \ingroup Core_Module * @@ -116,4 +118,6 @@ class OuterStride : public Stride OuterStride(Index v) : Base(v,0) {} }; +} // end namespace Eigen + #endif // EIGEN_STRIDE_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/Swap.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/Swap.h index 5fb032866..deb1d2831 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/Swap.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/Swap.h @@ -25,6 +25,8 @@ #ifndef EIGEN_SWAP_H #define EIGEN_SWAP_H +namespace Eigen { + /** \class SwapWrapper * \ingroup Core_Module * @@ -52,6 +54,15 @@ template class SwapWrapper inline Index cols() const { return m_expression.cols(); } inline Index outerStride() const { return m_expression.outerStride(); } inline Index innerStride() const { return m_expression.innerStride(); } + + typedef typename internal::conditional< + internal::is_lvalue::value, + Scalar, + const Scalar + >::type ScalarWithConstIfNotLvalue; + + inline ScalarWithConstIfNotLvalue* data() { return m_expression.data(); } + inline const Scalar* data() const { return m_expression.data(); } inline Scalar& coeffRef(Index row, Index col) { @@ -119,8 +130,12 @@ template class SwapWrapper _other.template writePacket(index, tmp); } + ExpressionType& expression() const { return m_expression; } + protected: ExpressionType& m_expression; }; +} // end namespace Eigen + #endif // EIGEN_SWAP_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/Transpose.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/Transpose.h index 3f7c7df6e..c62f74764 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/Transpose.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/Transpose.h @@ -26,6 +26,8 @@ #ifndef EIGEN_TRANSPOSE_H #define EIGEN_TRANSPOSE_H +namespace Eigen { + /** \class Transpose * \ingroup Core_Module * @@ -91,7 +93,7 @@ template class Transpose nestedExpression() { return m_matrix.const_cast_derived(); } protected: - const typename MatrixType::Nested m_matrix; + typename MatrixType::Nested m_matrix; }; namespace internal { @@ -152,12 +154,12 @@ template class TransposeImpl return derived().nestedExpression().coeffRef(index); } - inline const CoeffReturnType coeff(Index row, Index col) const + inline CoeffReturnType coeff(Index row, Index col) const { return derived().nestedExpression().coeff(col, row); } - inline const CoeffReturnType coeff(Index index) const + inline CoeffReturnType coeff(Index index) const { return derived().nestedExpression().coeff(index); } @@ -422,4 +424,6 @@ void DenseBase::checkTransposeAliasing(const OtherDerived& other) const } #endif +} // end namespace Eigen + #endif // EIGEN_TRANSPOSE_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/Transpositions.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/Transpositions.h index 88fdfb222..fa37822f8 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/Transpositions.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/Transpositions.h @@ -25,6 +25,8 @@ #ifndef EIGEN_TRANSPOSITIONS_H #define EIGEN_TRANSPOSITIONS_H +namespace Eigen { + /** \class Transpositions * \ingroup Core_Module * @@ -404,7 +406,7 @@ struct transposition_matrix_product_retval protected: const TranspositionType& m_transpositions; - const typename MatrixType::Nested m_matrix; + typename MatrixType::Nested m_matrix; }; } // end namespace internal @@ -444,4 +446,6 @@ class Transpose > const TranspositionType& m_transpositions; }; +} // end namespace Eigen + #endif // EIGEN_TRANSPOSITIONS_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/TriangularMatrix.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/TriangularMatrix.h index 033e81036..5e97e4052 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/TriangularMatrix.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/TriangularMatrix.h @@ -26,6 +26,8 @@ #ifndef EIGEN_TRIANGULARMATRIX_H #define EIGEN_TRIANGULARMATRIX_H +namespace Eigen { + namespace internal { template struct triangular_solve_retval; @@ -273,11 +275,8 @@ template class TriangularView inline const TriangularView conjugate() const { return m_matrix.conjugate(); } - /** \sa MatrixBase::adjoint() */ - inline TriangularView adjoint() - { return m_matrix.adjoint(); } /** \sa MatrixBase::adjoint() const */ - inline const TriangularView adjoint() const + inline const TriangularView adjoint() const { return m_matrix.adjoint(); } /** \sa MatrixBase::transpose() */ @@ -288,11 +287,13 @@ template class TriangularView } /** \sa MatrixBase::transpose() const */ inline const TriangularView,TransposeMode> transpose() const - { return m_matrix.transpose(); } + { + return m_matrix.transpose(); + } /** Efficient triangular matrix times vector/matrix product */ template - TriangularProduct + TriangularProduct operator*(const MatrixBase& rhs) const { return TriangularProduct @@ -375,7 +376,8 @@ template class TriangularView template void swap(MatrixBase const & other) { - TriangularView,Mode>(const_cast(m_matrix)).lazyAssign(other.derived()); + SwapWrapper swaper(const_cast(m_matrix)); + TriangularView,Mode>(swaper).lazyAssign(other.derived()); } Scalar determinant() const @@ -433,7 +435,7 @@ template class TriangularView template EIGEN_STRONG_INLINE TriangularView& assignProduct(const ProductBase& prod, const Scalar& alpha); - const MatrixTypeNested m_matrix; + MatrixTypeNested m_matrix; }; /*************************************************************************** @@ -452,7 +454,7 @@ struct triangular_assignment_selector typedef typename Derived1::Scalar Scalar; - inline static void run(Derived1 &dst, const Derived2 &src) + static inline void run(Derived1 &dst, const Derived2 &src) { triangular_assignment_selector::run(dst, src); @@ -480,7 +482,7 @@ struct triangular_assignment_selector template struct triangular_assignment_selector { - inline static void run(Derived1 &, const Derived2 &) {} + static inline void run(Derived1 &, const Derived2 &) {} }; template @@ -488,7 +490,7 @@ struct triangular_assignment_selector struct triangular_assignment_selector { typedef typename Derived1::Index Index; - inline static void run(Derived1 &dst, const Derived2 &src) + static inline void run(Derived1 &dst, const Derived2 &src) { for(Index j = 0; j < dst.cols(); ++j) { @@ -524,7 +526,7 @@ template struct triangular_assignment_selector { typedef typename Derived1::Index Index; - inline static void run(Derived1 &dst, const Derived2 &src) + static inline void run(Derived1 &dst, const Derived2 &src) { for(Index j = 0; j < dst.cols(); ++j) { @@ -542,7 +544,7 @@ template struct triangular_assignment_selector { typedef typename Derived1::Index Index; - inline static void run(Derived1 &dst, const Derived2 &src) + static inline void run(Derived1 &dst, const Derived2 &src) { for(Index j = 0; j < dst.cols(); ++j) { @@ -560,7 +562,7 @@ template struct triangular_assignment_selector { typedef typename Derived1::Index Index; - inline static void run(Derived1 &dst, const Derived2 &src) + static inline void run(Derived1 &dst, const Derived2 &src) { for(Index j = 0; j < dst.cols(); ++j) { @@ -580,7 +582,7 @@ template struct triangular_assignment_selector { typedef typename Derived1::Index Index; - inline static void run(Derived1 &dst, const Derived2 &src) + static inline void run(Derived1 &dst, const Derived2 &src) { for(Index j = 0; j < dst.cols(); ++j) { @@ -835,4 +837,6 @@ bool MatrixBase::isLowerTriangular(RealScalar prec) const return true; } +} // end namespace Eigen + #endif // EIGEN_TRIANGULARMATRIX_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/VectorBlock.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/VectorBlock.h index 858e4c786..66c9fd21a 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/VectorBlock.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/VectorBlock.h @@ -26,6 +26,8 @@ #ifndef EIGEN_VECTORBLOCK_H #define EIGEN_VECTORBLOCK_H +namespace Eigen { + /** \class VectorBlock * \ingroup Core_Module * @@ -292,5 +294,6 @@ DenseBase::tail() const return typename ConstFixedSegmentReturnType::Type(derived(), size() - Size); } +} // end namespace Eigen #endif // EIGEN_VECTORBLOCK_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/VectorwiseOp.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/VectorwiseOp.h index 20f688157..7b5be7cd5 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/VectorwiseOp.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/VectorwiseOp.h @@ -26,6 +26,8 @@ #ifndef EIGEN_PARTIAL_REDUX_H #define EIGEN_PARTIAL_REDUX_H +namespace Eigen { + /** \class PartialReduxExpr * \ingroup Core_Module * @@ -110,7 +112,7 @@ class PartialReduxExpr : internal::no_assignment_operator, } protected: - const MatrixTypeNested m_matrix; + MatrixTypeNested m_matrix; const MemberOp m_functor; }; @@ -237,7 +239,10 @@ template class VectorwiseOp typename ExtendedType::Type extendedTo(const DenseBase& other) const { - EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived); + EIGEN_STATIC_ASSERT(EIGEN_IMPLIES(Direction==Vertical, OtherDerived::MaxColsAtCompileTime==1), + YOU_PASSED_A_ROW_VECTOR_BUT_A_COLUMN_VECTOR_WAS_EXPECTED) + EIGEN_STATIC_ASSERT(EIGEN_IMPLIES(Direction==Horizontal, OtherDerived::MaxRowsAtCompileTime==1), + YOU_PASSED_A_COLUMN_VECTOR_BUT_A_ROW_VECTOR_WAS_EXPECTED) return typename ExtendedType::Type (other.derived(), Direction==Vertical ? 1 : m_matrix.rows(), @@ -418,10 +423,9 @@ template class VectorwiseOp ExpressionType& operator=(const DenseBase& other) { EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived) + EIGEN_STATIC_ASSERT_SAME_XPR_KIND(ExpressionType, OtherDerived) //eigen_assert((m_matrix.isNull()) == (other.isNull())); FIXME - for(Index j=0; j(m_matrix); + return const_cast(m_matrix = extendedTo(other.derived())); } /** Adds the vector \a other to each subvector of \c *this */ @@ -429,9 +433,8 @@ template class VectorwiseOp ExpressionType& operator+=(const DenseBase& other) { EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived) - for(Index j=0; j(m_matrix); + EIGEN_STATIC_ASSERT_SAME_XPR_KIND(ExpressionType, OtherDerived) + return const_cast(m_matrix += extendedTo(other.derived())); } /** Substracts the vector \a other to each subvector of \c *this */ @@ -439,8 +442,29 @@ template class VectorwiseOp ExpressionType& operator-=(const DenseBase& other) { EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived) - for(Index j=0; j(m_matrix -= extendedTo(other.derived())); + } + + /** Multiples each subvector of \c *this by the vector \a other */ + template + ExpressionType& operator*=(const DenseBase& other) + { + EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived) + EIGEN_STATIC_ASSERT_ARRAYXPR(ExpressionType) + EIGEN_STATIC_ASSERT_SAME_XPR_KIND(ExpressionType, OtherDerived) + m_matrix *= extendedTo(other.derived()); + return const_cast(m_matrix); + } + + /** Divides each subvector of \c *this by the vector \a other */ + template + ExpressionType& operator/=(const DenseBase& other) + { + EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived) + EIGEN_STATIC_ASSERT_ARRAYXPR(ExpressionType) + EIGEN_STATIC_ASSERT_SAME_XPR_KIND(ExpressionType, OtherDerived) + m_matrix /= extendedTo(other.derived()); return const_cast(m_matrix); } @@ -451,7 +475,8 @@ template class VectorwiseOp const typename ExtendedType::Type> operator+(const DenseBase& other) const { - EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived); + EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived) + EIGEN_STATIC_ASSERT_SAME_XPR_KIND(ExpressionType, OtherDerived) return m_matrix + extendedTo(other.derived()); } @@ -462,10 +487,39 @@ template class VectorwiseOp const typename ExtendedType::Type> operator-(const DenseBase& other) const { - EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived); + EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived) + EIGEN_STATIC_ASSERT_SAME_XPR_KIND(ExpressionType, OtherDerived) return m_matrix - extendedTo(other.derived()); } + /** Returns the expression where each subvector is the product of the vector \a other + * by the corresponding subvector of \c *this */ + template EIGEN_STRONG_INLINE + CwiseBinaryOp, + const ExpressionTypeNestedCleaned, + const typename ExtendedType::Type> + operator*(const DenseBase& other) const + { + EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived) + EIGEN_STATIC_ASSERT_ARRAYXPR(ExpressionType) + EIGEN_STATIC_ASSERT_SAME_XPR_KIND(ExpressionType, OtherDerived) + return m_matrix * extendedTo(other.derived()); + } + + /** Returns the expression where each subvector is the quotient of the corresponding + * subvector of \c *this by the vector \a other */ + template + CwiseBinaryOp, + const ExpressionTypeNestedCleaned, + const typename ExtendedType::Type> + operator/(const DenseBase& other) const + { + EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived) + EIGEN_STATIC_ASSERT_ARRAYXPR(ExpressionType) + EIGEN_STATIC_ASSERT_SAME_XPR_KIND(ExpressionType, OtherDerived) + return m_matrix / extendedTo(other.derived()); + } + /////////// Geometry module /////////// #if EIGEN2_SUPPORT_STAGE > STAGE20_RESOLVE_API_CONFLICTS @@ -509,7 +563,7 @@ template class VectorwiseOp * Example: \include MatrixBase_colwise.cpp * Output: \verbinclude MatrixBase_colwise.out * - * \sa rowwise(), class VectorwiseOp + * \sa rowwise(), class VectorwiseOp, \ref TutorialReductionsVisitorsBroadcasting */ template inline const typename DenseBase::ConstColwiseReturnType @@ -520,7 +574,7 @@ DenseBase::colwise() const /** \returns a writable VectorwiseOp wrapper of *this providing additional partial reduction operations * - * \sa rowwise(), class VectorwiseOp + * \sa rowwise(), class VectorwiseOp, \ref TutorialReductionsVisitorsBroadcasting */ template inline typename DenseBase::ColwiseReturnType @@ -534,7 +588,7 @@ DenseBase::colwise() * Example: \include MatrixBase_rowwise.cpp * Output: \verbinclude MatrixBase_rowwise.out * - * \sa colwise(), class VectorwiseOp + * \sa colwise(), class VectorwiseOp, \ref TutorialReductionsVisitorsBroadcasting */ template inline const typename DenseBase::ConstRowwiseReturnType @@ -545,7 +599,7 @@ DenseBase::rowwise() const /** \returns a writable VectorwiseOp wrapper of *this providing additional partial reduction operations * - * \sa colwise(), class VectorwiseOp + * \sa colwise(), class VectorwiseOp, \ref TutorialReductionsVisitorsBroadcasting */ template inline typename DenseBase::RowwiseReturnType @@ -554,4 +608,6 @@ DenseBase::rowwise() return derived(); } +} // end namespace Eigen + #endif // EIGEN_PARTIAL_REDUX_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/Visitor.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/Visitor.h index 378ebcba1..fd04fd978 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/Visitor.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/Visitor.h @@ -25,6 +25,8 @@ #ifndef EIGEN_VISITOR_H #define EIGEN_VISITOR_H +namespace Eigen { + namespace internal { template @@ -35,7 +37,7 @@ struct visitor_impl row = (UnrollCount-1) % Derived::RowsAtCompileTime }; - inline static void run(const Derived &mat, Visitor& visitor) + static inline void run(const Derived &mat, Visitor& visitor) { visitor_impl::run(mat, visitor); visitor(mat.coeff(row, col), row, col); @@ -45,7 +47,7 @@ struct visitor_impl template struct visitor_impl { - inline static void run(const Derived &mat, Visitor& visitor) + static inline void run(const Derived &mat, Visitor& visitor) { return visitor.init(mat.coeff(0, 0), 0, 0); } @@ -55,7 +57,7 @@ template struct visitor_impl { typedef typename Derived::Index Index; - inline static void run(const Derived& mat, Visitor& visitor) + static inline void run(const Derived& mat, Visitor& visitor) { visitor.init(mat.coeff(0,0), 0, 0); for(Index i = 1; i < mat.rows(); ++i) @@ -245,4 +247,6 @@ DenseBase::maxCoeff(IndexType* index) const return maxVisitor.res; } +} // end namespace Eigen + #endif // EIGEN_VISITOR_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/arch/AltiVec/Complex.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/arch/AltiVec/Complex.h index f8adf1b63..b2d866b71 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/arch/AltiVec/Complex.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/arch/AltiVec/Complex.h @@ -25,6 +25,8 @@ #ifndef EIGEN_COMPLEX_ALTIVEC_H #define EIGEN_COMPLEX_ALTIVEC_H +namespace Eigen { + namespace internal { static Packet4ui p4ui_CONJ_XOR = vec_mergeh((Packet4ui)p4i_ZERO, (Packet4ui)p4f_ZERO_);//{ 0x00000000, 0x80000000, 0x00000000, 0x80000000 }; @@ -168,7 +170,7 @@ template<> EIGEN_STRONG_INLINE std::complex predux_mul(const P template struct palign_impl { - EIGEN_STRONG_INLINE static void run(Packet2cf& first, const Packet2cf& second) + static EIGEN_STRONG_INLINE void run(Packet2cf& first, const Packet2cf& second) { if (Offset==1) { @@ -225,4 +227,6 @@ template<> EIGEN_STRONG_INLINE Packet2cf pcplxflip(const Packet2cf& x } // end namespace internal +} // end namespace Eigen + #endif // EIGEN_COMPLEX_ALTIVEC_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/arch/AltiVec/PacketMath.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/arch/AltiVec/PacketMath.h index dc34ebbd6..5b62b4c31 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/arch/AltiVec/PacketMath.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/arch/AltiVec/PacketMath.h @@ -25,6 +25,8 @@ #ifndef EIGEN_PACKET_MATH_ALTIVEC_H #define EIGEN_PACKET_MATH_ALTIVEC_H +namespace Eigen { + namespace internal { #ifndef EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD @@ -487,7 +489,7 @@ template<> EIGEN_STRONG_INLINE int predux_max(const Packet4i& a) template struct palign_impl { - EIGEN_STRONG_INLINE static void run(Packet4f& first, const Packet4f& second) + static EIGEN_STRONG_INLINE void run(Packet4f& first, const Packet4f& second) { if (Offset!=0) first = vec_sld(first, second, Offset*4); @@ -497,7 +499,7 @@ struct palign_impl template struct palign_impl { - EIGEN_STRONG_INLINE static void run(Packet4i& first, const Packet4i& second) + static EIGEN_STRONG_INLINE void run(Packet4i& first, const Packet4i& second) { if (Offset!=0) first = vec_sld(first, second, Offset*4); @@ -506,4 +508,6 @@ struct palign_impl } // end namespace internal +} // end namespace Eigen + #endif // EIGEN_PACKET_MATH_ALTIVEC_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/arch/NEON/Complex.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/arch/NEON/Complex.h index 212887184..72abb6f4a 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/arch/NEON/Complex.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/arch/NEON/Complex.h @@ -25,6 +25,8 @@ #ifndef EIGEN_COMPLEX_NEON_H #define EIGEN_COMPLEX_NEON_H +namespace Eigen { + namespace internal { static uint32x4_t p4ui_CONJ_XOR = EIGEN_INIT_NEON_PACKET4(0x00000000, 0x80000000, 0x00000000, 0x80000000); @@ -267,4 +269,6 @@ template<> EIGEN_STRONG_INLINE Packet2cf pdiv(const Packet2cf& a, con } // end namespace internal +} // end namespace Eigen + #endif // EIGEN_COMPLEX_NEON_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/arch/NEON/PacketMath.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/arch/NEON/PacketMath.h index 6c7cd1590..1eb082a5b 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/arch/NEON/PacketMath.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/arch/NEON/PacketMath.h @@ -27,6 +27,8 @@ #ifndef EIGEN_PACKET_MATH_NEON_H #define EIGEN_PACKET_MATH_NEON_H +namespace Eigen { + namespace internal { #ifndef EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD @@ -158,7 +160,8 @@ template<> EIGEN_STRONG_INLINE Packet4i pdiv(const Packet4i& /*a*/, co } // for some weird raisons, it has to be overloaded for packet of integers -template<> EIGEN_STRONG_INLINE Packet4i pmadd(const Packet4i& a, const Packet4i& b, const Packet4i& c) { return padd(pmul(a,b), c); } +template<> EIGEN_STRONG_INLINE Packet4f pmadd(const Packet4f& a, const Packet4f& b, const Packet4f& c) { return vmlaq_f32(c,a,b); } +template<> EIGEN_STRONG_INLINE Packet4i pmadd(const Packet4i& a, const Packet4i& b, const Packet4i& c) { return vmlaq_s32(c,a,b); } template<> EIGEN_STRONG_INLINE Packet4f pmin(const Packet4f& a, const Packet4f& b) { return vminq_f32(a,b); } template<> EIGEN_STRONG_INLINE Packet4i pmin(const Packet4i& a, const Packet4i& b) { return vminq_s32(a,b); } @@ -431,4 +434,6 @@ PALIGN_NEON(3,Packet4i,vextq_s32) } // end namespace internal +} // end namespace Eigen + #endif // EIGEN_PACKET_MATH_NEON_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/arch/SSE/Complex.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/arch/SSE/Complex.h index c352bb3e6..1615886ac 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/arch/SSE/Complex.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/arch/SSE/Complex.h @@ -25,6 +25,8 @@ #ifndef EIGEN_COMPLEX_SSE_H #define EIGEN_COMPLEX_SSE_H +namespace Eigen { + namespace internal { //---------- float ---------- @@ -102,7 +104,7 @@ template<> EIGEN_STRONG_INLINE Packet2cf pset1(const std::complex(&from)); #else res.v = _mm_loadl_pi(res.v, (const __m64*)&from); #endif @@ -151,7 +153,7 @@ template<> EIGEN_STRONG_INLINE std::complex predux_mul(const P template struct palign_impl { - EIGEN_STRONG_INLINE static void run(Packet2cf& first, const Packet2cf& second) + static EIGEN_STRONG_INLINE void run(Packet2cf& first, const Packet2cf& second) { if (Offset==1) { @@ -350,7 +352,7 @@ template<> EIGEN_STRONG_INLINE std::complex predux_mul(const template struct palign_impl { - EIGEN_STRONG_INLINE static void run(Packet1cd& /*first*/, const Packet1cd& /*second*/) + static EIGEN_STRONG_INLINE void run(Packet1cd& /*first*/, const Packet1cd& /*second*/) { // FIXME is it sure we never have to align a Packet1cd? // Even though a std::complex has 16 bytes, it is not necessarily aligned on a 16 bytes boundary... @@ -444,4 +446,6 @@ EIGEN_STRONG_INLINE Packet1cd pcplxflip/**/(const Packet1cd& x) } // end namespace internal +} // end namespace Eigen + #endif // EIGEN_COMPLEX_SSE_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/arch/SSE/MathFunctions.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/arch/SSE/MathFunctions.h index 9d56d8218..de2f06d5f 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/arch/SSE/MathFunctions.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/arch/SSE/MathFunctions.h @@ -30,6 +30,8 @@ #ifndef EIGEN_MATH_FUNCTIONS_SSE_H #define EIGEN_MATH_FUNCTIONS_SSE_H +namespace Eigen { + namespace internal { template<> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED @@ -121,7 +123,7 @@ Packet4f pexp(const Packet4f& _x) _EIGEN_DECLARE_CONST_Packet4i(0x7f, 0x7f); - _EIGEN_DECLARE_CONST_Packet4f(exp_hi, 88.3762626647949f); + _EIGEN_DECLARE_CONST_Packet4f(exp_hi, 88.3762626647950f); _EIGEN_DECLARE_CONST_Packet4f(exp_lo, -88.3762626647949f); _EIGEN_DECLARE_CONST_Packet4f(cephes_LOG2EF, 1.44269504088896341f); @@ -168,7 +170,7 @@ Packet4f pexp(const Packet4f& _x) y = pmadd(y, z, x); y = padd(y, p4f_1); - /* build 2^n */ + // build 2^n emm0 = _mm_cvttps_epi32(fx); emm0 = _mm_add_epi32(emm0, p4i_0x7f); emm0 = _mm_slli_epi32(emm0, 23); @@ -392,4 +394,6 @@ Packet4f psqrt(const Packet4f& _x) } // end namespace internal +} // end namespace Eigen + #endif // EIGEN_MATH_FUNCTIONS_SSE_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/arch/SSE/PacketMath.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/arch/SSE/PacketMath.h index 908e27368..8faeeefc9 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/arch/SSE/PacketMath.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/arch/SSE/PacketMath.h @@ -25,6 +25,8 @@ #ifndef EIGEN_PACKET_MATH_SSE_H #define EIGEN_PACKET_MATH_SSE_H +namespace Eigen { + namespace internal { #ifndef EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD @@ -110,9 +112,18 @@ template<> struct unpacket_traits { typedef float type; enum {size=4} template<> struct unpacket_traits { typedef double type; enum {size=2}; }; template<> struct unpacket_traits { typedef int type; enum {size=4}; }; +#if defined(_MSC_VER) && (_MSC_VER==1500) +// Workaround MSVC 9 internal compiler error. +// TODO: It has been detected with win64 builds (amd64), so let's check whether it also happens in 32bits+SSE mode +// TODO: let's check whether there does not exist a better fix, like adding a pset0() function. (it crashed on pset1(0)). +template<> EIGEN_STRONG_INLINE Packet4f pset1(const float& from) { return _mm_set_ps(from,from,from,from); } +template<> EIGEN_STRONG_INLINE Packet2d pset1(const double& from) { return _mm_set_pd(from,from); } +template<> EIGEN_STRONG_INLINE Packet4i pset1(const int& from) { return _mm_set_epi32(from,from,from,from); } +#else template<> EIGEN_STRONG_INLINE Packet4f pset1(const float& from) { return _mm_set1_ps(from); } template<> EIGEN_STRONG_INLINE Packet2d pset1(const double& from) { return _mm_set1_pd(from); } template<> EIGEN_STRONG_INLINE Packet4i pset1(const int& from) { return _mm_set1_epi32(from); } +#endif template<> EIGEN_STRONG_INLINE Packet4f plset(const float& a) { return _mm_add_ps(pset1(a), _mm_set_ps(3,2,1,0)); } template<> EIGEN_STRONG_INLINE Packet2d plset(const double& a) { return _mm_add_pd(pset1(a),_mm_set_pd(1,0)); } @@ -282,7 +293,7 @@ template<> EIGEN_STRONG_INLINE Packet4i ploadu(const int* from) template<> EIGEN_STRONG_INLINE Packet4f ploaddup(const float* from) { - return vec4f_swizzle1(_mm_castpd_ps(_mm_load_sd((const double*)from)), 0, 0, 1, 1); + return vec4f_swizzle1(_mm_castpd_ps(_mm_load_sd(reinterpret_cast(from))), 0, 0, 1, 1); } template<> EIGEN_STRONG_INLINE Packet2d ploaddup(const double* from) { return pset1(from[0]); } @@ -302,8 +313,8 @@ template<> EIGEN_STRONG_INLINE void pstoreu(double* to, const Packet2d& _mm_storel_pd((to), from); _mm_storeh_pd((to+1), from); } -template<> EIGEN_STRONG_INLINE void pstoreu(float* to, const Packet4f& from) { EIGEN_DEBUG_UNALIGNED_STORE pstoreu((double*)to, _mm_castps_pd(from)); } -template<> EIGEN_STRONG_INLINE void pstoreu(int* to, const Packet4i& from) { EIGEN_DEBUG_UNALIGNED_STORE pstoreu((double*)to, _mm_castsi128_pd(from)); } +template<> EIGEN_STRONG_INLINE void pstoreu(float* to, const Packet4f& from) { EIGEN_DEBUG_UNALIGNED_STORE pstoreu(reinterpret_cast(to), _mm_castps_pd(from)); } +template<> EIGEN_STRONG_INLINE void pstoreu(int* to, const Packet4i& from) { EIGEN_DEBUG_UNALIGNED_STORE pstoreu(reinterpret_cast(to), _mm_castsi128_pd(from)); } // some compilers might be tempted to perform multiple moves instead of using a vector path. template<> EIGEN_STRONG_INLINE void pstore1(float* to, const float& a) @@ -541,7 +552,7 @@ template<> EIGEN_STRONG_INLINE int predux_max(const Packet4i& a) template struct palign_impl { - EIGEN_STRONG_INLINE static void run(Packet4f& first, const Packet4f& second) + static EIGEN_STRONG_INLINE void run(Packet4f& first, const Packet4f& second) { if (Offset!=0) first = _mm_castsi128_ps(_mm_alignr_epi8(_mm_castps_si128(second), _mm_castps_si128(first), Offset*4)); @@ -551,7 +562,7 @@ struct palign_impl template struct palign_impl { - EIGEN_STRONG_INLINE static void run(Packet4i& first, const Packet4i& second) + static EIGEN_STRONG_INLINE void run(Packet4i& first, const Packet4i& second) { if (Offset!=0) first = _mm_alignr_epi8(second,first, Offset*4); @@ -561,7 +572,7 @@ struct palign_impl template struct palign_impl { - EIGEN_STRONG_INLINE static void run(Packet2d& first, const Packet2d& second) + static EIGEN_STRONG_INLINE void run(Packet2d& first, const Packet2d& second) { if (Offset==1) first = _mm_castsi128_pd(_mm_alignr_epi8(_mm_castpd_si128(second), _mm_castpd_si128(first), 8)); @@ -572,7 +583,7 @@ struct palign_impl template struct palign_impl { - EIGEN_STRONG_INLINE static void run(Packet4f& first, const Packet4f& second) + static EIGEN_STRONG_INLINE void run(Packet4f& first, const Packet4f& second) { if (Offset==1) { @@ -595,7 +606,7 @@ struct palign_impl template struct palign_impl { - EIGEN_STRONG_INLINE static void run(Packet4i& first, const Packet4i& second) + static EIGEN_STRONG_INLINE void run(Packet4i& first, const Packet4i& second) { if (Offset==1) { @@ -618,7 +629,7 @@ struct palign_impl template struct palign_impl { - EIGEN_STRONG_INLINE static void run(Packet2d& first, const Packet2d& second) + static EIGEN_STRONG_INLINE void run(Packet2d& first, const Packet2d& second) { if (Offset==1) { @@ -631,4 +642,6 @@ struct palign_impl } // end namespace internal +} // end namespace Eigen + #endif // EIGEN_PACKET_MATH_SSE_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/products/CoeffBasedProduct.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/products/CoeffBasedProduct.h index dc20f7e1e..8f53c43ad 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/products/CoeffBasedProduct.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/products/CoeffBasedProduct.h @@ -26,6 +26,8 @@ #ifndef EIGEN_COEFFBASED_PRODUCT_H #define EIGEN_COEFFBASED_PRODUCT_H +namespace Eigen { + namespace internal { /********************************************************************************* @@ -224,8 +226,8 @@ class CoeffBasedProduct { return reinterpret_cast(*this).diagonal(index); } protected: - const LhsNested m_lhs; - const RhsNested m_rhs; + typename internal::add_const_on_value_type::type m_lhs; + typename internal::add_const_on_value_type::type m_rhs; mutable PlainObject m_result; }; @@ -252,7 +254,7 @@ template struct product_coeff_impl { typedef typename Lhs::Index Index; - EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, RetScalar &res) + static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, RetScalar &res) { product_coeff_impl::run(row, col, lhs, rhs, res); res += lhs.coeff(row, UnrollingIndex) * rhs.coeff(UnrollingIndex, col); @@ -263,7 +265,7 @@ template struct product_coeff_impl { typedef typename Lhs::Index Index; - EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, RetScalar &res) + static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, RetScalar &res) { res = lhs.coeff(row, 0) * rhs.coeff(0, col); } @@ -273,7 +275,7 @@ template struct product_coeff_impl { typedef typename Lhs::Index Index; - EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, RetScalar& res) + static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, RetScalar& res) { eigen_assert(lhs.cols()>0 && "you are using a non initialized matrix"); res = lhs.coeff(row, 0) * rhs.coeff(0, col); @@ -291,7 +293,7 @@ struct product_coeff_vectorized_unroller { typedef typename Lhs::Index Index; enum { PacketSize = packet_traits::size }; - EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, typename Lhs::PacketScalar &pres) + static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, typename Lhs::PacketScalar &pres) { product_coeff_vectorized_unroller::run(row, col, lhs, rhs, pres); pres = padd(pres, pmul( lhs.template packet(row, UnrollingIndex) , rhs.template packet(UnrollingIndex, col) )); @@ -302,7 +304,7 @@ template struct product_coeff_vectorized_unroller<0, Lhs, Rhs, Packet> { typedef typename Lhs::Index Index; - EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, typename Lhs::PacketScalar &pres) + static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, typename Lhs::PacketScalar &pres) { pres = pmul(lhs.template packet(row, 0) , rhs.template packet(0, col)); } @@ -314,7 +316,7 @@ struct product_coeff_impl::size }; - EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, RetScalar &res) + static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, RetScalar &res) { Packet pres; product_coeff_vectorized_unroller::run(row, col, lhs, rhs, pres); @@ -327,7 +329,7 @@ template struct product_coeff_vectorized_dyn_selector { typedef typename Lhs::Index Index; - EIGEN_STRONG_INLINE static void run(Index /*row*/, Index col, const Lhs& lhs, const Rhs& rhs, typename Lhs::Scalar &res) + static EIGEN_STRONG_INLINE void run(Index /*row*/, Index col, const Lhs& lhs, const Rhs& rhs, typename Lhs::Scalar &res) { res = lhs.transpose().cwiseProduct(rhs.col(col)).sum(); } @@ -349,7 +351,7 @@ template struct product_coeff_vectorized_dyn_selector { typedef typename Lhs::Index Index; - EIGEN_STRONG_INLINE static void run(Index row, Index /*col*/, const Lhs& lhs, const Rhs& rhs, typename Lhs::Scalar &res) + static EIGEN_STRONG_INLINE void run(Index row, Index /*col*/, const Lhs& lhs, const Rhs& rhs, typename Lhs::Scalar &res) { res = lhs.row(row).transpose().cwiseProduct(rhs).sum(); } @@ -359,7 +361,7 @@ template struct product_coeff_vectorized_dyn_selector { typedef typename Lhs::Index Index; - EIGEN_STRONG_INLINE static void run(Index /*row*/, Index /*col*/, const Lhs& lhs, const Rhs& rhs, typename Lhs::Scalar &res) + static EIGEN_STRONG_INLINE void run(Index /*row*/, Index /*col*/, const Lhs& lhs, const Rhs& rhs, typename Lhs::Scalar &res) { res = lhs.transpose().cwiseProduct(rhs).sum(); } @@ -369,7 +371,7 @@ template struct product_coeff_impl { typedef typename Lhs::Index Index; - EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, typename Lhs::Scalar &res) + static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, typename Lhs::Scalar &res) { product_coeff_vectorized_dyn_selector::run(row, col, lhs, rhs, res); } @@ -383,7 +385,7 @@ template { typedef typename Lhs::Index Index; - EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Packet &res) + static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Packet &res) { product_packet_impl::run(row, col, lhs, rhs, res); res = pmadd(pset1(lhs.coeff(row, UnrollingIndex)), rhs.template packet(UnrollingIndex, col), res); @@ -394,7 +396,7 @@ template { typedef typename Lhs::Index Index; - EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Packet &res) + static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Packet &res) { product_packet_impl::run(row, col, lhs, rhs, res); res = pmadd(lhs.template packet(row, UnrollingIndex), pset1(rhs.coeff(UnrollingIndex, col)), res); @@ -405,7 +407,7 @@ template struct product_packet_impl { typedef typename Lhs::Index Index; - EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Packet &res) + static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Packet &res) { res = pmul(pset1(lhs.coeff(row, 0)),rhs.template packet(0, col)); } @@ -415,7 +417,7 @@ template struct product_packet_impl { typedef typename Lhs::Index Index; - EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Packet &res) + static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Packet &res) { res = pmul(lhs.template packet(row, 0), pset1(rhs.coeff(0, col))); } @@ -425,7 +427,7 @@ template struct product_packet_impl { typedef typename Lhs::Index Index; - EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Packet& res) + static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Packet& res) { eigen_assert(lhs.cols()>0 && "you are using a non initialized matrix"); res = pmul(pset1(lhs.coeff(row, 0)),rhs.template packet(0, col)); @@ -438,7 +440,7 @@ template struct product_packet_impl { typedef typename Lhs::Index Index; - EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Packet& res) + static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Packet& res) { eigen_assert(lhs.cols()>0 && "you are using a non initialized matrix"); res = pmul(lhs.template packet(row, 0), pset1(rhs.coeff(0, col))); @@ -449,4 +451,6 @@ struct product_packet_impl } // end namespace internal +} // end namespace Eigen + #endif // EIGEN_COEFFBASED_PRODUCT_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/products/GeneralBlockPanelKernel.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/products/GeneralBlockPanelKernel.h index cd1c37c78..d631fa28e 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/products/GeneralBlockPanelKernel.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/products/GeneralBlockPanelKernel.h @@ -25,12 +25,16 @@ #ifndef EIGEN_GENERAL_BLOCK_PANEL_H #define EIGEN_GENERAL_BLOCK_PANEL_H +namespace Eigen { + namespace internal { template class gebp_traits; -inline std::ptrdiff_t manage_caching_sizes_second_if_negative(std::ptrdiff_t a, std::ptrdiff_t b) + +/** \internal \returns b if a<=0, and returns a otherwise. */ +inline std::ptrdiff_t manage_caching_sizes_helper(std::ptrdiff_t a, std::ptrdiff_t b) { return a<=0 ? b : a; } @@ -38,9 +42,14 @@ inline std::ptrdiff_t manage_caching_sizes_second_if_negative(std::ptrdiff_t a, /** \internal */ inline void manage_caching_sizes(Action action, std::ptrdiff_t* l1=0, std::ptrdiff_t* l2=0) { - static std::ptrdiff_t m_l1CacheSize = manage_caching_sizes_second_if_negative(queryL1CacheSize(),8 * 1024); - static std::ptrdiff_t m_l2CacheSize = manage_caching_sizes_second_if_negative(queryTopLevelCacheSize(),1*1024*1024); - + static std::ptrdiff_t m_l1CacheSize = 0; + static std::ptrdiff_t m_l2CacheSize = 0; + if(m_l2CacheSize==0) + { + m_l1CacheSize = manage_caching_sizes_helper(queryL1CacheSize(),8 * 1024); + m_l2CacheSize = manage_caching_sizes_helper(queryTopLevelCacheSize(),1*1024*1024); + } + if(action==SetAction) { // set the cpu cache size and cache all block sizes from a global cache size in byte @@ -533,7 +542,7 @@ struct gebp_kernel ResPacketSize = Traits::ResPacketSize }; - EIGEN_FLATTEN_ATTRIB + EIGEN_DONT_INLINE EIGEN_FLATTEN_ATTRIB void operator()(ResScalar* res, Index resStride, const LhsScalar* blockA, const RhsScalar* blockB, Index rows, Index depth, Index cols, ResScalar alpha, Index strideA=-1, Index strideB=-1, Index offsetA=0, Index offsetB=0, RhsScalar* unpackedB = 0) { @@ -595,64 +604,64 @@ struct gebp_kernel if(nr==2) { LhsPacket A0, A1; - RhsPacket B0; + RhsPacket B_0; RhsPacket T0; EIGEN_ASM_COMMENT("mybegin2"); traits.loadLhs(&blA[0*LhsProgress], A0); traits.loadLhs(&blA[1*LhsProgress], A1); - traits.loadRhs(&blB[0*RhsProgress], B0); - traits.madd(A0,B0,C0,T0); - traits.madd(A1,B0,C4,B0); - traits.loadRhs(&blB[1*RhsProgress], B0); - traits.madd(A0,B0,C1,T0); - traits.madd(A1,B0,C5,B0); + traits.loadRhs(&blB[0*RhsProgress], B_0); + traits.madd(A0,B_0,C0,T0); + traits.madd(A1,B_0,C4,B_0); + traits.loadRhs(&blB[1*RhsProgress], B_0); + traits.madd(A0,B_0,C1,T0); + traits.madd(A1,B_0,C5,B_0); traits.loadLhs(&blA[2*LhsProgress], A0); traits.loadLhs(&blA[3*LhsProgress], A1); - traits.loadRhs(&blB[2*RhsProgress], B0); - traits.madd(A0,B0,C0,T0); - traits.madd(A1,B0,C4,B0); - traits.loadRhs(&blB[3*RhsProgress], B0); - traits.madd(A0,B0,C1,T0); - traits.madd(A1,B0,C5,B0); + traits.loadRhs(&blB[2*RhsProgress], B_0); + traits.madd(A0,B_0,C0,T0); + traits.madd(A1,B_0,C4,B_0); + traits.loadRhs(&blB[3*RhsProgress], B_0); + traits.madd(A0,B_0,C1,T0); + traits.madd(A1,B_0,C5,B_0); traits.loadLhs(&blA[4*LhsProgress], A0); traits.loadLhs(&blA[5*LhsProgress], A1); - traits.loadRhs(&blB[4*RhsProgress], B0); - traits.madd(A0,B0,C0,T0); - traits.madd(A1,B0,C4,B0); - traits.loadRhs(&blB[5*RhsProgress], B0); - traits.madd(A0,B0,C1,T0); - traits.madd(A1,B0,C5,B0); + traits.loadRhs(&blB[4*RhsProgress], B_0); + traits.madd(A0,B_0,C0,T0); + traits.madd(A1,B_0,C4,B_0); + traits.loadRhs(&blB[5*RhsProgress], B_0); + traits.madd(A0,B_0,C1,T0); + traits.madd(A1,B_0,C5,B_0); traits.loadLhs(&blA[6*LhsProgress], A0); traits.loadLhs(&blA[7*LhsProgress], A1); - traits.loadRhs(&blB[6*RhsProgress], B0); - traits.madd(A0,B0,C0,T0); - traits.madd(A1,B0,C4,B0); - traits.loadRhs(&blB[7*RhsProgress], B0); - traits.madd(A0,B0,C1,T0); - traits.madd(A1,B0,C5,B0); + traits.loadRhs(&blB[6*RhsProgress], B_0); + traits.madd(A0,B_0,C0,T0); + traits.madd(A1,B_0,C4,B_0); + traits.loadRhs(&blB[7*RhsProgress], B_0); + traits.madd(A0,B_0,C1,T0); + traits.madd(A1,B_0,C5,B_0); EIGEN_ASM_COMMENT("myend"); } else { EIGEN_ASM_COMMENT("mybegin4"); LhsPacket A0, A1; - RhsPacket B0, B1, B2, B3; + RhsPacket B_0, B1, B2, B3; RhsPacket T0; traits.loadLhs(&blA[0*LhsProgress], A0); traits.loadLhs(&blA[1*LhsProgress], A1); - traits.loadRhs(&blB[0*RhsProgress], B0); + traits.loadRhs(&blB[0*RhsProgress], B_0); traits.loadRhs(&blB[1*RhsProgress], B1); - traits.madd(A0,B0,C0,T0); + traits.madd(A0,B_0,C0,T0); traits.loadRhs(&blB[2*RhsProgress], B2); - traits.madd(A1,B0,C4,B0); + traits.madd(A1,B_0,C4,B_0); traits.loadRhs(&blB[3*RhsProgress], B3); - traits.loadRhs(&blB[4*RhsProgress], B0); + traits.loadRhs(&blB[4*RhsProgress], B_0); traits.madd(A0,B1,C1,T0); traits.madd(A1,B1,C5,B1); traits.loadRhs(&blB[5*RhsProgress], B1); @@ -664,9 +673,9 @@ EIGEN_ASM_COMMENT("mybegin4"); traits.madd(A1,B3,C7,B3); traits.loadLhs(&blA[3*LhsProgress], A1); traits.loadRhs(&blB[7*RhsProgress], B3); - traits.madd(A0,B0,C0,T0); - traits.madd(A1,B0,C4,B0); - traits.loadRhs(&blB[8*RhsProgress], B0); + traits.madd(A0,B_0,C0,T0); + traits.madd(A1,B_0,C4,B_0); + traits.loadRhs(&blB[8*RhsProgress], B_0); traits.madd(A0,B1,C1,T0); traits.madd(A1,B1,C5,B1); traits.loadRhs(&blB[9*RhsProgress], B1); @@ -679,9 +688,9 @@ EIGEN_ASM_COMMENT("mybegin4"); traits.loadLhs(&blA[5*LhsProgress], A1); traits.loadRhs(&blB[11*RhsProgress], B3); - traits.madd(A0,B0,C0,T0); - traits.madd(A1,B0,C4,B0); - traits.loadRhs(&blB[12*RhsProgress], B0); + traits.madd(A0,B_0,C0,T0); + traits.madd(A1,B_0,C4,B_0); + traits.loadRhs(&blB[12*RhsProgress], B_0); traits.madd(A0,B1,C1,T0); traits.madd(A1,B1,C5,B1); traits.loadRhs(&blB[13*RhsProgress], B1); @@ -693,8 +702,8 @@ EIGEN_ASM_COMMENT("mybegin4"); traits.madd(A1,B3,C7,B3); traits.loadLhs(&blA[7*LhsProgress], A1); traits.loadRhs(&blB[15*RhsProgress], B3); - traits.madd(A0,B0,C0,T0); - traits.madd(A1,B0,C4,B0); + traits.madd(A0,B_0,C0,T0); + traits.madd(A1,B_0,C4,B_0); traits.madd(A0,B1,C1,T0); traits.madd(A1,B1,C5,B1); traits.madd(A0,B2,C2,T0); @@ -712,32 +721,32 @@ EIGEN_ASM_COMMENT("mybegin4"); if(nr==2) { LhsPacket A0, A1; - RhsPacket B0; + RhsPacket B_0; RhsPacket T0; traits.loadLhs(&blA[0*LhsProgress], A0); traits.loadLhs(&blA[1*LhsProgress], A1); - traits.loadRhs(&blB[0*RhsProgress], B0); - traits.madd(A0,B0,C0,T0); - traits.madd(A1,B0,C4,B0); - traits.loadRhs(&blB[1*RhsProgress], B0); - traits.madd(A0,B0,C1,T0); - traits.madd(A1,B0,C5,B0); + traits.loadRhs(&blB[0*RhsProgress], B_0); + traits.madd(A0,B_0,C0,T0); + traits.madd(A1,B_0,C4,B_0); + traits.loadRhs(&blB[1*RhsProgress], B_0); + traits.madd(A0,B_0,C1,T0); + traits.madd(A1,B_0,C5,B_0); } else { LhsPacket A0, A1; - RhsPacket B0, B1, B2, B3; + RhsPacket B_0, B1, B2, B3; RhsPacket T0; traits.loadLhs(&blA[0*LhsProgress], A0); traits.loadLhs(&blA[1*LhsProgress], A1); - traits.loadRhs(&blB[0*RhsProgress], B0); + traits.loadRhs(&blB[0*RhsProgress], B_0); traits.loadRhs(&blB[1*RhsProgress], B1); - traits.madd(A0,B0,C0,T0); + traits.madd(A0,B_0,C0,T0); traits.loadRhs(&blB[2*RhsProgress], B2); - traits.madd(A1,B0,C4,B0); + traits.madd(A1,B_0,C4,B_0); traits.loadRhs(&blB[3*RhsProgress], B3); traits.madd(A0,B1,C1,T0); traits.madd(A1,B1,C5,B1); @@ -824,42 +833,42 @@ EIGEN_ASM_COMMENT("mybegin4"); if(nr==2) { LhsPacket A0; - RhsPacket B0, B1; + RhsPacket B_0, B1; traits.loadLhs(&blA[0*LhsProgress], A0); - traits.loadRhs(&blB[0*RhsProgress], B0); + traits.loadRhs(&blB[0*RhsProgress], B_0); traits.loadRhs(&blB[1*RhsProgress], B1); - traits.madd(A0,B0,C0,B0); - traits.loadRhs(&blB[2*RhsProgress], B0); + traits.madd(A0,B_0,C0,B_0); + traits.loadRhs(&blB[2*RhsProgress], B_0); traits.madd(A0,B1,C1,B1); traits.loadLhs(&blA[1*LhsProgress], A0); traits.loadRhs(&blB[3*RhsProgress], B1); - traits.madd(A0,B0,C0,B0); - traits.loadRhs(&blB[4*RhsProgress], B0); + traits.madd(A0,B_0,C0,B_0); + traits.loadRhs(&blB[4*RhsProgress], B_0); traits.madd(A0,B1,C1,B1); traits.loadLhs(&blA[2*LhsProgress], A0); traits.loadRhs(&blB[5*RhsProgress], B1); - traits.madd(A0,B0,C0,B0); - traits.loadRhs(&blB[6*RhsProgress], B0); + traits.madd(A0,B_0,C0,B_0); + traits.loadRhs(&blB[6*RhsProgress], B_0); traits.madd(A0,B1,C1,B1); traits.loadLhs(&blA[3*LhsProgress], A0); traits.loadRhs(&blB[7*RhsProgress], B1); - traits.madd(A0,B0,C0,B0); + traits.madd(A0,B_0,C0,B_0); traits.madd(A0,B1,C1,B1); } else { LhsPacket A0; - RhsPacket B0, B1, B2, B3; + RhsPacket B_0, B1, B2, B3; traits.loadLhs(&blA[0*LhsProgress], A0); - traits.loadRhs(&blB[0*RhsProgress], B0); + traits.loadRhs(&blB[0*RhsProgress], B_0); traits.loadRhs(&blB[1*RhsProgress], B1); - traits.madd(A0,B0,C0,B0); + traits.madd(A0,B_0,C0,B_0); traits.loadRhs(&blB[2*RhsProgress], B2); traits.loadRhs(&blB[3*RhsProgress], B3); - traits.loadRhs(&blB[4*RhsProgress], B0); + traits.loadRhs(&blB[4*RhsProgress], B_0); traits.madd(A0,B1,C1,B1); traits.loadRhs(&blB[5*RhsProgress], B1); traits.madd(A0,B2,C2,B2); @@ -867,8 +876,8 @@ EIGEN_ASM_COMMENT("mybegin4"); traits.madd(A0,B3,C3,B3); traits.loadLhs(&blA[1*LhsProgress], A0); traits.loadRhs(&blB[7*RhsProgress], B3); - traits.madd(A0,B0,C0,B0); - traits.loadRhs(&blB[8*RhsProgress], B0); + traits.madd(A0,B_0,C0,B_0); + traits.loadRhs(&blB[8*RhsProgress], B_0); traits.madd(A0,B1,C1,B1); traits.loadRhs(&blB[9*RhsProgress], B1); traits.madd(A0,B2,C2,B2); @@ -877,8 +886,8 @@ EIGEN_ASM_COMMENT("mybegin4"); traits.loadLhs(&blA[2*LhsProgress], A0); traits.loadRhs(&blB[11*RhsProgress], B3); - traits.madd(A0,B0,C0,B0); - traits.loadRhs(&blB[12*RhsProgress], B0); + traits.madd(A0,B_0,C0,B_0); + traits.loadRhs(&blB[12*RhsProgress], B_0); traits.madd(A0,B1,C1,B1); traits.loadRhs(&blB[13*RhsProgress], B1); traits.madd(A0,B2,C2,B2); @@ -887,7 +896,7 @@ EIGEN_ASM_COMMENT("mybegin4"); traits.loadLhs(&blA[3*LhsProgress], A0); traits.loadRhs(&blB[15*RhsProgress], B3); - traits.madd(A0,B0,C0,B0); + traits.madd(A0,B_0,C0,B_0); traits.madd(A0,B1,C1,B1); traits.madd(A0,B2,C2,B2); traits.madd(A0,B3,C3,B3); @@ -902,26 +911,26 @@ EIGEN_ASM_COMMENT("mybegin4"); if(nr==2) { LhsPacket A0; - RhsPacket B0, B1; + RhsPacket B_0, B1; traits.loadLhs(&blA[0*LhsProgress], A0); - traits.loadRhs(&blB[0*RhsProgress], B0); + traits.loadRhs(&blB[0*RhsProgress], B_0); traits.loadRhs(&blB[1*RhsProgress], B1); - traits.madd(A0,B0,C0,B0); + traits.madd(A0,B_0,C0,B_0); traits.madd(A0,B1,C1,B1); } else { LhsPacket A0; - RhsPacket B0, B1, B2, B3; + RhsPacket B_0, B1, B2, B3; traits.loadLhs(&blA[0*LhsProgress], A0); - traits.loadRhs(&blB[0*RhsProgress], B0); + traits.loadRhs(&blB[0*RhsProgress], B_0); traits.loadRhs(&blB[1*RhsProgress], B1); traits.loadRhs(&blB[2*RhsProgress], B2); traits.loadRhs(&blB[3*RhsProgress], B3); - traits.madd(A0,B0,C0,B0); + traits.madd(A0,B_0,C0,B_0); traits.madd(A0,B1,C1,B1); traits.madd(A0,B2,C2,B2); traits.madd(A0,B3,C3,B3); @@ -968,26 +977,26 @@ EIGEN_ASM_COMMENT("mybegin4"); if(nr==2) { LhsScalar A0; - RhsScalar B0, B1; + RhsScalar B_0, B1; A0 = blA[k]; - B0 = blB[0]; + B_0 = blB[0]; B1 = blB[1]; - MADD(cj,A0,B0,C0,B0); + MADD(cj,A0,B_0,C0,B_0); MADD(cj,A0,B1,C1,B1); } else { LhsScalar A0; - RhsScalar B0, B1, B2, B3; + RhsScalar B_0, B1, B2, B3; A0 = blA[k]; - B0 = blB[0]; + B_0 = blB[0]; B1 = blB[1]; B2 = blB[2]; B3 = blB[3]; - MADD(cj,A0,B0,C0,B0); + MADD(cj,A0,B_0,C0,B_0); MADD(cj,A0,B1,C1,B1); MADD(cj,A0,B2,C2,B2); MADD(cj,A0,B3,C3,B3); @@ -1024,14 +1033,14 @@ EIGEN_ASM_COMMENT("mybegin4"); for(Index k=0; k struct gemm_pack_lhs { - void operator()(Scalar* blockA, const Scalar* EIGEN_RESTRICT _lhs, Index lhsStride, Index depth, Index rows, + EIGEN_DONT_INLINE void operator()(Scalar* blockA, const Scalar* EIGEN_RESTRICT _lhs, Index lhsStride, Index depth, Index rows, Index stride=0, Index offset=0) { -// enum { PacketSize = packet_traits::size }; + typedef typename packet_traits::type Packet; + enum { PacketSize = packet_traits::size }; + + EIGEN_ASM_COMMENT("EIGEN PRODUCT PACK LHS"); eigen_assert(((!PanelMode) && stride==0 && offset==0) || (PanelMode && stride>=depth && offset<=stride)); + eigen_assert( (StorageOrder==RowMajor) || ((Pack1%PacketSize)==0 && Pack1<=4*PacketSize) ); conj_if::IsComplex && Conjugate> cj; const_blas_data_mapper lhs(_lhs,lhsStride); Index count = 0; @@ -1128,9 +1141,44 @@ struct gemm_pack_lhs for(Index i=0; i=1*PacketSize) A = ploadu(&lhs(i+0*PacketSize, k)); + if(Pack1>=2*PacketSize) B = ploadu(&lhs(i+1*PacketSize, k)); + if(Pack1>=3*PacketSize) C = ploadu(&lhs(i+2*PacketSize, k)); + if(Pack1>=4*PacketSize) D = ploadu(&lhs(i+3*PacketSize, k)); + if(Pack1>=1*PacketSize) { pstore(blockA+count, cj.pconj(A)); count+=PacketSize; } + if(Pack1>=2*PacketSize) { pstore(blockA+count, cj.pconj(B)); count+=PacketSize; } + if(Pack1>=3*PacketSize) { pstore(blockA+count, cj.pconj(C)); count+=PacketSize; } + if(Pack1>=4*PacketSize) { pstore(blockA+count, cj.pconj(D)); count+=PacketSize; } + } + } + else + { + for(Index k=0; k=Pack2) @@ -1164,9 +1212,10 @@ struct gemm_pack_rhs { typedef typename packet_traits::type Packet; enum { PacketSize = packet_traits::size }; - void operator()(Scalar* blockB, const Scalar* rhs, Index rhsStride, Index depth, Index cols, + EIGEN_DONT_INLINE void operator()(Scalar* blockB, const Scalar* rhs, Index rhsStride, Index depth, Index cols, Index stride=0, Index offset=0) { + EIGEN_ASM_COMMENT("EIGEN PRODUCT PACK RHS COLMAJOR"); eigen_assert(((!PanelMode) && stride==0 && offset==0) || (PanelMode && stride>=depth && offset<=stride)); conj_if::IsComplex && Conjugate> cj; Index packet_cols = (cols/nr) * nr; @@ -1211,9 +1260,10 @@ template { enum { PacketSize = packet_traits::size }; - void operator()(Scalar* blockB, const Scalar* rhs, Index rhsStride, Index depth, Index cols, + EIGEN_DONT_INLINE void operator()(Scalar* blockB, const Scalar* rhs, Index rhsStride, Index depth, Index cols, Index stride=0, Index offset=0) { + EIGEN_ASM_COMMENT("EIGEN PRODUCT PACK RHS ROWMAJOR"); eigen_assert(((!PanelMode) && stride==0 && offset==0) || (PanelMode && stride>=depth && offset<=stride)); conj_if::IsComplex && Conjugate> cj; Index packet_cols = (cols/nr) * nr; @@ -1279,4 +1329,6 @@ inline void setCpuCacheSizes(std::ptrdiff_t l1, std::ptrdiff_t l2) internal::manage_caching_sizes(SetAction, &l1, &l2); } +} // end namespace Eigen + #endif // EIGEN_GENERAL_BLOCK_PANEL_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/products/GeneralMatrixMatrix.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/products/GeneralMatrixMatrix.h index ae94a2795..76fc32032 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/products/GeneralMatrixMatrix.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/products/GeneralMatrixMatrix.h @@ -25,6 +25,8 @@ #ifndef EIGEN_GENERAL_MATRIX_MATRIX_H #define EIGEN_GENERAL_MATRIX_MATRIX_H +namespace Eigen { + namespace internal { template class level3_blocking; @@ -77,7 +79,7 @@ static void run(Index rows, Index cols, Index depth, typedef gebp_traits Traits; - Index kc = blocking.kc(); // cache block size along the K direction + Index kc = blocking.kc(); // cache block size along the K direction Index mc = (std::min)(rows,blocking.mc()); // cache block size along the M direction //Index nc = blocking.nc(); // cache block size along the N direction @@ -247,7 +249,7 @@ struct gemm_functor BlockingType& m_blocking; }; -template class gemm_blocking_space; template @@ -280,8 +282,8 @@ class level3_blocking inline RhsScalar* blockW() { return m_blockW; } }; -template -class gemm_blocking_space +template +class gemm_blocking_space : public level3_blocking< typename conditional::type, typename conditional::type> @@ -322,8 +324,8 @@ class gemm_blocking_space -class gemm_blocking_space +template +class gemm_blocking_space : public level3_blocking< typename conditional::type, typename conditional::type> @@ -347,7 +349,7 @@ class gemm_blocking_spacem_nc = Transpose ? rows : cols; this->m_kc = depth; - computeProductBlockingSizes(this->m_kc, this->m_mc, this->m_nc); + computeProductBlockingSizes(this->m_kc, this->m_mc, this->m_nc); m_sizeA = this->m_mc * this->m_kc; m_sizeB = this->m_kc * this->m_nc; m_sizeW = this->m_kc*Traits::WorkSpaceFactor; @@ -412,8 +414,8 @@ class GeneralProduct { eigen_assert(dst.rows()==m_lhs.rows() && dst.cols()==m_rhs.cols()); - const ActualLhsType lhs = LhsBlasTraits::extract(m_lhs); - const ActualRhsType rhs = RhsBlasTraits::extract(m_rhs); + typename internal::add_const_on_value_type::type lhs = LhsBlasTraits::extract(m_lhs); + typename internal::add_const_on_value_type::type rhs = RhsBlasTraits::extract(m_rhs); Scalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(m_lhs) * RhsBlasTraits::extractScalarFactor(m_rhs); @@ -436,4 +438,6 @@ class GeneralProduct } }; +} // end namespace Eigen + #endif // EIGEN_GENERAL_MATRIX_MATRIX_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h index 5043b64fe..74331ee4f 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h @@ -25,6 +25,8 @@ #ifndef EIGEN_GENERAL_MATRIX_MATRIX_TRIANGULAR_H #define EIGEN_GENERAL_MATRIX_MATRIX_TRIANGULAR_H +namespace Eigen { + namespace internal { /********************************************************************** @@ -42,14 +44,14 @@ struct tribb_kernel; template + int ResStorageOrder, int UpLo, int Version = Specialized> struct general_matrix_matrix_triangular_product; // as usual if the result is row major => we transpose the product template -struct general_matrix_matrix_triangular_product -{ + typename RhsScalar, int RhsStorageOrder, bool ConjugateRhs, int UpLo, int Version> +struct general_matrix_matrix_triangular_product +{ typedef typename scalar_product_traits::ReturnType ResScalar; static EIGEN_STRONG_INLINE void run(Index size, Index depth,const LhsScalar* lhs, Index lhsStride, const RhsScalar* rhs, Index rhsStride, ResScalar* res, Index resStride, ResScalar alpha) @@ -63,8 +65,8 @@ struct general_matrix_matrix_triangular_product -struct general_matrix_matrix_triangular_product + typename RhsScalar, int RhsStorageOrder, bool ConjugateRhs, int UpLo, int Version> +struct general_matrix_matrix_triangular_product { typedef typename scalar_product_traits::ReturnType ResScalar; static EIGEN_STRONG_INLINE void run(Index size, Index depth,const LhsScalar* _lhs, Index lhsStride, @@ -201,13 +203,13 @@ TriangularView& TriangularView::assignProduct( typedef internal::blas_traits LhsBlasTraits; typedef typename LhsBlasTraits::DirectLinearAccessType ActualLhs; typedef typename internal::remove_all::type _ActualLhs; - const ActualLhs actualLhs = LhsBlasTraits::extract(prod.lhs()); + typename internal::add_const_on_value_type::type actualLhs = LhsBlasTraits::extract(prod.lhs()); typedef typename internal::remove_all::type Rhs; typedef internal::blas_traits RhsBlasTraits; typedef typename RhsBlasTraits::DirectLinearAccessType ActualRhs; typedef typename internal::remove_all::type _ActualRhs; - const ActualRhs actualRhs = RhsBlasTraits::extract(prod.rhs()); + typename internal::add_const_on_value_type::type actualRhs = RhsBlasTraits::extract(prod.rhs()); typename ProductDerived::Scalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(prod.lhs().derived()) * RhsBlasTraits::extractScalarFactor(prod.rhs().derived()); @@ -222,4 +224,6 @@ TriangularView& TriangularView::assignProduct( return *this; } +} // end namespace Eigen + #endif // EIGEN_GENERAL_MATRIX_MATRIX_TRIANGULAR_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/products/GeneralMatrixMatrixTriangular_MKL.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/products/GeneralMatrixMatrixTriangular_MKL.h new file mode 100644 index 000000000..3deed068e --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/products/GeneralMatrixMatrixTriangular_MKL.h @@ -0,0 +1,146 @@ +/* + Copyright (c) 2011, Intel Corporation. All rights reserved. + + Redistribution and use in source and binary forms, with or without modification, + are permitted provided that the following conditions are met: + + * Redistributions of source code must retain the above copyright notice, this + list of conditions and the following disclaimer. + * Redistributions in binary form must reproduce the above copyright notice, + this list of conditions and the following disclaimer in the documentation + and/or other materials provided with the distribution. + * Neither the name of Intel Corporation nor the names of its contributors may + be used to endorse or promote products derived from this software without + specific prior written permission. + + THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND + ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED + WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE + DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR + ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES + (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; + LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON + ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS + SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + + ******************************************************************************** + * Content : Eigen bindings to Intel(R) MKL + * Level 3 BLAS SYRK/HERK implementation. + ******************************************************************************** +*/ + +#ifndef EIGEN_GENERAL_MATRIX_MATRIX_TRIANGULAR_MKL_H +#define EIGEN_GENERAL_MATRIX_MATRIX_TRIANGULAR_MKL_H + +namespace Eigen { + +namespace internal { + +template +struct general_matrix_matrix_rankupdate : + general_matrix_matrix_triangular_product< + Index,Scalar,AStorageOrder,ConjugateA,Scalar,AStorageOrder,ConjugateA,ResStorageOrder,UpLo,BuiltIn> {}; + + +// try to go to BLAS specialization +#define EIGEN_MKL_RANKUPDATE_SPECIALIZE(Scalar) \ +template \ +struct general_matrix_matrix_triangular_product { \ + static EIGEN_STRONG_INLINE void run(Index size, Index depth,const Scalar* lhs, Index lhsStride, \ + const Scalar* rhs, Index rhsStride, Scalar* res, Index resStride, Scalar alpha) \ + { \ + if (lhs==rhs) { \ + general_matrix_matrix_rankupdate \ + ::run(size,depth,lhs,lhsStride,rhs,rhsStride,res,resStride,alpha); \ + } else { \ + general_matrix_matrix_triangular_product \ + ::run(size,depth,lhs,lhsStride,rhs,rhsStride,res,resStride,alpha); \ + } \ + } \ +}; + +EIGEN_MKL_RANKUPDATE_SPECIALIZE(double) +//EIGEN_MKL_RANKUPDATE_SPECIALIZE(dcomplex) +EIGEN_MKL_RANKUPDATE_SPECIALIZE(float) +//EIGEN_MKL_RANKUPDATE_SPECIALIZE(scomplex) + +// SYRK for float/double +#define EIGEN_MKL_RANKUPDATE_R(EIGTYPE, MKLTYPE, MKLFUNC) \ +template \ +struct general_matrix_matrix_rankupdate { \ + enum { \ + IsLower = (UpLo&Lower) == Lower, \ + LowUp = IsLower ? Lower : Upper, \ + conjA = ((AStorageOrder==ColMajor) && ConjugateA) ? 1 : 0 \ + }; \ + static EIGEN_STRONG_INLINE void run(Index size, Index depth,const EIGTYPE* lhs, Index lhsStride, \ + const EIGTYPE* rhs, Index rhsStride, EIGTYPE* res, Index resStride, EIGTYPE alpha) \ + { \ + /* typedef Matrix MatrixRhs;*/ \ +\ + MKL_INT lda=lhsStride, ldc=resStride, n=size, k=depth; \ + char uplo=(IsLower) ? 'L' : 'U', trans=(AStorageOrder==RowMajor) ? 'T':'N'; \ + MKLTYPE alpha_, beta_; \ +\ +/* Set alpha_ & beta_ */ \ + assign_scalar_eig2mkl(alpha_, alpha); \ + assign_scalar_eig2mkl(beta_, EIGTYPE(1)); \ + MKLFUNC(&uplo, &trans, &n, &k, &alpha_, lhs, &lda, &beta_, res, &ldc); \ + } \ +}; + +// HERK for complex data +#define EIGEN_MKL_RANKUPDATE_C(EIGTYPE, MKLTYPE, RTYPE, MKLFUNC) \ +template \ +struct general_matrix_matrix_rankupdate { \ + enum { \ + IsLower = (UpLo&Lower) == Lower, \ + LowUp = IsLower ? Lower : Upper, \ + conjA = (((AStorageOrder==ColMajor) && ConjugateA) || ((AStorageOrder==RowMajor) && !ConjugateA)) ? 1 : 0 \ + }; \ + static EIGEN_STRONG_INLINE void run(Index size, Index depth,const EIGTYPE* lhs, Index lhsStride, \ + const EIGTYPE* rhs, Index rhsStride, EIGTYPE* res, Index resStride, EIGTYPE alpha) \ + { \ + typedef Matrix MatrixType; \ +\ + MKL_INT lda=lhsStride, ldc=resStride, n=size, k=depth; \ + char uplo=(IsLower) ? 'L' : 'U', trans=(AStorageOrder==RowMajor) ? 'C':'N'; \ + RTYPE alpha_, beta_; \ + const EIGTYPE* a_ptr; \ +\ +/* Set alpha_ & beta_ */ \ +/* assign_scalar_eig2mkl(alpha_, alpha); */\ +/* assign_scalar_eig2mkl(beta_, EIGTYPE(1));*/ \ + alpha_ = alpha.real(); \ + beta_ = 1.0; \ +/* Copy with conjugation in some cases*/ \ + MatrixType a; \ + if (conjA) { \ + Map > mapA(lhs,n,k,OuterStride<>(lhsStride)); \ + a = mapA.conjugate(); \ + lda = a.outerStride(); \ + a_ptr = a.data(); \ + } else a_ptr=lhs; \ + MKLFUNC(&uplo, &trans, &n, &k, &alpha_, (MKLTYPE*)a_ptr, &lda, &beta_, (MKLTYPE*)res, &ldc); \ + } \ +}; + + +EIGEN_MKL_RANKUPDATE_R(double, double, dsyrk) +EIGEN_MKL_RANKUPDATE_R(float, float, ssyrk) + +//EIGEN_MKL_RANKUPDATE_C(dcomplex, MKL_Complex16, double, zherk) +//EIGEN_MKL_RANKUPDATE_C(scomplex, MKL_Complex8, double, cherk) + + +} // end namespace internal + +} // end namespace Eigen + +#endif // EIGEN_GENERAL_MATRIX_MATRIX_TRIANGULAR_MKL_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/products/GeneralMatrixMatrix_MKL.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/products/GeneralMatrixMatrix_MKL.h new file mode 100644 index 000000000..060af328e --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/products/GeneralMatrixMatrix_MKL.h @@ -0,0 +1,118 @@ +/* + Copyright (c) 2011, Intel Corporation. All rights reserved. + + Redistribution and use in source and binary forms, with or without modification, + are permitted provided that the following conditions are met: + + * Redistributions of source code must retain the above copyright notice, this + list of conditions and the following disclaimer. + * Redistributions in binary form must reproduce the above copyright notice, + this list of conditions and the following disclaimer in the documentation + and/or other materials provided with the distribution. + * Neither the name of Intel Corporation nor the names of its contributors may + be used to endorse or promote products derived from this software without + specific prior written permission. + + THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND + ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED + WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE + DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR + ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES + (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; + LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON + ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS + SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + + ******************************************************************************** + * Content : Eigen bindings to Intel(R) MKL + * General matrix-matrix product functionality based on ?GEMM. + ******************************************************************************** +*/ + +#ifndef EIGEN_GENERAL_MATRIX_MATRIX_MKL_H +#define EIGEN_GENERAL_MATRIX_MATRIX_MKL_H + +namespace Eigen { + +namespace internal { + +/********************************************************************** +* This file implements general matrix-matrix multiplication using BLAS +* gemm function via partial specialization of +* general_matrix_matrix_product::run(..) method for float, double, +* std::complex and std::complex types +**********************************************************************/ + +// gemm specialization + +#define GEMM_SPECIALIZATION(EIGTYPE, EIGPREFIX, MKLTYPE, MKLPREFIX) \ +template< \ + typename Index, \ + int LhsStorageOrder, bool ConjugateLhs, \ + int RhsStorageOrder, bool ConjugateRhs> \ +struct general_matrix_matrix_product \ +{ \ +static void run(Index rows, Index cols, Index depth, \ + const EIGTYPE* _lhs, Index lhsStride, \ + const EIGTYPE* _rhs, Index rhsStride, \ + EIGTYPE* res, Index resStride, \ + EIGTYPE alpha, \ + level3_blocking& /*blocking*/, \ + GemmParallelInfo* /*info = 0*/) \ +{ \ + using std::conj; \ +\ + char transa, transb; \ + MKL_INT m, n, k, lda, ldb, ldc; \ + const EIGTYPE *a, *b; \ + MKLTYPE alpha_, beta_; \ + MatrixX##EIGPREFIX a_tmp, b_tmp; \ + EIGTYPE myone(1);\ +\ +/* Set transpose options */ \ + transa = (LhsStorageOrder==RowMajor) ? ((ConjugateLhs) ? 'C' : 'T') : 'N'; \ + transb = (RhsStorageOrder==RowMajor) ? ((ConjugateRhs) ? 'C' : 'T') : 'N'; \ +\ +/* Set m, n, k */ \ + m = (MKL_INT)rows; \ + n = (MKL_INT)cols; \ + k = (MKL_INT)depth; \ +\ +/* Set alpha_ & beta_ */ \ + assign_scalar_eig2mkl(alpha_, alpha); \ + assign_scalar_eig2mkl(beta_, myone); \ +\ +/* Set lda, ldb, ldc */ \ + lda = (MKL_INT)lhsStride; \ + ldb = (MKL_INT)rhsStride; \ + ldc = (MKL_INT)resStride; \ +\ +/* Set a, b, c */ \ + if ((LhsStorageOrder==ColMajor) && (ConjugateLhs)) { \ + Map > lhs(_lhs,m,k,OuterStride<>(lhsStride)); \ + a_tmp = lhs.conjugate(); \ + a = a_tmp.data(); \ + lda = a_tmp.outerStride(); \ + } else a = _lhs; \ +\ + if ((RhsStorageOrder==ColMajor) && (ConjugateRhs)) { \ + Map > rhs(_rhs,k,n,OuterStride<>(rhsStride)); \ + b_tmp = rhs.conjugate(); \ + b = b_tmp.data(); \ + ldb = b_tmp.outerStride(); \ + } else b = _rhs; \ +\ + MKLPREFIX##gemm(&transa, &transb, &m, &n, &k, &alpha_, (const MKLTYPE*)a, &lda, (const MKLTYPE*)b, &ldb, &beta_, (MKLTYPE*)res, &ldc); \ +}}; + +GEMM_SPECIALIZATION(double, d, double, d) +GEMM_SPECIALIZATION(float, f, float, s) +GEMM_SPECIALIZATION(dcomplex, cd, MKL_Complex16, z) +GEMM_SPECIALIZATION(scomplex, cf, MKL_Complex8, c) + +} // end namespase internal + +} // end namespace Eigen + +#endif // EIGEN_GENERAL_MATRIX_MATRIX_MKL_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/products/GeneralMatrixVector.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/products/GeneralMatrixVector.h index e0e2cbf8f..d868a66a1 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/products/GeneralMatrixVector.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/products/GeneralMatrixVector.h @@ -25,6 +25,8 @@ #ifndef EIGEN_GENERAL_MATRIX_VECTOR_H #define EIGEN_GENERAL_MATRIX_VECTOR_H +namespace Eigen { + namespace internal { /* Optimized col-major matrix * vector product: @@ -40,8 +42,8 @@ namespace internal { * |cplx |real |cplx | invalid, the caller has to do tmp: = A * B; C += alpha*tmp * |cplx |real |real | optimal case, vectorization possible via real-cplx mul */ -template -struct general_matrix_vector_product +template +struct general_matrix_vector_product { typedef typename scalar_product_traits::ReturnType ResScalar; @@ -99,7 +101,7 @@ EIGEN_DONT_INLINE static void run( // How many coeffs of the result do we have to skip to be aligned. // Here we assume data are at least aligned on the base scalar type. - Index alignedStart = first_aligned(res,size); + Index alignedStart = internal::first_aligned(res,size); Index alignedSize = ResPacketSize>1 ? alignedStart + ((size-alignedStart) & ~ResPacketAlignedMask) : 0; const Index peeledSize = peels>1 ? alignedStart + ((alignedSize-alignedStart) & ~PeelAlignedMask) : alignedStart; @@ -109,7 +111,7 @@ EIGEN_DONT_INLINE static void run( : FirstAligned; // we cannot assume the first element is aligned because of sub-matrices - const Index lhsAlignmentOffset = first_aligned(lhs,size); + const Index lhsAlignmentOffset = internal::first_aligned(lhs,size); // find how many columns do we have to skip to be aligned with the result (if possible) Index skipColumns = 0; @@ -296,8 +298,8 @@ EIGEN_DONT_INLINE static void run( * - alpha is always a complex (or converted to a complex) * - no vectorization */ -template -struct general_matrix_vector_product +template +struct general_matrix_vector_product { typedef typename scalar_product_traits::ReturnType ResScalar; @@ -351,7 +353,7 @@ EIGEN_DONT_INLINE static void run( // How many coeffs of the result do we have to skip to be aligned. // Here we assume data are at least aligned on the base scalar type // if that's not the case then vectorization is discarded, see below. - Index alignedStart = first_aligned(rhs, depth); + Index alignedStart = internal::first_aligned(rhs, depth); Index alignedSize = RhsPacketSize>1 ? alignedStart + ((depth-alignedStart) & ~RhsPacketAlignedMask) : 0; const Index peeledSize = peels>1 ? alignedStart + ((alignedSize-alignedStart) & ~PeelAlignedMask) : alignedStart; @@ -361,7 +363,7 @@ EIGEN_DONT_INLINE static void run( : FirstAligned; // we cannot assume the first element is aligned because of sub-matrices - const Index lhsAlignmentOffset = first_aligned(lhs,depth); + const Index lhsAlignmentOffset = internal::first_aligned(lhs,depth); // find how many rows do we have to skip to be aligned with rhs (if possible) Index skipRows = 0; @@ -556,4 +558,6 @@ EIGEN_DONT_INLINE static void run( } // end namespace internal +} // end namespace Eigen + #endif // EIGEN_GENERAL_MATRIX_VECTOR_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/products/GeneralMatrixVector_MKL.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/products/GeneralMatrixVector_MKL.h new file mode 100644 index 000000000..e9de6af3e --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/products/GeneralMatrixVector_MKL.h @@ -0,0 +1,131 @@ +/* + Copyright (c) 2011, Intel Corporation. All rights reserved. + + Redistribution and use in source and binary forms, with or without modification, + are permitted provided that the following conditions are met: + + * Redistributions of source code must retain the above copyright notice, this + list of conditions and the following disclaimer. + * Redistributions in binary form must reproduce the above copyright notice, + this list of conditions and the following disclaimer in the documentation + and/or other materials provided with the distribution. + * Neither the name of Intel Corporation nor the names of its contributors may + be used to endorse or promote products derived from this software without + specific prior written permission. + + THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND + ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED + WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE + DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR + ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES + (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; + LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON + ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS + SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + + ******************************************************************************** + * Content : Eigen bindings to Intel(R) MKL + * General matrix-vector product functionality based on ?GEMV. + ******************************************************************************** +*/ + +#ifndef EIGEN_GENERAL_MATRIX_VECTOR_MKL_H +#define EIGEN_GENERAL_MATRIX_VECTOR_MKL_H + +namespace Eigen { + +namespace internal { + +/********************************************************************** +* This file implements general matrix-vector multiplication using BLAS +* gemv function via partial specialization of +* general_matrix_vector_product::run(..) method for float, double, +* std::complex and std::complex types +**********************************************************************/ + +// gemv specialization + +template +struct general_matrix_vector_product_gemv : + general_matrix_vector_product {}; + +#define EIGEN_MKL_GEMV_SPECIALIZE(Scalar) \ +template \ +struct general_matrix_vector_product { \ +static EIGEN_DONT_INLINE void run( \ + Index rows, Index cols, \ + const Scalar* lhs, Index lhsStride, \ + const Scalar* rhs, Index rhsIncr, \ + Scalar* res, Index resIncr, Scalar alpha) \ +{ \ + if (ConjugateLhs) { \ + general_matrix_vector_product::run( \ + rows, cols, lhs, lhsStride, rhs, rhsIncr, res, resIncr, alpha); \ + } else { \ + general_matrix_vector_product_gemv::run( \ + rows, cols, lhs, lhsStride, rhs, rhsIncr, res, resIncr, alpha); \ + } \ +} \ +}; \ +template \ +struct general_matrix_vector_product { \ +static EIGEN_DONT_INLINE void run( \ + Index rows, Index cols, \ + const Scalar* lhs, Index lhsStride, \ + const Scalar* rhs, Index rhsIncr, \ + Scalar* res, Index resIncr, Scalar alpha) \ +{ \ + general_matrix_vector_product_gemv::run( \ + rows, cols, lhs, lhsStride, rhs, rhsIncr, res, resIncr, alpha); \ +} \ +}; \ + +EIGEN_MKL_GEMV_SPECIALIZE(double) +EIGEN_MKL_GEMV_SPECIALIZE(float) +EIGEN_MKL_GEMV_SPECIALIZE(dcomplex) +EIGEN_MKL_GEMV_SPECIALIZE(scomplex) + +#define EIGEN_MKL_GEMV_SPECIALIZATION(EIGTYPE,MKLTYPE,MKLPREFIX) \ +template \ +struct general_matrix_vector_product_gemv \ +{ \ +typedef Matrix GEMVVector;\ +\ +static EIGEN_DONT_INLINE void run( \ + Index rows, Index cols, \ + const EIGTYPE* lhs, Index lhsStride, \ + const EIGTYPE* rhs, Index rhsIncr, \ + EIGTYPE* res, Index resIncr, EIGTYPE alpha) \ +{ \ + MKL_INT m=rows, n=cols, lda=lhsStride, incx=rhsIncr, incy=resIncr; \ + MKLTYPE alpha_, beta_; \ + const EIGTYPE *x_ptr, myone(1); \ + char trans=(LhsStorageOrder==ColMajor) ? 'N' : (ConjugateLhs) ? 'C' : 'T'; \ + if (LhsStorageOrder==RowMajor) { \ + m=cols; \ + n=rows; \ + }\ + assign_scalar_eig2mkl(alpha_, alpha); \ + assign_scalar_eig2mkl(beta_, myone); \ + GEMVVector x_tmp; \ + if (ConjugateRhs) { \ + Map > map_x(rhs,cols,1,InnerStride<>(incx)); \ + x_tmp=map_x.conjugate(); \ + x_ptr=x_tmp.data(); \ + incx=1; \ + } else x_ptr=rhs; \ + MKLPREFIX##gemv(&trans, &m, &n, &alpha_, (const MKLTYPE*)lhs, &lda, (const MKLTYPE*)x_ptr, &incx, &beta_, (MKLTYPE*)res, &incy); \ +}\ +}; + +EIGEN_MKL_GEMV_SPECIALIZATION(double, double, d) +EIGEN_MKL_GEMV_SPECIALIZATION(float, float, s) +EIGEN_MKL_GEMV_SPECIALIZATION(dcomplex, MKL_Complex16, z) +EIGEN_MKL_GEMV_SPECIALIZATION(scomplex, MKL_Complex8, c) + +} // end namespase internal + +} // end namespace Eigen + +#endif // EIGEN_GENERAL_MATRIX_VECTOR_MKL_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/products/Parallelizer.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/products/Parallelizer.h index ecdedc363..725216162 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/products/Parallelizer.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/products/Parallelizer.h @@ -25,6 +25,8 @@ #ifndef EIGEN_PARALLELIZER_H #define EIGEN_PARALLELIZER_H +namespace Eigen { + namespace internal { /** \internal */ @@ -55,12 +57,23 @@ inline void manage_multi_threading(Action action, int* v) } } +} + +/** Must be call first when calling Eigen from multiple threads */ +inline void initParallel() +{ + int nbt; + internal::manage_multi_threading(GetAction, &nbt); + std::ptrdiff_t l1, l2; + internal::manage_caching_sizes(GetAction, &l1, &l2); +} + /** \returns the max number of threads reserved for Eigen * \sa setNbThreads */ inline int nbThreads() { int ret; - manage_multi_threading(GetAction, &ret); + internal::manage_multi_threading(GetAction, &ret); return ret; } @@ -68,9 +81,11 @@ inline int nbThreads() * \sa nbThreads */ inline void setNbThreads(int v) { - manage_multi_threading(SetAction, &v); + internal::manage_multi_threading(SetAction, &v); } +namespace internal { + template struct GemmParallelInfo { GemmParallelInfo() : sync(-1), users(0), rhs_start(0), rhs_length(0) {} @@ -85,7 +100,9 @@ template struct GemmParallelInfo template void parallelize_gemm(const Functor& func, Index rows, Index cols, bool transpose) { -#ifndef EIGEN_HAS_OPENMP + // TODO when EIGEN_USE_BLAS is defined, + // we should still enable OMP for other scalar types +#if !(defined (EIGEN_HAS_OPENMP)) || defined (EIGEN_USE_BLAS) // FIXME the transpose variable is only needed to properly split // the matrix product when multithreading is enabled. This is a temporary // fix to support row-major destination matrices. This whole @@ -117,6 +134,7 @@ void parallelize_gemm(const Functor& func, Index rows, Index cols, bool transpos if(threads==1) return func(0,rows, 0,cols); + Eigen::initParallel(); func.initParallelSession(); if(transpose) @@ -151,4 +169,6 @@ void parallelize_gemm(const Functor& func, Index rows, Index cols, bool transpos } // end namespace internal +} // end namespace Eigen + #endif // EIGEN_PARALLELIZER_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/products/SelfadjointMatrixMatrix.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/products/SelfadjointMatrixMatrix.h index ccd757cfa..91ba12081 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/products/SelfadjointMatrixMatrix.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/products/SelfadjointMatrixMatrix.h @@ -25,6 +25,8 @@ #ifndef EIGEN_SELFADJOINT_MATRIX_MATRIX_H #define EIGEN_SELFADJOINT_MATRIX_MATRIX_H +namespace Eigen { + namespace internal { // pack a selfadjoint block diagonal for use with the gebp_kernel @@ -400,8 +402,8 @@ struct SelfadjointProductMatrix { eigen_assert(dst.rows()==m_lhs.rows() && dst.cols()==m_rhs.cols()); - const ActualLhsType lhs = LhsBlasTraits::extract(m_lhs); - const ActualRhsType rhs = RhsBlasTraits::extract(m_rhs); + typename internal::add_const_on_value_type::type lhs = LhsBlasTraits::extract(m_lhs); + typename internal::add_const_on_value_type::type rhs = RhsBlasTraits::extract(m_rhs); Scalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(m_lhs) * RhsBlasTraits::extractScalarFactor(m_rhs); @@ -424,4 +426,6 @@ struct SelfadjointProductMatrix } }; +} // end namespace Eigen + #endif // EIGEN_SELFADJOINT_MATRIX_MATRIX_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/products/SelfadjointMatrixMatrix_MKL.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/products/SelfadjointMatrixMatrix_MKL.h new file mode 100644 index 000000000..4e5c4125c --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/products/SelfadjointMatrixMatrix_MKL.h @@ -0,0 +1,295 @@ +/* + Copyright (c) 2011, Intel Corporation. All rights reserved. + + Redistribution and use in source and binary forms, with or without modification, + are permitted provided that the following conditions are met: + + * Redistributions of source code must retain the above copyright notice, this + list of conditions and the following disclaimer. + * Redistributions in binary form must reproduce the above copyright notice, + this list of conditions and the following disclaimer in the documentation + and/or other materials provided with the distribution. + * Neither the name of Intel Corporation nor the names of its contributors may + be used to endorse or promote products derived from this software without + specific prior written permission. + + THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND + ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED + WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE + DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR + ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES + (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; + LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON + ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS + SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + + ******************************************************************************** + * Content : Eigen bindings to Intel(R) MKL + * Self adjoint matrix * matrix product functionality based on ?SYMM/?HEMM. + ******************************************************************************** +*/ + +#ifndef EIGEN_SELFADJOINT_MATRIX_MATRIX_MKL_H +#define EIGEN_SELFADJOINT_MATRIX_MATRIX_MKL_H + +namespace Eigen { + +namespace internal { + + +/* Optimized selfadjoint matrix * matrix (?SYMM/?HEMM) product */ + +#define EIGEN_MKL_SYMM_L(EIGTYPE, MKLTYPE, EIGPREFIX, MKLPREFIX) \ +template \ +struct product_selfadjoint_matrix \ +{\ +\ + static EIGEN_DONT_INLINE void run( \ + Index rows, Index cols, \ + const EIGTYPE* _lhs, Index lhsStride, \ + const EIGTYPE* _rhs, Index rhsStride, \ + EIGTYPE* res, Index resStride, \ + EIGTYPE alpha) \ + { \ + char side='L', uplo='L'; \ + MKL_INT m, n, lda, ldb, ldc; \ + const EIGTYPE *a, *b; \ + MKLTYPE alpha_, beta_; \ + MatrixX##EIGPREFIX b_tmp; \ + EIGTYPE myone(1);\ +\ +/* Set transpose options */ \ +/* Set m, n, k */ \ + m = (MKL_INT)rows; \ + n = (MKL_INT)cols; \ +\ +/* Set alpha_ & beta_ */ \ + assign_scalar_eig2mkl(alpha_, alpha); \ + assign_scalar_eig2mkl(beta_, myone); \ +\ +/* Set lda, ldb, ldc */ \ + lda = (MKL_INT)lhsStride; \ + ldb = (MKL_INT)rhsStride; \ + ldc = (MKL_INT)resStride; \ +\ +/* Set a, b, c */ \ + if (LhsStorageOrder==RowMajor) uplo='U'; \ + a = _lhs; \ +\ + if (RhsStorageOrder==RowMajor) { \ + Map > rhs(_rhs,n,m,OuterStride<>(rhsStride)); \ + b_tmp = rhs.adjoint(); \ + b = b_tmp.data(); \ + ldb = b_tmp.outerStride(); \ + } else b = _rhs; \ +\ + MKLPREFIX##symm(&side, &uplo, &m, &n, &alpha_, (const MKLTYPE*)a, &lda, (const MKLTYPE*)b, &ldb, &beta_, (MKLTYPE*)res, &ldc); \ +\ + } \ +}; + + +#define EIGEN_MKL_HEMM_L(EIGTYPE, MKLTYPE, EIGPREFIX, MKLPREFIX) \ +template \ +struct product_selfadjoint_matrix \ +{\ + static EIGEN_DONT_INLINE void run( \ + Index rows, Index cols, \ + const EIGTYPE* _lhs, Index lhsStride, \ + const EIGTYPE* _rhs, Index rhsStride, \ + EIGTYPE* res, Index resStride, \ + EIGTYPE alpha) \ + { \ + char side='L', uplo='L'; \ + MKL_INT m, n, lda, ldb, ldc; \ + const EIGTYPE *a, *b; \ + MKLTYPE alpha_, beta_; \ + MatrixX##EIGPREFIX b_tmp; \ + Matrix a_tmp; \ + EIGTYPE myone(1); \ +\ +/* Set transpose options */ \ +/* Set m, n, k */ \ + m = (MKL_INT)rows; \ + n = (MKL_INT)cols; \ +\ +/* Set alpha_ & beta_ */ \ + assign_scalar_eig2mkl(alpha_, alpha); \ + assign_scalar_eig2mkl(beta_, myone); \ +\ +/* Set lda, ldb, ldc */ \ + lda = (MKL_INT)lhsStride; \ + ldb = (MKL_INT)rhsStride; \ + ldc = (MKL_INT)resStride; \ +\ +/* Set a, b, c */ \ + if (((LhsStorageOrder==ColMajor) && ConjugateLhs) || ((LhsStorageOrder==RowMajor) && (!ConjugateLhs))) { \ + Map, 0, OuterStride<> > lhs(_lhs,m,m,OuterStride<>(lhsStride)); \ + a_tmp = lhs.conjugate(); \ + a = a_tmp.data(); \ + lda = a_tmp.outerStride(); \ + } else a = _lhs; \ + if (LhsStorageOrder==RowMajor) uplo='U'; \ +\ + if (RhsStorageOrder==ColMajor && (!ConjugateRhs)) { \ + b = _rhs; } \ + else { \ + if (RhsStorageOrder==ColMajor && ConjugateRhs) { \ + Map > rhs(_rhs,m,n,OuterStride<>(rhsStride)); \ + b_tmp = rhs.conjugate(); \ + } else \ + if (ConjugateRhs) { \ + Map > rhs(_rhs,n,m,OuterStride<>(rhsStride)); \ + b_tmp = rhs.adjoint(); \ + } else { \ + Map > rhs(_rhs,n,m,OuterStride<>(rhsStride)); \ + b_tmp = rhs.transpose(); \ + } \ + b = b_tmp.data(); \ + ldb = b_tmp.outerStride(); \ + } \ +\ + MKLPREFIX##hemm(&side, &uplo, &m, &n, &alpha_, (const MKLTYPE*)a, &lda, (const MKLTYPE*)b, &ldb, &beta_, (MKLTYPE*)res, &ldc); \ +\ + } \ +}; + +EIGEN_MKL_SYMM_L(double, double, d, d) +EIGEN_MKL_SYMM_L(float, float, f, s) +EIGEN_MKL_HEMM_L(dcomplex, MKL_Complex16, cd, z) +EIGEN_MKL_HEMM_L(scomplex, MKL_Complex8, cf, c) + + +/* Optimized matrix * selfadjoint matrix (?SYMM/?HEMM) product */ + +#define EIGEN_MKL_SYMM_R(EIGTYPE, MKLTYPE, EIGPREFIX, MKLPREFIX) \ +template \ +struct product_selfadjoint_matrix \ +{\ +\ + static EIGEN_DONT_INLINE void run( \ + Index rows, Index cols, \ + const EIGTYPE* _lhs, Index lhsStride, \ + const EIGTYPE* _rhs, Index rhsStride, \ + EIGTYPE* res, Index resStride, \ + EIGTYPE alpha) \ + { \ + char side='R', uplo='L'; \ + MKL_INT m, n, lda, ldb, ldc; \ + const EIGTYPE *a, *b; \ + MKLTYPE alpha_, beta_; \ + MatrixX##EIGPREFIX b_tmp; \ + EIGTYPE myone(1);\ +\ +/* Set m, n, k */ \ + m = (MKL_INT)rows; \ + n = (MKL_INT)cols; \ +\ +/* Set alpha_ & beta_ */ \ + assign_scalar_eig2mkl(alpha_, alpha); \ + assign_scalar_eig2mkl(beta_, myone); \ +\ +/* Set lda, ldb, ldc */ \ + lda = (MKL_INT)rhsStride; \ + ldb = (MKL_INT)lhsStride; \ + ldc = (MKL_INT)resStride; \ +\ +/* Set a, b, c */ \ + if (RhsStorageOrder==RowMajor) uplo='U'; \ + a = _rhs; \ +\ + if (LhsStorageOrder==RowMajor) { \ + Map > lhs(_lhs,n,m,OuterStride<>(rhsStride)); \ + b_tmp = lhs.adjoint(); \ + b = b_tmp.data(); \ + ldb = b_tmp.outerStride(); \ + } else b = _lhs; \ +\ + MKLPREFIX##symm(&side, &uplo, &m, &n, &alpha_, (const MKLTYPE*)a, &lda, (const MKLTYPE*)b, &ldb, &beta_, (MKLTYPE*)res, &ldc); \ +\ + } \ +}; + + +#define EIGEN_MKL_HEMM_R(EIGTYPE, MKLTYPE, EIGPREFIX, MKLPREFIX) \ +template \ +struct product_selfadjoint_matrix \ +{\ + static EIGEN_DONT_INLINE void run( \ + Index rows, Index cols, \ + const EIGTYPE* _lhs, Index lhsStride, \ + const EIGTYPE* _rhs, Index rhsStride, \ + EIGTYPE* res, Index resStride, \ + EIGTYPE alpha) \ + { \ + char side='R', uplo='L'; \ + MKL_INT m, n, lda, ldb, ldc; \ + const EIGTYPE *a, *b; \ + MKLTYPE alpha_, beta_; \ + MatrixX##EIGPREFIX b_tmp; \ + Matrix a_tmp; \ + EIGTYPE myone(1); \ +\ +/* Set m, n, k */ \ + m = (MKL_INT)rows; \ + n = (MKL_INT)cols; \ +\ +/* Set alpha_ & beta_ */ \ + assign_scalar_eig2mkl(alpha_, alpha); \ + assign_scalar_eig2mkl(beta_, myone); \ +\ +/* Set lda, ldb, ldc */ \ + lda = (MKL_INT)rhsStride; \ + ldb = (MKL_INT)lhsStride; \ + ldc = (MKL_INT)resStride; \ +\ +/* Set a, b, c */ \ + if (((RhsStorageOrder==ColMajor) && ConjugateRhs) || ((RhsStorageOrder==RowMajor) && (!ConjugateRhs))) { \ + Map, 0, OuterStride<> > rhs(_rhs,n,n,OuterStride<>(rhsStride)); \ + a_tmp = rhs.conjugate(); \ + a = a_tmp.data(); \ + lda = a_tmp.outerStride(); \ + } else a = _rhs; \ + if (RhsStorageOrder==RowMajor) uplo='U'; \ +\ + if (LhsStorageOrder==ColMajor && (!ConjugateLhs)) { \ + b = _lhs; } \ + else { \ + if (LhsStorageOrder==ColMajor && ConjugateLhs) { \ + Map > lhs(_lhs,m,n,OuterStride<>(lhsStride)); \ + b_tmp = lhs.conjugate(); \ + } else \ + if (ConjugateLhs) { \ + Map > lhs(_lhs,n,m,OuterStride<>(lhsStride)); \ + b_tmp = lhs.adjoint(); \ + } else { \ + Map > lhs(_lhs,n,m,OuterStride<>(lhsStride)); \ + b_tmp = lhs.transpose(); \ + } \ + b = b_tmp.data(); \ + ldb = b_tmp.outerStride(); \ + } \ +\ + MKLPREFIX##hemm(&side, &uplo, &m, &n, &alpha_, (const MKLTYPE*)a, &lda, (const MKLTYPE*)b, &ldb, &beta_, (MKLTYPE*)res, &ldc); \ + } \ +}; + +EIGEN_MKL_SYMM_R(double, double, d, d) +EIGEN_MKL_SYMM_R(float, float, f, s) +EIGEN_MKL_HEMM_R(dcomplex, MKL_Complex16, cd, z) +EIGEN_MKL_HEMM_R(scomplex, MKL_Complex8, cf, c) + +} // end namespace internal + +} // end namespace Eigen + +#endif // EIGEN_SELFADJOINT_MATRIX_MATRIX_MKL_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/products/SelfadjointMatrixVector.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/products/SelfadjointMatrixVector.h index d6121fc07..7f39ef01a 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/products/SelfadjointMatrixVector.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/products/SelfadjointMatrixVector.h @@ -25,6 +25,8 @@ #ifndef EIGEN_SELFADJOINT_MATRIX_VECTOR_H #define EIGEN_SELFADJOINT_MATRIX_VECTOR_H +namespace Eigen { + namespace internal { /* Optimized selfadjoint matrix * vector product: @@ -32,8 +34,15 @@ namespace internal { * the number of load/stores of the result by a factor 2 and to reduce * the instruction dependency. */ -template -static EIGEN_DONT_INLINE void product_selfadjoint_vector( + +template +struct selfadjoint_matrix_vector_product; + +template +struct selfadjoint_matrix_vector_product + +{ +static EIGEN_DONT_INLINE void run( Index size, const Scalar* lhs, Index lhsStride, const Scalar* _rhs, Index rhsIncr, @@ -85,14 +94,14 @@ static EIGEN_DONT_INLINE void product_selfadjoint_vector( Scalar t1 = cjAlpha * rhs[j+1]; Packet ptmp1 = pset1(t1); - Scalar t2 = 0; + Scalar t2(0); Packet ptmp2 = pset1(t2); - Scalar t3 = 0; + Scalar t3(0); Packet ptmp3 = pset1(t3); size_t starti = FirstTriangular ? 0 : j+2; size_t endi = FirstTriangular ? j : size; - size_t alignedStart = (starti) + first_aligned(&res[starti], endi-starti); + size_t alignedStart = (starti) + internal::first_aligned(&res[starti], endi-starti); size_t alignedEnd = alignedStart + ((endi-alignedStart)/(PacketSize))*(PacketSize); // TODO make sure this product is a real * complex and that the rhs is properly conjugated if needed @@ -148,7 +157,7 @@ static EIGEN_DONT_INLINE void product_selfadjoint_vector( register const Scalar* EIGEN_RESTRICT A0 = lhs + j*lhsStride; Scalar t1 = cjAlpha * rhs[j]; - Scalar t2 = 0; + Scalar t2(0); // TODO make sure this product is a real * complex and that the rhs is properly conjugated if needed res[j] += cjd.pmul(internal::real(A0[j]), t1); for (Index i=FirstTriangular ? 0 : j+1; i<(FirstTriangular ? j : size); i++) @@ -159,6 +168,7 @@ static EIGEN_DONT_INLINE void product_selfadjoint_vector( res[j] += alpha * t2; } } +}; } // end namespace internal @@ -193,8 +203,8 @@ struct SelfadjointProductMatrix eigen_assert(dest.rows()==m_lhs.rows() && dest.cols()==m_rhs.cols()); - const ActualLhsType lhs = LhsBlasTraits::extract(m_lhs); - const ActualRhsType rhs = RhsBlasTraits::extract(m_rhs); + typename internal::add_const_on_value_type::type lhs = LhsBlasTraits::extract(m_lhs); + typename internal::add_const_on_value_type::type rhs = RhsBlasTraits::extract(m_rhs); Scalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(m_lhs) * RhsBlasTraits::extractScalarFactor(m_rhs); @@ -232,7 +242,7 @@ struct SelfadjointProductMatrix } - internal::product_selfadjoint_vector::Flags&RowMajorBit) ? RowMajor : ColMajor, int(LhsUpLo), bool(LhsBlasTraits::NeedToConjugate), bool(RhsBlasTraits::NeedToConjugate)> + internal::selfadjoint_matrix_vector_product::Flags&RowMajorBit) ? RowMajor : ColMajor, int(LhsUpLo), bool(LhsBlasTraits::NeedToConjugate), bool(RhsBlasTraits::NeedToConjugate)>::run ( lhs.rows(), // size &lhs.coeffRef(0,0), lhs.outerStride(), // lhs info @@ -274,5 +284,6 @@ struct SelfadjointProductMatrix } }; +} // end namespace Eigen #endif // EIGEN_SELFADJOINT_MATRIX_VECTOR_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/products/SelfadjointMatrixVector_MKL.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/products/SelfadjointMatrixVector_MKL.h new file mode 100644 index 000000000..f88d483b6 --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/products/SelfadjointMatrixVector_MKL.h @@ -0,0 +1,114 @@ +/* + Copyright (c) 2011, Intel Corporation. All rights reserved. + + Redistribution and use in source and binary forms, with or without modification, + are permitted provided that the following conditions are met: + + * Redistributions of source code must retain the above copyright notice, this + list of conditions and the following disclaimer. + * Redistributions in binary form must reproduce the above copyright notice, + this list of conditions and the following disclaimer in the documentation + and/or other materials provided with the distribution. + * Neither the name of Intel Corporation nor the names of its contributors may + be used to endorse or promote products derived from this software without + specific prior written permission. + + THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND + ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED + WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE + DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR + ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES + (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; + LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON + ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS + SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + + ******************************************************************************** + * Content : Eigen bindings to Intel(R) MKL + * Selfadjoint matrix-vector product functionality based on ?SYMV/HEMV. + ******************************************************************************** +*/ + +#ifndef EIGEN_SELFADJOINT_MATRIX_VECTOR_MKL_H +#define EIGEN_SELFADJOINT_MATRIX_VECTOR_MKL_H + +namespace Eigen { + +namespace internal { + +/********************************************************************** +* This file implements selfadjoint matrix-vector multiplication using BLAS +**********************************************************************/ + +// symv/hemv specialization + +template +struct selfadjoint_matrix_vector_product_symv : + selfadjoint_matrix_vector_product {}; + +#define EIGEN_MKL_SYMV_SPECIALIZE(Scalar) \ +template \ +struct selfadjoint_matrix_vector_product { \ +static EIGEN_DONT_INLINE void run( \ + Index size, const Scalar* lhs, Index lhsStride, \ + const Scalar* _rhs, Index rhsIncr, Scalar* res, Scalar alpha) { \ + enum {\ + IsColMajor = StorageOrder==ColMajor \ + }; \ + if (IsColMajor == ConjugateLhs) {\ + selfadjoint_matrix_vector_product::run( \ + size, lhs, lhsStride, _rhs, rhsIncr, res, alpha); \ + } else {\ + selfadjoint_matrix_vector_product_symv::run( \ + size, lhs, lhsStride, _rhs, rhsIncr, res, alpha); \ + }\ + } \ +}; \ + +EIGEN_MKL_SYMV_SPECIALIZE(double) +EIGEN_MKL_SYMV_SPECIALIZE(float) +EIGEN_MKL_SYMV_SPECIALIZE(dcomplex) +EIGEN_MKL_SYMV_SPECIALIZE(scomplex) + +#define EIGEN_MKL_SYMV_SPECIALIZATION(EIGTYPE,MKLTYPE,MKLFUNC) \ +template \ +struct selfadjoint_matrix_vector_product_symv \ +{ \ +typedef Matrix SYMVVector;\ +\ +static EIGEN_DONT_INLINE void run( \ +Index size, const EIGTYPE* lhs, Index lhsStride, \ +const EIGTYPE* _rhs, Index rhsIncr, EIGTYPE* res, EIGTYPE alpha) \ +{ \ + enum {\ + IsRowMajor = StorageOrder==RowMajor ? 1 : 0, \ + IsLower = UpLo == Lower ? 1 : 0 \ + }; \ + MKL_INT n=size, lda=lhsStride, incx=rhsIncr, incy=1; \ + MKLTYPE alpha_, beta_; \ + const EIGTYPE *x_ptr, myone(1); \ + char uplo=(IsRowMajor) ? (IsLower ? 'U' : 'L') : (IsLower ? 'L' : 'U'); \ + assign_scalar_eig2mkl(alpha_, alpha); \ + assign_scalar_eig2mkl(beta_, myone); \ + SYMVVector x_tmp; \ + if (ConjugateRhs) { \ + Map > map_x(_rhs,size,1,InnerStride<>(incx)); \ + x_tmp=map_x.conjugate(); \ + x_ptr=x_tmp.data(); \ + incx=1; \ + } else x_ptr=_rhs; \ + MKLFUNC(&uplo, &n, &alpha_, (const MKLTYPE*)lhs, &lda, (const MKLTYPE*)x_ptr, &incx, &beta_, (MKLTYPE*)res, &incy); \ +}\ +}; + +EIGEN_MKL_SYMV_SPECIALIZATION(double, double, dsymv) +EIGEN_MKL_SYMV_SPECIALIZATION(float, float, ssymv) +EIGEN_MKL_SYMV_SPECIALIZATION(dcomplex, MKL_Complex16, zhemv) +EIGEN_MKL_SYMV_SPECIALIZATION(scomplex, MKL_Complex8, chemv) + +} // end namespace internal + +} // end namespace Eigen + +#endif // EIGEN_SELFADJOINT_MATRIX_VECTOR_MKL_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/products/SelfadjointProduct.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/products/SelfadjointProduct.h index 3a4523fa4..a3ff9e3e7 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/products/SelfadjointProduct.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/products/SelfadjointProduct.h @@ -31,6 +31,8 @@ * It corresponds to the level 3 SYRK and level 2 SYR Blas routines. **********************************************************************/ +namespace Eigen { + template struct selfadjoint_rank1_update; @@ -72,7 +74,7 @@ struct selfadjoint_product_selector typedef internal::blas_traits OtherBlasTraits; typedef typename OtherBlasTraits::DirectLinearAccessType ActualOtherType; typedef typename internal::remove_all::type _ActualOtherType; - const ActualOtherType actualOther = OtherBlasTraits::extract(other.derived()); + typename internal::add_const_on_value_type::type actualOther = OtherBlasTraits::extract(other.derived()); Scalar actualAlpha = alpha * OtherBlasTraits::extractScalarFactor(other.derived()); @@ -105,12 +107,12 @@ struct selfadjoint_product_selector typedef internal::blas_traits OtherBlasTraits; typedef typename OtherBlasTraits::DirectLinearAccessType ActualOtherType; typedef typename internal::remove_all::type _ActualOtherType; - const ActualOtherType actualOther = OtherBlasTraits::extract(other.derived()); + typename internal::add_const_on_value_type::type actualOther = OtherBlasTraits::extract(other.derived()); Scalar actualAlpha = alpha * OtherBlasTraits::extractScalarFactor(other.derived()); enum { IsRowMajor = (internal::traits::Flags&RowMajorBit) ? 1 : 0 }; - + internal::general_matrix_matrix_triangular_product::IsComplex, Scalar, _ActualOtherType::Flags&RowMajorBit ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits::IsComplex, @@ -133,4 +135,6 @@ SelfAdjointView& SelfAdjointView return *this; } +} // end namespace Eigen + #endif // EIGEN_SELFADJOINT_PRODUCT_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/products/SelfadjointRank2Update.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/products/SelfadjointRank2Update.h index 9f8b8438a..001cfb591 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/products/SelfadjointRank2Update.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/products/SelfadjointRank2Update.h @@ -25,6 +25,8 @@ #ifndef EIGEN_SELFADJOINTRANK2UPTADE_H #define EIGEN_SELFADJOINTRANK2UPTADE_H +namespace Eigen { + namespace internal { /* Optimized selfadjoint matrix += alpha * uv' + conj(alpha)*vu' @@ -76,12 +78,12 @@ SelfAdjointView& SelfAdjointView typedef internal::blas_traits UBlasTraits; typedef typename UBlasTraits::DirectLinearAccessType ActualUType; typedef typename internal::remove_all::type _ActualUType; - const ActualUType actualU = UBlasTraits::extract(u.derived()); + typename internal::add_const_on_value_type::type actualU = UBlasTraits::extract(u.derived()); typedef internal::blas_traits VBlasTraits; typedef typename VBlasTraits::DirectLinearAccessType ActualVType; typedef typename internal::remove_all::type _ActualVType; - const ActualVType actualV = VBlasTraits::extract(v.derived()); + typename internal::add_const_on_value_type::type actualV = VBlasTraits::extract(v.derived()); // If MatrixType is row major, then we use the routine for lower triangular in the upper triangular case and // vice versa, and take the complex conjugate of all coefficients and vector entries. @@ -101,4 +103,6 @@ SelfAdjointView& SelfAdjointView return *this; } +} // end namespace Eigen + #endif // EIGEN_SELFADJOINTRANK2UPTADE_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/products/TriangularMatrixMatrix.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/products/TriangularMatrixMatrix.h index 0c48d2efb..06053bfd9 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/products/TriangularMatrixMatrix.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/products/TriangularMatrixMatrix.h @@ -25,6 +25,8 @@ #ifndef EIGEN_TRIANGULAR_MATRIX_MATRIX_H #define EIGEN_TRIANGULAR_MATRIX_MATRIX_H +namespace Eigen { + namespace internal { // template @@ -58,16 +60,16 @@ template + int ResStorageOrder, int Version = Specialized> struct product_triangular_matrix_matrix; template + int RhsStorageOrder, bool ConjugateRhs, int Version> struct product_triangular_matrix_matrix + RhsStorageOrder,ConjugateRhs,RowMajor,Version> { static EIGEN_STRONG_INLINE void run( Index rows, Index cols, Index depth, @@ -91,15 +93,15 @@ struct product_triangular_matrix_matrix + int RhsStorageOrder, bool ConjugateRhs, int Version> struct product_triangular_matrix_matrix + RhsStorageOrder,ConjugateRhs,ColMajor,Version> { typedef gebp_traits Traits; enum { - SmallPanelWidth = EIGEN_PLAIN_ENUM_MAX(Traits::mr,Traits::nr), + SmallPanelWidth = 2 * EIGEN_PLAIN_ENUM_MAX(Traits::mr,Traits::nr), IsLower = (Mode&Lower) == Lower, SetDiag = (Mode&(ZeroDiag|UnitDiag)) ? 0 : 1 }; @@ -220,10 +222,10 @@ struct product_triangular_matrix_matrix + int RhsStorageOrder, bool ConjugateRhs, int Version> struct product_triangular_matrix_matrix + RhsStorageOrder,ConjugateRhs,ColMajor,Version> { typedef gebp_traits Traits; enum { @@ -378,8 +380,8 @@ struct TriangularProduct template void scaleAndAddTo(Dest& dst, Scalar alpha) const { - const ActualLhsType lhs = LhsBlasTraits::extract(m_lhs); - const ActualRhsType rhs = RhsBlasTraits::extract(m_rhs); + typename internal::add_const_on_value_type::type lhs = LhsBlasTraits::extract(m_lhs); + typename internal::add_const_on_value_type::type rhs = RhsBlasTraits::extract(m_rhs); Scalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(m_lhs) * RhsBlasTraits::extractScalarFactor(m_rhs); @@ -399,5 +401,6 @@ struct TriangularProduct } }; +} // end namespace Eigen #endif // EIGEN_TRIANGULAR_MATRIX_MATRIX_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/products/TriangularMatrixMatrix_MKL.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/products/TriangularMatrixMatrix_MKL.h new file mode 100644 index 000000000..8173da5bb --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/products/TriangularMatrixMatrix_MKL.h @@ -0,0 +1,309 @@ +/* + Copyright (c) 2011, Intel Corporation. All rights reserved. + + Redistribution and use in source and binary forms, with or without modification, + are permitted provided that the following conditions are met: + + * Redistributions of source code must retain the above copyright notice, this + list of conditions and the following disclaimer. + * Redistributions in binary form must reproduce the above copyright notice, + this list of conditions and the following disclaimer in the documentation + and/or other materials provided with the distribution. + * Neither the name of Intel Corporation nor the names of its contributors may + be used to endorse or promote products derived from this software without + specific prior written permission. + + THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND + ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED + WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE + DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR + ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES + (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; + LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON + ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS + SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + + ******************************************************************************** + * Content : Eigen bindings to Intel(R) MKL + * Triangular matrix * matrix product functionality based on ?TRMM. + ******************************************************************************** +*/ + +#ifndef EIGEN_TRIANGULAR_MATRIX_MATRIX_MKL_H +#define EIGEN_TRIANGULAR_MATRIX_MATRIX_MKL_H + +namespace Eigen { + +namespace internal { + + +template +struct product_triangular_matrix_matrix_trmm : + product_triangular_matrix_matrix {}; + + +// try to go to BLAS specialization +#define EIGEN_MKL_TRMM_SPECIALIZE(Scalar, LhsIsTriangular) \ +template \ +struct product_triangular_matrix_matrix { \ + static inline void run(Index _rows, Index _cols, Index _depth, const Scalar* _lhs, Index lhsStride,\ + const Scalar* _rhs, Index rhsStride, Scalar* res, Index resStride, Scalar alpha) { \ + product_triangular_matrix_matrix_trmm::run( \ + _rows, _cols, _depth, _lhs, lhsStride, _rhs, rhsStride, res, resStride, alpha); \ + } \ +}; + +EIGEN_MKL_TRMM_SPECIALIZE(double, true) +EIGEN_MKL_TRMM_SPECIALIZE(double, false) +EIGEN_MKL_TRMM_SPECIALIZE(dcomplex, true) +EIGEN_MKL_TRMM_SPECIALIZE(dcomplex, false) +EIGEN_MKL_TRMM_SPECIALIZE(float, true) +EIGEN_MKL_TRMM_SPECIALIZE(float, false) +EIGEN_MKL_TRMM_SPECIALIZE(scomplex, true) +EIGEN_MKL_TRMM_SPECIALIZE(scomplex, false) + +// implements col-major += alpha * op(triangular) * op(general) +#define EIGEN_MKL_TRMM_L(EIGTYPE, MKLTYPE, EIGPREFIX, MKLPREFIX) \ +template \ +struct product_triangular_matrix_matrix_trmm \ +{ \ + enum { \ + IsLower = (Mode&Lower) == Lower, \ + SetDiag = (Mode&(ZeroDiag|UnitDiag)) ? 0 : 1, \ + IsUnitDiag = (Mode&UnitDiag) ? 1 : 0, \ + IsZeroDiag = (Mode&ZeroDiag) ? 1 : 0, \ + LowUp = IsLower ? Lower : Upper, \ + conjA = ((LhsStorageOrder==ColMajor) && ConjugateLhs) ? 1 : 0 \ + }; \ +\ + static EIGEN_DONT_INLINE void run( \ + Index _rows, Index _cols, Index _depth, \ + const EIGTYPE* _lhs, Index lhsStride, \ + const EIGTYPE* _rhs, Index rhsStride, \ + EIGTYPE* res, Index resStride, \ + EIGTYPE alpha) \ + { \ + Index diagSize = (std::min)(_rows,_depth); \ + Index rows = IsLower ? _rows : diagSize; \ + Index depth = IsLower ? diagSize : _depth; \ + Index cols = _cols; \ +\ + typedef Matrix MatrixLhs; \ + typedef Matrix MatrixRhs; \ +\ +/* Non-square case - doesn't fit to MKL ?TRMM. Fall to default triangular product or call MKL ?GEMM*/ \ + if (rows != depth) { \ +\ + int nthr = mkl_domain_get_max_threads(MKL_BLAS); \ +\ + if (((nthr==1) && (((std::max)(rows,depth)-diagSize)/(double)diagSize < 0.5))) { \ + /* Most likely no benefit to call TRMM or GEMM from MKL*/ \ + product_triangular_matrix_matrix::run( \ + _rows, _cols, _depth, _lhs, lhsStride, _rhs, rhsStride, res, resStride, alpha); \ + /*std::cout << "TRMM_L: A is not square! Go to Eigen TRMM implementation!\n";*/ \ + } else { \ + /* Make sense to call GEMM */ \ + Map > lhsMap(_lhs,rows,depth,OuterStride<>(lhsStride)); \ + MatrixLhs aa_tmp=lhsMap.template triangularView(); \ + MKL_INT aStride = aa_tmp.outerStride(); \ + gemm_blocking_space blocking(_rows,_cols,_depth); \ + general_matrix_matrix_product::run( \ + rows, cols, depth, aa_tmp.data(), aStride, _rhs, rhsStride, res, resStride, alpha, blocking, 0); \ +\ + /*std::cout << "TRMM_L: A is not square! Go to MKL GEMM implementation! " << nthr<<" \n";*/ \ + } \ + return; \ + } \ + char side = 'L', transa, uplo, diag = 'N'; \ + EIGTYPE *b; \ + const EIGTYPE *a; \ + MKL_INT m, n, lda, ldb; \ + MKLTYPE alpha_; \ +\ +/* Set alpha_*/ \ + assign_scalar_eig2mkl(alpha_, alpha); \ +\ +/* Set m, n */ \ + m = (MKL_INT)diagSize; \ + n = (MKL_INT)cols; \ +\ +/* Set trans */ \ + transa = (LhsStorageOrder==RowMajor) ? ((ConjugateLhs) ? 'C' : 'T') : 'N'; \ +\ +/* Set b, ldb */ \ + Map > rhs(_rhs,depth,cols,OuterStride<>(rhsStride)); \ + MatrixX##EIGPREFIX b_tmp; \ +\ + if (ConjugateRhs) b_tmp = rhs.conjugate(); else b_tmp = rhs; \ + b = b_tmp.data(); \ + ldb = b_tmp.outerStride(); \ +\ +/* Set uplo */ \ + uplo = IsLower ? 'L' : 'U'; \ + if (LhsStorageOrder==RowMajor) uplo = (uplo == 'L') ? 'U' : 'L'; \ +/* Set a, lda */ \ + Map > lhs(_lhs,rows,depth,OuterStride<>(lhsStride)); \ + MatrixLhs a_tmp; \ +\ + if ((conjA!=0) || (SetDiag==0)) { \ + if (conjA) a_tmp = lhs.conjugate(); else a_tmp = lhs; \ + if (IsZeroDiag) \ + a_tmp.diagonal().setZero(); \ + else if (IsUnitDiag) \ + a_tmp.diagonal().setOnes();\ + a = a_tmp.data(); \ + lda = a_tmp.outerStride(); \ + } else { \ + a = _lhs; \ + lda = lhsStride; \ + } \ + /*std::cout << "TRMM_L: A is square! Go to MKL TRMM implementation! \n";*/ \ +/* call ?trmm*/ \ + MKLPREFIX##trmm(&side, &uplo, &transa, &diag, &m, &n, &alpha_, (const MKLTYPE*)a, &lda, (MKLTYPE*)b, &ldb); \ +\ +/* Add op(a_triangular)*b into res*/ \ + Map > res_tmp(res,rows,cols,OuterStride<>(resStride)); \ + res_tmp=res_tmp+b_tmp; \ + } \ +}; + +EIGEN_MKL_TRMM_L(double, double, d, d) +EIGEN_MKL_TRMM_L(dcomplex, MKL_Complex16, cd, z) +EIGEN_MKL_TRMM_L(float, float, f, s) +EIGEN_MKL_TRMM_L(scomplex, MKL_Complex8, cf, c) + +// implements col-major += alpha * op(general) * op(triangular) +#define EIGEN_MKL_TRMM_R(EIGTYPE, MKLTYPE, EIGPREFIX, MKLPREFIX) \ +template \ +struct product_triangular_matrix_matrix_trmm \ +{ \ + enum { \ + IsLower = (Mode&Lower) == Lower, \ + SetDiag = (Mode&(ZeroDiag|UnitDiag)) ? 0 : 1, \ + IsUnitDiag = (Mode&UnitDiag) ? 1 : 0, \ + IsZeroDiag = (Mode&ZeroDiag) ? 1 : 0, \ + LowUp = IsLower ? Lower : Upper, \ + conjA = ((RhsStorageOrder==ColMajor) && ConjugateRhs) ? 1 : 0 \ + }; \ +\ + static EIGEN_DONT_INLINE void run( \ + Index _rows, Index _cols, Index _depth, \ + const EIGTYPE* _lhs, Index lhsStride, \ + const EIGTYPE* _rhs, Index rhsStride, \ + EIGTYPE* res, Index resStride, \ + EIGTYPE alpha) \ + { \ + Index diagSize = (std::min)(_cols,_depth); \ + Index rows = _rows; \ + Index depth = IsLower ? _depth : diagSize; \ + Index cols = IsLower ? diagSize : _cols; \ +\ + typedef Matrix MatrixLhs; \ + typedef Matrix MatrixRhs; \ +\ +/* Non-square case - doesn't fit to MKL ?TRMM. Fall to default triangular product or call MKL ?GEMM*/ \ + if (cols != depth) { \ +\ + int nthr = mkl_domain_get_max_threads(MKL_BLAS); \ +\ + if ((nthr==1) && (((std::max)(cols,depth)-diagSize)/(double)diagSize < 0.5)) { \ + /* Most likely no benefit to call TRMM or GEMM from MKL*/ \ + product_triangular_matrix_matrix::run( \ + _rows, _cols, _depth, _lhs, lhsStride, _rhs, rhsStride, res, resStride, alpha); \ + /*std::cout << "TRMM_R: A is not square! Go to Eigen TRMM implementation!\n";*/ \ + } else { \ + /* Make sense to call GEMM */ \ + Map > rhsMap(_rhs,depth,cols, OuterStride<>(rhsStride)); \ + MatrixRhs aa_tmp=rhsMap.template triangularView(); \ + MKL_INT aStride = aa_tmp.outerStride(); \ + gemm_blocking_space blocking(_rows,_cols,_depth); \ + general_matrix_matrix_product::run( \ + rows, cols, depth, _lhs, lhsStride, aa_tmp.data(), aStride, res, resStride, alpha, blocking, 0); \ +\ + /*std::cout << "TRMM_R: A is not square! Go to MKL GEMM implementation! " << nthr<<" \n";*/ \ + } \ + return; \ + } \ + char side = 'R', transa, uplo, diag = 'N'; \ + EIGTYPE *b; \ + const EIGTYPE *a; \ + MKL_INT m, n, lda, ldb; \ + MKLTYPE alpha_; \ +\ +/* Set alpha_*/ \ + assign_scalar_eig2mkl(alpha_, alpha); \ +\ +/* Set m, n */ \ + m = (MKL_INT)rows; \ + n = (MKL_INT)diagSize; \ +\ +/* Set trans */ \ + transa = (RhsStorageOrder==RowMajor) ? ((ConjugateRhs) ? 'C' : 'T') : 'N'; \ +\ +/* Set b, ldb */ \ + Map > lhs(_lhs,rows,depth,OuterStride<>(lhsStride)); \ + MatrixX##EIGPREFIX b_tmp; \ +\ + if (ConjugateLhs) b_tmp = lhs.conjugate(); else b_tmp = lhs; \ + b = b_tmp.data(); \ + ldb = b_tmp.outerStride(); \ +\ +/* Set uplo */ \ + uplo = IsLower ? 'L' : 'U'; \ + if (RhsStorageOrder==RowMajor) uplo = (uplo == 'L') ? 'U' : 'L'; \ +/* Set a, lda */ \ + Map > rhs(_rhs,depth,cols, OuterStride<>(rhsStride)); \ + MatrixRhs a_tmp; \ +\ + if ((conjA!=0) || (SetDiag==0)) { \ + if (conjA) a_tmp = rhs.conjugate(); else a_tmp = rhs; \ + if (IsZeroDiag) \ + a_tmp.diagonal().setZero(); \ + else if (IsUnitDiag) \ + a_tmp.diagonal().setOnes();\ + a = a_tmp.data(); \ + lda = a_tmp.outerStride(); \ + } else { \ + a = _rhs; \ + lda = rhsStride; \ + } \ + /*std::cout << "TRMM_R: A is square! Go to MKL TRMM implementation! \n";*/ \ +/* call ?trmm*/ \ + MKLPREFIX##trmm(&side, &uplo, &transa, &diag, &m, &n, &alpha_, (const MKLTYPE*)a, &lda, (MKLTYPE*)b, &ldb); \ +\ +/* Add op(a_triangular)*b into res*/ \ + Map > res_tmp(res,rows,cols,OuterStride<>(resStride)); \ + res_tmp=res_tmp+b_tmp; \ + } \ +}; + +EIGEN_MKL_TRMM_R(double, double, d, d) +EIGEN_MKL_TRMM_R(dcomplex, MKL_Complex16, cd, z) +EIGEN_MKL_TRMM_R(float, float, f, s) +EIGEN_MKL_TRMM_R(scomplex, MKL_Complex8, cf, c) + +} // end namespace internal + +} // end namespace Eigen + +#endif // EIGEN_TRIANGULAR_MATRIX_MATRIX_MKL_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/products/TriangularMatrixVector.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/products/TriangularMatrixVector.h index 71b4a52ab..e1dc0c23e 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/products/TriangularMatrixVector.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/products/TriangularMatrixVector.h @@ -25,23 +25,29 @@ #ifndef EIGEN_TRIANGULARMATRIXVECTOR_H #define EIGEN_TRIANGULARMATRIXVECTOR_H +namespace Eigen { + namespace internal { -template -struct product_triangular_matrix_vector; +template +struct triangular_matrix_vector_product; -template -struct product_triangular_matrix_vector +template +struct triangular_matrix_vector_product { typedef typename scalar_product_traits::ReturnType ResScalar; enum { IsLower = ((Mode&Lower)==Lower), - HasUnitDiag = (Mode & UnitDiag)==UnitDiag + HasUnitDiag = (Mode & UnitDiag)==UnitDiag, + HasZeroDiag = (Mode & ZeroDiag)==ZeroDiag }; - static EIGEN_DONT_INLINE void run(Index rows, Index cols, const LhsScalar* _lhs, Index lhsStride, + static EIGEN_DONT_INLINE void run(Index _rows, Index _cols, const LhsScalar* _lhs, Index lhsStride, const RhsScalar* _rhs, Index rhsIncr, ResScalar* _res, Index resIncr, ResScalar alpha) { static const Index PanelWidth = EIGEN_TUNE_TRIANGULAR_PANEL_WIDTH; + Index size = (std::min)(_rows,_cols); + Index rows = IsLower ? _rows : (std::min)(_rows,_cols); + Index cols = IsLower ? (std::min)(_rows,_cols) : _cols; typedef Map, 0, OuterStride<> > LhsMap; const LhsMap lhs(_lhs,rows,cols,OuterStride<>(lhsStride)); @@ -54,45 +60,57 @@ struct product_triangular_matrix_vector > ResMap; ResMap res(_res,rows); - for (Index pi=0; pi0) + if ((!(HasUnitDiag||HasZeroDiag)) || (--r)>0) res.segment(s,r) += (alpha * cjRhs.coeff(i)) * cjLhs.col(i).segment(s,r); if (HasUnitDiag) res.coeffRef(i) += alpha * cjRhs.coeff(i); } - Index r = IsLower ? cols - pi - actualPanelWidth : pi; + Index r = IsLower ? rows - pi - actualPanelWidth : pi; if (r>0) { Index s = IsLower ? pi+actualPanelWidth : 0; - general_matrix_vector_product::run( + general_matrix_vector_product::run( r, actualPanelWidth, &lhs.coeffRef(s,pi), lhsStride, &rhs.coeffRef(pi), rhsIncr, &res.coeffRef(s), resIncr, alpha); } } + if((!IsLower) && cols>size) + { + general_matrix_vector_product::run( + rows, cols-size, + &lhs.coeffRef(0,size), lhsStride, + &rhs.coeffRef(size), rhsIncr, + _res, resIncr, alpha); + } } }; -template -struct product_triangular_matrix_vector +template +struct triangular_matrix_vector_product { typedef typename scalar_product_traits::ReturnType ResScalar; enum { IsLower = ((Mode&Lower)==Lower), - HasUnitDiag = (Mode & UnitDiag)==UnitDiag + HasUnitDiag = (Mode & UnitDiag)==UnitDiag, + HasZeroDiag = (Mode & ZeroDiag)==ZeroDiag }; - static void run(Index rows, Index cols, const LhsScalar* _lhs, Index lhsStride, + static void run(Index _rows, Index _cols, const LhsScalar* _lhs, Index lhsStride, const RhsScalar* _rhs, Index rhsIncr, ResScalar* _res, Index resIncr, ResScalar alpha) { static const Index PanelWidth = EIGEN_TUNE_TRIANGULAR_PANEL_WIDTH; + Index diagSize = (std::min)(_rows,_cols); + Index rows = IsLower ? _rows : diagSize; + Index cols = IsLower ? diagSize : _cols; typedef Map, 0, OuterStride<> > LhsMap; const LhsMap lhs(_lhs,rows,cols,OuterStride<>(lhsStride)); @@ -105,15 +123,15 @@ struct product_triangular_matrix_vector, 0, InnerStride<> > ResMap; ResMap res(_res,rows,InnerStride<>(resIncr)); - for (Index pi=0; pi0) + if ((!(HasUnitDiag||HasZeroDiag)) || (--r)>0) res.coeffRef(i) += alpha * (cjLhs.row(i).segment(s,r).cwiseProduct(cjRhs.segment(s,r).transpose())).sum(); if (HasUnitDiag) res.coeffRef(i) += alpha * cjRhs.coeff(i); @@ -122,13 +140,21 @@ struct product_triangular_matrix_vector0) { Index s = IsLower ? 0 : pi + actualPanelWidth; - general_matrix_vector_product::run( + general_matrix_vector_product::run( actualPanelWidth, r, &lhs.coeffRef(pi,s), lhsStride, &rhs.coeffRef(s), rhsIncr, &res.coeffRef(pi), resIncr, alpha); } } + if(IsLower && rows>diagSize) + { + general_matrix_vector_product::run( + rows-diagSize, cols, + &lhs.coeffRef(diagSize,0), lhsStride, + &rhs.coeffRef(0), rhsIncr, + &res.coeffRef(diagSize), resIncr, alpha); + } } }; @@ -180,7 +206,7 @@ struct TriangularProduct { eigen_assert(dst.rows()==m_lhs.rows() && dst.cols()==m_rhs.cols()); - typedef TriangularProduct<(Mode & UnitDiag) | ((Mode & Lower) ? Upper : Lower),true,Transpose,false,Transpose,true> TriangularProductTranspose; + typedef TriangularProduct<(Mode & (UnitDiag|ZeroDiag)) | ((Mode & Lower) ? Upper : Lower),true,Transpose,false,Transpose,true> TriangularProductTranspose; Transpose dstT(dst); internal::trmv_selector<(int(internal::traits::Flags)&RowMajorBit) ? ColMajor : RowMajor>::run( TriangularProductTranspose(m_rhs.transpose(),m_lhs.transpose()), dstT, alpha); @@ -208,8 +234,8 @@ template<> struct trmv_selector typedef typename ProductType::RhsBlasTraits RhsBlasTraits; typedef Map, Aligned> MappedDest; - const ActualLhsType actualLhs = LhsBlasTraits::extract(prod.lhs()); - const ActualRhsType actualRhs = RhsBlasTraits::extract(prod.rhs()); + typename internal::add_const_on_value_type::type actualLhs = LhsBlasTraits::extract(prod.lhs()); + typename internal::add_const_on_value_type::type actualRhs = RhsBlasTraits::extract(prod.rhs()); ResScalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(prod.lhs()) * RhsBlasTraits::extractScalarFactor(prod.rhs()); @@ -247,7 +273,7 @@ template<> struct trmv_selector MappedDest(actualDestPtr, dest.size()) = dest; } - internal::product_triangular_matrix_vector + internal::triangular_matrix_vector_product struct trmv_selector Map(actualRhsPtr, actualRhs.size()) = actualRhs; } - internal::product_triangular_matrix_vector + internal::triangular_matrix_vector_product struct trmv_selector } // end namespace internal +} // end namespace Eigen + #endif // EIGEN_TRIANGULARMATRIXVECTOR_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/products/TriangularMatrixVector_MKL.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/products/TriangularMatrixVector_MKL.h new file mode 100644 index 000000000..3c2c3049a --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/products/TriangularMatrixVector_MKL.h @@ -0,0 +1,247 @@ +/* + Copyright (c) 2011, Intel Corporation. All rights reserved. + + Redistribution and use in source and binary forms, with or without modification, + are permitted provided that the following conditions are met: + + * Redistributions of source code must retain the above copyright notice, this + list of conditions and the following disclaimer. + * Redistributions in binary form must reproduce the above copyright notice, + this list of conditions and the following disclaimer in the documentation + and/or other materials provided with the distribution. + * Neither the name of Intel Corporation nor the names of its contributors may + be used to endorse or promote products derived from this software without + specific prior written permission. + + THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND + ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED + WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE + DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR + ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES + (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; + LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON + ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS + SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + + ******************************************************************************** + * Content : Eigen bindings to Intel(R) MKL + * Triangular matrix-vector product functionality based on ?TRMV. + ******************************************************************************** +*/ + +#ifndef EIGEN_TRIANGULAR_MATRIX_VECTOR_MKL_H +#define EIGEN_TRIANGULAR_MATRIX_VECTOR_MKL_H + +namespace Eigen { + +namespace internal { + +/********************************************************************** +* This file implements triangular matrix-vector multiplication using BLAS +**********************************************************************/ + +// trmv/hemv specialization + +template +struct triangular_matrix_vector_product_trmv : + triangular_matrix_vector_product {}; + +#define EIGEN_MKL_TRMV_SPECIALIZE(Scalar) \ +template \ +struct triangular_matrix_vector_product { \ + static EIGEN_DONT_INLINE void run(Index _rows, Index _cols, const Scalar* _lhs, Index lhsStride, \ + const Scalar* _rhs, Index rhsIncr, Scalar* _res, Index resIncr, Scalar alpha) { \ + triangular_matrix_vector_product_trmv::run( \ + _rows, _cols, _lhs, lhsStride, _rhs, rhsIncr, _res, resIncr, alpha); \ + } \ +}; \ +template \ +struct triangular_matrix_vector_product { \ + static EIGEN_DONT_INLINE void run(Index _rows, Index _cols, const Scalar* _lhs, Index lhsStride, \ + const Scalar* _rhs, Index rhsIncr, Scalar* _res, Index resIncr, Scalar alpha) { \ + triangular_matrix_vector_product_trmv::run( \ + _rows, _cols, _lhs, lhsStride, _rhs, rhsIncr, _res, resIncr, alpha); \ + } \ +}; + +EIGEN_MKL_TRMV_SPECIALIZE(double) +EIGEN_MKL_TRMV_SPECIALIZE(float) +EIGEN_MKL_TRMV_SPECIALIZE(dcomplex) +EIGEN_MKL_TRMV_SPECIALIZE(scomplex) + +// implements col-major: res += alpha * op(triangular) * vector +#define EIGEN_MKL_TRMV_CM(EIGTYPE, MKLTYPE, EIGPREFIX, MKLPREFIX) \ +template \ +struct triangular_matrix_vector_product_trmv { \ + enum { \ + IsLower = (Mode&Lower) == Lower, \ + SetDiag = (Mode&(ZeroDiag|UnitDiag)) ? 0 : 1, \ + IsUnitDiag = (Mode&UnitDiag) ? 1 : 0, \ + IsZeroDiag = (Mode&ZeroDiag) ? 1 : 0, \ + LowUp = IsLower ? Lower : Upper \ + }; \ + static EIGEN_DONT_INLINE void run(Index _rows, Index _cols, const EIGTYPE* _lhs, Index lhsStride, \ + const EIGTYPE* _rhs, Index rhsIncr, EIGTYPE* _res, Index resIncr, EIGTYPE alpha) \ + { \ + if (ConjLhs || IsZeroDiag) { \ + triangular_matrix_vector_product::run( \ + _rows, _cols, _lhs, lhsStride, _rhs, rhsIncr, _res, resIncr, alpha); \ + return; \ + }\ + Index size = (std::min)(_rows,_cols); \ + Index rows = IsLower ? _rows : size; \ + Index cols = IsLower ? size : _cols; \ +\ + typedef VectorX##EIGPREFIX VectorRhs; \ + EIGTYPE *x, *y;\ +\ +/* Set x*/ \ + Map > rhs(_rhs,cols,InnerStride<>(rhsIncr)); \ + VectorRhs x_tmp; \ + if (ConjRhs) x_tmp = rhs.conjugate(); else x_tmp = rhs; \ + x = x_tmp.data(); \ +\ +/* Square part handling */\ +\ + char trans, uplo, diag; \ + MKL_INT m, n, lda, incx, incy; \ + EIGTYPE const *a; \ + MKLTYPE alpha_, beta_; \ + assign_scalar_eig2mkl(alpha_, alpha); \ + assign_scalar_eig2mkl(beta_, EIGTYPE(1)); \ +\ +/* Set m, n */ \ + n = (MKL_INT)size; \ + lda = lhsStride; \ + incx = 1; \ + incy = resIncr; \ +\ +/* Set uplo, trans and diag*/ \ + trans = 'N'; \ + uplo = IsLower ? 'L' : 'U'; \ + diag = IsUnitDiag ? 'U' : 'N'; \ +\ +/* call ?TRMV*/ \ + MKLPREFIX##trmv(&uplo, &trans, &diag, &n, (const MKLTYPE*)_lhs, &lda, (MKLTYPE*)x, &incx); \ +\ +/* Add op(a_tr)rhs into res*/ \ + MKLPREFIX##axpy(&n, &alpha_,(const MKLTYPE*)x, &incx, (MKLTYPE*)_res, &incy); \ +/* Non-square case - doesn't fit to MKL ?TRMV. Fall to default triangular product*/ \ + if (size<(std::max)(rows,cols)) { \ + typedef Matrix MatrixLhs; \ + if (ConjRhs) x_tmp = rhs.conjugate(); else x_tmp = rhs; \ + x = x_tmp.data(); \ + if (size \ +struct triangular_matrix_vector_product_trmv { \ + enum { \ + IsLower = (Mode&Lower) == Lower, \ + SetDiag = (Mode&(ZeroDiag|UnitDiag)) ? 0 : 1, \ + IsUnitDiag = (Mode&UnitDiag) ? 1 : 0, \ + IsZeroDiag = (Mode&ZeroDiag) ? 1 : 0, \ + LowUp = IsLower ? Lower : Upper \ + }; \ + static EIGEN_DONT_INLINE void run(Index _rows, Index _cols, const EIGTYPE* _lhs, Index lhsStride, \ + const EIGTYPE* _rhs, Index rhsIncr, EIGTYPE* _res, Index resIncr, EIGTYPE alpha) \ + { \ + if (IsZeroDiag) { \ + triangular_matrix_vector_product::run( \ + _rows, _cols, _lhs, lhsStride, _rhs, rhsIncr, _res, resIncr, alpha); \ + return; \ + }\ + Index size = (std::min)(_rows,_cols); \ + Index rows = IsLower ? _rows : size; \ + Index cols = IsLower ? size : _cols; \ +\ + typedef VectorX##EIGPREFIX VectorRhs; \ + EIGTYPE *x, *y;\ +\ +/* Set x*/ \ + Map > rhs(_rhs,cols,InnerStride<>(rhsIncr)); \ + VectorRhs x_tmp; \ + if (ConjRhs) x_tmp = rhs.conjugate(); else x_tmp = rhs; \ + x = x_tmp.data(); \ +\ +/* Square part handling */\ +\ + char trans, uplo, diag; \ + MKL_INT m, n, lda, incx, incy; \ + EIGTYPE const *a; \ + MKLTYPE alpha_, beta_; \ + assign_scalar_eig2mkl(alpha_, alpha); \ + assign_scalar_eig2mkl(beta_, EIGTYPE(1)); \ +\ +/* Set m, n */ \ + n = (MKL_INT)size; \ + lda = lhsStride; \ + incx = 1; \ + incy = resIncr; \ +\ +/* Set uplo, trans and diag*/ \ + trans = ConjLhs ? 'C' : 'T'; \ + uplo = IsLower ? 'U' : 'L'; \ + diag = IsUnitDiag ? 'U' : 'N'; \ +\ +/* call ?TRMV*/ \ + MKLPREFIX##trmv(&uplo, &trans, &diag, &n, (const MKLTYPE*)_lhs, &lda, (MKLTYPE*)x, &incx); \ +\ +/* Add op(a_tr)rhs into res*/ \ + MKLPREFIX##axpy(&n, &alpha_,(const MKLTYPE*)x, &incx, (MKLTYPE*)_res, &incy); \ +/* Non-square case - doesn't fit to MKL ?TRMV. Fall to default triangular product*/ \ + if (size<(std::max)(rows,cols)) { \ + typedef Matrix MatrixLhs; \ + if (ConjRhs) x_tmp = rhs.conjugate(); else x_tmp = rhs; \ + x = x_tmp.data(); \ + if (size& blocking) { triangular_solve_matrix< Scalar, Index, Side==OnTheLeft?OnTheRight:OnTheLeft, (Mode&UnitDiag) | ((Mode&Upper) ? Lower : Upper), NumTraits::IsComplex && Conjugate, TriStorageOrder==RowMajor ? ColMajor : RowMajor, ColMajor> - ::run(size, cols, tri, triStride, _other, otherStride); + ::run(size, cols, tri, triStride, _other, otherStride, blocking); } }; @@ -53,7 +56,8 @@ struct triangular_solve_matrix& blocking) { Index cols = otherSize; const_blas_data_mapper tri(_tri,triStride); @@ -65,22 +69,29 @@ struct triangular_solve_matrix(kc, mc, nc); + Index kc = blocking.kc(); // cache block size along the K direction + Index mc = (std::min)(size,blocking.mc()); // cache block size along the M direction + std::size_t sizeA = kc*mc; + std::size_t sizeB = kc*cols; std::size_t sizeW = kc*Traits::WorkSpaceFactor; - std::size_t sizeB = sizeW + kc*cols; - ei_declare_aligned_stack_constructed_variable(Scalar, blockA, kc*mc, 0); - ei_declare_aligned_stack_constructed_variable(Scalar, allocatedBlockB, sizeB, 0); - Scalar* blockB = allocatedBlockB + sizeW; + + ei_declare_aligned_stack_constructed_variable(Scalar, blockA, sizeA, blocking.blockA()); + ei_declare_aligned_stack_constructed_variable(Scalar, blockB, sizeB, blocking.blockB()); + ei_declare_aligned_stack_constructed_variable(Scalar, blockW, sizeW, blocking.blockW()); conj_if conj; gebp_kernel gebp_kernel; gemm_pack_lhs pack_lhs; gemm_pack_rhs pack_rhs; + // the goal here is to subdivise the Rhs panels such that we keep some cache + // coherence when accessing the rhs elements + std::ptrdiff_t l1, l2; + manage_caching_sizes(GetAction, &l1, &l2); + Index subcols = cols>0 ? l2/(4 * sizeof(Scalar) * otherStride) : 0; + subcols = std::max((subcols/Traits::nr)*Traits::nr, Traits::nr); + for(Index k2=IsLower ? 0 : size; IsLower ? k20; IsLower ? k2+=kc : k2-=kc) @@ -92,16 +103,18 @@ struct triangular_solve_matrix general block copy (done during the next step) - // - R1 = L1^-1 B => tricky part + // - R1 = A11^-1 B => tricky part // - update B from the new R1 => actually this has to be performed continuously during the above step - // - R2 = L2 * B => GEPP + // - R2 -= A21 * B => GEPP - // The tricky part: compute R1 = L1^-1 B while updating B from R1 - // The idea is to split L1 into multiple small vertical panels. - // Each panel can be split into a small triangular part A1 which is processed without optimization, - // and the remaining small part A2 which is processed using gebp with appropriate block strides + // The tricky part: compute R1 = A11^-1 B while updating B from R1 + // The idea is to split A11 into multiple small vertical panels. + // Each panel can be split into a small triangular part T1k which is processed without optimization, + // and the remaining small part T2k which is processed using gebp with appropriate block strides + for(Index j2=0; j2(actual_kc-k1, SmallPanelWidth); @@ -114,11 +127,11 @@ struct triangular_solve_matrix0) @@ -152,13 +165,13 @@ struct triangular_solve_matrix GEPP + + // R2 -= A21 * B => GEPP { Index start = IsLower ? k2+kc : 0; Index end = IsLower ? size : k2-kc; @@ -169,7 +182,7 @@ struct triangular_solve_matrix& blocking) { Index rows = otherSize; const_blas_data_mapper rhs(_tri,triStride); @@ -198,19 +212,16 @@ struct triangular_solve_matrix(Traits::Max_kc/4,size); // cache block size along the K direction -// Index mc = std::min(Traits::Max_mc,size); // cache block size along the M direction - // check that !!!! - Index kc = size; // cache block size along the K direction - Index mc = size; // cache block size along the M direction - Index nc = rows; // cache block size along the N direction - computeProductBlockingSizes(kc, mc, nc); + Index kc = blocking.kc(); // cache block size along the K direction + Index mc = (std::min)(rows,blocking.mc()); // cache block size along the M direction + std::size_t sizeA = kc*mc; + std::size_t sizeB = kc*size; std::size_t sizeW = kc*Traits::WorkSpaceFactor; - std::size_t sizeB = sizeW + kc*size; - ei_declare_aligned_stack_constructed_variable(Scalar, blockA, kc*mc, 0); - ei_declare_aligned_stack_constructed_variable(Scalar, allocatedBlockB, sizeB, 0); - Scalar* blockB = allocatedBlockB + sizeW; + + ei_declare_aligned_stack_constructed_variable(Scalar, blockA, sizeA, blocking.blockA()); + ei_declare_aligned_stack_constructed_variable(Scalar, blockB, sizeB, blocking.blockB()); + ei_declare_aligned_stack_constructed_variable(Scalar, blockW, sizeW, blocking.blockW()); conj_if conj; gebp_kernel gebp_kernel; @@ -277,7 +288,7 @@ struct triangular_solve_matrix0) gebp_kernel(_other+i2+startPanel*otherStride, otherStride, blockA, geb, actual_mc, actual_kc, rs, Scalar(-1), - -1, -1, 0, 0, allocatedBlockB); + -1, -1, 0, 0, blockW); } } } @@ -316,4 +327,6 @@ struct triangular_solve_matrix \ +struct triangular_solve_matrix \ +{ \ + enum { \ + IsLower = (Mode&Lower) == Lower, \ + IsUnitDiag = (Mode&UnitDiag) ? 1 : 0, \ + IsZeroDiag = (Mode&ZeroDiag) ? 1 : 0, \ + conjA = ((TriStorageOrder==ColMajor) && Conjugate) ? 1 : 0 \ + }; \ + static EIGEN_DONT_INLINE void run( \ + Index size, Index otherSize, \ + const EIGTYPE* _tri, Index triStride, \ + EIGTYPE* _other, Index otherStride, level3_blocking& /*blocking*/) \ + { \ + MKL_INT m = size, n = otherSize, lda, ldb; \ + char side = 'L', uplo, diag='N', transa; \ + /* Set alpha_ */ \ + MKLTYPE alpha; \ + EIGTYPE myone(1); \ + assign_scalar_eig2mkl(alpha, myone); \ + ldb = otherStride;\ +\ + const EIGTYPE *a; \ +/* Set trans */ \ + transa = (TriStorageOrder==RowMajor) ? ((Conjugate) ? 'C' : 'T') : 'N'; \ +/* Set uplo */ \ + uplo = IsLower ? 'L' : 'U'; \ + if (TriStorageOrder==RowMajor) uplo = (uplo == 'L') ? 'U' : 'L'; \ +/* Set a, lda */ \ + typedef Matrix MatrixTri; \ + Map > tri(_tri,size,size,OuterStride<>(triStride)); \ + MatrixTri a_tmp; \ +\ + if (conjA) { \ + a_tmp = tri.conjugate(); \ + a = a_tmp.data(); \ + lda = a_tmp.outerStride(); \ + } else { \ + a = _tri; \ + lda = triStride; \ + } \ + if (IsUnitDiag) diag='U'; \ +/* call ?trsm*/ \ + MKLPREFIX##trsm(&side, &uplo, &transa, &diag, &m, &n, &alpha, (const MKLTYPE*)a, &lda, (MKLTYPE*)_other, &ldb); \ + } \ +}; + +EIGEN_MKL_TRSM_L(double, double, d) +EIGEN_MKL_TRSM_L(dcomplex, MKL_Complex16, z) +EIGEN_MKL_TRSM_L(float, float, s) +EIGEN_MKL_TRSM_L(scomplex, MKL_Complex8, c) + + +// implements RightSide general * op(triangular)^-1 +#define EIGEN_MKL_TRSM_R(EIGTYPE, MKLTYPE, MKLPREFIX) \ +template \ +struct triangular_solve_matrix \ +{ \ + enum { \ + IsLower = (Mode&Lower) == Lower, \ + IsUnitDiag = (Mode&UnitDiag) ? 1 : 0, \ + IsZeroDiag = (Mode&ZeroDiag) ? 1 : 0, \ + conjA = ((TriStorageOrder==ColMajor) && Conjugate) ? 1 : 0 \ + }; \ + static EIGEN_DONT_INLINE void run( \ + Index size, Index otherSize, \ + const EIGTYPE* _tri, Index triStride, \ + EIGTYPE* _other, Index otherStride, level3_blocking& /*blocking*/) \ + { \ + MKL_INT m = otherSize, n = size, lda, ldb; \ + char side = 'R', uplo, diag='N', transa; \ + /* Set alpha_ */ \ + MKLTYPE alpha; \ + EIGTYPE myone(1); \ + assign_scalar_eig2mkl(alpha, myone); \ + ldb = otherStride;\ +\ + const EIGTYPE *a; \ +/* Set trans */ \ + transa = (TriStorageOrder==RowMajor) ? ((Conjugate) ? 'C' : 'T') : 'N'; \ +/* Set uplo */ \ + uplo = IsLower ? 'L' : 'U'; \ + if (TriStorageOrder==RowMajor) uplo = (uplo == 'L') ? 'U' : 'L'; \ +/* Set a, lda */ \ + typedef Matrix MatrixTri; \ + Map > tri(_tri,size,size,OuterStride<>(triStride)); \ + MatrixTri a_tmp; \ +\ + if (conjA) { \ + a_tmp = tri.conjugate(); \ + a = a_tmp.data(); \ + lda = a_tmp.outerStride(); \ + } else { \ + a = _tri; \ + lda = triStride; \ + } \ + if (IsUnitDiag) diag='U'; \ +/* call ?trsm*/ \ + MKLPREFIX##trsm(&side, &uplo, &transa, &diag, &m, &n, &alpha, (const MKLTYPE*)a, &lda, (MKLTYPE*)_other, &ldb); \ + /*std::cout << "TRMS_L specialization!\n";*/ \ + } \ +}; + +EIGEN_MKL_TRSM_R(double, double, d) +EIGEN_MKL_TRSM_R(dcomplex, MKL_Complex16, z) +EIGEN_MKL_TRSM_R(float, float, s) +EIGEN_MKL_TRSM_R(scomplex, MKL_Complex8, c) + + +} // end namespace internal + +} // end namespace Eigen + +#endif // EIGEN_TRIANGULAR_SOLVER_MATRIX_MKL_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/products/TriangularSolverVector.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/products/TriangularSolverVector.h index 639d4a5b4..f83a81061 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/products/TriangularSolverVector.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/products/TriangularSolverVector.h @@ -25,6 +25,8 @@ #ifndef EIGEN_TRIANGULAR_SOLVER_VECTOR_H #define EIGEN_TRIANGULAR_SOLVER_VECTOR_H +namespace Eigen { + namespace internal { template @@ -147,4 +149,6 @@ struct triangular_solve_vector struct general_matrix_matrix_product; -template +template struct general_matrix_vector_product; @@ -56,11 +58,15 @@ template struct conj_if; template<> struct conj_if { template inline T operator()(const T& x) { return conj(x); } + template + inline T pconj(const T& x) { return internal::pconj(x); } }; template<> struct conj_if { template inline const T& operator()(const T& x) { return x; } + template + inline const T& pconj(const T& x) { return x; } }; template struct conj_helper @@ -118,11 +124,11 @@ template struct conj_helper struct get_factor { - EIGEN_STRONG_INLINE static To run(const From& x) { return x; } + static EIGEN_STRONG_INLINE To run(const From& x) { return x; } }; template struct get_factor::Real> { - EIGEN_STRONG_INLINE static typename NumTraits::Real run(const Scalar& x) { return real(x); } + static EIGEN_STRONG_INLINE typename NumTraits::Real run(const Scalar& x) { return real(x); } }; // Lightweight helper class to access matrix coefficients. @@ -175,7 +181,7 @@ template struct blas_traits ExtractType, typename _ExtractType::PlainObject >::type DirectLinearAccessType; - static inline const ExtractType extract(const XprType& x) { return x; } + static inline ExtractType extract(const XprType& x) { return x; } static inline const Scalar extractScalarFactor(const XprType&) { return Scalar(1); } }; @@ -192,7 +198,7 @@ struct blas_traits, NestedXpr> > IsComplex = NumTraits::IsComplex, NeedToConjugate = Base::NeedToConjugate ? 0 : IsComplex }; - static inline const ExtractType extract(const XprType& x) { return Base::extract(x.nestedExpression()); } + static inline ExtractType extract(const XprType& x) { return Base::extract(x.nestedExpression()); } static inline Scalar extractScalarFactor(const XprType& x) { return conj(Base::extractScalarFactor(x.nestedExpression())); } }; @@ -204,7 +210,7 @@ struct blas_traits, NestedXpr> > typedef blas_traits Base; typedef CwiseUnaryOp, NestedXpr> XprType; typedef typename Base::ExtractType ExtractType; - static inline const ExtractType extract(const XprType& x) { return Base::extract(x.nestedExpression()); } + static inline ExtractType extract(const XprType& x) { return Base::extract(x.nestedExpression()); } static inline Scalar extractScalarFactor(const XprType& x) { return x.functor().m_other * Base::extractScalarFactor(x.nestedExpression()); } }; @@ -217,7 +223,7 @@ struct blas_traits, NestedXpr> > typedef blas_traits Base; typedef CwiseUnaryOp, NestedXpr> XprType; typedef typename Base::ExtractType ExtractType; - static inline const ExtractType extract(const XprType& x) { return Base::extract(x.nestedExpression()); } + static inline ExtractType extract(const XprType& x) { return Base::extract(x.nestedExpression()); } static inline Scalar extractScalarFactor(const XprType& x) { return - Base::extractScalarFactor(x.nestedExpression()); } }; @@ -239,7 +245,7 @@ struct blas_traits > enum { IsTransposed = Base::IsTransposed ? 0 : 1 }; - static inline const ExtractType extract(const XprType& x) { return Base::extract(x.nestedExpression()); } + static inline ExtractType extract(const XprType& x) { return Base::extract(x.nestedExpression()); } static inline Scalar extractScalarFactor(const XprType& x) { return Base::extractScalarFactor(x.nestedExpression()); } }; @@ -252,7 +258,7 @@ template::HasUsableDirectA struct extract_data_selector { static const typename T::Scalar* run(const T& m) { - return const_cast(&blas_traits::extract(m).coeffRef(0,0)); // FIXME this should be .data() + return blas_traits::extract(m).data(); } }; @@ -268,4 +274,6 @@ template const typename T::Scalar* extract_data(const T& m) } // end namespace internal +} // end namespace Eigen + #endif // EIGEN_BLASUTIL_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/util/Constants.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/util/Constants.h index c3dd3a09d..f34aac85a 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/util/Constants.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/util/Constants.h @@ -26,6 +26,8 @@ #ifndef EIGEN_CONSTANTS_H #define EIGEN_CONSTANTS_H +namespace Eigen { + /** This value means that a quantity is not known at compile-time, and that instead the value is * stored in some runtime variable. * @@ -188,7 +190,9 @@ enum { /** View matrix as an upper triangular matrix with zeros on the diagonal. */ StrictlyUpper=ZeroDiag|Upper, /** Used in BandMatrix and SelfAdjointView to indicate that the matrix is self-adjoint. */ - SelfAdjoint=0x10 + SelfAdjoint=0x10, + /** Used to support symmetric, non-selfadjoint, complex matrices. */ + Symmetric=0x20 }; /** \ingroup enums @@ -200,8 +204,6 @@ enum { Aligned=1 }; -enum { ConditionalJumpCost = 5 }; - /** \ingroup enums * Enum used by DenseBase::corner() in Eigen2 compatibility mode. */ // FIXME after the corner() API change, this was not needed anymore, except by AlignedBox @@ -223,8 +225,6 @@ enum DirectionType { BothDirections }; -enum ProductEvaluationMode { NormalProduct, CacheFriendlyProduct }; - /** \internal \ingroup enums * Enum to specify how to traverse the entries of a matrix. */ enum { @@ -257,6 +257,13 @@ enum { CompleteUnrolling }; +/** \internal \ingroup enums + * Enum to specify whether to use the default (built-in) implementation or the specialization. */ +enum { + Specialized, + BuiltIn +}; + /** \ingroup enums * Enum containing possible values for the \p _Options template parameter of * Matrix, Array and BandMatrix. */ @@ -280,26 +287,21 @@ enum { OnTheRight = 2 }; -/* the following could as well be written: - * enum NoChange_t { NoChange }; - * but it feels dangerous to disambiguate overloaded functions on enum/integer types. - * If on some platform it is really impossible to get rid of "unused variable" warnings, then - * we can always come back to that solution. +/* the following used to be written as: + * + * struct NoChange_t {}; + * namespace { + * EIGEN_UNUSED NoChange_t NoChange; + * } + * + * on the ground that it feels dangerous to disambiguate overloaded functions on enum/integer types. + * However, this leads to "variable declared but never referenced" warnings on Intel Composer XE, + * and we do not know how to get rid of them (bug 450). */ -struct NoChange_t {}; -namespace { - EIGEN_UNUSED NoChange_t NoChange; -} -struct Sequential_t {}; -namespace { - EIGEN_UNUSED Sequential_t Sequential; -} - -struct Default_t {}; -namespace { - EIGEN_UNUSED Default_t Default; -} +enum NoChange_t { NoChange }; +enum Sequential_t { Sequential }; +enum Default_t { Default }; /** \internal \ingroup enums * Used in AmbiVector. */ @@ -375,7 +377,7 @@ enum QRPreconditioners { #error The preprocessor symbol 'Success' is defined, possibly by the X11 header file X.h #endif -/** \ingroups enums +/** \ingroup enums * Enum for reporting the status of a computation. */ enum ComputationInfo { /** Computation was successful. */ @@ -383,7 +385,10 @@ enum ComputationInfo { /** The provided data did not satisfy the prerequisites. */ NumericalIssue = 1, /** Iterative procedure did not converge. */ - NoConvergence = 2 + NoConvergence = 2, + /** The inputs are invalid, or the algorithm has been improperly called. + * When assertions are enabled, such errors trigger an assert. */ + InvalidInput = 3 }; /** \ingroup enums @@ -436,4 +441,6 @@ struct MatrixXpr {}; /** The type used to identify an array expression */ struct ArrayXpr {}; +} // end namespace Eigen + #endif // EIGEN_CONSTANTS_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/util/DisableStupidWarnings.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/util/DisableStupidWarnings.h index 00730524b..6a0bf0629 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/util/DisableStupidWarnings.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/util/DisableStupidWarnings.h @@ -21,15 +21,13 @@ #elif defined __INTEL_COMPILER // 2196 - routine is both "inline" and "noinline" ("noinline" assumed) // ICC 12 generates this warning even without any inline keyword, when defining class methods 'inline' i.e. inside of class body - // 2536 - type qualifiers are meaningless here - // ICC 12 generates this warning when a function return type is const qualified, even if that type is a template-parameter-dependent // typedef that may be a reference type. // 279 - controlling expression is constant // ICC 12 generates this warning on assert(constant_expression_depending_on_template_params) and frankly this is a legitimate use case. #ifndef EIGEN_PERMANENTLY_DISABLE_STUPID_WARNINGS #pragma warning push #endif - #pragma warning disable 2196 2536 279 + #pragma warning disable 2196 279 #elif defined __clang__ // -Wconstant-logical-operand - warning: use of logical && with constant operand; switch to bitwise & or remove constant // this is really a stupid warning as it warns on compile-time expressions involving enums diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/util/ForwardDeclarations.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/util/ForwardDeclarations.h index 7fbccf98c..e5303f052 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/util/ForwardDeclarations.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/util/ForwardDeclarations.h @@ -26,6 +26,7 @@ #ifndef EIGEN_FORWARDDECLARATIONS_H #define EIGEN_FORWARDDECLARATIONS_H +namespace Eigen { namespace internal { template struct traits; @@ -133,6 +134,7 @@ template class WithFormat; template struct CommaInitializer; template class ReturnByValue; template class ArrayWrapper; +template class MatrixWrapper; namespace internal { template struct solve_retval_base; @@ -282,6 +284,8 @@ template class Homogeneous; // MatrixFunctions module template struct MatrixExponentialReturnValue; template class MatrixFunctionReturnValue; +template class MatrixSquareRootReturnValue; +template class MatrixLogarithmReturnValue; namespace internal { template @@ -304,4 +308,6 @@ template struct eigen2_part_return_type; } #endif +} // end namespace Eigen + #endif // EIGEN_FORWARDDECLARATIONS_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/util/MKL_support.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/util/MKL_support.h new file mode 100644 index 000000000..1e6e355d6 --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/util/MKL_support.h @@ -0,0 +1,109 @@ +/* + Copyright (c) 2011, Intel Corporation. All rights reserved. + + Redistribution and use in source and binary forms, with or without modification, + are permitted provided that the following conditions are met: + + * Redistributions of source code must retain the above copyright notice, this + list of conditions and the following disclaimer. + * Redistributions in binary form must reproduce the above copyright notice, + this list of conditions and the following disclaimer in the documentation + and/or other materials provided with the distribution. + * Neither the name of Intel Corporation nor the names of its contributors may + be used to endorse or promote products derived from this software without + specific prior written permission. + + THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND + ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED + WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE + DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR + ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES + (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; + LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON + ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS + SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + + ******************************************************************************** + * Content : Eigen bindings to Intel(R) MKL + * Include file with common MKL declarations + ******************************************************************************** +*/ + +#ifndef EIGEN_MKL_SUPPORT_H +#define EIGEN_MKL_SUPPORT_H + +#ifdef EIGEN_USE_MKL_ALL + #ifndef EIGEN_USE_BLAS + #define EIGEN_USE_BLAS + #endif + #ifndef EIGEN_USE_LAPACKE + #define EIGEN_USE_LAPACKE + #endif + #ifndef EIGEN_USE_MKL_VML + #define EIGEN_USE_MKL_VML + #endif +#endif + +#ifdef EIGEN_USE_LAPACKE_STRICT + #define EIGEN_USE_LAPACKE +#endif + +#if defined(EIGEN_USE_BLAS) || defined(EIGEN_USE_LAPACKE) || defined(EIGEN_USE_MKL_VML) + #define EIGEN_USE_MKL +#endif + +#if defined EIGEN_USE_MKL + +#include +#include +#define EIGEN_MKL_VML_THRESHOLD 128 + +namespace Eigen { + +typedef std::complex dcomplex; +typedef std::complex scomplex; + +namespace internal { + +template +static inline void assign_scalar_eig2mkl(MKLType& mklScalar, const EigenType& eigenScalar) { + mklScalar=eigenScalar; +} + +template +static inline void assign_conj_scalar_eig2mkl(MKLType& mklScalar, const EigenType& eigenScalar) { + mklScalar=eigenScalar; +} + +template <> +inline void assign_scalar_eig2mkl(MKL_Complex16& mklScalar, const dcomplex& eigenScalar) { + mklScalar.real=eigenScalar.real(); + mklScalar.imag=eigenScalar.imag(); +} + +template <> +inline void assign_scalar_eig2mkl(MKL_Complex8& mklScalar, const scomplex& eigenScalar) { + mklScalar.real=eigenScalar.real(); + mklScalar.imag=eigenScalar.imag(); +} + +template <> +inline void assign_conj_scalar_eig2mkl(MKL_Complex16& mklScalar, const dcomplex& eigenScalar) { + mklScalar.real=eigenScalar.real(); + mklScalar.imag=-eigenScalar.imag(); +} + +template <> +inline void assign_conj_scalar_eig2mkl(MKL_Complex8& mklScalar, const scomplex& eigenScalar) { + mklScalar.real=eigenScalar.real(); + mklScalar.imag=-eigenScalar.imag(); +} + +} // end namespace internal + +} // end namespace Eigen + +#endif + +#endif // EIGEN_MKL_SUPPORT_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/util/Macros.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/util/Macros.h index b7c2b79af..b361a05d4 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/util/Macros.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/util/Macros.h @@ -1,4 +1,3 @@ - // This file is part of Eigen, a lightweight C++ template library // for linear algebra. // @@ -28,8 +27,8 @@ #define EIGEN_MACROS_H #define EIGEN_WORLD_VERSION 3 -#define EIGEN_MAJOR_VERSION 0 -#define EIGEN_MINOR_VERSION 5 +#define EIGEN_MAJOR_VERSION 1 +#define EIGEN_MINOR_VERSION 0 #define EIGEN_VERSION_AT_LEAST(x,y,z) (EIGEN_WORLD_VERSION>x || (EIGEN_WORLD_VERSION>=x && \ (EIGEN_MAJOR_VERSION>y || (EIGEN_MAJOR_VERSION>=y && \ @@ -235,12 +234,16 @@ #define EIGEN_ONLY_USED_FOR_DEBUG(x) #endif -#if (defined __GNUC__) -#define EIGEN_DEPRECATED __attribute__((deprecated)) -#elif (defined _MSC_VER) -#define EIGEN_DEPRECATED __declspec(deprecated) +#ifndef EIGEN_NO_DEPRECATED_WARNING + #if (defined __GNUC__) + #define EIGEN_DEPRECATED __attribute__((deprecated)) + #elif (defined _MSC_VER) + #define EIGEN_DEPRECATED __declspec(deprecated) + #else + #define EIGEN_DEPRECATED + #endif #else -#define EIGEN_DEPRECATED + #define EIGEN_DEPRECATED #endif #if (defined __GNUC__) @@ -252,7 +255,7 @@ // Suppresses 'unused variable' warnings. #define EIGEN_UNUSED_VARIABLE(var) (void)var; -#if (defined __GNUC__) +#if !defined(EIGEN_ASM_COMMENT) && (defined __GNUC__) #define EIGEN_ASM_COMMENT(X) asm("#" X) #else #define EIGEN_ASM_COMMENT(X) @@ -265,7 +268,7 @@ * If we made alignment depend on whether or not EIGEN_VECTORIZE is defined, it would be impossible to link * vectorized and non-vectorized code. */ -#if (defined __GNUC__) || (defined __PGI) || (defined __IBMCPP__) +#if (defined __GNUC__) || (defined __PGI) || (defined __IBMCPP__) || (defined __ARMCC_VERSION) #define EIGEN_ALIGN_TO_BOUNDARY(n) __attribute__((aligned(n))) #elif (defined _MSC_VER) #define EIGEN_ALIGN_TO_BOUNDARY(n) __declspec(align(n)) diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/util/Memory.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/util/Memory.h index 023716dc9..56a16b5cb 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/util/Memory.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/util/Memory.h @@ -80,6 +80,8 @@ #define EIGEN_HAS_MM_MALLOC 0 #endif +namespace Eigen { + namespace internal { inline void throw_std_bad_alloc() @@ -457,7 +459,7 @@ template inline void conditional_aligned_delete_auto(T * * There is also the variant first_aligned(const MatrixBase&) defined in DenseCoeffsBase.h. */ template -inline static Index first_aligned(const Scalar* array, Index size) +static inline Index first_aligned(const Scalar* array, Index size) { typedef typename packet_traits::type Packet; enum { PacketSize = packet_traits::size, @@ -483,7 +485,26 @@ inline static Index first_aligned(const Scalar* array, Index size) } } -} // end namespace internal + +// std::copy is much slower than memcpy, so let's introduce a smart_copy which +// use memcpy on trivial types, i.e., on types that does not require an initialization ctor. +template struct smart_copy_helper; + +template void smart_copy(const T* start, const T* end, T* target) +{ + smart_copy_helper::RequireInitialization>::run(start, end, target); +} + +template struct smart_copy_helper { + static inline void run(const T* start, const T* end, T* target) + { memcpy(target, start, std::ptrdiff_t(end)-std::ptrdiff_t(start)); } +}; + +template struct smart_copy_helper { + static inline void run(const T* start, const T* end, T* target) + { std::copy(start, end, target); } +}; + /***************************************************************************** *** Implementation of runtime stack allocation (falling back to malloc) *** @@ -499,8 +520,6 @@ inline static Index first_aligned(const Scalar* array, Index size) #endif #endif -namespace internal { - // This helper class construct the allocated memory, and takes care of destructing and freeing the handled data // at destruction time. In practice this helper class is mainly useful to avoid memory leak in case of exceptions. template class aligned_stack_memory_handler @@ -531,14 +550,14 @@ template class aligned_stack_memory_handler bool m_deallocate; }; -} +} // end namespace internal /** \internal * Declares, allocates and construct an aligned buffer named NAME of SIZE elements of type TYPE on the stack * if SIZE is smaller than EIGEN_STACK_ALLOCATION_LIMIT, and if stack allocation is supported by the platform * (currently, this is Linux and Visual Studio only). Otherwise the memory is allocated on the heap. * The allocated buffer is automatically deleted when exiting the scope of this declaration. - * If BUFFER is non nul, then the declared variable is simply an alias for BUFFER, and no allocation/deletion occurs. + * If BUFFER is non null, then the declared variable is simply an alias for BUFFER, and no allocation/deletion occurs. * Here is an example: * \code * { @@ -619,7 +638,7 @@ template class aligned_stack_memory_handler #define EIGEN_MAKE_ALIGNED_OPERATOR_NEW EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF(true) #define EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF_VECTORIZABLE_FIXED_SIZE(Scalar,Size) \ - EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF(((Size)!=Eigen::Dynamic) && ((sizeof(Scalar)*(Size))%16==0)) + EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF(bool(((Size)!=Eigen::Dynamic) && ((sizeof(Scalar)*(Size))%16==0))) /****************************************************************************/ @@ -667,24 +686,24 @@ public: return &value; } - aligned_allocator() throw() + aligned_allocator() { } - aligned_allocator( const aligned_allocator& ) throw() + aligned_allocator( const aligned_allocator& ) { } template - aligned_allocator( const aligned_allocator& ) throw() + aligned_allocator( const aligned_allocator& ) { } - ~aligned_allocator() throw() + ~aligned_allocator() { } - size_type max_size() const throw() + size_type max_size() const { return (std::numeric_limits::max)(); } @@ -701,6 +720,15 @@ public: ::new( p ) T( value ); } + // Support for c++11 +#if (__cplusplus >= 201103L) + template + void construct(pointer p, Args&&... args) + { + ::new(p) T(std::forward(args)...); + } +#endif + void destroy( pointer p ) { p->~T(); @@ -720,19 +748,21 @@ public: //---------- Cache sizes ---------- -#if defined(__GNUC__) && ( defined(__i386__) || defined(__x86_64__) ) -# if defined(__PIC__) && defined(__i386__) - // Case for x86 with PIC -# define EIGEN_CPUID(abcd,func,id) \ - __asm__ __volatile__ ("xchgl %%ebx, %%esi;cpuid; xchgl %%ebx,%%esi": "=a" (abcd[0]), "=S" (abcd[1]), "=c" (abcd[2]), "=d" (abcd[3]) : "a" (func), "c" (id)); -# else - // Case for x86_64 or x86 w/o PIC -# define EIGEN_CPUID(abcd,func,id) \ - __asm__ __volatile__ ("cpuid": "=a" (abcd[0]), "=b" (abcd[1]), "=c" (abcd[2]), "=d" (abcd[3]) : "a" (func), "c" (id) ); -# endif -#elif defined(_MSC_VER) -# if (_MSC_VER > 1500) -# define EIGEN_CPUID(abcd,func,id) __cpuidex((int*)abcd,func,id) +#if !defined(EIGEN_NO_CPUID) +# if defined(__GNUC__) && ( defined(__i386__) || defined(__x86_64__) ) +# if defined(__PIC__) && defined(__i386__) + // Case for x86 with PIC +# define EIGEN_CPUID(abcd,func,id) \ + __asm__ __volatile__ ("xchgl %%ebx, %%esi;cpuid; xchgl %%ebx,%%esi": "=a" (abcd[0]), "=S" (abcd[1]), "=c" (abcd[2]), "=d" (abcd[3]) : "a" (func), "c" (id)); +# else + // Case for x86_64 or x86 w/o PIC +# define EIGEN_CPUID(abcd,func,id) \ + __asm__ __volatile__ ("cpuid": "=a" (abcd[0]), "=b" (abcd[1]), "=c" (abcd[2]), "=d" (abcd[3]) : "a" (func), "c" (id) ); +# endif +# elif defined(_MSC_VER) +# if (_MSC_VER > 1500) +# define EIGEN_CPUID(abcd,func,id) __cpuidex((int*)abcd,func,id) +# endif # endif #endif @@ -742,7 +772,7 @@ namespace internal { inline bool cpuid_is_vendor(int abcd[4], const char* vendor) { - return abcd[1]==((int*)(vendor))[0] && abcd[3]==((int*)(vendor))[1] && abcd[2]==((int*)(vendor))[2]; + return abcd[1]==(reinterpret_cast(vendor))[0] && abcd[3]==(reinterpret_cast(vendor))[1] && abcd[2]==(reinterpret_cast(vendor))[2]; } inline void queryCacheSizes_intel_direct(int& l1, int& l2, int& l3) @@ -932,4 +962,6 @@ inline int queryTopLevelCacheSize() } // end namespace internal +} // end namespace Eigen + #endif // EIGEN_MEMORY_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/util/Meta.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/util/Meta.h index 4518261ef..82c93f922 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/util/Meta.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/util/Meta.h @@ -26,6 +26,8 @@ #ifndef EIGEN_META_H #define EIGEN_META_H +namespace Eigen { + namespace internal { /** \internal @@ -80,8 +82,6 @@ template<> struct is_arithmetic { enum { value = true }; }; template<> struct is_arithmetic { enum { value = true }; }; template<> struct is_arithmetic { enum { value = true }; }; template<> struct is_arithmetic { enum { value = true }; }; -template<> struct is_arithmetic { enum { value = true }; }; -template<> struct is_arithmetic { enum { value = true }; }; template struct add_const { typedef const T type; }; template struct add_const { typedef T& type; }; @@ -103,6 +103,21 @@ template struct enable_if; template struct enable_if { typedef T type; }; + + +/** \internal + * A base class do disable default copy ctor and copy assignement operator. + */ +class noncopyable +{ + noncopyable(const noncopyable&); + const noncopyable& operator=(const noncopyable&); +protected: + noncopyable() {} + ~noncopyable() {} +}; + + /** \internal * Convenient struct to get the result type of a unary or binary functor. * @@ -226,4 +241,6 @@ template struct is_diagonal > } // end namespace internal +} // end namespace Eigen + #endif // EIGEN_META_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/util/StaticAssert.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/util/StaticAssert.h index 99c7c9972..9a5dbbbf3 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/util/StaticAssert.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/util/StaticAssert.h @@ -48,6 +48,8 @@ #else // not CXX0X + namespace Eigen { + namespace internal { template @@ -70,6 +72,7 @@ YOU_CALLED_A_DYNAMIC_SIZE_METHOD_ON_A_FIXED_SIZE_MATRIX_OR_VECTOR, UNALIGNED_LOAD_AND_STORE_OPERATIONS_UNIMPLEMENTED_ON_ALTIVEC, THIS_FUNCTION_IS_NOT_FOR_INTEGER_NUMERIC_TYPES, + FLOATING_POINT_ARGUMENT_PASSED__INTEGER_WAS_EXPECTED, NUMERIC_TYPE_MUST_BE_REAL, COEFFICIENT_WRITE_ACCESS_TO_SELFADJOINT_NOT_SUPPORTED, WRITING_TO_TRIANGULAR_PART_WITH_UNIT_DIAGONAL_IS_NOT_SUPPORTED, @@ -95,12 +98,20 @@ YOU_PERFORMED_AN_INVALID_TRANSFORMATION_CONVERSION, THIS_EXPRESSION_IS_NOT_A_LVALUE__IT_IS_READ_ONLY, YOU_ARE_TRYING_TO_USE_AN_INDEX_BASED_ACCESSOR_ON_AN_EXPRESSION_THAT_DOES_NOT_SUPPORT_THAT, - THIS_METHOD_IS_ONLY_FOR_1x1_EXPRESSIONS + THIS_METHOD_IS_ONLY_FOR_1x1_EXPRESSIONS, + THIS_METHOD_IS_ONLY_FOR_EXPRESSIONS_OF_BOOL, + THIS_METHOD_IS_ONLY_FOR_ARRAYS_NOT_MATRICES, + YOU_PASSED_A_ROW_VECTOR_BUT_A_COLUMN_VECTOR_WAS_EXPECTED, + YOU_PASSED_A_COLUMN_VECTOR_BUT_A_ROW_VECTOR_WAS_EXPECTED, + THE_INDEX_TYPE_MUST_BE_A_SIGNED_TYPE, + THE_STORAGE_ORDER_OF_BOTH_SIDES_MUST_MATCH }; }; } // end namespace internal + } // end namespace Eigen + // Specialized implementation for MSVC to avoid "conditional // expression is constant" warnings. This implementation doesn't // appear to work under GCC, hence the multiple implementations. @@ -195,4 +206,15 @@ EIGEN_STATIC_ASSERT(internal::is_lvalue::value, \ THIS_EXPRESSION_IS_NOT_A_LVALUE__IT_IS_READ_ONLY) +#define EIGEN_STATIC_ASSERT_ARRAYXPR(Derived) \ + EIGEN_STATIC_ASSERT((internal::is_same::XprKind, ArrayXpr>::value), \ + THIS_METHOD_IS_ONLY_FOR_ARRAYS_NOT_MATRICES) + +#define EIGEN_STATIC_ASSERT_SAME_XPR_KIND(Derived1, Derived2) \ + EIGEN_STATIC_ASSERT((internal::is_same::XprKind, \ + typename internal::traits::XprKind \ + >::value), \ + YOU_CANNOT_MIX_ARRAYS_AND_MATRICES) + + #endif // EIGEN_STATIC_ASSERT_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Core/util/XprHelper.h b/gtsam/3rdparty/Eigen/Eigen/src/Core/util/XprHelper.h index c2078f137..5bb0a624f 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Core/util/XprHelper.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Core/util/XprHelper.h @@ -37,6 +37,8 @@ #define EIGEN_EMPTY_STRUCT_CTOR(X) #endif +namespace Eigen { + typedef EIGEN_DEFAULT_DENSE_INDEX_TYPE DenseIndex; namespace internal { @@ -260,30 +262,27 @@ template struct plain_matrix_type_row_major // we should be able to get rid of this one too template struct must_nest_by_value { enum { ret = false }; }; -template -struct is_reference -{ - enum { ret = false }; -}; - -template -struct is_reference -{ - enum { ret = true }; -}; - -/** -* \internal The reference selector for template expressions. The idea is that we don't -* need to use references for expressions since they are light weight proxy -* objects which should generate no copying overhead. -**/ +/** \internal The reference selector for template expressions. The idea is that we don't + * need to use references for expressions since they are light weight proxy + * objects which should generate no copying overhead. */ template struct ref_selector { typedef typename conditional< bool(traits::Flags & NestByRefBit), T const&, - T + const T + >::type type; +}; + +/** \internal Adds the const qualifier on the value-type of T2 if and only if T1 is a const type */ +template +struct transfer_constness +{ + typedef typename conditional< + bool(internal::is_const::value), + typename internal::add_const_on_value_type::type, + T2 >::type type; }; @@ -297,6 +296,8 @@ struct ref_selector * \param T the type of the expression being nested * \param n the number of coefficient accesses in the nested expression for each coefficient access in the bigger expression. * + * Note that if no evaluation occur, then the constness of T is preserved. + * * Example. Suppose that a, b, and c are of type Matrix3d. The user forms the expression a*(b+c). * b+c is an expression "sum of matrices", which we will denote by S. In order to determine how to nest it, * the Product expression uses: nested::ret, which turns out to be Matrix3d because the internal logic of @@ -456,4 +457,6 @@ struct is_lvalue } // end namespace internal +} // end namespace Eigen + #endif // EIGEN_XPRHELPER_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Block.h b/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Block.h index bc28051e0..d77ff62bb 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Block.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Block.h @@ -26,6 +26,8 @@ #ifndef EIGEN_BLOCK2_H #define EIGEN_BLOCK2_H +namespace Eigen { + /** \returns a dynamic-size expression of a corner of *this. * * \param type the type of corner. Can be \a Eigen::TopLeft, \a Eigen::TopRight, @@ -134,4 +136,6 @@ DenseBase::corner(CornerType type) const } } +} // end namespace Eigen + #endif // EIGEN_BLOCK2_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Cwise.h b/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Cwise.h index 2dc83b6a7..383645b8e 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Cwise.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Cwise.h @@ -26,6 +26,8 @@ #ifndef EIGEN_CWISE_H #define EIGEN_CWISE_H +namespace Eigen { + /** \internal * convenient macro to defined the return type of a cwise binary operation */ #define EIGEN_CWISE_BINOP_RETURN_TYPE(OP) \ @@ -200,4 +202,6 @@ inline Cwise MatrixBase::cwise() return derived(); } +} // end namespace Eigen + #endif // EIGEN_CWISE_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/CwiseOperators.h b/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/CwiseOperators.h index 9c28559c3..207a167c1 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/CwiseOperators.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/CwiseOperators.h @@ -25,6 +25,8 @@ #ifndef EIGEN_ARRAY_CWISE_OPERATORS_H #define EIGEN_ARRAY_CWISE_OPERATORS_H +namespace Eigen { + /*************************************************************************** * The following functions were defined in Core ***************************************************************************/ @@ -306,4 +308,6 @@ inline ExpressionType& Cwise::operator-=(const Scalar& scalar) return m_matrix.const_cast_derived() = *this - scalar; } +} // end namespace Eigen + #endif // EIGEN_ARRAY_CWISE_OPERATORS_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Geometry/AlignedBox.h b/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Geometry/AlignedBox.h index 78df29d40..dd29dfc34 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Geometry/AlignedBox.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Geometry/AlignedBox.h @@ -24,6 +24,8 @@ // no include guard, we'll include this twice from All.h from Eigen2Support, and it's internal anyway +namespace Eigen { + /** \geometry_module \ingroup Geometry_Module * \nonstableyet * @@ -63,7 +65,7 @@ EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF_VECTORIZABLE_FIXED_SIZE(_Scalar,_AmbientDim== ~AlignedBox() {} /** \returns the dimension in which the box holds */ - inline int dim() const { return AmbientDimAtCompileTime==Dynamic ? m_min.size()-1 : int(AmbientDimAtCompileTime); } + inline int dim() const { return AmbientDimAtCompileTime==Dynamic ? m_min.size()-1 : AmbientDimAtCompileTime; } /** \returns true if the box is null, i.e, empty. */ inline bool isNull() const { return (m_min.cwise() > m_max).any(); } @@ -157,14 +159,16 @@ protected: template inline Scalar AlignedBox::squaredExteriorDistance(const VectorType& p) const { - Scalar dist2 = 0.; + Scalar dist2(0); Scalar aux; for (int k=0; k::toRotationMatrix(void) const return res; } + +} // end namespace Eigen diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Geometry/Hyperplane.h b/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Geometry/Hyperplane.h index 81c4f55b1..8b4f7a080 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Geometry/Hyperplane.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Geometry/Hyperplane.h @@ -25,6 +25,8 @@ // no include guard, we'll include this twice from All.h from Eigen2Support, and it's internal anyway +namespace Eigen { + /** \geometry_module \ingroup Geometry_Module * * \class Hyperplane @@ -263,3 +265,5 @@ protected: Coefficients m_coeffs; }; + +} // end namespace Eigen diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Geometry/ParametrizedLine.h b/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Geometry/ParametrizedLine.h index 411c4b570..cc8eb7089 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Geometry/ParametrizedLine.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Geometry/ParametrizedLine.h @@ -25,6 +25,7 @@ // no include guard, we'll include this twice from All.h from Eigen2Support, and it's internal anyway +namespace Eigen { /** \geometry_module \ingroup Geometry_Module * @@ -151,3 +152,5 @@ inline _Scalar ParametrizedLine<_Scalar, _AmbientDim>::intersection(const Hyperp return -(hyperplane.offset()+origin().eigen2_dot(hyperplane.normal())) /(direction().eigen2_dot(hyperplane.normal())); } + +} // end namespace Eigen diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Geometry/Quaternion.h b/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Geometry/Quaternion.h index a75fa42ae..616671c67 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Geometry/Quaternion.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Geometry/Quaternion.h @@ -24,6 +24,8 @@ // no include guard, we'll include this twice from All.h from Eigen2Support, and it's internal anyway +namespace Eigen { + template @@ -143,7 +145,7 @@ public: /** \returns a quaternion representing an identity rotation * \sa MatrixBase::Identity() */ - inline static Quaternion Identity() { return Quaternion(1, 0, 0, 0); } + static inline Quaternion Identity() { return Quaternion(1, 0, 0, 0); } /** \sa Quaternion::Identity(), MatrixBase::setIdentity() */ @@ -314,9 +316,9 @@ Quaternion::toRotationMatrix(void) const // it has to be inlined, and so the return by value is not an issue Matrix3 res; - const Scalar tx = 2*this->x(); - const Scalar ty = 2*this->y(); - const Scalar tz = 2*this->z(); + const Scalar tx = Scalar(2)*this->x(); + const Scalar ty = Scalar(2)*this->y(); + const Scalar tz = Scalar(2)*this->z(); const Scalar twx = tx*this->w(); const Scalar twy = ty*this->w(); const Scalar twz = tz*this->w(); @@ -327,15 +329,15 @@ Quaternion::toRotationMatrix(void) const const Scalar tyz = tz*this->y(); const Scalar tzz = tz*this->z(); - res.coeffRef(0,0) = 1-(tyy+tzz); + res.coeffRef(0,0) = Scalar(1)-(tyy+tzz); res.coeffRef(0,1) = txy-twz; res.coeffRef(0,2) = txz+twy; res.coeffRef(1,0) = txy+twz; - res.coeffRef(1,1) = 1-(txx+tzz); + res.coeffRef(1,1) = Scalar(1)-(txx+tzz); res.coeffRef(1,2) = tyz-twx; res.coeffRef(2,0) = txz-twy; res.coeffRef(2,1) = tyz+twx; - res.coeffRef(2,2) = 1-(txx+tyy); + res.coeffRef(2,2) = Scalar(1)-(txx+tyy); return res; } @@ -460,7 +462,7 @@ template struct ei_quaternion_assign_impl { typedef typename Other::Scalar Scalar; - inline static void run(Quaternion& q, const Other& mat) + static inline void run(Quaternion& q, const Other& mat) { // This algorithm comes from "Quaternion Calculus and Fast Animation", // Ken Shoemake, 1987 SIGGRAPH course notes @@ -499,8 +501,10 @@ template struct ei_quaternion_assign_impl { typedef typename Other::Scalar Scalar; - inline static void run(Quaternion& q, const Other& vec) + static inline void run(Quaternion& q, const Other& vec) { q.coeffs() = vec; } }; + +} // end namespace Eigen diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Geometry/Rotation2D.h b/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Geometry/Rotation2D.h index ee7c80e7e..0993fa5bb 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Geometry/Rotation2D.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Geometry/Rotation2D.h @@ -24,6 +24,7 @@ // no include guard, we'll include this twice from All.h from Eigen2Support, and it's internal anyway +namespace Eigen { /** \geometry_module \ingroup Geometry_Module * @@ -155,3 +156,5 @@ Rotation2D::toRotationMatrix(void) const Scalar cosA = ei_cos(m_angle); return (Matrix2() << cosA, -sinA, sinA, cosA).finished(); } + +} // end namespace Eigen diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Geometry/RotationBase.h b/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Geometry/RotationBase.h index 2f494f198..b65abfe0d 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Geometry/RotationBase.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Geometry/RotationBase.h @@ -24,6 +24,8 @@ // no include guard, we'll include this twice from All.h from Eigen2Support, and it's internal anyway +namespace Eigen { + // this file aims to contains the various representations of rotation/orientation // in 2D and 3D space excepted Matrix and Quaternion. @@ -113,22 +115,24 @@ Matrix<_Scalar, _Rows, _Cols, _Storage, _MaxRows, _MaxCols> * \sa class Transform, class Rotation2D, class Quaternion, class AngleAxis */ template -inline static Matrix ei_toRotationMatrix(const Scalar& s) +static inline Matrix ei_toRotationMatrix(const Scalar& s) { EIGEN_STATIC_ASSERT(Dim==2,YOU_MADE_A_PROGRAMMING_MISTAKE) return Rotation2D(s).toRotationMatrix(); } template -inline static Matrix ei_toRotationMatrix(const RotationBase& r) +static inline Matrix ei_toRotationMatrix(const RotationBase& r) { return r.toRotationMatrix(); } template -inline static const MatrixBase& ei_toRotationMatrix(const MatrixBase& mat) +static inline const MatrixBase& ei_toRotationMatrix(const MatrixBase& mat) { EIGEN_STATIC_ASSERT(OtherDerived::RowsAtCompileTime==Dim && OtherDerived::ColsAtCompileTime==Dim, YOU_MADE_A_PROGRAMMING_MISTAKE) return mat; } + +} // end namespace Eigen diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Geometry/Scaling.h b/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Geometry/Scaling.h index 108e6d7d5..8e47c78fe 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Geometry/Scaling.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Geometry/Scaling.h @@ -24,6 +24,7 @@ // no include guard, we'll include this twice from All.h from Eigen2Support, and it's internal anyway +namespace Eigen { /** \geometry_module \ingroup Geometry_Module * @@ -177,3 +178,5 @@ Scaling::operator* (const TransformType& t) const res.prescale(m_coeffs); return res; } + +} // end namespace Eigen diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Geometry/Transform.h b/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Geometry/Transform.h index 88956c86c..28dcc03b7 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Geometry/Transform.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Geometry/Transform.h @@ -25,6 +25,7 @@ // no include guard, we'll include this twice from All.h from Eigen2Support, and it's internal anyway +namespace Eigen { // Note that we have to pass Dim and HDim because it is not allowed to use a template // parameter to define a template specialization. To be more precise, in the following @@ -796,3 +797,5 @@ struct ei_transform_product_impl { return ((tr.linear() * other) + tr.translation()) * (Scalar(1) / ( (tr.matrix().template block<1,Dim>(Dim,0) * other).coeff(0) + tr.matrix().coeff(Dim,Dim))); } }; + +} // end namespace Eigen diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Geometry/Translation.h b/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Geometry/Translation.h index e651e3102..dd6256893 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Geometry/Translation.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Geometry/Translation.h @@ -24,6 +24,7 @@ // no include guard, we'll include this twice from All.h from Eigen2Support, and it's internal anyway +namespace Eigen { /** \geometry_module \ingroup Geometry_Module * @@ -194,3 +195,5 @@ Translation::operator* (const TransformType& t) const res.pretranslate(m_coeffs); return res; } + +} // end namespace Eigen diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/LU.h b/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/LU.h index c23c11baa..0620096af 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/LU.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/LU.h @@ -25,6 +25,8 @@ #ifndef EIGEN2_LU_H #define EIGEN2_LU_H +namespace Eigen { + template class LU : public FullPivLU { @@ -57,7 +59,6 @@ class LU : public FullPivLU > ImageResultType; typedef FullPivLU Base; - LU() : Base() {} template explicit LU(const T& t) : Base(t), m_originalMatrix(t) {} @@ -129,5 +130,6 @@ MatrixBase::eigen2_lu() const } #endif +} // end namespace Eigen #endif // EIGEN2_LU_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Lazy.h b/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Lazy.h index c4288ede2..a1fb9c753 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Lazy.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Lazy.h @@ -25,6 +25,8 @@ #ifndef EIGEN_LAZY_H #define EIGEN_LAZY_H +namespace Eigen { + /** \deprecated it is only used by lazy() which is deprecated * * \returns an expression of *this with added flags @@ -79,4 +81,6 @@ Derived& MatrixBase::operator-=(const Flaggedoffset() = - (result->normal().cwise()* mean).sum(); } +} // end namespace Eigen #endif // EIGEN2_LEASTSQUARES_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/MathFunctions.h b/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/MathFunctions.h index caa44e63f..2baf4bb8f 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/MathFunctions.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/MathFunctions.h @@ -25,6 +25,8 @@ #ifndef EIGEN2_MATH_FUNCTIONS_H #define EIGEN2_MATH_FUNCTIONS_H +namespace Eigen { + template inline typename NumTraits::Real ei_real(const T& x) { return internal::real(x); } template inline typename NumTraits::Real ei_imag(const T& x) { return internal::imag(x); } template inline T ei_conj(const T& x) { return internal::conj(x); } @@ -65,4 +67,6 @@ inline bool ei_isApproxOrLessThan(const Scalar& x, const Scalar& y, return internal::isApproxOrLessThan(x, y, precision); } +} // end namespace Eigen + #endif // EIGEN2_MATH_FUNCTIONS_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Memory.h b/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Memory.h index 028347541..0588e2b34 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Memory.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Memory.h @@ -25,6 +25,8 @@ #ifndef EIGEN2_MEMORY_H #define EIGEN2_MEMORY_H +namespace Eigen { + inline void* ei_aligned_malloc(size_t size) { return internal::aligned_malloc(size); } inline void ei_aligned_free(void *ptr) { internal::aligned_free(ptr); } inline void* ei_aligned_realloc(void *ptr, size_t new_size, size_t old_size) { return internal::aligned_realloc(ptr, new_size, old_size); } @@ -53,6 +55,6 @@ template inline void ei_aligned_delete(T *ptr, size_t size) return internal::aligned_delete(ptr, size); } - +} // end namespace Eigen #endif // EIGEN2_MACROS_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Meta.h b/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Meta.h index 6e500b79a..70c210822 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Meta.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Meta.h @@ -25,6 +25,8 @@ #ifndef EIGEN2_META_H #define EIGEN2_META_H +namespace Eigen { + template struct ei_traits : internal::traits {}; @@ -83,4 +85,6 @@ class ei_meta_sqrt template class ei_meta_sqrt { public: enum { ret = (SupX*SupX <= Y) ? SupX : InfX }; }; +} // end namespace Eigen + #endif // EIGEN2_META_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Minor.h b/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Minor.h index eda91cc32..964e9546d 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Minor.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/Minor.h @@ -25,6 +25,8 @@ #ifndef EIGEN_MINOR_H #define EIGEN_MINOR_H +namespace Eigen { + /** * \class Minor * @@ -125,4 +127,6 @@ MatrixBase::minor(Index row, Index col) const return Minor(derived(), row, col); } +} // end namespace Eigen + #endif // EIGEN_MINOR_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/QR.h b/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/QR.h index 64f5d5ccb..60fc21f56 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/QR.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/QR.h @@ -26,6 +26,8 @@ #ifndef EIGEN2_QR_H #define EIGEN2_QR_H +namespace Eigen { + template class QR : public HouseholderQR { @@ -75,5 +77,6 @@ MatrixBase::qr() const return QR(eval()); } +} // end namespace Eigen #endif // EIGEN2_QR_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/SVD.h b/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/SVD.h index 16b4b488f..ff3b8a416 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/SVD.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/SVD.h @@ -25,6 +25,8 @@ #ifndef EIGEN2_SVD_H #define EIGEN2_SVD_H +namespace Eigen { + /** \ingroup SVD_Module * \nonstableyet * @@ -390,7 +392,7 @@ void SVD::compute(const MatrixType& matrix) Scalar ek = e[k]/scale; Scalar b = ((spm1 + sp)*(spm1 - sp) + epm1*epm1)/Scalar(2); Scalar c = (sp*epm1)*(sp*epm1); - Scalar shift = 0.0; + Scalar shift(0); if ((b != 0.0) || (c != 0.0)) { shift = ei_sqrt(b*b + c); @@ -646,4 +648,6 @@ MatrixBase::svd() const return SVD(derived()); } +} // end namespace Eigen + #endif // EIGEN2_SVD_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/TriangularSolver.h b/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/TriangularSolver.h index e94e47a50..e3374d8c0 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/TriangularSolver.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/TriangularSolver.h @@ -25,6 +25,8 @@ #ifndef EIGEN_TRIANGULAR_SOLVER2_H #define EIGEN_TRIANGULAR_SOLVER2_H +namespace Eigen { + const unsigned int UnitDiagBit = UnitDiag; const unsigned int SelfAdjointBit = SelfAdjoint; const unsigned int UpperTriangularBit = Upper; @@ -49,5 +51,7 @@ void Flagged::solveTriangularInPlace(const MatrixB { m_matrix.template triangularView().solveInPlace(other.derived()); } + +} // end namespace Eigen #endif // EIGEN_TRIANGULAR_SOLVER2_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/VectorBlock.h b/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/VectorBlock.h index 010031d19..8967c9019 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/VectorBlock.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Eigen2Support/VectorBlock.h @@ -26,6 +26,8 @@ #ifndef EIGEN2_VECTORBLOCK_H #define EIGEN2_VECTORBLOCK_H +namespace Eigen { + /** \deprecated use DenseMase::head(Index) */ template inline VectorBlock @@ -102,4 +104,6 @@ MatrixBase::end() const return VectorBlock(derived(), size() - Size); } +} // end namespace Eigen + #endif // EIGEN2_VECTORBLOCK_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/ComplexEigenSolver.h b/gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/ComplexEigenSolver.h index 57e00227d..91b4fa1e2 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/ComplexEigenSolver.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/ComplexEigenSolver.h @@ -27,9 +27,10 @@ #ifndef EIGEN_COMPLEX_EIGEN_SOLVER_H #define EIGEN_COMPLEX_EIGEN_SOLVER_H -#include "./EigenvaluesCommon.h" #include "./ComplexSchur.h" +namespace Eigen { + /** \eigenvalues_module \ingroup Eigenvalues_Module * * @@ -328,5 +329,6 @@ void ComplexEigenSolver::sortEigenvalues(bool computeEigenvectors) } } +} // end namespace Eigen #endif // EIGEN_COMPLEX_EIGEN_SOLVER_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/ComplexSchur.h b/gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/ComplexSchur.h index ec93af2e5..1a49cca13 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/ComplexSchur.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/ComplexSchur.h @@ -27,9 +27,10 @@ #ifndef EIGEN_COMPLEX_SCHUR_H #define EIGEN_COMPLEX_SCHUR_H -#include "./EigenvaluesCommon.h" #include "./HessenbergDecomposition.h" +namespace Eigen { + namespace internal { template struct complex_schur_reduce_to_hessenberg; } @@ -227,46 +228,6 @@ template class ComplexSchur friend struct internal::complex_schur_reduce_to_hessenberg::IsComplex>; }; -namespace internal { - -/** Computes the principal value of the square root of the complex \a z. */ -template -std::complex sqrt(const std::complex &z) -{ - RealScalar t, tre, tim; - - t = abs(z); - - if (abs(real(z)) <= abs(imag(z))) - { - // No cancellation in these formulas - tre = sqrt(RealScalar(0.5)*(t + real(z))); - tim = sqrt(RealScalar(0.5)*(t - real(z))); - } - else - { - // Stable computation of the above formulas - if (z.real() > RealScalar(0)) - { - tre = t + z.real(); - tim = abs(imag(z))*sqrt(RealScalar(0.5)/tre); - tre = sqrt(RealScalar(0.5)*tre); - } - else - { - tim = t - z.real(); - tre = abs(imag(z))*sqrt(RealScalar(0.5)/tim); - tim = sqrt(RealScalar(0.5)*tim); - } - } - if(z.imag() < RealScalar(0)) - tim = -tim; - - return (std::complex(tre,tim)); -} -} // end namespace internal - - /** If m_matT(i+1,i) is neglegible in floating point arithmetic * compared to m_matT(i,i) and m_matT(j,j), then set it to zero and * return true, else return false. */ @@ -302,7 +263,7 @@ typename ComplexSchur::ComplexScalar ComplexSchur::compu ComplexScalar b = t.coeff(0,1) * t.coeff(1,0); ComplexScalar c = t.coeff(0,0) - t.coeff(1,1); - ComplexScalar disc = internal::sqrt(c*c + RealScalar(4)*b); + ComplexScalar disc = sqrt(c*c + RealScalar(4)*b); ComplexScalar det = t.coeff(0,0) * t.coeff(1,1) - b; ComplexScalar trace = t.coeff(0,0) + t.coeff(1,1); ComplexScalar eival1 = (trace + disc) / RealScalar(2); @@ -445,4 +406,6 @@ void ComplexSchur::reduceToTriangularForm(bool computeU) m_matUisUptodate = computeU; } +} // end namespace Eigen + #endif // EIGEN_COMPLEX_SCHUR_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/ComplexSchur_MKL.h b/gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/ComplexSchur_MKL.h new file mode 100644 index 000000000..e21a8d836 --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/ComplexSchur_MKL.h @@ -0,0 +1,94 @@ +/* + Copyright (c) 2011, Intel Corporation. All rights reserved. + + Redistribution and use in source and binary forms, with or without modification, + are permitted provided that the following conditions are met: + + * Redistributions of source code must retain the above copyright notice, this + list of conditions and the following disclaimer. + * Redistributions in binary form must reproduce the above copyright notice, + this list of conditions and the following disclaimer in the documentation + and/or other materials provided with the distribution. + * Neither the name of Intel Corporation nor the names of its contributors may + be used to endorse or promote products derived from this software without + specific prior written permission. + + THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND + ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED + WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE + DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR + ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES + (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; + LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON + ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS + SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + + ******************************************************************************** + * Content : Eigen bindings to Intel(R) MKL + * Complex Schur needed to complex unsymmetrical eigenvalues/eigenvectors. + ******************************************************************************** +*/ + +#ifndef EIGEN_COMPLEX_SCHUR_MKL_H +#define EIGEN_COMPLEX_SCHUR_MKL_H + +#include "Eigen/src/Core/util/MKL_support.h" + +namespace Eigen { + +/** \internal Specialization for the data types supported by MKL */ + +#define EIGEN_MKL_SCHUR_COMPLEX(EIGTYPE, MKLTYPE, MKLPREFIX, MKLPREFIX_U, EIGCOLROW, MKLCOLROW) \ +template<> \ +ComplexSchur >& \ +ComplexSchur >::compute(const Matrix& matrix, bool computeU) \ +{ \ + typedef Matrix MatrixType; \ + typedef MatrixType::Scalar Scalar; \ + typedef MatrixType::RealScalar RealScalar; \ + typedef std::complex ComplexScalar; \ +\ + assert(matrix.cols() == matrix.rows()); \ +\ + m_matUisUptodate = false; \ + if(matrix.cols() == 1) \ + { \ + m_matT = matrix.cast(); \ + if(computeU) m_matU = ComplexMatrixType::Identity(1,1); \ + m_info = Success; \ + m_isInitialized = true; \ + m_matUisUptodate = computeU; \ + return *this; \ + } \ + lapack_int n = matrix.cols(), sdim, info; \ + lapack_int lda = matrix.outerStride(); \ + lapack_int matrix_order = MKLCOLROW; \ + char jobvs, sort='N'; \ + LAPACK_##MKLPREFIX_U##_SELECT1 select = 0; \ + jobvs = (computeU) ? 'V' : 'N'; \ + m_matU.resize(n, n); \ + lapack_int ldvs = m_matU.outerStride(); \ + m_matT = matrix; \ + Matrix w; \ + w.resize(n, 1);\ + info = LAPACKE_##MKLPREFIX##gees( matrix_order, jobvs, sort, select, n, (MKLTYPE*)m_matT.data(), lda, &sdim, (MKLTYPE*)w.data(), (MKLTYPE*)m_matU.data(), ldvs ); \ + if(info == 0) \ + m_info = Success; \ + else \ + m_info = NoConvergence; \ +\ + m_isInitialized = true; \ + m_matUisUptodate = computeU; \ + return *this; \ +\ +} + +EIGEN_MKL_SCHUR_COMPLEX(dcomplex, MKL_Complex16, z, Z, ColMajor, LAPACK_COL_MAJOR) +EIGEN_MKL_SCHUR_COMPLEX(scomplex, MKL_Complex8, c, C, ColMajor, LAPACK_COL_MAJOR) +EIGEN_MKL_SCHUR_COMPLEX(dcomplex, MKL_Complex16, z, Z, RowMajor, LAPACK_ROW_MAJOR) +EIGEN_MKL_SCHUR_COMPLEX(scomplex, MKL_Complex8, c, C, RowMajor, LAPACK_ROW_MAJOR) + +} // end namespace Eigen + +#endif // EIGEN_COMPLEX_SCHUR_MKL_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/EigenSolver.h b/gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/EigenSolver.h index f57353c06..f9365ae59 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/EigenSolver.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/EigenSolver.h @@ -26,9 +26,10 @@ #ifndef EIGEN_EIGENSOLVER_H #define EIGEN_EIGENSOLVER_H -#include "./EigenvaluesCommon.h" #include "./RealSchur.h" +namespace Eigen { + /** \eigenvalues_module \ingroup Eigenvalues_Module * * @@ -432,7 +433,7 @@ void EigenSolver::doComputeEigenvectors() const Scalar eps = NumTraits::epsilon(); // inefficient! this is already computed in RealSchur - Scalar norm = 0.0; + Scalar norm(0); for (Index j = 0; j < size; ++j) { norm += m_matT.row(j).segment((std::max)(j-1,Index(0)), size-(std::max)(j-1,Index(0))).cwiseAbs().sum(); @@ -452,7 +453,7 @@ void EigenSolver::doComputeEigenvectors() // Scalar vector if (q == Scalar(0)) { - Scalar lastr=0, lastw=0; + Scalar lastr(0), lastw(0); Index l = n; m_matT.coeffRef(n,n) = 1.0; @@ -498,7 +499,7 @@ void EigenSolver::doComputeEigenvectors() } else if (q < Scalar(0) && n > 0) // Complex vector { - Scalar lastra=0, lastsa=0, lastw=0; + Scalar lastra(0), lastsa(0), lastw(0); Index l = n-1; // Last vector component imaginary so matrix is triangular @@ -588,4 +589,6 @@ void EigenSolver::doComputeEigenvectors() } } +} // end namespace Eigen + #endif // EIGEN_EIGENSOLVER_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/GeneralizedSelfAdjointEigenSolver.h b/gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/GeneralizedSelfAdjointEigenSolver.h index 980af14ce..4eb2b229d 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/GeneralizedSelfAdjointEigenSolver.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/GeneralizedSelfAdjointEigenSolver.h @@ -26,9 +26,10 @@ #ifndef EIGEN_GENERALIZEDSELFADJOINTEIGENSOLVER_H #define EIGEN_GENERALIZEDSELFADJOINTEIGENSOLVER_H -#include "./EigenvaluesCommon.h" #include "./Tridiagonalization.h" +namespace Eigen { + /** \eigenvalues_module \ingroup Eigenvalues_Module * * @@ -236,4 +237,6 @@ compute(const MatrixType& matA, const MatrixType& matB, int options) return *this; } +} // end namespace Eigen + #endif // EIGEN_GENERALIZEDSELFADJOINTEIGENSOLVER_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/HessenbergDecomposition.h b/gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/HessenbergDecomposition.h index c17f155a5..88e63eba4 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/HessenbergDecomposition.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/HessenbergDecomposition.h @@ -26,6 +26,8 @@ #ifndef EIGEN_HESSENBERGDECOMPOSITION_H #define EIGEN_HESSENBERGDECOMPOSITION_H +namespace Eigen { + namespace internal { template struct HessenbergDecompositionMatrixHReturnType; @@ -379,6 +381,8 @@ template struct HessenbergDecompositionMatrixHReturnType const HessenbergDecomposition& m_hess; }; -} +} // end namespace internal + +} // end namespace Eigen #endif // EIGEN_HESSENBERGDECOMPOSITION_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/MatrixBaseEigenvalues.h b/gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/MatrixBaseEigenvalues.h index 5591519fb..a004e7e63 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/MatrixBaseEigenvalues.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/MatrixBaseEigenvalues.h @@ -26,6 +26,8 @@ #ifndef EIGEN_MATRIXBASEEIGENVALUES_H #define EIGEN_MATRIXBASEEIGENVALUES_H +namespace Eigen { + namespace internal { template @@ -167,4 +169,6 @@ SelfAdjointView::operatorNorm() const return eigenvalues().cwiseAbs().maxCoeff(); } +} // end namespace Eigen + #endif diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/RealSchur.h b/gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/RealSchur.h index cc9af11c1..e204344e0 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/RealSchur.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/RealSchur.h @@ -26,9 +26,10 @@ #ifndef EIGEN_REAL_SCHUR_H #define EIGEN_REAL_SCHUR_H -#include "./EigenvaluesCommon.h" #include "./HessenbergDecomposition.h" +namespace Eigen { + /** \eigenvalues_module \ingroup Eigenvalues_Module * * @@ -235,41 +236,43 @@ RealSchur& RealSchur::compute(const MatrixType& matrix, // Rows iu+1,...,end are already brought in triangular form. Index iu = m_matT.cols() - 1; Index iter = 0; // iteration count - Scalar exshift = 0.0; // sum of exceptional shifts + Scalar exshift(0); // sum of exceptional shifts Scalar norm = computeNormOfT(); - while (iu >= 0) + if(norm!=0) { - Index il = findSmallSubdiagEntry(iu, norm); + while (iu >= 0) + { + Index il = findSmallSubdiagEntry(iu, norm); - // Check for convergence - if (il == iu) // One root found - { - m_matT.coeffRef(iu,iu) = m_matT.coeff(iu,iu) + exshift; - if (iu > 0) - m_matT.coeffRef(iu, iu-1) = Scalar(0); - iu--; - iter = 0; + // Check for convergence + if (il == iu) // One root found + { + m_matT.coeffRef(iu,iu) = m_matT.coeff(iu,iu) + exshift; + if (iu > 0) + m_matT.coeffRef(iu, iu-1) = Scalar(0); + iu--; + iter = 0; + } + else if (il == iu-1) // Two roots found + { + splitOffTwoRows(iu, computeU, exshift); + iu -= 2; + iter = 0; + } + else // No convergence yet + { + // The firstHouseholderVector vector has to be initialized to something to get rid of a silly GCC warning (-O1 -Wall -DNDEBUG ) + Vector3s firstHouseholderVector(0,0,0), shiftInfo; + computeShift(iu, iter, exshift, shiftInfo); + iter = iter + 1; + if (iter > m_maxIterations) break; + Index im; + initFrancisQRStep(il, iu, shiftInfo, im, firstHouseholderVector); + performFrancisQRStep(il, im, iu, computeU, firstHouseholderVector, workspace); + } } - else if (il == iu-1) // Two roots found - { - splitOffTwoRows(iu, computeU, exshift); - iu -= 2; - iter = 0; - } - else // No convergence yet - { - // The firstHouseholderVector vector has to be initialized to something to get rid of a silly GCC warning (-O1 -Wall -DNDEBUG ) - Vector3s firstHouseholderVector(0,0,0), shiftInfo; - computeShift(iu, iter, exshift, shiftInfo); - iter = iter + 1; - if (iter > m_maxIterations) break; - Index im; - initFrancisQRStep(il, iu, shiftInfo, im, firstHouseholderVector); - performFrancisQRStep(il, im, iu, computeU, firstHouseholderVector, workspace); - } - } - + } if(iter <= m_maxIterations) m_info = Success; else @@ -288,7 +291,7 @@ inline typename MatrixType::Scalar RealSchur::computeNormOfT() // FIXME to be efficient the following would requires a triangular reduxion code // Scalar norm = m_matT.upper().cwiseAbs().sum() // + m_matT.bottomLeftCorner(size-1,size-1).diagonal().cwiseAbs().sum(); - Scalar norm = 0.0; + Scalar norm(0); for (Index j = 0; j < size; ++j) norm += m_matT.row(j).segment((std::max)(j-1,Index(0)), size-(std::max)(j-1,Index(0))).cwiseAbs().sum(); return norm; @@ -471,4 +474,6 @@ inline void RealSchur::performFrancisQRStep(Index il, Index im, Inde } } +} // end namespace Eigen + #endif // EIGEN_REAL_SCHUR_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/RealSchur_MKL.h b/gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/RealSchur_MKL.h new file mode 100644 index 000000000..c9689520b --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/RealSchur_MKL.h @@ -0,0 +1,83 @@ +/* + Copyright (c) 2011, Intel Corporation. All rights reserved. + + Redistribution and use in source and binary forms, with or without modification, + are permitted provided that the following conditions are met: + + * Redistributions of source code must retain the above copyright notice, this + list of conditions and the following disclaimer. + * Redistributions in binary form must reproduce the above copyright notice, + this list of conditions and the following disclaimer in the documentation + and/or other materials provided with the distribution. + * Neither the name of Intel Corporation nor the names of its contributors may + be used to endorse or promote products derived from this software without + specific prior written permission. + + THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND + ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED + WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE + DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR + ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES + (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; + LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON + ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS + SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + + ******************************************************************************** + * Content : Eigen bindings to Intel(R) MKL + * Real Schur needed to real unsymmetrical eigenvalues/eigenvectors. + ******************************************************************************** +*/ + +#ifndef EIGEN_REAL_SCHUR_MKL_H +#define EIGEN_REAL_SCHUR_MKL_H + +#include "Eigen/src/Core/util/MKL_support.h" + +namespace Eigen { + +/** \internal Specialization for the data types supported by MKL */ + +#define EIGEN_MKL_SCHUR_REAL(EIGTYPE, MKLTYPE, MKLPREFIX, MKLPREFIX_U, EIGCOLROW, MKLCOLROW) \ +template<> \ +RealSchur >& \ +RealSchur >::compute(const Matrix& matrix, bool computeU) \ +{ \ + typedef Matrix MatrixType; \ + typedef MatrixType::Scalar Scalar; \ + typedef MatrixType::RealScalar RealScalar; \ +\ + assert(matrix.cols() == matrix.rows()); \ +\ + lapack_int n = matrix.cols(), sdim, info; \ + lapack_int lda = matrix.outerStride(); \ + lapack_int matrix_order = MKLCOLROW; \ + char jobvs, sort='N'; \ + LAPACK_##MKLPREFIX_U##_SELECT2 select = 0; \ + jobvs = (computeU) ? 'V' : 'N'; \ + m_matU.resize(n, n); \ + lapack_int ldvs = m_matU.outerStride(); \ + m_matT = matrix; \ + Matrix wr, wi; \ + wr.resize(n, 1); wi.resize(n, 1); \ + info = LAPACKE_##MKLPREFIX##gees( matrix_order, jobvs, sort, select, n, (MKLTYPE*)m_matT.data(), lda, &sdim, (MKLTYPE*)wr.data(), (MKLTYPE*)wi.data(), (MKLTYPE*)m_matU.data(), ldvs ); \ + if(info == 0) \ + m_info = Success; \ + else \ + m_info = NoConvergence; \ +\ + m_isInitialized = true; \ + m_matUisUptodate = computeU; \ + return *this; \ +\ +} + +EIGEN_MKL_SCHUR_REAL(double, double, d, D, ColMajor, LAPACK_COL_MAJOR) +EIGEN_MKL_SCHUR_REAL(float, float, s, S, ColMajor, LAPACK_COL_MAJOR) +EIGEN_MKL_SCHUR_REAL(double, double, d, D, RowMajor, LAPACK_ROW_MAJOR) +EIGEN_MKL_SCHUR_REAL(float, float, s, S, RowMajor, LAPACK_ROW_MAJOR) + +} // end namespace Eigen + +#endif // EIGEN_REAL_SCHUR_MKL_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h b/gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h index ad107c632..b4aa1ef20 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h @@ -26,12 +26,17 @@ #ifndef EIGEN_SELFADJOINTEIGENSOLVER_H #define EIGEN_SELFADJOINTEIGENSOLVER_H -#include "./EigenvaluesCommon.h" #include "./Tridiagonalization.h" +namespace Eigen { + template class GeneralizedSelfAdjointEigenSolver; +namespace internal { +template struct direct_selfadjoint_eigenvalues; +} + /** \eigenvalues_module \ingroup Eigenvalues_Module * * @@ -86,7 +91,7 @@ template class SelfAdjointEigenSolver Options = MatrixType::Options, MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime }; - + /** \brief Scalar type for matrices of type \p _MatrixType. */ typedef typename MatrixType::Scalar Scalar; typedef typename MatrixType::Index Index; @@ -98,6 +103,8 @@ template class SelfAdjointEigenSolver * complex. */ typedef typename NumTraits::Real RealScalar; + + friend struct internal::direct_selfadjoint_eigenvalues::IsComplex>; /** \brief Type for vector of eigenvalues as returned by eigenvalues(). * @@ -198,6 +205,22 @@ template class SelfAdjointEigenSolver * \sa SelfAdjointEigenSolver(const MatrixType&, int) */ SelfAdjointEigenSolver& compute(const MatrixType& matrix, int options = ComputeEigenvectors); + + /** \brief Computes eigendecomposition of given matrix using a direct algorithm + * + * This is a variant of compute(const MatrixType&, int options) which + * directly solves the underlying polynomial equation. + * + * Currently only 3x3 matrices for which the sizes are known at compile time are supported (e.g., Matrix3d). + * + * This method is usually significantly faster than the QR algorithm + * but it might also be less accurate. It is also worth noting that + * for 3x3 matrices it involves trigonometric operations which are + * not necessarily available for all scalar types. + * + * \sa compute(const MatrixType&, int options) + */ + SelfAdjointEigenSolver& computeDirect(const MatrixType& matrix, int options = ComputeEigenvectors); /** \brief Returns the eigenvectors of given matrix. * @@ -401,7 +424,7 @@ SelfAdjointEigenSolver& SelfAdjointEigenSolver // map the matrix coefficients to [-1:1] to avoid over- and underflow. RealScalar scale = matrix.cwiseAbs().maxCoeff(); - if(scale==Scalar(0)) scale = 1; + if(scale==RealScalar(0)) scale = RealScalar(1); mat = matrix / scale; m_subdiag.resize(n-1); internal::tridiagonalization_inplace(mat, diag, m_subdiag, computeEigenvectors); @@ -466,6 +489,264 @@ SelfAdjointEigenSolver& SelfAdjointEigenSolver return *this; } + +namespace internal { + +template struct direct_selfadjoint_eigenvalues +{ + static inline void run(SolverType& eig, const typename SolverType::MatrixType& A, int options) + { eig.compute(A,options); } +}; + +template struct direct_selfadjoint_eigenvalues +{ + typedef typename SolverType::MatrixType MatrixType; + typedef typename SolverType::RealVectorType VectorType; + typedef typename SolverType::Scalar Scalar; + + static inline void computeRoots(const MatrixType& m, VectorType& roots) + { + using std::sqrt; + using std::atan2; + using std::cos; + using std::sin; + const Scalar s_inv3 = Scalar(1.0)/Scalar(3.0); + const Scalar s_sqrt3 = sqrt(Scalar(3.0)); + + // The characteristic equation is x^3 - c2*x^2 + c1*x - c0 = 0. The + // eigenvalues are the roots to this equation, all guaranteed to be + // real-valued, because the matrix is symmetric. + Scalar c0 = m(0,0)*m(1,1)*m(2,2) + Scalar(2)*m(1,0)*m(2,0)*m(2,1) - m(0,0)*m(2,1)*m(2,1) - m(1,1)*m(2,0)*m(2,0) - m(2,2)*m(1,0)*m(1,0); + Scalar c1 = m(0,0)*m(1,1) - m(1,0)*m(1,0) + m(0,0)*m(2,2) - m(2,0)*m(2,0) + m(1,1)*m(2,2) - m(2,1)*m(2,1); + Scalar c2 = m(0,0) + m(1,1) + m(2,2); + + // Construct the parameters used in classifying the roots of the equation + // and in solving the equation for the roots in closed form. + Scalar c2_over_3 = c2*s_inv3; + Scalar a_over_3 = (c1 - c2*c2_over_3)*s_inv3; + if (a_over_3 > Scalar(0)) + a_over_3 = Scalar(0); + + Scalar half_b = Scalar(0.5)*(c0 + c2_over_3*(Scalar(2)*c2_over_3*c2_over_3 - c1)); + + Scalar q = half_b*half_b + a_over_3*a_over_3*a_over_3; + if (q > Scalar(0)) + q = Scalar(0); + + // Compute the eigenvalues by solving for the roots of the polynomial. + Scalar rho = sqrt(-a_over_3); + Scalar theta = atan2(sqrt(-q),half_b)*s_inv3; + Scalar cos_theta = cos(theta); + Scalar sin_theta = sin(theta); + roots(0) = c2_over_3 + Scalar(2)*rho*cos_theta; + roots(1) = c2_over_3 - rho*(cos_theta + s_sqrt3*sin_theta); + roots(2) = c2_over_3 - rho*(cos_theta - s_sqrt3*sin_theta); + + // Sort in increasing order. + if (roots(0) >= roots(1)) + std::swap(roots(0),roots(1)); + if (roots(1) >= roots(2)) + { + std::swap(roots(1),roots(2)); + if (roots(0) >= roots(1)) + std::swap(roots(0),roots(1)); + } + } + + static inline void run(SolverType& solver, const MatrixType& mat, int options) + { + using std::sqrt; + eigen_assert(mat.cols() == 3 && mat.cols() == mat.rows()); + eigen_assert((options&~(EigVecMask|GenEigMask))==0 + && (options&EigVecMask)!=EigVecMask + && "invalid option parameter"); + bool computeEigenvectors = (options&ComputeEigenvectors)==ComputeEigenvectors; + + MatrixType& eivecs = solver.m_eivec; + VectorType& eivals = solver.m_eivalues; + + // map the matrix coefficients to [-1:1] to avoid over- and underflow. + Scalar scale = mat.cwiseAbs().maxCoeff(); + MatrixType scaledMat = mat / scale; + + // compute the eigenvalues + computeRoots(scaledMat,eivals); + + // compute the eigen vectors + if(computeEigenvectors) + { + Scalar safeNorm2 = Eigen::NumTraits::epsilon(); + safeNorm2 *= safeNorm2; + if((eivals(2)-eivals(0))<=Eigen::NumTraits::epsilon()) + { + eivecs.setIdentity(); + } + else + { + scaledMat = scaledMat.template selfadjointView(); + MatrixType tmp; + tmp = scaledMat; + + Scalar d0 = eivals(2) - eivals(1); + Scalar d1 = eivals(1) - eivals(0); + int k = d0 > d1 ? 2 : 0; + d0 = d0 > d1 ? d1 : d0; + + tmp.diagonal().array () -= eivals(k); + VectorType cross; + Scalar n; + n = (cross = tmp.row(0).cross(tmp.row(1))).squaredNorm(); + + if(n>safeNorm2) + eivecs.col(k) = cross / sqrt(n); + else + { + n = (cross = tmp.row(0).cross(tmp.row(2))).squaredNorm(); + + if(n>safeNorm2) + eivecs.col(k) = cross / sqrt(n); + else + { + n = (cross = tmp.row(1).cross(tmp.row(2))).squaredNorm(); + + if(n>safeNorm2) + eivecs.col(k) = cross / sqrt(n); + else + { + // the input matrix and/or the eigenvaues probably contains some inf/NaN, + // => exit + // scale back to the original size. + eivals *= scale; + + solver.m_info = NumericalIssue; + solver.m_isInitialized = true; + solver.m_eigenvectorsOk = computeEigenvectors; + return; + } + } + } + + tmp = scaledMat; + tmp.diagonal().array() -= eivals(1); + + if(d0<=Eigen::NumTraits::epsilon()) + eivecs.col(1) = eivecs.col(k).unitOrthogonal(); + else + { + n = (cross = eivecs.col(k).cross(tmp.row(0).normalized())).squaredNorm(); + if(n>safeNorm2) + eivecs.col(1) = cross / sqrt(n); + else + { + n = (cross = eivecs.col(k).cross(tmp.row(1))).squaredNorm(); + if(n>safeNorm2) + eivecs.col(1) = cross / sqrt(n); + else + { + n = (cross = eivecs.col(k).cross(tmp.row(2))).squaredNorm(); + if(n>safeNorm2) + eivecs.col(1) = cross / sqrt(n); + else + { + // we should never reach this point, + // if so the last two eigenvalues are likely to ve very closed to each other + eivecs.col(1) = eivecs.col(k).unitOrthogonal(); + } + } + } + + // make sure that eivecs[1] is orthogonal to eivecs[2] + Scalar d = eivecs.col(1).dot(eivecs.col(k)); + eivecs.col(1) = (eivecs.col(1) - d * eivecs.col(k)).normalized(); + } + + eivecs.col(k==2 ? 0 : 2) = eivecs.col(k).cross(eivecs.col(1)).normalized(); + } + } + // Rescale back to the original size. + eivals *= scale; + + solver.m_info = Success; + solver.m_isInitialized = true; + solver.m_eigenvectorsOk = computeEigenvectors; + } +}; + +// 2x2 direct eigenvalues decomposition, code from Hauke Heibel +template struct direct_selfadjoint_eigenvalues +{ + typedef typename SolverType::MatrixType MatrixType; + typedef typename SolverType::RealVectorType VectorType; + typedef typename SolverType::Scalar Scalar; + + static inline void computeRoots(const MatrixType& m, VectorType& roots) + { + using std::sqrt; + const Scalar t0 = Scalar(0.5) * sqrt( abs2(m(0,0)-m(1,1)) + Scalar(4)*m(1,0)*m(1,0)); + const Scalar t1 = Scalar(0.5) * (m(0,0) + m(1,1)); + roots(0) = t1 - t0; + roots(1) = t1 + t0; + } + + static inline void run(SolverType& solver, const MatrixType& mat, int options) + { + eigen_assert(mat.cols() == 2 && mat.cols() == mat.rows()); + eigen_assert((options&~(EigVecMask|GenEigMask))==0 + && (options&EigVecMask)!=EigVecMask + && "invalid option parameter"); + bool computeEigenvectors = (options&ComputeEigenvectors)==ComputeEigenvectors; + + MatrixType& eivecs = solver.m_eivec; + VectorType& eivals = solver.m_eivalues; + + // map the matrix coefficients to [-1:1] to avoid over- and underflow. + Scalar scale = mat.cwiseAbs().maxCoeff(); + scale = (std::max)(scale,Scalar(1)); + MatrixType scaledMat = mat / scale; + + // Compute the eigenvalues + computeRoots(scaledMat,eivals); + + // compute the eigen vectors + if(computeEigenvectors) + { + scaledMat.diagonal().array () -= eivals(1); + Scalar a2 = abs2(scaledMat(0,0)); + Scalar c2 = abs2(scaledMat(1,1)); + Scalar b2 = abs2(scaledMat(1,0)); + if(a2>c2) + { + eivecs.col(1) << -scaledMat(1,0), scaledMat(0,0); + eivecs.col(1) /= sqrt(a2+b2); + } + else + { + eivecs.col(1) << -scaledMat(1,1), scaledMat(1,0); + eivecs.col(1) /= sqrt(c2+b2); + } + + eivecs.col(0) << eivecs.col(1).unitOrthogonal(); + } + + // Rescale back to the original size. + eivals *= scale; + + solver.m_info = Success; + solver.m_isInitialized = true; + solver.m_eigenvectorsOk = computeEigenvectors; + } +}; + +} + +template +SelfAdjointEigenSolver& SelfAdjointEigenSolver +::computeDirect(const MatrixType& matrix, int options) +{ + internal::direct_selfadjoint_eigenvalues::IsComplex>::run(*this,matrix,options); + return *this; +} + namespace internal { template static void tridiagonal_qr_step(RealScalar* diag, RealScalar* subdiag, Index start, Index end, Scalar* matrixQ, Index n) @@ -515,6 +796,9 @@ static void tridiagonal_qr_step(RealScalar* diag, RealScalar* subdiag, Index sta } } } + } // end namespace internal +} // end namespace Eigen + #endif // EIGEN_SELFADJOINTEIGENSOLVER_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/SelfAdjointEigenSolver_MKL.h b/gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/SelfAdjointEigenSolver_MKL.h new file mode 100644 index 000000000..5ebcd08e1 --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/SelfAdjointEigenSolver_MKL.h @@ -0,0 +1,92 @@ +/* + Copyright (c) 2011, Intel Corporation. All rights reserved. + + Redistribution and use in source and binary forms, with or without modification, + are permitted provided that the following conditions are met: + + * Redistributions of source code must retain the above copyright notice, this + list of conditions and the following disclaimer. + * Redistributions in binary form must reproduce the above copyright notice, + this list of conditions and the following disclaimer in the documentation + and/or other materials provided with the distribution. + * Neither the name of Intel Corporation nor the names of its contributors may + be used to endorse or promote products derived from this software without + specific prior written permission. + + THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND + ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED + WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE + DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR + ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES + (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; + LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON + ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS + SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + + ******************************************************************************** + * Content : Eigen bindings to Intel(R) MKL + * Self-adjoint eigenvalues/eigenvectors. + ******************************************************************************** +*/ + +#ifndef EIGEN_SAEIGENSOLVER_MKL_H +#define EIGEN_SAEIGENSOLVER_MKL_H + +#include "Eigen/src/Core/util/MKL_support.h" + +namespace Eigen { + +/** \internal Specialization for the data types supported by MKL */ + +#define EIGEN_MKL_EIG_SELFADJ(EIGTYPE, MKLTYPE, MKLRTYPE, MKLNAME, EIGCOLROW, MKLCOLROW ) \ +template<> \ +SelfAdjointEigenSolver >& \ +SelfAdjointEigenSolver >::compute(const Matrix& matrix, int options) \ +{ \ + eigen_assert(matrix.cols() == matrix.rows()); \ + eigen_assert((options&~(EigVecMask|GenEigMask))==0 \ + && (options&EigVecMask)!=EigVecMask \ + && "invalid option parameter"); \ + bool computeEigenvectors = (options&ComputeEigenvectors)==ComputeEigenvectors; \ + lapack_int n = matrix.cols(), lda, matrix_order, info; \ + m_eivalues.resize(n,1); \ + m_subdiag.resize(n-1); \ + m_eivec = matrix; \ +\ + if(n==1) \ + { \ + m_eivalues.coeffRef(0,0) = internal::real(matrix.coeff(0,0)); \ + if(computeEigenvectors) m_eivec.setOnes(n,n); \ + m_info = Success; \ + m_isInitialized = true; \ + m_eigenvectorsOk = computeEigenvectors; \ + return *this; \ + } \ +\ + lda = matrix.outerStride(); \ + matrix_order=MKLCOLROW; \ + char jobz, uplo='L'/*, range='A'*/; \ + jobz = computeEigenvectors ? 'V' : 'N'; \ +\ + info = LAPACKE_##MKLNAME( matrix_order, jobz, uplo, n, (MKLTYPE*)m_eivec.data(), lda, (MKLRTYPE*)m_eivalues.data() ); \ + m_info = (info==0) ? Success : NoConvergence; \ + m_isInitialized = true; \ + m_eigenvectorsOk = computeEigenvectors; \ + return *this; \ +} + + +EIGEN_MKL_EIG_SELFADJ(double, double, double, dsyev, ColMajor, LAPACK_COL_MAJOR) +EIGEN_MKL_EIG_SELFADJ(float, float, float, ssyev, ColMajor, LAPACK_COL_MAJOR) +EIGEN_MKL_EIG_SELFADJ(dcomplex, MKL_Complex16, double, zheev, ColMajor, LAPACK_COL_MAJOR) +EIGEN_MKL_EIG_SELFADJ(scomplex, MKL_Complex8, float, cheev, ColMajor, LAPACK_COL_MAJOR) + +EIGEN_MKL_EIG_SELFADJ(double, double, double, dsyev, RowMajor, LAPACK_ROW_MAJOR) +EIGEN_MKL_EIG_SELFADJ(float, float, float, ssyev, RowMajor, LAPACK_ROW_MAJOR) +EIGEN_MKL_EIG_SELFADJ(dcomplex, MKL_Complex16, double, zheev, RowMajor, LAPACK_ROW_MAJOR) +EIGEN_MKL_EIG_SELFADJ(scomplex, MKL_Complex8, float, cheev, RowMajor, LAPACK_ROW_MAJOR) + +} // end namespace Eigen + +#endif // EIGEN_SAEIGENSOLVER_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/Tridiagonalization.h b/gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/Tridiagonalization.h index ae4cdce7a..e8f0ac5d1 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/Tridiagonalization.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/Tridiagonalization.h @@ -26,6 +26,8 @@ #ifndef EIGEN_TRIDIAGONALIZATION_H #define EIGEN_TRIDIAGONALIZATION_H +namespace Eigen { + namespace internal { template struct TridiagonalizationMatrixTReturnType; @@ -97,13 +99,13 @@ template class Tridiagonalization typedef internal::TridiagonalizationMatrixTReturnType MatrixTReturnType; typedef typename internal::conditional::IsComplex, - const typename Diagonal::RealReturnType, + typename internal::add_const_on_value_type::RealReturnType>::type, const Diagonal >::type DiagonalReturnType; typedef typename internal::conditional::IsComplex, - const typename Diagonal< - Block >::RealReturnType, + typename internal::add_const_on_value_type >::RealReturnType>::type, const Diagonal< Block > >::type SubDiagonalReturnType; @@ -560,9 +562,11 @@ template struct TridiagonalizationMatrixTReturnType Index cols() const { return m_matrix.cols(); } protected: - const typename MatrixType::Nested m_matrix; + typename MatrixType::Nested m_matrix; }; } // end namespace internal +} // end namespace Eigen + #endif // EIGEN_TRIDIAGONALIZATION_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Geometry/AlignedBox.h b/gtsam/3rdparty/Eigen/Eigen/src/Geometry/AlignedBox.h index b51deb3f3..2cb894330 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Geometry/AlignedBox.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Geometry/AlignedBox.h @@ -25,6 +25,8 @@ #ifndef EIGEN_ALIGNEDBOX_H #define EIGEN_ALIGNEDBOX_H +namespace Eigen { + /** \geometry_module \ingroup Geometry_Module * * @@ -190,7 +192,7 @@ EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF_VECTORIZABLE_FIXED_SIZE(_Scalar,_AmbientDim) template inline bool contains(const MatrixBase& a_p) const { - const typename internal::nested::type p(a_p.derived()); + typename internal::nested::type p(a_p.derived()); return (m_min.array()<=p.array()).all() && (p.array()<=m_max.array()).all(); } @@ -202,7 +204,7 @@ EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF_VECTORIZABLE_FIXED_SIZE(_Scalar,_AmbientDim) template inline AlignedBox& extend(const MatrixBase& a_p) { - const typename internal::nested::type p(a_p.derived()); + typename internal::nested::type p(a_p.derived()); m_min = m_min.cwiseMin(p); m_max = m_max.cwiseMax(p); return *this; @@ -310,7 +312,7 @@ template inline Scalar AlignedBox::squaredExteriorDistance(const MatrixBase& a_p) const { const typename internal::nested::type p(a_p.derived()); - Scalar dist2 = 0.; + Scalar dist2(0); Scalar aux; for (Index k=0; k::squaredExteriorDistance(const Matri template inline Scalar AlignedBox::squaredExteriorDistance(const AlignedBox& b) const { - Scalar dist2 = 0.; + Scalar dist2(0); Scalar aux; for (Index k=0; k::squaredExteriorDistance(const Align return dist2; } +/** \defgroup alignedboxtypedefs Global aligned box typedefs + * + * \ingroup Geometry_Module + * + * Eigen defines several typedef shortcuts for most common aligned box types. + * + * The general patterns are the following: + * + * \c AlignedBoxSizeType where \c Size can be \c 1, \c 2,\c 3,\c 4 for fixed size boxes or \c X for dynamic size, + * and where \c Type can be \c i for integer, \c f for float, \c d for double. + * + * For example, \c AlignedBox3d is a fixed-size 3x3 aligned box type of doubles, and \c AlignedBoxXf is a dynamic-size aligned box of floats. + * + * \sa class AlignedBox + */ + +#define EIGEN_MAKE_TYPEDEFS(Type, TypeSuffix, Size, SizeSuffix) \ +/** \ingroup alignedboxtypedefs */ \ +typedef AlignedBox AlignedBox##SizeSuffix##TypeSuffix; + +#define EIGEN_MAKE_TYPEDEFS_ALL_SIZES(Type, TypeSuffix) \ +EIGEN_MAKE_TYPEDEFS(Type, TypeSuffix, 1, 1) \ +EIGEN_MAKE_TYPEDEFS(Type, TypeSuffix, 2, 2) \ +EIGEN_MAKE_TYPEDEFS(Type, TypeSuffix, 3, 3) \ +EIGEN_MAKE_TYPEDEFS(Type, TypeSuffix, 4, 4) \ +EIGEN_MAKE_TYPEDEFS(Type, TypeSuffix, Dynamic, X) + +EIGEN_MAKE_TYPEDEFS_ALL_SIZES(int, i) +EIGEN_MAKE_TYPEDEFS_ALL_SIZES(float, f) +EIGEN_MAKE_TYPEDEFS_ALL_SIZES(double, d) + +#undef EIGEN_MAKE_TYPEDEFS_ALL_SIZES +#undef EIGEN_MAKE_TYPEDEFS + +} // end namespace Eigen + #endif // EIGEN_ALIGNEDBOX_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Geometry/AngleAxis.h b/gtsam/3rdparty/Eigen/Eigen/src/Geometry/AngleAxis.h index 0ec4624cf..f0e3ff2b3 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Geometry/AngleAxis.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Geometry/AngleAxis.h @@ -25,6 +25,8 @@ #ifndef EIGEN_ANGLEAXIS_H #define EIGEN_ANGLEAXIS_H +namespace Eigen { + /** \geometry_module \ingroup Geometry_Module * * \class AngleAxis @@ -144,7 +146,7 @@ public: m_angle = Scalar(other.angle()); } - inline static const AngleAxis Identity() { return AngleAxis(0, Vector3::UnitX()); } + static inline const AngleAxis Identity() { return AngleAxis(0, Vector3::UnitX()); } /** \returns \c true if \c *this is approximately equal to \a other, within the precision * determined by \a prec. @@ -238,4 +240,6 @@ AngleAxis::toRotationMatrix(void) const return res; } +} // end namespace Eigen + #endif // EIGEN_ANGLEAXIS_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Geometry/EulerAngles.h b/gtsam/3rdparty/Eigen/Eigen/src/Geometry/EulerAngles.h index d246a6ebf..0ce7f957d 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Geometry/EulerAngles.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Geometry/EulerAngles.h @@ -25,6 +25,8 @@ #ifndef EIGEN_EULERANGLES_H #define EIGEN_EULERANGLES_H +namespace Eigen { + /** \geometry_module \ingroup Geometry_Module * * @@ -92,5 +94,6 @@ MatrixBase::eulerAngles(Index a0, Index a1, Index a2) const return res; } +} // end namespace Eigen #endif // EIGEN_EULERANGLES_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Geometry/Homogeneous.h b/gtsam/3rdparty/Eigen/Eigen/src/Geometry/Homogeneous.h index 2bc4f7e87..0c4cda01d 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Geometry/Homogeneous.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Geometry/Homogeneous.h @@ -25,6 +25,8 @@ #ifndef EIGEN_HOMOGENEOUS_H #define EIGEN_HOMOGENEOUS_H +namespace Eigen { + /** \geometry_module \ingroup Geometry_Module * * \class Homogeneous @@ -121,7 +123,7 @@ template class Homogeneous } protected: - const typename MatrixType::Nested m_matrix; + typename MatrixType::Nested m_matrix; }; /** \geometry_module @@ -216,8 +218,8 @@ template struct take_matrix_for_product > { typedef Transform TransformType; - typedef typename TransformType::ConstAffinePart type; - static const type run (const TransformType& x) { return x.affine(); } + typedef typename internal::add_const::type type; + static type run (const TransformType& x) { return x.affine(); } }; template @@ -270,8 +272,8 @@ struct homogeneous_left_product_impl,Lhs> .template replicate(m_rhs.cols()); } - const typename LhsMatrixTypeCleaned::Nested m_lhs; - const typename MatrixType::Nested m_rhs; + typename LhsMatrixTypeCleaned::Nested m_lhs; + typename MatrixType::Nested m_rhs; }; template @@ -309,10 +311,12 @@ struct homogeneous_right_product_impl,Rhs> .template replicate(m_lhs.rows()); } - const typename MatrixType::Nested m_lhs; - const typename Rhs::Nested m_rhs; + typename MatrixType::Nested m_lhs; + typename Rhs::Nested m_rhs; }; } // end namespace internal +} // end namespace Eigen + #endif // EIGEN_HOMOGENEOUS_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Geometry/Hyperplane.h b/gtsam/3rdparty/Eigen/Eigen/src/Geometry/Hyperplane.h index d85d3e553..6abf1664d 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Geometry/Hyperplane.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Geometry/Hyperplane.h @@ -26,6 +26,8 @@ #ifndef EIGEN_HYPERPLANE_H #define EIGEN_HYPERPLANE_H +namespace Eigen { + /** \geometry_module \ingroup Geometry_Module * * \class Hyperplane @@ -277,4 +279,6 @@ protected: Coefficients m_coeffs; }; +} // end namespace Eigen + #endif // EIGEN_HYPERPLANE_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Geometry/OrthoMethods.h b/gtsam/3rdparty/Eigen/Eigen/src/Geometry/OrthoMethods.h index 52b469881..0a8a81dd1 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Geometry/OrthoMethods.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Geometry/OrthoMethods.h @@ -26,6 +26,8 @@ #ifndef EIGEN_ORTHOMETHODS_H #define EIGEN_ORTHOMETHODS_H +namespace Eigen { + /** \geometry_module * * \returns the cross product of \c *this and \a other @@ -43,8 +45,8 @@ MatrixBase::cross(const MatrixBase& other) const // Note that there is no need for an expression here since the compiler // optimize such a small temporary very well (even within a complex expression) - const typename internal::nested::type lhs(derived()); - const typename internal::nested::type rhs(other.derived()); + typename internal::nested::type lhs(derived()); + typename internal::nested::type rhs(other.derived()); return typename cross_product_return_type::type( internal::conj(lhs.coeff(1) * rhs.coeff(2) - lhs.coeff(2) * rhs.coeff(1)), internal::conj(lhs.coeff(2) * rhs.coeff(0) - lhs.coeff(0) * rhs.coeff(2)), @@ -56,9 +58,9 @@ namespace internal { template< int Arch,typename VectorLhs,typename VectorRhs, typename Scalar = typename VectorLhs::Scalar, - bool Vectorizable = (VectorLhs::Flags&VectorRhs::Flags)&PacketAccessBit> + bool Vectorizable = bool((VectorLhs::Flags&VectorRhs::Flags)&PacketAccessBit)> struct cross3_impl { - inline static typename internal::plain_matrix_type::type + static inline typename internal::plain_matrix_type::type run(const VectorLhs& lhs, const VectorRhs& rhs) { return typename internal::plain_matrix_type::type( @@ -145,7 +147,7 @@ struct unitOrthogonal_selector typedef typename NumTraits::Real RealScalar; typedef typename Derived::Index Index; typedef Matrix Vector2; - inline static VectorType run(const Derived& src) + static inline VectorType run(const Derived& src) { VectorType perp = VectorType::Zero(src.size()); Index maxi = 0; @@ -167,7 +169,7 @@ struct unitOrthogonal_selector typedef typename plain_matrix_type::type VectorType; typedef typename traits::Scalar Scalar; typedef typename NumTraits::Real RealScalar; - inline static VectorType run(const Derived& src) + static inline VectorType run(const Derived& src) { VectorType perp; /* Let us compute the crossed product of *this with a vector @@ -205,7 +207,7 @@ template struct unitOrthogonal_selector { typedef typename plain_matrix_type::type VectorType; - inline static VectorType run(const Derived& src) + static inline VectorType run(const Derived& src) { return VectorType(-conj(src.y()), conj(src.x())).normalized(); } }; @@ -226,4 +228,6 @@ MatrixBase::unitOrthogonal() const return internal::unitOrthogonal_selector::run(derived()); } +} // end namespace Eigen + #endif // EIGEN_ORTHOMETHODS_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Geometry/ParametrizedLine.h b/gtsam/3rdparty/Eigen/Eigen/src/Geometry/ParametrizedLine.h index b90f9c088..ddbda83dc 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Geometry/ParametrizedLine.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Geometry/ParametrizedLine.h @@ -26,6 +26,8 @@ #ifndef EIGEN_PARAMETRIZEDLINE_H #define EIGEN_PARAMETRIZEDLINE_H +namespace Eigen { + /** \geometry_module \ingroup Geometry_Module * * \class ParametrizedLine @@ -106,8 +108,16 @@ public: VectorType projection(const VectorType& p) const { return origin() + direction().dot(p-origin()) * direction(); } + VectorType pointAt( Scalar t ) const; + + template + Scalar intersectionParameter(const Hyperplane<_Scalar, _AmbientDim, OtherOptions>& hyperplane) const; + template Scalar intersection(const Hyperplane<_Scalar, _AmbientDim, OtherOptions>& hyperplane) const; + + template + VectorType intersectionPoint(const Hyperplane<_Scalar, _AmbientDim, OtherOptions>& hyperplane) const; /** \returns \c *this with scalar type casted to \a NewScalarType * @@ -155,14 +165,46 @@ inline ParametrizedLine<_Scalar, _AmbientDim,_Options>::ParametrizedLine(const H origin() = -hyperplane.normal()*hyperplane.offset(); } -/** \returns the parameter value of the intersection between \c *this and the given hyperplane +/** \returns the point at \a t along this line + */ +template +inline typename ParametrizedLine<_Scalar, _AmbientDim,_Options>::VectorType +ParametrizedLine<_Scalar, _AmbientDim,_Options>::pointAt( _Scalar t ) const +{ + return origin() + (direction()*t); +} + +/** \returns the parameter value of the intersection between \c *this and the given \a hyperplane */ template template -inline _Scalar ParametrizedLine<_Scalar, _AmbientDim,_Options>::intersection(const Hyperplane<_Scalar, _AmbientDim, OtherOptions>& hyperplane) const +inline _Scalar ParametrizedLine<_Scalar, _AmbientDim,_Options>::intersectionParameter(const Hyperplane<_Scalar, _AmbientDim, OtherOptions>& hyperplane) const { return -(hyperplane.offset()+hyperplane.normal().dot(origin())) / hyperplane.normal().dot(direction()); } + +/** \deprecated use intersectionParameter() + * \returns the parameter value of the intersection between \c *this and the given \a hyperplane + */ +template +template +inline _Scalar ParametrizedLine<_Scalar, _AmbientDim,_Options>::intersection(const Hyperplane<_Scalar, _AmbientDim, OtherOptions>& hyperplane) const +{ + return intersectionParameter(hyperplane); +} + +/** \returns the point of the intersection between \c *this and the given hyperplane + */ +template +template +inline typename ParametrizedLine<_Scalar, _AmbientDim,_Options>::VectorType +ParametrizedLine<_Scalar, _AmbientDim,_Options>::intersectionPoint(const Hyperplane<_Scalar, _AmbientDim, OtherOptions>& hyperplane) const +{ + return pointAt(intersectionParameter(hyperplane)); +} + +} // end namespace Eigen + #endif // EIGEN_PARAMETRIZEDLINE_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Geometry/Quaternion.h b/gtsam/3rdparty/Eigen/Eigen/src/Geometry/Quaternion.h index 9180db67d..75083363c 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Geometry/Quaternion.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Geometry/Quaternion.h @@ -25,6 +25,8 @@ #ifndef EIGEN_QUATERNION_H #define EIGEN_QUATERNION_H +namespace Eigen { + /*************************************************************************** * Definition of QuaternionBase @@ -38,6 +40,12 @@ template class QuaternionBase : public RotationBase { @@ -109,7 +117,7 @@ public: /** \returns a quaternion representing an identity rotation * \sa MatrixBase::Identity() */ - inline static Quaternion Identity() { return Quaternion(1, 0, 0, 0); } + static inline Quaternion Identity() { return Quaternion(1, 0, 0, 0); } /** \sa QuaternionBase::Identity(), MatrixBase::setIdentity() */ @@ -278,6 +286,9 @@ public: explicit inline Quaternion(const Quaternion& other) { m_coeffs = other.coeffs().template cast(); } + template + static Quaternion FromTwoVectors(const MatrixBase& a, const MatrixBase& b); + inline Coefficients& coeffs() { return m_coeffs;} inline const Coefficients& coeffs() const { return m_coeffs;} @@ -287,7 +298,7 @@ protected: Coefficients m_coeffs; #ifndef EIGEN_PARSED_BY_DOXYGEN - EIGEN_STRONG_INLINE static void _check_template_params() + static EIGEN_STRONG_INLINE void _check_template_params() { EIGEN_STATIC_ASSERT( (_Options & DontAlign) == _Options, INVALID_MATRIX_TEMPLATE_PARAMETERS) @@ -434,7 +445,7 @@ typedef Map, Aligned> QuaternionMapAlignedd; namespace internal { template struct quat_product { - EIGEN_STRONG_INLINE static Quaternion run(const QuaternionBase& a, const QuaternionBase& b){ + static EIGEN_STRONG_INLINE Quaternion run(const QuaternionBase& a, const QuaternionBase& b){ return Quaternion ( a.w() * b.w() - a.x() * b.x() - a.y() * b.y() - a.z() * b.z(), @@ -544,9 +555,9 @@ QuaternionBase::toRotationMatrix(void) const // it has to be inlined, and so the return by value is not an issue Matrix3 res; - const Scalar tx = 2*this->x(); - const Scalar ty = 2*this->y(); - const Scalar tz = 2*this->z(); + const Scalar tx = Scalar(2)*this->x(); + const Scalar ty = Scalar(2)*this->y(); + const Scalar tz = Scalar(2)*this->z(); const Scalar twx = tx*this->w(); const Scalar twy = ty*this->w(); const Scalar twz = tz*this->w(); @@ -557,15 +568,15 @@ QuaternionBase::toRotationMatrix(void) const const Scalar tyz = tz*this->y(); const Scalar tzz = tz*this->z(); - res.coeffRef(0,0) = 1-(tyy+tzz); + res.coeffRef(0,0) = Scalar(1)-(tyy+tzz); res.coeffRef(0,1) = txy-twz; res.coeffRef(0,2) = txz+twy; res.coeffRef(1,0) = txy+twz; - res.coeffRef(1,1) = 1-(txx+tzz); + res.coeffRef(1,1) = Scalar(1)-(txx+tzz); res.coeffRef(1,2) = tyz-twx; res.coeffRef(2,0) = txz-twy; res.coeffRef(2,1) = tyz+twx; - res.coeffRef(2,2) = 1-(txx+tyy); + res.coeffRef(2,2) = Scalar(1)-(txx+tyy); return res; } @@ -618,6 +629,27 @@ inline Derived& QuaternionBase::setFromTwoVectors(const MatrixBase +template +Quaternion Quaternion::FromTwoVectors(const MatrixBase& a, const MatrixBase& b) +{ + Quaternion quat; + quat.setFromTwoVectors(a, b); + return quat; +} + + /** \returns the multiplicative inverse of \c *this * Note that in most cases, i.e., if you simply want the opposite rotation, * and/or the quaternion is normalized, then it is enough to use the conjugate. @@ -709,7 +741,7 @@ struct quaternionbase_assign_impl { typedef typename Other::Scalar Scalar; typedef DenseIndex Index; - template inline static void run(QuaternionBase& q, const Other& mat) + template static inline void run(QuaternionBase& q, const Other& mat) { // This algorithm comes from "Quaternion Calculus and Fast Animation", // Ken Shoemake, 1987 SIGGRAPH course notes @@ -748,7 +780,7 @@ template struct quaternionbase_assign_impl { typedef typename Other::Scalar Scalar; - template inline static void run(QuaternionBase& q, const Other& vec) + template static inline void run(QuaternionBase& q, const Other& vec) { q.coeffs() = vec; } @@ -756,4 +788,6 @@ struct quaternionbase_assign_impl } // end namespace internal +} // end namespace Eigen + #endif // EIGEN_QUATERNION_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Geometry/Rotation2D.h b/gtsam/3rdparty/Eigen/Eigen/src/Geometry/Rotation2D.h index cf36da1c5..4339e0f0f 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Geometry/Rotation2D.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Geometry/Rotation2D.h @@ -25,6 +25,8 @@ #ifndef EIGEN_ROTATION2D_H #define EIGEN_ROTATION2D_H +namespace Eigen { + /** \geometry_module \ingroup Geometry_Module * * \class Rotation2D @@ -121,7 +123,7 @@ public: m_angle = Scalar(other.angle()); } - inline static Rotation2D Identity() { return Rotation2D(0); } + static inline Rotation2D Identity() { return Rotation2D(0); } /** \returns \c true if \c *this is approximately equal to \a other, within the precision * determined by \a prec. @@ -162,4 +164,6 @@ Rotation2D::toRotationMatrix(void) const return (Matrix2() << cosA, -sinA, sinA, cosA).finished(); } +} // end namespace Eigen + #endif // EIGEN_ROTATION2D_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Geometry/RotationBase.h b/gtsam/3rdparty/Eigen/Eigen/src/Geometry/RotationBase.h index 1abf06bb6..0b8fb0a52 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Geometry/RotationBase.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Geometry/RotationBase.h @@ -25,6 +25,8 @@ #ifndef EIGEN_ROTATIONBASE_H #define EIGEN_ROTATIONBASE_H +namespace Eigen { + // forward declaration namespace internal { template @@ -115,7 +117,7 @@ struct rotation_base_generic_product_selector { enum { Dim = RotationDerived::Dim }; typedef Matrix ReturnType; - inline static ReturnType run(const RotationDerived& r, const MatrixType& m) + static inline ReturnType run(const RotationDerived& r, const MatrixType& m) { return r.toRotationMatrix() * m; } }; @@ -123,7 +125,7 @@ template struct rotation_base_generic_product_selector< RotationDerived, DiagonalMatrix, false > { typedef Transform ReturnType; - inline static ReturnType run(const RotationDerived& r, const DiagonalMatrix& m) + static inline ReturnType run(const RotationDerived& r, const DiagonalMatrix& m) { ReturnType res(r); res.linear() *= m; @@ -136,7 +138,7 @@ struct rotation_base_generic_product_selector ReturnType; - EIGEN_STRONG_INLINE static ReturnType run(const RotationDerived& r, const OtherVectorType& v) + static EIGEN_STRONG_INLINE ReturnType run(const RotationDerived& r, const OtherVectorType& v) { return r._transformVector(v); } @@ -192,20 +194,20 @@ namespace internal { * \sa class Transform, class Rotation2D, class Quaternion, class AngleAxis */ template -inline static Matrix toRotationMatrix(const Scalar& s) +static inline Matrix toRotationMatrix(const Scalar& s) { EIGEN_STATIC_ASSERT(Dim==2,YOU_MADE_A_PROGRAMMING_MISTAKE) return Rotation2D(s).toRotationMatrix(); } template -inline static Matrix toRotationMatrix(const RotationBase& r) +static inline Matrix toRotationMatrix(const RotationBase& r) { return r.toRotationMatrix(); } template -inline static const MatrixBase& toRotationMatrix(const MatrixBase& mat) +static inline const MatrixBase& toRotationMatrix(const MatrixBase& mat) { EIGEN_STATIC_ASSERT(OtherDerived::RowsAtCompileTime==Dim && OtherDerived::ColsAtCompileTime==Dim, YOU_MADE_A_PROGRAMMING_MISTAKE) @@ -214,4 +216,6 @@ inline static const MatrixBase& toRotationMatrix(const MatrixBase< } // end namespace internal +} // end namespace Eigen + #endif // EIGEN_ROTATIONBASE_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Geometry/Scaling.h b/gtsam/3rdparty/Eigen/Eigen/src/Geometry/Scaling.h index c911d13e1..080f33794 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Geometry/Scaling.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Geometry/Scaling.h @@ -25,6 +25,8 @@ #ifndef EIGEN_SCALING_H #define EIGEN_SCALING_H +namespace Eigen { + /** \geometry_module \ingroup Geometry_Module * * \class Scaling @@ -179,4 +181,6 @@ UniformScaling::operator* (const Transform& t return res; } +} // end namespace Eigen + #endif // EIGEN_SCALING_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Geometry/Transform.h b/gtsam/3rdparty/Eigen/Eigen/src/Geometry/Transform.h index 19d012572..e81305ccc 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Geometry/Transform.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Geometry/Transform.h @@ -27,6 +27,8 @@ #ifndef EIGEN_TRANSFORM_H #define EIGEN_TRANSFORM_H +namespace Eigen { + namespace internal { template @@ -37,7 +39,7 @@ struct transform_traits Dim = Transform::Dim, HDim = Transform::HDim, Mode = Transform::Mode, - IsProjective = (Mode==Projective) + IsProjective = (int(Mode)==int(Projective)) }; }; @@ -61,7 +63,7 @@ template< typename Lhs, typename Rhs, bool AnyProjective = transform_traits::IsProjective || - transform_traits::IsProjective> + transform_traits::IsProjective> struct transform_transform_product_impl; template< typename Other, @@ -207,9 +209,9 @@ public: /** type of the matrix used to represent the linear part of the transformation */ typedef Matrix LinearMatrixType; /** type of read/write reference to the linear part of the transformation */ - typedef Block LinearPart; + typedef Block LinearPart; /** type of read reference to the linear part of the transformation */ - typedef const Block ConstLinearPart; + typedef const Block ConstLinearPart; /** type of read/write reference to the affine part of the transformation */ typedef typename internal::conditional VectorType; /** type of a read/write reference to the translation part of the rotation */ - typedef Block TranslationPart; + typedef Block TranslationPart; /** type of a read reference to the translation part of the rotation */ - typedef const Block ConstTranslationPart; + typedef const Block ConstTranslationPart; /** corresponding translation type */ typedef Translation TranslationType; @@ -279,6 +281,9 @@ public: template inline explicit Transform(const EigenBase& other) { + EIGEN_STATIC_ASSERT((internal::is_same::value), + YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY); + check_template_params(); internal::transform_construct_from_matrix::run(this, other.derived()); } @@ -287,6 +292,9 @@ public: template inline Transform& operator=(const EigenBase& other) { + EIGEN_STATIC_ASSERT((internal::is_same::value), + YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY); + internal::transform_construct_from_matrix::run(this, other.derived()); return *this; } @@ -376,9 +384,9 @@ public: inline MatrixType& matrix() { return m_matrix; } /** \returns a read-only expression of the linear part of the transformation */ - inline ConstLinearPart linear() const { return m_matrix.template block(0,0); } + inline ConstLinearPart linear() const { return ConstLinearPart(m_matrix,0,0); } /** \returns a writable expression of the linear part of the transformation */ - inline LinearPart linear() { return m_matrix.template block(0,0); } + inline LinearPart linear() { return LinearPart(m_matrix,0,0); } /** \returns a read-only expression of the Dim x HDim affine part of the transformation */ inline ConstAffinePart affine() const { return take_affine_part::run(m_matrix); } @@ -386,9 +394,9 @@ public: inline AffinePart affine() { return take_affine_part::run(m_matrix); } /** \returns a read-only expression of the translation vector of the transformation */ - inline ConstTranslationPart translation() const { return m_matrix.template block(0,Dim); } + inline ConstTranslationPart translation() const { return ConstTranslationPart(m_matrix,0,Dim); } /** \returns a writable expression of the translation vector of the transformation */ - inline TranslationPart translation() { return m_matrix.template block(0,Dim); } + inline TranslationPart translation() { return TranslationPart(m_matrix,0,Dim); } /** \returns an expression of the product between the transform \c *this and a matrix expression \a other * @@ -460,15 +468,40 @@ public: { return internal::transform_transform_product_impl::run(*this,other); } - + + #ifdef __INTEL_COMPILER +private: + // this intermediate structure permits to workaround a bug in ICC 11: + // error: template instantiation resulted in unexpected function type of "Eigen::Transform + // (const Eigen::Transform &) const" + // (the meaning of a name may have changed since the template declaration -- the type of the template is: + // "Eigen::internal::transform_transform_product_impl, + // Eigen::Transform, >::ResultType (const Eigen::Transform &) const") + // + template struct icc_11_workaround + { + typedef internal::transform_transform_product_impl > ProductType; + typedef typename ProductType::ResultType ResultType; + }; + +public: /** Concatenates two different transformations */ template - inline const typename internal::transform_transform_product_impl< - Transform,Transform >::ResultType + inline typename icc_11_workaround::ResultType + operator * (const Transform& other) const + { + typedef typename icc_11_workaround::ProductType ProductType; + return ProductType::run(*this,other); + } + #else + /** Concatenates two different transformations */ + template + inline typename internal::transform_transform_product_impl >::ResultType operator * (const Transform& other) const { return internal::transform_transform_product_impl >::run(*this,other); } + #endif /** \sa MatrixBase::setIdentity() */ void setIdentity() { m_matrix.setIdentity(); } @@ -608,7 +641,7 @@ public: protected: #ifndef EIGEN_PARSED_BY_DOXYGEN - EIGEN_STRONG_INLINE static void check_template_params() + static EIGEN_STRONG_INLINE void check_template_params() { EIGEN_STATIC_ASSERT((Options & (DontAlign|RowMajor)) == Options, INVALID_MATRIX_TEMPLATE_PARAMETERS) } @@ -1219,7 +1252,7 @@ struct transform_right_product_impl< TransformType, MatrixType, 0 > { typedef typename MatrixType::PlainObject ResultType; - EIGEN_STRONG_INLINE static ResultType run(const TransformType& T, const MatrixType& other) + static EIGEN_STRONG_INLINE ResultType run(const TransformType& T, const MatrixType& other) { return T.matrix() * other; } @@ -1237,11 +1270,11 @@ struct transform_right_product_impl< TransformType, MatrixType, 1 > typedef typename MatrixType::PlainObject ResultType; - EIGEN_STRONG_INLINE static ResultType run(const TransformType& T, const MatrixType& other) + static EIGEN_STRONG_INLINE ResultType run(const TransformType& T, const MatrixType& other) { EIGEN_STATIC_ASSERT(OtherRows==HDim, YOU_MIXED_MATRICES_OF_DIFFERENT_SIZES); - typedef Block TopLeftLhs; + typedef Block TopLeftLhs; ResultType res(other.rows(),other.cols()); TopLeftLhs(res, 0, 0, Dim, other.cols()).noalias() = T.affine() * other; @@ -1263,15 +1296,13 @@ struct transform_right_product_impl< TransformType, MatrixType, 2 > typedef typename MatrixType::PlainObject ResultType; - EIGEN_STRONG_INLINE static ResultType run(const TransformType& T, const MatrixType& other) + static EIGEN_STRONG_INLINE ResultType run(const TransformType& T, const MatrixType& other) { EIGEN_STATIC_ASSERT(OtherRows==Dim, YOU_MIXED_MATRICES_OF_DIFFERENT_SIZES); - typedef Block TopLeftLhs; - - ResultType res(other.rows(),other.cols()); - TopLeftLhs(res, 0, 0, Dim, other.cols()).noalias() = T.linear() * other; - TopLeftLhs(res, 0, 0, Dim, other.cols()).colwise() += T.translation(); + typedef Block TopLeftLhs; + ResultType res(Replicate(T.translation(),1,other.cols())); + TopLeftLhs(res, 0, 0, Dim, other.cols()).noalias() += T.linear() * other; return res; } @@ -1391,6 +1422,37 @@ struct transform_transform_product_impl } }; +template +struct transform_transform_product_impl,Transform,true > +{ + typedef Transform Lhs; + typedef Transform Rhs; + typedef Transform ResultType; + static ResultType run(const Lhs& lhs, const Rhs& rhs) + { + ResultType res; + res.matrix().template topRows() = lhs.matrix() * rhs.matrix(); + res.matrix().row(Dim) = rhs.matrix().row(Dim); + return res; + } +}; + +template +struct transform_transform_product_impl,Transform,true > +{ + typedef Transform Lhs; + typedef Transform Rhs; + typedef Transform ResultType; + static ResultType run(const Lhs& lhs, const Rhs& rhs) + { + ResultType res(lhs.matrix().template leftCols() * rhs.matrix()); + res.matrix().col(Dim) += lhs.matrix().col(Dim); + return res; + } +}; + } // end namespace internal +} // end namespace Eigen + #endif // EIGEN_TRANSFORM_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Geometry/Translation.h b/gtsam/3rdparty/Eigen/Eigen/src/Geometry/Translation.h index d8fe50f98..8d77a3d23 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Geometry/Translation.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Geometry/Translation.h @@ -25,6 +25,8 @@ #ifndef EIGEN_TRANSLATION_H #define EIGEN_TRANSLATION_H +namespace Eigen { + /** \geometry_module \ingroup Geometry_Module * * \class Translation @@ -54,6 +56,8 @@ public: typedef Matrix LinearMatrixType; /** corresponding affine transformation type */ typedef Transform AffineTransformType; + /** corresponding isometric transformation type */ + typedef Transform IsometryTransformType; protected: @@ -114,8 +118,8 @@ public: /** Concatenates a translation and a rotation */ template - inline AffineTransformType operator*(const RotationBase& r) const - { return *this * r.toRotationMatrix(); } + inline IsometryTransformType operator*(const RotationBase& r) const + { return *this * IsometryTransformType(r); } /** \returns the concatenation of a linear transformation \a l with the translation \a t */ // its a nightmare to define a templated friend function outside its declaration @@ -212,4 +216,6 @@ Translation::operator* (const EigenBase& linear) const return res; } +} // end namespace Eigen + #endif // EIGEN_TRANSLATION_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Geometry/Umeyama.h b/gtsam/3rdparty/Eigen/Eigen/src/Geometry/Umeyama.h index b50f46173..4d4cc3632 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Geometry/Umeyama.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Geometry/Umeyama.h @@ -31,6 +31,8 @@ // * Eigen/SVD // * Eigen/Array +namespace Eigen { + #ifndef EIGEN_PARSED_BY_DOXYGEN // These helpers are required since it allows to use mixed types as parameters @@ -180,4 +182,6 @@ umeyama(const MatrixBase& src, const MatrixBase& dst, boo return Rt; } +} // end namespace Eigen + #endif // EIGEN_UMEYAMA_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Geometry/arch/Geometry_SSE.h b/gtsam/3rdparty/Eigen/Eigen/src/Geometry/arch/Geometry_SSE.h index cbe695c72..08d0f600a 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Geometry/arch/Geometry_SSE.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Geometry/arch/Geometry_SSE.h @@ -26,12 +26,14 @@ #ifndef EIGEN_GEOMETRY_SSE_H #define EIGEN_GEOMETRY_SSE_H +namespace Eigen { + namespace internal { template struct quat_product { - inline static Quaternion run(const QuaternionBase& _a, const QuaternionBase& _b) + static inline Quaternion run(const QuaternionBase& _a, const QuaternionBase& _b) { const __m128 mask = _mm_castsi128_ps(_mm_setr_epi32(0,0,0,0x80000000)); Quaternion res; @@ -53,7 +55,7 @@ struct quat_product template struct cross3_impl { - inline static typename plain_matrix_type::type + static inline typename plain_matrix_type::type run(const VectorLhs& lhs, const VectorRhs& rhs) { __m128 a = lhs.template packet(0); @@ -72,7 +74,7 @@ struct cross3_impl template struct quat_product { - inline static Quaternion run(const QuaternionBase& _a, const QuaternionBase& _b) + static inline Quaternion run(const QuaternionBase& _a, const QuaternionBase& _b) { const Packet2d mask = _mm_castsi128_pd(_mm_set_epi32(0x0,0x0,0x80000000,0x0)); @@ -96,7 +98,7 @@ struct quat_product */ t1 = padd(pmul(a_ww, b_xy), pmul(a_yy, b_zw)); t2 = psub(pmul(a_zz, b_xy), pmul(a_xx, b_zw)); -#ifdef __SSE3__ +#ifdef EIGEN_VECTORIZE_SSE3 EIGEN_UNUSED_VARIABLE(mask) pstore(&res.x(), _mm_addsub_pd(t1, preverse(t2))); #else @@ -110,7 +112,7 @@ struct quat_product */ t1 = psub(pmul(a_ww, b_zw), pmul(a_yy, b_xy)); t2 = padd(pmul(a_zz, b_zw), pmul(a_xx, b_xy)); -#ifdef __SSE3__ +#ifdef EIGEN_VECTORIZE_SSE3 EIGEN_UNUSED_VARIABLE(mask) pstore(&res.z(), preverse(_mm_addsub_pd(preverse(t1), t2))); #else @@ -123,4 +125,6 @@ struct quat_product } // end namespace internal +} // end namespace Eigen + #endif // EIGEN_GEOMETRY_SSE_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Householder/BlockHouseholder.h b/gtsam/3rdparty/Eigen/Eigen/src/Householder/BlockHouseholder.h index 23ce1bfbd..b69fd46d5 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Householder/BlockHouseholder.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Householder/BlockHouseholder.h @@ -28,6 +28,8 @@ // This file contains some helper function to deal with block householder reflectors +namespace Eigen { + namespace internal { /** \internal */ @@ -64,7 +66,7 @@ void apply_block_householder_on_the_left(MatrixType& mat, const VectorsType& vec Matrix T(nbVecs,nbVecs); make_block_householder_triangular_factor(T, vectors, hCoeffs); - const TriangularView& V(vectors); + const TriangularView& V(vectors); // A -= V T V^* A Matrix struct decrement_size { @@ -35,6 +37,22 @@ template struct decrement_size }; } +/** Computes the elementary reflector H such that: + * \f$ H *this = [ beta 0 ... 0]^T \f$ + * where the transformation H is: + * \f$ H = I - tau v v^*\f$ + * and the vector v is: + * \f$ v^T = [1 essential^T] \f$ + * + * The essential part of the vector \c v is stored in *this. + * + * On output: + * \param tau the scaling factor of the Householder transformation + * \param beta the result of H * \c *this + * + * \sa MatrixBase::makeHouseholder(), MatrixBase::applyHouseholderOnTheLeft(), + * MatrixBase::applyHouseholderOnTheRight() + */ template void MatrixBase::makeHouseholderInPlace(Scalar& tau, RealScalar& beta) { @@ -51,7 +69,7 @@ void MatrixBase::makeHouseholderInPlace(Scalar& tau, RealScalar& beta) * * On output: * \param essential the essential part of the vector \c v - * \param tau the scaling factor of the householder transformation + * \param tau the scaling factor of the Householder transformation * \param beta the result of H * \c *this * * \sa MatrixBase::makeHouseholderInPlace(), MatrixBase::applyHouseholderOnTheLeft(), @@ -86,6 +104,21 @@ void MatrixBase::makeHouseholder( } } +/** Apply the elementary reflector H given by + * \f$ H = I - tau v v^*\f$ + * with + * \f$ v^T = [1 essential^T] \f$ + * from the left to a vector or matrix. + * + * On input: + * \param essential the essential part of the vector \c v + * \param tau the scaling factor of the Householder transformation + * \param workspace a pointer to working space with at least + * this->cols() * essential.size() entries + * + * \sa MatrixBase::makeHouseholder(), MatrixBase::makeHouseholderInPlace(), + * MatrixBase::applyHouseholderOnTheRight() + */ template template void MatrixBase::applyHouseholderOnTheLeft( @@ -108,6 +141,21 @@ void MatrixBase::applyHouseholderOnTheLeft( } } +/** Apply the elementary reflector H given by + * \f$ H = I - tau v v^*\f$ + * with + * \f$ v^T = [1 essential^T] \f$ + * from the right to a vector or matrix. + * + * On input: + * \param essential the essential part of the vector \c v + * \param tau the scaling factor of the Householder transformation + * \param workspace a pointer to working space with at least + * this->cols() * essential.size() entries + * + * \sa MatrixBase::makeHouseholder(), MatrixBase::makeHouseholderInPlace(), + * MatrixBase::applyHouseholderOnTheLeft() + */ template template void MatrixBase::applyHouseholderOnTheRight( @@ -130,4 +178,6 @@ void MatrixBase::applyHouseholderOnTheRight( } } +} // end namespace Eigen + #endif // EIGEN_HOUSEHOLDER_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Householder/HouseholderSequence.h b/gtsam/3rdparty/Eigen/Eigen/src/Householder/HouseholderSequence.h index 717f29c99..1cb461b48 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Householder/HouseholderSequence.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Householder/HouseholderSequence.h @@ -26,6 +26,8 @@ #ifndef EIGEN_HOUSEHOLDER_SEQUENCE_H #define EIGEN_HOUSEHOLDER_SEQUENCE_H +namespace Eigen { + /** \ingroup Householder_Module * \householder_module * \class HouseholderSequence @@ -237,13 +239,20 @@ template class HouseholderS ConjugateReturnType inverse() const { return adjoint(); } /** \internal */ - template void evalTo(DestType& dst) const + template inline void evalTo(DestType& dst) const { - Index vecs = m_length; - // FIXME find a way to pass this temporary if the user wants to Matrix temp(rows()); - if( internal::is_same::type,DestType>::value + AutoAlign|ColMajor, DestType::MaxRowsAtCompileTime, 1> workspace(rows()); + evalTo(dst, workspace); + } + + /** \internal */ + template + void evalTo(Dest& dst, Workspace& workspace) const + { + workspace.resize(rows()); + Index vecs = m_length; + if( internal::is_same::type,Dest>::value && internal::extract_data(dst) == internal::extract_data(m_vectors)) { // in-place @@ -254,10 +263,10 @@ template class HouseholderS Index cornerSize = rows() - k - m_shift; if(m_trans) dst.bottomRightCorner(cornerSize, cornerSize) - .applyHouseholderOnTheRight(essentialVector(k), m_coeffs.coeff(k), &temp.coeffRef(0)); + .applyHouseholderOnTheRight(essentialVector(k), m_coeffs.coeff(k), workspace.data()); else dst.bottomRightCorner(cornerSize, cornerSize) - .applyHouseholderOnTheLeft(essentialVector(k), m_coeffs.coeff(k), &temp.coeffRef(0)); + .applyHouseholderOnTheLeft(essentialVector(k), m_coeffs.coeff(k), workspace.data()); // clear the off diagonal vector dst.col(k).tail(rows()-k-1).setZero(); @@ -274,10 +283,10 @@ template class HouseholderS Index cornerSize = rows() - k - m_shift; if(m_trans) dst.bottomRightCorner(cornerSize, cornerSize) - .applyHouseholderOnTheRight(essentialVector(k), m_coeffs.coeff(k), &temp.coeffRef(0)); + .applyHouseholderOnTheRight(essentialVector(k), m_coeffs.coeff(k), &workspace.coeffRef(0)); else dst.bottomRightCorner(cornerSize, cornerSize) - .applyHouseholderOnTheLeft(essentialVector(k), m_coeffs.coeff(k), &temp.coeffRef(0)); + .applyHouseholderOnTheLeft(essentialVector(k), m_coeffs.coeff(k), &workspace.coeffRef(0)); } } } @@ -285,24 +294,40 @@ template class HouseholderS /** \internal */ template inline void applyThisOnTheRight(Dest& dst) const { - Matrix temp(dst.rows()); + Matrix workspace(dst.rows()); + applyThisOnTheRight(dst, workspace); + } + + /** \internal */ + template + inline void applyThisOnTheRight(Dest& dst, Workspace& workspace) const + { + workspace.resize(dst.rows()); for(Index k = 0; k < m_length; ++k) { Index actual_k = m_trans ? m_length-k-1 : k; dst.rightCols(rows()-m_shift-actual_k) - .applyHouseholderOnTheRight(essentialVector(actual_k), m_coeffs.coeff(actual_k), &temp.coeffRef(0)); + .applyHouseholderOnTheRight(essentialVector(actual_k), m_coeffs.coeff(actual_k), workspace.data()); } } /** \internal */ template inline void applyThisOnTheLeft(Dest& dst) const { - Matrix temp(dst.cols()); + Matrix workspace(dst.cols()); + applyThisOnTheLeft(dst, workspace); + } + + /** \internal */ + template + inline void applyThisOnTheLeft(Dest& dst, Workspace& workspace) const + { + workspace.resize(dst.cols()); for(Index k = 0; k < m_length; ++k) { Index actual_k = m_trans ? k : m_length-k-1; dst.bottomRows(rows()-m_shift-actual_k) - .applyHouseholderOnTheLeft(essentialVector(actual_k), m_coeffs.coeff(actual_k), &temp.coeffRef(0)); + .applyHouseholderOnTheLeft(essentialVector(actual_k), m_coeffs.coeff(actual_k), workspace.data()); } } @@ -426,4 +451,6 @@ HouseholderSequence rightHouseholderSequence( return HouseholderSequence(v, h); } +} // end namespace Eigen + #endif // EIGEN_HOUSEHOLDER_SEQUENCE_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/IterativeLinearSolvers/BasicPreconditioners.h b/gtsam/3rdparty/Eigen/Eigen/src/IterativeLinearSolvers/BasicPreconditioners.h new file mode 100644 index 000000000..c9fe9c618 --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/src/IterativeLinearSolvers/BasicPreconditioners.h @@ -0,0 +1,163 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2011 Gael Guennebaud +// +// Eigen is free software; you can redistribute it and/or +// modify it under the terms of the GNU Lesser General Public +// License as published by the Free Software Foundation; either +// version 3 of the License, or (at your option) any later version. +// +// Alternatively, you can redistribute it and/or +// modify it under the terms of the GNU General Public License as +// published by the Free Software Foundation; either version 2 of +// the License, or (at your option) any later version. +// +// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY +// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the +// GNU General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public +// License and a copy of the GNU General Public License along with +// Eigen. If not, see . + +#ifndef EIGEN_BASIC_PRECONDITIONERS_H +#define EIGEN_BASIC_PRECONDITIONERS_H + +namespace Eigen { + +/** \ingroup IterativeLinearSolvers_Module + * \brief A preconditioner based on the digonal entries + * + * This class allows to approximately solve for A.x = b problems assuming A is a diagonal matrix. + * In other words, this preconditioner neglects all off diagonal entries and, in Eigen's language, solves for: + * \code + * A.diagonal().asDiagonal() . x = b + * \endcode + * + * \tparam _Scalar the type of the scalar. + * + * This preconditioner is suitable for both selfadjoint and general problems. + * The diagonal entries are pre-inverted and stored into a dense vector. + * + * \note A variant that has yet to be implemented would attempt to preserve the norm of each column. + * + */ +template +class DiagonalPreconditioner +{ + typedef _Scalar Scalar; + typedef Matrix Vector; + typedef typename Vector::Index Index; + + public: + typedef Matrix MatrixType; + + DiagonalPreconditioner() : m_isInitialized(false) {} + + template + DiagonalPreconditioner(const MatrixType& mat) : m_invdiag(mat.cols()) + { + compute(mat); + } + + Index rows() const { return m_invdiag.size(); } + Index cols() const { return m_invdiag.size(); } + + template + DiagonalPreconditioner& analyzePattern(const MatrixType& ) + { + return *this; + } + + template + DiagonalPreconditioner& factorize(const MatrixType& mat) + { + m_invdiag.resize(mat.cols()); + for(int j=0; j + DiagonalPreconditioner& compute(const MatrixType& mat) + { + return factorize(mat); + } + + template + void _solve(const Rhs& b, Dest& x) const + { + x = m_invdiag.array() * b.array() ; + } + + template inline const internal::solve_retval + solve(const MatrixBase& b) const + { + eigen_assert(m_isInitialized && "DiagonalPreconditioner is not initialized."); + eigen_assert(m_invdiag.size()==b.rows() + && "DiagonalPreconditioner::solve(): invalid number of rows of the right hand side matrix b"); + return internal::solve_retval(*this, b.derived()); + } + + protected: + Vector m_invdiag; + bool m_isInitialized; +}; + +namespace internal { + +template +struct solve_retval, Rhs> + : solve_retval_base, Rhs> +{ + typedef DiagonalPreconditioner<_MatrixType> Dec; + EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs) + + template void evalTo(Dest& dst) const + { + dec()._solve(rhs(),dst); + } +}; + +} + +/** \ingroup IterativeLinearSolvers_Module + * \brief A naive preconditioner which approximates any matrix as the identity matrix + * + * \sa class DiagonalPreconditioner + */ +class IdentityPreconditioner +{ + public: + + IdentityPreconditioner() {} + + template + IdentityPreconditioner(const MatrixType& ) {} + + template + IdentityPreconditioner& analyzePattern(const MatrixType& ) { return *this; } + + template + IdentityPreconditioner& factorize(const MatrixType& ) { return *this; } + + template + IdentityPreconditioner& compute(const MatrixType& ) { return *this; } + + template + inline const Rhs& solve(const Rhs& b) const { return b; } +}; + +} // end namespace Eigen + +#endif // EIGEN_BASIC_PRECONDITIONERS_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/IterativeLinearSolvers/BiCGSTAB.h b/gtsam/3rdparty/Eigen/Eigen/src/IterativeLinearSolvers/BiCGSTAB.h new file mode 100644 index 000000000..5f23968bc --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/src/IterativeLinearSolvers/BiCGSTAB.h @@ -0,0 +1,269 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2011 Gael Guennebaud +// Copyright (C) 2012 Désiré Nuentsa-Wakam +// +// Eigen is free software; you can redistribute it and/or +// modify it under the terms of the GNU Lesser General Public +// License as published by the Free Software Foundation; either +// version 3 of the License, or (at your option) any later version. +// +// Alternatively, you can redistribute it and/or +// modify it under the terms of the GNU General Public License as +// published by the Free Software Foundation; either version 2 of +// the License, or (at your option) any later version. +// +// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY +// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the +// GNU General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public +// License and a copy of the GNU General Public License along with +// Eigen. If not, see . + +#ifndef EIGEN_BICGSTAB_H +#define EIGEN_BICGSTAB_H + +namespace Eigen { + +namespace internal { + +/** \internal Low-level bi conjugate gradient stabilized algorithm + * \param mat The matrix A + * \param rhs The right hand side vector b + * \param x On input and initial solution, on output the computed solution. + * \param precond A preconditioner being able to efficiently solve for an + * approximation of Ax=b (regardless of b) + * \param iters On input the max number of iteration, on output the number of performed iterations. + * \param tol_error On input the tolerance error, on output an estimation of the relative error. + * \return false in the case of numerical issue, for example a break down of BiCGSTAB. + */ +template +bool bicgstab(const MatrixType& mat, const Rhs& rhs, Dest& x, + const Preconditioner& precond, int& iters, + typename Dest::RealScalar& tol_error) +{ + using std::sqrt; + using std::abs; + typedef typename Dest::RealScalar RealScalar; + typedef typename Dest::Scalar Scalar; + typedef Matrix VectorType; + RealScalar tol = tol_error; + int maxIters = iters; + + int n = mat.cols(); + VectorType r = rhs - mat * x; + VectorType r0 = r; + + RealScalar r0_sqnorm = r0.squaredNorm(); + Scalar rho = 1; + Scalar alpha = 1; + Scalar w = 1; + + VectorType v = VectorType::Zero(n), p = VectorType::Zero(n); + VectorType y(n), z(n); + VectorType kt(n), ks(n); + + VectorType s(n), t(n); + + RealScalar tol2 = tol*tol; + int i = 0; + + while ( r.squaredNorm()/r0_sqnorm > tol2 && i > +class BiCGSTAB; + +namespace internal { + +template< typename _MatrixType, typename _Preconditioner> +struct traits > +{ + typedef _MatrixType MatrixType; + typedef _Preconditioner Preconditioner; +}; + +} + +/** \ingroup IterativeLinearSolvers_Module + * \brief A bi conjugate gradient stabilized solver for sparse square problems + * + * This class allows to solve for A.x = b sparse linear problems using a bi conjugate gradient + * stabilized algorithm. The vectors x and b can be either dense or sparse. + * + * \tparam _MatrixType the type of the sparse matrix A, can be a dense or a sparse matrix. + * \tparam _Preconditioner the type of the preconditioner. Default is DiagonalPreconditioner + * + * The maximal number of iterations and tolerance value can be controlled via the setMaxIterations() + * and setTolerance() methods. The defaults are the size of the problem for the maximal number of iterations + * and NumTraits::epsilon() for the tolerance. + * + * This class can be used as the direct solver classes. Here is a typical usage example: + * \code + * int n = 10000; + * VectorXd x(n), b(n); + * SparseMatrix A(n,n); + * // fill A and b + * BiCGSTAB > solver; + * solver(A); + * x = solver.solve(b); + * std::cout << "#iterations: " << solver.iterations() << std::endl; + * std::cout << "estimated error: " << solver.error() << std::endl; + * // update b, and solve again + * x = solver.solve(b); + * \endcode + * + * By default the iterations start with x=0 as an initial guess of the solution. + * One can control the start using the solveWithGuess() method. Here is a step by + * step execution example starting with a random guess and printing the evolution + * of the estimated error: + * * \code + * x = VectorXd::Random(n); + * solver.setMaxIterations(1); + * int i = 0; + * do { + * x = solver.solveWithGuess(b,x); + * std::cout << i << " : " << solver.error() << std::endl; + * ++i; + * } while (solver.info()!=Success && i<100); + * \endcode + * Note that such a step by step excution is slightly slower. + * + * \sa class SimplicialCholesky, DiagonalPreconditioner, IdentityPreconditioner + */ +template< typename _MatrixType, typename _Preconditioner> +class BiCGSTAB : public IterativeSolverBase > +{ + typedef IterativeSolverBase Base; + using Base::mp_matrix; + using Base::m_error; + using Base::m_iterations; + using Base::m_info; + using Base::m_isInitialized; +public: + typedef _MatrixType MatrixType; + typedef typename MatrixType::Scalar Scalar; + typedef typename MatrixType::Index Index; + typedef typename MatrixType::RealScalar RealScalar; + typedef _Preconditioner Preconditioner; + +public: + + /** Default constructor. */ + BiCGSTAB() : Base() {} + + /** Initialize the solver with matrix \a A for further \c Ax=b solving. + * + * This constructor is a shortcut for the default constructor followed + * by a call to compute(). + * + * \warning this class stores a reference to the matrix A as well as some + * precomputed values that depend on it. Therefore, if \a A is changed + * this class becomes invalid. Call compute() to update it with the new + * matrix A, or modify a copy of A. + */ + BiCGSTAB(const MatrixType& A) : Base(A) {} + + ~BiCGSTAB() {} + + /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A + * \a x0 as an initial solution. + * + * \sa compute() + */ + template + inline const internal::solve_retval_with_guess + solveWithGuess(const MatrixBase& b, const Guess& x0) const + { + eigen_assert(m_isInitialized && "BiCGSTAB is not initialized."); + eigen_assert(Base::rows()==b.rows() + && "BiCGSTAB::solve(): invalid number of rows of the right hand side matrix b"); + return internal::solve_retval_with_guess + (*this, b.derived(), x0); + } + + /** \internal */ + template + void _solveWithGuess(const Rhs& b, Dest& x) const + { + bool failed = false; + for(int j=0; j + void _solve(const Rhs& b, Dest& x) const + { + x.setZero(); + _solveWithGuess(b,x); + } + +protected: + +}; + + +namespace internal { + + template +struct solve_retval, Rhs> + : solve_retval_base, Rhs> +{ + typedef BiCGSTAB<_MatrixType, _Preconditioner> Dec; + EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs) + + template void evalTo(Dest& dst) const + { + dec()._solve(rhs(),dst); + } +}; + +} // end namespace internal + +} // end namespace Eigen + +#endif // EIGEN_BICGSTAB_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/IterativeLinearSolvers/CMakeLists.txt b/gtsam/3rdparty/Eigen/Eigen/src/IterativeLinearSolvers/CMakeLists.txt new file mode 100644 index 000000000..59ccc0072 --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/src/IterativeLinearSolvers/CMakeLists.txt @@ -0,0 +1,6 @@ +FILE(GLOB Eigen_IterativeLinearSolvers_SRCS "*.h") + +INSTALL(FILES + ${Eigen_IterativeLinearSolvers_SRCS} + DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/IterativeLinearSolvers COMPONENT Devel + ) diff --git a/gtsam/3rdparty/Eigen/Eigen/src/IterativeLinearSolvers/ConjugateGradient.h b/gtsam/3rdparty/Eigen/Eigen/src/IterativeLinearSolvers/ConjugateGradient.h new file mode 100644 index 000000000..edab2299e --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/src/IterativeLinearSolvers/ConjugateGradient.h @@ -0,0 +1,266 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2011 Gael Guennebaud +// +// Eigen is free software; you can redistribute it and/or +// modify it under the terms of the GNU Lesser General Public +// License as published by the Free Software Foundation; either +// version 3 of the License, or (at your option) any later version. +// +// Alternatively, you can redistribute it and/or +// modify it under the terms of the GNU General Public License as +// published by the Free Software Foundation; either version 2 of +// the License, or (at your option) any later version. +// +// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY +// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the +// GNU General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public +// License and a copy of the GNU General Public License along with +// Eigen. If not, see . + +#ifndef EIGEN_CONJUGATE_GRADIENT_H +#define EIGEN_CONJUGATE_GRADIENT_H + +namespace Eigen { + +namespace internal { + +/** \internal Low-level conjugate gradient algorithm + * \param mat The matrix A + * \param rhs The right hand side vector b + * \param x On input and initial solution, on output the computed solution. + * \param precond A preconditioner being able to efficiently solve for an + * approximation of Ax=b (regardless of b) + * \param iters On input the max number of iteration, on output the number of performed iterations. + * \param tol_error On input the tolerance error, on output an estimation of the relative error. + */ +template +EIGEN_DONT_INLINE +void conjugate_gradient(const MatrixType& mat, const Rhs& rhs, Dest& x, + const Preconditioner& precond, int& iters, + typename Dest::RealScalar& tol_error) +{ + using std::sqrt; + using std::abs; + typedef typename Dest::RealScalar RealScalar; + typedef typename Dest::Scalar Scalar; + typedef Matrix VectorType; + + RealScalar tol = tol_error; + int maxIters = iters; + + int n = mat.cols(); + + VectorType residual = rhs - mat * x; //initial residual + VectorType p(n); + + p = precond.solve(residual); //initial search direction + + VectorType z(n), tmp(n); + RealScalar absNew = internal::real(residual.dot(p)); // the square of the absolute value of r scaled by invM + RealScalar rhsNorm2 = rhs.squaredNorm(); + RealScalar residualNorm2 = 0; + RealScalar threshold = tol*tol*rhsNorm2; + int i = 0; + while(i < maxIters) + { + tmp.noalias() = mat * p; // the bottleneck of the algorithm + + Scalar alpha = absNew / p.dot(tmp); // the amount we travel on dir + x += alpha * p; // update solution + residual -= alpha * tmp; // update residue + + residualNorm2 = residual.squaredNorm(); + if(residualNorm2 < threshold) + break; + + z = precond.solve(residual); // approximately solve for "A z = residual" + + RealScalar absOld = absNew; + absNew = internal::real(residual.dot(z)); // update the absolute value of r + RealScalar beta = absNew / absOld; // calculate the Gram-Schmidt value used to create the new search direction + p = z + beta * p; // update search direction + i++; + } + tol_error = sqrt(residualNorm2 / rhsNorm2); + iters = i; +} + +} + +template< typename _MatrixType, int _UpLo=Lower, + typename _Preconditioner = DiagonalPreconditioner > +class ConjugateGradient; + +namespace internal { + +template< typename _MatrixType, int _UpLo, typename _Preconditioner> +struct traits > +{ + typedef _MatrixType MatrixType; + typedef _Preconditioner Preconditioner; +}; + +} + +/** \ingroup IterativeLinearSolvers_Module + * \brief A conjugate gradient solver for sparse self-adjoint problems + * + * This class allows to solve for A.x = b sparse linear problems using a conjugate gradient algorithm. + * The sparse matrix A must be selfadjoint. The vectors x and b can be either dense or sparse. + * + * \tparam _MatrixType the type of the sparse matrix A, can be a dense or a sparse matrix. + * \tparam _UpLo the triangular part that will be used for the computations. It can be Lower + * or Upper. Default is Lower. + * \tparam _Preconditioner the type of the preconditioner. Default is DiagonalPreconditioner + * + * The maximal number of iterations and tolerance value can be controlled via the setMaxIterations() + * and setTolerance() methods. The defaults are the size of the problem for the maximal number of iterations + * and NumTraits::epsilon() for the tolerance. + * + * This class can be used as the direct solver classes. Here is a typical usage example: + * \code + * int n = 10000; + * VectorXd x(n), b(n); + * SparseMatrix A(n,n); + * // fill A and b + * ConjugateGradient > cg; + * cg.compute(A); + * x = cg.solve(b); + * std::cout << "#iterations: " << cg.iterations() << std::endl; + * std::cout << "estimated error: " << cg.error() << std::endl; + * // update b, and solve again + * x = cg.solve(b); + * \endcode + * + * By default the iterations start with x=0 as an initial guess of the solution. + * One can control the start using the solveWithGuess() method. Here is a step by + * step execution example starting with a random guess and printing the evolution + * of the estimated error: + * * \code + * x = VectorXd::Random(n); + * cg.setMaxIterations(1); + * int i = 0; + * do { + * x = cg.solveWithGuess(b,x); + * std::cout << i << " : " << cg.error() << std::endl; + * ++i; + * } while (cg.info()!=Success && i<100); + * \endcode + * Note that such a step by step excution is slightly slower. + * + * \sa class SimplicialCholesky, DiagonalPreconditioner, IdentityPreconditioner + */ +template< typename _MatrixType, int _UpLo, typename _Preconditioner> +class ConjugateGradient : public IterativeSolverBase > +{ + typedef IterativeSolverBase Base; + using Base::mp_matrix; + using Base::m_error; + using Base::m_iterations; + using Base::m_info; + using Base::m_isInitialized; +public: + typedef _MatrixType MatrixType; + typedef typename MatrixType::Scalar Scalar; + typedef typename MatrixType::Index Index; + typedef typename MatrixType::RealScalar RealScalar; + typedef _Preconditioner Preconditioner; + + enum { + UpLo = _UpLo + }; + +public: + + /** Default constructor. */ + ConjugateGradient() : Base() {} + + /** Initialize the solver with matrix \a A for further \c Ax=b solving. + * + * This constructor is a shortcut for the default constructor followed + * by a call to compute(). + * + * \warning this class stores a reference to the matrix A as well as some + * precomputed values that depend on it. Therefore, if \a A is changed + * this class becomes invalid. Call compute() to update it with the new + * matrix A, or modify a copy of A. + */ + ConjugateGradient(const MatrixType& A) : Base(A) {} + + ~ConjugateGradient() {} + + /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A + * \a x0 as an initial solution. + * + * \sa compute() + */ + template + inline const internal::solve_retval_with_guess + solveWithGuess(const MatrixBase& b, const Guess& x0) const + { + eigen_assert(m_isInitialized && "ConjugateGradient is not initialized."); + eigen_assert(Base::rows()==b.rows() + && "ConjugateGradient::solve(): invalid number of rows of the right hand side matrix b"); + return internal::solve_retval_with_guess + (*this, b.derived(), x0); + } + + /** \internal */ + template + void _solveWithGuess(const Rhs& b, Dest& x) const + { + m_iterations = Base::maxIterations(); + m_error = Base::m_tolerance; + + for(int j=0; jtemplate selfadjointView(), b.col(j), xj, + Base::m_preconditioner, m_iterations, m_error); + } + + m_isInitialized = true; + m_info = m_error <= Base::m_tolerance ? Success : NoConvergence; + } + + /** \internal */ + template + void _solve(const Rhs& b, Dest& x) const + { + x.setOnes(); + _solveWithGuess(b,x); + } + +protected: + +}; + + +namespace internal { + +template +struct solve_retval, Rhs> + : solve_retval_base, Rhs> +{ + typedef ConjugateGradient<_MatrixType,_UpLo,_Preconditioner> Dec; + EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs) + + template void evalTo(Dest& dst) const + { + dec()._solve(rhs(),dst); + } +}; + +} // end namespace internal + +} // end namespace Eigen + +#endif // EIGEN_CONJUGATE_GRADIENT_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/IterativeLinearSolvers/IncompleteLUT.h b/gtsam/3rdparty/Eigen/Eigen/src/IterativeLinearSolvers/IncompleteLUT.h new file mode 100644 index 000000000..32f152634 --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/src/IterativeLinearSolvers/IncompleteLUT.h @@ -0,0 +1,476 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2012 Désiré Nuentsa-Wakam +// +// Eigen is free software; you can redistribute it and/or +// modify it under the terms of the GNU Lesser General Public +// License as published by the Free Software Foundation; either +// version 3 of the License, or (at your option) any later version. +// +// Alternatively, you can redistribute it and/or +// modify it under the terms of the GNU General Public License as +// published by the Free Software Foundation; either version 2 of +// the License, or (at your option) any later version. +// +// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY +// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the +// GNU General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public +// License and a copy of the GNU General Public License along with +// Eigen. If not, see . + +#ifndef EIGEN_INCOMPLETE_LUT_H +#define EIGEN_INCOMPLETE_LUT_H + +namespace Eigen { + +/** + * \brief Incomplete LU factorization with dual-threshold strategy + * During the numerical factorization, two dropping rules are used : + * 1) any element whose magnitude is less than some tolerance is dropped. + * This tolerance is obtained by multiplying the input tolerance @p droptol + * by the average magnitude of all the original elements in the current row. + * 2) After the elimination of the row, only the @p fill largest elements in + * the L part and the @p fill largest elements in the U part are kept + * (in addition to the diagonal element ). Note that @p fill is computed from + * the input parameter @p fillfactor which is used the ratio to control the fill_in + * relatively to the initial number of nonzero elements. + * + * The two extreme cases are when @p droptol=0 (to keep all the @p fill*2 largest elements) + * and when @p fill=n/2 with @p droptol being different to zero. + * + * References : Yousef Saad, ILUT: A dual threshold incomplete LU factorization, + * Numerical Linear Algebra with Applications, 1(4), pp 387-402, 1994. + * + * NOTE : The following implementation is derived from the ILUT implementation + * in the SPARSKIT package, Copyright (C) 2005, the Regents of the University of Minnesota + * released under the terms of the GNU LGPL; + * see http://www-users.cs.umn.edu/~saad/software/SPARSKIT/README for more details. + */ +template +class IncompleteLUT : internal::noncopyable +{ + typedef _Scalar Scalar; + typedef typename NumTraits::Real RealScalar; + typedef Matrix Vector; + typedef SparseMatrix FactorType; + typedef SparseMatrix PermutType; + typedef typename FactorType::Index Index; + + public: + typedef Matrix MatrixType; + + IncompleteLUT() + : m_droptol(NumTraits::dummy_precision()), m_fillfactor(10), + m_analysisIsOk(false), m_factorizationIsOk(false), m_isInitialized(false) + {} + + template + IncompleteLUT(const MatrixType& mat, RealScalar droptol=NumTraits::dummy_precision(), int fillfactor = 10) + : m_droptol(droptol),m_fillfactor(fillfactor), + m_analysisIsOk(false),m_factorizationIsOk(false),m_isInitialized(false) + { + eigen_assert(fillfactor != 0); + compute(mat); + } + + Index rows() const { return m_lu.rows(); } + + Index cols() const { return m_lu.cols(); } + + /** \brief Reports whether previous computation was successful. + * + * \returns \c Success if computation was succesful, + * \c NumericalIssue if the matrix.appears to be negative. + */ + ComputationInfo info() const + { + eigen_assert(m_isInitialized && "IncompleteLUT is not initialized."); + return m_info; + } + + template + void analyzePattern(const MatrixType& amat); + + template + void factorize(const MatrixType& amat); + + /** + * Compute an incomplete LU factorization with dual threshold on the matrix mat + * No pivoting is done in this version + * + **/ + template + IncompleteLUT& compute(const MatrixType& amat) + { + analyzePattern(amat); + factorize(amat); + eigen_assert(m_factorizationIsOk == true); + m_isInitialized = true; + return *this; + } + + void setDroptol(RealScalar droptol); + void setFillfactor(int fillfactor); + + template + void _solve(const Rhs& b, Dest& x) const + { + x = m_Pinv * b; + x = m_lu.template triangularView().solve(x); + x = m_lu.template triangularView().solve(x); + x = m_P * x; + } + + template inline const internal::solve_retval + solve(const MatrixBase& b) const + { + eigen_assert(m_isInitialized && "IncompleteLUT is not initialized."); + eigen_assert(cols()==b.rows() + && "IncompleteLUT::solve(): invalid number of rows of the right hand side matrix b"); + return internal::solve_retval(*this, b.derived()); + } + +protected: + + template + int QuickSplit(VectorV &row, VectorI &ind, int ncut); + + + /** keeps off-diagonal entries; drops diagonal entries */ + struct keep_diag { + inline bool operator() (const Index& row, const Index& col, const Scalar&) const + { + return row!=col; + } + }; + +protected: + + FactorType m_lu; + RealScalar m_droptol; + int m_fillfactor; + bool m_analysisIsOk; + bool m_factorizationIsOk; + bool m_isInitialized; + ComputationInfo m_info; + PermutationMatrix m_P; // Fill-reducing permutation + PermutationMatrix m_Pinv; // Inverse permutation +}; + +/** + * Set control parameter droptol + * \param droptol Drop any element whose magnitude is less than this tolerance + **/ +template +void IncompleteLUT::setDroptol(RealScalar droptol) +{ + this->m_droptol = droptol; +} + +/** + * Set control parameter fillfactor + * \param fillfactor This is used to compute the number @p fill_in of largest elements to keep on each row. + **/ +template +void IncompleteLUT::setFillfactor(int fillfactor) +{ + this->m_fillfactor = fillfactor; +} + + +/** + * Compute a quick-sort split of a vector + * On output, the vector row is permuted such that its elements satisfy + * abs(row(i)) >= abs(row(ncut)) if incut + * \param row The vector of values + * \param ind The array of index for the elements in @p row + * \param ncut The number of largest elements to keep + **/ +template +template +int IncompleteLUT::QuickSplit(VectorV &row, VectorI &ind, int ncut) +{ + using std::swap; + int mid; + int n = row.size(); /* length of the vector */ + int first, last ; + + ncut--; /* to fit the zero-based indices */ + first = 0; + last = n-1; + if (ncut < first || ncut > last ) return 0; + + do { + mid = first; + RealScalar abskey = std::abs(row(mid)); + for (int j = first + 1; j <= last; j++) { + if ( std::abs(row(j)) > abskey) { + ++mid; + swap(row(mid), row(j)); + swap(ind(mid), ind(j)); + } + } + /* Interchange for the pivot element */ + swap(row(mid), row(first)); + swap(ind(mid), ind(first)); + + if (mid > ncut) last = mid - 1; + else if (mid < ncut ) first = mid + 1; + } while (mid != ncut ); + + return 0; /* mid is equal to ncut */ +} + +template +template +void IncompleteLUT::analyzePattern(const _MatrixType& amat) +{ + // Compute the Fill-reducing permutation + SparseMatrix mat1 = amat; + SparseMatrix mat2 = amat.transpose(); + // Symmetrize the pattern + // FIXME for a matrix with nearly symmetric pattern, mat2+mat1 is the appropriate choice. + // on the other hand for a really non-symmetric pattern, mat2*mat1 should be prefered... + SparseMatrix AtA = mat2 + mat1; + AtA.prune(keep_diag()); + internal::minimum_degree_ordering(AtA, m_P); // Then compute the AMD ordering... + + m_Pinv = m_P.inverse(); // ... and the inverse permutation + + m_analysisIsOk = true; +} + +template +template +void IncompleteLUT::factorize(const _MatrixType& amat) +{ + using std::sqrt; + using std::swap; + using std::abs; + + eigen_assert((amat.rows() == amat.cols()) && "The factorization should be done on a square matrix"); + int n = amat.cols(); // Size of the matrix + m_lu.resize(n,n); + // Declare Working vectors and variables + Vector u(n) ; // real values of the row -- maximum size is n -- + VectorXi ju(n); // column position of the values in u -- maximum size is n + VectorXi jr(n); // Indicate the position of the nonzero elements in the vector u -- A zero location is indicated by -1 + + // Apply the fill-reducing permutation + eigen_assert(m_analysisIsOk && "You must first call analyzePattern()"); + SparseMatrix mat; + mat = amat.twistedBy(m_Pinv); + + // Initialization + jr.fill(-1); + ju.fill(0); + u.fill(0); + + // number of largest elements to keep in each row: + int fill_in = static_cast (amat.nonZeros()*m_fillfactor)/n+1; + if (fill_in > n) fill_in = n; + + // number of largest nonzero elements to keep in the L and the U part of the current row: + int nnzL = fill_in/2; + int nnzU = nnzL; + m_lu.reserve(n * (nnzL + nnzU + 1)); + + // global loop over the rows of the sparse matrix + for (int ii = 0; ii < n; ii++) + { + // 1 - copy the lower and the upper part of the row i of mat in the working vector u + + int sizeu = 1; // number of nonzero elements in the upper part of the current row + int sizel = 0; // number of nonzero elements in the lower part of the current row + ju(ii) = ii; + u(ii) = 0; + jr(ii) = ii; + RealScalar rownorm = 0; + + typename FactorType::InnerIterator j_it(mat, ii); // Iterate through the current row ii + for (; j_it; ++j_it) + { + int k = j_it.index(); + if (k < ii) + { + // copy the lower part + ju(sizel) = k; + u(sizel) = j_it.value(); + jr(k) = sizel; + ++sizel; + } + else if (k == ii) + { + u(ii) = j_it.value(); + } + else + { + // copy the upper part + int jpos = ii + sizeu; + ju(jpos) = k; + u(jpos) = j_it.value(); + jr(k) = jpos; + ++sizeu; + } + rownorm += internal::abs2(j_it.value()); + } + + // 2 - detect possible zero row + if(rownorm==0) + { + m_info = NumericalIssue; + return; + } + // Take the 2-norm of the current row as a relative tolerance + rownorm = sqrt(rownorm); + + // 3 - eliminate the previous nonzero rows + int jj = 0; + int len = 0; + while (jj < sizel) + { + // In order to eliminate in the correct order, + // we must select first the smallest column index among ju(jj:sizel) + int k; + int minrow = ju.segment(jj,sizel-jj).minCoeff(&k); // k is relative to the segment + k += jj; + if (minrow != ju(jj)) + { + // swap the two locations + int j = ju(jj); + swap(ju(jj), ju(k)); + jr(minrow) = jj; jr(j) = k; + swap(u(jj), u(k)); + } + // Reset this location + jr(minrow) = -1; + + // Start elimination + typename FactorType::InnerIterator ki_it(m_lu, minrow); + while (ki_it && ki_it.index() < minrow) ++ki_it; + eigen_internal_assert(ki_it && ki_it.col()==minrow); + Scalar fact = u(jj) / ki_it.value(); + + // drop too small elements + if(abs(fact) <= m_droptol) + { + jj++; + continue; + } + + // linear combination of the current row ii and the row minrow + ++ki_it; + for (; ki_it; ++ki_it) + { + Scalar prod = fact * ki_it.value(); + int j = ki_it.index(); + int jpos = jr(j); + if (jpos == -1) // fill-in element + { + int newpos; + if (j >= ii) // dealing with the upper part + { + newpos = ii + sizeu; + sizeu++; + eigen_internal_assert(sizeu<=n); + } + else // dealing with the lower part + { + newpos = sizel; + sizel++; + eigen_internal_assert(sizel<=ii); + } + ju(newpos) = j; + u(newpos) = -prod; + jr(j) = newpos; + } + else + u(jpos) -= prod; + } + // store the pivot element + u(len) = fact; + ju(len) = minrow; + ++len; + + jj++; + } // end of the elimination on the row ii + + // reset the upper part of the pointer jr to zero + for(int k = 0; k m_droptol * rownorm ) + { + ++len; + u(ii + len) = u(ii + k); + ju(ii + len) = ju(ii + k); + } + } + sizeu = len + 1; // +1 to take into account the diagonal element + len = (std::min)(sizeu, nnzU); + typename Vector::SegmentReturnType uu(u.segment(ii+1, sizeu-1)); + typename VectorXi::SegmentReturnType juu(ju.segment(ii+1, sizeu-1)); + QuickSplit(uu, juu, len); + + // store the largest elements of the U part + for(int k = ii + 1; k < ii + len; k++) + m_lu.insertBackByOuterInnerUnordered(ii,ju(k)) = u(k); + } + + m_lu.finalize(); + m_lu.makeCompressed(); + + m_factorizationIsOk = true; + m_info = Success; +} + +namespace internal { + +template +struct solve_retval, Rhs> + : solve_retval_base, Rhs> +{ + typedef IncompleteLUT<_MatrixType> Dec; + EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs) + + template void evalTo(Dest& dst) const + { + dec()._solve(rhs(),dst); + } +}; + +} // end namespace internal + +} // end namespace Eigen + +#endif // EIGEN_INCOMPLETE_LUT_H + diff --git a/gtsam/3rdparty/Eigen/Eigen/src/IterativeLinearSolvers/IterativeSolverBase.h b/gtsam/3rdparty/Eigen/Eigen/src/IterativeLinearSolvers/IterativeSolverBase.h new file mode 100644 index 000000000..b27ad82ec --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/src/IterativeLinearSolvers/IterativeSolverBase.h @@ -0,0 +1,269 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2011 Gael Guennebaud +// +// Eigen is free software; you can redistribute it and/or +// modify it under the terms of the GNU Lesser General Public +// License as published by the Free Software Foundation; either +// version 3 of the License, or (at your option) any later version. +// +// Alternatively, you can redistribute it and/or +// modify it under the terms of the GNU General Public License as +// published by the Free Software Foundation; either version 2 of +// the License, or (at your option) any later version. +// +// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY +// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the +// GNU General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public +// License and a copy of the GNU General Public License along with +// Eigen. If not, see . + +#ifndef EIGEN_ITERATIVE_SOLVER_BASE_H +#define EIGEN_ITERATIVE_SOLVER_BASE_H + +namespace Eigen { + +/** \ingroup IterativeLinearSolvers_Module + * \brief Base class for linear iterative solvers + * + * \sa class SimplicialCholesky, DiagonalPreconditioner, IdentityPreconditioner + */ +template< typename Derived> +class IterativeSolverBase : internal::noncopyable +{ +public: + typedef typename internal::traits::MatrixType MatrixType; + typedef typename internal::traits::Preconditioner Preconditioner; + typedef typename MatrixType::Scalar Scalar; + typedef typename MatrixType::Index Index; + typedef typename MatrixType::RealScalar RealScalar; + +public: + + Derived& derived() { return *static_cast(this); } + const Derived& derived() const { return *static_cast(this); } + + /** Default constructor. */ + IterativeSolverBase() + : mp_matrix(0) + { + init(); + } + + /** Initialize the solver with matrix \a A for further \c Ax=b solving. + * + * This constructor is a shortcut for the default constructor followed + * by a call to compute(). + * + * \warning this class stores a reference to the matrix A as well as some + * precomputed values that depend on it. Therefore, if \a A is changed + * this class becomes invalid. Call compute() to update it with the new + * matrix A, or modify a copy of A. + */ + IterativeSolverBase(const MatrixType& A) + { + init(); + compute(A); + } + + ~IterativeSolverBase() {} + + /** Initializes the iterative solver for the sparcity pattern of the matrix \a A for further solving \c Ax=b problems. + * + * Currently, this function mostly call analyzePattern on the preconditioner. In the future + * we might, for instance, implement column reodering for faster matrix vector products. + */ + Derived& analyzePattern(const MatrixType& A) + { + m_preconditioner.analyzePattern(A); + m_isInitialized = true; + m_analysisIsOk = true; + m_info = Success; + return derived(); + } + + /** Initializes the iterative solver with the numerical values of the matrix \a A for further solving \c Ax=b problems. + * + * Currently, this function mostly call factorize on the preconditioner. + * + * \warning this class stores a reference to the matrix A as well as some + * precomputed values that depend on it. Therefore, if \a A is changed + * this class becomes invalid. Call compute() to update it with the new + * matrix A, or modify a copy of A. + */ + Derived& factorize(const MatrixType& A) + { + eigen_assert(m_analysisIsOk && "You must first call analyzePattern()"); + mp_matrix = &A; + m_preconditioner.factorize(A); + m_factorizationIsOk = true; + m_info = Success; + return derived(); + } + + /** Initializes the iterative solver with the matrix \a A for further solving \c Ax=b problems. + * + * Currently, this function mostly initialized/compute the preconditioner. In the future + * we might, for instance, implement column reodering for faster matrix vector products. + * + * \warning this class stores a reference to the matrix A as well as some + * precomputed values that depend on it. Therefore, if \a A is changed + * this class becomes invalid. Call compute() to update it with the new + * matrix A, or modify a copy of A. + */ + Derived& compute(const MatrixType& A) + { + mp_matrix = &A; + m_preconditioner.compute(A); + m_isInitialized = true; + m_analysisIsOk = true; + m_factorizationIsOk = true; + m_info = Success; + return derived(); + } + + /** \internal */ + Index rows() const { return mp_matrix ? mp_matrix->rows() : 0; } + /** \internal */ + Index cols() const { return mp_matrix ? mp_matrix->cols() : 0; } + + /** \returns the tolerance threshold used by the stopping criteria */ + RealScalar tolerance() const { return m_tolerance; } + + /** Sets the tolerance threshold used by the stopping criteria */ + Derived& setTolerance(RealScalar tolerance) + { + m_tolerance = tolerance; + return derived(); + } + + /** \returns a read-write reference to the preconditioner for custom configuration. */ + Preconditioner& preconditioner() { return m_preconditioner; } + + /** \returns a read-only reference to the preconditioner. */ + const Preconditioner& preconditioner() const { return m_preconditioner; } + + /** \returns the max number of iterations */ + int maxIterations() const + { + return (mp_matrix && m_maxIterations<0) ? mp_matrix->cols() : m_maxIterations; + } + + /** Sets the max number of iterations */ + Derived& setMaxIterations(int maxIters) + { + m_maxIterations = maxIters; + return derived(); + } + + /** \returns the number of iterations performed during the last solve */ + int iterations() const + { + eigen_assert(m_isInitialized && "ConjugateGradient is not initialized."); + return m_iterations; + } + + /** \returns the tolerance error reached during the last solve */ + RealScalar error() const + { + eigen_assert(m_isInitialized && "ConjugateGradient is not initialized."); + return m_error; + } + + /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A. + * + * \sa compute() + */ + template inline const internal::solve_retval + solve(const MatrixBase& b) const + { + eigen_assert(m_isInitialized && "IterativeSolverBase is not initialized."); + eigen_assert(rows()==b.rows() + && "IterativeSolverBase::solve(): invalid number of rows of the right hand side matrix b"); + return internal::solve_retval(derived(), b.derived()); + } + + /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A. + * + * \sa compute() + */ + template + inline const internal::sparse_solve_retval + solve(const SparseMatrixBase& b) const + { + eigen_assert(m_isInitialized && "IterativeSolverBase is not initialized."); + eigen_assert(rows()==b.rows() + && "IterativeSolverBase::solve(): invalid number of rows of the right hand side matrix b"); + return internal::sparse_solve_retval(*this, b.derived()); + } + + /** \returns Success if the iterations converged, and NoConvergence otherwise. */ + ComputationInfo info() const + { + eigen_assert(m_isInitialized && "IterativeSolverBase is not initialized."); + return m_info; + } + + /** \internal */ + template + void _solve_sparse(const Rhs& b, SparseMatrix &dest) const + { + eigen_assert(rows()==b.rows()); + + int rhsCols = b.cols(); + int size = b.rows(); + Eigen::Matrix tb(size); + Eigen::Matrix tx(size); + for(int k=0; k::epsilon(); + } + const MatrixType* mp_matrix; + Preconditioner m_preconditioner; + + int m_maxIterations; + RealScalar m_tolerance; + + mutable RealScalar m_error; + mutable int m_iterations; + mutable ComputationInfo m_info; + mutable bool m_isInitialized, m_analysisIsOk, m_factorizationIsOk; +}; + +namespace internal { + +template +struct sparse_solve_retval, Rhs> + : sparse_solve_retval_base, Rhs> +{ + typedef IterativeSolverBase Dec; + EIGEN_MAKE_SPARSE_SOLVE_HELPERS(Dec,Rhs) + + template void evalTo(Dest& dst) const + { + dec().derived()._solve_sparse(rhs(),dst); + } +}; + +} // end namespace internal + +} // end namespace Eigen + +#endif // EIGEN_ITERATIVE_SOLVER_BASE_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Jacobi/Jacobi.h b/gtsam/3rdparty/Eigen/Eigen/src/Jacobi/Jacobi.h index 98dea6800..691f5f22b 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Jacobi/Jacobi.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/Jacobi/Jacobi.h @@ -26,6 +26,8 @@ #ifndef EIGEN_JACOBI_H #define EIGEN_JACOBI_H +namespace Eigen { + /** \ingroup Jacobi_Module * \jacobi_module * \class JacobiRotation @@ -326,7 +328,7 @@ void /*EIGEN_DONT_INLINE*/ apply_rotation_in_the_plane(VectorX& _x, VectorY& _y, // both vectors are sequentially stored in memory => vectorization enum { Peeling = 2 }; - Index alignedStart = first_aligned(y, size); + Index alignedStart = internal::first_aligned(y, size); Index alignedEnd = alignedStart + ((size-alignedStart)/PacketSize)*PacketSize; const Packet pc = pset1(j.c()); @@ -344,7 +346,7 @@ void /*EIGEN_DONT_INLINE*/ apply_rotation_in_the_plane(VectorX& _x, VectorY& _y, Scalar* EIGEN_RESTRICT px = x + alignedStart; Scalar* EIGEN_RESTRICT py = y + alignedStart; - if(first_aligned(x, size)==alignedStart) + if(internal::first_aligned(x, size)==alignedStart) { for(Index i=alignedStart; i @@ -109,4 +111,6 @@ inline typename internal::traits::Scalar MatrixBase::determina return internal::determinant_impl::type>::run(derived()); } +} // end namespace Eigen + #endif // EIGEN_DETERMINANT_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/LU/FullPivLU.h b/gtsam/3rdparty/Eigen/Eigen/src/LU/FullPivLU.h index 46ae7d651..c342bc470 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/LU/FullPivLU.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/LU/FullPivLU.h @@ -25,6 +25,8 @@ #ifndef EIGEN_LU_H #define EIGEN_LU_H +namespace Eigen { + /** \ingroup LU_Module * * \class FullPivLU @@ -282,6 +284,7 @@ template class FullPivLU FullPivLU& setThreshold(Default_t) { m_usePrescribedThreshold = false; + return *this; } /** Returns the threshold that will be used by certain methods such as rank(). @@ -743,4 +746,6 @@ MatrixBase::fullPivLu() const return FullPivLU(eval()); } +} // end namespace Eigen + #endif // EIGEN_LU_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/LU/Inverse.h b/gtsam/3rdparty/Eigen/Eigen/src/LU/Inverse.h index 2d3e6d105..aa90dc8ad 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/LU/Inverse.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/LU/Inverse.h @@ -25,6 +25,8 @@ #ifndef EIGEN_INVERSE_H #define EIGEN_INVERSE_H +namespace Eigen { + namespace internal { /********************************** @@ -286,7 +288,7 @@ struct inverse_impl : public ReturnByValue > typedef typename MatrixType::Index Index; typedef typename internal::eval::type MatrixTypeNested; typedef typename remove_all::type MatrixTypeNestedCleaned; - const MatrixTypeNested m_matrix; + MatrixTypeNested m_matrix; inverse_impl(const MatrixType& matrix) : m_matrix(matrix) @@ -404,4 +406,6 @@ inline void MatrixBase::computeInverseWithCheck( computeInverseAndDetWithCheck(inverse,determinant,invertible,absDeterminantThreshold); } +} // end namespace Eigen + #endif // EIGEN_INVERSE_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/LU/PartialPivLU.h b/gtsam/3rdparty/Eigen/Eigen/src/LU/PartialPivLU.h index 09394b01f..8ae556eb6 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/LU/PartialPivLU.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/LU/PartialPivLU.h @@ -26,6 +26,8 @@ #ifndef EIGEN_PARTIALLU_H #define EIGEN_PARTIALLU_H +namespace Eigen { + /** \ingroup LU_Module * * \class PartialPivLU @@ -506,4 +508,6 @@ MatrixBase::lu() const } #endif +} // end namespace Eigen + #endif // EIGEN_PARTIALLU_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/LU/PartialPivLU_MKL.h b/gtsam/3rdparty/Eigen/Eigen/src/LU/PartialPivLU_MKL.h new file mode 100644 index 000000000..9035953c8 --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/src/LU/PartialPivLU_MKL.h @@ -0,0 +1,85 @@ +/* + Copyright (c) 2011, Intel Corporation. All rights reserved. + + Redistribution and use in source and binary forms, with or without modification, + are permitted provided that the following conditions are met: + + * Redistributions of source code must retain the above copyright notice, this + list of conditions and the following disclaimer. + * Redistributions in binary form must reproduce the above copyright notice, + this list of conditions and the following disclaimer in the documentation + and/or other materials provided with the distribution. + * Neither the name of Intel Corporation nor the names of its contributors may + be used to endorse or promote products derived from this software without + specific prior written permission. + + THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND + ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED + WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE + DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR + ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES + (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; + LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON + ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS + SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + + ******************************************************************************** + * Content : Eigen bindings to Intel(R) MKL + * LU decomposition with partial pivoting based on LAPACKE_?getrf function. + ******************************************************************************** +*/ + +#ifndef EIGEN_PARTIALLU_LAPACK_H +#define EIGEN_PARTIALLU_LAPACK_H + +#include "Eigen/src/Core/util/MKL_support.h" + +namespace Eigen { + +namespace internal { + +/** \internal Specialization for the data types supported by MKL */ + +#define EIGEN_MKL_LU_PARTPIV(EIGTYPE, MKLTYPE, MKLPREFIX) \ +template \ +struct partial_lu_impl \ +{ \ + /* \internal performs the LU decomposition in-place of the matrix represented */ \ + static lapack_int blocked_lu(lapack_int rows, lapack_int cols, EIGTYPE* lu_data, lapack_int luStride, lapack_int* row_transpositions, lapack_int& nb_transpositions, lapack_int maxBlockSize=256) \ + { \ + EIGEN_UNUSED_VARIABLE(maxBlockSize);\ + lapack_int matrix_order, first_zero_pivot; \ + lapack_int m, n, lda, *ipiv, info; \ + EIGTYPE* a; \ +/* Set up parameters for ?getrf */ \ + matrix_order = StorageOrder==RowMajor ? LAPACK_ROW_MAJOR : LAPACK_COL_MAJOR; \ + lda = luStride; \ + a = lu_data; \ + ipiv = row_transpositions; \ + m = rows; \ + n = cols; \ + nb_transpositions = 0; \ +\ + info = LAPACKE_##MKLPREFIX##getrf( matrix_order, m, n, (MKLTYPE*)a, lda, ipiv ); \ +\ + for(int i=0;i= 0); \ +/* something should be done with nb_transpositions */ \ +\ + first_zero_pivot = info; \ + return first_zero_pivot; \ + } \ +}; + +EIGEN_MKL_LU_PARTPIV(double, double, d) +EIGEN_MKL_LU_PARTPIV(float, float, s) +EIGEN_MKL_LU_PARTPIV(dcomplex, MKL_Complex16, z) +EIGEN_MKL_LU_PARTPIV(scomplex, MKL_Complex8, c) + +} // end namespace internal + +} // end namespace Eigen + +#endif // EIGEN_PARTIALLU_LAPACK_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/LU/arch/Inverse_SSE.h b/gtsam/3rdparty/Eigen/Eigen/src/LU/arch/Inverse_SSE.h index 4c6153f0a..afb8e4a1d 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/LU/arch/Inverse_SSE.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/LU/arch/Inverse_SSE.h @@ -42,6 +42,8 @@ #ifndef EIGEN_INVERSE_SSE_H #define EIGEN_INVERSE_SSE_H +namespace Eigen { + namespace internal { template @@ -335,6 +337,8 @@ struct compute_inverse_size4 } }; -} +} // end namespace internal + +} // end namespace Eigen #endif // EIGEN_INVERSE_SSE_H diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/SparseExtra/Amd.h b/gtsam/3rdparty/Eigen/Eigen/src/OrderingMethods/Amd.h similarity index 91% rename from gtsam/3rdparty/Eigen/unsupported/Eigen/src/SparseExtra/Amd.h rename to gtsam/3rdparty/Eigen/Eigen/src/OrderingMethods/Amd.h index 52fd56bc4..ec13077fe 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/SparseExtra/Amd.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/OrderingMethods/Amd.h @@ -48,13 +48,14 @@ Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA #ifndef EIGEN_SPARSE_AMD_H #define EIGEN_SPARSE_AMD_H +namespace Eigen { + namespace internal { - -#define CS_FLIP(i) (-(i)-2) -#define CS_UNFLIP(i) (((i) < 0) ? CS_FLIP(i) : (i)) -#define CS_MARKED(w,j) (w[j] < 0) -#define CS_MARK(w,j) { w[j] = CS_FLIP (w[j]); } +template inline T amd_flip(const T& i) { return -i-2; } +template inline T amd_unflip(const T& i) { return i<0 ? amd_flip(i) : i; } +template inline bool amd_marked(const T0* w, const T1& j) { return w[j]<0; } +template inline void amd_mark(const T0* w, const T1& j) { return w[j] = amd_flip(w[j]); } /* clear w */ template @@ -103,8 +104,9 @@ Index cs_tdfs(Index j, Index k, Index *head, const Index *next, Index *post, Ind * The input matrix \a C must be a selfadjoint compressed column major SparseMatrix object. Both the upper and lower parts have to be stored, but the diagonal entries are optional. * On exit the values of C are destroyed */ template -void minimum_degree_ordering(SparseMatrix& C, PermutationMatrix& perm) +void minimum_degree_ordering(SparseMatrix& C, PermutationMatrix& perm) { + using std::sqrt; typedef SparseMatrix CCS; int d, dk, dext, lemax = 0, e, elenk, eln, i, j, k, k1, @@ -113,7 +115,7 @@ void minimum_degree_ordering(SparseMatrix& C, Permutation unsigned int h; Index n = C.cols(); - dense = std::max (16, 10 * sqrt ((double) n)); /* find dense threshold */ + dense = std::max (16, Index(10 * sqrt(double(n)))); /* find dense threshold */ dense = std::min (n-2, dense); Index cnz = C.nonZeros(); @@ -133,8 +135,8 @@ void minimum_degree_ordering(SparseMatrix& C, Permutation Index* last = perm.indices().data(); /* use P as workspace for last */ /* --- Initialize quotient graph ---------------------------------------- */ - Index* Cp = C._outerIndexPtr(); - Index* Ci = C._innerIndexPtr(); + Index* Cp = C.outerIndexPtr(); + Index* Ci = C.innerIndexPtr(); for(k = 0; k < n; k++) len[k] = Cp[k+1] - Cp[k]; len[n] = 0; @@ -151,7 +153,7 @@ void minimum_degree_ordering(SparseMatrix& C, Permutation elen[i] = 0; // Ek of node i is empty degree[i] = len[i]; // degree of node i } - mark = cs_wclear (0, 0, w, n); /* clear w */ + mark = internal::cs_wclear(0, 0, w, n); /* clear w */ elen[n] = -2; /* n is a dead element */ Cp[n] = -1; /* n is a root of assembly tree */ w[n] = 0; /* n is a dead element */ @@ -172,7 +174,7 @@ void minimum_degree_ordering(SparseMatrix& C, Permutation nv[i] = 0; /* absorb i into element n */ elen[i] = -1; /* node i is dead */ nel++; - Cp[i] = CS_FLIP (n); + Cp[i] = amd_flip (n); nv[n]++; } else @@ -201,12 +203,12 @@ void minimum_degree_ordering(SparseMatrix& C, Permutation if((p = Cp[j]) >= 0) /* j is a live node or element */ { Cp[j] = Ci[p]; /* save first entry of object */ - Ci[p] = CS_FLIP (j); /* first entry is now CS_FLIP(j) */ + Ci[p] = amd_flip (j); /* first entry is now amd_flip(j) */ } } for(q = 0, p = 0; p < cnz; ) /* scan all of memory */ { - if((j = CS_FLIP (Ci[p++])) >= 0) /* found object j */ + if((j = amd_flip (Ci[p++])) >= 0) /* found object j */ { Ci[q] = Cp[j]; /* restore first entry of object */ Cp[j] = q++; /* new pointer to object j */ @@ -255,7 +257,7 @@ void minimum_degree_ordering(SparseMatrix& C, Permutation } if(e != k) { - Cp[e] = CS_FLIP (k); /* absorb e into k */ + Cp[e] = amd_flip (k); /* absorb e into k */ w[e] = 0; /* e is now a dead element */ } } @@ -266,7 +268,7 @@ void minimum_degree_ordering(SparseMatrix& C, Permutation elen[k] = -2; /* k is now an element */ /* --- Find set differences ----------------------------------------- */ - mark = cs_wclear (mark, lemax, w, n); /* clear w if necessary */ + mark = internal::cs_wclear(mark, lemax, w, n); /* clear w if necessary */ for(pk = pk1; pk < pk2; pk++) /* scan 1: find |Le\Lk| */ { i = Ci[pk]; @@ -308,7 +310,7 @@ void minimum_degree_ordering(SparseMatrix& C, Permutation } else { - Cp[e] = CS_FLIP (k); /* aggressive absorb. e->k */ + Cp[e] = amd_flip (k); /* aggressive absorb. e->k */ w[e] = 0; /* e is a dead element */ } } @@ -326,7 +328,7 @@ void minimum_degree_ordering(SparseMatrix& C, Permutation } if(d == 0) /* check for mass elimination */ { - Cp[i] = CS_FLIP (k); /* absorb i into k */ + Cp[i] = amd_flip (k); /* absorb i into k */ nvi = -nv[i]; dk -= nvi; /* |Lk| -= |i| */ nvk += nvi; /* |k| += nv[i] */ @@ -349,7 +351,7 @@ void minimum_degree_ordering(SparseMatrix& C, Permutation } /* scan2 is done */ degree[k] = dk; /* finalize |Lk| */ lemax = std::max(lemax, dk); - mark = cs_wclear (mark+lemax, lemax, w, n); /* clear w */ + mark = internal::cs_wclear(mark+lemax, lemax, w, n); /* clear w */ /* --- Supernode detection ------------------------------------------ */ for(pk = pk1; pk < pk2; pk++) @@ -374,7 +376,7 @@ void minimum_degree_ordering(SparseMatrix& C, Permutation } if(ok) /* i and j are identical */ { - Cp[j] = CS_FLIP (i); /* absorb j into i */ + Cp[j] = amd_flip (i); /* absorb j into i */ nv[i] += nv[j]; nv[j] = 0; elen[j] = -1; /* node j is dead */ @@ -416,7 +418,7 @@ void minimum_degree_ordering(SparseMatrix& C, Permutation } /* --- Postordering ----------------------------------------------------- */ - for(i = 0; i < n; i++) Cp[i] = CS_FLIP (Cp[i]);/* fix assembly tree */ + for(i = 0; i < n; i++) Cp[i] = amd_flip (Cp[i]);/* fix assembly tree */ for(j = 0; j <= n; j++) head[j] = -1; for(j = n; j >= 0; j--) /* place unordered nodes in lists */ { @@ -435,7 +437,7 @@ void minimum_degree_ordering(SparseMatrix& C, Permutation } for(k = 0, i = 0; i <= n; i++) /* postorder the assembly tree */ { - if(Cp[i] == -1) k = cs_tdfs (i, k, head, next, perm.indices().data(), w); + if(Cp[i] == -1) k = internal::cs_tdfs(i, k, head, next, perm.indices().data(), w); } perm.indices().conservativeResize(n); @@ -445,4 +447,6 @@ void minimum_degree_ordering(SparseMatrix& C, Permutation } // namespace internal +} // end namespace Eigen + #endif // EIGEN_SPARSE_AMD_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/OrderingMethods/CMakeLists.txt b/gtsam/3rdparty/Eigen/Eigen/src/OrderingMethods/CMakeLists.txt new file mode 100644 index 000000000..9f4bb2758 --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/src/OrderingMethods/CMakeLists.txt @@ -0,0 +1,6 @@ +FILE(GLOB Eigen_OrderingMethods_SRCS "*.h") + +INSTALL(FILES + ${Eigen_OrderingMethods_SRCS} + DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/OrderingMethods COMPONENT Devel + ) diff --git a/gtsam/3rdparty/Eigen/Eigen/src/PaStiXSupport/CMakeLists.txt b/gtsam/3rdparty/Eigen/Eigen/src/PaStiXSupport/CMakeLists.txt new file mode 100644 index 000000000..28c657e9b --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/src/PaStiXSupport/CMakeLists.txt @@ -0,0 +1,6 @@ +FILE(GLOB Eigen_PastixSupport_SRCS "*.h") + +INSTALL(FILES + ${Eigen_PastixSupport_SRCS} + DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/PaStiXSupport COMPONENT Devel + ) diff --git a/gtsam/3rdparty/Eigen/Eigen/src/PaStiXSupport/PaStiXSupport.h b/gtsam/3rdparty/Eigen/Eigen/src/PaStiXSupport/PaStiXSupport.h new file mode 100644 index 000000000..f687a5e6b --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/src/PaStiXSupport/PaStiXSupport.h @@ -0,0 +1,757 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2012 Désiré Nuentsa-Wakam +// +// Eigen is free software; you can redistribute it and/or +// modify it under the terms of the GNU Lesser General Public +// License as published by the Free Software Foundation; either +// version 3 of the License, or (at your option) any later version. +// +// Alternatively, you can redistribute it and/or +// modify it under the terms of the GNU General Public License as +// published by the Free Software Foundation; either version 2 of +// the License, or (at your option) any later version. +// +// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY +// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the +// GNU General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public +// License and a copy of the GNU General Public License along with +// Eigen. If not, see . + +#ifndef EIGEN_PASTIXSUPPORT_H +#define EIGEN_PASTIXSUPPORT_H + +namespace Eigen { + +/** \ingroup PaStiXSupport_Module + * \brief Interface to the PaStix solver + * + * This class is used to solve the linear systems A.X = B via the PaStix library. + * The matrix can be either real or complex, symmetric or not. + * + * \sa TutorialSparseDirectSolvers + */ +template class PastixLU; +template class PastixLLT; +template class PastixLDLT; + +namespace internal +{ + + template struct pastix_traits; + + template + struct pastix_traits< PastixLU<_MatrixType> > + { + typedef _MatrixType MatrixType; + typedef typename _MatrixType::Scalar Scalar; + typedef typename _MatrixType::RealScalar RealScalar; + typedef typename _MatrixType::Index Index; + }; + + template + struct pastix_traits< PastixLLT<_MatrixType,Options> > + { + typedef _MatrixType MatrixType; + typedef typename _MatrixType::Scalar Scalar; + typedef typename _MatrixType::RealScalar RealScalar; + typedef typename _MatrixType::Index Index; + }; + + template + struct pastix_traits< PastixLDLT<_MatrixType,Options> > + { + typedef _MatrixType MatrixType; + typedef typename _MatrixType::Scalar Scalar; + typedef typename _MatrixType::RealScalar RealScalar; + typedef typename _MatrixType::Index Index; + }; + + void eigen_pastix(pastix_data_t **pastix_data, int pastix_comm, int n, int *ptr, int *idx, float *vals, int *perm, int * invp, float *x, int nbrhs, int *iparm, double *dparm) + { + if (n == 0) { ptr = NULL; idx = NULL; vals = NULL; } + if (nbrhs == 0) {x = NULL; nbrhs=1;} + s_pastix(pastix_data, pastix_comm, n, ptr, idx, vals, perm, invp, x, nbrhs, iparm, dparm); + } + + void eigen_pastix(pastix_data_t **pastix_data, int pastix_comm, int n, int *ptr, int *idx, double *vals, int *perm, int * invp, double *x, int nbrhs, int *iparm, double *dparm) + { + if (n == 0) { ptr = NULL; idx = NULL; vals = NULL; } + if (nbrhs == 0) {x = NULL; nbrhs=1;} + d_pastix(pastix_data, pastix_comm, n, ptr, idx, vals, perm, invp, x, nbrhs, iparm, dparm); + } + + void eigen_pastix(pastix_data_t **pastix_data, int pastix_comm, int n, int *ptr, int *idx, std::complex *vals, int *perm, int * invp, std::complex *x, int nbrhs, int *iparm, double *dparm) + { + if (n == 0) { ptr = NULL; idx = NULL; vals = NULL; } + if (nbrhs == 0) {x = NULL; nbrhs=1;} + c_pastix(pastix_data, pastix_comm, n, ptr, idx, reinterpret_cast(vals), perm, invp, reinterpret_cast(x), nbrhs, iparm, dparm); + } + + void eigen_pastix(pastix_data_t **pastix_data, int pastix_comm, int n, int *ptr, int *idx, std::complex *vals, int *perm, int * invp, std::complex *x, int nbrhs, int *iparm, double *dparm) + { + if (n == 0) { ptr = NULL; idx = NULL; vals = NULL; } + if (nbrhs == 0) {x = NULL; nbrhs=1;} + z_pastix(pastix_data, pastix_comm, n, ptr, idx, reinterpret_cast(vals), perm, invp, reinterpret_cast(x), nbrhs, iparm, dparm); + } + + // Convert the matrix to Fortran-style Numbering + template + void c_to_fortran_numbering (MatrixType& mat) + { + if ( !(mat.outerIndexPtr()[0]) ) + { + int i; + for(i = 0; i <= mat.rows(); ++i) + ++mat.outerIndexPtr()[i]; + for(i = 0; i < mat.nonZeros(); ++i) + ++mat.innerIndexPtr()[i]; + } + } + + // Convert to C-style Numbering + template + void fortran_to_c_numbering (MatrixType& mat) + { + // Check the Numbering + if ( mat.outerIndexPtr()[0] == 1 ) + { // Convert to C-style numbering + int i; + for(i = 0; i <= mat.rows(); ++i) + --mat.outerIndexPtr()[i]; + for(i = 0; i < mat.nonZeros(); ++i) + --mat.innerIndexPtr()[i]; + } + } +} + +// This is the base class to interface with PaStiX functions. +// Users should not used this class directly. +template +class PastixBase : internal::noncopyable +{ + public: + typedef typename internal::pastix_traits::MatrixType _MatrixType; + typedef _MatrixType MatrixType; + typedef typename MatrixType::Scalar Scalar; + typedef typename MatrixType::RealScalar RealScalar; + typedef typename MatrixType::Index Index; + typedef Matrix Vector; + typedef SparseMatrix ColSpMatrix; + + public: + + PastixBase() : m_initisOk(false), m_analysisIsOk(false), m_factorizationIsOk(false), m_isInitialized(false), m_pastixdata(0), m_size(0) + { + init(); + } + + ~PastixBase() + { + clean(); + } + + /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A. + * + * \sa compute() + */ + template + inline const internal::solve_retval + solve(const MatrixBase& b) const + { + eigen_assert(m_isInitialized && "Pastix solver is not initialized."); + eigen_assert(rows()==b.rows() + && "PastixBase::solve(): invalid number of rows of the right hand side matrix b"); + return internal::solve_retval(*this, b.derived()); + } + + template + bool _solve (const MatrixBase &b, MatrixBase &x) const; + + /** \internal */ + template + void _solve_sparse(const Rhs& b, SparseMatrix &dest) const + { + eigen_assert(m_factorizationIsOk && "The decomposition is not in a valid state for solving, you must first call either compute() or symbolic()/numeric()"); + eigen_assert(rows()==b.rows()); + + // we process the sparse rhs per block of NbColsAtOnce columns temporarily stored into a dense matrix. + static const int NbColsAtOnce = 1; + int rhsCols = b.cols(); + int size = b.rows(); + Eigen::Matrix tmp(size,rhsCols); + for(int k=0; k(rhsCols-k, NbColsAtOnce); + tmp.leftCols(actualCols) = b.middleCols(k,actualCols); + tmp.leftCols(actualCols) = derived().solve(tmp.leftCols(actualCols)); + dest.middleCols(k,actualCols) = tmp.leftCols(actualCols).sparseView(); + } + } + + Derived& derived() + { + return *static_cast(this); + } + const Derived& derived() const + { + return *static_cast(this); + } + + /** Returns a reference to the integer vector IPARM of PaStiX parameters + * to modify the default parameters. + * The statistics related to the different phases of factorization and solve are saved here as well + * \sa analyzePattern() factorize() + */ + Array& iparm() + { + return m_iparm; + } + + /** Return a reference to a particular index parameter of the IPARM vector + * \sa iparm() + */ + + int& iparm(int idxparam) + { + return m_iparm(idxparam); + } + + /** Returns a reference to the double vector DPARM of PaStiX parameters + * The statistics related to the different phases of factorization and solve are saved here as well + * \sa analyzePattern() factorize() + */ + Array& dparm() + { + return m_dparm; + } + + + /** Return a reference to a particular index parameter of the DPARM vector + * \sa dparm() + */ + double& dparm(int idxparam) + { + return m_dparm(idxparam); + } + + inline Index cols() const { return m_size; } + inline Index rows() const { return m_size; } + + /** \brief Reports whether previous computation was successful. + * + * \returns \c Success if computation was succesful, + * \c NumericalIssue if the PaStiX reports a problem + * \c InvalidInput if the input matrix is invalid + * + * \sa iparm() + */ + ComputationInfo info() const + { + eigen_assert(m_isInitialized && "Decomposition is not initialized."); + return m_info; + } + + /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A. + * + * \sa compute() + */ + template + inline const internal::sparse_solve_retval + solve(const SparseMatrixBase& b) const + { + eigen_assert(m_isInitialized && "Pastix LU, LLT or LDLT is not initialized."); + eigen_assert(rows()==b.rows() + && "PastixBase::solve(): invalid number of rows of the right hand side matrix b"); + return internal::sparse_solve_retval(*this, b.derived()); + } + + protected: + + // Initialize the Pastix data structure, check the matrix + void init(); + + // Compute the ordering and the symbolic factorization + void analyzePattern(ColSpMatrix& mat); + + // Compute the numerical factorization + void factorize(ColSpMatrix& mat); + + // Free all the data allocated by Pastix + void clean() + { + eigen_assert(m_initisOk && "The Pastix structure should be allocated first"); + m_iparm(IPARM_START_TASK) = API_TASK_CLEAN; + m_iparm(IPARM_END_TASK) = API_TASK_CLEAN; + internal::eigen_pastix(&m_pastixdata, MPI_COMM_WORLD, 0, 0, 0, (Scalar*)0, + m_perm.data(), m_invp.data(), 0, 0, m_iparm.data(), m_dparm.data()); + } + + void compute(ColSpMatrix& mat); + + int m_initisOk; + int m_analysisIsOk; + int m_factorizationIsOk; + bool m_isInitialized; + mutable ComputationInfo m_info; + mutable pastix_data_t *m_pastixdata; // Data structure for pastix + mutable int m_comm; // The MPI communicator identifier + mutable Matrix m_iparm; // integer vector for the input parameters + mutable Matrix m_dparm; // Scalar vector for the input parameters + mutable Matrix m_perm; // Permutation vector + mutable Matrix m_invp; // Inverse permutation vector + mutable int m_size; // Size of the matrix +}; + + /** Initialize the PaStiX data structure. + *A first call to this function fills iparm and dparm with the default PaStiX parameters + * \sa iparm() dparm() + */ +template +void PastixBase::init() +{ + m_size = 0; + m_iparm.setZero(IPARM_SIZE); + m_dparm.setZero(DPARM_SIZE); + + m_iparm(IPARM_MODIFY_PARAMETER) = API_NO; + pastix(&m_pastixdata, MPI_COMM_WORLD, + 0, 0, 0, 0, + 0, 0, 0, 1, m_iparm.data(), m_dparm.data()); + + m_iparm[IPARM_MATRIX_VERIFICATION] = API_NO; + m_iparm[IPARM_VERBOSE] = 2; + m_iparm[IPARM_ORDERING] = API_ORDER_SCOTCH; + m_iparm[IPARM_INCOMPLETE] = API_NO; + m_iparm[IPARM_OOC_LIMIT] = 2000; + m_iparm[IPARM_RHS_MAKING] = API_RHS_B; + m_iparm(IPARM_MATRIX_VERIFICATION) = API_NO; + + m_iparm(IPARM_START_TASK) = API_TASK_INIT; + m_iparm(IPARM_END_TASK) = API_TASK_INIT; + internal::eigen_pastix(&m_pastixdata, MPI_COMM_WORLD, 0, 0, 0, (Scalar*)0, + 0, 0, 0, 0, m_iparm.data(), m_dparm.data()); + + // Check the returned error + if(m_iparm(IPARM_ERROR_NUMBER)) { + m_info = InvalidInput; + m_initisOk = false; + } + else { + m_info = Success; + m_initisOk = true; + } +} + +template +void PastixBase::compute(ColSpMatrix& mat) +{ + eigen_assert(mat.rows() == mat.cols() && "The input matrix should be squared"); + + analyzePattern(mat); + factorize(mat); + + m_iparm(IPARM_MATRIX_VERIFICATION) = API_NO; + m_isInitialized = m_factorizationIsOk; +} + + +template +void PastixBase::analyzePattern(ColSpMatrix& mat) +{ + eigen_assert(m_initisOk && "The initialization of PaSTiX failed"); + + // clean previous calls + if(m_size>0) + clean(); + + m_size = mat.rows(); + m_perm.resize(m_size); + m_invp.resize(m_size); + + m_iparm(IPARM_START_TASK) = API_TASK_ORDERING; + m_iparm(IPARM_END_TASK) = API_TASK_ANALYSE; + internal::eigen_pastix(&m_pastixdata, MPI_COMM_WORLD, m_size, mat.outerIndexPtr(), mat.innerIndexPtr(), + mat.valuePtr(), m_perm.data(), m_invp.data(), 0, 0, m_iparm.data(), m_dparm.data()); + + // Check the returned error + if(m_iparm(IPARM_ERROR_NUMBER)) + { + m_info = NumericalIssue; + m_analysisIsOk = false; + } + else + { + m_info = Success; + m_analysisIsOk = true; + } +} + +template +void PastixBase::factorize(ColSpMatrix& mat) +{ +// if(&m_cpyMat != &mat) m_cpyMat = mat; + eigen_assert(m_analysisIsOk && "The analysis phase should be called before the factorization phase"); + m_iparm(IPARM_START_TASK) = API_TASK_NUMFACT; + m_iparm(IPARM_END_TASK) = API_TASK_NUMFACT; + m_size = mat.rows(); + + internal::eigen_pastix(&m_pastixdata, MPI_COMM_WORLD, m_size, mat.outerIndexPtr(), mat.innerIndexPtr(), + mat.valuePtr(), m_perm.data(), m_invp.data(), 0, 0, m_iparm.data(), m_dparm.data()); + + // Check the returned error + if(m_iparm(IPARM_ERROR_NUMBER)) + { + m_info = NumericalIssue; + m_factorizationIsOk = false; + m_isInitialized = false; + } + else + { + m_info = Success; + m_factorizationIsOk = true; + m_isInitialized = true; + } +} + +/* Solve the system */ +template +template +bool PastixBase::_solve (const MatrixBase &b, MatrixBase &x) const +{ + eigen_assert(m_isInitialized && "The matrix should be factorized first"); + EIGEN_STATIC_ASSERT((Dest::Flags&RowMajorBit)==0, + THIS_METHOD_IS_ONLY_FOR_COLUMN_MAJOR_MATRICES); + int rhs = 1; + + x = b; /* on return, x is overwritten by the computed solution */ + + for (int i = 0; i < b.cols(); i++){ + m_iparm[IPARM_START_TASK] = API_TASK_SOLVE; + m_iparm[IPARM_END_TASK] = API_TASK_REFINE; + + internal::eigen_pastix(&m_pastixdata, MPI_COMM_WORLD, x.rows(), 0, 0, 0, + m_perm.data(), m_invp.data(), &x(0, i), rhs, m_iparm.data(), m_dparm.data()); + } + + // Check the returned error + m_info = m_iparm(IPARM_ERROR_NUMBER)==0 ? Success : NumericalIssue; + + return m_iparm(IPARM_ERROR_NUMBER)==0; +} + +/** \ingroup PaStiXSupport_Module + * \class PastixLU + * \brief Sparse direct LU solver based on PaStiX library + * + * This class is used to solve the linear systems A.X = B with a supernodal LU + * factorization in the PaStiX library. The matrix A should be squared and nonsingular + * PaStiX requires that the matrix A has a symmetric structural pattern. + * This interface can symmetrize the input matrix otherwise. + * The vectors or matrices X and B can be either dense or sparse. + * + * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<> + * \tparam IsStrSym Indicates if the input matrix has a symmetric pattern, default is false + * NOTE : Note that if the analysis and factorization phase are called separately, + * the input matrix will be symmetrized at each call, hence it is advised to + * symmetrize the matrix in a end-user program and set \p IsStrSym to true + * + * \sa \ref TutorialSparseDirectSolvers + * + */ +template +class PastixLU : public PastixBase< PastixLU<_MatrixType> > +{ + public: + typedef _MatrixType MatrixType; + typedef PastixBase > Base; + typedef typename Base::ColSpMatrix ColSpMatrix; + typedef typename MatrixType::Index Index; + + public: + PastixLU() : Base() + { + init(); + } + + PastixLU(const MatrixType& matrix):Base() + { + init(); + compute(matrix); + } + /** Compute the LU supernodal factorization of \p matrix. + * iparm and dparm can be used to tune the PaStiX parameters. + * see the PaStiX user's manual + * \sa analyzePattern() factorize() + */ + void compute (const MatrixType& matrix) + { + m_structureIsUptodate = false; + ColSpMatrix temp; + grabMatrix(matrix, temp); + Base::compute(temp); + } + /** Compute the LU symbolic factorization of \p matrix using its sparsity pattern. + * Several ordering methods can be used at this step. See the PaStiX user's manual. + * The result of this operation can be used with successive matrices having the same pattern as \p matrix + * \sa factorize() + */ + void analyzePattern(const MatrixType& matrix) + { + m_structureIsUptodate = false; + ColSpMatrix temp; + grabMatrix(matrix, temp); + Base::analyzePattern(temp); + } + + /** Compute the LU supernodal factorization of \p matrix + * WARNING The matrix \p matrix should have the same structural pattern + * as the same used in the analysis phase. + * \sa analyzePattern() + */ + void factorize(const MatrixType& matrix) + { + ColSpMatrix temp; + grabMatrix(matrix, temp); + Base::factorize(temp); + } + protected: + + void init() + { + m_structureIsUptodate = false; + m_iparm(IPARM_SYM) = API_SYM_NO; + m_iparm(IPARM_FACTORIZATION) = API_FACT_LU; + } + + void grabMatrix(const MatrixType& matrix, ColSpMatrix& out) + { + if(IsStrSym) + out = matrix; + else + { + if(!m_structureIsUptodate) + { + // update the transposed structure + m_transposedStructure = matrix.transpose(); + + // Set the elements of the matrix to zero + for (Index j=0; j + * \tparam UpLo The part of the matrix to use : Lower or Upper. The default is Lower as required by PaStiX + * + * \sa \ref TutorialSparseDirectSolvers + */ +template +class PastixLLT : public PastixBase< PastixLLT<_MatrixType, _UpLo> > +{ + public: + typedef _MatrixType MatrixType; + typedef PastixBase > Base; + typedef typename Base::ColSpMatrix ColSpMatrix; + + public: + enum { UpLo = _UpLo }; + PastixLLT() : Base() + { + init(); + } + + PastixLLT(const MatrixType& matrix):Base() + { + init(); + compute(matrix); + } + + /** Compute the L factor of the LL^T supernodal factorization of \p matrix + * \sa analyzePattern() factorize() + */ + void compute (const MatrixType& matrix) + { + ColSpMatrix temp; + grabMatrix(matrix, temp); + Base::compute(temp); + } + + /** Compute the LL^T symbolic factorization of \p matrix using its sparsity pattern + * The result of this operation can be used with successive matrices having the same pattern as \p matrix + * \sa factorize() + */ + void analyzePattern(const MatrixType& matrix) + { + ColSpMatrix temp; + grabMatrix(matrix, temp); + Base::analyzePattern(temp); + } + /** Compute the LL^T supernodal numerical factorization of \p matrix + * \sa analyzePattern() + */ + void factorize(const MatrixType& matrix) + { + ColSpMatrix temp; + grabMatrix(matrix, temp); + Base::factorize(temp); + } + protected: + using Base::m_iparm; + + void init() + { + m_iparm(IPARM_SYM) = API_SYM_YES; + m_iparm(IPARM_FACTORIZATION) = API_FACT_LLT; + } + + void grabMatrix(const MatrixType& matrix, ColSpMatrix& out) + { + // Pastix supports only lower, column-major matrices + out.template selfadjointView() = matrix.template selfadjointView(); + internal::c_to_fortran_numbering(out); + } +}; + +/** \ingroup PaStiXSupport_Module + * \class PastixLDLT + * \brief A sparse direct supernodal Cholesky (LLT) factorization and solver based on the PaStiX library + * + * This class is used to solve the linear systems A.X = B via a LDL^T supernodal Cholesky factorization + * available in the PaStiX library. The matrix A should be symmetric and positive definite + * WARNING Selfadjoint complex matrices are not supported in the current version of PaStiX + * The vectors or matrices X and B can be either dense or sparse + * + * \tparam MatrixType the type of the sparse matrix A, it must be a SparseMatrix<> + * \tparam UpLo The part of the matrix to use : Lower or Upper. The default is Lower as required by PaStiX + * + * \sa \ref TutorialSparseDirectSolvers + */ +template +class PastixLDLT : public PastixBase< PastixLDLT<_MatrixType, _UpLo> > +{ + public: + typedef _MatrixType MatrixType; + typedef PastixBase > Base; + typedef typename Base::ColSpMatrix ColSpMatrix; + + public: + enum { UpLo = _UpLo }; + PastixLDLT():Base() + { + init(); + } + + PastixLDLT(const MatrixType& matrix):Base() + { + init(); + compute(matrix); + } + + /** Compute the L and D factors of the LDL^T factorization of \p matrix + * \sa analyzePattern() factorize() + */ + void compute (const MatrixType& matrix) + { + ColSpMatrix temp; + grabMatrix(matrix, temp); + Base::compute(temp); + } + + /** Compute the LDL^T symbolic factorization of \p matrix using its sparsity pattern + * The result of this operation can be used with successive matrices having the same pattern as \p matrix + * \sa factorize() + */ + void analyzePattern(const MatrixType& matrix) + { + ColSpMatrix temp; + grabMatrix(matrix, temp); + Base::analyzePattern(temp); + } + /** Compute the LDL^T supernodal numerical factorization of \p matrix + * + */ + void factorize(const MatrixType& matrix) + { + ColSpMatrix temp; + grabMatrix(matrix, temp); + Base::factorize(temp); + } + + protected: + using Base::m_iparm; + + void init() + { + m_iparm(IPARM_SYM) = API_SYM_YES; + m_iparm(IPARM_FACTORIZATION) = API_FACT_LDLT; + } + + void grabMatrix(const MatrixType& matrix, ColSpMatrix& out) + { + // Pastix supports only lower, column-major matrices + out.template selfadjointView() = matrix.template selfadjointView(); + internal::c_to_fortran_numbering(out); + } +}; + +namespace internal { + +template +struct solve_retval, Rhs> + : solve_retval_base, Rhs> +{ + typedef PastixBase<_MatrixType> Dec; + EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs) + + template void evalTo(Dest& dst) const + { + dec()._solve(rhs(),dst); + } +}; + +template +struct sparse_solve_retval, Rhs> + : sparse_solve_retval_base, Rhs> +{ + typedef PastixBase<_MatrixType> Dec; + EIGEN_MAKE_SPARSE_SOLVE_HELPERS(Dec,Rhs) + + template void evalTo(Dest& dst) const + { + dec()._solve_sparse(rhs(),dst); + } +}; + +} // end namespace internal + +} // end namespace Eigen + +#endif diff --git a/gtsam/3rdparty/Eigen/Eigen/src/PardisoSupport/CMakeLists.txt b/gtsam/3rdparty/Eigen/Eigen/src/PardisoSupport/CMakeLists.txt new file mode 100644 index 000000000..a097ab401 --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/src/PardisoSupport/CMakeLists.txt @@ -0,0 +1,6 @@ +FILE(GLOB Eigen_PardisoSupport_SRCS "*.h") + +INSTALL(FILES + ${Eigen_PardisoSupport_SRCS} + DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/PardisoSupport COMPONENT Devel + ) diff --git a/gtsam/3rdparty/Eigen/Eigen/src/PardisoSupport/PardisoSupport.h b/gtsam/3rdparty/Eigen/Eigen/src/PardisoSupport/PardisoSupport.h new file mode 100644 index 000000000..e6defc8c3 --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/src/PardisoSupport/PardisoSupport.h @@ -0,0 +1,614 @@ +/* + Copyright (c) 2011, Intel Corporation. All rights reserved. + + Redistribution and use in source and binary forms, with or without modification, + are permitted provided that the following conditions are met: + + * Redistributions of source code must retain the above copyright notice, this + list of conditions and the following disclaimer. + * Redistributions in binary form must reproduce the above copyright notice, + this list of conditions and the following disclaimer in the documentation + and/or other materials provided with the distribution. + * Neither the name of Intel Corporation nor the names of its contributors may + be used to endorse or promote products derived from this software without + specific prior written permission. + + THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND + ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED + WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE + DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR + ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES + (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; + LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON + ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS + SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + + ******************************************************************************** + * Content : Eigen bindings to Intel(R) MKL PARDISO + ******************************************************************************** +*/ + +#ifndef EIGEN_PARDISOSUPPORT_H +#define EIGEN_PARDISOSUPPORT_H + +namespace Eigen { + +template class PardisoLU; +template class PardisoLLT; +template class PardisoLDLT; + +namespace internal +{ + template + struct pardiso_run_selector + { + static Index run( _MKL_DSS_HANDLE_t pt, Index maxfct, Index mnum, Index type, Index phase, Index n, void *a, + Index *ia, Index *ja, Index *perm, Index nrhs, Index *iparm, Index msglvl, void *b, void *x) + { + Index error = 0; + ::pardiso(pt, &maxfct, &mnum, &type, &phase, &n, a, ia, ja, perm, &nrhs, iparm, &msglvl, b, x, &error); + return error; + } + }; + template<> + struct pardiso_run_selector + { + typedef long long int Index; + static Index run( _MKL_DSS_HANDLE_t pt, Index maxfct, Index mnum, Index type, Index phase, Index n, void *a, + Index *ia, Index *ja, Index *perm, Index nrhs, Index *iparm, Index msglvl, void *b, void *x) + { + Index error = 0; + ::pardiso_64(pt, &maxfct, &mnum, &type, &phase, &n, a, ia, ja, perm, &nrhs, iparm, &msglvl, b, x, &error); + return error; + } + }; + + template struct pardiso_traits; + + template + struct pardiso_traits< PardisoLU<_MatrixType> > + { + typedef _MatrixType MatrixType; + typedef typename _MatrixType::Scalar Scalar; + typedef typename _MatrixType::RealScalar RealScalar; + typedef typename _MatrixType::Index Index; + }; + + template + struct pardiso_traits< PardisoLLT<_MatrixType, Options> > + { + typedef _MatrixType MatrixType; + typedef typename _MatrixType::Scalar Scalar; + typedef typename _MatrixType::RealScalar RealScalar; + typedef typename _MatrixType::Index Index; + }; + + template + struct pardiso_traits< PardisoLDLT<_MatrixType, Options> > + { + typedef _MatrixType MatrixType; + typedef typename _MatrixType::Scalar Scalar; + typedef typename _MatrixType::RealScalar RealScalar; + typedef typename _MatrixType::Index Index; + }; + +} + +template +class PardisoImpl +{ + typedef internal::pardiso_traits Traits; + public: + typedef typename Traits::MatrixType MatrixType; + typedef typename Traits::Scalar Scalar; + typedef typename Traits::RealScalar RealScalar; + typedef typename Traits::Index Index; + typedef SparseMatrix SparseMatrixType; + typedef Matrix VectorType; + typedef Matrix IntRowVectorType; + typedef Matrix IntColVectorType; + enum { + ScalarIsComplex = NumTraits::IsComplex + }; + + PardisoImpl() + { + eigen_assert((sizeof(Index) >= sizeof(_INTEGER_t) && sizeof(Index) <= 8) && "Non-supported index type"); + m_iparm.setZero(); + m_msglvl = 0; // No output + m_initialized = false; + } + + ~PardisoImpl() + { + pardisoRelease(); + } + + inline Index cols() const { return m_size; } + inline Index rows() const { return m_size; } + + /** \brief Reports whether previous computation was successful. + * + * \returns \c Success if computation was succesful, + * \c NumericalIssue if the matrix appears to be negative. + */ + ComputationInfo info() const + { + eigen_assert(m_initialized && "Decomposition is not initialized."); + return m_info; + } + + /** \warning for advanced usage only. + * \returns a reference to the parameter array controlling PARDISO. + * See the PARDISO manual to know how to use it. */ + Array& pardisoParameterArray() + { + return m_iparm; + } + + /** Performs a symbolic decomposition on the sparcity of \a matrix. + * + * This function is particularly useful when solving for several problems having the same structure. + * + * \sa factorize() + */ + Derived& analyzePattern(const MatrixType& matrix); + + /** Performs a numeric decomposition of \a matrix + * + * The given matrix must has the same sparcity than the matrix on which the symbolic decomposition has been performed. + * + * \sa analyzePattern() + */ + Derived& factorize(const MatrixType& matrix); + + Derived& compute(const MatrixType& matrix); + + /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A. + * + * \sa compute() + */ + template + inline const internal::solve_retval + solve(const MatrixBase& b) const + { + eigen_assert(m_initialized && "Pardiso solver is not initialized."); + eigen_assert(rows()==b.rows() + && "PardisoImpl::solve(): invalid number of rows of the right hand side matrix b"); + return internal::solve_retval(*this, b.derived()); + } + + /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A. + * + * \sa compute() + */ + template + inline const internal::sparse_solve_retval + solve(const SparseMatrixBase& b) const + { + eigen_assert(m_initialized && "Pardiso solver is not initialized."); + eigen_assert(rows()==b.rows() + && "PardisoImpl::solve(): invalid number of rows of the right hand side matrix b"); + return internal::sparse_solve_retval(*this, b.derived()); + } + + Derived& derived() + { + return *static_cast(this); + } + const Derived& derived() const + { + return *static_cast(this); + } + + template + bool _solve(const MatrixBase &b, MatrixBase& x) const; + + /** \internal */ + template + void _solve_sparse(const Rhs& b, SparseMatrix &dest) const + { + eigen_assert(m_size==b.rows()); + + // we process the sparse rhs per block of NbColsAtOnce columns temporarily stored into a dense matrix. + static const int NbColsAtOnce = 4; + int rhsCols = b.cols(); + int size = b.rows(); + // Pardiso cannot solve in-place, + // so we need two temporaries + Eigen::Matrix tmp_rhs(size,rhsCols); + Eigen::Matrix tmp_res(size,rhsCols); + for(int k=0; k(rhsCols-k, NbColsAtOnce); + tmp_rhs.leftCols(actualCols) = b.middleCols(k,actualCols); + tmp_res.leftCols(actualCols) = derived().solve(tmp_rhs.leftCols(actualCols)); + dest.middleCols(k,actualCols) = tmp_res.leftCols(actualCols).sparseView(); + } + } + + protected: + void pardisoRelease() + { + if(m_initialized) // Factorization ran at least once + { + internal::pardiso_run_selector::run(m_pt, 1, 1, m_type, -1, m_size, 0, 0, 0, m_perm.data(), 0, + m_iparm.data(), m_msglvl, 0, 0); + } + } + + void pardisoInit(int type) + { + m_type = type; + bool symmetric = abs(m_type) < 10; + m_iparm[0] = 1; // No solver default + m_iparm[1] = 3; // use Metis for the ordering + m_iparm[2] = 1; // Numbers of processors, value of OMP_NUM_THREADS + m_iparm[3] = 0; // No iterative-direct algorithm + m_iparm[4] = 0; // No user fill-in reducing permutation + m_iparm[5] = 0; // Write solution into x + m_iparm[6] = 0; // Not in use + m_iparm[7] = 2; // Max numbers of iterative refinement steps + m_iparm[8] = 0; // Not in use + m_iparm[9] = 13; // Perturb the pivot elements with 1E-13 + m_iparm[10] = symmetric ? 0 : 1; // Use nonsymmetric permutation and scaling MPS + m_iparm[11] = 0; // Not in use + m_iparm[12] = symmetric ? 0 : 1; // Maximum weighted matching algorithm is switched-off (default for symmetric). + // Try m_iparm[12] = 1 in case of inappropriate accuracy + m_iparm[13] = 0; // Output: Number of perturbed pivots + m_iparm[14] = 0; // Not in use + m_iparm[15] = 0; // Not in use + m_iparm[16] = 0; // Not in use + m_iparm[17] = -1; // Output: Number of nonzeros in the factor LU + m_iparm[18] = -1; // Output: Mflops for LU factorization + m_iparm[19] = 0; // Output: Numbers of CG Iterations + + m_iparm[20] = 0; // 1x1 pivoting + m_iparm[26] = 0; // No matrix checker + m_iparm[27] = (sizeof(RealScalar) == 4) ? 1 : 0; + m_iparm[34] = 1; // C indexing + m_iparm[59] = 1; // Automatic switch between In-Core and Out-of-Core modes + } + + protected: + // cached data to reduce reallocation, etc. + + void manageErrorCode(Index error) + { + switch(error) + { + case 0: + m_info = Success; + break; + case -4: + case -7: + m_info = NumericalIssue; + break; + default: + m_info = InvalidInput; + } + } + + mutable SparseMatrixType m_matrix; + ComputationInfo m_info; + bool m_initialized, m_analysisIsOk, m_factorizationIsOk; + Index m_type, m_msglvl; + mutable void *m_pt[64]; + mutable Array m_iparm; + mutable IntColVectorType m_perm; + Index m_size; + + private: + PardisoImpl(PardisoImpl &) {} +}; + +template +Derived& PardisoImpl::compute(const MatrixType& a) +{ + m_size = a.rows(); + eigen_assert(a.rows() == a.cols()); + + pardisoRelease(); + memset(m_pt, 0, sizeof(m_pt)); + m_perm.setZero(m_size); + derived().getMatrix(a); + + Index error; + error = internal::pardiso_run_selector::run(m_pt, 1, 1, m_type, 12, m_size, + m_matrix.valuePtr(), m_matrix.outerIndexPtr(), m_matrix.innerIndexPtr(), + m_perm.data(), 0, m_iparm.data(), m_msglvl, NULL, NULL); + + manageErrorCode(error); + m_analysisIsOk = true; + m_factorizationIsOk = true; + m_initialized = true; + return derived(); +} + +template +Derived& PardisoImpl::analyzePattern(const MatrixType& a) +{ + m_size = a.rows(); + eigen_assert(m_size == a.cols()); + + pardisoRelease(); + memset(m_pt, 0, sizeof(m_pt)); + m_perm.setZero(m_size); + derived().getMatrix(a); + + Index error; + error = internal::pardiso_run_selector::run(m_pt, 1, 1, m_type, 11, m_size, + m_matrix.valuePtr(), m_matrix.outerIndexPtr(), m_matrix.innerIndexPtr(), + m_perm.data(), 0, m_iparm.data(), m_msglvl, NULL, NULL); + + manageErrorCode(error); + m_analysisIsOk = true; + m_factorizationIsOk = false; + m_initialized = true; + return derived(); +} + +template +Derived& PardisoImpl::factorize(const MatrixType& a) +{ + eigen_assert(m_analysisIsOk && "You must first call analyzePattern()"); + eigen_assert(m_size == a.rows() && m_size == a.cols()); + + derived().getMatrix(a); + + Index error; + error = internal::pardiso_run_selector::run(m_pt, 1, 1, m_type, 22, m_size, + m_matrix.valuePtr(), m_matrix.outerIndexPtr(), m_matrix.innerIndexPtr(), + m_perm.data(), 0, m_iparm.data(), m_msglvl, NULL, NULL); + + manageErrorCode(error); + m_factorizationIsOk = true; + return derived(); +} + +template +template +bool PardisoImpl::_solve(const MatrixBase &b, MatrixBase& x) const +{ + if(m_iparm[0] == 0) // Factorization was not computed + return false; + + //Index n = m_matrix.rows(); + Index nrhs = Index(b.cols()); + eigen_assert(m_size==b.rows()); + eigen_assert(((MatrixBase::Flags & RowMajorBit) == 0 || nrhs == 1) && "Row-major right hand sides are not supported"); + eigen_assert(((MatrixBase::Flags & RowMajorBit) == 0 || nrhs == 1) && "Row-major matrices of unknowns are not supported"); + eigen_assert(((nrhs == 1) || b.outerStride() == b.rows())); + + +// switch (transposed) { +// case SvNoTrans : m_iparm[11] = 0 ; break; +// case SvTranspose : m_iparm[11] = 2 ; break; +// case SvAdjoint : m_iparm[11] = 1 ; break; +// default: +// //std::cerr << "Eigen: transposition option \"" << transposed << "\" not supported by the PARDISO backend\n"; +// m_iparm[11] = 0; +// } + + Scalar* rhs_ptr = const_cast(b.derived().data()); + Matrix tmp; + + // Pardiso cannot solve in-place + if(rhs_ptr == x.derived().data()) + { + tmp = b; + rhs_ptr = tmp.data(); + } + + Index error; + error = internal::pardiso_run_selector::run(m_pt, 1, 1, m_type, 33, m_size, + m_matrix.valuePtr(), m_matrix.outerIndexPtr(), m_matrix.innerIndexPtr(), + m_perm.data(), nrhs, m_iparm.data(), m_msglvl, + rhs_ptr, x.derived().data()); + + return error==0; +} + + +/** \ingroup PardisoSupport_Module + * \class PardisoLU + * \brief A sparse direct LU factorization and solver based on the PARDISO library + * + * This class allows to solve for A.X = B sparse linear problems via a direct LU factorization + * using the Intel MKL PARDISO library. The sparse matrix A must be squared and invertible. + * The vectors or matrices X and B can be either dense or sparse. + * + * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<> + * + * \sa \ref TutorialSparseDirectSolvers + */ +template +class PardisoLU : public PardisoImpl< PardisoLU > +{ + protected: + typedef PardisoImpl< PardisoLU > Base; + typedef typename Base::Scalar Scalar; + typedef typename Base::RealScalar RealScalar; + using Base::pardisoInit; + using Base::m_matrix; + friend class PardisoImpl< PardisoLU >; + + public: + + using Base::compute; + using Base::solve; + + PardisoLU() + : Base() + { + pardisoInit(Base::ScalarIsComplex ? 13 : 11); + } + + PardisoLU(const MatrixType& matrix) + : Base() + { + pardisoInit(Base::ScalarIsComplex ? 13 : 11); + compute(matrix); + } + protected: + void getMatrix(const MatrixType& matrix) + { + m_matrix = matrix; + } + + private: + PardisoLU(PardisoLU& ) {} +}; + +/** \ingroup PardisoSupport_Module + * \class PardisoLLT + * \brief A sparse direct Cholesky (LLT) factorization and solver based on the PARDISO library + * + * This class allows to solve for A.X = B sparse linear problems via a LL^T Cholesky factorization + * using the Intel MKL PARDISO library. The sparse matrix A must be selfajoint and positive definite. + * The vectors or matrices X and B can be either dense or sparse. + * + * \tparam MatrixType the type of the sparse matrix A, it must be a SparseMatrix<> + * \tparam UpLo can be any bitwise combination of Upper, Lower. The default is Upper, meaning only the upper triangular part has to be used. + * Upper|Lower can be used to tell both triangular parts can be used as input. + * + * \sa \ref TutorialSparseDirectSolvers + */ +template +class PardisoLLT : public PardisoImpl< PardisoLLT > +{ + protected: + typedef PardisoImpl< PardisoLLT > Base; + typedef typename Base::Scalar Scalar; + typedef typename Base::Index Index; + typedef typename Base::RealScalar RealScalar; + using Base::pardisoInit; + using Base::m_matrix; + friend class PardisoImpl< PardisoLLT >; + + public: + + enum { UpLo = _UpLo }; + using Base::compute; + using Base::solve; + + PardisoLLT() + : Base() + { + pardisoInit(Base::ScalarIsComplex ? 4 : 2); + } + + PardisoLLT(const MatrixType& matrix) + : Base() + { + pardisoInit(Base::ScalarIsComplex ? 4 : 2); + compute(matrix); + } + + protected: + + void getMatrix(const MatrixType& matrix) + { + // PARDISO supports only upper, row-major matrices + PermutationMatrix p_null; + m_matrix.resize(matrix.rows(), matrix.cols()); + m_matrix.template selfadjointView() = matrix.template selfadjointView().twistedBy(p_null); + } + + private: + PardisoLLT(PardisoLLT& ) {} +}; + +/** \ingroup PardisoSupport_Module + * \class PardisoLDLT + * \brief A sparse direct Cholesky (LDLT) factorization and solver based on the PARDISO library + * + * This class allows to solve for A.X = B sparse linear problems via a LDL^T Cholesky factorization + * using the Intel MKL PARDISO library. The sparse matrix A is assumed to be selfajoint and positive definite. + * For complex matrices, A can also be symmetric only, see the \a Options template parameter. + * The vectors or matrices X and B can be either dense or sparse. + * + * \tparam MatrixType the type of the sparse matrix A, it must be a SparseMatrix<> + * \tparam Options can be any bitwise combination of Upper, Lower, and Symmetric. The default is Upper, meaning only the upper triangular part has to be used. + * Symmetric can be used for symmetric, non-selfadjoint complex matrices, the default being to assume a selfadjoint matrix. + * Upper|Lower can be used to tell both triangular parts can be used as input. + * + * \sa \ref TutorialSparseDirectSolvers + */ +template +class PardisoLDLT : public PardisoImpl< PardisoLDLT > +{ + protected: + typedef PardisoImpl< PardisoLDLT > Base; + typedef typename Base::Scalar Scalar; + typedef typename Base::Index Index; + typedef typename Base::RealScalar RealScalar; + using Base::pardisoInit; + using Base::m_matrix; + friend class PardisoImpl< PardisoLDLT >; + + public: + + using Base::compute; + using Base::solve; + enum { UpLo = Options&(Upper|Lower) }; + + PardisoLDLT() + : Base() + { + pardisoInit(Base::ScalarIsComplex ? ( bool(Options&Symmetric) ? 6 : -4 ) : -2); + } + + PardisoLDLT(const MatrixType& matrix) + : Base() + { + pardisoInit(Base::ScalarIsComplex ? ( bool(Options&Symmetric) ? 6 : -4 ) : -2); + compute(matrix); + } + + void getMatrix(const MatrixType& matrix) + { + // PARDISO supports only upper, row-major matrices + PermutationMatrix p_null; + m_matrix.resize(matrix.rows(), matrix.cols()); + m_matrix.template selfadjointView() = matrix.template selfadjointView().twistedBy(p_null); + } + + private: + PardisoLDLT(PardisoLDLT& ) {} +}; + +namespace internal { + +template +struct solve_retval, Rhs> + : solve_retval_base, Rhs> +{ + typedef PardisoImpl<_Derived> Dec; + EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs) + + template void evalTo(Dest& dst) const + { + dec()._solve(rhs(),dst); + } +}; + +template +struct sparse_solve_retval, Rhs> + : sparse_solve_retval_base, Rhs> +{ + typedef PardisoImpl Dec; + EIGEN_MAKE_SPARSE_SOLVE_HELPERS(Dec,Rhs) + + template void evalTo(Dest& dst) const + { + dec().derived()._solve_sparse(rhs(),dst); + } +}; + +} // end namespace internal + +} // end namespace Eigen + +#endif // EIGEN_PARDISOSUPPORT_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/QR/ColPivHouseholderQR.h b/gtsam/3rdparty/Eigen/Eigen/src/QR/ColPivHouseholderQR.h index f04c6038d..9550b6bf6 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/QR/ColPivHouseholderQR.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/QR/ColPivHouseholderQR.h @@ -26,6 +26,8 @@ #ifndef EIGEN_COLPIVOTINGHOUSEHOLDERQR_H #define EIGEN_COLPIVOTINGHOUSEHOLDERQR_H +namespace Eigen { + /** \ingroup QR_Module * * \class ColPivHouseholderQR @@ -528,5 +530,6 @@ MatrixBase::colPivHouseholderQr() const return ColPivHouseholderQR(eval()); } +} // end namespace Eigen #endif // EIGEN_COLPIVOTINGHOUSEHOLDERQR_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/QR/ColPivHouseholderQR_MKL.h b/gtsam/3rdparty/Eigen/Eigen/src/QR/ColPivHouseholderQR_MKL.h new file mode 100644 index 000000000..0ad66d3f8 --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/src/QR/ColPivHouseholderQR_MKL.h @@ -0,0 +1,98 @@ +/* + Copyright (c) 2011, Intel Corporation. All rights reserved. + + Redistribution and use in source and binary forms, with or without modification, + are permitted provided that the following conditions are met: + + * Redistributions of source code must retain the above copyright notice, this + list of conditions and the following disclaimer. + * Redistributions in binary form must reproduce the above copyright notice, + this list of conditions and the following disclaimer in the documentation + and/or other materials provided with the distribution. + * Neither the name of Intel Corporation nor the names of its contributors may + be used to endorse or promote products derived from this software without + specific prior written permission. + + THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND + ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED + WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE + DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR + ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES + (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; + LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON + ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS + SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + + ******************************************************************************** + * Content : Eigen bindings to Intel(R) MKL + * Householder QR decomposition of a matrix with column pivoting based on + * LAPACKE_?geqp3 function. + ******************************************************************************** +*/ + +#ifndef EIGEN_COLPIVOTINGHOUSEHOLDERQR_MKL_H +#define EIGEN_COLPIVOTINGHOUSEHOLDERQR_MKL_H + +#include "Eigen/src/Core/util/MKL_support.h" + +namespace Eigen { + +/** \internal Specialization for the data types supported by MKL */ + +#define EIGEN_MKL_QR_COLPIV(EIGTYPE, MKLTYPE, MKLPREFIX, EIGCOLROW, MKLCOLROW) \ +template<> \ +ColPivHouseholderQR >& \ +ColPivHouseholderQR >::compute( \ + const Matrix& matrix) \ +\ +{ \ + typedef Matrix MatrixType; \ + typedef MatrixType::Scalar Scalar; \ + typedef MatrixType::RealScalar RealScalar; \ + Index rows = matrix.rows();\ + Index cols = matrix.cols();\ + Index size = matrix.diagonalSize();\ +\ + m_qr = matrix;\ + m_hCoeffs.resize(size);\ +\ + m_colsTranspositions.resize(cols);\ + /*Index number_of_transpositions = 0;*/ \ +\ + m_nonzero_pivots = 0; \ + m_maxpivot = RealScalar(0);\ + m_colsPermutation.resize(cols); \ + m_colsPermutation.indices().setZero(); \ +\ + lapack_int lda = m_qr.outerStride(), i; \ + lapack_int matrix_order = MKLCOLROW; \ + LAPACKE_##MKLPREFIX##geqp3( matrix_order, rows, cols, (MKLTYPE*)m_qr.data(), lda, (lapack_int*)m_colsPermutation.indices().data(), (MKLTYPE*)m_hCoeffs.data()); \ + m_isInitialized = true; \ + m_maxpivot=m_qr.diagonal().cwiseAbs().maxCoeff(); \ + m_hCoeffs.adjointInPlace(); \ + RealScalar premultiplied_threshold = internal::abs(m_maxpivot) * threshold(); \ + lapack_int *perm = m_colsPermutation.indices().data(); \ + for(i=0;i premultiplied_threshold);\ + } \ + for(i=0;i struct FullPivHouseholderQRMatrixQReturnType; + +template +struct traits > +{ + typedef typename MatrixType::PlainObject ReturnType; +}; + +} + /** \ingroup QR_Module * * \class FullPivHouseholderQR @@ -62,7 +76,7 @@ template class FullPivHouseholderQR typedef typename MatrixType::Scalar Scalar; typedef typename MatrixType::RealScalar RealScalar; typedef typename MatrixType::Index Index; - typedef Matrix MatrixQType; + typedef internal::FullPivHouseholderQRMatrixQReturnType MatrixQReturnType; typedef typename internal::plain_diag_type::type HCoeffsType; typedef Matrix IntRowVectorType; typedef PermutationMatrix PermutationType; @@ -139,7 +153,9 @@ template class FullPivHouseholderQR return internal::solve_retval(*this, b.derived()); } - MatrixQType matrixQ(void) const; + /** \returns Expression object representing the matrix Q + */ + MatrixQReturnType matrixQ(void) const; /** \returns a reference to the matrix where the Householder QR decomposition is stored */ @@ -508,28 +524,73 @@ struct solve_retval, Rhs> } }; +/** \ingroup QR_Module + * + * \brief Expression type for return value of FullPivHouseholderQR::matrixQ() + * + * \tparam MatrixType type of underlying dense matrix + */ +template struct FullPivHouseholderQRMatrixQReturnType + : public ReturnByValue > +{ +public: + typedef typename MatrixType::Index Index; + typedef typename internal::plain_col_type::type IntColVectorType; + typedef typename internal::plain_diag_type::type HCoeffsType; + typedef Matrix WorkVectorType; + + FullPivHouseholderQRMatrixQReturnType(const MatrixType& qr, + const HCoeffsType& hCoeffs, + const IntColVectorType& rowsTranspositions) + : m_qr(qr), + m_hCoeffs(hCoeffs), + m_rowsTranspositions(rowsTranspositions) + {} + + template + void evalTo(ResultType& result) const + { + const Index rows = m_qr.rows(); + WorkVectorType workspace(rows); + evalTo(result, workspace); + } + + template + void evalTo(ResultType& result, WorkVectorType& workspace) const + { + // compute the product H'_0 H'_1 ... H'_n-1, + // where H_k is the k-th Householder transformation I - h_k v_k v_k' + // and v_k is the k-th Householder vector [1,m_qr(k+1,k), m_qr(k+2,k), ...] + const Index rows = m_qr.rows(); + const Index cols = m_qr.cols(); + const Index size = (std::min)(rows, cols); + workspace.resize(rows); + result.setIdentity(rows, rows); + for (Index k = size-1; k >= 0; k--) + { + result.block(k, k, rows-k, rows-k) + .applyHouseholderOnTheLeft(m_qr.col(k).tail(rows-k-1), internal::conj(m_hCoeffs.coeff(k)), &workspace.coeffRef(k)); + result.row(k).swap(result.row(m_rowsTranspositions.coeff(k))); + } + } + + Index rows() const { return m_qr.rows(); } + Index cols() const { return m_qr.rows(); } + +protected: + typename MatrixType::Nested m_qr; + typename HCoeffsType::Nested m_hCoeffs; + typename IntColVectorType::Nested m_rowsTranspositions; +}; + } // end namespace internal -/** \returns the matrix Q */ template -typename FullPivHouseholderQR::MatrixQType FullPivHouseholderQR::matrixQ() const +inline typename FullPivHouseholderQR::MatrixQReturnType FullPivHouseholderQR::matrixQ() const { eigen_assert(m_isInitialized && "FullPivHouseholderQR is not initialized."); - // compute the product H'_0 H'_1 ... H'_n-1, - // where H_k is the k-th Householder transformation I - h_k v_k v_k' - // and v_k is the k-th Householder vector [1,m_qr(k+1,k), m_qr(k+2,k), ...] - Index rows = m_qr.rows(); - Index cols = m_qr.cols(); - Index size = (std::min)(rows,cols); - MatrixQType res = MatrixQType::Identity(rows, rows); - Matrix temp(rows); - for (Index k = size-1; k >= 0; k--) - { - res.block(k, k, rows-k, rows-k) - .applyHouseholderOnTheLeft(m_qr.col(k).tail(rows-k-1), internal::conj(m_hCoeffs.coeff(k)), &temp.coeffRef(k)); - res.row(k).swap(res.row(m_rows_transpositions.coeff(k))); - } - return res; + return MatrixQReturnType(m_qr, m_hCoeffs, m_rows_transpositions); } /** \return the full-pivoting Householder QR decomposition of \c *this. @@ -543,4 +604,6 @@ MatrixBase::fullPivHouseholderQr() const return FullPivHouseholderQR(eval()); } +} // end namespace Eigen + #endif // EIGEN_FULLPIVOTINGHOUSEHOLDERQR_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/QR/HouseholderQR.h b/gtsam/3rdparty/Eigen/Eigen/src/QR/HouseholderQR.h index 9ee96de26..59f6fcaa2 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/QR/HouseholderQR.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/QR/HouseholderQR.h @@ -27,6 +27,8 @@ #ifndef EIGEN_QR_H #define EIGEN_QR_H +namespace Eigen { + /** \ingroup QR_Module * * @@ -351,5 +353,6 @@ MatrixBase::householderQr() const return HouseholderQR(eval()); } +} // end namespace Eigen #endif // EIGEN_QR_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/QR/HouseholderQR_MKL.h b/gtsam/3rdparty/Eigen/Eigen/src/QR/HouseholderQR_MKL.h new file mode 100644 index 000000000..5313de604 --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/src/QR/HouseholderQR_MKL.h @@ -0,0 +1,69 @@ +/* + Copyright (c) 2011, Intel Corporation. All rights reserved. + + Redistribution and use in source and binary forms, with or without modification, + are permitted provided that the following conditions are met: + + * Redistributions of source code must retain the above copyright notice, this + list of conditions and the following disclaimer. + * Redistributions in binary form must reproduce the above copyright notice, + this list of conditions and the following disclaimer in the documentation + and/or other materials provided with the distribution. + * Neither the name of Intel Corporation nor the names of its contributors may + be used to endorse or promote products derived from this software without + specific prior written permission. + + THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND + ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED + WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE + DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR + ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES + (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; + LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON + ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS + SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + + ******************************************************************************** + * Content : Eigen bindings to Intel(R) MKL + * Householder QR decomposition of a matrix w/o pivoting based on + * LAPACKE_?geqrf function. + ******************************************************************************** +*/ + +#ifndef EIGEN_QR_MKL_H +#define EIGEN_QR_MKL_H + +#include "Eigen/src/Core/util/MKL_support.h" + +namespace Eigen { + +namespace internal { + +/** \internal Specialization for the data types supported by MKL */ + +#define EIGEN_MKL_QR_NOPIV(EIGTYPE, MKLTYPE, MKLPREFIX) \ +template \ +void householder_qr_inplace_blocked(MatrixQR& mat, HCoeffs& hCoeffs, \ + typename MatrixQR::Index maxBlockSize=32, \ + EIGTYPE* tempData = 0) \ +{ \ + lapack_int m = mat.rows(); \ + lapack_int n = mat.cols(); \ + lapack_int lda = mat.outerStride(); \ + lapack_int matrix_order = (MatrixQR::IsRowMajor) ? LAPACK_ROW_MAJOR : LAPACK_COL_MAJOR; \ + LAPACKE_##MKLPREFIX##geqrf( matrix_order, m, n, (MKLTYPE*)mat.data(), lda, (MKLTYPE*)hCoeffs.data()); \ + hCoeffs.adjointInPlace(); \ +\ +} + +EIGEN_MKL_QR_NOPIV(double, double, d) +EIGEN_MKL_QR_NOPIV(float, float, s) +EIGEN_MKL_QR_NOPIV(dcomplex, MKL_Complex16, z) +EIGEN_MKL_QR_NOPIV(scomplex, MKL_Complex8, c) + +} // end namespace internal + +} // end namespace Eigen + +#endif // EIGEN_QR_MKL_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/SVD/JacobiSVD.h b/gtsam/3rdparty/Eigen/Eigen/src/SVD/JacobiSVD.h index 3c423095c..9eadaa9fc 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/SVD/JacobiSVD.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/SVD/JacobiSVD.h @@ -25,6 +25,8 @@ #ifndef EIGEN_JACOBISVD_H #define EIGEN_JACOBISVD_H +namespace Eigen { + namespace internal { // forward declaration (needed by ICC) // the empty body is required by MSVC @@ -61,9 +63,12 @@ template struct qr_preconditioner_impl {}; template -struct qr_preconditioner_impl +class qr_preconditioner_impl { - static bool run(JacobiSVD&, const MatrixType&) +public: + typedef typename MatrixType::Index Index; + void allocate(const JacobiSVD&) {} + bool run(JacobiSVD&, const MatrixType&) { return false; } @@ -72,134 +77,279 @@ struct qr_preconditioner_impl /*** preconditioner using FullPivHouseholderQR ***/ template -struct qr_preconditioner_impl +class qr_preconditioner_impl { - static bool run(JacobiSVD& svd, const MatrixType& matrix) +public: + typedef typename MatrixType::Index Index; + typedef typename MatrixType::Scalar Scalar; + enum + { + RowsAtCompileTime = MatrixType::RowsAtCompileTime, + MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime + }; + typedef Matrix WorkspaceType; + + void allocate(const JacobiSVD& svd) + { + if (svd.rows() != m_qr.rows() || svd.cols() != m_qr.cols()) + { + m_qr = FullPivHouseholderQR(svd.rows(), svd.cols()); + } + if (svd.m_computeFullU) m_workspace.resize(svd.rows()); + } + + bool run(JacobiSVD& svd, const MatrixType& matrix) { if(matrix.rows() > matrix.cols()) { - FullPivHouseholderQR qr(matrix); - svd.m_workMatrix = qr.matrixQR().block(0,0,matrix.cols(),matrix.cols()).template triangularView(); - if(svd.m_computeFullU) svd.m_matrixU = qr.matrixQ(); - if(svd.computeV()) svd.m_matrixV = qr.colsPermutation(); + m_qr.compute(matrix); + svd.m_workMatrix = m_qr.matrixQR().block(0,0,matrix.cols(),matrix.cols()).template triangularView(); + if(svd.m_computeFullU) m_qr.matrixQ().evalTo(svd.m_matrixU, m_workspace); + if(svd.computeV()) svd.m_matrixV = m_qr.colsPermutation(); return true; } return false; } +private: + FullPivHouseholderQR m_qr; + WorkspaceType m_workspace; }; template -struct qr_preconditioner_impl +class qr_preconditioner_impl { - static bool run(JacobiSVD& svd, const MatrixType& matrix) +public: + typedef typename MatrixType::Index Index; + typedef typename MatrixType::Scalar Scalar; + enum + { + RowsAtCompileTime = MatrixType::RowsAtCompileTime, + ColsAtCompileTime = MatrixType::ColsAtCompileTime, + MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime, + MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime, + Options = MatrixType::Options + }; + typedef Matrix + TransposeTypeWithSameStorageOrder; + + void allocate(const JacobiSVD& svd) + { + if (svd.cols() != m_qr.rows() || svd.rows() != m_qr.cols()) + { + m_qr = FullPivHouseholderQR(svd.cols(), svd.rows()); + } + m_adjoint.resize(svd.cols(), svd.rows()); + if (svd.m_computeFullV) m_workspace.resize(svd.cols()); + } + + bool run(JacobiSVD& svd, const MatrixType& matrix) { if(matrix.cols() > matrix.rows()) { - typedef Matrix - TransposeTypeWithSameStorageOrder; - FullPivHouseholderQR qr(matrix.adjoint()); - svd.m_workMatrix = qr.matrixQR().block(0,0,matrix.rows(),matrix.rows()).template triangularView().adjoint(); - if(svd.m_computeFullV) svd.m_matrixV = qr.matrixQ(); - if(svd.computeU()) svd.m_matrixU = qr.colsPermutation(); + m_adjoint = matrix.adjoint(); + m_qr.compute(m_adjoint); + svd.m_workMatrix = m_qr.matrixQR().block(0,0,matrix.rows(),matrix.rows()).template triangularView().adjoint(); + if(svd.m_computeFullV) m_qr.matrixQ().evalTo(svd.m_matrixV, m_workspace); + if(svd.computeU()) svd.m_matrixU = m_qr.colsPermutation(); return true; } else return false; } +private: + FullPivHouseholderQR m_qr; + TransposeTypeWithSameStorageOrder m_adjoint; + typename internal::plain_row_type::type m_workspace; }; /*** preconditioner using ColPivHouseholderQR ***/ template -struct qr_preconditioner_impl +class qr_preconditioner_impl { - static bool run(JacobiSVD& svd, const MatrixType& matrix) +public: + typedef typename MatrixType::Index Index; + + void allocate(const JacobiSVD& svd) + { + if (svd.rows() != m_qr.rows() || svd.cols() != m_qr.cols()) + { + m_qr = ColPivHouseholderQR(svd.rows(), svd.cols()); + } + if (svd.m_computeFullU) m_workspace.resize(svd.rows()); + else if (svd.m_computeThinU) m_workspace.resize(svd.cols()); + } + + bool run(JacobiSVD& svd, const MatrixType& matrix) { if(matrix.rows() > matrix.cols()) { - ColPivHouseholderQR qr(matrix); - svd.m_workMatrix = qr.matrixQR().block(0,0,matrix.cols(),matrix.cols()).template triangularView(); - if(svd.m_computeFullU) svd.m_matrixU = qr.householderQ(); - else if(svd.m_computeThinU) { + m_qr.compute(matrix); + svd.m_workMatrix = m_qr.matrixQR().block(0,0,matrix.cols(),matrix.cols()).template triangularView(); + if(svd.m_computeFullU) m_qr.householderQ().evalTo(svd.m_matrixU, m_workspace); + else if(svd.m_computeThinU) + { svd.m_matrixU.setIdentity(matrix.rows(), matrix.cols()); - qr.householderQ().applyThisOnTheLeft(svd.m_matrixU); + m_qr.householderQ().applyThisOnTheLeft(svd.m_matrixU, m_workspace); } - if(svd.computeV()) svd.m_matrixV = qr.colsPermutation(); + if(svd.computeV()) svd.m_matrixV = m_qr.colsPermutation(); return true; } return false; } + +private: + ColPivHouseholderQR m_qr; + typename internal::plain_col_type::type m_workspace; }; template -struct qr_preconditioner_impl +class qr_preconditioner_impl { - static bool run(JacobiSVD& svd, const MatrixType& matrix) +public: + typedef typename MatrixType::Index Index; + typedef typename MatrixType::Scalar Scalar; + enum + { + RowsAtCompileTime = MatrixType::RowsAtCompileTime, + ColsAtCompileTime = MatrixType::ColsAtCompileTime, + MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime, + MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime, + Options = MatrixType::Options + }; + + typedef Matrix + TransposeTypeWithSameStorageOrder; + + void allocate(const JacobiSVD& svd) + { + if (svd.cols() != m_qr.rows() || svd.rows() != m_qr.cols()) + { + m_qr = ColPivHouseholderQR(svd.cols(), svd.rows()); + } + if (svd.m_computeFullV) m_workspace.resize(svd.cols()); + else if (svd.m_computeThinV) m_workspace.resize(svd.rows()); + m_adjoint.resize(svd.cols(), svd.rows()); + } + + bool run(JacobiSVD& svd, const MatrixType& matrix) { if(matrix.cols() > matrix.rows()) { - typedef Matrix - TransposeTypeWithSameStorageOrder; - ColPivHouseholderQR qr(matrix.adjoint()); - svd.m_workMatrix = qr.matrixQR().block(0,0,matrix.rows(),matrix.rows()).template triangularView().adjoint(); - if(svd.m_computeFullV) svd.m_matrixV = qr.householderQ(); - else if(svd.m_computeThinV) { + m_adjoint = matrix.adjoint(); + m_qr.compute(m_adjoint); + + svd.m_workMatrix = m_qr.matrixQR().block(0,0,matrix.rows(),matrix.rows()).template triangularView().adjoint(); + if(svd.m_computeFullV) m_qr.householderQ().evalTo(svd.m_matrixV, m_workspace); + else if(svd.m_computeThinV) + { svd.m_matrixV.setIdentity(matrix.cols(), matrix.rows()); - qr.householderQ().applyThisOnTheLeft(svd.m_matrixV); + m_qr.householderQ().applyThisOnTheLeft(svd.m_matrixV, m_workspace); } - if(svd.computeU()) svd.m_matrixU = qr.colsPermutation(); + if(svd.computeU()) svd.m_matrixU = m_qr.colsPermutation(); return true; } else return false; } + +private: + ColPivHouseholderQR m_qr; + TransposeTypeWithSameStorageOrder m_adjoint; + typename internal::plain_row_type::type m_workspace; }; /*** preconditioner using HouseholderQR ***/ template -struct qr_preconditioner_impl +class qr_preconditioner_impl { - static bool run(JacobiSVD& svd, const MatrixType& matrix) +public: + typedef typename MatrixType::Index Index; + + void allocate(const JacobiSVD& svd) + { + if (svd.rows() != m_qr.rows() || svd.cols() != m_qr.cols()) + { + m_qr = HouseholderQR(svd.rows(), svd.cols()); + } + if (svd.m_computeFullU) m_workspace.resize(svd.rows()); + else if (svd.m_computeThinU) m_workspace.resize(svd.cols()); + } + + bool run(JacobiSVD& svd, const MatrixType& matrix) { if(matrix.rows() > matrix.cols()) { - HouseholderQR qr(matrix); - svd.m_workMatrix = qr.matrixQR().block(0,0,matrix.cols(),matrix.cols()).template triangularView(); - if(svd.m_computeFullU) svd.m_matrixU = qr.householderQ(); - else if(svd.m_computeThinU) { + m_qr.compute(matrix); + svd.m_workMatrix = m_qr.matrixQR().block(0,0,matrix.cols(),matrix.cols()).template triangularView(); + if(svd.m_computeFullU) m_qr.householderQ().evalTo(svd.m_matrixU, m_workspace); + else if(svd.m_computeThinU) + { svd.m_matrixU.setIdentity(matrix.rows(), matrix.cols()); - qr.householderQ().applyThisOnTheLeft(svd.m_matrixU); + m_qr.householderQ().applyThisOnTheLeft(svd.m_matrixU, m_workspace); } if(svd.computeV()) svd.m_matrixV.setIdentity(matrix.cols(), matrix.cols()); return true; } return false; } +private: + HouseholderQR m_qr; + typename internal::plain_col_type::type m_workspace; }; template -struct qr_preconditioner_impl +class qr_preconditioner_impl { - static bool run(JacobiSVD& svd, const MatrixType& matrix) +public: + typedef typename MatrixType::Index Index; + typedef typename MatrixType::Scalar Scalar; + enum + { + RowsAtCompileTime = MatrixType::RowsAtCompileTime, + ColsAtCompileTime = MatrixType::ColsAtCompileTime, + MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime, + MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime, + Options = MatrixType::Options + }; + + typedef Matrix + TransposeTypeWithSameStorageOrder; + + void allocate(const JacobiSVD& svd) + { + if (svd.cols() != m_qr.rows() || svd.rows() != m_qr.cols()) + { + m_qr = HouseholderQR(svd.cols(), svd.rows()); + } + if (svd.m_computeFullV) m_workspace.resize(svd.cols()); + else if (svd.m_computeThinV) m_workspace.resize(svd.rows()); + m_adjoint.resize(svd.cols(), svd.rows()); + } + + bool run(JacobiSVD& svd, const MatrixType& matrix) { if(matrix.cols() > matrix.rows()) { - typedef Matrix - TransposeTypeWithSameStorageOrder; - HouseholderQR qr(matrix.adjoint()); - svd.m_workMatrix = qr.matrixQR().block(0,0,matrix.rows(),matrix.rows()).template triangularView().adjoint(); - if(svd.m_computeFullV) svd.m_matrixV = qr.householderQ(); - else if(svd.m_computeThinV) { + m_adjoint = matrix.adjoint(); + m_qr.compute(m_adjoint); + + svd.m_workMatrix = m_qr.matrixQR().block(0,0,matrix.rows(),matrix.rows()).template triangularView().adjoint(); + if(svd.m_computeFullV) m_qr.householderQ().evalTo(svd.m_matrixV, m_workspace); + else if(svd.m_computeThinV) + { svd.m_matrixV.setIdentity(matrix.cols(), matrix.rows()); - qr.householderQ().applyThisOnTheLeft(svd.m_matrixV); + m_qr.householderQ().applyThisOnTheLeft(svd.m_matrixV, m_workspace); } if(svd.computeU()) svd.m_matrixU.setIdentity(matrix.rows(), matrix.rows()); return true; } else return false; } + +private: + HouseholderQR m_qr; + TransposeTypeWithSameStorageOrder m_adjoint; + typename internal::plain_row_type::type m_workspace; }; /*** 2x2 SVD implementation @@ -316,7 +466,7 @@ void real_2x2_jacobi_svd(const MatrixType& matrix, Index p, Index q, * Here's an example demonstrating basic usage: * \include JacobiSVD_basic.cpp * Output: \verbinclude JacobiSVD_basic.out - * + * * This JacobiSVD class is a two-sided Jacobi R-SVD decomposition, ensuring optimal reliability and accuracy. The downside is that it's slower than * bidiagonalizing SVD algorithms for large square matrices; however its complexity is still \f$ O(n^2p) \f$ where \a n is the smaller dimension and * \a p is the greater dimension, meaning that it is still of the same order of complexity as the faster bidiagonalizing R-SVD algorithms. @@ -324,7 +474,7 @@ void real_2x2_jacobi_svd(const MatrixType& matrix, Index p, Index q, * * If the input matrix has inf or nan coefficients, the result of the computation is undefined, but the computation is guaranteed to * terminate in finite (and reasonable) time. - * + * * The possible values for QRPreconditioner are: * \li ColPivHouseholderQRPreconditioner is the default. In practice it's very safe. It uses column-pivoting QR. * \li FullPivHouseholderQRPreconditioner, is the safest and slowest. It uses full-pivoting QR. @@ -494,7 +644,7 @@ template class JacobiSVD * \param b the right-hand-side of the equation to solve. * * \note Solving requires both U and V to be computed. Thin U and V are enough, there is no need for full U or V. - * + * * \note SVD solving is implicitly least-squares. Thus, this method serves both purposes of exact solving and least-squares solving. * In other words, the returned solution is guaranteed to minimize the Euclidean norm \f$ \Vert A x - b \Vert \f$. */ @@ -535,6 +685,9 @@ template class JacobiSVD friend struct internal::svd_precondition_2x2_block_to_be_real; template friend struct internal::qr_preconditioner_impl; + + internal::qr_preconditioner_impl m_qr_precond_morecols; + internal::qr_preconditioner_impl m_qr_precond_morerows; }; template @@ -578,6 +731,9 @@ void JacobiSVD::allocate(Index rows, Index cols, u : m_computeThinV ? m_diagSize : 0); m_workMatrix.resize(m_diagSize, m_diagSize); + + if(m_cols>m_rows) m_qr_precond_morecols.allocate(*this); + if(m_rows>m_cols) m_qr_precond_morerows.allocate(*this); } template @@ -595,8 +751,7 @@ JacobiSVD::compute(const MatrixType& matrix, unsig /*** step 1. The R-SVD step: we use a QR decomposition to reduce to the case of a square matrix */ - if(!internal::qr_preconditioner_impl::run(*this, matrix) - && !internal::qr_preconditioner_impl::run(*this, matrix)) + if(!m_qr_precond_morecols.run(*this, matrix) && !m_qr_precond_morerows.run(*this, matrix)) { m_workMatrix = matrix.block(0,0,m_diagSize,m_diagSize); if(m_computeFullU) m_matrixU.setIdentity(m_rows,m_rows); @@ -722,6 +877,6 @@ MatrixBase::jacobiSvd(unsigned int computationOptions) const return JacobiSVD(*this, computationOptions); } - +} // end namespace Eigen #endif // EIGEN_JACOBISVD_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/SVD/JacobiSVD_MKL.h b/gtsam/3rdparty/Eigen/Eigen/src/SVD/JacobiSVD_MKL.h new file mode 100644 index 000000000..1eeafca49 --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/src/SVD/JacobiSVD_MKL.h @@ -0,0 +1,92 @@ +/* + Copyright (c) 2011, Intel Corporation. All rights reserved. + + Redistribution and use in source and binary forms, with or without modification, + are permitted provided that the following conditions are met: + + * Redistributions of source code must retain the above copyright notice, this + list of conditions and the following disclaimer. + * Redistributions in binary form must reproduce the above copyright notice, + this list of conditions and the following disclaimer in the documentation + and/or other materials provided with the distribution. + * Neither the name of Intel Corporation nor the names of its contributors may + be used to endorse or promote products derived from this software without + specific prior written permission. + + THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND + ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED + WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE + DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR + ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES + (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; + LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON + ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS + SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + + ******************************************************************************** + * Content : Eigen bindings to Intel(R) MKL + * Singular Value Decomposition - SVD. + ******************************************************************************** +*/ + +#ifndef EIGEN_JACOBISVD_MKL_H +#define EIGEN_JACOBISVD_MKL_H + +#include "Eigen/src/Core/util/MKL_support.h" + +namespace Eigen { + +/** \internal Specialization for the data types supported by MKL */ + +#define EIGEN_MKL_SVD(EIGTYPE, MKLTYPE, MKLRTYPE, MKLPREFIX, EIGCOLROW, MKLCOLROW) \ +template<> \ +JacobiSVD, ColPivHouseholderQRPreconditioner>& \ +JacobiSVD, ColPivHouseholderQRPreconditioner>::compute(const Matrix& matrix, unsigned int computationOptions) \ +{ \ + typedef Matrix MatrixType; \ + typedef MatrixType::Scalar Scalar; \ + typedef MatrixType::RealScalar RealScalar; \ + allocate(matrix.rows(), matrix.cols(), computationOptions); \ +\ + /*const RealScalar precision = RealScalar(2) * NumTraits::epsilon();*/ \ + m_nonzeroSingularValues = m_diagSize; \ +\ + lapack_int lda = matrix.outerStride(), ldu, ldvt; \ + lapack_int matrix_order = MKLCOLROW; \ + char jobu, jobvt; \ + MKLTYPE *u, *vt, dummy; \ + jobu = (m_computeFullU) ? 'A' : (m_computeThinU) ? 'S' : 'N'; \ + jobvt = (m_computeFullV) ? 'A' : (m_computeThinV) ? 'S' : 'N'; \ + if (computeU()) { \ + ldu = m_matrixU.outerStride(); \ + u = (MKLTYPE*)m_matrixU.data(); \ + } else { ldu=1; u=&dummy; }\ + MatrixType localV; \ + ldvt = (m_computeFullV) ? m_cols : (m_computeThinV) ? m_diagSize : 1; \ + if (computeV()) { \ + localV.resize(ldvt, m_cols); \ + vt = (MKLTYPE*)localV.data(); \ + } else { ldvt=1; vt=&dummy; }\ + Matrix superb; superb.resize(m_diagSize, 1); \ + MatrixType m_temp; m_temp = matrix; \ + LAPACKE_##MKLPREFIX##gesvd( matrix_order, jobu, jobvt, m_rows, m_cols, (MKLTYPE*)m_temp.data(), lda, (MKLRTYPE*)m_singularValues.data(), u, ldu, vt, ldvt, superb.data()); \ + if (computeV()) m_matrixV = localV.adjoint(); \ + /* for(int i=0;i::bidiagonalization() const } // end namespace internal +} // end namespace Eigen + #endif // EIGEN_BIDIAGONALIZATION_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Sparse/CMakeLists.txt b/gtsam/3rdparty/Eigen/Eigen/src/Sparse/CMakeLists.txt deleted file mode 100644 index aa1468812..000000000 --- a/gtsam/3rdparty/Eigen/Eigen/src/Sparse/CMakeLists.txt +++ /dev/null @@ -1,6 +0,0 @@ -FILE(GLOB Eigen_Sparse_SRCS "*.h") - -INSTALL(FILES - ${Eigen_Sparse_SRCS} - DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/Sparse COMPONENT Devel - ) diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseMatrix.h b/gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseMatrix.h deleted file mode 100644 index 0e175ec6e..000000000 --- a/gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseMatrix.h +++ /dev/null @@ -1,651 +0,0 @@ -// This file is part of Eigen, a lightweight C++ template library -// for linear algebra. -// -// Copyright (C) 2008-2010 Gael Guennebaud -// -// Eigen is free software; you can redistribute it and/or -// modify it under the terms of the GNU Lesser General Public -// License as published by the Free Software Foundation; either -// version 3 of the License, or (at your option) any later version. -// -// Alternatively, you can redistribute it and/or -// modify it under the terms of the GNU General Public License as -// published by the Free Software Foundation; either version 2 of -// the License, or (at your option) any later version. -// -// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY -// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS -// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the -// GNU General Public License for more details. -// -// You should have received a copy of the GNU Lesser General Public -// License and a copy of the GNU General Public License along with -// Eigen. If not, see . - -#ifndef EIGEN_SPARSEMATRIX_H -#define EIGEN_SPARSEMATRIX_H - -/** \ingroup Sparse_Module - * - * \class SparseMatrix - * - * \brief The main sparse matrix class - * - * This class implements a sparse matrix using the very common compressed row/column storage - * scheme. - * - * \tparam _Scalar the scalar type, i.e. the type of the coefficients - * \tparam _Options Union of bit flags controlling the storage scheme. Currently the only possibility - * is RowMajor. The default is 0 which means column-major. - * \tparam _Index the type of the indices. Default is \c int. - * - * See http://www.netlib.org/linalg/html_templates/node91.html for details on the storage scheme. - * - * This class can be extended with the help of the plugin mechanism described on the page - * \ref TopicCustomizingEigen by defining the preprocessor symbol \c EIGEN_SPARSEMATRIX_PLUGIN. - */ - -namespace internal { -template -struct traits > -{ - typedef _Scalar Scalar; - typedef _Index Index; - typedef Sparse StorageKind; - typedef MatrixXpr XprKind; - enum { - RowsAtCompileTime = Dynamic, - ColsAtCompileTime = Dynamic, - MaxRowsAtCompileTime = Dynamic, - MaxColsAtCompileTime = Dynamic, - Flags = _Options | NestByRefBit | LvalueBit, - CoeffReadCost = NumTraits::ReadCost, - SupportedAccessPatterns = InnerRandomAccessPattern - }; -}; - -} // end namespace internal - -template -class SparseMatrix - : public SparseMatrixBase > -{ - public: - EIGEN_SPARSE_PUBLIC_INTERFACE(SparseMatrix) -// using Base::operator=; - EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(SparseMatrix, +=) - EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(SparseMatrix, -=) - // FIXME: why are these operator already alvailable ??? - // EIGEN_SPARSE_INHERIT_SCALAR_ASSIGNMENT_OPERATOR(SparseMatrix, *=) - // EIGEN_SPARSE_INHERIT_SCALAR_ASSIGNMENT_OPERATOR(SparseMatrix, /=) - - typedef MappedSparseMatrix Map; - using Base::IsRowMajor; - typedef CompressedStorage Storage; - enum { - Options = _Options - }; - - protected: - - typedef SparseMatrix TransposedSparseMatrix; - - Index m_outerSize; - Index m_innerSize; - Index* m_outerIndex; - CompressedStorage m_data; - - public: - - inline Index rows() const { return IsRowMajor ? m_outerSize : m_innerSize; } - inline Index cols() const { return IsRowMajor ? m_innerSize : m_outerSize; } - - inline Index innerSize() const { return m_innerSize; } - inline Index outerSize() const { return m_outerSize; } - inline Index innerNonZeros(Index j) const { return m_outerIndex[j+1]-m_outerIndex[j]; } - - inline const Scalar* _valuePtr() const { return &m_data.value(0); } - inline Scalar* _valuePtr() { return &m_data.value(0); } - - inline const Index* _innerIndexPtr() const { return &m_data.index(0); } - inline Index* _innerIndexPtr() { return &m_data.index(0); } - - inline const Index* _outerIndexPtr() const { return m_outerIndex; } - inline Index* _outerIndexPtr() { return m_outerIndex; } - - inline Storage& data() { return m_data; } - inline const Storage& data() const { return m_data; } - - inline Scalar coeff(Index row, Index col) const - { - const Index outer = IsRowMajor ? row : col; - const Index inner = IsRowMajor ? col : row; - return m_data.atInRange(m_outerIndex[outer], m_outerIndex[outer+1], inner); - } - - inline Scalar& coeffRef(Index row, Index col) - { - const Index outer = IsRowMajor ? row : col; - const Index inner = IsRowMajor ? col : row; - - Index start = m_outerIndex[outer]; - Index end = m_outerIndex[outer+1]; - eigen_assert(end>=start && "you probably called coeffRef on a non finalized matrix"); - eigen_assert(end>start && "coeffRef cannot be called on a zero coefficient"); - const Index p = m_data.searchLowerIndex(start,end-1,inner); - eigen_assert((p(m_data.size()); } - - /** Preallocates \a reserveSize non zeros */ - inline void reserve(Index reserveSize) - { - m_data.reserve(reserveSize); - } - - //--- low level purely coherent filling --- - - /** \returns a reference to the non zero coefficient at position \a row, \a col assuming that: - * - the nonzero does not already exist - * - the new coefficient is the last one according to the storage order - * - * Before filling a given inner vector you must call the statVec(Index) function. - * - * After an insertion session, you should call the finalize() function. - * - * \sa insert, insertBackByOuterInner, startVec */ - inline Scalar& insertBack(Index row, Index col) - { - return insertBackByOuterInner(IsRowMajor?row:col, IsRowMajor?col:row); - } - - /** \sa insertBack, startVec */ - inline Scalar& insertBackByOuterInner(Index outer, Index inner) - { - eigen_assert(size_t(m_outerIndex[outer+1]) == m_data.size() && "Invalid ordered insertion (invalid outer index)"); - eigen_assert( (m_outerIndex[outer+1]-m_outerIndex[outer]==0 || m_data.index(m_data.size()-1)=0 && m_outerIndex[previousOuter]==0) - { - m_outerIndex[previousOuter] = static_cast(m_data.size()); - --previousOuter; - } - m_outerIndex[outer+1] = m_outerIndex[outer]; - } - - // here we have to handle the tricky case where the outerIndex array - // starts with: [ 0 0 0 0 0 1 ...] and we are inserting in, e.g., - // the 2nd inner vector... - bool isLastVec = (!(previousOuter==-1 && m_data.size()!=0)) - && (size_t(m_outerIndex[outer+1]) == m_data.size()); - - size_t startId = m_outerIndex[outer]; - // FIXME let's make sure sizeof(long int) == sizeof(size_t) - size_t p = m_outerIndex[outer+1]; - ++m_outerIndex[outer+1]; - - float reallocRatio = 1; - if (m_data.allocatedSize()<=m_data.size()) - { - // if there is no preallocated memory, let's reserve a minimum of 32 elements - if (m_data.size()==0) - { - m_data.reserve(32); - } - else - { - // we need to reallocate the data, to reduce multiple reallocations - // we use a smart resize algorithm based on the current filling ratio - // in addition, we use float to avoid integers overflows - float nnzEstimate = float(m_outerIndex[outer])*float(m_outerSize)/float(outer+1); - reallocRatio = (nnzEstimate-float(m_data.size()))/float(m_data.size()); - // furthermore we bound the realloc ratio to: - // 1) reduce multiple minor realloc when the matrix is almost filled - // 2) avoid to allocate too much memory when the matrix is almost empty - reallocRatio = (std::min)((std::max)(reallocRatio,1.5f),8.f); - } - } - m_data.resize(m_data.size()+1,reallocRatio); - - if (!isLastVec) - { - if (previousOuter==-1) - { - // oops wrong guess. - // let's correct the outer offsets - for (Index k=0; k<=(outer+1); ++k) - m_outerIndex[k] = 0; - Index k=outer+1; - while(m_outerIndex[k]==0) - m_outerIndex[k++] = 1; - while (k<=m_outerSize && m_outerIndex[k]!=0) - m_outerIndex[k++]++; - p = 0; - --k; - k = m_outerIndex[k]-1; - while (k>0) - { - m_data.index(k) = m_data.index(k-1); - m_data.value(k) = m_data.value(k-1); - k--; - } - } - else - { - // we are not inserting into the last inner vec - // update outer indices: - Index j = outer+2; - while (j<=m_outerSize && m_outerIndex[j]!=0) - m_outerIndex[j++]++; - --j; - // shift data of last vecs: - Index k = m_outerIndex[j]-1; - while (k>=Index(p)) - { - m_data.index(k) = m_data.index(k-1); - m_data.value(k) = m_data.value(k-1); - k--; - } - } - } - - while ( (p > startId) && (m_data.index(p-1) > inner) ) - { - m_data.index(p) = m_data.index(p-1); - m_data.value(p) = m_data.value(p-1); - --p; - } - - m_data.index(p) = inner; - return (m_data.value(p) = 0); - } - - - - - /** Must be called after inserting a set of non zero entries. - */ - inline void finalize() - { - Index size = static_cast(m_data.size()); - Index i = m_outerSize; - // find the last filled column - while (i>=0 && m_outerIndex[i]==0) - --i; - ++i; - while (i<=m_outerSize) - { - m_outerIndex[i] = size; - ++i; - } - } - - /** Suppress all nonzeros which are smaller than \a reference under the tolerence \a epsilon */ - void prune(Scalar reference, RealScalar epsilon = NumTraits::dummy_precision()) - { - prune(default_prunning_func(reference,epsilon)); - } - - /** Suppress all nonzeros which do not satisfy the predicate \a keep. - * The functor type \a KeepFunc must implement the following function: - * \code - * bool operator() (const Index& row, const Index& col, const Scalar& value) const; - * \endcode - * \sa prune(Scalar,RealScalar) - */ - template - void prune(const KeepFunc& keep = KeepFunc()) - { - Index k = 0; - for(Index j=0; j - inline SparseMatrix(const SparseMatrixBase& other) - : m_outerSize(0), m_innerSize(0), m_outerIndex(0) - { - *this = other.derived(); - } - - /** Copy constructor */ - inline SparseMatrix(const SparseMatrix& other) - : Base(), m_outerSize(0), m_innerSize(0), m_outerIndex(0) - { - *this = other.derived(); - } - - /** Swap the content of two sparse matrices of same type (optimization) */ - inline void swap(SparseMatrix& other) - { - //EIGEN_DBG_SPARSE(std::cout << "SparseMatrix:: swap\n"); - std::swap(m_outerIndex, other.m_outerIndex); - std::swap(m_innerSize, other.m_innerSize); - std::swap(m_outerSize, other.m_outerSize); - m_data.swap(other.m_data); - } - - inline SparseMatrix& operator=(const SparseMatrix& other) - { -// std::cout << "SparseMatrix& operator=(const SparseMatrix& other)\n"; - if (other.isRValue()) - { - swap(other.const_cast_derived()); - } - else - { - resize(other.rows(), other.cols()); - memcpy(m_outerIndex, other.m_outerIndex, (m_outerSize+1)*sizeof(Index)); - m_data = other.m_data; - } - return *this; - } - - #ifndef EIGEN_PARSED_BY_DOXYGEN - template - inline SparseMatrix& operator=(const SparseSparseProduct& product) - { return Base::operator=(product); } - - template - inline SparseMatrix& operator=(const ReturnByValue& other) - { return Base::operator=(other); } - - template - inline SparseMatrix& operator=(const EigenBase& other) - { return Base::operator=(other); } - #endif - - template - EIGEN_DONT_INLINE SparseMatrix& operator=(const SparseMatrixBase& other) - { - const bool needToTranspose = (Flags & RowMajorBit) != (OtherDerived::Flags & RowMajorBit); - if (needToTranspose) - { - // two passes algorithm: - // 1 - compute the number of coeffs per dest inner vector - // 2 - do the actual copy/eval - // Since each coeff of the rhs has to be evaluated twice, let's evaluate it if needed - typedef typename internal::nested::type OtherCopy; - typedef typename internal::remove_all::type _OtherCopy; - OtherCopy otherCopy(other.derived()); - - resize(other.rows(), other.cols()); - Eigen::Map > (m_outerIndex,outerSize()).setZero(); - // pass 1 - // FIXME the above copy could be merged with that pass - for (Index j=0; j::operator=(other.derived()); - } - } - - friend std::ostream & operator << (std::ostream & s, const SparseMatrix& m) - { - EIGEN_DBG_SPARSE( - s << "Nonzero entries:\n"; - for (Index i=0; i&>(m); - return s; - } - - /** Destructor */ - inline ~SparseMatrix() - { - delete[] m_outerIndex; - } - - /** Overloaded for performance */ - Scalar sum() const; - - public: - - /** \deprecated use setZero() and reserve() - * Initializes the filling process of \c *this. - * \param reserveSize approximate number of nonzeros - * Note that the matrix \c *this is zero-ed. - */ - EIGEN_DEPRECATED void startFill(Index reserveSize = 1000) - { - setZero(); - m_data.reserve(reserveSize); - } - - /** \deprecated use insert() - * Like fill() but with random inner coordinates. - */ - EIGEN_DEPRECATED Scalar& fillrand(Index row, Index col) - { - return insert(row,col); - } - - /** \deprecated use insert() - */ - EIGEN_DEPRECATED Scalar& fill(Index row, Index col) - { - const Index outer = IsRowMajor ? row : col; - const Index inner = IsRowMajor ? col : row; - - if (m_outerIndex[outer+1]==0) - { - // we start a new inner vector - Index i = outer; - while (i>=0 && m_outerIndex[i]==0) - { - m_outerIndex[i] = m_data.size(); - --i; - } - m_outerIndex[outer+1] = m_outerIndex[outer]; - } - else - { - eigen_assert(m_data.index(m_data.size()-1) -class SparseMatrix::InnerIterator -{ - public: - InnerIterator(const SparseMatrix& mat, Index outer) - : m_values(mat._valuePtr()), m_indices(mat._innerIndexPtr()), m_outer(outer), m_id(mat.m_outerIndex[outer]), m_end(mat.m_outerIndex[outer+1]) - {} - - inline InnerIterator& operator++() { m_id++; return *this; } - - inline const Scalar& value() const { return m_values[m_id]; } - inline Scalar& valueRef() { return const_cast(m_values[m_id]); } - - inline Index index() const { return m_indices[m_id]; } - inline Index outer() const { return m_outer; } - inline Index row() const { return IsRowMajor ? m_outer : index(); } - inline Index col() const { return IsRowMajor ? index() : m_outer; } - - inline operator bool() const { return (m_id < m_end); } - - protected: - const Scalar* m_values; - const Index* m_indices; - const Index m_outer; - Index m_id; - const Index m_end; -}; - -#endif // EIGEN_SPARSEMATRIX_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseSparseProduct.h b/gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseSparseProduct.h deleted file mode 100644 index 19abcd1f8..000000000 --- a/gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseSparseProduct.h +++ /dev/null @@ -1,401 +0,0 @@ -// This file is part of Eigen, a lightweight C++ template library -// for linear algebra. -// -// Copyright (C) 2008-2010 Gael Guennebaud -// -// Eigen is free software; you can redistribute it and/or -// modify it under the terms of the GNU Lesser General Public -// License as published by the Free Software Foundation; either -// version 3 of the License, or (at your option) any later version. -// -// Alternatively, you can redistribute it and/or -// modify it under the terms of the GNU General Public License as -// published by the Free Software Foundation; either version 2 of -// the License, or (at your option) any later version. -// -// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY -// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS -// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the -// GNU General Public License for more details. -// -// You should have received a copy of the GNU Lesser General Public -// License and a copy of the GNU General Public License along with -// Eigen. If not, see . - -#ifndef EIGEN_SPARSESPARSEPRODUCT_H -#define EIGEN_SPARSESPARSEPRODUCT_H - -namespace internal { - -template -static void sparse_product_impl2(const Lhs& lhs, const Rhs& rhs, ResultType& res) -{ - typedef typename remove_all::type::Scalar Scalar; - typedef typename remove_all::type::Index Index; - - // make sure to call innerSize/outerSize since we fake the storage order. - Index rows = lhs.innerSize(); - Index cols = rhs.outerSize(); - eigen_assert(lhs.outerSize() == rhs.innerSize()); - - std::vector mask(rows,false); - Matrix values(rows); - Matrix indices(rows); - - // estimate the number of non zero entries - float ratioLhs = float(lhs.nonZeros())/(float(lhs.rows())*float(lhs.cols())); - float avgNnzPerRhsColumn = float(rhs.nonZeros())/float(cols); - float ratioRes = (std::min)(ratioLhs * avgNnzPerRhsColumn, 1.f); - -// int t200 = rows/(log2(200)*1.39); -// int t = (rows*100)/139; - - res.resize(rows, cols); - res.reserve(Index(ratioRes*rows*cols)); - // we compute each column of the result, one after the other - for (Index j=0; j use a quick sort - // otherwise => loop through the entire vector - // In order to avoid to perform an expensive log2 when the - // result is clearly very sparse we use a linear bound up to 200. -// if((nnz<200 && nnz1) std::sort(indices.data(),indices.data()+nnz); -// for(int k=0; k -static void sparse_product_impl(const Lhs& lhs, const Rhs& rhs, ResultType& res) -{ -// return sparse_product_impl2(lhs,rhs,res); - - typedef typename remove_all::type::Scalar Scalar; - typedef typename remove_all::type::Index Index; - - // make sure to call innerSize/outerSize since we fake the storage order. - Index rows = lhs.innerSize(); - Index cols = rhs.outerSize(); - //int size = lhs.outerSize(); - eigen_assert(lhs.outerSize() == rhs.innerSize()); - - // allocate a temporary buffer - AmbiVector tempVector(rows); - - // estimate the number of non zero entries - float ratioLhs = float(lhs.nonZeros())/(float(lhs.rows())*float(lhs.cols())); - float avgNnzPerRhsColumn = float(rhs.nonZeros())/float(cols); - float ratioRes = (std::min)(ratioLhs * avgNnzPerRhsColumn, 1.f); - - // mimics a resizeByInnerOuter: - if(ResultType::IsRowMajor) - res.resize(cols, rows); - else - res.resize(rows, cols); - - res.reserve(Index(ratioRes*rows*cols)); - for (Index j=0; j::Iterator it(tempVector); it; ++it) - res.insertBackByOuterInner(j,it.index()) = it.value(); - } - res.finalize(); -} - -template::Flags&RowMajorBit, - int RhsStorageOrder = traits::Flags&RowMajorBit, - int ResStorageOrder = traits::Flags&RowMajorBit> -struct sparse_product_selector; - -template -struct sparse_product_selector -{ - typedef typename traits::type>::Scalar Scalar; - - static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res) - { -// std::cerr << __LINE__ << "\n"; - typename remove_all::type _res(res.rows(), res.cols()); - sparse_product_impl(lhs, rhs, _res); - res.swap(_res); - } -}; - -template -struct sparse_product_selector -{ - static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res) - { -// std::cerr << __LINE__ << "\n"; - // we need a col-major matrix to hold the result - typedef SparseMatrix SparseTemporaryType; - SparseTemporaryType _res(res.rows(), res.cols()); - sparse_product_impl(lhs, rhs, _res); - res = _res; - } -}; - -template -struct sparse_product_selector -{ - static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res) - { -// std::cerr << __LINE__ << "\n"; - // let's transpose the product to get a column x column product - typename remove_all::type _res(res.rows(), res.cols()); - sparse_product_impl(rhs, lhs, _res); - res.swap(_res); - } -}; - -template -struct sparse_product_selector -{ - static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res) - { -// std::cerr << "here...\n"; - typedef SparseMatrix ColMajorMatrix; - ColMajorMatrix colLhs(lhs); - ColMajorMatrix colRhs(rhs); -// std::cerr << "more...\n"; - sparse_product_impl(colLhs, colRhs, res); -// std::cerr << "OK.\n"; - - // let's transpose the product to get a column x column product - -// typedef SparseMatrix SparseTemporaryType; -// SparseTemporaryType _res(res.cols(), res.rows()); -// sparse_product_impl(rhs, lhs, _res); -// res = _res.transpose(); - } -}; - -// NOTE the 2 others cases (col row *) must never occur since they are caught -// by ProductReturnType which transforms it to (col col *) by evaluating rhs. - -} // end namespace internal - -// sparse = sparse * sparse -template -template -inline Derived& SparseMatrixBase::operator=(const SparseSparseProduct& product) -{ -// std::cerr << "there..." << typeid(Lhs).name() << " " << typeid(Lhs).name() << " " << (Derived::Flags&&RowMajorBit) << "\n"; - internal::sparse_product_selector< - typename internal::remove_all::type, - typename internal::remove_all::type, - Derived>::run(product.lhs(),product.rhs(),derived()); - return derived(); -} - -namespace internal { - -template::Flags&RowMajorBit, - int RhsStorageOrder = traits::Flags&RowMajorBit, - int ResStorageOrder = traits::Flags&RowMajorBit> -struct sparse_product_selector2; - -template -struct sparse_product_selector2 -{ - typedef typename traits::type>::Scalar Scalar; - - static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res) - { - sparse_product_impl2(lhs, rhs, res); - } -}; - -template -struct sparse_product_selector2 -{ - static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res) - { - // prevent warnings until the code is fixed - EIGEN_UNUSED_VARIABLE(lhs); - EIGEN_UNUSED_VARIABLE(rhs); - EIGEN_UNUSED_VARIABLE(res); - -// typedef SparseMatrix RowMajorMatrix; -// RowMajorMatrix rhsRow = rhs; -// RowMajorMatrix resRow(res.rows(), res.cols()); -// sparse_product_impl2(rhsRow, lhs, resRow); -// res = resRow; - } -}; - -template -struct sparse_product_selector2 -{ - static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res) - { - typedef SparseMatrix RowMajorMatrix; - RowMajorMatrix lhsRow = lhs; - RowMajorMatrix resRow(res.rows(), res.cols()); - sparse_product_impl2(rhs, lhsRow, resRow); - res = resRow; - } -}; - -template -struct sparse_product_selector2 -{ - static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res) - { - typedef SparseMatrix RowMajorMatrix; - RowMajorMatrix resRow(res.rows(), res.cols()); - sparse_product_impl2(rhs, lhs, resRow); - res = resRow; - } -}; - - -template -struct sparse_product_selector2 -{ - typedef typename traits::type>::Scalar Scalar; - - static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res) - { - typedef SparseMatrix ColMajorMatrix; - ColMajorMatrix resCol(res.rows(), res.cols()); - sparse_product_impl2(lhs, rhs, resCol); - res = resCol; - } -}; - -template -struct sparse_product_selector2 -{ - static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res) - { - typedef SparseMatrix ColMajorMatrix; - ColMajorMatrix lhsCol = lhs; - ColMajorMatrix resCol(res.rows(), res.cols()); - sparse_product_impl2(lhsCol, rhs, resCol); - res = resCol; - } -}; - -template -struct sparse_product_selector2 -{ - static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res) - { - typedef SparseMatrix ColMajorMatrix; - ColMajorMatrix rhsCol = rhs; - ColMajorMatrix resCol(res.rows(), res.cols()); - sparse_product_impl2(lhs, rhsCol, resCol); - res = resCol; - } -}; - -template -struct sparse_product_selector2 -{ - static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res) - { - typedef SparseMatrix ColMajorMatrix; -// ColMajorMatrix lhsTr(lhs); -// ColMajorMatrix rhsTr(rhs); -// ColMajorMatrix aux(res.rows(), res.cols()); -// sparse_product_impl2(rhs, lhs, aux); -// // ColMajorMatrix aux2 = aux.transpose(); -// res = aux; - typedef SparseMatrix ColMajorMatrix; - ColMajorMatrix lhsCol(lhs); - ColMajorMatrix rhsCol(rhs); - ColMajorMatrix resCol(res.rows(), res.cols()); - sparse_product_impl2(lhsCol, rhsCol, resCol); - res = resCol; - } -}; - -} // end namespace internal - -template -template -inline void SparseMatrixBase::_experimentalNewProduct(const Lhs& lhs, const Rhs& rhs) -{ - //derived().resize(lhs.rows(), rhs.cols()); - internal::sparse_product_selector2< - typename internal::remove_all::type, - typename internal::remove_all::type, - Derived>::run(lhs,rhs,derived()); -} - -// sparse * sparse -template -template -inline const typename SparseSparseProductReturnType::Type -SparseMatrixBase::operator*(const SparseMatrixBase &other) const -{ - return typename SparseSparseProductReturnType::Type(derived(), other.derived()); -} - -#endif // EIGEN_SPARSESPARSEPRODUCT_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseTriangularView.h b/gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseTriangularView.h deleted file mode 100644 index 319eaf066..000000000 --- a/gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseTriangularView.h +++ /dev/null @@ -1,100 +0,0 @@ -// This file is part of Eigen, a lightweight C++ template library -// for linear algebra. -// -// Copyright (C) 2009 Gael Guennebaud -// -// Eigen is free software; you can redistribute it and/or -// modify it under the terms of the GNU Lesser General Public -// License as published by the Free Software Foundation; either -// version 3 of the License, or (at your option) any later version. -// -// Alternatively, you can redistribute it and/or -// modify it under the terms of the GNU General Public License as -// published by the Free Software Foundation; either version 2 of -// the License, or (at your option) any later version. -// -// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY -// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS -// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the -// GNU General Public License for more details. -// -// You should have received a copy of the GNU Lesser General Public -// License and a copy of the GNU General Public License along with -// Eigen. If not, see . - -#ifndef EIGEN_SPARSE_TRIANGULARVIEW_H -#define EIGEN_SPARSE_TRIANGULARVIEW_H - -namespace internal { - -template -struct traits > -: public traits -{}; - -} // namespace internal - -template class SparseTriangularView - : public SparseMatrixBase > -{ - enum { SkipFirst = (Mode==Lower && !(MatrixType::Flags&RowMajorBit)) - || (Mode==Upper && (MatrixType::Flags&RowMajorBit)) }; - public: - - EIGEN_SPARSE_PUBLIC_INTERFACE(SparseTriangularView) - - class InnerIterator; - - inline Index rows() const { return m_matrix.rows(); } - inline Index cols() const { return m_matrix.cols(); } - - typedef typename internal::conditional::ret, - MatrixType, const MatrixType&>::type MatrixTypeNested; - - inline SparseTriangularView(const MatrixType& matrix) : m_matrix(matrix) {} - - /** \internal */ - inline const MatrixType& nestedExpression() const { return m_matrix; } - - template - typename internal::plain_matrix_type_column_major::type - solve(const MatrixBase& other) const; - - template void solveInPlace(MatrixBase& other) const; - template void solveInPlace(SparseMatrixBase& other) const; - - protected: - MatrixTypeNested m_matrix; -}; - -template -class SparseTriangularView::InnerIterator : public MatrixType::InnerIterator -{ - typedef typename MatrixType::InnerIterator Base; - public: - - EIGEN_STRONG_INLINE InnerIterator(const SparseTriangularView& view, Index outer) - : Base(view.nestedExpression(), outer) - { - if(SkipFirst) - while((*this) && this->index()index() <= this->outer()); - } -}; - -template -template -inline const SparseTriangularView -SparseMatrixBase::triangularView() const -{ - return derived(); -} - -#endif // EIGEN_SPARSE_TRIANGULARVIEW_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/SparseCholesky/CMakeLists.txt b/gtsam/3rdparty/Eigen/Eigen/src/SparseCholesky/CMakeLists.txt new file mode 100644 index 000000000..375a59d7a --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/src/SparseCholesky/CMakeLists.txt @@ -0,0 +1,6 @@ +FILE(GLOB Eigen_SparseCholesky_SRCS "*.h") + +INSTALL(FILES + ${Eigen_SparseCholesky_SRCS} + DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/SparseCholesky COMPONENT Devel + ) diff --git a/gtsam/3rdparty/Eigen/Eigen/src/SparseCholesky/SimplicialCholesky.h b/gtsam/3rdparty/Eigen/Eigen/src/SparseCholesky/SimplicialCholesky.h new file mode 100644 index 000000000..e5d98933f --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/src/SparseCholesky/SimplicialCholesky.h @@ -0,0 +1,886 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2008-2010 Gael Guennebaud +// +// Eigen is free software; you can redistribute it and/or +// modify it under the terms of the GNU Lesser General Public +// License as published by the Free Software Foundation; either +// version 3 of the License, or (at your option) any later version. +// +// Alternatively, you can redistribute it and/or +// modify it under the terms of the GNU General Public License as +// published by the Free Software Foundation; either version 2 of +// the License, or (at your option) any later version. +// +// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY +// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the +// GNU General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public +// License and a copy of the GNU General Public License along with +// Eigen. If not, see . + +/* + +NOTE: the _symbolic, and _numeric functions has been adapted from + the LDL library: + +LDL Copyright (c) 2005 by Timothy A. Davis. All Rights Reserved. + +LDL License: + + Your use or distribution of LDL or any modified version of + LDL implies that you agree to this License. + + This library is free software; you can redistribute it and/or + modify it under the terms of the GNU Lesser General Public + License as published by the Free Software Foundation; either + version 2.1 of the License, or (at your option) any later version. + + This library is distributed in the hope that it will be useful, + but WITHOUT ANY WARRANTY; without even the implied warranty of + MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU + Lesser General Public License for more details. + + You should have received a copy of the GNU Lesser General Public + License along with this library; if not, write to the Free Software + Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 + USA + + Permission is hereby granted to use or copy this program under the + terms of the GNU LGPL, provided that the Copyright, this License, + and the Availability of the original version is retained on all copies. + User documentation of any code that uses this code or any modified + version of this code must cite the Copyright, this License, the + Availability note, and "Used by permission." Permission to modify + the code and to distribute modified code is granted, provided the + Copyright, this License, and the Availability note are retained, + and a notice that the code was modified is included. + */ + +#ifndef EIGEN_SIMPLICIAL_CHOLESKY_H +#define EIGEN_SIMPLICIAL_CHOLESKY_H + +namespace Eigen { + +enum SimplicialCholeskyMode { + SimplicialCholeskyLLT, + SimplicialCholeskyLDLT +}; + +/** \ingroup SparseCholesky_Module + * \brief A direct sparse Cholesky factorizations + * + * These classes provide LL^T and LDL^T Cholesky factorizations of sparse matrices that are + * selfadjoint and positive definite. The factorization allows for solving A.X = B where + * X and B can be either dense or sparse. + * + * In order to reduce the fill-in, a symmetric permutation P is applied prior to the factorization + * such that the factorized matrix is P A P^-1. + * + * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<> + * \tparam _UpLo the triangular part that will be used for the computations. It can be Lower + * or Upper. Default is Lower. + * + */ +template +class SimplicialCholeskyBase : internal::noncopyable +{ + public: + typedef typename internal::traits::MatrixType MatrixType; + enum { UpLo = internal::traits::UpLo }; + typedef typename MatrixType::Scalar Scalar; + typedef typename MatrixType::RealScalar RealScalar; + typedef typename MatrixType::Index Index; + typedef SparseMatrix CholMatrixType; + typedef Matrix VectorType; + + public: + + /** Default constructor */ + SimplicialCholeskyBase() + : m_info(Success), m_isInitialized(false), m_shiftOffset(0), m_shiftScale(1) + {} + + SimplicialCholeskyBase(const MatrixType& matrix) + : m_info(Success), m_isInitialized(false), m_shiftOffset(0), m_shiftScale(1) + { + derived().compute(matrix); + } + + ~SimplicialCholeskyBase() + { + } + + Derived& derived() { return *static_cast(this); } + const Derived& derived() const { return *static_cast(this); } + + inline Index cols() const { return m_matrix.cols(); } + inline Index rows() const { return m_matrix.rows(); } + + /** \brief Reports whether previous computation was successful. + * + * \returns \c Success if computation was succesful, + * \c NumericalIssue if the matrix.appears to be negative. + */ + ComputationInfo info() const + { + eigen_assert(m_isInitialized && "Decomposition is not initialized."); + return m_info; + } + + /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A. + * + * \sa compute() + */ + template + inline const internal::solve_retval + solve(const MatrixBase& b) const + { + eigen_assert(m_isInitialized && "Simplicial LLT or LDLT is not initialized."); + eigen_assert(rows()==b.rows() + && "SimplicialCholeskyBase::solve(): invalid number of rows of the right hand side matrix b"); + return internal::solve_retval(*this, b.derived()); + } + + /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A. + * + * \sa compute() + */ + template + inline const internal::sparse_solve_retval + solve(const SparseMatrixBase& b) const + { + eigen_assert(m_isInitialized && "Simplicial LLT or LDLT is not initialized."); + eigen_assert(rows()==b.rows() + && "SimplicialCholesky::solve(): invalid number of rows of the right hand side matrix b"); + return internal::sparse_solve_retval(*this, b.derived()); + } + + /** \returns the permutation P + * \sa permutationPinv() */ + const PermutationMatrix& permutationP() const + { return m_P; } + + /** \returns the inverse P^-1 of the permutation P + * \sa permutationP() */ + const PermutationMatrix& permutationPinv() const + { return m_Pinv; } + + /** Sets the shift parameters that will be used to adjust the diagonal coefficients during the numerical factorization. + * + * During the numerical factorization, the diagonal coefficients are transformed by the following linear model:\n + * \c d_ii = \a offset + \a scale * \c d_ii + * + * The default is the identity transformation with \a offset=0, and \a scale=1. + * + * \returns a reference to \c *this. + */ + Derived& setShift(const RealScalar& offset, const RealScalar& scale = 1) + { + m_shiftOffset = offset; + m_shiftScale = scale; + return derived(); + } + +#ifndef EIGEN_PARSED_BY_DOXYGEN + /** \internal */ + template + void dumpMemory(Stream& s) + { + int total = 0; + s << " L: " << ((total+=(m_matrix.cols()+1) * sizeof(int) + m_matrix.nonZeros()*(sizeof(int)+sizeof(Scalar))) >> 20) << "Mb" << "\n"; + s << " diag: " << ((total+=m_diag.size() * sizeof(Scalar)) >> 20) << "Mb" << "\n"; + s << " tree: " << ((total+=m_parent.size() * sizeof(int)) >> 20) << "Mb" << "\n"; + s << " nonzeros: " << ((total+=m_nonZerosPerCol.size() * sizeof(int)) >> 20) << "Mb" << "\n"; + s << " perm: " << ((total+=m_P.size() * sizeof(int)) >> 20) << "Mb" << "\n"; + s << " perm^-1: " << ((total+=m_Pinv.size() * sizeof(int)) >> 20) << "Mb" << "\n"; + s << " TOTAL: " << (total>> 20) << "Mb" << "\n"; + } + + /** \internal */ + template + void _solve(const MatrixBase &b, MatrixBase &dest) const + { + eigen_assert(m_factorizationIsOk && "The decomposition is not in a valid state for solving, you must first call either compute() or symbolic()/numeric()"); + eigen_assert(m_matrix.rows()==b.rows()); + + if(m_info!=Success) + return; + + if(m_P.size()>0) + dest = m_P * b; + else + dest = b; + + if(m_matrix.nonZeros()>0) // otherwise L==I + derived().matrixL().solveInPlace(dest); + + if(m_diag.size()>0) + dest = m_diag.asDiagonal().inverse() * dest; + + if (m_matrix.nonZeros()>0) // otherwise U==I + derived().matrixU().solveInPlace(dest); + + if(m_P.size()>0) + dest = m_Pinv * dest; + } + + /** \internal */ + template + void _solve_sparse(const Rhs& b, SparseMatrix &dest) const + { + eigen_assert(m_factorizationIsOk && "The decomposition is not in a valid state for solving, you must first call either compute() or symbolic()/numeric()"); + eigen_assert(m_matrix.rows()==b.rows()); + + // we process the sparse rhs per block of NbColsAtOnce columns temporarily stored into a dense matrix. + static const int NbColsAtOnce = 4; + int rhsCols = b.cols(); + int size = b.rows(); + Eigen::Matrix tmp(size,rhsCols); + for(int k=0; k(rhsCols-k, NbColsAtOnce); + tmp.leftCols(actualCols) = b.middleCols(k,actualCols); + tmp.leftCols(actualCols) = derived().solve(tmp.leftCols(actualCols)); + dest.middleCols(k,actualCols) = tmp.leftCols(actualCols).sparseView(); + } + } + +#endif // EIGEN_PARSED_BY_DOXYGEN + + protected: + + /** Computes the sparse Cholesky decomposition of \a matrix */ + template + void compute(const MatrixType& matrix) + { + eigen_assert(matrix.rows()==matrix.cols()); + Index size = matrix.cols(); + CholMatrixType ap(size,size); + ordering(matrix, ap); + analyzePattern_preordered(ap, DoLDLT); + factorize_preordered(ap); + } + + template + void factorize(const MatrixType& a) + { + eigen_assert(a.rows()==a.cols()); + int size = a.cols(); + CholMatrixType ap(size,size); + ap.template selfadjointView() = a.template selfadjointView().twistedBy(m_P); + factorize_preordered(ap); + } + + template + void factorize_preordered(const CholMatrixType& a); + + void analyzePattern(const MatrixType& a, bool doLDLT) + { + eigen_assert(a.rows()==a.cols()); + int size = a.cols(); + CholMatrixType ap(size,size); + ordering(a, ap); + analyzePattern_preordered(ap,doLDLT); + } + void analyzePattern_preordered(const CholMatrixType& a, bool doLDLT); + + void ordering(const MatrixType& a, CholMatrixType& ap); + + /** keeps off-diagonal entries; drops diagonal entries */ + struct keep_diag { + inline bool operator() (const Index& row, const Index& col, const Scalar&) const + { + return row!=col; + } + }; + + mutable ComputationInfo m_info; + bool m_isInitialized; + bool m_factorizationIsOk; + bool m_analysisIsOk; + + CholMatrixType m_matrix; + VectorType m_diag; // the diagonal coefficients (LDLT mode) + VectorXi m_parent; // elimination tree + VectorXi m_nonZerosPerCol; + PermutationMatrix m_P; // the permutation + PermutationMatrix m_Pinv; // the inverse permutation + + RealScalar m_shiftOffset; + RealScalar m_shiftScale; +}; + +template class SimplicialLLT; +template class SimplicialLDLT; +template class SimplicialCholesky; + +namespace internal { + +template struct traits > +{ + typedef _MatrixType MatrixType; + enum { UpLo = _UpLo }; + typedef typename MatrixType::Scalar Scalar; + typedef typename MatrixType::Index Index; + typedef SparseMatrix CholMatrixType; + typedef SparseTriangularView MatrixL; + typedef SparseTriangularView MatrixU; + static inline MatrixL getL(const MatrixType& m) { return m; } + static inline MatrixU getU(const MatrixType& m) { return m.adjoint(); } +}; + +template struct traits > +{ + typedef _MatrixType MatrixType; + enum { UpLo = _UpLo }; + typedef typename MatrixType::Scalar Scalar; + typedef typename MatrixType::Index Index; + typedef SparseMatrix CholMatrixType; + typedef SparseTriangularView MatrixL; + typedef SparseTriangularView MatrixU; + static inline MatrixL getL(const MatrixType& m) { return m; } + static inline MatrixU getU(const MatrixType& m) { return m.adjoint(); } +}; + +template struct traits > +{ + typedef _MatrixType MatrixType; + enum { UpLo = _UpLo }; +}; + +} + +/** \ingroup SparseCholesky_Module + * \class SimplicialLLT + * \brief A direct sparse LLT Cholesky factorizations + * + * This class provides a LL^T Cholesky factorizations of sparse matrices that are + * selfadjoint and positive definite. The factorization allows for solving A.X = B where + * X and B can be either dense or sparse. + * + * In order to reduce the fill-in, a symmetric permutation P is applied prior to the factorization + * such that the factorized matrix is P A P^-1. + * + * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<> + * \tparam _UpLo the triangular part that will be used for the computations. It can be Lower + * or Upper. Default is Lower. + * + * \sa class SimplicialLDLT + */ +template + class SimplicialLLT : public SimplicialCholeskyBase > +{ +public: + typedef _MatrixType MatrixType; + enum { UpLo = _UpLo }; + typedef SimplicialCholeskyBase Base; + typedef typename MatrixType::Scalar Scalar; + typedef typename MatrixType::RealScalar RealScalar; + typedef typename MatrixType::Index Index; + typedef SparseMatrix CholMatrixType; + typedef Matrix VectorType; + typedef internal::traits Traits; + typedef typename Traits::MatrixL MatrixL; + typedef typename Traits::MatrixU MatrixU; +public: + /** Default constructor */ + SimplicialLLT() : Base() {} + /** Constructs and performs the LLT factorization of \a matrix */ + SimplicialLLT(const MatrixType& matrix) + : Base(matrix) {} + + /** \returns an expression of the factor L */ + inline const MatrixL matrixL() const { + eigen_assert(Base::m_factorizationIsOk && "Simplicial LLT not factorized"); + return Traits::getL(Base::m_matrix); + } + + /** \returns an expression of the factor U (= L^*) */ + inline const MatrixU matrixU() const { + eigen_assert(Base::m_factorizationIsOk && "Simplicial LLT not factorized"); + return Traits::getU(Base::m_matrix); + } + + /** Computes the sparse Cholesky decomposition of \a matrix */ + SimplicialLLT& compute(const MatrixType& matrix) + { + Base::template compute(matrix); + return *this; + } + + /** Performs a symbolic decomposition on the sparcity of \a matrix. + * + * This function is particularly useful when solving for several problems having the same structure. + * + * \sa factorize() + */ + void analyzePattern(const MatrixType& a) + { + Base::analyzePattern(a, false); + } + + /** Performs a numeric decomposition of \a matrix + * + * The given matrix must has the same sparcity than the matrix on which the symbolic decomposition has been performed. + * + * \sa analyzePattern() + */ + void factorize(const MatrixType& a) + { + Base::template factorize(a); + } + + /** \returns the determinant of the underlying matrix from the current factorization */ + Scalar determinant() const + { + Scalar detL = Base::m_matrix.diagonal().prod(); + return internal::abs2(detL); + } +}; + +/** \ingroup SparseCholesky_Module + * \class SimplicialLDLT + * \brief A direct sparse LDLT Cholesky factorizations without square root. + * + * This class provides a LDL^T Cholesky factorizations without square root of sparse matrices that are + * selfadjoint and positive definite. The factorization allows for solving A.X = B where + * X and B can be either dense or sparse. + * + * In order to reduce the fill-in, a symmetric permutation P is applied prior to the factorization + * such that the factorized matrix is P A P^-1. + * + * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<> + * \tparam _UpLo the triangular part that will be used for the computations. It can be Lower + * or Upper. Default is Lower. + * + * \sa class SimplicialLLT + */ +template + class SimplicialLDLT : public SimplicialCholeskyBase > +{ +public: + typedef _MatrixType MatrixType; + enum { UpLo = _UpLo }; + typedef SimplicialCholeskyBase Base; + typedef typename MatrixType::Scalar Scalar; + typedef typename MatrixType::RealScalar RealScalar; + typedef typename MatrixType::Index Index; + typedef SparseMatrix CholMatrixType; + typedef Matrix VectorType; + typedef internal::traits Traits; + typedef typename Traits::MatrixL MatrixL; + typedef typename Traits::MatrixU MatrixU; +public: + /** Default constructor */ + SimplicialLDLT() : Base() {} + + /** Constructs and performs the LLT factorization of \a matrix */ + SimplicialLDLT(const MatrixType& matrix) + : Base(matrix) {} + + /** \returns a vector expression of the diagonal D */ + inline const VectorType vectorD() const { + eigen_assert(Base::m_factorizationIsOk && "Simplicial LDLT not factorized"); + return Base::m_diag; + } + /** \returns an expression of the factor L */ + inline const MatrixL matrixL() const { + eigen_assert(Base::m_factorizationIsOk && "Simplicial LDLT not factorized"); + return Traits::getL(Base::m_matrix); + } + + /** \returns an expression of the factor U (= L^*) */ + inline const MatrixU matrixU() const { + eigen_assert(Base::m_factorizationIsOk && "Simplicial LDLT not factorized"); + return Traits::getU(Base::m_matrix); + } + + /** Computes the sparse Cholesky decomposition of \a matrix */ + SimplicialLDLT& compute(const MatrixType& matrix) + { + Base::template compute(matrix); + return *this; + } + + /** Performs a symbolic decomposition on the sparcity of \a matrix. + * + * This function is particularly useful when solving for several problems having the same structure. + * + * \sa factorize() + */ + void analyzePattern(const MatrixType& a) + { + Base::analyzePattern(a, true); + } + + /** Performs a numeric decomposition of \a matrix + * + * The given matrix must has the same sparcity than the matrix on which the symbolic decomposition has been performed. + * + * \sa analyzePattern() + */ + void factorize(const MatrixType& a) + { + Base::template factorize(a); + } + + /** \returns the determinant of the underlying matrix from the current factorization */ + Scalar determinant() const + { + return Base::m_diag.prod(); + } +}; + +/** \deprecated use SimplicialLDLT or class SimplicialLLT + * \ingroup SparseCholesky_Module + * \class SimplicialCholesky + * + * \sa class SimplicialLDLT, class SimplicialLLT + */ +template + class SimplicialCholesky : public SimplicialCholeskyBase > +{ +public: + typedef _MatrixType MatrixType; + enum { UpLo = _UpLo }; + typedef SimplicialCholeskyBase Base; + typedef typename MatrixType::Scalar Scalar; + typedef typename MatrixType::RealScalar RealScalar; + typedef typename MatrixType::Index Index; + typedef SparseMatrix CholMatrixType; + typedef Matrix VectorType; + typedef internal::traits Traits; + typedef internal::traits > LDLTTraits; + typedef internal::traits > LLTTraits; + public: + SimplicialCholesky() : Base(), m_LDLT(true) {} + + SimplicialCholesky(const MatrixType& matrix) + : Base(), m_LDLT(true) + { + compute(matrix); + } + + SimplicialCholesky& setMode(SimplicialCholeskyMode mode) + { + switch(mode) + { + case SimplicialCholeskyLLT: + m_LDLT = false; + break; + case SimplicialCholeskyLDLT: + m_LDLT = true; + break; + default: + break; + } + + return *this; + } + + inline const VectorType vectorD() const { + eigen_assert(Base::m_factorizationIsOk && "Simplicial Cholesky not factorized"); + return Base::m_diag; + } + inline const CholMatrixType rawMatrix() const { + eigen_assert(Base::m_factorizationIsOk && "Simplicial Cholesky not factorized"); + return Base::m_matrix; + } + + /** Computes the sparse Cholesky decomposition of \a matrix */ + SimplicialCholesky& compute(const MatrixType& matrix) + { + if(m_LDLT) + Base::template compute(matrix); + else + Base::template compute(matrix); + return *this; + } + + /** Performs a symbolic decomposition on the sparcity of \a matrix. + * + * This function is particularly useful when solving for several problems having the same structure. + * + * \sa factorize() + */ + void analyzePattern(const MatrixType& a) + { + Base::analyzePattern(a, m_LDLT); + } + + /** Performs a numeric decomposition of \a matrix + * + * The given matrix must has the same sparcity than the matrix on which the symbolic decomposition has been performed. + * + * \sa analyzePattern() + */ + void factorize(const MatrixType& a) + { + if(m_LDLT) + Base::template factorize(a); + else + Base::template factorize(a); + } + + /** \internal */ + template + void _solve(const MatrixBase &b, MatrixBase &dest) const + { + eigen_assert(Base::m_factorizationIsOk && "The decomposition is not in a valid state for solving, you must first call either compute() or symbolic()/numeric()"); + eigen_assert(Base::m_matrix.rows()==b.rows()); + + if(Base::m_info!=Success) + return; + + if(Base::m_P.size()>0) + dest = Base::m_P * b; + else + dest = b; + + if(Base::m_matrix.nonZeros()>0) // otherwise L==I + { + if(m_LDLT) + LDLTTraits::getL(Base::m_matrix).solveInPlace(dest); + else + LLTTraits::getL(Base::m_matrix).solveInPlace(dest); + } + + if(Base::m_diag.size()>0) + dest = Base::m_diag.asDiagonal().inverse() * dest; + + if (Base::m_matrix.nonZeros()>0) // otherwise I==I + { + if(m_LDLT) + LDLTTraits::getU(Base::m_matrix).solveInPlace(dest); + else + LLTTraits::getU(Base::m_matrix).solveInPlace(dest); + } + + if(Base::m_P.size()>0) + dest = Base::m_Pinv * dest; + } + + Scalar determinant() const + { + if(m_LDLT) + { + return Base::m_diag.prod(); + } + else + { + Scalar detL = Diagonal(Base::m_matrix).prod(); + return internal::abs2(detL); + } + } + + protected: + bool m_LDLT; +}; + +template +void SimplicialCholeskyBase::ordering(const MatrixType& a, CholMatrixType& ap) +{ + eigen_assert(a.rows()==a.cols()); + const Index size = a.rows(); + // TODO allows to configure the permutation + // Note that amd compute the inverse permutation + { + CholMatrixType C; + C = a.template selfadjointView(); + // remove diagonal entries: + // seems not to be needed + // C.prune(keep_diag()); + internal::minimum_degree_ordering(C, m_Pinv); + } + + if(m_Pinv.size()>0) + m_P = m_Pinv.inverse(); + else + m_P.resize(0); + + ap.resize(size,size); + ap.template selfadjointView() = a.template selfadjointView().twistedBy(m_P); +} + +template +void SimplicialCholeskyBase::analyzePattern_preordered(const CholMatrixType& ap, bool doLDLT) +{ + const Index size = ap.rows(); + m_matrix.resize(size, size); + m_parent.resize(size); + m_nonZerosPerCol.resize(size); + + ei_declare_aligned_stack_constructed_variable(Index, tags, size, 0); + + for(Index k = 0; k < size; ++k) + { + /* L(k,:) pattern: all nodes reachable in etree from nz in A(0:k-1,k) */ + m_parent[k] = -1; /* parent of k is not yet known */ + tags[k] = k; /* mark node k as visited */ + m_nonZerosPerCol[k] = 0; /* count of nonzeros in column k of L */ + for(typename CholMatrixType::InnerIterator it(ap,k); it; ++it) + { + Index i = it.index(); + if(i < k) + { + /* follow path from i to root of etree, stop at flagged node */ + for(; tags[i] != k; i = m_parent[i]) + { + /* find parent of i if not yet determined */ + if (m_parent[i] == -1) + m_parent[i] = k; + m_nonZerosPerCol[i]++; /* L (k,i) is nonzero */ + tags[i] = k; /* mark i as visited */ + } + } + } + } + + /* construct Lp index array from m_nonZerosPerCol column counts */ + Index* Lp = m_matrix.outerIndexPtr(); + Lp[0] = 0; + for(Index k = 0; k < size; ++k) + Lp[k+1] = Lp[k] + m_nonZerosPerCol[k] + (doLDLT ? 0 : 1); + + m_matrix.resizeNonZeros(Lp[size]); + + m_isInitialized = true; + m_info = Success; + m_analysisIsOk = true; + m_factorizationIsOk = false; +} + + +template +template +void SimplicialCholeskyBase::factorize_preordered(const CholMatrixType& ap) +{ + eigen_assert(m_analysisIsOk && "You must first call analyzePattern()"); + eigen_assert(ap.rows()==ap.cols()); + const Index size = ap.rows(); + eigen_assert(m_parent.size()==size); + eigen_assert(m_nonZerosPerCol.size()==size); + + const Index* Lp = m_matrix.outerIndexPtr(); + Index* Li = m_matrix.innerIndexPtr(); + Scalar* Lx = m_matrix.valuePtr(); + + ei_declare_aligned_stack_constructed_variable(Scalar, y, size, 0); + ei_declare_aligned_stack_constructed_variable(Index, pattern, size, 0); + ei_declare_aligned_stack_constructed_variable(Index, tags, size, 0); + + bool ok = true; + m_diag.resize(DoLDLT ? size : 0); + + for(Index k = 0; k < size; ++k) + { + // compute nonzero pattern of kth row of L, in topological order + y[k] = 0.0; // Y(0:k) is now all zero + Index top = size; // stack for pattern is empty + tags[k] = k; // mark node k as visited + m_nonZerosPerCol[k] = 0; // count of nonzeros in column k of L + for(typename MatrixType::InnerIterator it(ap,k); it; ++it) + { + Index i = it.index(); + if(i <= k) + { + y[i] += internal::conj(it.value()); /* scatter A(i,k) into Y (sum duplicates) */ + Index len; + for(len = 0; tags[i] != k; i = m_parent[i]) + { + pattern[len++] = i; /* L(k,i) is nonzero */ + tags[i] = k; /* mark i as visited */ + } + while(len > 0) + pattern[--top] = pattern[--len]; + } + } + + /* compute numerical values kth row of L (a sparse triangular solve) */ + + RealScalar d = internal::real(y[k]) * m_shiftScale + m_shiftOffset; // get D(k,k), apply the shift function, and clear Y(k) + y[k] = 0.0; + for(; top < size; ++top) + { + Index i = pattern[top]; /* pattern[top:n-1] is pattern of L(:,k) */ + Scalar yi = y[i]; /* get and clear Y(i) */ + y[i] = 0.0; + + /* the nonzero entry L(k,i) */ + Scalar l_ki; + if(DoLDLT) + l_ki = yi / m_diag[i]; + else + yi = l_ki = yi / Lx[Lp[i]]; + + Index p2 = Lp[i] + m_nonZerosPerCol[i]; + Index p; + for(p = Lp[i] + (DoLDLT ? 0 : 1); p < p2; ++p) + y[Li[p]] -= internal::conj(Lx[p]) * yi; + d -= internal::real(l_ki * internal::conj(yi)); + Li[p] = k; /* store L(k,i) in column form of L */ + Lx[p] = l_ki; + ++m_nonZerosPerCol[i]; /* increment count of nonzeros in col i */ + } + if(DoLDLT) + { + m_diag[k] = d; + if(d == RealScalar(0)) + { + ok = false; /* failure, D(k,k) is zero */ + break; + } + } + else + { + Index p = Lp[k] + m_nonZerosPerCol[k]++; + Li[p] = k ; /* store L(k,k) = sqrt (d) in column k */ + if(d <= RealScalar(0)) { + ok = false; /* failure, matrix is not positive definite */ + break; + } + Lx[p] = internal::sqrt(d) ; + } + } + + m_info = ok ? Success : NumericalIssue; + m_factorizationIsOk = true; +} + +namespace internal { + +template +struct solve_retval, Rhs> + : solve_retval_base, Rhs> +{ + typedef SimplicialCholeskyBase Dec; + EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs) + + template void evalTo(Dest& dst) const + { + dec().derived()._solve(rhs(),dst); + } +}; + +template +struct sparse_solve_retval, Rhs> + : sparse_solve_retval_base, Rhs> +{ + typedef SimplicialCholeskyBase Dec; + EIGEN_MAKE_SPARSE_SOLVE_HELPERS(Dec,Rhs) + + template void evalTo(Dest& dst) const + { + dec().derived()._solve_sparse(rhs(),dst); + } +}; + +} // end namespace internal + +} // end namespace Eigen + +#endif // EIGEN_SIMPLICIAL_CHOLESKY_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Sparse/AmbiVector.h b/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/AmbiVector.h similarity index 98% rename from gtsam/3rdparty/Eigen/Eigen/src/Sparse/AmbiVector.h rename to gtsam/3rdparty/Eigen/Eigen/src/SparseCore/AmbiVector.h index 2ea8ba309..8ec63107a 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Sparse/AmbiVector.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/AmbiVector.h @@ -25,6 +25,10 @@ #ifndef EIGEN_AMBIVECTOR_H #define EIGEN_AMBIVECTOR_H +namespace Eigen { + +namespace internal { + /** \internal * Hybrid sparse/dense vector class designed for intensive read-write operations. * @@ -299,7 +303,7 @@ class AmbiVector<_Scalar,_Index>::Iterator * In practice, all coefficients having a magnitude smaller than \a epsilon * are skipped. */ - Iterator(const AmbiVector& vec, RealScalar epsilon = RealScalar(0.1)*NumTraits::dummy_precision()) + Iterator(const AmbiVector& vec, RealScalar epsilon = 0) : m_vector(vec) { m_epsilon = epsilon; @@ -315,7 +319,7 @@ class AmbiVector<_Scalar,_Index>::Iterator { ListEl* EIGEN_RESTRICT llElements = reinterpret_cast(m_vector.m_buffer); m_currentEl = m_vector.m_llStart; - while (m_currentEl>=0 && internal::abs(llElements[m_currentEl].value)=0 && internal::abs(llElements[m_currentEl].value)<=m_epsilon) m_currentEl = llElements[m_currentEl].next; if (m_currentEl<0) { @@ -375,5 +379,8 @@ class AmbiVector<_Scalar,_Index>::Iterator bool m_isDense; // mode of the vector }; +} // end namespace internal + +} // end namespace Eigen #endif // EIGEN_AMBIVECTOR_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/CMakeLists.txt b/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/CMakeLists.txt new file mode 100644 index 000000000..d860452a6 --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/CMakeLists.txt @@ -0,0 +1,6 @@ +FILE(GLOB Eigen_SparseCore_SRCS "*.h") + +INSTALL(FILES + ${Eigen_SparseCore_SRCS} + DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/SparseCore COMPONENT Devel + ) diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Sparse/CompressedStorage.h b/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/CompressedStorage.h similarity index 95% rename from gtsam/3rdparty/Eigen/Eigen/src/Sparse/CompressedStorage.h rename to gtsam/3rdparty/Eigen/Eigen/src/SparseCore/CompressedStorage.h index b3bde272e..fa2bfd763 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Sparse/CompressedStorage.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/CompressedStorage.h @@ -25,7 +25,12 @@ #ifndef EIGEN_COMPRESSED_STORAGE_H #define EIGEN_COMPRESSED_STORAGE_H -/** Stores a sparse set of values as a list of values and a list of indices. +namespace Eigen { + +namespace internal { + +/** \internal + * Stores a sparse set of values as a list of values and a list of indices. * */ template @@ -218,8 +223,8 @@ class CompressedStorage Index* newIndices = new Index[size]; size_t copySize = (std::min)(size, m_size); // copy - memcpy(newValues, m_values, copySize * sizeof(Scalar)); - memcpy(newIndices, m_indices, copySize * sizeof(Index)); + internal::smart_copy(m_values, m_values+copySize, newValues); + internal::smart_copy(m_indices, m_indices+copySize, newIndices); // delete old stuff delete[] m_values; delete[] m_indices; @@ -236,4 +241,8 @@ class CompressedStorage }; +} // end namespace internal + +} // end namespace Eigen + #endif // EIGEN_COMPRESSED_STORAGE_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/ConservativeSparseSparseProduct.h b/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/ConservativeSparseSparseProduct.h new file mode 100644 index 000000000..0fb4c1c97 --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/ConservativeSparseSparseProduct.h @@ -0,0 +1,260 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2008-2011 Gael Guennebaud +// +// Eigen is free software; you can redistribute it and/or +// modify it under the terms of the GNU Lesser General Public +// License as published by the Free Software Foundation; either +// version 3 of the License, or (at your option) any later version. +// +// Alternatively, you can redistribute it and/or +// modify it under the terms of the GNU General Public License as +// published by the Free Software Foundation; either version 2 of +// the License, or (at your option) any later version. +// +// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY +// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the +// GNU General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public +// License and a copy of the GNU General Public License along with +// Eigen. If not, see . + +#ifndef EIGEN_CONSERVATIVESPARSESPARSEPRODUCT_H +#define EIGEN_CONSERVATIVESPARSESPARSEPRODUCT_H + +namespace Eigen { + +namespace internal { + +template +static void conservative_sparse_sparse_product_impl(const Lhs& lhs, const Rhs& rhs, ResultType& res) +{ + typedef typename remove_all::type::Scalar Scalar; + typedef typename remove_all::type::Index Index; + + // make sure to call innerSize/outerSize since we fake the storage order. + Index rows = lhs.innerSize(); + Index cols = rhs.outerSize(); + eigen_assert(lhs.outerSize() == rhs.innerSize()); + + std::vector mask(rows,false); + Matrix values(rows); + Matrix indices(rows); + + // estimate the number of non zero entries + // given a rhs column containing Y non zeros, we assume that the respective Y columns + // of the lhs differs in average of one non zeros, thus the number of non zeros for + // the product of a rhs column with the lhs is X+Y where X is the average number of non zero + // per column of the lhs. + // Therefore, we have nnz(lhs*rhs) = nnz(lhs) + nnz(rhs) + Index estimated_nnz_prod = lhs.nonZeros() + rhs.nonZeros(); + + res.setZero(); + res.reserve(Index(estimated_nnz_prod)); + // we compute each column of the result, one after the other + for (Index j=0; j use a quick sort + // otherwise => loop through the entire vector + // In order to avoid to perform an expensive log2 when the + // result is clearly very sparse we use a linear bound up to 200. + //if((nnz<200 && nnz1) std::sort(indices.data(),indices.data()+nnz); + for(int k=0; k::Flags&RowMajorBit, + int RhsStorageOrder = traits::Flags&RowMajorBit, + int ResStorageOrder = traits::Flags&RowMajorBit> +struct conservative_sparse_sparse_product_selector; + +template +struct conservative_sparse_sparse_product_selector +{ + typedef typename remove_all::type LhsCleaned; + typedef typename LhsCleaned::Scalar Scalar; + + static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res) + { + typedef SparseMatrix RowMajorMatrix; + typedef SparseMatrix ColMajorMatrix; + ColMajorMatrix resCol(lhs.rows(),rhs.cols()); + internal::conservative_sparse_sparse_product_impl(lhs, rhs, resCol); + // sort the non zeros: + RowMajorMatrix resRow(resCol); + res = resRow; + } +}; + +template +struct conservative_sparse_sparse_product_selector +{ + static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res) + { + typedef SparseMatrix RowMajorMatrix; + RowMajorMatrix rhsRow = rhs; + RowMajorMatrix resRow(lhs.rows(), rhs.cols()); + internal::conservative_sparse_sparse_product_impl(rhsRow, lhs, resRow); + res = resRow; + } +}; + +template +struct conservative_sparse_sparse_product_selector +{ + static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res) + { + typedef SparseMatrix RowMajorMatrix; + RowMajorMatrix lhsRow = lhs; + RowMajorMatrix resRow(lhs.rows(), rhs.cols()); + internal::conservative_sparse_sparse_product_impl(rhs, lhsRow, resRow); + res = resRow; + } +}; + +template +struct conservative_sparse_sparse_product_selector +{ + static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res) + { + typedef SparseMatrix RowMajorMatrix; + RowMajorMatrix resRow(lhs.rows(), rhs.cols()); + internal::conservative_sparse_sparse_product_impl(rhs, lhs, resRow); + res = resRow; + } +}; + + +template +struct conservative_sparse_sparse_product_selector +{ + typedef typename traits::type>::Scalar Scalar; + + static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res) + { + typedef SparseMatrix ColMajorMatrix; + ColMajorMatrix resCol(lhs.rows(), rhs.cols()); + internal::conservative_sparse_sparse_product_impl(lhs, rhs, resCol); + res = resCol; + } +}; + +template +struct conservative_sparse_sparse_product_selector +{ + static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res) + { + typedef SparseMatrix ColMajorMatrix; + ColMajorMatrix lhsCol = lhs; + ColMajorMatrix resCol(lhs.rows(), rhs.cols()); + internal::conservative_sparse_sparse_product_impl(lhsCol, rhs, resCol); + res = resCol; + } +}; + +template +struct conservative_sparse_sparse_product_selector +{ + static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res) + { + typedef SparseMatrix ColMajorMatrix; + ColMajorMatrix rhsCol = rhs; + ColMajorMatrix resCol(lhs.rows(), rhs.cols()); + internal::conservative_sparse_sparse_product_impl(lhs, rhsCol, resCol); + res = resCol; + } +}; + +template +struct conservative_sparse_sparse_product_selector +{ + static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res) + { + typedef SparseMatrix RowMajorMatrix; + typedef SparseMatrix ColMajorMatrix; + RowMajorMatrix resRow(lhs.rows(),rhs.cols()); + internal::conservative_sparse_sparse_product_impl(rhs, lhs, resRow); + // sort the non zeros: + ColMajorMatrix resCol(resRow); + res = resCol; + } +}; + +} // end namespace internal + +} // end namespace Eigen + +#endif // EIGEN_CONSERVATIVESPARSESPARSEPRODUCT_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Sparse/CoreIterators.h b/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/CoreIterators.h similarity index 96% rename from gtsam/3rdparty/Eigen/Eigen/src/Sparse/CoreIterators.h rename to gtsam/3rdparty/Eigen/Eigen/src/SparseCore/CoreIterators.h index b4beaeee6..ea51e9231 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Sparse/CoreIterators.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/CoreIterators.h @@ -25,10 +25,13 @@ #ifndef EIGEN_COREITERATORS_H #define EIGEN_COREITERATORS_H +namespace Eigen { + /* This file contains the respective InnerIterator definition of the expressions defined in Eigen/Core */ -/** \class InnerIterator +/** \ingroup SparseCore_Module + * \class InnerIterator * \brief An InnerIterator allows to loop over the element of a sparse (or dense) matrix or expression * * todo @@ -68,4 +71,6 @@ template class DenseBase::InnerIterator const Index m_end; }; +} // end namespace Eigen + #endif // EIGEN_COREITERATORS_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Sparse/MappedSparseMatrix.h b/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/MappedSparseMatrix.h similarity index 74% rename from gtsam/3rdparty/Eigen/Eigen/src/Sparse/MappedSparseMatrix.h rename to gtsam/3rdparty/Eigen/Eigen/src/SparseCore/MappedSparseMatrix.h index 31a431fb2..fc7f9d143 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Sparse/MappedSparseMatrix.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/MappedSparseMatrix.h @@ -25,6 +25,8 @@ #ifndef EIGEN_MAPPED_SPARSEMATRIX_H #define EIGEN_MAPPED_SPARSEMATRIX_H +namespace Eigen { + /** \class MappedSparseMatrix * * \brief Sparse matrix @@ -46,9 +48,9 @@ class MappedSparseMatrix { public: EIGEN_SPARSE_PUBLIC_INTERFACE(MappedSparseMatrix) + enum { IsRowMajor = Base::IsRowMajor }; protected: - enum { IsRowMajor = Base::IsRowMajor }; Index m_outerSize; Index m_innerSize; @@ -63,18 +65,17 @@ class MappedSparseMatrix inline Index cols() const { return IsRowMajor ? m_innerSize : m_outerSize; } inline Index innerSize() const { return m_innerSize; } inline Index outerSize() const { return m_outerSize; } - inline Index innerNonZeros(Index j) const { return m_outerIndex[j+1]-m_outerIndex[j]; } //---------------------------------------- // direct access interface - inline const Scalar* _valuePtr() const { return m_values; } - inline Scalar* _valuePtr() { return m_values; } + inline const Scalar* valuePtr() const { return m_values; } + inline Scalar* valuePtr() { return m_values; } - inline const Index* _innerIndexPtr() const { return m_innerIndices; } - inline Index* _innerIndexPtr() { return m_innerIndices; } + inline const Index* innerIndexPtr() const { return m_innerIndices; } + inline Index* innerIndexPtr() { return m_innerIndices; } - inline const Index* _outerIndexPtr() const { return m_outerIndex; } - inline Index* _outerIndexPtr() { return m_outerIndex; } + inline const Index* outerIndexPtr() const { return m_outerIndex; } + inline Index* outerIndexPtr() { return m_outerIndex; } //---------------------------------------- inline Scalar coeff(Index row, Index col) const @@ -112,6 +113,7 @@ class MappedSparseMatrix } class InnerIterator; + class ReverseInnerIterator; /** \returns the number of non zero coefficients */ inline Index nonZeros() const { return m_nnz; } @@ -132,23 +134,17 @@ class MappedSparseMatrix::InnerIterator InnerIterator(const MappedSparseMatrix& mat, Index outer) : m_matrix(mat), m_outer(outer), - m_id(mat._outerIndexPtr()[outer]), + m_id(mat.outerIndexPtr()[outer]), m_start(m_id), - m_end(mat._outerIndexPtr()[outer+1]) - {} - - template - InnerIterator(const Flagged& mat, Index outer) - : m_matrix(mat._expression()), m_id(m_matrix._outerIndexPtr()[outer]), - m_start(m_id), m_end(m_matrix._outerIndexPtr()[outer+1]) + m_end(mat.outerIndexPtr()[outer+1]) {} inline InnerIterator& operator++() { m_id++; return *this; } - inline Scalar value() const { return m_matrix._valuePtr()[m_id]; } - inline Scalar& valueRef() { return const_cast(m_matrix._valuePtr()[m_id]); } + inline Scalar value() const { return m_matrix.valuePtr()[m_id]; } + inline Scalar& valueRef() { return const_cast(m_matrix.valuePtr()[m_id]); } - inline Index index() const { return m_matrix._innerIndexPtr()[m_id]; } + inline Index index() const { return m_matrix.innerIndexPtr()[m_id]; } inline Index row() const { return IsRowMajor ? m_outer : index(); } inline Index col() const { return IsRowMajor ? index() : m_outer; } @@ -162,4 +158,37 @@ class MappedSparseMatrix::InnerIterator const Index m_end; }; +template +class MappedSparseMatrix::ReverseInnerIterator +{ + public: + ReverseInnerIterator(const MappedSparseMatrix& mat, Index outer) + : m_matrix(mat), + m_outer(outer), + m_id(mat.outerIndexPtr()[outer+1]), + m_start(mat.outerIndexPtr()[outer]), + m_end(m_id) + {} + + inline ReverseInnerIterator& operator--() { m_id--; return *this; } + + inline Scalar value() const { return m_matrix.valuePtr()[m_id-1]; } + inline Scalar& valueRef() { return const_cast(m_matrix.valuePtr()[m_id-1]); } + + inline Index index() const { return m_matrix.innerIndexPtr()[m_id-1]; } + inline Index row() const { return IsRowMajor ? m_outer : index(); } + inline Index col() const { return IsRowMajor ? index() : m_outer; } + + inline operator bool() const { return (m_id <= m_end) && (m_id>m_start); } + + protected: + const MappedSparseMatrix& m_matrix; + const Index m_outer; + Index m_id; + const Index m_start; + const Index m_end; +}; + +} // end namespace Eigen + #endif // EIGEN_MAPPED_SPARSEMATRIX_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseAssign.h b/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseAssign.h similarity index 100% rename from gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseAssign.h rename to gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseAssign.h diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseBlock.h b/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseBlock.h similarity index 71% rename from gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseBlock.h rename to gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseBlock.h index 8079c9999..189538f39 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseBlock.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseBlock.h @@ -25,6 +25,8 @@ #ifndef EIGEN_SPARSE_BLOCK_H #define EIGEN_SPARSE_BLOCK_H +namespace Eigen { + namespace internal { template struct traits > @@ -65,6 +67,17 @@ class SparseInnerVectorSet : internal::no_assignment_operator, protected: Index m_outer; }; + class ReverseInnerIterator: public MatrixType::ReverseInnerIterator + { + public: + inline ReverseInnerIterator(const SparseInnerVectorSet& xpr, Index outer) + : MatrixType::ReverseInnerIterator(xpr.m_matrix, xpr.m_outerStart + outer), m_outer(outer) + {} + inline Index row() const { return IsRowMajor ? m_outer : this->index(); } + inline Index col() const { return IsRowMajor ? this->index() : m_outer; } + protected: + Index m_outer; + }; inline SparseInnerVectorSet(const MatrixType& matrix, Index outerStart, Index outerSize) : m_matrix(matrix), m_outerStart(outerStart), m_outerSize(outerSize) @@ -101,15 +114,16 @@ class SparseInnerVectorSet : internal::no_assignment_operator, const internal::variable_if_dynamic m_outerSize; }; + /*************************************************************************** -* specialisation for DynamicSparseMatrix +* specialisation for SparseMatrix ***************************************************************************/ -template -class SparseInnerVectorSet, Size> - : public SparseMatrixBase, Size> > +template +class SparseInnerVectorSet, Size> + : public SparseMatrixBase, Size> > { - typedef DynamicSparseMatrix<_Scalar, _Options> MatrixType; + typedef SparseMatrix<_Scalar, _Options, _Index> MatrixType; public: enum { IsRowMajor = internal::traits::IsRowMajor }; @@ -126,98 +140,11 @@ class SparseInnerVectorSet, Size> protected: Index m_outer; }; - - inline SparseInnerVectorSet(const MatrixType& matrix, Index outerStart, Index outerSize) - : m_matrix(matrix), m_outerStart(outerStart), m_outerSize(outerSize) - { - eigen_assert( (outerStart>=0) && ((outerStart+outerSize)<=matrix.outerSize()) ); - } - - inline SparseInnerVectorSet(const MatrixType& matrix, Index outer) - : m_matrix(matrix), m_outerStart(outer), m_outerSize(Size) - { - eigen_assert(Size!=Dynamic); - eigen_assert( (outer>=0) && (outer - inline SparseInnerVectorSet& operator=(const SparseMatrixBase& other) - { - if (IsRowMajor != ((OtherDerived::Flags&RowMajorBit)==RowMajorBit)) - { - // need to transpose => perform a block evaluation followed by a big swap - DynamicSparseMatrix aux(other); - *this = aux.markAsRValue(); - } - else - { - // evaluate/copy vector per vector - for (Index j=0; j aux(other.innerVector(j)); - m_matrix.const_cast_derived()._data()[m_outerStart+j].swap(aux._data()); - } - } - return *this; - } - - inline SparseInnerVectorSet& operator=(const SparseInnerVectorSet& other) - { - return operator=(other); - } - - Index nonZeros() const - { - Index count = 0; - for (Index j=0; j0); - return m_matrix.data()[m_outerStart].vale(m_matrix.data()[m_outerStart].size()-1); - } - -// template -// inline SparseInnerVectorSet& operator=(const SparseMatrixBase& other) -// { -// return *this; -// } - - EIGEN_STRONG_INLINE Index rows() const { return IsRowMajor ? m_outerSize.value() : m_matrix.rows(); } - EIGEN_STRONG_INLINE Index cols() const { return IsRowMajor ? m_matrix.cols() : m_outerSize.value(); } - - protected: - - const typename MatrixType::Nested m_matrix; - Index m_outerStart; - const internal::variable_if_dynamic m_outerSize; - -}; - - -/*************************************************************************** -* specialisation for SparseMatrix -***************************************************************************/ - -template -class SparseInnerVectorSet, Size> - : public SparseMatrixBase, Size> > -{ - typedef SparseMatrix<_Scalar, _Options> MatrixType; - public: - - enum { IsRowMajor = internal::traits::IsRowMajor }; - - EIGEN_SPARSE_PUBLIC_INTERFACE(SparseInnerVectorSet) - class InnerIterator: public MatrixType::InnerIterator + class ReverseInnerIterator: public MatrixType::ReverseInnerIterator { public: - inline InnerIterator(const SparseInnerVectorSet& xpr, Index outer) - : MatrixType::InnerIterator(xpr.m_matrix, xpr.m_outerStart + outer), m_outer(outer) + inline ReverseInnerIterator(const SparseInnerVectorSet& xpr, Index outer) + : MatrixType::ReverseInnerIterator(xpr.m_matrix, xpr.m_outerStart + outer), m_outer(outer) {} inline Index row() const { return IsRowMajor ? m_outer : this->index(); } inline Index col() const { return IsRowMajor ? this->index() : m_outer; } @@ -243,19 +170,19 @@ class SparseInnerVectorSet, Size> { typedef typename internal::remove_all::type _NestedMatrixType; _NestedMatrixType& matrix = const_cast<_NestedMatrixType&>(m_matrix);; - // This assignement is slow if this vector set not empty + // This assignement is slow if this vector set is not empty // and/or it is not at the end of the nonzeros of the underlying matrix. // 1 - eval to a temporary to avoid transposition and/or aliasing issues SparseMatrix tmp(other); // 2 - let's check whether there is enough allocated memory - Index nnz = tmp.nonZeros(); - Index nnz_previous = nonZeros(); - Index free_size = matrix.data().allocatedSize() - nnz_previous; - std::size_t nnz_head = m_outerStart==0 ? 0 : matrix._outerIndexPtr()[m_outerStart]; - std::size_t tail = m_matrix._outerIndexPtr()[m_outerStart+m_outerSize.value()]; - std::size_t nnz_tail = matrix.nonZeros() - tail; + Index nnz = tmp.nonZeros(); + Index nnz_previous = nonZeros(); + Index free_size = Index(matrix.data().allocatedSize()) + nnz_previous; + Index nnz_head = m_outerStart==0 ? 0 : matrix.outerIndexPtr()[m_outerStart]; + Index tail = m_matrix.outerIndexPtr()[m_outerStart+m_outerSize.value()]; + Index nnz_tail = matrix.nonZeros() - tail; if(nnz>free_size) { @@ -298,15 +225,15 @@ class SparseInnerVectorSet, Size> // update outer index pointers Index p = nnz_head; - for(Index k=1; k, Size> return operator=(other); } - inline const Scalar* _valuePtr() const - { return m_matrix._valuePtr() + m_matrix._outerIndexPtr()[m_outerStart]; } - inline Scalar* _valuePtr() - { return m_matrix.const_cast_derived()._valuePtr() + m_matrix._outerIndexPtr()[m_outerStart]; } + inline const Scalar* valuePtr() const + { return m_matrix.valuePtr() + m_matrix.outerIndexPtr()[m_outerStart]; } + inline Scalar* valuePtr() + { return m_matrix.const_cast_derived().valuePtr() + m_matrix.outerIndexPtr()[m_outerStart]; } - inline const Index* _innerIndexPtr() const - { return m_matrix._innerIndexPtr() + m_matrix._outerIndexPtr()[m_outerStart]; } - inline Index* _innerIndexPtr() - { return m_matrix.const_cast_derived()._innerIndexPtr() + m_matrix._outerIndexPtr()[m_outerStart]; } + inline const Index* innerIndexPtr() const + { return m_matrix.innerIndexPtr() + m_matrix.outerIndexPtr()[m_outerStart]; } + inline Index* innerIndexPtr() + { return m_matrix.const_cast_derived().innerIndexPtr() + m_matrix.outerIndexPtr()[m_outerStart]; } - inline const Index* _outerIndexPtr() const - { return m_matrix._outerIndexPtr() + m_outerStart; } - inline Index* _outerIndexPtr() - { return m_matrix.const_cast_derived()._outerIndexPtr() + m_outerStart; } + inline const Index* outerIndexPtr() const + { return m_matrix.outerIndexPtr() + m_outerStart; } + inline Index* outerIndexPtr() + { return m_matrix.const_cast_derived().outerIndexPtr() + m_outerStart; } Index nonZeros() const { - return std::size_t(m_matrix._outerIndexPtr()[m_outerStart+m_outerSize.value()]) - - std::size_t(m_matrix._outerIndexPtr()[m_outerStart]); + if(m_matrix.isCompressed()) + return std::size_t(m_matrix.outerIndexPtr()[m_outerStart+m_outerSize.value()]) + - std::size_t(m_matrix.outerIndexPtr()[m_outerStart]); + else if(m_outerSize.value()==0) + return 0; + else + return Map >(m_matrix.innerNonZeroPtr()+m_outerStart, m_outerSize.value()).sum(); } const Scalar& lastCoeff() const { EIGEN_STATIC_ASSERT_VECTOR_ONLY(SparseInnerVectorSet); eigen_assert(nonZeros()>0); - return m_matrix._valuePtr()[m_matrix._outerIndexPtr()[m_outerStart+1]-1]; + if(m_matrix.isCompressed()) + return m_matrix.valuePtr()[m_matrix.outerIndexPtr()[m_outerStart+1]-1]; + else + return m_matrix.valuePtr()[m_matrix.outerIndexPtr()[m_outerStart]+m_matrix.innerNonZeroPtr()[m_outerStart]-1]; } // template @@ -356,7 +291,7 @@ class SparseInnerVectorSet, Size> protected: - const typename MatrixType::Nested m_matrix; + typename MatrixType::Nested m_matrix; Index m_outerStart; const internal::variable_if_dynamic m_outerSize; @@ -412,11 +347,9 @@ template const SparseInnerVectorSet SparseMatrixBase::innerVector(Index outer) const { return SparseInnerVectorSet(derived(), outer); } -//---------- - /** \returns the i-th row of the matrix \c *this. For row-major matrix only. */ template -SparseInnerVectorSet SparseMatrixBase::subrows(Index start, Index size) +SparseInnerVectorSet SparseMatrixBase::middleRows(Index start, Index size) { EIGEN_STATIC_ASSERT(IsRowMajor,THIS_METHOD_IS_ONLY_FOR_ROW_MAJOR_MATRICES); return innerVectors(start, size); @@ -425,7 +358,7 @@ SparseInnerVectorSet SparseMatrixBase::subrows(Index s /** \returns the i-th row of the matrix \c *this. For row-major matrix only. * (read-only version) */ template -const SparseInnerVectorSet SparseMatrixBase::subrows(Index start, Index size) const +const SparseInnerVectorSet SparseMatrixBase::middleRows(Index start, Index size) const { EIGEN_STATIC_ASSERT(IsRowMajor,THIS_METHOD_IS_ONLY_FOR_ROW_MAJOR_MATRICES); return innerVectors(start, size); @@ -433,7 +366,7 @@ const SparseInnerVectorSet SparseMatrixBase::subrows(I /** \returns the i-th column of the matrix \c *this. For column-major matrix only. */ template -SparseInnerVectorSet SparseMatrixBase::subcols(Index start, Index size) +SparseInnerVectorSet SparseMatrixBase::middleCols(Index start, Index size) { EIGEN_STATIC_ASSERT(!IsRowMajor,THIS_METHOD_IS_ONLY_FOR_COLUMN_MAJOR_MATRICES); return innerVectors(start, size); @@ -442,12 +375,14 @@ SparseInnerVectorSet SparseMatrixBase::subcols(Index s /** \returns the i-th column of the matrix \c *this. For column-major matrix only. * (read-only version) */ template -const SparseInnerVectorSet SparseMatrixBase::subcols(Index start, Index size) const +const SparseInnerVectorSet SparseMatrixBase::middleCols(Index start, Index size) const { EIGEN_STATIC_ASSERT(!IsRowMajor,THIS_METHOD_IS_ONLY_FOR_COLUMN_MAJOR_MATRICES); return innerVectors(start, size); } + + /** \returns the \a outer -th column (resp. row) of the matrix \c *this if \c *this * is col-major (resp. row-major). */ @@ -462,4 +397,6 @@ template const SparseInnerVectorSet SparseMatrixBase::innerVectors(Index outerStart, Index outerSize) const { return SparseInnerVectorSet(derived(), outerStart, outerSize); } +} // end namespace Eigen + #endif // EIGEN_SPARSE_BLOCK_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseCwiseBinaryOp.h b/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseCwiseBinaryOp.h similarity index 84% rename from gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseCwiseBinaryOp.h rename to gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseCwiseBinaryOp.h index cde5bbc03..28167066a 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseCwiseBinaryOp.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseCwiseBinaryOp.h @@ -25,6 +25,8 @@ #ifndef EIGEN_SPARSE_CWISE_BINARY_OP_H #define EIGEN_SPARSE_CWISE_BINARY_OP_H +namespace Eigen { + // Here we have to handle 3 cases: // 1 - sparse op dense // 2 - dense op sparse @@ -63,8 +65,18 @@ class CwiseBinaryOpImpl { public: class InnerIterator; + class ReverseInnerIterator; typedef CwiseBinaryOp Derived; EIGEN_SPARSE_PUBLIC_INTERFACE(Derived) + CwiseBinaryOpImpl() + { + typedef typename internal::traits::StorageKind LhsStorageKind; + typedef typename internal::traits::StorageKind RhsStorageKind; + EIGEN_STATIC_ASSERT(( + (!internal::is_same::value) + || ((Lhs::Flags&RowMajorBit) == (Rhs::Flags&RowMajorBit))), + THE_STORAGE_ORDER_OF_BOTH_SIDES_MUST_MATCH); + } }; template @@ -76,7 +88,7 @@ class CwiseBinaryOpImpl::InnerIterator typedef internal::sparse_cwise_binary_op_inner_iterator_selector< BinaryOp,Lhs,Rhs, InnerIterator> Base; - EIGEN_STRONG_INLINE InnerIterator(const CwiseBinaryOpImpl& binOp, Index outer) + EIGEN_STRONG_INLINE InnerIterator(const CwiseBinaryOpImpl& binOp, typename CwiseBinaryOpImpl::Index outer) : Base(binOp.derived(),outer) {} }; @@ -246,7 +258,7 @@ class sparse_cwise_binary_op_inner_iterator_selector, Lhs, EIGEN_STRONG_INLINE operator bool() const { return m_lhsIter; } protected: - const RhsNested m_rhs; + RhsNested m_rhs; LhsIterator m_lhsIter; const BinaryFunc m_functor; const Index m_outer; @@ -298,16 +310,6 @@ class sparse_cwise_binary_op_inner_iterator_selector, Lhs, * Implementation of SparseMatrixBase and SparseCwise functions/operators ***************************************************************************/ -// template -// template -// EIGEN_STRONG_INLINE const CwiseBinaryOp::Scalar>, -// Derived, OtherDerived> -// SparseMatrixBase::operator-(const SparseMatrixBase &other) const -// { -// return CwiseBinaryOp, -// Derived, OtherDerived>(derived(), other.derived()); -// } - template template EIGEN_STRONG_INLINE Derived & @@ -316,14 +318,6 @@ SparseMatrixBase::operator-=(const SparseMatrixBase &othe return *this = derived() - other.derived(); } -// template -// template -// EIGEN_STRONG_INLINE const CwiseBinaryOp::Scalar>, Derived, OtherDerived> -// SparseMatrixBase::operator+(const SparseMatrixBase &other) const -// { -// return CwiseBinaryOp, Derived, OtherDerived>(derived(), other.derived()); -// } - template template EIGEN_STRONG_INLINE Derived & @@ -332,14 +326,6 @@ SparseMatrixBase::operator+=(const SparseMatrixBase& othe return *this = derived() + other.derived(); } -// template -// template -// EIGEN_STRONG_INLINE const EIGEN_SPARSE_CWISE_PRODUCT_RETURN_TYPE -// SparseCwise::operator*(const SparseMatrixBase &other) const -// { -// return EIGEN_SPARSE_CWISE_PRODUCT_RETURN_TYPE(_expression(), other.derived()); -// } - template template EIGEN_STRONG_INLINE const EIGEN_SPARSE_CWISE_PRODUCT_RETURN_TYPE @@ -348,28 +334,6 @@ SparseMatrixBase::cwiseProduct(const MatrixBase &other) c return EIGEN_SPARSE_CWISE_PRODUCT_RETURN_TYPE(derived(), other.derived()); } -// template -// template -// EIGEN_STRONG_INLINE const EIGEN_SPARSE_CWISE_BINOP_RETURN_TYPE(internal::scalar_quotient_op) -// SparseCwise::operator/(const SparseMatrixBase &other) const -// { -// return EIGEN_SPARSE_CWISE_BINOP_RETURN_TYPE(internal::scalar_quotient_op)(_expression(), other.derived()); -// } -// -// template -// template -// EIGEN_STRONG_INLINE const EIGEN_SPARSE_CWISE_BINOP_RETURN_TYPE(internal::scalar_quotient_op) -// SparseCwise::operator/(const MatrixBase &other) const -// { -// return EIGEN_SPARSE_CWISE_BINOP_RETURN_TYPE(internal::scalar_quotient_op)(_expression(), other.derived()); -// } - -// template -// template -// inline ExpressionType& SparseCwise::operator*=(const SparseMatrixBase &other) -// { -// return m_matrix.const_cast_derived() = _expression() * other.derived(); -// } - +} // end namespace Eigen #endif // EIGEN_SPARSE_CWISE_BINARY_OP_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseCwiseUnaryOp.h b/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseCwiseUnaryOp.h similarity index 50% rename from gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseCwiseUnaryOp.h rename to gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseCwiseUnaryOp.h index aa068835f..2a63cf2af 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseCwiseUnaryOp.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseCwiseUnaryOp.h @@ -25,18 +25,7 @@ #ifndef EIGEN_SPARSE_CWISE_UNARY_OP_H #define EIGEN_SPARSE_CWISE_UNARY_OP_H -// template -// struct internal::traits > : internal::traits -// { -// typedef typename internal::result_of< -// UnaryOp(typename MatrixType::Scalar) -// >::type Scalar; -// typedef typename MatrixType::Nested MatrixTypeNested; -// typedef typename internal::remove_reference::type _MatrixTypeNested; -// enum { -// CoeffReadCost = _MatrixTypeNested::CoeffReadCost + internal::functor_traits::Cost -// }; -// }; +namespace Eigen { template class CwiseUnaryOpImpl @@ -45,39 +34,61 @@ class CwiseUnaryOpImpl public: class InnerIterator; -// typedef typename internal::remove_reference::type _LhsNested; + class ReverseInnerIterator; typedef CwiseUnaryOp Derived; EIGEN_SPARSE_PUBLIC_INTERFACE(Derived) + + protected: + typedef typename internal::traits::_XprTypeNested _MatrixTypeNested; + typedef typename _MatrixTypeNested::InnerIterator MatrixTypeIterator; + typedef typename _MatrixTypeNested::ReverseInnerIterator MatrixTypeReverseIterator; }; template class CwiseUnaryOpImpl::InnerIterator + : public CwiseUnaryOpImpl::MatrixTypeIterator { typedef typename CwiseUnaryOpImpl::Scalar Scalar; - typedef typename internal::traits::_XprTypeNested _MatrixTypeNested; - typedef typename _MatrixTypeNested::InnerIterator MatrixTypeIterator; - typedef typename MatrixType::Index Index; + typedef typename CwiseUnaryOpImpl::MatrixTypeIterator Base; public: - EIGEN_STRONG_INLINE InnerIterator(const CwiseUnaryOpImpl& unaryOp, Index outer) - : m_iter(unaryOp.derived().nestedExpression(),outer), m_functor(unaryOp.derived().functor()) + EIGEN_STRONG_INLINE InnerIterator(const CwiseUnaryOpImpl& unaryOp, typename CwiseUnaryOpImpl::Index outer) + : Base(unaryOp.derived().nestedExpression(),outer), m_functor(unaryOp.derived().functor()) {} EIGEN_STRONG_INLINE InnerIterator& operator++() - { ++m_iter; return *this; } + { Base::operator++(); return *this; } - EIGEN_STRONG_INLINE Scalar value() const { return m_functor(m_iter.value()); } - - EIGEN_STRONG_INLINE Index index() const { return m_iter.index(); } - EIGEN_STRONG_INLINE Index row() const { return m_iter.row(); } - EIGEN_STRONG_INLINE Index col() const { return m_iter.col(); } - - EIGEN_STRONG_INLINE operator bool() const { return m_iter; } + EIGEN_STRONG_INLINE typename CwiseUnaryOpImpl::Scalar value() const { return m_functor(Base::value()); } protected: - MatrixTypeIterator m_iter; const UnaryOp m_functor; + private: + typename CwiseUnaryOpImpl::Scalar& valueRef(); +}; + +template +class CwiseUnaryOpImpl::ReverseInnerIterator + : public CwiseUnaryOpImpl::MatrixTypeReverseIterator +{ + typedef typename CwiseUnaryOpImpl::Scalar Scalar; + typedef typename CwiseUnaryOpImpl::MatrixTypeReverseIterator Base; + public: + + EIGEN_STRONG_INLINE ReverseInnerIterator(const CwiseUnaryOpImpl& unaryOp, typename CwiseUnaryOpImpl::Index outer) + : Base(unaryOp.derived().nestedExpression(),outer), m_functor(unaryOp.derived().functor()) + {} + + EIGEN_STRONG_INLINE ReverseInnerIterator& operator--() + { Base::operator--(); return *this; } + + EIGEN_STRONG_INLINE typename CwiseUnaryOpImpl::Scalar value() const { return m_functor(Base::value()); } + + protected: + const UnaryOp m_functor; + private: + typename CwiseUnaryOpImpl::Scalar& valueRef(); }; template @@ -87,39 +98,58 @@ class CwiseUnaryViewImpl public: class InnerIterator; -// typedef typename internal::remove_reference::type _LhsNested; + class ReverseInnerIterator; typedef CwiseUnaryView Derived; EIGEN_SPARSE_PUBLIC_INTERFACE(Derived) + + protected: + typedef typename internal::traits::_MatrixTypeNested _MatrixTypeNested; + typedef typename _MatrixTypeNested::InnerIterator MatrixTypeIterator; + typedef typename _MatrixTypeNested::ReverseInnerIterator MatrixTypeReverseIterator; }; template class CwiseUnaryViewImpl::InnerIterator + : public CwiseUnaryViewImpl::MatrixTypeIterator { typedef typename CwiseUnaryViewImpl::Scalar Scalar; - typedef typename internal::traits::_MatrixTypeNested _MatrixTypeNested; - typedef typename _MatrixTypeNested::InnerIterator MatrixTypeIterator; - typedef typename MatrixType::Index Index; + typedef typename CwiseUnaryViewImpl::MatrixTypeIterator Base; public: - EIGEN_STRONG_INLINE InnerIterator(const CwiseUnaryViewImpl& unaryView, Index outer) - : m_iter(unaryView.derived().nestedExpression(),outer), m_functor(unaryView.derived().functor()) + EIGEN_STRONG_INLINE InnerIterator(const CwiseUnaryViewImpl& unaryOp, typename CwiseUnaryViewImpl::Index outer) + : Base(unaryOp.derived().nestedExpression(),outer), m_functor(unaryOp.derived().functor()) {} EIGEN_STRONG_INLINE InnerIterator& operator++() - { ++m_iter; return *this; } + { Base::operator++(); return *this; } - EIGEN_STRONG_INLINE Scalar value() const { return m_functor(m_iter.value()); } - EIGEN_STRONG_INLINE Scalar& valueRef() { return m_functor(m_iter.valueRef()); } - - EIGEN_STRONG_INLINE Index index() const { return m_iter.index(); } - EIGEN_STRONG_INLINE Index row() const { return m_iter.row(); } - EIGEN_STRONG_INLINE Index col() const { return m_iter.col(); } - - EIGEN_STRONG_INLINE operator bool() const { return m_iter; } + EIGEN_STRONG_INLINE typename CwiseUnaryViewImpl::Scalar value() const { return m_functor(Base::value()); } + EIGEN_STRONG_INLINE typename CwiseUnaryViewImpl::Scalar& valueRef() { return m_functor(Base::valueRef()); } + + protected: + const ViewOp m_functor; +}; + +template +class CwiseUnaryViewImpl::ReverseInnerIterator + : public CwiseUnaryViewImpl::MatrixTypeReverseIterator +{ + typedef typename CwiseUnaryViewImpl::Scalar Scalar; + typedef typename CwiseUnaryViewImpl::MatrixTypeReverseIterator Base; + public: + + EIGEN_STRONG_INLINE ReverseInnerIterator(const CwiseUnaryViewImpl& unaryOp, typename CwiseUnaryViewImpl::Index outer) + : Base(unaryOp.derived().nestedExpression(),outer), m_functor(unaryOp.derived().functor()) + {} + + EIGEN_STRONG_INLINE ReverseInnerIterator& operator--() + { Base::operator--(); return *this; } + + EIGEN_STRONG_INLINE typename CwiseUnaryViewImpl::Scalar value() const { return m_functor(Base::value()); } + EIGEN_STRONG_INLINE typename CwiseUnaryViewImpl::Scalar& valueRef() { return m_functor(Base::valueRef()); } protected: - MatrixTypeIterator m_iter; const ViewOp m_functor; }; @@ -143,4 +173,6 @@ SparseMatrixBase::operator/=(const Scalar& other) return derived(); } +} // end namespace Eigen + #endif // EIGEN_SPARSE_CWISE_UNARY_OP_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseDenseProduct.h b/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseDenseProduct.h similarity index 61% rename from gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseDenseProduct.h rename to gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseDenseProduct.h index 0f77aa5be..00ba606be 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseDenseProduct.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseDenseProduct.h @@ -25,6 +25,8 @@ #ifndef EIGEN_SPARSEDENSEPRODUCT_H #define EIGEN_SPARSEDENSEPRODUCT_H +namespace Eigen { + template struct SparseDenseProductReturnType { typedef SparseTimeDenseProduct Type; @@ -149,6 +151,102 @@ struct traits > typedef Dense StorageKind; typedef MatrixXpr XprKind; }; + +template +struct sparse_time_dense_product_impl; + +template +struct sparse_time_dense_product_impl +{ + typedef typename internal::remove_all::type Lhs; + typedef typename internal::remove_all::type Rhs; + typedef typename internal::remove_all::type Res; + typedef typename Lhs::Index Index; + typedef typename Lhs::InnerIterator LhsInnerIterator; + static void run(const SparseLhsType& lhs, const DenseRhsType& rhs, DenseResType& res, typename Res::Scalar alpha) + { + for(Index c=0; c +struct sparse_time_dense_product_impl +{ + typedef typename internal::remove_all::type Lhs; + typedef typename internal::remove_all::type Rhs; + typedef typename internal::remove_all::type Res; + typedef typename Lhs::InnerIterator LhsInnerIterator; + typedef typename Lhs::Index Index; + static void run(const SparseLhsType& lhs, const DenseRhsType& rhs, DenseResType& res, typename Res::Scalar alpha) + { + for(Index c=0; c +struct sparse_time_dense_product_impl +{ + typedef typename internal::remove_all::type Lhs; + typedef typename internal::remove_all::type Rhs; + typedef typename internal::remove_all::type Res; + typedef typename Lhs::InnerIterator LhsInnerIterator; + typedef typename Lhs::Index Index; + static void run(const SparseLhsType& lhs, const DenseRhsType& rhs, DenseResType& res, typename Res::Scalar alpha) + { + for(Index j=0; j +struct sparse_time_dense_product_impl +{ + typedef typename internal::remove_all::type Lhs; + typedef typename internal::remove_all::type Rhs; + typedef typename internal::remove_all::type Res; + typedef typename Lhs::InnerIterator LhsInnerIterator; + typedef typename Lhs::Index Index; + static void run(const SparseLhsType& lhs, const DenseRhsType& rhs, DenseResType& res, typename Res::Scalar alpha) + { + for(Index j=0; j +inline void sparse_time_dense_product(const SparseLhsType& lhs, const DenseRhsType& rhs, DenseResType& res, const AlphaType& alpha) +{ + sparse_time_dense_product_impl::run(lhs, rhs, res, alpha); +} + } // end namespace internal template @@ -163,21 +261,7 @@ class SparseTimeDenseProduct template void scaleAndAddTo(Dest& dest, Scalar alpha) const { - typedef typename internal::remove_all::type _Lhs; - typedef typename internal::remove_all::type _Rhs; - typedef typename _Lhs::InnerIterator LhsInnerIterator; - enum { LhsIsRowMajor = (_Lhs::Flags&RowMajorBit)==RowMajorBit }; - for(Index j=0; j void scaleAndAddTo(Dest& dest, Scalar alpha) const { - typedef typename internal::remove_all::type _Rhs; - typedef typename _Rhs::InnerIterator RhsInnerIterator; - enum { RhsIsRowMajor = (_Rhs::Flags&RowMajorBit)==RowMajorBit }; - for(Index j=0; j lhs_t(m_lhs); + Transpose rhs_t(m_rhs); + Transpose dest_t(dest); + internal::sparse_time_dense_product(rhs_t, lhs_t, dest_t, alpha); } private: @@ -228,4 +310,6 @@ SparseMatrixBase::operator*(const MatrixBase &other) cons return typename SparseDenseProductReturnType::Type(derived(), other.derived()); } +} // end namespace Eigen + #endif // EIGEN_SPARSEDENSEPRODUCT_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseDiagonalProduct.h b/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseDiagonalProduct.h similarity index 99% rename from gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseDiagonalProduct.h rename to gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseDiagonalProduct.h index fb9a29c05..b09c4a715 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseDiagonalProduct.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseDiagonalProduct.h @@ -25,6 +25,8 @@ #ifndef EIGEN_SPARSE_DIAGONAL_PRODUCT_H #define EIGEN_SPARSE_DIAGONAL_PRODUCT_H +namespace Eigen { + // The product of a diagonal matrix with a sparse matrix can be easily // implemented using expression template. // We have two consider very different cases: @@ -192,4 +194,6 @@ SparseMatrixBase::operator*(const DiagonalBase &other) co return SparseDiagonalProduct(this->derived(), other.derived()); } +} // end namespace Eigen + #endif // EIGEN_SPARSE_DIAGONAL_PRODUCT_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseDot.h b/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseDot.h similarity index 86% rename from gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseDot.h rename to gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseDot.h index 1f10f71a4..ebb63d36b 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseDot.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseDot.h @@ -25,6 +25,8 @@ #ifndef EIGEN_SPARSE_DOT_H #define EIGEN_SPARSE_DOT_H +namespace Eigen { + template template typename internal::traits::Scalar @@ -40,7 +42,7 @@ SparseMatrixBase::dot(const MatrixBase& other) const eigen_assert(other.size()>0 && "you are using a non initialized vector"); typename Derived::InnerIterator i(derived(),0); - Scalar res = 0; + Scalar res(0); while (i) { res += internal::conj(i.value()) * other.coeff(i.index()); @@ -62,9 +64,17 @@ SparseMatrixBase::dot(const SparseMatrixBase& other) cons eigen_assert(size() == other.size()); - typename Derived::InnerIterator i(derived(),0); - typename OtherDerived::InnerIterator j(other.derived(),0); - Scalar res = 0; + typedef typename Derived::Nested Nested; + typedef typename OtherDerived::Nested OtherNested; + typedef typename internal::remove_all::type NestedCleaned; + typedef typename internal::remove_all::type OtherNestedCleaned; + + const Nested nthis(derived()); + const OtherNested nother(other.derived()); + + typename NestedCleaned::InnerIterator i(nthis,0); + typename OtherNestedCleaned::InnerIterator j(nother,0); + Scalar res(0); while (i && j) { if (i.index()==j.index()) @@ -94,4 +104,6 @@ SparseMatrixBase::norm() const return internal::sqrt(squaredNorm()); } +} // end namespace Eigen + #endif // EIGEN_SPARSE_DOT_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseFuzzy.h b/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseFuzzy.h similarity index 100% rename from gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseFuzzy.h rename to gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseFuzzy.h diff --git a/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseMatrix.h b/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseMatrix.h new file mode 100644 index 000000000..214f130f5 --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseMatrix.h @@ -0,0 +1,1127 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2008-2010 Gael Guennebaud +// +// Eigen is free software; you can redistribute it and/or +// modify it under the terms of the GNU Lesser General Public +// License as published by the Free Software Foundation; either +// version 3 of the License, or (at your option) any later version. +// +// Alternatively, you can redistribute it and/or +// modify it under the terms of the GNU General Public License as +// published by the Free Software Foundation; either version 2 of +// the License, or (at your option) any later version. +// +// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY +// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the +// GNU General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public +// License and a copy of the GNU General Public License along with +// Eigen. If not, see . + +#ifndef EIGEN_SPARSEMATRIX_H +#define EIGEN_SPARSEMATRIX_H + +namespace Eigen { + +/** \ingroup SparseCore_Module + * + * \class SparseMatrix + * + * \brief A versatible sparse matrix representation + * + * This class implements a more versatile variants of the common \em compressed row/column storage format. + * Each colmun's (resp. row) non zeros are stored as a pair of value with associated row (resp. colmiun) index. + * All the non zeros are stored in a single large buffer. Unlike the \em compressed format, there might be extra + * space inbetween the nonzeros of two successive colmuns (resp. rows) such that insertion of new non-zero + * can be done with limited memory reallocation and copies. + * + * A call to the function makeCompressed() turns the matrix into the standard \em compressed format + * compatible with many library. + * + * More details on this storage sceheme are given in the \ref TutorialSparse "manual pages". + * + * \tparam _Scalar the scalar type, i.e. the type of the coefficients + * \tparam _Options Union of bit flags controlling the storage scheme. Currently the only possibility + * is RowMajor. The default is 0 which means column-major. + * \tparam _Index the type of the indices. It has to be a \b signed type (e.g., short, int, std::ptrdiff_t). Default is \c int. + * + * This class can be extended with the help of the plugin mechanism described on the page + * \ref TopicCustomizingEigen by defining the preprocessor symbol \c EIGEN_SPARSEMATRIX_PLUGIN. + */ + +namespace internal { +template +struct traits > +{ + typedef _Scalar Scalar; + typedef _Index Index; + typedef Sparse StorageKind; + typedef MatrixXpr XprKind; + enum { + RowsAtCompileTime = Dynamic, + ColsAtCompileTime = Dynamic, + MaxRowsAtCompileTime = Dynamic, + MaxColsAtCompileTime = Dynamic, + Flags = _Options | NestByRefBit | LvalueBit, + CoeffReadCost = NumTraits::ReadCost, + SupportedAccessPatterns = InnerRandomAccessPattern + }; +}; + +template +struct traits, DiagIndex> > +{ + typedef SparseMatrix<_Scalar, _Options, _Index> MatrixType; + typedef typename nested::type MatrixTypeNested; + typedef typename remove_reference::type _MatrixTypeNested; + + typedef _Scalar Scalar; + typedef Dense StorageKind; + typedef _Index Index; + typedef MatrixXpr XprKind; + + enum { + RowsAtCompileTime = Dynamic, + ColsAtCompileTime = 1, + MaxRowsAtCompileTime = Dynamic, + MaxColsAtCompileTime = 1, + Flags = 0, + CoeffReadCost = _MatrixTypeNested::CoeffReadCost*10 + }; +}; + +} // end namespace internal + +template +class SparseMatrix + : public SparseMatrixBase > +{ + public: + EIGEN_SPARSE_PUBLIC_INTERFACE(SparseMatrix) + EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(SparseMatrix, +=) + EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(SparseMatrix, -=) + + typedef MappedSparseMatrix Map; + using Base::IsRowMajor; + typedef internal::CompressedStorage Storage; + enum { + Options = _Options + }; + + protected: + + typedef SparseMatrix TransposedSparseMatrix; + + Index m_outerSize; + Index m_innerSize; + Index* m_outerIndex; + Index* m_innerNonZeros; // optional, if null then the data is compressed + Storage m_data; + + Eigen::Map > innerNonZeros() { return Eigen::Map >(m_innerNonZeros, m_innerNonZeros?m_outerSize:0); } + const Eigen::Map > innerNonZeros() const { return Eigen::Map >(m_innerNonZeros, m_innerNonZeros?m_outerSize:0); } + + public: + + /** \returns whether \c *this is in compressed form. */ + inline bool isCompressed() const { return m_innerNonZeros==0; } + + /** \returns the number of rows of the matrix */ + inline Index rows() const { return IsRowMajor ? m_outerSize : m_innerSize; } + /** \returns the number of columns of the matrix */ + inline Index cols() const { return IsRowMajor ? m_innerSize : m_outerSize; } + + /** \returns the number of rows (resp. columns) of the matrix if the storage order column major (resp. row major) */ + inline Index innerSize() const { return m_innerSize; } + /** \returns the number of columns (resp. rows) of the matrix if the storage order column major (resp. row major) */ + inline Index outerSize() const { return m_outerSize; } + + /** \returns a const pointer to the array of values. + * This function is aimed at interoperability with other libraries. + * \sa innerIndexPtr(), outerIndexPtr() */ + inline const Scalar* valuePtr() const { return &m_data.value(0); } + /** \returns a non-const pointer to the array of values. + * This function is aimed at interoperability with other libraries. + * \sa innerIndexPtr(), outerIndexPtr() */ + inline Scalar* valuePtr() { return &m_data.value(0); } + + /** \returns a const pointer to the array of inner indices. + * This function is aimed at interoperability with other libraries. + * \sa valuePtr(), outerIndexPtr() */ + inline const Index* innerIndexPtr() const { return &m_data.index(0); } + /** \returns a non-const pointer to the array of inner indices. + * This function is aimed at interoperability with other libraries. + * \sa valuePtr(), outerIndexPtr() */ + inline Index* innerIndexPtr() { return &m_data.index(0); } + + /** \returns a const pointer to the array of the starting positions of the inner vectors. + * This function is aimed at interoperability with other libraries. + * \sa valuePtr(), innerIndexPtr() */ + inline const Index* outerIndexPtr() const { return m_outerIndex; } + /** \returns a non-const pointer to the array of the starting positions of the inner vectors. + * This function is aimed at interoperability with other libraries. + * \sa valuePtr(), innerIndexPtr() */ + inline Index* outerIndexPtr() { return m_outerIndex; } + + /** \returns a const pointer to the array of the number of non zeros of the inner vectors. + * This function is aimed at interoperability with other libraries. + * \warning it returns the null pointer 0 in compressed mode */ + inline const Index* innerNonZeroPtr() const { return m_innerNonZeros; } + /** \returns a non-const pointer to the array of the number of non zeros of the inner vectors. + * This function is aimed at interoperability with other libraries. + * \warning it returns the null pointer 0 in compressed mode */ + inline Index* innerNonZeroPtr() { return m_innerNonZeros; } + + /** \internal */ + inline Storage& data() { return m_data; } + /** \internal */ + inline const Storage& data() const { return m_data; } + + /** \returns the value of the matrix at position \a i, \a j + * This function returns Scalar(0) if the element is an explicit \em zero */ + inline Scalar coeff(Index row, Index col) const + { + const Index outer = IsRowMajor ? row : col; + const Index inner = IsRowMajor ? col : row; + Index end = m_innerNonZeros ? m_outerIndex[outer] + m_innerNonZeros[outer] : m_outerIndex[outer+1]; + return m_data.atInRange(m_outerIndex[outer], end, inner); + } + + /** \returns a non-const reference to the value of the matrix at position \a i, \a j + * + * If the element does not exist then it is inserted via the insert(Index,Index) function + * which itself turns the matrix into a non compressed form if that was not the case. + * + * This is a O(log(nnz_j)) operation (binary search) plus the cost of insert(Index,Index) + * function if the element does not already exist. + */ + inline Scalar& coeffRef(Index row, Index col) + { + const Index outer = IsRowMajor ? row : col; + const Index inner = IsRowMajor ? col : row; + + Index start = m_outerIndex[outer]; + Index end = m_innerNonZeros ? m_outerIndex[outer] + m_innerNonZeros[outer] : m_outerIndex[outer+1]; + eigen_assert(end>=start && "you probably called coeffRef on a non finalized matrix"); + if(end<=start) + return insert(row,col); + const Index p = m_data.searchLowerIndex(start,end-1,inner); + if((p(m_data.size()); + } + + /** Preallocates \a reserveSize non zeros. + * + * Precondition: the matrix must be in compressed mode. */ + inline void reserve(Index reserveSize) + { + eigen_assert(isCompressed() && "This function does not make sense in non compressed mode."); + m_data.reserve(reserveSize); + } + + #ifdef EIGEN_PARSED_BY_DOXYGEN + /** Preallocates \a reserveSize[\c j] non zeros for each column (resp. row) \c j. + * + * This function turns the matrix in non-compressed mode */ + template + inline void reserve(const SizesType& reserveSizes); + #else + template + inline void reserve(const SizesType& reserveSizes, const typename SizesType::value_type& enableif = typename SizesType::value_type()) + { + EIGEN_UNUSED_VARIABLE(enableif); + reserveInnerVectors(reserveSizes); + } + template + inline void reserve(const SizesType& reserveSizes, const typename SizesType::Scalar& enableif = typename SizesType::Scalar()) + { + EIGEN_UNUSED_VARIABLE(enableif); + reserveInnerVectors(reserveSizes); + } + #endif // EIGEN_PARSED_BY_DOXYGEN + protected: + template + inline void reserveInnerVectors(const SizesType& reserveSizes) + { + + if(isCompressed()) + { + std::size_t totalReserveSize = 0; + // turn the matrix into non-compressed mode + m_innerNonZeros = new Index[m_outerSize]; + + // temporarily use m_innerSizes to hold the new starting points. + Index* newOuterIndex = m_innerNonZeros; + + Index count = 0; + for(Index j=0; j=0; --j) + { + ptrdiff_t innerNNZ = previousOuterIndex - m_outerIndex[j]; + for(std::ptrdiff_t i=innerNNZ-1; i>=0; --i) + { + m_data.index(newOuterIndex[j]+i) = m_data.index(m_outerIndex[j]+i); + m_data.value(newOuterIndex[j]+i) = m_data.value(m_outerIndex[j]+i); + } + previousOuterIndex = m_outerIndex[j]; + m_outerIndex[j] = newOuterIndex[j]; + m_innerNonZeros[j] = innerNNZ; + } + m_outerIndex[m_outerSize] = m_outerIndex[m_outerSize-1] + m_innerNonZeros[m_outerSize-1] + reserveSizes[m_outerSize-1]; + + m_data.resize(m_outerIndex[m_outerSize]); + } + else + { + Index* newOuterIndex = new Index[m_outerSize+1]; + Index count = 0; + for(Index j=0; j(reserveSizes[j], alreadyReserved); + count += toReserve + m_innerNonZeros[j]; + } + newOuterIndex[m_outerSize] = count; + + m_data.resize(count); + for(ptrdiff_t j=m_outerSize-1; j>=0; --j) + { + std::ptrdiff_t offset = newOuterIndex[j] - m_outerIndex[j]; + if(offset>0) + { + std::ptrdiff_t innerNNZ = m_innerNonZeros[j]; + for(std::ptrdiff_t i=innerNNZ-1; i>=0; --i) + { + m_data.index(newOuterIndex[j]+i) = m_data.index(m_outerIndex[j]+i); + m_data.value(newOuterIndex[j]+i) = m_data.value(m_outerIndex[j]+i); + } + } + } + + std::swap(m_outerIndex, newOuterIndex); + delete[] newOuterIndex; + } + + } + public: + + //--- low level purely coherent filling --- + + /** \internal + * \returns a reference to the non zero coefficient at position \a row, \a col assuming that: + * - the nonzero does not already exist + * - the new coefficient is the last one according to the storage order + * + * Before filling a given inner vector you must call the statVec(Index) function. + * + * After an insertion session, you should call the finalize() function. + * + * \sa insert, insertBackByOuterInner, startVec */ + inline Scalar& insertBack(Index row, Index col) + { + return insertBackByOuterInner(IsRowMajor?row:col, IsRowMajor?col:row); + } + + /** \internal + * \sa insertBack, startVec */ + inline Scalar& insertBackByOuterInner(Index outer, Index inner) + { + eigen_assert(size_t(m_outerIndex[outer+1]) == m_data.size() && "Invalid ordered insertion (invalid outer index)"); + eigen_assert( (m_outerIndex[outer+1]-m_outerIndex[outer]==0 || m_data.index(m_data.size()-1)(m_data.size()); + Index i = m_outerSize; + // find the last filled column + while (i>=0 && m_outerIndex[i]==0) + --i; + ++i; + while (i<=m_outerSize) + { + m_outerIndex[i] = size; + ++i; + } + } + } + + //--- + + template + void setFromTriplets(const InputIterators& begin, const InputIterators& end); + + void sumupDuplicates(); + + //--- + + /** \internal + * same as insert(Index,Index) except that the indices are given relative to the storage order */ + EIGEN_DONT_INLINE Scalar& insertByOuterInner(Index j, Index i) + { + return insert(IsRowMajor ? j : i, IsRowMajor ? i : j); + } + + /** Turns the matrix into the \em compressed format. + */ + void makeCompressed() + { + if(isCompressed()) + return; + + Index oldStart = m_outerIndex[1]; + m_outerIndex[1] = m_innerNonZeros[0]; + for(Index j=1; j0) + { + for(Index k=0; k::dummy_precision()) + { + prune(default_prunning_func(reference,epsilon)); + } + + /** Turns the matrix into compressed format, and suppresses all nonzeros which do not satisfy the predicate \a keep. + * The functor type \a KeepFunc must implement the following function: + * \code + * bool operator() (const Index& row, const Index& col, const Scalar& value) const; + * \endcode + * \sa prune(Scalar,RealScalar) + */ + template + void prune(const KeepFunc& keep = KeepFunc()) + { + // TODO optimize the uncompressed mode to avoid moving and allocating the data twice + // TODO also implement a unit test + makeCompressed(); + + Index k = 0; + for(Index j=0; j diagonal() const { return *this; } + + /** Default constructor yielding an empty \c 0 \c x \c 0 matrix */ + inline SparseMatrix() + : m_outerSize(-1), m_innerSize(0), m_outerIndex(0), m_innerNonZeros(0) + { + check_template_parameters(); + resize(0, 0); + } + + /** Constructs a \a rows \c x \a cols empty matrix */ + inline SparseMatrix(Index rows, Index cols) + : m_outerSize(0), m_innerSize(0), m_outerIndex(0), m_innerNonZeros(0) + { + check_template_parameters(); + resize(rows, cols); + } + + /** Constructs a sparse matrix from the sparse expression \a other */ + template + inline SparseMatrix(const SparseMatrixBase& other) + : m_outerSize(0), m_innerSize(0), m_outerIndex(0), m_innerNonZeros(0) + { + check_template_parameters(); + *this = other.derived(); + } + + /** Copy constructor (it performs a deep copy) */ + inline SparseMatrix(const SparseMatrix& other) + : Base(), m_outerSize(0), m_innerSize(0), m_outerIndex(0), m_innerNonZeros(0) + { + check_template_parameters(); + *this = other.derived(); + } + + /** Swaps the content of two sparse matrices of the same type. + * This is a fast operation that simply swaps the underlying pointers and parameters. */ + inline void swap(SparseMatrix& other) + { + //EIGEN_DBG_SPARSE(std::cout << "SparseMatrix:: swap\n"); + std::swap(m_outerIndex, other.m_outerIndex); + std::swap(m_innerSize, other.m_innerSize); + std::swap(m_outerSize, other.m_outerSize); + std::swap(m_innerNonZeros, other.m_innerNonZeros); + m_data.swap(other.m_data); + } + + inline SparseMatrix& operator=(const SparseMatrix& other) + { + if (other.isRValue()) + { + swap(other.const_cast_derived()); + } + else + { + initAssignment(other); + if(other.isCompressed()) + { + memcpy(m_outerIndex, other.m_outerIndex, (m_outerSize+1)*sizeof(Index)); + m_data = other.m_data; + } + else + { + Base::operator=(other); + } + } + return *this; + } + + #ifndef EIGEN_PARSED_BY_DOXYGEN + template + inline SparseMatrix& operator=(const SparseSparseProduct& product) + { return Base::operator=(product); } + + template + inline SparseMatrix& operator=(const ReturnByValue& other) + { return Base::operator=(other.derived()); } + + template + inline SparseMatrix& operator=(const EigenBase& other) + { return Base::operator=(other.derived()); } + #endif + + template + EIGEN_DONT_INLINE SparseMatrix& operator=(const SparseMatrixBase& other) + { + initAssignment(other.derived()); + const bool needToTranspose = (Flags & RowMajorBit) != (OtherDerived::Flags & RowMajorBit); + if (needToTranspose) + { + // two passes algorithm: + // 1 - compute the number of coeffs per dest inner vector + // 2 - do the actual copy/eval + // Since each coeff of the rhs has to be evaluated twice, let's evaluate it if needed + typedef typename internal::nested::type OtherCopy; + typedef typename internal::remove_all::type _OtherCopy; + OtherCopy otherCopy(other.derived()); + + Eigen::Map > (m_outerIndex,outerSize()).setZero(); + // pass 1 + // FIXME the above copy could be merged with that pass + for (Index j=0; j&>(m); + return s; + } + + /** Destructor */ + inline ~SparseMatrix() + { + delete[] m_outerIndex; + delete[] m_innerNonZeros; + } + +#ifndef EIGEN_PARSED_BY_DOXYGEN + /** Overloaded for performance */ + Scalar sum() const; +#endif + +# ifdef EIGEN_SPARSEMATRIX_PLUGIN +# include EIGEN_SPARSEMATRIX_PLUGIN +# endif + +protected: + + template + void initAssignment(const Other& other) + { + resize(other.rows(), other.cols()); + if(m_innerNonZeros) + { + delete[] m_innerNonZeros; + m_innerNonZeros = 0; + } + } + + /** \internal + * \sa insert(Index,Index) */ + EIGEN_DONT_INLINE Scalar& insertCompressed(Index row, Index col) + { + eigen_assert(isCompressed()); + + const Index outer = IsRowMajor ? row : col; + const Index inner = IsRowMajor ? col : row; + + Index previousOuter = outer; + if (m_outerIndex[outer+1]==0) + { + // we start a new inner vector + while (previousOuter>=0 && m_outerIndex[previousOuter]==0) + { + m_outerIndex[previousOuter] = static_cast(m_data.size()); + --previousOuter; + } + m_outerIndex[outer+1] = m_outerIndex[outer]; + } + + // here we have to handle the tricky case where the outerIndex array + // starts with: [ 0 0 0 0 0 1 ...] and we are inserted in, e.g., + // the 2nd inner vector... + bool isLastVec = (!(previousOuter==-1 && m_data.size()!=0)) + && (size_t(m_outerIndex[outer+1]) == m_data.size()); + + size_t startId = m_outerIndex[outer]; + // FIXME let's make sure sizeof(long int) == sizeof(size_t) + size_t p = m_outerIndex[outer+1]; + ++m_outerIndex[outer+1]; + + float reallocRatio = 1; + if (m_data.allocatedSize()<=m_data.size()) + { + // if there is no preallocated memory, let's reserve a minimum of 32 elements + if (m_data.size()==0) + { + m_data.reserve(32); + } + else + { + // we need to reallocate the data, to reduce multiple reallocations + // we use a smart resize algorithm based on the current filling ratio + // in addition, we use float to avoid integers overflows + float nnzEstimate = float(m_outerIndex[outer])*float(m_outerSize)/float(outer+1); + reallocRatio = (nnzEstimate-float(m_data.size()))/float(m_data.size()); + // furthermore we bound the realloc ratio to: + // 1) reduce multiple minor realloc when the matrix is almost filled + // 2) avoid to allocate too much memory when the matrix is almost empty + reallocRatio = (std::min)((std::max)(reallocRatio,1.5f),8.f); + } + } + m_data.resize(m_data.size()+1,reallocRatio); + + if (!isLastVec) + { + if (previousOuter==-1) + { + // oops wrong guess. + // let's correct the outer offsets + for (Index k=0; k<=(outer+1); ++k) + m_outerIndex[k] = 0; + Index k=outer+1; + while(m_outerIndex[k]==0) + m_outerIndex[k++] = 1; + while (k<=m_outerSize && m_outerIndex[k]!=0) + m_outerIndex[k++]++; + p = 0; + --k; + k = m_outerIndex[k]-1; + while (k>0) + { + m_data.index(k) = m_data.index(k-1); + m_data.value(k) = m_data.value(k-1); + k--; + } + } + else + { + // we are not inserting into the last inner vec + // update outer indices: + Index j = outer+2; + while (j<=m_outerSize && m_outerIndex[j]!=0) + m_outerIndex[j++]++; + --j; + // shift data of last vecs: + Index k = m_outerIndex[j]-1; + while (k>=Index(p)) + { + m_data.index(k) = m_data.index(k-1); + m_data.value(k) = m_data.value(k-1); + k--; + } + } + } + + while ( (p > startId) && (m_data.index(p-1) > inner) ) + { + m_data.index(p) = m_data.index(p-1); + m_data.value(p) = m_data.value(p-1); + --p; + } + + m_data.index(p) = inner; + return (m_data.value(p) = 0); + } + + /** \internal + * A vector object that is equal to 0 everywhere but v at the position i */ + class SingletonVector + { + Index m_index; + Index m_value; + public: + typedef Index value_type; + SingletonVector(Index i, Index v) + : m_index(i), m_value(v) + {} + + Index operator[](Index i) const { return i==m_index ? m_value : 0; } + }; + + /** \internal + * \sa insert(Index,Index) */ + EIGEN_DONT_INLINE Scalar& insertUncompressed(Index row, Index col) + { + eigen_assert(!isCompressed()); + + const Index outer = IsRowMajor ? row : col; + const Index inner = IsRowMajor ? col : row; + + std::ptrdiff_t room = m_outerIndex[outer+1] - m_outerIndex[outer]; + std::ptrdiff_t innerNNZ = m_innerNonZeros[outer]; + if(innerNNZ>=room) + { + // this inner vector is full, we need to reallocate the whole buffer :( + reserve(SingletonVector(outer,std::max(2,innerNNZ))); + } + + Index startId = m_outerIndex[outer]; + Index p = startId + m_innerNonZeros[outer]; + while ( (p > startId) && (m_data.index(p-1) > inner) ) + { + m_data.index(p) = m_data.index(p-1); + m_data.value(p) = m_data.value(p-1); + --p; + } + + m_innerNonZeros[outer]++; + + m_data.index(p) = inner; + return (m_data.value(p) = 0); + } + +public: + /** \internal + * \sa insert(Index,Index) */ + inline Scalar& insertBackUncompressed(Index row, Index col) + { + const Index outer = IsRowMajor ? row : col; + const Index inner = IsRowMajor ? col : row; + + eigen_assert(!isCompressed()); + eigen_assert(m_innerNonZeros[outer]<=(m_outerIndex[outer+1] - m_outerIndex[outer])); + + Index p = m_outerIndex[outer] + m_innerNonZeros[outer]; + m_innerNonZeros[outer]++; + m_data.index(p) = inner; + return (m_data.value(p) = 0); + } + +private: + static void check_template_parameters() + { + EIGEN_STATIC_ASSERT(NumTraits::IsSigned,THE_INDEX_TYPE_MUST_BE_A_SIGNED_TYPE); + } + + struct default_prunning_func { + default_prunning_func(Scalar ref, RealScalar eps) : reference(ref), epsilon(eps) {} + inline bool operator() (const Index&, const Index&, const Scalar& value) const + { + return !internal::isMuchSmallerThan(value, reference, epsilon); + } + Scalar reference; + RealScalar epsilon; + }; +}; + +template +class SparseMatrix::InnerIterator +{ + public: + InnerIterator(const SparseMatrix& mat, Index outer) + : m_values(mat.valuePtr()), m_indices(mat.innerIndexPtr()), m_outer(outer), m_id(mat.m_outerIndex[outer]) + { + if(mat.isCompressed()) + m_end = mat.m_outerIndex[outer+1]; + else + m_end = m_id + mat.m_innerNonZeros[outer]; + } + + inline InnerIterator& operator++() { m_id++; return *this; } + + inline const Scalar& value() const { return m_values[m_id]; } + inline Scalar& valueRef() { return const_cast(m_values[m_id]); } + + inline Index index() const { return m_indices[m_id]; } + inline Index outer() const { return m_outer; } + inline Index row() const { return IsRowMajor ? m_outer : index(); } + inline Index col() const { return IsRowMajor ? index() : m_outer; } + + inline operator bool() const { return (m_id < m_end); } + + protected: + const Scalar* m_values; + const Index* m_indices; + const Index m_outer; + Index m_id; + Index m_end; +}; + +template +class SparseMatrix::ReverseInnerIterator +{ + public: + ReverseInnerIterator(const SparseMatrix& mat, Index outer) + : m_values(mat.valuePtr()), m_indices(mat.innerIndexPtr()), m_outer(outer), m_start(mat.m_outerIndex[outer]) + { + if(mat.isCompressed()) + m_id = mat.m_outerIndex[outer+1]; + else + m_id = m_start + mat.m_innerNonZeros[outer]; + } + + inline ReverseInnerIterator& operator--() { --m_id; return *this; } + + inline const Scalar& value() const { return m_values[m_id-1]; } + inline Scalar& valueRef() { return const_cast(m_values[m_id-1]); } + + inline Index index() const { return m_indices[m_id-1]; } + inline Index outer() const { return m_outer; } + inline Index row() const { return IsRowMajor ? m_outer : index(); } + inline Index col() const { return IsRowMajor ? index() : m_outer; } + + inline operator bool() const { return (m_id > m_start); } + + protected: + const Scalar* m_values; + const Index* m_indices; + const Index m_outer; + Index m_id; + const Index m_start; +}; + +namespace internal { + +template +void set_from_triplets(const InputIterator& begin, const InputIterator& end, SparseMatrixType& mat, int Options = 0) +{ + EIGEN_UNUSED_VARIABLE(Options); + enum { IsRowMajor = SparseMatrixType::IsRowMajor }; + typedef typename SparseMatrixType::Scalar Scalar; + typedef typename SparseMatrixType::Index Index; + SparseMatrix trMat(mat.rows(),mat.cols()); + + // pass 1: count the nnz per inner-vector + VectorXi wi(trMat.outerSize()); + wi.setZero(); + for(InputIterator it(begin); it!=end; ++it) + wi(IsRowMajor ? it->col() : it->row())++; + + // pass 2: insert all the elements into trMat + trMat.reserve(wi); + for(InputIterator it(begin); it!=end; ++it) + trMat.insertBackUncompressed(it->row(),it->col()) = it->value(); + + // pass 3: + trMat.sumupDuplicates(); + + // pass 4: transposed copy -> implicit sorting + mat = trMat; +} + +} + + +/** Fill the matrix \c *this with the list of \em triplets defined by the iterator range \a begin - \b. + * + * A \em triplet is a tuple (i,j,value) defining a non-zero element. + * The input list of triplets does not have to be sorted, and can contains duplicated elements. + * In any case, the result is a \b sorted and \b compressed sparse matrix where the duplicates have been summed up. + * This is a \em O(n) operation, with \em n the number of triplet elements. + * The initial contents of \c *this is destroyed. + * The matrix \c *this must be properly resized beforehand using the SparseMatrix(Index,Index) constructor, + * or the resize(Index,Index) method. The sizes are not extracted from the triplet list. + * + * The \a InputIterators value_type must provide the following interface: + * \code + * Scalar value() const; // the value + * Scalar row() const; // the row index i + * Scalar col() const; // the column index j + * \endcode + * See for instance the Eigen::Triplet template class. + * + * Here is a typical usage example: + * \code + typedef Triplet T; + std::vector tripletList; + triplets.reserve(estimation_of_entries); + for(...) + { + // ... + tripletList.push_back(T(i,j,v_ij)); + } + SparseMatrixType m(rows,cols); + m.setFromTriplets(tripletList.begin(), tripletList.end()); + // m is ready to go! + * \endcode + * + * \warning The list of triplets is read multiple times (at least twice). Therefore, it is not recommended to define + * an abstract iterator over a complex data-structure that would be expensive to evaluate. The triplets should rather + * be explicitely stored into a std::vector for instance. + */ +template +template +void SparseMatrix::setFromTriplets(const InputIterators& begin, const InputIterators& end) +{ + internal::set_from_triplets(begin, end, *this); +} + +/** \internal */ +template +void SparseMatrix::sumupDuplicates() +{ + eigen_assert(!isCompressed()); + // TODO, in practice we should be able to use m_innerNonZeros for that task + VectorXi wi(innerSize()); + wi.fill(-1); + Index count = 0; + // for each inner-vector, wi[inner_index] will hold the position of first element into the index/value buffers + for(int j=0; j=start) + { + // we already meet this entry => accumulate it + m_data.value(wi(i)) += m_data.value(k); + } + else + { + m_data.value(count) = m_data.value(k); + m_data.index(count) = m_data.index(k); + wi(i) = count; + ++count; + } + } + m_outerIndex[j] = start; + } + m_outerIndex[m_outerSize] = count; + + // turn the matrix into compressed form + delete[] m_innerNonZeros; + m_innerNonZeros = 0; + m_data.resize(m_outerIndex[m_outerSize]); +} + +} // end namespace Eigen + +#endif // EIGEN_SPARSEMATRIX_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseMatrixBase.h b/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseMatrixBase.h similarity index 55% rename from gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseMatrixBase.h rename to gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseMatrixBase.h index c01981bc9..9d7b83577 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseMatrixBase.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseMatrixBase.h @@ -1,7 +1,7 @@ // This file is part of Eigen, a lightweight C++ template library // for linear algebra. // -// Copyright (C) 2008-2009 Gael Guennebaud +// Copyright (C) 2008-2011 Gael Guennebaud // // Eigen is free software; you can redistribute it and/or // modify it under the terms of the GNU Lesser General Public @@ -25,7 +25,9 @@ #ifndef EIGEN_SPARSEMATRIXBASE_H #define EIGEN_SPARSEMATRIXBASE_H -/** \ingroup Sparse_Module +namespace Eigen { + +/** \ingroup SparseCore_Module * * \class SparseMatrixBase * @@ -44,6 +46,9 @@ template class SparseMatrixBase : public EigenBase typedef typename internal::packet_traits::type PacketScalar; typedef typename internal::traits::StorageKind StorageKind; typedef typename internal::traits::Index Index; + typedef typename internal::add_const_on_value_type_if_arithmetic< + typename internal::packet_traits::type + >::type PacketReturnType; typedef SparseMatrixBase StorageBaseType; typedef EigenBase Base; @@ -54,8 +59,6 @@ template class SparseMatrixBase : public EigenBase other.derived().evalTo(derived()); return derived(); } - -// using Base::operator=; enum { @@ -107,15 +110,6 @@ template class SparseMatrixBase : public EigenBase #endif }; - /* \internal the return type of MatrixBase::conjugate() */ -// typedef typename internal::conditional::IsComplex, -// const SparseCwiseUnaryOp, Derived>, -// const Derived& -// >::type ConjugateReturnType; - /* \internal the return type of MatrixBase::real() */ -// typedef SparseCwiseUnaryOp, Derived> RealReturnType; - /* \internal the return type of MatrixBase::imag() */ -// typedef SparseCwiseUnaryOp, Derived> ImagReturnType; /** \internal the return type of MatrixBase::adjoint() */ typedef typename internal::conditional::IsComplex, CwiseUnaryOp, Eigen::Transpose >, @@ -125,16 +119,6 @@ template class SparseMatrixBase : public EigenBase typedef SparseMatrix PlainObject; -#define EIGEN_CURRENT_STORAGE_BASE_CLASS Eigen::SparseMatrixBase -# include "../plugins/CommonCwiseUnaryOps.h" -# include "../plugins/CommonCwiseBinaryOps.h" -# include "../plugins/MatrixCwiseUnaryOps.h" -# include "../plugins/MatrixCwiseBinaryOps.h" -# ifdef EIGEN_SPARSEMATRIXBASE_PLUGIN -# include EIGEN_SPARSEMATRIXBASE_PLUGIN -# endif -# undef EIGEN_CURRENT_STORAGE_BASE_CLASS -#undef EIGEN_CURRENT_STORAGE_BASE_CLASS #ifndef EIGEN_PARSED_BY_DOXYGEN /** This is the "real scalar" type; if the \a Scalar type is already real numbers @@ -162,12 +146,24 @@ template class SparseMatrixBase : public EigenBase { return *static_cast(const_cast(this)); } #endif // not EIGEN_PARSED_BY_DOXYGEN - /** \returns the number of rows. \sa cols(), RowsAtCompileTime */ +#define EIGEN_CURRENT_STORAGE_BASE_CLASS Eigen::SparseMatrixBase +# include "../plugins/CommonCwiseUnaryOps.h" +# include "../plugins/CommonCwiseBinaryOps.h" +# include "../plugins/MatrixCwiseUnaryOps.h" +# include "../plugins/MatrixCwiseBinaryOps.h" +# ifdef EIGEN_SPARSEMATRIXBASE_PLUGIN +# include EIGEN_SPARSEMATRIXBASE_PLUGIN +# endif +# undef EIGEN_CURRENT_STORAGE_BASE_CLASS +#undef EIGEN_CURRENT_STORAGE_BASE_CLASS + + + /** \returns the number of rows. \sa cols() */ inline Index rows() const { return derived().rows(); } - /** \returns the number of columns. \sa rows(), ColsAtCompileTime*/ + /** \returns the number of columns. \sa rows() */ inline Index cols() const { return derived().cols(); } /** \returns the number of coefficients, which is \a rows()*cols(). - * \sa rows(), cols(), SizeAtCompileTime. */ + * \sa rows(), cols(). */ inline Index size() const { return rows() * cols(); } /** \returns the number of nonzero coefficients which is in practice the number * of stored coefficients. */ @@ -188,16 +184,7 @@ template class SparseMatrixBase : public EigenBase Derived& markAsRValue() { m_isRValue = true; return derived(); } SparseMatrixBase() : m_isRValue(false) { /* TODO check flags */ } - - inline Derived& operator=(const Derived& other) - { -// std::cout << "Derived& operator=(const Derived& other)\n"; -// if (other.isRValue()) -// derived().swap(other.const_cast_derived()); -// else - this->operator=(other); - return derived(); - } + template Derived& operator=(const ReturnByValue& other) @@ -207,10 +194,54 @@ template class SparseMatrixBase : public EigenBase } + template + inline Derived& operator=(const SparseMatrixBase& other) + { + return assign(other.derived()); + } + + inline Derived& operator=(const Derived& other) + { +// if (other.isRValue()) +// derived().swap(other.const_cast_derived()); +// else + return assign(other.derived()); + } + + protected: + + template + inline Derived& assign(const OtherDerived& other) + { + const bool transpose = (Flags & RowMajorBit) != (OtherDerived::Flags & RowMajorBit); + const Index outerSize = (int(OtherDerived::Flags) & RowMajorBit) ? other.rows() : other.cols(); + if ((!transpose) && other.isRValue()) + { + // eval without temporary + derived().resize(other.rows(), other.cols()); + derived().setZero(); + derived().reserve((std::max)(this->rows(),this->cols())*2); + for (Index j=0; j inline void assignGeneric(const OtherDerived& other) { -// std::cout << "Derived& operator=(const MatrixBase& other)\n"; //const bool transpose = (Flags & RowMajorBit) != (OtherDerived::Flags & RowMajorBit); eigen_assert(( ((internal::traits::SupportedAccessPatterns&OuterRandomAccessPattern)==OuterRandomAccessPattern) || (!((Flags & RowMajorBit) != (OtherDerived::Flags & RowMajorBit)))) && @@ -230,8 +261,7 @@ template class SparseMatrixBase : public EigenBase for (typename OtherDerived::InnerIterator it(other.derived(), j); it; ++it) { Scalar v = it.value(); - if (v!=Scalar(0)) - temp.insertBackByOuterInner(Flip?it.index():j,Flip?j:it.index()) = v; + temp.insertBackByOuterInner(Flip?it.index():j,Flip?j:it.index()) = v; } } temp.finalize(); @@ -239,54 +269,23 @@ template class SparseMatrixBase : public EigenBase derived() = temp.markAsRValue(); } - - template - inline Derived& operator=(const SparseMatrixBase& other) - { -// std::cout << typeid(OtherDerived).name() << "\n"; -// std::cout << Flags << " " << OtherDerived::Flags << "\n"; - const bool transpose = (Flags & RowMajorBit) != (OtherDerived::Flags & RowMajorBit); -// std::cout << "eval transpose = " << transpose << "\n"; - const Index outerSize = (int(OtherDerived::Flags) & RowMajorBit) ? other.rows() : other.cols(); - if ((!transpose) && other.isRValue()) - { - // eval without temporary - derived().resize(other.rows(), other.cols()); - derived().setZero(); - derived().reserve((std::max)(this->rows(),this->cols())*2); - for (Index j=0; j inline Derived& operator=(const SparseSparseProduct& product); - template - inline void _experimentalNewProduct(const Lhs& lhs, const Rhs& rhs); - friend std::ostream & operator << (std::ostream & s, const SparseMatrixBase& m) { + typedef typename Derived::Nested Nested; + typedef typename internal::remove_all::type NestedCleaned; + if (Flags&RowMajorBit) { - for (Index row=0; row class SparseMatrixBase : public EigenBase } else { + const Nested nm(m.derived()); if (m.cols() == 1) { Index row = 0; - for (typename Derived::InnerIterator it(m.derived(), 0); it; ++it) + for (typename NestedCleaned::InnerIterator it(nm.derived(), 0); it; ++it) { for ( ; row class SparseMatrixBase : public EigenBase } else { - SparseMatrix trans = m.derived(); - s << trans; + SparseMatrix trans = m; + s << static_cast >&>(trans); } } return s; } -// const SparseCwiseUnaryOp::Scalar>,Derived> operator-() const; - -// template -// const CwiseBinaryOp::Scalar>, Derived, OtherDerived> -// operator+(const SparseMatrixBase &other) const; - -// template -// const CwiseBinaryOp::Scalar>, Derived, OtherDerived> -// operator-(const SparseMatrixBase &other) const; - template Derived& operator+=(const SparseMatrixBase& other); template Derived& operator-=(const SparseMatrixBase& other); -// template -// Derived& operator+=(const Flagged, 0, EvalBeforeNestingBit | EvalBeforeAssigningBit>& other); - Derived& operator*=(const Scalar& other); Derived& operator/=(const Scalar& other); @@ -358,16 +345,6 @@ template class SparseMatrixBase : public EigenBase EIGEN_STRONG_INLINE const EIGEN_SPARSE_CWISE_PRODUCT_RETURN_TYPE cwiseProduct(const MatrixBase &other) const; -// const SparseCwiseUnaryOp::Scalar>, Derived> -// operator*(const Scalar& scalar) const; -// const SparseCwiseUnaryOp::Scalar>, Derived> -// operator/(const Scalar& scalar) const; - -// inline friend const SparseCwiseUnaryOp::Scalar>, Derived> -// operator*(const Scalar& scalar, const SparseMatrixBase& matrix) -// { return matrix*scalar; } - - // sparse * sparse template const typename SparseSparseProductReturnType::Type @@ -394,6 +371,12 @@ template class SparseMatrixBase : public EigenBase template const typename SparseDenseProductReturnType::Type operator*(const MatrixBase &other) const; + + /** \returns an expression of P H P^-1 where H is the matrix represented by \c *this */ + SparseSymmetricPermutationProduct twistedBy(const PermutationMatrix& perm) const + { + return SparseSymmetricPermutationProduct(derived(), perm); + } template Derived& operator*=(const SparseMatrixBase& other); @@ -407,8 +390,6 @@ template class SparseMatrixBase : public EigenBase // deprecated template void solveTriangularInPlace(MatrixBase& other) const; -// template -// void solveTriangularInPlace(SparseMatrixBase& other) const; #endif // EIGEN2_SUPPORT template @@ -421,12 +402,9 @@ template class SparseMatrixBase : public EigenBase template Scalar dot(const SparseMatrixBase& other) const; RealScalar squaredNorm() const; RealScalar norm() const; -// const PlainObject normalized() const; -// void normalize(); Transpose transpose() { return derived(); } const Transpose transpose() const { return derived(); } - // void transposeInPlace(); const AdjointReturnType adjoint() const { return transpose(); } // sub-vector @@ -442,77 +420,14 @@ template class SparseMatrixBase : public EigenBase const SparseInnerVectorSet subrows(Index start, Index size) const; SparseInnerVectorSet subcols(Index start, Index size); const SparseInnerVectorSet subcols(Index start, Index size) const; + + SparseInnerVectorSet middleRows(Index start, Index size); + const SparseInnerVectorSet middleRows(Index start, Index size) const; + SparseInnerVectorSet middleCols(Index start, Index size); + const SparseInnerVectorSet middleCols(Index start, Index size) const; SparseInnerVectorSet innerVectors(Index outerStart, Index outerSize); const SparseInnerVectorSet innerVectors(Index outerStart, Index outerSize) const; -// typename BlockReturnType::Type block(int startRow, int startCol, int blockRows, int blockCols); -// const typename BlockReturnType::Type -// block(int startRow, int startCol, int blockRows, int blockCols) const; -// -// typename BlockReturnType::SubVectorType segment(int start, int size); -// const typename BlockReturnType::SubVectorType segment(int start, int size) const; -// -// typename BlockReturnType::SubVectorType start(int size); -// const typename BlockReturnType::SubVectorType start(int size) const; -// -// typename BlockReturnType::SubVectorType end(int size); -// const typename BlockReturnType::SubVectorType end(int size) const; -// -// template -// typename BlockReturnType::Type block(int startRow, int startCol); -// template -// const typename BlockReturnType::Type block(int startRow, int startCol) const; - -// template typename BlockReturnType::SubVectorType start(void); -// template const typename BlockReturnType::SubVectorType start() const; - -// template typename BlockReturnType::SubVectorType end(); -// template const typename BlockReturnType::SubVectorType end() const; - -// template typename BlockReturnType::SubVectorType segment(int start); -// template const typename BlockReturnType::SubVectorType segment(int start) const; - -// Diagonal diagonal(); -// const Diagonal diagonal() const; - -// template Part part(); -// template const Part part() const; - - -// static const ConstantReturnType Constant(int rows, int cols, const Scalar& value); -// static const ConstantReturnType Constant(int size, const Scalar& value); -// static const ConstantReturnType Constant(const Scalar& value); - -// template -// static const CwiseNullaryOp NullaryExpr(int rows, int cols, const CustomNullaryOp& func); -// template -// static const CwiseNullaryOp NullaryExpr(int size, const CustomNullaryOp& func); -// template -// static const CwiseNullaryOp NullaryExpr(const CustomNullaryOp& func); - -// static const ConstantReturnType Zero(int rows, int cols); -// static const ConstantReturnType Zero(int size); -// static const ConstantReturnType Zero(); -// static const ConstantReturnType Ones(int rows, int cols); -// static const ConstantReturnType Ones(int size); -// static const ConstantReturnType Ones(); -// static const IdentityReturnType Identity(); -// static const IdentityReturnType Identity(int rows, int cols); -// static const BasisReturnType Unit(int size, int i); -// static const BasisReturnType Unit(int i); -// static const BasisReturnType UnitX(); -// static const BasisReturnType UnitY(); -// static const BasisReturnType UnitZ(); -// static const BasisReturnType UnitW(); - -// const DiagonalMatrix asDiagonal() const; - -// Derived& setConstant(const Scalar& value); -// Derived& setZero(); -// Derived& setOnes(); -// Derived& setRandom(); -// Derived& setIdentity(); - /** \internal use operator= */ template void evalTo(MatrixBase& dst) const @@ -537,37 +452,6 @@ template class SparseMatrixBase : public EigenBase bool isApprox(const MatrixBase& other, RealScalar prec = NumTraits::dummy_precision()) const { return toDense().isApprox(other,prec); } -// bool isMuchSmallerThan(const RealScalar& other, -// RealScalar prec = NumTraits::dummy_precision()) const; -// template -// bool isMuchSmallerThan(const MatrixBase& other, -// RealScalar prec = NumTraits::dummy_precision()) const; - -// bool isApproxToConstant(const Scalar& value, RealScalar prec = NumTraits::dummy_precision()) const; -// bool isZero(RealScalar prec = NumTraits::dummy_precision()) const; -// bool isOnes(RealScalar prec = NumTraits::dummy_precision()) const; -// bool isIdentity(RealScalar prec = NumTraits::dummy_precision()) const; -// bool isDiagonal(RealScalar prec = NumTraits::dummy_precision()) const; - -// bool isUpper(RealScalar prec = NumTraits::dummy_precision()) const; -// bool isLower(RealScalar prec = NumTraits::dummy_precision()) const; - -// template -// bool isOrthogonal(const MatrixBase& other, -// RealScalar prec = NumTraits::dummy_precision()) const; -// bool isUnitary(RealScalar prec = NumTraits::dummy_precision()) const; - -// template -// inline bool operator==(const MatrixBase& other) const -// { return (cwise() == other).all(); } - -// template -// inline bool operator!=(const MatrixBase& other) const -// { return (cwise() != other).any(); } - - -// template -// const SparseCwiseUnaryOp::Scalar, NewType>, Derived> cast() const; /** \returns the matrix or vector obtained by evaluating this expression. * @@ -577,130 +461,13 @@ template class SparseMatrixBase : public EigenBase inline const typename internal::eval::type eval() const { return typename internal::eval::type(derived()); } -// template -// void swap(MatrixBase const & other); - -// template -// const SparseFlagged marked() const; -// const Flagged lazy() const; - - /** \returns number of elements to skip to pass from one row (resp. column) to another - * for a row-major (resp. column-major) matrix. - * Combined with coeffRef() and the \ref flags flags, it allows a direct access to the data - * of the underlying matrix. - */ -// inline int stride(void) const { return derived().stride(); } - -// FIXME -// ConjugateReturnType conjugate() const; -// const RealReturnType real() const; -// const ImagReturnType imag() const; - -// template -// const SparseCwiseUnaryOp unaryExpr(const CustomUnaryOp& func = CustomUnaryOp()) const; - -// template -// const CwiseBinaryOp -// binaryExpr(const MatrixBase &other, const CustomBinaryOp& func = CustomBinaryOp()) const; - - Scalar sum() const; -// Scalar trace() const; - -// typename internal::traits::Scalar minCoeff() const; -// typename internal::traits::Scalar maxCoeff() const; - -// typename internal::traits::Scalar minCoeff(int* row, int* col = 0) const; -// typename internal::traits::Scalar maxCoeff(int* row, int* col = 0) const; - -// template -// typename internal::result_of::Scalar)>::type -// redux(const BinaryOp& func) const; - -// template -// void visit(Visitor& func) const; - - -// const SparseCwise cwise() const; -// SparseCwise cwise(); - -// inline const WithFormat format(const IOFormat& fmt) const; - -/////////// Array module /////////// - /* - bool all(void) const; - bool any(void) const; - - const VectorwiseOp rowwise() const; - const VectorwiseOp colwise() const; - - static const CwiseNullaryOp,Derived> Random(int rows, int cols); - static const CwiseNullaryOp,Derived> Random(int size); - static const CwiseNullaryOp,Derived> Random(); - - template - const Select - select(const MatrixBase& thenMatrix, - const MatrixBase& elseMatrix) const; - - template - inline const Select - select(const MatrixBase& thenMatrix, typename ThenDerived::Scalar elseScalar) const; - - template - inline const Select - select(typename ElseDerived::Scalar thenScalar, const MatrixBase& elseMatrix) const; - - template RealScalar lpNorm() const; - */ - - -// template -// Scalar dot(const MatrixBase& other) const -// { -// EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived) -// EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived) -// EIGEN_STATIC_ASSERT((internal::is_same::value), -// YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY) -// -// eigen_assert(derived().size() == other.size()); -// // short version, but the assembly looks more complicated because -// // of the CwiseBinaryOp iterator complexity -// // return res = (derived().cwise() * other.derived().conjugate()).sum(); -// -// // optimized, generic version -// typename Derived::InnerIterator i(derived(),0); -// typename OtherDerived::InnerIterator j(other.derived(),0); -// Scalar res = 0; -// while (i && j) -// { -// if (i.index()==j.index()) -// { -// // std::cerr << i.value() << " * " << j.value() << "\n"; -// res += i.value() * internal::conj(j.value()); -// ++i; ++j; -// } -// else if (i.index() +// +// Eigen is free software; you can redistribute it and/or +// modify it under the terms of the GNU Lesser General Public +// License as published by the Free Software Foundation; either +// version 3 of the License, or (at your option) any later version. +// +// Alternatively, you can redistribute it and/or +// modify it under the terms of the GNU General Public License as +// published by the Free Software Foundation; either version 2 of +// the License, or (at your option) any later version. +// +// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY +// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the +// GNU General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public +// License and a copy of the GNU General Public License along with +// Eigen. If not, see . + +#ifndef EIGEN_SPARSE_PERMUTATION_H +#define EIGEN_SPARSE_PERMUTATION_H + +// This file implements sparse * permutation products + +namespace Eigen { + +namespace internal { + +template +struct traits > +{ + typedef typename remove_all::type MatrixTypeNestedCleaned; + typedef typename MatrixTypeNestedCleaned::Scalar Scalar; + typedef typename MatrixTypeNestedCleaned::Index Index; + enum { + SrcStorageOrder = MatrixTypeNestedCleaned::Flags&RowMajorBit ? RowMajor : ColMajor, + MoveOuter = SrcStorageOrder==RowMajor ? Side==OnTheLeft : Side==OnTheRight + }; + + typedef typename internal::conditional, + SparseMatrix >::type ReturnType; +}; + +template +struct permut_sparsematrix_product_retval + : public ReturnByValue > +{ + typedef typename remove_all::type MatrixTypeNestedCleaned; + typedef typename MatrixTypeNestedCleaned::Scalar Scalar; + typedef typename MatrixTypeNestedCleaned::Index Index; + + enum { + SrcStorageOrder = MatrixTypeNestedCleaned::Flags&RowMajorBit ? RowMajor : ColMajor, + MoveOuter = SrcStorageOrder==RowMajor ? Side==OnTheLeft : Side==OnTheRight + }; + + permut_sparsematrix_product_retval(const PermutationType& perm, const MatrixType& matrix) + : m_permutation(perm), m_matrix(matrix) + {} + + inline int rows() const { return m_matrix.rows(); } + inline int cols() const { return m_matrix.cols(); } + + template inline void evalTo(Dest& dst) const + { + if(MoveOuter) + { + SparseMatrix tmp(m_matrix.rows(), m_matrix.cols()); + VectorXi sizes(m_matrix.outerSize()); + for(Index j=0; j tmp(m_matrix.rows(), m_matrix.cols()); + VectorXi sizes(tmp.outerSize()); + sizes.setZero(); + PermutationMatrix perm; + if((Side==OnTheLeft) ^ Transposed) + perm = m_permutation; + else + perm = m_permutation.transpose(); + + for(Index j=0; j +inline const internal::permut_sparsematrix_product_retval, SparseDerived, OnTheRight, false> +operator*(const SparseMatrixBase& matrix, const PermutationBase& perm) +{ + return internal::permut_sparsematrix_product_retval, SparseDerived, OnTheRight, false>(perm, matrix.derived()); +} + +/** \returns the matrix with the permutation applied to the rows + */ +template +inline const internal::permut_sparsematrix_product_retval, SparseDerived, OnTheLeft, false> +operator*( const PermutationBase& perm, const SparseMatrixBase& matrix) +{ + return internal::permut_sparsematrix_product_retval, SparseDerived, OnTheLeft, false>(perm, matrix.derived()); +} + + + +/** \returns the matrix with the inverse permutation applied to the columns. + */ +template +inline const internal::permut_sparsematrix_product_retval, SparseDerived, OnTheRight, true> +operator*(const SparseMatrixBase& matrix, const Transpose >& tperm) +{ + return internal::permut_sparsematrix_product_retval, SparseDerived, OnTheRight, true>(tperm.nestedPermutation(), matrix.derived()); +} + +/** \returns the matrix with the inverse permutation applied to the rows. + */ +template +inline const internal::permut_sparsematrix_product_retval, SparseDerived, OnTheLeft, true> +operator*(const Transpose >& tperm, const SparseMatrixBase& matrix) +{ + return internal::permut_sparsematrix_product_retval, SparseDerived, OnTheLeft, true>(tperm.nestedPermutation(), matrix.derived()); +} + +} // end namespace Eigen + +#endif // EIGEN_SPARSE_SELFADJOINTVIEW_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseProduct.h b/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseProduct.h similarity index 68% rename from gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseProduct.h rename to gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseProduct.h index 1c1f54706..813dbf624 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseProduct.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseProduct.h @@ -25,6 +25,8 @@ #ifndef EIGEN_SPARSEPRODUCT_H #define EIGEN_SPARSEPRODUCT_H +namespace Eigen { + template struct SparseSparseProductReturnType { @@ -38,11 +40,11 @@ struct SparseSparseProductReturnType typedef typename internal::conditional, - const typename internal::nested::type>::type LhsNested; + typename internal::nested::type>::type LhsNested; typedef typename internal::conditional, - const typename internal::nested::type>::type RhsNested; + typename internal::nested::type>::type RhsNested; typedef SparseSparseProduct Type; }; @@ -106,9 +108,42 @@ class SparseSparseProduct : internal::no_assignment_operator, template EIGEN_STRONG_INLINE SparseSparseProduct(const Lhs& lhs, const Rhs& rhs) - : m_lhs(lhs), m_rhs(rhs) + : m_lhs(lhs), m_rhs(rhs), m_tolerance(0), m_conservative(true) { - eigen_assert(lhs.cols() == rhs.rows()); + init(); + } + + template + EIGEN_STRONG_INLINE SparseSparseProduct(const Lhs& lhs, const Rhs& rhs, RealScalar tolerance) + : m_lhs(lhs), m_rhs(rhs), m_tolerance(tolerance), m_conservative(false) + { + init(); + } + + SparseSparseProduct pruned(Scalar reference = 0, RealScalar epsilon = NumTraits::dummy_precision()) const + { + return SparseSparseProduct(m_lhs,m_rhs,internal::abs(reference)*epsilon); + } + + template + void evalTo(Dest& result) const + { + if(m_conservative) + internal::conservative_sparse_sparse_product_selector<_LhsNested, _RhsNested, Dest>::run(lhs(),rhs(),result); + else + internal::sparse_sparse_product_with_pruning_selector<_LhsNested, _RhsNested, Dest>::run(lhs(),rhs(),result,m_tolerance); + } + + EIGEN_STRONG_INLINE Index rows() const { return m_lhs.rows(); } + EIGEN_STRONG_INLINE Index cols() const { return m_rhs.cols(); } + + EIGEN_STRONG_INLINE const _LhsNested& lhs() const { return m_lhs; } + EIGEN_STRONG_INLINE const _RhsNested& rhs() const { return m_rhs; } + + protected: + void init() + { + eigen_assert(m_lhs.cols() == m_rhs.rows()); enum { ProductIsValid = _LhsNested::ColsAtCompileTime==Dynamic @@ -127,15 +162,40 @@ class SparseSparseProduct : internal::no_assignment_operator, EIGEN_STATIC_ASSERT(ProductIsValid || SameSizes, INVALID_MATRIX_PRODUCT) } - EIGEN_STRONG_INLINE Index rows() const { return m_lhs.rows(); } - EIGEN_STRONG_INLINE Index cols() const { return m_rhs.cols(); } - - EIGEN_STRONG_INLINE const _LhsNested& lhs() const { return m_lhs; } - EIGEN_STRONG_INLINE const _RhsNested& rhs() const { return m_rhs; } - - protected: LhsNested m_lhs; RhsNested m_rhs; + RealScalar m_tolerance; + bool m_conservative; }; +// sparse = sparse * sparse +template +template +inline Derived& SparseMatrixBase::operator=(const SparseSparseProduct& product) +{ + product.evalTo(derived()); + return derived(); +} + +/** \returns an expression of the product of two sparse matrices. + * By default a conservative product preserving the symbolic non zeros is performed. + * The automatic pruning of the small values can be achieved by calling the pruned() function + * in which case a totally different product algorithm is employed: + * \code + * C = (A*B).pruned(); // supress numerical zeros (exact) + * C = (A*B).pruned(ref); + * C = (A*B).pruned(ref,epsilon); + * \endcode + * where \c ref is a meaningful non zero reference value. + * */ +template +template +inline const typename SparseSparseProductReturnType::Type +SparseMatrixBase::operator*(const SparseMatrixBase &other) const +{ + return typename SparseSparseProductReturnType::Type(derived(), other.derived()); +} + +} // end namespace Eigen + #endif // EIGEN_SPARSEPRODUCT_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseRedux.h b/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseRedux.h similarity index 97% rename from gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseRedux.h rename to gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseRedux.h index afc49de7a..73fb9a318 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseRedux.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseRedux.h @@ -25,12 +25,14 @@ #ifndef EIGEN_SPARSEREDUX_H #define EIGEN_SPARSEREDUX_H +namespace Eigen { + template typename internal::traits::Scalar SparseMatrixBase::sum() const { eigen_assert(rows()>0 && cols()>0 && "you are using a non initialized matrix"); - Scalar res = 0; + Scalar res(0); for (Index j=0; j::sum() const return Matrix::Map(&m_data.value(0), m_data.size()).sum(); } +} // end namespace Eigen + #endif // EIGEN_SPARSEREDUX_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseSelfAdjointView.h b/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseSelfAdjointView.h similarity index 77% rename from gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseSelfAdjointView.h rename to gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseSelfAdjointView.h index d82044c78..c925a894d 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseSelfAdjointView.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseSelfAdjointView.h @@ -25,8 +25,10 @@ #ifndef EIGEN_SPARSE_SELFADJOINTVIEW_H #define EIGEN_SPARSE_SELFADJOINTVIEW_H -/** \class SparseSelfAdjointView - * +namespace Eigen { + +/** \ingroup SparseCore_Module + * \class SparseSelfAdjointView * * \brief Pseudo expression to manipulate a triangular sparse matrix as a selfadjoint matrix. * @@ -45,9 +47,6 @@ class SparseSelfAdjointTimeDenseProduct; template class DenseTimeSparseSelfAdjointProduct; -template -class SparseSymmetricPermutationProduct; - namespace internal { template @@ -106,9 +105,6 @@ template class SparseSelfAdjointView * * \returns a reference to \c *this * - * Note that it is faster to set alpha=0 than initializing the matrix to zero - * and then keep the default value alpha=1. - * * To perform \f$ this = this + \alpha ( u^* u ) \f$ you can simply * call this function with u.adjoint(). */ @@ -116,21 +112,21 @@ template class SparseSelfAdjointView SparseSelfAdjointView& rankUpdate(const SparseMatrixBase& u, Scalar alpha = Scalar(1)); /** \internal triggered by sparse_matrix = SparseSelfadjointView; */ - template void evalTo(SparseMatrix& _dest) const + template void evalTo(SparseMatrix& _dest) const { internal::permute_symm_to_fullsymm(m_matrix, _dest); } - template void evalTo(DynamicSparseMatrix& _dest) const + template void evalTo(DynamicSparseMatrix& _dest) const { // TODO directly evaluate into _dest; - SparseMatrix tmp(_dest.rows(),_dest.cols()); + SparseMatrix tmp(_dest.rows(),_dest.cols()); internal::permute_symm_to_fullsymm(m_matrix, tmp); _dest = tmp; } - /** \returns an expression of P^-1 H P */ - SparseSymmetricPermutationProduct<_MatrixTypeNested,UpLo> twistedBy(const PermutationMatrix& perm) const + /** \returns an expression of P H P^-1 */ + SparseSymmetricPermutationProduct<_MatrixTypeNested,UpLo> twistedBy(const PermutationMatrix& perm) const { return SparseSymmetricPermutationProduct<_MatrixTypeNested,UpLo>(m_matrix, perm); } @@ -141,6 +137,20 @@ template class SparseSelfAdjointView permutedMatrix.evalTo(*this); return *this; } + + + SparseSelfAdjointView& operator=(const SparseSelfAdjointView& src) + { + PermutationMatrix pnull; + return *this = src.twistedBy(pnull); + } + + template + SparseSelfAdjointView& operator=(const SparseSelfAdjointView& src) + { + PermutationMatrix pnull; + return *this = src.twistedBy(pnull); + } // const SparseLLT llt() const; @@ -148,7 +158,7 @@ template class SparseSelfAdjointView protected: - const typename MatrixType::Nested m_matrix; + typename MatrixType::Nested m_matrix; mutable VectorI m_countPerRow; mutable VectorI m_countPerCol; }; @@ -230,12 +240,15 @@ class SparseSelfAdjointTimeDenseProduct for (Index j=0; j dest_j(dest.row(LhsIsRowMajor ? j : 0)); for(; (ProcessFirstHalf ? i && i.index() < j : i) ; ++i) { Index a = LhsIsRowMajor ? j : i.index(); @@ -300,7 +313,7 @@ void permute_symm_to_fullsymm(const MatrixType& mat, SparseMatrixj) || (UpLo==Upper && ic) || ( UpLo==Upper && rj) || (UpLo==Upper && ic) || ( (UpLo&Upper)==Upper && r -void permute_symm_to_symm(const MatrixType& mat, SparseMatrix& _dest, const typename MatrixType::Index* perm) +template +void permute_symm_to_symm(const MatrixType& mat, SparseMatrix& _dest, const typename MatrixType::Index* perm) { typedef typename MatrixType::Index Index; typedef typename MatrixType::Scalar Scalar; - typedef SparseMatrix Dest; - Dest& dest(_dest.derived()); + SparseMatrix& dest(_dest.derived()); typedef Matrix VectorI; - //internal::conj_if cj; + enum { + SrcOrder = MatrixType::IsRowMajor ? RowMajor : ColMajor, + StorageOrderMatch = int(SrcOrder) == int(DstOrder), + DstUpLo = DstOrder==RowMajor ? (_DstUpLo==Upper ? Lower : Upper) : _DstUpLo, + SrcUpLo = SrcOrder==RowMajor ? (_SrcUpLo==Upper ? Lower : Upper) : _SrcUpLo + }; Index size = mat.rows(); VectorI count(size); @@ -379,37 +412,40 @@ void permute_symm_to_symm(const MatrixType& mat, SparseMatrixj)) + if((int(SrcUpLo)==int(Lower) && ij)) continue; Index ip = perm ? perm[i] : i; - count[DstUpLo==Lower ? (std::min)(ip,jp) : (std::max)(ip,jp)]++; + count[int(DstUpLo)==int(Lower) ? (std::min)(ip,jp) : (std::max)(ip,jp)]++; } } - dest._outerIndexPtr()[0] = 0; + dest.outerIndexPtr()[0] = 0; for(Index j=0; jj)) + if((int(SrcUpLo)==int(Lower) && ij)) continue; + Index jp = perm ? perm[j] : j; Index ip = perm? perm[i] : i; - Index k = count[DstUpLo==Lower ? (std::min)(ip,jp) : (std::max)(ip,jp)]++; - dest._innerIndexPtr()[k] = DstUpLo==Lower ? (std::max)(ip,jp) : (std::min)(ip,jp); - if((DstUpLo==Lower && ipjp)) - dest._valuePtr()[k] = conj(it.value()); + Index k = count[int(DstUpLo)==int(Lower) ? (std::min)(ip,jp) : (std::max)(ip,jp)]++; + dest.innerIndexPtr()[k] = int(DstUpLo)==int(Lower) ? (std::max)(ip,jp) : (std::min)(ip,jp); + + if(!StorageOrderMatch) std::swap(ip,jp); + if( ((int(DstUpLo)==int(Lower) && ipjp))) + dest.valuePtr()[k] = conj(it.value()); else - dest._valuePtr()[k] = it.value(); + dest.valuePtr()[k] = it.value(); } } } @@ -420,10 +456,12 @@ template class SparseSymmetricPermutationProduct : public EigenBase > { - typedef PermutationMatrix Perm; public: typedef typename MatrixType::Scalar Scalar; typedef typename MatrixType::Index Index; + protected: + typedef PermutationMatrix Perm; + public: typedef Matrix VectorI; typedef typename MatrixType::Nested MatrixTypeNested; typedef typename internal::remove_all::type _MatrixTypeNested; @@ -435,7 +473,8 @@ class SparseSymmetricPermutationProduct inline Index rows() const { return m_matrix.rows(); } inline Index cols() const { return m_matrix.cols(); } - template void evalTo(SparseMatrix& _dest) const + template + void evalTo(SparseMatrix& _dest) const { internal::permute_symm_to_fullsymm(m_matrix,_dest,m_perm.indices().data()); } @@ -446,9 +485,11 @@ class SparseSymmetricPermutationProduct } protected: - const MatrixTypeNested m_matrix; + MatrixTypeNested m_matrix; const Perm& m_perm; }; +} // end namespace Eigen + #endif // EIGEN_SPARSE_SELFADJOINTVIEW_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseSparseProductWithPruning.h b/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseSparseProductWithPruning.h new file mode 100644 index 000000000..abd4fda82 --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseSparseProductWithPruning.h @@ -0,0 +1,164 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2008-2011 Gael Guennebaud +// +// Eigen is free software; you can redistribute it and/or +// modify it under the terms of the GNU Lesser General Public +// License as published by the Free Software Foundation; either +// version 3 of the License, or (at your option) any later version. +// +// Alternatively, you can redistribute it and/or +// modify it under the terms of the GNU General Public License as +// published by the Free Software Foundation; either version 2 of +// the License, or (at your option) any later version. +// +// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY +// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the +// GNU General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public +// License and a copy of the GNU General Public License along with +// Eigen. If not, see . + +#ifndef EIGEN_SPARSESPARSEPRODUCTWITHPRUNING_H +#define EIGEN_SPARSESPARSEPRODUCTWITHPRUNING_H + +namespace Eigen { + +namespace internal { + + +// perform a pseudo in-place sparse * sparse product assuming all matrices are col major +template +static void sparse_sparse_product_with_pruning_impl(const Lhs& lhs, const Rhs& rhs, ResultType& res, typename ResultType::RealScalar tolerance) +{ + // return sparse_sparse_product_with_pruning_impl2(lhs,rhs,res); + + typedef typename remove_all::type::Scalar Scalar; + typedef typename remove_all::type::Index Index; + + // make sure to call innerSize/outerSize since we fake the storage order. + Index rows = lhs.innerSize(); + Index cols = rhs.outerSize(); + //int size = lhs.outerSize(); + eigen_assert(lhs.outerSize() == rhs.innerSize()); + + // allocate a temporary buffer + AmbiVector tempVector(rows); + + // estimate the number of non zero entries + // given a rhs column containing Y non zeros, we assume that the respective Y columns + // of the lhs differs in average of one non zeros, thus the number of non zeros for + // the product of a rhs column with the lhs is X+Y where X is the average number of non zero + // per column of the lhs. + // Therefore, we have nnz(lhs*rhs) = nnz(lhs) + nnz(rhs) + Index estimated_nnz_prod = lhs.nonZeros() + rhs.nonZeros(); + + // mimics a resizeByInnerOuter: + if(ResultType::IsRowMajor) + res.resize(cols, rows); + else + res.resize(rows, cols); + + res.reserve(estimated_nnz_prod); + double ratioColRes = double(estimated_nnz_prod)/double(lhs.rows()*rhs.cols()); + for (Index j=0; j::Iterator it(tempVector,tolerance); it; ++it) + res.insertBackByOuterInner(j,it.index()) = it.value(); + } + res.finalize(); +} + +template::Flags&RowMajorBit, + int RhsStorageOrder = traits::Flags&RowMajorBit, + int ResStorageOrder = traits::Flags&RowMajorBit> +struct sparse_sparse_product_with_pruning_selector; + +template +struct sparse_sparse_product_with_pruning_selector +{ + typedef typename traits::type>::Scalar Scalar; + typedef typename ResultType::RealScalar RealScalar; + + static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res, RealScalar tolerance) + { + typename remove_all::type _res(res.rows(), res.cols()); + internal::sparse_sparse_product_with_pruning_impl(lhs, rhs, _res, tolerance); + res.swap(_res); + } +}; + +template +struct sparse_sparse_product_with_pruning_selector +{ + typedef typename ResultType::RealScalar RealScalar; + static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res, RealScalar tolerance) + { + // we need a col-major matrix to hold the result + typedef SparseMatrix SparseTemporaryType; + SparseTemporaryType _res(res.rows(), res.cols()); + internal::sparse_sparse_product_with_pruning_impl(lhs, rhs, _res, tolerance); + res = _res; + } +}; + +template +struct sparse_sparse_product_with_pruning_selector +{ + typedef typename ResultType::RealScalar RealScalar; + static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res, RealScalar tolerance) + { + // let's transpose the product to get a column x column product + typename remove_all::type _res(res.rows(), res.cols()); + internal::sparse_sparse_product_with_pruning_impl(rhs, lhs, _res, tolerance); + res.swap(_res); + } +}; + +template +struct sparse_sparse_product_with_pruning_selector +{ + typedef typename ResultType::RealScalar RealScalar; + static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res, RealScalar tolerance) + { + typedef SparseMatrix ColMajorMatrix; + ColMajorMatrix colLhs(lhs); + ColMajorMatrix colRhs(rhs); + internal::sparse_sparse_product_with_pruning_impl(colLhs, colRhs, res, tolerance); + + // let's transpose the product to get a column x column product +// typedef SparseMatrix SparseTemporaryType; +// SparseTemporaryType _res(res.cols(), res.rows()); +// sparse_sparse_product_with_pruning_impl(rhs, lhs, _res); +// res = _res.transpose(); + } +}; + +// NOTE the 2 others cases (col row *) must never occur since they are caught +// by ProductReturnType which transforms it to (col col *) by evaluating rhs. + +} // end namespace internal + +} // end namespace Eigen + +#endif // EIGEN_SPARSESPARSEPRODUCTWITHPRUNING_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseTranspose.h b/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseTranspose.h similarity index 73% rename from gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseTranspose.h rename to gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseTranspose.h index 2aea2fa32..07d9e0bbd 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseTranspose.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseTranspose.h @@ -25,6 +25,8 @@ #ifndef EIGEN_SPARSETRANSPOSE_H #define EIGEN_SPARSETRANSPOSE_H +namespace Eigen { + template class TransposeImpl : public SparseMatrixBase > { @@ -39,17 +41,21 @@ template class TransposeImpl inline Index nonZeros() const { return derived().nestedExpression().nonZeros(); } }; +// NOTE: VC10 trigger an ICE if don't put typename TransposeImpl:: in front of Index, +// a typedef typename TransposeImpl::Index Index; +// does not fix the issue. +// An alternative is to define the nested class in the parent class itself. template class TransposeImpl::InnerIterator : public _MatrixTypeNested::InnerIterator { typedef typename _MatrixTypeNested::InnerIterator Base; public: - EIGEN_STRONG_INLINE InnerIterator(const TransposeImpl& trans, Index outer) + EIGEN_STRONG_INLINE InnerIterator(const TransposeImpl& trans, typename TransposeImpl::Index outer) : Base(trans.derived().nestedExpression(), outer) {} - inline Index row() const { return Base::col(); } - inline Index col() const { return Base::row(); } + inline typename TransposeImpl::Index row() const { return Base::col(); } + inline typename TransposeImpl::Index col() const { return Base::row(); } }; template class TransposeImpl::ReverseInnerIterator @@ -58,11 +64,13 @@ template class TransposeImpl::ReverseInn typedef typename _MatrixTypeNested::ReverseInnerIterator Base; public: - EIGEN_STRONG_INLINE ReverseInnerIterator(const TransposeImpl& xpr, Index outer) + EIGEN_STRONG_INLINE ReverseInnerIterator(const TransposeImpl& xpr, typename TransposeImpl::Index outer) : Base(xpr.derived().nestedExpression(), outer) {} - inline Index row() const { return Base::col(); } - inline Index col() const { return Base::row(); } + inline typename TransposeImpl::Index row() const { return Base::col(); } + inline typename TransposeImpl::Index col() const { return Base::row(); } }; +} // end namespace Eigen + #endif // EIGEN_SPARSETRANSPOSE_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseTriangularView.h b/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseTriangularView.h new file mode 100644 index 000000000..59aab5756 --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseTriangularView.h @@ -0,0 +1,179 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2009 Gael Guennebaud +// +// Eigen is free software; you can redistribute it and/or +// modify it under the terms of the GNU Lesser General Public +// License as published by the Free Software Foundation; either +// version 3 of the License, or (at your option) any later version. +// +// Alternatively, you can redistribute it and/or +// modify it under the terms of the GNU General Public License as +// published by the Free Software Foundation; either version 2 of +// the License, or (at your option) any later version. +// +// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY +// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the +// GNU General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public +// License and a copy of the GNU General Public License along with +// Eigen. If not, see . + +#ifndef EIGEN_SPARSE_TRIANGULARVIEW_H +#define EIGEN_SPARSE_TRIANGULARVIEW_H + +namespace Eigen { + +namespace internal { + +template +struct traits > +: public traits +{}; + +} // namespace internal + +template class SparseTriangularView + : public SparseMatrixBase > +{ + enum { SkipFirst = ((Mode&Lower) && !(MatrixType::Flags&RowMajorBit)) + || ((Mode&Upper) && (MatrixType::Flags&RowMajorBit)), + SkipLast = !SkipFirst, + HasUnitDiag = (Mode&UnitDiag) ? 1 : 0 + }; + + public: + + EIGEN_SPARSE_PUBLIC_INTERFACE(SparseTriangularView) + + class InnerIterator; + class ReverseInnerIterator; + + inline Index rows() const { return m_matrix.rows(); } + inline Index cols() const { return m_matrix.cols(); } + + typedef typename MatrixType::Nested MatrixTypeNested; + typedef typename internal::remove_reference::type MatrixTypeNestedNonRef; + typedef typename internal::remove_all::type MatrixTypeNestedCleaned; + + inline SparseTriangularView(const MatrixType& matrix) : m_matrix(matrix) {} + + /** \internal */ + inline const MatrixTypeNestedCleaned& nestedExpression() const { return m_matrix; } + + template + typename internal::plain_matrix_type_column_major::type + solve(const MatrixBase& other) const; + + template void solveInPlace(MatrixBase& other) const; + template void solveInPlace(SparseMatrixBase& other) const; + + protected: + MatrixTypeNested m_matrix; +}; + +template +class SparseTriangularView::InnerIterator : public MatrixTypeNestedCleaned::InnerIterator +{ + typedef typename MatrixTypeNestedCleaned::InnerIterator Base; + public: + + EIGEN_STRONG_INLINE InnerIterator(const SparseTriangularView& view, Index outer) + : Base(view.nestedExpression(), outer), m_returnOne(false) + { + if(SkipFirst) + { + while((*this) && (HasUnitDiag ? this->index()<=outer : this->index()=Base::outer())) + { + if((!SkipFirst) && Base::operator bool()) + Base::operator++(); + m_returnOne = true; + } + } + + EIGEN_STRONG_INLINE InnerIterator& operator++() + { + if(HasUnitDiag && m_returnOne) + m_returnOne = false; + else + { + Base::operator++(); + if(HasUnitDiag && (!SkipFirst) && ((!Base::operator bool()) || Base::index()>=Base::outer())) + { + if((!SkipFirst) && Base::operator bool()) + Base::operator++(); + m_returnOne = true; + } + } + return *this; + } + + inline Index row() const { return Base::row(); } + inline Index col() const { return Base::col(); } + inline Index index() const + { + if(HasUnitDiag && m_returnOne) return Base::outer(); + else return Base::index(); + } + inline Scalar value() const + { + if(HasUnitDiag && m_returnOne) return Scalar(1); + else return Base::value(); + } + + EIGEN_STRONG_INLINE operator bool() const + { + if(HasUnitDiag && m_returnOne) + return true; + return (SkipFirst ? Base::operator bool() : (Base::operator bool() && this->index() <= this->outer())); + } + protected: + bool m_returnOne; +}; + +template +class SparseTriangularView::ReverseInnerIterator : public MatrixTypeNestedCleaned::ReverseInnerIterator +{ + typedef typename MatrixTypeNestedCleaned::ReverseInnerIterator Base; + public: + + EIGEN_STRONG_INLINE ReverseInnerIterator(const SparseTriangularView& view, Index outer) + : Base(view.nestedExpression(), outer) + { + eigen_assert((!HasUnitDiag) && "ReverseInnerIterator does not support yet triangular views with a unit diagonal"); + if(SkipLast) + while((*this) && this->index()>outer) + --(*this); + } + + EIGEN_STRONG_INLINE InnerIterator& operator--() + { Base::operator--(); return *this; } + + inline Index row() const { return Base::row(); } + inline Index col() const { return Base::col(); } + + EIGEN_STRONG_INLINE operator bool() const + { + return SkipLast ? Base::operator bool() : (Base::operator bool() && this->index() >= this->outer()); + } +}; + +template +template +inline const SparseTriangularView +SparseMatrixBase::triangularView() const +{ + return derived(); +} + +} // end namespace Eigen + +#endif // EIGEN_SPARSE_TRIANGULARVIEW_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseUtil.h b/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseUtil.h similarity index 67% rename from gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseUtil.h rename to gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseUtil.h index db9ae98e7..050b65253 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseUtil.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseUtil.h @@ -25,6 +25,8 @@ #ifndef EIGEN_SPARSEUTIL_H #define EIGEN_SPARSEUTIL_H +namespace Eigen { + #ifdef NDEBUG #define EIGEN_DBG_SPARSE(X) #else @@ -58,22 +60,22 @@ EIGEN_SPARSE_INHERIT_SCALAR_ASSIGNMENT_OPERATOR(Derived, /=) #define _EIGEN_SPARSE_PUBLIC_INTERFACE(Derived, BaseClass) \ typedef BaseClass Base; \ - typedef typename Eigen::internal::traits::Scalar Scalar; \ + typedef typename Eigen::internal::traits::Scalar Scalar; \ typedef typename Eigen::NumTraits::Real RealScalar; \ - typedef typename Eigen::internal::nested::type Nested; \ - typedef typename Eigen::internal::traits::StorageKind StorageKind; \ - typedef typename Eigen::internal::traits::Index Index; \ - enum { RowsAtCompileTime = Eigen::internal::traits::RowsAtCompileTime, \ - ColsAtCompileTime = Eigen::internal::traits::ColsAtCompileTime, \ - Flags = Eigen::internal::traits::Flags, \ - CoeffReadCost = Eigen::internal::traits::CoeffReadCost, \ + typedef typename Eigen::internal::nested::type Nested; \ + typedef typename Eigen::internal::traits::StorageKind StorageKind; \ + typedef typename Eigen::internal::traits::Index Index; \ + enum { RowsAtCompileTime = Eigen::internal::traits::RowsAtCompileTime, \ + ColsAtCompileTime = Eigen::internal::traits::ColsAtCompileTime, \ + Flags = Eigen::internal::traits::Flags, \ + CoeffReadCost = Eigen::internal::traits::CoeffReadCost, \ SizeAtCompileTime = Base::SizeAtCompileTime, \ IsVectorAtCompileTime = Base::IsVectorAtCompileTime }; \ using Base::derived; \ using Base::const_cast_derived; #define EIGEN_SPARSE_PUBLIC_INTERFACE(Derived) \ - _EIGEN_SPARSE_PUBLIC_INTERFACE(Derived, Eigen::SparseMatrixBase) + _EIGEN_SPARSE_PUBLIC_INTERFACE(Derived, Eigen::SparseMatrixBase) const int CoherentAccessPattern = 0x1; const int InnerRandomAccessPattern = 0x2 | CoherentAccessPattern; @@ -100,20 +102,43 @@ template class SparseDenseOuterProdu template struct SparseSparseProductReturnType; template::ColsAtCompileTime> struct DenseSparseProductReturnType; template::ColsAtCompileTime> struct SparseDenseProductReturnType; +template class SparseSymmetricPermutationProduct; namespace internal { -template struct eval -{ - typedef typename traits::Scalar _Scalar; - enum { - _Flags = traits::Flags - }; +template struct sparse_eval; +template struct eval + : public sparse_eval::RowsAtCompileTime,traits::ColsAtCompileTime> +{}; + +template struct sparse_eval { + typedef typename traits::Scalar _Scalar; + enum { _Flags = traits::Flags| RowMajorBit }; + public: + typedef SparseVector<_Scalar, _Flags> type; +}; + +template struct sparse_eval { + typedef typename traits::Scalar _Scalar; + enum { _Flags = traits::Flags & (~RowMajorBit) }; + public: + typedef SparseVector<_Scalar, _Flags> type; +}; + +template struct sparse_eval { + typedef typename traits::Scalar _Scalar; + enum { _Flags = traits::Flags }; public: typedef SparseMatrix<_Scalar, _Flags> type; }; +template struct sparse_eval { + typedef typename traits::Scalar _Scalar; + public: + typedef Matrix<_Scalar, 1, 1> type; +}; + template struct plain_matrix_type { typedef typename traits::Scalar _Scalar; @@ -127,4 +152,37 @@ template struct plain_matrix_type } // end namespace internal +/** \ingroup SparseCore_Module + * + * \class Triplet + * + * \brief A small structure to hold a non zero as a triplet (i,j,value). + * + * \sa SparseMatrix::setFromTriplets() + */ +template +class Triplet +{ +public: + Triplet() : m_row(0), m_col(0), m_value(0) {} + + Triplet(const Index& i, const Index& j, const Scalar& v = Scalar(0)) + : m_row(i), m_col(j), m_value(v) + {} + + /** \returns the row index of the element */ + const Index& row() const { return m_row; } + + /** \returns the column index of the element */ + const Index& col() const { return m_col; } + + /** \returns the value of the element */ + const Scalar& value() const { return m_value; } +protected: + Index m_row, m_col; + Scalar m_value; +}; + +} // end namespace Eigen + #endif // EIGEN_SPARSEUTIL_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseVector.h b/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseVector.h similarity index 70% rename from gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseVector.h rename to gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseVector.h index ce4bb51a2..e81347705 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseVector.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseVector.h @@ -25,7 +25,10 @@ #ifndef EIGEN_SPARSEVECTOR_H #define EIGEN_SPARSEVECTOR_H -/** \class SparseVector +namespace Eigen { + +/** \ingroup SparseCore_Module + * \class SparseVector * * \brief a sparse vector class * @@ -46,13 +49,13 @@ struct traits > typedef Sparse StorageKind; typedef MatrixXpr XprKind; enum { - IsColVector = _Options & RowMajorBit ? 0 : 1, + IsColVector = (_Options & RowMajorBit) ? 0 : 1, RowsAtCompileTime = IsColVector ? Dynamic : 1, ColsAtCompileTime = IsColVector ? 1 : Dynamic, MaxRowsAtCompileTime = RowsAtCompileTime, MaxColsAtCompileTime = ColsAtCompileTime, - Flags = _Options | NestByRefBit | LvalueBit, + Flags = _Options | NestByRefBit | LvalueBit | (IsColVector ? 0 : RowMajorBit), CoeffReadCost = NumTraits::ReadCost, SupportedAccessPatterns = InnerRandomAccessPattern }; @@ -67,7 +70,6 @@ class SparseVector EIGEN_SPARSE_PUBLIC_INTERFACE(SparseVector) EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(SparseVector, +=) EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(SparseVector, -=) -// EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(SparseVector, =) protected: public: @@ -79,11 +81,11 @@ class SparseVector Options = _Options }; - CompressedStorage m_data; + internal::CompressedStorage m_data; Index m_size; - CompressedStorage& _data() { return m_data; } - CompressedStorage& _data() const { return m_data; } + internal::CompressedStorage& _data() { return m_data; } + internal::CompressedStorage& _data() const { return m_data; } public: @@ -91,13 +93,12 @@ class SparseVector EIGEN_STRONG_INLINE Index cols() const { return IsColVector ? 1 : m_size; } EIGEN_STRONG_INLINE Index innerSize() const { return m_size; } EIGEN_STRONG_INLINE Index outerSize() const { return 1; } - EIGEN_STRONG_INLINE Index innerNonZeros(Index j) const { eigen_assert(j==0); return m_size; } - EIGEN_STRONG_INLINE const Scalar* _valuePtr() const { return &m_data.value(0); } - EIGEN_STRONG_INLINE Scalar* _valuePtr() { return &m_data.value(0); } + EIGEN_STRONG_INLINE const Scalar* valuePtr() const { return &m_data.value(0); } + EIGEN_STRONG_INLINE Scalar* valuePtr() { return &m_data.value(0); } - EIGEN_STRONG_INLINE const Index* _innerIndexPtr() const { return &m_data.index(0); } - EIGEN_STRONG_INLINE Index* _innerIndexPtr() { return &m_data.index(0); } + EIGEN_STRONG_INLINE const Index* innerIndexPtr() const { return &m_data.index(0); } + EIGEN_STRONG_INLINE Index* innerIndexPtr() { return &m_data.index(0); } inline Scalar coeff(Index row, Index col) const { @@ -126,6 +127,7 @@ class SparseVector public: class InnerIterator; + class ReverseInnerIterator; inline void setZero() { m_data.clear(); } @@ -134,11 +136,13 @@ class SparseVector inline void startVec(Index outer) { + EIGEN_UNUSED_VARIABLE(outer); eigen_assert(outer==0); } inline Scalar& insertBackByOuterInner(Index outer, Index inner) { + EIGEN_UNUSED_VARIABLE(outer); eigen_assert(outer==0); return insertBack(inner); } @@ -158,7 +162,7 @@ class SparseVector Scalar& insert(Index i) { Index startId = 0; - Index p = m_data.size() - 1; + Index p = Index(m_data.size()) - 1; // TODO smart realloc m_data.resize(p+2,1); @@ -205,13 +209,6 @@ class SparseVector inline SparseVector(Index rows, Index cols) : m_size(0) { resize(rows,cols); } - template - inline SparseVector(const MatrixBase& other) - : m_size(0) - { - *this = other.derived(); - } - template inline SparseVector(const SparseMatrixBase& other) : m_size(0) @@ -249,9 +246,9 @@ class SparseVector inline SparseVector& operator=(const SparseMatrixBase& other) { if (int(RowsAtCompileTime)!=int(OtherDerived::RowsAtCompileTime)) - return Base::operator=(other.transpose()); + return assign(other.transpose()); else - return Base::operator=(other); + return assign(other); } #ifndef EIGEN_PARSED_BY_DOXYGEN @@ -262,56 +259,6 @@ class SparseVector } #endif -// const bool needToTranspose = (Flags & RowMajorBit) != (OtherDerived::Flags & RowMajorBit); -// if (needToTranspose) -// { -// // two passes algorithm: -// // 1 - compute the number of coeffs per dest inner vector -// // 2 - do the actual copy/eval -// // Since each coeff of the rhs has to be evaluated twice, let's evauluate it if needed -// typedef typename internal::nested::type OtherCopy; -// OtherCopy otherCopy(other.derived()); -// typedef typename internal::remove_all::type _OtherCopy; -// -// resize(other.rows(), other.cols()); -// Eigen::Map(m_outerIndex,outerSize()).setZero(); -// // pass 1 -// // FIXME the above copy could be merged with that pass -// for (int j=0; j::operator=(other.derived()); -// } -// } - friend std::ostream & operator << (std::ostream & s, const SparseVector& m) { for (Index i=0; i + EIGEN_DONT_INLINE SparseVector& assign(const SparseMatrixBase& _other) + { + const OtherDerived& other(_other.derived()); + const bool needToTranspose = (Flags & RowMajorBit) != (OtherDerived::Flags & RowMajorBit); + if(needToTranspose) + { + Index size = other.size(); + Index nnz = other.nonZeros(); + resize(size); + reserve(nnz); + for(Index i=0; i @@ -399,18 +351,14 @@ class SparseVector::InnerIterator InnerIterator(const SparseVector& vec, Index outer=0) : m_data(vec.m_data), m_id(0), m_end(static_cast(m_data.size())) { + EIGEN_UNUSED_VARIABLE(outer); eigen_assert(outer==0); } - InnerIterator(const CompressedStorage& data) + InnerIterator(const internal::CompressedStorage& data) : m_data(data), m_id(0), m_end(static_cast(m_data.size())) {} - template - InnerIterator(const Flagged& vec, Index ) - : m_data(vec._expression().m_data), m_id(0), m_end(m_data.size()) - {} - inline InnerIterator& operator++() { m_id++; return *this; } inline Scalar value() const { return m_data.value(m_id); } @@ -423,9 +371,43 @@ class SparseVector::InnerIterator inline operator bool() const { return (m_id < m_end); } protected: - const CompressedStorage& m_data; + const internal::CompressedStorage& m_data; Index m_id; const Index m_end; }; +template +class SparseVector::ReverseInnerIterator +{ + public: + ReverseInnerIterator(const SparseVector& vec, Index outer=0) + : m_data(vec.m_data), m_id(static_cast(m_data.size())), m_start(0) + { + EIGEN_UNUSED_VARIABLE(outer); + eigen_assert(outer==0); + } + + ReverseInnerIterator(const internal::CompressedStorage& data) + : m_data(data), m_id(static_cast(m_data.size())), m_start(0) + {} + + inline ReverseInnerIterator& operator--() { m_id--; return *this; } + + inline Scalar value() const { return m_data.value(m_id-1); } + inline Scalar& valueRef() { return const_cast(m_data.value(m_id-1)); } + + inline Index index() const { return m_data.index(m_id-1); } + inline Index row() const { return IsColVector ? index() : 0; } + inline Index col() const { return IsColVector ? 0 : index(); } + + inline operator bool() const { return (m_id > m_start); } + + protected: + const internal::CompressedStorage& m_data; + Index m_id; + const Index m_start; +}; + +} // end namespace Eigen + #endif // EIGEN_SPARSEVECTOR_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseView.h b/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseView.h similarity index 91% rename from gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseView.h rename to gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseView.h index 243065610..43a3adb24 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Sparse/SparseView.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/SparseView.h @@ -1,7 +1,7 @@ // This file is part of Eigen, a lightweight C++ template library // for linear algebra. // -// Copyright (C) 2010 Gael Guennebaud +// Copyright (C) 2011 Gael Guennebaud // Copyright (C) 2010 Daniel Lowengrub // // Eigen is free software; you can redistribute it and/or @@ -26,6 +26,8 @@ #ifndef EIGEN_SPARSEVIEW_H #define EIGEN_SPARSEVIEW_H +namespace Eigen { + namespace internal { template @@ -61,7 +63,7 @@ public: inline Index outerSize() const { return m_matrix.outerSize(); } protected: - const MatrixTypeNested m_matrix; + MatrixTypeNested m_matrix; Scalar m_reference; typename NumTraits::Real m_epsilon; }; @@ -92,10 +94,10 @@ protected: private: void incrementToNonZero() { - while(internal::isMuchSmallerThan(value(), m_view.m_reference, m_view.m_epsilon) && (bool(*this))) - { - IterBase::operator++(); - } + while((bool(*this)) && internal::isMuchSmallerThan(value(), m_view.m_reference, m_view.m_epsilon)) + { + IterBase::operator++(); + } } }; @@ -106,4 +108,6 @@ const SparseView MatrixBase::sparseView(const Scalar& m_refere return SparseView(derived(), m_reference, m_epsilon); } +} // end namespace Eigen + #endif diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Sparse/TriangularSolver.h b/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/TriangularSolver.h similarity index 89% rename from gtsam/3rdparty/Eigen/Eigen/src/Sparse/TriangularSolver.h rename to gtsam/3rdparty/Eigen/Eigen/src/SparseCore/TriangularSolver.h index 62bb8bb44..9a45e8f41 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Sparse/TriangularSolver.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/SparseCore/TriangularSolver.h @@ -25,6 +25,8 @@ #ifndef EIGEN_SPARSETRIANGULARSOLVER_H #define EIGEN_SPARSETRIANGULARSOLVER_H +namespace Eigen { + namespace internal { template for(int i=0; i for(int i=lhs.rows()-1 ; i>=0 ; --i) { Scalar tmp = other.coeff(i,col); + Scalar l_ii = 0; typename Lhs::InnerIterator it(lhs, i); - if (it && it.index() == i) + while(it && it.index() if (Mode & UnitDiag) other.coeffRef(i,col) = tmp; else - { - typename Lhs::InnerIterator it(lhs, i); - eigen_assert(it && it.index() == i); - other.coeffRef(i,col) = tmp/it.value(); - } + other.coeffRef(i,col) = tmp/l_ii; } } } @@ -118,9 +125,11 @@ struct sparse_solve_triangular_selector if (tmp!=Scalar(0)) // optimization when other is actually sparse { typename Lhs::InnerIterator it(lhs, i); + while(it && it.index() { if(!(Mode & UnitDiag)) { - // FIXME lhs.coeff(i,i) might not be always efficient while it must simply be the - // last element of the column ! - other.coeffRef(i,col) /= lhs.innerVector(i).lastCoeff(); + // TODO replace this by a binary search. make sure the binary search is safe for partially sorted elements + typename Lhs::ReverseInnerIterator it(lhs, i); + while(it && it.index()!=i) + --it; + eigen_assert(it && it.index()==i); + other.coeffRef(i,col) /= it.value(); } typename Lhs::InnerIterator it(lhs, i); for(; it && it.index() template void SparseTriangularView::solveInPlace(MatrixBase& other) const { - eigen_assert(m_matrix.cols() == m_matrix.rows()); - eigen_assert(m_matrix.cols() == other.rows()); - eigen_assert(!(Mode & ZeroDiag)); - eigen_assert((Mode & (Upper|Lower)) != 0); + eigen_assert(m_matrix.cols() == m_matrix.rows() && m_matrix.cols() == other.rows()); + eigen_assert((!(Mode & ZeroDiag)) && bool(Mode & (Upper|Lower))); enum { copy = internal::traits::Flags & RowMajorBit }; @@ -295,10 +305,8 @@ template template void SparseTriangularView::solveInPlace(SparseMatrixBase& other) const { - eigen_assert(m_matrix.cols() == m_matrix.rows()); - eigen_assert(m_matrix.cols() == other.rows()); - eigen_assert(!(Mode & ZeroDiag)); - eigen_assert((Mode & (Upper|Lower)) != 0); + eigen_assert(m_matrix.cols() == m_matrix.rows() && m_matrix.cols() == other.rows()); + eigen_assert( (!(Mode & ZeroDiag)) && bool(Mode & (Upper|Lower))); // enum { copy = internal::traits::Flags & RowMajorBit }; @@ -336,4 +344,6 @@ SparseMatrixBase::solveTriangular(const MatrixBase& other } #endif // EIGEN2_SUPPORT +} // end namespace Eigen + #endif // EIGEN_SPARSETRIANGULARSOLVER_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/SuperLUSupport/CMakeLists.txt b/gtsam/3rdparty/Eigen/Eigen/src/SuperLUSupport/CMakeLists.txt new file mode 100644 index 000000000..b28ebe583 --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/src/SuperLUSupport/CMakeLists.txt @@ -0,0 +1,6 @@ +FILE(GLOB Eigen_SuperLUSupport_SRCS "*.h") + +INSTALL(FILES + ${Eigen_SuperLUSupport_SRCS} + DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/SuperLUSupport COMPONENT Devel + ) diff --git a/gtsam/3rdparty/Eigen/Eigen/src/SuperLUSupport/SuperLUSupport.h b/gtsam/3rdparty/Eigen/Eigen/src/SuperLUSupport/SuperLUSupport.h new file mode 100644 index 000000000..6c3eb6858 --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/src/SuperLUSupport/SuperLUSupport.h @@ -0,0 +1,1040 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2008-2011 Gael Guennebaud +// +// Eigen is free software; you can redistribute it and/or +// modify it under the terms of the GNU Lesser General Public +// License as published by the Free Software Foundation; either +// version 3 of the License, or (at your option) any later version. +// +// Alternatively, you can redistribute it and/or +// modify it under the terms of the GNU General Public License as +// published by the Free Software Foundation; either version 2 of +// the License, or (at your option) any later version. +// +// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY +// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the +// GNU General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public +// License and a copy of the GNU General Public License along with +// Eigen. If not, see . + +#ifndef EIGEN_SUPERLUSUPPORT_H +#define EIGEN_SUPERLUSUPPORT_H + +namespace Eigen { + +#define DECL_GSSVX(PREFIX,FLOATTYPE,KEYTYPE) \ + extern "C" { \ + typedef struct { FLOATTYPE for_lu; FLOATTYPE total_needed; int expansions; } PREFIX##mem_usage_t; \ + extern void PREFIX##gssvx(superlu_options_t *, SuperMatrix *, int *, int *, int *, \ + char *, FLOATTYPE *, FLOATTYPE *, SuperMatrix *, SuperMatrix *, \ + void *, int, SuperMatrix *, SuperMatrix *, \ + FLOATTYPE *, FLOATTYPE *, FLOATTYPE *, FLOATTYPE *, \ + PREFIX##mem_usage_t *, SuperLUStat_t *, int *); \ + } \ + inline float SuperLU_gssvx(superlu_options_t *options, SuperMatrix *A, \ + int *perm_c, int *perm_r, int *etree, char *equed, \ + FLOATTYPE *R, FLOATTYPE *C, SuperMatrix *L, \ + SuperMatrix *U, void *work, int lwork, \ + SuperMatrix *B, SuperMatrix *X, \ + FLOATTYPE *recip_pivot_growth, \ + FLOATTYPE *rcond, FLOATTYPE *ferr, FLOATTYPE *berr, \ + SuperLUStat_t *stats, int *info, KEYTYPE) { \ + PREFIX##mem_usage_t mem_usage; \ + PREFIX##gssvx(options, A, perm_c, perm_r, etree, equed, R, C, L, \ + U, work, lwork, B, X, recip_pivot_growth, rcond, \ + ferr, berr, &mem_usage, stats, info); \ + return mem_usage.for_lu; /* bytes used by the factor storage */ \ + } + +DECL_GSSVX(s,float,float) +DECL_GSSVX(c,float,std::complex) +DECL_GSSVX(d,double,double) +DECL_GSSVX(z,double,std::complex) + +#ifdef MILU_ALPHA +#define EIGEN_SUPERLU_HAS_ILU +#endif + +#ifdef EIGEN_SUPERLU_HAS_ILU + +// similarly for the incomplete factorization using gsisx +#define DECL_GSISX(PREFIX,FLOATTYPE,KEYTYPE) \ + extern "C" { \ + extern void PREFIX##gsisx(superlu_options_t *, SuperMatrix *, int *, int *, int *, \ + char *, FLOATTYPE *, FLOATTYPE *, SuperMatrix *, SuperMatrix *, \ + void *, int, SuperMatrix *, SuperMatrix *, FLOATTYPE *, FLOATTYPE *, \ + PREFIX##mem_usage_t *, SuperLUStat_t *, int *); \ + } \ + inline float SuperLU_gsisx(superlu_options_t *options, SuperMatrix *A, \ + int *perm_c, int *perm_r, int *etree, char *equed, \ + FLOATTYPE *R, FLOATTYPE *C, SuperMatrix *L, \ + SuperMatrix *U, void *work, int lwork, \ + SuperMatrix *B, SuperMatrix *X, \ + FLOATTYPE *recip_pivot_growth, \ + FLOATTYPE *rcond, \ + SuperLUStat_t *stats, int *info, KEYTYPE) { \ + PREFIX##mem_usage_t mem_usage; \ + PREFIX##gsisx(options, A, perm_c, perm_r, etree, equed, R, C, L, \ + U, work, lwork, B, X, recip_pivot_growth, rcond, \ + &mem_usage, stats, info); \ + return mem_usage.for_lu; /* bytes used by the factor storage */ \ + } + +DECL_GSISX(s,float,float) +DECL_GSISX(c,float,std::complex) +DECL_GSISX(d,double,double) +DECL_GSISX(z,double,std::complex) + +#endif + +template +struct SluMatrixMapHelper; + +/** \internal + * + * A wrapper class for SuperLU matrices. It supports only compressed sparse matrices + * and dense matrices. Supernodal and other fancy format are not supported by this wrapper. + * + * This wrapper class mainly aims to avoids the need of dynamic allocation of the storage structure. + */ +struct SluMatrix : SuperMatrix +{ + SluMatrix() + { + Store = &storage; + } + + SluMatrix(const SluMatrix& other) + : SuperMatrix(other) + { + Store = &storage; + storage = other.storage; + } + + SluMatrix& operator=(const SluMatrix& other) + { + SuperMatrix::operator=(static_cast(other)); + Store = &storage; + storage = other.storage; + return *this; + } + + struct + { + union {int nnz;int lda;}; + void *values; + int *innerInd; + int *outerInd; + } storage; + + void setStorageType(Stype_t t) + { + Stype = t; + if (t==SLU_NC || t==SLU_NR || t==SLU_DN) + Store = &storage; + else + { + eigen_assert(false && "storage type not supported"); + Store = 0; + } + } + + template + void setScalarType() + { + if (internal::is_same::value) + Dtype = SLU_S; + else if (internal::is_same::value) + Dtype = SLU_D; + else if (internal::is_same >::value) + Dtype = SLU_C; + else if (internal::is_same >::value) + Dtype = SLU_Z; + else + { + eigen_assert(false && "Scalar type not supported by SuperLU"); + } + } + + template + static SluMatrix Map(MatrixBase& _mat) + { + MatrixType& mat(_mat.derived()); + eigen_assert( ((MatrixType::Flags&RowMajorBit)!=RowMajorBit) && "row-major dense matrices are not supported by SuperLU"); + SluMatrix res; + res.setStorageType(SLU_DN); + res.setScalarType(); + res.Mtype = SLU_GE; + + res.nrow = mat.rows(); + res.ncol = mat.cols(); + + res.storage.lda = MatrixType::IsVectorAtCompileTime ? mat.size() : mat.outerStride(); + res.storage.values = mat.data(); + return res; + } + + template + static SluMatrix Map(SparseMatrixBase& mat) + { + SluMatrix res; + if ((MatrixType::Flags&RowMajorBit)==RowMajorBit) + { + res.setStorageType(SLU_NR); + res.nrow = mat.cols(); + res.ncol = mat.rows(); + } + else + { + res.setStorageType(SLU_NC); + res.nrow = mat.rows(); + res.ncol = mat.cols(); + } + + res.Mtype = SLU_GE; + + res.storage.nnz = mat.nonZeros(); + res.storage.values = mat.derived().valuePtr(); + res.storage.innerInd = mat.derived().innerIndexPtr(); + res.storage.outerInd = mat.derived().outerIndexPtr(); + + res.setScalarType(); + + // FIXME the following is not very accurate + if (MatrixType::Flags & Upper) + res.Mtype = SLU_TRU; + if (MatrixType::Flags & Lower) + res.Mtype = SLU_TRL; + + eigen_assert(((MatrixType::Flags & SelfAdjoint)==0) && "SelfAdjoint matrix shape not supported by SuperLU"); + + return res; + } +}; + +template +struct SluMatrixMapHelper > +{ + typedef Matrix MatrixType; + static void run(MatrixType& mat, SluMatrix& res) + { + eigen_assert( ((Options&RowMajor)!=RowMajor) && "row-major dense matrices is not supported by SuperLU"); + res.setStorageType(SLU_DN); + res.setScalarType(); + res.Mtype = SLU_GE; + + res.nrow = mat.rows(); + res.ncol = mat.cols(); + + res.storage.lda = mat.outerStride(); + res.storage.values = mat.data(); + } +}; + +template +struct SluMatrixMapHelper > +{ + typedef Derived MatrixType; + static void run(MatrixType& mat, SluMatrix& res) + { + if ((MatrixType::Flags&RowMajorBit)==RowMajorBit) + { + res.setStorageType(SLU_NR); + res.nrow = mat.cols(); + res.ncol = mat.rows(); + } + else + { + res.setStorageType(SLU_NC); + res.nrow = mat.rows(); + res.ncol = mat.cols(); + } + + res.Mtype = SLU_GE; + + res.storage.nnz = mat.nonZeros(); + res.storage.values = mat.valuePtr(); + res.storage.innerInd = mat.innerIndexPtr(); + res.storage.outerInd = mat.outerIndexPtr(); + + res.setScalarType(); + + // FIXME the following is not very accurate + if (MatrixType::Flags & Upper) + res.Mtype = SLU_TRU; + if (MatrixType::Flags & Lower) + res.Mtype = SLU_TRL; + + eigen_assert(((MatrixType::Flags & SelfAdjoint)==0) && "SelfAdjoint matrix shape not supported by SuperLU"); + } +}; + +namespace internal { + +template +SluMatrix asSluMatrix(MatrixType& mat) +{ + return SluMatrix::Map(mat); +} + +/** View a Super LU matrix as an Eigen expression */ +template +MappedSparseMatrix map_superlu(SluMatrix& sluMat) +{ + eigen_assert((Flags&RowMajor)==RowMajor && sluMat.Stype == SLU_NR + || (Flags&ColMajor)==ColMajor && sluMat.Stype == SLU_NC); + + Index outerSize = (Flags&RowMajor)==RowMajor ? sluMat.ncol : sluMat.nrow; + + return MappedSparseMatrix( + sluMat.nrow, sluMat.ncol, sluMat.storage.outerInd[outerSize], + sluMat.storage.outerInd, sluMat.storage.innerInd, reinterpret_cast(sluMat.storage.values) ); +} + +} // end namespace internal + +/** \ingroup SuperLUSupport_Module + * \class SuperLUBase + * \brief The base class for the direct and incomplete LU factorization of SuperLU + */ +template +class SuperLUBase : internal::noncopyable +{ + public: + typedef _MatrixType MatrixType; + typedef typename MatrixType::Scalar Scalar; + typedef typename MatrixType::RealScalar RealScalar; + typedef typename MatrixType::Index Index; + typedef Matrix Vector; + typedef Matrix IntRowVectorType; + typedef Matrix IntColVectorType; + typedef SparseMatrix LUMatrixType; + + public: + + SuperLUBase() {} + + ~SuperLUBase() + { + clearFactors(); + } + + Derived& derived() { return *static_cast(this); } + const Derived& derived() const { return *static_cast(this); } + + inline Index rows() const { return m_matrix.rows(); } + inline Index cols() const { return m_matrix.cols(); } + + /** \returns a reference to the Super LU option object to configure the Super LU algorithms. */ + inline superlu_options_t& options() { return m_sluOptions; } + + /** \brief Reports whether previous computation was successful. + * + * \returns \c Success if computation was succesful, + * \c NumericalIssue if the matrix.appears to be negative. + */ + ComputationInfo info() const + { + eigen_assert(m_isInitialized && "Decomposition is not initialized."); + return m_info; + } + + /** Computes the sparse Cholesky decomposition of \a matrix */ + void compute(const MatrixType& matrix) + { + derived().analyzePattern(matrix); + derived().factorize(matrix); + } + + /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A. + * + * \sa compute() + */ + template + inline const internal::solve_retval solve(const MatrixBase& b) const + { + eigen_assert(m_isInitialized && "SuperLU is not initialized."); + eigen_assert(rows()==b.rows() + && "SuperLU::solve(): invalid number of rows of the right hand side matrix b"); + return internal::solve_retval(*this, b.derived()); + } + + /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A. + * + * \sa compute() + */ +// template +// inline const internal::sparse_solve_retval solve(const SparseMatrixBase& b) const +// { +// eigen_assert(m_isInitialized && "SuperLU is not initialized."); +// eigen_assert(rows()==b.rows() +// && "SuperLU::solve(): invalid number of rows of the right hand side matrix b"); +// return internal::sparse_solve_retval(*this, b.derived()); +// } + + /** Performs a symbolic decomposition on the sparcity of \a matrix. + * + * This function is particularly useful when solving for several problems having the same structure. + * + * \sa factorize() + */ + void analyzePattern(const MatrixType& /*matrix*/) + { + m_isInitialized = true; + m_info = Success; + m_analysisIsOk = true; + m_factorizationIsOk = false; + } + + template + void dumpMemory(Stream& s) + {} + + protected: + + void initFactorization(const MatrixType& a) + { + set_default_options(&this->m_sluOptions); + + const int size = a.rows(); + m_matrix = a; + + m_sluA = internal::asSluMatrix(m_matrix); + clearFactors(); + + m_p.resize(size); + m_q.resize(size); + m_sluRscale.resize(size); + m_sluCscale.resize(size); + m_sluEtree.resize(size); + + // set empty B and X + m_sluB.setStorageType(SLU_DN); + m_sluB.setScalarType(); + m_sluB.Mtype = SLU_GE; + m_sluB.storage.values = 0; + m_sluB.nrow = 0; + m_sluB.ncol = 0; + m_sluB.storage.lda = size; + m_sluX = m_sluB; + + m_extractedDataAreDirty = true; + } + + void init() + { + m_info = InvalidInput; + m_isInitialized = false; + m_sluL.Store = 0; + m_sluU.Store = 0; + } + + void extractData() const; + + void clearFactors() + { + if(m_sluL.Store) + Destroy_SuperNode_Matrix(&m_sluL); + if(m_sluU.Store) + Destroy_CompCol_Matrix(&m_sluU); + + m_sluL.Store = 0; + m_sluU.Store = 0; + + memset(&m_sluL,0,sizeof m_sluL); + memset(&m_sluU,0,sizeof m_sluU); + } + + // cached data to reduce reallocation, etc. + mutable LUMatrixType m_l; + mutable LUMatrixType m_u; + mutable IntColVectorType m_p; + mutable IntRowVectorType m_q; + + mutable LUMatrixType m_matrix; // copy of the factorized matrix + mutable SluMatrix m_sluA; + mutable SuperMatrix m_sluL, m_sluU; + mutable SluMatrix m_sluB, m_sluX; + mutable SuperLUStat_t m_sluStat; + mutable superlu_options_t m_sluOptions; + mutable std::vector m_sluEtree; + mutable Matrix m_sluRscale, m_sluCscale; + mutable Matrix m_sluFerr, m_sluBerr; + mutable char m_sluEqued; + + mutable ComputationInfo m_info; + bool m_isInitialized; + int m_factorizationIsOk; + int m_analysisIsOk; + mutable bool m_extractedDataAreDirty; + + private: + SuperLUBase(SuperLUBase& ) { } +}; + + +/** \ingroup SuperLUSupport_Module + * \class SuperLU + * \brief A sparse direct LU factorization and solver based on the SuperLU library + * + * This class allows to solve for A.X = B sparse linear problems via a direct LU factorization + * using the SuperLU library. The sparse matrix A must be squared and invertible. The vectors or matrices + * X and B can be either dense or sparse. + * + * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<> + * + * \sa \ref TutorialSparseDirectSolvers + */ +template +class SuperLU : public SuperLUBase<_MatrixType,SuperLU<_MatrixType> > +{ + public: + typedef SuperLUBase<_MatrixType,SuperLU> Base; + typedef _MatrixType MatrixType; + typedef typename Base::Scalar Scalar; + typedef typename Base::RealScalar RealScalar; + typedef typename Base::Index Index; + typedef typename Base::IntRowVectorType IntRowVectorType; + typedef typename Base::IntColVectorType IntColVectorType; + typedef typename Base::LUMatrixType LUMatrixType; + typedef TriangularView LMatrixType; + typedef TriangularView UMatrixType; + + public: + + SuperLU() : Base() { init(); } + + SuperLU(const MatrixType& matrix) : Base() + { + Base::init(); + compute(matrix); + } + + ~SuperLU() + { + } + + /** Performs a symbolic decomposition on the sparcity of \a matrix. + * + * This function is particularly useful when solving for several problems having the same structure. + * + * \sa factorize() + */ + void analyzePattern(const MatrixType& matrix) + { + m_info = InvalidInput; + m_isInitialized = false; + Base::analyzePattern(matrix); + } + + /** Performs a numeric decomposition of \a matrix + * + * The given matrix must has the same sparcity than the matrix on which the symbolic decomposition has been performed. + * + * \sa analyzePattern() + */ + void factorize(const MatrixType& matrix); + + #ifndef EIGEN_PARSED_BY_DOXYGEN + /** \internal */ + template + void _solve(const MatrixBase &b, MatrixBase &dest) const; + #endif // EIGEN_PARSED_BY_DOXYGEN + + inline const LMatrixType& matrixL() const + { + if (m_extractedDataAreDirty) this->extractData(); + return m_l; + } + + inline const UMatrixType& matrixU() const + { + if (m_extractedDataAreDirty) this->extractData(); + return m_u; + } + + inline const IntColVectorType& permutationP() const + { + if (m_extractedDataAreDirty) this->extractData(); + return m_p; + } + + inline const IntRowVectorType& permutationQ() const + { + if (m_extractedDataAreDirty) this->extractData(); + return m_q; + } + + Scalar determinant() const; + + protected: + + using Base::m_matrix; + using Base::m_sluOptions; + using Base::m_sluA; + using Base::m_sluB; + using Base::m_sluX; + using Base::m_p; + using Base::m_q; + using Base::m_sluEtree; + using Base::m_sluEqued; + using Base::m_sluRscale; + using Base::m_sluCscale; + using Base::m_sluL; + using Base::m_sluU; + using Base::m_sluStat; + using Base::m_sluFerr; + using Base::m_sluBerr; + using Base::m_l; + using Base::m_u; + + using Base::m_analysisIsOk; + using Base::m_factorizationIsOk; + using Base::m_extractedDataAreDirty; + using Base::m_isInitialized; + using Base::m_info; + + void init() + { + Base::init(); + + set_default_options(&this->m_sluOptions); + m_sluOptions.PrintStat = NO; + m_sluOptions.ConditionNumber = NO; + m_sluOptions.Trans = NOTRANS; + m_sluOptions.ColPerm = COLAMD; + } + + + private: + SuperLU(SuperLU& ) { } +}; + +template +void SuperLU::factorize(const MatrixType& a) +{ + eigen_assert(m_analysisIsOk && "You must first call analyzePattern()"); + if(!m_analysisIsOk) + { + m_info = InvalidInput; + return; + } + + this->initFactorization(a); + + int info = 0; + RealScalar recip_pivot_growth, rcond; + RealScalar ferr, berr; + + StatInit(&m_sluStat); + SuperLU_gssvx(&m_sluOptions, &m_sluA, m_q.data(), m_p.data(), &m_sluEtree[0], + &m_sluEqued, &m_sluRscale[0], &m_sluCscale[0], + &m_sluL, &m_sluU, + NULL, 0, + &m_sluB, &m_sluX, + &recip_pivot_growth, &rcond, + &ferr, &berr, + &m_sluStat, &info, Scalar()); + StatFree(&m_sluStat); + + m_extractedDataAreDirty = true; + + // FIXME how to better check for errors ??? + m_info = info == 0 ? Success : NumericalIssue; + m_factorizationIsOk = true; +} + +template +template +void SuperLU::_solve(const MatrixBase &b, MatrixBase& x) const +{ + eigen_assert(m_factorizationIsOk && "The decomposition is not in a valid state for solving, you must first call either compute() or analyzePattern()/factorize()"); + + const int size = m_matrix.rows(); + const int rhsCols = b.cols(); + eigen_assert(size==b.rows()); + + m_sluOptions.Trans = NOTRANS; + m_sluOptions.Fact = FACTORED; + m_sluOptions.IterRefine = NOREFINE; + + + m_sluFerr.resize(rhsCols); + m_sluBerr.resize(rhsCols); + m_sluB = SluMatrix::Map(b.const_cast_derived()); + m_sluX = SluMatrix::Map(x.derived()); + + typename Rhs::PlainObject b_cpy; + if(m_sluEqued!='N') + { + b_cpy = b; + m_sluB = SluMatrix::Map(b_cpy.const_cast_derived()); + } + + StatInit(&m_sluStat); + int info = 0; + RealScalar recip_pivot_growth, rcond; + SuperLU_gssvx(&m_sluOptions, &m_sluA, + m_q.data(), m_p.data(), + &m_sluEtree[0], &m_sluEqued, + &m_sluRscale[0], &m_sluCscale[0], + &m_sluL, &m_sluU, + NULL, 0, + &m_sluB, &m_sluX, + &recip_pivot_growth, &rcond, + &m_sluFerr[0], &m_sluBerr[0], + &m_sluStat, &info, Scalar()); + StatFree(&m_sluStat); + m_info = info==0 ? Success : NumericalIssue; +} + +// the code of this extractData() function has been adapted from the SuperLU's Matlab support code, +// +// Copyright (c) 1994 by Xerox Corporation. All rights reserved. +// +// THIS MATERIAL IS PROVIDED AS IS, WITH ABSOLUTELY NO WARRANTY +// EXPRESSED OR IMPLIED. ANY USE IS AT YOUR OWN RISK. +// +template +void SuperLUBase::extractData() const +{ + eigen_assert(m_factorizationIsOk && "The decomposition is not in a valid state for extracting factors, you must first call either compute() or analyzePattern()/factorize()"); + if (m_extractedDataAreDirty) + { + int upper; + int fsupc, istart, nsupr; + int lastl = 0, lastu = 0; + SCformat *Lstore = static_cast(m_sluL.Store); + NCformat *Ustore = static_cast(m_sluU.Store); + Scalar *SNptr; + + const int size = m_matrix.rows(); + m_l.resize(size,size); + m_l.resizeNonZeros(Lstore->nnz); + m_u.resize(size,size); + m_u.resizeNonZeros(Ustore->nnz); + + int* Lcol = m_l.outerIndexPtr(); + int* Lrow = m_l.innerIndexPtr(); + Scalar* Lval = m_l.valuePtr(); + + int* Ucol = m_u.outerIndexPtr(); + int* Urow = m_u.innerIndexPtr(); + Scalar* Uval = m_u.valuePtr(); + + Ucol[0] = 0; + Ucol[0] = 0; + + /* for each supernode */ + for (int k = 0; k <= Lstore->nsuper; ++k) + { + fsupc = L_FST_SUPC(k); + istart = L_SUB_START(fsupc); + nsupr = L_SUB_START(fsupc+1) - istart; + upper = 1; + + /* for each column in the supernode */ + for (int j = fsupc; j < L_FST_SUPC(k+1); ++j) + { + SNptr = &((Scalar*)Lstore->nzval)[L_NZ_START(j)]; + + /* Extract U */ + for (int i = U_NZ_START(j); i < U_NZ_START(j+1); ++i) + { + Uval[lastu] = ((Scalar*)Ustore->nzval)[i]; + /* Matlab doesn't like explicit zero. */ + if (Uval[lastu] != 0.0) + Urow[lastu++] = U_SUB(i); + } + for (int i = 0; i < upper; ++i) + { + /* upper triangle in the supernode */ + Uval[lastu] = SNptr[i]; + /* Matlab doesn't like explicit zero. */ + if (Uval[lastu] != 0.0) + Urow[lastu++] = L_SUB(istart+i); + } + Ucol[j+1] = lastu; + + /* Extract L */ + Lval[lastl] = 1.0; /* unit diagonal */ + Lrow[lastl++] = L_SUB(istart + upper - 1); + for (int i = upper; i < nsupr; ++i) + { + Lval[lastl] = SNptr[i]; + /* Matlab doesn't like explicit zero. */ + if (Lval[lastl] != 0.0) + Lrow[lastl++] = L_SUB(istart+i); + } + Lcol[j+1] = lastl; + + ++upper; + } /* for j ... */ + + } /* for k ... */ + + // squeeze the matrices : + m_l.resizeNonZeros(lastl); + m_u.resizeNonZeros(lastu); + + m_extractedDataAreDirty = false; + } +} + +template +typename SuperLU::Scalar SuperLU::determinant() const +{ + eigen_assert(m_factorizationIsOk && "The decomposition is not in a valid state for computing the determinant, you must first call either compute() or analyzePattern()/factorize()"); + + if (m_extractedDataAreDirty) + this->extractData(); + + Scalar det = Scalar(1); + for (int j=0; j 0) + { + int lastId = m_u.outerIndexPtr()[j+1]-1; + eigen_assert(m_u.innerIndexPtr()[lastId]<=j); + if (m_u.innerIndexPtr()[lastId]==j) + det *= m_u.valuePtr()[lastId]; + } + } + if(m_sluEqued!='N') + return det/m_sluRscale.prod()/m_sluCscale.prod(); + else + return det; +} + +#ifdef EIGEN_PARSED_BY_DOXYGEN +#define EIGEN_SUPERLU_HAS_ILU +#endif + +#ifdef EIGEN_SUPERLU_HAS_ILU + +/** \ingroup SuperLUSupport_Module + * \class SuperILU + * \brief A sparse direct \b incomplete LU factorization and solver based on the SuperLU library + * + * This class allows to solve for an approximate solution of A.X = B sparse linear problems via an incomplete LU factorization + * using the SuperLU library. This class is aimed to be used as a preconditioner of the iterative linear solvers. + * + * \warning This class requires SuperLU 4 or later. + * + * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<> + * + * \sa \ref TutorialSparseDirectSolvers, class ConjugateGradient, class BiCGSTAB + */ + +template +class SuperILU : public SuperLUBase<_MatrixType,SuperILU<_MatrixType> > +{ + public: + typedef SuperLUBase<_MatrixType,SuperILU> Base; + typedef _MatrixType MatrixType; + typedef typename Base::Scalar Scalar; + typedef typename Base::RealScalar RealScalar; + typedef typename Base::Index Index; + + public: + + SuperILU() : Base() { init(); } + + SuperILU(const MatrixType& matrix) : Base() + { + init(); + compute(matrix); + } + + ~SuperILU() + { + } + + /** Performs a symbolic decomposition on the sparcity of \a matrix. + * + * This function is particularly useful when solving for several problems having the same structure. + * + * \sa factorize() + */ + void analyzePattern(const MatrixType& matrix) + { + Base::analyzePattern(matrix); + } + + /** Performs a numeric decomposition of \a matrix + * + * The given matrix must has the same sparcity than the matrix on which the symbolic decomposition has been performed. + * + * \sa analyzePattern() + */ + void factorize(const MatrixType& matrix); + + #ifndef EIGEN_PARSED_BY_DOXYGEN + /** \internal */ + template + void _solve(const MatrixBase &b, MatrixBase &dest) const; + #endif // EIGEN_PARSED_BY_DOXYGEN + + protected: + + using Base::m_matrix; + using Base::m_sluOptions; + using Base::m_sluA; + using Base::m_sluB; + using Base::m_sluX; + using Base::m_p; + using Base::m_q; + using Base::m_sluEtree; + using Base::m_sluEqued; + using Base::m_sluRscale; + using Base::m_sluCscale; + using Base::m_sluL; + using Base::m_sluU; + using Base::m_sluStat; + using Base::m_sluFerr; + using Base::m_sluBerr; + using Base::m_l; + using Base::m_u; + + using Base::m_analysisIsOk; + using Base::m_factorizationIsOk; + using Base::m_extractedDataAreDirty; + using Base::m_isInitialized; + using Base::m_info; + + void init() + { + Base::init(); + + ilu_set_default_options(&m_sluOptions); + m_sluOptions.PrintStat = NO; + m_sluOptions.ConditionNumber = NO; + m_sluOptions.Trans = NOTRANS; + m_sluOptions.ColPerm = MMD_AT_PLUS_A; + + // no attempt to preserve column sum + m_sluOptions.ILU_MILU = SILU; + // only basic ILU(k) support -- no direct control over memory consumption + // better to use ILU_DropRule = DROP_BASIC | DROP_AREA + // and set ILU_FillFactor to max memory growth + m_sluOptions.ILU_DropRule = DROP_BASIC; + m_sluOptions.ILU_DropTol = NumTraits::dummy_precision()*10; + } + + private: + SuperILU(SuperILU& ) { } +}; + +template +void SuperILU::factorize(const MatrixType& a) +{ + eigen_assert(m_analysisIsOk && "You must first call analyzePattern()"); + if(!m_analysisIsOk) + { + m_info = InvalidInput; + return; + } + + this->initFactorization(a); + + int info = 0; + RealScalar recip_pivot_growth, rcond; + + StatInit(&m_sluStat); + SuperLU_gsisx(&m_sluOptions, &m_sluA, m_q.data(), m_p.data(), &m_sluEtree[0], + &m_sluEqued, &m_sluRscale[0], &m_sluCscale[0], + &m_sluL, &m_sluU, + NULL, 0, + &m_sluB, &m_sluX, + &recip_pivot_growth, &rcond, + &m_sluStat, &info, Scalar()); + StatFree(&m_sluStat); + + // FIXME how to better check for errors ??? + m_info = info == 0 ? Success : NumericalIssue; + m_factorizationIsOk = true; +} + +template +template +void SuperILU::_solve(const MatrixBase &b, MatrixBase& x) const +{ + eigen_assert(m_factorizationIsOk && "The decomposition is not in a valid state for solving, you must first call either compute() or analyzePattern()/factorize()"); + + const int size = m_matrix.rows(); + const int rhsCols = b.cols(); + eigen_assert(size==b.rows()); + + m_sluOptions.Trans = NOTRANS; + m_sluOptions.Fact = FACTORED; + m_sluOptions.IterRefine = NOREFINE; + + m_sluFerr.resize(rhsCols); + m_sluBerr.resize(rhsCols); + m_sluB = SluMatrix::Map(b.const_cast_derived()); + m_sluX = SluMatrix::Map(x.derived()); + + typename Rhs::PlainObject b_cpy; + if(m_sluEqued!='N') + { + b_cpy = b; + m_sluB = SluMatrix::Map(b_cpy.const_cast_derived()); + } + + int info = 0; + RealScalar recip_pivot_growth, rcond; + + StatInit(&m_sluStat); + SuperLU_gsisx(&m_sluOptions, &m_sluA, + m_q.data(), m_p.data(), + &m_sluEtree[0], &m_sluEqued, + &m_sluRscale[0], &m_sluCscale[0], + &m_sluL, &m_sluU, + NULL, 0, + &m_sluB, &m_sluX, + &recip_pivot_growth, &rcond, + &m_sluStat, &info, Scalar()); + StatFree(&m_sluStat); + + m_info = info==0 ? Success : NumericalIssue; +} +#endif + +namespace internal { + +template +struct solve_retval, Rhs> + : solve_retval_base, Rhs> +{ + typedef SuperLUBase<_MatrixType,Derived> Dec; + EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs) + + template void evalTo(Dest& dst) const + { + dec().derived()._solve(rhs(),dst); + } +}; + +template +struct sparse_solve_retval, Rhs> + : sparse_solve_retval_base, Rhs> +{ + typedef SuperLUBase<_MatrixType,Derived> Dec; + EIGEN_MAKE_SPARSE_SOLVE_HELPERS(Dec,Rhs) + + template void evalTo(Dest& dst) const + { + dec().derived()._solve(rhs(),dst); + } +}; + +} // end namespace internal + +} // end namespace Eigen + +#endif // EIGEN_SUPERLUSUPPORT_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/UmfPackSupport/CMakeLists.txt b/gtsam/3rdparty/Eigen/Eigen/src/UmfPackSupport/CMakeLists.txt new file mode 100644 index 000000000..a57de0020 --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/src/UmfPackSupport/CMakeLists.txt @@ -0,0 +1,6 @@ +FILE(GLOB Eigen_UmfPackSupport_SRCS "*.h") + +INSTALL(FILES + ${Eigen_UmfPackSupport_SRCS} + DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/UmfPackSupport COMPONENT Devel + ) diff --git a/gtsam/3rdparty/Eigen/Eigen/src/UmfPackSupport/UmfPackSupport.h b/gtsam/3rdparty/Eigen/Eigen/src/UmfPackSupport/UmfPackSupport.h new file mode 100644 index 000000000..f98a4c8c0 --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/src/UmfPackSupport/UmfPackSupport.h @@ -0,0 +1,446 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2008-2011 Gael Guennebaud +// +// Eigen is free software; you can redistribute it and/or +// modify it under the terms of the GNU Lesser General Public +// License as published by the Free Software Foundation; either +// version 3 of the License, or (at your option) any later version. +// +// Alternatively, you can redistribute it and/or +// modify it under the terms of the GNU General Public License as +// published by the Free Software Foundation; either version 2 of +// the License, or (at your option) any later version. +// +// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY +// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the +// GNU General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public +// License and a copy of the GNU General Public License along with +// Eigen. If not, see . + +#ifndef EIGEN_UMFPACKSUPPORT_H +#define EIGEN_UMFPACKSUPPORT_H + +namespace Eigen { + +/* TODO extract L, extract U, compute det, etc... */ + +// generic double/complex wrapper functions: + +inline void umfpack_free_numeric(void **Numeric, double) +{ umfpack_di_free_numeric(Numeric); *Numeric = 0; } + +inline void umfpack_free_numeric(void **Numeric, std::complex) +{ umfpack_zi_free_numeric(Numeric); *Numeric = 0; } + +inline void umfpack_free_symbolic(void **Symbolic, double) +{ umfpack_di_free_symbolic(Symbolic); *Symbolic = 0; } + +inline void umfpack_free_symbolic(void **Symbolic, std::complex) +{ umfpack_zi_free_symbolic(Symbolic); *Symbolic = 0; } + +inline int umfpack_symbolic(int n_row,int n_col, + const int Ap[], const int Ai[], const double Ax[], void **Symbolic, + const double Control [UMFPACK_CONTROL], double Info [UMFPACK_INFO]) +{ + return umfpack_di_symbolic(n_row,n_col,Ap,Ai,Ax,Symbolic,Control,Info); +} + +inline int umfpack_symbolic(int n_row,int n_col, + const int Ap[], const int Ai[], const std::complex Ax[], void **Symbolic, + const double Control [UMFPACK_CONTROL], double Info [UMFPACK_INFO]) +{ + return umfpack_zi_symbolic(n_row,n_col,Ap,Ai,&internal::real_ref(Ax[0]),0,Symbolic,Control,Info); +} + +inline int umfpack_numeric( const int Ap[], const int Ai[], const double Ax[], + void *Symbolic, void **Numeric, + const double Control[UMFPACK_CONTROL],double Info [UMFPACK_INFO]) +{ + return umfpack_di_numeric(Ap,Ai,Ax,Symbolic,Numeric,Control,Info); +} + +inline int umfpack_numeric( const int Ap[], const int Ai[], const std::complex Ax[], + void *Symbolic, void **Numeric, + const double Control[UMFPACK_CONTROL],double Info [UMFPACK_INFO]) +{ + return umfpack_zi_numeric(Ap,Ai,&internal::real_ref(Ax[0]),0,Symbolic,Numeric,Control,Info); +} + +inline int umfpack_solve( int sys, const int Ap[], const int Ai[], const double Ax[], + double X[], const double B[], void *Numeric, + const double Control[UMFPACK_CONTROL], double Info[UMFPACK_INFO]) +{ + return umfpack_di_solve(sys,Ap,Ai,Ax,X,B,Numeric,Control,Info); +} + +inline int umfpack_solve( int sys, const int Ap[], const int Ai[], const std::complex Ax[], + std::complex X[], const std::complex B[], void *Numeric, + const double Control[UMFPACK_CONTROL], double Info[UMFPACK_INFO]) +{ + return umfpack_zi_solve(sys,Ap,Ai,&internal::real_ref(Ax[0]),0,&internal::real_ref(X[0]),0,&internal::real_ref(B[0]),0,Numeric,Control,Info); +} + +inline int umfpack_get_lunz(int *lnz, int *unz, int *n_row, int *n_col, int *nz_udiag, void *Numeric, double) +{ + return umfpack_di_get_lunz(lnz,unz,n_row,n_col,nz_udiag,Numeric); +} + +inline int umfpack_get_lunz(int *lnz, int *unz, int *n_row, int *n_col, int *nz_udiag, void *Numeric, std::complex) +{ + return umfpack_zi_get_lunz(lnz,unz,n_row,n_col,nz_udiag,Numeric); +} + +inline int umfpack_get_numeric(int Lp[], int Lj[], double Lx[], int Up[], int Ui[], double Ux[], + int P[], int Q[], double Dx[], int *do_recip, double Rs[], void *Numeric) +{ + return umfpack_di_get_numeric(Lp,Lj,Lx,Up,Ui,Ux,P,Q,Dx,do_recip,Rs,Numeric); +} + +inline int umfpack_get_numeric(int Lp[], int Lj[], std::complex Lx[], int Up[], int Ui[], std::complex Ux[], + int P[], int Q[], std::complex Dx[], int *do_recip, double Rs[], void *Numeric) +{ + double& lx0_real = internal::real_ref(Lx[0]); + double& ux0_real = internal::real_ref(Ux[0]); + double& dx0_real = internal::real_ref(Dx[0]); + return umfpack_zi_get_numeric(Lp,Lj,Lx?&lx0_real:0,0,Up,Ui,Ux?&ux0_real:0,0,P,Q, + Dx?&dx0_real:0,0,do_recip,Rs,Numeric); +} + +inline int umfpack_get_determinant(double *Mx, double *Ex, void *NumericHandle, double User_Info [UMFPACK_INFO]) +{ + return umfpack_di_get_determinant(Mx,Ex,NumericHandle,User_Info); +} + +inline int umfpack_get_determinant(std::complex *Mx, double *Ex, void *NumericHandle, double User_Info [UMFPACK_INFO]) +{ + double& mx_real = internal::real_ref(*Mx); + return umfpack_zi_get_determinant(&mx_real,0,Ex,NumericHandle,User_Info); +} + +/** \ingroup UmfPackSupport_Module + * \brief A sparse LU factorization and solver based on UmfPack + * + * This class allows to solve for A.X = B sparse linear problems via a LU factorization + * using the UmfPack library. The sparse matrix A must be squared and full rank. + * The vectors or matrices X and B can be either dense or sparse. + * + * \WARNING The input matrix A should be in a \b compressed and \b column-major form. + * Otherwise an expensive copy will be made. You can call the inexpensive makeCompressed() to get a compressed matrix. + * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<> + * + * \sa \ref TutorialSparseDirectSolvers + */ +template +class UmfPackLU : internal::noncopyable +{ + public: + typedef _MatrixType MatrixType; + typedef typename MatrixType::Scalar Scalar; + typedef typename MatrixType::RealScalar RealScalar; + typedef typename MatrixType::Index Index; + typedef Matrix Vector; + typedef Matrix IntRowVectorType; + typedef Matrix IntColVectorType; + typedef SparseMatrix LUMatrixType; + typedef SparseMatrix UmfpackMatrixType; + + public: + + UmfPackLU() { init(); } + + UmfPackLU(const MatrixType& matrix) + { + init(); + compute(matrix); + } + + ~UmfPackLU() + { + if(m_symbolic) umfpack_free_symbolic(&m_symbolic,Scalar()); + if(m_numeric) umfpack_free_numeric(&m_numeric,Scalar()); + } + + inline Index rows() const { return m_copyMatrix.rows(); } + inline Index cols() const { return m_copyMatrix.cols(); } + + /** \brief Reports whether previous computation was successful. + * + * \returns \c Success if computation was succesful, + * \c NumericalIssue if the matrix.appears to be negative. + */ + ComputationInfo info() const + { + eigen_assert(m_isInitialized && "Decomposition is not initialized."); + return m_info; + } + + inline const LUMatrixType& matrixL() const + { + if (m_extractedDataAreDirty) extractData(); + return m_l; + } + + inline const LUMatrixType& matrixU() const + { + if (m_extractedDataAreDirty) extractData(); + return m_u; + } + + inline const IntColVectorType& permutationP() const + { + if (m_extractedDataAreDirty) extractData(); + return m_p; + } + + inline const IntRowVectorType& permutationQ() const + { + if (m_extractedDataAreDirty) extractData(); + return m_q; + } + + /** Computes the sparse Cholesky decomposition of \a matrix + * Note that the matrix should be column-major, and in compressed format for best performance. + * \sa SparseMatrix::makeCompressed(). + */ + void compute(const MatrixType& matrix) + { + analyzePattern(matrix); + factorize(matrix); + } + + /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A. + * + * \sa compute() + */ + template + inline const internal::solve_retval solve(const MatrixBase& b) const + { + eigen_assert(m_isInitialized && "UmfPackLU is not initialized."); + eigen_assert(rows()==b.rows() + && "UmfPackLU::solve(): invalid number of rows of the right hand side matrix b"); + return internal::solve_retval(*this, b.derived()); + } + + /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A. + * + * \sa compute() + */ +// template +// inline const internal::sparse_solve_retval solve(const SparseMatrixBase& b) const +// { +// eigen_assert(m_isInitialized && "UmfPAckLU is not initialized."); +// eigen_assert(rows()==b.rows() +// && "UmfPAckLU::solve(): invalid number of rows of the right hand side matrix b"); +// return internal::sparse_solve_retval(*this, b.derived()); +// } + + /** Performs a symbolic decomposition on the sparcity of \a matrix. + * + * This function is particularly useful when solving for several problems having the same structure. + * + * \sa factorize(), compute() + */ + void analyzePattern(const MatrixType& matrix) + { + if(m_symbolic) + umfpack_free_symbolic(&m_symbolic,Scalar()); + if(m_numeric) + umfpack_free_numeric(&m_numeric,Scalar()); + + grapInput(matrix); + + int errorCode = 0; + errorCode = umfpack_symbolic(matrix.rows(), matrix.cols(), m_outerIndexPtr, m_innerIndexPtr, m_valuePtr, + &m_symbolic, 0, 0); + + m_isInitialized = true; + m_info = errorCode ? InvalidInput : Success; + m_analysisIsOk = true; + m_factorizationIsOk = false; + } + + /** Performs a numeric decomposition of \a matrix + * + * The given matrix must has the same sparcity than the matrix on which the pattern anylysis has been performed. + * + * \sa analyzePattern(), compute() + */ + void factorize(const MatrixType& matrix) + { + eigen_assert(m_analysisIsOk && "UmfPackLU: you must first call analyzePattern()"); + if(m_numeric) + umfpack_free_numeric(&m_numeric,Scalar()); + + grapInput(matrix); + + int errorCode; + errorCode = umfpack_numeric(m_outerIndexPtr, m_innerIndexPtr, m_valuePtr, + m_symbolic, &m_numeric, 0, 0); + + m_info = errorCode ? NumericalIssue : Success; + m_factorizationIsOk = true; + } + + #ifndef EIGEN_PARSED_BY_DOXYGEN + /** \internal */ + template + bool _solve(const MatrixBase &b, MatrixBase &x) const; + #endif + + Scalar determinant() const; + + void extractData() const; + + protected: + + + void init() + { + m_info = InvalidInput; + m_isInitialized = false; + m_numeric = 0; + m_symbolic = 0; + m_outerIndexPtr = 0; + m_innerIndexPtr = 0; + m_valuePtr = 0; + } + + void grapInput(const MatrixType& mat) + { + m_copyMatrix.resize(mat.rows(), mat.cols()); + if( ((MatrixType::Flags&RowMajorBit)==RowMajorBit) || sizeof(typename MatrixType::Index)!=sizeof(int) || !mat.isCompressed() ) + { + // non supported input -> copy + m_copyMatrix = mat; + m_outerIndexPtr = m_copyMatrix.outerIndexPtr(); + m_innerIndexPtr = m_copyMatrix.innerIndexPtr(); + m_valuePtr = m_copyMatrix.valuePtr(); + } + else + { + m_outerIndexPtr = mat.outerIndexPtr(); + m_innerIndexPtr = mat.innerIndexPtr(); + m_valuePtr = mat.valuePtr(); + } + } + + // cached data to reduce reallocation, etc. + mutable LUMatrixType m_l; + mutable LUMatrixType m_u; + mutable IntColVectorType m_p; + mutable IntRowVectorType m_q; + + UmfpackMatrixType m_copyMatrix; + const Scalar* m_valuePtr; + const int* m_outerIndexPtr; + const int* m_innerIndexPtr; + void* m_numeric; + void* m_symbolic; + + mutable ComputationInfo m_info; + bool m_isInitialized; + int m_factorizationIsOk; + int m_analysisIsOk; + mutable bool m_extractedDataAreDirty; + + private: + UmfPackLU(UmfPackLU& ) { } +}; + + +template +void UmfPackLU::extractData() const +{ + if (m_extractedDataAreDirty) + { + // get size of the data + int lnz, unz, rows, cols, nz_udiag; + umfpack_get_lunz(&lnz, &unz, &rows, &cols, &nz_udiag, m_numeric, Scalar()); + + // allocate data + m_l.resize(rows,(std::min)(rows,cols)); + m_l.resizeNonZeros(lnz); + + m_u.resize((std::min)(rows,cols),cols); + m_u.resizeNonZeros(unz); + + m_p.resize(rows); + m_q.resize(cols); + + // extract + umfpack_get_numeric(m_l.outerIndexPtr(), m_l.innerIndexPtr(), m_l.valuePtr(), + m_u.outerIndexPtr(), m_u.innerIndexPtr(), m_u.valuePtr(), + m_p.data(), m_q.data(), 0, 0, 0, m_numeric); + + m_extractedDataAreDirty = false; + } +} + +template +typename UmfPackLU::Scalar UmfPackLU::determinant() const +{ + Scalar det; + umfpack_get_determinant(&det, 0, m_numeric, 0); + return det; +} + +template +template +bool UmfPackLU::_solve(const MatrixBase &b, MatrixBase &x) const +{ + const int rhsCols = b.cols(); + eigen_assert((BDerived::Flags&RowMajorBit)==0 && "UmfPackLU backend does not support non col-major rhs yet"); + eigen_assert((XDerived::Flags&RowMajorBit)==0 && "UmfPackLU backend does not support non col-major result yet"); + + int errorCode; + for (int j=0; j +struct solve_retval, Rhs> + : solve_retval_base, Rhs> +{ + typedef UmfPackLU<_MatrixType> Dec; + EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs) + + template void evalTo(Dest& dst) const + { + dec()._solve(rhs(),dst); + } +}; + +template +struct sparse_solve_retval, Rhs> + : sparse_solve_retval_base, Rhs> +{ + typedef UmfPackLU<_MatrixType> Dec; + EIGEN_MAKE_SPARSE_SOLVE_HELPERS(Dec,Rhs) + + template void evalTo(Dest& dst) const + { + dec()._solve(rhs(),dst); + } +}; + +} // end namespace internal + +} // end namespace Eigen + +#endif // EIGEN_UMFPACKSUPPORT_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/misc/Image.h b/gtsam/3rdparty/Eigen/Eigen/src/misc/Image.h index 19b3e08cb..7643a0836 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/misc/Image.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/misc/Image.h @@ -25,6 +25,8 @@ #ifndef EIGEN_MISC_IMAGE_H #define EIGEN_MISC_IMAGE_H +namespace Eigen { + namespace internal { /** \class image_retval_base @@ -92,4 +94,6 @@ template struct image_retval_base image_retval(const DecompositionType& dec, const MatrixType& originalMatrix) \ : Base(dec, originalMatrix) {} +} // end namespace Eigen + #endif // EIGEN_MISC_IMAGE_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/misc/Kernel.h b/gtsam/3rdparty/Eigen/Eigen/src/misc/Kernel.h index 0115970e8..37bc392ef 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/misc/Kernel.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/misc/Kernel.h @@ -25,6 +25,8 @@ #ifndef EIGEN_MISC_KERNEL_H #define EIGEN_MISC_KERNEL_H +namespace Eigen { + namespace internal { /** \class kernel_retval_base @@ -89,4 +91,6 @@ template struct kernel_retval_base using Base::cols; \ kernel_retval(const DecompositionType& dec) : Base(dec) {} +} // end namespace Eigen + #endif // EIGEN_MISC_KERNEL_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/misc/Solve.h b/gtsam/3rdparty/Eigen/Eigen/src/misc/Solve.h index b7cbcadb3..2afd078d4 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/misc/Solve.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/misc/Solve.h @@ -25,6 +25,8 @@ #ifndef EIGEN_MISC_SOLVE_H #define EIGEN_MISC_SOLVE_H +namespace Eigen { + namespace internal { /** \class solve_retval_base @@ -66,7 +68,7 @@ template struct solve_retval_base protected: const DecompositionType& m_dec; - const typename Rhs::Nested m_rhs; + typename Rhs::Nested m_rhs; }; } // end namespace internal @@ -84,4 +86,6 @@ template struct solve_retval_base solve_retval(const DecompositionType& dec, const Rhs& rhs) \ : Base(dec, rhs) {} +} // end namespace Eigen + #endif // EIGEN_MISC_SOLVE_H diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/SparseExtra/Solve.h b/gtsam/3rdparty/Eigen/Eigen/src/misc/SparseSolve.h similarity index 70% rename from gtsam/3rdparty/Eigen/unsupported/Eigen/src/SparseExtra/Solve.h rename to gtsam/3rdparty/Eigen/Eigen/src/misc/SparseSolve.h index 19449e9de..aca34b2d1 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/SparseExtra/Solve.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/misc/SparseSolve.h @@ -25,6 +25,8 @@ #ifndef EIGEN_SPARSE_SOLVE_H #define EIGEN_SPARSE_SOLVE_H +namespace Eigen { + namespace internal { template struct sparse_solve_retval_base; @@ -61,7 +63,7 @@ template struct sparse_solve_retval_b protected: const DecompositionType& m_dec; - const typename Rhs::Nested m_rhs; + typename Rhs::Nested m_rhs; }; #define EIGEN_MAKE_SPARSE_SOLVE_HELPERS(DecompositionType,Rhs) \ @@ -76,7 +78,49 @@ template struct sparse_solve_retval_b using Base::cols; \ sparse_solve_retval(const DecompositionType& dec, const Rhs& rhs) \ : Base(dec, rhs) {} - + + + +template struct solve_retval_with_guess; + +template +struct traits > +{ + typedef typename DecompositionType::MatrixType MatrixType; + typedef Matrix ReturnType; +}; + +template struct solve_retval_with_guess + : public ReturnByValue > +{ + typedef typename DecompositionType::Index Index; + + solve_retval_with_guess(const DecompositionType& dec, const Rhs& rhs, const Guess& guess) + : m_dec(dec), m_rhs(rhs), m_guess(guess) + {} + + inline Index rows() const { return m_dec.cols(); } + inline Index cols() const { return m_rhs.cols(); } + + template inline void evalTo(Dest& dst) const + { + dst = m_guess; + m_dec._solveWithGuess(m_rhs,dst); + } + + protected: + const DecompositionType& m_dec; + const typename Rhs::Nested m_rhs; + const typename Guess::Nested m_guess; +}; + } // namepsace internal +} // end namespace Eigen + #endif // EIGEN_SPARSE_SOLVE_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/misc/blas.h b/gtsam/3rdparty/Eigen/Eigen/src/misc/blas.h new file mode 100644 index 000000000..6fce99ed5 --- /dev/null +++ b/gtsam/3rdparty/Eigen/Eigen/src/misc/blas.h @@ -0,0 +1,658 @@ +#ifndef BLAS_H +#define BLAS_H + +#ifdef __cplusplus +extern "C" +{ +#endif + +#define BLASFUNC(FUNC) FUNC##_ + +#ifdef __WIN64__ +typedef long long BLASLONG; +typedef unsigned long long BLASULONG; +#else +typedef long BLASLONG; +typedef unsigned long BLASULONG; +#endif + +int BLASFUNC(xerbla)(const char *, int *info, int); + +float BLASFUNC(sdot) (int *, float *, int *, float *, int *); +float BLASFUNC(sdsdot)(int *, float *, float *, int *, float *, int *); + +double BLASFUNC(dsdot) (int *, float *, int *, float *, int *); +double BLASFUNC(ddot) (int *, double *, int *, double *, int *); +double BLASFUNC(qdot) (int *, double *, int *, double *, int *); + +int BLASFUNC(cdotuw) (int *, float *, int *, float *, int *, float*); +int BLASFUNC(cdotcw) (int *, float *, int *, float *, int *, float*); +int BLASFUNC(zdotuw) (int *, double *, int *, double *, int *, double*); +int BLASFUNC(zdotcw) (int *, double *, int *, double *, int *, double*); + +int BLASFUNC(saxpy) (int *, float *, float *, int *, float *, int *); +int BLASFUNC(daxpy) (int *, double *, double *, int *, double *, int *); +int BLASFUNC(qaxpy) (int *, double *, double *, int *, double *, int *); +int BLASFUNC(caxpy) (int *, float *, float *, int *, float *, int *); +int BLASFUNC(zaxpy) (int *, double *, double *, int *, double *, int *); +int BLASFUNC(xaxpy) (int *, double *, double *, int *, double *, int *); +int BLASFUNC(caxpyc)(int *, float *, float *, int *, float *, int *); +int BLASFUNC(zaxpyc)(int *, double *, double *, int *, double *, int *); +int BLASFUNC(xaxpyc)(int *, double *, double *, int *, double *, int *); + +int BLASFUNC(scopy) (int *, float *, int *, float *, int *); +int BLASFUNC(dcopy) (int *, double *, int *, double *, int *); +int BLASFUNC(qcopy) (int *, double *, int *, double *, int *); +int BLASFUNC(ccopy) (int *, float *, int *, float *, int *); +int BLASFUNC(zcopy) (int *, double *, int *, double *, int *); +int BLASFUNC(xcopy) (int *, double *, int *, double *, int *); + +int BLASFUNC(sswap) (int *, float *, int *, float *, int *); +int BLASFUNC(dswap) (int *, double *, int *, double *, int *); +int BLASFUNC(qswap) (int *, double *, int *, double *, int *); +int BLASFUNC(cswap) (int *, float *, int *, float *, int *); +int BLASFUNC(zswap) (int *, double *, int *, double *, int *); +int BLASFUNC(xswap) (int *, double *, int *, double *, int *); + +float BLASFUNC(sasum) (int *, float *, int *); +float BLASFUNC(scasum)(int *, float *, int *); +double BLASFUNC(dasum) (int *, double *, int *); +double BLASFUNC(qasum) (int *, double *, int *); +double BLASFUNC(dzasum)(int *, double *, int *); +double BLASFUNC(qxasum)(int *, double *, int *); + +int BLASFUNC(isamax)(int *, float *, int *); +int BLASFUNC(idamax)(int *, double *, int *); +int BLASFUNC(iqamax)(int *, double *, int *); +int BLASFUNC(icamax)(int *, float *, int *); +int BLASFUNC(izamax)(int *, double *, int *); +int BLASFUNC(ixamax)(int *, double *, int *); + +int BLASFUNC(ismax) (int *, float *, int *); +int BLASFUNC(idmax) (int *, double *, int *); +int BLASFUNC(iqmax) (int *, double *, int *); +int BLASFUNC(icmax) (int *, float *, int *); +int BLASFUNC(izmax) (int *, double *, int *); +int BLASFUNC(ixmax) (int *, double *, int *); + +int BLASFUNC(isamin)(int *, float *, int *); +int BLASFUNC(idamin)(int *, double *, int *); +int BLASFUNC(iqamin)(int *, double *, int *); +int BLASFUNC(icamin)(int *, float *, int *); +int BLASFUNC(izamin)(int *, double *, int *); +int BLASFUNC(ixamin)(int *, double *, int *); + +int BLASFUNC(ismin)(int *, float *, int *); +int BLASFUNC(idmin)(int *, double *, int *); +int BLASFUNC(iqmin)(int *, double *, int *); +int BLASFUNC(icmin)(int *, float *, int *); +int BLASFUNC(izmin)(int *, double *, int *); +int BLASFUNC(ixmin)(int *, double *, int *); + +float BLASFUNC(samax) (int *, float *, int *); +double BLASFUNC(damax) (int *, double *, int *); +double BLASFUNC(qamax) (int *, double *, int *); +float BLASFUNC(scamax)(int *, float *, int *); +double BLASFUNC(dzamax)(int *, double *, int *); +double BLASFUNC(qxamax)(int *, double *, int *); + +float BLASFUNC(samin) (int *, float *, int *); +double BLASFUNC(damin) (int *, double *, int *); +double BLASFUNC(qamin) (int *, double *, int *); +float BLASFUNC(scamin)(int *, float *, int *); +double BLASFUNC(dzamin)(int *, double *, int *); +double BLASFUNC(qxamin)(int *, double *, int *); + +float BLASFUNC(smax) (int *, float *, int *); +double BLASFUNC(dmax) (int *, double *, int *); +double BLASFUNC(qmax) (int *, double *, int *); +float BLASFUNC(scmax) (int *, float *, int *); +double BLASFUNC(dzmax) (int *, double *, int *); +double BLASFUNC(qxmax) (int *, double *, int *); + +float BLASFUNC(smin) (int *, float *, int *); +double BLASFUNC(dmin) (int *, double *, int *); +double BLASFUNC(qmin) (int *, double *, int *); +float BLASFUNC(scmin) (int *, float *, int *); +double BLASFUNC(dzmin) (int *, double *, int *); +double BLASFUNC(qxmin) (int *, double *, int *); + +int BLASFUNC(sscal) (int *, float *, float *, int *); +int BLASFUNC(dscal) (int *, double *, double *, int *); +int BLASFUNC(qscal) (int *, double *, double *, int *); +int BLASFUNC(cscal) (int *, float *, float *, int *); +int BLASFUNC(zscal) (int *, double *, double *, int *); +int BLASFUNC(xscal) (int *, double *, double *, int *); +int BLASFUNC(csscal)(int *, float *, float *, int *); +int BLASFUNC(zdscal)(int *, double *, double *, int *); +int BLASFUNC(xqscal)(int *, double *, double *, int *); + +float BLASFUNC(snrm2) (int *, float *, int *); +float BLASFUNC(scnrm2)(int *, float *, int *); + +double BLASFUNC(dnrm2) (int *, double *, int *); +double BLASFUNC(qnrm2) (int *, double *, int *); +double BLASFUNC(dznrm2)(int *, double *, int *); +double BLASFUNC(qxnrm2)(int *, double *, int *); + +int BLASFUNC(srot) (int *, float *, int *, float *, int *, float *, float *); +int BLASFUNC(drot) (int *, double *, int *, double *, int *, double *, double *); +int BLASFUNC(qrot) (int *, double *, int *, double *, int *, double *, double *); +int BLASFUNC(csrot) (int *, float *, int *, float *, int *, float *, float *); +int BLASFUNC(zdrot) (int *, double *, int *, double *, int *, double *, double *); +int BLASFUNC(xqrot) (int *, double *, int *, double *, int *, double *, double *); + +int BLASFUNC(srotg) (float *, float *, float *, float *); +int BLASFUNC(drotg) (double *, double *, double *, double *); +int BLASFUNC(qrotg) (double *, double *, double *, double *); +int BLASFUNC(crotg) (float *, float *, float *, float *); +int BLASFUNC(zrotg) (double *, double *, double *, double *); +int BLASFUNC(xrotg) (double *, double *, double *, double *); + +int BLASFUNC(srotmg)(float *, float *, float *, float *, float *); +int BLASFUNC(drotmg)(double *, double *, double *, double *, double *); + +int BLASFUNC(srotm) (int *, float *, int *, float *, int *, float *); +int BLASFUNC(drotm) (int *, double *, int *, double *, int *, double *); +int BLASFUNC(qrotm) (int *, double *, int *, double *, int *, double *); + +/* Level 2 routines */ + +int BLASFUNC(sger)(int *, int *, float *, float *, int *, + float *, int *, float *, int *); +int BLASFUNC(dger)(int *, int *, double *, double *, int *, + double *, int *, double *, int *); +int BLASFUNC(qger)(int *, int *, double *, double *, int *, + double *, int *, double *, int *); +int BLASFUNC(cgeru)(int *, int *, float *, float *, int *, + float *, int *, float *, int *); +int BLASFUNC(cgerc)(int *, int *, float *, float *, int *, + float *, int *, float *, int *); +int BLASFUNC(zgeru)(int *, int *, double *, double *, int *, + double *, int *, double *, int *); +int BLASFUNC(zgerc)(int *, int *, double *, double *, int *, + double *, int *, double *, int *); +int BLASFUNC(xgeru)(int *, int *, double *, double *, int *, + double *, int *, double *, int *); +int BLASFUNC(xgerc)(int *, int *, double *, double *, int *, + double *, int *, double *, int *); + +int BLASFUNC(sgemv)(char *, int *, int *, float *, float *, int *, + float *, int *, float *, float *, int *); +int BLASFUNC(dgemv)(char *, int *, int *, double *, double *, int *, + double *, int *, double *, double *, int *); +int BLASFUNC(qgemv)(char *, int *, int *, double *, double *, int *, + double *, int *, double *, double *, int *); +int BLASFUNC(cgemv)(char *, int *, int *, float *, float *, int *, + float *, int *, float *, float *, int *); +int BLASFUNC(zgemv)(char *, int *, int *, double *, double *, int *, + double *, int *, double *, double *, int *); +int BLASFUNC(xgemv)(char *, int *, int *, double *, double *, int *, + double *, int *, double *, double *, int *); + +int BLASFUNC(strsv) (char *, char *, char *, int *, float *, int *, + float *, int *); +int BLASFUNC(dtrsv) (char *, char *, char *, int *, double *, int *, + double *, int *); +int BLASFUNC(qtrsv) (char *, char *, char *, int *, double *, int *, + double *, int *); +int BLASFUNC(ctrsv) (char *, char *, char *, int *, float *, int *, + float *, int *); +int BLASFUNC(ztrsv) (char *, char *, char *, int *, double *, int *, + double *, int *); +int BLASFUNC(xtrsv) (char *, char *, char *, int *, double *, int *, + double *, int *); + +int BLASFUNC(stpsv) (char *, char *, char *, int *, float *, float *, int *); +int BLASFUNC(dtpsv) (char *, char *, char *, int *, double *, double *, int *); +int BLASFUNC(qtpsv) (char *, char *, char *, int *, double *, double *, int *); +int BLASFUNC(ctpsv) (char *, char *, char *, int *, float *, float *, int *); +int BLASFUNC(ztpsv) (char *, char *, char *, int *, double *, double *, int *); +int BLASFUNC(xtpsv) (char *, char *, char *, int *, double *, double *, int *); + +int BLASFUNC(strmv) (char *, char *, char *, int *, float *, int *, + float *, int *); +int BLASFUNC(dtrmv) (char *, char *, char *, int *, double *, int *, + double *, int *); +int BLASFUNC(qtrmv) (char *, char *, char *, int *, double *, int *, + double *, int *); +int BLASFUNC(ctrmv) (char *, char *, char *, int *, float *, int *, + float *, int *); +int BLASFUNC(ztrmv) (char *, char *, char *, int *, double *, int *, + double *, int *); +int BLASFUNC(xtrmv) (char *, char *, char *, int *, double *, int *, + double *, int *); + +int BLASFUNC(stpmv) (char *, char *, char *, int *, float *, float *, int *); +int BLASFUNC(dtpmv) (char *, char *, char *, int *, double *, double *, int *); +int BLASFUNC(qtpmv) (char *, char *, char *, int *, double *, double *, int *); +int BLASFUNC(ctpmv) (char *, char *, char *, int *, float *, float *, int *); +int BLASFUNC(ztpmv) (char *, char *, char *, int *, double *, double *, int *); +int BLASFUNC(xtpmv) (char *, char *, char *, int *, double *, double *, int *); + +int BLASFUNC(stbmv) (char *, char *, char *, int *, int *, float *, int *, float *, int *); +int BLASFUNC(dtbmv) (char *, char *, char *, int *, int *, double *, int *, double *, int *); +int BLASFUNC(qtbmv) (char *, char *, char *, int *, int *, double *, int *, double *, int *); +int BLASFUNC(ctbmv) (char *, char *, char *, int *, int *, float *, int *, float *, int *); +int BLASFUNC(ztbmv) (char *, char *, char *, int *, int *, double *, int *, double *, int *); +int BLASFUNC(xtbmv) (char *, char *, char *, int *, int *, double *, int *, double *, int *); + +int BLASFUNC(stbsv) (char *, char *, char *, int *, int *, float *, int *, float *, int *); +int BLASFUNC(dtbsv) (char *, char *, char *, int *, int *, double *, int *, double *, int *); +int BLASFUNC(qtbsv) (char *, char *, char *, int *, int *, double *, int *, double *, int *); +int BLASFUNC(ctbsv) (char *, char *, char *, int *, int *, float *, int *, float *, int *); +int BLASFUNC(ztbsv) (char *, char *, char *, int *, int *, double *, int *, double *, int *); +int BLASFUNC(xtbsv) (char *, char *, char *, int *, int *, double *, int *, double *, int *); + +int BLASFUNC(ssymv) (char *, int *, float *, float *, int *, + float *, int *, float *, float *, int *); +int BLASFUNC(dsymv) (char *, int *, double *, double *, int *, + double *, int *, double *, double *, int *); +int BLASFUNC(qsymv) (char *, int *, double *, double *, int *, + double *, int *, double *, double *, int *); +int BLASFUNC(csymv) (char *, int *, float *, float *, int *, + float *, int *, float *, float *, int *); +int BLASFUNC(zsymv) (char *, int *, double *, double *, int *, + double *, int *, double *, double *, int *); +int BLASFUNC(xsymv) (char *, int *, double *, double *, int *, + double *, int *, double *, double *, int *); + +int BLASFUNC(sspmv) (char *, int *, float *, float *, + float *, int *, float *, float *, int *); +int BLASFUNC(dspmv) (char *, int *, double *, double *, + double *, int *, double *, double *, int *); +int BLASFUNC(qspmv) (char *, int *, double *, double *, + double *, int *, double *, double *, int *); +int BLASFUNC(cspmv) (char *, int *, float *, float *, + float *, int *, float *, float *, int *); +int BLASFUNC(zspmv) (char *, int *, double *, double *, + double *, int *, double *, double *, int *); +int BLASFUNC(xspmv) (char *, int *, double *, double *, + double *, int *, double *, double *, int *); + +int BLASFUNC(ssyr) (char *, int *, float *, float *, int *, + float *, int *); +int BLASFUNC(dsyr) (char *, int *, double *, double *, int *, + double *, int *); +int BLASFUNC(qsyr) (char *, int *, double *, double *, int *, + double *, int *); +int BLASFUNC(csyr) (char *, int *, float *, float *, int *, + float *, int *); +int BLASFUNC(zsyr) (char *, int *, double *, double *, int *, + double *, int *); +int BLASFUNC(xsyr) (char *, int *, double *, double *, int *, + double *, int *); + +int BLASFUNC(ssyr2) (char *, int *, float *, + float *, int *, float *, int *, float *, int *); +int BLASFUNC(dsyr2) (char *, int *, double *, + double *, int *, double *, int *, double *, int *); +int BLASFUNC(qsyr2) (char *, int *, double *, + double *, int *, double *, int *, double *, int *); +int BLASFUNC(csyr2) (char *, int *, float *, + float *, int *, float *, int *, float *, int *); +int BLASFUNC(zsyr2) (char *, int *, double *, + double *, int *, double *, int *, double *, int *); +int BLASFUNC(xsyr2) (char *, int *, double *, + double *, int *, double *, int *, double *, int *); + +int BLASFUNC(sspr) (char *, int *, float *, float *, int *, + float *); +int BLASFUNC(dspr) (char *, int *, double *, double *, int *, + double *); +int BLASFUNC(qspr) (char *, int *, double *, double *, int *, + double *); +int BLASFUNC(cspr) (char *, int *, float *, float *, int *, + float *); +int BLASFUNC(zspr) (char *, int *, double *, double *, int *, + double *); +int BLASFUNC(xspr) (char *, int *, double *, double *, int *, + double *); + +int BLASFUNC(sspr2) (char *, int *, float *, + float *, int *, float *, int *, float *); +int BLASFUNC(dspr2) (char *, int *, double *, + double *, int *, double *, int *, double *); +int BLASFUNC(qspr2) (char *, int *, double *, + double *, int *, double *, int *, double *); +int BLASFUNC(cspr2) (char *, int *, float *, + float *, int *, float *, int *, float *); +int BLASFUNC(zspr2) (char *, int *, double *, + double *, int *, double *, int *, double *); +int BLASFUNC(xspr2) (char *, int *, double *, + double *, int *, double *, int *, double *); + +int BLASFUNC(cher) (char *, int *, float *, float *, int *, + float *, int *); +int BLASFUNC(zher) (char *, int *, double *, double *, int *, + double *, int *); +int BLASFUNC(xher) (char *, int *, double *, double *, int *, + double *, int *); + +int BLASFUNC(chpr) (char *, int *, float *, float *, int *, float *); +int BLASFUNC(zhpr) (char *, int *, double *, double *, int *, double *); +int BLASFUNC(xhpr) (char *, int *, double *, double *, int *, double *); + +int BLASFUNC(cher2) (char *, int *, float *, + float *, int *, float *, int *, float *, int *); +int BLASFUNC(zher2) (char *, int *, double *, + double *, int *, double *, int *, double *, int *); +int BLASFUNC(xher2) (char *, int *, double *, + double *, int *, double *, int *, double *, int *); + +int BLASFUNC(chpr2) (char *, int *, float *, + float *, int *, float *, int *, float *); +int BLASFUNC(zhpr2) (char *, int *, double *, + double *, int *, double *, int *, double *); +int BLASFUNC(xhpr2) (char *, int *, double *, + double *, int *, double *, int *, double *); + +int BLASFUNC(chemv) (char *, int *, float *, float *, int *, + float *, int *, float *, float *, int *); +int BLASFUNC(zhemv) (char *, int *, double *, double *, int *, + double *, int *, double *, double *, int *); +int BLASFUNC(xhemv) (char *, int *, double *, double *, int *, + double *, int *, double *, double *, int *); + +int BLASFUNC(chpmv) (char *, int *, float *, float *, + float *, int *, float *, float *, int *); +int BLASFUNC(zhpmv) (char *, int *, double *, double *, + double *, int *, double *, double *, int *); +int BLASFUNC(xhpmv) (char *, int *, double *, double *, + double *, int *, double *, double *, int *); + +int BLASFUNC(snorm)(char *, int *, int *, float *, int *); +int BLASFUNC(dnorm)(char *, int *, int *, double *, int *); +int BLASFUNC(cnorm)(char *, int *, int *, float *, int *); +int BLASFUNC(znorm)(char *, int *, int *, double *, int *); + +int BLASFUNC(sgbmv)(char *, int *, int *, int *, int *, float *, float *, int *, + float *, int *, float *, float *, int *); +int BLASFUNC(dgbmv)(char *, int *, int *, int *, int *, double *, double *, int *, + double *, int *, double *, double *, int *); +int BLASFUNC(qgbmv)(char *, int *, int *, int *, int *, double *, double *, int *, + double *, int *, double *, double *, int *); +int BLASFUNC(cgbmv)(char *, int *, int *, int *, int *, float *, float *, int *, + float *, int *, float *, float *, int *); +int BLASFUNC(zgbmv)(char *, int *, int *, int *, int *, double *, double *, int *, + double *, int *, double *, double *, int *); +int BLASFUNC(xgbmv)(char *, int *, int *, int *, int *, double *, double *, int *, + double *, int *, double *, double *, int *); + +int BLASFUNC(ssbmv)(char *, int *, int *, float *, float *, int *, + float *, int *, float *, float *, int *); +int BLASFUNC(dsbmv)(char *, int *, int *, double *, double *, int *, + double *, int *, double *, double *, int *); +int BLASFUNC(qsbmv)(char *, int *, int *, double *, double *, int *, + double *, int *, double *, double *, int *); +int BLASFUNC(csbmv)(char *, int *, int *, float *, float *, int *, + float *, int *, float *, float *, int *); +int BLASFUNC(zsbmv)(char *, int *, int *, double *, double *, int *, + double *, int *, double *, double *, int *); +int BLASFUNC(xsbmv)(char *, int *, int *, double *, double *, int *, + double *, int *, double *, double *, int *); + +int BLASFUNC(chbmv)(char *, int *, int *, float *, float *, int *, + float *, int *, float *, float *, int *); +int BLASFUNC(zhbmv)(char *, int *, int *, double *, double *, int *, + double *, int *, double *, double *, int *); +int BLASFUNC(xhbmv)(char *, int *, int *, double *, double *, int *, + double *, int *, double *, double *, int *); + +/* Level 3 routines */ + +int BLASFUNC(sgemm)(char *, char *, int *, int *, int *, float *, + float *, int *, float *, int *, float *, float *, int *); +int BLASFUNC(dgemm)(char *, char *, int *, int *, int *, double *, + double *, int *, double *, int *, double *, double *, int *); +int BLASFUNC(qgemm)(char *, char *, int *, int *, int *, double *, + double *, int *, double *, int *, double *, double *, int *); +int BLASFUNC(cgemm)(char *, char *, int *, int *, int *, float *, + float *, int *, float *, int *, float *, float *, int *); +int BLASFUNC(zgemm)(char *, char *, int *, int *, int *, double *, + double *, int *, double *, int *, double *, double *, int *); +int BLASFUNC(xgemm)(char *, char *, int *, int *, int *, double *, + double *, int *, double *, int *, double *, double *, int *); + +int BLASFUNC(cgemm3m)(char *, char *, int *, int *, int *, float *, + float *, int *, float *, int *, float *, float *, int *); +int BLASFUNC(zgemm3m)(char *, char *, int *, int *, int *, double *, + double *, int *, double *, int *, double *, double *, int *); +int BLASFUNC(xgemm3m)(char *, char *, int *, int *, int *, double *, + double *, int *, double *, int *, double *, double *, int *); + +int BLASFUNC(sge2mm)(char *, char *, char *, int *, int *, + float *, float *, int *, float *, int *, + float *, float *, int *); +int BLASFUNC(dge2mm)(char *, char *, char *, int *, int *, + double *, double *, int *, double *, int *, + double *, double *, int *); +int BLASFUNC(cge2mm)(char *, char *, char *, int *, int *, + float *, float *, int *, float *, int *, + float *, float *, int *); +int BLASFUNC(zge2mm)(char *, char *, char *, int *, int *, + double *, double *, int *, double *, int *, + double *, double *, int *); + +int BLASFUNC(strsm)(char *, char *, char *, char *, int *, int *, + float *, float *, int *, float *, int *); +int BLASFUNC(dtrsm)(char *, char *, char *, char *, int *, int *, + double *, double *, int *, double *, int *); +int BLASFUNC(qtrsm)(char *, char *, char *, char *, int *, int *, + double *, double *, int *, double *, int *); +int BLASFUNC(ctrsm)(char *, char *, char *, char *, int *, int *, + float *, float *, int *, float *, int *); +int BLASFUNC(ztrsm)(char *, char *, char *, char *, int *, int *, + double *, double *, int *, double *, int *); +int BLASFUNC(xtrsm)(char *, char *, char *, char *, int *, int *, + double *, double *, int *, double *, int *); + +int BLASFUNC(strmm)(char *, char *, char *, char *, int *, int *, + float *, float *, int *, float *, int *); +int BLASFUNC(dtrmm)(char *, char *, char *, char *, int *, int *, + double *, double *, int *, double *, int *); +int BLASFUNC(qtrmm)(char *, char *, char *, char *, int *, int *, + double *, double *, int *, double *, int *); +int BLASFUNC(ctrmm)(char *, char *, char *, char *, int *, int *, + float *, float *, int *, float *, int *); +int BLASFUNC(ztrmm)(char *, char *, char *, char *, int *, int *, + double *, double *, int *, double *, int *); +int BLASFUNC(xtrmm)(char *, char *, char *, char *, int *, int *, + double *, double *, int *, double *, int *); + +int BLASFUNC(ssymm)(char *, char *, int *, int *, float *, float *, int *, + float *, int *, float *, float *, int *); +int BLASFUNC(dsymm)(char *, char *, int *, int *, double *, double *, int *, + double *, int *, double *, double *, int *); +int BLASFUNC(qsymm)(char *, char *, int *, int *, double *, double *, int *, + double *, int *, double *, double *, int *); +int BLASFUNC(csymm)(char *, char *, int *, int *, float *, float *, int *, + float *, int *, float *, float *, int *); +int BLASFUNC(zsymm)(char *, char *, int *, int *, double *, double *, int *, + double *, int *, double *, double *, int *); +int BLASFUNC(xsymm)(char *, char *, int *, int *, double *, double *, int *, + double *, int *, double *, double *, int *); + +int BLASFUNC(csymm3m)(char *, char *, int *, int *, float *, float *, int *, + float *, int *, float *, float *, int *); +int BLASFUNC(zsymm3m)(char *, char *, int *, int *, double *, double *, int *, + double *, int *, double *, double *, int *); +int BLASFUNC(xsymm3m)(char *, char *, int *, int *, double *, double *, int *, + double *, int *, double *, double *, int *); + +int BLASFUNC(ssyrk)(char *, char *, int *, int *, float *, float *, int *, + float *, float *, int *); +int BLASFUNC(dsyrk)(char *, char *, int *, int *, double *, double *, int *, + double *, double *, int *); +int BLASFUNC(qsyrk)(char *, char *, int *, int *, double *, double *, int *, + double *, double *, int *); +int BLASFUNC(csyrk)(char *, char *, int *, int *, float *, float *, int *, + float *, float *, int *); +int BLASFUNC(zsyrk)(char *, char *, int *, int *, double *, double *, int *, + double *, double *, int *); +int BLASFUNC(xsyrk)(char *, char *, int *, int *, double *, double *, int *, + double *, double *, int *); + +int BLASFUNC(ssyr2k)(char *, char *, int *, int *, float *, float *, int *, + float *, int *, float *, float *, int *); +int BLASFUNC(dsyr2k)(char *, char *, int *, int *, double *, double *, int *, + double*, int *, double *, double *, int *); +int BLASFUNC(qsyr2k)(char *, char *, int *, int *, double *, double *, int *, + double*, int *, double *, double *, int *); +int BLASFUNC(csyr2k)(char *, char *, int *, int *, float *, float *, int *, + float *, int *, float *, float *, int *); +int BLASFUNC(zsyr2k)(char *, char *, int *, int *, double *, double *, int *, + double*, int *, double *, double *, int *); +int BLASFUNC(xsyr2k)(char *, char *, int *, int *, double *, double *, int *, + double*, int *, double *, double *, int *); + +int BLASFUNC(chemm)(char *, char *, int *, int *, float *, float *, int *, + float *, int *, float *, float *, int *); +int BLASFUNC(zhemm)(char *, char *, int *, int *, double *, double *, int *, + double *, int *, double *, double *, int *); +int BLASFUNC(xhemm)(char *, char *, int *, int *, double *, double *, int *, + double *, int *, double *, double *, int *); + +int BLASFUNC(chemm3m)(char *, char *, int *, int *, float *, float *, int *, + float *, int *, float *, float *, int *); +int BLASFUNC(zhemm3m)(char *, char *, int *, int *, double *, double *, int *, + double *, int *, double *, double *, int *); +int BLASFUNC(xhemm3m)(char *, char *, int *, int *, double *, double *, int *, + double *, int *, double *, double *, int *); + +int BLASFUNC(cherk)(char *, char *, int *, int *, float *, float *, int *, + float *, float *, int *); +int BLASFUNC(zherk)(char *, char *, int *, int *, double *, double *, int *, + double *, double *, int *); +int BLASFUNC(xherk)(char *, char *, int *, int *, double *, double *, int *, + double *, double *, int *); + +int BLASFUNC(cher2k)(char *, char *, int *, int *, float *, float *, int *, + float *, int *, float *, float *, int *); +int BLASFUNC(zher2k)(char *, char *, int *, int *, double *, double *, int *, + double*, int *, double *, double *, int *); +int BLASFUNC(xher2k)(char *, char *, int *, int *, double *, double *, int *, + double*, int *, double *, double *, int *); +int BLASFUNC(cher2m)(char *, char *, char *, int *, int *, float *, float *, int *, + float *, int *, float *, float *, int *); +int BLASFUNC(zher2m)(char *, char *, char *, int *, int *, double *, double *, int *, + double*, int *, double *, double *, int *); +int BLASFUNC(xher2m)(char *, char *, char *, int *, int *, double *, double *, int *, + double*, int *, double *, double *, int *); + +int BLASFUNC(sgemt)(char *, int *, int *, float *, float *, int *, + float *, int *); +int BLASFUNC(dgemt)(char *, int *, int *, double *, double *, int *, + double *, int *); +int BLASFUNC(cgemt)(char *, int *, int *, float *, float *, int *, + float *, int *); +int BLASFUNC(zgemt)(char *, int *, int *, double *, double *, int *, + double *, int *); + +int BLASFUNC(sgema)(char *, char *, int *, int *, float *, + float *, int *, float *, float *, int *, float *, int *); +int BLASFUNC(dgema)(char *, char *, int *, int *, double *, + double *, int *, double*, double *, int *, double*, int *); +int BLASFUNC(cgema)(char *, char *, int *, int *, float *, + float *, int *, float *, float *, int *, float *, int *); +int BLASFUNC(zgema)(char *, char *, int *, int *, double *, + double *, int *, double*, double *, int *, double*, int *); + +int BLASFUNC(sgems)(char *, char *, int *, int *, float *, + float *, int *, float *, float *, int *, float *, int *); +int BLASFUNC(dgems)(char *, char *, int *, int *, double *, + double *, int *, double*, double *, int *, double*, int *); +int BLASFUNC(cgems)(char *, char *, int *, int *, float *, + float *, int *, float *, float *, int *, float *, int *); +int BLASFUNC(zgems)(char *, char *, int *, int *, double *, + double *, int *, double*, double *, int *, double*, int *); + +int BLASFUNC(sgetf2)(int *, int *, float *, int *, int *, int *); +int BLASFUNC(dgetf2)(int *, int *, double *, int *, int *, int *); +int BLASFUNC(qgetf2)(int *, int *, double *, int *, int *, int *); +int BLASFUNC(cgetf2)(int *, int *, float *, int *, int *, int *); +int BLASFUNC(zgetf2)(int *, int *, double *, int *, int *, int *); +int BLASFUNC(xgetf2)(int *, int *, double *, int *, int *, int *); + +int BLASFUNC(sgetrf)(int *, int *, float *, int *, int *, int *); +int BLASFUNC(dgetrf)(int *, int *, double *, int *, int *, int *); +int BLASFUNC(qgetrf)(int *, int *, double *, int *, int *, int *); +int BLASFUNC(cgetrf)(int *, int *, float *, int *, int *, int *); +int BLASFUNC(zgetrf)(int *, int *, double *, int *, int *, int *); +int BLASFUNC(xgetrf)(int *, int *, double *, int *, int *, int *); + +int BLASFUNC(slaswp)(int *, float *, int *, int *, int *, int *, int *); +int BLASFUNC(dlaswp)(int *, double *, int *, int *, int *, int *, int *); +int BLASFUNC(qlaswp)(int *, double *, int *, int *, int *, int *, int *); +int BLASFUNC(claswp)(int *, float *, int *, int *, int *, int *, int *); +int BLASFUNC(zlaswp)(int *, double *, int *, int *, int *, int *, int *); +int BLASFUNC(xlaswp)(int *, double *, int *, int *, int *, int *, int *); + +int BLASFUNC(sgetrs)(char *, int *, int *, float *, int *, int *, float *, int *, int *); +int BLASFUNC(dgetrs)(char *, int *, int *, double *, int *, int *, double *, int *, int *); +int BLASFUNC(qgetrs)(char *, int *, int *, double *, int *, int *, double *, int *, int *); +int BLASFUNC(cgetrs)(char *, int *, int *, float *, int *, int *, float *, int *, int *); +int BLASFUNC(zgetrs)(char *, int *, int *, double *, int *, int *, double *, int *, int *); +int BLASFUNC(xgetrs)(char *, int *, int *, double *, int *, int *, double *, int *, int *); + +int BLASFUNC(sgesv)(int *, int *, float *, int *, int *, float *, int *, int *); +int BLASFUNC(dgesv)(int *, int *, double *, int *, int *, double*, int *, int *); +int BLASFUNC(qgesv)(int *, int *, double *, int *, int *, double*, int *, int *); +int BLASFUNC(cgesv)(int *, int *, float *, int *, int *, float *, int *, int *); +int BLASFUNC(zgesv)(int *, int *, double *, int *, int *, double*, int *, int *); +int BLASFUNC(xgesv)(int *, int *, double *, int *, int *, double*, int *, int *); + +int BLASFUNC(spotf2)(char *, int *, float *, int *, int *); +int BLASFUNC(dpotf2)(char *, int *, double *, int *, int *); +int BLASFUNC(qpotf2)(char *, int *, double *, int *, int *); +int BLASFUNC(cpotf2)(char *, int *, float *, int *, int *); +int BLASFUNC(zpotf2)(char *, int *, double *, int *, int *); +int BLASFUNC(xpotf2)(char *, int *, double *, int *, int *); + +int BLASFUNC(spotrf)(char *, int *, float *, int *, int *); +int BLASFUNC(dpotrf)(char *, int *, double *, int *, int *); +int BLASFUNC(qpotrf)(char *, int *, double *, int *, int *); +int BLASFUNC(cpotrf)(char *, int *, float *, int *, int *); +int BLASFUNC(zpotrf)(char *, int *, double *, int *, int *); +int BLASFUNC(xpotrf)(char *, int *, double *, int *, int *); + +int BLASFUNC(slauu2)(char *, int *, float *, int *, int *); +int BLASFUNC(dlauu2)(char *, int *, double *, int *, int *); +int BLASFUNC(qlauu2)(char *, int *, double *, int *, int *); +int BLASFUNC(clauu2)(char *, int *, float *, int *, int *); +int BLASFUNC(zlauu2)(char *, int *, double *, int *, int *); +int BLASFUNC(xlauu2)(char *, int *, double *, int *, int *); + +int BLASFUNC(slauum)(char *, int *, float *, int *, int *); +int BLASFUNC(dlauum)(char *, int *, double *, int *, int *); +int BLASFUNC(qlauum)(char *, int *, double *, int *, int *); +int BLASFUNC(clauum)(char *, int *, float *, int *, int *); +int BLASFUNC(zlauum)(char *, int *, double *, int *, int *); +int BLASFUNC(xlauum)(char *, int *, double *, int *, int *); + +int BLASFUNC(strti2)(char *, char *, int *, float *, int *, int *); +int BLASFUNC(dtrti2)(char *, char *, int *, double *, int *, int *); +int BLASFUNC(qtrti2)(char *, char *, int *, double *, int *, int *); +int BLASFUNC(ctrti2)(char *, char *, int *, float *, int *, int *); +int BLASFUNC(ztrti2)(char *, char *, int *, double *, int *, int *); +int BLASFUNC(xtrti2)(char *, char *, int *, double *, int *, int *); + +int BLASFUNC(strtri)(char *, char *, int *, float *, int *, int *); +int BLASFUNC(dtrtri)(char *, char *, int *, double *, int *, int *); +int BLASFUNC(qtrtri)(char *, char *, int *, double *, int *, int *); +int BLASFUNC(ctrtri)(char *, char *, int *, float *, int *, int *); +int BLASFUNC(ztrtri)(char *, char *, int *, double *, int *, int *); +int BLASFUNC(xtrtri)(char *, char *, int *, double *, int *, int *); + +int BLASFUNC(spotri)(char *, int *, float *, int *, int *); +int BLASFUNC(dpotri)(char *, int *, double *, int *, int *); +int BLASFUNC(qpotri)(char *, int *, double *, int *, int *); +int BLASFUNC(cpotri)(char *, int *, float *, int *, int *); +int BLASFUNC(zpotri)(char *, int *, double *, int *, int *); +int BLASFUNC(xpotri)(char *, int *, double *, int *, int *); + +#ifdef __cplusplus +} +#endif + +#endif diff --git a/gtsam/3rdparty/Eigen/Eigen/src/plugins/ArrayCwiseBinaryOps.h b/gtsam/3rdparty/Eigen/Eigen/src/plugins/ArrayCwiseBinaryOps.h index 7d509e78f..5b979ebf8 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/plugins/ArrayCwiseBinaryOps.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/plugins/ArrayCwiseBinaryOps.h @@ -29,6 +29,16 @@ operator/(const EIGEN_CURRENT_STORAGE_BASE_CLASS &other) const */ EIGEN_MAKE_CWISE_BINARY_OP(min,internal::scalar_min_op) +/** \returns an expression of the coefficient-wise min of \c *this and scalar \a other + * + * \sa max() + */ +EIGEN_STRONG_INLINE const CwiseBinaryOp, const Derived, const ConstantReturnType> +(min)(const Scalar &other) const +{ + return (min)(Derived::PlainObject::Constant(rows(), cols(), other)); +} + /** \returns an expression of the coefficient-wise max of \c *this and \a other * * Example: \include Cwise_max.cpp @@ -38,6 +48,16 @@ EIGEN_MAKE_CWISE_BINARY_OP(min,internal::scalar_min_op) */ EIGEN_MAKE_CWISE_BINARY_OP(max,internal::scalar_max_op) +/** \returns an expression of the coefficient-wise max of \c *this and scalar \a other + * + * \sa min() + */ +EIGEN_STRONG_INLINE const CwiseBinaryOp, const Derived, const ConstantReturnType> +(max)(const Scalar &other) const +{ + return (max)(Derived::PlainObject::Constant(rows(), cols(), other)); +} + /** \returns an expression of the coefficient-wise \< operator of *this and \a other * * Example: \include Cwise_less.cpp @@ -141,3 +161,39 @@ operator-(const Scalar& scalar,const EIGEN_CURRENT_STORAGE_BASE_CLASS& { return (-other) + scalar; } + +/** \returns an expression of the coefficient-wise && operator of *this and \a other + * + * \warning this operator is for expression of bool only. + * + * Example: \include Cwise_boolean_and.cpp + * Output: \verbinclude Cwise_boolean_and.out + * + * \sa operator||(), select() + */ +template +inline const CwiseBinaryOp +operator&&(const EIGEN_CURRENT_STORAGE_BASE_CLASS &other) const +{ + EIGEN_STATIC_ASSERT((internal::is_same::value && internal::is_same::value), + THIS_METHOD_IS_ONLY_FOR_EXPRESSIONS_OF_BOOL); + return CwiseBinaryOp(derived(),other.derived()); +} + +/** \returns an expression of the coefficient-wise || operator of *this and \a other + * + * \warning this operator is for expression of bool only. + * + * Example: \include Cwise_boolean_or.cpp + * Output: \verbinclude Cwise_boolean_or.out + * + * \sa operator&&(), select() + */ +template +inline const CwiseBinaryOp +operator||(const EIGEN_CURRENT_STORAGE_BASE_CLASS &other) const +{ + EIGEN_STATIC_ASSERT((internal::is_same::value && internal::is_same::value), + THIS_METHOD_IS_ONLY_FOR_EXPRESSIONS_OF_BOOL); + return CwiseBinaryOp(derived(),other.derived()); +} diff --git a/gtsam/3rdparty/Eigen/Eigen/src/plugins/MatrixCwiseBinaryOps.h b/gtsam/3rdparty/Eigen/Eigen/src/plugins/MatrixCwiseBinaryOps.h index 35183f91f..566f4c1f4 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/plugins/MatrixCwiseBinaryOps.h +++ b/gtsam/3rdparty/Eigen/Eigen/src/plugins/MatrixCwiseBinaryOps.h @@ -91,6 +91,16 @@ cwiseMin(const EIGEN_CURRENT_STORAGE_BASE_CLASS &other) const return CwiseBinaryOp, const Derived, const OtherDerived>(derived(), other.derived()); } +/** \returns an expression of the coefficient-wise min of *this and scalar \a other + * + * \sa class CwiseBinaryOp, min() + */ +EIGEN_STRONG_INLINE const CwiseBinaryOp, const Derived, const ConstantReturnType> +cwiseMin(const Scalar &other) const +{ + return cwiseMin(Derived::PlainObject::Constant(rows(), cols(), other)); +} + /** \returns an expression of the coefficient-wise max of *this and \a other * * Example: \include MatrixBase_cwiseMax.cpp @@ -105,6 +115,17 @@ cwiseMax(const EIGEN_CURRENT_STORAGE_BASE_CLASS &other) const return CwiseBinaryOp, const Derived, const OtherDerived>(derived(), other.derived()); } +/** \returns an expression of the coefficient-wise max of *this and scalar \a other + * + * \sa class CwiseBinaryOp, min() + */ +EIGEN_STRONG_INLINE const CwiseBinaryOp, const Derived, const ConstantReturnType> +cwiseMax(const Scalar &other) const +{ + return cwiseMax(Derived::PlainObject::Constant(rows(), cols(), other)); +} + + /** \returns an expression of the coefficient-wise quotient of *this and \a other * * Example: \include MatrixBase_cwiseQuotient.cpp diff --git a/gtsam/3rdparty/Eigen/bench/BenchSparseUtil.h b/gtsam/3rdparty/Eigen/bench/BenchSparseUtil.h index ff836bffe..13981f6b7 100644 --- a/gtsam/3rdparty/Eigen/bench/BenchSparseUtil.h +++ b/gtsam/3rdparty/Eigen/bench/BenchSparseUtil.h @@ -26,7 +26,7 @@ typedef SparseMatrix EigenSparseMatrix; void fillMatrix(float density, int rows, int cols, EigenSparseMatrix& dst) { - dst.reserve(rows*cols*density); + dst.reserve(double(rows)*cols*density); for(int j = 0; j < cols; j++) { for(int i = 0; i < rows; i++) @@ -122,22 +122,24 @@ void eiToCSparse(const EigenSparseMatrix& src, cs* &dst) #include #include #include -// #include -// using namespace boost; -// using namespace boost::numeric; -// using namespace boost::numeric::ublas; +typedef boost::numeric::ublas::compressed_matrix UBlasSparse; -typedef boost::numeric::ublas::compressed_matrix UblasMatrix; - -void eiToUblas(const EigenSparseMatrix& src, UblasMatrix& dst) +void eiToUblas(const EigenSparseMatrix& src, UBlasSparse& dst) { + dst.resize(src.rows(), src.cols(), false); for (int j=0; j +void eiToUblasVec(const EigenType& src, UblasType& dst) +{ + dst.resize(src.size()); + for (int j=0; j +#elif defined(__APPLE__) +#include +#include #else # include #endif @@ -76,6 +79,7 @@ public: inline void reset() { m_bests.fill(1e9); + m_worsts.fill(0); m_totals.setZero(); } inline void start() @@ -89,40 +93,52 @@ public: m_times[REAL_TIMER] = getRealTime() - m_starts[REAL_TIMER]; #if EIGEN_VERSION_AT_LEAST(2,90,0) m_bests = m_bests.cwiseMin(m_times); + m_worsts = m_worsts.cwiseMax(m_times); #else m_bests(0) = std::min(m_bests(0),m_times(0)); m_bests(1) = std::min(m_bests(1),m_times(1)); + m_worsts(0) = std::max(m_worsts(0),m_times(0)); + m_worsts(1) = std::max(m_worsts(1),m_times(1)); #endif m_totals += m_times; } /** Return the elapsed time in seconds between the last start/stop pair */ - inline double value(int TIMER = CPU_TIMER) + inline double value(int TIMER = CPU_TIMER) const { return m_times[TIMER]; } /** Return the best elapsed time in seconds */ - inline double best(int TIMER = CPU_TIMER) + inline double best(int TIMER = CPU_TIMER) const { return m_bests[TIMER]; } + /** Return the worst elapsed time in seconds + */ + inline double worst(int TIMER = CPU_TIMER) const + { + return m_worsts[TIMER]; + } + /** Return the total elapsed time in seconds. */ - inline double total(int TIMER = CPU_TIMER) + inline double total(int TIMER = CPU_TIMER) const { return m_totals[TIMER]; } - inline double getCpuTime() + inline double getCpuTime() const { #ifdef _WIN32 LARGE_INTEGER query_ticks; QueryPerformanceCounter(&query_ticks); return query_ticks.QuadPart/m_frequency; +#elif __APPLE__ + return double(mach_absolute_time())*1e-9; #else timespec ts; clock_gettime(CLOCK_PROCESS_CPUTIME_ID, &ts); @@ -130,12 +146,14 @@ public: #endif } - inline double getRealTime() + inline double getRealTime() const { #ifdef _WIN32 SYSTEMTIME st; GetSystemTime(&st); return (double)st.wSecond + 1.e-3 * (double)st.wMilliseconds; +#elif __APPLE__ + return double(mach_absolute_time())*1e-9; #else timespec ts; clock_gettime(CLOCK_REALTIME, &ts); @@ -150,8 +168,11 @@ protected: Vector2d m_starts; Vector2d m_times; Vector2d m_bests; + Vector2d m_worsts; Vector2d m_totals; +public: + EIGEN_MAKE_ALIGNED_OPERATOR_NEW }; #define BENCH(TIMER,TRIES,REP,CODE) { \ diff --git a/gtsam/3rdparty/Eigen/bench/BenchUtil.h b/gtsam/3rdparty/Eigen/bench/BenchUtil.h index 9798fa385..8883a1380 100644 --- a/gtsam/3rdparty/Eigen/bench/BenchUtil.h +++ b/gtsam/3rdparty/Eigen/bench/BenchUtil.h @@ -69,4 +69,24 @@ void eiToGsl(const EigenMatrixType& src, gsl_matrix** dst) } #endif +#ifdef BENCH_UBLAS +#include +#include +template +void eiToUblas(const EigenMatrixType& src, UblasMatrixType& dst) +{ + dst.resize(src.rows(),src.cols()); + for (int j=0; j +void eiToUblasVec(const EigenType& src, UblasType& dst) +{ + dst.resize(src.size()); + for (int j=0; j(kc, mc, nc); + internal::computeProductBlockingSizes(kc, mc, nc); std::cout << "blocking size (mc x kc) = " << mc << " x " << kc << "\n"; C r = c; @@ -188,23 +189,22 @@ int main(int argc, char ** argv) blas_gemm(a,b,r); c.noalias() += a * b; if(!r.isApprox(c)) std::cerr << "Warning, your product is crap!\n\n"; -// std::cerr << r << "\n\n" << c << "\n\n"; #else gemm(a,b,c); r.noalias() += a.cast() * b.cast(); if(!r.isApprox(c)) std::cerr << "Warning, your product is crap!\n\n"; -// std::cerr << c << "\n\n"; -// std::cerr << r << "\n\n"; #endif #ifdef HAVE_BLAS BenchTimer tblas; + c = rc; BENCH(tblas, tries, rep, blas_gemm(a,b,c)); std::cout << "blas cpu " << tblas.best(CPU_TIMER)/rep << "s \t" << (double(m)*n*p*rep*2/tblas.best(CPU_TIMER))*1e-9 << " GFLOPS \t(" << tblas.total(CPU_TIMER) << "s)\n"; std::cout << "blas real " << tblas.best(REAL_TIMER)/rep << "s \t" << (double(m)*n*p*rep*2/tblas.best(REAL_TIMER))*1e-9 << " GFLOPS \t(" << tblas.total(REAL_TIMER) << "s)\n"; #endif BenchTimer tmt; + c = rc; BENCH(tmt, tries, rep, gemm(a,b,c)); std::cout << "eigen cpu " << tmt.best(CPU_TIMER)/rep << "s \t" << (double(m)*n*p*rep*2/tmt.best(CPU_TIMER))*1e-9 << " GFLOPS \t(" << tmt.total(CPU_TIMER) << "s)\n"; std::cout << "eigen real " << tmt.best(REAL_TIMER)/rep << "s \t" << (double(m)*n*p*rep*2/tmt.best(REAL_TIMER))*1e-9 << " GFLOPS \t(" << tmt.total(REAL_TIMER) << "s)\n"; @@ -213,8 +213,9 @@ int main(int argc, char ** argv) if(procs>1) { BenchTimer tmono; - //omp_set_num_threads(1); - Eigen::setNbThreads(1); + omp_set_num_threads(1); + Eigen::internal::setNbThreads(1); + c = rc; BENCH(tmono, tries, rep, gemm(a,b,c)); std::cout << "eigen mono cpu " << tmono.best(CPU_TIMER)/rep << "s \t" << (double(m)*n*p*rep*2/tmono.best(CPU_TIMER))*1e-9 << " GFLOPS \t(" << tmono.total(CPU_TIMER) << "s)\n"; std::cout << "eigen mono real " << tmono.best(REAL_TIMER)/rep << "s \t" << (double(m)*n*p*rep*2/tmono.best(REAL_TIMER))*1e-9 << " GFLOPS \t(" << tmono.total(REAL_TIMER) << "s)\n"; diff --git a/gtsam/3rdparty/Eigen/bench/btl/CMakeLists.txt b/gtsam/3rdparty/Eigen/bench/btl/CMakeLists.txt index 95ffbf42a..119b470d9 100644 --- a/gtsam/3rdparty/Eigen/bench/btl/CMakeLists.txt +++ b/gtsam/3rdparty/Eigen/bench/btl/CMakeLists.txt @@ -2,7 +2,7 @@ PROJECT(BTL) CMAKE_MINIMUM_REQUIRED(VERSION 2.6.2) -set(CMAKE_MODULE_PATH ${PROJECT_SOURCE_DIR}/cmake) +set(CMAKE_MODULE_PATH ${PROJECT_SOURCE_DIR}/cmake ${Eigen_SOURCE_DIR}/cmake) include(MacroOptionalAddSubdirectory) OPTION(BTL_NOVEC "Disable SSE/Altivec optimizations when possible" OFF) @@ -90,17 +90,14 @@ endmacro(btl_add_target_property) ENABLE_TESTING() add_subdirectory(libs/eigen3) -# add_subdirectory(libs/hand_vec) +add_subdirectory(libs/eigen2) +add_subdirectory(libs/BLAS) +add_subdirectory(libs/ublas) add_subdirectory(libs/gmm) add_subdirectory(libs/mtl4) -add_subdirectory(libs/ublas) add_subdirectory(libs/blitz) add_subdirectory(libs/tvmet) -add_subdirectory(libs/C_BLAS) -add_subdirectory(libs/f77) -add_subdirectory(libs/C) add_subdirectory(libs/STL) -add_subdirectory(libs/STL_algo) add_subdirectory(data) diff --git a/gtsam/3rdparty/Eigen/bench/btl/actions/action_aat_product.hh b/gtsam/3rdparty/Eigen/bench/btl/actions/action_aat_product.hh index 92930e219..aa5b35c94 100644 --- a/gtsam/3rdparty/Eigen/bench/btl/actions/action_aat_product.hh +++ b/gtsam/3rdparty/Eigen/bench/btl/actions/action_aat_product.hh @@ -87,7 +87,7 @@ public : } double nb_op_base( void ){ - return 2.0*_size*_size*_size; + return double(_size)*double(_size)*double(_size); } inline void initialize( void ){ diff --git a/gtsam/3rdparty/Eigen/bench/btl/actions/action_hessenberg.hh b/gtsam/3rdparty/Eigen/bench/btl/actions/action_hessenberg.hh index a46964657..2100ebd89 100644 --- a/gtsam/3rdparty/Eigen/bench/btl/actions/action_hessenberg.hh +++ b/gtsam/3rdparty/Eigen/bench/btl/actions/action_hessenberg.hh @@ -136,14 +136,17 @@ public : Action_tridiagonalization( int size ):_size(size) { - MESSAGE("Action_hessenberg Ctor"); + MESSAGE("Action_tridiagonalization Ctor"); // STL vector initialization - typename Interface::stl_matrix tmp; - init_matrix(tmp,_size); - init_matrix(X_stl,_size); - STL_interface::ata_product(tmp,X_stl,_size); - + init_matrix(X_stl,_size); + + for(int i=0; i<_size; ++i) + { + for(int j=0; j(C_stl,_size); init_matrix(resu_stl,_size); @@ -155,9 +158,9 @@ public : _cost = 0; for (int j=0; j<_size-2; ++j) { - int r = std::max(0,_size-j-1); - int b = std::max(0,_size-j-2); - _cost += 6 + 3*b + r*r*8; + double r = std::max(0,_size-j-1); + double b = std::max(0,_size-j-2); + _cost += 6. + 3.*b + r*r*8.; } } diff --git a/gtsam/3rdparty/Eigen/bench/btl/actions/basic_actions.hh b/gtsam/3rdparty/Eigen/bench/btl/actions/basic_actions.hh index 62442f01f..a3333ea26 100644 --- a/gtsam/3rdparty/Eigen/bench/btl/actions/basic_actions.hh +++ b/gtsam/3rdparty/Eigen/bench/btl/actions/basic_actions.hh @@ -6,7 +6,7 @@ #include "action_atv_product.hh" #include "action_matrix_matrix_product.hh" -#include "action_ata_product.hh" +// #include "action_ata_product.hh" #include "action_aat_product.hh" #include "action_trisolve.hh" diff --git a/gtsam/3rdparty/Eigen/bench/btl/cmake/FindEigen3.cmake b/gtsam/3rdparty/Eigen/bench/btl/cmake/FindEigen3.cmake deleted file mode 100644 index 9c546a05d..000000000 --- a/gtsam/3rdparty/Eigen/bench/btl/cmake/FindEigen3.cmake +++ /dev/null @@ -1,81 +0,0 @@ -# - Try to find Eigen3 lib -# -# This module supports requiring a minimum version, e.g. you can do -# find_package(Eigen3 3.1.2) -# to require version 3.1.2 or newer of Eigen3. -# -# Once done this will define -# -# EIGEN3_FOUND - system has eigen lib with correct version -# EIGEN3_INCLUDE_DIR - the eigen include directory -# EIGEN3_VERSION - eigen version - -# Copyright (c) 2006, 2007 Montel Laurent, -# Copyright (c) 2008, 2009 Gael Guennebaud, -# Copyright (c) 2009 Benoit Jacob -# Redistribution and use is allowed according to the terms of the 2-clause BSD license. - -if(NOT Eigen3_FIND_VERSION) - if(NOT Eigen3_FIND_VERSION_MAJOR) - set(Eigen3_FIND_VERSION_MAJOR 2) - endif(NOT Eigen3_FIND_VERSION_MAJOR) - if(NOT Eigen3_FIND_VERSION_MINOR) - set(Eigen3_FIND_VERSION_MINOR 91) - endif(NOT Eigen3_FIND_VERSION_MINOR) - if(NOT Eigen3_FIND_VERSION_PATCH) - set(Eigen3_FIND_VERSION_PATCH 0) - endif(NOT Eigen3_FIND_VERSION_PATCH) - - set(Eigen3_FIND_VERSION "${Eigen3_FIND_VERSION_MAJOR}.${Eigen3_FIND_VERSION_MINOR}.${Eigen3_FIND_VERSION_PATCH}") -endif(NOT Eigen3_FIND_VERSION) - -macro(_eigen3_check_version) - file(READ "${EIGEN3_INCLUDE_DIR}/Eigen/src/Core/util/Macros.h" _eigen3_version_header) - - string(REGEX MATCH "define[ \t]+EIGEN_WORLD_VERSION[ \t]+([0-9]+)" _eigen3_world_version_match "${_eigen3_version_header}") - set(EIGEN3_WORLD_VERSION "${CMAKE_MATCH_1}") - string(REGEX MATCH "define[ \t]+EIGEN_MAJOR_VERSION[ \t]+([0-9]+)" _eigen3_major_version_match "${_eigen3_version_header}") - set(EIGEN3_MAJOR_VERSION "${CMAKE_MATCH_1}") - string(REGEX MATCH "define[ \t]+EIGEN_MINOR_VERSION[ \t]+([0-9]+)" _eigen3_minor_version_match "${_eigen3_version_header}") - set(EIGEN3_MINOR_VERSION "${CMAKE_MATCH_1}") - - set(EIGEN3_VERSION ${EIGEN3_WORLD_VERSION}.${EIGEN3_MAJOR_VERSION}.${EIGEN3_MINOR_VERSION}) - if(${EIGEN3_VERSION} VERSION_LESS ${Eigen3_FIND_VERSION}) - set(EIGEN3_VERSION_OK FALSE) - else(${EIGEN3_VERSION} VERSION_LESS ${Eigen3_FIND_VERSION}) - set(EIGEN3_VERSION_OK TRUE) - endif(${EIGEN3_VERSION} VERSION_LESS ${Eigen3_FIND_VERSION}) - - if(NOT EIGEN3_VERSION_OK) - - message(STATUS "Eigen3 version ${EIGEN3_VERSION} found in ${EIGEN3_INCLUDE_DIR}, " - "but at least version ${Eigen3_FIND_VERSION} is required") - endif(NOT EIGEN3_VERSION_OK) -endmacro(_eigen3_check_version) - -if (EIGEN3_INCLUDE_DIR) - - # in cache already - _eigen3_check_version() - set(EIGEN3_FOUND ${EIGEN3_VERSION_OK}) - -else (EIGEN3_INCLUDE_DIR) - - find_path(EIGEN3_INCLUDE_DIR NAMES signature_of_eigen3_matrix_library - PATHS - ${CMAKE_INSTALL_PREFIX}/include - ${KDE4_INCLUDE_DIR} - PATH_SUFFIXES eigen3 eigen - ) - - if(EIGEN3_INCLUDE_DIR) - _eigen3_check_version() - endif(EIGEN3_INCLUDE_DIR) - - include(FindPackageHandleStandardArgs) - find_package_handle_standard_args(Eigen3 DEFAULT_MSG EIGEN3_INCLUDE_DIR EIGEN3_VERSION_OK) - - mark_as_advanced(EIGEN3_INCLUDE_DIR) - -endif(EIGEN3_INCLUDE_DIR) - diff --git a/gtsam/3rdparty/Eigen/bench/btl/data/action_settings.txt b/gtsam/3rdparty/Eigen/bench/btl/data/action_settings.txt index da80f56a0..e32213e22 100644 --- a/gtsam/3rdparty/Eigen/bench/btl/data/action_settings.txt +++ b/gtsam/3rdparty/Eigen/bench/btl/data/action_settings.txt @@ -5,6 +5,7 @@ axpby ; "{/*1.5 Y = alpha X + beta Y}" ; "vector size" ; 5:1000000 axpy ; "{/*1.5 Y += alpha X}" ; "vector size" ; 5:1000000 matrix_matrix ; "{/*1.5 matrix matrix product}" ; "matrix size" ; 4:3000 matrix_vector ; "{/*1.5 matrix vector product}" ; "matrix size" ; 4:3000 +trmm ; "{/*1.5 triangular matrix matrix product}" ; "matrix size" ; 4:3000 trisolve_vector ; "{/*1.5 triangular solver - vector (X = inv(L) X)}" ; "size" ; 4:3000 trisolve_matrix ; "{/*1.5 triangular solver - matrix (M = inv(L) M)}" ; "size" ; 4:3000 cholesky ; "{/*1.5 Cholesky decomposition}" ; "matrix size" ; 4:3000 diff --git a/gtsam/3rdparty/Eigen/bench/btl/data/go_mean b/gtsam/3rdparty/Eigen/bench/btl/data/go_mean index 37f29fa17..42338ca27 100755 --- a/gtsam/3rdparty/Eigen/bench/btl/data/go_mean +++ b/gtsam/3rdparty/Eigen/bench/btl/data/go_mean @@ -27,7 +27,7 @@ echo '
    '\ '
  • ' `cat /proc/cpuinfo | grep "model name" | head -n 1`\ ' (' `uname -m` ')
    • '\ '
  • compiler: ' `cat compiler_version.txt` '
    • '\ - '
  • eigen2: ' `svn info $EIGENDIR | grep Revision` '
    • '\ + '
  • eigen3: ' `hg identify -i $EIGENDIR` '
    • '\ '
' \ '

' >> $webpagefilename @@ -37,11 +37,11 @@ source mk_mean_script.sh matrix_vector $1 11 50 300 1000 $mode $prefix source mk_mean_script.sh atv $1 11 50 300 1000 $mode $prefix source mk_mean_script.sh matrix_matrix $1 11 100 300 1000 $mode $prefix source mk_mean_script.sh aat $1 11 100 300 1000 $mode $prefix -source mk_mean_script.sh ata $1 11 100 300 1000 $mode $prefix +# source mk_mean_script.sh ata $1 11 100 300 1000 $mode $prefix +source mk_mean_script.sh trmm $1 11 100 300 1000 $mode $prefix source mk_mean_script.sh trisolve_vector $1 11 100 300 1000 $mode $prefix source mk_mean_script.sh trisolve_matrix $1 11 100 300 1000 $mode $prefix source mk_mean_script.sh cholesky $1 11 100 300 1000 $mode $prefix -source mk_mean_script.sh complete_lu_decomp $1 11 100 300 1000 $mode $prefix source mk_mean_script.sh partial_lu_decomp $1 11 100 300 1000 $mode $prefix source mk_mean_script.sh tridiagonalization $1 11 100 300 1000 $mode $prefix source mk_mean_script.sh hessenberg $1 11 100 300 1000 $mode $prefix @@ -49,6 +49,7 @@ source mk_mean_script.sh symv $1 11 50 300 1000 $mode $prefix source mk_mean_script.sh syr2 $1 11 50 300 1000 $mode $prefix source mk_mean_script.sh ger $1 11 50 300 1000 $mode $prefix source mk_mean_script.sh rot $1 11 2500 100000 250000 $mode $prefix +source mk_mean_script.sh complete_lu_decomp $1 11 100 300 1000 $mode $prefix fi diff --git a/gtsam/3rdparty/Eigen/bench/btl/data/perlib_plot_settings.txt b/gtsam/3rdparty/Eigen/bench/btl/data/perlib_plot_settings.txt index 82b09ce26..6844bab28 100644 --- a/gtsam/3rdparty/Eigen/bench/btl/data/perlib_plot_settings.txt +++ b/gtsam/3rdparty/Eigen/bench/btl/data/perlib_plot_settings.txt @@ -1,10 +1,12 @@ eigen3 ; with lines lw 4 lt 1 lc rgbcolor "black" +eigen2 ; with lines lw 3 lt 1 lc rgbcolor "#999999" +EigenBLAS ; with lines lw 3 lt 3 lc rgbcolor "#999999" eigen3_novec ; with lines lw 2 lt 1 lc rgbcolor "#999999" eigen3_nogccvec ; with lines lw 2 lt 2 lc rgbcolor "#991010" -INTEL_MKL ; with lines lw 3 lt 2 lc rgbcolor "#00b7ff" -ATLAS ; with lines lw 3 lt 1 lc rgbcolor "#52e657" +INTEL_MKL ; with lines lw 3 lt 1 lc rgbcolor "#ff0000" +ATLAS ; with lines lw 3 lt 1 lc rgbcolor "#008000" gmm ; with lines lw 3 lt 1 lc rgbcolor "#0000ff" -ublas ; with lines lw 3 lt 1 lc rgbcolor "#ff0000" +ublas ; with lines lw 3 lt 1 lc rgbcolor "#00b7ff" mtl4 ; with lines lw 3 lt 1 lc rgbcolor "#d18847" blitz ; with lines lw 3 lt 1 lc rgbcolor "#ff00ff" F77 ; with lines lw 3 lt 3 lc rgbcolor "#e6e64c" diff --git a/gtsam/3rdparty/Eigen/bench/btl/libs/C_BLAS/CMakeLists.txt b/gtsam/3rdparty/Eigen/bench/btl/libs/BLAS/CMakeLists.txt similarity index 69% rename from gtsam/3rdparty/Eigen/bench/btl/libs/C_BLAS/CMakeLists.txt rename to gtsam/3rdparty/Eigen/bench/btl/libs/BLAS/CMakeLists.txt index 59065cb9b..de42fe047 100644 --- a/gtsam/3rdparty/Eigen/bench/btl/libs/C_BLAS/CMakeLists.txt +++ b/gtsam/3rdparty/Eigen/bench/btl/libs/BLAS/CMakeLists.txt @@ -1,7 +1,6 @@ find_package(ATLAS) if (ATLAS_FOUND) - include_directories(${PROJECT_SOURCE_DIR}/libs/f77) btl_add_bench(btl_atlas main.cpp) if(BUILD_btl_atlas) target_link_libraries(btl_atlas ${ATLAS_LIBRARIES}) @@ -11,7 +10,6 @@ endif (ATLAS_FOUND) find_package(MKL) if (MKL_FOUND) - include_directories(${PROJECT_SOURCE_DIR}/libs/f77) btl_add_bench(btl_mkl main.cpp) if(BUILD_btl_mkl) target_link_libraries(btl_mkl ${MKL_LIBRARIES}) @@ -19,33 +17,44 @@ if (MKL_FOUND) endif(BUILD_btl_mkl) endif (MKL_FOUND) -find_package(GOTO) -if (GOTO_FOUND) - include_directories(${PROJECT_SOURCE_DIR}/libs/f77) - btl_add_bench(btl_goto main.cpp) - if(BUILD_btl_goto) - target_link_libraries(btl_goto ${GOTO_LIBRARIES} ) - set_target_properties(btl_goto PROPERTIES COMPILE_FLAGS "-DCBLASNAME=GOTO -DPUREBLAS") - endif(BUILD_btl_goto) -endif (GOTO_FOUND) - find_package(GOTO2) if (GOTO2_FOUND) - include_directories(${PROJECT_SOURCE_DIR}/libs/f77) btl_add_bench(btl_goto2 main.cpp) if(BUILD_btl_goto2) target_link_libraries(btl_goto2 ${GOTO_LIBRARIES} ) - set_target_properties(btl_goto2 PROPERTIES COMPILE_FLAGS "-DCBLASNAME=GOTO2 -DPUREBLAS") + set_target_properties(btl_goto2 PROPERTIES COMPILE_FLAGS "-DCBLASNAME=GOTO2") endif(BUILD_btl_goto2) endif (GOTO2_FOUND) +find_package(GOTO) +if (GOTO_FOUND) + if(GOTO2_FOUND) + btl_add_bench(btl_goto main.cpp OFF) + else() + btl_add_bench(btl_goto main.cpp) + endif() + if(BUILD_btl_goto) + target_link_libraries(btl_goto ${GOTO_LIBRARIES} ) + set_target_properties(btl_goto PROPERTIES COMPILE_FLAGS "-DCBLASNAME=GOTO") + endif(BUILD_btl_goto) +endif (GOTO_FOUND) + find_package(ACML) if (ACML_FOUND) - include_directories(${PROJECT_SOURCE_DIR}/libs/f77) btl_add_bench(btl_acml main.cpp) if(BUILD_btl_acml) target_link_libraries(btl_acml ${ACML_LIBRARIES} ) - set_target_properties(btl_acml PROPERTIES COMPILE_FLAGS "-DCBLASNAME=ACML -DHAS_LAPACK=1 -DPUREBLAS") + set_target_properties(btl_acml PROPERTIES COMPILE_FLAGS "-DCBLASNAME=ACML -DHAS_LAPACK=1") endif(BUILD_btl_acml) endif (ACML_FOUND) + +if(Eigen_SOURCE_DIR AND CMAKE_Fortran_COMPILER_WORKS) + # we are inside Eigen and blas/lapack interface is compilable + include_directories(${Eigen_SOURCE_DIR}) + btl_add_bench(btl_eigenblas main.cpp) + if(BUILD_btl_eigenblas) + target_link_libraries(btl_eigenblas eigen_blas eigen_lapack ) + set_target_properties(btl_eigenblas PROPERTIES COMPILE_FLAGS "-DCBLASNAME=EigenBLAS") + endif() +endif() diff --git a/gtsam/3rdparty/Eigen/bench/btl/libs/C_BLAS/blas.h b/gtsam/3rdparty/Eigen/bench/btl/libs/BLAS/blas.h similarity index 100% rename from gtsam/3rdparty/Eigen/bench/btl/libs/C_BLAS/blas.h rename to gtsam/3rdparty/Eigen/bench/btl/libs/BLAS/blas.h diff --git a/gtsam/3rdparty/Eigen/bench/btl/libs/BLAS/blas_interface.hh b/gtsam/3rdparty/Eigen/bench/btl/libs/BLAS/blas_interface.hh new file mode 100644 index 000000000..651054632 --- /dev/null +++ b/gtsam/3rdparty/Eigen/bench/btl/libs/BLAS/blas_interface.hh @@ -0,0 +1,83 @@ +//===================================================== +// File : blas_interface.hh +// Author : L. Plagne +// Copyright (C) EDF R&D, lun sep 30 14:23:28 CEST 2002 +//===================================================== +// +// This program is free software; you can redistribute it and/or +// modify it under the terms of the GNU General Public License +// as published by the Free Software Foundation; either version 2 +// of the License, or (at your option) any later version. +// +// This program is distributed in the hope that it will be useful, +// but WITHOUT ANY WARRANTY; without even the implied warranty of +// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +// GNU General Public License for more details. +// You should have received a copy of the GNU General Public License +// along with this program; if not, write to the Free Software +// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA. +// +#ifndef blas_PRODUIT_MATRICE_VECTEUR_HH +#define blas_PRODUIT_MATRICE_VECTEUR_HH + +#include +#include +extern "C" +{ +#include "blas.h" + + // Cholesky Factorization +// void spotrf_(const char* uplo, const int* n, float *a, const int* ld, int* info); +// void dpotrf_(const char* uplo, const int* n, double *a, const int* ld, int* info); + void ssytrd_(char *uplo, const int *n, float *a, const int *lda, float *d, float *e, float *tau, float *work, int *lwork, int *info ); + void dsytrd_(char *uplo, const int *n, double *a, const int *lda, double *d, double *e, double *tau, double *work, int *lwork, int *info ); + void sgehrd_( const int *n, int *ilo, int *ihi, float *a, const int *lda, float *tau, float *work, int *lwork, int *info ); + void dgehrd_( const int *n, int *ilo, int *ihi, double *a, const int *lda, double *tau, double *work, int *lwork, int *info ); + + // LU row pivoting +// void dgetrf_( int *m, int *n, double *a, int *lda, int *ipiv, int *info ); +// void sgetrf_(const int* m, const int* n, float *a, const int* ld, int* ipivot, int* info); + // LU full pivoting + void sgetc2_(const int* n, float *a, const int *lda, int *ipiv, int *jpiv, int*info ); + void dgetc2_(const int* n, double *a, const int *lda, int *ipiv, int *jpiv, int*info ); +#ifdef HAS_LAPACK +#endif +} + +#define MAKE_STRING2(S) #S +#define MAKE_STRING(S) MAKE_STRING2(S) + +#define CAT2(A,B) A##B +#define CAT(A,B) CAT2(A,B) + + +template class blas_interface; + + +static char notrans = 'N'; +static char trans = 'T'; +static char nonunit = 'N'; +static char lower = 'L'; +static char right = 'R'; +static char left = 'L'; +static int intone = 1; + + + +#define SCALAR float +#define SCALAR_PREFIX s +#include "blas_interface_impl.hh" +#undef SCALAR +#undef SCALAR_PREFIX + + +#define SCALAR double +#define SCALAR_PREFIX d +#include "blas_interface_impl.hh" +#undef SCALAR +#undef SCALAR_PREFIX + +#endif + + + diff --git a/gtsam/3rdparty/Eigen/bench/btl/libs/BLAS/blas_interface_impl.hh b/gtsam/3rdparty/Eigen/bench/btl/libs/BLAS/blas_interface_impl.hh new file mode 100644 index 000000000..0e84df038 --- /dev/null +++ b/gtsam/3rdparty/Eigen/bench/btl/libs/BLAS/blas_interface_impl.hh @@ -0,0 +1,151 @@ + +#define BLAS_FUNC(NAME) CAT(CAT(SCALAR_PREFIX,NAME),_) + +template<> class blas_interface : public c_interface_base +{ + +public : + + static SCALAR fone; + static SCALAR fzero; + + static inline std::string name() + { + return MAKE_STRING(CBLASNAME); + } + + static inline void matrix_vector_product(gene_matrix & A, gene_vector & B, gene_vector & X, int N){ + BLAS_FUNC(gemv)(¬rans,&N,&N,&fone,A,&N,B,&intone,&fzero,X,&intone); + } + + static inline void symv(gene_matrix & A, gene_vector & B, gene_vector & X, int N){ + BLAS_FUNC(symv)(&lower, &N,&fone,A,&N,B,&intone,&fzero,X,&intone); + } + + static inline void syr2(gene_matrix & A, gene_vector & B, gene_vector & X, int N){ + BLAS_FUNC(syr2)(&lower,&N,&fone,B,&intone,X,&intone,A,&N); + } + + static inline void ger(gene_matrix & A, gene_vector & X, gene_vector & Y, int N){ + BLAS_FUNC(ger)(&N,&N,&fone,X,&intone,Y,&intone,A,&N); + } + + static inline void rot(gene_vector & A, gene_vector & B, SCALAR c, SCALAR s, int N){ + BLAS_FUNC(rot)(&N,A,&intone,B,&intone,&c,&s); + } + + static inline void atv_product(gene_matrix & A, gene_vector & B, gene_vector & X, int N){ + BLAS_FUNC(gemv)(&trans,&N,&N,&fone,A,&N,B,&intone,&fzero,X,&intone); + } + + static inline void matrix_matrix_product(gene_matrix & A, gene_matrix & B, gene_matrix & X, int N){ + BLAS_FUNC(gemm)(¬rans,¬rans,&N,&N,&N,&fone,A,&N,B,&N,&fzero,X,&N); + } + + static inline void transposed_matrix_matrix_product(gene_matrix & A, gene_matrix & B, gene_matrix & X, int N){ + BLAS_FUNC(gemm)(¬rans,¬rans,&N,&N,&N,&fone,A,&N,B,&N,&fzero,X,&N); + } + +// static inline void ata_product(gene_matrix & A, gene_matrix & X, int N){ +// ssyrk_(&lower,&trans,&N,&N,&fone,A,&N,&fzero,X,&N); +// } + + static inline void aat_product(gene_matrix & A, gene_matrix & X, int N){ + BLAS_FUNC(syrk)(&lower,¬rans,&N,&N,&fone,A,&N,&fzero,X,&N); + } + + static inline void axpy(SCALAR coef, const gene_vector & X, gene_vector & Y, int N){ + BLAS_FUNC(axpy)(&N,&coef,X,&intone,Y,&intone); + } + + static inline void axpby(SCALAR a, const gene_vector & X, SCALAR b, gene_vector & Y, int N){ + BLAS_FUNC(scal)(&N,&b,Y,&intone); + BLAS_FUNC(axpy)(&N,&a,X,&intone,Y,&intone); + } + + static inline void cholesky(const gene_matrix & X, gene_matrix & C, int N){ + int N2 = N*N; + BLAS_FUNC(copy)(&N2, X, &intone, C, &intone); + char uplo = 'L'; + int info = 0; + BLAS_FUNC(potrf)(&uplo, &N, C, &N, &info); + if(info!=0) std::cerr << "potrf_ error " << info << "\n"; + } + + static inline void partial_lu_decomp(const gene_matrix & X, gene_matrix & C, int N){ + int N2 = N*N; + BLAS_FUNC(copy)(&N2, X, &intone, C, &intone); + char uplo = 'L'; + int info = 0; + int * ipiv = (int*)alloca(sizeof(int)*N); + BLAS_FUNC(getrf)(&N, &N, C, &N, ipiv, &info); + if(info!=0) std::cerr << "getrf_ error " << info << "\n"; + } + + static inline void trisolve_lower(const gene_matrix & L, const gene_vector& B, gene_vector & X, int N){ + BLAS_FUNC(copy)(&N, B, &intone, X, &intone); + BLAS_FUNC(trsv)(&lower, ¬rans, &nonunit, &N, L, &N, X, &intone); + } + + static inline void trisolve_lower_matrix(const gene_matrix & L, const gene_matrix& B, gene_matrix & X, int N){ + BLAS_FUNC(copy)(&N, B, &intone, X, &intone); + BLAS_FUNC(trsm)(&right, &lower, ¬rans, &nonunit, &N, &N, &fone, L, &N, X, &N); + } + + static inline void trmm(gene_matrix & A, gene_matrix & B, gene_matrix & X, int N){ + BLAS_FUNC(trmm)(&left, &lower, ¬rans,&nonunit, &N,&N,&fone,A,&N,B,&N); + } + + #ifdef HAS_LAPACK + + static inline void lu_decomp(const gene_matrix & X, gene_matrix & C, int N){ + int N2 = N*N; + BLAS_FUNC(copy)(&N2, X, &intone, C, &intone); + char uplo = 'L'; + int info = 0; + int * ipiv = (int*)alloca(sizeof(int)*N); + int * jpiv = (int*)alloca(sizeof(int)*N); + BLAS_FUNC(getc2)(&N, C, &N, ipiv, jpiv, &info); + } + + + + static inline void hessenberg(const gene_matrix & X, gene_matrix & C, int N){ + { + int N2 = N*N; + int inc = 1; + BLAS_FUNC(copy)(&N2, X, &inc, C, &inc); + } + int info = 0; + int ilo = 1; + int ihi = N; + int bsize = 64; + int worksize = N*bsize; + SCALAR* d = new SCALAR[N+worksize]; + BLAS_FUNC(gehrd)(&N, &ilo, &ihi, C, &N, d, d+N, &worksize, &info); + delete[] d; + } + + static inline void tridiagonalization(const gene_matrix & X, gene_matrix & C, int N){ + { + int N2 = N*N; + int inc = 1; + BLAS_FUNC(copy)(&N2, X, &inc, C, &inc); + } + char uplo = 'U'; + int info = 0; + int ilo = 1; + int ihi = N; + int bsize = 64; + int worksize = N*bsize; + SCALAR* d = new SCALAR[3*N+worksize]; + BLAS_FUNC(sytrd)(&uplo, &N, C, &N, d, d+N, d+2*N, d+3*N, &worksize, &info); + delete[] d; + } + + #endif // HAS_LAPACK + +}; + +SCALAR blas_interface::fone = SCALAR(1); +SCALAR blas_interface::fzero = SCALAR(0); diff --git a/gtsam/3rdparty/Eigen/bench/btl/libs/f77/f77_interface_base.hh b/gtsam/3rdparty/Eigen/bench/btl/libs/BLAS/c_interface_base.h similarity index 51% rename from gtsam/3rdparty/Eigen/bench/btl/libs/f77/f77_interface_base.hh rename to gtsam/3rdparty/Eigen/bench/btl/libs/BLAS/c_interface_base.h index ab8a18295..515d8dcfc 100644 --- a/gtsam/3rdparty/Eigen/bench/btl/libs/f77/f77_interface_base.hh +++ b/gtsam/3rdparty/Eigen/bench/btl/libs/BLAS/c_interface_base.h @@ -1,38 +1,21 @@ -//===================================================== -// File : f77_interface_base.hh -// Author : L. Plagne -// Copyright (C) EDF R&D, lun sep 30 14:23:25 CEST 2002 -//===================================================== -// -// This program is free software; you can redistribute it and/or -// modify it under the terms of the GNU General Public License -// as published by the Free Software Foundation; either version 2 -// of the License, or (at your option) any later version. -// -// This program is distributed in the hope that it will be useful, -// but WITHOUT ANY WARRANTY; without even the implied warranty of -// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the -// GNU General Public License for more details. -// You should have received a copy of the GNU General Public License -// along with this program; if not, write to the Free Software -// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA. -// -#ifndef F77_INTERFACE_BASE_HH -#define F77_INTERFACE_BASE_HH + +#ifndef BTL_C_INTERFACE_BASE_H +#define BTL_C_INTERFACE_BASE_H #include "utilities.h" #include -template -class f77_interface_base{ + +template class c_interface_base +{ public: - typedef real real_type ; - typedef std::vector stl_vector; - typedef std::vector stl_matrix; + typedef real real_type; + typedef std::vector stl_vector; + typedef std::vector stl_matrix; - typedef real * gene_matrix; - typedef real * gene_vector; + typedef real* gene_matrix; + typedef real* gene_vector; static void free_matrix(gene_matrix & A, int N){ delete A; @@ -87,5 +70,4 @@ public: }; - #endif diff --git a/gtsam/3rdparty/Eigen/bench/btl/libs/BLAS/main.cpp b/gtsam/3rdparty/Eigen/bench/btl/libs/BLAS/main.cpp new file mode 100644 index 000000000..8347c9f0b --- /dev/null +++ b/gtsam/3rdparty/Eigen/bench/btl/libs/BLAS/main.cpp @@ -0,0 +1,73 @@ +//===================================================== +// File : main.cpp +// Author : L. Plagne +// Copyright (C) EDF R&D, lun sep 30 14:23:28 CEST 2002 +//===================================================== +// +// This program is free software; you can redistribute it and/or +// modify it under the terms of the GNU General Public License +// as published by the Free Software Foundation; either version 2 +// of the License, or (at your option) any later version. +// +// This program is distributed in the hope that it will be useful, +// but WITHOUT ANY WARRANTY; without even the implied warranty of +// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +// GNU General Public License for more details. +// You should have received a copy of the GNU General Public License +// along with this program; if not, write to the Free Software +// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA. +// +#include "utilities.h" +#include "blas_interface.hh" +#include "bench.hh" +#include "basic_actions.hh" + +#include "action_cholesky.hh" +#include "action_lu_decomp.hh" +#include "action_partial_lu.hh" +#include "action_trisolve_matrix.hh" + +#ifdef HAS_LAPACK +#include "action_hessenberg.hh" +#endif + +BTL_MAIN; + +int main() +{ + + bench > >(MIN_AXPY,MAX_AXPY,NB_POINT); + bench > >(MIN_AXPY,MAX_AXPY,NB_POINT); + + bench > >(MIN_MV,MAX_MV,NB_POINT); + bench > >(MIN_MV,MAX_MV,NB_POINT); + bench > >(MIN_MV,MAX_MV,NB_POINT); + bench > >(MIN_MV,MAX_MV,NB_POINT); + + bench > >(MIN_MV,MAX_MV,NB_POINT); + bench > >(MIN_AXPY,MAX_AXPY,NB_POINT); + + bench > >(MIN_MM,MAX_MM,NB_POINT); +// bench > >(MIN_MM,MAX_MM,NB_POINT); + bench > >(MIN_MM,MAX_MM,NB_POINT); + + bench > >(MIN_MM,MAX_MM,NB_POINT); + bench > >(MIN_MM,MAX_MM,NB_POINT); + + bench > >(MIN_MM,MAX_MM,NB_POINT); + + bench > >(MIN_MM,MAX_MM,NB_POINT); + bench > >(MIN_MM,MAX_MM,NB_POINT); + + #ifdef HAS_LAPACK + bench > >(MIN_MM,MAX_MM,NB_POINT); + bench > >(MIN_MM,MAX_MM,NB_POINT); + bench > >(MIN_MM,MAX_MM,NB_POINT); + #endif + + //bench > >(MIN_LU,MAX_LU,NB_POINT); + + return 0; +} + + diff --git a/gtsam/3rdparty/Eigen/bench/btl/libs/C/CMakeLists.txt b/gtsam/3rdparty/Eigen/bench/btl/libs/C/CMakeLists.txt deleted file mode 100644 index 3d4d24cee..000000000 --- a/gtsam/3rdparty/Eigen/bench/btl/libs/C/CMakeLists.txt +++ /dev/null @@ -1,3 +0,0 @@ -include_directories(${PROJECT_SOURCE_DIR}/libs/f77) -btl_add_bench(btl_C main.cpp OFF) -# set_target_properties(btl_C PROPERTIES COMPILE_FLAGS "-fpeel-loops") \ No newline at end of file diff --git a/gtsam/3rdparty/Eigen/bench/btl/libs/C/C_interface.hh b/gtsam/3rdparty/Eigen/bench/btl/libs/C/C_interface.hh deleted file mode 100755 index d6092517d..000000000 --- a/gtsam/3rdparty/Eigen/bench/btl/libs/C/C_interface.hh +++ /dev/null @@ -1,117 +0,0 @@ -//===================================================== -// File : C_interface.hh -// Author : L. Plagne -// Copyright (C) EDF R&D, lun sep 30 14:23:23 CEST 2002 -//===================================================== -// -// This program is free software; you can redistribute it and/or -// modify it under the terms of the GNU General Public License -// as published by the Free Software Foundation; either version 2 -// of the License, or (at your option) any later version. -// -// This program is distributed in the hope that it will be useful, -// but WITHOUT ANY WARRANTY; without even the implied warranty of -// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the -// GNU General Public License for more details. -// You should have received a copy of the GNU General Public License -// along with this program; if not, write to the Free Software -// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA. -// -#ifndef C_INTERFACE_HH -#define C_INTERFACE_HH - -#include "f77_interface.hh" - -template -class C_interface : public f77_interface_base { - -public : - - typedef typename f77_interface_base::gene_matrix gene_matrix; - typedef typename f77_interface_base::gene_vector gene_vector; - - static inline std::string name() { return "C"; } - - static inline void matrix_vector_product(const gene_matrix & A, const gene_vector & B, gene_vector & X, int N) - { -// for (int i=0;i -// Copyright (C) EDF R&D, lun sep 30 14:23:28 CEST 2002 -//===================================================== -// -// This program is free software; you can redistribute it and/or -// modify it under the terms of the GNU General Public License -// as published by the Free Software Foundation; either version 2 -// of the License, or (at your option) any later version. -// -// This program is distributed in the hope that it will be useful, -// but WITHOUT ANY WARRANTY; without even the implied warranty of -// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the -// GNU General Public License for more details. -// You should have received a copy of the GNU General Public License -// along with this program; if not, write to the Free Software -// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA. -// -#ifndef C_BLAS_PRODUIT_MATRICE_VECTEUR_HH -#define C_BLAS_PRODUIT_MATRICE_VECTEUR_HH - -#include "f77_interface.hh" -#include -extern "C" -{ -#include "cblas.h" - -// #ifdef PUREBLAS -#include "blas.h" -// #endif - -// void sgemm_(const char *transa, const char *transb, const int *m, const int *n, const int *k, -// const float *alpha, const float *a, const int *lda, const float *b, const int *ldb, -// const float *beta, float *c, const int *ldc); -// -// void sgemv_(const char *trans, const int *m, const int *n, const float *alpha, -// const float *a, const int *lda, const float *x, const int *incx, -// const float *beta, float *y, const int *incy); -// -// void ssymv_(const char *trans, const char* uplo, -// const int* N, const float* alpha, const float *A, -// const int* lda, const float *X, const int* incX, -// const float* beta, float *Y, const int* incY); -// -// void sscal_(const int *n, const float *alpha, const float *x, const int *incx); -// -// void saxpy_(const int *n, const float *alpha, const float *x, const int *incx, -// float *y, const int *incy); -// -// void strsv_(const char *uplo, const char *trans, const char *diag, const int *n, -// const float *a, const int *lda, float *x, const int *incx); -// -// void scopy_(const int *n, const float *x, const int *incx, float *y, const int *incy); - - // Cholesky Factorization -// #include "mkl_lapack.h" -// void spotrf_(const char* uplo, const int* n, float *a, const int* ld, int* info); -// void dpotrf_(const char* uplo, const int* n, double *a, const int* ld, int* info); - void ssytrd_(char *uplo, const int *n, float *a, const int *lda, float *d, float *e, float *tau, float *work, int *lwork, int *info ); - void sgehrd_( const int *n, int *ilo, int *ihi, float *a, const int *lda, float *tau, float *work, int *lwork, int *info ); - - // LU row pivoting -// void dgetrf_( int *m, int *n, double *a, int *lda, int *ipiv, int *info ); -// void sgetrf_(const int* m, const int* n, float *a, const int* ld, int* ipivot, int* info); - // LU full pivoting - void sgetc2_(const int* n, float *a, const int *lda, int *ipiv, int *jpiv, int*info ); -#ifdef HAS_LAPACK -#endif -} - -#define MAKE_STRING2(S) #S -#define MAKE_STRING(S) MAKE_STRING2(S) - -template -class C_BLAS_interface : public f77_interface_base -{ -public : - - typedef typename f77_interface_base::gene_matrix gene_matrix; - typedef typename f77_interface_base::gene_vector gene_vector; - - static inline std::string name( void ) - { - return MAKE_STRING(CBLASNAME); - } - - static inline void matrix_vector_product(gene_matrix & A, gene_vector & B, gene_vector & X, int N) - { - cblas_dgemv(CblasColMajor,CblasNoTrans,N,N,1.0,A,N,B,1,0.0,X,1); - } - - static inline void atv_product(gene_matrix & A, gene_vector & B, gene_vector & X, int N) - { - cblas_dgemv(CblasColMajor,CblasTrans,N,N,1.0,A,N,B,1,0.0,X,1); - } - - static inline void symv(gene_matrix & A, gene_vector & B, gene_vector & X, int N) - { - cblas_dsymv(CblasColMajor,CblasLower,CblasTrans,N,N,1.0,A,N,B,1,0.0,X,1); - } - - static inline void matrix_matrix_product(gene_matrix & A, gene_matrix & B, gene_matrix & X, int N){ - cblas_dgemm(CblasColMajor,CblasNoTrans,CblasNoTrans,N,N,N,1.0,A,N,B,N,0.0,X,N); - } - - static inline void transposed_matrix_matrix_product(gene_matrix & A, gene_matrix & B, gene_matrix & X, int N){ - cblas_dgemm(CblasColMajor,CblasTrans,CblasTrans,N,N,N,1.0,A,N,B,N,0.0,X,N); - } - - static inline void ata_product(gene_matrix & A, gene_matrix & X, int N){ - cblas_dgemm(CblasColMajor,CblasTrans,CblasNoTrans,N,N,N,1.0,A,N,A,N,0.0,X,N); - } - - static inline void aat_product(gene_matrix & A, gene_matrix & X, int N){ - cblas_dgemm(CblasColMajor,CblasNoTrans,CblasTrans,N,N,N,1.0,A,N,A,N,0.0,X,N); - } - - static inline void axpy(real coef, const gene_vector & X, gene_vector & Y, int N){ - cblas_daxpy(N,coef,X,1,Y,1); - } - - static inline void axpby(real a, const gene_vector & X, real b, gene_vector & Y, int N){ - cblas_dscal(N,b,Y,1); - cblas_daxpy(N,a,X,1,Y,1); - } - -}; - -static float fone = 1; -static float fzero = 0; -static char notrans = 'N'; -static char trans = 'T'; -static char nonunit = 'N'; -static char lower = 'L'; -static char right = 'R'; -static char left = 'L'; -static int intone = 1; - -template<> -class C_BLAS_interface : public f77_interface_base -{ - -public : - - static inline std::string name( void ) - { - return MAKE_STRING(CBLASNAME); - } - - static inline void matrix_vector_product(gene_matrix & A, gene_vector & B, gene_vector & X, int N){ - #ifdef PUREBLAS - sgemv_(¬rans,&N,&N,&fone,A,&N,B,&intone,&fzero,X,&intone); - #else - cblas_sgemv(CblasColMajor,CblasNoTrans,N,N,1.0,A,N,B,1,0.0,X,1); - #endif - } - - static inline void symv(gene_matrix & A, gene_vector & B, gene_vector & X, int N){ - #ifdef PUREBLAS - ssymv_(&lower, &N,&fone,A,&N,B,&intone,&fzero,X,&intone); - #else - cblas_ssymv(CblasColMajor,CblasLower,N,1.0,A,N,B,1,0.0,X,1); - #endif - } - - static inline void syr2(gene_matrix & A, gene_vector & B, gene_vector & X, int N){ - #ifdef PUREBLAS - ssyr2_(&lower,&N,&fone,B,&intone,X,&intone,A,&N); - #else - cblas_ssyr2(CblasColMajor,CblasLower,N,1.0,B,1,X,1,A,N); - #endif - } - - static inline void ger(gene_matrix & A, gene_vector & X, gene_vector & Y, int N){ - #ifdef PUREBLAS - sger_(&N,&N,&fone,X,&intone,Y,&intone,A,&N); - #else - cblas_sger(CblasColMajor,N,N,1.0,X,1,Y,1,A,N); - #endif - } - - static inline void rot(gene_vector & A, gene_vector & B, float c, float s, int N){ - #ifdef PUREBLAS - srot_(&N,A,&intone,B,&intone,&c,&s); - #else - cblas_srot(N,A,1,B,1,c,s); - #endif - } - - static inline void atv_product(gene_matrix & A, gene_vector & B, gene_vector & X, int N){ - #ifdef PUREBLAS - sgemv_(&trans,&N,&N,&fone,A,&N,B,&intone,&fzero,X,&intone); - #else - cblas_sgemv(CblasColMajor,CblasTrans,N,N,1.0,A,N,B,1,0.0,X,1); - #endif - } - - static inline void matrix_matrix_product(gene_matrix & A, gene_matrix & B, gene_matrix & X, int N){ - #ifdef PUREBLAS - sgemm_(¬rans,¬rans,&N,&N,&N,&fone,A,&N,B,&N,&fzero,X,&N); - #else - cblas_sgemm(CblasColMajor,CblasNoTrans,CblasNoTrans,N,N,N,1.0,A,N,B,N,0.0,X,N); - #endif - } - - static inline void transposed_matrix_matrix_product(gene_matrix & A, gene_matrix & B, gene_matrix & X, int N){ - #ifdef PUREBLAS - sgemm_(¬rans,¬rans,&N,&N,&N,&fone,A,&N,B,&N,&fzero,X,&N); - #else - cblas_sgemm(CblasColMajor,CblasNoTrans,CblasNoTrans,N,N,N,1.0,A,N,B,N,0.0,X,N); - #endif - } - - static inline void ata_product(gene_matrix & A, gene_matrix & X, int N){ - #ifdef PUREBLAS - sgemm_(&trans,¬rans,&N,&N,&N,&fone,A,&N,A,&N,&fzero,X,&N); - #else - cblas_sgemm(CblasColMajor,CblasTrans,CblasNoTrans,N,N,N,1.0,A,N,A,N,0.0,X,N); - #endif - } - - static inline void aat_product(gene_matrix & A, gene_matrix & X, int N){ - #ifdef PUREBLAS - sgemm_(¬rans,&trans,&N,&N,&N,&fone,A,&N,A,&N,&fzero,X,&N); - #else - cblas_sgemm(CblasColMajor,CblasNoTrans,CblasTrans,N,N,N,1.0,A,N,A,N,0.0,X,N); - #endif - } - - static inline void axpy(float coef, const gene_vector & X, gene_vector & Y, int N){ - #ifdef PUREBLAS - saxpy_(&N,&coef,X,&intone,Y,&intone); - #else - cblas_saxpy(N,coef,X,1,Y,1); - #endif - } - - static inline void axpby(float a, const gene_vector & X, float b, gene_vector & Y, int N){ - #ifdef PUREBLAS - sscal_(&N,&b,Y,&intone); - saxpy_(&N,&a,X,&intone,Y,&intone); - #else - cblas_sscal(N,b,Y,1); - cblas_saxpy(N,a,X,1,Y,1); - #endif - } - - static inline void cholesky(const gene_matrix & X, gene_matrix & C, int N){ - int N2 = N*N; - scopy_(&N2, X, &intone, C, &intone); - char uplo = 'L'; - int info = 0; - spotrf_(&uplo, &N, C, &N, &info); - if(info!=0) std::cerr << "spotrf_ error " << info << "\n"; - } - - static inline void partial_lu_decomp(const gene_matrix & X, gene_matrix & C, int N){ - int N2 = N*N; - scopy_(&N2, X, &intone, C, &intone); - char uplo = 'L'; - int info = 0; - int * ipiv = (int*)alloca(sizeof(int)*N); - sgetrf_(&N, &N, C, &N, ipiv, &info); - if(info!=0) std::cerr << "sgetrf_ error " << info << "\n"; - } - - #ifdef HAS_LAPACK - - static inline void lu_decomp(const gene_matrix & X, gene_matrix & C, int N){ - int N2 = N*N; - scopy_(&N2, X, &intone, C, &intone); - char uplo = 'L'; - int info = 0; - int * ipiv = (int*)alloca(sizeof(int)*N); - int * jpiv = (int*)alloca(sizeof(int)*N); - sgetc2_(&N, C, &N, ipiv, jpiv, &info); - } - - - - static inline void hessenberg(const gene_matrix & X, gene_matrix & C, int N){ -#ifdef PUREBLAS - { - int N2 = N*N; - int inc = 1; - scopy_(&N2, X, &inc, C, &inc); - } -#else - cblas_scopy(N*N, X, 1, C, 1); -#endif - int info = 0; - int ilo = 1; - int ihi = N; - int bsize = 64; - int worksize = N*bsize; - float* d = new float[N+worksize]; - sgehrd_(&N, &ilo, &ihi, C, &N, d, d+N, &worksize, &info); - delete[] d; - } - - static inline void tridiagonalization(const gene_matrix & X, gene_matrix & C, int N){ -#ifdef PUREBLAS - { - int N2 = N*N; - int inc = 1; - scopy_(&N2, X, &inc, C, &inc); - } -#else - cblas_scopy(N*N, X, 1, C, 1); -#endif - char uplo = 'U'; - int info = 0; - int ilo = 1; - int ihi = N; - int bsize = 64; - int worksize = N*bsize; - float* d = new float[3*N+worksize]; - ssytrd_(&uplo, &N, C, &N, d, d+N, d+2*N, d+3*N, &worksize, &info); - delete[] d; - } - #endif - - static inline void trisolve_lower(const gene_matrix & L, const gene_vector& B, gene_vector & X, int N){ - #ifdef PUREBLAS - scopy_(&N, B, &intone, X, &intone); - strsv_(&lower, ¬rans, &nonunit, &N, L, &N, X, &intone); - #else - cblas_scopy(N, B, 1, X, 1); - cblas_strsv(CblasColMajor, CblasLower, CblasNoTrans, CblasNonUnit, N, L, N, X, 1); - #endif - } - - static inline void trisolve_lower_matrix(const gene_matrix & L, const gene_matrix& B, gene_matrix & X, int N){ - #ifdef PUREBLAS - scopy_(&N, B, &intone, X, &intone); - strsm_(&right, &lower, ¬rans, &nonunit, &N, &N, &fone, L, &N, X, &N); - #else - cblas_scopy(N, B, 1, X, 1); - cblas_strsm(CblasColMajor, CblasRight, CblasLower, CblasNoTrans, CblasNonUnit, N, N, 1, L, N, X, N); - #endif - } - - static inline void trmm(gene_matrix & A, gene_matrix & B, gene_matrix & X, int N){ - #ifdef PUREBLAS - strmm_(&left, &lower, ¬rans,&nonunit, &N,&N,&fone,A,&N,B,&N); - #else - cblas_strmm(CblasColMajor, CblasLeft, CblasLower, CblasNoTrans,CblasNonUnit, N,N,1,A,N,B,N); - #endif - } - -}; - - -#endif - - - diff --git a/gtsam/3rdparty/Eigen/bench/btl/libs/C_BLAS/cblas.h b/gtsam/3rdparty/Eigen/bench/btl/libs/C_BLAS/cblas.h deleted file mode 100644 index 4087ffb92..000000000 --- a/gtsam/3rdparty/Eigen/bench/btl/libs/C_BLAS/cblas.h +++ /dev/null @@ -1,596 +0,0 @@ -#ifndef CBLAS_H - -#ifndef CBLAS_ENUM_DEFINED_H - #define CBLAS_ENUM_DEFINED_H - enum CBLAS_ORDER {CblasRowMajor=101, CblasColMajor=102 }; - enum CBLAS_TRANSPOSE {CblasNoTrans=111, CblasTrans=112, CblasConjTrans=113, - AtlasConj=114}; - enum CBLAS_UPLO {CblasUpper=121, CblasLower=122}; - enum CBLAS_DIAG {CblasNonUnit=131, CblasUnit=132}; - enum CBLAS_SIDE {CblasLeft=141, CblasRight=142}; -#endif - -#ifndef CBLAS_ENUM_ONLY -#define CBLAS_H -#define CBLAS_INDEX int - -int cblas_errprn(int ierr, int info, char *form, ...); - -/* - * =========================================================================== - * Prototypes for level 1 BLAS functions (complex are recast as routines) - * =========================================================================== - */ -float cblas_sdsdot(const int N, const float alpha, const float *X, - const int incX, const float *Y, const int incY); -double cblas_dsdot(const int N, const float *X, const int incX, const float *Y, - const int incY); -float cblas_sdot(const int N, const float *X, const int incX, - const float *Y, const int incY); -double cblas_ddot(const int N, const double *X, const int incX, - const double *Y, const int incY); -/* - * Functions having prefixes Z and C only - */ -void cblas_cdotu_sub(const int N, const void *X, const int incX, - const void *Y, const int incY, void *dotu); -void cblas_cdotc_sub(const int N, const void *X, const int incX, - const void *Y, const int incY, void *dotc); - -void cblas_zdotu_sub(const int N, const void *X, const int incX, - const void *Y, const int incY, void *dotu); -void cblas_zdotc_sub(const int N, const void *X, const int incX, - const void *Y, const int incY, void *dotc); - - -/* - * Functions having prefixes S D SC DZ - */ -float cblas_snrm2(const int N, const float *X, const int incX); -float cblas_sasum(const int N, const float *X, const int incX); - -double cblas_dnrm2(const int N, const double *X, const int incX); -double cblas_dasum(const int N, const double *X, const int incX); - -float cblas_scnrm2(const int N, const void *X, const int incX); -float cblas_scasum(const int N, const void *X, const int incX); - -double cblas_dznrm2(const int N, const void *X, const int incX); -double cblas_dzasum(const int N, const void *X, const int incX); - - -/* - * Functions having standard 4 prefixes (S D C Z) - */ -CBLAS_INDEX cblas_isamax(const int N, const float *X, const int incX); -CBLAS_INDEX cblas_idamax(const int N, const double *X, const int incX); -CBLAS_INDEX cblas_icamax(const int N, const void *X, const int incX); -CBLAS_INDEX cblas_izamax(const int N, const void *X, const int incX); - -/* - * =========================================================================== - * Prototypes for level 1 BLAS routines - * =========================================================================== - */ - -/* - * Routines with standard 4 prefixes (s, d, c, z) - */ -void cblas_sswap(const int N, float *X, const int incX, - float *Y, const int incY); -void cblas_scopy(const int N, const float *X, const int incX, - float *Y, const int incY); -void cblas_saxpy(const int N, const float alpha, const float *X, - const int incX, float *Y, const int incY); -void catlas_saxpby(const int N, const float alpha, const float *X, - const int incX, const float beta, float *Y, const int incY); -void catlas_sset - (const int N, const float alpha, float *X, const int incX); - -void cblas_dswap(const int N, double *X, const int incX, - double *Y, const int incY); -void cblas_dcopy(const int N, const double *X, const int incX, - double *Y, const int incY); -void cblas_daxpy(const int N, const double alpha, const double *X, - const int incX, double *Y, const int incY); -void catlas_daxpby(const int N, const double alpha, const double *X, - const int incX, const double beta, double *Y, const int incY); -void catlas_dset - (const int N, const double alpha, double *X, const int incX); - -void cblas_cswap(const int N, void *X, const int incX, - void *Y, const int incY); -void cblas_ccopy(const int N, const void *X, const int incX, - void *Y, const int incY); -void cblas_caxpy(const int N, const void *alpha, const void *X, - const int incX, void *Y, const int incY); -void catlas_caxpby(const int N, const void *alpha, const void *X, - const int incX, const void *beta, void *Y, const int incY); -void catlas_cset - (const int N, const void *alpha, void *X, const int incX); - -void cblas_zswap(const int N, void *X, const int incX, - void *Y, const int incY); -void cblas_zcopy(const int N, const void *X, const int incX, - void *Y, const int incY); -void cblas_zaxpy(const int N, const void *alpha, const void *X, - const int incX, void *Y, const int incY); -void catlas_zaxpby(const int N, const void *alpha, const void *X, - const int incX, const void *beta, void *Y, const int incY); -void catlas_zset - (const int N, const void *alpha, void *X, const int incX); - - -/* - * Routines with S and D prefix only - */ -void cblas_srotg(float *a, float *b, float *c, float *s); -void cblas_srotmg(float *d1, float *d2, float *b1, const float b2, float *P); -void cblas_srot(const int N, float *X, const int incX, - float *Y, const int incY, const float c, const float s); -void cblas_srotm(const int N, float *X, const int incX, - float *Y, const int incY, const float *P); - -void cblas_drotg(double *a, double *b, double *c, double *s); -void cblas_drotmg(double *d1, double *d2, double *b1, const double b2, double *P); -void cblas_drot(const int N, double *X, const int incX, - double *Y, const int incY, const double c, const double s); -void cblas_drotm(const int N, double *X, const int incX, - double *Y, const int incY, const double *P); - - -/* - * Routines with S D C Z CS and ZD prefixes - */ -void cblas_sscal(const int N, const float alpha, float *X, const int incX); -void cblas_dscal(const int N, const double alpha, double *X, const int incX); -void cblas_cscal(const int N, const void *alpha, void *X, const int incX); -void cblas_zscal(const int N, const void *alpha, void *X, const int incX); -void cblas_csscal(const int N, const float alpha, void *X, const int incX); -void cblas_zdscal(const int N, const double alpha, void *X, const int incX); - -/* - * Extra reference routines provided by ATLAS, but not mandated by the standard - */ -void cblas_crotg(void *a, void *b, void *c, void *s); -void cblas_zrotg(void *a, void *b, void *c, void *s); -void cblas_csrot(const int N, void *X, const int incX, void *Y, const int incY, - const float c, const float s); -void cblas_zdrot(const int N, void *X, const int incX, void *Y, const int incY, - const double c, const double s); - -/* - * =========================================================================== - * Prototypes for level 2 BLAS - * =========================================================================== - */ - -/* - * Routines with standard 4 prefixes (S, D, C, Z) - */ -void cblas_sgemv(const enum CBLAS_ORDER Order, - const enum CBLAS_TRANSPOSE TransA, const int M, const int N, - const float alpha, const float *A, const int lda, - const float *X, const int incX, const float beta, - float *Y, const int incY); -void cblas_sgbmv(const enum CBLAS_ORDER Order, - const enum CBLAS_TRANSPOSE TransA, const int M, const int N, - const int KL, const int KU, const float alpha, - const float *A, const int lda, const float *X, - const int incX, const float beta, float *Y, const int incY); -void cblas_strmv(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, - const int N, const float *A, const int lda, - float *X, const int incX); -void cblas_stbmv(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, - const int N, const int K, const float *A, const int lda, - float *X, const int incX); -void cblas_stpmv(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, - const int N, const float *Ap, float *X, const int incX); -void cblas_strsv(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, - const int N, const float *A, const int lda, float *X, - const int incX); -void cblas_stbsv(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, - const int N, const int K, const float *A, const int lda, - float *X, const int incX); -void cblas_stpsv(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, - const int N, const float *Ap, float *X, const int incX); - -void cblas_dgemv(const enum CBLAS_ORDER Order, - const enum CBLAS_TRANSPOSE TransA, const int M, const int N, - const double alpha, const double *A, const int lda, - const double *X, const int incX, const double beta, - double *Y, const int incY); -void cblas_dgbmv(const enum CBLAS_ORDER Order, - const enum CBLAS_TRANSPOSE TransA, const int M, const int N, - const int KL, const int KU, const double alpha, - const double *A, const int lda, const double *X, - const int incX, const double beta, double *Y, const int incY); -void cblas_dtrmv(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, - const int N, const double *A, const int lda, - double *X, const int incX); -void cblas_dtbmv(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, - const int N, const int K, const double *A, const int lda, - double *X, const int incX); -void cblas_dtpmv(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, - const int N, const double *Ap, double *X, const int incX); -void cblas_dtrsv(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, - const int N, const double *A, const int lda, double *X, - const int incX); -void cblas_dtbsv(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, - const int N, const int K, const double *A, const int lda, - double *X, const int incX); -void cblas_dtpsv(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, - const int N, const double *Ap, double *X, const int incX); - -void cblas_cgemv(const enum CBLAS_ORDER Order, - const enum CBLAS_TRANSPOSE TransA, const int M, const int N, - const void *alpha, const void *A, const int lda, - const void *X, const int incX, const void *beta, - void *Y, const int incY); -void cblas_cgbmv(const enum CBLAS_ORDER Order, - const enum CBLAS_TRANSPOSE TransA, const int M, const int N, - const int KL, const int KU, const void *alpha, - const void *A, const int lda, const void *X, - const int incX, const void *beta, void *Y, const int incY); -void cblas_ctrmv(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, - const int N, const void *A, const int lda, - void *X, const int incX); -void cblas_ctbmv(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, - const int N, const int K, const void *A, const int lda, - void *X, const int incX); -void cblas_ctpmv(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, - const int N, const void *Ap, void *X, const int incX); -void cblas_ctrsv(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, - const int N, const void *A, const int lda, void *X, - const int incX); -void cblas_ctbsv(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, - const int N, const int K, const void *A, const int lda, - void *X, const int incX); -void cblas_ctpsv(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, - const int N, const void *Ap, void *X, const int incX); - -void cblas_zgemv(const enum CBLAS_ORDER Order, - const enum CBLAS_TRANSPOSE TransA, const int M, const int N, - const void *alpha, const void *A, const int lda, - const void *X, const int incX, const void *beta, - void *Y, const int incY); -void cblas_zgbmv(const enum CBLAS_ORDER Order, - const enum CBLAS_TRANSPOSE TransA, const int M, const int N, - const int KL, const int KU, const void *alpha, - const void *A, const int lda, const void *X, - const int incX, const void *beta, void *Y, const int incY); -void cblas_ztrmv(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, - const int N, const void *A, const int lda, - void *X, const int incX); -void cblas_ztbmv(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, - const int N, const int K, const void *A, const int lda, - void *X, const int incX); -void cblas_ztpmv(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, - const int N, const void *Ap, void *X, const int incX); -void cblas_ztrsv(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, - const int N, const void *A, const int lda, void *X, - const int incX); -void cblas_ztbsv(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, - const int N, const int K, const void *A, const int lda, - void *X, const int incX); -void cblas_ztpsv(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, - const int N, const void *Ap, void *X, const int incX); - - -/* - * Routines with S and D prefixes only - */ -void cblas_ssymv(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const int N, const float alpha, const float *A, - const int lda, const float *X, const int incX, - const float beta, float *Y, const int incY); -void cblas_ssbmv(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const int N, const int K, const float alpha, const float *A, - const int lda, const float *X, const int incX, - const float beta, float *Y, const int incY); -void cblas_sspmv(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const int N, const float alpha, const float *Ap, - const float *X, const int incX, - const float beta, float *Y, const int incY); -void cblas_sger(const enum CBLAS_ORDER Order, const int M, const int N, - const float alpha, const float *X, const int incX, - const float *Y, const int incY, float *A, const int lda); -void cblas_ssyr(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const int N, const float alpha, const float *X, - const int incX, float *A, const int lda); -void cblas_sspr(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const int N, const float alpha, const float *X, - const int incX, float *Ap); -void cblas_ssyr2(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const int N, const float alpha, const float *X, - const int incX, const float *Y, const int incY, float *A, - const int lda); -void cblas_sspr2(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const int N, const float alpha, const float *X, - const int incX, const float *Y, const int incY, float *A); - -void cblas_dsymv(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const int N, const double alpha, const double *A, - const int lda, const double *X, const int incX, - const double beta, double *Y, const int incY); -void cblas_dsbmv(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const int N, const int K, const double alpha, const double *A, - const int lda, const double *X, const int incX, - const double beta, double *Y, const int incY); -void cblas_dspmv(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const int N, const double alpha, const double *Ap, - const double *X, const int incX, - const double beta, double *Y, const int incY); -void cblas_dger(const enum CBLAS_ORDER Order, const int M, const int N, - const double alpha, const double *X, const int incX, - const double *Y, const int incY, double *A, const int lda); -void cblas_dsyr(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const int N, const double alpha, const double *X, - const int incX, double *A, const int lda); -void cblas_dspr(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const int N, const double alpha, const double *X, - const int incX, double *Ap); -void cblas_dsyr2(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const int N, const double alpha, const double *X, - const int incX, const double *Y, const int incY, double *A, - const int lda); -void cblas_dspr2(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const int N, const double alpha, const double *X, - const int incX, const double *Y, const int incY, double *A); - - -/* - * Routines with C and Z prefixes only - */ -void cblas_chemv(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const int N, const void *alpha, const void *A, - const int lda, const void *X, const int incX, - const void *beta, void *Y, const int incY); -void cblas_chbmv(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const int N, const int K, const void *alpha, const void *A, - const int lda, const void *X, const int incX, - const void *beta, void *Y, const int incY); -void cblas_chpmv(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const int N, const void *alpha, const void *Ap, - const void *X, const int incX, - const void *beta, void *Y, const int incY); -void cblas_cgeru(const enum CBLAS_ORDER Order, const int M, const int N, - const void *alpha, const void *X, const int incX, - const void *Y, const int incY, void *A, const int lda); -void cblas_cgerc(const enum CBLAS_ORDER Order, const int M, const int N, - const void *alpha, const void *X, const int incX, - const void *Y, const int incY, void *A, const int lda); -void cblas_cher(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const int N, const float alpha, const void *X, const int incX, - void *A, const int lda); -void cblas_chpr(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const int N, const float alpha, const void *X, - const int incX, void *A); -void cblas_cher2(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, const int N, - const void *alpha, const void *X, const int incX, - const void *Y, const int incY, void *A, const int lda); -void cblas_chpr2(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, const int N, - const void *alpha, const void *X, const int incX, - const void *Y, const int incY, void *Ap); - -void cblas_zhemv(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const int N, const void *alpha, const void *A, - const int lda, const void *X, const int incX, - const void *beta, void *Y, const int incY); -void cblas_zhbmv(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const int N, const int K, const void *alpha, const void *A, - const int lda, const void *X, const int incX, - const void *beta, void *Y, const int incY); -void cblas_zhpmv(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const int N, const void *alpha, const void *Ap, - const void *X, const int incX, - const void *beta, void *Y, const int incY); -void cblas_zgeru(const enum CBLAS_ORDER Order, const int M, const int N, - const void *alpha, const void *X, const int incX, - const void *Y, const int incY, void *A, const int lda); -void cblas_zgerc(const enum CBLAS_ORDER Order, const int M, const int N, - const void *alpha, const void *X, const int incX, - const void *Y, const int incY, void *A, const int lda); -void cblas_zher(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const int N, const double alpha, const void *X, const int incX, - void *A, const int lda); -void cblas_zhpr(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const int N, const double alpha, const void *X, - const int incX, void *A); -void cblas_zher2(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, const int N, - const void *alpha, const void *X, const int incX, - const void *Y, const int incY, void *A, const int lda); -void cblas_zhpr2(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, const int N, - const void *alpha, const void *X, const int incX, - const void *Y, const int incY, void *Ap); - -/* - * =========================================================================== - * Prototypes for level 3 BLAS - * =========================================================================== - */ - -/* - * Routines with standard 4 prefixes (S, D, C, Z) - */ -void cblas_sgemm(const enum CBLAS_ORDER Order, const enum CBLAS_TRANSPOSE TransA, - const enum CBLAS_TRANSPOSE TransB, const int M, const int N, - const int K, const float alpha, const float *A, - const int lda, const float *B, const int ldb, - const float beta, float *C, const int ldc); -void cblas_ssymm(const enum CBLAS_ORDER Order, const enum CBLAS_SIDE Side, - const enum CBLAS_UPLO Uplo, const int M, const int N, - const float alpha, const float *A, const int lda, - const float *B, const int ldb, const float beta, - float *C, const int ldc); -void cblas_ssyrk(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE Trans, const int N, const int K, - const float alpha, const float *A, const int lda, - const float beta, float *C, const int ldc); -void cblas_ssyr2k(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE Trans, const int N, const int K, - const float alpha, const float *A, const int lda, - const float *B, const int ldb, const float beta, - float *C, const int ldc); -void cblas_strmm(const enum CBLAS_ORDER Order, const enum CBLAS_SIDE Side, - const enum CBLAS_UPLO Uplo, const enum CBLAS_TRANSPOSE TransA, - const enum CBLAS_DIAG Diag, const int M, const int N, - const float alpha, const float *A, const int lda, - float *B, const int ldb); -void cblas_strsm(const enum CBLAS_ORDER Order, const enum CBLAS_SIDE Side, - const enum CBLAS_UPLO Uplo, const enum CBLAS_TRANSPOSE TransA, - const enum CBLAS_DIAG Diag, const int M, const int N, - const float alpha, const float *A, const int lda, - float *B, const int ldb); - -void cblas_dgemm(const enum CBLAS_ORDER Order, const enum CBLAS_TRANSPOSE TransA, - const enum CBLAS_TRANSPOSE TransB, const int M, const int N, - const int K, const double alpha, const double *A, - const int lda, const double *B, const int ldb, - const double beta, double *C, const int ldc); -void cblas_dsymm(const enum CBLAS_ORDER Order, const enum CBLAS_SIDE Side, - const enum CBLAS_UPLO Uplo, const int M, const int N, - const double alpha, const double *A, const int lda, - const double *B, const int ldb, const double beta, - double *C, const int ldc); -void cblas_dsyrk(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE Trans, const int N, const int K, - const double alpha, const double *A, const int lda, - const double beta, double *C, const int ldc); -void cblas_dsyr2k(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE Trans, const int N, const int K, - const double alpha, const double *A, const int lda, - const double *B, const int ldb, const double beta, - double *C, const int ldc); -void cblas_dtrmm(const enum CBLAS_ORDER Order, const enum CBLAS_SIDE Side, - const enum CBLAS_UPLO Uplo, const enum CBLAS_TRANSPOSE TransA, - const enum CBLAS_DIAG Diag, const int M, const int N, - const double alpha, const double *A, const int lda, - double *B, const int ldb); -void cblas_dtrsm(const enum CBLAS_ORDER Order, const enum CBLAS_SIDE Side, - const enum CBLAS_UPLO Uplo, const enum CBLAS_TRANSPOSE TransA, - const enum CBLAS_DIAG Diag, const int M, const int N, - const double alpha, const double *A, const int lda, - double *B, const int ldb); - -void cblas_cgemm(const enum CBLAS_ORDER Order, const enum CBLAS_TRANSPOSE TransA, - const enum CBLAS_TRANSPOSE TransB, const int M, const int N, - const int K, const void *alpha, const void *A, - const int lda, const void *B, const int ldb, - const void *beta, void *C, const int ldc); -void cblas_csymm(const enum CBLAS_ORDER Order, const enum CBLAS_SIDE Side, - const enum CBLAS_UPLO Uplo, const int M, const int N, - const void *alpha, const void *A, const int lda, - const void *B, const int ldb, const void *beta, - void *C, const int ldc); -void cblas_csyrk(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE Trans, const int N, const int K, - const void *alpha, const void *A, const int lda, - const void *beta, void *C, const int ldc); -void cblas_csyr2k(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE Trans, const int N, const int K, - const void *alpha, const void *A, const int lda, - const void *B, const int ldb, const void *beta, - void *C, const int ldc); -void cblas_ctrmm(const enum CBLAS_ORDER Order, const enum CBLAS_SIDE Side, - const enum CBLAS_UPLO Uplo, const enum CBLAS_TRANSPOSE TransA, - const enum CBLAS_DIAG Diag, const int M, const int N, - const void *alpha, const void *A, const int lda, - void *B, const int ldb); -void cblas_ctrsm(const enum CBLAS_ORDER Order, const enum CBLAS_SIDE Side, - const enum CBLAS_UPLO Uplo, const enum CBLAS_TRANSPOSE TransA, - const enum CBLAS_DIAG Diag, const int M, const int N, - const void *alpha, const void *A, const int lda, - void *B, const int ldb); - -void cblas_zgemm(const enum CBLAS_ORDER Order, const enum CBLAS_TRANSPOSE TransA, - const enum CBLAS_TRANSPOSE TransB, const int M, const int N, - const int K, const void *alpha, const void *A, - const int lda, const void *B, const int ldb, - const void *beta, void *C, const int ldc); -void cblas_zsymm(const enum CBLAS_ORDER Order, const enum CBLAS_SIDE Side, - const enum CBLAS_UPLO Uplo, const int M, const int N, - const void *alpha, const void *A, const int lda, - const void *B, const int ldb, const void *beta, - void *C, const int ldc); -void cblas_zsyrk(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE Trans, const int N, const int K, - const void *alpha, const void *A, const int lda, - const void *beta, void *C, const int ldc); -void cblas_zsyr2k(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE Trans, const int N, const int K, - const void *alpha, const void *A, const int lda, - const void *B, const int ldb, const void *beta, - void *C, const int ldc); -void cblas_ztrmm(const enum CBLAS_ORDER Order, const enum CBLAS_SIDE Side, - const enum CBLAS_UPLO Uplo, const enum CBLAS_TRANSPOSE TransA, - const enum CBLAS_DIAG Diag, const int M, const int N, - const void *alpha, const void *A, const int lda, - void *B, const int ldb); -void cblas_ztrsm(const enum CBLAS_ORDER Order, const enum CBLAS_SIDE Side, - const enum CBLAS_UPLO Uplo, const enum CBLAS_TRANSPOSE TransA, - const enum CBLAS_DIAG Diag, const int M, const int N, - const void *alpha, const void *A, const int lda, - void *B, const int ldb); - - -/* - * Routines with prefixes C and Z only - */ -void cblas_chemm(const enum CBLAS_ORDER Order, const enum CBLAS_SIDE Side, - const enum CBLAS_UPLO Uplo, const int M, const int N, - const void *alpha, const void *A, const int lda, - const void *B, const int ldb, const void *beta, - void *C, const int ldc); -void cblas_cherk(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE Trans, const int N, const int K, - const float alpha, const void *A, const int lda, - const float beta, void *C, const int ldc); -void cblas_cher2k(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE Trans, const int N, const int K, - const void *alpha, const void *A, const int lda, - const void *B, const int ldb, const float beta, - void *C, const int ldc); -void cblas_zhemm(const enum CBLAS_ORDER Order, const enum CBLAS_SIDE Side, - const enum CBLAS_UPLO Uplo, const int M, const int N, - const void *alpha, const void *A, const int lda, - const void *B, const int ldb, const void *beta, - void *C, const int ldc); -void cblas_zherk(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE Trans, const int N, const int K, - const double alpha, const void *A, const int lda, - const double beta, void *C, const int ldc); -void cblas_zher2k(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE Trans, const int N, const int K, - const void *alpha, const void *A, const int lda, - const void *B, const int ldb, const double beta, - void *C, const int ldc); - -int cblas_errprn(int ierr, int info, char *form, ...); - -#endif /* end #ifdef CBLAS_ENUM_ONLY */ -#endif diff --git a/gtsam/3rdparty/Eigen/bench/btl/libs/C_BLAS/main.cpp b/gtsam/3rdparty/Eigen/bench/btl/libs/C_BLAS/main.cpp deleted file mode 100644 index 99f512f9b..000000000 --- a/gtsam/3rdparty/Eigen/bench/btl/libs/C_BLAS/main.cpp +++ /dev/null @@ -1,73 +0,0 @@ -//===================================================== -// File : main.cpp -// Author : L. Plagne -// Copyright (C) EDF R&D, lun sep 30 14:23:28 CEST 2002 -//===================================================== -// -// This program is free software; you can redistribute it and/or -// modify it under the terms of the GNU General Public License -// as published by the Free Software Foundation; either version 2 -// of the License, or (at your option) any later version. -// -// This program is distributed in the hope that it will be useful, -// but WITHOUT ANY WARRANTY; without even the implied warranty of -// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the -// GNU General Public License for more details. -// You should have received a copy of the GNU General Public License -// along with this program; if not, write to the Free Software -// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA. -// -#include "utilities.h" -#include "C_BLAS_interface.hh" -#include "bench.hh" -#include "basic_actions.hh" - -#include "action_cholesky.hh" -#include "action_lu_decomp.hh" -#include "action_partial_lu.hh" -#include "action_trisolve_matrix.hh" - -#ifdef HAS_LAPACK -#include "action_hessenberg.hh" -#endif - -BTL_MAIN; - -int main() -{ - - bench > >(MIN_AXPY,MAX_AXPY,NB_POINT); - bench > >(MIN_AXPY,MAX_AXPY,NB_POINT); - - bench > >(MIN_MV,MAX_MV,NB_POINT); - bench > >(MIN_MV,MAX_MV,NB_POINT); - bench > >(MIN_MV,MAX_MV,NB_POINT); - bench > >(MIN_MV,MAX_MV,NB_POINT); - - bench > >(MIN_MV,MAX_MV,NB_POINT); - bench > >(MIN_AXPY,MAX_AXPY,NB_POINT); - - bench > >(MIN_MM,MAX_MM,NB_POINT); - bench > >(MIN_MM,MAX_MM,NB_POINT); - bench > >(MIN_MM,MAX_MM,NB_POINT); - - bench > >(MIN_MM,MAX_MM,NB_POINT); - bench > >(MIN_MM,MAX_MM,NB_POINT); - - bench > >(MIN_MM,MAX_MM,NB_POINT); - - bench > >(MIN_MM,MAX_MM,NB_POINT); - bench > >(MIN_MM,MAX_MM,NB_POINT); - - #ifdef HAS_LAPACK - bench > >(MIN_MM,MAX_MM,NB_POINT); - bench > >(MIN_MM,MAX_MM,NB_POINT); - bench > >(MIN_MM,MAX_MM,NB_POINT); - #endif - - //bench > >(MIN_LU,MAX_LU,NB_POINT); - - return 0; -} - - diff --git a/gtsam/3rdparty/Eigen/bench/btl/libs/STL/STL_interface.hh b/gtsam/3rdparty/Eigen/bench/btl/libs/STL/STL_interface.hh index 0b73382f3..93e76bd55 100644 --- a/gtsam/3rdparty/Eigen/bench/btl/libs/STL/STL_interface.hh +++ b/gtsam/3rdparty/Eigen/bench/btl/libs/STL/STL_interface.hh @@ -78,18 +78,18 @@ public : cible[i][j]=source[i][j]; } - static inline void ata_product(const gene_matrix & A, gene_matrix & X, int N) - { - real somme; - for (int j=0;j=j) + { + for (int k=0;k -// Copyright (C) EDF R&D, lun sep 30 14:23:24 CEST 2002 -//===================================================== -// -// This program is free software; you can redistribute it and/or -// modify it under the terms of the GNU General Public License -// as published by the Free Software Foundation; either version 2 -// of the License, or (at your option) any later version. -// -// This program is distributed in the hope that it will be useful, -// but WITHOUT ANY WARRANTY; without even the implied warranty of -// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the -// GNU General Public License for more details. -// You should have received a copy of the GNU General Public License -// along with this program; if not, write to the Free Software -// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA. -// -#ifndef STL_ALGO_INTERFACE_HH -#define STL_ALGO_INTERFACE_HH -#include -#include -#include -#include -#include "utilities.h" - - -template -class STL_algo_interface{ - -public : - - typedef real real_type ; - - typedef std::vector stl_vector; - typedef std::vector stl_matrix; - - typedef stl_matrix gene_matrix; - - typedef stl_vector gene_vector; - - static inline std::string name( void ) - { - return "STL_algo"; - } - - static void free_matrix(gene_matrix & A, int N){} - - static void free_vector(gene_vector & B){} - - static inline void matrix_from_stl(gene_matrix & A, stl_matrix & A_stl){ - A=A_stl ; - } - - static inline void vector_from_stl(gene_vector & B, stl_vector & B_stl){ - B=B_stl ; - } - - static inline void vector_to_stl(gene_vector & B, stl_vector & B_stl){ - B_stl=B ; - } - - static inline void matrix_to_stl(gene_matrix & A, stl_matrix & A_stl){ - A_stl=A ; - } - - static inline void copy_vector(const gene_vector & source, gene_vector & cible, int N){ - for (int i=0;i -// Copyright (C) EDF R&D, lun sep 30 14:23:25 CEST 2002 +// Copyright (C) 2008 Gael Guennebaud //===================================================== // // This program is free software; you can redistribute it and/or @@ -18,28 +16,29 @@ // Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA. // #include "utilities.h" -#include "f77_interface.hh" -#include "bench.hh" +#include "eigen3_interface.hh" +#include "static/bench_static.hh" #include "action_matrix_vector_product.hh" #include "action_matrix_matrix_product.hh" #include "action_axpy.hh" #include "action_lu_solve.hh" #include "action_ata_product.hh" #include "action_aat_product.hh" +#include "action_atv_product.hh" +#include "action_cholesky.hh" +#include "action_trisolve.hh" BTL_MAIN; int main() { - bench > >(MIN_AXPY,MAX_AXPY,NB_POINT); - bench > >(MIN_MV,MAX_MV,NB_POINT); - - bench > >(MIN_MM,MAX_MM,NB_POINT); - - bench > >(MIN_MM,MAX_MM,NB_POINT); - - bench > >(MIN_MM,MAX_MM,NB_POINT); + bench_static(); + bench_static(); + bench_static(); + bench_static(); + bench_static(); + bench_static(); return 0; } diff --git a/gtsam/3rdparty/Eigen/bench/btl/libs/eigen2/eigen2_interface.hh b/gtsam/3rdparty/Eigen/bench/btl/libs/eigen2/eigen2_interface.hh new file mode 100644 index 000000000..47fe58135 --- /dev/null +++ b/gtsam/3rdparty/Eigen/bench/btl/libs/eigen2/eigen2_interface.hh @@ -0,0 +1,168 @@ +//===================================================== +// Copyright (C) 2008 Gael Guennebaud +//===================================================== +// +// This program is free software; you can redistribute it and/or +// modify it under the terms of the GNU General Public License +// as published by the Free Software Foundation; either version 2 +// of the License, or (at your option) any later version. +// +// This program is distributed in the hope that it will be useful, +// but WITHOUT ANY WARRANTY; without even the implied warranty of +// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +// GNU General Public License for more details. +// You should have received a copy of the GNU General Public License +// along with this program; if not, write to the Free Software +// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA. +// +#ifndef EIGEN2_INTERFACE_HH +#define EIGEN2_INTERFACE_HH +// #include +#include +#include +#include +#include +#include +#include "btl.hh" + +using namespace Eigen; + +template +class eigen2_interface +{ + +public : + + enum {IsFixedSize = (SIZE!=Dynamic)}; + + typedef real real_type; + + typedef std::vector stl_vector; + typedef std::vector stl_matrix; + + typedef Eigen::Matrix gene_matrix; + typedef Eigen::Matrix gene_vector; + + static inline std::string name( void ) + { + #if defined(EIGEN_VECTORIZE_SSE) + if (SIZE==Dynamic) return "eigen2"; else return "tiny_eigen2"; + #elif defined(EIGEN_VECTORIZE_ALTIVEC) + if (SIZE==Dynamic) return "eigen2"; else return "tiny_eigen2"; + #else + if (SIZE==Dynamic) return "eigen2_novec"; else return "tiny_eigen2_novec"; + #endif + } + + static void free_matrix(gene_matrix & A, int N) {} + + static void free_vector(gene_vector & B) {} + + static BTL_DONT_INLINE void matrix_from_stl(gene_matrix & A, stl_matrix & A_stl){ + A.resize(A_stl[0].size(), A_stl.size()); + + for (int j=0; j().solveTriangular(B); + } + + static inline void trisolve_lower_matrix(const gene_matrix & L, const gene_matrix& B, gene_matrix& X, int N){ + X = L.template marked().solveTriangular(B); + } + + static inline void cholesky(const gene_matrix & X, gene_matrix & C, int N){ + C = X.llt().matrixL(); +// C = X; +// Cholesky::computeInPlace(C); +// Cholesky::computeInPlaceBlock(C); + } + + static inline void lu_decomp(const gene_matrix & X, gene_matrix & C, int N){ + C = X.lu().matrixLU(); +// C = X.inverse(); + } + + static inline void tridiagonalization(const gene_matrix & X, gene_matrix & C, int N){ + C = Tridiagonalization(X).packedMatrix(); + } + + static inline void hessenberg(const gene_matrix & X, gene_matrix & C, int N){ + C = HessenbergDecomposition(X).packedMatrix(); + } + + + +}; + +#endif diff --git a/gtsam/3rdparty/Eigen/bench/btl/libs/eigen2/main_adv.cpp b/gtsam/3rdparty/Eigen/bench/btl/libs/eigen2/main_adv.cpp new file mode 100644 index 000000000..fe3368925 --- /dev/null +++ b/gtsam/3rdparty/Eigen/bench/btl/libs/eigen2/main_adv.cpp @@ -0,0 +1,44 @@ +//===================================================== +// Copyright (C) 2008 Gael Guennebaud +//===================================================== +// +// This program is free software; you can redistribute it and/or +// modify it under the terms of the GNU General Public License +// as published by the Free Software Foundation; either version 2 +// of the License, or (at your option) any later version. +// +// This program is distributed in the hope that it will be useful, +// but WITHOUT ANY WARRANTY; without even the implied warranty of +// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +// GNU General Public License for more details. +// You should have received a copy of the GNU General Public License +// along with this program; if not, write to the Free Software +// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA. +// +#include "utilities.h" +#include "eigen2_interface.hh" +#include "bench.hh" +#include "action_trisolve.hh" +#include "action_trisolve_matrix.hh" +#include "action_cholesky.hh" +#include "action_hessenberg.hh" +#include "action_lu_decomp.hh" +// #include "action_partial_lu.hh" + +BTL_MAIN; + +int main() +{ + bench > >(MIN_MM,MAX_MM,NB_POINT); + bench > >(MIN_MM,MAX_MM,NB_POINT); + bench > >(MIN_MM,MAX_MM,NB_POINT); + bench > >(MIN_MM,MAX_MM,NB_POINT); +// bench > >(MIN_MM,MAX_MM,NB_POINT); + + bench > >(MIN_MM,MAX_MM,NB_POINT); + bench > >(MIN_MM,MAX_MM,NB_POINT); + + return 0; +} + + diff --git a/gtsam/3rdparty/Eigen/bench/btl/libs/STL_algo/main.cpp b/gtsam/3rdparty/Eigen/bench/btl/libs/eigen2/main_linear.cpp similarity index 70% rename from gtsam/3rdparty/Eigen/bench/btl/libs/STL_algo/main.cpp rename to gtsam/3rdparty/Eigen/bench/btl/libs/eigen2/main_linear.cpp index 9ce2d947e..c17d16c08 100644 --- a/gtsam/3rdparty/Eigen/bench/btl/libs/STL_algo/main.cpp +++ b/gtsam/3rdparty/Eigen/bench/btl/libs/eigen2/main_linear.cpp @@ -1,7 +1,5 @@ //===================================================== -// File : main.cpp -// Author : L. Plagne -// Copyright (C) EDF R&D, lun sep 30 14:23:23 CEST 2002 +// Copyright (C) 2008 Gael Guennebaud //===================================================== // // This program is free software; you can redistribute it and/or @@ -18,21 +16,18 @@ // Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA. // #include "utilities.h" -#include "STL_algo_interface.hh" +#include "eigen2_interface.hh" #include "bench.hh" -#include "action_atv_product.hh" -#include "action_axpy.hh" +#include "basic_actions.hh" BTL_MAIN; int main() { - - bench > >(MIN_MV,MAX_MV,NB_POINT); - - bench > >(MIN_AXPY,MAX_AXPY,NB_POINT); - + bench > >(MIN_AXPY,MAX_AXPY,NB_POINT); + bench > >(MIN_AXPY,MAX_AXPY,NB_POINT); + return 0; } diff --git a/gtsam/3rdparty/Eigen/bench/btl/libs/f77/test_interface.hh b/gtsam/3rdparty/Eigen/bench/btl/libs/eigen2/main_matmat.cpp similarity index 59% rename from gtsam/3rdparty/Eigen/bench/btl/libs/f77/test_interface.hh rename to gtsam/3rdparty/Eigen/bench/btl/libs/eigen2/main_matmat.cpp index 230c8dbc8..cd9dc9cb0 100644 --- a/gtsam/3rdparty/Eigen/bench/btl/libs/f77/test_interface.hh +++ b/gtsam/3rdparty/Eigen/bench/btl/libs/eigen2/main_matmat.cpp @@ -1,14 +1,12 @@ //===================================================== -// File : test_interface.hh -// Author : L. Plagne -// Copyright (C) EDF R&D, lun sep 30 14:23:25 CEST 2002 +// Copyright (C) 2008 Gael Guennebaud //===================================================== -// +// // This program is free software; you can redistribute it and/or // modify it under the terms of the GNU General Public License // as published by the Free Software Foundation; either version 2 // of the License, or (at your option) any later version. -// +// // This program is distributed in the hope that it will be useful, // but WITHOUT ANY WARRANTY; without even the implied warranty of // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the @@ -16,21 +14,22 @@ // You should have received a copy of the GNU General Public License // along with this program; if not, write to the Free Software // Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA. -// -#ifndef TEST_INTERFACE_HH -#define TEST_INTERFACE_HH - -template< class Interface > -void test_interface( void ){ - - Interface::interface_name(); - - typename Interface::gene_matrix A; - - +// +#include "utilities.h" +#include "eigen2_interface.hh" +#include "bench.hh" +#include "basic_actions.hh" +BTL_MAIN; +int main() +{ + bench > >(MIN_MM,MAX_MM,NB_POINT); +// bench > >(MIN_MM,MAX_MM,NB_POINT); + bench > >(MIN_MM,MAX_MM,NB_POINT); +// bench > >(MIN_MM,MAX_MM,NB_POINT); + return 0; } -#endif + diff --git a/gtsam/3rdparty/Eigen/bench/btl/libs/C/main.cpp b/gtsam/3rdparty/Eigen/bench/btl/libs/eigen2/main_vecmat.cpp similarity index 50% rename from gtsam/3rdparty/Eigen/bench/btl/libs/C/main.cpp rename to gtsam/3rdparty/Eigen/bench/btl/libs/eigen2/main_vecmat.cpp index f0a0e5c65..8b66cd2d9 100644 --- a/gtsam/3rdparty/Eigen/bench/btl/libs/C/main.cpp +++ b/gtsam/3rdparty/Eigen/bench/btl/libs/eigen2/main_vecmat.cpp @@ -1,7 +1,5 @@ //===================================================== -// File : main.cpp -// Author : L. Plagne -// Copyright (C) EDF R&D, lun sep 30 14:23:23 CEST 2002 +// Copyright (C) 2008 Gael Guennebaud //===================================================== // // This program is free software; you can redistribute it and/or @@ -18,29 +16,19 @@ // Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA. // #include "utilities.h" +#include "eigen2_interface.hh" #include "bench.hh" -#include "C_interface.hh" -#include "action_matrix_vector_product.hh" -#include "action_atv_product.hh" -#include "action_matrix_matrix_product.hh" -#include "action_axpy.hh" -#include "action_ata_product.hh" -#include "action_aat_product.hh" -//#include "action_lu_solve.hh" -#include "timers/mixed_perf_analyzer.hh" +#include "basic_actions.hh" BTL_MAIN; int main() { - - bench > >(MIN_MV,MAX_MV,NB_POINT); - bench > >(MIN_MV,MAX_MV,NB_POINT); - bench > >(MIN_MM,MAX_MM,NB_POINT); - bench > >(MIN_MM,MAX_MM,NB_POINT); - bench > >(MIN_MM,MAX_MM,NB_POINT); - bench > >(MIN_AXPY,MAX_AXPY,NB_POINT); - + bench > >(MIN_MV,MAX_MV,NB_POINT); + bench > >(MIN_MV,MAX_MV,NB_POINT); +// bench > >(MIN_MV,MAX_MV,NB_POINT); +// bench > >(MIN_MV,MAX_MV,NB_POINT); +// bench > >(MIN_MV,MAX_MV,NB_POINT); return 0; } diff --git a/gtsam/3rdparty/Eigen/bench/btl/libs/eigen3/CMakeLists.txt b/gtsam/3rdparty/Eigen/bench/btl/libs/eigen3/CMakeLists.txt index 334eb14a8..00cae23d3 100644 --- a/gtsam/3rdparty/Eigen/bench/btl/libs/eigen3/CMakeLists.txt +++ b/gtsam/3rdparty/Eigen/bench/btl/libs/eigen3/CMakeLists.txt @@ -1,5 +1,13 @@ -find_package(Eigen3) + +if((NOT EIGEN3_INCLUDE_DIR) AND Eigen_SOURCE_DIR) + # unless EIGEN3_INCLUDE_DIR is defined, let's use current Eigen version + set(EIGEN3_INCLUDE_DIR ${Eigen_SOURCE_DIR}) + set(EIGEN3_FOUND TRUE) +else() + find_package(Eigen3) +endif() + if (EIGEN3_FOUND) include_directories(${EIGEN3_INCLUDE_DIR}) @@ -28,10 +36,10 @@ if (EIGEN3_FOUND) if(NOT BTL_NOVEC) - btl_add_bench(btl_eigen3_novec_linear main_linear.cpp) - btl_add_bench(btl_eigen3_novec_vecmat main_vecmat.cpp) - btl_add_bench(btl_eigen3_novec_matmat main_matmat.cpp) - btl_add_bench(btl_eigen3_novec_adv main_adv.cpp ) + btl_add_bench(btl_eigen3_novec_linear main_linear.cpp OFF) + btl_add_bench(btl_eigen3_novec_vecmat main_vecmat.cpp OFF) + btl_add_bench(btl_eigen3_novec_matmat main_matmat.cpp OFF) + btl_add_bench(btl_eigen3_novec_adv main_adv.cpp OFF) btl_add_target_property(btl_eigen3_novec_linear COMPILE_FLAGS "-fno-exceptions -DEIGEN_DONT_VECTORIZE -DBTL_PREFIX=eigen3_novec") btl_add_target_property(btl_eigen3_novec_vecmat COMPILE_FLAGS "-fno-exceptions -DEIGEN_DONT_VECTORIZE -DBTL_PREFIX=eigen3_novec") btl_add_target_property(btl_eigen3_novec_matmat COMPILE_FLAGS "-fno-exceptions -DEIGEN_DONT_VECTORIZE -DBTL_PREFIX=eigen3_novec") diff --git a/gtsam/3rdparty/Eigen/bench/btl/libs/eigen3/eigen3_interface.hh b/gtsam/3rdparty/Eigen/bench/btl/libs/eigen3/eigen3_interface.hh index bd5eb4b6b..31bcc1f93 100644 --- a/gtsam/3rdparty/Eigen/bench/btl/libs/eigen3/eigen3_interface.hh +++ b/gtsam/3rdparty/Eigen/bench/btl/libs/eigen3/eigen3_interface.hh @@ -92,12 +92,13 @@ public : X.noalias() = A.transpose()*B.transpose(); } - static inline void ata_product(const gene_matrix & A, gene_matrix & X, int N){ - X.noalias() = A.transpose()*A; - } +// static inline void ata_product(const gene_matrix & A, gene_matrix & X, int N){ +// X.noalias() = A.transpose()*A; +// } static inline void aat_product(const gene_matrix & A, gene_matrix & X, int N){ - X.noalias() = A*A.transpose(); + X.template triangularView().setZero(); + X.template selfadjointView().rankUpdate(A); } static inline void matrix_vector_product(const gene_matrix & A, const gene_vector & B, gene_vector & X, int N){ @@ -194,16 +195,16 @@ public : } static inline void trisolve_lower_matrix(const gene_matrix & L, const gene_matrix& B, gene_matrix& X, int N){ - X = L.template triangularView().solve(B); + X = L.template triangularView().solve(B); } static inline void trmm(const gene_matrix & L, const gene_matrix& B, gene_matrix& X, int N){ - X = L.template triangularView() * B; + X.noalias() = L.template triangularView() * B; } static inline void cholesky(const gene_matrix & X, gene_matrix & C, int N){ C = X; - internal::llt_inplace::blocked(C); + internal::llt_inplace::blocked(C); //C = X.llt().matrixL(); // C = X; // Cholesky::computeInPlace(C); diff --git a/gtsam/3rdparty/Eigen/bench/btl/libs/eigen3/main_matmat.cpp b/gtsam/3rdparty/Eigen/bench/btl/libs/eigen3/main_matmat.cpp index 052810a16..926fa2b01 100644 --- a/gtsam/3rdparty/Eigen/bench/btl/libs/eigen3/main_matmat.cpp +++ b/gtsam/3rdparty/Eigen/bench/btl/libs/eigen3/main_matmat.cpp @@ -25,7 +25,7 @@ BTL_MAIN; int main() { bench > >(MIN_MM,MAX_MM,NB_POINT); - bench > >(MIN_MM,MAX_MM,NB_POINT); +// bench > >(MIN_MM,MAX_MM,NB_POINT); bench > >(MIN_MM,MAX_MM,NB_POINT); bench > >(MIN_MM,MAX_MM,NB_POINT); diff --git a/gtsam/3rdparty/Eigen/bench/btl/libs/f77/CMakeLists.txt b/gtsam/3rdparty/Eigen/bench/btl/libs/f77/CMakeLists.txt deleted file mode 100644 index cecb9160c..000000000 --- a/gtsam/3rdparty/Eigen/bench/btl/libs/f77/CMakeLists.txt +++ /dev/null @@ -1,6 +0,0 @@ -if(CMAKE_MINOR_VERSION GREATER 4) - if(NOT MSVC) - enable_language(Fortran) - endif(NOT MSVC) - btl_add_bench(btl_f77 main.cpp dmxv.f smxv.f dmxm.f smxm.f daxpy.f saxpy.f data.f sata.f daat.f saat.f OFF) -endif(CMAKE_MINOR_VERSION GREATER 4) \ No newline at end of file diff --git a/gtsam/3rdparty/Eigen/bench/btl/libs/f77/daat.f b/gtsam/3rdparty/Eigen/bench/btl/libs/f77/daat.f deleted file mode 100644 index a50329a66..000000000 --- a/gtsam/3rdparty/Eigen/bench/btl/libs/f77/daat.f +++ /dev/null @@ -1,14 +0,0 @@ - SUBROUTINE DAAT(A,X,N) -** -** X = AT * A - REAL*8 A(N,N),X(N,N),R - DO 20 I=1,N - DO 20 J=1,N - R=0. - DO 10 K=1,N - R=R+A(I,K)*A(J,K) - 10 CONTINUE - X(I,J)=R - 20 CONTINUE - RETURN - END diff --git a/gtsam/3rdparty/Eigen/bench/btl/libs/f77/data.f b/gtsam/3rdparty/Eigen/bench/btl/libs/f77/data.f deleted file mode 100644 index 709211ca5..000000000 --- a/gtsam/3rdparty/Eigen/bench/btl/libs/f77/data.f +++ /dev/null @@ -1,14 +0,0 @@ - SUBROUTINE DATA(A,X,N) -** -** X = AT * A - REAL*8 A(N,N),X(N,N),R - DO 20 I=1,N - DO 20 J=1,N - R=0. - DO 10 K=1,N - R=R+A(K,I)*A(K,J) - 10 CONTINUE - X(I,J)=R - 20 CONTINUE - RETURN - END diff --git a/gtsam/3rdparty/Eigen/bench/btl/libs/f77/daxpy.f b/gtsam/3rdparty/Eigen/bench/btl/libs/f77/daxpy.f deleted file mode 100644 index 29514a222..000000000 --- a/gtsam/3rdparty/Eigen/bench/btl/libs/f77/daxpy.f +++ /dev/null @@ -1,18 +0,0 @@ - SUBROUTINE DAXPYF(N,A,X,Y) -** *************************************** -** CALCULE Y = Y + A*X -** *************************************** -*>N NOMBRE D'OPERATIONS A FAIRE -*>A CONSTANTE MULTIPLICATIVE -*>X TABLEAU -*=Y TABLEAU DES RESULTATS -*A R. SANCHEZ ( EARLY WINTER 1987 ) -*V M.F. ROBEAU - REAL*8 X(1),Y(1) - REAL*8 A - DO 10 I=1,N - Y(I)=Y(I)+A*X(I) - 10 CONTINUE - RETURN - END - diff --git a/gtsam/3rdparty/Eigen/bench/btl/libs/f77/dmxm.f b/gtsam/3rdparty/Eigen/bench/btl/libs/f77/dmxm.f deleted file mode 100644 index eb7ef9006..000000000 --- a/gtsam/3rdparty/Eigen/bench/btl/libs/f77/dmxm.f +++ /dev/null @@ -1,32 +0,0 @@ - SUBROUTINE DMXM(A,N,B,M,C,L) -** -** C = A * B -** A ET B MATRICES A(N,M) B(M,L) ==> C(N,L) -** -*>A PREMIERE MATRICE -*>N PREMIERE DIMENSION DE A ET DE C -*>B DEUXIEME MATRICE -*>M DEUXIEME DIMENSION DE A ET PERMIERE DE B -*L DEUXIEME DIMENSION DE B ET DE C -*A R. SANCHEZ ( EARLY WINTER 1987 ) -*V M.F. ROBEAU -*M AM BAUDRON - AVRIL 94 -*: ERREUR DANS L'APPEL A L'UTILITAIRE SGEMM -*: APPEL A L'UTILITAIRE SGEMM DE LA LIBRAIRIE BLAS SUR HP -*M AM BAUDRON - NOVEMBRE 1991 -*: ERREUR ( SOMME SUR LES TERMES PAS FAITE ) -*: APPEL A L'UTILITAIRE SGEMM DE LA LIBRAIRIE BLAS SUR RISC -*M AM BAUDRON - MAI 1993 -*: CHANGEMENT DES %IF LOCAL SUN MIPS SUITE A INTRODUCTION VERSION IBM - REAL*8 A(N,M),B(M,L),C(N,L),R - DO 20 I=1,N - DO 20 J=1,L - R=0. - DO 10 K=1,M - R=R+A(I,K)*B(K,J) - 10 CONTINUE - C(I,J)=R - 20 CONTINUE - RETURN - END diff --git a/gtsam/3rdparty/Eigen/bench/btl/libs/f77/dmxm.f.mfr b/gtsam/3rdparty/Eigen/bench/btl/libs/f77/dmxm.f.mfr deleted file mode 100644 index 82ccac9a5..000000000 --- a/gtsam/3rdparty/Eigen/bench/btl/libs/f77/dmxm.f.mfr +++ /dev/null @@ -1,36 +0,0 @@ - - SUBROUTINE DMXM(A,N,B,M,C,L) -** -** C = A * B -** A ET B MATRICES A(N,M) B(M,L) ==> C(N,L) -** -*>A PREMIERE MATRICE -*>N PREMIERE DIMENSION DE A ET DE C -*>B DEUXIEME MATRICE -*>M DEUXIEME DIMENSION DE A ET PERMIERE DE B -*L DEUXIEME DIMENSION DE B ET DE C -*A R. SANCHEZ ( EARLY WINTER 1987 ) -*V M.F. ROBEAU -*M AM BAUDRON - AVRIL 94 -*: ERREUR DANS L'APPEL A L'UTILITAIRE SGEMM -*: APPEL A L'UTILITAIRE SGEMM DE LA LIBRAIRIE BLAS SUR HP -*M AM BAUDRON - NOVEMBRE 1991 -*: ERREUR ( SOMME SUR LES TERMES PAS FAITE ) -*: APPEL A L'UTILITAIRE SGEMM DE LA LIBRAIRIE BLAS SUR RISC -*M AM BAUDRON - MAI 1993 -*: CHANGEMENT DES %IF LOCAL SUN MIPS SUITE A INTRODUCTION VERSION IBM - REAL*8 A(N,M),B(M,L),C(N,L),R - DO 5 J=1,L - DO 5 I=1,N - C(I,J)=0. - 5 CONTINUE - DO 10 K=1,M - DO 20 J=1,L - R=B(K,J) - DO 20 I=1,N - C(I,J)=C(I,J)+A(I,K)*R - 20 CONTINUE - 10 CONTINUE - RETURN - END diff --git a/gtsam/3rdparty/Eigen/bench/btl/libs/f77/dmxv.f b/gtsam/3rdparty/Eigen/bench/btl/libs/f77/dmxv.f deleted file mode 100644 index bd7e4d550..000000000 --- a/gtsam/3rdparty/Eigen/bench/btl/libs/f77/dmxv.f +++ /dev/null @@ -1,39 +0,0 @@ - SUBROUTINE DMXV(A,N,X,M,R) -C -** -** VERSION DOUBLE PRECISION DE MXV -** R = A * X -** A MATRICE A(N,M) -** R ET X VECTEURS -** -*>A PREMIERE MATRICE -*>N PREMIERE DIMENSION DE A -*>X VECTEUR -*>M DEUXIEME DIMENSION DE A -* -// Copyright (C) EDF R&D, lun sep 30 14:23:24 CEST 2002 -//===================================================== -// -// This program is free software; you can redistribute it and/or -// modify it under the terms of the GNU General Public License -// as published by the Free Software Foundation; either version 2 -// of the License, or (at your option) any later version. -// -// This program is distributed in the hope that it will be useful, -// but WITHOUT ANY WARRANTY; without even the implied warranty of -// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the -// GNU General Public License for more details. -// You should have received a copy of the GNU General Public License -// along with this program; if not, write to the Free Software -// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA. -// -#ifndef F77_INTERFACE_HH -#define F77_INTERFACE_HH -#include "f77_interface_base.hh" -#include - -extern "C" -{ - void dmxv_(double * A, int * N, double * X, int * M, double *R); - void smxv_(float * A, int * N, float * X, int * M, float *R); - - void dmxm_(double * A, int * N, double * B, int * M, double *C, int * K); - void smxm_(float * A, int * N, float * B, int * M, float *C, int * K); - - void data_(double * A, double *X, int * N); - void sata_(float * A, float *X, int * N); - - void daat_(double * A, double *X, int * N); - void saat_(float * A, float *X, int * N); - - void saxpyf_(int * N, float * coef, float * X, float *Y); - void daxpyf_(int * N, double * coef, double * X, double *Y); -} - -template -class f77_interface : public f77_interface_base -{ -public : - - typedef typename f77_interface_base::gene_matrix gene_matrix; - typedef typename f77_interface_base::gene_vector gene_vector; - - static inline std::string name( void ) - { - return "f77"; - } - - static inline void matrix_vector_product(gene_matrix & A, gene_vector & B, gene_vector & X, int N) - { - dmxv_(A,&N,B,&N,X); - } - - static inline void matrix_matrix_product(gene_matrix & A, gene_matrix & B, gene_matrix & X, int N) - { - dmxm_(A,&N,B,&N,X,&N); - } - - static inline void ata_product(gene_matrix & A, gene_matrix & X, int N) - { - data_(A,X,&N); - } - - static inline void aat_product(gene_matrix & A, gene_matrix & X, int N) - { - daat_(A,X,&N); - } - - static inline void axpy(real coef, const gene_vector & X, gene_vector & Y, int N) - { - int one=1; - daxpyf_(&N,&coef,X,Y); - } - - -}; - - -template<> -class f77_interface : public f77_interface_base -{ -public : - - static inline std::string name( void ) - { - return "F77"; - } - - - static inline void matrix_vector_product(gene_matrix & A, gene_vector & B, gene_vector & X, int N) - { - smxv_(A,&N,B,&N,X); - } - - static inline void matrix_matrix_product(gene_matrix & A, gene_matrix & B, gene_matrix & X, int N) - { - smxm_(A,&N,B,&N,X,&N); - } - - static inline void ata_product(gene_matrix & A, gene_matrix & X, int N) - { - sata_(A,X,&N); - } - - static inline void aat_product(gene_matrix & A, gene_matrix & X, int N) - { - saat_(A,X,&N); - } - - - static inline void axpy(float coef, const gene_vector & X, gene_vector & Y, int N) - { - saxpyf_(&N,&coef,X,Y); - } - -}; - - -#endif - - - diff --git a/gtsam/3rdparty/Eigen/bench/btl/libs/f77/saat.f b/gtsam/3rdparty/Eigen/bench/btl/libs/f77/saat.f deleted file mode 100644 index 5d1855d2c..000000000 --- a/gtsam/3rdparty/Eigen/bench/btl/libs/f77/saat.f +++ /dev/null @@ -1,14 +0,0 @@ - SUBROUTINE SAAT(A,X,N) -** -** X = AT * A - REAL*4 A(N,N),X(N,N) - DO 20 I=1,N - DO 20 J=1,N - R=0. - DO 10 K=1,N - R=R+A(I,K)*A(J,K) - 10 CONTINUE - X(I,J)=R - 20 CONTINUE - RETURN - END diff --git a/gtsam/3rdparty/Eigen/bench/btl/libs/f77/sata.f b/gtsam/3rdparty/Eigen/bench/btl/libs/f77/sata.f deleted file mode 100644 index 3ab83d958..000000000 --- a/gtsam/3rdparty/Eigen/bench/btl/libs/f77/sata.f +++ /dev/null @@ -1,14 +0,0 @@ - SUBROUTINE SATA(A,X,N) -** -** X = AT * A - REAL*4 A(N,N),X(N,N) - DO 20 I=1,N - DO 20 J=1,N - R=0. - DO 10 K=1,N - R=R+A(K,I)*A(K,J) - 10 CONTINUE - X(I,J)=R - 20 CONTINUE - RETURN - END diff --git a/gtsam/3rdparty/Eigen/bench/btl/libs/f77/saxpy.f b/gtsam/3rdparty/Eigen/bench/btl/libs/f77/saxpy.f deleted file mode 100644 index d0f74fd70..000000000 --- a/gtsam/3rdparty/Eigen/bench/btl/libs/f77/saxpy.f +++ /dev/null @@ -1,16 +0,0 @@ - SUBROUTINE SAXPYF(N,A,X,Y) -** *************************************** -** CALCULE Y = Y + A*X -** *************************************** -*>N NOMBRE D'OPERATIONS A FAIRE -*>A CONSTANTE MULTIPLICATIVE -*>X TABLEAU -*=Y TABLEAU DES RESULTATS -*A R. SANCHEZ ( EARLY WINTER 1987 ) -*V M.F. ROBEAU - DIMENSION X(1),Y(1) - DO 10 I=1,N - Y(I)=Y(I)+A*X(I) - 10 CONTINUE - RETURN - END diff --git a/gtsam/3rdparty/Eigen/bench/btl/libs/f77/smxm.f b/gtsam/3rdparty/Eigen/bench/btl/libs/f77/smxm.f deleted file mode 100644 index a1e63adca..000000000 --- a/gtsam/3rdparty/Eigen/bench/btl/libs/f77/smxm.f +++ /dev/null @@ -1,32 +0,0 @@ - SUBROUTINE SMXM(A,N,B,M,C,L) -** -** C = A * B -** A ET B MATRICES A(N,M) B(M,L) ==> C(N,L) -** -*>A PREMIERE MATRICE -*>N PREMIERE DIMENSION DE A ET DE C -*>B DEUXIEME MATRICE -*>M DEUXIEME DIMENSION DE A ET PERMIERE DE B -*L DEUXIEME DIMENSION DE B ET DE C -*A R. SANCHEZ ( EARLY WINTER 1987 ) -*V M.F. ROBEAU -*M AM BAUDRON - AVRIL 94 -*: ERREUR DANS L'APPEL A L'UTILITAIRE SGEMM -*: APPEL A L'UTILITAIRE SGEMM DE LA LIBRAIRIE BLAS SUR HP -*M AM BAUDRON - NOVEMBRE 1991 -*: ERREUR ( SOMME SUR LES TERMES PAS FAITE ) -*: APPEL A L'UTILITAIRE SGEMM DE LA LIBRAIRIE BLAS SUR RISC -*M AM BAUDRON - MAI 1993 -*: CHANGEMENT DES %IF LOCAL SUN MIPS SUITE A INTRODUCTION VERSION IBM - DIMENSION A(N,M),B(M,L),C(N,L) - DO 20 I=1,N - DO 20 J=1,L - R=0. - DO 10 K=1,M - R=R+A(I,K)*B(K,J) - 10 CONTINUE - C(I,J)=R - 20 CONTINUE - RETURN - END diff --git a/gtsam/3rdparty/Eigen/bench/btl/libs/f77/smxv.f b/gtsam/3rdparty/Eigen/bench/btl/libs/f77/smxv.f deleted file mode 100644 index d2f7ed24e..000000000 --- a/gtsam/3rdparty/Eigen/bench/btl/libs/f77/smxv.f +++ /dev/null @@ -1,38 +0,0 @@ - SUBROUTINE SMXV(A,N,X,M,R) -C -** -** VERSION DOUBLE PRECISION DE MXV -** R = A * X -** A MATRICE A(N,M) -** R ET X VECTEURS -** -*>A PREMIERE MATRICE -*>N PREMIERE DIMENSION DE A -*>X VECTEUR -*>M DEUXIEME DIMENSION DE A -* ipvt(N); gmm::lu_factor(R, ipvt); diff --git a/gtsam/3rdparty/Eigen/bench/btl/libs/gmm/main.cpp b/gtsam/3rdparty/Eigen/bench/btl/libs/gmm/main.cpp index b1f51edb6..1f0c051eb 100644 --- a/gtsam/3rdparty/Eigen/bench/btl/libs/gmm/main.cpp +++ b/gtsam/3rdparty/Eigen/bench/btl/libs/gmm/main.cpp @@ -20,7 +20,7 @@ #include "bench.hh" #include "basic_actions.hh" #include "action_hessenberg.hh" -#include "action_lu_decomp.hh" +#include "action_partial_lu.hh" BTL_MAIN; @@ -34,13 +34,13 @@ int main() bench > >(MIN_MV,MAX_MV,NB_POINT); bench > >(MIN_MM,MAX_MM,NB_POINT); - bench > >(MIN_MM,MAX_MM,NB_POINT); - bench > >(MIN_MM,MAX_MM,NB_POINT); +// bench > >(MIN_MM,MAX_MM,NB_POINT); +// bench > >(MIN_MM,MAX_MM,NB_POINT); bench > >(MIN_MM,MAX_MM,NB_POINT); //bench > >(MIN_LU,MAX_LU,NB_POINT); - bench > >(MIN_MM,MAX_MM,NB_POINT); + bench > >(MIN_MM,MAX_MM,NB_POINT); bench > >(MIN_MM,MAX_MM,NB_POINT); bench > >(MIN_MM,MAX_MM,NB_POINT); diff --git a/gtsam/3rdparty/Eigen/bench/btl/libs/hand_vec/CMakeLists.txt b/gtsam/3rdparty/Eigen/bench/btl/libs/hand_vec/CMakeLists.txt deleted file mode 100644 index 3fffbfe8a..000000000 --- a/gtsam/3rdparty/Eigen/bench/btl/libs/hand_vec/CMakeLists.txt +++ /dev/null @@ -1,12 +0,0 @@ -find_package(Eigen2) -if (EIGEN2_FOUND) - - include_directories(${EIGEN2_INCLUDE_DIR} ${PROJECT_SOURCE_DIR}/libs/f77) - btl_add_bench(btl_hand_vec main.cpp OFF) - - btl_add_bench(btl_hand_peeling main.cpp OFF) - if (BUILD_btl_hand_peeling) - set_target_properties(btl_hand_peeling PROPERTIES COMPILE_FLAGS "-DPEELING") - endif (BUILD_btl_hand_peeling) - -endif (EIGEN2_FOUND) \ No newline at end of file diff --git a/gtsam/3rdparty/Eigen/bench/btl/libs/hand_vec/hand_vec_interface.hh b/gtsam/3rdparty/Eigen/bench/btl/libs/hand_vec/hand_vec_interface.hh deleted file mode 100755 index 0bb4b64ca..000000000 --- a/gtsam/3rdparty/Eigen/bench/btl/libs/hand_vec/hand_vec_interface.hh +++ /dev/null @@ -1,886 +0,0 @@ -//===================================================== -// File : hand_vec_interface.hh -// Copyright (C) 2008 Gael Guennebaud -//===================================================== -// -// This program is free software; you can redistribute it and/or -// modify it under the terms of the GNU General Public License -// as published by the Free Software Foundation; either version 2 -// of the License, or (at your option) any later version. -// -// This program is distributed in the hope that it will be useful, -// but WITHOUT ANY WARRANTY; without even the implied warranty of -// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the -// GNU General Public License for more details. -// You should have received a copy of the GNU General Public License -// along with this program; if not, write to the Free Software -// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA. -// -#ifndef HAND_VEC_INTERFACE_HH -#define HAND_VEC_INTERFACE_HH - -#include -#include "f77_interface.hh" - -using namespace Eigen; - -template -class hand_vec_interface : public f77_interface_base { - -public : - - typedef typename internal::packet_traits::type Packet; - static const int PacketSize = internal::packet_traits::size; - - typedef typename f77_interface_base::stl_matrix stl_matrix; - typedef typename f77_interface_base::stl_vector stl_vector; - typedef typename f77_interface_base::gene_matrix gene_matrix; - typedef typename f77_interface_base::gene_vector gene_vector; - - static void free_matrix(gene_matrix & A, int N){ - internal::aligned_free(A); - } - - static void free_vector(gene_vector & B){ - internal::aligned_free(B); - } - - static inline void matrix_from_stl(gene_matrix & A, stl_matrix & A_stl){ - int N = A_stl.size(); - A = (real*)internal::aligned_malloc(N*N*sizeof(real)); - for (int j=0;j0) - { -// for (size_t j = 0;j0) - { - bool aligned0 = (iN0 % PacketSize) == 0; - if (aligned0) - for (int j = 0;j0) -// { -// // int aligned0 = (iN0 % PacketSize); -// int aligned1 = (iN1 % PacketSize); -// -// if (aligned1==0) -// { -// for (int j = 0;j0) -// { -// bool aligned0 = (iN0 % PacketSize) == 0; -// if (aligned0) -// for (int j = 0;j0) -// { -// bool aligned0 = (iN0 % PacketSize) == 0; -// bool aligned1 = (iN1 % PacketSize) == 0; -// -// if (aligned0 && aligned1) -// { -// for (int j = 0;j0) -// { -// bool aligned0 = (iN0 % PacketSize) == 0; -// if (aligned0) -// for (int j = 0;j0) -// { -// bool aligned = (iN % PacketSize) == 0; -// if (aligned) -// { -// #ifdef PEELING -// Packet A0, A1, A2, X0, X1, X2; -// int ANP = (AN/(8*PacketSize))*8*PacketSize; -// for (int j = 0;j0) - { - int align1 = (iN1 % PacketSize); - if (align1==0) - { - for (int j = 0;j0) - { - if (iN0 % PacketSize==0) - for (int j = 0;j0) -// { -// bool aligned = (iN % PacketSize) == 0; -// if (aligned) -// { -// #ifdef PEELING -// int ANP = (AN/(8*PacketSize))*8*PacketSize; -// for (int j = 0;j0) - { - Packet pcoef = internal::pset1(coef); - #ifdef PEELING - const int peelSize = 3; - int ANP = (AN/(peelSize*PacketSize))*peelSize*PacketSize; - float* X1 = X + PacketSize; - float* Y1 = Y + PacketSize; - float* X2 = X + 2*PacketSize; - float* Y2 = Y + 2*PacketSize; - Packet x0,x1,x2,y0,y1,y2; - for (int j = 0;j -// Copyright (C) EDF R&D, lun sep 30 14:23:23 CEST 2002 -//===================================================== -// -// This program is free software; you can redistribute it and/or -// modify it under the terms of the GNU General Public License -// as published by the Free Software Foundation; either version 2 -// of the License, or (at your option) any later version. -// -// This program is distributed in the hope that it will be useful, -// but WITHOUT ANY WARRANTY; without even the implied warranty of -// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the -// GNU General Public License for more details. -// You should have received a copy of the GNU General Public License -// along with this program; if not, write to the Free Software -// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA. -// -#include "utilities.h" -#include "bench.hh" -#include "hand_vec_interface.hh" -#include "action_matrix_vector_product.hh" -#include "action_atv_product.hh" -#include "action_matrix_matrix_product.hh" -#include "action_axpy.hh" -#include "action_ata_product.hh" -#include "action_aat_product.hh" -#include "basic_actions.hh" -//#include "action_lu_solve.hh" -// #include "timers/mixed_perf_analyzer.hh" - -BTL_MAIN; - -int main() -{ - - bench > >(MIN_MV,MAX_MV,NB_POINT); - bench > >(MIN_MV,MAX_MV,NB_POINT); -// bench > >(MIN_MM,MAX_MM,NB_POINT); -// bench > >(MIN_MM,MAX_MM,NB_POINT); -// bench > >(MIN_MM,MAX_MM,NB_POINT); - bench > >(MIN_MM,MAX_MM,NB_POINT); - bench > >(MIN_AXPY,MAX_AXPY,NB_POINT); - - - return 0; -} - - diff --git a/gtsam/3rdparty/Eigen/bench/btl/libs/mtl4/mtl4_interface.hh b/gtsam/3rdparty/Eigen/bench/btl/libs/mtl4/mtl4_interface.hh index a2f067f73..3795ac61e 100644 --- a/gtsam/3rdparty/Eigen/bench/btl/libs/mtl4/mtl4_interface.hh +++ b/gtsam/3rdparty/Eigen/bench/btl/libs/mtl4/mtl4_interface.hh @@ -92,9 +92,9 @@ public : X = (trans(A)*trans(B)); } - static inline void ata_product(const gene_matrix & A, gene_matrix & X, int N){ - X = (trans(A)*A); - } +// static inline void ata_product(const gene_matrix & A, gene_matrix & X, int N){ +// X = (trans(A)*A); +// } static inline void aat_product(const gene_matrix & A, gene_matrix & X, int N){ X = (A*trans(A)); diff --git a/gtsam/3rdparty/Eigen/bench/btl/libs/ublas/main.cpp b/gtsam/3rdparty/Eigen/bench/btl/libs/ublas/main.cpp index 22d697225..e2e77ee1f 100644 --- a/gtsam/3rdparty/Eigen/bench/btl/libs/ublas/main.cpp +++ b/gtsam/3rdparty/Eigen/bench/btl/libs/ublas/main.cpp @@ -33,8 +33,8 @@ int main() bench > >(MIN_MV,MAX_MV,NB_POINT); bench > >(MIN_MM,MAX_MM,NB_POINT); - bench > >(MIN_MM,MAX_MM,NB_POINT); - bench > >(MIN_MM,MAX_MM,NB_POINT); +// bench > >(MIN_MM,MAX_MM,NB_POINT); +// bench > >(MIN_MM,MAX_MM,NB_POINT); bench > >(MIN_MM,MAX_MM,NB_POINT); diff --git a/gtsam/3rdparty/Eigen/bench/sparse_dense_product.cpp b/gtsam/3rdparty/Eigen/bench/sparse_dense_product.cpp index bfe46122d..f3f519406 100644 --- a/gtsam/3rdparty/Eigen/bench/sparse_dense_product.cpp +++ b/gtsam/3rdparty/Eigen/bench/sparse_dense_product.cpp @@ -4,7 +4,7 @@ // -DNOGMM -DNOMTL -DCSPARSE // -I /home/gael/Coding/LinearAlgebra/CSparse/Include/ /home/gael/Coding/LinearAlgebra/CSparse/Lib/libcsparse.a #ifndef SIZE -#define SIZE 10000 +#define SIZE 650000 #endif #ifndef DENSITY @@ -62,7 +62,8 @@ int main(int argc, char *argv[]) BenchTimer timer; for (float density = DENSITY; density>=MINDENSITY; density*=0.5) { - fillMatrix(density, rows, cols, sm1); + //fillMatrix(density, rows, cols, sm1); + fillMatrix2(7, rows, cols, sm1); // dense matrices #ifdef DENSEMATRIX @@ -76,14 +77,14 @@ int main(int argc, char *argv[]) for (int k=0; k uv1, uv2; + eiToUblasVec(v1,uv1); + eiToUblasVec(v2,uv2); + +// std::vector gmmV1(cols), gmmV2(cols); +// Map >(&gmmV1[0], cols) = v1; +// Map >(&gmmV2[0], cols) = v2; + + BENCH( uv2 = boost::numeric::ublas::prod(m1, uv1); ) + std::cout << " a * v:\t" << timer.value() << endl; + +// BENCH( boost::ublas::prod(gmm::transposed(m1), gmmV1, gmmV2); ) +// std::cout << " a' * v:\t" << timer.value() << endl; + } + #endif // MTL4 #ifndef NOMTL diff --git a/gtsam/3rdparty/Eigen/bench/sparse_product.cpp b/gtsam/3rdparty/Eigen/bench/sparse_product.cpp index 0b5558b89..d2fc44f0d 100644 --- a/gtsam/3rdparty/Eigen/bench/sparse_product.cpp +++ b/gtsam/3rdparty/Eigen/bench/sparse_product.cpp @@ -20,6 +20,7 @@ #include #include "BenchTimer.h" +#include "BenchUtil.h" #include "BenchSparseUtil.h" #ifndef NBTRIES @@ -228,16 +229,12 @@ int main(int argc, char *argv[]) eiToCSparse(sm1, m1); eiToCSparse(sm2, m2); -// timer.reset(); -// timer.start(); -// for (int k=0; k + +void bench_printhelp() +{ + cout<< " \nbenchsolver : performs a benchmark of all the solvers available in Eigen \n\n"; + cout<< " MATRIX FOLDER : \n"; + cout<< " The matrices for the benchmark should be collected in a folder specified with an environment variable EIGEN_MATRIXDIR \n"; + cout<< " This folder should contain the subfolders real/ and complex/ : \n"; + cout<< " The matrices are stored using the matrix market coordinate format \n"; + cout<< " The matrix and associated right-hand side (rhs) files are named respectively \n"; + cout<< " as MatrixName.mtx and MatrixName_b.mtx. If the rhs does not exist, a random one is generated. \n"; + cout<< " If a matrix is SPD, the matrix should be named as MatrixName_SPD.mtx \n"; + cout<< " If a true solution exists, it should be named as MatrixName_x.mtx; \n" ; + cout<< " it will be used to compute the norm of the error relative to the computed solutions\n\n"; + cout<< " OPTIONS : \n"; + cout<< " -h or --help \n print this help and return\n\n"; + cout<< " -d matrixdir \n Use matrixdir as the matrix folder instead of the one specified in the environment variable EIGEN_MATRIXDIR\n\n"; + cout<< " -o outputfile.html \n Output the statistics to a html file \n\n"; + cout<< " --eps Sets the relative tolerance for iterative solvers (default 1e-08) \n\n"; + cout<< " --maxits Sets the maximum number of iterations (default 1000) \n\n"; + +} +int main(int argc, char ** args) +{ + + bool help = ( get_options(argc, args, "-h") || get_options(argc, args, "--help") ); + if(help) { + bench_printhelp(); + return 0; + } + + // Get the location of the test matrices + string matrix_dir; + if (!get_options(argc, args, "-d", &matrix_dir)) + { + if(getenv("EIGEN_MATRIXDIR") == NULL){ + std::cerr << "Please, specify the location of the matrices with -d mat_folder or the environment variable EIGEN_MATRIXDIR \n"; + std::cerr << " Run with --help to see the list of all the available options \n"; + return -1; + } + matrix_dir = getenv("EIGEN_MATRIXDIR"); + } + + std::ofstream statbuf; + string statFile ; + + // Get the file to write the statistics + bool statFileExists = get_options(argc, args, "-o", &statFile); + if(statFileExists) + { + statbuf.open(statFile.c_str(), std::ios::out); + if(statbuf.good()){ + statFileExists = true; + printStatheader(statbuf); + statbuf.close(); + } + else + std::cerr << "Unable to open the provided file for writting... \n"; + } + + // Get the maximum number of iterations and the tolerance + int maxiters = 1000; + double tol = 1e-08; + string inval; + if (get_options(argc, args, "--eps", &inval)) + tol = atof(inval.c_str()); + if(get_options(argc, args, "--maxits", &inval)) + maxiters = atoi(inval.c_str()); + + string current_dir; + // Test the matrices in %EIGEN_MATRIXDIR/real + current_dir = matrix_dir + "/real"; + Browse_Matrices(current_dir, statFileExists, statFile,maxiters, tol); + + // Test the matrices in %EIGEN_MATRIXDIR/complex + current_dir = matrix_dir + "/complex"; + Browse_Matrices >(current_dir, statFileExists, statFile, maxiters, tol); + + if(statFileExists) + { + statbuf.open(statFile.c_str(), std::ios::app); + statbuf << " \n"; + cout << "\n Output written in " << statFile << " ...\n"; + statbuf.close(); + } + + return 0; +} + + diff --git a/gtsam/3rdparty/Eigen/bench/spbench/spbenchsolver.h b/gtsam/3rdparty/Eigen/bench/spbench/spbenchsolver.h new file mode 100644 index 000000000..6d765a997 --- /dev/null +++ b/gtsam/3rdparty/Eigen/bench/spbench/spbenchsolver.h @@ -0,0 +1,548 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2012 Désiré Nuentsa-Wakam +// +// Eigen is free software; you can redistribute it and/or +// modify it under the terms of the GNU Lesser General Public +// License as published by the Free Software Foundation; either +// version 3 of the License, or (at your option) any later version. +// +// Alternatively, you can redistribute it and/or +// modify it under the terms of the GNU General Public License as +// published by the Free Software Foundation; either version 2 of +// the License, or (at your option) any later version. +// +// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY +// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the +// GNU General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public +// License and a copy of the GNU General Public License along with +// Eigen. If not, see . + + +#include +#include +#include "Eigen/SparseCore" +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +#ifdef EIGEN_CHOLMOD_SUPPORT +#include +#endif + +#ifdef EIGEN_UMFPACK_SUPPORT +#include +#endif + +#ifdef EIGEN_PARDISO_SUPPORT +#include +#endif + +#ifdef EIGEN_SUPERLU_SUPPORT +#include +#endif + +#ifdef EIGEN_PASTIX_SUPPORT +#include +#endif + +// CONSTANTS +#define EIGEN_UMFPACK 0 +#define EIGEN_SUPERLU 1 +#define EIGEN_PASTIX 2 +#define EIGEN_PARDISO 3 +#define EIGEN_BICGSTAB 4 +#define EIGEN_BICGSTAB_ILUT 5 +#define EIGEN_GMRES 6 +#define EIGEN_GMRES_ILUT 7 +#define EIGEN_SIMPLICIAL_LDLT 8 +#define EIGEN_CHOLMOD_LDLT 9 +#define EIGEN_PASTIX_LDLT 10 +#define EIGEN_PARDISO_LDLT 11 +#define EIGEN_SIMPLICIAL_LLT 12 +#define EIGEN_CHOLMOD_SUPERNODAL_LLT 13 +#define EIGEN_CHOLMOD_SIMPLICIAL_LLT 14 +#define EIGEN_PASTIX_LLT 15 +#define EIGEN_PARDISO_LLT 16 +#define EIGEN_CG 17 +#define EIGEN_CG_PRECOND 18 +#define EIGEN_ALL_SOLVERS 19 + +using namespace Eigen; +using namespace std; + +struct Stats{ + ComputationInfo info; + double total_time; + double compute_time; + double solve_time; + double rel_error; + int memory_used; + int iterations; + int isavail; + int isIterative; +}; + +// Global variables for input parameters +int MaximumIters; // Maximum number of iterations +double RelErr; // Relative error of the computed solution + +template inline typename NumTraits::Real test_precision() { return NumTraits::dummy_precision(); } +template<> inline float test_precision() { return 1e-3f; } +template<> inline double test_precision() { return 1e-6; } +template<> inline float test_precision >() { return test_precision(); } +template<> inline double test_precision >() { return test_precision(); } + +void printStatheader(std::ofstream& out) +{ + int LUcnt = 0; + string LUlist =" ", LLTlist = " LLT", LDLTlist = " LDLT "; + +#ifdef EIGEN_UMFPACK_SUPPORT + LUlist += " UMFPACK "; LUcnt++; +#endif +#ifdef EIGEN_SUPERLU_SUPPORT + LUlist += " SUPERLU "; LUcnt++; +#endif +#ifdef EIGEN_CHOLMOD_SUPPORT + LLTlist += " CHOLMOD SP LLT CHOLMOD LLT"; + LDLTlist += "CHOLMOD LDLT"; +#endif +#ifdef EIGEN_PARDISO_SUPPORT + LUlist += " PARDISO LU"; LUcnt++; + LLTlist += " PARDISO LLT"; + LDLTlist += " PARDISO LDLT"; +#endif +#ifdef EIGEN_PASTIX_SUPPORT + LUlist += " PASTIX LU"; LUcnt++; + LLTlist += " PASTIX LLT"; + LDLTlist += " PASTIX LDLT"; +#endif + + out << "\n "; + out << "
Matrix N NNZ "; + if (LUcnt) out << LUlist; + out << " BiCGSTAB BiCGSTAB+ILUT"<< "GMRES+ILUT" < CG "<< std::endl; +} + + +template +Stats call_solver(Solver &solver, const typename Solver::MatrixType& A, const Matrix& b, const Matrix& refX) +{ + Stats stat; + Matrix x; + BenchTimer timer; + timer.reset(); + timer.start(); + solver.compute(A); + if (solver.info() != Success) + { + stat.info = NumericalIssue; + std::cerr << "Solver failed ... \n"; + return stat; + } + timer.stop(); + stat.compute_time = timer.value(); + + timer.reset(); + timer.start(); + x = solver.solve(b); + if (solver.info() == NumericalIssue) + { + stat.info = NumericalIssue; + std::cerr << "Solver failed ... \n"; + return stat; + } + + timer.stop(); + stat.solve_time = timer.value(); + stat.total_time = stat.solve_time + stat.compute_time; + stat.memory_used = 0; + // Verify the relative error + if(refX.size() != 0) + stat.rel_error = (refX - x).norm()/refX.norm(); + else + { + // Compute the relative residual norm + Matrix temp; + temp = A * x; + stat.rel_error = (b-temp).norm()/b.norm(); + } + if ( stat.rel_error > RelErr ) + { + stat.info = NoConvergence; + return stat; + } + else + { + stat.info = Success; + return stat; + } +} + +template +Stats call_directsolver(Solver& solver, const typename Solver::MatrixType& A, const Matrix& b, const Matrix& refX) +{ + Stats stat; + stat = call_solver(solver, A, b, refX); + return stat; +} + +template +Stats call_itersolver(Solver &solver, const typename Solver::MatrixType& A, const Matrix& b, const Matrix& refX) +{ + Stats stat; + solver.setTolerance(RelErr); + solver.setMaxIterations(MaximumIters); + + stat = call_solver(solver, A, b, refX); + stat.iterations = solver.iterations(); + return stat; +} + +inline void printStatItem(Stats *stat, int solver_id, int& best_time_id, double& best_time_val) +{ + stat[solver_id].isavail = 1; + + if (stat[solver_id].info == NumericalIssue) + { + cout << " SOLVER FAILED ... Probably a numerical issue \n"; + return; + } + if (stat[solver_id].info == NoConvergence){ + cout << "REL. ERROR " << stat[solver_id].rel_error; + if(stat[solver_id].isIterative == 1) + cout << " (" << stat[solver_id].iterations << ") \n"; + return; + } + + // Record the best CPU time + if (!best_time_val) + { + best_time_val = stat[solver_id].total_time; + best_time_id = solver_id; + } + else if (stat[solver_id].total_time < best_time_val) + { + best_time_val = stat[solver_id].total_time; + best_time_id = solver_id; + } + // Print statistics to standard output + if (stat[solver_id].info == Success){ + cout<< "COMPUTE TIME : " << stat[solver_id].compute_time<< " \n"; + cout<< "SOLVE TIME : " << stat[solver_id].solve_time<< " \n"; + cout<< "TOTAL TIME : " << stat[solver_id].total_time<< " \n"; + cout << "REL. ERROR : " << stat[solver_id].rel_error ; + if(stat[solver_id].isIterative == 1) { + cout << " (" << stat[solver_id].iterations << ") "; + } + cout << std::endl; + } + +} + + +/* Print the results from all solvers corresponding to a particular matrix + * The best CPU time is printed in bold + */ +inline void printHtmlStatLine(Stats *stat, int best_time_id, string& statline) +{ + + string markup; + ostringstream compute,solve,total,error; + for (int i = 0; i < EIGEN_ALL_SOLVERS; i++) + { + if (stat[i].isavail == 0) continue; + if(i == best_time_id) + markup = ""; + else + markup = ""; + + if (stat[i].info == Success){ + compute << markup << stat[i].compute_time; + solve << markup << stat[i].solve_time; + total << markup << stat[i].total_time; + error << " " << stat[i].rel_error; + if(stat[i].isIterative == 1) { + error << " (" << stat[i].iterations << ") "; + } + } + else { + compute << " -" ; + solve << " -" ; + total << " -" ; + if(stat[i].info == NoConvergence){ + error << " "<< stat[i].rel_error ; + if(stat[i].isIterative == 1) + error << " (" << stat[i].iterations << ") "; + } + else error << " - "; + } + } + + statline = "Compute Time " + compute.str() + "\n" + + "
Solve Time " + solve.str() + "\n" + + "
Total Time " + total.str() + "\n" + +"
Error(Iter)" + error.str() + "\n"; + +} + +template +int SelectSolvers(const SparseMatrix&A, unsigned int sym, Matrix& b, const Matrix& refX, Stats *stat) +{ + typedef SparseMatrix SpMat; + // First, deal with Nonsymmetric and symmetric matrices + int best_time_id = 0; + double best_time_val = 0.0; + //UMFPACK + #ifdef EIGEN_UMFPACK_SUPPORT + { + cout << "Solving with UMFPACK LU ... \n"; + UmfPackLU solver; + stat[EIGEN_UMFPACK] = call_directsolver(solver, A, b, refX); + printStatItem(stat, EIGEN_UMFPACK, best_time_id, best_time_val); + } + #endif + //SuperLU + #ifdef EIGEN_SUPERLU_SUPPORT + { + cout << "\nSolving with SUPERLU ... \n"; + SuperLU solver; + stat[EIGEN_SUPERLU] = call_directsolver(solver, A, b, refX); + printStatItem(stat, EIGEN_SUPERLU, best_time_id, best_time_val); + } + #endif + + // PaStix LU + #ifdef EIGEN_PASTIX_SUPPORT + { + cout << "\nSolving with PASTIX LU ... \n"; + PastixLU solver; + stat[EIGEN_PASTIX] = call_directsolver(solver, A, b, refX) ; + printStatItem(stat, EIGEN_PASTIX, best_time_id, best_time_val); + } + #endif + + //PARDISO LU + #ifdef EIGEN_PARDISO_SUPPORT + { + cout << "\nSolving with PARDISO LU ... \n"; + PardisoLU solver; + stat[EIGEN_PARDISO] = call_directsolver(solver, A, b, refX); + printStatItem(stat, EIGEN_PARDISO, best_time_id, best_time_val); + } + #endif + + + + //BiCGSTAB + { + cout << "\nSolving with BiCGSTAB ... \n"; + BiCGSTAB solver; + stat[EIGEN_BICGSTAB] = call_itersolver(solver, A, b, refX); + stat[EIGEN_BICGSTAB].isIterative = 1; + printStatItem(stat, EIGEN_BICGSTAB, best_time_id, best_time_val); + } + //BiCGSTAB+ILUT + { + cout << "\nSolving with BiCGSTAB and ILUT ... \n"; + BiCGSTAB > solver; + stat[EIGEN_BICGSTAB_ILUT] = call_itersolver(solver, A, b, refX); + stat[EIGEN_BICGSTAB_ILUT].isIterative = 1; + printStatItem(stat, EIGEN_BICGSTAB_ILUT, best_time_id, best_time_val); + } + + + //GMRES +// { +// cout << "\nSolving with GMRES ... \n"; +// GMRES solver; +// stat[EIGEN_GMRES] = call_itersolver(solver, A, b, refX); +// stat[EIGEN_GMRES].isIterative = 1; +// printStatItem(stat, EIGEN_GMRES, best_time_id, best_time_val); +// } + //GMRES+ILUT + { + cout << "\nSolving with GMRES and ILUT ... \n"; + GMRES > solver; + stat[EIGEN_GMRES_ILUT] = call_itersolver(solver, A, b, refX); + stat[EIGEN_GMRES_ILUT].isIterative = 1; + printStatItem(stat, EIGEN_GMRES_ILUT, best_time_id, best_time_val); + } + + // Hermitian and not necessarily positive-definites + if (sym != NonSymmetric) + { + // Internal Cholesky + { + cout << "\nSolving with Simplicial LDLT ... \n"; + SimplicialLDLT solver; + stat[EIGEN_SIMPLICIAL_LDLT] = call_directsolver(solver, A, b, refX); + printStatItem(stat, EIGEN_SIMPLICIAL_LDLT, best_time_id, best_time_val); + } + + // CHOLMOD + #ifdef EIGEN_CHOLMOD_SUPPORT + { + cout << "\nSolving with CHOLMOD LDLT ... \n"; + CholmodDecomposition solver; + solver.setMode(CholmodLDLt); + stat[EIGEN_CHOLMOD_LDLT] = call_directsolver(solver, A, b, refX); + printStatItem(stat,EIGEN_CHOLMOD_LDLT, best_time_id, best_time_val); + } + #endif + + //PASTIX LLT + #ifdef EIGEN_PASTIX_SUPPORT + { + cout << "\nSolving with PASTIX LDLT ... \n"; + PastixLDLT solver; + stat[EIGEN_PASTIX_LDLT] = call_directsolver(solver, A, b, refX); + printStatItem(stat,EIGEN_PASTIX_LDLT, best_time_id, best_time_val); + } + #endif + + //PARDISO LLT + #ifdef EIGEN_PARDISO_SUPPORT + { + cout << "\nSolving with PARDISO LDLT ... \n"; + PardisoLDLT solver; + stat[EIGEN_PARDISO_LDLT] = call_directsolver(solver, A, b, refX); + printStatItem(stat,EIGEN_PARDISO_LDLT, best_time_id, best_time_val); + } + #endif + } + + // Now, symmetric POSITIVE DEFINITE matrices + if (sym == SPD) + { + + //Internal Sparse Cholesky + { + cout << "\nSolving with SIMPLICIAL LLT ... \n"; + SimplicialLLT solver; + stat[EIGEN_SIMPLICIAL_LLT] = call_directsolver(solver, A, b, refX); + printStatItem(stat,EIGEN_SIMPLICIAL_LLT, best_time_id, best_time_val); + } + + // CHOLMOD + #ifdef EIGEN_CHOLMOD_SUPPORT + { + // CholMOD SuperNodal LLT + cout << "\nSolving with CHOLMOD LLT (Supernodal)... \n"; + CholmodDecomposition solver; + solver.setMode(CholmodSupernodalLLt); + stat[EIGEN_CHOLMOD_SUPERNODAL_LLT] = call_directsolver(solver, A, b, refX); + printStatItem(stat,EIGEN_CHOLMOD_SUPERNODAL_LLT, best_time_id, best_time_val); + // CholMod Simplicial LLT + cout << "\nSolving with CHOLMOD LLT (Simplicial) ... \n"; + solver.setMode(CholmodSimplicialLLt); + stat[EIGEN_CHOLMOD_SIMPLICIAL_LLT] = call_directsolver(solver, A, b, refX); + printStatItem(stat,EIGEN_CHOLMOD_SIMPLICIAL_LLT, best_time_id, best_time_val); + } + #endif + + //PASTIX LLT + #ifdef EIGEN_PASTIX_SUPPORT + { + cout << "\nSolving with PASTIX LLT ... \n"; + PastixLLT solver; + stat[EIGEN_PASTIX_LLT] = call_directsolver(solver, A, b, refX); + printStatItem(stat,EIGEN_PASTIX_LLT, best_time_id, best_time_val); + } + #endif + + //PARDISO LLT + #ifdef EIGEN_PARDISO_SUPPORT + { + cout << "\nSolving with PARDISO LLT ... \n"; + PardisoLLT solver; + stat[EIGEN_PARDISO_LLT] = call_directsolver(solver, A, b, refX); + printStatItem(stat,EIGEN_PARDISO_LLT, best_time_id, best_time_val); + } + #endif + + // Internal CG + { + cout << "\nSolving with CG ... \n"; + ConjugateGradient solver; + stat[EIGEN_CG] = call_itersolver(solver, A, b, refX); + stat[EIGEN_CG].isIterative = 1; + printStatItem(stat,EIGEN_CG, best_time_id, best_time_val); + } + //CG+IdentityPreconditioner +// { +// cout << "\nSolving with CG and IdentityPreconditioner ... \n"; +// ConjugateGradient solver; +// stat[EIGEN_CG_PRECOND] = call_itersolver(solver, A, b, refX); +// stat[EIGEN_CG_PRECOND].isIterative = 1; +// printStatItem(stat,EIGEN_CG_PRECOND, best_time_id, best_time_val); +// } + } // End SPD matrices + + return best_time_id; +} + +/* Browse all the matrices available in the specified folder + * and solve the associated linear system. + * The results of each solve are printed in the standard output + * and optionally in the provided html file + */ +template +void Browse_Matrices(const string folder, bool statFileExists, std::string& statFile, int maxiters, double tol) +{ + MaximumIters = maxiters; // Maximum number of iterations, global variable + RelErr = tol; //Relative residual error as stopping criterion for iterative solvers + MatrixMarketIterator it(folder); + Stats stat[EIGEN_ALL_SOLVERS]; + for ( ; it; ++it) + { + for (int i = 0; i < EIGEN_ALL_SOLVERS; i++) + { + stat[i].isavail = 0; + stat[i].isIterative = 0; + } + + int best_time_id; + cout<< "\n\n===================================================== \n"; + cout<< " ====== SOLVING WITH MATRIX " << it.matname() << " ====\n"; + cout<< " =================================================== \n\n"; + Matrix refX; + if(it.hasrefX()) refX = it.refX(); + best_time_id = SelectSolvers(it.matrix(), it.sym(), it.rhs(), refX, &stat[0]); + + if(statFileExists) + { + string statline; + printHtmlStatLine(&stat[0], best_time_id, statline); + std::ofstream statbuf(statFile.c_str(), std::ios::app); + statbuf << "
" << it.matname() << " " + << it.matrix().rows() << " " << it.matrix().nonZeros()<< " "<< statline ; + statbuf.close(); + } + } +} + +bool get_options(int argc, char **args, string option, string* value=0) +{ + int idx = 1, found=false; + while (idx +// +// Eigen is free software; you can redistribute it and/or +// modify it under the terms of the GNU Lesser General Public +// License as published by the Free Software Foundation; either +// version 3 of the License, or (at your option) any later version. +// +// Alternatively, you can redistribute it and/or +// modify it under the terms of the GNU General Public License as +// published by the Free Software Foundation; either version 2 of +// the License, or (at your option) any later version. +// +// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY +// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the +// GNU General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public +// License and a copy of the GNU General Public License along with +// Eigen. If not, see . + +#ifndef EIGEN_BAND_TRIANGULARSOLVER_H +#define EIGEN_BAND_TRIANGULARSOLVER_H + +namespace internal { + + /* \internal + * Solve Ax=b with A a band triangular matrix + * TODO: extend it to matrices for x abd b */ +template +struct band_solve_triangular_selector; + + +template +struct band_solve_triangular_selector +{ + typedef Map, 0, OuterStride<> > LhsMap; + typedef Map > RhsMap; + enum { IsLower = (Mode&Lower) ? 1 : 0 }; + static void run(Index size, Index k, const LhsScalar* _lhs, Index lhsStride, RhsScalar* _other) + { + const LhsMap lhs(_lhs,size,k+1,OuterStride<>(lhsStride)); + RhsMap other(_other,size,1); + typename internal::conditional< + ConjLhs, + const CwiseUnaryOp,LhsMap>, + const LhsMap&> + ::type cjLhs(lhs); + + for(int col=0 ; col0) + other.coeffRef(i,col) -= cjLhs.row(i).segment(actual_start,actual_k).transpose() + .cwiseProduct(other.col(col).segment(IsLower ? i-actual_k : i+1,actual_k)).sum(); + + if((Mode&UnitDiag)==0) + other.coeffRef(i,col) /= cjLhs(i,IsLower ? k : 0); + } + } + } + +}; + +template +struct band_solve_triangular_selector +{ + typedef Map, 0, OuterStride<> > LhsMap; + typedef Map > RhsMap; + enum { IsLower = (Mode&Lower) ? 1 : 0 }; + static void run(Index size, Index k, const LhsScalar* _lhs, Index lhsStride, RhsScalar* _other) + { + const LhsMap lhs(_lhs,k+1,size,OuterStride<>(lhsStride)); + RhsMap other(_other,size,1); + typename internal::conditional< + ConjLhs, + const CwiseUnaryOp,LhsMap>, + const LhsMap&> + ::type cjLhs(lhs); + + for(int col=0 ; col0) + other.col(col).segment(IsLower ? i+1 : i-actual_k, actual_k) + -= other.coeff(i,col) * cjLhs.col(i).segment(actual_start,actual_k); + + } + } + } +}; + + +} // end namespace internal + +#endif // EIGEN_BAND_TRIANGULARSOLVER_H diff --git a/gtsam/3rdparty/Eigen/blas/CMakeLists.txt b/gtsam/3rdparty/Eigen/blas/CMakeLists.txt index 5f2e3cd32..453d5874c 100644 --- a/gtsam/3rdparty/Eigen/blas/CMakeLists.txt +++ b/gtsam/3rdparty/Eigen/blas/CMakeLists.txt @@ -1,27 +1,34 @@ project(EigenBlas CXX) -if( NOT DEFINED EIGEN_Fortran_COMPILER_WORKS OR EIGEN_Fortran_COMPILER_WORKS) +include("../cmake/language_support.cmake") +workaround_9220(Fortran EIGEN_Fortran_COMPILER_WORKS) + +if(EIGEN_Fortran_COMPILER_WORKS) enable_language(Fortran OPTIONAL) - - if(CMAKE_Fortran_COMPILER_WORKS) - set(EIGEN_Fortran_COMPILER_WORKS TRUE CACHE INTERNAL "workaround cmake's enable_language issue") - else() - set(EIGEN_Fortran_COMPILER_WORKS FALSE CACHE INTERNAL "workaround cmake's enable_language issue") - endif() - endif() -if(CMAKE_Fortran_COMPILER_WORKS) - add_custom_target(blas) -set(EigenBlas_SRCS single.cpp double.cpp complex_single.cpp complex_double.cpp xerbla.cpp +set(EigenBlas_SRCS single.cpp double.cpp complex_single.cpp complex_double.cpp xerbla.cpp) + +if(EIGEN_Fortran_COMPILER_WORKS) + +set(EigenBlas_SRCS ${EigenBlas_SRCS} complexdots.f srotm.f srotmg.f drotm.f drotmg.f - lsame.f chpr2.f ctbsv.f dspmv.f dtbmv.f dtpsv.f ssbmv.f sspr.f stpmv.f zhpr2.f ztbsv.f chbmv.f chpr.f ctpmv.f dspr2.f dtbsv.f sspmv.f stbmv.f stpsv.f zhbmv.f zhpr.f ztpmv.f chpmv.f ctbmv.f ctpsv.f dsbmv.f dspr.f dtpmv.f sspr2.f stbsv.f zhpmv.f ztbmv.f ztpsv.f + lsame.f chpr2.f dspmv.f dtpsv.f ssbmv.f sspr.f stpmv.f + zhpr2.f chbmv.f chpr.f ctpmv.f dspr2.f sspmv.f stpsv.f + zhbmv.f zhpr.f ztpmv.f chpmv.f ctpsv.f dsbmv.f dspr.f dtpmv.f sspr2.f + zhpmv.f ztpsv.f + dtbmv.f stbmv.f ctbmv.f ztbmv.f ) +else() + +message(WARNING " No fortran compiler has been detected, the blas build will be incomplete.") + +endif() add_library(eigen_blas_static ${EigenBlas_SRCS}) add_library(eigen_blas SHARED ${EigenBlas_SRCS}) @@ -33,11 +40,12 @@ endif() add_dependencies(blas eigen_blas eigen_blas_static) -install(TARGETS eigen_blas +install(TARGETS eigen_blas eigen_blas_static RUNTIME DESTINATION bin LIBRARY DESTINATION lib ARCHIVE DESTINATION lib) +if(EIGEN_Fortran_COMPILER_WORKS) if(EIGEN_LEAVE_TEST_IN_ALL_TARGET) add_subdirectory(testing) # can't do EXCLUDE_FROM_ALL here, breaks CTest @@ -45,4 +53,5 @@ else() add_subdirectory(testing EXCLUDE_FROM_ALL) endif() -endif(CMAKE_Fortran_COMPILER_WORKS) +endif() + diff --git a/gtsam/3rdparty/Eigen/blas/common.h b/gtsam/3rdparty/Eigen/blas/common.h index ed93642f9..ada833a90 100644 --- a/gtsam/3rdparty/Eigen/blas/common.h +++ b/gtsam/3rdparty/Eigen/blas/common.h @@ -32,16 +32,8 @@ #error the token SCALAR must be defined to compile this file #endif -#ifdef __cplusplus -extern "C" -{ -#endif +#include -#include "../bench/btl/libs/C_BLAS/blas.h" - -#ifdef __cplusplus -} -#endif #define NOTR 0 #define TR 1 @@ -93,6 +85,12 @@ inline bool check_uplo(const char* uplo) #include #include + + +namespace Eigen { +#include "BandTriangularSolver.h" +} + using namespace Eigen; typedef SCALAR Scalar; diff --git a/gtsam/3rdparty/Eigen/blas/ctbsv.f b/gtsam/3rdparty/Eigen/blas/ctbsv.f deleted file mode 100644 index 853b9d75e..000000000 --- a/gtsam/3rdparty/Eigen/blas/ctbsv.f +++ /dev/null @@ -1,370 +0,0 @@ - SUBROUTINE CTBSV(UPLO,TRANS,DIAG,N,K,A,LDA,X,INCX) -* .. Scalar Arguments .. - INTEGER INCX,K,LDA,N - CHARACTER DIAG,TRANS,UPLO -* .. -* .. Array Arguments .. - COMPLEX A(LDA,*),X(*) -* .. -* -* Purpose -* ======= -* -* CTBSV solves one of the systems of equations -* -* A*x = b, or A'*x = b, or conjg( A' )*x = b, -* -* where b and x are n element vectors and A is an n by n unit, or -* non-unit, upper or lower triangular band matrix, with ( k + 1 ) -* diagonals. -* -* No test for singularity or near-singularity is included in this -* routine. Such tests must be performed before calling this routine. -* -* Arguments -* ========== -* -* UPLO - CHARACTER*1. -* On entry, UPLO specifies whether the matrix is an upper or -* lower triangular matrix as follows: -* -* UPLO = 'U' or 'u' A is an upper triangular matrix. -* -* UPLO = 'L' or 'l' A is a lower triangular matrix. -* -* Unchanged on exit. -* -* TRANS - CHARACTER*1. -* On entry, TRANS specifies the equations to be solved as -* follows: -* -* TRANS = 'N' or 'n' A*x = b. -* -* TRANS = 'T' or 't' A'*x = b. -* -* TRANS = 'C' or 'c' conjg( A' )*x = b. -* -* Unchanged on exit. -* -* DIAG - CHARACTER*1. -* On entry, DIAG specifies whether or not A is unit -* triangular as follows: -* -* DIAG = 'U' or 'u' A is assumed to be unit triangular. -* -* DIAG = 'N' or 'n' A is not assumed to be unit -* triangular. -* -* Unchanged on exit. -* -* N - INTEGER. -* On entry, N specifies the order of the matrix A. -* N must be at least zero. -* Unchanged on exit. -* -* K - INTEGER. -* On entry with UPLO = 'U' or 'u', K specifies the number of -* super-diagonals of the matrix A. -* On entry with UPLO = 'L' or 'l', K specifies the number of -* sub-diagonals of the matrix A. -* K must satisfy 0 .le. K. -* Unchanged on exit. -* -* A - COMPLEX array of DIMENSION ( LDA, n ). -* Before entry with UPLO = 'U' or 'u', the leading ( k + 1 ) -* by n part of the array A must contain the upper triangular -* band part of the matrix of coefficients, supplied column by -* column, with the leading diagonal of the matrix in row -* ( k + 1 ) of the array, the first super-diagonal starting at -* position 2 in row k, and so on. The top left k by k triangle -* of the array A is not referenced. -* The following program segment will transfer an upper -* triangular band matrix from conventional full matrix storage -* to band storage: -* -* DO 20, J = 1, N -* M = K + 1 - J -* DO 10, I = MAX( 1, J - K ), J -* A( M + I, J ) = matrix( I, J ) -* 10 CONTINUE -* 20 CONTINUE -* -* Before entry with UPLO = 'L' or 'l', the leading ( k + 1 ) -* by n part of the array A must contain the lower triangular -* band part of the matrix of coefficients, supplied column by -* column, with the leading diagonal of the matrix in row 1 of -* the array, the first sub-diagonal starting at position 1 in -* row 2, and so on. The bottom right k by k triangle of the -* array A is not referenced. -* The following program segment will transfer a lower -* triangular band matrix from conventional full matrix storage -* to band storage: -* -* DO 20, J = 1, N -* M = 1 - J -* DO 10, I = J, MIN( N, J + K ) -* A( M + I, J ) = matrix( I, J ) -* 10 CONTINUE -* 20 CONTINUE -* -* Note that when DIAG = 'U' or 'u' the elements of the array A -* corresponding to the diagonal elements of the matrix are not -* referenced, but are assumed to be unity. -* Unchanged on exit. -* -* LDA - INTEGER. -* On entry, LDA specifies the first dimension of A as declared -* in the calling (sub) program. LDA must be at least -* ( k + 1 ). -* Unchanged on exit. -* -* X - COMPLEX array of dimension at least -* ( 1 + ( n - 1 )*abs( INCX ) ). -* Before entry, the incremented array X must contain the n -* element right-hand side vector b. On exit, X is overwritten -* with the solution vector x. -* -* INCX - INTEGER. -* On entry, INCX specifies the increment for the elements of -* X. INCX must not be zero. -* Unchanged on exit. -* -* Further Details -* =============== -* -* Level 2 Blas routine. -* -* -- Written on 22-October-1986. -* Jack Dongarra, Argonne National Lab. -* Jeremy Du Croz, Nag Central Office. -* Sven Hammarling, Nag Central Office. -* Richard Hanson, Sandia National Labs. -* -* ===================================================================== -* -* .. Parameters .. - COMPLEX ZERO - PARAMETER (ZERO= (0.0E+0,0.0E+0)) -* .. -* .. Local Scalars .. - COMPLEX TEMP - INTEGER I,INFO,IX,J,JX,KPLUS1,KX,L - LOGICAL NOCONJ,NOUNIT -* .. -* .. External Functions .. - LOGICAL LSAME - EXTERNAL LSAME -* .. -* .. External Subroutines .. - EXTERNAL XERBLA -* .. -* .. Intrinsic Functions .. - INTRINSIC CONJG,MAX,MIN -* .. -* -* Test the input parameters. -* - INFO = 0 - IF (.NOT.LSAME(UPLO,'U') .AND. .NOT.LSAME(UPLO,'L')) THEN - INFO = 1 - ELSE IF (.NOT.LSAME(TRANS,'N') .AND. .NOT.LSAME(TRANS,'T') .AND. - + .NOT.LSAME(TRANS,'C')) THEN - INFO = 2 - ELSE IF (.NOT.LSAME(DIAG,'U') .AND. .NOT.LSAME(DIAG,'N')) THEN - INFO = 3 - ELSE IF (N.LT.0) THEN - INFO = 4 - ELSE IF (K.LT.0) THEN - INFO = 5 - ELSE IF (LDA.LT. (K+1)) THEN - INFO = 7 - ELSE IF (INCX.EQ.0) THEN - INFO = 9 - END IF - IF (INFO.NE.0) THEN - CALL XERBLA('CTBSV ',INFO) - RETURN - END IF -* -* Quick return if possible. -* - IF (N.EQ.0) RETURN -* - NOCONJ = LSAME(TRANS,'T') - NOUNIT = LSAME(DIAG,'N') -* -* Set up the start point in X if the increment is not unity. This -* will be ( N - 1 )*INCX too small for descending loops. -* - IF (INCX.LE.0) THEN - KX = 1 - (N-1)*INCX - ELSE IF (INCX.NE.1) THEN - KX = 1 - END IF -* -* Start the operations. In this version the elements of A are -* accessed by sequentially with one pass through A. -* - IF (LSAME(TRANS,'N')) THEN -* -* Form x := inv( A )*x. -* - IF (LSAME(UPLO,'U')) THEN - KPLUS1 = K + 1 - IF (INCX.EQ.1) THEN - DO 20 J = N,1,-1 - IF (X(J).NE.ZERO) THEN - L = KPLUS1 - J - IF (NOUNIT) X(J) = X(J)/A(KPLUS1,J) - TEMP = X(J) - DO 10 I = J - 1,MAX(1,J-K),-1 - X(I) = X(I) - TEMP*A(L+I,J) - 10 CONTINUE - END IF - 20 CONTINUE - ELSE - KX = KX + (N-1)*INCX - JX = KX - DO 40 J = N,1,-1 - KX = KX - INCX - IF (X(JX).NE.ZERO) THEN - IX = KX - L = KPLUS1 - J - IF (NOUNIT) X(JX) = X(JX)/A(KPLUS1,J) - TEMP = X(JX) - DO 30 I = J - 1,MAX(1,J-K),-1 - X(IX) = X(IX) - TEMP*A(L+I,J) - IX = IX - INCX - 30 CONTINUE - END IF - JX = JX - INCX - 40 CONTINUE - END IF - ELSE - IF (INCX.EQ.1) THEN - DO 60 J = 1,N - IF (X(J).NE.ZERO) THEN - L = 1 - J - IF (NOUNIT) X(J) = X(J)/A(1,J) - TEMP = X(J) - DO 50 I = J + 1,MIN(N,J+K) - X(I) = X(I) - TEMP*A(L+I,J) - 50 CONTINUE - END IF - 60 CONTINUE - ELSE - JX = KX - DO 80 J = 1,N - KX = KX + INCX - IF (X(JX).NE.ZERO) THEN - IX = KX - L = 1 - J - IF (NOUNIT) X(JX) = X(JX)/A(1,J) - TEMP = X(JX) - DO 70 I = J + 1,MIN(N,J+K) - X(IX) = X(IX) - TEMP*A(L+I,J) - IX = IX + INCX - 70 CONTINUE - END IF - JX = JX + INCX - 80 CONTINUE - END IF - END IF - ELSE -* -* Form x := inv( A' )*x or x := inv( conjg( A') )*x. -* - IF (LSAME(UPLO,'U')) THEN - KPLUS1 = K + 1 - IF (INCX.EQ.1) THEN - DO 110 J = 1,N - TEMP = X(J) - L = KPLUS1 - J - IF (NOCONJ) THEN - DO 90 I = MAX(1,J-K),J - 1 - TEMP = TEMP - A(L+I,J)*X(I) - 90 CONTINUE - IF (NOUNIT) TEMP = TEMP/A(KPLUS1,J) - ELSE - DO 100 I = MAX(1,J-K),J - 1 - TEMP = TEMP - CONJG(A(L+I,J))*X(I) - 100 CONTINUE - IF (NOUNIT) TEMP = TEMP/CONJG(A(KPLUS1,J)) - END IF - X(J) = TEMP - 110 CONTINUE - ELSE - JX = KX - DO 140 J = 1,N - TEMP = X(JX) - IX = KX - L = KPLUS1 - J - IF (NOCONJ) THEN - DO 120 I = MAX(1,J-K),J - 1 - TEMP = TEMP - A(L+I,J)*X(IX) - IX = IX + INCX - 120 CONTINUE - IF (NOUNIT) TEMP = TEMP/A(KPLUS1,J) - ELSE - DO 130 I = MAX(1,J-K),J - 1 - TEMP = TEMP - CONJG(A(L+I,J))*X(IX) - IX = IX + INCX - 130 CONTINUE - IF (NOUNIT) TEMP = TEMP/CONJG(A(KPLUS1,J)) - END IF - X(JX) = TEMP - JX = JX + INCX - IF (J.GT.K) KX = KX + INCX - 140 CONTINUE - END IF - ELSE - IF (INCX.EQ.1) THEN - DO 170 J = N,1,-1 - TEMP = X(J) - L = 1 - J - IF (NOCONJ) THEN - DO 150 I = MIN(N,J+K),J + 1,-1 - TEMP = TEMP - A(L+I,J)*X(I) - 150 CONTINUE - IF (NOUNIT) TEMP = TEMP/A(1,J) - ELSE - DO 160 I = MIN(N,J+K),J + 1,-1 - TEMP = TEMP - CONJG(A(L+I,J))*X(I) - 160 CONTINUE - IF (NOUNIT) TEMP = TEMP/CONJG(A(1,J)) - END IF - X(J) = TEMP - 170 CONTINUE - ELSE - KX = KX + (N-1)*INCX - JX = KX - DO 200 J = N,1,-1 - TEMP = X(JX) - IX = KX - L = 1 - J - IF (NOCONJ) THEN - DO 180 I = MIN(N,J+K),J + 1,-1 - TEMP = TEMP - A(L+I,J)*X(IX) - IX = IX - INCX - 180 CONTINUE - IF (NOUNIT) TEMP = TEMP/A(1,J) - ELSE - DO 190 I = MIN(N,J+K),J + 1,-1 - TEMP = TEMP - CONJG(A(L+I,J))*X(IX) - IX = IX - INCX - 190 CONTINUE - IF (NOUNIT) TEMP = TEMP/CONJG(A(1,J)) - END IF - X(JX) = TEMP - JX = JX - INCX - IF ((N-J).GE.K) KX = KX - INCX - 200 CONTINUE - END IF - END IF - END IF -* - RETURN -* -* End of CTBSV . -* - END diff --git a/gtsam/3rdparty/Eigen/blas/dtbsv.f b/gtsam/3rdparty/Eigen/blas/dtbsv.f deleted file mode 100644 index cfeb0b82b..000000000 --- a/gtsam/3rdparty/Eigen/blas/dtbsv.f +++ /dev/null @@ -1,339 +0,0 @@ - SUBROUTINE DTBSV(UPLO,TRANS,DIAG,N,K,A,LDA,X,INCX) -* .. Scalar Arguments .. - INTEGER INCX,K,LDA,N - CHARACTER DIAG,TRANS,UPLO -* .. -* .. Array Arguments .. - DOUBLE PRECISION A(LDA,*),X(*) -* .. -* -* Purpose -* ======= -* -* DTBSV solves one of the systems of equations -* -* A*x = b, or A'*x = b, -* -* where b and x are n element vectors and A is an n by n unit, or -* non-unit, upper or lower triangular band matrix, with ( k + 1 ) -* diagonals. -* -* No test for singularity or near-singularity is included in this -* routine. Such tests must be performed before calling this routine. -* -* Arguments -* ========== -* -* UPLO - CHARACTER*1. -* On entry, UPLO specifies whether the matrix is an upper or -* lower triangular matrix as follows: -* -* UPLO = 'U' or 'u' A is an upper triangular matrix. -* -* UPLO = 'L' or 'l' A is a lower triangular matrix. -* -* Unchanged on exit. -* -* TRANS - CHARACTER*1. -* On entry, TRANS specifies the equations to be solved as -* follows: -* -* TRANS = 'N' or 'n' A*x = b. -* -* TRANS = 'T' or 't' A'*x = b. -* -* TRANS = 'C' or 'c' A'*x = b. -* -* Unchanged on exit. -* -* DIAG - CHARACTER*1. -* On entry, DIAG specifies whether or not A is unit -* triangular as follows: -* -* DIAG = 'U' or 'u' A is assumed to be unit triangular. -* -* DIAG = 'N' or 'n' A is not assumed to be unit -* triangular. -* -* Unchanged on exit. -* -* N - INTEGER. -* On entry, N specifies the order of the matrix A. -* N must be at least zero. -* Unchanged on exit. -* -* K - INTEGER. -* On entry with UPLO = 'U' or 'u', K specifies the number of -* super-diagonals of the matrix A. -* On entry with UPLO = 'L' or 'l', K specifies the number of -* sub-diagonals of the matrix A. -* K must satisfy 0 .le. K. -* Unchanged on exit. -* -* A - DOUBLE PRECISION array of DIMENSION ( LDA, n ). -* Before entry with UPLO = 'U' or 'u', the leading ( k + 1 ) -* by n part of the array A must contain the upper triangular -* band part of the matrix of coefficients, supplied column by -* column, with the leading diagonal of the matrix in row -* ( k + 1 ) of the array, the first super-diagonal starting at -* position 2 in row k, and so on. The top left k by k triangle -* of the array A is not referenced. -* The following program segment will transfer an upper -* triangular band matrix from conventional full matrix storage -* to band storage: -* -* DO 20, J = 1, N -* M = K + 1 - J -* DO 10, I = MAX( 1, J - K ), J -* A( M + I, J ) = matrix( I, J ) -* 10 CONTINUE -* 20 CONTINUE -* -* Before entry with UPLO = 'L' or 'l', the leading ( k + 1 ) -* by n part of the array A must contain the lower triangular -* band part of the matrix of coefficients, supplied column by -* column, with the leading diagonal of the matrix in row 1 of -* the array, the first sub-diagonal starting at position 1 in -* row 2, and so on. The bottom right k by k triangle of the -* array A is not referenced. -* The following program segment will transfer a lower -* triangular band matrix from conventional full matrix storage -* to band storage: -* -* DO 20, J = 1, N -* M = 1 - J -* DO 10, I = J, MIN( N, J + K ) -* A( M + I, J ) = matrix( I, J ) -* 10 CONTINUE -* 20 CONTINUE -* -* Note that when DIAG = 'U' or 'u' the elements of the array A -* corresponding to the diagonal elements of the matrix are not -* referenced, but are assumed to be unity. -* Unchanged on exit. -* -* LDA - INTEGER. -* On entry, LDA specifies the first dimension of A as declared -* in the calling (sub) program. LDA must be at least -* ( k + 1 ). -* Unchanged on exit. -* -* X - DOUBLE PRECISION array of dimension at least -* ( 1 + ( n - 1 )*abs( INCX ) ). -* Before entry, the incremented array X must contain the n -* element right-hand side vector b. On exit, X is overwritten -* with the solution vector x. -* -* INCX - INTEGER. -* On entry, INCX specifies the increment for the elements of -* X. INCX must not be zero. -* Unchanged on exit. -* -* Further Details -* =============== -* -* Level 2 Blas routine. -* -* -- Written on 22-October-1986. -* Jack Dongarra, Argonne National Lab. -* Jeremy Du Croz, Nag Central Office. -* Sven Hammarling, Nag Central Office. -* Richard Hanson, Sandia National Labs. -* -* ===================================================================== -* -* .. Parameters .. - DOUBLE PRECISION ZERO - PARAMETER (ZERO=0.0D+0) -* .. -* .. Local Scalars .. - DOUBLE PRECISION TEMP - INTEGER I,INFO,IX,J,JX,KPLUS1,KX,L - LOGICAL NOUNIT -* .. -* .. External Functions .. - LOGICAL LSAME - EXTERNAL LSAME -* .. -* .. External Subroutines .. - EXTERNAL XERBLA -* .. -* .. Intrinsic Functions .. - INTRINSIC MAX,MIN -* .. -* -* Test the input parameters. -* - INFO = 0 - IF (.NOT.LSAME(UPLO,'U') .AND. .NOT.LSAME(UPLO,'L')) THEN - INFO = 1 - ELSE IF (.NOT.LSAME(TRANS,'N') .AND. .NOT.LSAME(TRANS,'T') .AND. - + .NOT.LSAME(TRANS,'C')) THEN - INFO = 2 - ELSE IF (.NOT.LSAME(DIAG,'U') .AND. .NOT.LSAME(DIAG,'N')) THEN - INFO = 3 - ELSE IF (N.LT.0) THEN - INFO = 4 - ELSE IF (K.LT.0) THEN - INFO = 5 - ELSE IF (LDA.LT. (K+1)) THEN - INFO = 7 - ELSE IF (INCX.EQ.0) THEN - INFO = 9 - END IF - IF (INFO.NE.0) THEN - CALL XERBLA('DTBSV ',INFO) - RETURN - END IF -* -* Quick return if possible. -* - IF (N.EQ.0) RETURN -* - NOUNIT = LSAME(DIAG,'N') -* -* Set up the start point in X if the increment is not unity. This -* will be ( N - 1 )*INCX too small for descending loops. -* - IF (INCX.LE.0) THEN - KX = 1 - (N-1)*INCX - ELSE IF (INCX.NE.1) THEN - KX = 1 - END IF -* -* Start the operations. In this version the elements of A are -* accessed by sequentially with one pass through A. -* - IF (LSAME(TRANS,'N')) THEN -* -* Form x := inv( A )*x. -* - IF (LSAME(UPLO,'U')) THEN - KPLUS1 = K + 1 - IF (INCX.EQ.1) THEN - DO 20 J = N,1,-1 - IF (X(J).NE.ZERO) THEN - L = KPLUS1 - J - IF (NOUNIT) X(J) = X(J)/A(KPLUS1,J) - TEMP = X(J) - DO 10 I = J - 1,MAX(1,J-K),-1 - X(I) = X(I) - TEMP*A(L+I,J) - 10 CONTINUE - END IF - 20 CONTINUE - ELSE - KX = KX + (N-1)*INCX - JX = KX - DO 40 J = N,1,-1 - KX = KX - INCX - IF (X(JX).NE.ZERO) THEN - IX = KX - L = KPLUS1 - J - IF (NOUNIT) X(JX) = X(JX)/A(KPLUS1,J) - TEMP = X(JX) - DO 30 I = J - 1,MAX(1,J-K),-1 - X(IX) = X(IX) - TEMP*A(L+I,J) - IX = IX - INCX - 30 CONTINUE - END IF - JX = JX - INCX - 40 CONTINUE - END IF - ELSE - IF (INCX.EQ.1) THEN - DO 60 J = 1,N - IF (X(J).NE.ZERO) THEN - L = 1 - J - IF (NOUNIT) X(J) = X(J)/A(1,J) - TEMP = X(J) - DO 50 I = J + 1,MIN(N,J+K) - X(I) = X(I) - TEMP*A(L+I,J) - 50 CONTINUE - END IF - 60 CONTINUE - ELSE - JX = KX - DO 80 J = 1,N - KX = KX + INCX - IF (X(JX).NE.ZERO) THEN - IX = KX - L = 1 - J - IF (NOUNIT) X(JX) = X(JX)/A(1,J) - TEMP = X(JX) - DO 70 I = J + 1,MIN(N,J+K) - X(IX) = X(IX) - TEMP*A(L+I,J) - IX = IX + INCX - 70 CONTINUE - END IF - JX = JX + INCX - 80 CONTINUE - END IF - END IF - ELSE -* -* Form x := inv( A')*x. -* - IF (LSAME(UPLO,'U')) THEN - KPLUS1 = K + 1 - IF (INCX.EQ.1) THEN - DO 100 J = 1,N - TEMP = X(J) - L = KPLUS1 - J - DO 90 I = MAX(1,J-K),J - 1 - TEMP = TEMP - A(L+I,J)*X(I) - 90 CONTINUE - IF (NOUNIT) TEMP = TEMP/A(KPLUS1,J) - X(J) = TEMP - 100 CONTINUE - ELSE - JX = KX - DO 120 J = 1,N - TEMP = X(JX) - IX = KX - L = KPLUS1 - J - DO 110 I = MAX(1,J-K),J - 1 - TEMP = TEMP - A(L+I,J)*X(IX) - IX = IX + INCX - 110 CONTINUE - IF (NOUNIT) TEMP = TEMP/A(KPLUS1,J) - X(JX) = TEMP - JX = JX + INCX - IF (J.GT.K) KX = KX + INCX - 120 CONTINUE - END IF - ELSE - IF (INCX.EQ.1) THEN - DO 140 J = N,1,-1 - TEMP = X(J) - L = 1 - J - DO 130 I = MIN(N,J+K),J + 1,-1 - TEMP = TEMP - A(L+I,J)*X(I) - 130 CONTINUE - IF (NOUNIT) TEMP = TEMP/A(1,J) - X(J) = TEMP - 140 CONTINUE - ELSE - KX = KX + (N-1)*INCX - JX = KX - DO 160 J = N,1,-1 - TEMP = X(JX) - IX = KX - L = 1 - J - DO 150 I = MIN(N,J+K),J + 1,-1 - TEMP = TEMP - A(L+I,J)*X(IX) - IX = IX - INCX - 150 CONTINUE - IF (NOUNIT) TEMP = TEMP/A(1,J) - X(JX) = TEMP - JX = JX - INCX - IF ((N-J).GE.K) KX = KX - INCX - 160 CONTINUE - END IF - END IF - END IF -* - RETURN -* -* End of DTBSV . -* - END diff --git a/gtsam/3rdparty/Eigen/blas/level2_impl.h b/gtsam/3rdparty/Eigen/blas/level2_impl.h index 8cbc2f424..46a3e7005 100644 --- a/gtsam/3rdparty/Eigen/blas/level2_impl.h +++ b/gtsam/3rdparty/Eigen/blas/level2_impl.h @@ -151,21 +151,21 @@ int EIGEN_BLAS_FUNC(trmv)(char *uplo, char *opa, char *diag, int *n, RealScalar for(int k=0; k<16; ++k) func[k] = 0; - func[NOTR | (UP << 2) | (NUNIT << 3)] = (internal::product_triangular_matrix_vector::run); - func[TR | (UP << 2) | (NUNIT << 3)] = (internal::product_triangular_matrix_vector::run); - func[ADJ | (UP << 2) | (NUNIT << 3)] = (internal::product_triangular_matrix_vector::run); + func[NOTR | (UP << 2) | (NUNIT << 3)] = (internal::triangular_matrix_vector_product::run); + func[TR | (UP << 2) | (NUNIT << 3)] = (internal::triangular_matrix_vector_product::run); + func[ADJ | (UP << 2) | (NUNIT << 3)] = (internal::triangular_matrix_vector_product::run); - func[NOTR | (LO << 2) | (NUNIT << 3)] = (internal::product_triangular_matrix_vector::run); - func[TR | (LO << 2) | (NUNIT << 3)] = (internal::product_triangular_matrix_vector::run); - func[ADJ | (LO << 2) | (NUNIT << 3)] = (internal::product_triangular_matrix_vector::run); + func[NOTR | (LO << 2) | (NUNIT << 3)] = (internal::triangular_matrix_vector_product::run); + func[TR | (LO << 2) | (NUNIT << 3)] = (internal::triangular_matrix_vector_product::run); + func[ADJ | (LO << 2) | (NUNIT << 3)] = (internal::triangular_matrix_vector_product::run); - func[NOTR | (UP << 2) | (UNIT << 3)] = (internal::product_triangular_matrix_vector::run); - func[TR | (UP << 2) | (UNIT << 3)] = (internal::product_triangular_matrix_vector::run); - func[ADJ | (UP << 2) | (UNIT << 3)] = (internal::product_triangular_matrix_vector::run); + func[NOTR | (UP << 2) | (UNIT << 3)] = (internal::triangular_matrix_vector_product::run); + func[TR | (UP << 2) | (UNIT << 3)] = (internal::triangular_matrix_vector_product::run); + func[ADJ | (UP << 2) | (UNIT << 3)] = (internal::triangular_matrix_vector_product::run); - func[NOTR | (LO << 2) | (UNIT << 3)] = (internal::product_triangular_matrix_vector::run); - func[TR | (LO << 2) | (UNIT << 3)] = (internal::product_triangular_matrix_vector::run); - func[ADJ | (LO << 2) | (UNIT << 3)] = (internal::product_triangular_matrix_vector::run); + func[NOTR | (LO << 2) | (UNIT << 3)] = (internal::triangular_matrix_vector_product::run); + func[TR | (LO << 2) | (UNIT << 3)] = (internal::triangular_matrix_vector_product::run); + func[ADJ | (LO << 2) | (UNIT << 3)] = (internal::triangular_matrix_vector_product::run); init = true; } @@ -271,6 +271,7 @@ int EIGEN_BLAS_FUNC(gbmv)(char *trans, int *m, int *n, int *kl, int *ku, RealSca return 0; } +#if 0 /** TBMV performs one of the matrix-vector operations * * x := A*x, or x := A'*x, @@ -278,10 +279,56 @@ int EIGEN_BLAS_FUNC(gbmv)(char *trans, int *m, int *n, int *kl, int *ku, RealSca * where x is an n element vector and A is an n by n unit, or non-unit, * upper or lower triangular band matrix, with ( k + 1 ) diagonals. */ -// int EIGEN_BLAS_FUNC(tbmv)(char *uplo, char *trans, char *diag, int *n, int *k, RealScalar *a, int *lda, RealScalar *x, int *incx) -// { -// return 1; -// } +int EIGEN_BLAS_FUNC(tbmv)(char *uplo, char *opa, char *diag, int *n, int *k, RealScalar *pa, int *lda, RealScalar *px, int *incx) +{ + Scalar* a = reinterpret_cast(pa); + Scalar* x = reinterpret_cast(px); + int coeff_rows = *k + 1; + + int info = 0; + if(UPLO(*uplo)==INVALID) info = 1; + else if(OP(*opa)==INVALID) info = 2; + else if(DIAG(*diag)==INVALID) info = 3; + else if(*n<0) info = 4; + else if(*k<0) info = 5; + else if(*lda::run); + func[TR | (UP << 2) | (NUNIT << 3)] = (internal::band_solve_triangular_selector::run); + func[ADJ | (UP << 2) | (NUNIT << 3)] = (internal::band_solve_triangular_selector::run); + + func[NOTR | (LO << 2) | (NUNIT << 3)] = (internal::band_solve_triangular_selector::run); + func[TR | (LO << 2) | (NUNIT << 3)] = (internal::band_solve_triangular_selector::run); + func[ADJ | (LO << 2) | (NUNIT << 3)] = (internal::band_solve_triangular_selector::run); + + func[NOTR | (UP << 2) | (UNIT << 3)] = (internal::band_solve_triangular_selector::run); + func[TR | (UP << 2) | (UNIT << 3)] = (internal::band_solve_triangular_selector::run); + func[ADJ | (UP << 2) | (UNIT << 3)] = (internal::band_solve_triangular_selector::run); + + func[NOTR | (LO << 2) | (UNIT << 3)] = (internal::band_solve_triangular_selector::run); + func[TR | (LO << 2) | (UNIT << 3)] = (internal::band_solve_triangular_selector::run); + func[ADJ | (LO << 2) | (UNIT << 3)] = (internal::band_solve_triangular_selector::run); + + init = true; + } + + Scalar* a = reinterpret_cast(pa); + Scalar* x = reinterpret_cast(px); + int coeff_rows = *k+1; + + int info = 0; + if(UPLO(*uplo)==INVALID) info = 1; + else if(OP(*op)==INVALID) info = 2; + else if(DIAG(*diag)==INVALID) info = 3; + else if(*n<0) info = 4; + else if(*k<0) info = 5; + else if(*lda=16 || func[code]==0) + return 0; + + func[code](*n, *k, a, *lda, actual_x); + + if(actual_x!=x) delete[] copy_back(actual_x,x,actual_n,*incx); + + return 0; +} /** DTPMV performs one of the matrix-vector operations * diff --git a/gtsam/3rdparty/Eigen/blas/level3_impl.h b/gtsam/3rdparty/Eigen/blas/level3_impl.h index 0a3aa98b8..4f4f39080 100644 --- a/gtsam/3rdparty/Eigen/blas/level3_impl.h +++ b/gtsam/3rdparty/Eigen/blas/level3_impl.h @@ -81,7 +81,7 @@ int EIGEN_BLAS_FUNC(gemm)(char *opa, char *opb, int *m, int *n, int *k, RealScal int EIGEN_BLAS_FUNC(trsm)(char *side, char *uplo, char *opa, char *diag, int *m, int *n, RealScalar *palpha, RealScalar *pa, int *lda, RealScalar *pb, int *ldb) { // std::cerr << "in trsm " << *side << " " << *uplo << " " << *opa << " " << *diag << " " << *m << "," << *n << " " << *palpha << " " << *lda << " " << *ldb<< "\n"; - typedef void (*functype)(DenseIndex, DenseIndex, const Scalar *, DenseIndex, Scalar *, DenseIndex); + typedef void (*functype)(DenseIndex, DenseIndex, const Scalar *, DenseIndex, Scalar *, DenseIndex, internal::level3_blocking&); static functype func[32]; static bool init = false; @@ -143,11 +143,17 @@ int EIGEN_BLAS_FUNC(trsm)(char *side, char *uplo, char *opa, char *diag, int *m, return xerbla_(SCALAR_SUFFIX_UP"TRSM ",&info,6); int code = OP(*opa) | (SIDE(*side) << 2) | (UPLO(*uplo) << 3) | (DIAG(*diag) << 4); - + if(SIDE(*side)==LEFT) - func[code](*m, *n, a, *lda, b, *ldb); + { + internal::gemm_blocking_space blocking(*m,*n,*m); + func[code](*m, *n, a, *lda, b, *ldb, blocking); + } else - func[code](*n, *m, a, *lda, b, *ldb); + { + internal::gemm_blocking_space blocking(*m,*n,*n); + func[code](*n, *m, a, *lda, b, *ldb, blocking); + } if(alpha!=Scalar(1)) matrix(b,*m,*n,*ldb) *= alpha; diff --git a/gtsam/3rdparty/Eigen/blas/stbsv.f b/gtsam/3rdparty/Eigen/blas/stbsv.f deleted file mode 100644 index b846be85c..000000000 --- a/gtsam/3rdparty/Eigen/blas/stbsv.f +++ /dev/null @@ -1,339 +0,0 @@ - SUBROUTINE STBSV(UPLO,TRANS,DIAG,N,K,A,LDA,X,INCX) -* .. Scalar Arguments .. - INTEGER INCX,K,LDA,N - CHARACTER DIAG,TRANS,UPLO -* .. -* .. Array Arguments .. - REAL A(LDA,*),X(*) -* .. -* -* Purpose -* ======= -* -* STBSV solves one of the systems of equations -* -* A*x = b, or A'*x = b, -* -* where b and x are n element vectors and A is an n by n unit, or -* non-unit, upper or lower triangular band matrix, with ( k + 1 ) -* diagonals. -* -* No test for singularity or near-singularity is included in this -* routine. Such tests must be performed before calling this routine. -* -* Arguments -* ========== -* -* UPLO - CHARACTER*1. -* On entry, UPLO specifies whether the matrix is an upper or -* lower triangular matrix as follows: -* -* UPLO = 'U' or 'u' A is an upper triangular matrix. -* -* UPLO = 'L' or 'l' A is a lower triangular matrix. -* -* Unchanged on exit. -* -* TRANS - CHARACTER*1. -* On entry, TRANS specifies the equations to be solved as -* follows: -* -* TRANS = 'N' or 'n' A*x = b. -* -* TRANS = 'T' or 't' A'*x = b. -* -* TRANS = 'C' or 'c' A'*x = b. -* -* Unchanged on exit. -* -* DIAG - CHARACTER*1. -* On entry, DIAG specifies whether or not A is unit -* triangular as follows: -* -* DIAG = 'U' or 'u' A is assumed to be unit triangular. -* -* DIAG = 'N' or 'n' A is not assumed to be unit -* triangular. -* -* Unchanged on exit. -* -* N - INTEGER. -* On entry, N specifies the order of the matrix A. -* N must be at least zero. -* Unchanged on exit. -* -* K - INTEGER. -* On entry with UPLO = 'U' or 'u', K specifies the number of -* super-diagonals of the matrix A. -* On entry with UPLO = 'L' or 'l', K specifies the number of -* sub-diagonals of the matrix A. -* K must satisfy 0 .le. K. -* Unchanged on exit. -* -* A - REAL array of DIMENSION ( LDA, n ). -* Before entry with UPLO = 'U' or 'u', the leading ( k + 1 ) -* by n part of the array A must contain the upper triangular -* band part of the matrix of coefficients, supplied column by -* column, with the leading diagonal of the matrix in row -* ( k + 1 ) of the array, the first super-diagonal starting at -* position 2 in row k, and so on. The top left k by k triangle -* of the array A is not referenced. -* The following program segment will transfer an upper -* triangular band matrix from conventional full matrix storage -* to band storage: -* -* DO 20, J = 1, N -* M = K + 1 - J -* DO 10, I = MAX( 1, J - K ), J -* A( M + I, J ) = matrix( I, J ) -* 10 CONTINUE -* 20 CONTINUE -* -* Before entry with UPLO = 'L' or 'l', the leading ( k + 1 ) -* by n part of the array A must contain the lower triangular -* band part of the matrix of coefficients, supplied column by -* column, with the leading diagonal of the matrix in row 1 of -* the array, the first sub-diagonal starting at position 1 in -* row 2, and so on. The bottom right k by k triangle of the -* array A is not referenced. -* The following program segment will transfer a lower -* triangular band matrix from conventional full matrix storage -* to band storage: -* -* DO 20, J = 1, N -* M = 1 - J -* DO 10, I = J, MIN( N, J + K ) -* A( M + I, J ) = matrix( I, J ) -* 10 CONTINUE -* 20 CONTINUE -* -* Note that when DIAG = 'U' or 'u' the elements of the array A -* corresponding to the diagonal elements of the matrix are not -* referenced, but are assumed to be unity. -* Unchanged on exit. -* -* LDA - INTEGER. -* On entry, LDA specifies the first dimension of A as declared -* in the calling (sub) program. LDA must be at least -* ( k + 1 ). -* Unchanged on exit. -* -* X - REAL array of dimension at least -* ( 1 + ( n - 1 )*abs( INCX ) ). -* Before entry, the incremented array X must contain the n -* element right-hand side vector b. On exit, X is overwritten -* with the solution vector x. -* -* INCX - INTEGER. -* On entry, INCX specifies the increment for the elements of -* X. INCX must not be zero. -* Unchanged on exit. -* -* Further Details -* =============== -* -* Level 2 Blas routine. -* -* -- Written on 22-October-1986. -* Jack Dongarra, Argonne National Lab. -* Jeremy Du Croz, Nag Central Office. -* Sven Hammarling, Nag Central Office. -* Richard Hanson, Sandia National Labs. -* -* ===================================================================== -* -* .. Parameters .. - REAL ZERO - PARAMETER (ZERO=0.0E+0) -* .. -* .. Local Scalars .. - REAL TEMP - INTEGER I,INFO,IX,J,JX,KPLUS1,KX,L - LOGICAL NOUNIT -* .. -* .. External Functions .. - LOGICAL LSAME - EXTERNAL LSAME -* .. -* .. External Subroutines .. - EXTERNAL XERBLA -* .. -* .. Intrinsic Functions .. - INTRINSIC MAX,MIN -* .. -* -* Test the input parameters. -* - INFO = 0 - IF (.NOT.LSAME(UPLO,'U') .AND. .NOT.LSAME(UPLO,'L')) THEN - INFO = 1 - ELSE IF (.NOT.LSAME(TRANS,'N') .AND. .NOT.LSAME(TRANS,'T') .AND. - + .NOT.LSAME(TRANS,'C')) THEN - INFO = 2 - ELSE IF (.NOT.LSAME(DIAG,'U') .AND. .NOT.LSAME(DIAG,'N')) THEN - INFO = 3 - ELSE IF (N.LT.0) THEN - INFO = 4 - ELSE IF (K.LT.0) THEN - INFO = 5 - ELSE IF (LDA.LT. (K+1)) THEN - INFO = 7 - ELSE IF (INCX.EQ.0) THEN - INFO = 9 - END IF - IF (INFO.NE.0) THEN - CALL XERBLA('STBSV ',INFO) - RETURN - END IF -* -* Quick return if possible. -* - IF (N.EQ.0) RETURN -* - NOUNIT = LSAME(DIAG,'N') -* -* Set up the start point in X if the increment is not unity. This -* will be ( N - 1 )*INCX too small for descending loops. -* - IF (INCX.LE.0) THEN - KX = 1 - (N-1)*INCX - ELSE IF (INCX.NE.1) THEN - KX = 1 - END IF -* -* Start the operations. In this version the elements of A are -* accessed by sequentially with one pass through A. -* - IF (LSAME(TRANS,'N')) THEN -* -* Form x := inv( A )*x. -* - IF (LSAME(UPLO,'U')) THEN - KPLUS1 = K + 1 - IF (INCX.EQ.1) THEN - DO 20 J = N,1,-1 - IF (X(J).NE.ZERO) THEN - L = KPLUS1 - J - IF (NOUNIT) X(J) = X(J)/A(KPLUS1,J) - TEMP = X(J) - DO 10 I = J - 1,MAX(1,J-K),-1 - X(I) = X(I) - TEMP*A(L+I,J) - 10 CONTINUE - END IF - 20 CONTINUE - ELSE - KX = KX + (N-1)*INCX - JX = KX - DO 40 J = N,1,-1 - KX = KX - INCX - IF (X(JX).NE.ZERO) THEN - IX = KX - L = KPLUS1 - J - IF (NOUNIT) X(JX) = X(JX)/A(KPLUS1,J) - TEMP = X(JX) - DO 30 I = J - 1,MAX(1,J-K),-1 - X(IX) = X(IX) - TEMP*A(L+I,J) - IX = IX - INCX - 30 CONTINUE - END IF - JX = JX - INCX - 40 CONTINUE - END IF - ELSE - IF (INCX.EQ.1) THEN - DO 60 J = 1,N - IF (X(J).NE.ZERO) THEN - L = 1 - J - IF (NOUNIT) X(J) = X(J)/A(1,J) - TEMP = X(J) - DO 50 I = J + 1,MIN(N,J+K) - X(I) = X(I) - TEMP*A(L+I,J) - 50 CONTINUE - END IF - 60 CONTINUE - ELSE - JX = KX - DO 80 J = 1,N - KX = KX + INCX - IF (X(JX).NE.ZERO) THEN - IX = KX - L = 1 - J - IF (NOUNIT) X(JX) = X(JX)/A(1,J) - TEMP = X(JX) - DO 70 I = J + 1,MIN(N,J+K) - X(IX) = X(IX) - TEMP*A(L+I,J) - IX = IX + INCX - 70 CONTINUE - END IF - JX = JX + INCX - 80 CONTINUE - END IF - END IF - ELSE -* -* Form x := inv( A')*x. -* - IF (LSAME(UPLO,'U')) THEN - KPLUS1 = K + 1 - IF (INCX.EQ.1) THEN - DO 100 J = 1,N - TEMP = X(J) - L = KPLUS1 - J - DO 90 I = MAX(1,J-K),J - 1 - TEMP = TEMP - A(L+I,J)*X(I) - 90 CONTINUE - IF (NOUNIT) TEMP = TEMP/A(KPLUS1,J) - X(J) = TEMP - 100 CONTINUE - ELSE - JX = KX - DO 120 J = 1,N - TEMP = X(JX) - IX = KX - L = KPLUS1 - J - DO 110 I = MAX(1,J-K),J - 1 - TEMP = TEMP - A(L+I,J)*X(IX) - IX = IX + INCX - 110 CONTINUE - IF (NOUNIT) TEMP = TEMP/A(KPLUS1,J) - X(JX) = TEMP - JX = JX + INCX - IF (J.GT.K) KX = KX + INCX - 120 CONTINUE - END IF - ELSE - IF (INCX.EQ.1) THEN - DO 140 J = N,1,-1 - TEMP = X(J) - L = 1 - J - DO 130 I = MIN(N,J+K),J + 1,-1 - TEMP = TEMP - A(L+I,J)*X(I) - 130 CONTINUE - IF (NOUNIT) TEMP = TEMP/A(1,J) - X(J) = TEMP - 140 CONTINUE - ELSE - KX = KX + (N-1)*INCX - JX = KX - DO 160 J = N,1,-1 - TEMP = X(JX) - IX = KX - L = 1 - J - DO 150 I = MIN(N,J+K),J + 1,-1 - TEMP = TEMP - A(L+I,J)*X(IX) - IX = IX - INCX - 150 CONTINUE - IF (NOUNIT) TEMP = TEMP/A(1,J) - X(JX) = TEMP - JX = JX - INCX - IF ((N-J).GE.K) KX = KX - INCX - 160 CONTINUE - END IF - END IF - END IF -* - RETURN -* -* End of STBSV . -* - END diff --git a/gtsam/3rdparty/Eigen/blas/testing/runblastest.sh b/gtsam/3rdparty/Eigen/blas/testing/runblastest.sh index aa634a2ce..4ffaf0111 100755 --- a/gtsam/3rdparty/Eigen/blas/testing/runblastest.sh +++ b/gtsam/3rdparty/Eigen/blas/testing/runblastest.sh @@ -27,11 +27,17 @@ else if [ -f $1.summ ]; then if [ `grep "FATAL ERROR" $1.summ | wc -l` -gt 0 ]; then echo -e $red "Test $1 failed (FATAL ERROR, read the file $1.summ for details)" $black + echo -e $blue + cat .runtest.log + echo -e $black exit 1; fi if [ `grep "FAILED THE TESTS OF ERROR-EXITS" $1.summ | wc -l` -gt 0 ]; then echo -e $red "Test $1 failed (FAILED THE TESTS OF ERROR-EXITS, read the file $1.summ for details)" $black + echo -e $blue + cat .runtest.log + echo -e $black exit 1; fi fi diff --git a/gtsam/3rdparty/Eigen/blas/xerbla.cpp b/gtsam/3rdparty/Eigen/blas/xerbla.cpp index bda1d2f46..0d57710fe 100644 --- a/gtsam/3rdparty/Eigen/blas/xerbla.cpp +++ b/gtsam/3rdparty/Eigen/blas/xerbla.cpp @@ -1,12 +1,18 @@ #include +#if (defined __GNUC__) +#define EIGEN_WEAK_LINKING __attribute__ ((weak)) +#else +#define EIGEN_WEAK_LINKING +#endif + #ifdef __cplusplus extern "C" { #endif -int xerbla_(const char * msg, int *info, int) +EIGEN_WEAK_LINKING int xerbla_(const char * msg, int *info, int) { std::cerr << "Eigen BLAS ERROR #" << *info << ": " << msg << "\n"; return 0; diff --git a/gtsam/3rdparty/Eigen/blas/ztbsv.f b/gtsam/3rdparty/Eigen/blas/ztbsv.f deleted file mode 100644 index 42b234a77..000000000 --- a/gtsam/3rdparty/Eigen/blas/ztbsv.f +++ /dev/null @@ -1,370 +0,0 @@ - SUBROUTINE ZTBSV(UPLO,TRANS,DIAG,N,K,A,LDA,X,INCX) -* .. Scalar Arguments .. - INTEGER INCX,K,LDA,N - CHARACTER DIAG,TRANS,UPLO -* .. -* .. Array Arguments .. - DOUBLE COMPLEX A(LDA,*),X(*) -* .. -* -* Purpose -* ======= -* -* ZTBSV solves one of the systems of equations -* -* A*x = b, or A'*x = b, or conjg( A' )*x = b, -* -* where b and x are n element vectors and A is an n by n unit, or -* non-unit, upper or lower triangular band matrix, with ( k + 1 ) -* diagonals. -* -* No test for singularity or near-singularity is included in this -* routine. Such tests must be performed before calling this routine. -* -* Arguments -* ========== -* -* UPLO - CHARACTER*1. -* On entry, UPLO specifies whether the matrix is an upper or -* lower triangular matrix as follows: -* -* UPLO = 'U' or 'u' A is an upper triangular matrix. -* -* UPLO = 'L' or 'l' A is a lower triangular matrix. -* -* Unchanged on exit. -* -* TRANS - CHARACTER*1. -* On entry, TRANS specifies the equations to be solved as -* follows: -* -* TRANS = 'N' or 'n' A*x = b. -* -* TRANS = 'T' or 't' A'*x = b. -* -* TRANS = 'C' or 'c' conjg( A' )*x = b. -* -* Unchanged on exit. -* -* DIAG - CHARACTER*1. -* On entry, DIAG specifies whether or not A is unit -* triangular as follows: -* -* DIAG = 'U' or 'u' A is assumed to be unit triangular. -* -* DIAG = 'N' or 'n' A is not assumed to be unit -* triangular. -* -* Unchanged on exit. -* -* N - INTEGER. -* On entry, N specifies the order of the matrix A. -* N must be at least zero. -* Unchanged on exit. -* -* K - INTEGER. -* On entry with UPLO = 'U' or 'u', K specifies the number of -* super-diagonals of the matrix A. -* On entry with UPLO = 'L' or 'l', K specifies the number of -* sub-diagonals of the matrix A. -* K must satisfy 0 .le. K. -* Unchanged on exit. -* -* A - COMPLEX*16 array of DIMENSION ( LDA, n ). -* Before entry with UPLO = 'U' or 'u', the leading ( k + 1 ) -* by n part of the array A must contain the upper triangular -* band part of the matrix of coefficients, supplied column by -* column, with the leading diagonal of the matrix in row -* ( k + 1 ) of the array, the first super-diagonal starting at -* position 2 in row k, and so on. The top left k by k triangle -* of the array A is not referenced. -* The following program segment will transfer an upper -* triangular band matrix from conventional full matrix storage -* to band storage: -* -* DO 20, J = 1, N -* M = K + 1 - J -* DO 10, I = MAX( 1, J - K ), J -* A( M + I, J ) = matrix( I, J ) -* 10 CONTINUE -* 20 CONTINUE -* -* Before entry with UPLO = 'L' or 'l', the leading ( k + 1 ) -* by n part of the array A must contain the lower triangular -* band part of the matrix of coefficients, supplied column by -* column, with the leading diagonal of the matrix in row 1 of -* the array, the first sub-diagonal starting at position 1 in -* row 2, and so on. The bottom right k by k triangle of the -* array A is not referenced. -* The following program segment will transfer a lower -* triangular band matrix from conventional full matrix storage -* to band storage: -* -* DO 20, J = 1, N -* M = 1 - J -* DO 10, I = J, MIN( N, J + K ) -* A( M + I, J ) = matrix( I, J ) -* 10 CONTINUE -* 20 CONTINUE -* -* Note that when DIAG = 'U' or 'u' the elements of the array A -* corresponding to the diagonal elements of the matrix are not -* referenced, but are assumed to be unity. -* Unchanged on exit. -* -* LDA - INTEGER. -* On entry, LDA specifies the first dimension of A as declared -* in the calling (sub) program. LDA must be at least -* ( k + 1 ). -* Unchanged on exit. -* -* X - COMPLEX*16 array of dimension at least -* ( 1 + ( n - 1 )*abs( INCX ) ). -* Before entry, the incremented array X must contain the n -* element right-hand side vector b. On exit, X is overwritten -* with the solution vector x. -* -* INCX - INTEGER. -* On entry, INCX specifies the increment for the elements of -* X. INCX must not be zero. -* Unchanged on exit. -* -* Further Details -* =============== -* -* Level 2 Blas routine. -* -* -- Written on 22-October-1986. -* Jack Dongarra, Argonne National Lab. -* Jeremy Du Croz, Nag Central Office. -* Sven Hammarling, Nag Central Office. -* Richard Hanson, Sandia National Labs. -* -* ===================================================================== -* -* .. Parameters .. - DOUBLE COMPLEX ZERO - PARAMETER (ZERO= (0.0D+0,0.0D+0)) -* .. -* .. Local Scalars .. - DOUBLE COMPLEX TEMP - INTEGER I,INFO,IX,J,JX,KPLUS1,KX,L - LOGICAL NOCONJ,NOUNIT -* .. -* .. External Functions .. - LOGICAL LSAME - EXTERNAL LSAME -* .. -* .. External Subroutines .. - EXTERNAL XERBLA -* .. -* .. Intrinsic Functions .. - INTRINSIC DCONJG,MAX,MIN -* .. -* -* Test the input parameters. -* - INFO = 0 - IF (.NOT.LSAME(UPLO,'U') .AND. .NOT.LSAME(UPLO,'L')) THEN - INFO = 1 - ELSE IF (.NOT.LSAME(TRANS,'N') .AND. .NOT.LSAME(TRANS,'T') .AND. - + .NOT.LSAME(TRANS,'C')) THEN - INFO = 2 - ELSE IF (.NOT.LSAME(DIAG,'U') .AND. .NOT.LSAME(DIAG,'N')) THEN - INFO = 3 - ELSE IF (N.LT.0) THEN - INFO = 4 - ELSE IF (K.LT.0) THEN - INFO = 5 - ELSE IF (LDA.LT. (K+1)) THEN - INFO = 7 - ELSE IF (INCX.EQ.0) THEN - INFO = 9 - END IF - IF (INFO.NE.0) THEN - CALL XERBLA('ZTBSV ',INFO) - RETURN - END IF -* -* Quick return if possible. -* - IF (N.EQ.0) RETURN -* - NOCONJ = LSAME(TRANS,'T') - NOUNIT = LSAME(DIAG,'N') -* -* Set up the start point in X if the increment is not unity. This -* will be ( N - 1 )*INCX too small for descending loops. -* - IF (INCX.LE.0) THEN - KX = 1 - (N-1)*INCX - ELSE IF (INCX.NE.1) THEN - KX = 1 - END IF -* -* Start the operations. In this version the elements of A are -* accessed by sequentially with one pass through A. -* - IF (LSAME(TRANS,'N')) THEN -* -* Form x := inv( A )*x. -* - IF (LSAME(UPLO,'U')) THEN - KPLUS1 = K + 1 - IF (INCX.EQ.1) THEN - DO 20 J = N,1,-1 - IF (X(J).NE.ZERO) THEN - L = KPLUS1 - J - IF (NOUNIT) X(J) = X(J)/A(KPLUS1,J) - TEMP = X(J) - DO 10 I = J - 1,MAX(1,J-K),-1 - X(I) = X(I) - TEMP*A(L+I,J) - 10 CONTINUE - END IF - 20 CONTINUE - ELSE - KX = KX + (N-1)*INCX - JX = KX - DO 40 J = N,1,-1 - KX = KX - INCX - IF (X(JX).NE.ZERO) THEN - IX = KX - L = KPLUS1 - J - IF (NOUNIT) X(JX) = X(JX)/A(KPLUS1,J) - TEMP = X(JX) - DO 30 I = J - 1,MAX(1,J-K),-1 - X(IX) = X(IX) - TEMP*A(L+I,J) - IX = IX - INCX - 30 CONTINUE - END IF - JX = JX - INCX - 40 CONTINUE - END IF - ELSE - IF (INCX.EQ.1) THEN - DO 60 J = 1,N - IF (X(J).NE.ZERO) THEN - L = 1 - J - IF (NOUNIT) X(J) = X(J)/A(1,J) - TEMP = X(J) - DO 50 I = J + 1,MIN(N,J+K) - X(I) = X(I) - TEMP*A(L+I,J) - 50 CONTINUE - END IF - 60 CONTINUE - ELSE - JX = KX - DO 80 J = 1,N - KX = KX + INCX - IF (X(JX).NE.ZERO) THEN - IX = KX - L = 1 - J - IF (NOUNIT) X(JX) = X(JX)/A(1,J) - TEMP = X(JX) - DO 70 I = J + 1,MIN(N,J+K) - X(IX) = X(IX) - TEMP*A(L+I,J) - IX = IX + INCX - 70 CONTINUE - END IF - JX = JX + INCX - 80 CONTINUE - END IF - END IF - ELSE -* -* Form x := inv( A' )*x or x := inv( conjg( A') )*x. -* - IF (LSAME(UPLO,'U')) THEN - KPLUS1 = K + 1 - IF (INCX.EQ.1) THEN - DO 110 J = 1,N - TEMP = X(J) - L = KPLUS1 - J - IF (NOCONJ) THEN - DO 90 I = MAX(1,J-K),J - 1 - TEMP = TEMP - A(L+I,J)*X(I) - 90 CONTINUE - IF (NOUNIT) TEMP = TEMP/A(KPLUS1,J) - ELSE - DO 100 I = MAX(1,J-K),J - 1 - TEMP = TEMP - DCONJG(A(L+I,J))*X(I) - 100 CONTINUE - IF (NOUNIT) TEMP = TEMP/DCONJG(A(KPLUS1,J)) - END IF - X(J) = TEMP - 110 CONTINUE - ELSE - JX = KX - DO 140 J = 1,N - TEMP = X(JX) - IX = KX - L = KPLUS1 - J - IF (NOCONJ) THEN - DO 120 I = MAX(1,J-K),J - 1 - TEMP = TEMP - A(L+I,J)*X(IX) - IX = IX + INCX - 120 CONTINUE - IF (NOUNIT) TEMP = TEMP/A(KPLUS1,J) - ELSE - DO 130 I = MAX(1,J-K),J - 1 - TEMP = TEMP - DCONJG(A(L+I,J))*X(IX) - IX = IX + INCX - 130 CONTINUE - IF (NOUNIT) TEMP = TEMP/DCONJG(A(KPLUS1,J)) - END IF - X(JX) = TEMP - JX = JX + INCX - IF (J.GT.K) KX = KX + INCX - 140 CONTINUE - END IF - ELSE - IF (INCX.EQ.1) THEN - DO 170 J = N,1,-1 - TEMP = X(J) - L = 1 - J - IF (NOCONJ) THEN - DO 150 I = MIN(N,J+K),J + 1,-1 - TEMP = TEMP - A(L+I,J)*X(I) - 150 CONTINUE - IF (NOUNIT) TEMP = TEMP/A(1,J) - ELSE - DO 160 I = MIN(N,J+K),J + 1,-1 - TEMP = TEMP - DCONJG(A(L+I,J))*X(I) - 160 CONTINUE - IF (NOUNIT) TEMP = TEMP/DCONJG(A(1,J)) - END IF - X(J) = TEMP - 170 CONTINUE - ELSE - KX = KX + (N-1)*INCX - JX = KX - DO 200 J = N,1,-1 - TEMP = X(JX) - IX = KX - L = 1 - J - IF (NOCONJ) THEN - DO 180 I = MIN(N,J+K),J + 1,-1 - TEMP = TEMP - A(L+I,J)*X(IX) - IX = IX - INCX - 180 CONTINUE - IF (NOUNIT) TEMP = TEMP/A(1,J) - ELSE - DO 190 I = MIN(N,J+K),J + 1,-1 - TEMP = TEMP - DCONJG(A(L+I,J))*X(IX) - IX = IX - INCX - 190 CONTINUE - IF (NOUNIT) TEMP = TEMP/DCONJG(A(1,J)) - END IF - X(JX) = TEMP - JX = JX - INCX - IF ((N-J).GE.K) KX = KX - INCX - 200 CONTINUE - END IF - END IF - END IF -* - RETURN -* -* End of ZTBSV . -* - END diff --git a/gtsam/3rdparty/Eigen/cmake/CMakeDetermineVSServicePack.cmake b/gtsam/3rdparty/Eigen/cmake/CMakeDetermineVSServicePack.cmake new file mode 100644 index 000000000..b89462308 --- /dev/null +++ b/gtsam/3rdparty/Eigen/cmake/CMakeDetermineVSServicePack.cmake @@ -0,0 +1,103 @@ +# - Includes a public function for assisting users in trying to determine the +# Visual Studio service pack in use. +# +# Sets the passed in variable to one of the following values or an empty +# string if unknown. +# vc80 +# vc80sp1 +# vc90 +# vc90sp1 +# +# Usage: +# =========================== +# +# if(MSVC) +# include(CMakeDetermineVSServicePack) +# DetermineVSServicePack( my_service_pack ) +# +# if( my_service_pack ) +# message(STATUS "Detected: ${my_service_pack}") +# endif() +# endif() +# +# =========================== + +#============================================================================= +# Copyright 2009-2010 Kitware, Inc. +# Copyright 2009-2010 Philip Lowman +# +# Distributed under the OSI-approved BSD License (the "License"); +# see accompanying file Copyright.txt for details. +# +# This software is distributed WITHOUT ANY WARRANTY; without even the +# implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. +# See the License for more information. +#============================================================================= +# (To distribute this file outside of CMake, substitute the full +# License text for the above reference.) + +# [INTERNAL] +# Please do not call this function directly +function(_DetermineVSServicePackFromCompiler _OUT_VAR _cl_version) + if (${_cl_version} VERSION_EQUAL "14.00.50727.42") + set(_version "vc80") + elseif(${_cl_version} VERSION_EQUAL "14.00.50727.762") + set(_version "vc80sp1") + elseif(${_cl_version} VERSION_EQUAL "15.00.21022.08") + set(_version "vc90") + elseif(${_cl_version} VERSION_EQUAL "15.00.30729.01") + set(_version "vc90sp1") + elseif(${_cl_version} VERSION_EQUAL "16.00.30319.01") + set(_version "vc100") + else() + set(_version "") + endif() + set(${_OUT_VAR} ${_version} PARENT_SCOPE) +endfunction() + +# +# A function to call to determine the Visual Studio service pack +# in use. See documentation above. +function(DetermineVSServicePack _pack) + if(NOT DETERMINED_VS_SERVICE_PACK OR NOT ${_pack}) + if(${CMAKE_BUILD_TOOL} STREQUAL "nmake") + EXECUTE_PROCESS(COMMAND ${CMAKE_CXX_COMPILER} "/?" + ERROR_VARIABLE _output) + set(DETERMINED_VS_SERVICE_PACK ${_output}) + else() + file(WRITE "${CMAKE_BINARY_DIR}/return0.cc" + "int main() { return 0; }\n") + + try_compile(DETERMINED_VS_SERVICE_PACK + "${CMAKE_BINARY_DIR}" + "${CMAKE_BINARY_DIR}/return0.cc" + OUTPUT_VARIABLE _output + COPY_FILE "${CMAKE_BINARY_DIR}/return0.cc") + + file(REMOVE "${CMAKE_BINARY_DIR}/return0.cc") + endif() + + if(DETERMINED_VS_SERVICE_PACK AND _output) + string(REGEX MATCH "Compiler Version [0-9]+.[0-9]+.[0-9]+.[0-9]+" + _cl_version "${_output}") + if(_cl_version) + string(REGEX MATCHALL "[0-9]+" + _cl_version_list "${_cl_version}") + list(GET _cl_version_list 0 _major) + list(GET _cl_version_list 1 _minor) + list(GET _cl_version_list 2 _patch) + list(GET _cl_version_list 3 _tweak) + + set(_cl_version_string ${_major}.${_minor}.${_patch}.${_tweak}) + + # Call helper function to determine VS version + _DetermineVSServicePackFromCompiler(_sp "${_cl_version_string}") + if(_sp) + #set(${_pack} "${_sp}(${_cl_version_string})" CACHE INTERNAL + set(${_pack} "${_sp}" CACHE INTERNAL + "The Visual Studio Release with Service Pack") + endif() + endif() + endif() + endif() +endfunction() diff --git a/gtsam/3rdparty/Eigen/cmake/EigenConfigureTesting.cmake b/gtsam/3rdparty/Eigen/cmake/EigenConfigureTesting.cmake new file mode 100644 index 000000000..cf8f32c01 --- /dev/null +++ b/gtsam/3rdparty/Eigen/cmake/EigenConfigureTesting.cmake @@ -0,0 +1,79 @@ +include(EigenTesting) +include(CheckCXXSourceCompiles) + +# configure the "site" and "buildname" +ei_set_sitename() + +# retrieve and store the build string +ei_set_build_string() + +add_custom_target(buildtests) +add_custom_target(check COMMAND "ctest") +add_dependencies(check buildtests) + +# check whether /bin/bash exists +find_file(EIGEN_BIN_BASH_EXISTS "/bin/bash" PATHS "/" NO_DEFAULT_PATH) + +# CMake/Ctest does not allow us to change the build command, +# so we have to workaround by directly editing the generated DartConfiguration.tcl file +# save CMAKE_MAKE_PROGRAM +set(CMAKE_MAKE_PROGRAM_SAVE ${CMAKE_MAKE_PROGRAM}) +# and set a fake one +set(CMAKE_MAKE_PROGRAM "@EIGEN_MAKECOMMAND_PLACEHOLDER@") + +# This call activates testing and generates the DartConfiguration.tcl +include(CTest) + +# overwrite default DartConfiguration.tcl +# The worarounds are different for each version of the MSVC IDE +if(MSVC_IDE) + if(MSVC_VERSION EQUAL 1600) # MSVC 2010 + set(EIGEN_MAKECOMMAND_PLACEHOLDER "${CMAKE_MAKE_PROGRAM_SAVE} buildtests.vcxproj /p:Configuration=\${CTEST_CONFIGURATION_TYPE} \n# ") + else() # MSVC 2008 (TODO check MSVC 2005) + set(EIGEN_MAKECOMMAND_PLACEHOLDER "${CMAKE_MAKE_PROGRAM_SAVE} Eigen.sln /build \"Release\" /project buildtests \n# ") + endif() +else() + # for make and nmake + set(EIGEN_MAKECOMMAND_PLACEHOLDER "${CMAKE_MAKE_PROGRAM_SAVE} buildtests") +endif() + +# copy ctest properties, which currently +# o raise the warning levels +configure_file(${CMAKE_BINARY_DIR}/DartConfiguration.tcl ${CMAKE_BINARY_DIR}/DartConfiguration.tcl) + +# restore default CMAKE_MAKE_PROGRAM +set(CMAKE_MAKE_PROGRAM ${CMAKE_MAKE_PROGRAM_SAVE}) +# un-set temporary variables so that it is like they never existed. +# CMake 2.6.3 introduces the more logical unset() syntax for this. +set(CMAKE_MAKE_PROGRAM_SAVE) +set(EIGEN_MAKECOMMAND_PLACEHOLDER) + +configure_file(${CMAKE_SOURCE_DIR}/CTestCustom.cmake.in ${CMAKE_BINARY_DIR}/CTestCustom.cmake) + +# some documentation of this function would be nice +ei_init_testing() + +# configure Eigen related testing options +option(EIGEN_NO_ASSERTION_CHECKING "Disable checking of assertions using exceptions" OFF) +option(EIGEN_DEBUG_ASSERTS "Enable advanced debuging of assertions" OFF) + +if(CMAKE_COMPILER_IS_GNUCXX) + option(EIGEN_COVERAGE_TESTING "Enable/disable gcov" OFF) + if(EIGEN_COVERAGE_TESTING) + set(COVERAGE_FLAGS "-fprofile-arcs -ftest-coverage") + set(CTEST_CUSTOM_COVERAGE_EXCLUDE "/test/") + else(EIGEN_COVERAGE_TESTING) + set(COVERAGE_FLAGS "") + endif(EIGEN_COVERAGE_TESTING) + if(EIGEN_TEST_C++0x) + set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=gnu++0x") + endif(EIGEN_TEST_C++0x) + if(CMAKE_SYSTEM_NAME MATCHES Linux) + set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} ${COVERAGE_FLAGS} -g2") + set(CMAKE_CXX_FLAGS_RELWITHDEBINFO "${CMAKE_CXX_FLAGS_RELWITHDEBINFO} ${COVERAGE_FLAGS} -O2 -g2") + set(CMAKE_CXX_FLAGS_RELEASE "${CMAKE_CXX_FLAGS_RELEASE} ${COVERAGE_FLAGS} -fno-inline-functions") + set(CMAKE_CXX_FLAGS_DEBUG "${CMAKE_CXX_FLAGS_DEBUG} ${COVERAGE_FLAGS} -O0 -g3") + endif(CMAKE_SYSTEM_NAME MATCHES Linux) +elseif(MSVC) + set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} /D_CRT_SECURE_NO_WARNINGS /D_SCL_SECURE_NO_WARNINGS") +endif(CMAKE_COMPILER_IS_GNUCXX) diff --git a/gtsam/3rdparty/Eigen/cmake/EigenDetermineOSVersion.cmake b/gtsam/3rdparty/Eigen/cmake/EigenDetermineOSVersion.cmake new file mode 100644 index 000000000..3c48d4c37 --- /dev/null +++ b/gtsam/3rdparty/Eigen/cmake/EigenDetermineOSVersion.cmake @@ -0,0 +1,46 @@ +# The utility function DetermineOSVersion aims at providing an +# improved version of the CMake variable ${CMAKE_SYSTEM} on Windows +# machines. +# +# Usage: +# include(EigenDetermineOSVersion) +# DetermineOSVersion(OS_VERSION) +# message("OS: ${OS_VERSION}") + +# - A little helper variable which should not be directly called +function(DetermineShortWindowsName WIN_VERSION win_num_version) + if (${win_num_version} VERSION_EQUAL "6.1") + set(_version "win7") + elseif(${win_num_version} VERSION_EQUAL "6.0") + set(_version "winVista") + elseif(${win_num_version} VERSION_EQUAL "5.2") + set(_version "winXpProf") + elseif(${win_num_version} VERSION_EQUAL "5.1") + set(_version "winXp") + elseif(${win_num_version} VERSION_EQUAL "5.0") + set(_version "win2000Prof") + else() + set(_version "unknownWin") + endif() + set(${WIN_VERSION} ${_version} PARENT_SCOPE) +endfunction() + +function(DetermineOSVersion OS_VERSION) + if (WIN32) + file (TO_NATIVE_PATH "$ENV{COMSPEC}" SHELL) + exec_program( ${SHELL} ARGS "/c" "ver" OUTPUT_VARIABLE ver_output) + + string(REGEX MATCHALL "[0-9]+" + ver_list "${ver_output}") + list(GET ver_list 0 _major) + list(GET ver_list 1 _minor) + + set(win_num_version ${_major}.${_minor}) + DetermineShortWindowsName(win_version "${win_num_version}") + if(win_version) + set(${OS_VERSION} ${win_version} PARENT_SCOPE) + endif() + else() + set(${OS_VERSION} ${CMAKE_SYSTEM} PARENT_SCOPE) + endif() +endfunction() diff --git a/gtsam/3rdparty/Eigen/cmake/EigenTesting.cmake b/gtsam/3rdparty/Eigen/cmake/EigenTesting.cmake index 4c8039315..266043974 100644 --- a/gtsam/3rdparty/Eigen/cmake/EigenTesting.cmake +++ b/gtsam/3rdparty/Eigen/cmake/EigenTesting.cmake @@ -1,11 +1,11 @@ -option(EIGEN_NO_ASSERTION_CHECKING "Disable checking of assertions using exceptions" OFF) -option(EIGEN_DEBUG_ASSERTS "Enable advanced debuging of assertions" OFF) - -include(CheckCXXSourceCompiles) macro(ei_add_property prop value) - get_property(previous GLOBAL PROPERTY ${prop}) - set_property(GLOBAL PROPERTY ${prop} "${previous} ${value}") + get_property(previous GLOBAL PROPERTY ${prop}) + if ((NOT previous) OR (previous STREQUAL "")) + set_property(GLOBAL PROPERTY ${prop} "${value}") + else() + set_property(GLOBAL PROPERTY ${prop} "${previous} ${value}") + endif() endmacro(ei_add_property) #internal. See documentation of ei_add_test for details. @@ -27,6 +27,8 @@ macro(ei_add_test_internal testname testname_with_suffix) ei_add_target_property(${targetname} COMPILE_FLAGS "-DEIGEN_DEBUG_ASSERTS=1") endif(EIGEN_DEBUG_ASSERTS) endif(EIGEN_NO_ASSERTION_CHECKING) + + ei_add_target_property(${targetname} COMPILE_FLAGS "-DEIGEN_TEST_MAX_SIZE=${EIGEN_TEST_MAX_SIZE}") ei_add_target_property(${targetname} COMPILE_FLAGS "-DEIGEN_TEST_FUNC=${testname}") @@ -38,6 +40,10 @@ macro(ei_add_test_internal testname testname_with_suffix) if(${ARGC} GREATER 2) ei_add_target_property(${targetname} COMPILE_FLAGS "${ARGV2}") endif(${ARGC} GREATER 2) + + if(EIGEN_TEST_CUSTOM_CXX_FLAGS) + ei_add_target_property(${targetname} COMPILE_FLAGS "${EIGEN_TEST_CUSTOM_CXX_FLAGS}") + endif() if(EIGEN_STANDARD_LIBRARIES_TO_LINK_TO) target_link_libraries(${targetname} ${EIGEN_STANDARD_LIBRARIES_TO_LINK_TO}) @@ -45,6 +51,9 @@ macro(ei_add_test_internal testname testname_with_suffix) if(EXTERNAL_LIBS) target_link_libraries(${targetname} ${EXTERNAL_LIBS}) endif() + if(EIGEN_TEST_CUSTOM_LINKER_FLAGS) + target_link_libraries(${targetname} ${EIGEN_TEST_CUSTOM_LINKER_FLAGS}) + endif() if(${ARGC} GREATER 3) set(libs_to_link ${ARGV3}) @@ -59,15 +68,11 @@ macro(ei_add_test_internal testname testname_with_suffix) endif() endif() - if(WIN32) - if(CYGWIN) - add_test(${testname_with_suffix} "${Eigen_SOURCE_DIR}/test/runtest.sh" "${testname_with_suffix}") - else(CYGWIN) - add_test(${testname_with_suffix} "${targetname}") - endif(CYGWIN) - else(WIN32) + if(EIGEN_BIN_BASH_EXISTS) add_test(${testname_with_suffix} "${Eigen_SOURCE_DIR}/test/runtest.sh" "${testname_with_suffix}") - endif(WIN32) + else() + add_test(${testname_with_suffix} "${targetname}") + endif() endmacro(ei_add_test_internal) @@ -120,9 +125,9 @@ macro(ei_add_test testname) file(READ "${testname}.cpp" test_source) set(parts 0) - string(REGEX MATCHALL "CALL_SUBTEST_[0-9]+|EIGEN_TEST_PART_[0-9]+" + string(REGEX MATCHALL "CALL_SUBTEST_[0-9]+|EIGEN_TEST_PART_[0-9]+|EIGEN_SUFFIXES(;[0-9]+)+" occurences "${test_source}") - string(REGEX REPLACE "CALL_SUBTEST_|EIGEN_TEST_PART_" "" suffixes "${occurences}") + string(REGEX REPLACE "CALL_SUBTEST_|EIGEN_TEST_PART_|EIGEN_SUFFIXES" "" suffixes "${occurences}") list(REMOVE_DUPLICATES suffixes) if(EIGEN_SPLIT_LARGE_TESTS AND suffixes) add_custom_target(${testname}) @@ -181,12 +186,13 @@ endmacro(ei_add_failtest) # print a summary of the different options macro(ei_testing_print_summary) - message(STATUS "************************************************************") message(STATUS "*** Eigen's unit tests configuration summary ***") message(STATUS "************************************************************") message(STATUS "") message(STATUS "Build type: ${CMAKE_BUILD_TYPE}") + message(STATUS "Build site: ${SITE}") + message(STATUS "Build string: ${BUILDNAME}") get_property(EIGEN_TESTING_SUMMARY GLOBAL PROPERTY EIGEN_TESTING_SUMMARY) get_property(EIGEN_TESTED_BACKENDS GLOBAL PROPERTY EIGEN_TESTED_BACKENDS) get_property(EIGEN_MISSING_BACKENDS GLOBAL PROPERTY EIGEN_MISSING_BACKENDS) @@ -204,6 +210,8 @@ macro(ei_testing_print_summary) elseif(EIGEN_TEST_NO_EXPLICIT_VECTORIZATION) message(STATUS "Explicit vectorization disabled (alignment kept enabled)") else() + + message(STATUS "Maximal matrix/vector size: ${EIGEN_TEST_MAX_SIZE}") if(EIGEN_TEST_SSE2) message(STATUS "SSE2: ON") @@ -252,7 +260,6 @@ macro(ei_testing_print_summary) message(STATUS "\n${EIGEN_TESTING_SUMMARY}") message(STATUS "************************************************************") - endmacro(ei_testing_print_summary) macro(ei_init_testing) @@ -271,25 +278,200 @@ macro(ei_init_testing) set_property(GLOBAL PROPERTY EIGEN_FAILTEST_FAILURE_COUNT "0") set_property(GLOBAL PROPERTY EIGEN_FAILTEST_COUNT "0") + + # uncomment anytime you change the ei_get_compilerver_from_cxx_version_string macro + # ei_test_get_compilerver_from_cxx_version_string() endmacro(ei_init_testing) -if(CMAKE_COMPILER_IS_GNUCXX) - option(EIGEN_COVERAGE_TESTING "Enable/disable gcov" OFF) - if(EIGEN_COVERAGE_TESTING) - set(COVERAGE_FLAGS "-fprofile-arcs -ftest-coverage") - set(CTEST_CUSTOM_COVERAGE_EXCLUDE "/test/") - else(EIGEN_COVERAGE_TESTING) - set(COVERAGE_FLAGS "") - endif(EIGEN_COVERAGE_TESTING) - if(EIGEN_TEST_C++0x) - set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=gnu++0x") - endif(EIGEN_TEST_C++0x) - if(CMAKE_SYSTEM_NAME MATCHES Linux) - set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} ${COVERAGE_FLAGS} -g2") - set(CMAKE_CXX_FLAGS_RELWITHDEBINFO "${CMAKE_CXX_FLAGS_RELWITHDEBINFO} ${COVERAGE_FLAGS} -O2 -g2") - set(CMAKE_CXX_FLAGS_RELEASE "${CMAKE_CXX_FLAGS_RELEASE} ${COVERAGE_FLAGS} -fno-inline-functions") - set(CMAKE_CXX_FLAGS_DEBUG "${CMAKE_CXX_FLAGS_DEBUG} ${COVERAGE_FLAGS} -O0 -g3") - endif(CMAKE_SYSTEM_NAME MATCHES Linux) -elseif(MSVC) - set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} /D_CRT_SECURE_NO_WARNINGS /D_SCL_SECURE_NO_WARNINGS") -endif(CMAKE_COMPILER_IS_GNUCXX) +macro(ei_set_sitename) + # if the sitename is not yet set, try to set it + if(NOT ${SITE} OR ${SITE} STREQUAL "") + set(eigen_computername $ENV{COMPUTERNAME}) + set(eigen_hostname $ENV{HOSTNAME}) + if(eigen_hostname) + set(SITE ${eigen_hostname}) + elseif(eigen_computername) + set(SITE ${eigen_computername}) + endif() + endif() + # in case it is already set, enforce lower case + if(SITE) + string(TOLOWER ${SITE} SITE) + endif() +endmacro(ei_set_sitename) + +macro(ei_get_compilerver VAR) + if(MSVC) + # on windows system, we use a modified CMake script + include(CMakeDetermineVSServicePack) + DetermineVSServicePack( my_service_pack ) + + if( my_service_pack ) + set(${VAR} ${my_service_pack}) + else() + set(${VAR} "na") + endif() + else() + # on all other system we rely on ${CMAKE_CXX_COMPILER} + # supporting a "--version" flag + execute_process(COMMAND ${CMAKE_CXX_COMPILER} --version + COMMAND head -n 1 + OUTPUT_VARIABLE eigen_cxx_compiler_version_string OUTPUT_STRIP_TRAILING_WHITESPACE) + + ei_get_compilerver_from_cxx_version_string(${eigen_cxx_compiler_version_string} CNAME CVER) + + set(${VAR} "${CNAME}-${CVER}") + endif() +endmacro(ei_get_compilerver) + +# Extract compiler name and version from a raw version string +# WARNING: if you edit thid macro, then please test it by uncommenting +# the testing macro call in ei_init_testing() of the EigenTesting.cmake file. +# See also the ei_test_get_compilerver_from_cxx_version_string macro at the end of the file +macro(ei_get_compilerver_from_cxx_version_string VERSTRING CNAME CVER) + # extract possible compiler names + string(REGEX MATCH "g\\+\\+" ei_has_gpp ${VERSTRING}) + string(REGEX MATCH "llvm|LLVM" ei_has_llvm ${VERSTRING}) + string(REGEX MATCH "gcc|GCC" ei_has_gcc ${VERSTRING}) + string(REGEX MATCH "icpc|ICC" ei_has_icpc ${VERSTRING}) + string(REGEX MATCH "clang|CLANG" ei_has_clang ${VERSTRING}) + + # combine them + if((ei_has_llvm) AND (ei_has_gpp OR ei_has_gcc)) + set(${CNAME} "llvm-g++") + elseif((ei_has_llvm) AND (ei_has_clang)) + set(${CNAME} "llvm-clang++") + elseif(ei_has_icpc) + set(${CNAME} "icpc") + elseif(ei_has_gpp OR ei_has_gcc) + set(${CNAME} "g++") + else() + set(${CNAME} "_") + endif() + + # extract possible version numbers + # first try to extract 3 isolated numbers: + string(REGEX MATCH " [0-9]+\\.[0-9]+\\.[0-9]+" eicver ${VERSTRING}) + if(NOT eicver) + # try to extract 2 isolated ones: + string(REGEX MATCH " [0-9]+\\.[0-9]+" eicver ${VERSTRING}) + if(NOT eicver) + # try to extract 3: + string(REGEX MATCH "[^0-9][0-9]+\\.[0-9]+\\.[0-9]+" eicver ${VERSTRING}) + if(NOT eicver) + # try to extract 2: + string(REGEX MATCH "[^0-9][0-9]+\\.[0-9]+" eicver ${VERSTRING}) + else() + set(eicver " _") + endif() + endif() + endif() + + string(REGEX REPLACE ".(.*)" "\\1" ${CVER} ${eicver}) + +endmacro(ei_get_compilerver_from_cxx_version_string) + +macro(ei_get_cxxflags VAR) + set(${VAR} "") + ei_is_64bit_env(IS_64BIT_ENV) + if(EIGEN_TEST_NEON) + set(${VAR} NEON) + elseif(EIGEN_TEST_ALTIVEC) + set(${VAR} ALVEC) + elseif(EIGEN_TEST_SSE4_2) + set(${VAR} SSE42) + elseif(EIGEN_TEST_SSE4_1) + set(${VAR} SSE41) + elseif(EIGEN_TEST_SSSE3) + set(${VAR} SSSE3) + elseif(EIGEN_TEST_SSE3) + set(${VAR} SSE3) + elseif(EIGEN_TEST_SSE2 OR IS_64BIT_ENV) + set(${VAR} SSE2) + endif() + + if(EIGEN_TEST_OPENMP) + if (${VAR} STREQUAL "") + set(${VAR} OMP) + else() + set(${VAR} ${${VAR}}-OMP) + endif() + endif() + + if(EIGEN_DEFAULT_TO_ROW_MAJOR) + if (${VAR} STREQUAL "") + set(${VAR} ROW) + else() + set(${VAR} ${${VAR}}-ROWMAJ) + endif() + endif() +endmacro(ei_get_cxxflags) + +macro(ei_set_build_string) + ei_get_compilerver(LOCAL_COMPILER_VERSION) + ei_get_cxxflags(LOCAL_COMPILER_FLAGS) + + include(EigenDetermineOSVersion) + DetermineOSVersion(OS_VERSION) + + set(TMP_BUILD_STRING ${OS_VERSION}-${LOCAL_COMPILER_VERSION}) + + if (NOT ${LOCAL_COMPILER_FLAGS} STREQUAL "") + set(TMP_BUILD_STRING ${TMP_BUILD_STRING}-${LOCAL_COMPILER_FLAGS}) + endif() + + ei_is_64bit_env(IS_64BIT_ENV) + if(NOT IS_64BIT_ENV) + set(TMP_BUILD_STRING ${TMP_BUILD_STRING}-32bit) + else() + set(TMP_BUILD_STRING ${TMP_BUILD_STRING}-64bit) + endif() + + string(TOLOWER ${TMP_BUILD_STRING} BUILDNAME) +endmacro(ei_set_build_string) + +macro(ei_is_64bit_env VAR) + + file(WRITE "${CMAKE_CURRENT_BINARY_DIR}/is64.cpp" + "int main() { return (sizeof(int*) == 8 ? 1 : 0); } + ") + try_run(run_res compile_res + ${CMAKE_CURRENT_BINARY_DIR} "${CMAKE_CURRENT_BINARY_DIR}/is64.cpp" + RUN_OUTPUT_VARIABLE run_output) + + if(compile_res AND run_res) + set(${VAR} ${run_res}) + elseif(CMAKE_CL_64) + set(${VAR} 1) + elseif("$ENV{Platform}" STREQUAL "X64") # nmake 64 bit + set(${VAR} 1) + endif() +endmacro(ei_is_64bit_env) + + +# helper macro for testing ei_get_compilerver_from_cxx_version_string +# STR: raw version string +# REFNAME: expected compiler name +# REFVER: expected compiler version +macro(ei_test1_get_compilerver_from_cxx_version_string STR REFNAME REFVER) + ei_get_compilerver_from_cxx_version_string(${STR} CNAME CVER) + if((NOT ${REFNAME} STREQUAL ${CNAME}) OR (NOT ${REFVER} STREQUAL ${CVER})) + message("STATUS ei_get_compilerver_from_cxx_version_string error:") + message("Expected \"${REFNAME}-${REFVER}\", got \"${CNAME}-${CVER}\"") + endif() +endmacro(ei_test1_get_compilerver_from_cxx_version_string) + +# macro for testing ei_get_compilerver_from_cxx_version_string +# feel free to add more version strings +macro(ei_test_get_compilerver_from_cxx_version_string) + ei_test1_get_compilerver_from_cxx_version_string("g++ (SUSE Linux) 4.5.3 20110428 [gcc-4_5-branch revision 173117]" "g++" "4.5.3") + ei_test1_get_compilerver_from_cxx_version_string("c++ (GCC) 4.5.1 20100924 (Red Hat 4.5.1-4)" "g++" "4.5.1") + ei_test1_get_compilerver_from_cxx_version_string("icpc (ICC) 11.0 20081105" "icpc" "11.0") + ei_test1_get_compilerver_from_cxx_version_string("g++-3.4 (GCC) 3.4.6" "g++" "3.4.6") + ei_test1_get_compilerver_from_cxx_version_string("SUSE Linux clang version 3.0 (branches/release_30 145598) (based on LLVM 3.0)" "llvm-clang++" "3.0") + ei_test1_get_compilerver_from_cxx_version_string("icpc (ICC) 12.0.5 20110719" "icpc" "12.0.5") + ei_test1_get_compilerver_from_cxx_version_string("Apple clang version 2.1 (tags/Apple/clang-163.7.1) (based on LLVM 3.0svn)" "llvm-clang++" "2.1") + ei_test1_get_compilerver_from_cxx_version_string("i686-apple-darwin11-llvm-g++-4.2 (GCC) 4.2.1 (Based on Apple Inc. build 5658) (LLVM build 2335.15.00)" "llvm-g++" "4.2.1") + ei_test1_get_compilerver_from_cxx_version_string("g++-mp-4.4 (GCC) 4.4.6" "g++" "4.4.6") + ei_test1_get_compilerver_from_cxx_version_string("g++-mp-4.4 (GCC) 2011" "g++" "4.4") +endmacro(ei_test_get_compilerver_from_cxx_version_string) diff --git a/gtsam/3rdparty/Eigen/cmake/FindCholmod.cmake b/gtsam/3rdparty/Eigen/cmake/FindCholmod.cmake index a5e132b64..9095bea31 100644 --- a/gtsam/3rdparty/Eigen/cmake/FindCholmod.cmake +++ b/gtsam/3rdparty/Eigen/cmake/FindCholmod.cmake @@ -13,6 +13,7 @@ find_path(CHOLMOD_INCLUDES ${INCLUDE_INSTALL_DIR} PATH_SUFFIXES suitesparse + ufsparse ) find_library(CHOLMOD_LIBRARIES cholmod PATHS $ENV{CHOLMODDIR} ${LIB_INSTALL_DIR}) diff --git a/gtsam/3rdparty/Eigen/cmake/FindEigen2.cmake b/gtsam/3rdparty/Eigen/cmake/FindEigen2.cmake index da95bb0f5..a834b8872 100644 --- a/gtsam/3rdparty/Eigen/cmake/FindEigen2.cmake +++ b/gtsam/3rdparty/Eigen/cmake/FindEigen2.cmake @@ -39,11 +39,11 @@ macro(_eigen2_check_version) set(EIGEN2_MINOR_VERSION "${CMAKE_MATCH_1}") set(EIGEN2_VERSION ${EIGEN2_WORLD_VERSION}.${EIGEN2_MAJOR_VERSION}.${EIGEN2_MINOR_VERSION}) - if(${EIGEN2_VERSION} VERSION_LESS ${Eigen2_FIND_VERSION}) + if((${EIGEN2_WORLD_VERSION} NOTEQUAL 2) OR (${EIGEN2_MAJOR_VERSION} GREATER 10) OR (${EIGEN2_VERSION} VERSION_LESS ${Eigen2_FIND_VERSION})) set(EIGEN2_VERSION_OK FALSE) - else(${EIGEN2_VERSION} VERSION_LESS ${Eigen2_FIND_VERSION}) + else() set(EIGEN2_VERSION_OK TRUE) - endif(${EIGEN2_VERSION} VERSION_LESS ${Eigen2_FIND_VERSION}) + endif() if(NOT EIGEN2_VERSION_OK) diff --git a/gtsam/3rdparty/Eigen/cmake/FindFFTW.cmake b/gtsam/3rdparty/Eigen/cmake/FindFFTW.cmake index 58b10ea11..a9e9925e7 100644 --- a/gtsam/3rdparty/Eigen/cmake/FindFFTW.cmake +++ b/gtsam/3rdparty/Eigen/cmake/FindFFTW.cmake @@ -1,31 +1,119 @@ +# - Find the FFTW library +# +# Usage: +# find_package(FFTW [REQUIRED] [QUIET] ) +# +# It sets the following variables: +# FFTW_FOUND ... true if fftw is found on the system +# FFTW_LIBRARIES ... full path to fftw library +# FFTW_INCLUDES ... fftw include directory +# +# The following variables will be checked by the function +# FFTW_USE_STATIC_LIBS ... if true, only static libraries are found +# FFTW_ROOT ... if set, the libraries are exclusively searched +# under this path +# FFTW_LIBRARY ... fftw library to use +# FFTW_INCLUDE_DIR ... fftw include directory +# -if (FFTW_INCLUDES AND FFTW_LIBRARIES) - set(FFTW_FIND_QUIETLY TRUE) -endif (FFTW_INCLUDES AND FFTW_LIBRARIES) - -find_path(FFTW_INCLUDES - NAMES - fftw3.h - PATHS - $ENV{FFTWDIR} - ${INCLUDE_INSTALL_DIR} -) - -find_library(FFTWF_LIB NAMES fftw3f PATHS $ENV{FFTWDIR} ${LIB_INSTALL_DIR}) -find_library(FFTW_LIB NAMES fftw3 PATHS $ENV{FFTWDIR} ${LIB_INSTALL_DIR}) -set(FFTW_LIBRARIES "${FFTWF_LIB} ${FFTW_LIB}" ) - -find_library(FFTWL_LIB NAMES fftw3l PATHS $ENV{FFTWDIR} ${LIB_INSTALL_DIR}) - -if(FFTWL_LIB) -set(FFTW_LIBRARIES "${FFTW_LIBRARIES} ${FFTWL_LIB}") +#If environment variable FFTWDIR is specified, it has same effect as FFTW_ROOT +if( NOT FFTW_ROOT AND ENV{FFTWDIR} ) + set( FFTW_ROOT $ENV{FFTWDIR} ) endif() +# Check if we can use PkgConfig +find_package(PkgConfig) -message(STATUS "FFTW ${FFTW_LIBRARIES}" ) +#Determine from PKG +if( PKG_CONFIG_FOUND AND NOT FFTW_ROOT ) + pkg_check_modules( PKG_FFTW QUIET "fftw3" ) +endif() + +#Check whether to search static or dynamic libs +set( CMAKE_FIND_LIBRARY_SUFFIXES_SAV ${CMAKE_FIND_LIBRARY_SUFFIXES} ) + +if( ${FFTW_USE_STATIC_LIBS} ) + set( CMAKE_FIND_LIBRARY_SUFFIXES ${CMAKE_STATIC_LIBRARY_SUFFIX} ) +else() + set( CMAKE_FIND_LIBRARY_SUFFIXES ${CMAKE_SHARED_LIBRARY_SUFFIX} ) +endif() + +if( FFTW_ROOT ) + + #find libs + find_library( + FFTW_LIB + NAMES "fftw3" + PATHS ${FFTW_ROOT} + PATH_SUFFIXES "lib" "lib64" + NO_DEFAULT_PATH + ) + + find_library( + FFTWF_LIB + NAMES "fftw3f" + PATHS ${FFTW_ROOT} + PATH_SUFFIXES "lib" "lib64" + NO_DEFAULT_PATH + ) + + find_library( + FFTWL_LIB + NAMES "fftw3l" + PATHS ${FFTW_ROOT} + PATH_SUFFIXES "lib" "lib64" + NO_DEFAULT_PATH + ) + + #find includes + find_path( + FFTW_INCLUDES + NAMES "fftw3.h" + PATHS ${FFTW_ROOT} + PATH_SUFFIXES "include" + NO_DEFAULT_PATH + ) + +else() + + find_library( + FFTW_LIB + NAMES "fftw3" + PATHS ${PKG_FFTW_LIBRARY_DIRS} ${LIB_INSTALL_DIR} + ) + + find_library( + FFTWF_LIB + NAMES "fftw3f" + PATHS ${PKG_FFTW_LIBRARY_DIRS} ${LIB_INSTALL_DIR} + ) + + + find_library( + FFTWL_LIB + NAMES "fftw3l" + PATHS ${PKG_FFTW_LIBRARY_DIRS} ${LIB_INSTALL_DIR} + ) + + find_path( + FFTW_INCLUDES + NAMES "fftw3.h" + PATHS ${PKG_FFTW_INCLUDE_DIRS} ${INCLUDE_INSTALL_DIR} + ) + +endif( FFTW_ROOT ) + +set(FFTW_LIBRARIES ${FFTW_LIB} ${FFTWF_LIB}) + +if(FFTWL_LIB) + set(FFTW_LIBRARIES ${FFTW_LIBRARIES} ${FFTWL_LIB}) +endif() + +set( CMAKE_FIND_LIBRARY_SUFFIXES ${CMAKE_FIND_LIBRARY_SUFFIXES_SAV} ) include(FindPackageHandleStandardArgs) find_package_handle_standard_args(FFTW DEFAULT_MSG FFTW_INCLUDES FFTW_LIBRARIES) mark_as_advanced(FFTW_INCLUDES FFTW_LIBRARIES) + diff --git a/gtsam/3rdparty/Eigen/cmake/FindMetis.cmake b/gtsam/3rdparty/Eigen/cmake/FindMetis.cmake new file mode 100644 index 000000000..e4d6ef258 --- /dev/null +++ b/gtsam/3rdparty/Eigen/cmake/FindMetis.cmake @@ -0,0 +1,24 @@ +# Pastix requires METIS or METIS (partitioning and reordering tools) + +if (METIS_INCLUDES AND METIS_LIBRARIES) + set(METIS_FIND_QUIETLY TRUE) +endif (METIS_INCLUDES AND METIS_LIBRARIES) + +find_path(METIS_INCLUDES + NAMES + metis.h + PATHS + $ENV{METISDIR} + ${INCLUDE_INSTALL_DIR} + PATH_SUFFIXES + metis +) + + +find_library(METIS_LIBRARIES metis PATHS $ENV{METISDIR} ${LIB_INSTALL_DIR}) + +include(FindPackageHandleStandardArgs) +find_package_handle_standard_args(METIS DEFAULT_MSG + METIS_INCLUDES METIS_LIBRARIES) + +mark_as_advanced(METIS_INCLUDES METIS_LIBRARIES) diff --git a/gtsam/3rdparty/Eigen/cmake/FindPastix.cmake b/gtsam/3rdparty/Eigen/cmake/FindPastix.cmake new file mode 100644 index 000000000..e2e6c810d --- /dev/null +++ b/gtsam/3rdparty/Eigen/cmake/FindPastix.cmake @@ -0,0 +1,25 @@ +# Pastix lib requires linking to a blas library. +# It is up to the user of this module to find a BLAS and link to it. +# Pastix requires SCOTCH or METIS (partitioning and reordering tools) as well + +if (PASTIX_INCLUDES AND PASTIX_LIBRARIES) + set(PASTIX_FIND_QUIETLY TRUE) +endif (PASTIX_INCLUDES AND PASTIX_LIBRARIES) + +find_path(PASTIX_INCLUDES + NAMES + pastix_nompi.h + PATHS + $ENV{PASTIXDIR} + ${INCLUDE_INSTALL_DIR} +) + +find_library(PASTIX_LIBRARIES pastix PATHS $ENV{PASTIXDIR} ${LIB_INSTALL_DIR}) + + + +include(FindPackageHandleStandardArgs) +find_package_handle_standard_args(PASTIX DEFAULT_MSG + PASTIX_INCLUDES PASTIX_LIBRARIES) + +mark_as_advanced(PASTIX_INCLUDES PASTIX_LIBRARIES) diff --git a/gtsam/3rdparty/Eigen/cmake/FindScotch.cmake b/gtsam/3rdparty/Eigen/cmake/FindScotch.cmake new file mode 100644 index 000000000..530340b16 --- /dev/null +++ b/gtsam/3rdparty/Eigen/cmake/FindScotch.cmake @@ -0,0 +1,24 @@ +# Pastix requires SCOTCH or METIS (partitioning and reordering tools) + +if (SCOTCH_INCLUDES AND SCOTCH_LIBRARIES) + set(SCOTCH_FIND_QUIETLY TRUE) +endif (SCOTCH_INCLUDES AND SCOTCH_LIBRARIES) + +find_path(SCOTCH_INCLUDES + NAMES + scotch.h + PATHS + $ENV{SCOTCHDIR} + ${INCLUDE_INSTALL_DIR} + PATH_SUFFIXES + scotch +) + + +find_library(SCOTCH_LIBRARIES scotch PATHS $ENV{SCOTCHDIR} ${LIB_INSTALL_DIR}) + +include(FindPackageHandleStandardArgs) +find_package_handle_standard_args(SCOTCH DEFAULT_MSG + SCOTCH_INCLUDES SCOTCH_LIBRARIES) + +mark_as_advanced(SCOTCH_INCLUDES SCOTCH_LIBRARIES) diff --git a/gtsam/3rdparty/Eigen/cmake/FindUmfpack.cmake b/gtsam/3rdparty/Eigen/cmake/FindUmfpack.cmake index 4b6f24f93..d42c3c4a2 100644 --- a/gtsam/3rdparty/Eigen/cmake/FindUmfpack.cmake +++ b/gtsam/3rdparty/Eigen/cmake/FindUmfpack.cmake @@ -13,6 +13,7 @@ find_path(UMFPACK_INCLUDES ${INCLUDE_INSTALL_DIR} PATH_SUFFIXES suitesparse + ufsparse ) find_library(UMFPACK_LIBRARIES umfpack PATHS $ENV{UMFPACKDIR} ${LIB_INSTALL_DIR}) diff --git a/gtsam/3rdparty/Eigen/cmake/language_support.cmake b/gtsam/3rdparty/Eigen/cmake/language_support.cmake new file mode 100644 index 000000000..3414e6ea6 --- /dev/null +++ b/gtsam/3rdparty/Eigen/cmake/language_support.cmake @@ -0,0 +1,64 @@ +# cmake/modules/language_support.cmake +# +# Temporary additional general language support is contained within this +# file. + +# This additional function definition is needed to provide a workaround for +# CMake bug 9220. + +# On debian testing (cmake 2.6.2), I get return code zero when calling +# cmake the first time, but cmake crashes when running a second time +# as follows: +# +# -- The Fortran compiler identification is unknown +# CMake Error at /usr/share/cmake-2.6/Modules/CMakeFortranInformation.cmake:7 (GET_FILENAME_COMPONENT): +# get_filename_component called with incorrect number of arguments +# Call Stack (most recent call first): +# CMakeLists.txt:3 (enable_language) +# +# My workaround is to invoke cmake twice. If both return codes are zero, +# it is safe to invoke ENABLE_LANGUAGE(Fortran OPTIONAL) + +function(workaround_9220 language language_works) + #message("DEBUG: language = ${language}") + set(text + "project(test NONE) + cmake_minimum_required(VERSION 2.6.0) + enable_language(${language} OPTIONAL) + ") + file(REMOVE_RECURSE ${CMAKE_BINARY_DIR}/language_tests/${language}) + file(MAKE_DIRECTORY ${CMAKE_BINARY_DIR}/language_tests/${language}) + file(WRITE ${CMAKE_BINARY_DIR}/language_tests/${language}/CMakeLists.txt + ${text}) + execute_process( + COMMAND ${CMAKE_COMMAND} . + WORKING_DIRECTORY ${CMAKE_BINARY_DIR}/language_tests/${language} + RESULT_VARIABLE return_code + OUTPUT_QUIET + ERROR_QUIET + ) + + if(return_code EQUAL 0) + # Second run + execute_process ( + COMMAND ${CMAKE_COMMAND} . + WORKING_DIRECTORY ${CMAKE_BINARY_DIR}/language_tests/${language} + RESULT_VARIABLE return_code + OUTPUT_QUIET + ERROR_QUIET + ) + if(return_code EQUAL 0) + set(${language_works} ON PARENT_SCOPE) + else(return_code EQUAL 0) + set(${language_works} OFF PARENT_SCOPE) + endif(return_code EQUAL 0) + else(return_code EQUAL 0) + set(${language_works} OFF PARENT_SCOPE) + endif(return_code EQUAL 0) +endfunction(workaround_9220) + +# Temporary tests of the above function. +#workaround_9220(CXX CXX_language_works) +#message("CXX_language_works = ${CXX_language_works}") +#workaround_9220(CXXp CXXp_language_works) +#message("CXXp_language_works = ${CXXp_language_works}") diff --git a/gtsam/3rdparty/Eigen/debug/gdb/printers.py b/gtsam/3rdparty/Eigen/debug/gdb/printers.py index 02823b8a2..8dab8fffb 100644 --- a/gtsam/3rdparty/Eigen/debug/gdb/printers.py +++ b/gtsam/3rdparty/Eigen/debug/gdb/printers.py @@ -31,9 +31,15 @@ # To use it: # -# * create a directory and put the file as well as an empty __init__.py in that directory +# * Create a directory and put the file as well as an empty __init__.py in +# that directory. # * Create a ~/.gdbinit file, that contains the following: - +# python +# import sys +# sys.path.insert(0, '/path/to/eigen/printer/directory') +# from printers import register_eigen_printers +# register_eigen_printers (None) +# end import gdb import re @@ -41,10 +47,14 @@ import itertools class EigenMatrixPrinter: - "Print Eigen Matrix of some kind" + "Print Eigen Matrix or Array of some kind" - def __init__(self, val): + def __init__(self, variety, val): "Extract all the necessary information" + + # Save the variety (presumably "Matrix" or "Array") for later usage + self.variety = variety + # The gdb extension does not support value template arguments - need to extract them by hand type = val.type if type.code == gdb.TYPE_CODE_REF: @@ -55,7 +65,7 @@ class EigenMatrixPrinter: m = regex.findall(tag)[0][1:-1] template_params = m.split(',') template_params = map(lambda x:x.replace(" ", ""), template_params) - + if template_params[1] == '-0x00000000000000001' or template_params[1] == '-0x000000001': self.rows = val['m_storage']['m_rows'] else: @@ -71,9 +81,9 @@ class EigenMatrixPrinter: self.options = template_params[3]; self.rowMajor = (int(self.options) & 0x1) - + self.innerType = self.type.template_argument(0) - + self.val = val # Fixed size matrices have a struct as their storage, so we need to walk through this @@ -90,12 +100,12 @@ class EigenMatrixPrinter: self.currentRow = 0 self.currentCol = 0 self.rowMajor = rowMajor - + def __iter__ (self): return self - + def next(self): - + row = self.currentRow col = self.currentCol if self.rowMajor == 0: @@ -115,7 +125,7 @@ class EigenMatrixPrinter: self.currentCol = 0 self.currentRow = self.currentRow + 1 - + item = self.dataPtr.dereference() self.dataPtr = self.dataPtr + 1 if (self.cols == 1): #if it's a column vector @@ -123,17 +133,17 @@ class EigenMatrixPrinter: elif (self.rows == 1): #if it's a row vector return ('[%d]' % (col,), item) return ('[%d,%d]' % (row, col), item) - + def children(self): return self._iterator(self.rows, self.cols, self.data, self.rowMajor) - + def to_string(self): - return "Eigen::Matrix<%s,%d,%d,%s> (data ptr: %s)" % (self.innerType, self.rows, self.cols, "RowMajor" if self.rowMajor else "ColMajor", self.data) + return "Eigen::%s<%s,%d,%d,%s> (data ptr: %s)" % (self.variety, self.innerType, self.rows, self.cols, "RowMajor" if self.rowMajor else "ColMajor", self.data) class EigenQuaternionPrinter: "Print an Eigen Quaternion" - + def __init__(self, val): "Extract all the necessary information" # The gdb extension does not support value template arguments - need to extract them by hand @@ -153,18 +163,18 @@ class EigenQuaternionPrinter: self.dataPtr = dataPtr self.currentElement = 0 self.elementNames = ['x', 'y', 'z', 'w'] - + def __iter__ (self): return self - + def next(self): element = self.currentElement - + if self.currentElement >= 4: #there are 4 elements in a quanternion raise StopIteration self.currentElement = self.currentElement + 1 - + item = self.dataPtr.dereference() self.dataPtr = self.dataPtr + 1 return ('[%s]' % (self.elementNames[element],), item) @@ -172,13 +182,14 @@ class EigenQuaternionPrinter: def children(self): return self._iterator(self.data) - + def to_string(self): return "Eigen::Quaternion<%s> (data ptr: %s)" % (self.innerType, self.data) def build_eigen_dictionary (): pretty_printers_dict[re.compile('^Eigen::Quaternion<.*>$')] = lambda val: EigenQuaternionPrinter(val) - pretty_printers_dict[re.compile('^Eigen::Matrix<.*>$')] = lambda val: EigenMatrixPrinter(val) + pretty_printers_dict[re.compile('^Eigen::Matrix<.*>$')] = lambda val: EigenMatrixPrinter("Matrix", val) + pretty_printers_dict[re.compile('^Eigen::Array<.*>$')] = lambda val: EigenMatrixPrinter("Array", val) def register_eigen_printers(obj): "Register eigen pretty-printers with objfile Obj" @@ -189,22 +200,22 @@ def register_eigen_printers(obj): def lookup_function(val): "Look-up and return a pretty-printer that can print va." - + type = val.type - + if type.code == gdb.TYPE_CODE_REF: type = type.target() type = type.unqualified().strip_typedefs() - + typename = type.tag if typename == None: return None - + for function in pretty_printers_dict: if function.search(typename): return pretty_printers_dict[function](val) - + return None pretty_printers_dict = {} diff --git a/gtsam/3rdparty/Eigen/debug/msvc/eigen_autoexp_part.dat b/gtsam/3rdparty/Eigen/debug/msvc/eigen_autoexp_part.dat index ba7eefc8e..07aa43739 100644 --- a/gtsam/3rdparty/Eigen/debug/msvc/eigen_autoexp_part.dat +++ b/gtsam/3rdparty/Eigen/debug/msvc/eigen_autoexp_part.dat @@ -1,295 +1,295 @@ -; *************************************************************** -; * Eigen Visualizer -; * -; * Author: Hauke Heibel -; * -; * Support the enhanced debugging of the following Eigen -; * types (*: any, +:fixed dimension) : -; * -; * - Eigen::Matrix<*,4,1,*,*,*> and Eigen::Matrix<*,1,4,*,*,*> -; * - Eigen::Matrix<*,3,1,*,*,*> and Eigen::Matrix<*,1,3,*,*,*> -; * - Eigen::Matrix<*,2,1,*,*,*> and Eigen::Matrix<*,1,2,*,*,*> -; * - Eigen::Matrix<*,-1,-1,*,*,*> -; * - Eigen::Matrix<*,+,-1,*,*,*> -; * - Eigen::Matrix<*,-1,+,*,*,*> -; * - Eigen::Matrix<*,+,+,*,*,*> -; * -; * Matrices are displayed properly independantly of the memory -; * alignment (RowMajor vs. ColMajor). -; * -; * This file is distributed WITHOUT ANY WARRANTY. Please ensure -; * that your original autoexp.dat file is copied to a safe -; * place before proceeding with its modification. -; *************************************************************** - -[Visualizer] - -; Fixed size 4-vectors -Eigen::Matrix<*,4,1,*,*,*>|Eigen::Matrix<*,1,4,*,*,*>{ - children - ( - #( - [internals]: [$c,!], - x : ($c.m_storage.m_data.array)[0], - y : ($c.m_storage.m_data.array)[1], - z : ($c.m_storage.m_data.array)[2], - w : ($c.m_storage.m_data.array)[3] - ) - ) - - preview - ( - #( - "[", - 4, - "](", - #array(expr: $e.m_storage.m_data.array[$i], size: 4), - ")" - ) - ) -} - -; Fixed size 3-vectors -Eigen::Matrix<*,3,1,*,*,*>|Eigen::Matrix<*,1,3,*,*,*>{ - children - ( - #( - [internals]: [$c,!], - x : ($c.m_storage.m_data.array)[0], - y : ($c.m_storage.m_data.array)[1], - z : ($c.m_storage.m_data.array)[2] - ) - ) - - preview - ( - #( - "[", - 3, - "](", - #array(expr: $e.m_storage.m_data.array[$i], size: 3), - ")" - ) - ) -} - -; Fixed size 2-vectors -Eigen::Matrix<*,2,1,*,*,*>|Eigen::Matrix<*,1,2,*,*,*>{ - children - ( - #( - [internals]: [$c,!], - x : ($c.m_storage.m_data.array)[0], - y : ($c.m_storage.m_data.array)[1] - ) - ) - - preview - ( - #( - "[", - 2, - "](", - #array(expr: $e.m_storage.m_data.array[$i], size: 2), - ")" - ) - ) -} - -; Fixed size 1-vectors -Eigen::Matrix<*,1,1,*,*,*>|Eigen::Matrix<*,1,1,*,*,*>{ - children - ( - #( - [internals]: [$c,!], - x : ($c.m_storage.m_data.array)[0] - ) - ) - - preview - ( - #( - "[", - 1, - "](", - #array(expr: $e.m_storage.m_data.array[$i], size: 1), - ")" - ) - ) -} - -; Dynamic matrices (ColMajor and RowMajor support) -Eigen::Matrix<*,-1,-1,*,*,*>{ - children - ( - #( - [internals]: [$c,!], - rows: $c.m_storage.m_rows, - cols: $c.m_storage.m_cols, - ; Check for RowMajorBit - #if ($c.Flags & 0x1) ( - #array( - rank: 2, - base: 0, - expr: ($c.m_storage.m_data)[($i % $c.m_storage.m_rows)*$c.m_storage.m_cols + (($i- $i % $c.m_storage.m_rows)/$c.m_storage.m_rows)], - size: ($r==1)*$c.m_storage.m_rows+($r==0)*$c.m_storage.m_cols - ) - ) #else ( - #array( - rank: 2, - base: 0, - expr: ($c.m_storage.m_data)[$i], - size: ($r==1)*$c.m_storage.m_rows+($r==0)*$c.m_storage.m_cols - ) - ) - ) - ) - - preview - ( - #( - "[", - $c.m_storage.m_rows, - ",", - $c.m_storage.m_cols, - "](", - #array( - expr : [($c.m_storage.m_data)[$i],g], - size : $c.m_storage.m_rows*$c.m_storage.m_cols - ), - ")" - ) - ) -} - -; Fixed rows, dynamic columns matrix (ColMajor and RowMajor support) -Eigen::Matrix<*,*,-1,*,*,*>{ - children - ( - #( - [internals]: [$c,!], - rows: $c.RowsAtCompileTime, - cols: $c.m_storage.m_cols, - ; Check for RowMajorBit - #if ($c.Flags & 0x1) ( - #array( - rank: 2, - base: 0, - expr: ($c.m_storage.m_data)[($i % $c.RowsAtCompileTime)*$c.m_storage.m_cols + (($i- $i % $c.RowsAtCompileTime)/$c.RowsAtCompileTime)], - size: ($r==1)*$c.RowsAtCompileTime+($r==0)*$c.m_storage.m_cols - ) - ) #else ( - #array( - rank: 2, - base: 0, - expr: ($c.m_storage.m_data)[$i], - size: ($r==1)*$c.RowsAtCompileTime+($r==0)*$c.m_storage.m_cols - ) - ) - ) - ) - - preview - ( - #( - "[", - $c.RowsAtCompileTime, - ",", - $c.m_storage.m_cols, - "](", - #array( - expr : [($c.m_storage.m_data)[$i],g], - size : $c.RowsAtCompileTime*$c.m_storage.m_cols - ), - ")" - ) - ) -} - -; Dynamic rows, fixed columns matrix (ColMajor and RowMajor support) -Eigen::Matrix<*,-1,*,*,*,*>{ - children - ( - #( - [internals]: [$c,!], - rows: $c.m_storage.m_rows, - cols: $c.ColsAtCompileTime, - ; Check for RowMajorBit - #if ($c.Flags & 0x1) ( - #array( - rank: 2, - base: 0, - expr: ($c.m_storage.m_data)[($i % $c.m_storage.m_rows)*$c.ColsAtCompileTime + (($i- $i % $c.m_storage.m_rows)/$c.m_storage.m_rows)], - size: ($r==1)*$c.m_storage.m_rows+($r==0)*$c.ColsAtCompileTime - ) - ) #else ( - #array( - rank: 2, - base: 0, - expr: ($c.m_storage.m_data)[$i], - size: ($r==1)*$c.m_storage.m_rows+($r==0)*$c.ColsAtCompileTime - ) - ) - ) - ) - - preview - ( - #( - "[", - $c.m_storage.m_rows, - ",", - $c.ColsAtCompileTime, - "](", - #array( - expr : [($c.m_storage.m_data)[$i],g], - size : $c.m_storage.m_rows*$c.ColsAtCompileTime - ), - ")" - ) - ) -} - -; Fixed size matrix (ColMajor and RowMajor support) -Eigen::Matrix<*,*,*,*,*,*>{ - children - ( - #( - [internals]: [$c,!], - rows: $c.RowsAtCompileTime, - cols: $c.ColsAtCompileTime, - ; Check for RowMajorBit - #if ($c.Flags & 0x1) ( - #array( - rank: 2, - base: 0, - expr: ($c.m_storage.m_data.array)[($i % $c.RowsAtCompileTime)*$c.ColsAtCompileTime + (($i- $i % $c.RowsAtCompileTime)/$c.RowsAtCompileTime)], - size: ($r==1)*$c.RowsAtCompileTime+($r==0)*$c.ColsAtCompileTime - ) - ) #else ( - #array( - rank: 2, - base: 0, - expr: ($c.m_storage.m_data.array)[$i], - size: ($r==1)*$c.RowsAtCompileTime+($r==0)*$c.ColsAtCompileTime - ) - ) - ) - ) - - preview - ( - #( - "[", - $c.RowsAtCompileTime, - ",", - $c.ColsAtCompileTime, - "](", - #array( - expr : [($c.m_storage.m_data.array)[$i],g], - size : $c.RowsAtCompileTime*$c.ColsAtCompileTime - ), - ")" - ) - ) -} +; *************************************************************** +; * Eigen Visualizer +; * +; * Author: Hauke Heibel +; * +; * Support the enhanced debugging of the following Eigen +; * types (*: any, +:fixed dimension) : +; * +; * - Eigen::Matrix<*,4,1,*,*,*> and Eigen::Matrix<*,1,4,*,*,*> +; * - Eigen::Matrix<*,3,1,*,*,*> and Eigen::Matrix<*,1,3,*,*,*> +; * - Eigen::Matrix<*,2,1,*,*,*> and Eigen::Matrix<*,1,2,*,*,*> +; * - Eigen::Matrix<*,-1,-1,*,*,*> +; * - Eigen::Matrix<*,+,-1,*,*,*> +; * - Eigen::Matrix<*,-1,+,*,*,*> +; * - Eigen::Matrix<*,+,+,*,*,*> +; * +; * Matrices are displayed properly independantly of the memory +; * alignment (RowMajor vs. ColMajor). +; * +; * This file is distributed WITHOUT ANY WARRANTY. Please ensure +; * that your original autoexp.dat file is copied to a safe +; * place before proceeding with its modification. +; *************************************************************** + +[Visualizer] + +; Fixed size 4-vectors +Eigen::Matrix<*,4,1,*,*,*>|Eigen::Matrix<*,1,4,*,*,*>{ + children + ( + #( + [internals]: [$c,!], + x : ($c.m_storage.m_data.array)[0], + y : ($c.m_storage.m_data.array)[1], + z : ($c.m_storage.m_data.array)[2], + w : ($c.m_storage.m_data.array)[3] + ) + ) + + preview + ( + #( + "[", + 4, + "](", + #array(expr: $e.m_storage.m_data.array[$i], size: 4), + ")" + ) + ) +} + +; Fixed size 3-vectors +Eigen::Matrix<*,3,1,*,*,*>|Eigen::Matrix<*,1,3,*,*,*>{ + children + ( + #( + [internals]: [$c,!], + x : ($c.m_storage.m_data.array)[0], + y : ($c.m_storage.m_data.array)[1], + z : ($c.m_storage.m_data.array)[2] + ) + ) + + preview + ( + #( + "[", + 3, + "](", + #array(expr: $e.m_storage.m_data.array[$i], size: 3), + ")" + ) + ) +} + +; Fixed size 2-vectors +Eigen::Matrix<*,2,1,*,*,*>|Eigen::Matrix<*,1,2,*,*,*>{ + children + ( + #( + [internals]: [$c,!], + x : ($c.m_storage.m_data.array)[0], + y : ($c.m_storage.m_data.array)[1] + ) + ) + + preview + ( + #( + "[", + 2, + "](", + #array(expr: $e.m_storage.m_data.array[$i], size: 2), + ")" + ) + ) +} + +; Fixed size 1-vectors +Eigen::Matrix<*,1,1,*,*,*>|Eigen::Matrix<*,1,1,*,*,*>{ + children + ( + #( + [internals]: [$c,!], + x : ($c.m_storage.m_data.array)[0] + ) + ) + + preview + ( + #( + "[", + 1, + "](", + #array(expr: $e.m_storage.m_data.array[$i], size: 1), + ")" + ) + ) +} + +; Dynamic matrices (ColMajor and RowMajor support) +Eigen::Matrix<*,-1,-1,*,*,*>{ + children + ( + #( + [internals]: [$c,!], + rows: $c.m_storage.m_rows, + cols: $c.m_storage.m_cols, + ; Check for RowMajorBit + #if ($c.Flags & 0x1) ( + #array( + rank: 2, + base: 0, + expr: ($c.m_storage.m_data)[($i % $c.m_storage.m_rows)*$c.m_storage.m_cols + (($i- $i % $c.m_storage.m_rows)/$c.m_storage.m_rows)], + size: ($r==1)*$c.m_storage.m_rows+($r==0)*$c.m_storage.m_cols + ) + ) #else ( + #array( + rank: 2, + base: 0, + expr: ($c.m_storage.m_data)[$i], + size: ($r==1)*$c.m_storage.m_rows+($r==0)*$c.m_storage.m_cols + ) + ) + ) + ) + + preview + ( + #( + "[", + $c.m_storage.m_rows, + ",", + $c.m_storage.m_cols, + "](", + #array( + expr : [($c.m_storage.m_data)[$i],g], + size : $c.m_storage.m_rows*$c.m_storage.m_cols + ), + ")" + ) + ) +} + +; Fixed rows, dynamic columns matrix (ColMajor and RowMajor support) +Eigen::Matrix<*,*,-1,*,*,*>{ + children + ( + #( + [internals]: [$c,!], + rows: $c.RowsAtCompileTime, + cols: $c.m_storage.m_cols, + ; Check for RowMajorBit + #if ($c.Flags & 0x1) ( + #array( + rank: 2, + base: 0, + expr: ($c.m_storage.m_data)[($i % $c.RowsAtCompileTime)*$c.m_storage.m_cols + (($i- $i % $c.RowsAtCompileTime)/$c.RowsAtCompileTime)], + size: ($r==1)*$c.RowsAtCompileTime+($r==0)*$c.m_storage.m_cols + ) + ) #else ( + #array( + rank: 2, + base: 0, + expr: ($c.m_storage.m_data)[$i], + size: ($r==1)*$c.RowsAtCompileTime+($r==0)*$c.m_storage.m_cols + ) + ) + ) + ) + + preview + ( + #( + "[", + $c.RowsAtCompileTime, + ",", + $c.m_storage.m_cols, + "](", + #array( + expr : [($c.m_storage.m_data)[$i],g], + size : $c.RowsAtCompileTime*$c.m_storage.m_cols + ), + ")" + ) + ) +} + +; Dynamic rows, fixed columns matrix (ColMajor and RowMajor support) +Eigen::Matrix<*,-1,*,*,*,*>{ + children + ( + #( + [internals]: [$c,!], + rows: $c.m_storage.m_rows, + cols: $c.ColsAtCompileTime, + ; Check for RowMajorBit + #if ($c.Flags & 0x1) ( + #array( + rank: 2, + base: 0, + expr: ($c.m_storage.m_data)[($i % $c.m_storage.m_rows)*$c.ColsAtCompileTime + (($i- $i % $c.m_storage.m_rows)/$c.m_storage.m_rows)], + size: ($r==1)*$c.m_storage.m_rows+($r==0)*$c.ColsAtCompileTime + ) + ) #else ( + #array( + rank: 2, + base: 0, + expr: ($c.m_storage.m_data)[$i], + size: ($r==1)*$c.m_storage.m_rows+($r==0)*$c.ColsAtCompileTime + ) + ) + ) + ) + + preview + ( + #( + "[", + $c.m_storage.m_rows, + ",", + $c.ColsAtCompileTime, + "](", + #array( + expr : [($c.m_storage.m_data)[$i],g], + size : $c.m_storage.m_rows*$c.ColsAtCompileTime + ), + ")" + ) + ) +} + +; Fixed size matrix (ColMajor and RowMajor support) +Eigen::Matrix<*,*,*,*,*,*>{ + children + ( + #( + [internals]: [$c,!], + rows: $c.RowsAtCompileTime, + cols: $c.ColsAtCompileTime, + ; Check for RowMajorBit + #if ($c.Flags & 0x1) ( + #array( + rank: 2, + base: 0, + expr: ($c.m_storage.m_data.array)[($i % $c.RowsAtCompileTime)*$c.ColsAtCompileTime + (($i- $i % $c.RowsAtCompileTime)/$c.RowsAtCompileTime)], + size: ($r==1)*$c.RowsAtCompileTime+($r==0)*$c.ColsAtCompileTime + ) + ) #else ( + #array( + rank: 2, + base: 0, + expr: ($c.m_storage.m_data.array)[$i], + size: ($r==1)*$c.RowsAtCompileTime+($r==0)*$c.ColsAtCompileTime + ) + ) + ) + ) + + preview + ( + #( + "[", + $c.RowsAtCompileTime, + ",", + $c.ColsAtCompileTime, + "](", + #array( + expr : [($c.m_storage.m_data.array)[$i],g], + size : $c.RowsAtCompileTime*$c.ColsAtCompileTime + ), + ")" + ) + ) +} diff --git a/gtsam/3rdparty/Eigen/doc/C00_QuickStartGuide.dox b/gtsam/3rdparty/Eigen/doc/C00_QuickStartGuide.dox index ad772b2e1..8534cb0c3 100644 --- a/gtsam/3rdparty/Eigen/doc/C00_QuickStartGuide.dox +++ b/gtsam/3rdparty/Eigen/doc/C00_QuickStartGuide.dox @@ -25,6 +25,10 @@ There is no library to link to. The only thing that you need to keep in mind whe \code g++ -I /path/to/eigen/ my_program.cpp -o my_program \endcode +On Linux or Mac OS X, another option is to symlink or copy the Eigen folder into /usr/local/include/. This way, you can compile the program with: + +\code g++ my_program.cpp -o my_program \endcode + When you run the program, it produces the following output: \include QuickStart_example.out diff --git a/gtsam/3rdparty/Eigen/doc/C06_TutorialLinearAlgebra.dox b/gtsam/3rdparty/Eigen/doc/C06_TutorialLinearAlgebra.dox index 77f13f4a0..e8b3b7953 100644 --- a/gtsam/3rdparty/Eigen/doc/C06_TutorialLinearAlgebra.dox +++ b/gtsam/3rdparty/Eigen/doc/C06_TutorialLinearAlgebra.dox @@ -144,6 +144,9 @@ You need an eigendecomposition here, see available such decompositions on \ref T Make sure to check if your matrix is self-adjoint, as is often the case in these problems. Here's an example using SelfAdjointEigenSolver, it could easily be adapted to general matrices using EigenSolver or ComplexEigenSolver. +The computation of eigenvalues and eigenvectors does not necessarily converge, but such failure to converge is +very rare. The call to info() is to check for this possibility. + diff --git a/gtsam/3rdparty/Eigen/doc/C07_TutorialReductionsVisitorsBroadcasting.dox b/gtsam/3rdparty/Eigen/doc/C07_TutorialReductionsVisitorsBroadcasting.dox index e58ff6e2c..f3879b8b9 100644 --- a/gtsam/3rdparty/Eigen/doc/C07_TutorialReductionsVisitorsBroadcasting.dox +++ b/gtsam/3rdparty/Eigen/doc/C07_TutorialReductionsVisitorsBroadcasting.dox @@ -191,12 +191,27 @@ This can be accomplished with: \verbinclude Tutorial_ReductionsVisitorsBroadcasting_broadcast_simple.out
Example:Output:
+We can interpret the instruction mat.colwise() += v in two equivalent ways. It adds the vector \c v +to every column of the matrix. Alternatively, it can be interpreted as repeating the vector \c v four times to +form a four-by-two matrix which is then added to \c mat: +\f[ +\begin{bmatrix} 1 & 2 & 6 & 9 \\ 3 & 1 & 7 & 2 \end{bmatrix} ++ \begin{bmatrix} 0 & 0 & 0 & 0 \\ 1 & 1 & 1 & 1 \end{bmatrix} += \begin{bmatrix} 1 & 2 & 6 & 9 \\ 4 & 2 & 8 & 3 \end{bmatrix}. +\f] +The operators -=, + and - can also be used column-wise and row-wise. On arrays, we +can also use the operators *=, /=, * and / to perform coefficient-wise +multiplication and division column-wise or row-wise. These operators are not available on matrices because it +is not clear what they would do. If you want multiply column 0 of a matrix \c mat with \c v(0), column 1 with +\c v(1), and so on, then use mat = mat * v.asDiagonal(). + It is important to point out that the vector to be added column-wise or row-wise must be of type Vector, and cannot be a Matrix. If this is not met then you will get compile-time error. This also means that broadcasting operations can only be applied with an object of type Vector, when operating with Matrix. -The same applies for the Array class, where the equivalent for VectorXf is ArrayXf. +The same applies for the Array class, where the equivalent for VectorXf is ArrayXf. As always, you should +not mix arrays and matrices in the same expression. -Therefore, to perform the same operation row-wise we can do: +To perform the same operation row-wise we can do: diff --git a/gtsam/3rdparty/Eigen/doc/C08_TutorialGeometry.dox b/gtsam/3rdparty/Eigen/doc/C08_TutorialGeometry.dox index 452abda10..b9e9eba12 100644 --- a/gtsam/3rdparty/Eigen/doc/C08_TutorialGeometry.dox +++ b/gtsam/3rdparty/Eigen/doc/C08_TutorialGeometry.dox @@ -45,16 +45,17 @@ But note that unfortunately, because of how C++ works, you can \b not do this: Rotation2D rot2(angle_in_radian);\endcode +AngleAxis aa(angle_in_radian, Vector3f(ax,ay,az));\endcode +The axis vector must be normalized. +Scaling(sx, sy) +Scaling(sx, sy, sz) +Scaling(s) +Scaling(vecN)\endcode +Transform t = Translation3f(p) * AngleAxisf(a,axis) * Scaling(s);\endcode +Matrix t = Rotation2Df(a) * Scaling(s); +Matrix t = AngleAxisf(a,axis) * Scaling(s);\endcode
Example:Output:
3D rotation as an \ref AngleAxis "angle + axis"\code -AngleAxis aa(angle_in_radian, Vector3f(ax,ay,az));\endcode
3D rotation as a \ref Quaternion "quaternion"\code Quaternion q; q = AngleAxis(angle_in_radian, axis);\endcode
N-D Scaling\code -Scaling(sx, sy) -Scaling(sx, sy, sz) -Scaling(s) -Scaling(vecN)\endcode
N-D Translation\code Translation(tx, ty) @@ -64,13 +65,13 @@ Translation(vecN)\endcode
N-D \ref TutorialGeoTransform "Affine transformation"\code Transform t = concatenation_of_any_transformations; -Transform t = Translation3f(p) * AngleAxisf(a,axis) * Scaling3f(s);\endcode
N-D Linear transformations \n (pure rotations, \n scaling, etc.)\code Matrix t = concatenation_of_rotations_and_scalings; -Matrix t = Rotation2Df(a) * Scaling2f(s); -Matrix t = AngleAxisf(a,axis) * Scaling3f(s);\endcode
Notes on rotations\n To transform more than a single vector the preferred @@ -92,8 +93,8 @@ Rotation2Df r; r = Matrix2f(..); // assumes a pure rotation matrix AngleAxisf aa; aa = Quaternionf(..); AngleAxisf aa; aa = Matrix3f(..); // assumes a pure rotation matrix Matrix2f m; m = Rotation2Df(..); -Matrix3f m; m = Quaternionf(..); Matrix3f m; m = Scaling3f(..); -Affine3f m; m = AngleAxis3f(..); Affine3f m; m = Scaling3f(..); +Matrix3f m; m = Quaternionf(..); Matrix3f m; m = Scaling(..); +Affine3f m; m = AngleAxis3f(..); Affine3f m; m = Scaling(..); Affine3f m; m = Translation3f(..); Affine3f m; m = Matrix3f(..); \endcode
@@ -207,10 +208,10 @@ t.scale(s); t.prescale(Vector_(sx,sy,..)); t.prescale(s); \endcode\code -t *= Scaling_(sx,sy,..); -t *= Scaling_(s); -t = Scaling_(sx,sy,..) * t; -t = Scaling_(s) * t; +t *= Scaling(sx,sy,..); +t *= Scaling(s); +t = Scaling(sx,sy,..) * t; +t = Scaling(s) * t; \endcode Shear transformation \n ( \b 2D \b only ! )\code t.shear(sx,sy); @@ -224,7 +225,7 @@ Note that in both API, any many transformations can be concatenated in a single t.pretranslate(..).rotate(..).translate(..).scale(..); \endcode \code -t = Translation_(..) * t * RotationType(..) * Translation_(..) * Scaling_(..); +t = Translation_(..) * t * RotationType(..) * Translation_(..) * Scaling(..); \endcode diff --git a/gtsam/3rdparty/Eigen/doc/C09_TutorialSparse.dox b/gtsam/3rdparty/Eigen/doc/C09_TutorialSparse.dox index 737f4cc09..34154bd0d 100644 --- a/gtsam/3rdparty/Eigen/doc/C09_TutorialSparse.dox +++ b/gtsam/3rdparty/Eigen/doc/C09_TutorialSparse.dox @@ -8,82 +8,144 @@ namespace Eigen { \b Table \b of \b contents \n - \ref TutorialSparseIntro + - \ref TutorialSparseExample "Example" + - \ref TutorialSparseSparseMatrix - \ref TutorialSparseFilling - - \ref TutorialSparseFeatureSet - \ref TutorialSparseDirectSolvers + - \ref TutorialSparseFeatureSet + - \ref TutorialSparse_BasicOps + - \ref TutorialSparse_Products + - \ref TutorialSparse_TriangularSelfadjoint + - \ref TutorialSparse_Submat + +
-\section TutorialSparseIntro Sparse matrix representations +Manipulating and solving sparse problems involves various modules which are summarized below: -In many applications (e.g., finite element methods) it is common to deal with very large matrices where only a few coefficients are different than zero. Both in term of memory consumption and performance, it is fundamental to use an adequate representation storing only nonzero coefficients. Such a matrix is called a sparse matrix. - -\b Declaring \b sparse \b matrices \b and \b vectors \n -The SparseMatrix class is the main sparse matrix representation of the Eigen's sparse module which offers high performance, low memory usage, and compatibility with most of sparse linear algebra packages. Because of its limited flexibility, we also provide a DynamicSparseMatrix variante taillored for low-level sparse matrix assembly. Both of them can be either row major or column major: - -\code -#include -SparseMatrix > m1(1000,2000); // declare a 1000x2000 col-major compressed sparse matrix of complex -SparseMatrix m2(1000,2000); // declare a 1000x2000 row-major compressed sparse matrix of double -DynamicSparseMatrix > m1(1000,2000); // declare a 1000x2000 col-major dynamic sparse matrix of complex -DynamicSparseMatrix m2(1000,2000); // declare a 1000x2000 row-major dynamic sparse matrix of double -\endcode - -Although a sparse matrix could also be used to represent a sparse vector, for that purpose it is better to use the specialized SparseVector class: -\code -SparseVector > v1(1000); // declare a column sparse vector of complex of size 1000 -SparseVector v2(1000); // declare a row sparse vector of double of size 1000 -\endcode -Note that here the size of a vector denotes its dimension and not the number of nonzero coefficients which is initially zero (like sparse matrices). - - -\b Overview \b of \b the \b internal \b sparse \b storage \n -In order to get the best of the Eigen's sparse objects, it is important to have a rough idea of the way they are internally stored. The SparseMatrix class implements the common and generic Compressed Column/Row Storage scheme. It consists of three compact arrays storing the values with their respective inner coordinates, and pointer indices to the begining of each outer vector. For instance, let \c m be a column-major sparse matrix. Then its nonzero coefficients are sequentially stored in memory in a column-major order (\em values). A second array of integer stores the respective row index of each coefficient (\em inner \em indices). Finally, a third array of integer, having the same length than the number of columns, stores the index in the previous arrays of the first element of each column (\em outer \em indices). - -Here is an example, with the matrix: - - - - - + + + + +
03000
2200017
75010
00000
001408
ModuleHeader fileContents
\link Sparse_Module SparseCore \endlink\code#include \endcodeSparseMatrix and SparseVector classes, matrix assembly, basic sparse linear algebra (including sparse triangular solvers)
\link SparseCholesky_Module SparseCholesky \endlink\code#include \endcodeDirect sparse LLT and LDLT Cholesky factorization to solve sparse self-adjoint positive definite problems
\link IterativeLinearSolvers_Module IterativeLinearSolvers \endlink\code#include \endcodeIterative solvers to solve large general linear square problems (including self-adjoint positive definite problems)
\code#include \endcodeIncludes all the above modules
-and its internal representation using the Compressed Column Storage format: +\section TutorialSparseIntro Sparse matrix representation + +In many applications (e.g., finite element methods) it is common to deal with very large matrices where only a few coefficients are different from zero. In such cases, memory consumption can be reduced and performance increased by using a specialized representation storing only the nonzero coefficients. Such a matrix is called a sparse matrix. + +\b The \b %SparseMatrix \b class + +The class SparseMatrix is the main sparse matrix representation of Eigen's sparse module; it offers high performance and low memory usage. +It implements a more versatile variant of the widely-used Compressed Column (or Row) Storage scheme. +It consists of four compact arrays: + - \c Values: stores the coefficient values of the non-zeros. + - \c InnerIndices: stores the row (resp. column) indices of the non-zeros. + - \c OuterStarts: stores for each column (resp. row) the index of the first non-zero in the previous two arrays. + - \c InnerNNZs: stores the number of non-zeros of each column (resp. row). +The word \c inner refers to an \em inner \em vector that is a column for a column-major matrix, or a row for a row-major matrix. +The word \c outer refers to the other direction. + +This storage scheme is better explained on an example. The following matrix + + + + + + +
03 00 0
220 0017
75 01 0
00 00 0
00140 8
+ +and one of its possible sparse, \b column \b major representation: + + + +
Values: 227_3514__1_178
InnerIndices: 12_02 4__2_ 14
+ + + +
OuterStarts:035810\em 12
InnerNNZs: 2211 2
+ +Currently the elements of a given inner vector are guaranteed to be always sorted by increasing inner indices. +The \c "_" indicates available free space to quickly insert new elements. +Assuming no reallocation is needed, the insertion of a random element is therefore in O(nnz_j) where nnz_j is the number of nonzeros of the respective inner vector. +On the other hand, inserting elements with increasing inner indices in a given inner vector is much more efficient since this only requires to increase the respective \c InnerNNZs entry that is a O(1) operation. + +The case where no empty space is available is a special case, and is refered as the \em compressed mode. +It corresponds to the widely used Compressed Column (or Row) Storage schemes (CCS or CRS). +Any SparseMatrix can be turned to this form by calling the SparseMatrix::makeCompressed() function. +In this case, one can remark that the \c InnerNNZs array is redundant with \c OuterStarts because we the equality: \c InnerNNZs[j] = \c OuterStarts[j+1]-\c OuterStarts[j]. +Therefore, in practice a call to SparseMatrix::makeCompressed() frees this buffer. + +It is worth noting that most of our wrappers to external libraries requires compressed matrices as inputs. + +The results of %Eigen's operations always produces \b compressed sparse matrices. +On the other hand, the insertion of a new element into a SparseMatrix converts this later to the \b uncompressed mode. + +Here is the previous matrix represented in compressed mode: - + +
Values: 22735141178
Inner indices: 1202 42 14
InnerIndices: 1202 42 14
+ +
OuterStarts:02456\em 8
-Outer indices:
02456\em 7
-As you might guess, here the storage order is even more important than with dense matrices. We will therefore often make a clear difference between the \em inner and \em outer dimensions. For instance, it is efficient to loop over the coefficients of an \em inner \em vector (e.g., a column of a column-major matrix), but completely inefficient to do the same for an \em outer \em vector (e.g., a row of a column-major matrix). +A SparseVector is a special case of a SparseMatrix where only the \c Values and \c InnerIndices arrays are stored. +There is no notion of compressed/uncompressed mode for a SparseVector. -The SparseVector class implements the same compressed storage scheme but, of course, without any outer index buffer. -Since all nonzero coefficients of such a matrix are sequentially stored in memory, inserting a new nonzero near the "beginning" of the matrix can be extremely costly. As described below (\ref TutorialSparseFilling), one strategy is to fill nonzero coefficients in order. In cases where this is not possible, Eigen's sparse module also provides a DynamicSparseMatrix class which allows efficient random insertion. DynamicSparseMatrix is essentially implemented as an array of SparseVector, where the values and inner-indices arrays have been split into multiple small and resizable arrays. Assuming the number of nonzeros per inner vector is relatively small, this modification allows for very fast random insertion at the cost of a slight memory overhead (due to extra memory preallocated by each inner vector to avoid an expensive memory reallocation at every insertion) and a loss of compatibility with other sparse libraries used by some of our high-level solvers. Once complete, a DynamicSparseMatrix can be converted to a SparseMatrix to permit usage of these sparse libraries. +\section TutorialSparseExample First example -To summarize, it is recommended to use SparseMatrix whenever possible, and reserve the use of DynamicSparseMatrix to assemble a sparse matrix in cases when a SparseMatrix is not flexible enough. The respective pros/cons of both representations are summarized in the following table: +Before describing each individual class, let's start with the following typical example: solving the Lapace equation \f$ \nabla u = 0 \f$ on a regular 2D grid using a finite difference scheme and Dirichlet boundary conditions. +Such problem can be mathematically expressed as a linear problem of the form \f$ Ax=b \f$ where \f$ x \f$ is the vector of \c m unknowns (in our case, the values of the pixels), \f$ b \f$ is the right hand side vector resulting from the boundary conditions, and \f$ A \f$ is an \f$ m \times m \f$ matrix containing only a few non-zero elements resulting from the discretization of the Laplacian operator. - - - - - - - - - - - - - -
SparseMatrixDynamicSparseMatrix
memory efficiency*****
sorted insertion******
random insertion \n in sorted inner vector****
sorted insertion \n in random inner vector-***
random insertion-**
coeff wise unary operators******
coeff wise binary operators******
matrix products*****(*)
transpose*****
redux*****
*= scalar*****
Compatibility with highlevel solvers \n (TAUCS, Cholmod, SuperLU, UmfPack)***-
+ +\include Tutorial_sparse_example.cpp + + +\image html Tutorial_sparse_example.jpeg + + +In this example, we start by defining a column-major sparse matrix type of double \c SparseMatrix, and a triplet list of the same scalar type \c Triplet. A triplet is a simple object representing a non-zero entry as the triplet: \c row index, \c column index, \c value. + +In the main function, we declare a list \c coefficients of triplets (as a std vector) and the right hand side vector \f$ b \f$ which are filled by the \a buildProblem function. +The raw and flat list of non-zero entries is then converted to a true SparseMatrix object \c A. +Note that the elements of the list do not have to be sorted, and possible duplicate entries will be summed up. + +The last step consists of effectively solving the assembled problem. +Since the resulting matrix \c A is symmetric by construction, we can perform a direct Cholesky factorization via the SimplicialLDLT class which behaves like its LDLT counterpart for dense objects. + +The resulting vector \c x contains the pixel values as a 1D array which is saved to a jpeg file shown on the right of the code above. + +Describing the \a buildProblem and \a save functions is out of the scope of this tutorial. They are given \ref TutorialSparse_example_details "here" for the curious and reproducibility purpose. -\b Matrix \b and \b vector \b properties \n -Here mat and vec represent any sparse-matrix and sparse-vector type, respectively. +\section TutorialSparseSparseMatrix The SparseMatrix class + +\b %Matrix \b and \b vector \b properties \n + +The SparseMatrix and SparseVector classes take three template arguments: + * the scalar type (e.g., double) + * the storage order (ColMajor or RowMajor, the default is RowMajor) + * the inner index type (default is \c int). + +As for dense Matrix objects, constructors takes the size of the object. +Here are some examples: + +\code +SparseMatrix > mat(1000,2000); // declares a 1000x2000 column-major compressed sparse matrix of complex +SparseMatrix mat(1000,2000); // declares a 1000x2000 row-major compressed sparse matrix of double +SparseVector > vec(1000); // declares a column sparse vector of complex of size 1000 +SparseVector vec(1000); // declares a row sparse vector of double of size 1000 +\endcode + +In the rest of the tutorial, \c mat and \c vec represent any sparse-matrix and sparse-vector objects, respectively. + +The dimensions of a matrix can be queried using the following functions: \b Iterating \b over \b the \b nonzero \b coefficients \n -Iterating over the coefficients of a sparse matrix can be done only in the same order as the storage order. Here is an example: +Random access to the elements of a sparse object can be done through the \c coeffRef(i,j) function. +However, this function involves a quite expensive binary search. +In most cases, one only wants to iterate over the non-zeros elements. This is achieved by a standard loop over the outer dimension, and then by iterating over the non-zeros of the current inner vector via an InnerIterator. Thus, the non-zero entries have to be visited in the same order than the storage order. +Here is an example:
Standard \n dimensions\code mat.rows() @@ -105,13 +167,16 @@ vec.nonZeros() \endcode
\code -SparseMatrixType mat(rows,cols); -for (int k=0; k mat(rows,cols); +for (int k=0; k::InnerIterator it(mat,k); it; ++it) { it.value(); it.row(); // row index @@ -130,129 +195,258 @@ for (SparseVector::InnerIterator it(vec); it; ++it) \endcode
+For a writable expression, the referenced value can be modified using the valueRef() function. +If the type of the sparse matrix or vector depends on a template parameter, then the \c typename keyword is +required to indicate that \c InnerIterator denotes a type; see \ref TopicTemplateKeyword for details. \section TutorialSparseFilling Filling a sparse matrix -Owing to the special storage scheme of a SparseMatrix, it is obvious that for performance reasons a sparse matrix cannot be filled as easily as a dense matrix. For instance the cost of a purely random insertion into a SparseMatrix is in O(nnz) where nnz is the current number of non zeros. In order to cover all uses cases with best efficiency, Eigen provides various mechanisms, from the easiest but slowest, to the fastest but restrictive one. +Because of the special storage scheme of a SparseMatrix, special care has to be taken when adding new nonzero entries. +For instance, the cost of a single purely random insertion into a SparseMatrix is \c O(nnz), where \c nnz is the current number of non-zero coefficients. -If you don't have any prior knowledge about the order your matrix will be filled, then the best choice is to use a DynamicSparseMatrix. With a DynamicSparseMatrix, you can add or modify any coefficients at any time using the coeffRef(row,col) method. Here is an example: +The simplest way to create a sparse matrix while guaranteeing good performance is thus to first build a list of so-called \em triplets, and then convert it to a SparseMatrix. + +Here is a typical usage example: \code -DynamicSparseMatrix aux(1000,1000); -aux.reserve(estimated_number_of_non_zero); // optional -for (...) - for each j // the j can be random - for each i interacting with j // the i can be random - aux.coeffRef(i,j) += foo(i,j); -\endcode -Then the DynamicSparseMatrix object can be converted to a compact SparseMatrix to be used, e.g., by one of our supported solver: -\code -SparseMatrix mat(aux); -\endcode - -In order to optimize this process, instead of the generic coeffRef(i,j) method one can also use: - - \code m.insert(i,j) = value; \endcode which assumes the coefficient of coordinate (row,col) does not already exist (otherwise this is a programming error and your program will stop). - - \code m.insertBack(i,j) = value; \endcode which, in addition to the requirements of insert(), also assumes that the coefficient of coordinate (row,col) will be inserted at the end of the target inner-vector. More precisely, if the matrix m is column major, then the row index of the last non zero coefficient of the j-th column must be smaller than i. - - -Actually, the SparseMatrix class also supports random insertion via the insert() method. However, its uses should be reserved in cases where the inserted non zero is nearly the last one of the compact storage array. In practice, this means it should be used only to perform random (or sorted) insertion into the current inner-vector while filling the inner-vectors in an increasing order. Moreover, with a SparseMatrix an insertion session must be closed by a call to finalize() before any use of the matrix. Here is an example for a column major matrix: - -\code -SparseMatrix mat(1000,1000); -mat.reserve(estimated_number_of_non_zero); // optional -for each j // should be in increasing order for performance reasons - for each i interacting with j // the i can be random - mat.insert(i,j) = foo(i,j); // optional for a DynamicSparseMatrix -mat.finalize(); -\endcode - -Finally, the fastest way to fill a SparseMatrix object is to insert the elements in a purely coherence order (increasing inner index per increasing outer index). To this end, Eigen provides a very low but optimal API and illustrated below: - -\code -SparseMatrix mat(1000,1000); -mat.reserve(estimated_number_of_non_zero); // optional -for(int j=0; j<1000; ++j) +typedef Eigen::Triplet T; +std::vector tripletList; +triplets.reserve(estimation_of_entries); +for(...) { - mat.startVec(j); // optional for a DynamicSparseMatrix - for each i interacting with j // with increasing i - mat.insertBack(i,j) = foo(i,j); + // ... + tripletList.push_back(T(i,j,v_ij)); } -mat.finalize(); // optional for a DynamicSparseMatrix +SparseMatrixType mat(rows,cols); +mat.setFromTriplets(tripletList.begin(), tripletList.end()); +// mat is ready to go! \endcode -Note that there also exist the insertBackByOuterInner(Index outer, Index, inner) function which allows to write code agnostic to the storage order. +The \c std::vector of triplets might contain the elements in arbitrary order, and might even contain duplicated elements that will be summed up by setFromTriplets(). +See the SparseMatrix::setFromTriplets() function and class Triplet for more details. -\section TutorialSparseFeatureSet Supported operators and functions -In the following \em sm denote a sparse matrix, \em sv a sparse vector, \em dm a dense matrix, and \em dv a dense vector. -In Eigen's sparse module we chose to expose only the subset of the dense matrix API which can be efficiently implemented. Moreover, all combinations are not always possible. For instance, it is not possible to add two sparse matrices having two different storage order. On the other hand it is perfectly fine to evaluate a sparse matrix/expression to a matrix having a different storage order: +In some cases, however, slightly higher performance, and lower memory consumption can be reached by directly inserting the non-zeros into the destination matrix. +A typical scenario of this approach is illustrated bellow: \code -SparseMatrixType sm1, sm2, sm3; -sm3 = sm1.transpose() + sm2; // invalid -sm3 = SparseMatrixType(sm1.transpose()) + sm2; // correct +1: SparseMatrix mat(rows,cols); // default is column major +2: mat.reserve(VectorXi::Constant(cols,6)); +3: for each i,j such that v_ij != 0 +4: mat.insert(i,j) = v_ij; // alternative: mat.coeffRef(i,j) += v_ij; +5: mat.makeCompressed(); // optional \endcode -Here are some examples of the supported operations: +- The key ingredient here is the line 2 where we reserve room for 6 non-zeros per column. In many cases, the number of non-zeros per column or row can easily be known in advance. If it varies significantly for each inner vector, then it is possible to specify a reserve size for each inner vector by providing a vector object with an operator[](int j) returning the reserve size of the \c j-th inner vector (e.g., via a VectorXi or std::vector). If only a rought estimate of the number of nonzeros per inner-vector can be obtained, it is highly recommended to overestimate it rather than the opposite. If this line is omitted, then the first insertion of a new element will reserve room for 2 elements per inner vector. +- The line 4 performs a sorted insertion. In this example, the ideal case is when the \c j-th column is not full and contains non-zeros whose inner-indices are smaller than \c i. In this case, this operation boils down to trivial O(1) operation. +- When calling insert(i,j) the element \c i \c ,j must not already exists, otherwise use the coeffRef(i,j) method that will allow to, e.g., accumulate values. This method first performs a binary search and finally calls insert(i,j) if the element does not already exist. It is more flexible than insert() but also more costly. +- The line 5 suppresses the remaining empty space and transforms the matrix into a compressed column storage. + + +\section TutorialSparseDirectSolvers Solving linear problems + +%Eigen currently provides a limited set of built-in solvers, as well as wrappers to external solver libraries. +They are summarized in the following table: + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
ClassModuleSolver kindMatrix kindFeatures related to performanceDependencies,License

Notes

SimplicialLLT \link SparseCholesky_Module SparseCholesky \endlinkDirect LLt factorizationSPDFill-in reducingbuilt-in, LGPLSimplicialLDLT is often preferable
SimplicialLDLT \link SparseCholesky_Module SparseCholesky \endlinkDirect LDLt factorizationSPDFill-in reducingbuilt-in, LGPLRecommended for very sparse and not too large problems (e.g., 2D Poisson eq.)
ConjugateGradient\link IterativeLinearSolvers_Module IterativeLinearSolvers \endlinkClassic iterative CGSPDPreconditionningbuilt-in, LGPLRecommended for large symmetric problems (e.g., 3D Poisson eq.)
BiCGSTAB\link IterativeLinearSolvers_Module IterativeLinearSolvers \endlinkIterative stabilized bi-conjugate gradientSquarePreconditionningbuilt-in, LGPLMight not always converge
PastixLLT \n PastixLDLT \n PastixLU\link PaStiXSupport_Module PaStiXSupport \endlinkDirect LLt, LDLt, LU factorizationsSPD \n SPD \n SquareFill-in reducing, Leverage fast dense algebra, MultithreadingRequires the PaStiX package, \b CeCILL-C optimized for tough problems and symmetric patterns
CholmodSupernodalLLT\link CholmodSupport_Module CholmodSupport \endlinkDirect LLt factorizationSPDFill-in reducing, Leverage fast dense algebraRequires the SuiteSparse package, \b GPL
UmfPackLU\link UmfPackSupport_Module UmfPackSupport \endlinkDirect LU factorizationSquareFill-in reducing, Leverage fast dense algebraRequires the SuiteSparse package, \b GPL
SuperLU\link SuperLUSupport_Module SuperLUSupport \endlinkDirect LU factorizationSquareFill-in reducing, Leverage fast dense algebraRequires the SuperLU library, (BSD-like)
+ +Here \c SPD means symmetric positive definite. + +All these solvers follow the same general concept. +Here is a typical and general example: \code -s_1 *= 0.5; -sm4 = sm1 + sm2 + sm3; // only if s_1, s_2 and s_3 have the same storage order -sm3 = sm1 * sm2; -dv3 = sm1 * dv2; -dm3 = sm1 * dm2; -dm3 = dm2 * sm1; -sm3 = sm1.cwiseProduct(sm2); // only if s_1 and s_2 have the same storage order -dv2 = sm1.triangularView().solve(dv2); -\endcode - -The product of a sparse matrix A by a dense matrix/vector dv with A symmetric can be optimized by telling that to Eigen: -\code -res = A.selfadjointView<>() * dv; // if all coefficients of A are stored -res = A.selfadjointView() * dv; // if only the upper part of A is stored -res = A.selfadjointView() * dv; // if only the lower part of A is stored -\endcode - - -\section TutorialSparseDirectSolvers Using the direct solvers - -To solve a sparse problem you currently have to use one or multiple of the following "unsupported" module: -- \ref SparseExtra_Module - - \b solvers: SparseLLT, SparseLDLT (\#include ) - - \b notes: built-in basic LLT and LDLT solvers -- \ref CholmodSupport_Module - - \b solver: SparseLLT (\#include ) - - \b notes: LLT solving using Cholmod, requires a SparseMatrix object. (recommended for symmetric/selfadjoint problems) -- \ref UmfPackSupport_Module - - \b solver: SparseLU (\#include ) - - \b notes: LU solving using UmfPack, requires a SparseMatrix object (recommended for squared matrices) -- \ref SuperLUSupport_Module - - \b solver: SparseLU (\#include ) - - \b notes: (LU solving using SuperLU, requires a SparseMatrix object, recommended for squared matrices) -- \ref TaucsSupport_Module - - \b solver: SparseLLT (\#include ) - - \b notes: LLT solving using Taucs, requires a SparseMatrix object (not recommended) - -\warning Those modules are currently considered to be "unsupported" because 1) they are not documented, and 2) their API is likely to change in the future. - -Here is a typical example: -\code -#include +#include // ... SparseMatrix A; // fill A VectorXd b, x; // fill b -// solve Ax = b using UmfPack: -SparseLU,UmfPack> lu_of_A(A); -if(!lu_of_A.succeeded()) { - // decomposiiton failed +// solve Ax = b +SolverClassName > solver; +solver.compute(A); +if(solver.info()!=Succeeded) { + // decomposition failed return; } -if(!lu_of_A.solve(b,&x)) { +x = solver.solve(b); +if(solver.info()!=Succeeded) { // solving failed return; } +// solve for another right hand side: +x1 = solver.solve(b1); \endcode -See also the class SparseLLT, class SparseLU, and class SparseLDLT. +For \c SPD solvers, a second optional template argument allows to specify which triangular part have to be used, e.g.: + +\code +#include + +ConjugateGradient, Eigen::Upper> solver; +x = solver.compute(A).solve(b); +\endcode +In the above example, only the upper triangular part of the input matrix A is considered for solving. The opposite triangle might either be empty or contain arbitrary values. + +In the case where multiple problems with the same sparcity pattern have to be solved, then the "compute" step can be decomposed as follow: +\code +SolverClassName > solver; +solver.analyzePattern(A); // for this step the numerical values of A are not used +solver.factorize(A); +x1 = solver.solve(b1); +x2 = solver.solve(b2); +... +A = ...; // modify the values of the nonzeros of A, the nonzeros pattern must stay unchanged +solver.factorize(A); +x1 = solver.solve(b1); +x2 = solver.solve(b2); +... +\endcode +The compute() method is equivalent to calling both analyzePattern() and factorize(). + +Finally, each solver provides some specific features, such as determinant, access to the factors, controls of the iterations, and so on. +More details are availble in the documentations of the respective classes. + + +\section TutorialSparseFeatureSet Supported operators and functions + +Because of their special storage format, sparse matrices cannot offer the same level of flexbility than dense matrices. +In Eigen's sparse module we chose to expose only the subset of the dense matrix API which can be efficiently implemented. +In the following \em sm denotes a sparse matrix, \em sv a sparse vector, \em dm a dense matrix, and \em dv a dense vector. + +\subsection TutorialSparse_BasicOps Basic operations + +%Sparse expressions support most of the unary and binary coefficient wise operations: +\code +sm1.real() sm1.imag() -sm1 0.5*sm1 +sm1+sm2 sm1-sm2 sm1.cwiseProduct(sm2) +\endcode +However, a strong restriction is that the storage orders must match. For instance, in the following example: +\code +sm4 = sm1 + sm2 + sm3; +\endcode +sm1, sm2, and sm3 must all be row-major or all column major. +On the other hand, there is no restriction on the target matrix sm4. +For instance, this means that for computing \f$ A^T + A \f$, the matrix \f$ A^T \f$ must be evaluated into a temporary matrix of compatible storage order: +\code +SparseMatrix A, B; +B = SparseMatrix(A.transpose()) + A; +\endcode + +Binary coefficient wise operators can also mix sparse and dense expressions: +\code +sm2 = sm1.cwiseProduct(dm1); +dm2 = sm1 + dm1; +\endcode + + +%Sparse expressions also support transposition: +\code +sm1 = sm2.transpose(); +sm1 = sm2.adjoint(); +\endcode +However, there is no transposeInPlace() method. + + +\subsection TutorialSparse_Products Matrix products + +%Eigen supports various kind of sparse matrix products which are summarize below: + - \b sparse-dense: + \code +dv2 = sm1 * dv1; +dm2 = dm1 * sm1.adjoint(); +dm2 = 2. * sm1 * dm1; + \endcode + - \b symmetric \b sparse-dense. The product of a sparse symmetric matrix with a dense matrix (or vector) can also be optimized by specifying the symmetry with selfadjointView(): + \code +dm2 = sm1.selfadjointView<>() * dm1; // if all coefficients of A are stored +dm2 = A.selfadjointView() * dm1; // if only the upper part of A is stored +dm2 = A.selfadjointView() * dm1; // if only the lower part of A is stored + \endcode + - \b sparse-sparse. For sparse-sparse products, two different algorithms are available. The default one is conservative and preserve the explicit zeros that might appear: + \code +sm3 = sm1 * sm2; +sm3 = 4 * sm1.adjoint() * sm2; + \endcode + The second algorithm prunes on the fly the explicit zeros, or the values smaller than a given threshold. It is enabled and controlled through the prune() functions: + \code +sm3 = (sm1 * sm2).prune(); // removes numerical zeros +sm3 = (sm1 * sm2).prune(ref); // removes elements much smaller than ref +sm3 = (sm1 * sm2).prune(ref,epsilon); // removes elements smaller than ref*epsilon + \endcode + + - \b permutations. Finally, permutations can be applied to sparse matrices too: + \code +PermutationMatrix P = ...; +sm2 = P * sm1; +sm2 = sm1 * P.inverse(); +sm2 = sm1.transpose() * P; + \endcode + + +\subsection TutorialSparse_TriangularSelfadjoint Triangular and selfadjoint views + +Just as with dense matrices, the triangularView() function can be used to address a triangular part of the matrix, and perform triangular solves with a dense right hand side: +\code +dm2 = sm1.triangularView(dm1); +dv2 = sm1.transpose().triangularView(dv1); +\endcode + +The selfadjointView() function permits various operations: + - optimized sparse-dense matrix products: + \code +dm2 = sm1.selfadjointView<>() * dm1; // if all coefficients of A are stored +dm2 = A.selfadjointView() * dm1; // if only the upper part of A is stored +dm2 = A.selfadjointView() * dm1; // if only the lower part of A is stored + \endcode + - copy of triangular parts: + \code +sm2 = sm1.selfadjointView(); // makes a full selfadjoint matrix from the upper triangular part +sm2.selfadjointView() = sm1.selfadjointView(); // copies the upper triangular part to the lower triangular part + \endcode + - application of symmetric permutations: + \code +PermutationMatrix P = ...; +sm2 = A.selfadjointView().twistedBy(P); // compute P S P' from the upper triangular part of A, and make it a full matrix +sm2.selfadjointView() = A.selfadjointView().twistedBy(P); // compute P S P' from the lower triangular part of A, and then only compute the lower part + \endcode + +\subsection TutorialSparse_Submat Sub-matrices + +%Sparse matrices does not support yet the addressing of arbitrary sub matrices. Currently, one can only reference a set of contiguous \em inner vectors, i.e., a set of contiguous rows for a row-major matrix, or a set of contiguous columns for a column major matrix: +\code + sm1.innerVector(j); // returns an expression of the j-th column (resp. row) of the matrix if sm1 is col-major (resp. row-major) + sm1.innerVectors(j, nb); // returns an expression of the nb columns (resp. row) starting from the j-th column (resp. row) + // of the matrix if sm1 is col-major (resp. row-major) + sm1.middleRows(j, nb); // for row major matrices only, get a range of nb rows + sm1.middleCols(j, nb); // for column major matrices only, get a range of nb columns +\endcode \li \b Next: \ref TutorialMapClass diff --git a/gtsam/3rdparty/Eigen/doc/CMakeLists.txt b/gtsam/3rdparty/Eigen/doc/CMakeLists.txt index 50ce7ee0c..96bff41bf 100644 --- a/gtsam/3rdparty/Eigen/doc/CMakeLists.txt +++ b/gtsam/3rdparty/Eigen/doc/CMakeLists.txt @@ -36,6 +36,7 @@ set(snippets_targets "") add_definitions("-DEIGEN_MAKING_DOCS") add_subdirectory(examples) +add_subdirectory(special_examples) add_subdirectory(snippets) add_custom_target( diff --git a/gtsam/3rdparty/Eigen/doc/D09_StructHavingEigenMembers.dox b/gtsam/3rdparty/Eigen/doc/D09_StructHavingEigenMembers.dox index d6a24d951..51789ca9c 100644 --- a/gtsam/3rdparty/Eigen/doc/D09_StructHavingEigenMembers.dox +++ b/gtsam/3rdparty/Eigen/doc/D09_StructHavingEigenMembers.dox @@ -10,6 +10,7 @@ namespace Eigen { - \ref movetotop - \ref bugineigen - \ref conditional + - \ref othersolutions \section summary Executive Summary @@ -55,6 +56,8 @@ Foo *foo = new Foo; This macro makes "new Foo" always return an aligned pointer. +If this approach is too intrusive, see also the \ref othersolutions. + \section why Why is this needed? OK let's say that your code looks like this: @@ -132,6 +135,64 @@ Foo<4> *foo4 = new Foo<4>; // foo4 is guaranteed to be 128bit-aligned Foo<3> *foo3 = new Foo<3>; // foo3 has only the system default alignment guarantee \endcode + +\section othersolutions Other solutions + +In case putting the EIGEN_MAKE_ALIGNED_OPERATOR_NEW macro everywhere is too intrusive, there exists at least two other solutions. + +\subsection othersolutions1 Disabling alignment + +The first is to disable alignment requirement for the fixed size members: +\code +class Foo +{ + ... + Eigen::Matrix v; + ... +}; +\endcode +This has for effect to disable vectorization when using \c v. +If a function of Foo uses it several times, then it still possible to re-enable vectorization by copying it into an aligned temporary vector: +\code +void Foo::bar() +{ + Eigen::Vector2d av(v); + // use av instead of v + ... + // if av changed, then do: + v = av; +} +\endcode + +\subsection othersolutions2 Private structure + +The second consist in storing the fixed-size objects into a private struct which will be dynamically allocated at the construction time of the main object: + +\code +struct Foo_d +{ + EIGEN_MAKE_ALIGNED_OPERATOR_NEW + Vector2d v; + ... +}; + + +struct Foo { + Foo() { init_d(); } + ~Foo() { delete d; } + void bar() + { + // use d->v instead of v + ... + } +private: + void init_d() { d = new Foo_d; } + Foo_d* d; +}; +\endcode + +The clear advantage here is that the class Foo remains unchanged regarding alignment issues. The drawback is that a heap allocation will be required whatsoever. + */ } diff --git a/gtsam/3rdparty/Eigen/doc/Doxyfile.in b/gtsam/3rdparty/Eigen/doc/Doxyfile.in index 6a659d9c2..e9e89d486 100644 --- a/gtsam/3rdparty/Eigen/doc/Doxyfile.in +++ b/gtsam/3rdparty/Eigen/doc/Doxyfile.in @@ -108,7 +108,7 @@ ALWAYS_DETAILED_SEC = NO # members were ordinary class members. Constructors, destructors and assignment # operators of the base classes will not be shown. -INLINE_INHERITED_MEMB = NO +INLINE_INHERITED_MEMB = YES # If the FULL_PATH_NAMES tag is set to YES then Doxygen will prepend the full # path before files name in the file list and in the header files. If set @@ -206,7 +206,6 @@ ALIASES = "only_for_vectors=This is only for vectors (either row- "qr_module=This is defined in the %QR module. \code #include \endcode" \ "svd_module=This is defined in the %SVD module. \code #include \endcode" \ "label=\bug" \ - "redstar=*" \ "matrixworld=*" \ "arrayworld=*" \ "note_about_arbitrary_choice_of_solution=If there exists more than one solution, this method will arbitrarily choose one." \ @@ -303,7 +302,7 @@ TYPEDEF_HIDES_STRUCT = NO # Private class members and static file members will be hidden unless # the EXTRACT_PRIVATE and EXTRACT_STATIC tags are set to YES -EXTRACT_ALL = NO +EXTRACT_ALL = YES # If the EXTRACT_PRIVATE tag is set to YES all private members of a class # will be included in the documentation. @@ -561,8 +560,7 @@ WARN_LOGFILE = # with spaces. INPUT = "${Eigen_SOURCE_DIR}/Eigen" \ - "${Eigen_SOURCE_DIR}/doc" \ - "${Eigen_BINARY_DIR}/doc" + "${Eigen_SOURCE_DIR}/doc" # This tag can be used to specify the character encoding of the source files # that doxygen parses. Internally doxygen uses the UTF-8 encoding, which is @@ -585,13 +583,17 @@ FILE_PATTERNS = * # should be searched for input files as well. Possible values are YES and NO. # If left blank NO is used. -RECURSIVE = NO +RECURSIVE = YES # The EXCLUDE tag can be used to specify files and/or directories that should # excluded from the INPUT source files. This way you can easily exclude a # subdirectory from a directory tree whose root is specified with the INPUT tag. -EXCLUDE = +EXCLUDE = "${Eigen_SOURCE_DIR}/Eigen/Eigen2Support" \ + "${Eigen_SOURCE_DIR}/Eigen/src/Eigen2Support" \ + "${Eigen_SOURCE_DIR}/doc/examples" \ + "${Eigen_SOURCE_DIR}/doc/special_examples" \ + "${Eigen_SOURCE_DIR}/doc/snippets" # The EXCLUDE_SYMLINKS tag can be used select whether or not files or # directories that are symbolic links (a Unix filesystem feature) are excluded @@ -627,10 +629,8 @@ EXCLUDE_PATTERNS = CMake* \ # wildcard * is used, a substring. Examples: ANamespace, AClass, # AClass::ANamespace, ANamespace::*Test -# This is used to clean up the "class hierarchy" page - -EXCLUDE_SYMBOLS = EigenBase<* SparseMatrixBase<* DenseBase<* MatrixBase<* Matrix<* \ - ProductReturnType<* RotationBase<* Stride<* BandMatrix<* Block<* +# This could used to clean up the "class hierarchy" page +EXCLUDE_SYMBOLS = internal::* Flagged* *InnerIterator* DenseStorage<* # The EXAMPLE_PATH tag can be used to specify one or more files or # directories that contain example code fragments that are included (see @@ -639,7 +639,9 @@ EXCLUDE_SYMBOLS = EigenBase<* SparseMatrixBase<* DenseBase<* MatrixBase<* EXAMPLE_PATH = "${Eigen_SOURCE_DIR}/doc/snippets" \ "${Eigen_BINARY_DIR}/doc/snippets" \ "${Eigen_SOURCE_DIR}/doc/examples" \ - "${Eigen_BINARY_DIR}/doc/examples" + "${Eigen_BINARY_DIR}/doc/examples" \ + "${Eigen_SOURCE_DIR}/doc/special_examples" \ + "${Eigen_BINARY_DIR}/doc/special_examples" # If the value of the EXAMPLE_PATH tag contains directories, you can use the # EXAMPLE_PATTERNS tag to specify one or more wildcard pattern (like *.cpp @@ -1229,7 +1231,8 @@ EXPAND_AS_DEFINED = EIGEN_MAKE_TYPEDEFS \ EIGEN_CWISE_BINOP_RETURN_TYPE \ EIGEN_CWISE_PRODUCT_RETURN_TYPE \ EIGEN_CURRENT_STORAGE_BASE_CLASS \ - _EIGEN_GENERIC_PUBLIC_INTERFACE + _EIGEN_GENERIC_PUBLIC_INTERFACE \ + EIGEN2_SUPPORT # If the SKIP_FUNCTION_MACROS tag is set to YES (the default) then # doxygen's preprocessor will remove all function-like macros that are alone diff --git a/gtsam/3rdparty/Eigen/doc/I00_CustomizingEigen.dox b/gtsam/3rdparty/Eigen/doc/I00_CustomizingEigen.dox index 766ff6f95..623ef31e1 100644 --- a/gtsam/3rdparty/Eigen/doc/I00_CustomizingEigen.dox +++ b/gtsam/3rdparty/Eigen/doc/I00_CustomizingEigen.dox @@ -120,19 +120,22 @@ Eigen::MatrixBase, 10000, 1, 2, 10000, 1> \anchor user_defined_scalars \section CustomScalarType Using custom scalar types -By default, Eigen currently supports the following scalar types: \c int, \c float, \c double, \c std::complex, \c std::complex, \c long \c double, \c long \c long \c int (64 bits integers), and \c bool. The \c long \c double is especially useful on x86-64 systems or when the SSE2 instruction set is enabled because it enforces the use of x87 registers with extended accuracy. +By default, Eigen currently supports standard floating-point types (\c float, \c double, \c std::complex, \c std::complex, \c long \c double), as well as all integrale types (e.g., \c int, \c unsigned \c int, \c short, etc.), and \c bool. +On x86-64 systems, \c long \c double permits to locally enforces the use of x87 registers with extended accuracy (in comparison to SSE). In order to add support for a custom type \c T you need: - 1 - make sure the common operator (+,-,*,/,etc.) are supported by the type \c T - 2 - add a specialization of struct Eigen::NumTraits (see \ref NumTraits) - 3 - define a couple of math functions for your type such as: internal::sqrt, internal::abs, etc... +-# make sure the common operator (+,-,*,/,etc.) are supported by the type \c T +-# add a specialization of struct Eigen::NumTraits (see \ref NumTraits) +-# define the math functions that makes sense for your type. This includes standard ones like sqrt, pow, sin, tan, conj, real, imag, etc, as well as abs2 which is Eigen specific. (see the file Eigen/src/Core/MathFunctions.h) +The math function should be defined in the same namespace than \c T, or in the \c std namespace though that second appraoch is not recommended. + Here is a concrete example adding support for the Adolc's \c adouble type. Adolc is an automatic differentiation library. The type \c adouble is basically a real value tracking the values of any number of partial derivatives. \code -#ifndef ADLOCSUPPORT_H -#define ADLOCSUPPORT_H +#ifndef ADOLCSUPPORT_H +#define ADOLCSUPPORT_H #define ADOLC_TAPELESS #include @@ -141,6 +144,7 @@ Here is a concrete example adding support for the Adolc's \c adouble type. struct NumTraits + : NumTraits // permits to get the epsilon, dummy_precision, lowest, highest functions { typedef adtl::adouble Real; typedef adtl::adouble NonInteger; @@ -149,35 +153,27 @@ template<> struct NumTraits enum { IsComplex = 0, IsInteger = 0, - IsSigned, + IsSigned = 1, + RequireInitialization = 1, ReadCost = 1, - AddCost = 1, - MulCost = 1 + AddCost = 3, + MulCost = 3 }; }; } -// the Adolc's type adouble is defined in the adtl namespace -// therefore, the following internal::* functions *must* be defined -// in the same namespace namespace adtl { - inline const adouble& internal::conj(const adouble& x) { return x; } - inline const adouble& internal::real(const adouble& x) { return x; } - inline adouble internal::imag(const adouble&) { return 0.; } - inline adouble internal::abs(const adouble& x) { return fabs(x); } - inline adouble internal::abs2(const adouble& x) { return x*x; } - inline adouble internal::sqrt(const adouble& x) { return sqrt(x); } - inline adouble internal::exp(const adouble& x) { return exp(x); } - inline adouble internal::log(const adouble& x) { return log(x); } - inline adouble internal::sin(const adouble& x) { return sin(x); } - inline adouble internal::cos(const adouble& x) { return cos(x); } - inline adouble internal::pow(const adouble& x, adouble y) { return pow(x, y); } +inline const adouble& conj(const adouble& x) { return x; } +inline const adouble& real(const adouble& x) { return x; } +inline adouble imag(const adouble&) { return 0.; } +inline adouble abs(const adouble& x) { return fabs(x); } +inline adouble abs2(const adouble& x) { return x*x; } } -#endif // ADLOCSUPPORT_H +#endif // ADOLCSUPPORT_H \endcode diff --git a/gtsam/3rdparty/Eigen/doc/I09_Vectorization.dox b/gtsam/3rdparty/Eigen/doc/I09_Vectorization.dox index 63831e59f..274d0451b 100644 --- a/gtsam/3rdparty/Eigen/doc/I09_Vectorization.dox +++ b/gtsam/3rdparty/Eigen/doc/I09_Vectorization.dox @@ -1,6 +1,6 @@ namespace Eigen { -/** \page TopicVectorization Vectorizaion +/** \page TopicVectorization Vectorization TODO: write this dox page! diff --git a/gtsam/3rdparty/Eigen/doc/I14_PreprocessorDirectives.dox b/gtsam/3rdparty/Eigen/doc/I14_PreprocessorDirectives.dox index b34fc84cf..2826a7f50 100644 --- a/gtsam/3rdparty/Eigen/doc/I14_PreprocessorDirectives.dox +++ b/gtsam/3rdparty/Eigen/doc/I14_PreprocessorDirectives.dox @@ -2,66 +2,75 @@ namespace Eigen { /** \page TopicPreprocessorDirectives Preprocessor directives -You can control some aspects of Eigen by defining the preprocessor tokens using \c \#define. These macros -should be defined before any Eigen headers are included. Often they are best set in the project options. +You can control some aspects of %Eigen by defining the preprocessor tokens using \c \#define. These macros +should be defined before any %Eigen headers are included. Often they are best set in the project options. -This page lists the preprocesor tokens recognised by Eigen. +This page lists the preprocesor tokens recognised by %Eigen. Table of contents - \ref TopicPreprocessorDirectivesMajor - \ref TopicPreprocessorDirectivesAssertions - \ref TopicPreprocessorDirectivesPerformance - \ref TopicPreprocessorDirectivesPlugins + - \ref TopicPreprocessorDirectivesDevelopers \section TopicPreprocessorDirectivesMajor Macros with major effects +These macros have a major effect and typically break the API (Application Programming Interface) and/or the +ABI (Application Binary Interface). This can be rather dangerous: if parts of your program are compiled with +one option, and other parts (or libraries that you use) are compiled with another option, your program may +fail to link or exhibit subtle bugs. Nevertheless, these options can be useful for people who know what they +are doing. + - \b EIGEN2_SUPPORT - if defined, enables the Eigen2 compatibility mode. This is meant to ease the transition of Eigen2 to Eigen3 (see \ref Eigen2ToEigen3). Not defined by default. - \b EIGEN2_SUPPORT_STAGEnn_xxx (for various values of nn and xxx) - staged migration path from Eigen2 to Eigen3; see \ref Eigen2SupportModes. - - \b EIGEN_DEFAULT_TO_ROW_MAJOR - when defined, the default storage order for matrices becomes row-major - instead of column-major. Not defined by default. - \b EIGEN_DEFAULT_DENSE_INDEX_TYPE - the type for column and row indices in matrices, vectors and array (DenseBase::Index). Set to \c std::ptrdiff_t by default. - \b EIGEN_DEFAULT_IO_FORMAT - the IOFormat to use when printing a matrix if no #IOFormat is specified. Defaults to the #IOFormat constructed by the default constructor IOFormat(). - \b EIGEN_INITIALIZE_MATRICES_BY_ZERO - if defined, all entries of newly constructed matrices and arrays are initializes to zero, as are new entries in matrices and arrays after resizing. Not defined by default. + - \b EIGEN_NO_AUTOMATIC_RESIZING - if defined, the matrices (or arrays) on both sides of an assignment + a = b have to be of the same size; otherwise, %Eigen automatically resizes \c a so that it is of + the correct size. Not defined by default. \section TopicPreprocessorDirectivesAssertions Assertions -The Eigen library contains many assertions to guard against programming errors, both at compile time and at +The %Eigen library contains many assertions to guard against programming errors, both at compile time and at run time. However, these assertions do cost time and can thus be turned off. - - \b EIGEN_NO_DEBUG - disables Eigen's assertions if defined. Not defined by default, unless the + - \b EIGEN_NO_DEBUG - disables %Eigen's assertions if defined. Not defined by default, unless the \c NDEBUG macro is defined (this is a standard C++ macro which disables all asserts). - \b EIGEN_NO_STATIC_ASSERT - if defined, compile-time static assertions are replaced by runtime assertions; this saves compilation time. Not defined by default. - - \b EIGEN_INTERNAL_DEBUGGING - if defined, enables assertions in Eigen's internal routines. This is useful - for debugging Eigen itself. Not defined by default. + - \b eigen_assert - macro with one argument that is used inside %Eigen for assertions. By default, it is + basically defined to be \c assert, which aborts the program if the assertion is violated. Redefine this + macro if you want to do something else, like throwing an exception. \section TopicPreprocessorDirectivesPerformance Alignment, vectorization and performance tweaking - - \b EIGEN_DONT_ALIGN - disables alignment completely. Eigen will not try to align its objects and does not + - \b EIGEN_DONT_ALIGN - disables alignment completely. %Eigen will not try to align its objects and does not expect that any objects passed to it are aligned. This will turn off vectorization. Not defined by default. - \b EIGEN_DONT_ALIGN_STATICALLY - disables alignment of arrays on the stack. Not defined by default, unless \c EIGEN_DONT_ALIGN is defined. - \b EIGEN_DONT_VECTORIZE - disables explicit vectorization when defined. Not defined by default, unless - alignment is disabled by Eigen's platform test or the user defining \c EIGEN_DONT_ALIGN. + alignment is disabled by %Eigen's platform test or the user defining \c EIGEN_DONT_ALIGN. - \b EIGEN_FAST_MATH - enables some optimizations which might affect the accuracy of the result. The only optimization this currently includes is single precision sin() and cos() in the present of SSE vectorization. Defined by default. - \b EIGEN_UNROLLING_LIMIT - defines the size of a loop to enable meta unrolling. Set it to zero to disable - unrolling. The size of a loop here is expressed in Eigen's own notion of "number of FLOPS", it does not + unrolling. The size of a loop here is expressed in %Eigen's own notion of "number of FLOPS", it does not correspond to the number of iterations or the number of instructions. The default is value 100. \section TopicPreprocessorDirectivesPlugins Plugins -It is possible to add new methods to many fundamental classes in Eigen by writing a plugin. As explained in +It is possible to add new methods to many fundamental classes in %Eigen by writing a plugin. As explained in the section \ref ExtendingMatrixBase, the plugin is specified by defining a \c EIGEN_xxx_PLUGIN macro. The following macros are supported; none of them are defined by default. @@ -81,6 +90,21 @@ following macros are supported; none of them are defined by default. - \b EIGEN_FUNCTORS_PLUGIN - filename of plugin for adding new functors and specializations of functor_traits. +\section TopicPreprocessorDirectivesDevelopers Macros for Eigen developers + +These macros are mainly meant for people developing %Eigen and for testing purposes. Even though, they might be useful for power users and the curious for debugging and testing purpose, they \b should \b not \b be \b used by real-word code. + + - \b EIGEN_DEFAULT_TO_ROW_MAJOR - when defined, the default storage order for matrices becomes row-major + instead of column-major. Not defined by default. + - \b EIGEN_INTERNAL_DEBUGGING - if defined, enables assertions in %Eigen's internal routines. This is useful + for debugging %Eigen itself. Not defined by default. + - \b EIGEN_NO_MALLOC - if defined, any request from inside the %Eigen to allocate memory from the heap + results in an assertion failure. This is useful to check that some routine does not allocate memory + dynamically. Not defined by default. + - \b EIGEN_RUNTIME_NO_MALLOC - if defined, a new switch is introduced which can be turned on and off by + calling set_is_malloc_allowed(bool). If malloc is not allowed and %Eigen tries to allocate memory + dynamically anyway, an assertion failure results. Not defined by default. + */ } diff --git a/gtsam/3rdparty/Eigen/doc/I15_StorageOrders.dox b/gtsam/3rdparty/Eigen/doc/I15_StorageOrders.dox index 6b56ca8f8..7418912a6 100644 --- a/gtsam/3rdparty/Eigen/doc/I15_StorageOrders.dox +++ b/gtsam/3rdparty/Eigen/doc/I15_StorageOrders.dox @@ -60,10 +60,8 @@ parameter is set to \c RowMajor, then the matrix or array is stored in row-major \c ColMajor, then it is stored in column-major order. This mechanism is used in the above Eigen program to specify the storage order. -If the storage order is not specified, then Eigen normally defaults to storing the entry in column-major -order. This is also the case if one of the convenience typedefs (\c Matrix3f, \c ArrayXXd, etc.) is -used. However, it is possible to change the default to row-major order by defining the -\c EIGEN_DEFAULT_TO_ROW_MAJOR \ref TopicPreprocessorDirectives "preprocessor directive". +If the storage order is not specified, then Eigen defaults to storing the entry in column-major. This is also +the case if one of the convenience typedefs (\c Matrix3f, \c ArrayXXd, etc.) is used. Matrices and arrays using one storage order can be assigned to matrices and arrays using the other storage order, as happens in the above program when \c Arowmajor is initialized using \c Acolmajor. Eigen will reorder diff --git a/gtsam/3rdparty/Eigen/doc/I16_TemplateKeyword.dox b/gtsam/3rdparty/Eigen/doc/I16_TemplateKeyword.dox new file mode 100644 index 000000000..324532310 --- /dev/null +++ b/gtsam/3rdparty/Eigen/doc/I16_TemplateKeyword.dox @@ -0,0 +1,136 @@ +namespace Eigen { + +/** \page TopicTemplateKeyword The template and typename keywords in C++ + +There are two uses for the \c template and \c typename keywords in C++. One of them is fairly well known +amongst programmers: to define templates. The other use is more obscure: to specify that an expression refers +to a template function or a type. This regularly trips up programmers that use the %Eigen library, often +leading to error messages from the compiler that are difficult to understand. + +Table of contents + - \ref TopicTemplateKeywordToDefineTemplates + - \ref TopicTemplateKeywordExample + - \ref TopicTemplateKeywordExplanation + - \ref TopicTemplateKeywordResources + + +\section TopicTemplateKeywordToDefineTemplates Using the template and typename keywords to define templates + +The \c template and \c typename keywords are routinely used to define templates. This is not the topic of this +page as we assume that the reader is aware of this (otherwise consult a C++ book). The following example +should illustrate this use of the \c template keyword. + +\code +template +bool isPositive(T x) +{ + return x > 0; +} +\endcode + +We could just as well have written template <class T>; the keywords \c typename and \c class have the +same meaning in this context. + + +\section TopicTemplateKeywordExample An example showing the second use of the template keyword + +Let us illustrate the second use of the \c template keyword with an example. Suppose we want to write a +function which copies all entries in the upper triangular part of a matrix into another matrix, while keeping +the lower triangular part unchanged. A straightforward implementation would be as follows: + + + + +
Example:Output:
+\include TemplateKeyword_simple.cpp + +\verbinclude TemplateKeyword_simple.out +
+ +That works fine, but it is not very flexible. First, it only works with dynamic-size matrices of +single-precision floats; the function \c copyUpperTriangularPart() does not accept static-size matrices or +matrices with double-precision numbers. Second, if you use an expression such as +mat.topLeftCorner(3,3) as the parameter \c src, then this is copied into a temporary variable of type +MatrixXf; this copy can be avoided. + +As explained in \ref TopicFunctionTakingEigenTypes, both issues can be resolved by making +\c copyUpperTriangularPart() accept any object of type MatrixBase. This leads to the following code: + + + + +
Example:Output:
+\include TemplateKeyword_flexible.cpp + +\verbinclude TemplateKeyword_flexible.out +
+ +The one line in the body of the function \c copyUpperTriangularPart() shows the second, more obscure use of +the \c template keyword in C++. Even though it may look strange, the \c template keywords are necessary +according to the standard. Without it, the compiler may reject the code with an error message like "no match +for operator<". + + +\section TopicTemplateKeywordExplanation Explanation + +The reason that the \c template keyword is necessary in the last example has to do with the rules for how +templates are supposed to be compiled in C++. The compiler has to check the code for correct syntax at the +point where the template is defined, without knowing the actual value of the template arguments (\c Derived1 +and \c Derived2 in the example). That means that the compiler cannot know that dst.triangularPart is +a member template and that the following < symbol is part of the delimiter for the template +parameter. Another possibility would be that dst.triangularPart is a member variable with the < +symbol refering to the operator<() function. In fact, the compiler should choose the second +possibility, according to the standard. If dst.triangularPart is a member template (as in our case), +the programmer should specify this explicitly with the \c template keyword and write dst.template +triangularPart. + +The precise rules are rather complicated, but ignoring some subtleties we can summarize them as follows: +- A dependent name is name that depends (directly or indirectly) on a template parameter. In the + example, \c dst is a dependent name because it is of type MatrixBase<Derived1> which depends + on the template parameter \c Derived1. +- If the code contains either one of the contructions xxx.yyy or xxx->yyy and \c xxx is a + dependent name and \c yyy refers to a member template, then the \c template keyword must be used before + \c yyy, leading to xxx.template yyy or xxx->template yyy. +- If the code contains the contruction xxx::yyy and \c xxx is a dependent name and \c yyy refers to a + member typedef, then the \c typename keyword must be used before the whole construction, leading to + typename xxx::yyy. + +As an example where the \c typename keyword is required, consider the following code in \ref TutorialSparse +for iterating over the non-zero entries of a sparse matrix type: + +\code +SparseMatrixType mat(rows,cols); +for (int k=0; k +void iterateOverSparseMatrix(const SparseMatrix& mat; +{ + for (int k=0; k::InnerIterator it(mat,k); it; ++it) + { + /* ... */ + } +} +\endcode + + +\section TopicTemplateKeywordResources Resources for further reading + +For more information and a fuller explanation of this topic, the reader may consult the following sources: +- The book "C++ Template Metaprogramming" by David Abrahams and Aleksey Gurtovoy contains a very good + explanation in Appendix B ("The typename and template Keywords") which formed the basis for this page. +- http://pages.cs.wisc.edu/~driscoll/typename.html +- http://www.parashift.com/c++-faq-lite/templates.html#faq-35.18 +- http://www.comeaucomputing.com/techtalk/templates/#templateprefix +- http://www.comeaucomputing.com/techtalk/templates/#typename + +*/ +} diff --git a/gtsam/3rdparty/Eigen/doc/Overview.dox b/gtsam/3rdparty/Eigen/doc/Overview.dox index 68e07ad63..2657c85bc 100644 --- a/gtsam/3rdparty/Eigen/doc/Overview.dox +++ b/gtsam/3rdparty/Eigen/doc/Overview.dox @@ -34,12 +34,15 @@ For a first contact with Eigen, the best place is to have a look at the \ref Get - \ref TopicLazyEvaluation - \ref TopicLinearAlgebraDecompositions - \ref TopicCustomizingEigen + - \ref TopicMultiThreading - \ref TopicPreprocessorDirectives - \ref TopicStorageOrders - \ref TopicInsideEigenExample - \ref TopicWritingEfficientProductExpression - \ref TopicClassHierarchy - \ref TopicFunctionTakingEigenTypes + - \ref TopicTemplateKeyword + - \ref TopicUsingIntelMKL - Topics related to alignment issues - \ref TopicUnalignedArrayAssert - \ref TopicFixedSizeVectorizable diff --git a/gtsam/3rdparty/Eigen/doc/QuickReference.dox b/gtsam/3rdparty/Eigen/doc/QuickReference.dox index e23ff7ce5..3310d390a 100644 --- a/gtsam/3rdparty/Eigen/doc/QuickReference.dox +++ b/gtsam/3rdparty/Eigen/doc/QuickReference.dox @@ -412,8 +412,8 @@ array1 <= array2 array1 >= array2 array1 <= scalar array1 >= scalar array1 == array2 array1 != array2 array1 == scalar array1 != scalar \endcode Trigo, power, and \n misc functions \n and the STL variants\code -array1.min(array2) std::min(array1,array2) -array1.max(array2) std::max(array1,array2) +array1.min(array2) +array1.max(array2) array1.abs2() array1.abs() std::abs(array1) array1.sqrt() std::sqrt(array1) @@ -440,10 +440,10 @@ Eigen provides several reduction methods such as: \link DenseBase::sum() sum() \endlink, \link DenseBase::prod() prod() \endlink, \link MatrixBase::trace() trace() \endlink \matrixworld, \link MatrixBase::norm() norm() \endlink \matrixworld, \link MatrixBase::squaredNorm() squaredNorm() \endlink \matrixworld, -\link DenseBase::all() all() \endlink \redstar,and \link DenseBase::any() any() \endlink \redstar. +\link DenseBase::all() all() \endlink, and \link DenseBase::any() any() \endlink. All reduction operations can be done matrix-wise, -\link DenseBase::colwise() column-wise \endlink \redstar or -\link DenseBase::rowwise() row-wise \endlink \redstar. Usage example: +\link DenseBase::colwise() column-wise \endlink or +\link DenseBase::rowwise() row-wise \endlink. Usage example:
\code 5 3 1 @@ -586,6 +586,9 @@ mat3 = mat1 * diag1.inverse() TriangularView gives a view on a triangular part of a dense matrix and allows to perform optimized operations on it. The opposite triangular part is never referenced and can be used to store other information. +\note The .triangularView() template member function requires the \c template keyword if it is used on an +object of a type that depends on a template parameter; see \ref TopicTemplateKeyword for details. +
OperationCode
@@ -630,6 +633,9 @@ Just as for triangular matrix, you can reference any triangular part of a square matrix and perform special and optimized operations. Again the opposite triangular part is never referenced and can be used to store other information. +\note The .selfadjointView() template member function requires the \c template keyword if it is used on an +object of a type that depends on a template parameter; see \ref TopicTemplateKeyword for details. + - + @@ -94,7 +94,7 @@ namespace Eigen { - + @@ -132,7 +132,7 @@ namespace Eigen { - + @@ -245,6 +245,10 @@ namespace Eigen {
Blocking
Means the algorithm can work per block, whence guaranteeing a good scaling of the performance for large matrices.
+
Implicit Multi Threading (MT)
+
Means the algorithm can take advantage of multicore processors via OpenMP. "Implicit" means the algortihm itself is not parallelized, but that it relies on parallelized matrix-matrix product rountines.
+
Explicit Multi Threading (MT)
+
Means the algorithm is explicitely parallelized to take advantage of multicore processors via OpenMP.
Meta-unroller
Means the algorithm is automatically and explicitly unrolled for very small fixed size matrices.
diff --git a/gtsam/3rdparty/Eigen/doc/TopicMultithreading.dox b/gtsam/3rdparty/Eigen/doc/TopicMultithreading.dox new file mode 100644 index 000000000..f7d082668 --- /dev/null +++ b/gtsam/3rdparty/Eigen/doc/TopicMultithreading.dox @@ -0,0 +1,46 @@ +namespace Eigen { + +/** \page TopicMultiThreading Eigen and multi-threading + +\section TopicMultiThreading_MakingEigenMT Make Eigen run in parallel + +Some Eigen's algorithms can exploit the multiple cores present in your hardware. To this end, it is enough to enable OpenMP on your compiler, for instance: + * GCC: \c -fopenmp + * ICC: \c -openmp + * MSVC: check the respective option in the build properties. +You can control the number of thread that will be used using either the OpenMP API or Eiegn's API using the following priority: +\code + OMP_NUM_THREADS=n ./my_program + omp_set_num_threads(n); + Eigen::setNbThreads(n); +\endcode +Unless setNbThreads has been called, Eigen uses the number of threads specified by OpenMP. You can restore this bahavior by calling \code setNbThreads(0); \endcode +You can query the number of threads that will be used with: +\code +n = Eigen::nbThreads(n); +\endcode +You can disable Eigen's multi threading at compile time by defining the EIGEN_DONT_PARALLELIZE preprocessor token. + +Currently, the following algorithms can make use of multi-threading: + * general matrix - matrix products + * PartialPivLU + +\section TopicMultiThreading_UsingEigenWithMT Using Eigen in a multi-threaded application + +In the case your own application is multithreaded, and multiple threads make calls to Eigen, then you have to initialize Eigen by calling the following routine \b before creating the threads: +\code +#include + +int main(int argc, char** argv) +{ + Eigen::initParallel(); + + ... +} +\endcode + +In the case your application is parallelized with OpenMP, you might want to disable Eigen's own parallization as detailed in the previous section. + +*/ + +} diff --git a/gtsam/3rdparty/Eigen/doc/TutorialSparse_example_details.dox b/gtsam/3rdparty/Eigen/doc/TutorialSparse_example_details.dox new file mode 100644 index 000000000..0438da8bb --- /dev/null +++ b/gtsam/3rdparty/Eigen/doc/TutorialSparse_example_details.dox @@ -0,0 +1,4 @@ +/** +\page TutorialSparse_example_details +\include Tutorial_sparse_example_details.cpp +*/ diff --git a/gtsam/3rdparty/Eigen/doc/UsingIntelMKL.dox b/gtsam/3rdparty/Eigen/doc/UsingIntelMKL.dox new file mode 100644 index 000000000..379ee3ffd --- /dev/null +++ b/gtsam/3rdparty/Eigen/doc/UsingIntelMKL.dox @@ -0,0 +1,168 @@ +/* + Copyright (c) 2011, Intel Corporation. All rights reserved. + Copyright (C) 2011 Gael Guennebaud + + Redistribution and use in source and binary forms, with or without modification, + are permitted provided that the following conditions are met: + + * Redistributions of source code must retain the above copyright notice, this + list of conditions and the following disclaimer. + * Redistributions in binary form must reproduce the above copyright notice, + this list of conditions and the following disclaimer in the documentation + and/or other materials provided with the distribution. + * Neither the name of Intel Corporation nor the names of its contributors may + be used to endorse or promote products derived from this software without + specific prior written permission. + + THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND + ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED + WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE + DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR + ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES + (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; + LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON + ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS + SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + + ******************************************************************************** + * Content : Documentation on the use of Intel MKL through Eigen + ******************************************************************************** +*/ + +namespace Eigen { + +/** \page TopicUsingIntelMKL Using Intel® Math Kernel Library from Eigen + +\section TopicUsingIntelMKL_Intro Eigen and Intel® Math Kernel Library (Intel® MKL) + +Since Eigen version 3.1 and later, users can benefit from built-in Intel MKL optimizations with an installed copy of Intel MKL 10.3 (or later). + Intel MKL provides highly optimized multi-threaded mathematical routines for x86-compatible architectures. +Intel MKL is available on Linux, Mac and Windows for both Intel64 and IA32 architectures. + +\warning Be aware that Intel® MKL is a proprietary software. It is the responsibility of the users to buy MKL licenses for their products. Moreover, the license of the user product has to allow linking to proprietary software that excludes any unmodified versions of the GPL. As a consequence, this also means that Eigen has to be used through the LGPL3+ license. + +Using Intel MKL through Eigen is easy: +-# define the \c EIGEN_USE_MKL_ALL macro before including any Eigen's header +-# link your program to MKL libraries (see the MKL linking advisor) +-# on a 64bits system, you must use the LP64 interface (not the ILP64 one) + +When doing so, a number of Eigen's algorithms are silently substituted with calls to Intel MKL routines. +These substitutions apply only for \b Dynamic \b or \b large enough objects with one of the following four standard scalar types: \c float, \c double, \c complex, and \c complex. +Operations on other scalar types or mixing reals and complexes will continue to use the built-in algorithms. + +In addition you can coarsely select choose which parts will be substituted by defining one or multiple of the following macros: + +
OperationCode
diff --git a/gtsam/3rdparty/Eigen/doc/SparseQuickReference.dox b/gtsam/3rdparty/Eigen/doc/SparseQuickReference.dox new file mode 100644 index 000000000..7d6eb0fa9 --- /dev/null +++ b/gtsam/3rdparty/Eigen/doc/SparseQuickReference.dox @@ -0,0 +1,198 @@ +namespace Eigen { +/** \page SparseQuickRefPage Quick reference guide for sparse matrices + +\b Table \b of \b contents + - \ref Constructors + - \ref SparseMatrixInsertion + - \ref SparseBasicInfos + - \ref SparseBasicOps + - \ref SparseInterops + - \ref sparsepermutation + - \ref sparsesubmatrices + - \ref sparseselfadjointview +\n + +
+ +In this page, we give a quick summary of the main operations available for sparse matrices in the class SparseMatrix. First, it is recommended to read first the introductory tutorial at \ref TutorialSparse. The important point to have in mind when working on sparse matrices is how they are stored : +i.e either row major or column major. The default is column major. Most arithmetic operations on sparse matrices will assert that they have the same storage order. Moreover, when interacting with external libraries that are not yet supported by Eigen, it is important to know how to send the required matrix pointers. + +\section Constructors Constructors and assignments +SparseMatrix is the core class to build and manipulate sparse matrices in Eigen. It takes as template parameters the Scalar type and the storage order, either RowMajor or ColumnMajor. The default is ColumnMajor. + +\code + SparseMatrix sm1(1000,1000); // 1000x1000 compressed sparse matrix of double. + SparseMatrix,RowMajor> sm2; // Compressed row major matrix of complex double. +\endcode +The copy constructor and assignment can be used to convert matrices from a storage order to another +\code + SparseMatrix sm1; + // Eventually fill the matrix sm1 ... + SparseMatrix sm2(sm1), sm3; // Initialize sm2 with sm1. + sm3 = sm1; // Assignment and evaluations modify the storage order. + \endcode + +\section SparseMatrixInsertion Allocating and inserting values +resize() and reserve() are used to set the size and allocate space for nonzero elements + \code + sm1.resize(m,n); //Change sm to a mxn matrix. + sm1.reserve(nnz); // Allocate room for nnz nonzeros elements. + \endcode +Note that when calling reserve(), it is not required that nnz is the exact number of nonzero elements in the final matrix. However, an exact estimation will avoid multiple reallocations during the insertion phase. + +Insertions of values in the sparse matrix can be done directly by looping over nonzero elements and use the insert() function +\code +// Direct insertion of the value v_ij; + sm1.insert(i, j) = v_ij; // It is assumed that v_ij does not already exist in the matrix. +\endcode + +After insertion, a value at (i,j) can be modified using coeffRef() +\code + // Update the value v_ij + sm1.coeffRef(i,j) = v_ij; + sm1.coeffRef(i,j) += v_ij; + sm1.coeffRef(i,j) -= v_ij; + ... +\endcode + +The recommended way to insert values is to build a list of triplets (row, col, val) and then call setFromTriplets(). +\code + sm1.setFromTriplets(TripletList.begin(), TripletList.end()); +\endcode +A complete example is available at \ref TutorialSparseFilling. + +The following functions can be used to set constant or random values in the matrix. +\code + sm1.setZero(); // Reset the matrix with zero elements + ... +\endcode + +\section SparseBasicInfos Matrix properties +Beyond the functions rows() and cols() that are used to get the number of rows and columns, there are some useful functions that are available to easily get some informations from the matrix. + + + + +
\code + sm1.rows(); // Number of rows + sm1.cols(); // Number of columns + sm1.nonZeros(); // Number of non zero values + sm1.outerSize(); // Number of columns (resp. rows) for a column major (resp. row major ) + sm1.innerSize(); // Number of rows (resp. columns) for a row major (resp. column major) + sm1.norm(); // (Euclidian ??) norm of the matrix + sm1.squaredNorm(); // + sm1.isVector(); // Check if sm1 is a sparse vector or a sparse matrix + ... + \endcode
+ +\section SparseBasicOps Arithmetic operations +It is easy to perform arithmetic operations on sparse matrices provided that the dimensions are adequate and that the matrices have the same storage order. Note that the evaluation can always be done in a matrix with a different storage order. + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Operations Code Notes
add subtract \code + sm3 = sm1 + sm2; + sm3 = sm1 - sm2; + sm2 += sm1; + sm2 -= sm1; \endcode + + sm1 and sm2 should have the same storage order +
+ scalar product\code + sm3 = sm1 * s1; sm3 *= s1; + sm3 = s1 * sm1 + s2 * sm2; sm3 /= s1;\endcode + + Many combinations are possible if the dimensions and the storage order agree. +
Product \code + sm3 = sm1 * sm2; + dm2 = sm1 * dm1; + dv2 = sm1 * dv1; + \endcode +
transposition, adjoint \code + sm2 = sm1.transpose(); + sm2 = sm1.adjoint(); + \endcode + Note that the transposition change the storage order. There is no support for transposeInPlace(). +
+ Component-wise ops + \code + sm1.cwiseProduct(sm2); + sm1.cwiseQuotient(sm2); + sm1.cwiseMin(sm2); + sm1.cwiseMax(sm2); + sm1.cwiseAbs(); + sm1.cwiseSqrt(); + \endcode + sm1 and sm2 should have the same storage order +
+ + +\section SparseInterops Low-level storage +There are a set of low-levels functions to get the standard compressed storage pointers. The matrix should be in compressed mode which can be checked by calling isCompressed(); makeCompressed() should do the job otherwise. +\code + // Scalar pointer to the values of the matrix, size nnz + sm1.valuePtr(); + // Index pointer to get the row indices (resp. column indices) for column major (resp. row major) matrix, size nnz + sm1.innerIndexPtr(); + // Index pointer to the beginning of each row (resp. column) in valuePtr() and innerIndexPtr() for column major (row major). The size is outersize()+1; + sm1.outerIndexPtr(); +\endcode +These pointers can therefore be easily used to send the matrix to some external libraries/solvers that are not yet supported by Eigen. + +\section sparsepermutation Permutations, submatrices and Selfadjoint Views +In many cases, it is necessary to reorder the rows and/or the columns of the sparse matrix for several purposes : fill-in reducing during matrix decomposition, better data locality for sparse matrix-vector products... The class PermutationMatrix is available to this end. + \code + PermutationMatrix perm; + // Reserve and fill the values of perm; + perm.inverse(n); // Compute eventually the inverse permutation + sm1.twistedBy(perm) //Apply the permutation on rows and columns + sm2 = sm1 * perm; // ??? Apply the permutation on columns ???; + sm2 = perm * sm1; // ??? Apply the permutation on rows ???; + \endcode + +\section sparsesubmatrices Sub-matrices +The following functions are useful to extract a block of rows (resp. columns) from a row-major (resp. column major) sparse matrix. Note that because of the particular storage, it is not ?? efficient ?? to extract a submatrix comprising a certain number of subrows and subcolumns. + \code + sm1.innerVector(outer); // Returns the outer -th column (resp. row) of the matrix if sm is col-major (resp. row-major) + sm1.innerVectors(outer); // Returns the outer -th column (resp. row) of the matrix if mat is col-major (resp. row-major) + sm1.middleRows(start, numRows); // For row major matrices, get a range of numRows rows + sm1.middleCols(start, numCols); // For column major matrices, get a range of numCols cols + \endcode + Examples : + +\section sparseselfadjointview Sparse triangular and selfadjoint Views + \code + sm2 = sm1.triangularview(); // Get the lower triangular part of the matrix. + dv2 = sm1.triangularView().solve(dv1); // Solve the linear system with the uppper triangular part. + sm2 = sm1.selfadjointview(); // Build a selfadjoint matrix from the lower part of sm1. + \endcode + + +*/ +} diff --git a/gtsam/3rdparty/Eigen/doc/TopicLinearAlgebraDecompositions.dox b/gtsam/3rdparty/Eigen/doc/TopicLinearAlgebraDecompositions.dox index 5684a495f..faa564b93 100644 --- a/gtsam/3rdparty/Eigen/doc/TopicLinearAlgebraDecompositions.dox +++ b/gtsam/3rdparty/Eigen/doc/TopicLinearAlgebraDecompositions.dox @@ -34,7 +34,7 @@ namespace Eigen { 		- Yes ExcellentBlockingBlocking, Implicit MT
- Yes ExcellentBlocking \n Soon: meta unrollerBlocking
Eigenvalues/vectors - GoodSoon: specializations for 2x2 and 3x3Closed forms for 2x2 and 3x3
+ + + + + +
\c EIGEN_USE_BLAS Enables the use of external BLAS level 2 and 3 routines (currently works with Intel MKL only)
\c EIGEN_USE_LAPACKE Enables the use of external Lapack routines via the Intel Lapacke C interface to Lapack (currently works with Intel MKL only)
\c EIGEN_USE_LAPACKE_STRICT Same as \c EIGEN_USE_LAPACKE but algorithm of lower robustness are disabled. This currently concerns only JacobiSVD which otherwise would be replaced by \c gesvd that is less robust than Jacobi rotations.
\c EIGEN_USE_MKL_VML Enables the use of Intel VML (vector operations)
\c EIGEN_USE_MKL_ALL Defines \c EIGEN_USE_BLAS, \c EIGEN_USE_LAPACKE, and \c EIGEN_USE_MKL_VML
+ +Finally, the PARDISO sparse solver shipped with Intel MKL can be used through the \ref PardisoLU, \ref PardisoLLT and \ref PardisoLDLT classes of the \ref PARDISOSupport_Module. + + +\section TopicUsingIntelMKL_SupportedFeatures List of supported features + +The breadth of Eigen functionality covered by Intel MKL is listed in the table below. + + + + + + + + + + + +
Functional domainCode exampleMKL routines
Matrix-matrix operations \n \c EIGEN_USE_BLAS \code +m1*m2.transpose(); +m1.selfadjointView()*m2; +m1*m2.triangularView(); +m1.selfadjointView().rankUpdate(m2,1.0); +\endcode\code +?gemm +?symm/?hemm +?trmm +dsyrk/ssyrk +\endcode
Matrix-vector operations \n \c EIGEN_USE_BLAS \code +m1.adjoint()*b; +m1.selfadjointView()*b; +m1.triangularView()*b; +\endcode\code +?gemv +?symv/?hemv +?trmv +\endcode
LU decomposition \n \c EIGEN_USE_LAPACKE \n \c EIGEN_USE_LAPACKE_STRICT \code +v1 = m1.lu().solve(v2); +\endcode\code +?getrf +\endcode
Cholesky decomposition \n \c EIGEN_USE_LAPACKE \n \c EIGEN_USE_LAPACKE_STRICT \code +v1 = m2.selfadjointView().llt().solve(v2); +\endcode\code +?potrf +\endcode
QR decomposition \n \c EIGEN_USE_LAPACKE \n \c EIGEN_USE_LAPACKE_STRICT \code +m1.householderQr(); +m1.colPivHouseholderQr(); +\endcode\code +?geqrf +?geqp3 +\endcode
Singular value decomposition \n \c EIGEN_USE_LAPACKE \code +JacobiSVD svd; +svd.compute(m1, ComputeThinV); +\endcode\code +?gesvd +\endcode
Eigen-value decompositions \n \c EIGEN_USE_LAPACKE \n \c EIGEN_USE_LAPACKE_STRICT \code +EigenSolver es(m1); +ComplexEigenSolver ces(m1); +SelfAdjointEigenSolver saes(m1+m1.transpose()); +GeneralizedSelfAdjointEigenSolver + gsaes(m1+m1.transpose(),m2+m2.transpose()); +\endcode\code +?gees +?gees +?syev/?heev +?syev/?heev, +?potrf +\endcode
Schur decomposition \n \c EIGEN_USE_LAPACKE \n \c EIGEN_USE_LAPACKE_STRICT \code +RealSchur schurR(m1); +ComplexSchur schurC(m1); +\endcode\code +?gees +\endcode
Vector Math \n \c EIGEN_USE_MKL_VML \code +v2=v1.array().sin(); +v2=v1.array().asin(); +v2=v1.array().cos(); +v2=v1.array().acos(); +v2=v1.array().tan(); +v2=v1.array().exp(); +v2=v1.array().log(); +v2=v1.array().sqrt(); +v2=v1.array().square(); +v2=v1.array().pow(1.5); +\endcode\code +v?Sin +v?Asin +v?Cos +v?Acos +v?Tan +v?Exp +v?Ln +v?Sqrt +v?Sqr +v?Powx +\endcode
+In the examples, m1 and m2 are dense matrices and v1 and v2 are dense vectors. + + +\section TopicUsingIntelMKL_Links Links +- Intel MKL can be purchased and downloaded here. +- Intel MKL is also bundled with Intel Composer XE. + + +*/ + +} \ No newline at end of file diff --git a/gtsam/3rdparty/Eigen/doc/eigendoxy.css b/gtsam/3rdparty/Eigen/doc/eigendoxy.css index e62958831..c6c16286d 100644 --- a/gtsam/3rdparty/Eigen/doc/eigendoxy.css +++ b/gtsam/3rdparty/Eigen/doc/eigendoxy.css @@ -904,3 +904,8 @@ div.eimainmenu { h3.version { text-align: center; } + + +td.width20em p.endtd { + width: 20em; +} diff --git a/gtsam/3rdparty/Eigen/doc/examples/TemplateKeyword_flexible.cpp b/gtsam/3rdparty/Eigen/doc/examples/TemplateKeyword_flexible.cpp new file mode 100644 index 000000000..9d85292dd --- /dev/null +++ b/gtsam/3rdparty/Eigen/doc/examples/TemplateKeyword_flexible.cpp @@ -0,0 +1,22 @@ +#include +#include + +using namespace Eigen; + +template +void copyUpperTriangularPart(MatrixBase& dst, const MatrixBase& src) +{ + /* Note the 'template' keywords in the following line! */ + dst.template triangularView() = src.template triangularView(); +} + +int main() +{ + MatrixXi m1 = MatrixXi::Ones(5,5); + MatrixXi m2 = MatrixXi::Random(4,4); + std::cout << "m2 before copy:" << std::endl; + std::cout << m2 << std::endl << std::endl; + copyUpperTriangularPart(m2, m1.topLeftCorner(4,4)); + std::cout << "m2 after copy:" << std::endl; + std::cout << m2 << std::endl << std::endl; +} diff --git a/gtsam/3rdparty/Eigen/doc/examples/TemplateKeyword_simple.cpp b/gtsam/3rdparty/Eigen/doc/examples/TemplateKeyword_simple.cpp new file mode 100644 index 000000000..6998c1769 --- /dev/null +++ b/gtsam/3rdparty/Eigen/doc/examples/TemplateKeyword_simple.cpp @@ -0,0 +1,20 @@ +#include +#include + +using namespace Eigen; + +void copyUpperTriangularPart(MatrixXf& dst, const MatrixXf& src) +{ + dst.triangularView() = src.triangularView(); +} + +int main() +{ + MatrixXf m1 = MatrixXf::Ones(4,4); + MatrixXf m2 = MatrixXf::Random(4,4); + std::cout << "m2 before copy:" << std::endl; + std::cout << m2 << std::endl << std::endl; + copyUpperTriangularPart(m2, m1); + std::cout << "m2 after copy:" << std::endl; + std::cout << m2 << std::endl << std::endl; +} diff --git a/gtsam/3rdparty/Eigen/doc/examples/Tutorial_ReductionsVisitorsBroadcasting_broadcast_simple_rowwise.cpp b/gtsam/3rdparty/Eigen/doc/examples/Tutorial_ReductionsVisitorsBroadcasting_broadcast_simple_rowwise.cpp index 9959c7909..d87c96ab1 100644 --- a/gtsam/3rdparty/Eigen/doc/examples/Tutorial_ReductionsVisitorsBroadcasting_broadcast_simple_rowwise.cpp +++ b/gtsam/3rdparty/Eigen/doc/examples/Tutorial_ReductionsVisitorsBroadcasting_broadcast_simple_rowwise.cpp @@ -13,7 +13,7 @@ int main() v << 0,1,2,3; //add v to each row of m - mat.rowwise() += v; + mat.rowwise() += v.transpose(); std::cout << "Broadcasting result: " << std::endl; std::cout << mat << std::endl; diff --git a/gtsam/3rdparty/Eigen/doc/snippets/Cwise_boolean_and.cpp b/gtsam/3rdparty/Eigen/doc/snippets/Cwise_boolean_and.cpp new file mode 100644 index 000000000..df6b60d92 --- /dev/null +++ b/gtsam/3rdparty/Eigen/doc/snippets/Cwise_boolean_and.cpp @@ -0,0 +1,2 @@ +Array3d v(-1,2,1), w(-3,2,3); +cout << ((v lltOfA(A); // compute the Cholesky decomposition of A +MatrixXd L = lltOfA.matrixL(); // retrieve factor L in the decomposition +// The previous two lines can also be written as "L = A.llt().matrixL()" + +cout << "The Cholesky factor L is" << endl << L << endl; +cout << "To check this, let us compute L * L.transpose()" << endl; +cout << L * L.transpose() << endl; +cout << "This should equal the matrix A" << endl; diff --git a/gtsam/3rdparty/Eigen/doc/snippets/compile_snippet.cpp.in b/gtsam/3rdparty/Eigen/doc/snippets/compile_snippet.cpp.in index 474542380..894cd526c 100644 --- a/gtsam/3rdparty/Eigen/doc/snippets/compile_snippet.cpp.in +++ b/gtsam/3rdparty/Eigen/doc/snippets/compile_snippet.cpp.in @@ -1,10 +1,4 @@ -#include -#include -#include -#include -#include -#include -#include +#include #include using namespace Eigen; diff --git a/gtsam/3rdparty/Eigen/doc/special_examples/CMakeLists.txt b/gtsam/3rdparty/Eigen/doc/special_examples/CMakeLists.txt new file mode 100644 index 000000000..eeeae1d2a --- /dev/null +++ b/gtsam/3rdparty/Eigen/doc/special_examples/CMakeLists.txt @@ -0,0 +1,20 @@ + +if(NOT EIGEN_TEST_NOQT) + find_package(Qt4) + if(QT4_FOUND) + include(${QT_USE_FILE}) + endif() +endif(NOT EIGEN_TEST_NOQT) + + +if(QT4_FOUND) + add_executable(Tutorial_sparse_example Tutorial_sparse_example.cpp Tutorial_sparse_example_details.cpp) + target_link_libraries(Tutorial_sparse_example ${EIGEN_STANDARD_LIBRARIES_TO_LINK_TO} ${QT_QTCORE_LIBRARY} ${QT_QTGUI_LIBRARY}) + + add_custom_command( + TARGET Tutorial_sparse_example + POST_BUILD + COMMAND Tutorial_sparse_example + ARGS ${CMAKE_CURRENT_BINARY_DIR}/../html/Tutorial_sparse_example.jpeg + ) +endif(QT4_FOUND) diff --git a/gtsam/3rdparty/Eigen/doc/special_examples/Tutorial_sparse_example.cpp b/gtsam/3rdparty/Eigen/doc/special_examples/Tutorial_sparse_example.cpp new file mode 100644 index 000000000..002f19f01 --- /dev/null +++ b/gtsam/3rdparty/Eigen/doc/special_examples/Tutorial_sparse_example.cpp @@ -0,0 +1,32 @@ +#include +#include + +typedef Eigen::SparseMatrix SpMat; // declares a column-major sparse matrix type of double +typedef Eigen::Triplet T; + +void buildProblem(std::vector& coefficients, Eigen::VectorXd& b, int n); +void saveAsBitmap(const Eigen::VectorXd& x, int n, const char* filename); + +int main(int argc, char** argv) +{ + int n = 300; // size of the image + int m = n*n; // number of unknows (=number of pixels) + + // Assembly: + std::vector coefficients; // list of non-zeros coefficients + Eigen::VectorXd b(m); // the right hand side-vector resulting from the constraints + buildProblem(coefficients, b, n); + + SpMat A(m,m); + A.setFromTriplets(coefficients.begin(), coefficients.end()); + + // Solving: + Eigen::SimplicialCholesky chol(A); // performs a Cholesky factorization of A + Eigen::VectorXd x = chol.solve(b); // use the factorization to solve for the given right hand side + + // Export the result to a file: + saveAsBitmap(x, n, argv[1]); + + return 0; +} + diff --git a/gtsam/3rdparty/Eigen/doc/special_examples/Tutorial_sparse_example_details.cpp b/gtsam/3rdparty/Eigen/doc/special_examples/Tutorial_sparse_example_details.cpp new file mode 100644 index 000000000..8c3020b63 --- /dev/null +++ b/gtsam/3rdparty/Eigen/doc/special_examples/Tutorial_sparse_example_details.cpp @@ -0,0 +1,44 @@ +#include +#include +#include + +typedef Eigen::SparseMatrix SpMat; // declares a column-major sparse matrix type of double +typedef Eigen::Triplet T; + +void insertCoefficient(int id, int i, int j, double w, std::vector& coeffs, + Eigen::VectorXd& b, const Eigen::VectorXd& boundary) +{ + int n = boundary.size(); + int id1 = i+j*n; + + if(i==-1 || i==n) b(id) -= w * boundary(j); // constrained coeffcieint + else if(j==-1 || j==n) b(id) -= w * boundary(i); // constrained coeffcieint + else coeffs.push_back(T(id,id1,w)); // unknown coefficient +} + +void buildProblem(std::vector& coefficients, Eigen::VectorXd& b, int n) +{ + b.setZero(); + Eigen::ArrayXd boundary = Eigen::ArrayXd::LinSpaced(n, 0,M_PI).sin().pow(2); + for(int j=0; j bits = (x*255).cast(); + QImage img(bits.data(), n,n,QImage::Format_Indexed8); + img.setColorCount(256); + for(int i=0;i<256;i++) img.setColor(i,qRgb(i,i,i)); + img.save(filename); +} diff --git a/gtsam/3rdparty/Eigen/lapack/CMakeLists.txt b/gtsam/3rdparty/Eigen/lapack/CMakeLists.txt index 96d6a416d..062845a3f 100644 --- a/gtsam/3rdparty/Eigen/lapack/CMakeLists.txt +++ b/gtsam/3rdparty/Eigen/lapack/CMakeLists.txt @@ -1,27 +1,23 @@ project(EigenLapack CXX) -if( NOT DEFINED EIGEN_Fortran_COMPILER_WORKS OR EIGEN_Fortran_COMPILER_WORKS) +include("../cmake/language_support.cmake") +workaround_9220(Fortran EIGEN_Fortran_COMPILER_WORKS) + +if(EIGEN_Fortran_COMPILER_WORKS) enable_language(Fortran OPTIONAL) - - if(CMAKE_Fortran_COMPILER_WORKS) - set(EIGEN_Fortran_COMPILER_WORKS TRUE CACHE INTERNAL "workaround cmake's enable_language issue") - else() - set(EIGEN_Fortran_COMPILER_WORKS FALSE CACHE INTERNAL "workaround cmake's enable_language issue") - endif() - endif() -if(CMAKE_Fortran_COMPILER_WORKS) - add_custom_target(lapack) include_directories(../blas) set(EigenLapack_SRCS -single.cpp double.cpp complex_single.cpp complex_double.cpp +single.cpp double.cpp complex_single.cpp complex_double.cpp ../blas/xerbla.cpp ) +if(EIGEN_Fortran_COMPILER_WORKS) + get_filename_component(eigen_full_path_to_reference_to_reference_lapack "./reference/" ABSOLUTE) if(EXISTS ${eigen_full_path_to_reference_to_reference_lapack}) set(EigenLapack_SRCS ${EigenLapack_SRCS} @@ -357,6 +353,8 @@ reference/ctbcon.f reference/dormhr.f reference/sla_ ) endif() +endif(EIGEN_Fortran_COMPILER_WORKS) + add_library(eigen_lapack_static ${EigenLapack_SRCS}) add_library(eigen_lapack SHARED ${EigenLapack_SRCS}) @@ -365,14 +363,12 @@ if(EIGEN_STANDARD_LIBRARIES_TO_LINK_TO) target_link_libraries(eigen_lapack ${EIGEN_STANDARD_LIBRARIES_TO_LINK_TO}) endif() -# add_dependencies(lapack eigen_lapack eigen_lapack_static) -add_dependencies(lapack eigen_lapack_static) - -# install(TARGETS eigen_lapack -# RUNTIME DESTINATION bin -# LIBRARY DESTINATION lib -# ARCHIVE DESTINATION lib) +add_dependencies(lapack eigen_lapack eigen_lapack_static) +install(TARGETS eigen_lapack eigen_lapack_static + RUNTIME DESTINATION bin + LIBRARY DESTINATION lib + ARCHIVE DESTINATION lib) # add_subdirectory(testing) -endif(CMAKE_Fortran_COMPILER_WORKS) + diff --git a/gtsam/3rdparty/Eigen/lapack/cholesky.cpp b/gtsam/3rdparty/Eigen/lapack/cholesky.cpp index c3a72c3c5..c51a8a29b 100644 --- a/gtsam/3rdparty/Eigen/lapack/cholesky.cpp +++ b/gtsam/3rdparty/Eigen/lapack/cholesky.cpp @@ -41,8 +41,8 @@ EIGEN_LAPACK_FUNC(potrf,(char* uplo, int *n, RealScalar *pa, int *lda, int *info Scalar* a = reinterpret_cast(pa); MatrixType A(a,*n,*n,*lda); int ret; - if(UPLO(*uplo)==UP) ret = internal::llt_inplace::blocked(A); - else ret = internal::llt_inplace::blocked(A); + if(UPLO(*uplo)==UP) ret = internal::llt_inplace::blocked(A); + else ret = internal::llt_inplace::blocked(A); if(ret>=0) *info = ret+1; diff --git a/gtsam/3rdparty/Eigen/scripts/eigen_gen_docs b/gtsam/3rdparty/Eigen/scripts/eigen_gen_docs index e97e9ab8f..921d600ed 100644 --- a/gtsam/3rdparty/Eigen/scripts/eigen_gen_docs +++ b/gtsam/3rdparty/Eigen/scripts/eigen_gen_docs @@ -8,14 +8,15 @@ USER=${USER:-'orzel'} #ulimit -v 1024000 # step 1 : build -# todo if 'build is not there, create one: mkdir build -p (cd build && cmake .. && make doc) || { echo "make failed"; exit 1; } -#todo: n+1 where n = number of cpus #step 2 : upload -# (the '/' at the end of path are very important, see rsync documentation) -rsync -az --no-p build/doc/html/ $USER@ssh.tuxfamily.org:eigen/eigen.tuxfamily.org-web/htdocs/dox-3.0/ || { echo "upload failed"; exit 1; } +# (the '/' at the end of path is very important, see rsync documentation) +rsync -az --no-p --delete build/doc/html/ $USER@ssh.tuxfamily.org:eigen/eigen.tuxfamily.org-web/htdocs/dox-devel/ || { echo "upload failed"; exit 1; } + +#step 3 : fix the perm +ssh $USER@ssh.tuxfamily.org 'chmod -R g+w /home/eigen/eigen.tuxfamily.org-web/htdocs/dox-devel' || { echo "perm failed"; exit 1; } echo "Uploaded successfully" diff --git a/gtsam/3rdparty/Eigen/test/CMakeLists.txt b/gtsam/3rdparty/Eigen/test/CMakeLists.txt index fab7de0d4..6f8fc4ae3 100644 --- a/gtsam/3rdparty/Eigen/test/CMakeLists.txt +++ b/gtsam/3rdparty/Eigen/test/CMakeLists.txt @@ -1,17 +1,90 @@ -find_package(GSL) -if(GSL_FOUND AND GSL_VERSION_MINOR LESS 9) - set(GSL_FOUND "") -endif(GSL_FOUND AND GSL_VERSION_MINOR LESS 9) -if(GSL_FOUND) - add_definitions("-DHAS_GSL" ${GSL_DEFINITIONS}) - include_directories(${GSL_INCLUDE_DIR}) - ei_add_property(EIGEN_TESTED_BACKENDS "GSL, ") -else(GSL_FOUND) - ei_add_property(EIGEN_MISSING_BACKENDS "GSL, ") - set(GSL_LIBRARIES "") -endif(GSL_FOUND) +# generate split test header file +message(STATUS ${CMAKE_CURRENT_BINARY_DIR}) +file(WRITE ${CMAKE_CURRENT_BINARY_DIR}/split_test_helper.h "") +foreach(i RANGE 1 999) + file(APPEND ${CMAKE_CURRENT_BINARY_DIR}/split_test_helper.h + "#ifdef EIGEN_TEST_PART_${i}\n" + "#define CALL_SUBTEST_${i}(FUNC) CALL_SUBTEST(FUNC)\n" + "#else\n" + "#define CALL_SUBTEST_${i}(FUNC)\n" + "#endif\n\n" + ) +endforeach() +# configure blas/lapack (use Eigen's ones) +set(BLAS_FOUND TRUE) +set(LAPACK_FOUND TRUE) +set(BLAS_LIBRARIES eigen_blas) +set(LAPACK_LIBRARIES eigen_lapack) + +set(EIGEN_TEST_MATRIX_DIR "" CACHE STRING "Enable testing of realword sparse matrices contained in the specified path") +if(EIGEN_TEST_MATRIX_DIR) + if(NOT WIN32) + message(STATUS "Test realworld sparse matrices: ${EIGEN_TEST_MATRIX_DIR}") + add_definitions( -DTEST_REAL_CASES="${EIGEN_TEST_MATRIX_DIR}" ) + else(NOT WIN32) + message(STATUS "REAL CASES CAN NOT BE CURRENTLY TESTED ON WIN32") + endif(NOT WIN32) +endif(EIGEN_TEST_MATRIX_DIR) + +set(SPARSE_LIBS " ") + +find_package(Cholmod) +if(CHOLMOD_FOUND AND BLAS_FOUND AND LAPACK_FOUND) + add_definitions("-DEIGEN_CHOLMOD_SUPPORT") + include_directories(${CHOLMOD_INCLUDES}) + set(SPARSE_LIBS ${SPARSE_LIBS} ${CHOLMOD_LIBRARIES} ${BLAS_LIBRARIES} ${LAPACK_LIBRARIES}) + set(CHOLMOD_ALL_LIBS ${CHOLMOD_LIBRARIES} ${BLAS_LIBRARIES} ${LAPACK_LIBRARIES}) + ei_add_property(EIGEN_TESTED_BACKENDS "Cholmod, ") +else() + ei_add_property(EIGEN_MISSING_BACKENDS "Cholmod, ") +endif() + +find_package(Umfpack) +if(UMFPACK_FOUND AND BLAS_FOUND) + add_definitions("-DEIGEN_UMFPACK_SUPPORT") + include_directories(${UMFPACK_INCLUDES}) + set(SPARSE_LIBS ${SPARSE_LIBS} ${UMFPACK_LIBRARIES} ${BLAS_LIBRARIES}) + set(UMFPACK_ALL_LIBS ${UMFPACK_LIBRARIES} ${BLAS_LIBRARIES}) + ei_add_property(EIGEN_TESTED_BACKENDS "UmfPack, ") +else() + ei_add_property(EIGEN_MISSING_BACKENDS "UmfPack, ") +endif() + +find_package(SuperLU) +if(SUPERLU_FOUND AND BLAS_FOUND) + add_definitions("-DEIGEN_SUPERLU_SUPPORT") + include_directories(${SUPERLU_INCLUDES}) + set(SPARSE_LIBS ${SPARSE_LIBS} ${SUPERLU_LIBRARIES} ${BLAS_LIBRARIES}) + set(SUPERLU_ALL_LIBS ${SUPERLU_LIBRARIES} ${BLAS_LIBRARIES}) + ei_add_property(EIGEN_TESTED_BACKENDS "SuperLU, ") +else() + ei_add_property(EIGEN_MISSING_BACKENDS "SuperLU, ") +endif() + + +find_package(Pastix) +find_package(Scotch) +find_package(Metis) +if(PASTIX_FOUND AND BLAS_FOUND) + add_definitions("-DEIGEN_PASTIX_SUPPORT") + include_directories(${PASTIX_INCLUDES}) + if(SCOTCH_FOUND) + include_directories(${SCOTCH_INCLUDES}) + set(PASTIX_LIBRARIES ${PASTIX_LIBRARIES} ${SCOTCH_LIBRARIES}) + elseif(METIS_FOUND) + include_directories(${METIS_INCLUDES}) + set(PASTIX_LIBRARIES ${PASTIX_LIBRARIES} ${METIS_LIBRARIES}) + else(SCOTCH_FOUND) + ei_add_property(EIGEN_MISSING_BACKENDS "PaStiX, ") + endif(SCOTCH_FOUND) + set(SPARSE_LIBS ${SPARSE_LIBS} ${PASTIX_LIBRARIES} ${ORDERING_LIBRARIES} ${BLAS_LIBRARIES}) + set(PASTIX_ALL_LIBS ${PASTIX_LIBRARIES} ${BLAS_LIBRARIES}) + ei_add_property(EIGEN_TESTED_BACKENDS "PaStiX, ") +else() + ei_add_property(EIGEN_MISSING_BACKENDS "PaStiX, ") +endif() option(EIGEN_TEST_NOQT "Disable Qt support in unit tests" OFF) if(NOT EIGEN_TEST_NOQT) @@ -75,7 +148,7 @@ ei_add_test(product_mmtr) ei_add_test(product_notemporary) ei_add_test(stable_norm) ei_add_test(bandmatrix) -ei_add_test(cholesky "" "${GSL_LIBRARIES}") +ei_add_test(cholesky) ei_add_test(lu) ei_add_test(determinant) ei_add_test(inverse) @@ -86,8 +159,8 @@ ei_add_test(upperbidiagonalization) ei_add_test(hessenberg) ei_add_test(schur_real) ei_add_test(schur_complex) -ei_add_test(eigensolver_selfadjoint "" "${GSL_LIBRARIES}") -ei_add_test(eigensolver_generic "" "${GSL_LIBRARIES}") +ei_add_test(eigensolver_selfadjoint) +ei_add_test(eigensolver_generic) ei_add_test(eigensolver_complex) ei_add_test(jacobi) ei_add_test(jacobisvd) @@ -110,12 +183,13 @@ endif(QT4_FOUND) ei_add_test(sparse_vector) ei_add_test(sparse_basic) ei_add_test(sparse_product) -ei_add_test(sparse_solvers "" "${SPARSE_LIBS}") +ei_add_test(sparse_solvers) ei_add_test(umeyama) ei_add_test(householder) ei_add_test(swap) ei_add_test(conservative_resize) ei_add_test(permutationmatrices) +ei_add_test(sparse_permutations) ei_add_test(eigen2support) ei_add_test(nullary) ei_add_test(nesting_ops "${CMAKE_CXX_FLAGS_DEBUG}") @@ -123,6 +197,32 @@ ei_add_test(zerosized) ei_add_test(dontalign) ei_add_test(sizeoverflow) ei_add_test(prec_inverse_4x4) +ei_add_test(vectorwiseop) + +ei_add_test(simplicial_cholesky) +ei_add_test(conjugate_gradient) +ei_add_test(bicgstab) + + +if(UMFPACK_FOUND) + ei_add_test(umfpack_support "" "${UMFPACK_ALL_LIBS}") +endif() + +if(SUPERLU_FOUND) + ei_add_test(superlu_support "" "${SUPERLU_ALL_LIBS}") +endif() + +if(CHOLMOD_FOUND) + ei_add_test(cholmod_support "" "${CHOLMOD_ALL_LIBS}") +endif() + +if(PARDISO_FOUND) + ei_add_test(pardiso_support "" "${PARDISO_ALL_LIBS}") +endif() + +if(PASTIX_FOUND AND (SCOTCH_FOUND OR METIS_FOUND)) + ei_add_test(pastix_support "" "${PASTIX_ALL_LIBS}") +endif() string(TOLOWER "${CMAKE_CXX_COMPILER}" cmake_cxx_compiler_tolower) if(cmake_cxx_compiler_tolower MATCHES "qcc") diff --git a/gtsam/3rdparty/Eigen/test/adjoint.cpp b/gtsam/3rdparty/Eigen/test/adjoint.cpp index d8d2aaa1b..140283477 100644 --- a/gtsam/3rdparty/Eigen/test/adjoint.cpp +++ b/gtsam/3rdparty/Eigen/test/adjoint.cpp @@ -43,8 +43,6 @@ template void adjoint(const MatrixType& m) MatrixType m1 = MatrixType::Random(rows, cols), m2 = MatrixType::Random(rows, cols), m3(rows, cols), - mzero = MatrixType::Zero(rows, cols), - identity = SquareMatrixType::Identity(rows, rows), square = SquareMatrixType::Random(rows, rows); VectorType v1 = VectorType::Random(rows), v2 = VectorType::Random(rows), @@ -65,15 +63,23 @@ template void adjoint(const MatrixType& m) // check basic properties of dot, norm, norm2 typedef typename NumTraits::Real RealScalar; - RealScalar ref = NumTraits::IsInteger ? 0 : (std::max)((s1 * v1 + s2 * v2).norm(),v3.norm()); + RealScalar ref = NumTraits::IsInteger ? RealScalar(0) : (std::max)((s1 * v1 + s2 * v2).norm(),v3.norm()); VERIFY(test_isApproxWithRef((s1 * v1 + s2 * v2).dot(v3), internal::conj(s1) * v1.dot(v3) + internal::conj(s2) * v2.dot(v3), ref)); VERIFY(test_isApproxWithRef(v3.dot(s1 * v1 + s2 * v2), s1*v3.dot(v1)+s2*v3.dot(v2), ref)); VERIFY_IS_APPROX(internal::conj(v1.dot(v2)), v2.dot(v1)); VERIFY_IS_APPROX(internal::real(v1.dot(v1)), v1.squaredNorm()); - if(!NumTraits::IsInteger) + if(!NumTraits::IsInteger) { VERIFY_IS_APPROX(v1.squaredNorm(), v1.norm() * v1.norm()); + // check normalized() and normalize() + VERIFY_IS_APPROX(v1, v1.norm() * v1.normalized()); + v3 = v1; + v3.normalize(); + VERIFY_IS_APPROX(v1, v1.norm() * v3); + VERIFY_IS_APPROX(v3, v1.normalized()); + VERIFY_IS_APPROX(v3.norm(), RealScalar(1)); + } VERIFY_IS_MUCH_SMALLER_THAN(internal::abs(vzero.dot(v1)), static_cast(1)); - + // check compatibility of dot and adjoint ref = NumTraits::IsInteger ? 0 : (std::max)((std::max)(v1.norm(),v2.norm()),(std::max)((square * v2).norm(),(square.adjoint() * v1).norm())); @@ -119,11 +125,11 @@ void test_adjoint() CALL_SUBTEST_1( adjoint(Matrix()) ); CALL_SUBTEST_2( adjoint(Matrix3d()) ); CALL_SUBTEST_3( adjoint(Matrix4f()) ); - CALL_SUBTEST_4( adjoint(MatrixXcf(internal::random(1,50), internal::random(1,50))) ); - CALL_SUBTEST_5( adjoint(MatrixXi(internal::random(1,50), internal::random(1,50))) ); - CALL_SUBTEST_6( adjoint(MatrixXf(internal::random(1,50), internal::random(1,50))) ); + CALL_SUBTEST_4( adjoint(MatrixXcf(internal::random(1,EIGEN_TEST_MAX_SIZE/2), internal::random(1,EIGEN_TEST_MAX_SIZE/2))) ); + CALL_SUBTEST_5( adjoint(MatrixXi(internal::random(1,EIGEN_TEST_MAX_SIZE), internal::random(1,EIGEN_TEST_MAX_SIZE))) ); + CALL_SUBTEST_6( adjoint(MatrixXf(internal::random(1,EIGEN_TEST_MAX_SIZE), internal::random(1,EIGEN_TEST_MAX_SIZE))) ); } - // test a large matrix only once + // test a large static matrix only once CALL_SUBTEST_7( adjoint(Matrix()) ); #ifdef EIGEN_TEST_PART_4 diff --git a/gtsam/3rdparty/Eigen/test/array.cpp b/gtsam/3rdparty/Eigen/test/array.cpp index 6964075ea..912c28c88 100644 --- a/gtsam/3rdparty/Eigen/test/array.cpp +++ b/gtsam/3rdparty/Eigen/test/array.cpp @@ -43,7 +43,7 @@ template void array(const ArrayType& m) RowVectorType rv1 = RowVectorType::Random(cols); Scalar s1 = internal::random(), - s2 = internal::random(); + s2 = internal::random(); // scalar addition VERIFY_IS_APPROX(m1 + s1, s1 + m1); @@ -149,6 +149,12 @@ template void comparisons(const ArrayType& m) // count VERIFY(((m1.abs()+1)>RealScalar(0.1)).count() == rows*cols); + // and/or + VERIFY( (m1RealScalar(0)).count() == 0); + VERIFY( (m1=RealScalar(0)).count() == rows*cols); + RealScalar a = m1.abs().mean(); + VERIFY( (m1<-a || m1>a).count() == (m1.abs()>a).count()); + typedef Array ArrayOfIndices; // TODO allows colwise/rowwise for array @@ -169,7 +175,9 @@ template void array_real(const ArrayType& m) m2 = ArrayType::Random(rows, cols), m3(rows, cols); - // these these are mostly to check possible compilation issues. + Scalar s1 = internal::random(); + + // these tests are mostly to check possible compilation issues. VERIFY_IS_APPROX(m1.sin(), std::sin(m1)); VERIFY_IS_APPROX(m1.sin(), internal::sin(m1)); VERIFY_IS_APPROX(m1.cos(), std::cos(m1)); @@ -180,7 +188,7 @@ template void array_real(const ArrayType& m) VERIFY_IS_APPROX(m1.acos(), internal::acos(m1)); VERIFY_IS_APPROX(m1.tan(), std::tan(m1)); VERIFY_IS_APPROX(m1.tan(), internal::tan(m1)); - + VERIFY_IS_APPROX(internal::cos(m1+RealScalar(3)*m2), internal::cos((m1+RealScalar(3)*m2).eval())); VERIFY_IS_APPROX(std::cos(m1+RealScalar(3)*m2), std::cos((m1+RealScalar(3)*m2).eval())); @@ -203,9 +211,67 @@ template void array_real(const ArrayType& m) VERIFY_IS_APPROX(m1.pow(2), m1.square()); VERIFY_IS_APPROX(std::pow(m1,2), m1.square()); + + ArrayType exponents = ArrayType::Constant(rows, cols, RealScalar(2)); + VERIFY_IS_APPROX(std::pow(m1,exponents), m1.square()); + m3 = m1.abs(); VERIFY_IS_APPROX(m3.pow(RealScalar(0.5)), m3.sqrt()); VERIFY_IS_APPROX(std::pow(m3,RealScalar(0.5)), m3.sqrt()); + + // scalar by array division + const RealScalar tiny = std::sqrt(std::numeric_limits::epsilon()); + s1 += Scalar(tiny); + m1 += ArrayType::Constant(rows,cols,Scalar(tiny)); + VERIFY_IS_APPROX(s1/m1, s1 * m1.inverse()); +} + +template void array_complex(const ArrayType& m) +{ + typedef typename ArrayType::Index Index; + + Index rows = m.rows(); + Index cols = m.cols(); + + ArrayType m1 = ArrayType::Random(rows, cols), + m2(rows, cols); + + for (Index i = 0; i < m.rows(); ++i) + for (Index j = 0; j < m.cols(); ++j) + m2(i,j) = std::sqrt(m1(i,j)); + + VERIFY_IS_APPROX(m1.sqrt(), m2); + VERIFY_IS_APPROX(m1.sqrt(), std::sqrt(m1)); + VERIFY_IS_APPROX(m1.sqrt(), internal::sqrt(m1)); +} + +template void min_max(const ArrayType& m) +{ + typedef typename ArrayType::Index Index; + typedef typename ArrayType::Scalar Scalar; + + Index rows = m.rows(); + Index cols = m.cols(); + + ArrayType m1 = ArrayType::Random(rows, cols); + + // min/max with array + Scalar maxM1 = m1.maxCoeff(); + Scalar minM1 = m1.minCoeff(); + + VERIFY_IS_APPROX(ArrayType::Constant(rows,cols, minM1), (m1.min)(ArrayType::Constant(rows,cols, minM1))); + VERIFY_IS_APPROX(m1, (m1.min)(ArrayType::Constant(rows,cols, maxM1))); + + VERIFY_IS_APPROX(ArrayType::Constant(rows,cols, maxM1), (m1.max)(ArrayType::Constant(rows,cols, maxM1))); + VERIFY_IS_APPROX(m1, (m1.max)(ArrayType::Constant(rows,cols, minM1))); + + // min/max with scalar input + VERIFY_IS_APPROX(ArrayType::Constant(rows,cols, minM1), (m1.min)( minM1)); + VERIFY_IS_APPROX(m1, (m1.min)( maxM1)); + + VERIFY_IS_APPROX(ArrayType::Constant(rows,cols, maxM1), (m1.max)( maxM1)); + VERIFY_IS_APPROX(m1, (m1.max)( minM1)); + } void test_array() @@ -214,22 +280,32 @@ void test_array() CALL_SUBTEST_1( array(Array()) ); CALL_SUBTEST_2( array(Array22f()) ); CALL_SUBTEST_3( array(Array44d()) ); - CALL_SUBTEST_4( array(ArrayXXcf(3, 3)) ); - CALL_SUBTEST_5( array(ArrayXXf(8, 12)) ); - CALL_SUBTEST_6( array(ArrayXXi(8, 12)) ); + CALL_SUBTEST_4( array(ArrayXXcf(internal::random(1,EIGEN_TEST_MAX_SIZE), internal::random(1,EIGEN_TEST_MAX_SIZE))) ); + CALL_SUBTEST_5( array(ArrayXXf(internal::random(1,EIGEN_TEST_MAX_SIZE), internal::random(1,EIGEN_TEST_MAX_SIZE))) ); + CALL_SUBTEST_6( array(ArrayXXi(internal::random(1,EIGEN_TEST_MAX_SIZE), internal::random(1,EIGEN_TEST_MAX_SIZE))) ); } for(int i = 0; i < g_repeat; i++) { CALL_SUBTEST_1( comparisons(Array()) ); CALL_SUBTEST_2( comparisons(Array22f()) ); CALL_SUBTEST_3( comparisons(Array44d()) ); - CALL_SUBTEST_5( comparisons(ArrayXXf(8, 12)) ); - CALL_SUBTEST_6( comparisons(ArrayXXi(8, 12)) ); + CALL_SUBTEST_5( comparisons(ArrayXXf(internal::random(1,EIGEN_TEST_MAX_SIZE), internal::random(1,EIGEN_TEST_MAX_SIZE))) ); + CALL_SUBTEST_6( comparisons(ArrayXXi(internal::random(1,EIGEN_TEST_MAX_SIZE), internal::random(1,EIGEN_TEST_MAX_SIZE))) ); + } + for(int i = 0; i < g_repeat; i++) { + CALL_SUBTEST_1( min_max(Array()) ); + CALL_SUBTEST_2( min_max(Array22f()) ); + CALL_SUBTEST_3( min_max(Array44d()) ); + CALL_SUBTEST_5( min_max(ArrayXXf(internal::random(1,EIGEN_TEST_MAX_SIZE), internal::random(1,EIGEN_TEST_MAX_SIZE))) ); + CALL_SUBTEST_6( min_max(ArrayXXi(internal::random(1,EIGEN_TEST_MAX_SIZE), internal::random(1,EIGEN_TEST_MAX_SIZE))) ); } for(int i = 0; i < g_repeat; i++) { CALL_SUBTEST_1( array_real(Array()) ); CALL_SUBTEST_2( array_real(Array22f()) ); CALL_SUBTEST_3( array_real(Array44d()) ); - CALL_SUBTEST_5( array_real(ArrayXXf(8, 12)) ); + CALL_SUBTEST_5( array_real(ArrayXXf(internal::random(1,EIGEN_TEST_MAX_SIZE), internal::random(1,EIGEN_TEST_MAX_SIZE))) ); + } + for(int i = 0; i < g_repeat; i++) { + CALL_SUBTEST_4( array_complex(ArrayXXcf(internal::random(1,EIGEN_TEST_MAX_SIZE), internal::random(1,EIGEN_TEST_MAX_SIZE))) ); } VERIFY((internal::is_same< internal::global_math_functions_filtering_base::type, int >::value)); diff --git a/gtsam/3rdparty/Eigen/test/array_for_matrix.cpp b/gtsam/3rdparty/Eigen/test/array_for_matrix.cpp index 45e0930ce..465b8998b 100644 --- a/gtsam/3rdparty/Eigen/test/array_for_matrix.cpp +++ b/gtsam/3rdparty/Eigen/test/array_for_matrix.cpp @@ -156,30 +156,65 @@ template void lpNorm(const VectorType& v) VERIFY_IS_APPROX(internal::pow(u.template lpNorm<5>(), typename VectorType::RealScalar(5)), u.array().abs().pow(5).sum()); } +template void cwise_min_max(const MatrixType& m) +{ + typedef typename MatrixType::Index Index; + typedef typename MatrixType::Scalar Scalar; + + Index rows = m.rows(); + Index cols = m.cols(); + + MatrixType m1 = MatrixType::Random(rows, cols); + + // min/max with array + Scalar maxM1 = m1.maxCoeff(); + Scalar minM1 = m1.minCoeff(); + + VERIFY_IS_APPROX(MatrixType::Constant(rows,cols, minM1), m1.cwiseMin(MatrixType::Constant(rows,cols, minM1))); + VERIFY_IS_APPROX(m1, m1.cwiseMin(MatrixType::Constant(rows,cols, maxM1))); + + VERIFY_IS_APPROX(MatrixType::Constant(rows,cols, maxM1), m1.cwiseMax(MatrixType::Constant(rows,cols, maxM1))); + VERIFY_IS_APPROX(m1, m1.cwiseMax(MatrixType::Constant(rows,cols, minM1))); + + // min/max with scalar input + VERIFY_IS_APPROX(MatrixType::Constant(rows,cols, minM1), m1.cwiseMin( minM1)); + VERIFY_IS_APPROX(m1, m1.cwiseMin( maxM1)); + + VERIFY_IS_APPROX(MatrixType::Constant(rows,cols, maxM1), m1.cwiseMax( maxM1)); + VERIFY_IS_APPROX(m1, m1.cwiseMax( minM1)); + +} + void test_array_for_matrix() { - int maxsize = 40; for(int i = 0; i < g_repeat; i++) { CALL_SUBTEST_1( array_for_matrix(Matrix()) ); CALL_SUBTEST_2( array_for_matrix(Matrix2f()) ); CALL_SUBTEST_3( array_for_matrix(Matrix4d()) ); - CALL_SUBTEST_4( array_for_matrix(MatrixXcf(internal::random(1,maxsize), internal::random(1,maxsize))) ); - CALL_SUBTEST_5( array_for_matrix(MatrixXf(internal::random(1,maxsize), internal::random(1,maxsize))) ); - CALL_SUBTEST_6( array_for_matrix(MatrixXi(internal::random(1,maxsize), internal::random(1,maxsize))) ); + CALL_SUBTEST_4( array_for_matrix(MatrixXcf(internal::random(1,EIGEN_TEST_MAX_SIZE), internal::random(1,EIGEN_TEST_MAX_SIZE))) ); + CALL_SUBTEST_5( array_for_matrix(MatrixXf(internal::random(1,EIGEN_TEST_MAX_SIZE), internal::random(1,EIGEN_TEST_MAX_SIZE))) ); + CALL_SUBTEST_6( array_for_matrix(MatrixXi(internal::random(1,EIGEN_TEST_MAX_SIZE), internal::random(1,EIGEN_TEST_MAX_SIZE))) ); } for(int i = 0; i < g_repeat; i++) { CALL_SUBTEST_1( comparisons(Matrix()) ); CALL_SUBTEST_2( comparisons(Matrix2f()) ); CALL_SUBTEST_3( comparisons(Matrix4d()) ); - CALL_SUBTEST_5( comparisons(MatrixXf(internal::random(1,maxsize), internal::random(1,maxsize))) ); - CALL_SUBTEST_6( comparisons(MatrixXi(internal::random(1,maxsize), internal::random(1,maxsize))) ); + CALL_SUBTEST_5( comparisons(MatrixXf(internal::random(1,EIGEN_TEST_MAX_SIZE), internal::random(1,EIGEN_TEST_MAX_SIZE))) ); + CALL_SUBTEST_6( comparisons(MatrixXi(internal::random(1,EIGEN_TEST_MAX_SIZE), internal::random(1,EIGEN_TEST_MAX_SIZE))) ); + } + for(int i = 0; i < g_repeat; i++) { + CALL_SUBTEST_1( cwise_min_max(Matrix()) ); + CALL_SUBTEST_2( cwise_min_max(Matrix2f()) ); + CALL_SUBTEST_3( cwise_min_max(Matrix4d()) ); + CALL_SUBTEST_5( cwise_min_max(MatrixXf(internal::random(1,EIGEN_TEST_MAX_SIZE), internal::random(1,EIGEN_TEST_MAX_SIZE))) ); + CALL_SUBTEST_6( cwise_min_max(MatrixXi(internal::random(1,EIGEN_TEST_MAX_SIZE), internal::random(1,EIGEN_TEST_MAX_SIZE))) ); } for(int i = 0; i < g_repeat; i++) { CALL_SUBTEST_1( lpNorm(Matrix()) ); CALL_SUBTEST_2( lpNorm(Vector2f()) ); CALL_SUBTEST_7( lpNorm(Vector3d()) ); CALL_SUBTEST_8( lpNorm(Vector4f()) ); - CALL_SUBTEST_5( lpNorm(VectorXf(internal::random(1,maxsize))) ); - CALL_SUBTEST_4( lpNorm(VectorXcf(internal::random(1,maxsize))) ); + CALL_SUBTEST_5( lpNorm(VectorXf(internal::random(1,EIGEN_TEST_MAX_SIZE))) ); + CALL_SUBTEST_4( lpNorm(VectorXcf(internal::random(1,EIGEN_TEST_MAX_SIZE))) ); } } diff --git a/gtsam/3rdparty/Eigen/test/basicstuff.cpp b/gtsam/3rdparty/Eigen/test/basicstuff.cpp index 9f3966818..76ecffd68 100644 --- a/gtsam/3rdparty/Eigen/test/basicstuff.cpp +++ b/gtsam/3rdparty/Eigen/test/basicstuff.cpp @@ -42,11 +42,8 @@ template void basicStuff(const MatrixType& m) m2 = MatrixType::Random(rows, cols), m3(rows, cols), mzero = MatrixType::Zero(rows, cols), - identity = Matrix - ::Identity(rows, rows), square = Matrix::Random(rows, rows); VectorType v1 = VectorType::Random(rows), - v2 = VectorType::Random(rows), vzero = VectorType::Zero(rows); SquareMatrixType sm1 = SquareMatrixType::Random(rows,rows), sm2(rows,rows); @@ -215,14 +212,14 @@ void test_basicstuff() for(int i = 0; i < g_repeat; i++) { CALL_SUBTEST_1( basicStuff(Matrix()) ); CALL_SUBTEST_2( basicStuff(Matrix4d()) ); - CALL_SUBTEST_3( basicStuff(MatrixXcf(internal::random(1,100), internal::random(1,100))) ); - CALL_SUBTEST_4( basicStuff(MatrixXi(internal::random(1,100), internal::random(1,100))) ); - CALL_SUBTEST_5( basicStuff(MatrixXcd(internal::random(1,100), internal::random(1,100))) ); + CALL_SUBTEST_3( basicStuff(MatrixXcf(internal::random(1,EIGEN_TEST_MAX_SIZE), internal::random(1,EIGEN_TEST_MAX_SIZE))) ); + CALL_SUBTEST_4( basicStuff(MatrixXi(internal::random(1,EIGEN_TEST_MAX_SIZE), internal::random(1,EIGEN_TEST_MAX_SIZE))) ); + CALL_SUBTEST_5( basicStuff(MatrixXcd(internal::random(1,EIGEN_TEST_MAX_SIZE), internal::random(1,EIGEN_TEST_MAX_SIZE))) ); CALL_SUBTEST_6( basicStuff(Matrix()) ); - CALL_SUBTEST_7( basicStuff(Matrix(internal::random(1,100),internal::random(1,100))) ); + CALL_SUBTEST_7( basicStuff(Matrix(internal::random(1,EIGEN_TEST_MAX_SIZE),internal::random(1,EIGEN_TEST_MAX_SIZE))) ); - CALL_SUBTEST_3( basicStuffComplex(MatrixXcf(internal::random(1,100), internal::random(1,100))) ); - CALL_SUBTEST_5( basicStuffComplex(MatrixXcd(internal::random(1,100), internal::random(1,100))) ); + CALL_SUBTEST_3( basicStuffComplex(MatrixXcf(internal::random(1,EIGEN_TEST_MAX_SIZE), internal::random(1,EIGEN_TEST_MAX_SIZE))) ); + CALL_SUBTEST_5( basicStuffComplex(MatrixXcd(internal::random(1,EIGEN_TEST_MAX_SIZE), internal::random(1,EIGEN_TEST_MAX_SIZE))) ); } CALL_SUBTEST_1(fixedSizeMatrixConstruction()); diff --git a/gtsam/3rdparty/Eigen/test/bicgstab.cpp b/gtsam/3rdparty/Eigen/test/bicgstab.cpp new file mode 100644 index 000000000..2b6403583 --- /dev/null +++ b/gtsam/3rdparty/Eigen/test/bicgstab.cpp @@ -0,0 +1,45 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2011 Gael Guennebaud +// +// Eigen is free software; you can redistribute it and/or +// modify it under the terms of the GNU Lesser General Public +// License as published by the Free Software Foundation; either +// version 3 of the License, or (at your option) any later version. +// +// Alternatively, you can redistribute it and/or +// modify it under the terms of the GNU General Public License as +// published by the Free Software Foundation; either version 2 of +// the License, or (at your option) any later version. +// +// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY +// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the +// GNU General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public +// License and a copy of the GNU General Public License along with +// Eigen. If not, see . + +#include "sparse_solver.h" +#include + +template void test_bicgstab_T() +{ + BiCGSTAB, DiagonalPreconditioner > bicgstab_colmajor_diag; + BiCGSTAB, IdentityPreconditioner > bicgstab_colmajor_I; + BiCGSTAB, IncompleteLUT > bicgstab_colmajor_ilut; + //BiCGSTAB, SSORPreconditioner > bicgstab_colmajor_ssor; + + CALL_SUBTEST( check_sparse_square_solving(bicgstab_colmajor_diag) ); +// CALL_SUBTEST( check_sparse_square_solving(bicgstab_colmajor_I) ); + CALL_SUBTEST( check_sparse_square_solving(bicgstab_colmajor_ilut) ); + //CALL_SUBTEST( check_sparse_square_solving(bicgstab_colmajor_ssor) ); +} + +void test_bicgstab() +{ + CALL_SUBTEST_1(test_bicgstab_T()); + CALL_SUBTEST_2(test_bicgstab_T >()); +} diff --git a/gtsam/3rdparty/Eigen/test/block.cpp b/gtsam/3rdparty/Eigen/test/block.cpp index 70852ee48..07d5ce792 100644 --- a/gtsam/3rdparty/Eigen/test/block.cpp +++ b/gtsam/3rdparty/Eigen/test/block.cpp @@ -42,12 +42,8 @@ template void block(const MatrixType& m) m1_copy = m1, m2 = MatrixType::Random(rows, cols), m3(rows, cols), - mzero = MatrixType::Zero(rows, cols), ones = MatrixType::Ones(rows, cols); - VectorType v1 = VectorType::Random(rows), - v2 = VectorType::Random(rows), - v3 = VectorType::Random(rows), - vzero = VectorType::Zero(rows); + VectorType v1 = VectorType::Random(rows); Scalar s1 = internal::random(); diff --git a/gtsam/3rdparty/Eigen/test/cholesky.cpp b/gtsam/3rdparty/Eigen/test/cholesky.cpp index ae4342cee..4f2516d26 100644 --- a/gtsam/3rdparty/Eigen/test/cholesky.cpp +++ b/gtsam/3rdparty/Eigen/test/cholesky.cpp @@ -41,9 +41,37 @@ static int nb_temporaries; VERIFY( (#XPR) && nb_temporaries==N ); \ } -#ifdef HAS_GSL -#include "gsl_helper.h" -#endif +template class CholType> void test_chol_update(const MatrixType& symm) +{ + typedef typename MatrixType::Scalar Scalar; + typedef typename MatrixType::RealScalar RealScalar; + typedef Matrix VectorType; + + MatrixType symmLo = symm.template triangularView(); + MatrixType symmUp = symm.template triangularView(); + MatrixType symmCpy = symm; + + CholType chollo(symmLo); + CholType cholup(symmUp); + + for (int k=0; k<10; ++k) + { + VectorType vec = VectorType::Random(symm.rows()); + RealScalar sigma = internal::random(); + symmCpy += sigma * vec * vec.adjoint(); + + // we are doing some downdates, so it might be the case that the matrix is not SPD anymore + CholType chol(symmCpy); + if(chol.info()!=Success) + break; + + chollo.rankUpdate(vec, sigma); + VERIFY_IS_APPROX(symmCpy, chollo.reconstructedMatrix()); + + cholup.rankUpdate(vec, sigma); + VERIFY_IS_APPROX(symmCpy, cholup.reconstructedMatrix()); + } +} template void cholesky(const MatrixType& m) { @@ -77,34 +105,6 @@ template void cholesky(const MatrixType& m) // FIXME: currently that fails !! //symm.template part().setZero(); - #ifdef HAS_GSL -// if (internal::is_same::value) -// { -// typedef GslTraits Gsl; -// typename Gsl::Matrix gMatA=0, gSymm=0; -// typename Gsl::Vector gVecB=0, gVecX=0; -// convert(symm, gSymm); -// convert(symm, gMatA); -// convert(vecB, gVecB); -// convert(vecB, gVecX); -// Gsl::cholesky(gMatA); -// Gsl::cholesky_solve(gMatA, gVecB, gVecX); -// VectorType vecX(rows), _vecX, _vecB; -// convert(gVecX, _vecX); -// symm.llt().solve(vecB, &vecX); -// Gsl::prod(gSymm, gVecX, gVecB); -// convert(gVecB, _vecB); -// // test gsl itself ! -// VERIFY_IS_APPROX(vecB, _vecB); -// VERIFY_IS_APPROX(vecX, _vecX); -// -// Gsl::free(gMatA); -// Gsl::free(gSymm); -// Gsl::free(gVecB); -// Gsl::free(gVecX); -// } - #endif - { LLT chollo(symmLo); VERIFY_IS_APPROX(symm, chollo.reconstructedMatrix()); @@ -124,6 +124,11 @@ template void cholesky(const MatrixType& m) MatrixType neg = -symmLo; chollo.compute(neg); VERIFY(chollo.info()==NumericalIssue); + + VERIFY_IS_APPROX(MatrixType(chollo.matrixL().transpose().conjugate()), MatrixType(chollo.matrixU())); + VERIFY_IS_APPROX(MatrixType(chollo.matrixU().transpose().conjugate()), MatrixType(chollo.matrixL())); + VERIFY_IS_APPROX(MatrixType(cholup.matrixL().transpose().conjugate()), MatrixType(cholup.matrixU())); + VERIFY_IS_APPROX(MatrixType(cholup.matrixU().transpose().conjugate()), MatrixType(cholup.matrixL())); } // LDLT @@ -152,6 +157,11 @@ template void cholesky(const MatrixType& m) matX = ldltup.solve(matB); VERIFY_IS_APPROX(symm * matX, matB); + VERIFY_IS_APPROX(MatrixType(ldltlo.matrixL().transpose().conjugate()), MatrixType(ldltlo.matrixU())); + VERIFY_IS_APPROX(MatrixType(ldltlo.matrixU().transpose().conjugate()), MatrixType(ldltlo.matrixL())); + VERIFY_IS_APPROX(MatrixType(ldltup.matrixL().transpose().conjugate()), MatrixType(ldltup.matrixU())); + VERIFY_IS_APPROX(MatrixType(ldltup.matrixU().transpose().conjugate()), MatrixType(ldltup.matrixL())); + if(MatrixType::RowsAtCompileTime==Dynamic) { // note : each inplace permutation requires a small temporary vector (mask) @@ -166,6 +176,10 @@ template void cholesky(const MatrixType& m) VERIFY_EVALUATION_COUNT(matX = ldltup.solve(matX), 0); VERIFY_IS_APPROX(matX, ldltup.solve(matB).eval()); } + + // restore + if(sign == -1) + symm = -symm; } // test some special use cases of SelfCwiseBinaryOp: @@ -182,7 +196,10 @@ template void cholesky(const MatrixType& m) m2 = m1; m2.noalias() -= symmLo.template selfadjointView().llt().solve(matB); VERIFY_IS_APPROX(m2, m1 - symmLo.template selfadjointView().llt().solve(matB)); - + + // update/downdate + CALL_SUBTEST(( test_chol_update(symm) )); + CALL_SUBTEST(( test_chol_update(symm) )); } template void cholesky_cplx(const MatrixType& m) @@ -242,7 +259,6 @@ template void cholesky_cplx(const MatrixType& m) // matX = ldltlo.solve(matB); // VERIFY_IS_APPROX(symm * matX, matB); } - } // regression test for bug 241 @@ -290,9 +306,9 @@ void test_cholesky() CALL_SUBTEST_3( cholesky_bug241(Matrix2d()) ); CALL_SUBTEST_4( cholesky(Matrix3f()) ); CALL_SUBTEST_5( cholesky(Matrix4d()) ); - s = internal::random(1,200); + s = internal::random(1,EIGEN_TEST_MAX_SIZE); CALL_SUBTEST_2( cholesky(MatrixXd(s,s)) ); - s = internal::random(1,100); + s = internal::random(1,EIGEN_TEST_MAX_SIZE/2); CALL_SUBTEST_6( cholesky_cplx(MatrixXcd(s,s)) ); } @@ -304,4 +320,6 @@ void test_cholesky() // Test problem size constructors CALL_SUBTEST_9( LLT(10) ); CALL_SUBTEST_9( LDLT(10) ); + + EIGEN_UNUSED_VARIABLE(s) } diff --git a/gtsam/3rdparty/Eigen/test/cholmod_support.cpp b/gtsam/3rdparty/Eigen/test/cholmod_support.cpp new file mode 100644 index 000000000..1ebba2438 --- /dev/null +++ b/gtsam/3rdparty/Eigen/test/cholmod_support.cpp @@ -0,0 +1,71 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2011 Gael Guennebaud +// +// Eigen is free software; you can redistribute it and/or +// modify it under the terms of the GNU Lesser General Public +// License as published by the Free Software Foundation; either +// version 3 of the License, or (at your option) any later version. +// +// Alternatively, you can redistribute it and/or +// modify it under the terms of the GNU General Public License as +// published by the Free Software Foundation; either version 2 of +// the License, or (at your option) any later version. +// +// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY +// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the +// GNU General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public +// License and a copy of the GNU General Public License along with +// Eigen. If not, see . + +#include "sparse_solver.h" + +#include + +template void test_cholmod_T() +{ + CholmodDecomposition, Lower> g_chol_colmajor_lower; g_chol_colmajor_lower.setMode(CholmodSupernodalLLt); + CholmodDecomposition, Upper> g_chol_colmajor_upper; g_chol_colmajor_upper.setMode(CholmodSupernodalLLt); + CholmodDecomposition, Lower> g_llt_colmajor_lower; g_llt_colmajor_lower.setMode(CholmodSimplicialLLt); + CholmodDecomposition, Upper> g_llt_colmajor_upper; g_llt_colmajor_upper.setMode(CholmodSimplicialLLt); + CholmodDecomposition, Lower> g_ldlt_colmajor_lower; g_ldlt_colmajor_lower.setMode(CholmodLDLt); + CholmodDecomposition, Upper> g_ldlt_colmajor_upper; g_ldlt_colmajor_upper.setMode(CholmodLDLt); + + CholmodSupernodalLLT, Lower> chol_colmajor_lower; + CholmodSupernodalLLT, Upper> chol_colmajor_upper; + CholmodSimplicialLLT, Lower> llt_colmajor_lower; + CholmodSimplicialLLT, Upper> llt_colmajor_upper; + CholmodSimplicialLDLT, Lower> ldlt_colmajor_lower; + CholmodSimplicialLDLT, Upper> ldlt_colmajor_upper; + + check_sparse_spd_solving(g_chol_colmajor_lower); + check_sparse_spd_solving(g_chol_colmajor_upper); + check_sparse_spd_solving(g_llt_colmajor_lower); + check_sparse_spd_solving(g_llt_colmajor_upper); + check_sparse_spd_solving(g_ldlt_colmajor_lower); + check_sparse_spd_solving(g_ldlt_colmajor_upper); + + check_sparse_spd_solving(chol_colmajor_lower); + check_sparse_spd_solving(chol_colmajor_upper); + check_sparse_spd_solving(llt_colmajor_lower); + check_sparse_spd_solving(llt_colmajor_upper); + check_sparse_spd_solving(ldlt_colmajor_lower); + check_sparse_spd_solving(ldlt_colmajor_upper); + +// check_sparse_spd_determinant(chol_colmajor_lower); +// check_sparse_spd_determinant(chol_colmajor_upper); +// check_sparse_spd_determinant(llt_colmajor_lower); +// check_sparse_spd_determinant(llt_colmajor_upper); +// check_sparse_spd_determinant(ldlt_colmajor_lower); +// check_sparse_spd_determinant(ldlt_colmajor_upper); +} + +void test_cholmod_support() +{ + CALL_SUBTEST_1(test_cholmod_T()); + CALL_SUBTEST_2(test_cholmod_T >()); +} diff --git a/gtsam/3rdparty/Eigen/test/conjugate_gradient.cpp b/gtsam/3rdparty/Eigen/test/conjugate_gradient.cpp new file mode 100644 index 000000000..f24f35817 --- /dev/null +++ b/gtsam/3rdparty/Eigen/test/conjugate_gradient.cpp @@ -0,0 +1,45 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2011 Gael Guennebaud +// +// Eigen is free software; you can redistribute it and/or +// modify it under the terms of the GNU Lesser General Public +// License as published by the Free Software Foundation; either +// version 3 of the License, or (at your option) any later version. +// +// Alternatively, you can redistribute it and/or +// modify it under the terms of the GNU General Public License as +// published by the Free Software Foundation; either version 2 of +// the License, or (at your option) any later version. +// +// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY +// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the +// GNU General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public +// License and a copy of the GNU General Public License along with +// Eigen. If not, see . + +#include "sparse_solver.h" +#include + +template void test_conjugate_gradient_T() +{ + ConjugateGradient, Lower> cg_colmajor_lower_diag; + ConjugateGradient, Upper> cg_colmajor_upper_diag; + ConjugateGradient, Lower, IdentityPreconditioner> cg_colmajor_lower_I; + ConjugateGradient, Upper, IdentityPreconditioner> cg_colmajor_upper_I; + + CALL_SUBTEST( check_sparse_spd_solving(cg_colmajor_lower_diag) ); + CALL_SUBTEST( check_sparse_spd_solving(cg_colmajor_upper_diag) ); + CALL_SUBTEST( check_sparse_spd_solving(cg_colmajor_lower_I) ); + CALL_SUBTEST( check_sparse_spd_solving(cg_colmajor_upper_I) ); +} + +void test_conjugate_gradient() +{ + CALL_SUBTEST_1(test_conjugate_gradient_T()); + CALL_SUBTEST_2(test_conjugate_gradient_T >()); +} diff --git a/gtsam/3rdparty/Eigen/test/cwiseop.cpp b/gtsam/3rdparty/Eigen/test/cwiseop.cpp index 07ef599be..b3ca94e3a 100644 --- a/gtsam/3rdparty/Eigen/test/cwiseop.cpp +++ b/gtsam/3rdparty/Eigen/test/cwiseop.cpp @@ -60,11 +60,8 @@ template void cwiseops(const MatrixType& m) mzero = MatrixType::Zero(rows, cols), mones = MatrixType::Ones(rows, cols), identity = Matrix - ::Identity(rows, rows), - square = Matrix::Random(rows, rows); - VectorType v1 = VectorType::Random(rows), - v2 = VectorType::Random(rows), - vzero = VectorType::Zero(rows), + ::Identity(rows, rows); + VectorType vzero = VectorType::Zero(rows), vones = VectorType::Ones(rows), v3(rows); @@ -175,9 +172,9 @@ void test_cwiseop() for(int i = 0; i < g_repeat ; i++) { CALL_SUBTEST_1( cwiseops(Matrix()) ); CALL_SUBTEST_2( cwiseops(Matrix4d()) ); - CALL_SUBTEST_3( cwiseops(MatrixXf(3, 3)) ); - CALL_SUBTEST_4( cwiseops(MatrixXf(22, 22)) ); - CALL_SUBTEST_5( cwiseops(MatrixXi(8, 12)) ); - CALL_SUBTEST_6( cwiseops(MatrixXd(20, 20)) ); + CALL_SUBTEST_3( cwiseops(MatrixXf(internal::random(1,EIGEN_TEST_MAX_SIZE), internal::random(1,EIGEN_TEST_MAX_SIZE))) ); + CALL_SUBTEST_4( cwiseops(MatrixXf(internal::random(1,EIGEN_TEST_MAX_SIZE), internal::random(1,EIGEN_TEST_MAX_SIZE))) ); + CALL_SUBTEST_5( cwiseops(MatrixXi(internal::random(1,EIGEN_TEST_MAX_SIZE), internal::random(1,EIGEN_TEST_MAX_SIZE))) ); + CALL_SUBTEST_6( cwiseops(MatrixXd(internal::random(1,EIGEN_TEST_MAX_SIZE), internal::random(1,EIGEN_TEST_MAX_SIZE))) ); } } diff --git a/gtsam/3rdparty/Eigen/test/determinant.cpp b/gtsam/3rdparty/Eigen/test/determinant.cpp index dcf64387d..6c8d3baab 100644 --- a/gtsam/3rdparty/Eigen/test/determinant.cpp +++ b/gtsam/3rdparty/Eigen/test/determinant.cpp @@ -68,13 +68,15 @@ template void determinant(const MatrixType& m) void test_determinant() { + int s; for(int i = 0; i < g_repeat; i++) { CALL_SUBTEST_1( determinant(Matrix()) ); CALL_SUBTEST_2( determinant(Matrix()) ); CALL_SUBTEST_3( determinant(Matrix()) ); CALL_SUBTEST_4( determinant(Matrix()) ); CALL_SUBTEST_5( determinant(Matrix, 10, 10>()) ); - CALL_SUBTEST_6( determinant(MatrixXd(20, 20)) ); + s = internal::random(1,EIGEN_TEST_MAX_SIZE/4); + CALL_SUBTEST_6( determinant(MatrixXd(s, s)) ); } - CALL_SUBTEST_6( determinant(MatrixXd(200, 200)) ); + EIGEN_UNUSED_VARIABLE(s) } diff --git a/gtsam/3rdparty/Eigen/test/diagonal.cpp b/gtsam/3rdparty/Eigen/test/diagonal.cpp index 50b341dfe..94a30e2f4 100644 --- a/gtsam/3rdparty/Eigen/test/diagonal.cpp +++ b/gtsam/3rdparty/Eigen/test/diagonal.cpp @@ -74,10 +74,10 @@ void test_diagonal() for(int i = 0; i < g_repeat; i++) { CALL_SUBTEST_1( diagonal(Matrix()) ); CALL_SUBTEST_2( diagonal(Matrix4d()) ); - CALL_SUBTEST_2( diagonal(MatrixXcf(3, 3)) ); - CALL_SUBTEST_2( diagonal(MatrixXi(8, 12)) ); - CALL_SUBTEST_2( diagonal(MatrixXcd(20, 20)) ); - CALL_SUBTEST_1( diagonal(MatrixXf(21, 19)) ); + CALL_SUBTEST_2( diagonal(MatrixXcf(internal::random(1,EIGEN_TEST_MAX_SIZE), internal::random(1,EIGEN_TEST_MAX_SIZE))) ); + CALL_SUBTEST_2( diagonal(MatrixXi(internal::random(1,EIGEN_TEST_MAX_SIZE), internal::random(1,EIGEN_TEST_MAX_SIZE))) ); + CALL_SUBTEST_2( diagonal(MatrixXcd(internal::random(1,EIGEN_TEST_MAX_SIZE), internal::random(1,EIGEN_TEST_MAX_SIZE))) ); + CALL_SUBTEST_1( diagonal(MatrixXf(internal::random(1,EIGEN_TEST_MAX_SIZE), internal::random(1,EIGEN_TEST_MAX_SIZE))) ); CALL_SUBTEST_1( diagonal(Matrix(3, 4)) ); } } diff --git a/gtsam/3rdparty/Eigen/test/diagonalmatrices.cpp b/gtsam/3rdparty/Eigen/test/diagonalmatrices.cpp index 9d6f069c6..d84f4e9f3 100644 --- a/gtsam/3rdparty/Eigen/test/diagonalmatrices.cpp +++ b/gtsam/3rdparty/Eigen/test/diagonalmatrices.cpp @@ -101,9 +101,9 @@ void test_diagonalmatrices() CALL_SUBTEST_3( diagonalmatrices(Matrix()) ); CALL_SUBTEST_4( diagonalmatrices(Matrix4d()) ); CALL_SUBTEST_5( diagonalmatrices(Matrix()) ); - CALL_SUBTEST_6( diagonalmatrices(MatrixXcf(3, 5)) ); - CALL_SUBTEST_7( diagonalmatrices(MatrixXi(10, 8)) ); - CALL_SUBTEST_8( diagonalmatrices(Matrix(20, 20)) ); - CALL_SUBTEST_9( diagonalmatrices(MatrixXf(21, 24)) ); + CALL_SUBTEST_6( diagonalmatrices(MatrixXcf(internal::random(1,EIGEN_TEST_MAX_SIZE), internal::random(1,EIGEN_TEST_MAX_SIZE))) ); + CALL_SUBTEST_7( diagonalmatrices(MatrixXi(internal::random(1,EIGEN_TEST_MAX_SIZE), internal::random(1,EIGEN_TEST_MAX_SIZE))) ); + CALL_SUBTEST_8( diagonalmatrices(Matrix(internal::random(1,EIGEN_TEST_MAX_SIZE), internal::random(1,EIGEN_TEST_MAX_SIZE))) ); + CALL_SUBTEST_9( diagonalmatrices(MatrixXf(internal::random(1,EIGEN_TEST_MAX_SIZE), internal::random(1,EIGEN_TEST_MAX_SIZE))) ); } } diff --git a/gtsam/3rdparty/Eigen/test/eigen2/main.h b/gtsam/3rdparty/Eigen/test/eigen2/main.h index b361a44d9..9d0defa39 100644 --- a/gtsam/3rdparty/Eigen/test/eigen2/main.h +++ b/gtsam/3rdparty/Eigen/test/eigen2/main.h @@ -29,10 +29,6 @@ #include #include -#ifdef NDEBUG -#undef NDEBUG -#endif - #ifndef EIGEN_TEST_FUNC #error EIGEN_TEST_FUNC must be defined #endif diff --git a/gtsam/3rdparty/Eigen/test/eigen2support.cpp b/gtsam/3rdparty/Eigen/test/eigen2support.cpp index a7269fed5..5d0202e34 100644 --- a/gtsam/3rdparty/Eigen/test/eigen2support.cpp +++ b/gtsam/3rdparty/Eigen/test/eigen2support.cpp @@ -35,7 +35,6 @@ template void eigen2support(const MatrixType& m) Index cols = m.cols(); MatrixType m1 = MatrixType::Random(rows, cols), - m2 = MatrixType::Random(rows, cols), m3(rows, cols); Scalar s1 = internal::random(), diff --git a/gtsam/3rdparty/Eigen/test/eigensolver_complex.cpp b/gtsam/3rdparty/Eigen/test/eigensolver_complex.cpp index 99e9ee864..1cd55a2cd 100644 --- a/gtsam/3rdparty/Eigen/test/eigensolver_complex.cpp +++ b/gtsam/3rdparty/Eigen/test/eigensolver_complex.cpp @@ -108,18 +108,23 @@ template void eigensolver_verify_assert(const MatrixType& m void test_eigensolver_complex() { + int s; for(int i = 0; i < g_repeat; i++) { CALL_SUBTEST_1( eigensolver(Matrix4cf()) ); - CALL_SUBTEST_2( eigensolver(MatrixXcd(14,14)) ); + s = internal::random(1,EIGEN_TEST_MAX_SIZE/4); + CALL_SUBTEST_2( eigensolver(MatrixXcd(s,s)) ); CALL_SUBTEST_3( eigensolver(Matrix, 1, 1>()) ); CALL_SUBTEST_4( eigensolver(Matrix3f()) ); } CALL_SUBTEST_1( eigensolver_verify_assert(Matrix4cf()) ); - CALL_SUBTEST_2( eigensolver_verify_assert(MatrixXcd(14,14)) ); + s = internal::random(1,EIGEN_TEST_MAX_SIZE/4); + CALL_SUBTEST_2( eigensolver_verify_assert(MatrixXcd(s,s)) ); CALL_SUBTEST_3( eigensolver_verify_assert(Matrix, 1, 1>()) ); CALL_SUBTEST_4( eigensolver_verify_assert(Matrix3f()) ); // Test problem size constructors - CALL_SUBTEST_5(ComplexEigenSolver(10)); + CALL_SUBTEST_5(ComplexEigenSolver(s)); + + EIGEN_UNUSED_VARIABLE(s) } diff --git a/gtsam/3rdparty/Eigen/test/eigensolver_generic.cpp b/gtsam/3rdparty/Eigen/test/eigensolver_generic.cpp index 8476f026d..2e9cdc7a5 100644 --- a/gtsam/3rdparty/Eigen/test/eigensolver_generic.cpp +++ b/gtsam/3rdparty/Eigen/test/eigensolver_generic.cpp @@ -27,10 +27,6 @@ #include #include -#ifdef HAS_GSL -#include "gsl_helper.h" -#endif - template void eigensolver(const MatrixType& m) { typedef typename MatrixType::Index Index; @@ -97,9 +93,11 @@ template void eigensolver_verify_assert(const MatrixType& m void test_eigensolver_generic() { + int s; for(int i = 0; i < g_repeat; i++) { CALL_SUBTEST_1( eigensolver(Matrix4f()) ); - CALL_SUBTEST_2( eigensolver(MatrixXd(17,17)) ); + s = internal::random(1,EIGEN_TEST_MAX_SIZE/4); + CALL_SUBTEST_2( eigensolver(MatrixXd(s,s)) ); // some trivial but implementation-wise tricky cases CALL_SUBTEST_2( eigensolver(MatrixXd(1,1)) ); @@ -109,10 +107,24 @@ void test_eigensolver_generic() } CALL_SUBTEST_1( eigensolver_verify_assert(Matrix4f()) ); - CALL_SUBTEST_2( eigensolver_verify_assert(MatrixXd(17,17)) ); + s = internal::random(1,EIGEN_TEST_MAX_SIZE/4); + CALL_SUBTEST_2( eigensolver_verify_assert(MatrixXd(s,s)) ); CALL_SUBTEST_3( eigensolver_verify_assert(Matrix()) ); CALL_SUBTEST_4( eigensolver_verify_assert(Matrix2d()) ); // Test problem size constructors - CALL_SUBTEST_5(EigenSolver(10)); + CALL_SUBTEST_5(EigenSolver(s)); + + // regression test for bug 410 + CALL_SUBTEST_2( + { + MatrixXd A(1,1); + A(0,0) = std::sqrt(-1.); + Eigen::EigenSolver solver(A); + MatrixXd V(1, 1); + V(0,0) = solver.eigenvectors()(0,0).real(); + } + ); + + EIGEN_UNUSED_VARIABLE(s) } diff --git a/gtsam/3rdparty/Eigen/test/eigensolver_selfadjoint.cpp b/gtsam/3rdparty/Eigen/test/eigensolver_selfadjoint.cpp index b85bcc289..26d3d1f70 100644 --- a/gtsam/3rdparty/Eigen/test/eigensolver_selfadjoint.cpp +++ b/gtsam/3rdparty/Eigen/test/eigensolver_selfadjoint.cpp @@ -27,10 +27,6 @@ #include #include -#ifdef HAS_GSL -#include "gsl_helper.h" -#endif - template void selfadjointeigensolver(const MatrixType& m) { typedef typename MatrixType::Index Index; @@ -59,64 +55,25 @@ template void selfadjointeigensolver(const MatrixType& m) symmB.template triangularView().setZero(); SelfAdjointEigenSolver eiSymm(symmA); + SelfAdjointEigenSolver eiDirect; + eiDirect.computeDirect(symmA); // generalized eigen pb GeneralizedSelfAdjointEigenSolver eiSymmGen(symmA, symmB); - #ifdef HAS_GSL - if (internal::is_same::value) - { - // restore symmA and symmB. - symmA = MatrixType(symmA.template selfadjointView()); - symmB = MatrixType(symmB.template selfadjointView()); - typedef GslTraits Gsl; - typename Gsl::Matrix gEvec=0, gSymmA=0, gSymmB=0; - typename GslTraits::Vector gEval=0; - RealVectorType _eval; - MatrixType _evec; - convert(symmA, gSymmA); - convert(symmB, gSymmB); - convert(symmA, gEvec); - gEval = GslTraits::createVector(rows); - - Gsl::eigen_symm(gSymmA, gEval, gEvec); - convert(gEval, _eval); - convert(gEvec, _evec); - - // test gsl itself ! - VERIFY((symmA * _evec).isApprox(_evec * _eval.asDiagonal(), largerEps)); - - // compare with eigen - VERIFY_IS_APPROX(_eval, eiSymm.eigenvalues()); - VERIFY_IS_APPROX(_evec.cwiseAbs(), eiSymm.eigenvectors().cwiseAbs()); - - // generalized pb - Gsl::eigen_symm_gen(gSymmA, gSymmB, gEval, gEvec); - convert(gEval, _eval); - convert(gEvec, _evec); - // test GSL itself: - VERIFY((symmA * _evec).isApprox(symmB * (_evec * _eval.asDiagonal()), largerEps)); - - // compare with eigen - MatrixType normalized_eivec = eiSymmGen.eigenvectors()*eiSymmGen.eigenvectors().colwise().norm().asDiagonal().inverse(); - VERIFY_IS_APPROX(_eval, eiSymmGen.eigenvalues()); - VERIFY_IS_APPROX(_evec.cwiseAbs(), normalized_eivec.cwiseAbs()); - - Gsl::free(gSymmA); - Gsl::free(gSymmB); - GslTraits::free(gEval); - Gsl::free(gEvec); - } - #endif - VERIFY_IS_EQUAL(eiSymm.info(), Success); VERIFY((symmA.template selfadjointView() * eiSymm.eigenvectors()).isApprox( eiSymm.eigenvectors() * eiSymm.eigenvalues().asDiagonal(), largerEps)); VERIFY_IS_APPROX(symmA.template selfadjointView().eigenvalues(), eiSymm.eigenvalues()); + + VERIFY_IS_EQUAL(eiDirect.info(), Success); + VERIFY((symmA.template selfadjointView() * eiDirect.eigenvectors()).isApprox( + eiDirect.eigenvectors() * eiDirect.eigenvalues().asDiagonal(), largerEps)); + VERIFY_IS_APPROX(symmA.template selfadjointView().eigenvalues(), eiDirect.eigenvalues()); SelfAdjointEigenSolver eiSymmNoEivecs(symmA, false); VERIFY_IS_EQUAL(eiSymmNoEivecs.info(), Success); VERIFY_IS_APPROX(eiSymm.eigenvalues(), eiSymmNoEivecs.eigenvalues()); - + // generalized eigen problem Ax = lBx eiSymmGen.compute(symmA, symmB,Ax_lBx); VERIFY_IS_EQUAL(eiSymmGen.info(), Success); @@ -171,15 +128,21 @@ template void selfadjointeigensolver(const MatrixType& m) void test_eigensolver_selfadjoint() { + int s; for(int i = 0; i < g_repeat; i++) { - // very important to test a 3x3 matrix since we provide a special path for it + // very important to test 3x3 and 2x2 matrices since we provide special paths for them + CALL_SUBTEST_1( selfadjointeigensolver(Matrix2d()) ); CALL_SUBTEST_1( selfadjointeigensolver(Matrix3f()) ); CALL_SUBTEST_2( selfadjointeigensolver(Matrix4d()) ); - CALL_SUBTEST_3( selfadjointeigensolver(MatrixXf(10,10)) ); - CALL_SUBTEST_4( selfadjointeigensolver(MatrixXd(19,19)) ); - CALL_SUBTEST_5( selfadjointeigensolver(MatrixXcd(17,17)) ); + s = internal::random(1,EIGEN_TEST_MAX_SIZE/4); + CALL_SUBTEST_3( selfadjointeigensolver(MatrixXf(s,s)) ); + s = internal::random(1,EIGEN_TEST_MAX_SIZE/4); + CALL_SUBTEST_4( selfadjointeigensolver(MatrixXd(s,s)) ); + s = internal::random(1,EIGEN_TEST_MAX_SIZE/4); + CALL_SUBTEST_5( selfadjointeigensolver(MatrixXcd(s,s)) ); - CALL_SUBTEST_9( selfadjointeigensolver(Matrix,Dynamic,Dynamic,RowMajor>(17,17)) ); + s = internal::random(1,EIGEN_TEST_MAX_SIZE/4); + CALL_SUBTEST_9( selfadjointeigensolver(Matrix,Dynamic,Dynamic,RowMajor>(s,s)) ); // some trivial but implementation-wise tricky cases CALL_SUBTEST_4( selfadjointeigensolver(MatrixXd(1,1)) ); @@ -189,7 +152,10 @@ void test_eigensolver_selfadjoint() } // Test problem size constructors - CALL_SUBTEST_8(SelfAdjointEigenSolver(10)); - CALL_SUBTEST_8(Tridiagonalization(10)); + s = internal::random(1,EIGEN_TEST_MAX_SIZE/4); + CALL_SUBTEST_8(SelfAdjointEigenSolver(s)); + CALL_SUBTEST_8(Tridiagonalization(s)); + + EIGEN_UNUSED_VARIABLE(s) } diff --git a/gtsam/3rdparty/Eigen/test/geo_alignedbox.cpp b/gtsam/3rdparty/Eigen/test/geo_alignedbox.cpp index 738ca3150..724133725 100644 --- a/gtsam/3rdparty/Eigen/test/geo_alignedbox.cpp +++ b/gtsam/3rdparty/Eigen/test/geo_alignedbox.cpp @@ -113,7 +113,7 @@ void specificTest1() Vector2f m; m << -1.0f, -2.0f; Vector2f M; M << 1.0f, 5.0f; - typedef AlignedBox BoxType; + typedef AlignedBox2f BoxType; BoxType box( m, M ); Vector2f sides = M-m; @@ -140,7 +140,7 @@ void specificTest2() Vector3i m; m << -1, -2, 0; Vector3i M; M << 1, 5, 3; - typedef AlignedBox BoxType; + typedef AlignedBox3i BoxType; BoxType box( m, M ); Vector3i sides = M-m; @@ -165,21 +165,21 @@ void test_geo_alignedbox() { for(int i = 0; i < g_repeat; i++) { - CALL_SUBTEST_1( alignedbox(AlignedBox()) ); - CALL_SUBTEST_2( alignedboxCastTests(AlignedBox()) ); + CALL_SUBTEST_1( alignedbox(AlignedBox2f()) ); + CALL_SUBTEST_2( alignedboxCastTests(AlignedBox2f()) ); - CALL_SUBTEST_3( alignedbox(AlignedBox()) ); - CALL_SUBTEST_4( alignedboxCastTests(AlignedBox()) ); + CALL_SUBTEST_3( alignedbox(AlignedBox3f()) ); + CALL_SUBTEST_4( alignedboxCastTests(AlignedBox3f()) ); - CALL_SUBTEST_5( alignedbox(AlignedBox()) ); - CALL_SUBTEST_6( alignedboxCastTests(AlignedBox()) ); + CALL_SUBTEST_5( alignedbox(AlignedBox4d()) ); + CALL_SUBTEST_6( alignedboxCastTests(AlignedBox4d()) ); - CALL_SUBTEST_7( alignedbox(AlignedBox()) ); - CALL_SUBTEST_8( alignedboxCastTests(AlignedBox()) ); + CALL_SUBTEST_7( alignedbox(AlignedBox1d()) ); + CALL_SUBTEST_8( alignedboxCastTests(AlignedBox1d()) ); - CALL_SUBTEST_9( alignedbox(AlignedBox()) ); - CALL_SUBTEST_10( alignedbox(AlignedBox()) ); - CALL_SUBTEST_11( alignedbox(AlignedBox()) ); + CALL_SUBTEST_9( alignedbox(AlignedBox1i()) ); + CALL_SUBTEST_10( alignedbox(AlignedBox2i()) ); + CALL_SUBTEST_11( alignedbox(AlignedBox3i()) ); } CALL_SUBTEST_12( specificTest1() ); CALL_SUBTEST_13( specificTest2() ); diff --git a/gtsam/3rdparty/Eigen/test/geo_eulerangles.cpp b/gtsam/3rdparty/Eigen/test/geo_eulerangles.cpp index f82cb8fbe..8029a694e 100644 --- a/gtsam/3rdparty/Eigen/test/geo_eulerangles.cpp +++ b/gtsam/3rdparty/Eigen/test/geo_eulerangles.cpp @@ -42,7 +42,6 @@ template void eulerangles(void) #define VERIFY_EULER(I,J,K, X,Y,Z) { \ Vector3 ea = m.eulerAngles(I,J,K); \ - Matrix3 m1 = Matrix3(AngleAxisx(ea[0], Vector3::Unit##X()) * AngleAxisx(ea[1], Vector3::Unit##Y()) * AngleAxisx(ea[2], Vector3::Unit##Z())); \ VERIFY_IS_APPROX(m, Matrix3(AngleAxisx(ea[0], Vector3::Unit##X()) * AngleAxisx(ea[1], Vector3::Unit##Y()) * AngleAxisx(ea[2], Vector3::Unit##Z()))); \ } VERIFY_EULER(0,1,2, X,Y,Z); diff --git a/gtsam/3rdparty/Eigen/test/geo_homogeneous.cpp b/gtsam/3rdparty/Eigen/test/geo_homogeneous.cpp index 26254b757..3efcb77db 100644 --- a/gtsam/3rdparty/Eigen/test/geo_homogeneous.cpp +++ b/gtsam/3rdparty/Eigen/test/geo_homogeneous.cpp @@ -42,17 +42,13 @@ template void homogeneous(void) typedef Matrix T3MatrixType; VectorType v0 = VectorType::Random(), - v1 = VectorType::Random(), ones = VectorType::Ones(); - HVectorType hv0 = HVectorType::Random(), - hv1 = HVectorType::Random(); + HVectorType hv0 = HVectorType::Random(); - MatrixType m0 = MatrixType::Random(), - m1 = MatrixType::Random(); + MatrixType m0 = MatrixType::Random(); - HMatrixType hm0 = HMatrixType::Random(), - hm1 = HMatrixType::Random(); + HMatrixType hm0 = HMatrixType::Random(); hv0 << v0, 1; VERIFY_IS_APPROX(v0.homogeneous(), hv0); diff --git a/gtsam/3rdparty/Eigen/test/geo_orthomethods.cpp b/gtsam/3rdparty/Eigen/test/geo_orthomethods.cpp index 020ae7103..aa3c8b61d 100644 --- a/gtsam/3rdparty/Eigen/test/geo_orthomethods.cpp +++ b/gtsam/3rdparty/Eigen/test/geo_orthomethods.cpp @@ -88,9 +88,7 @@ template void orthomethods(int size=Size) typedef Matrix MatrixN3; typedef Matrix Vector3; - VectorType v0 = VectorType::Random(size), - v1 = VectorType::Random(size), - v2 = VectorType::Random(size); + VectorType v0 = VectorType::Random(size); // unitOrthogonal VERIFY_IS_MUCH_SMALLER_THAN(v0.unitOrthogonal().dot(v0), Scalar(1)); diff --git a/gtsam/3rdparty/Eigen/test/geo_parametrizedline.cpp b/gtsam/3rdparty/Eigen/test/geo_parametrizedline.cpp index 13f98fdd6..a289e70de 100644 --- a/gtsam/3rdparty/Eigen/test/geo_parametrizedline.cpp +++ b/gtsam/3rdparty/Eigen/test/geo_parametrizedline.cpp @@ -40,6 +40,7 @@ template void parametrizedline(const LineType& _line) typedef Matrix VectorType; typedef Matrix MatrixType; + typedef Hyperplane HyperplaneType; VectorType p0 = VectorType::Random(dim); VectorType p1 = VectorType::Random(dim); @@ -64,6 +65,16 @@ template void parametrizedline(const LineType& _line) VERIFY_IS_APPROX(hp1f.template cast(),l0); ParametrizedLine hp1d = l0.template cast(); VERIFY_IS_APPROX(hp1d.template cast(),l0); + + // intersections + VectorType p2 = VectorType::Random(dim); + VectorType n2 = VectorType::Random(dim).normalized(); + HyperplaneType hp(p2,n2); + Scalar t = l0.intersectionParameter(hp); + VectorType pi = l0.pointAt(t); + VERIFY_IS_MUCH_SMALLER_THAN(hp.signedDistance(pi), RealScalar(1)); + VERIFY_IS_MUCH_SMALLER_THAN(l0.distance(pi), RealScalar(1)); + VERIFY_IS_APPROX(l0.intersectionPoint(hp), pi); } template void parametrizedline_alignment() diff --git a/gtsam/3rdparty/Eigen/test/geo_quaternion.cpp b/gtsam/3rdparty/Eigen/test/geo_quaternion.cpp index 7adbe0b3d..b73ae9cd4 100644 --- a/gtsam/3rdparty/Eigen/test/geo_quaternion.cpp +++ b/gtsam/3rdparty/Eigen/test/geo_quaternion.cpp @@ -142,6 +142,17 @@ template void quaternion(void) VERIFY_IS_APPROX(-v3.normalized(),(q2.setFromTwoVectors(v1,-v3)*v1).normalized()); } + // from two vector creation static function + VERIFY_IS_APPROX( v2.normalized(),(Quaternionx::FromTwoVectors(v1, v2)*v1).normalized()); + VERIFY_IS_APPROX( v1.normalized(),(Quaternionx::FromTwoVectors(v1, v1)*v1).normalized()); + VERIFY_IS_APPROX(-v1.normalized(),(Quaternionx::FromTwoVectors(v1,-v1)*v1).normalized()); + if (internal::is_same::value) + { + v3 = (v1.array()+eps).matrix(); + VERIFY_IS_APPROX( v3.normalized(),(Quaternionx::FromTwoVectors(v1, v3)*v1).normalized()); + VERIFY_IS_APPROX(-v3.normalized(),(Quaternionx::FromTwoVectors(v1,-v3)*v1).normalized()); + } + // inverse and conjugate VERIFY_IS_APPROX(q1 * (q1.inverse() * v1), v1); VERIFY_IS_APPROX(q1 * (q1.conjugate() * v1), v1); diff --git a/gtsam/3rdparty/Eigen/test/geo_transformations.cpp b/gtsam/3rdparty/Eigen/test/geo_transformations.cpp index b606de2fb..e9f05cfb6 100644 --- a/gtsam/3rdparty/Eigen/test/geo_transformations.cpp +++ b/gtsam/3rdparty/Eigen/test/geo_transformations.cpp @@ -122,9 +122,7 @@ template void transformations() typedef Translation Translation3; Vector3 v0 = Vector3::Random(), - v1 = Vector3::Random(), - v2 = Vector3::Random(); - Vector2 u0 = Vector2::Random(); + v1 = Vector3::Random(); Matrix3 matrot1, m; Scalar a = internal::random(-Scalar(M_PI), Scalar(M_PI)); @@ -284,9 +282,9 @@ template void transformations() // mat * aligned scaling and mat * translation t1 = (Matrix3(q1) * AlignedScaling3(v0)) * Translation3(v0); VERIFY_IS_APPROX(t0.matrix(), t1.matrix()); - t1 = (Matrix3(q1) * Scaling(v0)) * Translation3(v0); + t1 = (Matrix3(q1) * Eigen::Scaling(v0)) * Translation3(v0); VERIFY_IS_APPROX(t0.matrix(), t1.matrix()); - t1 = (q1 * Scaling(v0)) * Translation3(v0); + t1 = (q1 * Eigen::Scaling(v0)) * Translation3(v0); VERIFY_IS_APPROX(t0.matrix(), t1.matrix()); // mat * transformation and aligned scaling * translation t1 = Matrix3(q1) * (AlignedScaling3(v0) * Translation3(v0)); @@ -295,18 +293,18 @@ template void transformations() t0.setIdentity(); t0.scale(s0).translate(v0); - t1 = Scaling(s0) * Translation3(v0); + t1 = Eigen::Scaling(s0) * Translation3(v0); VERIFY_IS_APPROX(t0.matrix(), t1.matrix()); t0.prescale(s0); - t1 = Scaling(s0) * t1; + t1 = Eigen::Scaling(s0) * t1; VERIFY_IS_APPROX(t0.matrix(), t1.matrix()); t0 = t3; t0.scale(s0); - t1 = t3 * Scaling(s0,s0,s0); + t1 = t3 * Eigen::Scaling(s0,s0,s0); VERIFY_IS_APPROX(t0.matrix(), t1.matrix()); t0.prescale(s0); - t1 = Scaling(s0,s0,s0) * t1; + t1 = Eigen::Scaling(s0,s0,s0) * t1; VERIFY_IS_APPROX(t0.matrix(), t1.matrix()); @@ -448,6 +446,29 @@ template void transform_alignment() #endif } +template void transform_products() +{ + typedef Matrix Mat; + typedef Transform Proj; + typedef Transform Aff; + typedef Transform AffC; + + Proj p; p.matrix().setRandom(); + Aff a; a.linear().setRandom(); a.translation().setRandom(); + AffC ac = a; + + Mat p_m(p.matrix()), a_m(a.matrix()); + + VERIFY_IS_APPROX((p*p).matrix(), p_m*p_m); + VERIFY_IS_APPROX((a*a).matrix(), a_m*a_m); + VERIFY_IS_APPROX((p*a).matrix(), p_m*a_m); + VERIFY_IS_APPROX((a*p).matrix(), a_m*p_m); + VERIFY_IS_APPROX((ac*a).matrix(), a_m*a_m); + VERIFY_IS_APPROX((a*ac).matrix(), a_m*a_m); + VERIFY_IS_APPROX((p*ac).matrix(), p_m*a_m); + VERIFY_IS_APPROX((ac*p).matrix(), a_m*p_m); +} + void test_geo_transformations() { for(int i = 0; i < g_repeat; i++) { @@ -470,5 +491,9 @@ void test_geo_transformations() CALL_SUBTEST_6(( transformations() )); CALL_SUBTEST_6(( transformations() )); + + + CALL_SUBTEST_7(( transform_products() )); + CALL_SUBTEST_7(( transform_products() )); } } diff --git a/gtsam/3rdparty/Eigen/test/gsl_helper.h b/gtsam/3rdparty/Eigen/test/gsl_helper.h deleted file mode 100644 index d6172d2ff..000000000 --- a/gtsam/3rdparty/Eigen/test/gsl_helper.h +++ /dev/null @@ -1,212 +0,0 @@ -// This file is part of Eigen, a lightweight C++ template library -// for linear algebra. -// -// Copyright (C) 2008 Gael Guennebaud -// -// Eigen is free software; you can redistribute it and/or -// modify it under the terms of the GNU Lesser General Public -// License as published by the Free Software Foundation; either -// version 3 of the License, or (at your option) any later version. -// -// Alternatively, you can redistribute it and/or -// modify it under the terms of the GNU General Public License as -// published by the Free Software Foundation; either version 2 of -// the License, or (at your option) any later version. -// -// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY -// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS -// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the -// GNU General Public License for more details. -// -// You should have received a copy of the GNU Lesser General Public -// License and a copy of the GNU General Public License along with -// Eigen. If not, see . - -#ifndef EIGEN_GSL_HELPER -#define EIGEN_GSL_HELPER - -#include - -#include -#include -#include -#include -#include -#include -#include - -namespace Eigen { - -template::IsComplex> struct GslTraits -{ - typedef gsl_matrix* Matrix; - typedef gsl_vector* Vector; - static Matrix createMatrix(int rows, int cols) { return gsl_matrix_alloc(rows,cols); } - static Vector createVector(int size) { return gsl_vector_alloc(size); } - static void free(Matrix& m) { gsl_matrix_free(m); m=0; } - static void free(Vector& m) { gsl_vector_free(m); m=0; } - static void prod(const Matrix& m, const Vector& v, Vector& x) { gsl_blas_dgemv(CblasNoTrans,1,m,v,0,x); } - static void cholesky(Matrix& m) { gsl_linalg_cholesky_decomp(m); } - static void cholesky_solve(const Matrix& m, const Vector& b, Vector& x) { gsl_linalg_cholesky_solve(m,b,x); } - static void eigen_symm(const Matrix& m, Vector& eval, Matrix& evec) - { - gsl_eigen_symmv_workspace * w = gsl_eigen_symmv_alloc(m->size1); - Matrix a = createMatrix(m->size1, m->size2); - gsl_matrix_memcpy(a, m); - gsl_eigen_symmv(a,eval,evec,w); - gsl_eigen_symmv_sort(eval, evec, GSL_EIGEN_SORT_VAL_ASC); - gsl_eigen_symmv_free(w); - free(a); - } - static void eigen_symm_gen(const Matrix& m, const Matrix& _b, Vector& eval, Matrix& evec) - { - gsl_eigen_gensymmv_workspace * w = gsl_eigen_gensymmv_alloc(m->size1); - Matrix a = createMatrix(m->size1, m->size2); - Matrix b = createMatrix(_b->size1, _b->size2); - gsl_matrix_memcpy(a, m); - gsl_matrix_memcpy(b, _b); - gsl_eigen_gensymmv(a,b,eval,evec,w); - gsl_eigen_symmv_sort(eval, evec, GSL_EIGEN_SORT_VAL_ASC); - gsl_eigen_gensymmv_free(w); - free(a); - } - - template - static void eigen_poly_solve(const EIGEN_VECTOR& poly, EIGEN_ROOTS& roots ) - { - const int deg = poly.size()-1; - double *z = new double[2*deg]; - double *a = new double[poly.size()]; - for( int i=0; i struct GslTraits -{ - typedef gsl_matrix_complex* Matrix; - typedef gsl_vector_complex* Vector; - static Matrix createMatrix(int rows, int cols) { return gsl_matrix_complex_alloc(rows,cols); } - static Vector createVector(int size) { return gsl_vector_complex_alloc(size); } - static void free(Matrix& m) { gsl_matrix_complex_free(m); m=0; } - static void free(Vector& m) { gsl_vector_complex_free(m); m=0; } - static void cholesky(Matrix& m) { gsl_linalg_complex_cholesky_decomp(m); } - static void cholesky_solve(const Matrix& m, const Vector& b, Vector& x) { gsl_linalg_complex_cholesky_solve(m,b,x); } - static void prod(const Matrix& m, const Vector& v, Vector& x) - { gsl_blas_zgemv(CblasNoTrans,gsl_complex_rect(1,0),m,v,gsl_complex_rect(0,0),x); } - static void eigen_symm(const Matrix& m, gsl_vector* &eval, Matrix& evec) - { - gsl_eigen_hermv_workspace * w = gsl_eigen_hermv_alloc(m->size1); - Matrix a = createMatrix(m->size1, m->size2); - gsl_matrix_complex_memcpy(a, m); - gsl_eigen_hermv(a,eval,evec,w); - gsl_eigen_hermv_sort(eval, evec, GSL_EIGEN_SORT_VAL_ASC); - gsl_eigen_hermv_free(w); - free(a); - } - static void eigen_symm_gen(const Matrix& m, const Matrix& _b, gsl_vector* &eval, Matrix& evec) - { - gsl_eigen_genhermv_workspace * w = gsl_eigen_genhermv_alloc(m->size1); - Matrix a = createMatrix(m->size1, m->size2); - Matrix b = createMatrix(_b->size1, _b->size2); - gsl_matrix_complex_memcpy(a, m); - gsl_matrix_complex_memcpy(b, _b); - gsl_eigen_genhermv(a,b,eval,evec,w); - gsl_eigen_hermv_sort(eval, evec, GSL_EIGEN_SORT_VAL_ASC); - gsl_eigen_genhermv_free(w); - free(a); - } -}; - -template -void convert(const MatrixType& m, gsl_matrix* &res) -{ -// if (res) -// gsl_matrix_free(res); - res = gsl_matrix_alloc(m.rows(), m.cols()); - for (int i=0 ; i -void convert(const gsl_matrix* m, MatrixType& res) -{ - res.resize(int(m->size1), int(m->size2)); - for (int i=0 ; i -void convert(const VectorType& m, gsl_vector* &res) -{ - if (res) gsl_vector_free(res); - res = gsl_vector_alloc(m.size()); - for (int i=0 ; i -void convert(const gsl_vector* m, VectorType& res) -{ - res.resize (m->size); - for (int i=0 ; i -void convert(const MatrixType& m, gsl_matrix_complex* &res) -{ - res = gsl_matrix_complex_alloc(m.rows(), m.cols()); - for (int i=0 ; i -void convert(const gsl_matrix_complex* m, MatrixType& res) -{ - res.resize(int(m->size1), int(m->size2)); - for (int i=0 ; i -void convert(const VectorType& m, gsl_vector_complex* &res) -{ - res = gsl_vector_complex_alloc(m.size()); - for (int i=0 ; i -void convert(const gsl_vector_complex* m, VectorType& res) -{ - res.resize(m->size); - for (int i=0 ; i,1>() )); CALL_SUBTEST_2(( hessenberg,2>() )); CALL_SUBTEST_3(( hessenberg,4>() )); - CALL_SUBTEST_4(( hessenberg(internal::random(1,320)) )); - CALL_SUBTEST_5(( hessenberg,Dynamic>(internal::random(1,320)) )); + CALL_SUBTEST_4(( hessenberg(internal::random(1,EIGEN_TEST_MAX_SIZE)) )); + CALL_SUBTEST_5(( hessenberg,Dynamic>(internal::random(1,EIGEN_TEST_MAX_SIZE)) )); // Test problem size constructors CALL_SUBTEST_6(HessenbergDecomposition(10)); diff --git a/gtsam/3rdparty/Eigen/test/householder.cpp b/gtsam/3rdparty/Eigen/test/householder.cpp index e77fa7ad0..6f6f317ea 100644 --- a/gtsam/3rdparty/Eigen/test/householder.cpp +++ b/gtsam/3rdparty/Eigen/test/householder.cpp @@ -130,9 +130,9 @@ void test_householder() CALL_SUBTEST_2( householder(Matrix()) ); CALL_SUBTEST_3( householder(Matrix()) ); CALL_SUBTEST_4( householder(Matrix()) ); - CALL_SUBTEST_5( householder(MatrixXd(10,12)) ); - CALL_SUBTEST_6( householder(MatrixXcf(16,17)) ); - CALL_SUBTEST_7( householder(MatrixXf(25,7)) ); + CALL_SUBTEST_5( householder(MatrixXd(internal::random(1,EIGEN_TEST_MAX_SIZE),internal::random(1,EIGEN_TEST_MAX_SIZE))) ); + CALL_SUBTEST_6( householder(MatrixXcf(internal::random(1,EIGEN_TEST_MAX_SIZE),internal::random(1,EIGEN_TEST_MAX_SIZE))) ); + CALL_SUBTEST_7( householder(MatrixXf(internal::random(1,EIGEN_TEST_MAX_SIZE),internal::random(1,EIGEN_TEST_MAX_SIZE))) ); CALL_SUBTEST_8( householder(Matrix()) ); } } diff --git a/gtsam/3rdparty/Eigen/test/inverse.cpp b/gtsam/3rdparty/Eigen/test/inverse.cpp index f0c69e78c..81702432f 100644 --- a/gtsam/3rdparty/Eigen/test/inverse.cpp +++ b/gtsam/3rdparty/Eigen/test/inverse.cpp @@ -41,7 +41,6 @@ template void inverse(const MatrixType& m) MatrixType m1(rows, cols), m2(rows, cols), - mzero = MatrixType::Zero(rows, cols), identity = MatrixType::Identity(rows, rows); createRandomPIMatrixOfRank(rows,rows,rows,m1); m2 = m1.inverse(); @@ -114,4 +113,5 @@ void test_inverse() CALL_SUBTEST_7( inverse(Matrix4d()) ); CALL_SUBTEST_7( inverse(Matrix()) ); } + EIGEN_UNUSED_VARIABLE(s) } diff --git a/gtsam/3rdparty/Eigen/test/jacobi.cpp b/gtsam/3rdparty/Eigen/test/jacobi.cpp index 6464c63c5..4d462226c 100644 --- a/gtsam/3rdparty/Eigen/test/jacobi.cpp +++ b/gtsam/3rdparty/Eigen/test/jacobi.cpp @@ -82,8 +82,8 @@ void test_jacobi() CALL_SUBTEST_3(( jacobi() )); CALL_SUBTEST_3(( jacobi >() )); - int r = internal::random(2, 20), - c = internal::random(2, 20); + int r = internal::random(2, internal::random(1,EIGEN_TEST_MAX_SIZE)/2), + c = internal::random(2, internal::random(1,EIGEN_TEST_MAX_SIZE)/2); CALL_SUBTEST_4(( jacobi(MatrixXf(r,c)) )); CALL_SUBTEST_5(( jacobi(MatrixXcd(r,c)) )); CALL_SUBTEST_5(( jacobi >(MatrixXcd(r,c)) )); diff --git a/gtsam/3rdparty/Eigen/test/jacobisvd.cpp b/gtsam/3rdparty/Eigen/test/jacobisvd.cpp index 45873832a..3012fbe75 100644 --- a/gtsam/3rdparty/Eigen/test/jacobisvd.cpp +++ b/gtsam/3rdparty/Eigen/test/jacobisvd.cpp @@ -131,6 +131,12 @@ void jacobisvd_test_all_computation_options(const MatrixType& m) jacobisvd_solve(m, ComputeFullU | ComputeThinV); jacobisvd_solve(m, ComputeThinU | ComputeFullV); jacobisvd_solve(m, ComputeThinU | ComputeThinV); + + // test reconstruction + typedef typename MatrixType::Index Index; + Index diagSize = (std::min)(m.rows(), m.cols()); + JacobiSVD svd(m, ComputeThinU | ComputeThinV); + VERIFY_IS_APPROX(m, svd.matrixU().leftCols(diagSize) * svd.singularValues().asDiagonal() * svd.matrixV().leftCols(diagSize).adjoint()); } } @@ -248,9 +254,17 @@ void jacobisvd_inf_nan() // matrices containing denormal numbers. void jacobisvd_bug286() { +#if defined __INTEL_COMPILER +// shut up warning #239: floating point underflow +#pragma warning push +#pragma warning disable 239 +#endif Matrix2d M; M << -7.90884e-313, -4.94e-324, 0, 5.60844e-313; +#if defined __INTEL_COMPILER +#pragma warning pop +#endif JacobiSVD svd; svd.compute(M); // just check we don't loop indefinitely } @@ -333,8 +347,8 @@ void test_jacobisvd() CALL_SUBTEST_7( jacobisvd_inf_nan() ); } - CALL_SUBTEST_7(( jacobisvd(MatrixXf(internal::random(100, 150), internal::random(100, 150))) )); - CALL_SUBTEST_8(( jacobisvd(MatrixXcd(internal::random(80, 100), internal::random(80, 100))) )); + CALL_SUBTEST_7(( jacobisvd(MatrixXf(internal::random(EIGEN_TEST_MAX_SIZE/4, EIGEN_TEST_MAX_SIZE/2), internal::random(EIGEN_TEST_MAX_SIZE/4, EIGEN_TEST_MAX_SIZE/2))) )); + CALL_SUBTEST_8(( jacobisvd(MatrixXcd(internal::random(EIGEN_TEST_MAX_SIZE/4, EIGEN_TEST_MAX_SIZE/3), internal::random(EIGEN_TEST_MAX_SIZE/4, EIGEN_TEST_MAX_SIZE/3))) )); // test matrixbase method CALL_SUBTEST_1(( jacobisvd_method() )); diff --git a/gtsam/3rdparty/Eigen/test/linearstructure.cpp b/gtsam/3rdparty/Eigen/test/linearstructure.cpp index 312102701..bbfdaacc1 100644 --- a/gtsam/3rdparty/Eigen/test/linearstructure.cpp +++ b/gtsam/3rdparty/Eigen/test/linearstructure.cpp @@ -39,8 +39,7 @@ template void linearStructure(const MatrixType& m) // to test it, hence I consider that we will have tested Random.h MatrixType m1 = MatrixType::Random(rows, cols), m2 = MatrixType::Random(rows, cols), - m3(rows, cols), - mzero = MatrixType::Zero(rows, cols); + m3(rows, cols); Scalar s1 = internal::random(); while (internal::abs(s1)<1e-3) s1 = internal::random(); @@ -90,10 +89,10 @@ void test_linearstructure() CALL_SUBTEST_2( linearStructure(Matrix2f()) ); CALL_SUBTEST_3( linearStructure(Vector3d()) ); CALL_SUBTEST_4( linearStructure(Matrix4d()) ); - CALL_SUBTEST_5( linearStructure(MatrixXcf(3, 3)) ); - CALL_SUBTEST_6( linearStructure(MatrixXf(8, 12)) ); - CALL_SUBTEST_7( linearStructure(MatrixXi(8, 12)) ); - CALL_SUBTEST_8( linearStructure(MatrixXcd(20, 20)) ); - CALL_SUBTEST_9( linearStructure(ArrayXXf(12, 8)) ); + CALL_SUBTEST_5( linearStructure(MatrixXcf(internal::random(1,EIGEN_TEST_MAX_SIZE/2), internal::random(1,EIGEN_TEST_MAX_SIZE/2))) ); + CALL_SUBTEST_6( linearStructure(MatrixXf (internal::random(1,EIGEN_TEST_MAX_SIZE), internal::random(1,EIGEN_TEST_MAX_SIZE))) ); + CALL_SUBTEST_7( linearStructure(MatrixXi (internal::random(1,EIGEN_TEST_MAX_SIZE), internal::random(1,EIGEN_TEST_MAX_SIZE))) ); + CALL_SUBTEST_8( linearStructure(MatrixXcd(internal::random(1,EIGEN_TEST_MAX_SIZE/2), internal::random(1,EIGEN_TEST_MAX_SIZE/2))) ); + CALL_SUBTEST_9( linearStructure(ArrayXXf (internal::random(1,EIGEN_TEST_MAX_SIZE), internal::random(1,EIGEN_TEST_MAX_SIZE))) ); } } diff --git a/gtsam/3rdparty/Eigen/test/lu.cpp b/gtsam/3rdparty/Eigen/test/lu.cpp index 552364d29..253f68542 100644 --- a/gtsam/3rdparty/Eigen/test/lu.cpp +++ b/gtsam/3rdparty/Eigen/test/lu.cpp @@ -37,7 +37,7 @@ template void lu_non_invertible() Index rows, cols, cols2; if(MatrixType::RowsAtCompileTime==Dynamic) { - rows = internal::random(2,200); + rows = internal::random(2,EIGEN_TEST_MAX_SIZE); } else { @@ -45,8 +45,8 @@ template void lu_non_invertible() } if(MatrixType::ColsAtCompileTime==Dynamic) { - cols = internal::random(2,200); - cols2 = internal::random(2,200); + cols = internal::random(2,EIGEN_TEST_MAX_SIZE); + cols2 = internal::random(2,EIGEN_TEST_MAX_SIZE); } else { @@ -117,7 +117,7 @@ template void lu_invertible() */ typedef typename MatrixType::Scalar Scalar; typedef typename NumTraits::Real RealScalar; - int size = internal::random(1,200); + int size = internal::random(1,EIGEN_TEST_MAX_SIZE); MatrixType m1(size, size), m2(size, size), m3(size, size); FullPivLU lu; diff --git a/gtsam/3rdparty/Eigen/test/main.h b/gtsam/3rdparty/Eigen/test/main.h index 4510c1905..991194e30 100644 --- a/gtsam/3rdparty/Eigen/test/main.h +++ b/gtsam/3rdparty/Eigen/test/main.h @@ -27,6 +27,7 @@ #include #include #include +#include #include #include #include @@ -40,6 +41,13 @@ #define min(A,B) please_protect_your_min_with_parentheses #define max(A,B) please_protect_your_max_with_parentheses +#define FORBIDDEN_IDENTIFIER (this_identifier_is_forbidden_to_avoid_clashes) this_identifier_is_forbidden_to_avoid_clashes +// B0 is defined in POSIX header termios.h +#define B0 FORBIDDEN_IDENTIFIER + +// the following file is automatically generated by cmake +#include "split_test_helper.h" + #ifdef NDEBUG #undef NDEBUG #endif @@ -186,7 +194,7 @@ static void verify_impl(bool condition, const char *testname, const char *file, } } -#define VERIFY(a) verify_impl(a, g_test_stack.back().c_str(), __FILE__, __LINE__, EI_PP_MAKE_STRING(a)) +#define VERIFY(a) ::verify_impl(a, g_test_stack.back().c_str(), __FILE__, __LINE__, EI_PP_MAKE_STRING(a)) #define VERIFY_IS_EQUAL(a, b) VERIFY(test_is_equal(a, b)) #define VERIFY_IS_APPROX(a, b) VERIFY(test_isApprox(a, b)) @@ -204,101 +212,6 @@ static void verify_impl(bool condition, const char *testname, const char *file, g_test_stack.pop_back(); \ } while (0) -#ifdef EIGEN_TEST_PART_1 -#define CALL_SUBTEST_1(FUNC) CALL_SUBTEST(FUNC) -#else -#define CALL_SUBTEST_1(FUNC) -#endif - -#ifdef EIGEN_TEST_PART_2 -#define CALL_SUBTEST_2(FUNC) CALL_SUBTEST(FUNC) -#else -#define CALL_SUBTEST_2(FUNC) -#endif - -#ifdef EIGEN_TEST_PART_3 -#define CALL_SUBTEST_3(FUNC) CALL_SUBTEST(FUNC) -#else -#define CALL_SUBTEST_3(FUNC) -#endif - -#ifdef EIGEN_TEST_PART_4 -#define CALL_SUBTEST_4(FUNC) CALL_SUBTEST(FUNC) -#else -#define CALL_SUBTEST_4(FUNC) -#endif - -#ifdef EIGEN_TEST_PART_5 -#define CALL_SUBTEST_5(FUNC) CALL_SUBTEST(FUNC) -#else -#define CALL_SUBTEST_5(FUNC) -#endif - -#ifdef EIGEN_TEST_PART_6 -#define CALL_SUBTEST_6(FUNC) CALL_SUBTEST(FUNC) -#else -#define CALL_SUBTEST_6(FUNC) -#endif - -#ifdef EIGEN_TEST_PART_7 -#define CALL_SUBTEST_7(FUNC) CALL_SUBTEST(FUNC) -#else -#define CALL_SUBTEST_7(FUNC) -#endif - -#ifdef EIGEN_TEST_PART_8 -#define CALL_SUBTEST_8(FUNC) CALL_SUBTEST(FUNC) -#else -#define CALL_SUBTEST_8(FUNC) -#endif - -#ifdef EIGEN_TEST_PART_9 -#define CALL_SUBTEST_9(FUNC) CALL_SUBTEST(FUNC) -#else -#define CALL_SUBTEST_9(FUNC) -#endif - -#ifdef EIGEN_TEST_PART_10 -#define CALL_SUBTEST_10(FUNC) CALL_SUBTEST(FUNC) -#else -#define CALL_SUBTEST_10(FUNC) -#endif - -#ifdef EIGEN_TEST_PART_11 -#define CALL_SUBTEST_11(FUNC) CALL_SUBTEST(FUNC) -#else -#define CALL_SUBTEST_11(FUNC) -#endif - -#ifdef EIGEN_TEST_PART_12 -#define CALL_SUBTEST_12(FUNC) CALL_SUBTEST(FUNC) -#else -#define CALL_SUBTEST_12(FUNC) -#endif - -#ifdef EIGEN_TEST_PART_13 -#define CALL_SUBTEST_13(FUNC) CALL_SUBTEST(FUNC) -#else -#define CALL_SUBTEST_13(FUNC) -#endif - -#ifdef EIGEN_TEST_PART_14 -#define CALL_SUBTEST_14(FUNC) CALL_SUBTEST(FUNC) -#else -#define CALL_SUBTEST_14(FUNC) -#endif - -#ifdef EIGEN_TEST_PART_15 -#define CALL_SUBTEST_15(FUNC) CALL_SUBTEST(FUNC) -#else -#define CALL_SUBTEST_15(FUNC) -#endif - -#ifdef EIGEN_TEST_PART_16 -#define CALL_SUBTEST_16(FUNC) CALL_SUBTEST(FUNC) -#else -#define CALL_SUBTEST_16(FUNC) -#endif namespace Eigen { @@ -447,6 +360,23 @@ void createRandomPIMatrixOfRank(typename MatrixType::Index desired_rank, typenam m = qra.householderQ() * d * qrb.householderQ(); } +template +void randomPermutationVector(PermutationVectorType& v, typename PermutationVectorType::Index size) +{ + typedef typename PermutationVectorType::Index Index; + typedef typename PermutationVectorType::Scalar Scalar; + v.resize(size); + for(Index i = 0; i < size; ++i) v(i) = Scalar(i); + if(size == 1) return; + for(Index n = 0; n < 3 * size; ++n) + { + Index i = internal::random(0, size-1); + Index j; + do j = internal::random(0, size-1); while(j==i); + std::swap(v(i), v(j)); + } +} + } // end namespace Eigen template struct GetDifferentType; diff --git a/gtsam/3rdparty/Eigen/test/mixingtypes.cpp b/gtsam/3rdparty/Eigen/test/mixingtypes.cpp index 8afb733cd..6819f934e 100644 --- a/gtsam/3rdparty/Eigen/test/mixingtypes.cpp +++ b/gtsam/3rdparty/Eigen/test/mixingtypes.cpp @@ -143,5 +143,5 @@ void test_mixingtypes() { CALL_SUBTEST_1(mixingtypes<3>()); CALL_SUBTEST_2(mixingtypes<4>()); - CALL_SUBTEST_3(mixingtypes(internal::random(1,310))); + CALL_SUBTEST_3(mixingtypes(internal::random(1,EIGEN_TEST_MAX_SIZE))); } diff --git a/gtsam/3rdparty/Eigen/test/nomalloc.cpp b/gtsam/3rdparty/Eigen/test/nomalloc.cpp index 96ff16dae..1feeff4bc 100644 --- a/gtsam/3rdparty/Eigen/test/nomalloc.cpp +++ b/gtsam/3rdparty/Eigen/test/nomalloc.cpp @@ -52,15 +52,7 @@ template void nomalloc(const MatrixType& m) MatrixType m1 = MatrixType::Random(rows, cols), m2 = MatrixType::Random(rows, cols), - m3(rows, cols), - mzero = MatrixType::Zero(rows, cols), - identity = Matrix - ::Identity(rows, rows), - square = Matrix - ::Random(rows, rows); - VectorType v1 = VectorType::Random(rows), - v2 = VectorType::Random(rows), - vzero = VectorType::Zero(rows); + m3(rows, cols); Scalar s1 = internal::random(); @@ -137,13 +129,20 @@ void ctms_decompositions() 0, maxSize, maxSize> ComplexMatrix; - const Matrix A(Matrix::Random(size, size)); + const Matrix A(Matrix::Random(size, size)), B(Matrix::Random(size, size)); + Matrix X(size,size); const ComplexMatrix complexA(ComplexMatrix::Random(size, size)); const Matrix saA = A.adjoint() * A; + const Vector b(Vector::Random(size)); + Vector x(size); // Cholesky module Eigen::LLT LLT; LLT.compute(A); + X = LLT.solve(B); + x = LLT.solve(b); Eigen::LDLT LDLT; LDLT.compute(A); + X = LDLT.solve(B); + x = LDLT.solve(b); // Eigenvalues module Eigen::HessenbergDecomposition hessDecomp; hessDecomp.compute(complexA); @@ -155,12 +154,22 @@ void ctms_decompositions() // LU module Eigen::PartialPivLU ppLU; ppLU.compute(A); + X = ppLU.solve(B); + x = ppLU.solve(b); Eigen::FullPivLU fpLU; fpLU.compute(A); + X = fpLU.solve(B); + x = fpLU.solve(b); // QR module Eigen::HouseholderQR hQR; hQR.compute(A); + X = hQR.solve(B); + x = hQR.solve(b); Eigen::ColPivHouseholderQR cpQR; cpQR.compute(A); + // FIXME X = cpQR.solve(B); + x = cpQR.solve(b); Eigen::FullPivHouseholderQR fpQR; fpQR.compute(A); + // FIXME X = fpQR.solve(B); + x = fpQR.solve(b); // SVD module Eigen::JacobiSVD jSVD; jSVD.compute(A, ComputeFullU | ComputeFullV); diff --git a/gtsam/3rdparty/Eigen/test/nullary.cpp b/gtsam/3rdparty/Eigen/test/nullary.cpp index 0df15c081..6c9ee5f34 100644 --- a/gtsam/3rdparty/Eigen/test/nullary.cpp +++ b/gtsam/3rdparty/Eigen/test/nullary.cpp @@ -52,11 +52,14 @@ void testVectorType(const VectorType& base) { typedef typename internal::traits::Index Index; typedef typename internal::traits::Scalar Scalar; - Scalar low = internal::random(-500,500); - Scalar high = internal::random(-500,500); - if (low>high) std::swap(low,high); + const Index size = base.size(); - const Scalar step = (high-low)/(size-1); + + Scalar high = internal::random(-500,500); + Scalar low = (size == 1 ? high : internal::random(-500,500)); + if (low>high) std::swap(low,high); + + const Scalar step = ((size == 1) ? 1 : (high-low)/(size-1)); // check whether the result yields what we expect it to do VectorType m(base); @@ -76,8 +79,8 @@ void testVectorType(const VectorType& base) VERIFY( (MatrixXd(RowVectorXd::LinSpaced(3, 0, 1)) - RowVector3d(0, 0.5, 1)).norm() < std::numeric_limits::epsilon() ); // These guys sometimes fail! This is not good. Any ideas how to fix them!? -// VERIFY( m(m.size()-1) == high ); -// VERIFY( m(0) == low ); + //VERIFY( m(m.size()-1) == high ); + //VERIFY( m(0) == low ); // sequential access version m = VectorType::LinSpaced(Sequential,size,low,high); @@ -97,6 +100,12 @@ void testVectorType(const VectorType& base) Matrix size_changer(size+50); size_changer.setLinSpaced(size,low,high); VERIFY( size_changer.size() == size ); + + typedef Matrix ScalarMatrix; + ScalarMatrix scalar; + scalar.setLinSpaced(1,low,high); + VERIFY_IS_APPROX( scalar, ScalarMatrix::Constant(high) ); + VERIFY_IS_APPROX( ScalarMatrix::LinSpaced(1,low,high), ScalarMatrix::Constant(high) ); } template @@ -124,5 +133,6 @@ void test_nullary() CALL_SUBTEST_6( testVectorType(Vector3d()) ); CALL_SUBTEST_7( testVectorType(VectorXf(internal::random(1,300))) ); CALL_SUBTEST_8( testVectorType(Vector3f()) ); + CALL_SUBTEST_8( testVectorType(Matrix()) ); } } diff --git a/gtsam/3rdparty/Eigen/test/pardiso_support.cpp b/gtsam/3rdparty/Eigen/test/pardiso_support.cpp new file mode 100644 index 000000000..67efad6d8 --- /dev/null +++ b/gtsam/3rdparty/Eigen/test/pardiso_support.cpp @@ -0,0 +1,29 @@ +/* + Intel Copyright (C) .... +*/ + +#include "sparse_solver.h" +#include + +template void test_pardiso_T() +{ + PardisoLLT < SparseMatrix, Lower> pardiso_llt_lower; + PardisoLLT < SparseMatrix, Upper> pardiso_llt_upper; + PardisoLDLT < SparseMatrix, Lower> pardiso_ldlt_lower; + PardisoLDLT < SparseMatrix, Upper> pardiso_ldlt_upper; + PardisoLU < SparseMatrix > pardiso_lu; + + check_sparse_spd_solving(pardiso_llt_lower); + check_sparse_spd_solving(pardiso_llt_upper); + check_sparse_spd_solving(pardiso_ldlt_lower); + check_sparse_spd_solving(pardiso_ldlt_upper); + check_sparse_square_solving(pardiso_lu); +} + +void test_pardiso_support() +{ + CALL_SUBTEST_1(test_pardiso_T()); + CALL_SUBTEST_2(test_pardiso_T()); + CALL_SUBTEST_3(test_pardiso_T< std::complex >()); + CALL_SUBTEST_4(test_pardiso_T< std::complex >()); +} diff --git a/gtsam/3rdparty/Eigen/test/pastix_support.cpp b/gtsam/3rdparty/Eigen/test/pastix_support.cpp new file mode 100644 index 000000000..dbce30d1c --- /dev/null +++ b/gtsam/3rdparty/Eigen/test/pastix_support.cpp @@ -0,0 +1,59 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2008-2012 Gael Guennebaud +// Copyright (C) 2012 Désiré Nuentsa-Wakam +// +// Eigen is free software; you can redistribute it and/or +// modify it under the terms of the GNU Lesser General Public +// License as published by the Free Software Foundation; either +// version 3 of the License, or (at your option) any later version. +// +// Alternatively, you can redistribute it and/or +// modify it under the terms of the GNU General Public License as +// published by the Free Software Foundation; either version 2 of +// the License, or (at your option) any later version. +// +// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY +// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the +// GNU General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public +// License and a copy of the GNU General Public License along with +// Eigen. If not, see . +#include "sparse_solver.h" +#include +#include + + +template void test_pastix_T() +{ + PastixLLT< SparseMatrix, Eigen::Lower > pastix_llt_lower; + PastixLDLT< SparseMatrix, Eigen::Lower > pastix_ldlt_lower; + PastixLLT< SparseMatrix, Eigen::Upper > pastix_llt_upper; + PastixLDLT< SparseMatrix, Eigen::Upper > pastix_ldlt_upper; + PastixLU< SparseMatrix > pastix_lu; + + check_sparse_spd_solving(pastix_llt_lower); + check_sparse_spd_solving(pastix_ldlt_lower); + check_sparse_spd_solving(pastix_llt_upper); + check_sparse_spd_solving(pastix_ldlt_upper); + check_sparse_square_solving(pastix_lu); +} + +// There is no support for selfadjoint matrices with PaStiX. +// Complex symmetric matrices should pass though +template void test_pastix_T_LU() +{ + PastixLU< SparseMatrix > pastix_lu; + check_sparse_square_solving(pastix_lu); +} + +void test_pastix_support() +{ + CALL_SUBTEST_1(test_pastix_T()); + CALL_SUBTEST_2(test_pastix_T()); + CALL_SUBTEST_3( (test_pastix_T_LU >()) ); + CALL_SUBTEST_4(test_pastix_T_LU >()); +} \ No newline at end of file diff --git a/gtsam/3rdparty/Eigen/test/permutationmatrices.cpp b/gtsam/3rdparty/Eigen/test/permutationmatrices.cpp index d0fa01310..308838c70 100644 --- a/gtsam/3rdparty/Eigen/test/permutationmatrices.cpp +++ b/gtsam/3rdparty/Eigen/test/permutationmatrices.cpp @@ -24,23 +24,6 @@ #include "main.h" -template -void randomPermutationVector(PermutationVectorType& v, typename PermutationVectorType::Index size) -{ - typedef typename PermutationVectorType::Index Index; - typedef typename PermutationVectorType::Scalar Scalar; - v.resize(size); - for(Index i = 0; i < size; ++i) v(i) = Scalar(i); - if(size == 1) return; - for(Index n = 0; n < 3 * size; ++n) - { - Index i = internal::random(0, size-1); - Index j; - do j = internal::random(0, size-1); while(j==i); - std::swap(v(i), v(j)); - } -} - using namespace std; template void permutationmatrices(const MatrixType& m) { diff --git a/gtsam/3rdparty/Eigen/test/product.h b/gtsam/3rdparty/Eigen/test/product.h index 40ae4d51b..e77f8c41e 100644 --- a/gtsam/3rdparty/Eigen/test/product.h +++ b/gtsam/3rdparty/Eigen/test/product.h @@ -54,8 +54,7 @@ template void product(const MatrixType& m) // to test it, hence I consider that we will have tested Random.h MatrixType m1 = MatrixType::Random(rows, cols), m2 = MatrixType::Random(rows, cols), - m3(rows, cols), - mzero = MatrixType::Zero(rows, cols); + m3(rows, cols); RowSquareMatrixType identity = RowSquareMatrixType::Identity(rows, rows), square = RowSquareMatrixType::Random(rows, rows), @@ -63,9 +62,7 @@ template void product(const MatrixType& m) ColSquareMatrixType square2 = ColSquareMatrixType::Random(cols, cols), res2 = ColSquareMatrixType::Random(cols, cols); - RowVectorType v1 = RowVectorType::Random(rows), - v2 = RowVectorType::Random(rows), - vzero = RowVectorType::Zero(rows); + RowVectorType v1 = RowVectorType::Random(rows); ColVectorType vc2 = ColVectorType::Random(cols), vcres(cols); OtherMajorMatrixType tm1 = m1; diff --git a/gtsam/3rdparty/Eigen/test/product_extra.cpp b/gtsam/3rdparty/Eigen/test/product_extra.cpp index 15dc5ab96..ca302b469 100644 --- a/gtsam/3rdparty/Eigen/test/product_extra.cpp +++ b/gtsam/3rdparty/Eigen/test/product_extra.cpp @@ -153,11 +153,11 @@ void zero_sized_objects() void test_product_extra() { for(int i = 0; i < g_repeat; i++) { - CALL_SUBTEST_1( product_extra(MatrixXf(internal::random(1,320), internal::random(1,320))) ); - CALL_SUBTEST_2( product_extra(MatrixXd(internal::random(1,320), internal::random(1,320))) ); + CALL_SUBTEST_1( product_extra(MatrixXf(internal::random(1,EIGEN_TEST_MAX_SIZE), internal::random(1,EIGEN_TEST_MAX_SIZE))) ); + CALL_SUBTEST_2( product_extra(MatrixXd(internal::random(1,EIGEN_TEST_MAX_SIZE), internal::random(1,EIGEN_TEST_MAX_SIZE))) ); CALL_SUBTEST_2( mat_mat_scalar_scalar_product() ); - CALL_SUBTEST_3( product_extra(MatrixXcf(internal::random(1,150), internal::random(1,150))) ); - CALL_SUBTEST_4( product_extra(MatrixXcd(internal::random(1,150), internal::random(1,150))) ); + CALL_SUBTEST_3( product_extra(MatrixXcf(internal::random(1,EIGEN_TEST_MAX_SIZE/2), internal::random(1,EIGEN_TEST_MAX_SIZE/2))) ); + CALL_SUBTEST_4( product_extra(MatrixXcd(internal::random(1,EIGEN_TEST_MAX_SIZE/2), internal::random(1,EIGEN_TEST_MAX_SIZE/2))) ); CALL_SUBTEST_5( zero_sized_objects() ); } } diff --git a/gtsam/3rdparty/Eigen/test/product_large.cpp b/gtsam/3rdparty/Eigen/test/product_large.cpp index 8ed937068..6f7a91b84 100644 --- a/gtsam/3rdparty/Eigen/test/product_large.cpp +++ b/gtsam/3rdparty/Eigen/test/product_large.cpp @@ -27,11 +27,11 @@ void test_product_large() { for(int i = 0; i < g_repeat; i++) { - CALL_SUBTEST_1( product(MatrixXf(internal::random(1,320), internal::random(1,320))) ); - CALL_SUBTEST_2( product(MatrixXd(internal::random(1,320), internal::random(1,320))) ); - CALL_SUBTEST_3( product(MatrixXi(internal::random(1,320), internal::random(1,320))) ); - CALL_SUBTEST_4( product(MatrixXcf(internal::random(1,150), internal::random(1,150))) ); - CALL_SUBTEST_5( product(Matrix(internal::random(1,320), internal::random(1,320))) ); + CALL_SUBTEST_1( product(MatrixXf(internal::random(1,EIGEN_TEST_MAX_SIZE), internal::random(1,EIGEN_TEST_MAX_SIZE))) ); + CALL_SUBTEST_2( product(MatrixXd(internal::random(1,EIGEN_TEST_MAX_SIZE), internal::random(1,EIGEN_TEST_MAX_SIZE))) ); + CALL_SUBTEST_3( product(MatrixXi(internal::random(1,EIGEN_TEST_MAX_SIZE), internal::random(1,EIGEN_TEST_MAX_SIZE))) ); + CALL_SUBTEST_4( product(MatrixXcf(internal::random(1,EIGEN_TEST_MAX_SIZE/2), internal::random(1,EIGEN_TEST_MAX_SIZE/2))) ); + CALL_SUBTEST_5( product(Matrix(internal::random(1,EIGEN_TEST_MAX_SIZE), internal::random(1,EIGEN_TEST_MAX_SIZE))) ); } #if defined EIGEN_TEST_PART_6 diff --git a/gtsam/3rdparty/Eigen/test/product_mmtr.cpp b/gtsam/3rdparty/Eigen/test/product_mmtr.cpp index 1048a894d..c6ceb487f 100644 --- a/gtsam/3rdparty/Eigen/test/product_mmtr.cpp +++ b/gtsam/3rdparty/Eigen/test/product_mmtr.cpp @@ -72,9 +72,9 @@ void test_product_mmtr() { for(int i = 0; i < g_repeat ; i++) { - CALL_SUBTEST_1((mmtr(internal::random(1,320)))); - CALL_SUBTEST_2((mmtr(internal::random(1,320)))); - CALL_SUBTEST_3((mmtr >(internal::random(1,200)))); - CALL_SUBTEST_4((mmtr >(internal::random(1,200)))); + CALL_SUBTEST_1((mmtr(internal::random(1,EIGEN_TEST_MAX_SIZE)))); + CALL_SUBTEST_2((mmtr(internal::random(1,EIGEN_TEST_MAX_SIZE)))); + CALL_SUBTEST_3((mmtr >(internal::random(1,EIGEN_TEST_MAX_SIZE/2)))); + CALL_SUBTEST_4((mmtr >(internal::random(1,EIGEN_TEST_MAX_SIZE/2)))); } } diff --git a/gtsam/3rdparty/Eigen/test/product_notemporary.cpp b/gtsam/3rdparty/Eigen/test/product_notemporary.cpp index 980e2bbaf..1a9dc14d9 100644 --- a/gtsam/3rdparty/Eigen/test/product_notemporary.cpp +++ b/gtsam/3rdparty/Eigen/test/product_notemporary.cpp @@ -141,13 +141,13 @@ void test_product_notemporary() { int s; for(int i = 0; i < g_repeat; i++) { - s = internal::random(16,320); + s = internal::random(16,EIGEN_TEST_MAX_SIZE); CALL_SUBTEST_1( product_notemporary(MatrixXf(s, s)) ); - s = internal::random(16,320); + s = internal::random(16,EIGEN_TEST_MAX_SIZE); CALL_SUBTEST_2( product_notemporary(MatrixXd(s, s)) ); - s = internal::random(16,120); + s = internal::random(16,EIGEN_TEST_MAX_SIZE/2); CALL_SUBTEST_3( product_notemporary(MatrixXcf(s,s)) ); - s = internal::random(16,120); + s = internal::random(16,EIGEN_TEST_MAX_SIZE/2); CALL_SUBTEST_4( product_notemporary(MatrixXcd(s,s)) ); } } diff --git a/gtsam/3rdparty/Eigen/test/product_selfadjoint.cpp b/gtsam/3rdparty/Eigen/test/product_selfadjoint.cpp index ca84969eb..6c1d83bf2 100644 --- a/gtsam/3rdparty/Eigen/test/product_selfadjoint.cpp +++ b/gtsam/3rdparty/Eigen/test/product_selfadjoint.cpp @@ -83,13 +83,14 @@ void test_product_selfadjoint() CALL_SUBTEST_1( product_selfadjoint(Matrix()) ); CALL_SUBTEST_2( product_selfadjoint(Matrix()) ); CALL_SUBTEST_3( product_selfadjoint(Matrix3d()) ); - s = internal::random(1,150); + s = internal::random(1,EIGEN_TEST_MAX_SIZE/2); CALL_SUBTEST_4( product_selfadjoint(MatrixXcf(s, s)) ); - s = internal::random(1,150); + s = internal::random(1,EIGEN_TEST_MAX_SIZE/2); CALL_SUBTEST_5( product_selfadjoint(MatrixXcd(s,s)) ); - s = internal::random(1,320); + s = internal::random(1,EIGEN_TEST_MAX_SIZE); CALL_SUBTEST_6( product_selfadjoint(MatrixXd(s,s)) ); - s = internal::random(1,320); + s = internal::random(1,EIGEN_TEST_MAX_SIZE); CALL_SUBTEST_7( product_selfadjoint(Matrix(s,s)) ); } + EIGEN_UNUSED_VARIABLE(s) } diff --git a/gtsam/3rdparty/Eigen/test/product_small.cpp b/gtsam/3rdparty/Eigen/test/product_small.cpp index d7f1c09ff..cf430a2d3 100644 --- a/gtsam/3rdparty/Eigen/test/product_small.cpp +++ b/gtsam/3rdparty/Eigen/test/product_small.cpp @@ -25,6 +25,25 @@ #define EIGEN_NO_STATIC_ASSERT #include "product.h" +// regression test for bug 447 +void product1x1() +{ + Matrix matAstatic; + Matrix matBstatic; + matAstatic.setRandom(); + matBstatic.setRandom(); + VERIFY_IS_APPROX( (matAstatic * matBstatic).coeff(0,0), + matAstatic.cwiseProduct(matBstatic.transpose()).sum() ); + + MatrixXf matAdynamic(1,3); + MatrixXf matBdynamic(3,1); + matAdynamic.setRandom(); + matBdynamic.setRandom(); + VERIFY_IS_APPROX( (matAdynamic * matBdynamic).coeff(0,0), + matAdynamic.cwiseProduct(matBdynamic.transpose()).sum() ); +} + + void test_product_small() { for(int i = 0; i < g_repeat; i++) { @@ -33,6 +52,7 @@ void test_product_small() CALL_SUBTEST_3( product(Matrix3d()) ); CALL_SUBTEST_4( product(Matrix4d()) ); CALL_SUBTEST_5( product(Matrix4f()) ); + CALL_SUBTEST_6( product1x1() ); } #ifdef EIGEN_TEST_PART_6 diff --git a/gtsam/3rdparty/Eigen/test/product_symm.cpp b/gtsam/3rdparty/Eigen/test/product_symm.cpp index 21c2f605b..4585c3b6a 100644 --- a/gtsam/3rdparty/Eigen/test/product_symm.cpp +++ b/gtsam/3rdparty/Eigen/test/product_symm.cpp @@ -98,14 +98,14 @@ void test_product_symm() { for(int i = 0; i < g_repeat ; i++) { - CALL_SUBTEST_1(( symm(internal::random(1,320),internal::random(1,320)) )); - CALL_SUBTEST_2(( symm(internal::random(1,320),internal::random(1,320)) )); - CALL_SUBTEST_3(( symm,Dynamic,Dynamic>(internal::random(1,200),internal::random(1,200)) )); - CALL_SUBTEST_4(( symm,Dynamic,Dynamic>(internal::random(1,200),internal::random(1,200)) )); + CALL_SUBTEST_1(( symm(internal::random(1,EIGEN_TEST_MAX_SIZE),internal::random(1,EIGEN_TEST_MAX_SIZE)) )); + CALL_SUBTEST_2(( symm(internal::random(1,EIGEN_TEST_MAX_SIZE),internal::random(1,EIGEN_TEST_MAX_SIZE)) )); + CALL_SUBTEST_3(( symm,Dynamic,Dynamic>(internal::random(1,EIGEN_TEST_MAX_SIZE/2),internal::random(1,EIGEN_TEST_MAX_SIZE/2)) )); + CALL_SUBTEST_4(( symm,Dynamic,Dynamic>(internal::random(1,EIGEN_TEST_MAX_SIZE/2),internal::random(1,EIGEN_TEST_MAX_SIZE/2)) )); - CALL_SUBTEST_5(( symm(internal::random(1,320)) )); - CALL_SUBTEST_6(( symm(internal::random(1,320)) )); - CALL_SUBTEST_7(( symm,Dynamic,1>(internal::random(1,320)) )); - CALL_SUBTEST_8(( symm,Dynamic,1>(internal::random(1,320)) )); + CALL_SUBTEST_5(( symm(internal::random(1,EIGEN_TEST_MAX_SIZE)) )); + CALL_SUBTEST_6(( symm(internal::random(1,EIGEN_TEST_MAX_SIZE)) )); + CALL_SUBTEST_7(( symm,Dynamic,1>(internal::random(1,EIGEN_TEST_MAX_SIZE)) )); + CALL_SUBTEST_8(( symm,Dynamic,1>(internal::random(1,EIGEN_TEST_MAX_SIZE)) )); } } diff --git a/gtsam/3rdparty/Eigen/test/product_syrk.cpp b/gtsam/3rdparty/Eigen/test/product_syrk.cpp index 553410b9b..71285acb1 100644 --- a/gtsam/3rdparty/Eigen/test/product_syrk.cpp +++ b/gtsam/3rdparty/Eigen/test/product_syrk.cpp @@ -101,13 +101,13 @@ void test_product_syrk() for(int i = 0; i < g_repeat ; i++) { int s; - s = internal::random(1,320); + s = internal::random(1,EIGEN_TEST_MAX_SIZE); CALL_SUBTEST_1( syrk(MatrixXf(s, s)) ); - s = internal::random(1,320); + s = internal::random(1,EIGEN_TEST_MAX_SIZE); CALL_SUBTEST_2( syrk(MatrixXd(s, s)) ); - s = internal::random(1,200); + s = internal::random(1,EIGEN_TEST_MAX_SIZE/2); CALL_SUBTEST_3( syrk(MatrixXcf(s, s)) ); - s = internal::random(1,200); + s = internal::random(1,EIGEN_TEST_MAX_SIZE/2); CALL_SUBTEST_4( syrk(MatrixXcd(s, s)) ); } } diff --git a/gtsam/3rdparty/Eigen/test/product_trmm.cpp b/gtsam/3rdparty/Eigen/test/product_trmm.cpp index e117f6931..dab05d8b0 100644 --- a/gtsam/3rdparty/Eigen/test/product_trmm.cpp +++ b/gtsam/3rdparty/Eigen/test/product_trmm.cpp @@ -24,70 +24,100 @@ #include "main.h" -template void trmm(int size,int /*othersize*/) +template +void trmm(int rows=internal::random(1,EIGEN_TEST_MAX_SIZE), + int cols=internal::random(1,EIGEN_TEST_MAX_SIZE), + int otherCols = OtherCols==Dynamic?internal::random(1,EIGEN_TEST_MAX_SIZE):OtherCols) { typedef typename NumTraits::Real RealScalar; - typedef Matrix MatrixColMaj; - typedef Matrix MatrixRowMaj; + typedef Matrix TriMatrix; + typedef Matrix OnTheRight; + typedef Matrix OnTheLeft; + + typedef Matrix ResXS; + typedef Matrix ResSX; - DenseIndex rows = size; - DenseIndex cols = internal::random(1,size); - - MatrixColMaj triV(rows,cols), triH(cols,rows), upTri(cols,rows), loTri(rows,cols), - unitUpTri(cols,rows), unitLoTri(rows,cols), strictlyUpTri(cols,rows), strictlyLoTri(rows,cols); - MatrixColMaj ge1(rows,cols), ge2(cols,rows), ge3; - MatrixRowMaj rge3; + TriMatrix mat(rows,cols), tri(rows,cols), triTr(cols,rows); + + OnTheRight ge_right(cols,otherCols); + OnTheLeft ge_left(otherCols,rows); + ResSX ge_sx, ge_sx_save; + ResXS ge_xs, ge_xs_save; Scalar s1 = internal::random(), s2 = internal::random(); - triV.setRandom(); - triH.setRandom(); - loTri = triV.template triangularView(); - upTri = triH.template triangularView(); - unitLoTri = triV.template triangularView(); - unitUpTri = triH.template triangularView(); - strictlyLoTri = triV.template triangularView(); - strictlyUpTri = triH.template triangularView(); - ge1.setRandom(); - ge2.setRandom(); + mat.setRandom(); + tri = mat.template triangularView(); + triTr = mat.transpose().template triangularView(); + ge_right.setRandom(); + ge_left.setRandom(); - VERIFY_IS_APPROX( ge3 = triV.template triangularView() * ge2, loTri * ge2); - VERIFY_IS_APPROX( ge3 = ge2 * triV.template triangularView(), ge2 * loTri); - VERIFY_IS_APPROX( ge3 = triH.template triangularView() * ge1, upTri * ge1); - VERIFY_IS_APPROX( ge3 = ge1 * triH.template triangularView(), ge1 * upTri); - VERIFY_IS_APPROX( ge3 = (s1*triV.adjoint()).template triangularView() * (s2*ge1), s1*loTri.adjoint() * (s2*ge1)); - VERIFY_IS_APPROX( ge3 = ge1 * triV.adjoint().template triangularView(), ge1 * loTri.adjoint()); - VERIFY_IS_APPROX( ge3 = triH.adjoint().template triangularView() * ge2, upTri.adjoint() * ge2); - VERIFY_IS_APPROX( ge3 = ge2 * triH.adjoint().template triangularView(), ge2 * upTri.adjoint()); - VERIFY_IS_APPROX( ge3 = triV.template triangularView() * ge1.adjoint(), loTri * ge1.adjoint()); - VERIFY_IS_APPROX( ge3 = ge1.adjoint() * triV.template triangularView(), ge1.adjoint() * loTri); - VERIFY_IS_APPROX( ge3 = triH.template triangularView() * ge2.adjoint(), upTri * ge2.adjoint()); - VERIFY_IS_APPROX(rge3.noalias() = triH.template triangularView() * ge2.adjoint(), upTri * ge2.adjoint()); - VERIFY_IS_APPROX( ge3 = (s1*triV).adjoint().template triangularView() * ge2.adjoint(), internal::conj(s1) * loTri.adjoint() * ge2.adjoint()); - VERIFY_IS_APPROX(rge3.noalias() = triV.adjoint().template triangularView() * ge2.adjoint(), loTri.adjoint() * ge2.adjoint()); - VERIFY_IS_APPROX( ge3 = triH.adjoint().template triangularView() * ge1.adjoint(), upTri.adjoint() * ge1.adjoint()); - VERIFY_IS_APPROX(rge3.noalias() = triH.adjoint().template triangularView() * ge1.adjoint(), upTri.adjoint() * ge1.adjoint()); - - VERIFY_IS_APPROX( ge3 = triV.template triangularView() * ge2, unitLoTri * ge2); - VERIFY_IS_APPROX( rge3.noalias() = ge2 * triV.template triangularView(), ge2 * unitLoTri); - VERIFY_IS_APPROX( ge3 = ge2 * triV.template triangularView(), ge2 * unitLoTri); - VERIFY_IS_APPROX( ge3 = (s1*triV).adjoint().template triangularView() * ge2.adjoint(), internal::conj(s1) * unitLoTri.adjoint() * ge2.adjoint()); - - VERIFY_IS_APPROX( ge3 = triV.template triangularView() * ge2, strictlyLoTri * ge2); - VERIFY_IS_APPROX( rge3.noalias() = ge2 * triV.template triangularView(), ge2 * strictlyLoTri); - VERIFY_IS_APPROX( ge3 = ge2 * triV.template triangularView(), ge2 * strictlyLoTri); - VERIFY_IS_APPROX( ge3 = (s1*triV).adjoint().template triangularView() * ge2.adjoint(), internal::conj(s1) * strictlyLoTri.adjoint() * ge2.adjoint()); + VERIFY_IS_APPROX( ge_xs = mat.template triangularView() * ge_right, tri * ge_right); + VERIFY_IS_APPROX( ge_sx = ge_left * mat.template triangularView(), ge_left * tri); + + VERIFY_IS_APPROX( ge_xs.noalias() = mat.template triangularView() * ge_right, tri * ge_right); + VERIFY_IS_APPROX( ge_sx.noalias() = ge_left * mat.template triangularView(), ge_left * tri); + + VERIFY_IS_APPROX( ge_xs.noalias() = (s1*mat.adjoint()).template triangularView() * (s2*ge_left.transpose()), s1*triTr.conjugate() * (s2*ge_left.transpose())); + VERIFY_IS_APPROX( ge_sx.noalias() = ge_right.transpose() * mat.adjoint().template triangularView(), ge_right.transpose() * triTr.conjugate()); + + VERIFY_IS_APPROX( ge_xs.noalias() = (s1*mat.adjoint()).template triangularView() * (s2*ge_left.adjoint()), s1*triTr.conjugate() * (s2*ge_left.adjoint())); + VERIFY_IS_APPROX( ge_sx.noalias() = ge_right.adjoint() * mat.adjoint().template triangularView(), ge_right.adjoint() * triTr.conjugate()); + + ge_xs_save = ge_xs; + VERIFY_IS_APPROX( (ge_xs_save + s1*triTr.conjugate() * (s2*ge_left.adjoint())).eval(), ge_xs.noalias() += (s1*mat.adjoint()).template triangularView() * (s2*ge_left.adjoint()) ); + ge_sx_save = ge_sx; + VERIFY_IS_APPROX( ge_sx_save - (ge_right.adjoint() * (-s1 * triTr).conjugate()).eval(), ge_sx.noalias() -= (ge_right.adjoint() * (-s1 * mat).adjoint().template triangularView()).eval()); + + VERIFY_IS_APPROX( ge_xs = (s1*mat).adjoint().template triangularView() * ge_left.adjoint(), internal::conj(s1) * triTr.conjugate() * ge_left.adjoint()); + + // TODO check with sub-matrix expressions ? } +template +void trmv(int rows=internal::random(1,EIGEN_TEST_MAX_SIZE), int cols=internal::random(1,EIGEN_TEST_MAX_SIZE)) +{ + trmm(rows,cols,1); +} + +template +void trmm(int rows=internal::random(1,EIGEN_TEST_MAX_SIZE), int cols=internal::random(1,EIGEN_TEST_MAX_SIZE), int otherCols = internal::random(1,EIGEN_TEST_MAX_SIZE)) +{ + trmm(rows,cols,otherCols); +} + +#define CALL_ALL_ORDERS(NB,SCALAR,MODE) \ + EIGEN_CAT(CALL_SUBTEST_,NB)((trmm())); \ + EIGEN_CAT(CALL_SUBTEST_,NB)((trmm())); \ + EIGEN_CAT(CALL_SUBTEST_,NB)((trmm())); \ + EIGEN_CAT(CALL_SUBTEST_,NB)((trmm())); \ + EIGEN_CAT(CALL_SUBTEST_,NB)((trmm())); \ + EIGEN_CAT(CALL_SUBTEST_,NB)((trmm())); \ + EIGEN_CAT(CALL_SUBTEST_,NB)((trmm())); \ + EIGEN_CAT(CALL_SUBTEST_,NB)((trmm())); \ + \ + EIGEN_CAT(CALL_SUBTEST_1,NB)((trmv())); \ + EIGEN_CAT(CALL_SUBTEST_1,NB)((trmv())); + + +#define CALL_ALL(NB,SCALAR) \ + CALL_ALL_ORDERS(EIGEN_CAT(1,NB),SCALAR,Upper) \ + CALL_ALL_ORDERS(EIGEN_CAT(2,NB),SCALAR,UnitUpper) \ + CALL_ALL_ORDERS(EIGEN_CAT(3,NB),SCALAR,StrictlyUpper) \ + CALL_ALL_ORDERS(EIGEN_CAT(1,NB),SCALAR,Lower) \ + CALL_ALL_ORDERS(EIGEN_CAT(2,NB),SCALAR,UnitLower) \ + CALL_ALL_ORDERS(EIGEN_CAT(3,NB),SCALAR,StrictlyLower) + + void test_product_trmm() { for(int i = 0; i < g_repeat ; i++) { - CALL_SUBTEST_1((trmm(internal::random(1,320),internal::random(1,320)))); - CALL_SUBTEST_2((trmm(internal::random(1,320),internal::random(1,320)))); - CALL_SUBTEST_3((trmm >(internal::random(1,200),internal::random(1,200)))); - CALL_SUBTEST_4((trmm >(internal::random(1,200),internal::random(1,200)))); + CALL_ALL(1,float); // EIGEN_SUFFIXES;11;111;21;121;31;131 + CALL_ALL(2,double); // EIGEN_SUFFIXES;12;112;22;122;32;132 + CALL_ALL(3,std::complex); // EIGEN_SUFFIXES;13;113;23;123;33;133 + CALL_ALL(4,std::complex); // EIGEN_SUFFIXES;14;114;24;124;34;134 } } diff --git a/gtsam/3rdparty/Eigen/test/product_trmv.cpp b/gtsam/3rdparty/Eigen/test/product_trmv.cpp index cfb7355ff..52707d22b 100644 --- a/gtsam/3rdparty/Eigen/test/product_trmv.cpp +++ b/gtsam/3rdparty/Eigen/test/product_trmv.cpp @@ -93,11 +93,12 @@ void test_product_trmv() CALL_SUBTEST_1( trmv(Matrix()) ); CALL_SUBTEST_2( trmv(Matrix()) ); CALL_SUBTEST_3( trmv(Matrix3d()) ); - s = internal::random(1,200); + s = internal::random(1,EIGEN_TEST_MAX_SIZE/2); CALL_SUBTEST_4( trmv(MatrixXcf(s,s)) ); - s = internal::random(1,200); + s = internal::random(1,EIGEN_TEST_MAX_SIZE/2); CALL_SUBTEST_5( trmv(MatrixXcd(s,s)) ); - s = internal::random(1,320); + s = internal::random(1,EIGEN_TEST_MAX_SIZE); CALL_SUBTEST_6( trmv(Matrix(s, s)) ); } + EIGEN_UNUSED_VARIABLE(s); } diff --git a/gtsam/3rdparty/Eigen/test/product_trsolve.cpp b/gtsam/3rdparty/Eigen/test/product_trsolve.cpp index c207cc500..20380accd 100644 --- a/gtsam/3rdparty/Eigen/test/product_trsolve.cpp +++ b/gtsam/3rdparty/Eigen/test/product_trsolve.cpp @@ -93,14 +93,14 @@ void test_product_trsolve() for(int i = 0; i < g_repeat ; i++) { // matrices - CALL_SUBTEST_1((trsolve(internal::random(1,320),internal::random(1,320)))); - CALL_SUBTEST_2((trsolve(internal::random(1,320),internal::random(1,320)))); - CALL_SUBTEST_3((trsolve,Dynamic,Dynamic>(internal::random(1,200),internal::random(1,200)))); - CALL_SUBTEST_4((trsolve,Dynamic,Dynamic>(internal::random(1,200),internal::random(1,200)))); + CALL_SUBTEST_1((trsolve(internal::random(1,EIGEN_TEST_MAX_SIZE),internal::random(1,EIGEN_TEST_MAX_SIZE)))); + CALL_SUBTEST_2((trsolve(internal::random(1,EIGEN_TEST_MAX_SIZE),internal::random(1,EIGEN_TEST_MAX_SIZE)))); + CALL_SUBTEST_3((trsolve,Dynamic,Dynamic>(internal::random(1,EIGEN_TEST_MAX_SIZE/2),internal::random(1,EIGEN_TEST_MAX_SIZE/2)))); + CALL_SUBTEST_4((trsolve,Dynamic,Dynamic>(internal::random(1,EIGEN_TEST_MAX_SIZE/2),internal::random(1,EIGEN_TEST_MAX_SIZE/2)))); // vectors - CALL_SUBTEST_1((trsolve(internal::random(1,320)))); - CALL_SUBTEST_5((trsolve,Dynamic,1>(internal::random(1,320)))); + CALL_SUBTEST_1((trsolve(internal::random(1,EIGEN_TEST_MAX_SIZE)))); + CALL_SUBTEST_5((trsolve,Dynamic,1>(internal::random(1,EIGEN_TEST_MAX_SIZE)))); CALL_SUBTEST_6((trsolve())); CALL_SUBTEST_7((trsolve())); CALL_SUBTEST_8((trsolve,4,1>())); diff --git a/gtsam/3rdparty/Eigen/test/qr.cpp b/gtsam/3rdparty/Eigen/test/qr.cpp index 7e9ac9df9..6005c0e27 100644 --- a/gtsam/3rdparty/Eigen/test/qr.cpp +++ b/gtsam/3rdparty/Eigen/test/qr.cpp @@ -114,8 +114,8 @@ template void qr_verify_assert() void test_qr() { for(int i = 0; i < g_repeat; i++) { - CALL_SUBTEST_1( qr(MatrixXf(internal::random(1,200),internal::random(1,200))) ); - CALL_SUBTEST_2( qr(MatrixXcd(internal::random(1,200),internal::random(1,200))) ); + CALL_SUBTEST_1( qr(MatrixXf(internal::random(1,EIGEN_TEST_MAX_SIZE),internal::random(1,EIGEN_TEST_MAX_SIZE))) ); + CALL_SUBTEST_2( qr(MatrixXcd(internal::random(1,EIGEN_TEST_MAX_SIZE/2),internal::random(1,EIGEN_TEST_MAX_SIZE/2))) ); CALL_SUBTEST_3(( qr_fixedsize, 2 >() )); CALL_SUBTEST_4(( qr_fixedsize, 4 >() )); CALL_SUBTEST_5(( qr_fixedsize, 7 >() )); diff --git a/gtsam/3rdparty/Eigen/test/qr_colpivoting.cpp b/gtsam/3rdparty/Eigen/test/qr_colpivoting.cpp index 3cf651fa7..cdcf060ef 100644 --- a/gtsam/3rdparty/Eigen/test/qr_colpivoting.cpp +++ b/gtsam/3rdparty/Eigen/test/qr_colpivoting.cpp @@ -30,7 +30,7 @@ template void qr() { typedef typename MatrixType::Index Index; - Index rows = internal::random(2,200), cols = internal::random(2,200), cols2 = internal::random(2,200); + Index rows = internal::random(2,EIGEN_TEST_MAX_SIZE), cols = internal::random(2,EIGEN_TEST_MAX_SIZE), cols2 = internal::random(2,EIGEN_TEST_MAX_SIZE); Index rank = internal::random(1, (std::min)(rows, cols)-1); typedef typename MatrixType::Scalar Scalar; diff --git a/gtsam/3rdparty/Eigen/test/redux.cpp b/gtsam/3rdparty/Eigen/test/redux.cpp index a8bcf3b51..61d1bf911 100644 --- a/gtsam/3rdparty/Eigen/test/redux.cpp +++ b/gtsam/3rdparty/Eigen/test/redux.cpp @@ -35,6 +35,10 @@ template void matrixRedux(const MatrixType& m) MatrixType m1 = MatrixType::Random(rows, cols); + // The entries of m1 are uniformly distributed in [0,1], so m1.prod() is very small. This may lead to test + // failures if we underflow into denormals. Thus, we scale so that entires are close to 1. + MatrixType m1_for_prod = MatrixType::Ones(rows, cols) + Scalar(0.2) * m1; + VERIFY_IS_MUCH_SMALLER_THAN(MatrixType::Zero(rows, cols).sum(), Scalar(1)); VERIFY_IS_APPROX(MatrixType::Ones(rows, cols).sum(), Scalar(float(rows*cols))); // the float() here to shut up excessive MSVC warning about int->complex conversion being lossy Scalar s(0), p(1), minc(internal::real(m1.coeff(0))), maxc(internal::real(m1.coeff(0))); @@ -42,7 +46,7 @@ template void matrixRedux(const MatrixType& m) for(int i = 0; i < rows; i++) { s += m1(i,j); - p *= m1(i,j); + p *= m1_for_prod(i,j); minc = (std::min)(internal::real(minc), internal::real(m1(i,j))); maxc = (std::max)(internal::real(maxc), internal::real(m1(i,j))); } @@ -50,7 +54,7 @@ template void matrixRedux(const MatrixType& m) VERIFY_IS_APPROX(m1.sum(), s); VERIFY_IS_APPROX(m1.mean(), mean); - VERIFY_IS_APPROX(m1.prod(), p); + VERIFY_IS_APPROX(m1_for_prod.prod(), p); VERIFY_IS_APPROX(m1.real().minCoeff(), internal::real(minc)); VERIFY_IS_APPROX(m1.real().maxCoeff(), internal::real(maxc)); @@ -61,7 +65,7 @@ template void matrixRedux(const MatrixType& m) Index c1 = internal::random(c0+1,cols)-c0; VERIFY_IS_APPROX(m1.block(r0,c0,r1,c1).sum(), m1.block(r0,c0,r1,c1).eval().sum()); VERIFY_IS_APPROX(m1.block(r0,c0,r1,c1).mean(), m1.block(r0,c0,r1,c1).eval().mean()); - VERIFY_IS_APPROX(m1.block(r0,c0,r1,c1).prod(), m1.block(r0,c0,r1,c1).eval().prod()); + VERIFY_IS_APPROX(m1_for_prod.block(r0,c0,r1,c1).prod(), m1_for_prod.block(r0,c0,r1,c1).eval().prod()); VERIFY_IS_APPROX(m1.block(r0,c0,r1,c1).real().minCoeff(), m1.block(r0,c0,r1,c1).real().eval().minCoeff()); VERIFY_IS_APPROX(m1.block(r0,c0,r1,c1).real().maxCoeff(), m1.block(r0,c0,r1,c1).real().eval().maxCoeff()); @@ -78,6 +82,8 @@ template void vectorRedux(const VectorType& w) Index size = w.size(); VectorType v = VectorType::Random(size); + VectorType v_for_prod = VectorType::Ones(size) + Scalar(0.2) * v; // see comment above declaration of m1_for_prod + for(int i = 1; i < size; i++) { Scalar s(0), p(1); @@ -85,12 +91,12 @@ template void vectorRedux(const VectorType& w) for(int j = 0; j < i; j++) { s += v[j]; - p *= v[j]; + p *= v_for_prod[j]; minc = (std::min)(minc, internal::real(v[j])); maxc = (std::max)(maxc, internal::real(v[j])); } VERIFY_IS_MUCH_SMALLER_THAN(internal::abs(s - v.head(i).sum()), Scalar(1)); - VERIFY_IS_APPROX(p, v.head(i).prod()); + VERIFY_IS_APPROX(p, v_for_prod.head(i).prod()); VERIFY_IS_APPROX(minc, v.real().head(i).minCoeff()); VERIFY_IS_APPROX(maxc, v.real().head(i).maxCoeff()); } @@ -102,12 +108,12 @@ template void vectorRedux(const VectorType& w) for(int j = i; j < size; j++) { s += v[j]; - p *= v[j]; + p *= v_for_prod[j]; minc = (std::min)(minc, internal::real(v[j])); maxc = (std::max)(maxc, internal::real(v[j])); } VERIFY_IS_MUCH_SMALLER_THAN(internal::abs(s - v.tail(size-i).sum()), Scalar(1)); - VERIFY_IS_APPROX(p, v.tail(size-i).prod()); + VERIFY_IS_APPROX(p, v_for_prod.tail(size-i).prod()); VERIFY_IS_APPROX(minc, v.real().tail(size-i).minCoeff()); VERIFY_IS_APPROX(maxc, v.real().tail(size-i).maxCoeff()); } @@ -119,12 +125,12 @@ template void vectorRedux(const VectorType& w) for(int j = i; j < size-i; j++) { s += v[j]; - p *= v[j]; + p *= v_for_prod[j]; minc = (std::min)(minc, internal::real(v[j])); maxc = (std::max)(maxc, internal::real(v[j])); } VERIFY_IS_MUCH_SMALLER_THAN(internal::abs(s - v.segment(i, size-2*i).sum()), Scalar(1)); - VERIFY_IS_APPROX(p, v.segment(i, size-2*i).prod()); + VERIFY_IS_APPROX(p, v_for_prod.segment(i, size-2*i).prod()); VERIFY_IS_APPROX(minc, v.real().segment(i, size-2*i).minCoeff()); VERIFY_IS_APPROX(maxc, v.real().segment(i, size-2*i).maxCoeff()); } @@ -139,6 +145,9 @@ template void vectorRedux(const VectorType& w) void test_redux() { + // the max size cannot be too large, otherwise reduxion operations obviously generate large errors. + int maxsize = (std::min)(100,EIGEN_TEST_MAX_SIZE); + EIGEN_UNUSED_VARIABLE(maxsize); for(int i = 0; i < g_repeat; i++) { CALL_SUBTEST_1( matrixRedux(Matrix()) ); CALL_SUBTEST_1( matrixRedux(Array()) ); @@ -146,19 +155,19 @@ void test_redux() CALL_SUBTEST_2( matrixRedux(Array2f()) ); CALL_SUBTEST_3( matrixRedux(Matrix4d()) ); CALL_SUBTEST_3( matrixRedux(Array4d()) ); - CALL_SUBTEST_4( matrixRedux(MatrixXcf(3, 3)) ); - CALL_SUBTEST_4( matrixRedux(ArrayXXcf(3, 3)) ); - CALL_SUBTEST_5( matrixRedux(MatrixXd(8, 12)) ); - CALL_SUBTEST_5( matrixRedux(ArrayXXd(8, 12)) ); - CALL_SUBTEST_6( matrixRedux(MatrixXi(8, 12)) ); - CALL_SUBTEST_6( matrixRedux(ArrayXXi(8, 12)) ); + CALL_SUBTEST_4( matrixRedux(MatrixXcf(internal::random(1,maxsize), internal::random(1,maxsize))) ); + CALL_SUBTEST_4( matrixRedux(ArrayXXcf(internal::random(1,maxsize), internal::random(1,maxsize))) ); + CALL_SUBTEST_5( matrixRedux(MatrixXd (internal::random(1,maxsize), internal::random(1,maxsize))) ); + CALL_SUBTEST_5( matrixRedux(ArrayXXd (internal::random(1,maxsize), internal::random(1,maxsize))) ); + CALL_SUBTEST_6( matrixRedux(MatrixXi (internal::random(1,maxsize), internal::random(1,maxsize))) ); + CALL_SUBTEST_6( matrixRedux(ArrayXXi (internal::random(1,maxsize), internal::random(1,maxsize))) ); } for(int i = 0; i < g_repeat; i++) { CALL_SUBTEST_7( vectorRedux(Vector4f()) ); CALL_SUBTEST_7( vectorRedux(Array4f()) ); - CALL_SUBTEST_5( vectorRedux(VectorXd(10)) ); - CALL_SUBTEST_5( vectorRedux(ArrayXd(10)) ); - CALL_SUBTEST_8( vectorRedux(VectorXf(33)) ); - CALL_SUBTEST_8( vectorRedux(ArrayXf(33)) ); + CALL_SUBTEST_5( vectorRedux(VectorXd(internal::random(1,maxsize))) ); + CALL_SUBTEST_5( vectorRedux(ArrayXd(internal::random(1,maxsize))) ); + CALL_SUBTEST_8( vectorRedux(VectorXf(internal::random(1,maxsize))) ); + CALL_SUBTEST_8( vectorRedux(ArrayXf(internal::random(1,maxsize))) ); } } diff --git a/gtsam/3rdparty/Eigen/test/schur_complex.cpp b/gtsam/3rdparty/Eigen/test/schur_complex.cpp index a2a89fd67..15532e2cc 100644 --- a/gtsam/3rdparty/Eigen/test/schur_complex.cpp +++ b/gtsam/3rdparty/Eigen/test/schur_complex.cpp @@ -80,7 +80,7 @@ template void schur(int size = MatrixType::ColsAtCompileTim void test_schur_complex() { CALL_SUBTEST_1(( schur() )); - CALL_SUBTEST_2(( schur(internal::random(1,50)) )); + CALL_SUBTEST_2(( schur(internal::random(1,EIGEN_TEST_MAX_SIZE/4)) )); CALL_SUBTEST_3(( schur, 1, 1> >() )); CALL_SUBTEST_4(( schur >() )); diff --git a/gtsam/3rdparty/Eigen/test/schur_real.cpp b/gtsam/3rdparty/Eigen/test/schur_real.cpp index 58717fa1a..ba0947d8c 100644 --- a/gtsam/3rdparty/Eigen/test/schur_real.cpp +++ b/gtsam/3rdparty/Eigen/test/schur_real.cpp @@ -99,7 +99,7 @@ template void schur(int size = MatrixType::ColsAtCompileTim void test_schur_real() { CALL_SUBTEST_1(( schur() )); - CALL_SUBTEST_2(( schur(internal::random(1,50)) )); + CALL_SUBTEST_2(( schur(internal::random(1,EIGEN_TEST_MAX_SIZE/4)) )); CALL_SUBTEST_3(( schur >() )); CALL_SUBTEST_4(( schur >() )); diff --git a/gtsam/3rdparty/Eigen/test/selfadjoint.cpp b/gtsam/3rdparty/Eigen/test/selfadjoint.cpp index 622045f20..db66017c1 100644 --- a/gtsam/3rdparty/Eigen/test/selfadjoint.cpp +++ b/gtsam/3rdparty/Eigen/test/selfadjoint.cpp @@ -54,20 +54,23 @@ template void selfadjoint(const MatrixType& m) void bug_159() { - Matrix3d m = Matrix3d::Random().selfadjointView(); + Matrix3d m = Matrix3d::Random().selfadjointView(); + EIGEN_UNUSED_VARIABLE(m) } void test_selfadjoint() { for(int i = 0; i < g_repeat ; i++) { - int s = internal::random(1,20); EIGEN_UNUSED_VARIABLE(s); + int s = internal::random(1,EIGEN_TEST_MAX_SIZE); EIGEN_UNUSED_VARIABLE(s); CALL_SUBTEST_1( selfadjoint(Matrix()) ); CALL_SUBTEST_2( selfadjoint(Matrix()) ); CALL_SUBTEST_3( selfadjoint(Matrix3cf()) ); CALL_SUBTEST_4( selfadjoint(MatrixXcd(s,s)) ); CALL_SUBTEST_5( selfadjoint(Matrix(s, s)) ); + + EIGEN_UNUSED_VARIABLE(s) } CALL_SUBTEST_1( bug_159() ); diff --git a/gtsam/3rdparty/Eigen/test/simplicial_cholesky.cpp b/gtsam/3rdparty/Eigen/test/simplicial_cholesky.cpp new file mode 100644 index 000000000..f1af0e467 --- /dev/null +++ b/gtsam/3rdparty/Eigen/test/simplicial_cholesky.cpp @@ -0,0 +1,55 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2011 Gael Guennebaud +// +// Eigen is free software; you can redistribute it and/or +// modify it under the terms of the GNU Lesser General Public +// License as published by the Free Software Foundation; either +// version 3 of the License, or (at your option) any later version. +// +// Alternatively, you can redistribute it and/or +// modify it under the terms of the GNU General Public License as +// published by the Free Software Foundation; either version 2 of +// the License, or (at your option) any later version. +// +// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY +// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the +// GNU General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public +// License and a copy of the GNU General Public License along with +// Eigen. If not, see . + +#include "sparse_solver.h" + +template void test_simplicial_cholesky_T() +{ + SimplicialCholesky, Lower> chol_colmajor_lower; + SimplicialCholesky, Upper> chol_colmajor_upper; + SimplicialLLT, Lower> llt_colmajor_lower; + SimplicialLDLT, Upper> llt_colmajor_upper; + SimplicialLDLT, Lower> ldlt_colmajor_lower; + SimplicialLDLT, Upper> ldlt_colmajor_upper; + + check_sparse_spd_solving(chol_colmajor_lower); + check_sparse_spd_solving(chol_colmajor_upper); + check_sparse_spd_solving(llt_colmajor_lower); + check_sparse_spd_solving(llt_colmajor_upper); + check_sparse_spd_solving(ldlt_colmajor_lower); + check_sparse_spd_solving(ldlt_colmajor_upper); + + check_sparse_spd_determinant(chol_colmajor_lower); + check_sparse_spd_determinant(chol_colmajor_upper); + check_sparse_spd_determinant(llt_colmajor_lower); + check_sparse_spd_determinant(llt_colmajor_upper); + check_sparse_spd_determinant(ldlt_colmajor_lower); + check_sparse_spd_determinant(ldlt_colmajor_upper); +} + +void test_simplicial_cholesky() +{ + CALL_SUBTEST_1(test_simplicial_cholesky_T()); + CALL_SUBTEST_2(test_simplicial_cholesky_T >()); +} diff --git a/gtsam/3rdparty/Eigen/test/smallvectors.cpp b/gtsam/3rdparty/Eigen/test/smallvectors.cpp index 144944162..4c09d4ec6 100644 --- a/gtsam/3rdparty/Eigen/test/smallvectors.cpp +++ b/gtsam/3rdparty/Eigen/test/smallvectors.cpp @@ -22,6 +22,7 @@ // License and a copy of the GNU General Public License along with // Eigen. If not, see . +#define EIGEN_NO_STATIC_ASSERT #include "main.h" template void smallVectors() @@ -29,6 +30,7 @@ template void smallVectors() typedef Matrix V2; typedef Matrix V3; typedef Matrix V4; + typedef Matrix VX; Scalar x1 = internal::random(), x2 = internal::random(), x3 = internal::random(), @@ -45,6 +47,29 @@ template void smallVectors() VERIFY_IS_APPROX(x3, v3.z()); VERIFY_IS_APPROX(x3, v4.z()); VERIFY_IS_APPROX(x4, v4.w()); + + if (!NumTraits::IsInteger) + { + VERIFY_RAISES_ASSERT(V3(2, 1)) + VERIFY_RAISES_ASSERT(V3(3, 2)) + VERIFY_RAISES_ASSERT(V3(Scalar(3), 1)) + VERIFY_RAISES_ASSERT(V3(3, Scalar(1))) + VERIFY_RAISES_ASSERT(V3(Scalar(3), Scalar(1))) + VERIFY_RAISES_ASSERT(V3(Scalar(123), Scalar(123))) + + VERIFY_RAISES_ASSERT(V4(1, 3)) + VERIFY_RAISES_ASSERT(V4(2, 4)) + VERIFY_RAISES_ASSERT(V4(1, Scalar(4))) + VERIFY_RAISES_ASSERT(V4(Scalar(1), 4)) + VERIFY_RAISES_ASSERT(V4(Scalar(1), Scalar(4))) + VERIFY_RAISES_ASSERT(V4(Scalar(123), Scalar(123))) + + VERIFY_RAISES_ASSERT(VX(3, 2)) + VERIFY_RAISES_ASSERT(VX(Scalar(3), 1)) + VERIFY_RAISES_ASSERT(VX(3, Scalar(1))) + VERIFY_RAISES_ASSERT(VX(Scalar(3), Scalar(1))) + VERIFY_RAISES_ASSERT(VX(Scalar(123), Scalar(123))) + } } void test_smallvectors() diff --git a/gtsam/3rdparty/Eigen/test/sparse.h b/gtsam/3rdparty/Eigen/test/sparse.h index cc9da4855..860d9ad9c 100644 --- a/gtsam/3rdparty/Eigen/test/sparse.h +++ b/gtsam/3rdparty/Eigen/test/sparse.h @@ -1,7 +1,7 @@ // This file is part of Eigen, a lightweight C++ template library // for linear algebra. // -// Copyright (C) 2008 Daniel Gomez Ferro +// Copyright (C) 2008-2011 Gael Guennebaud // // Eigen is free software; you can redistribute it and/or // modify it under the terms of the GNU Lesser General Public @@ -23,6 +23,7 @@ // Eigen. If not, see . #ifndef EIGEN_TESTSPARSE_H +#define EIGEN_TESTSPARSE_H #define EIGEN_YES_I_KNOW_SPARSE_MODULE_IS_NOT_STABLE_YET @@ -67,30 +68,36 @@ enum { * \param zeroCoords and nonzeroCoords allows to get the coordinate lists of the non zero, * and zero coefficients respectively. */ -template void +template void initSparse(double density, - Matrix& refMat, - SparseMatrix& sparseMat, + Matrix& refMat, + SparseMatrix& sparseMat, int flags = 0, std::vector* zeroCoords = 0, std::vector* nonzeroCoords = 0) { + enum { IsRowMajor = SparseMatrix::IsRowMajor }; sparseMat.setZero(); - sparseMat.reserve(int(refMat.rows()*refMat.cols()*density)); - for(int j=0; j(0,1) < density) ? internal::random() : Scalar(0); if ((flags&ForceNonZeroDiag) && (i==j)) { v = internal::random()*Scalar(3.); v = v*v + Scalar(5.); } - if ((flags & MakeLowerTriangular) && j>i) + if ((flags & MakeLowerTriangular) && aj>ai) v = Scalar(0); - else if ((flags & MakeUpperTriangular) && jpush_back(Vector2i(i,j)); + nonzeroCoords->push_back(Vector2i(ai,aj)); } else if (zeroCoords) { - zeroCoords->push_back(Vector2i(i,j)); + zeroCoords->push_back(Vector2i(ai,aj)); } - refMat(i,j) = v; + refMat(ai,aj) = v; } } - sparseMat.finalize(); + //sparseMat.finalize(); } -template void +template void initSparse(double density, - Matrix& refMat, - DynamicSparseMatrix& sparseMat, + Matrix& refMat, + DynamicSparseMatrix& sparseMat, int flags = 0, std::vector* zeroCoords = 0, std::vector* nonzeroCoords = 0) { + enum { IsRowMajor = DynamicSparseMatrix::IsRowMajor }; sparseMat.setZero(); sparseMat.reserve(int(refMat.rows()*refMat.cols()*density)); - for(int j=0; j(0,1) < density) ? internal::random() : Scalar(0); if ((flags&ForceNonZeroDiag) && (i==j)) { v = internal::random()*Scalar(3.); v = v*v + Scalar(5.); } - if ((flags & MakeLowerTriangular) && j>i) + if ((flags & MakeLowerTriangular) && aj>ai) v = Scalar(0); - else if ((flags & MakeUpperTriangular) && jpush_back(Vector2i(i,j)); + nonzeroCoords->push_back(Vector2i(ai,aj)); } else if (zeroCoords) { - zeroCoords->push_back(Vector2i(i,j)); + zeroCoords->push_back(Vector2i(ai,aj)); } - refMat(i,j) = v; + refMat(ai,aj) = v; } } sparseMat.finalize(); @@ -181,4 +193,5 @@ initSparse(double density, } } +#include #endif // EIGEN_TESTSPARSE_H diff --git a/gtsam/3rdparty/Eigen/test/sparse_basic.cpp b/gtsam/3rdparty/Eigen/test/sparse_basic.cpp index 6f54d2ebc..637c5db51 100644 --- a/gtsam/3rdparty/Eigen/test/sparse_basic.cpp +++ b/gtsam/3rdparty/Eigen/test/sparse_basic.cpp @@ -1,6 +1,7 @@ // This file is part of Eigen, a lightweight C++ template library // for linear algebra. // +// Copyright (C) 2008-2011 Gael Guennebaud // Copyright (C) 2008 Daniel Gomez Ferro // // Eigen is free software; you can redistribute it and/or @@ -109,7 +110,8 @@ template void sparse_basic(const SparseMatrixType& re DenseMatrix m1(rows,cols); m1.setZero(); SparseMatrixType m2(rows,cols); - m2.reserve(10); + if(internal::random()%2) + m2.reserve(VectorXi::Constant(m2.outerSize(), 2)); for (int j=0; j void sparse_basic(const SparseMatrixType& re DenseMatrix m1(rows,cols); m1.setZero(); SparseMatrixType m2(rows,cols); - m2.reserve(10); + if(internal::random()%2) + m2.reserve(VectorXi::Constant(m2.outerSize(), 2)); + for (int k=0; k(0,rows-1); + int j = internal::random(0,cols-1); + if ((m1.coeff(i,j)==Scalar(0)) && (internal::random()%2)) + m2.insert(i,j) = m1(i,j) = internal::random(); + else + { + Scalar v = internal::random(); + m2.coeffRef(i,j) += v; + m1(i,j) += v; + } + } + VERIFY_IS_APPROX(m2,m1); + } + + // test insert (un-compressed) + for(int mode=0;mode<4;++mode) + { + DenseMatrix m1(rows,cols); + m1.setZero(); + SparseMatrixType m2(rows,cols); + VectorXi r(VectorXi::Constant(m2.outerSize(), ((mode%2)==0) ? m2.innerSize() : std::max(1,m2.innerSize()/8))); + m2.reserve(r); for (int k=0; k(0,rows-1); int j = internal::random(0,cols-1); if (m1.coeff(i,j)==Scalar(0)) m2.insert(i,j) = m1(i,j) = internal::random(); + if(mode==3) + m2.reserve(r); } - m2.finalize(); + if(internal::random()%2) + m2.makeCompressed(); VERIFY_IS_APPROX(m2,m1); } @@ -166,7 +196,13 @@ template void sparse_basic(const SparseMatrixType& re VERIFY_IS_APPROX(m1+=m2, refM1+=refM2); VERIFY_IS_APPROX(m1-=m2, refM1-=refM2); - VERIFY_IS_APPROX(m1.col(0).dot(refM2.row(0)), refM1.col(0).dot(refM2.row(0))); + if(SparseMatrixType::IsRowMajor) + VERIFY_IS_APPROX(m1.innerVector(0).dot(refM2.row(0)), refM1.row(0).dot(refM2.row(0))); + else + VERIFY_IS_APPROX(m1.innerVector(0).dot(refM2.row(0)), refM1.col(0).dot(refM2.row(0))); + + VERIFY_IS_APPROX(m1.conjugate(), refM1.conjugate()); + VERIFY_IS_APPROX(m1.real(), refM1.real()); refM4.setRandom(); // sparse cwise* dense @@ -190,10 +226,37 @@ template void sparse_basic(const SparseMatrixType& re DenseMatrix refMat2 = DenseMatrix::Zero(rows, rows); SparseMatrixType m2(rows, rows); initSparse(density, refMat2, m2); - int j0 = internal::random(0,rows-1); - int j1 = internal::random(0,rows-1); - VERIFY_IS_APPROX(m2.innerVector(j0), refMat2.col(j0)); - VERIFY_IS_APPROX(m2.innerVector(j0)+m2.innerVector(j1), refMat2.col(j0)+refMat2.col(j1)); + int j0 = internal::random(0,rows-1); + int j1 = internal::random(0,rows-1); + if(SparseMatrixType::IsRowMajor) + VERIFY_IS_APPROX(m2.innerVector(j0), refMat2.row(j0)); + else + VERIFY_IS_APPROX(m2.innerVector(j0), refMat2.col(j0)); + + if(SparseMatrixType::IsRowMajor) + VERIFY_IS_APPROX(m2.innerVector(j0)+m2.innerVector(j1), refMat2.row(j0)+refMat2.row(j1)); + else + VERIFY_IS_APPROX(m2.innerVector(j0)+m2.innerVector(j1), refMat2.col(j0)+refMat2.col(j1)); + + SparseMatrixType m3(rows,rows); + m3.reserve(VectorXi::Constant(rows,rows/2)); + for(int j=0; j0) + VERIFY(j==internal::real(m3.innerVector(j).lastCoeff())); + } + m3.makeCompressed(); + for(int j=0; j0) + VERIFY(j==internal::real(m3.innerVector(j).lastCoeff())); + } + //m2.innerVector(j0) = 2*m2.innerVector(j1); //refMat2.col(j0) = 2*refMat2.col(j1); //VERIFY_IS_APPROX(m2, refMat2); @@ -204,12 +267,19 @@ template void sparse_basic(const SparseMatrixType& re DenseMatrix refMat2 = DenseMatrix::Zero(rows, rows); SparseMatrixType m2(rows, rows); initSparse(density, refMat2, m2); - int j0 = internal::random(0,rows-2); - int j1 = internal::random(0,rows-2); + int j0 = internal::random(0,rows-2); + int j1 = internal::random(0,rows-2); int n0 = internal::random(1,rows-(std::max)(j0,j1)); - VERIFY_IS_APPROX(m2.innerVectors(j0,n0), refMat2.block(0,j0,rows,n0)); - VERIFY_IS_APPROX(m2.innerVectors(j0,n0)+m2.innerVectors(j1,n0), - refMat2.block(0,j0,rows,n0)+refMat2.block(0,j1,rows,n0)); + if(SparseMatrixType::IsRowMajor) + VERIFY_IS_APPROX(m2.innerVectors(j0,n0), refMat2.block(j0,0,n0,cols)); + else + VERIFY_IS_APPROX(m2.innerVectors(j0,n0), refMat2.block(0,j0,rows,n0)); + if(SparseMatrixType::IsRowMajor) + VERIFY_IS_APPROX(m2.innerVectors(j0,n0)+m2.innerVectors(j1,n0), + refMat2.block(j0,0,n0,cols)+refMat2.block(j1,0,n0,cols)); + else + VERIFY_IS_APPROX(m2.innerVectors(j0,n0)+m2.innerVectors(j1,n0), + refMat2.block(0,j0,rows,n0)+refMat2.block(0,j1,rows,n0)); //m2.innerVectors(j0,n0) = m2.innerVectors(j0,n0) + m2.innerVectors(j1,n0); //refMat2.block(0,j0,rows,n0) = refMat2.block(0,j0,rows,n0) + refMat2.block(0,j1,rows,n0); } @@ -239,7 +309,11 @@ template void sparse_basic(const SparseMatrixType& re else { countTrueNonZero++; - m2.insertBackByOuterInner(j,i) = refM2(i,j) = Scalar(1); + m2.insertBackByOuterInner(j,i) = Scalar(1); + if(SparseMatrixType::IsRowMajor) + refM2(j,i) = Scalar(1); + else + refM2(i,j) = Scalar(1); } } } @@ -250,8 +324,52 @@ template void sparse_basic(const SparseMatrixType& re VERIFY(countTrueNonZero==m2.nonZeros()); VERIFY_IS_APPROX(m2, refM2); } + + // test setFromTriplets + { + typedef Triplet TripletType; + std::vector triplets; + int ntriplets = rows*cols; + triplets.reserve(ntriplets); + DenseMatrix refMat(rows,cols); + refMat.setZero(); + for(int i=0;i(0,rows-1); + int c = internal::random(0,cols-1); + Scalar v = internal::random(); + triplets.push_back(TripletType(r,c,v)); + refMat(r,c) += v; + } + SparseMatrixType m(rows,cols); + m.setFromTriplets(triplets.begin(), triplets.end()); + VERIFY_IS_APPROX(m, refMat); + } + + // test triangularView + { + DenseMatrix refMat2(rows, rows), refMat3(rows, rows); + SparseMatrixType m2(rows, rows), m3(rows, rows); + initSparse(density, refMat2, m2); + refMat3 = refMat2.template triangularView(); + m3 = m2.template triangularView(); + VERIFY_IS_APPROX(m3, refMat3); + + refMat3 = refMat2.template triangularView(); + m3 = m2.template triangularView(); + VERIFY_IS_APPROX(m3, refMat3); + + refMat3 = refMat2.template triangularView(); + m3 = m2.template triangularView(); + VERIFY_IS_APPROX(m3, refMat3); + + refMat3 = refMat2.template triangularView(); + m3 = m2.template triangularView(); + VERIFY_IS_APPROX(m3, refMat3); + } // test selfadjointView + if(!SparseMatrixType::IsRowMajor) { DenseMatrix refMat2(rows, rows), refMat3(rows, rows); SparseMatrixType m2(rows, rows), m3(rows, rows); @@ -268,15 +386,25 @@ template void sparse_basic(const SparseMatrixType& re initSparse(density, refMat2, m2); VERIFY_IS_APPROX(m2.eval(), refMat2.sparseView().eval()); } + + // test diagonal + { + DenseMatrix refMat2 = DenseMatrix::Zero(rows, rows); + SparseMatrixType m2(rows, rows); + initSparse(density, refMat2, m2); + VERIFY_IS_APPROX(m2.diagonal(), refMat2.diagonal().eval()); + } } void test_sparse_basic() { for(int i = 0; i < g_repeat; i++) { - CALL_SUBTEST_1( sparse_basic(SparseMatrix(8, 8)) ); - CALL_SUBTEST_2( sparse_basic(SparseMatrix >(16, 16)) ); - CALL_SUBTEST_1( sparse_basic(SparseMatrix(33, 33)) ); - - CALL_SUBTEST_3( sparse_basic(DynamicSparseMatrix(8, 8)) ); + int s = Eigen::internal::random(1,50); + CALL_SUBTEST_1(( sparse_basic(SparseMatrix(8, 8)) )); + CALL_SUBTEST_2(( sparse_basic(SparseMatrix, ColMajor>(s, s)) )); + CALL_SUBTEST_2(( sparse_basic(SparseMatrix, RowMajor>(s, s)) )); + CALL_SUBTEST_1(( sparse_basic(SparseMatrix(s, s)) )); + CALL_SUBTEST_1(( sparse_basic(SparseMatrix(s, s)) )); + CALL_SUBTEST_1(( sparse_basic(SparseMatrix(s, s)) )); } } diff --git a/gtsam/3rdparty/Eigen/test/sparse_permutations.cpp b/gtsam/3rdparty/Eigen/test/sparse_permutations.cpp new file mode 100644 index 000000000..4d22e358e --- /dev/null +++ b/gtsam/3rdparty/Eigen/test/sparse_permutations.cpp @@ -0,0 +1,202 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2011 Gael Guennebaud +// +// Eigen is free software; you can redistribute it and/or +// modify it under the terms of the GNU Lesser General Public +// License as published by the Free Software Foundation; either +// version 3 of the License, or (at your option) any later version. +// +// Alternatively, you can redistribute it and/or +// modify it under the terms of the GNU General Public License as +// published by the Free Software Foundation; either version 2 of +// the License, or (at your option) any later version. +// +// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY +// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the +// GNU General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public +// License and a copy of the GNU General Public License along with +// Eigen. If not, see . + +#include "sparse.h" + +template void sparse_permutations(const SparseMatrixType& ref) +{ + typedef typename SparseMatrixType::Index Index; + + const Index rows = ref.rows(); + const Index cols = ref.cols(); + typedef typename SparseMatrixType::Scalar Scalar; + typedef typename SparseMatrixType::Index Index; + typedef SparseMatrix OtherSparseMatrixType; + typedef Matrix DenseMatrix; + typedef Matrix VectorI; + + double density = (std::max)(8./(rows*cols), 0.01); + + SparseMatrixType mat(rows, cols), up(rows,cols), lo(rows,cols); + OtherSparseMatrixType res; + DenseMatrix mat_d = DenseMatrix::Zero(rows, cols), up_sym_d, lo_sym_d, res_d; + + initSparse(density, mat_d, mat, 0); + + up = mat.template triangularView(); + lo = mat.template triangularView(); + + up_sym_d = mat_d.template selfadjointView(); + lo_sym_d = mat_d.template selfadjointView(); + + VERIFY_IS_APPROX(mat, mat_d); + VERIFY_IS_APPROX(up, DenseMatrix(mat_d.template triangularView())); + VERIFY_IS_APPROX(lo, DenseMatrix(mat_d.template triangularView())); + + PermutationMatrix p, p_null; + VectorI pi; + randomPermutationVector(pi, cols); + p.indices() = pi; + + res = mat*p; + res_d = mat_d*p; + VERIFY(res.isApprox(res_d) && "mat*p"); + + res = p*mat; + res_d = p*mat_d; + VERIFY(res.isApprox(res_d) && "p*mat"); + + res = mat*p.inverse(); + res_d = mat*p.inverse(); + VERIFY(res.isApprox(res_d) && "mat*inv(p)"); + + res = p.inverse()*mat; + res_d = p.inverse()*mat_d; + VERIFY(res.isApprox(res_d) && "inv(p)*mat"); + + res = mat.twistedBy(p); + res_d = (p * mat_d) * p.inverse(); + VERIFY(res.isApprox(res_d) && "p*mat*inv(p)"); + + + res = mat.template selfadjointView().twistedBy(p_null); + res_d = up_sym_d; + VERIFY(res.isApprox(res_d) && "full selfadjoint upper to full"); + + res = mat.template selfadjointView().twistedBy(p_null); + res_d = lo_sym_d; + VERIFY(res.isApprox(res_d) && "full selfadjoint lower to full"); + + + res = up.template selfadjointView().twistedBy(p_null); + res_d = up_sym_d; + VERIFY(res.isApprox(res_d) && "upper selfadjoint to full"); + + res = lo.template selfadjointView().twistedBy(p_null); + res_d = lo_sym_d; + VERIFY(res.isApprox(res_d) && "lower selfadjoint full"); + + + res = mat.template selfadjointView(); + res_d = up_sym_d; + VERIFY(res.isApprox(res_d) && "full selfadjoint upper to full"); + + res = mat.template selfadjointView(); + res_d = lo_sym_d; + VERIFY(res.isApprox(res_d) && "full selfadjoint lower to full"); + + res = up.template selfadjointView(); + res_d = up_sym_d; + VERIFY(res.isApprox(res_d) && "upper selfadjoint to full"); + + res = lo.template selfadjointView(); + res_d = lo_sym_d; + VERIFY(res.isApprox(res_d) && "lower selfadjoint full"); + + + res.template selfadjointView() = mat.template selfadjointView(); + res_d = up_sym_d.template triangularView(); + VERIFY(res.isApprox(res_d) && "full selfadjoint upper to upper"); + + res.template selfadjointView() = mat.template selfadjointView(); + res_d = up_sym_d.template triangularView(); + VERIFY(res.isApprox(res_d) && "full selfadjoint upper to lower"); + + res.template selfadjointView() = mat.template selfadjointView(); + res_d = lo_sym_d.template triangularView(); + VERIFY(res.isApprox(res_d) && "full selfadjoint lower to upper"); + + res.template selfadjointView() = mat.template selfadjointView(); + res_d = lo_sym_d.template triangularView(); + VERIFY(res.isApprox(res_d) && "full selfadjoint lower to lower"); + + + + res.template selfadjointView() = mat.template selfadjointView().twistedBy(p); + res_d = ((p * up_sym_d) * p.inverse()).eval().template triangularView(); + VERIFY(res.isApprox(res_d) && "full selfadjoint upper twisted to upper"); + + res.template selfadjointView() = mat.template selfadjointView().twistedBy(p); + res_d = ((p * lo_sym_d) * p.inverse()).eval().template triangularView(); + VERIFY(res.isApprox(res_d) && "full selfadjoint lower twisted to upper"); + + res.template selfadjointView() = mat.template selfadjointView().twistedBy(p); + res_d = ((p * lo_sym_d) * p.inverse()).eval().template triangularView(); + VERIFY(res.isApprox(res_d) && "full selfadjoint lower twisted to lower"); + + res.template selfadjointView() = mat.template selfadjointView().twistedBy(p); + res_d = ((p * up_sym_d) * p.inverse()).eval().template triangularView(); + VERIFY(res.isApprox(res_d) && "full selfadjoint upper twisted to lower"); + + + res.template selfadjointView() = up.template selfadjointView().twistedBy(p); + res_d = ((p * up_sym_d) * p.inverse()).eval().template triangularView(); + VERIFY(res.isApprox(res_d) && "upper selfadjoint twisted to upper"); + + res.template selfadjointView() = lo.template selfadjointView().twistedBy(p); + res_d = ((p * lo_sym_d) * p.inverse()).eval().template triangularView(); + VERIFY(res.isApprox(res_d) && "lower selfadjoint twisted to upper"); + + res.template selfadjointView() = lo.template selfadjointView().twistedBy(p); + res_d = ((p * lo_sym_d) * p.inverse()).eval().template triangularView(); + VERIFY(res.isApprox(res_d) && "lower selfadjoint twisted to lower"); + + res.template selfadjointView() = up.template selfadjointView().twistedBy(p); + res_d = ((p * up_sym_d) * p.inverse()).eval().template triangularView(); + VERIFY(res.isApprox(res_d) && "upper selfadjoint twisted to lower"); + + + res = mat.template selfadjointView().twistedBy(p); + res_d = (p * up_sym_d) * p.inverse(); + VERIFY(res.isApprox(res_d) && "full selfadjoint upper twisted to full"); + + res = mat.template selfadjointView().twistedBy(p); + res_d = (p * lo_sym_d) * p.inverse(); + VERIFY(res.isApprox(res_d) && "full selfadjoint lower twisted to full"); + + res = up.template selfadjointView().twistedBy(p); + res_d = (p * up_sym_d) * p.inverse(); + VERIFY(res.isApprox(res_d) && "upper selfadjoint twisted to full"); + + res = lo.template selfadjointView().twistedBy(p); + res_d = (p * lo_sym_d) * p.inverse(); + VERIFY(res.isApprox(res_d) && "lower selfadjoint twisted to full"); +} + +template void sparse_permutations_all(int size) +{ + CALL_SUBTEST(( sparse_permutations(SparseMatrix(size,size)) )); + CALL_SUBTEST(( sparse_permutations(SparseMatrix(size,size)) )); + CALL_SUBTEST(( sparse_permutations(SparseMatrix(size,size)) )); + CALL_SUBTEST(( sparse_permutations(SparseMatrix(size,size)) )); +} + +void test_sparse_permutations() +{ + for(int i = 0; i < g_repeat; i++) { + int s = Eigen::internal::random(1,50); + CALL_SUBTEST_1(( sparse_permutations_all(s) )); + CALL_SUBTEST_2(( sparse_permutations_all >(s) )); + } +} diff --git a/gtsam/3rdparty/Eigen/test/sparse_product.cpp b/gtsam/3rdparty/Eigen/test/sparse_product.cpp index a53ab3f1b..2c28d1131 100644 --- a/gtsam/3rdparty/Eigen/test/sparse_product.cpp +++ b/gtsam/3rdparty/Eigen/test/sparse_product.cpp @@ -1,7 +1,7 @@ // This file is part of Eigen, a lightweight C++ template library // for linear algebra. // -// Copyright (C) 2008 Daniel Gomez Ferro +// Copyright (C) 2008-2011 Gael Guennebaud // // Eigen is free software; you can redistribute it and/or // modify it under the terms of the GNU Lesser General Public @@ -24,11 +24,37 @@ #include "sparse.h" -template void sparse_product(const SparseMatrixType& ref) +template struct test_outer; + +template struct test_outer { + static void run(SparseMatrixType& m2, SparseMatrixType& m4, DenseMatrix& refMat2, DenseMatrix& refMat4) { + int c = internal::random(0,m2.cols()-1); + int c1 = internal::random(0,m2.cols()-1); + VERIFY_IS_APPROX(m4=m2.col(c)*refMat2.col(c1).transpose(), refMat4=refMat2.col(c)*refMat2.col(c1).transpose()); + VERIFY_IS_APPROX(m4=refMat2.col(c1)*m2.col(c).transpose(), refMat4=refMat2.col(c1)*refMat2.col(c).transpose()); + } +}; + +template struct test_outer { + static void run(SparseMatrixType& m2, SparseMatrixType& m4, DenseMatrix& refMat2, DenseMatrix& refMat4) { + int r = internal::random(0,m2.rows()-1); + int c1 = internal::random(0,m2.cols()-1); + VERIFY_IS_APPROX(m4=m2.row(r).transpose()*refMat2.col(c1).transpose(), refMat4=refMat2.row(r).transpose()*refMat2.col(c1).transpose()); + VERIFY_IS_APPROX(m4=refMat2.col(c1)*m2.row(r), refMat4=refMat2.col(c1)*refMat2.row(r)); + } +}; + +// (m2,m4,refMat2,refMat4,dv1); +// VERIFY_IS_APPROX(m4=m2.innerVector(c)*dv1.transpose(), refMat4=refMat2.colVector(c)*dv1.transpose()); +// VERIFY_IS_APPROX(m4=dv1*mcm.col(c).transpose(), refMat4=dv1*refMat2.col(c).transpose()); + +template void sparse_product() { typedef typename SparseMatrixType::Index Index; - const Index rows = ref.rows(); - const Index cols = ref.cols(); + Index n = 100; + const Index rows = internal::random(1,n); + const Index cols = internal::random(1,n); + const Index depth = internal::random(1,n); typedef typename SparseMatrixType::Scalar Scalar; enum { Flags = SparseMatrixType::Flags }; @@ -41,50 +67,71 @@ template void sparse_product(const SparseMatrixType& // test matrix-matrix product { - DenseMatrix refMat2 = DenseMatrix::Zero(rows, rows); - DenseMatrix refMat3 = DenseMatrix::Zero(rows, rows); - DenseMatrix refMat4 = DenseMatrix::Zero(rows, rows); - DenseMatrix refMat5 = DenseMatrix::Random(rows, rows); + DenseMatrix refMat2 = DenseMatrix::Zero(rows, depth); + DenseMatrix refMat2t = DenseMatrix::Zero(depth, rows); + DenseMatrix refMat3 = DenseMatrix::Zero(depth, cols); + DenseMatrix refMat3t = DenseMatrix::Zero(cols, depth); + DenseMatrix refMat4 = DenseMatrix::Zero(rows, cols); + DenseMatrix refMat4t = DenseMatrix::Zero(cols, rows); + DenseMatrix refMat5 = DenseMatrix::Random(depth, cols); + DenseMatrix refMat6 = DenseMatrix::Random(rows, rows); DenseMatrix dm4 = DenseMatrix::Zero(rows, rows); - DenseVector dv1 = DenseVector::Random(rows); - SparseMatrixType m2(rows, rows); - SparseMatrixType m3(rows, rows); - SparseMatrixType m4(rows, rows); - initSparse(density, refMat2, m2); - initSparse(density, refMat3, m3); - initSparse(density, refMat4, m4); +// DenseVector dv1 = DenseVector::Random(rows); + SparseMatrixType m2 (rows, depth); + SparseMatrixType m2t(depth, rows); + SparseMatrixType m3 (depth, cols); + SparseMatrixType m3t(cols, depth); + SparseMatrixType m4 (rows, cols); + SparseMatrixType m4t(cols, rows); + SparseMatrixType m6(rows, rows); + initSparse(density, refMat2, m2); + initSparse(density, refMat2t, m2t); + initSparse(density, refMat3, m3); + initSparse(density, refMat3t, m3t); + initSparse(density, refMat4, m4); + initSparse(density, refMat4t, m4t); + initSparse(density, refMat6, m6); - int c = internal::random(0,rows-1); +// int c = internal::random(0,depth-1); + // sparse * sparse VERIFY_IS_APPROX(m4=m2*m3, refMat4=refMat2*refMat3); - VERIFY_IS_APPROX(m4=m2.transpose()*m3, refMat4=refMat2.transpose()*refMat3); - VERIFY_IS_APPROX(m4=m2.transpose()*m3.transpose(), refMat4=refMat2.transpose()*refMat3.transpose()); - VERIFY_IS_APPROX(m4=m2*m3.transpose(), refMat4=refMat2*refMat3.transpose()); + VERIFY_IS_APPROX(m4=m2t.transpose()*m3, refMat4=refMat2t.transpose()*refMat3); + VERIFY_IS_APPROX(m4=m2t.transpose()*m3t.transpose(), refMat4=refMat2t.transpose()*refMat3t.transpose()); + VERIFY_IS_APPROX(m4=m2*m3t.transpose(), refMat4=refMat2*refMat3t.transpose()); VERIFY_IS_APPROX(m4 = m2*m3/s1, refMat4 = refMat2*refMat3/s1); VERIFY_IS_APPROX(m4 = m2*m3*s1, refMat4 = refMat2*refMat3*s1); VERIFY_IS_APPROX(m4 = s2*m2*m3*s1, refMat4 = s2*refMat2*refMat3*s1); + VERIFY_IS_APPROX(m4=(m2*m3).pruned(0), refMat4=refMat2*refMat3); + VERIFY_IS_APPROX(m4=(m2t.transpose()*m3).pruned(0), refMat4=refMat2t.transpose()*refMat3); + VERIFY_IS_APPROX(m4=(m2t.transpose()*m3t.transpose()).pruned(0), refMat4=refMat2t.transpose()*refMat3t.transpose()); + VERIFY_IS_APPROX(m4=(m2*m3t.transpose()).pruned(0), refMat4=refMat2*refMat3t.transpose()); + + // test aliasing + m4 = m2; refMat4 = refMat2; + VERIFY_IS_APPROX(m4=m4*m3, refMat4=refMat4*refMat3); + // sparse * dense VERIFY_IS_APPROX(dm4=m2*refMat3, refMat4=refMat2*refMat3); - VERIFY_IS_APPROX(dm4=m2*refMat3.transpose(), refMat4=refMat2*refMat3.transpose()); - VERIFY_IS_APPROX(dm4=m2.transpose()*refMat3, refMat4=refMat2.transpose()*refMat3); - VERIFY_IS_APPROX(dm4=m2.transpose()*refMat3.transpose(), refMat4=refMat2.transpose()*refMat3.transpose()); + VERIFY_IS_APPROX(dm4=m2*refMat3t.transpose(), refMat4=refMat2*refMat3t.transpose()); + VERIFY_IS_APPROX(dm4=m2t.transpose()*refMat3, refMat4=refMat2t.transpose()*refMat3); + VERIFY_IS_APPROX(dm4=m2t.transpose()*refMat3t.transpose(), refMat4=refMat2t.transpose()*refMat3t.transpose()); VERIFY_IS_APPROX(dm4=m2*(refMat3+refMat3), refMat4=refMat2*(refMat3+refMat3)); - VERIFY_IS_APPROX(dm4=m2.transpose()*(refMat3+refMat5)*0.5, refMat4=refMat2.transpose()*(refMat3+refMat5)*0.5); + VERIFY_IS_APPROX(dm4=m2t.transpose()*(refMat3+refMat5)*0.5, refMat4=refMat2t.transpose()*(refMat3+refMat5)*0.5); // dense * sparse VERIFY_IS_APPROX(dm4=refMat2*m3, refMat4=refMat2*refMat3); - VERIFY_IS_APPROX(dm4=refMat2*m3.transpose(), refMat4=refMat2*refMat3.transpose()); - VERIFY_IS_APPROX(dm4=refMat2.transpose()*m3, refMat4=refMat2.transpose()*refMat3); - VERIFY_IS_APPROX(dm4=refMat2.transpose()*m3.transpose(), refMat4=refMat2.transpose()*refMat3.transpose()); + VERIFY_IS_APPROX(dm4=refMat2*m3t.transpose(), refMat4=refMat2*refMat3t.transpose()); + VERIFY_IS_APPROX(dm4=refMat2t.transpose()*m3, refMat4=refMat2t.transpose()*refMat3); + VERIFY_IS_APPROX(dm4=refMat2t.transpose()*m3t.transpose(), refMat4=refMat2t.transpose()*refMat3t.transpose()); // sparse * dense and dense * sparse outer product - VERIFY_IS_APPROX(m4=m2.col(c)*dv1.transpose(), refMat4=refMat2.col(c)*dv1.transpose()); - VERIFY_IS_APPROX(m4=dv1*m2.col(c).transpose(), refMat4=dv1*refMat2.col(c).transpose()); + test_outer::run(m2,m4,refMat2,refMat4); - VERIFY_IS_APPROX(m3=m3*m3, refMat3=refMat3*refMat3); + VERIFY_IS_APPROX(m6=m6*m6, refMat6=refMat6*refMat6); } // test matrix - diagonal product @@ -116,18 +163,19 @@ template void sparse_product(const SparseMatrixType& do { initSparse(density, refUp, mUp, ForceRealDiag|/*ForceNonZeroDiag|*/MakeUpperTriangular); } while (refUp.isZero()); - refLo = refUp.transpose().conjugate(); - mLo = mUp.transpose().conjugate(); + refLo = refUp.adjoint(); + mLo = mUp.adjoint(); refS = refUp + refLo; refS.diagonal() *= 0.5; mS = mUp + mLo; + // TODO be able to address the diagonal.... for (int k=0; k void sparse_produc void test_sparse_product() { for(int i = 0; i < g_repeat; i++) { - CALL_SUBTEST_1( sparse_product(SparseMatrix(8, 8)) ); - CALL_SUBTEST_2( sparse_product(SparseMatrix >(16, 16)) ); - CALL_SUBTEST_1( sparse_product(SparseMatrix(33, 33)) ); - - CALL_SUBTEST_3( sparse_product(DynamicSparseMatrix(8, 8)) ); - + CALL_SUBTEST_1( (sparse_product >()) ); + CALL_SUBTEST_1( (sparse_product >()) ); + CALL_SUBTEST_2( (sparse_product, ColMajor > >()) ); + CALL_SUBTEST_2( (sparse_product, RowMajor > >()) ); CALL_SUBTEST_4( (sparse_product_regression_test, Matrix >()) ); } } diff --git a/gtsam/3rdparty/Eigen/test/sparse_solver.h b/gtsam/3rdparty/Eigen/test/sparse_solver.h new file mode 100644 index 000000000..69bf716ed --- /dev/null +++ b/gtsam/3rdparty/Eigen/test/sparse_solver.h @@ -0,0 +1,324 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2011 Gael Guennebaud +// +// Eigen is free software; you can redistribute it and/or +// modify it under the terms of the GNU Lesser General Public +// License as published by the Free Software Foundation; either +// version 3 of the License, or (at your option) any later version. +// +// Alternatively, you can redistribute it and/or +// modify it under the terms of the GNU General Public License as +// published by the Free Software Foundation; either version 2 of +// the License, or (at your option) any later version. +// +// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY +// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the +// GNU General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public +// License and a copy of the GNU General Public License along with +// Eigen. If not, see . + +#include "sparse.h" +#include + +template +void check_sparse_solving(Solver& solver, const typename Solver::MatrixType& A, const Rhs& b, const DenseMat& dA, const DenseRhs& db) +{ + typedef typename Solver::MatrixType Mat; + typedef typename Mat::Scalar Scalar; + + DenseRhs refX = dA.lu().solve(db); + + Rhs x(b.rows(), b.cols()); + Rhs oldb = b; + + solver.compute(A); + if (solver.info() != Success) + { + std::cerr << "sparse solver testing: factorization failed (check_sparse_solving)\n"; + exit(0); + return; + } + x = solver.solve(b); + if (solver.info() != Success) + { + std::cerr << "sparse solver testing: solving failed\n"; + return; + } + VERIFY(oldb.isApprox(b) && "sparse solver testing: the rhs should not be modified!"); + + VERIFY(x.isApprox(refX,test_precision())); + + x.setZero(); + // test the analyze/factorize API + solver.analyzePattern(A); + solver.factorize(A); + if (solver.info() != Success) + { + std::cerr << "sparse solver testing: factorization failed (check_sparse_solving)\n"; + exit(0); + return; + } + x = solver.solve(b); + if (solver.info() != Success) + { + std::cerr << "sparse solver testing: solving failed\n"; + return; + } + VERIFY(oldb.isApprox(b) && "sparse solver testing: the rhs should not be modified!"); + + VERIFY(x.isApprox(refX,test_precision())); + + // test Block as the result and rhs: + { + DenseRhs x(db.rows(), db.cols()); + DenseRhs b(db), oldb(db); + x.setZero(); + x.block(0,0,x.rows(),x.cols()) = solver.solve(b.block(0,0,b.rows(),b.cols())); + VERIFY(oldb.isApprox(b) && "sparse solver testing: the rhs should not be modified!"); + VERIFY(x.isApprox(refX,test_precision())); + } +} + +template +void check_sparse_solving_real_cases(Solver& solver, const typename Solver::MatrixType& A, const Rhs& b, const Rhs& refX) +{ + typedef typename Solver::MatrixType Mat; + typedef typename Mat::Scalar Scalar; + typedef typename Mat::RealScalar RealScalar; + + Rhs x(b.rows(), b.cols()); + + solver.compute(A); + if (solver.info() != Success) + { + std::cerr << "sparse solver testing: factorization failed (check_sparse_solving_real_cases)\n"; + exit(0); + return; + } + x = solver.solve(b); + if (solver.info() != Success) + { + std::cerr << "sparse solver testing: solving failed\n"; + return; + } + + RealScalar res_error; + // Compute the norm of the relative error + if(refX.size() != 0) + res_error = (refX - x).norm()/refX.norm(); + else + { + // Compute the relative residual norm + res_error = (b - A * x).norm()/b.norm(); + } + if (res_error > test_precision() ){ + std::cerr << "Test " << g_test_stack.back() << " failed in "EI_PP_MAKE_STRING(__FILE__) + << " (" << EI_PP_MAKE_STRING(__LINE__) << ")" << std::endl << std::endl; + abort(); + } + +} +template +void check_sparse_determinant(Solver& solver, const typename Solver::MatrixType& A, const DenseMat& dA) +{ + typedef typename Solver::MatrixType Mat; + typedef typename Mat::Scalar Scalar; + typedef typename Mat::RealScalar RealScalar; + + solver.compute(A); + if (solver.info() != Success) + { + std::cerr << "sparse solver testing: factorization failed (check_sparse_determinant)\n"; + return; + } + + Scalar refDet = dA.determinant(); + VERIFY_IS_APPROX(refDet,solver.determinant()); +} + + +template +int generate_sparse_spd_problem(Solver& , typename Solver::MatrixType& A, typename Solver::MatrixType& halfA, DenseMat& dA, int maxSize = 300) +{ + typedef typename Solver::MatrixType Mat; + typedef typename Mat::Scalar Scalar; + typedef Matrix DenseMatrix; + + int size = internal::random(1,maxSize); + double density = (std::max)(8./(size*size), 0.01); + + Mat M(size, size); + DenseMatrix dM(size, size); + + initSparse(density, dM, M, ForceNonZeroDiag); + + A = M * M.adjoint(); + dA = dM * dM.adjoint(); + + halfA.resize(size,size); + halfA.template selfadjointView().rankUpdate(M); + + return size; +} + + +#ifdef TEST_REAL_CASES +template +inline std::string get_matrixfolder() +{ + std::string mat_folder = TEST_REAL_CASES; + if( internal::is_same >::value || internal::is_same >::value ) + mat_folder = mat_folder + static_cast("/complex/"); + else + mat_folder = mat_folder + static_cast("/real/"); + return mat_folder; +} +#endif + +template void check_sparse_spd_solving(Solver& solver) +{ + typedef typename Solver::MatrixType Mat; + typedef typename Mat::Scalar Scalar; + typedef typename Mat::Index Index; + typedef SparseMatrix SpMat; + typedef Matrix DenseMatrix; + typedef Matrix DenseVector; + + // generate the problem + Mat A, halfA; + DenseMatrix dA; + int size = generate_sparse_spd_problem(solver, A, halfA, dA); + + // generate the right hand sides + int rhsCols = internal::random(1,16); + double density = (std::max)(8./(size*rhsCols), 0.1); + SpMat B(size,rhsCols); + DenseVector b = DenseVector::Random(size); + DenseMatrix dB(size,rhsCols); + initSparse(density, dB, B, ForceNonZeroDiag); + + for (int i = 0; i < g_repeat; i++) { + check_sparse_solving(solver, A, b, dA, b); + check_sparse_solving(solver, halfA, b, dA, b); + check_sparse_solving(solver, A, dB, dA, dB); + check_sparse_solving(solver, halfA, dB, dA, dB); + check_sparse_solving(solver, A, B, dA, dB); + check_sparse_solving(solver, halfA, B, dA, dB); + } + + // First, get the folder +#ifdef TEST_REAL_CASES + if (internal::is_same::value + || internal::is_same >::value) + return ; + + std::string mat_folder = get_matrixfolder(); + MatrixMarketIterator it(mat_folder); + for (; it; ++it) + { + if (it.sym() == SPD){ + Mat halfA; + PermutationMatrix pnull; + halfA.template selfadjointView() = it.matrix().template triangularView().twistedBy(pnull); + + std::cout<< " ==== SOLVING WITH MATRIX " << it.matname() << " ==== \n"; + check_sparse_solving_real_cases(solver, it.matrix(), it.rhs(), it.refX()); + check_sparse_solving_real_cases(solver, halfA, it.rhs(), it.refX()); + } + } +#endif +} + +template void check_sparse_spd_determinant(Solver& solver) +{ + typedef typename Solver::MatrixType Mat; + typedef typename Mat::Scalar Scalar; + typedef Matrix DenseMatrix; + + // generate the problem + Mat A, halfA; + DenseMatrix dA; + generate_sparse_spd_problem(solver, A, halfA, dA, 30); + + for (int i = 0; i < g_repeat; i++) { + check_sparse_determinant(solver, A, dA); + check_sparse_determinant(solver, halfA, dA ); + } +} + +template +int generate_sparse_square_problem(Solver&, typename Solver::MatrixType& A, DenseMat& dA, int maxSize = 300) +{ + typedef typename Solver::MatrixType Mat; + typedef typename Mat::Scalar Scalar; + typedef Matrix DenseMatrix; + + int size = internal::random(1,maxSize); + double density = (std::max)(8./(size*size), 0.01); + + A.resize(size,size); + dA.resize(size,size); + + initSparse(density, dA, A, ForceNonZeroDiag); + + return size; +} + +template void check_sparse_square_solving(Solver& solver) +{ + typedef typename Solver::MatrixType Mat; + typedef typename Mat::Scalar Scalar; + typedef Matrix DenseMatrix; + typedef Matrix DenseVector; + + int rhsCols = internal::random(1,16); + + Mat A; + DenseMatrix dA; + int size = generate_sparse_square_problem(solver, A, dA); + + DenseVector b = DenseVector::Random(size); + DenseMatrix dB = DenseMatrix::Random(size,rhsCols); + A.makeCompressed(); + for (int i = 0; i < g_repeat; i++) { + check_sparse_solving(solver, A, b, dA, b); + check_sparse_solving(solver, A, dB, dA, dB); + } + + // First, get the folder +#ifdef TEST_REAL_CASES + if (internal::is_same::value + || internal::is_same >::value) + return ; + + std::string mat_folder = get_matrixfolder(); + MatrixMarketIterator it(mat_folder); + for (; it; ++it) + { + std::cout<< " ==== SOLVING WITH MATRIX " << it.matname() << " ==== \n"; + check_sparse_solving_real_cases(solver, it.matrix(), it.rhs(), it.refX()); + } +#endif + +} + +template void check_sparse_square_determinant(Solver& solver) +{ + typedef typename Solver::MatrixType Mat; + typedef typename Mat::Scalar Scalar; + typedef Matrix DenseMatrix; + + // generate the problem + Mat A; + DenseMatrix dA; + generate_sparse_square_problem(solver, A, dA, 30); + A.makeCompressed(); + for (int i = 0; i < g_repeat; i++) { + check_sparse_determinant(solver, A, dA); + } +} diff --git a/gtsam/3rdparty/Eigen/test/sparse_solvers.cpp b/gtsam/3rdparty/Eigen/test/sparse_solvers.cpp index 12a1cb9b6..a3d79b0ea 100644 --- a/gtsam/3rdparty/Eigen/test/sparse_solvers.cpp +++ b/gtsam/3rdparty/Eigen/test/sparse_solvers.cpp @@ -72,6 +72,15 @@ template void sparse_solvers(int rows, int cols) initSparse(density, refMat2, m2, ForceNonZeroDiag|MakeUpperTriangular, &zeroCoords, &nonzeroCoords); VERIFY_IS_APPROX(refMat2.template triangularView().solve(vec2), m2.template triangularView().solve(vec3)); + VERIFY_IS_APPROX(refMat2.conjugate().template triangularView().solve(vec2), + m2.conjugate().template triangularView().solve(vec3)); + { + SparseMatrix cm2(m2); + //Index rows, Index cols, Index nnz, Index* outerIndexPtr, Index* innerIndexPtr, Scalar* valuePtr + MappedSparseMatrix mm2(rows, cols, cm2.nonZeros(), cm2.outerIndexPtr(), cm2.innerIndexPtr(), cm2.valuePtr()); + VERIFY_IS_APPROX(refMat2.conjugate().template triangularView().solve(vec2), + mm2.conjugate().template triangularView().solve(vec3)); + } // lower - transpose initSparse(density, refMat2, m2, ForceNonZeroDiag|MakeLowerTriangular, &zeroCoords, &nonzeroCoords); diff --git a/gtsam/3rdparty/Eigen/test/sparse_vector.cpp b/gtsam/3rdparty/Eigen/test/sparse_vector.cpp index e0c281c83..09d36a51b 100644 --- a/gtsam/3rdparty/Eigen/test/sparse_vector.cpp +++ b/gtsam/3rdparty/Eigen/test/sparse_vector.cpp @@ -1,7 +1,7 @@ // This file is part of Eigen, a lightweight C++ template library // for linear algebra. // -// Copyright (C) 2008 Daniel Gomez Ferro +// Copyright (C) 2008-2011 Gael Guennebaud // // Eigen is free software; you can redistribute it and/or // modify it under the terms of the GNU Lesser General Public @@ -34,9 +34,9 @@ template void sparse_vector(int rows, int cols) typedef SparseMatrix SparseMatrixType; Scalar eps = 1e-6; - SparseMatrixType m1(rows,cols); + SparseMatrixType m1(rows,rows); SparseVectorType v1(rows), v2(rows), v3(rows); - DenseMatrix refM1 = DenseMatrix::Zero(rows, cols); + DenseMatrix refM1 = DenseMatrix::Zero(rows, rows); DenseVector refV1 = DenseVector::Random(rows), refV2 = DenseVector::Random(rows), refV3 = DenseVector::Random(rows); @@ -86,6 +86,11 @@ template void sparse_vector(int rows, int cols) VERIFY_IS_APPROX(v1.dot(v2), refV1.dot(refV2)); VERIFY_IS_APPROX(v1.dot(refV2), refV1.dot(refV2)); + VERIFY_IS_APPROX(v1.dot(m1*v2), refV1.dot(refM1*refV2)); + int i = internal::random(0,rows-1); + VERIFY_IS_APPROX(v1.dot(m1.col(i)), refV1.dot(refM1.col(i))); + + VERIFY_IS_APPROX(v1.squaredNorm(), refV1.squaredNorm()); } diff --git a/gtsam/3rdparty/Eigen/test/superlu_support.cpp b/gtsam/3rdparty/Eigen/test/superlu_support.cpp new file mode 100644 index 000000000..ad435943b --- /dev/null +++ b/gtsam/3rdparty/Eigen/test/superlu_support.cpp @@ -0,0 +1,37 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2011 Gael Guennebaud +// +// Eigen is free software; you can redistribute it and/or +// modify it under the terms of the GNU Lesser General Public +// License as published by the Free Software Foundation; either +// version 3 of the License, or (at your option) any later version. +// +// Alternatively, you can redistribute it and/or +// modify it under the terms of the GNU General Public License as +// published by the Free Software Foundation; either version 2 of +// the License, or (at your option) any later version. +// +// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY +// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the +// GNU General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public +// License and a copy of the GNU General Public License along with +// Eigen. If not, see . + +#include "sparse_solver.h" + +#include + +void test_superlu_support() +{ + SuperLU > superlu_double_colmajor; + SuperLU > > superlu_cplxdouble_colmajor; + CALL_SUBTEST_1( check_sparse_square_solving(superlu_double_colmajor) ); + CALL_SUBTEST_2( check_sparse_square_solving(superlu_cplxdouble_colmajor) ); + CALL_SUBTEST_1( check_sparse_square_determinant(superlu_double_colmajor) ); + CALL_SUBTEST_2( check_sparse_square_determinant(superlu_cplxdouble_colmajor) ); +} diff --git a/gtsam/3rdparty/Eigen/test/triangular.cpp b/gtsam/3rdparty/Eigen/test/triangular.cpp index 69decb793..4db8f8482 100644 --- a/gtsam/3rdparty/Eigen/test/triangular.cpp +++ b/gtsam/3rdparty/Eigen/test/triangular.cpp @@ -42,16 +42,8 @@ template void triangular_square(const MatrixType& m) m3(rows, cols), m4(rows, cols), r1(rows, cols), - r2(rows, cols), - mzero = MatrixType::Zero(rows, cols), - mones = MatrixType::Ones(rows, cols), - identity = Matrix - ::Identity(rows, rows), - square = Matrix - ::Random(rows, rows); - VectorType v1 = VectorType::Random(rows), - v2 = VectorType::Random(rows), - vzero = VectorType::Zero(rows); + r2(rows, cols); + VectorType v2 = VectorType::Random(rows); MatrixType m1up = m1.template triangularView(); MatrixType m2up = m2.template triangularView(); @@ -113,14 +105,14 @@ template void triangular_square(const MatrixType& m) // check M * inv(L) using in place API m4 = m3; - m3.transpose().template triangularView().solveInPlace(trm4); - VERIFY(m4.cwiseAbs().isIdentity(test_precision())); + m1.transpose().template triangularView().solveInPlace(trm4); + VERIFY_IS_APPROX(m4 * m1.template triangularView(), m3); // check M * inv(U) using in place API m3 = m1.template triangularView(); m4 = m3; m3.transpose().template triangularView().solveInPlace(trm4); - VERIFY(m4.cwiseAbs().isIdentity(test_precision())); + VERIFY_IS_APPROX(m4 * m1.template triangularView(), m3); // check solve with unit diagonal m3 = m1.template triangularView(); @@ -158,21 +150,12 @@ template void triangular_rect(const MatrixType& m) m3(rows, cols), m4(rows, cols), r1(rows, cols), - r2(rows, cols), - mzero = MatrixType::Zero(rows, cols), - mones = MatrixType::Ones(rows, cols); - RMatrixType identity = Matrix - ::Identity(rows, rows), - square = Matrix - ::Random(rows, rows); - VectorType v1 = VectorType::Random(rows), - v2 = VectorType::Random(rows), - vzero = VectorType::Zero(rows); + r2(rows, cols); MatrixType m1up = m1.template triangularView(); MatrixType m2up = m2.template triangularView(); - if (rows*cols>1) + if (rows>1 && cols>1) { VERIFY(m1up.isUpperTriangular()); VERIFY(m2up.transpose().isLowerTriangular()); @@ -237,15 +220,17 @@ template void triangular_rect(const MatrixType& m) void bug_159() { - Matrix3d m = Matrix3d::Random().triangularView(); + Matrix3d m = Matrix3d::Random().triangularView(); + EIGEN_UNUSED_VARIABLE(m) } void test_triangular() { + int maxsize = (std::min)(EIGEN_TEST_MAX_SIZE,20); for(int i = 0; i < g_repeat ; i++) { - int r = internal::random(2,20); EIGEN_UNUSED_VARIABLE(r); - int c = internal::random(2,20); EIGEN_UNUSED_VARIABLE(c); + int r = internal::random(2,maxsize); EIGEN_UNUSED_VARIABLE(r); + int c = internal::random(2,maxsize); EIGEN_UNUSED_VARIABLE(c); CALL_SUBTEST_1( triangular_square(Matrix()) ); CALL_SUBTEST_2( triangular_square(Matrix()) ); diff --git a/gtsam/3rdparty/Eigen/test/umfpack_support.cpp b/gtsam/3rdparty/Eigen/test/umfpack_support.cpp new file mode 100644 index 000000000..1922aa959 --- /dev/null +++ b/gtsam/3rdparty/Eigen/test/umfpack_support.cpp @@ -0,0 +1,46 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2011 Gael Guennebaud +// +// Eigen is free software; you can redistribute it and/or +// modify it under the terms of the GNU Lesser General Public +// License as published by the Free Software Foundation; either +// version 3 of the License, or (at your option) any later version. +// +// Alternatively, you can redistribute it and/or +// modify it under the terms of the GNU General Public License as +// published by the Free Software Foundation; either version 2 of +// the License, or (at your option) any later version. +// +// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY +// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the +// GNU General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public +// License and a copy of the GNU General Public License along with +// Eigen. If not, see . + +#include "sparse_solver.h" + +#include + +template void test_umfpack_support_T() +{ + UmfPackLU > umfpack_colmajor; + UmfPackLU > umfpack_rowmajor; + + check_sparse_square_solving(umfpack_colmajor); + check_sparse_square_solving(umfpack_rowmajor); + + check_sparse_square_determinant(umfpack_colmajor); + check_sparse_square_determinant(umfpack_rowmajor); +} + +void test_umfpack_support() +{ + CALL_SUBTEST_1(test_umfpack_support_T()); + CALL_SUBTEST_2(test_umfpack_support_T >()); +} + diff --git a/gtsam/3rdparty/Eigen/test/vectorwiseop.cpp b/gtsam/3rdparty/Eigen/test/vectorwiseop.cpp new file mode 100644 index 000000000..d3518b7ec --- /dev/null +++ b/gtsam/3rdparty/Eigen/test/vectorwiseop.cpp @@ -0,0 +1,187 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2011 Benoit Jacob +// +// Eigen is free software; you can redistribute it and/or +// modify it under the terms of the GNU Lesser General Public +// License as published by the Free Software Foundation; either +// version 3 of the License, or (at your option) any later version. +// +// Alternatively, you can redistribute it and/or +// modify it under the terms of the GNU General Public License as +// published by the Free Software Foundation; either version 2 of +// the License, or (at your option) any later version. +// +// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY +// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the +// GNU General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public +// License and a copy of the GNU General Public License along with +// Eigen. If not, see . + +#define EIGEN_NO_STATIC_ASSERT + +#include "main.h" + +template void vectorwiseop_array(const ArrayType& m) +{ + typedef typename ArrayType::Index Index; + typedef typename ArrayType::Scalar Scalar; + typedef typename NumTraits::Real RealScalar; + typedef Array ColVectorType; + typedef Array RowVectorType; + + Index rows = m.rows(); + Index cols = m.cols(); + Index r = internal::random(0, rows-1), + c = internal::random(0, cols-1); + + ArrayType m1 = ArrayType::Random(rows, cols), + m2(rows, cols), + m3(rows, cols); + + ColVectorType colvec = ColVectorType::Random(rows); + RowVectorType rowvec = RowVectorType::Random(cols); + + // test addition + + m2 = m1; + m2.colwise() += colvec; + VERIFY_IS_APPROX(m2, m1.colwise() + colvec); + VERIFY_IS_APPROX(m2.col(c), m1.col(c) + colvec); + + VERIFY_RAISES_ASSERT(m2.colwise() += colvec.transpose()); + VERIFY_RAISES_ASSERT(m1.colwise() + colvec.transpose()); + + m2 = m1; + m2.rowwise() += rowvec; + VERIFY_IS_APPROX(m2, m1.rowwise() + rowvec); + VERIFY_IS_APPROX(m2.row(r), m1.row(r) + rowvec); + + VERIFY_RAISES_ASSERT(m2.rowwise() += rowvec.transpose()); + VERIFY_RAISES_ASSERT(m1.rowwise() + rowvec.transpose()); + + // test substraction + + m2 = m1; + m2.colwise() -= colvec; + VERIFY_IS_APPROX(m2, m1.colwise() - colvec); + VERIFY_IS_APPROX(m2.col(c), m1.col(c) - colvec); + + VERIFY_RAISES_ASSERT(m2.colwise() -= colvec.transpose()); + VERIFY_RAISES_ASSERT(m1.colwise() - colvec.transpose()); + + m2 = m1; + m2.rowwise() -= rowvec; + VERIFY_IS_APPROX(m2, m1.rowwise() - rowvec); + VERIFY_IS_APPROX(m2.row(r), m1.row(r) - rowvec); + + VERIFY_RAISES_ASSERT(m2.rowwise() -= rowvec.transpose()); + VERIFY_RAISES_ASSERT(m1.rowwise() - rowvec.transpose()); + + // test multiplication + + m2 = m1; + m2.colwise() *= colvec; + VERIFY_IS_APPROX(m2, m1.colwise() * colvec); + VERIFY_IS_APPROX(m2.col(c), m1.col(c) * colvec); + + VERIFY_RAISES_ASSERT(m2.colwise() *= colvec.transpose()); + VERIFY_RAISES_ASSERT(m1.colwise() * colvec.transpose()); + + m2 = m1; + m2.rowwise() *= rowvec; + VERIFY_IS_APPROX(m2, m1.rowwise() * rowvec); + VERIFY_IS_APPROX(m2.row(r), m1.row(r) * rowvec); + + VERIFY_RAISES_ASSERT(m2.rowwise() *= rowvec.transpose()); + VERIFY_RAISES_ASSERT(m1.rowwise() * rowvec.transpose()); + + // test quotient + + m2 = m1; + m2.colwise() /= colvec; + VERIFY_IS_APPROX(m2, m1.colwise() / colvec); + VERIFY_IS_APPROX(m2.col(c), m1.col(c) / colvec); + + VERIFY_RAISES_ASSERT(m2.colwise() /= colvec.transpose()); + VERIFY_RAISES_ASSERT(m1.colwise() / colvec.transpose()); + + m2 = m1; + m2.rowwise() /= rowvec; + VERIFY_IS_APPROX(m2, m1.rowwise() / rowvec); + VERIFY_IS_APPROX(m2.row(r), m1.row(r) / rowvec); + + VERIFY_RAISES_ASSERT(m2.rowwise() /= rowvec.transpose()); + VERIFY_RAISES_ASSERT(m1.rowwise() / rowvec.transpose()); +} + +template void vectorwiseop_matrix(const MatrixType& m) +{ + typedef typename MatrixType::Index Index; + typedef typename MatrixType::Scalar Scalar; + typedef typename NumTraits::Real RealScalar; + typedef Matrix ColVectorType; + typedef Matrix RowVectorType; + + Index rows = m.rows(); + Index cols = m.cols(); + Index r = internal::random(0, rows-1), + c = internal::random(0, cols-1); + + MatrixType m1 = MatrixType::Random(rows, cols), + m2(rows, cols), + m3(rows, cols); + + ColVectorType colvec = ColVectorType::Random(rows); + RowVectorType rowvec = RowVectorType::Random(cols); + + // test addition + + m2 = m1; + m2.colwise() += colvec; + VERIFY_IS_APPROX(m2, m1.colwise() + colvec); + VERIFY_IS_APPROX(m2.col(c), m1.col(c) + colvec); + + VERIFY_RAISES_ASSERT(m2.colwise() += colvec.transpose()); + VERIFY_RAISES_ASSERT(m1.colwise() + colvec.transpose()); + + m2 = m1; + m2.rowwise() += rowvec; + VERIFY_IS_APPROX(m2, m1.rowwise() + rowvec); + VERIFY_IS_APPROX(m2.row(r), m1.row(r) + rowvec); + + VERIFY_RAISES_ASSERT(m2.rowwise() += rowvec.transpose()); + VERIFY_RAISES_ASSERT(m1.rowwise() + rowvec.transpose()); + + // test substraction + + m2 = m1; + m2.colwise() -= colvec; + VERIFY_IS_APPROX(m2, m1.colwise() - colvec); + VERIFY_IS_APPROX(m2.col(c), m1.col(c) - colvec); + + VERIFY_RAISES_ASSERT(m2.colwise() -= colvec.transpose()); + VERIFY_RAISES_ASSERT(m1.colwise() - colvec.transpose()); + + m2 = m1; + m2.rowwise() -= rowvec; + VERIFY_IS_APPROX(m2, m1.rowwise() - rowvec); + VERIFY_IS_APPROX(m2.row(r), m1.row(r) - rowvec); + + VERIFY_RAISES_ASSERT(m2.rowwise() -= rowvec.transpose()); + VERIFY_RAISES_ASSERT(m1.rowwise() - rowvec.transpose()); +} + +void test_vectorwiseop() +{ + CALL_SUBTEST_1(vectorwiseop_array(Array22cd())); + CALL_SUBTEST_2(vectorwiseop_array(Array())); + CALL_SUBTEST_3(vectorwiseop_array(ArrayXXf(3, 4))); + CALL_SUBTEST_4(vectorwiseop_matrix(Matrix4cf())); + CALL_SUBTEST_5(vectorwiseop_matrix(Matrix())); + CALL_SUBTEST_6(vectorwiseop_matrix(MatrixXd(7,2))); +} diff --git a/gtsam/3rdparty/Eigen/test/zerosized.cpp b/gtsam/3rdparty/Eigen/test/zerosized.cpp index 06e31cc09..c5d2cc6ed 100644 --- a/gtsam/3rdparty/Eigen/test/zerosized.cpp +++ b/gtsam/3rdparty/Eigen/test/zerosized.cpp @@ -62,8 +62,13 @@ void test_zerosized() zeroSizedMatrix(); zeroSizedMatrix >(); zeroSizedMatrix(); + zeroSizedMatrix >(); + zeroSizedMatrix >(); + zeroSizedMatrix >(); + zeroSizedMatrix >(); zeroSizedVector(); zeroSizedVector(); zeroSizedVector(); + zeroSizedVector >(); } diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/AdolcForward b/gtsam/3rdparty/Eigen/unsupported/Eigen/AdolcForward index 6c0a68d67..477c75378 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/AdolcForward +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/AdolcForward @@ -79,33 +79,22 @@ namespace Eigen { } // namespace Eigen -// the Adolc's type adouble is defined in the adtl namespace -// therefore, the following internal::* functions *must* be defined -// in the same namespace -namespace Eigen { +// Eigen's require a few additional functions which must be defined in the same namespace +// than the custom scalar type own namespace +namespace adtl { - namespace internal { - - inline const adtl::adouble& conj(const adtl::adouble& x) { return x; } - inline const adtl::adouble& real(const adtl::adouble& x) { return x; } - inline adtl::adouble imag(const adtl::adouble&) { return 0.; } - inline adtl::adouble abs(const adtl::adouble& x) { return adtl::fabs(x); } - inline adtl::adouble abs2(const adtl::adouble& x) { return x*x; } - - using adtl::sqrt; - using adtl::exp; - using adtl::log; - using adtl::sin; - using adtl::cos; - using adtl::pow; - - } +inline const adouble& conj(const adouble& x) { return x; } +inline const adouble& real(const adouble& x) { return x; } +inline adouble imag(const adouble&) { return 0.; } +inline adouble abs(const adouble& x) { return fabs(x); } +inline adouble abs2(const adouble& x) { return x*x; } } namespace Eigen { template<> struct NumTraits + : NumTraits { typedef adtl::adouble Real; typedef adtl::adouble NonInteger; diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/BVH b/gtsam/3rdparty/Eigen/unsupported/Eigen/BVH index f307da2f7..d50b2bdab 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/BVH +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/BVH @@ -97,8 +97,9 @@ namespace Eigen { * The following is a simple but complete example for how to use the BVH to accelerate the search for a closest red-blue point pair: * \include BVH_Example.cpp * Output: \verbinclude BVH_Example.out - */ +} + //@{ #include "src/BVH/BVAlgorithms.h" @@ -106,6 +107,4 @@ namespace Eigen { //@} -} - #endif // EIGEN_BVH_MODULE_H diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/CMakeLists.txt b/gtsam/3rdparty/Eigen/unsupported/Eigen/CMakeLists.txt index 219ec8ead..e961e72c5 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/CMakeLists.txt +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/CMakeLists.txt @@ -1,6 +1,6 @@ set(Eigen_HEADERS AdolcForward BVH IterativeSolvers MatrixFunctions MoreVectorization AutoDiff AlignedVector3 Polynomials - CholmodSupport FFT NonLinearOptimization SparseExtra SuperLUSupport UmfPackSupport IterativeSolvers - NumericalDiff Skyline MPRealSupport OpenGLSupport + FFT NonLinearOptimization SparseExtra IterativeSolvers + NumericalDiff Skyline MPRealSupport OpenGLSupport KroneckerProduct Splines ) install(FILES diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/CholmodSupport b/gtsam/3rdparty/Eigen/unsupported/Eigen/CholmodSupport deleted file mode 100644 index 8a4a130c3..000000000 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/CholmodSupport +++ /dev/null @@ -1,33 +0,0 @@ -#ifndef EIGEN_CHOLMODSUPPORT_MODULE_H -#define EIGEN_CHOLMODSUPPORT_MODULE_H - -#include "SparseExtra" - -#include "../../Eigen/src/Core/util/DisableStupidWarnings.h" - -extern "C" { - #include -} - -namespace Eigen { - -/** \ingroup Unsupported_modules - * \defgroup CholmodSupport_Module Cholmod Support module - * - * - * \code - * #include - * \endcode - */ - -struct Cholmod {}; -#include "src/SparseExtra/CholmodSupportLegacy.h" -#include "src/SparseExtra/CholmodSupport.h" - - -} // namespace Eigen - -#include "../../Eigen/src/Core/util/ReenableStupidWarnings.h" - -#endif // EIGEN_CHOLMODSUPPORT_MODULE_H - diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/FFT b/gtsam/3rdparty/Eigen/unsupported/Eigen/FFT index c56bd63d6..e2ec71307 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/FFT +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/FFT @@ -86,23 +86,23 @@ #ifdef EIGEN_FFTW_DEFAULT // FFTW: faster, GPL -- incompatible with Eigen in LGPL form, bigger code size # include +# include "src/FFT/ei_fftw_impl.h" namespace Eigen { -# include "src/FFT/ei_fftw_impl.h" //template typedef struct internal::fftw_impl default_fft_impl; this does not work template struct default_fft_impl : public internal::fftw_impl {}; } #elif defined EIGEN_MKL_DEFAULT // TODO // intel Math Kernel Library: fastest, commercial -- may be incompatible with Eigen in GPL form +# include "src/FFT/ei_imklfft_impl.h" namespace Eigen { -# include "src/FFT/ei_imklfft_impl.h" template struct default_fft_impl : public internal::imklfft_impl {}; } #else // internal::kissfft_impl: small, free, reasonably efficient default, derived from kissfft // +# include "src/FFT/ei_kissfft_impl.h" namespace Eigen { -# include "src/FFT/ei_kissfft_impl.h" template struct default_fft_impl : public internal::kissfft_impl {}; } diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/IterativeSolvers b/gtsam/3rdparty/Eigen/unsupported/Eigen/IterativeSolvers index bf1a9460b..4645153aa 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/IterativeSolvers +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/IterativeSolvers @@ -25,27 +25,31 @@ #ifndef EIGEN_ITERATIVE_SOLVERS_MODULE_H #define EIGEN_ITERATIVE_SOLVERS_MODULE_H -#include - -namespace Eigen { +#include /** \ingroup Unsupported_modules * \defgroup IterativeSolvers_Module Iterative solvers module * This module aims to provide various iterative linear and non linear solver algorithms. * It currently provides: * - a constrained conjugate gradient - * + * - a Householder GMRES implementation * \code * #include * \endcode */ //@{ +#include "../../Eigen/src/misc/Solve.h" +#include "../../Eigen/src/misc/SparseSolve.h" + #include "src/IterativeSolvers/IterationController.h" #include "src/IterativeSolvers/ConstrainedConjGrad.h" +#include "src/IterativeSolvers/IncompleteLU.h" +#include "../../Eigen/Jacobi" +#include "../../Eigen/Householder" +#include "src/IterativeSolvers/GMRES.h" +//#include "src/IterativeSolvers/SSORPreconditioner.h" //@} -} - #endif // EIGEN_ITERATIVE_SOLVERS_MODULE_H diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/KroneckerProduct b/gtsam/3rdparty/Eigen/unsupported/Eigen/KroneckerProduct new file mode 100644 index 000000000..796e386ad --- /dev/null +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/KroneckerProduct @@ -0,0 +1,26 @@ +#ifndef EIGEN_KRONECKER_PRODUCT_MODULE_H +#define EIGEN_KRONECKER_PRODUCT_MODULE_H + +#include "../../Eigen/Core" + +#include "../../Eigen/src/Core/util/DisableStupidWarnings.h" + +namespace Eigen { + +/** \ingroup Unsupported_modules + * \defgroup KroneckerProduct_Module KroneckerProduct module + * + * This module contains an experimental Kronecker product implementation. + * + * \code + * #include + * \endcode + */ + +} // namespace Eigen + +#include "src/KroneckerProduct/KroneckerTensorProduct.h" + +#include "../../Eigen/src/Core/util/ReenableStupidWarnings.h" + +#endif // EIGEN_KRONECKER_PRODUCT_MODULE_H diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/MPRealSupport b/gtsam/3rdparty/Eigen/unsupported/Eigen/MPRealSupport index 8f2396353..b5fe5e404 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/MPRealSupport +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/MPRealSupport @@ -30,11 +30,12 @@ #ifndef EIGEN_MPREALSUPPORT_MODULE_H #define EIGEN_MPREALSUPPORT_MODULE_H +#include #include #include namespace Eigen { - + /** \ingroup Unsupported_modules * \defgroup MPRealSupport_Module MPFRC++ Support module * @@ -43,7 +44,7 @@ namespace Eigen { * \endcode * * This module provides support for multi precision floating point numbers - * via the MPFR C++ + * via the MPFR C++ * library which itself is built upon MPFR/GMP. * * You can find a copy of MPFR C++ that is known to be compatible in the unsupported/test/mpreal folder. @@ -52,7 +53,7 @@ namespace Eigen { * \code #include -#include +#include #include using namespace mpfr; using namespace Eigen; @@ -106,7 +107,7 @@ int main() } }; - namespace internal { +namespace internal { template<> mpfr::mpreal random() { @@ -146,8 +147,17 @@ int main() { return a <= b || isApprox(a, b, prec); } + + template<> inline long double cast(const mpfr::mpreal& x) + { return x.toLDouble(); } + template<> inline double cast(const mpfr::mpreal& x) + { return x.toDouble(); } + template<> inline long cast(const mpfr::mpreal& x) + { return x.toLong(); } + template<> inline int cast(const mpfr::mpreal& x) + { return int(x.toLong()); } - } // end namespace internal +} // end namespace internal } #endif // EIGEN_MPREALSUPPORT_MODULE_H diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/MatrixFunctions b/gtsam/3rdparty/Eigen/unsupported/Eigen/MatrixFunctions index d39c49e53..13eda8fc8 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/MatrixFunctions +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/MatrixFunctions @@ -25,6 +25,7 @@ #ifndef EIGEN_MATRIX_FUNCTIONS #define EIGEN_MATRIX_FUNCTIONS +#include #include #include #include @@ -33,8 +34,6 @@ #include #include -namespace Eigen { - /** \ingroup Unsupported_modules * \defgroup MatrixFunctions_Module Matrix functions module * \brief This module aims to provide various methods for the computation of @@ -50,9 +49,11 @@ namespace Eigen { * - \ref matrixbase_cos "MatrixBase::cos()", for computing the matrix cosine * - \ref matrixbase_cosh "MatrixBase::cosh()", for computing the matrix hyperbolic cosine * - \ref matrixbase_exp "MatrixBase::exp()", for computing the matrix exponential + * - \ref matrixbase_log "MatrixBase::log()", for computing the matrix logarithm * - \ref matrixbase_matrixfunction "MatrixBase::matrixFunction()", for computing general matrix functions * - \ref matrixbase_sin "MatrixBase::sin()", for computing the matrix sine * - \ref matrixbase_sinh "MatrixBase::sinh()", for computing the matrix hyperbolic sine + * - \ref matrixbase_sqrt "MatrixBase::sqrt()", for computing the matrix square root * * These methods are the main entry points to this module. * @@ -69,6 +70,8 @@ namespace Eigen { #include "src/MatrixFunctions/MatrixExponential.h" #include "src/MatrixFunctions/MatrixFunction.h" +#include "src/MatrixFunctions/MatrixSquareRoot.h" +#include "src/MatrixFunctions/MatrixLogarithm.h" @@ -166,10 +169,67 @@ the z-axis. \include MatrixExponential.cpp Output: \verbinclude MatrixExponential.out -\note \p M has to be a matrix of \c float, \c double, -\c complex or \c complex . +\note \p M has to be a matrix of \c float, \c double, \c long double +\c complex, \c complex, or \c complex . +\section matrixbase_log MatrixBase::log() + +Compute the matrix logarithm. + +\code +const MatrixLogarithmReturnValue MatrixBase::log() const +\endcode + +\param[in] M invertible matrix whose logarithm is to be computed. +\returns expression representing the matrix logarithm root of \p M. + +The matrix logarithm of \f$ M \f$ is a matrix \f$ X \f$ such that +\f$ \exp(X) = M \f$ where exp denotes the matrix exponential. As for +the scalar logarithm, the equation \f$ \exp(X) = M \f$ may have +multiple solutions; this function returns a matrix whose eigenvalues +have imaginary part in the interval \f$ (-\pi,\pi] \f$. + +In the real case, the matrix \f$ M \f$ should be invertible and +it should have no eigenvalues which are real and negative (pairs of +complex conjugate eigenvalues are allowed). In the complex case, it +only needs to be invertible. + +This function computes the matrix logarithm using the Schur-Parlett +algorithm as implemented by MatrixBase::matrixFunction(). The +logarithm of an atomic block is computed by MatrixLogarithmAtomic, +which uses direct computation for 1-by-1 and 2-by-2 blocks and an +inverse scaling-and-squaring algorithm for bigger blocks, with the +square roots computed by MatrixBase::sqrt(). + +Details of the algorithm can be found in Section 11.6.2 of: +Nicholas J. Higham, +Functions of Matrices: Theory and Computation, +SIAM 2008. ISBN 978-0-898716-46-7. + +Example: The following program checks that +\f[ \log \left[ \begin{array}{ccc} + \frac12\sqrt2 & -\frac12\sqrt2 & 0 \\ + \frac12\sqrt2 & \frac12\sqrt2 & 0 \\ + 0 & 0 & 1 + \end{array} \right] = \left[ \begin{array}{ccc} + 0 & \frac14\pi & 0 \\ + -\frac14\pi & 0 & 0 \\ + 0 & 0 & 0 + \end{array} \right]. \f] +This corresponds to a rotation of \f$ \frac14\pi \f$ radians around +the z-axis. This is the inverse of the example used in the +documentation of \ref matrixbase_exp "exp()". + +\include MatrixLogarithm.cpp +Output: \verbinclude MatrixLogarithm.out + +\note \p M has to be a matrix of \c float, \c double, \c long double +\c complex, \c complex, or \c complex . + +\sa MatrixBase::exp(), MatrixBase::matrixFunction(), + class MatrixLogarithmAtomic, MatrixBase::sqrt(). + \section matrixbase_matrixfunction MatrixBase::matrixFunction() @@ -245,7 +305,7 @@ Output: \verbinclude MatrixSine.out -\section matrixbase_sinh const MatrixBase::sinh() +\section matrixbase_sinh MatrixBase::sinh() Compute the matrix hyperbolic sine. @@ -261,9 +321,75 @@ This function calls \ref matrixbase_matrixfunction "matrixFunction()" with StdSt Example: \include MatrixSinh.cpp Output: \verbinclude MatrixSinh.out -*/ -} +\section matrixbase_sqrt MatrixBase::sqrt() + +Compute the matrix square root. + +\code +const MatrixSquareRootReturnValue MatrixBase::sqrt() const +\endcode + +\param[in] M invertible matrix whose square root is to be computed. +\returns expression representing the matrix square root of \p M. + +The matrix square root of \f$ M \f$ is the matrix \f$ M^{1/2} \f$ +whose square is the original matrix; so if \f$ S = M^{1/2} \f$ then +\f$ S^2 = M \f$. + +In the real case, the matrix \f$ M \f$ should be invertible and +it should have no eigenvalues which are real and negative (pairs of +complex conjugate eigenvalues are allowed). In that case, the matrix +has a square root which is also real, and this is the square root +computed by this function. + +The matrix square root is computed by first reducing the matrix to +quasi-triangular form with the real Schur decomposition. The square +root of the quasi-triangular matrix can then be computed directly. The +cost is approximately \f$ 25 n^3 \f$ real flops for the real Schur +decomposition and \f$ 3\frac13 n^3 \f$ real flops for the remainder +(though the computation time in practice is likely more than this +indicates). + +Details of the algorithm can be found in: Nicholas J. Highan, +"Computing real square roots of a real matrix", Linear Algebra +Appl., 88/89:405–430, 1987. + +If the matrix is positive-definite symmetric, then the square +root is also positive-definite symmetric. In this case, it is best to +use SelfAdjointEigenSolver::operatorSqrt() to compute it. + +In the complex case, the matrix \f$ M \f$ should be invertible; +this is a restriction of the algorithm. The square root computed by +this algorithm is the one whose eigenvalues have an argument in the +interval \f$ (-\frac12\pi, \frac12\pi] \f$. This is the usual branch +cut. + +The computation is the same as in the real case, except that the +complex Schur decomposition is used to reduce the matrix to a +triangular matrix. The theoretical cost is the same. Details are in: +Åke Björck and Sven Hammarling, "A Schur method for the +square root of a matrix", Linear Algebra Appl., +52/53:127–140, 1983. + +Example: The following program checks that the square root of +\f[ \left[ \begin{array}{cc} + \cos(\frac13\pi) & -\sin(\frac13\pi) \\ + \sin(\frac13\pi) & \cos(\frac13\pi) + \end{array} \right], \f] +corresponding to a rotation over 60 degrees, is a rotation over 30 degrees: +\f[ \left[ \begin{array}{cc} + \cos(\frac16\pi) & -\sin(\frac16\pi) \\ + \sin(\frac16\pi) & \cos(\frac16\pi) + \end{array} \right]. \f] + +\include MatrixSquareRoot.cpp +Output: \verbinclude MatrixSquareRoot.out + +\sa class RealSchur, class ComplexSchur, class MatrixSquareRoot, + SelfAdjointEigenSolver::operatorSqrt(). + +*/ #endif // EIGEN_MATRIX_FUNCTIONS diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/MoreVectorization b/gtsam/3rdparty/Eigen/unsupported/Eigen/MoreVectorization index 26a01cd29..9f0a39f75 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/MoreVectorization +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/MoreVectorization @@ -9,8 +9,8 @@ namespace Eigen { * \defgroup MoreVectorization More vectorization module */ -#include "src/MoreVectorization/MathFunctions.h" - } +#include "src/MoreVectorization/MathFunctions.h" + #endif // EIGEN_MOREVECTORIZATION_MODULE_H diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/NonLinearOptimization b/gtsam/3rdparty/Eigen/unsupported/Eigen/NonLinearOptimization index e19db33cc..0a384d649 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/NonLinearOptimization +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/NonLinearOptimization @@ -32,8 +32,6 @@ #include #include -namespace Eigen { - /** \ingroup Unsupported_modules * \defgroup NonLinearOptimization_Module Non linear optimization module * @@ -147,8 +145,5 @@ namespace Eigen { #include "src/NonLinearOptimization/HybridNonLinearSolver.h" #include "src/NonLinearOptimization/LevenbergMarquardt.h" -} - - #endif // EIGEN_NONLINEAROPTIMIZATION_MODULE diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/NumericalDiff b/gtsam/3rdparty/Eigen/unsupported/Eigen/NumericalDiff index 2a59c14d5..eebee076d 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/NumericalDiff +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/NumericalDiff @@ -59,12 +59,13 @@ namespace Eigen { * package. * */ +} + //@{ #include "src/NumericalDiff/NumericalDiff.h" //@} -} #endif // EIGEN_NUMERICALDIFF_MODULE diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/Polynomials b/gtsam/3rdparty/Eigen/unsupported/Eigen/Polynomials index 2c2f3e100..fa58b006d 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/Polynomials +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/Polynomials @@ -16,8 +16,6 @@ #undef EIGEN_HIDE_HEAVY_CODE #endif -namespace Eigen { - /** \ingroup Unsupported_modules * \defgroup Polynomials_Module Polynomials module * @@ -129,8 +127,6 @@ namespace Eigen { Output: \verbinclude PolynomialSolver1.out */ -} // namespace Eigen - #include #endif // EIGEN_POLYNOMIALS_MODULE_H diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/Skyline b/gtsam/3rdparty/Eigen/unsupported/Eigen/Skyline index 5247b2eab..c9823f358 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/Skyline +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/Skyline @@ -11,15 +11,13 @@ #include #include -namespace Eigen { - - /** \ingroup Unsupported_modules - * \defgroup Skyline_Module Skyline module - * - * - * - * - */ +/** \ingroup Unsupported_modules + * \defgroup Skyline_Module Skyline module + * + * + * + * + */ #include "src/Skyline/SkylineUtil.h" #include "src/Skyline/SkylineMatrixBase.h" @@ -28,8 +26,6 @@ namespace Eigen { #include "src/Skyline/SkylineInplaceLU.h" #include "src/Skyline/SkylineProduct.h" -} // namespace Eigen - #include "Eigen/src/Core/util/ReenableStupidWarnings.h" #endif // EIGEN_SKYLINE_MODULE_H diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/SparseExtra b/gtsam/3rdparty/Eigen/unsupported/Eigen/SparseExtra index 7bab7c72b..340c34736 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/SparseExtra +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/SparseExtra @@ -10,13 +10,13 @@ #include #include #include +#include +#include #ifdef EIGEN_GOOGLEHASH_SUPPORT #include #endif -namespace Eigen { - /** \ingroup Unsupported_modules * \defgroup SparseExtra_Module SparseExtra module * @@ -27,42 +27,20 @@ namespace Eigen { * \endcode */ -struct DefaultBackend {}; - - -// solver flags -enum { - CompleteFactorization = 0x0000, // the default - IncompleteFactorization = 0x0001, - MemoryEfficient = 0x0002, - - // For LLT Cholesky: - SupernodalMultifrontal = 0x0010, - SupernodalLeftLooking = 0x0020, - - // Ordering methods: - NaturalOrdering = 0x0100, // the default - MinimumDegree_AT_PLUS_A = 0x0200, - MinimumDegree_ATA = 0x0300, - ColApproxMinimumDegree = 0x0400, - Metis = 0x0500, - Scotch = 0x0600, - Chaco = 0x0700, - OrderingMask = 0x0f00 -}; #include "../../Eigen/src/misc/Solve.h" +#include "../../Eigen/src/misc/SparseSolve.h" +#include "src/SparseExtra/DynamicSparseMatrix.h" +#include "src/SparseExtra/BlockOfDynamicSparseMatrix.h" #include "src/SparseExtra/RandomSetter.h" -#include "src/SparseExtra/Solve.h" -#include "src/SparseExtra/Amd.h" -#include "src/SparseExtra/SimplicialCholesky.h" -#include "src/SparseExtra/SparseLLT.h" -#include "src/SparseExtra/SparseLDLTLegacy.h" -#include "src/SparseExtra/SparseLU.h" +#include "src/SparseExtra/MarketIO.h" -} // namespace Eigen +#if !defined(_WIN32) +#include +#include "src/SparseExtra/MatrixMarketIterator.h" +#endif #include "../../Eigen/src/Core/util/ReenableStupidWarnings.h" diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/EigenvaluesCommon.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/Splines similarity index 63% rename from gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/EigenvaluesCommon.h rename to gtsam/3rdparty/Eigen/unsupported/Eigen/Splines index 749bea795..33769b0e4 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Eigenvalues/EigenvaluesCommon.h +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/Splines @@ -1,7 +1,7 @@ // This file is part of Eigen, a lightweight C++ template library // for linear algebra. // -// Copyright (C) 2010 Jitse Niesen +// Copyright (C) 20010-2011 Hauke Heibel // // Eigen is free software; you can redistribute it and/or // modify it under the terms of the GNU Lesser General Public @@ -22,10 +22,25 @@ // License and a copy of the GNU General Public License along with // Eigen. If not, see . -#ifndef EIGEN_EIGENVALUES_COMMON_H -#define EIGEN_EIGENVALUES_COMMON_H +#ifndef EIGEN_SPLINES_MODULE_H +#define EIGEN_SPLINES_MODULE_H +namespace Eigen +{ +/** \ingroup Unsupported_modules + * \defgroup Splines_Module Spline and spline fitting module + * + * This module provides a simple multi-dimensional spline class while + * offering most basic functionality to fit a spline to point sets. + * + * \code + * #include + * \endcode + */ +} +#include "src/Splines/SplineFwd.h" +#include "src/Splines/Spline.h" +#include "src/Splines/SplineFitting.h" -#endif // EIGEN_EIGENVALUES_COMMON_H - +#endif // EIGEN_SPLINES_MODULE_H diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/SuperLUSupport b/gtsam/3rdparty/Eigen/unsupported/Eigen/SuperLUSupport deleted file mode 100644 index 89cb649b2..000000000 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/SuperLUSupport +++ /dev/null @@ -1,35 +0,0 @@ -#ifndef EIGEN_SUPERLUSUPPORT_MODULE_H -#define EIGEN_SUPERLUSUPPORT_MODULE_H - -#include "SparseExtra" - -#include "../../Eigen/src/Core/util/DisableStupidWarnings.h" - -typedef int int_t; -#include -#include -#include - -namespace Eigen { struct SluMatrix; } - -namespace Eigen { - -/** \ingroup Unsupported_modules - * \defgroup SuperLUSupport_Module Super LU support - * - * - * - * \code - * #include - * \endcode - */ - -struct SuperLU {}; - -#include "src/SparseExtra/SuperLUSupport.h" - -} // namespace Eigen - -#include "../../Eigen/src/Core/util/ReenableStupidWarnings.h" - -#endif // EIGEN_SUPERLUSUPPORT_MODULE_H diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/UmfPackSupport b/gtsam/3rdparty/Eigen/unsupported/Eigen/UmfPackSupport deleted file mode 100644 index c8b1e7c1f..000000000 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/UmfPackSupport +++ /dev/null @@ -1,33 +0,0 @@ -#ifndef EIGEN_UMFPACKSUPPORT_MODULE_H -#define EIGEN_UMFPACKSUPPORT_MODULE_H - -#include "SparseExtra" - -#include "../../Eigen/src/Core/util/DisableStupidWarnings.h" - -extern "C" { -#include -} - -namespace Eigen { - -/** \ingroup Unsupported_modules - * \defgroup UmfPackSupport_Module UmfPack support module - * - * - * - * - * \code - * #include - * \endcode - */ - -struct UmfPack {}; - -#include "src/SparseExtra/UmfPackSupport.h" - -} // namespace Eigen - -#include "../../Eigen/src/Core/util/ReenableStupidWarnings.h" - -#endif // EIGEN_UMFPACKSUPPORT_MODULE_H diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/AutoDiff/AutoDiffJacobian.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/AutoDiff/AutoDiffJacobian.h index 4fe168a88..e5442a5ef 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/AutoDiff/AutoDiffJacobian.h +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/AutoDiff/AutoDiffJacobian.h @@ -40,7 +40,7 @@ public: template AutoDiffJacobian(const T0& a0, const T1& a1) : Functor(a0, a1) {} template - AutoDiffJacobian(const T0& a0, const T1& a1, const T1& a2) : Functor(a0, a1, a2) {} + AutoDiffJacobian(const T0& a0, const T1& a1, const T2& a2) : Functor(a0, a1, a2) {} enum { InputsAtCompileTime = Functor::InputsAtCompileTime, diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/AutoDiff/AutoDiffScalar.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/AutoDiff/AutoDiffScalar.h index 7517035d9..70d3222f5 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/AutoDiff/AutoDiffScalar.h +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/AutoDiff/AutoDiffScalar.h @@ -101,7 +101,7 @@ class AutoDiffScalar /** Conversion from a scalar constant to an active scalar. * The derivatives are set to zero. */ - explicit AutoDiffScalar(const Real& value) + /*explicit*/ AutoDiffScalar(const Real& value) : m_value(value) { if(m_derivatives.size()>0) @@ -151,6 +151,27 @@ class AutoDiffScalar inline const DerType& derivatives() const { return m_derivatives; } inline DerType& derivatives() { return m_derivatives; } + inline bool operator< (const Scalar& other) const { return m_value < other; } + inline bool operator<=(const Scalar& other) const { return m_value <= other; } + inline bool operator> (const Scalar& other) const { return m_value > other; } + inline bool operator>=(const Scalar& other) const { return m_value >= other; } + inline bool operator==(const Scalar& other) const { return m_value == other; } + inline bool operator!=(const Scalar& other) const { return m_value != other; } + + friend inline bool operator< (const Scalar& a, const AutoDiffScalar& b) { return a < b.value(); } + friend inline bool operator<=(const Scalar& a, const AutoDiffScalar& b) { return a <= b.value(); } + friend inline bool operator> (const Scalar& a, const AutoDiffScalar& b) { return a > b.value(); } + friend inline bool operator>=(const Scalar& a, const AutoDiffScalar& b) { return a >= b.value(); } + friend inline bool operator==(const Scalar& a, const AutoDiffScalar& b) { return a == b.value(); } + friend inline bool operator!=(const Scalar& a, const AutoDiffScalar& b) { return a != b.value(); } + + template inline bool operator< (const AutoDiffScalar& b) const { return m_value < b.value(); } + template inline bool operator<=(const AutoDiffScalar& b) const { return m_value <= b.value(); } + template inline bool operator> (const AutoDiffScalar& b) const { return m_value > b.value(); } + template inline bool operator>=(const AutoDiffScalar& b) const { return m_value >= b.value(); } + template inline bool operator==(const AutoDiffScalar& b) const { return m_value == b.value(); } + template inline bool operator!=(const AutoDiffScalar& b) const { return m_value != b.value(); } + inline const AutoDiffScalar operator+(const Scalar& other) const { return AutoDiffScalar(m_value + other, m_derivatives); @@ -195,6 +216,24 @@ class AutoDiffScalar return *this; } + inline const AutoDiffScalar operator-(const Scalar& b) const + { + return AutoDiffScalar(m_value - b, m_derivatives); + } + + friend inline const AutoDiffScalar, const DerType> > + operator-(const Scalar& a, const AutoDiffScalar& b) + { + return AutoDiffScalar, const DerType> > + (a - b.value(), -b.derivatives()); + } + + inline AutoDiffScalar& operator-=(const Scalar& other) + { + value() -= other; + return *this; + } + template inline const AutoDiffScalar, const DerType,const typename internal::remove_all::type> > operator-(const AutoDiffScalar& other) const @@ -213,7 +252,6 @@ class AutoDiffScalar return *this; } - template inline const AutoDiffScalar, const DerType> > operator-() const { @@ -267,7 +305,7 @@ class AutoDiffScalar { return AutoDiffScalar, const DerType> >( other / a.value(), - a.derivatives() * (-Scalar(1)/other)); + a.derivatives() * (Scalar(-other) / (a.value()*a.value()))); } // inline const AutoDiffScalar, DerType>::Type > @@ -330,6 +368,19 @@ class AutoDiffScalar return *this; } + inline AutoDiffScalar& operator/=(const Scalar& other) + { + *this = *this / other; + return *this; + } + + template + inline AutoDiffScalar& operator/=(const AutoDiffScalar& other) + { + *this = *this / other; + return *this; + } + protected: Scalar m_value; DerType m_derivatives; @@ -463,16 +514,14 @@ template ReturnType; }; -template -struct scalar_product_traits,T> +template +struct scalar_product_traits,typename DerType::Scalar> { typedef AutoDiffScalar ReturnType; }; } // end namespace internal -} // end namespace Eigen - #define EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(FUNC,CODE) \ template \ inline const Eigen::AutoDiffScalar::type>::Scalar>, const typename Eigen::internal::remove_all::type> > \ @@ -483,87 +532,109 @@ struct scalar_product_traits,T> CODE; \ } -namespace std -{ - EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(abs, - return ReturnType(std::abs(x.value()), x.derivatives() * (sign(x.value())));) - - EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(sqrt, - Scalar sqrtx = std::sqrt(x.value()); - return ReturnType(sqrtx,x.derivatives() * (Scalar(0.5) / sqrtx));) - - EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(cos, - return ReturnType(std::cos(x.value()), x.derivatives() * (-std::sin(x.value())));) - - EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(sin, - return ReturnType(std::sin(x.value()),x.derivatives() * std::cos(x.value()));) - - EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(exp, - Scalar expx = std::exp(x.value()); - return ReturnType(expx,x.derivatives() * expx);) - - EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(log, - return ReturnType(std::log(x.value()),x.derivatives() * (Scalar(1)/x.value()));) - - template - inline const Eigen::AutoDiffScalar::Scalar>, const DerType> > - pow(const Eigen::AutoDiffScalar& x, typename Eigen::internal::traits::Scalar y) - { - using namespace Eigen; - typedef typename Eigen::internal::traits::Scalar Scalar; - return AutoDiffScalar, const DerType> >( - std::pow(x.value(),y), - x.derivatives() * (y * std::pow(x.value(),y-1))); - } - -} - -namespace Eigen { - -namespace internal { - template inline const AutoDiffScalar& conj(const AutoDiffScalar& x) { return x; } template inline const AutoDiffScalar& real(const AutoDiffScalar& x) { return x; } template inline typename DerType::Scalar imag(const AutoDiffScalar&) { return 0.; } +template +inline AutoDiffScalar (min)(const AutoDiffScalar& x, const T& y) { return (x <= y ? x : y); } +template +inline AutoDiffScalar (max)(const AutoDiffScalar& x, const T& y) { return (x >= y ? x : y); } +template +inline AutoDiffScalar (min)(const T& x, const AutoDiffScalar& y) { return (x < y ? x : y); } +template +inline AutoDiffScalar (max)(const T& x, const AutoDiffScalar& y) { return (x > y ? x : y); } +#define sign(x) x >= 0 ? 1 : -1 // required for abs function below + EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(abs, + using std::abs; return ReturnType(abs(x.value()), x.derivatives() * (sign(x.value())));) EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(abs2, + using internal::abs2; return ReturnType(abs2(x.value()), x.derivatives() * (Scalar(2)*x.value()));) EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(sqrt, + using std::sqrt; Scalar sqrtx = sqrt(x.value()); return ReturnType(sqrtx,x.derivatives() * (Scalar(0.5) / sqrtx));) EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(cos, + using std::cos; + using std::sin; return ReturnType(cos(x.value()), x.derivatives() * (-sin(x.value())));) EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(sin, + using std::sin; + using std::cos; return ReturnType(sin(x.value()),x.derivatives() * cos(x.value()));) EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(exp, + using std::exp; Scalar expx = exp(x.value()); return ReturnType(expx,x.derivatives() * expx);) EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(log, + using std::log; return ReturnType(log(x.value()),x.derivatives() * (Scalar(1)/x.value()));) template -inline const AutoDiffScalar::Scalar>, DerType> > -pow(const AutoDiffScalar& x, typename traits::Scalar y) -{ return std::pow(x,y);} +inline const Eigen::AutoDiffScalar::Scalar>, const DerType> > +pow(const Eigen::AutoDiffScalar& x, typename Eigen::internal::traits::Scalar y) +{ + using namespace Eigen; + typedef typename Eigen::internal::traits::Scalar Scalar; + return AutoDiffScalar, const DerType> >( + std::pow(x.value(),y), + x.derivatives() * (y * std::pow(x.value(),y-1))); +} -} // end namespace internal + +template +inline const AutoDiffScalar::Scalar,Dynamic,1> > +atan2(const AutoDiffScalar& a, const AutoDiffScalar& b) +{ + using std::atan2; + using std::max; + typedef typename internal::traits::Scalar Scalar; + typedef AutoDiffScalar > PlainADS; + PlainADS ret; + ret.value() = atan2(a.value(), b.value()); + + Scalar tmp2 = a.value() * a.value(); + Scalar tmp3 = b.value() * b.value(); + Scalar tmp4 = tmp3/(tmp2+tmp3); + + if (tmp4!=0) + ret.derivatives() = (a.derivatives() * b.value() - a.value() * b.derivatives()) * (tmp2+tmp3); + + return ret; +} + +EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(tan, + using std::tan; + using std::cos; + return ReturnType(tan(x.value()),x.derivatives() * (Scalar(1)/internal::abs2(cos(x.value()))));) + +EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(asin, + using std::sqrt; + using std::asin; + return ReturnType(asin(x.value()),x.derivatives() * (Scalar(1)/sqrt(1-internal::abs2(x.value()))));) + +EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY(acos, + using std::sqrt; + using std::acos; + return ReturnType(acos(x.value()),x.derivatives() * (Scalar(-1)/sqrt(1-internal::abs2(x.value()))));) #undef EIGEN_AUTODIFF_DECLARE_GLOBAL_UNARY template struct NumTraits > : NumTraits< typename NumTraits::Real > { + typedef AutoDiffScalar::Real,DerType::RowsAtCompileTime,DerType::ColsAtCompileTime> > Real; typedef AutoDiffScalar NonInteger; typedef AutoDiffScalar& Nested; enum{ diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/BVH/BVAlgorithms.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/BVH/BVAlgorithms.h index d65a97740..6cba656ff 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/BVH/BVAlgorithms.h +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/BVH/BVAlgorithms.h @@ -25,6 +25,8 @@ #ifndef EIGEN_BVALGORITHMS_H #define EIGEN_BVALGORITHMS_H +namespace Eigen { + namespace internal { #ifndef EIGEN_PARSED_BY_DOXYGEN @@ -301,4 +303,6 @@ typename Minimizer::Scalar BVMinimize(const BVH1 &tree1, const BVH2 &tree2, Mini return minimum; } +} // end namespace Eigen + #endif // EIGEN_BVALGORITHMS_H diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/BVH/KdBVH.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/BVH/KdBVH.h index 028b4811e..13a154d5c 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/BVH/KdBVH.h +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/BVH/KdBVH.h @@ -25,6 +25,8 @@ #ifndef KDBVH_H_INCLUDED #define KDBVH_H_INCLUDED +namespace Eigen { + namespace internal { //internal pair class for the BVH--used instead of std::pair because of alignment @@ -69,7 +71,7 @@ struct get_boxes_helper { * * \param _Scalar The underlying scalar type of the bounding boxes * \param _Dim The dimension of the space in which the hierarchy lives - * \param _Object The object type that lives in the hierarchy. It must have value semantics. Either internal::bounding_box(_Object) must + * \param _Object The object type that lives in the hierarchy. It must have value semantics. Either bounding_box(_Object) must * be defined and return an AlignedBox<_Scalar, _Dim> or bounding boxes must be provided to the tree initializer. * * This class provides a simple (as opposed to optimized) implementation of a bounding volume hierarchy analogous to a Kd-tree. @@ -92,14 +94,14 @@ public: KdBVH() {} - /** Given an iterator range over \a Object references, constructs the BVH. Requires that internal::bounding_box(Object) return a Volume. */ + /** Given an iterator range over \a Object references, constructs the BVH. Requires that bounding_box(Object) return a Volume. */ template KdBVH(Iter begin, Iter end) { init(begin, end, 0, 0); } //int is recognized by init as not being an iterator type /** Given an iterator range over \a Object references and an iterator range over their bounding boxes, constructs the BVH */ template KdBVH(OIter begin, OIter end, BIter boxBegin, BIter boxEnd) { init(begin, end, boxBegin, boxEnd); } /** Given an iterator range over \a Object references, constructs the BVH, overwriting whatever is in there currently. - * Requires that internal::bounding_box(Object) return a Volume. */ + * Requires that bounding_box(Object) return a Volume. */ template void init(Iter begin, Iter end) { init(begin, end, 0, 0); } /** Given an iterator range over \a Object references and an iterator range over their bounding boxes, @@ -230,4 +232,6 @@ private: ObjectList objects; }; +} // end namespace Eigen + #endif //KDBVH_H_INCLUDED diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/CMakeLists.txt b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/CMakeLists.txt index cd442cefa..f3180b52b 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/CMakeLists.txt +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/CMakeLists.txt @@ -9,3 +9,5 @@ ADD_SUBDIRECTORY(NumericalDiff) ADD_SUBDIRECTORY(Polynomials) ADD_SUBDIRECTORY(Skyline) ADD_SUBDIRECTORY(SparseExtra) +ADD_SUBDIRECTORY(KroneckerProduct) +ADD_SUBDIRECTORY(Splines) diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/FFT/ei_fftw_impl.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/FFT/ei_fftw_impl.h index a06f6739e..5c36db70c 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/FFT/ei_fftw_impl.h +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/FFT/ei_fftw_impl.h @@ -22,6 +22,8 @@ // License and a copy of the GNU General Public License along with // Eigen. If not, see . +namespace Eigen { + namespace internal { // FFTW uses non-const arguments @@ -269,4 +271,6 @@ namespace internal { } // end namespace internal +} // end namespace Eigen + /* vim: set filetype=cpp et sw=2 ts=2 ai: */ diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/FFT/ei_kissfft_impl.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/FFT/ei_kissfft_impl.h index 04b98b083..c3cbb7f01 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/FFT/ei_kissfft_impl.h +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/FFT/ei_kissfft_impl.h @@ -22,6 +22,8 @@ // License and a copy of the GNU General Public License along with // Eigen. If not, see . +namespace Eigen { + namespace internal { // This FFT implementation was derived from kissfft http:sourceforge.net/projects/kissfft @@ -426,5 +428,6 @@ struct kissfft_impl } // end namespace internal -/* vim: set filetype=cpp et sw=2 ts=2 ai: */ +} // end namespace Eigen +/* vim: set filetype=cpp et sw=2 ts=2 ai: */ diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/IterativeSolvers/ConstrainedConjGrad.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/IterativeSolvers/ConstrainedConjGrad.h index 4d8e183ee..f8a550553 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/IterativeSolvers/ConstrainedConjGrad.h +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/IterativeSolvers/ConstrainedConjGrad.h @@ -50,6 +50,8 @@ #include +namespace Eigen { + namespace internal { /** \ingroup IterativeSolvers_Module @@ -195,4 +197,6 @@ void constrained_cg(const TMatrix& A, const CMatrix& C, VectorX& x, } // end namespace internal +} // end namespace Eigen + #endif // EIGEN_CONSTRAINEDCG_H diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/IterativeSolvers/GMRES.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/IterativeSolvers/GMRES.h new file mode 100644 index 000000000..e100617d1 --- /dev/null +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/IterativeSolvers/GMRES.h @@ -0,0 +1,394 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2011 Gael Guennebaud +// Copyright (C) 2012 Kolja Brix +// +// Eigen is free software; you can redistribute it and/or +// modify it under the terms of the GNU Lesser General Public +// License as published by the Free Software Foundation; either +// version 3 of the License, or (at your option) any later version. +// +// Alternatively, you can redistribute it and/or +// modify it under the terms of the GNU General Public License as +// published by the Free Software Foundation; either version 2 of +// the License, or (at your option) any later version. +// +// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY +// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the +// GNU General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public +// License and a copy of the GNU General Public License along with +// Eigen. If not, see . + +#ifndef EIGEN_GMRES_H +#define EIGEN_GMRES_H + +namespace Eigen { + +namespace internal { + +/** + * Generalized Minimal Residual Algorithm based on the + * Arnoldi algorithm implemented with Householder reflections. + * + * Parameters: + * \param mat matrix of linear system of equations + * \param Rhs right hand side vector of linear system of equations + * \param x on input: initial guess, on output: solution + * \param precond preconditioner used + * \param iters on input: maximum number of iterations to perform + * on output: number of iterations performed + * \param restart number of iterations for a restart + * \param tol_error on input: residual tolerance + * on output: residuum achieved + * + * \sa IterativeMethods::bicgstab() + * + * + * For references, please see: + * + * Saad, Y. and Schultz, M. H. + * GMRES: A Generalized Minimal Residual Algorithm for Solving Nonsymmetric Linear Systems. + * SIAM J.Sci.Stat.Comp. 7, 1986, pp. 856 - 869. + * + * Saad, Y. + * Iterative Methods for Sparse Linear Systems. + * Society for Industrial and Applied Mathematics, Philadelphia, 2003. + * + * Walker, H. F. + * Implementations of the GMRES method. + * Comput.Phys.Comm. 53, 1989, pp. 311 - 320. + * + * Walker, H. F. + * Implementation of the GMRES Method using Householder Transformations. + * SIAM J.Sci.Stat.Comp. 9, 1988, pp. 152 - 163. + * + */ +template +bool gmres(const MatrixType & mat, const Rhs & rhs, Dest & x, const Preconditioner & precond, + int &iters, const int &restart, typename Dest::RealScalar & tol_error) { + + using std::sqrt; + using std::abs; + + typedef typename Dest::RealScalar RealScalar; + typedef typename Dest::Scalar Scalar; + typedef Matrix < RealScalar, Dynamic, 1 > RealVectorType; + typedef Matrix < Scalar, Dynamic, 1 > VectorType; + typedef Matrix < Scalar, Dynamic, Dynamic > FMatrixType; + + RealScalar tol = tol_error; + const int maxIters = iters; + iters = 0; + + const int m = mat.rows(); + + VectorType p0 = rhs - mat*x; + VectorType r0 = precond.solve(p0); +// RealScalar r0_sqnorm = r0.squaredNorm(); + + VectorType w = VectorType::Zero(restart + 1); + + FMatrixType H = FMatrixType::Zero(m, restart + 1); + VectorType tau = VectorType::Zero(restart + 1); + std::vector < JacobiRotation < Scalar > > G(restart); + + // generate first Householder vector + VectorType e; + RealScalar beta; + r0.makeHouseholder(e, tau.coeffRef(0), beta); + w(0)=(Scalar) beta; + H.bottomLeftCorner(m - 1, 1) = e; + + for (int k = 1; k <= restart; ++k) { + + ++iters; + + VectorType v = VectorType::Unit(m, k - 1), workspace(m); + + // apply Householder reflections H_{1} ... H_{k-1} to v + for (int i = k - 1; i >= 0; --i) { + v.tail(m - i).applyHouseholderOnTheLeft(H.col(i).tail(m - i - 1), tau.coeffRef(i), workspace.data()); + } + + // apply matrix M to v: v = mat * v; + VectorType t=mat*v; + v=precond.solve(t); + + // apply Householder reflections H_{k-1} ... H_{1} to v + for (int i = 0; i < k; ++i) { + v.tail(m - i).applyHouseholderOnTheLeft(H.col(i).tail(m - i - 1), tau.coeffRef(i), workspace.data()); + } + + if (v.tail(m - k).norm() != 0.0) { + + if (k <= restart) { + + // generate new Householder vector + VectorType e(m - k - 1); + RealScalar beta; + v.tail(m - k).makeHouseholder(e, tau.coeffRef(k), beta); + H.col(k).tail(m - k - 1) = e; + + // apply Householder reflection H_{k} to v + v.tail(m - k).applyHouseholderOnTheLeft(H.col(k).tail(m - k - 1), tau.coeffRef(k), workspace.data()); + + } + } + + if (k > 1) { + for (int i = 0; i < k - 1; ++i) { + // apply old Givens rotations to v + v.applyOnTheLeft(i, i + 1, G[i].adjoint()); + } + } + + if (k ().solveInPlace(y); + + // use Horner-like scheme to calculate solution vector + VectorType x_new = y(k - 1) * VectorType::Unit(m, k - 1); + + // apply Householder reflection H_{k} to x_new + x_new.tail(m - k + 1).applyHouseholderOnTheLeft(H.col(k - 1).tail(m - k), tau.coeffRef(k - 1), workspace.data()); + + for (int i = k - 2; i >= 0; --i) { + x_new += y(i) * VectorType::Unit(m, i); + // apply Householder reflection H_{i} to x_new + x_new.tail(m - i).applyHouseholderOnTheLeft(H.col(i).tail(m - i - 1), tau.coeffRef(i), workspace.data()); + } + + x += x_new; + + if (stop) { + return true; + } else { + k=0; + + // reset data for a restart r0 = rhs - mat * x; + VectorType p0=mat*x; + VectorType p1=precond.solve(p0); + r0 = rhs - p1; +// r0_sqnorm = r0.squaredNorm(); + w = VectorType::Zero(restart + 1); + H = FMatrixType::Zero(m, restart + 1); + tau = VectorType::Zero(restart + 1); + + // generate first Householder vector + RealScalar beta; + r0.makeHouseholder(e, tau.coeffRef(0), beta); + w(0)=(Scalar) beta; + H.bottomLeftCorner(m - 1, 1) = e; + + } + + } + + + + } + + return false; + +} + +} + +template< typename _MatrixType, + typename _Preconditioner = DiagonalPreconditioner > +class GMRES; + +namespace internal { + +template< typename _MatrixType, typename _Preconditioner> +struct traits > +{ + typedef _MatrixType MatrixType; + typedef _Preconditioner Preconditioner; +}; + +} + +/** \ingroup IterativeLinearSolvers_Module + * \brief A GMRES solver for sparse square problems + * + * This class allows to solve for A.x = b sparse linear problems using a generalized minimal + * residual method. The vectors x and b can be either dense or sparse. + * + * \tparam _MatrixType the type of the sparse matrix A, can be a dense or a sparse matrix. + * \tparam _Preconditioner the type of the preconditioner. Default is DiagonalPreconditioner + * + * The maximal number of iterations and tolerance value can be controlled via the setMaxIterations() + * and setTolerance() methods. The defaults are the size of the problem for the maximal number of iterations + * and NumTraits::epsilon() for the tolerance. + * + * This class can be used as the direct solver classes. Here is a typical usage example: + * \code + * int n = 10000; + * VectorXd x(n), b(n); + * SparseMatrix A(n,n); + * // fill A and b + * GMRES > solver(A); + * x = solver.solve(b); + * std::cout << "#iterations: " << solver.iterations() << std::endl; + * std::cout << "estimated error: " << solver.error() << std::endl; + * // update b, and solve again + * x = solver.solve(b); + * \endcode + * + * By default the iterations start with x=0 as an initial guess of the solution. + * One can control the start using the solveWithGuess() method. Here is a step by + * step execution example starting with a random guess and printing the evolution + * of the estimated error: + * * \code + * x = VectorXd::Random(n); + * solver.setMaxIterations(1); + * int i = 0; + * do { + * x = solver.solveWithGuess(b,x); + * std::cout << i << " : " << solver.error() << std::endl; + * ++i; + * } while (solver.info()!=Success && i<100); + * \endcode + * Note that such a step by step excution is slightly slower. + * + * \sa class SimplicialCholesky, DiagonalPreconditioner, IdentityPreconditioner + */ +template< typename _MatrixType, typename _Preconditioner> +class GMRES : public IterativeSolverBase > +{ + typedef IterativeSolverBase Base; + using Base::mp_matrix; + using Base::m_error; + using Base::m_iterations; + using Base::m_info; + using Base::m_isInitialized; + +private: + int m_restart; + +public: + typedef _MatrixType MatrixType; + typedef typename MatrixType::Scalar Scalar; + typedef typename MatrixType::Index Index; + typedef typename MatrixType::RealScalar RealScalar; + typedef _Preconditioner Preconditioner; + +public: + + /** Default constructor. */ + GMRES() : Base(), m_restart(30) {} + + /** Initialize the solver with matrix \a A for further \c Ax=b solving. + * + * This constructor is a shortcut for the default constructor followed + * by a call to compute(). + * + * \warning this class stores a reference to the matrix A as well as some + * precomputed values that depend on it. Therefore, if \a A is changed + * this class becomes invalid. Call compute() to update it with the new + * matrix A, or modify a copy of A. + */ + GMRES(const MatrixType& A) : Base(A), m_restart(30) {} + + ~GMRES() {} + + /** Get the number of iterations after that a restart is performed. + */ + int get_restart() { return m_restart; } + + /** Set the number of iterations after that a restart is performed. + * \param restart number of iterations for a restarti, default is 30. + */ + void set_restart(const int restart) { m_restart=restart; } + + /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A + * \a x0 as an initial solution. + * + * \sa compute() + */ + template + inline const internal::solve_retval_with_guess + solveWithGuess(const MatrixBase& b, const Guess& x0) const + { + eigen_assert(m_isInitialized && "GMRES is not initialized."); + eigen_assert(Base::rows()==b.rows() + && "GMRES::solve(): invalid number of rows of the right hand side matrix b"); + return internal::solve_retval_with_guess + (*this, b.derived(), x0); + } + + /** \internal */ + template + void _solveWithGuess(const Rhs& b, Dest& x) const + { + bool failed = false; + for(int j=0; j + void _solve(const Rhs& b, Dest& x) const + { + x.setZero(); + _solveWithGuess(b,x); + } + +protected: + +}; + + +namespace internal { + + template +struct solve_retval, Rhs> + : solve_retval_base, Rhs> +{ + typedef GMRES<_MatrixType, _Preconditioner> Dec; + EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs) + + template void evalTo(Dest& dst) const + { + dec()._solve(rhs(),dst); + } +}; + +} // end namespace internal + +} // end namespace Eigen + +#endif // EIGEN_GMRES_H diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/IterativeSolvers/IncompleteLU.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/IterativeSolvers/IncompleteLU.h new file mode 100644 index 000000000..e02f1f0c8 --- /dev/null +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/IterativeSolvers/IncompleteLU.h @@ -0,0 +1,128 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2011 Gael Guennebaud +// +// Eigen is free software; you can redistribute it and/or +// modify it under the terms of the GNU Lesser General Public +// License as published by the Free Software Foundation; either +// version 3 of the License, or (at your option) any later version. +// +// Alternatively, you can redistribute it and/or +// modify it under the terms of the GNU General Public License as +// published by the Free Software Foundation; either version 2 of +// the License, or (at your option) any later version. +// +// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY +// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the +// GNU General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public +// License and a copy of the GNU General Public License along with +// Eigen. If not, see . + +#ifndef EIGEN_INCOMPLETE_LU_H +#define EIGEN_INCOMPLETE_LU_H + +namespace Eigen { + +template +class IncompleteLU +{ + typedef _Scalar Scalar; + typedef Matrix Vector; + typedef typename Vector::Index Index; + typedef SparseMatrix FactorType; + + public: + typedef Matrix MatrixType; + + IncompleteLU() : m_isInitialized(false) {} + + template + IncompleteLU(const MatrixType& mat) : m_isInitialized(false) + { + compute(mat); + } + + Index rows() const { return m_lu.rows(); } + Index cols() const { return m_lu.cols(); } + + template + IncompleteLU& compute(const MatrixType& mat) + { + m_lu = mat; + int size = mat.cols(); + Vector diag(size); + for(int i=0; i + void _solve(const Rhs& b, Dest& x) const + { + x = m_lu.template triangularView().solve(b); + x = m_lu.template triangularView().solve(x); + } + + template inline const internal::solve_retval + solve(const MatrixBase& b) const + { + eigen_assert(m_isInitialized && "IncompleteLU is not initialized."); + eigen_assert(cols()==b.rows() + && "IncompleteLU::solve(): invalid number of rows of the right hand side matrix b"); + return internal::solve_retval(*this, b.derived()); + } + + protected: + FactorType m_lu; + bool m_isInitialized; +}; + +namespace internal { + +template +struct solve_retval, Rhs> + : solve_retval_base, Rhs> +{ + typedef IncompleteLU<_MatrixType> Dec; + EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs) + + template void evalTo(Dest& dst) const + { + dec()._solve(rhs(),dst); + } +}; + +} // end namespace internal + +} // end namespace Eigen + +#endif // EIGEN_INCOMPLETE_LU_H diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/IterativeSolvers/IterationController.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/IterativeSolvers/IterationController.h index a65793cd5..dfb97e239 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/IterativeSolvers/IterationController.h +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/IterativeSolvers/IterationController.h @@ -75,6 +75,8 @@ #ifndef EIGEN_ITERATION_CONTROLLER_H #define EIGEN_ITERATION_CONTROLLER_H +namespace Eigen { + /** \ingroup IterativeSolvers_Module * \class IterationController * @@ -163,4 +165,6 @@ class IterationController }; +} // end namespace Eigen + #endif // EIGEN_ITERATION_CONTROLLER_H diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/IterativeSolvers/Scaling.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/IterativeSolvers/Scaling.h new file mode 100644 index 000000000..4aad69d0e --- /dev/null +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/IterativeSolvers/Scaling.h @@ -0,0 +1,200 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2012 Desire NUENTSA WAKAM . + +#ifndef EIGEN_SCALING_H +#define EIGEN_SCALING_H +/** + * \ingroup IterativeSolvers_Module + * \brief iterative scaling algorithm to equilibrate rows and column norms in matrices + * + * This class can be used as a preprocessing tool to accelerate the convergence of iterative methods + * + * This feature is useful to limit the pivoting amount during LU/ILU factorization + * The scaling strategy as presented here preserves the symmetry of the problem + * NOTE It is assumed that the matrix does not have empty row or column, + * + * Example with key steps + * \code + * VectorXd x(n), b(n); + * SparseMatrix A; + * // fill A and b; + * Scaling > scal; + * // Compute the left and right scaling vectors. The matrix is equilibrated at output + * scal.computeRef(A); + * // Scale the right hand side + * b = scal.LeftScaling().cwiseProduct(b); + * // Now, solve the equilibrated linear system with any available solver + * + * // Scale back the computed solution + * x = scal.RightScaling().cwiseProduct(x); + * \endcode + * + * \tparam _MatrixType the type of the matrix. It should be a real square sparsematrix + * + * References : D. Ruiz and B. Ucar, A Symmetry Preserving Algorithm for Matrix Scaling, INRIA Research report RR-7552 + * + * \sa \ref IncompleteLUT + */ +using std::abs; +using namespace Eigen; +template +class Scaling +{ + public: + typedef _MatrixType MatrixType; + typedef typename MatrixType::Scalar Scalar; + typedef typename MatrixType::Index Index; + + public: + Scaling() { init(); } + + Scaling(const MatrixType& matrix) + { + init(); + compute(matrix); + } + + ~Scaling() { } + + /** + * Compute the left and right diagonal matrices to scale the input matrix @p mat + * + * FIXME This algorithm will be modified such that the diagonal elements are permuted on the diagonal. + * + * \sa LeftScaling() RightScaling() + */ + void compute (const MatrixType& mat) + { + int m = mat.rows(); + int n = mat.cols(); + assert((m>0 && m == n) && "Please give a non - empty matrix"); + m_left.resize(m); + m_right.resize(n); + m_left.setOnes(); + m_right.setOnes(); + m_matrix = mat; + VectorXd Dr, Dc, DrRes, DcRes; // Temporary Left and right scaling vectors + Dr.resize(m); Dc.resize(n); + DrRes.resize(m); DcRes.resize(n); + double EpsRow = 1.0, EpsCol = 1.0; + int its = 0; + do + { // Iterate until the infinite norm of each row and column is approximately 1 + // Get the maximum value in each row and column + Dr.setZero(); Dc.setZero(); + for (int k=0; km_tol || EpsCol > m_tol) && (its < m_maxits) ); + m_isInitialized = true; + } + /** Compute the left and right vectors to scale the vectors + * the input matrix is scaled with the computed vectors at output + * + * \sa compute() + */ + void computeRef (MatrixType& mat) + { + compute (mat); + mat = m_matrix; + } + /** Get the vector to scale the rows of the matrix + */ + VectorXd& LeftScaling() + { + return m_left; + } + + /** Get the vector to scale the columns of the matrix + */ + VectorXd& RightScaling() + { + return m_right; + } + + /** Set the tolerance for the convergence of the iterative scaling algorithm + */ + void setTolerance(double tol) + { + m_tol = tol; + } + + protected: + + void init() + { + m_tol = 1e-10; + m_maxits = 5; + m_isInitialized = false; + } + + MatrixType m_matrix; + mutable ComputationInfo m_info; + bool m_isInitialized; + VectorXd m_left; // Left scaling vector + VectorXd m_right; // m_right scaling vector + double m_tol; + int m_maxits; // Maximum number of iterations allowed +}; + +#endif \ No newline at end of file diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/KroneckerProduct/CMakeLists.txt b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/KroneckerProduct/CMakeLists.txt new file mode 100644 index 000000000..4daefebee --- /dev/null +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/KroneckerProduct/CMakeLists.txt @@ -0,0 +1,6 @@ +FILE(GLOB Eigen_KroneckerProduct_SRCS "*.h") + +INSTALL(FILES + ${Eigen_KroneckerProduct_SRCS} + DESTINATION ${INCLUDE_INSTALL_DIR}/unsupported/Eigen/src/KroneckerProduct COMPONENT Devel + ) diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/KroneckerProduct/KroneckerTensorProduct.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/KroneckerProduct/KroneckerTensorProduct.h new file mode 100644 index 000000000..4627705ce --- /dev/null +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/KroneckerProduct/KroneckerTensorProduct.h @@ -0,0 +1,172 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2011 Kolja Brix +// Copyright (C) 2011 Andreas Platen +// +// Eigen is free software; you can redistribute it and/or +// modify it under the terms of the GNU Lesser General Public +// License as published by the Free Software Foundation; either +// version 3 of the License, or (at your option) any later version. +// +// Alternatively, you can redistribute it and/or +// modify it under the terms of the GNU General Public License as +// published by the Free Software Foundation; either version 2 of +// the License, or (at your option) any later version. +// +// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY +// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the +// GNU General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public +// License and a copy of the GNU General Public License along with +// Eigen. If not, see . + + +#ifndef KRONECKER_TENSOR_PRODUCT_H +#define KRONECKER_TENSOR_PRODUCT_H + + +namespace Eigen { + +namespace internal { + +/*! + * Kronecker tensor product helper function for dense matrices + * + * \param A Dense matrix A + * \param B Dense matrix B + * \param AB_ Kronecker tensor product of A and B + */ +template +void kroneckerProduct_full(const Derived_A& A, const Derived_B& B, Derived_AB & AB) +{ + const unsigned int Ar = A.rows(), + Ac = A.cols(), + Br = B.rows(), + Bc = B.cols(); + for (unsigned int i=0; i +void kroneckerProduct_sparse(const Derived_A &A, const Derived_B &B, Derived_AB &AB) +{ + const unsigned int Ar = A.rows(), + Ac = A.cols(), + Br = B.rows(), + Bc = B.cols(); + AB.resize(Ar*Br,Ac*Bc); + AB.resizeNonZeros(0); + AB.reserve(A.nonZeros()*B.nonZeros()); + + for (int kA=0; kA +void kroneckerProduct(const MatrixBase& a, const MatrixBase& b, Matrix& c) +{ + c.resize(a.rows()*b.rows(),a.cols()*b.cols()); + internal::kroneckerProduct_full(a.derived(), b.derived(), c); +} + +/*! + * Computes Kronecker tensor product of two dense matrices + * + * Remark: this function uses the const cast hack and has been + * implemented to make the function call possible, where the + * output matrix is a submatrix, e.g. + * kroneckerProduct(A,B,AB.block(2,5,6,6)); + * + * \param a Dense matrix a + * \param b Dense matrix b + * \param c Kronecker tensor product of a and b + */ +template +void kroneckerProduct(const MatrixBase& a, const MatrixBase& b, MatrixBase const & c_) +{ + MatrixBase& c = const_cast& >(c_); + internal::kroneckerProduct_full(a.derived(), b.derived(), c.derived()); +} + +/*! + * Computes Kronecker tensor product of a dense and a sparse matrix + * + * \param a Dense matrix a + * \param b Sparse matrix b + * \param c Kronecker tensor product of a and b + */ +template +void kroneckerProduct(const MatrixBase& a, const SparseMatrixBase& b, SparseMatrixBase& c) +{ + internal::kroneckerProduct_sparse(a.derived(), b.derived(), c.derived()); +} + +/*! + * Computes Kronecker tensor product of a sparse and a dense matrix + * + * \param a Sparse matrix a + * \param b Dense matrix b + * \param c Kronecker tensor product of a and b + */ +template +void kroneckerProduct(const SparseMatrixBase& a, const MatrixBase& b, SparseMatrixBase& c) +{ + internal::kroneckerProduct_sparse(a.derived(), b.derived(), c.derived()); +} + +/*! + * Computes Kronecker tensor product of two sparse matrices + * + * \param a Sparse matrix a + * \param b Sparse matrix b + * \param c Kronecker tensor product of a and b + */ +template +void kroneckerProduct(const SparseMatrixBase& a, const SparseMatrixBase& b, SparseMatrixBase& c) +{ + internal::kroneckerProduct_sparse(a.derived(), b.derived(), c.derived()); +} + +} // end namespace Eigen + +#endif // KRONECKER_TENSOR_PRODUCT_H diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/MatrixFunctions/MatrixExponential.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/MatrixFunctions/MatrixExponential.h index 50c0ca84e..6cdd65748 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/MatrixFunctions/MatrixExponential.h +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/MatrixFunctions/MatrixExponential.h @@ -2,6 +2,7 @@ // for linear algebra. // // Copyright (C) 2009, 2010 Jitse Niesen +// Copyright (C) 2011 Chen-Pang He // // Eigen is free software; you can redistribute it and/or // modify it under the terms of the GNU Lesser General Public @@ -25,7 +26,11 @@ #ifndef EIGEN_MATRIX_EXPONENTIAL #define EIGEN_MATRIX_EXPONENTIAL -#ifdef _MSC_VER +#include "StemFunction.h" + +namespace Eigen { + +#if defined(_MSC_VER) || defined(__FreeBSD__) template Scalar log2(Scalar v) { using std::log; return log(v)/log(Scalar(2)); } #endif @@ -107,6 +112,17 @@ class MatrixExponential { */ void pade13(const MatrixType &A); + /** \brief Compute the (17,17)-Padé approximant to the exponential. + * + * After exit, \f$ (V+U)(V-U)^{-1} \f$ is the Padé + * approximant of \f$ \exp(A) \f$ around \f$ A = 0 \f$. + * + * This function activates only if your long double is double-double or quadruple. + * + * \param[in] A Argument of matrix exponential + */ + void pade17(const MatrixType &A); + /** \brief Compute Padé approximant to the exponential. * * Computes \c m_U, \c m_V and \c m_squarings such that @@ -127,17 +143,24 @@ class MatrixExponential { * \sa computeUV(double); */ void computeUV(float); + + /** \brief Compute Padé approximant to the exponential. + * + * \sa computeUV(double); + */ + void computeUV(long double); typedef typename internal::traits::Scalar Scalar; typedef typename NumTraits::Real RealScalar; + typedef typename std::complex ComplexScalar; /** \brief Reference to matrix whose exponential is to be computed. */ typename internal::nested::type m_M; - /** \brief Even-degree terms in numerator of Padé approximant. */ + /** \brief Odd-degree terms in numerator of Padé approximant. */ MatrixType m_U; - /** \brief Odd-degree terms in numerator of Padé approximant. */ + /** \brief Even-degree terms in numerator of Padé approximant. */ MatrixType m_V; /** \brief Used for temporary storage. */ @@ -153,7 +176,7 @@ class MatrixExponential { int m_squarings; /** \brief L1 norm of m_M. */ - float m_l1norm; + RealScalar m_l1norm; }; template @@ -165,7 +188,7 @@ MatrixExponential::MatrixExponential(const MatrixType &M) : m_tmp2(M.rows(),M.cols()), m_Id(MatrixType::Identity(M.rows(), M.cols())), m_squarings(0), - m_l1norm(static_cast(M.cwiseAbs().colwise().sum().maxCoeff())) + m_l1norm(M.cwiseAbs().colwise().sum().maxCoeff()) { /* empty body */ } @@ -174,18 +197,24 @@ template template void MatrixExponential::compute(ResultType &result) { +#if LDBL_MANT_DIG > 112 // rarely happens + if(sizeof(RealScalar) > 14) { + result = m_M.matrixFunction(StdStemFunctions::exp); + return; + } +#endif computeUV(RealScalar()); - m_tmp1 = m_U + m_V; // numerator of Pade approximant - m_tmp2 = -m_U + m_V; // denominator of Pade approximant + m_tmp1 = m_U + m_V; // numerator of Pade approximant + m_tmp2 = -m_U + m_V; // denominator of Pade approximant result = m_tmp2.partialPivLu().solve(m_tmp1); for (int i=0; i EIGEN_STRONG_INLINE void MatrixExponential::pade3(const MatrixType &A) { - const Scalar b[] = {120., 60., 12., 1.}; + const RealScalar b[] = {120., 60., 12., 1.}; m_tmp1.noalias() = A * A; m_tmp2 = b[3]*m_tmp1 + b[1]*m_Id; m_U.noalias() = A * m_tmp2; @@ -195,7 +224,7 @@ EIGEN_STRONG_INLINE void MatrixExponential::pade3(const MatrixType & template EIGEN_STRONG_INLINE void MatrixExponential::pade5(const MatrixType &A) { - const Scalar b[] = {30240., 15120., 3360., 420., 30., 1.}; + const RealScalar b[] = {30240., 15120., 3360., 420., 30., 1.}; MatrixType A2 = A * A; m_tmp1.noalias() = A2 * A2; m_tmp2 = b[5]*m_tmp1 + b[3]*A2 + b[1]*m_Id; @@ -206,7 +235,7 @@ EIGEN_STRONG_INLINE void MatrixExponential::pade5(const MatrixType & template EIGEN_STRONG_INLINE void MatrixExponential::pade7(const MatrixType &A) { - const Scalar b[] = {17297280., 8648640., 1995840., 277200., 25200., 1512., 56., 1.}; + const RealScalar b[] = {17297280., 8648640., 1995840., 277200., 25200., 1512., 56., 1.}; MatrixType A2 = A * A; MatrixType A4 = A2 * A2; m_tmp1.noalias() = A4 * A2; @@ -218,7 +247,7 @@ EIGEN_STRONG_INLINE void MatrixExponential::pade7(const MatrixType & template EIGEN_STRONG_INLINE void MatrixExponential::pade9(const MatrixType &A) { - const Scalar b[] = {17643225600., 8821612800., 2075673600., 302702400., 30270240., + const RealScalar b[] = {17643225600., 8821612800., 2075673600., 302702400., 30270240., 2162160., 110880., 3960., 90., 1.}; MatrixType A2 = A * A; MatrixType A4 = A2 * A2; @@ -232,7 +261,7 @@ EIGEN_STRONG_INLINE void MatrixExponential::pade9(const MatrixType & template EIGEN_STRONG_INLINE void MatrixExponential::pade13(const MatrixType &A) { - const Scalar b[] = {64764752532480000., 32382376266240000., 7771770303897600., + const RealScalar b[] = {64764752532480000., 32382376266240000., 7771770303897600., 1187353796428800., 129060195264000., 10559470521600., 670442572800., 33522128640., 1323241920., 40840800., 960960., 16380., 182., 1.}; MatrixType A2 = A * A; @@ -247,6 +276,30 @@ EIGEN_STRONG_INLINE void MatrixExponential::pade13(const MatrixType m_V += b[6]*m_tmp1 + b[4]*A4 + b[2]*A2 + b[0]*m_Id; } +#if LDBL_MANT_DIG > 64 +template +EIGEN_STRONG_INLINE void MatrixExponential::pade17(const MatrixType &A) +{ + const RealScalar b[] = {830034394580628357120000.L, 415017197290314178560000.L, + 100610229646136770560000.L, 15720348382208870400000.L, + 1774878043152614400000.L, 153822763739893248000.L, 10608466464820224000.L, + 595373117923584000.L, 27563570274240000.L, 1060137318240000.L, + 33924394183680.L, 899510451840.L, 19554575040.L, 341863200.L, 4651200.L, + 46512.L, 306.L, 1.L}; + MatrixType A2 = A * A; + MatrixType A4 = A2 * A2; + MatrixType A6 = A4 * A2; + m_tmp1.noalias() = A4 * A4; + m_V = b[17]*m_tmp1 + b[15]*A6 + b[13]*A4 + b[11]*A2; // used for temporary storage + m_tmp2.noalias() = m_tmp1 * m_V; + m_tmp2 += b[9]*m_tmp1 + b[7]*A6 + b[5]*A4 + b[3]*A2 + b[1]*m_Id; + m_U.noalias() = A * m_tmp2; + m_tmp2 = b[16]*m_tmp1 + b[14]*A6 + b[12]*A4 + b[10]*A2; + m_V.noalias() = m_tmp1 * m_tmp2; + m_V += b[8]*m_tmp1 + b[6]*A6 + b[4]*A4 + b[2]*A2 + b[0]*m_Id; +} +#endif + template void MatrixExponential::computeUV(float) { @@ -260,7 +313,7 @@ void MatrixExponential::computeUV(float) } else { const float maxnorm = 3.925724783138660f; m_squarings = (max)(0, (int)ceil(log2(m_l1norm / maxnorm))); - MatrixType A = m_M / pow(Scalar(2), Scalar(static_cast(m_squarings))); + MatrixType A = m_M / pow(Scalar(2), m_squarings); pade7(A); } } @@ -282,11 +335,74 @@ void MatrixExponential::computeUV(double) } else { const double maxnorm = 5.371920351148152; m_squarings = (max)(0, (int)ceil(log2(m_l1norm / maxnorm))); - MatrixType A = m_M / pow(Scalar(2), Scalar(m_squarings)); + MatrixType A = m_M / pow(Scalar(2), m_squarings); pade13(A); } } +template +void MatrixExponential::computeUV(long double) +{ + using std::max; + using std::pow; + using std::ceil; +#if LDBL_MANT_DIG == 53 // double precision + computeUV(double()); +#elif LDBL_MANT_DIG <= 64 // extended precision + if (m_l1norm < 4.1968497232266989671e-003L) { + pade3(m_M); + } else if (m_l1norm < 1.1848116734693823091e-001L) { + pade5(m_M); + } else if (m_l1norm < 5.5170388480686700274e-001L) { + pade7(m_M); + } else if (m_l1norm < 1.3759868875587845383e+000L) { + pade9(m_M); + } else { + const long double maxnorm = 4.0246098906697353063L; + m_squarings = (max)(0, (int)ceil(log2(m_l1norm / maxnorm))); + MatrixType A = m_M / pow(Scalar(2), m_squarings); + pade13(A); + } +#elif LDBL_MANT_DIG <= 106 // double-double + if (m_l1norm < 3.2787892205607026992947488108213e-005L) { + pade3(m_M); + } else if (m_l1norm < 6.4467025060072760084130906076332e-003L) { + pade5(m_M); + } else if (m_l1norm < 6.8988028496595374751374122881143e-002L) { + pade7(m_M); + } else if (m_l1norm < 2.7339737518502231741495857201670e-001L) { + pade9(m_M); + } else if (m_l1norm < 1.3203382096514474905666448850278e+000L) { + pade13(m_M); + } else { + const long double maxnorm = 3.2579440895405400856599663723517L; + m_squarings = (max)(0, (int)ceil(log2(m_l1norm / maxnorm))); + MatrixType A = m_M / pow(Scalar(2), m_squarings); + pade17(A); + } +#elif LDBL_MANT_DIG <= 112 // quadruple precison + if (m_l1norm < 1.639394610288918690547467954466970e-005L) { + pade3(m_M); + } else if (m_l1norm < 4.253237712165275566025884344433009e-003L) { + pade5(m_M); + } else if (m_l1norm < 5.125804063165764409885122032933142e-002L) { + pade7(m_M); + } else if (m_l1norm < 2.170000765161155195453205651889853e-001L) { + pade9(m_M); + } else if (m_l1norm < 1.125358383453143065081397882891878e+000L) { + pade13(m_M); + } else { + const long double maxnorm = 2.884233277829519311757165057717815L; + m_squarings = (max)(0, (int)ceil(log2(m_l1norm / maxnorm))); + MatrixType A = m_M / pow(Scalar(2), m_squarings); + pade17(A); + } +#else + // this case should be handled in compute() + eigen_assert(false && "Bug in MatrixExponential"); +#endif // LDBL_MANT_DIG +} + /** \ingroup MatrixFunctions_Module * * \brief Proxy for the matrix exponential of some matrix (expression). @@ -348,4 +464,6 @@ const MatrixExponentialReturnValue MatrixBase::exp() const return MatrixExponentialReturnValue(derived()); } +} // end namespace Eigen + #endif // EIGEN_MATRIX_EXPONENTIAL diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/MatrixFunctions/MatrixFunction.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/MatrixFunctions/MatrixFunction.h index 4b9d8a102..859de7288 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/MatrixFunctions/MatrixFunction.h +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/MatrixFunctions/MatrixFunction.h @@ -1,7 +1,7 @@ // This file is part of Eigen, a lightweight C++ template library // for linear algebra. // -// Copyright (C) 2009, 2010 Jitse Niesen +// Copyright (C) 2009-2011 Jitse Niesen // // Eigen is free software; you can redistribute it and/or // modify it under the terms of the GNU Lesser General Public @@ -29,31 +29,39 @@ #include "MatrixFunctionAtomic.h" +namespace Eigen { + /** \ingroup MatrixFunctions_Module - * \brief Class for computing matrix exponentials. - * \tparam MatrixType type of the argument of the matrix function, - * expected to be an instantiation of the Matrix class template. + * \brief Class for computing matrix functions. + * \tparam MatrixType type of the argument of the matrix function, + * expected to be an instantiation of the Matrix class template. + * \tparam AtomicType type for computing matrix function of atomic blocks. + * \tparam IsComplex used internally to select correct specialization. + * + * This class implements the Schur-Parlett algorithm for computing matrix functions. The spectrum of the + * matrix is divided in clustered of eigenvalues that lies close together. This class delegates the + * computation of the matrix function on every block corresponding to these clusters to an object of type + * \p AtomicType and uses these results to compute the matrix function of the whole matrix. The class + * \p AtomicType should have a \p compute() member function for computing the matrix function of a block. + * + * \sa class MatrixFunctionAtomic, class MatrixLogarithmAtomic */ -template ::Scalar>::IsComplex> +template ::Scalar>::IsComplex> class MatrixFunction { - private: - - typedef typename internal::traits::Index Index; - typedef typename internal::traits::Scalar Scalar; - typedef typename internal::stem_function::type StemFunction; - public: /** \brief Constructor. * - * \param[in] A argument of matrix function, should be a square matrix. - * \param[in] f an entire function; \c f(x,n) should compute the n-th derivative of f at x. + * \param[in] A argument of matrix function, should be a square matrix. + * \param[in] atomic class for computing matrix function of atomic blocks. * - * The class stores a reference to \p A, so it should not be + * The class stores references to \p A and \p atomic, so they should not be * changed (or destroyed) before compute() is called. */ - MatrixFunction(const MatrixType& A, StemFunction f); + MatrixFunction(const MatrixType& A, AtomicType& atomic); /** \brief Compute the matrix function. * @@ -68,11 +76,11 @@ class MatrixFunction }; -/** \ingroup MatrixFunctions_Module - * \brief Partial specialization of MatrixFunction for real matrices \internal +/** \internal \ingroup MatrixFunctions_Module + * \brief Partial specialization of MatrixFunction for real matrices */ -template -class MatrixFunction +template +class MatrixFunction { private: @@ -86,16 +94,15 @@ class MatrixFunction typedef std::complex ComplexScalar; typedef Matrix ComplexMatrix; - typedef typename internal::stem_function::type StemFunction; public: /** \brief Constructor. * - * \param[in] A argument of matrix function, should be a square matrix. - * \param[in] f an entire function; \c f(x,n) should compute the n-th derivative of f at x. + * \param[in] A argument of matrix function, should be a square matrix. + * \param[in] atomic class for computing matrix function of atomic blocks. */ - MatrixFunction(const MatrixType& A, StemFunction f) : m_A(A), m_f(f) { } + MatrixFunction(const MatrixType& A, AtomicType& atomic) : m_A(A), m_atomic(atomic) { } /** \brief Compute the matrix function. * @@ -111,24 +118,24 @@ class MatrixFunction { ComplexMatrix CA = m_A.template cast(); ComplexMatrix Cresult; - MatrixFunction mf(CA, m_f); + MatrixFunction mf(CA, m_atomic); mf.compute(Cresult); result = Cresult.real(); } private: typename internal::nested::type m_A; /**< \brief Reference to argument of matrix function. */ - StemFunction *m_f; /**< \brief Stem function for matrix function under consideration */ + AtomicType& m_atomic; /**< \brief Class for computing matrix function of atomic blocks. */ MatrixFunction& operator=(const MatrixFunction&); }; -/** \ingroup MatrixFunctions_Module - * \brief Partial specialization of MatrixFunction for complex matrices \internal +/** \internal \ingroup MatrixFunctions_Module + * \brief Partial specialization of MatrixFunction for complex matrices */ -template -class MatrixFunction +template +class MatrixFunction { private: @@ -139,7 +146,6 @@ class MatrixFunction static const int ColsAtCompileTime = Traits::ColsAtCompileTime; static const int Options = MatrixType::Options; typedef typename NumTraits::Real RealScalar; - typedef typename internal::stem_function::type StemFunction; typedef Matrix VectorType; typedef Matrix IntVectorType; typedef Matrix DynamicIntVectorType; @@ -149,7 +155,7 @@ class MatrixFunction public: - MatrixFunction(const MatrixType& A, StemFunction f); + MatrixFunction(const MatrixType& A, AtomicType& atomic); template void compute(ResultType& result); private: @@ -168,7 +174,7 @@ class MatrixFunction DynMatrixType solveTriangularSylvester(const DynMatrixType& A, const DynMatrixType& B, const DynMatrixType& C); typename internal::nested::type m_A; /**< \brief Reference to argument of matrix function. */ - StemFunction *m_f; /**< \brief Stem function for matrix function under consideration */ + AtomicType& m_atomic; /**< \brief Class for computing matrix function of atomic blocks. */ MatrixType m_T; /**< \brief Triangular part of Schur decomposition */ MatrixType m_U; /**< \brief Unitary part of Schur decomposition */ MatrixType m_fT; /**< \brief %Matrix function applied to #m_T */ @@ -191,12 +197,12 @@ class MatrixFunction /** \brief Constructor. * - * \param[in] A argument of matrix function, should be a square matrix. - * \param[in] f an entire function; \c f(x,n) should compute the n-th derivative of f at x. + * \param[in] A argument of matrix function, should be a square matrix. + * \param[in] atomic class for computing matrix function of atomic blocks. */ -template -MatrixFunction::MatrixFunction(const MatrixType& A, StemFunction f) : - m_A(A), m_f(f) +template +MatrixFunction::MatrixFunction(const MatrixType& A, AtomicType& atomic) + : m_A(A), m_atomic(atomic) { /* empty body */ } @@ -206,9 +212,9 @@ MatrixFunction::MatrixFunction(const MatrixType& A, StemFunction f * \param[out] result the function \p f applied to \p A, as * specified in the constructor. */ -template +template template -void MatrixFunction::compute(ResultType& result) +void MatrixFunction::compute(ResultType& result) { computeSchurDecomposition(); partitionEigenvalues(); @@ -222,8 +228,8 @@ void MatrixFunction::compute(ResultType& result) } /** \brief Store the Schur decomposition of #m_A in #m_T and #m_U */ -template -void MatrixFunction::computeSchurDecomposition() +template +void MatrixFunction::computeSchurDecomposition() { const ComplexSchur schurOfA(m_A); m_T = schurOfA.matrixT(); @@ -241,8 +247,8 @@ void MatrixFunction::computeSchurDecomposition() * The implementation follows Algorithm 4.1 in the paper of Davies * and Higham. */ -template -void MatrixFunction::partitionEigenvalues() +template +void MatrixFunction::partitionEigenvalues() { const Index rows = m_T.rows(); VectorType diag = m_T.diagonal(); // contains eigenvalues of A @@ -278,8 +284,8 @@ void MatrixFunction::partitionEigenvalues() * \returns Iterator to cluster containing \c key, or * \c m_clusters.end() if no cluster in m_clusters contains \c key. */ -template -typename MatrixFunction::ListOfClusters::iterator MatrixFunction::findCluster(Scalar key) +template +typename MatrixFunction::ListOfClusters::iterator MatrixFunction::findCluster(Scalar key) { typename Cluster::iterator j; for (typename ListOfClusters::iterator i = m_clusters.begin(); i != m_clusters.end(); ++i) { @@ -291,8 +297,8 @@ typename MatrixFunction::ListOfClusters::iterator MatrixFunction -void MatrixFunction::computeClusterSize() +template +void MatrixFunction::computeClusterSize() { const Index rows = m_T.rows(); VectorType diag = m_T.diagonal(); @@ -313,8 +319,8 @@ void MatrixFunction::computeClusterSize() } /** \brief Compute #m_blockStart using #m_clusterSize */ -template -void MatrixFunction::computeBlockStart() +template +void MatrixFunction::computeBlockStart() { m_blockStart.resize(m_clusterSize.rows()); m_blockStart(0) = 0; @@ -324,8 +330,8 @@ void MatrixFunction::computeBlockStart() } /** \brief Compute #m_permutation using #m_eivalToCluster and #m_blockStart */ -template -void MatrixFunction::constructPermutation() +template +void MatrixFunction::constructPermutation() { DynamicIntVectorType indexNextEntry = m_blockStart; m_permutation.resize(m_T.rows()); @@ -337,8 +343,8 @@ void MatrixFunction::constructPermutation() } /** \brief Permute Schur decomposition in #m_U and #m_T according to #m_permutation */ -template -void MatrixFunction::permuteSchur() +template +void MatrixFunction::permuteSchur() { IntVectorType p = m_permutation; for (Index i = 0; i < p.rows() - 1; i++) { @@ -355,8 +361,8 @@ void MatrixFunction::permuteSchur() } /** \brief Swap rows \a index and \a index+1 in Schur decomposition in #m_U and #m_T */ -template -void MatrixFunction::swapEntriesInSchur(Index index) +template +void MatrixFunction::swapEntriesInSchur(Index index) { JacobiRotation rotation; rotation.makeGivens(m_T(index, index+1), m_T(index+1, index+1) - m_T(index, index)); @@ -367,25 +373,23 @@ void MatrixFunction::swapEntriesInSchur(Index index) /** \brief Compute block diagonal part of #m_fT. * - * This routine computes the matrix function #m_f applied to the block - * diagonal part of #m_T, with the blocking given by #m_blockStart. The - * result is stored in #m_fT. The off-diagonal parts of #m_fT are set - * to zero. + * This routine computes the matrix function applied to the block diagonal part of #m_T, with the blocking + * given by #m_blockStart. The matrix function of each diagonal block is computed by #m_atomic. The + * off-diagonal parts of #m_fT are set to zero. */ -template -void MatrixFunction::computeBlockAtomic() +template +void MatrixFunction::computeBlockAtomic() { m_fT.resize(m_T.rows(), m_T.cols()); m_fT.setZero(); - MatrixFunctionAtomic mfa(m_f); for (Index i = 0; i < m_clusterSize.rows(); ++i) { - block(m_fT, i, i) = mfa.compute(block(m_T, i, i)); + block(m_fT, i, i) = m_atomic.compute(block(m_T, i, i)); } } /** \brief Return block of matrix according to blocking given by #m_blockStart */ -template -Block MatrixFunction::block(MatrixType& A, Index i, Index j) +template +Block MatrixFunction::block(MatrixType& A, Index i, Index j) { return A.block(m_blockStart(i), m_blockStart(j), m_clusterSize(i), m_clusterSize(j)); } @@ -393,12 +397,12 @@ Block MatrixFunction::block(MatrixType& A, Index i, In /** \brief Compute part of #m_fT above block diagonal. * * This routine assumes that the block diagonal part of #m_fT (which - * equals #m_f applied to #m_T) has already been computed and computes + * equals the matrix function applied to #m_T) has already been computed and computes * the part above the block diagonal. The part below the diagonal is * zero, because #m_T is upper triangular. */ -template -void MatrixFunction::computeOffDiagonal() +template +void MatrixFunction::computeOffDiagonal() { for (Index diagIndex = 1; diagIndex < m_clusterSize.rows(); diagIndex++) { for (Index blockIndex = 0; blockIndex < m_clusterSize.rows() - diagIndex; blockIndex++) { @@ -439,8 +443,8 @@ void MatrixFunction::computeOffDiagonal() * solution). In that case, these equations can be evaluated in the * order \f$ i=m,\ldots,1 \f$ and \f$ j=1,\ldots,n \f$. */ -template -typename MatrixFunction::DynMatrixType MatrixFunction::solveTriangularSylvester( +template +typename MatrixFunction::DynMatrixType MatrixFunction::solveTriangularSylvester( const DynMatrixType& A, const DynMatrixType& B, const DynMatrixType& C) @@ -520,8 +524,18 @@ template class MatrixFunctionReturnValue template inline void evalTo(ResultType& result) const { - const typename Derived::PlainObject Aevaluated = m_A.eval(); - MatrixFunction mf(Aevaluated, m_f); + typedef typename Derived::PlainObject PlainObject; + typedef internal::traits Traits; + static const int RowsAtCompileTime = Traits::RowsAtCompileTime; + static const int ColsAtCompileTime = Traits::ColsAtCompileTime; + static const int Options = PlainObject::Options; + typedef std::complex::Real> ComplexScalar; + typedef Matrix DynMatrixType; + typedef MatrixFunctionAtomic AtomicType; + AtomicType atomic(m_f); + + const PlainObject Aevaluated = m_A.eval(); + MatrixFunction mf(Aevaluated, atomic); mf.compute(result); } @@ -586,4 +600,6 @@ const MatrixFunctionReturnValue MatrixBase::cosh() const return MatrixFunctionReturnValue(derived(), StdStemFunctions::cosh); } +} // end namespace Eigen + #endif // EIGEN_MATRIX_FUNCTION diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/MatrixFunctions/MatrixFunctionAtomic.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/MatrixFunctions/MatrixFunctionAtomic.h index d08766921..97ab662fe 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/MatrixFunctions/MatrixFunctionAtomic.h +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/MatrixFunctions/MatrixFunctionAtomic.h @@ -25,6 +25,8 @@ #ifndef EIGEN_MATRIX_FUNCTION_ATOMIC #define EIGEN_MATRIX_FUNCTION_ATOMIC +namespace Eigen { + /** \ingroup MatrixFunctions_Module * \class MatrixFunctionAtomic * \brief Helper class for computing matrix functions of atomic matrices. @@ -139,4 +141,6 @@ bool MatrixFunctionAtomic::taylorConverged(Index s, const MatrixType return false; } +} // end namespace Eigen + #endif // EIGEN_MATRIX_FUNCTION_ATOMIC diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/MatrixFunctions/MatrixLogarithm.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/MatrixFunctions/MatrixLogarithm.h new file mode 100644 index 000000000..e6f25b73c --- /dev/null +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/MatrixFunctions/MatrixLogarithm.h @@ -0,0 +1,510 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2011 Jitse Niesen +// Copyright (C) 2011 Chen-Pang He +// +// Eigen is free software; you can redistribute it and/or +// modify it under the terms of the GNU Lesser General Public +// License as published by the Free Software Foundation; either +// version 3 of the License, or (at your option) any later version. +// +// Alternatively, you can redistribute it and/or +// modify it under the terms of the GNU General Public License as +// published by the Free Software Foundation; either version 2 of +// the License, or (at your option) any later version. +// +// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY +// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the +// GNU General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public +// License and a copy of the GNU General Public License along with +// Eigen. If not, see . + +#ifndef EIGEN_MATRIX_LOGARITHM +#define EIGEN_MATRIX_LOGARITHM + +#ifndef M_PI +#define M_PI 3.141592653589793238462643383279503L +#endif + +namespace Eigen { + +/** \ingroup MatrixFunctions_Module + * \class MatrixLogarithmAtomic + * \brief Helper class for computing matrix logarithm of atomic matrices. + * + * \internal + * Here, an atomic matrix is a triangular matrix whose diagonal + * entries are close to each other. + * + * \sa class MatrixFunctionAtomic, MatrixBase::log() + */ +template +class MatrixLogarithmAtomic +{ +public: + + typedef typename MatrixType::Scalar Scalar; + // typedef typename MatrixType::Index Index; + typedef typename NumTraits::Real RealScalar; + // typedef typename internal::stem_function::type StemFunction; + // typedef Matrix VectorType; + + /** \brief Constructor. */ + MatrixLogarithmAtomic() { } + + /** \brief Compute matrix logarithm of atomic matrix + * \param[in] A argument of matrix logarithm, should be upper triangular and atomic + * \returns The logarithm of \p A. + */ + MatrixType compute(const MatrixType& A); + +private: + + void compute2x2(const MatrixType& A, MatrixType& result); + void computeBig(const MatrixType& A, MatrixType& result); + static Scalar atanh(Scalar x); + int getPadeDegree(float normTminusI); + int getPadeDegree(double normTminusI); + int getPadeDegree(long double normTminusI); + void computePade(MatrixType& result, const MatrixType& T, int degree); + void computePade3(MatrixType& result, const MatrixType& T); + void computePade4(MatrixType& result, const MatrixType& T); + void computePade5(MatrixType& result, const MatrixType& T); + void computePade6(MatrixType& result, const MatrixType& T); + void computePade7(MatrixType& result, const MatrixType& T); + void computePade8(MatrixType& result, const MatrixType& T); + void computePade9(MatrixType& result, const MatrixType& T); + void computePade10(MatrixType& result, const MatrixType& T); + void computePade11(MatrixType& result, const MatrixType& T); + + static const int minPadeDegree = 3; + static const int maxPadeDegree = std::numeric_limits::digits<= 24? 5: // single precision + std::numeric_limits::digits<= 53? 7: // double precision + std::numeric_limits::digits<= 64? 8: // extended precision + std::numeric_limits::digits<=106? 10: 11; // double-double or quadruple precision + + // Prevent copying + MatrixLogarithmAtomic(const MatrixLogarithmAtomic&); + MatrixLogarithmAtomic& operator=(const MatrixLogarithmAtomic&); +}; + +/** \brief Compute logarithm of triangular matrix with clustered eigenvalues. */ +template +MatrixType MatrixLogarithmAtomic::compute(const MatrixType& A) +{ + using std::log; + MatrixType result(A.rows(), A.rows()); + if (A.rows() == 1) + result(0,0) = log(A(0,0)); + else if (A.rows() == 2) + compute2x2(A, result); + else + computeBig(A, result); + return result; +} + +/** \brief Compute atanh (inverse hyperbolic tangent). */ +template +typename MatrixType::Scalar MatrixLogarithmAtomic::atanh(typename MatrixType::Scalar x) +{ + using std::abs; + using std::sqrt; + if (abs(x) > sqrt(NumTraits::epsilon())) + return Scalar(0.5) * log((Scalar(1) + x) / (Scalar(1) - x)); + else + return x + x*x*x / Scalar(3); +} + +/** \brief Compute logarithm of 2x2 triangular matrix. */ +template +void MatrixLogarithmAtomic::compute2x2(const MatrixType& A, MatrixType& result) +{ + using std::abs; + using std::ceil; + using std::imag; + using std::log; + + Scalar logA00 = log(A(0,0)); + Scalar logA11 = log(A(1,1)); + + result(0,0) = logA00; + result(1,0) = Scalar(0); + result(1,1) = logA11; + + if (A(0,0) == A(1,1)) { + result(0,1) = A(0,1) / A(0,0); + } else if ((abs(A(0,0)) < 0.5*abs(A(1,1))) || (abs(A(0,0)) > 2*abs(A(1,1)))) { + result(0,1) = A(0,1) * (logA11 - logA00) / (A(1,1) - A(0,0)); + } else { + // computation in previous branch is inaccurate if A(1,1) \approx A(0,0) + int unwindingNumber = static_cast(ceil((imag(logA11 - logA00) - M_PI) / (2*M_PI))); + Scalar z = (A(1,1) - A(0,0)) / (A(1,1) + A(0,0)); + result(0,1) = A(0,1) * (Scalar(2) * atanh(z) + Scalar(0,2*M_PI*unwindingNumber)) / (A(1,1) - A(0,0)); + } +} + +/** \brief Compute logarithm of triangular matrices with size > 2. + * \details This uses a inverse scale-and-square algorithm. */ +template +void MatrixLogarithmAtomic::computeBig(const MatrixType& A, MatrixType& result) +{ + int numberOfSquareRoots = 0; + int numberOfExtraSquareRoots = 0; + int degree; + MatrixType T = A; + const RealScalar maxNormForPade = maxPadeDegree<= 5? 5.3149729967117310e-1: // single precision + maxPadeDegree<= 7? 2.6429608311114350e-1: // double precision + maxPadeDegree<= 8? 2.32777776523703892094e-1L: // extended precision + maxPadeDegree<=10? 1.05026503471351080481093652651105e-1L: // double-double + 1.1880960220216759245467951592883642e-1L; // quadruple precision + + while (true) { + RealScalar normTminusI = (T - MatrixType::Identity(T.rows(), T.rows())).cwiseAbs().colwise().sum().maxCoeff(); + if (normTminusI < maxNormForPade) { + degree = getPadeDegree(normTminusI); + int degree2 = getPadeDegree(normTminusI / RealScalar(2)); + if ((degree - degree2 <= 1) || (numberOfExtraSquareRoots == 1)) + break; + ++numberOfExtraSquareRoots; + } + MatrixType sqrtT; + MatrixSquareRootTriangular(T).compute(sqrtT); + T = sqrtT; + ++numberOfSquareRoots; + } + + computePade(result, T, degree); + result *= pow(RealScalar(2), numberOfSquareRoots); +} + +/* \brief Get suitable degree for Pade approximation. (specialized for RealScalar = float) */ +template +int MatrixLogarithmAtomic::getPadeDegree(float normTminusI) +{ + const float maxNormForPade[] = { 2.5111573934555054e-1 /* degree = 3 */ , 4.0535837411880493e-1, + 5.3149729967117310e-1 }; + for (int degree = 3; degree <= maxPadeDegree; ++degree) + if (normTminusI <= maxNormForPade[degree - minPadeDegree]) + return degree; + assert(false); // this line should never be reached +} + +/* \brief Get suitable degree for Pade approximation. (specialized for RealScalar = double) */ +template +int MatrixLogarithmAtomic::getPadeDegree(double normTminusI) +{ + const double maxNormForPade[] = { 1.6206284795015624e-2 /* degree = 3 */ , 5.3873532631381171e-2, + 1.1352802267628681e-1, 1.8662860613541288e-1, 2.642960831111435e-1 }; + for (int degree = 3; degree <= maxPadeDegree; ++degree) + if (normTminusI <= maxNormForPade[degree - minPadeDegree]) + return degree; + assert(false); // this line should never be reached +} + +/* \brief Get suitable degree for Pade approximation. (specialized for RealScalar = long double) */ +template +int MatrixLogarithmAtomic::getPadeDegree(long double normTminusI) +{ +#if LDBL_MANT_DIG == 53 // double precision + const double maxNormForPade[] = { 1.6206284795015624e-2 /* degree = 3 */ , 5.3873532631381171e-2, + 1.1352802267628681e-1, 1.8662860613541288e-1, 2.642960831111435e-1 }; +#elif LDBL_MANT_DIG <= 64 // extended precision + const double maxNormForPade[] = { 5.48256690357782863103e-3 /* degree = 3 */, 2.34559162387971167321e-2, + 5.84603923897347449857e-2, 1.08486423756725170223e-1, 1.68385767881294446649e-1, + 2.32777776523703892094e-1 }; +#elif LDBL_MANT_DIG <= 106 // double-double + const double maxNormForPade[] = { 8.58970550342939562202529664318890e-5 /* degree = 3 */, + 9.34074328446359654039446552677759e-4, 4.26117194647672175773064114582860e-3, + 1.21546224740281848743149666560464e-2, 2.61100544998339436713088248557444e-2, + 4.66170074627052749243018566390567e-2, 7.32585144444135027565872014932387e-2, + 1.05026503471351080481093652651105e-1 }; +#else // quadruple precision + const double maxNormForPade[] = { 4.7419931187193005048501568167858103e-5 /* degree = 3 */, + 5.8853168473544560470387769480192666e-4, 2.9216120366601315391789493628113520e-3, + 8.8415758124319434347116734705174308e-3, 1.9850836029449446668518049562565291e-2, + 3.6688019729653446926585242192447447e-2, 5.9290962294020186998954055264528393e-2, + 8.6998436081634343903250580992127677e-2, 1.1880960220216759245467951592883642e-1 }; +#endif + for (int degree = 3; degree <= maxPadeDegree; ++degree) + if (normTminusI <= maxNormForPade[degree - minPadeDegree]) + return degree; + assert(false); // this line should never be reached +} + +/* \brief Compute Pade approximation to matrix logarithm */ +template +void MatrixLogarithmAtomic::computePade(MatrixType& result, const MatrixType& T, int degree) +{ + switch (degree) { + case 3: computePade3(result, T); break; + case 4: computePade4(result, T); break; + case 5: computePade5(result, T); break; + case 6: computePade6(result, T); break; + case 7: computePade7(result, T); break; + case 8: computePade8(result, T); break; + case 9: computePade9(result, T); break; + case 10: computePade10(result, T); break; + case 11: computePade11(result, T); break; + default: assert(false); // should never happen + } +} + +template +void MatrixLogarithmAtomic::computePade3(MatrixType& result, const MatrixType& T) +{ + const int degree = 3; + const RealScalar nodes[] = { 0.1127016653792583114820734600217600L, 0.5000000000000000000000000000000000L, + 0.8872983346207416885179265399782400L }; + const RealScalar weights[] = { 0.2777777777777777777777777777777778L, 0.4444444444444444444444444444444444L, + 0.2777777777777777777777777777777778L }; + assert(degree <= maxPadeDegree); + MatrixType TminusI = T - MatrixType::Identity(T.rows(), T.rows()); + result.setZero(T.rows(), T.rows()); + for (int k = 0; k < degree; ++k) + result += weights[k] * (MatrixType::Identity(T.rows(), T.rows()) + nodes[k] * TminusI) + .template triangularView().solve(TminusI); +} + +template +void MatrixLogarithmAtomic::computePade4(MatrixType& result, const MatrixType& T) +{ + const int degree = 4; + const RealScalar nodes[] = { 0.0694318442029737123880267555535953L, 0.3300094782075718675986671204483777L, + 0.6699905217924281324013328795516223L, 0.9305681557970262876119732444464048L }; + const RealScalar weights[] = { 0.1739274225687269286865319746109997L, 0.3260725774312730713134680253890003L, + 0.3260725774312730713134680253890003L, 0.1739274225687269286865319746109997L }; + assert(degree <= maxPadeDegree); + MatrixType TminusI = T - MatrixType::Identity(T.rows(), T.rows()); + result.setZero(T.rows(), T.rows()); + for (int k = 0; k < degree; ++k) + result += weights[k] * (MatrixType::Identity(T.rows(), T.rows()) + nodes[k] * TminusI) + .template triangularView().solve(TminusI); +} + +template +void MatrixLogarithmAtomic::computePade5(MatrixType& result, const MatrixType& T) +{ + const int degree = 5; + const RealScalar nodes[] = { 0.0469100770306680036011865608503035L, 0.2307653449471584544818427896498956L, + 0.5000000000000000000000000000000000L, 0.7692346550528415455181572103501044L, + 0.9530899229693319963988134391496965L }; + const RealScalar weights[] = { 0.1184634425280945437571320203599587L, 0.2393143352496832340206457574178191L, + 0.2844444444444444444444444444444444L, 0.2393143352496832340206457574178191L, + 0.1184634425280945437571320203599587L }; + assert(degree <= maxPadeDegree); + MatrixType TminusI = T - MatrixType::Identity(T.rows(), T.rows()); + result.setZero(T.rows(), T.rows()); + for (int k = 0; k < degree; ++k) + result += weights[k] * (MatrixType::Identity(T.rows(), T.rows()) + nodes[k] * TminusI) + .template triangularView().solve(TminusI); +} + +template +void MatrixLogarithmAtomic::computePade6(MatrixType& result, const MatrixType& T) +{ + const int degree = 6; + const RealScalar nodes[] = { 0.0337652428984239860938492227530027L, 0.1693953067668677431693002024900473L, + 0.3806904069584015456847491391596440L, 0.6193095930415984543152508608403560L, + 0.8306046932331322568306997975099527L, 0.9662347571015760139061507772469973L }; + const RealScalar weights[] = { 0.0856622461895851725201480710863665L, 0.1803807865240693037849167569188581L, + 0.2339569672863455236949351719947755L, 0.2339569672863455236949351719947755L, + 0.1803807865240693037849167569188581L, 0.0856622461895851725201480710863665L }; + assert(degree <= maxPadeDegree); + MatrixType TminusI = T - MatrixType::Identity(T.rows(), T.rows()); + result.setZero(T.rows(), T.rows()); + for (int k = 0; k < degree; ++k) + result += weights[k] * (MatrixType::Identity(T.rows(), T.rows()) + nodes[k] * TminusI) + .template triangularView().solve(TminusI); +} + +template +void MatrixLogarithmAtomic::computePade7(MatrixType& result, const MatrixType& T) +{ + const int degree = 7; + const RealScalar nodes[] = { 0.0254460438286207377369051579760744L, 0.1292344072003027800680676133596058L, + 0.2970774243113014165466967939615193L, 0.5000000000000000000000000000000000L, + 0.7029225756886985834533032060384807L, 0.8707655927996972199319323866403942L, + 0.9745539561713792622630948420239256L }; + const RealScalar weights[] = { 0.0647424830844348466353057163395410L, 0.1398526957446383339507338857118898L, + 0.1909150252525594724751848877444876L, 0.2089795918367346938775510204081633L, + 0.1909150252525594724751848877444876L, 0.1398526957446383339507338857118898L, + 0.0647424830844348466353057163395410L }; + assert(degree <= maxPadeDegree); + MatrixType TminusI = T - MatrixType::Identity(T.rows(), T.rows()); + result.setZero(T.rows(), T.rows()); + for (int k = 0; k < degree; ++k) + result += weights[k] * (MatrixType::Identity(T.rows(), T.rows()) + nodes[k] * TminusI) + .template triangularView().solve(TminusI); +} + +template +void MatrixLogarithmAtomic::computePade8(MatrixType& result, const MatrixType& T) +{ + const int degree = 8; + const RealScalar nodes[] = { 0.0198550717512318841582195657152635L, 0.1016667612931866302042230317620848L, + 0.2372337950418355070911304754053768L, 0.4082826787521750975302619288199080L, + 0.5917173212478249024697380711800920L, 0.7627662049581644929088695245946232L, + 0.8983332387068133697957769682379152L, 0.9801449282487681158417804342847365L }; + const RealScalar weights[] = { 0.0506142681451881295762656771549811L, 0.1111905172266872352721779972131204L, + 0.1568533229389436436689811009933007L, 0.1813418916891809914825752246385978L, + 0.1813418916891809914825752246385978L, 0.1568533229389436436689811009933007L, + 0.1111905172266872352721779972131204L, 0.0506142681451881295762656771549811L }; + assert(degree <= maxPadeDegree); + MatrixType TminusI = T - MatrixType::Identity(T.rows(), T.rows()); + result.setZero(T.rows(), T.rows()); + for (int k = 0; k < degree; ++k) + result += weights[k] * (MatrixType::Identity(T.rows(), T.rows()) + nodes[k] * TminusI) + .template triangularView().solve(TminusI); +} + +template +void MatrixLogarithmAtomic::computePade9(MatrixType& result, const MatrixType& T) +{ + const int degree = 9; + const RealScalar nodes[] = { 0.0159198802461869550822118985481636L, 0.0819844463366821028502851059651326L, + 0.1933142836497048013456489803292629L, 0.3378732882980955354807309926783317L, + 0.5000000000000000000000000000000000L, 0.6621267117019044645192690073216683L, + 0.8066857163502951986543510196707371L, 0.9180155536633178971497148940348674L, + 0.9840801197538130449177881014518364L }; + const RealScalar weights[] = { 0.0406371941807872059859460790552618L, 0.0903240803474287020292360156214564L, + 0.1303053482014677311593714347093164L, 0.1561735385200014200343152032922218L, + 0.1651196775006298815822625346434870L, 0.1561735385200014200343152032922218L, + 0.1303053482014677311593714347093164L, 0.0903240803474287020292360156214564L, + 0.0406371941807872059859460790552618L }; + assert(degree <= maxPadeDegree); + MatrixType TminusI = T - MatrixType::Identity(T.rows(), T.rows()); + result.setZero(T.rows(), T.rows()); + for (int k = 0; k < degree; ++k) + result += weights[k] * (MatrixType::Identity(T.rows(), T.rows()) + nodes[k] * TminusI) + .template triangularView().solve(TminusI); +} + +template +void MatrixLogarithmAtomic::computePade10(MatrixType& result, const MatrixType& T) +{ + const int degree = 10; + const RealScalar nodes[] = { 0.0130467357414141399610179939577740L, 0.0674683166555077446339516557882535L, + 0.1602952158504877968828363174425632L, 0.2833023029353764046003670284171079L, + 0.4255628305091843945575869994351400L, 0.5744371694908156054424130005648600L, + 0.7166976970646235953996329715828921L, 0.8397047841495122031171636825574368L, + 0.9325316833444922553660483442117465L, 0.9869532642585858600389820060422260L }; + const RealScalar weights[] = { 0.0333356721543440687967844049466659L, 0.0747256745752902965728881698288487L, + 0.1095431812579910219977674671140816L, 0.1346333596549981775456134607847347L, + 0.1477621123573764350869464973256692L, 0.1477621123573764350869464973256692L, + 0.1346333596549981775456134607847347L, 0.1095431812579910219977674671140816L, + 0.0747256745752902965728881698288487L, 0.0333356721543440687967844049466659L }; + assert(degree <= maxPadeDegree); + MatrixType TminusI = T - MatrixType::Identity(T.rows(), T.rows()); + result.setZero(T.rows(), T.rows()); + for (int k = 0; k < degree; ++k) + result += weights[k] * (MatrixType::Identity(T.rows(), T.rows()) + nodes[k] * TminusI) + .template triangularView().solve(TminusI); +} + +template +void MatrixLogarithmAtomic::computePade11(MatrixType& result, const MatrixType& T) +{ + const int degree = 11; + const RealScalar nodes[] = { 0.0108856709269715035980309994385713L, 0.0564687001159523504624211153480364L, + 0.1349239972129753379532918739844233L, 0.2404519353965940920371371652706952L, + 0.3652284220238275138342340072995692L, 0.5000000000000000000000000000000000L, + 0.6347715779761724861657659927004308L, 0.7595480646034059079628628347293048L, + 0.8650760027870246620467081260155767L, 0.9435312998840476495375788846519636L, + 0.9891143290730284964019690005614287L }; + const RealScalar weights[] = { 0.0278342835580868332413768602212743L, 0.0627901847324523123173471496119701L, + 0.0931451054638671257130488207158280L, 0.1165968822959952399592618524215876L, + 0.1314022722551233310903444349452546L, 0.1364625433889503153572417641681711L, + 0.1314022722551233310903444349452546L, 0.1165968822959952399592618524215876L, + 0.0931451054638671257130488207158280L, 0.0627901847324523123173471496119701L, + 0.0278342835580868332413768602212743L }; + assert(degree <= maxPadeDegree); + MatrixType TminusI = T - MatrixType::Identity(T.rows(), T.rows()); + result.setZero(T.rows(), T.rows()); + for (int k = 0; k < degree; ++k) + result += weights[k] * (MatrixType::Identity(T.rows(), T.rows()) + nodes[k] * TminusI) + .template triangularView().solve(TminusI); +} + +/** \ingroup MatrixFunctions_Module + * + * \brief Proxy for the matrix logarithm of some matrix (expression). + * + * \tparam Derived Type of the argument to the matrix function. + * + * This class holds the argument to the matrix function until it is + * assigned or evaluated for some other reason (so the argument + * should not be changed in the meantime). It is the return type of + * matrixBase::matrixLogarithm() and most of the time this is the + * only way it is used. + */ +template class MatrixLogarithmReturnValue +: public ReturnByValue > +{ +public: + + typedef typename Derived::Scalar Scalar; + typedef typename Derived::Index Index; + + /** \brief Constructor. + * + * \param[in] A %Matrix (expression) forming the argument of the matrix logarithm. + */ + MatrixLogarithmReturnValue(const Derived& A) : m_A(A) { } + + /** \brief Compute the matrix logarithm. + * + * \param[out] result Logarithm of \p A, where \A is as specified in the constructor. + */ + template + inline void evalTo(ResultType& result) const + { + typedef typename Derived::PlainObject PlainObject; + typedef internal::traits Traits; + static const int RowsAtCompileTime = Traits::RowsAtCompileTime; + static const int ColsAtCompileTime = Traits::ColsAtCompileTime; + static const int Options = PlainObject::Options; + typedef std::complex::Real> ComplexScalar; + typedef Matrix DynMatrixType; + typedef MatrixLogarithmAtomic AtomicType; + AtomicType atomic; + + const PlainObject Aevaluated = m_A.eval(); + MatrixFunction mf(Aevaluated, atomic); + mf.compute(result); + } + + Index rows() const { return m_A.rows(); } + Index cols() const { return m_A.cols(); } + +private: + typename internal::nested::type m_A; + + MatrixLogarithmReturnValue& operator=(const MatrixLogarithmReturnValue&); +}; + +namespace internal { + template + struct traits > + { + typedef typename Derived::PlainObject ReturnType; + }; +} + + +/********** MatrixBase method **********/ + + +template +const MatrixLogarithmReturnValue MatrixBase::log() const +{ + eigen_assert(rows() == cols()); + return MatrixLogarithmReturnValue(derived()); +} + +} // end namespace Eigen + +#endif // EIGEN_MATRIX_LOGARITHM diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/MatrixFunctions/MatrixSquareRoot.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/MatrixFunctions/MatrixSquareRoot.h new file mode 100644 index 000000000..658cd334c --- /dev/null +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/MatrixFunctions/MatrixSquareRoot.h @@ -0,0 +1,499 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2011 Jitse Niesen +// +// Eigen is free software; you can redistribute it and/or +// modify it under the terms of the GNU Lesser General Public +// License as published by the Free Software Foundation; either +// version 3 of the License, or (at your option) any later version. +// +// Alternatively, you can redistribute it and/or +// modify it under the terms of the GNU General Public License as +// published by the Free Software Foundation; either version 2 of +// the License, or (at your option) any later version. +// +// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY +// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the +// GNU General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public +// License and a copy of the GNU General Public License along with +// Eigen. If not, see . + +#ifndef EIGEN_MATRIX_SQUARE_ROOT +#define EIGEN_MATRIX_SQUARE_ROOT + +namespace Eigen { + +/** \ingroup MatrixFunctions_Module + * \brief Class for computing matrix square roots of upper quasi-triangular matrices. + * \tparam MatrixType type of the argument of the matrix square root, + * expected to be an instantiation of the Matrix class template. + * + * This class computes the square root of the upper quasi-triangular + * matrix stored in the upper Hessenberg part of the matrix passed to + * the constructor. + * + * \sa MatrixSquareRoot, MatrixSquareRootTriangular + */ +template +class MatrixSquareRootQuasiTriangular +{ + public: + + /** \brief Constructor. + * + * \param[in] A upper quasi-triangular matrix whose square root + * is to be computed. + * + * The class stores a reference to \p A, so it should not be + * changed (or destroyed) before compute() is called. + */ + MatrixSquareRootQuasiTriangular(const MatrixType& A) + : m_A(A) + { + eigen_assert(A.rows() == A.cols()); + } + + /** \brief Compute the matrix square root + * + * \param[out] result square root of \p A, as specified in the constructor. + * + * Only the upper Hessenberg part of \p result is updated, the + * rest is not touched. See MatrixBase::sqrt() for details on + * how this computation is implemented. + */ + template void compute(ResultType &result); + + private: + typedef typename MatrixType::Index Index; + typedef typename MatrixType::Scalar Scalar; + + void computeDiagonalPartOfSqrt(MatrixType& sqrtT, const MatrixType& T); + void computeOffDiagonalPartOfSqrt(MatrixType& sqrtT, const MatrixType& T); + void compute2x2diagonalBlock(MatrixType& sqrtT, const MatrixType& T, typename MatrixType::Index i); + void compute1x1offDiagonalBlock(MatrixType& sqrtT, const MatrixType& T, + typename MatrixType::Index i, typename MatrixType::Index j); + void compute1x2offDiagonalBlock(MatrixType& sqrtT, const MatrixType& T, + typename MatrixType::Index i, typename MatrixType::Index j); + void compute2x1offDiagonalBlock(MatrixType& sqrtT, const MatrixType& T, + typename MatrixType::Index i, typename MatrixType::Index j); + void compute2x2offDiagonalBlock(MatrixType& sqrtT, const MatrixType& T, + typename MatrixType::Index i, typename MatrixType::Index j); + + template + static void solveAuxiliaryEquation(SmallMatrixType& X, const SmallMatrixType& A, + const SmallMatrixType& B, const SmallMatrixType& C); + + const MatrixType& m_A; +}; + +template +template +void MatrixSquareRootQuasiTriangular::compute(ResultType &result) +{ + // Compute Schur decomposition of m_A + const RealSchur schurOfA(m_A); + const MatrixType& T = schurOfA.matrixT(); + const MatrixType& U = schurOfA.matrixU(); + + // Compute square root of T + MatrixType sqrtT = MatrixType::Zero(m_A.rows(), m_A.rows()); + computeDiagonalPartOfSqrt(sqrtT, T); + computeOffDiagonalPartOfSqrt(sqrtT, T); + + // Compute square root of m_A + result = U * sqrtT * U.adjoint(); +} + +// pre: T is quasi-upper-triangular and sqrtT is a zero matrix of the same size +// post: the diagonal blocks of sqrtT are the square roots of the diagonal blocks of T +template +void MatrixSquareRootQuasiTriangular::computeDiagonalPartOfSqrt(MatrixType& sqrtT, + const MatrixType& T) +{ + const Index size = m_A.rows(); + for (Index i = 0; i < size; i++) { + if (i == size - 1 || T.coeff(i+1, i) == 0) { + eigen_assert(T(i,i) > 0); + sqrtT.coeffRef(i,i) = internal::sqrt(T.coeff(i,i)); + } + else { + compute2x2diagonalBlock(sqrtT, T, i); + ++i; + } + } +} + +// pre: T is quasi-upper-triangular and diagonal blocks of sqrtT are square root of diagonal blocks of T. +// post: sqrtT is the square root of T. +template +void MatrixSquareRootQuasiTriangular::computeOffDiagonalPartOfSqrt(MatrixType& sqrtT, + const MatrixType& T) +{ + const Index size = m_A.rows(); + for (Index j = 1; j < size; j++) { + if (T.coeff(j, j-1) != 0) // if T(j-1:j, j-1:j) is a 2-by-2 block + continue; + for (Index i = j-1; i >= 0; i--) { + if (i > 0 && T.coeff(i, i-1) != 0) // if T(i-1:i, i-1:i) is a 2-by-2 block + continue; + bool iBlockIs2x2 = (i < size - 1) && (T.coeff(i+1, i) != 0); + bool jBlockIs2x2 = (j < size - 1) && (T.coeff(j+1, j) != 0); + if (iBlockIs2x2 && jBlockIs2x2) + compute2x2offDiagonalBlock(sqrtT, T, i, j); + else if (iBlockIs2x2 && !jBlockIs2x2) + compute2x1offDiagonalBlock(sqrtT, T, i, j); + else if (!iBlockIs2x2 && jBlockIs2x2) + compute1x2offDiagonalBlock(sqrtT, T, i, j); + else if (!iBlockIs2x2 && !jBlockIs2x2) + compute1x1offDiagonalBlock(sqrtT, T, i, j); + } + } +} + +// pre: T.block(i,i,2,2) has complex conjugate eigenvalues +// post: sqrtT.block(i,i,2,2) is square root of T.block(i,i,2,2) +template +void MatrixSquareRootQuasiTriangular + ::compute2x2diagonalBlock(MatrixType& sqrtT, const MatrixType& T, typename MatrixType::Index i) +{ + // TODO: This case (2-by-2 blocks with complex conjugate eigenvalues) is probably hidden somewhere + // in EigenSolver. If we expose it, we could call it directly from here. + Matrix block = T.template block<2,2>(i,i); + EigenSolver > es(block); + sqrtT.template block<2,2>(i,i) + = (es.eigenvectors() * es.eigenvalues().cwiseSqrt().asDiagonal() * es.eigenvectors().inverse()).real(); +} + +// pre: block structure of T is such that (i,j) is a 1x1 block, +// all blocks of sqrtT to left of and below (i,j) are correct +// post: sqrtT(i,j) has the correct value +template +void MatrixSquareRootQuasiTriangular + ::compute1x1offDiagonalBlock(MatrixType& sqrtT, const MatrixType& T, + typename MatrixType::Index i, typename MatrixType::Index j) +{ + Scalar tmp = (sqrtT.row(i).segment(i+1,j-i-1) * sqrtT.col(j).segment(i+1,j-i-1)).value(); + sqrtT.coeffRef(i,j) = (T.coeff(i,j) - tmp) / (sqrtT.coeff(i,i) + sqrtT.coeff(j,j)); +} + +// similar to compute1x1offDiagonalBlock() +template +void MatrixSquareRootQuasiTriangular + ::compute1x2offDiagonalBlock(MatrixType& sqrtT, const MatrixType& T, + typename MatrixType::Index i, typename MatrixType::Index j) +{ + Matrix rhs = T.template block<1,2>(i,j); + if (j-i > 1) + rhs -= sqrtT.block(i, i+1, 1, j-i-1) * sqrtT.block(i+1, j, j-i-1, 2); + Matrix A = sqrtT.coeff(i,i) * Matrix::Identity(); + A += sqrtT.template block<2,2>(j,j).transpose(); + sqrtT.template block<1,2>(i,j).transpose() = A.fullPivLu().solve(rhs.transpose()); +} + +// similar to compute1x1offDiagonalBlock() +template +void MatrixSquareRootQuasiTriangular + ::compute2x1offDiagonalBlock(MatrixType& sqrtT, const MatrixType& T, + typename MatrixType::Index i, typename MatrixType::Index j) +{ + Matrix rhs = T.template block<2,1>(i,j); + if (j-i > 2) + rhs -= sqrtT.block(i, i+2, 2, j-i-2) * sqrtT.block(i+2, j, j-i-2, 1); + Matrix A = sqrtT.coeff(j,j) * Matrix::Identity(); + A += sqrtT.template block<2,2>(i,i); + sqrtT.template block<2,1>(i,j) = A.fullPivLu().solve(rhs); +} + +// similar to compute1x1offDiagonalBlock() +template +void MatrixSquareRootQuasiTriangular + ::compute2x2offDiagonalBlock(MatrixType& sqrtT, const MatrixType& T, + typename MatrixType::Index i, typename MatrixType::Index j) +{ + Matrix A = sqrtT.template block<2,2>(i,i); + Matrix B = sqrtT.template block<2,2>(j,j); + Matrix C = T.template block<2,2>(i,j); + if (j-i > 2) + C -= sqrtT.block(i, i+2, 2, j-i-2) * sqrtT.block(i+2, j, j-i-2, 2); + Matrix X; + solveAuxiliaryEquation(X, A, B, C); + sqrtT.template block<2,2>(i,j) = X; +} + +// solves the equation A X + X B = C where all matrices are 2-by-2 +template +template +void MatrixSquareRootQuasiTriangular + ::solveAuxiliaryEquation(SmallMatrixType& X, const SmallMatrixType& A, + const SmallMatrixType& B, const SmallMatrixType& C) +{ + EIGEN_STATIC_ASSERT((internal::is_same >::value), + EIGEN_INTERNAL_ERROR_PLEASE_FILE_A_BUG_REPORT); + + Matrix coeffMatrix = Matrix::Zero(); + coeffMatrix.coeffRef(0,0) = A.coeff(0,0) + B.coeff(0,0); + coeffMatrix.coeffRef(1,1) = A.coeff(0,0) + B.coeff(1,1); + coeffMatrix.coeffRef(2,2) = A.coeff(1,1) + B.coeff(0,0); + coeffMatrix.coeffRef(3,3) = A.coeff(1,1) + B.coeff(1,1); + coeffMatrix.coeffRef(0,1) = B.coeff(1,0); + coeffMatrix.coeffRef(0,2) = A.coeff(0,1); + coeffMatrix.coeffRef(1,0) = B.coeff(0,1); + coeffMatrix.coeffRef(1,3) = A.coeff(0,1); + coeffMatrix.coeffRef(2,0) = A.coeff(1,0); + coeffMatrix.coeffRef(2,3) = B.coeff(1,0); + coeffMatrix.coeffRef(3,1) = A.coeff(1,0); + coeffMatrix.coeffRef(3,2) = B.coeff(0,1); + + Matrix rhs; + rhs.coeffRef(0) = C.coeff(0,0); + rhs.coeffRef(1) = C.coeff(0,1); + rhs.coeffRef(2) = C.coeff(1,0); + rhs.coeffRef(3) = C.coeff(1,1); + + Matrix result; + result = coeffMatrix.fullPivLu().solve(rhs); + + X.coeffRef(0,0) = result.coeff(0); + X.coeffRef(0,1) = result.coeff(1); + X.coeffRef(1,0) = result.coeff(2); + X.coeffRef(1,1) = result.coeff(3); +} + + +/** \ingroup MatrixFunctions_Module + * \brief Class for computing matrix square roots of upper triangular matrices. + * \tparam MatrixType type of the argument of the matrix square root, + * expected to be an instantiation of the Matrix class template. + * + * This class computes the square root of the upper triangular matrix + * stored in the upper triangular part (including the diagonal) of + * the matrix passed to the constructor. + * + * \sa MatrixSquareRoot, MatrixSquareRootQuasiTriangular + */ +template +class MatrixSquareRootTriangular +{ + public: + MatrixSquareRootTriangular(const MatrixType& A) + : m_A(A) + { + eigen_assert(A.rows() == A.cols()); + } + + /** \brief Compute the matrix square root + * + * \param[out] result square root of \p A, as specified in the constructor. + * + * Only the upper triangular part (including the diagonal) of + * \p result is updated, the rest is not touched. See + * MatrixBase::sqrt() for details on how this computation is + * implemented. + */ + template void compute(ResultType &result); + + private: + const MatrixType& m_A; +}; + +template +template +void MatrixSquareRootTriangular::compute(ResultType &result) +{ + // Compute Schur decomposition of m_A + const ComplexSchur schurOfA(m_A); + const MatrixType& T = schurOfA.matrixT(); + const MatrixType& U = schurOfA.matrixU(); + + // Compute square root of T and store it in upper triangular part of result + // This uses that the square root of triangular matrices can be computed directly. + result.resize(m_A.rows(), m_A.cols()); + typedef typename MatrixType::Index Index; + for (Index i = 0; i < m_A.rows(); i++) { + result.coeffRef(i,i) = internal::sqrt(T.coeff(i,i)); + } + for (Index j = 1; j < m_A.cols(); j++) { + for (Index i = j-1; i >= 0; i--) { + typedef typename MatrixType::Scalar Scalar; + // if i = j-1, then segment has length 0 so tmp = 0 + Scalar tmp = (result.row(i).segment(i+1,j-i-1) * result.col(j).segment(i+1,j-i-1)).value(); + // denominator may be zero if original matrix is singular + result.coeffRef(i,j) = (T.coeff(i,j) - tmp) / (result.coeff(i,i) + result.coeff(j,j)); + } + } + + // Compute square root of m_A as U * result * U.adjoint() + MatrixType tmp; + tmp.noalias() = U * result.template triangularView(); + result.noalias() = tmp * U.adjoint(); +} + + +/** \ingroup MatrixFunctions_Module + * \brief Class for computing matrix square roots of general matrices. + * \tparam MatrixType type of the argument of the matrix square root, + * expected to be an instantiation of the Matrix class template. + * + * \sa MatrixSquareRootTriangular, MatrixSquareRootQuasiTriangular, MatrixBase::sqrt() + */ +template ::Scalar>::IsComplex> +class MatrixSquareRoot +{ + public: + + /** \brief Constructor. + * + * \param[in] A matrix whose square root is to be computed. + * + * The class stores a reference to \p A, so it should not be + * changed (or destroyed) before compute() is called. + */ + MatrixSquareRoot(const MatrixType& A); + + /** \brief Compute the matrix square root + * + * \param[out] result square root of \p A, as specified in the constructor. + * + * See MatrixBase::sqrt() for details on how this computation is + * implemented. + */ + template void compute(ResultType &result); +}; + + +// ********** Partial specialization for real matrices ********** + +template +class MatrixSquareRoot +{ + public: + + MatrixSquareRoot(const MatrixType& A) + : m_A(A) + { + eigen_assert(A.rows() == A.cols()); + } + + template void compute(ResultType &result) + { + // Compute Schur decomposition of m_A + const RealSchur schurOfA(m_A); + const MatrixType& T = schurOfA.matrixT(); + const MatrixType& U = schurOfA.matrixU(); + + // Compute square root of T + MatrixSquareRootQuasiTriangular tmp(T); + MatrixType sqrtT = MatrixType::Zero(m_A.rows(), m_A.rows()); + tmp.compute(sqrtT); + + // Compute square root of m_A + result = U * sqrtT * U.adjoint(); + } + + private: + const MatrixType& m_A; +}; + + +// ********** Partial specialization for complex matrices ********** + +template +class MatrixSquareRoot +{ + public: + + MatrixSquareRoot(const MatrixType& A) + : m_A(A) + { + eigen_assert(A.rows() == A.cols()); + } + + template void compute(ResultType &result) + { + // Compute Schur decomposition of m_A + const ComplexSchur schurOfA(m_A); + const MatrixType& T = schurOfA.matrixT(); + const MatrixType& U = schurOfA.matrixU(); + + // Compute square root of T + MatrixSquareRootTriangular tmp(T); + MatrixType sqrtT = MatrixType::Zero(m_A.rows(), m_A.rows()); + tmp.compute(sqrtT); + + // Compute square root of m_A + result = U * sqrtT * U.adjoint(); + } + + private: + const MatrixType& m_A; +}; + + +/** \ingroup MatrixFunctions_Module + * + * \brief Proxy for the matrix square root of some matrix (expression). + * + * \tparam Derived Type of the argument to the matrix square root. + * + * This class holds the argument to the matrix square root until it + * is assigned or evaluated for some other reason (so the argument + * should not be changed in the meantime). It is the return type of + * MatrixBase::sqrt() and most of the time this is the only way it is + * used. + */ +template class MatrixSquareRootReturnValue +: public ReturnByValue > +{ + typedef typename Derived::Index Index; + public: + /** \brief Constructor. + * + * \param[in] src %Matrix (expression) forming the argument of the + * matrix square root. + */ + MatrixSquareRootReturnValue(const Derived& src) : m_src(src) { } + + /** \brief Compute the matrix square root. + * + * \param[out] result the matrix square root of \p src in the + * constructor. + */ + template + inline void evalTo(ResultType& result) const + { + const typename Derived::PlainObject srcEvaluated = m_src.eval(); + MatrixSquareRoot me(srcEvaluated); + me.compute(result); + } + + Index rows() const { return m_src.rows(); } + Index cols() const { return m_src.cols(); } + + protected: + const Derived& m_src; + private: + MatrixSquareRootReturnValue& operator=(const MatrixSquareRootReturnValue&); +}; + +namespace internal { +template +struct traits > +{ + typedef typename Derived::PlainObject ReturnType; +}; +} + +template +const MatrixSquareRootReturnValue MatrixBase::sqrt() const +{ + eigen_assert(rows() == cols()); + return MatrixSquareRootReturnValue(derived()); +} + +} // end namespace Eigen + +#endif // EIGEN_MATRIX_FUNCTION diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/MatrixFunctions/StemFunction.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/MatrixFunctions/StemFunction.h index 260690b63..3de68ec3a 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/MatrixFunctions/StemFunction.h +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/MatrixFunctions/StemFunction.h @@ -25,6 +25,8 @@ #ifndef EIGEN_STEM_FUNCTION #define EIGEN_STEM_FUNCTION +namespace Eigen { + /** \ingroup MatrixFunctions_Module * \brief Stem functions corresponding to standard mathematical functions. */ @@ -113,4 +115,6 @@ class StdStemFunctions }; // end of class StdStemFunctions +} // end namespace Eigen + #endif // EIGEN_STEM_FUNCTION diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/MoreVectorization/MathFunctions.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/MoreVectorization/MathFunctions.h index bc948d0bd..123f4016e 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/MoreVectorization/MathFunctions.h +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/MoreVectorization/MathFunctions.h @@ -26,6 +26,8 @@ #ifndef EIGEN_MOREVECTORIZATION_MATHFUNCTIONS_H #define EIGEN_MOREVECTORIZATION_MATHFUNCTIONS_H +namespace Eigen { + namespace internal { /** \internal \returns the arcsin of \a a (coeff-wise) */ @@ -99,8 +101,10 @@ template<> EIGEN_DONT_INLINE Packet4f pasin(Packet4f x) return _mm_xor_ps(z, sign_bit); } +#endif // EIGEN_VECTORIZE_SSE + } // end namespace internal -#endif +} // end namespace Eigen #endif // EIGEN_MOREVECTORIZATION_MATHFUNCTIONS_H diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/NonLinearOptimization/HybridNonLinearSolver.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/NonLinearOptimization/HybridNonLinearSolver.h index 37abb6117..aa9430359 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/NonLinearOptimization/HybridNonLinearSolver.h +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/NonLinearOptimization/HybridNonLinearSolver.h @@ -28,6 +28,8 @@ #ifndef EIGEN_HYBRIDNONLINEARSOLVER_H #define EIGEN_HYBRIDNONLINEARSOLVER_H +namespace Eigen { + namespace HybridNonLinearSolverSpace { enum Status { Running = -1, @@ -602,6 +604,8 @@ HybridNonLinearSolver::solveNumericalDiff(FVectorType &x) return status; } -//vim: ai ts=4 sts=4 et sw=4 +} // end namespace Eigen + #endif // EIGEN_HYBRIDNONLINEARSOLVER_H +//vim: ai ts=4 sts=4 et sw=4 diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/NonLinearOptimization/LevenbergMarquardt.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/NonLinearOptimization/LevenbergMarquardt.h index 0ae681b1c..1cb501a66 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/NonLinearOptimization/LevenbergMarquardt.h +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/NonLinearOptimization/LevenbergMarquardt.h @@ -28,6 +28,7 @@ #ifndef EIGEN_LEVENBERGMARQUARDT__H #define EIGEN_LEVENBERGMARQUARDT__H +namespace Eigen { namespace LevenbergMarquardtSpace { enum Status { @@ -640,7 +641,7 @@ LevenbergMarquardt::lmdif1( NumericalDiff numDiff(functor); // embedded LevenbergMarquardt - LevenbergMarquardt > lm(numDiff); + LevenbergMarquardt, Scalar > lm(numDiff); lm.parameters.ftol = tol; lm.parameters.xtol = tol; lm.parameters.maxfev = 200*(n+1); @@ -651,6 +652,8 @@ LevenbergMarquardt::lmdif1( return info; } -//vim: ai ts=4 sts=4 et sw=4 +} // end namespace Eigen + #endif // EIGEN_LEVENBERGMARQUARDT__H +//vim: ai ts=4 sts=4 et sw=4 diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/NonLinearOptimization/chkder.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/NonLinearOptimization/chkder.h index bc0cb1880..fd3e0bc4a 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/NonLinearOptimization/chkder.h +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/NonLinearOptimization/chkder.h @@ -2,6 +2,8 @@ #define chkder_log10e 0.43429448190325182765 #define chkder_factor 100. +namespace Eigen { + namespace internal { template @@ -58,3 +60,4 @@ void chkder( } // end namespace internal +} // end namespace Eigen diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/NonLinearOptimization/covar.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/NonLinearOptimization/covar.h index 6c77916f5..c73a09645 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/NonLinearOptimization/covar.h +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/NonLinearOptimization/covar.h @@ -1,3 +1,5 @@ +namespace Eigen { + namespace internal { template @@ -63,3 +65,5 @@ void covar( } } // end namespace internal + +} // end namespace Eigen diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/NonLinearOptimization/dogleg.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/NonLinearOptimization/dogleg.h index cbdcf4b71..4fbc98bfc 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/NonLinearOptimization/dogleg.h +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/NonLinearOptimization/dogleg.h @@ -1,3 +1,5 @@ +namespace Eigen { + namespace internal { template @@ -98,3 +100,5 @@ algo_end: } } // end namespace internal + +} // end namespace Eigen diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/NonLinearOptimization/fdjac1.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/NonLinearOptimization/fdjac1.h index 0a26c2061..1cabe69ae 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/NonLinearOptimization/fdjac1.h +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/NonLinearOptimization/fdjac1.h @@ -1,3 +1,5 @@ +namespace Eigen { + namespace internal { template @@ -70,3 +72,5 @@ DenseIndex fdjac1( } } // end namespace internal + +} // end namespace Eigen diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/NonLinearOptimization/lmpar.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/NonLinearOptimization/lmpar.h index 62f4aabc9..cc1ca530f 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/NonLinearOptimization/lmpar.h +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/NonLinearOptimization/lmpar.h @@ -1,3 +1,5 @@ +namespace Eigen { + namespace internal { template @@ -288,3 +290,5 @@ void lmpar2( } } // end namespace internal + +} // end namespace Eigen diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/NonLinearOptimization/qrsolv.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/NonLinearOptimization/qrsolv.h index cb1764a41..feafd62a8 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/NonLinearOptimization/qrsolv.h +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/NonLinearOptimization/qrsolv.h @@ -1,3 +1,5 @@ +namespace Eigen { + namespace internal { // TODO : once qrsolv2 is removed, use ColPivHouseholderQR or PermutationMatrix instead of ipvt @@ -85,3 +87,5 @@ void qrsolv( } } // end namespace internal + +} // end namespace Eigen diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/NonLinearOptimization/r1mpyq.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/NonLinearOptimization/r1mpyq.h index ffe505cd5..36ff700e9 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/NonLinearOptimization/r1mpyq.h +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/NonLinearOptimization/r1mpyq.h @@ -1,3 +1,5 @@ +namespace Eigen { + namespace internal { // TODO : move this to GivensQR once there's such a thing in Eigen @@ -24,3 +26,5 @@ void r1mpyq(DenseIndex m, DenseIndex n, Scalar *a, const std::vector @@ -93,3 +95,5 @@ void r1updt( } } // end namespace internal + +} // end namespace Eigen diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/NonLinearOptimization/rwupdt.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/NonLinearOptimization/rwupdt.h index ab83f9b25..9ce079e22 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/NonLinearOptimization/rwupdt.h +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/NonLinearOptimization/rwupdt.h @@ -1,3 +1,5 @@ +namespace Eigen { + namespace internal { template @@ -44,3 +46,4 @@ void rwupdt( } // end namespace internal +} // end namespace Eigen diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/NumericalDiff/NumericalDiff.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/NumericalDiff/NumericalDiff.h index 52dc0ec01..8651585f2 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/NumericalDiff/NumericalDiff.h +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/NumericalDiff/NumericalDiff.h @@ -28,6 +28,8 @@ #ifndef EIGEN_NUMERICAL_DIFF_H #define EIGEN_NUMERICAL_DIFF_H +namespace Eigen { + enum NumericalDiffMode { Forward, Central @@ -64,7 +66,7 @@ public: template NumericalDiff(const T0& a0, const T1& a1) : Functor(a0, a1), epsfcn(0) {} template - NumericalDiff(const T0& a0, const T1& a1, const T1& a2) : Functor(a0, a1, a2), epsfcn(0) {} + NumericalDiff(const T0& a0, const T1& a1, const T2& a2) : Functor(a0, a1, a2), epsfcn(0) {} enum { InputsAtCompileTime = Functor::InputsAtCompileTime, @@ -134,6 +136,8 @@ private: NumericalDiff& operator=(const NumericalDiff&); }; +} // end namespace Eigen + //vim: ai ts=4 sts=4 et sw=4 #endif // EIGEN_NUMERICAL_DIFF_H diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/Polynomials/Companion.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/Polynomials/Companion.h index 608951d3c..8936b8fad 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/Polynomials/Companion.h +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/Polynomials/Companion.h @@ -29,10 +29,12 @@ // * Eigen/Core // * Eigen/src/PolynomialSolver.h -#ifndef EIGEN_PARSED_BY_DOXYGEN +namespace Eigen { namespace internal { +#ifndef EIGEN_PARSED_BY_DOXYGEN + template T radix(){ return 2; } @@ -283,4 +285,6 @@ void companion<_Scalar,_Deg>::balance() } // end namespace internal +} // end namespace Eigen + #endif // EIGEN_COMPANION_H diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/Polynomials/PolynomialSolver.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/Polynomials/PolynomialSolver.h index 417b93df2..71295a105 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/Polynomials/PolynomialSolver.h +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/Polynomials/PolynomialSolver.h @@ -25,6 +25,8 @@ #ifndef EIGEN_POLYNOMIAL_SOLVER_H #define EIGEN_POLYNOMIAL_SOLVER_H +namespace Eigen { + /** \ingroup Polynomials_Module * \class PolynomialSolverBase. * @@ -394,4 +396,6 @@ class PolynomialSolver<_Scalar,1> : public PolynomialSolverBase<_Scalar,1> using PS_Base::m_roots; }; +} // end namespace Eigen + #endif // EIGEN_POLYNOMIAL_SOLVER_H diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/Polynomials/PolynomialUtils.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/Polynomials/PolynomialUtils.h index 65942c52a..1fb1ed139 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/Polynomials/PolynomialUtils.h +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/Polynomials/PolynomialUtils.h @@ -25,6 +25,8 @@ #ifndef EIGEN_POLYNOMIAL_UTILS_H #define EIGEN_POLYNOMIAL_UTILS_H +namespace Eigen { + /** \ingroup Polynomials_Module * \returns the evaluation of the polynomial at x using Horner algorithm. * @@ -149,5 +151,6 @@ void roots_to_monicPolynomial( const RootVector& rv, Polynomial& poly ) } } +} // end namespace Eigen #endif // EIGEN_POLYNOMIAL_UTILS_H diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/Skyline/SkylineInplaceLU.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/Skyline/SkylineInplaceLU.h index 51537402e..ef36ac9b6 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/Skyline/SkylineInplaceLU.h +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/Skyline/SkylineInplaceLU.h @@ -25,6 +25,8 @@ #ifndef EIGEN_SKYLINEINPLACELU_H #define EIGEN_SKYLINEINPLACELU_H +namespace Eigen { + /** \ingroup Skyline_Module * * \class SkylineInplaceLU @@ -360,4 +362,6 @@ bool SkylineInplaceLU::solve(const MatrixBase &b, MatrixBa return true; } +} // end namespace Eigen + #endif // EIGEN_SKYLINELU_H diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/Skyline/SkylineMatrix.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/Skyline/SkylineMatrix.h index 31810df08..98a19ce53 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/Skyline/SkylineMatrix.h +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/Skyline/SkylineMatrix.h @@ -28,6 +28,8 @@ #include "SkylineStorage.h" #include "SkylineMatrixBase.h" +namespace Eigen { + /** \ingroup Skyline_Module * * \class SkylineMatrix @@ -870,4 +872,6 @@ protected: const Index m_end; }; +} // end namespace Eigen + #endif // EIGEN_SkylineMatrix_H diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/Skyline/SkylineMatrixBase.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/Skyline/SkylineMatrixBase.h index 4d0c2397c..72131eb3f 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/Skyline/SkylineMatrixBase.h +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/Skyline/SkylineMatrixBase.h @@ -27,6 +27,8 @@ #include "SkylineUtil.h" +namespace Eigen { + /** \ingroup Skyline_Module * * \class SkylineMatrixBase @@ -220,4 +222,6 @@ protected: bool m_isRValue; }; +} // end namespace Eigen + #endif // EIGEN_SkylineMatrixBase_H diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/Skyline/SkylineProduct.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/Skyline/SkylineProduct.h index aeedc47ec..fb653b446 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/Skyline/SkylineProduct.h +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/Skyline/SkylineProduct.h @@ -25,6 +25,8 @@ #ifndef EIGEN_SKYLINEPRODUCT_H #define EIGEN_SKYLINEPRODUCT_H +namespace Eigen { + template struct SkylineProductReturnType { typedef const typename internal::nested::type LhsNested; @@ -303,4 +305,6 @@ SkylineMatrixBase::operator*(const MatrixBase &other) con return typename SkylineProductReturnType::Type(derived(), other.derived()); } +} // end namespace Eigen + #endif // EIGEN_SKYLINEPRODUCT_H diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/Skyline/SkylineStorage.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/Skyline/SkylineStorage.h index 62806bfb6..5721dee90 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/Skyline/SkylineStorage.h +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/Skyline/SkylineStorage.h @@ -25,6 +25,8 @@ #ifndef EIGEN_SKYLINE_STORAGE_H #define EIGEN_SKYLINE_STORAGE_H +namespace Eigen { + /** Stores a skyline set of values in three structures : * The diagonal elements * The upper elements @@ -267,4 +269,6 @@ public: }; +} // end namespace Eigen + #endif // EIGEN_COMPRESSED_STORAGE_H diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/Skyline/SkylineUtil.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/Skyline/SkylineUtil.h index e0512476f..5c5bd8bda 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/Skyline/SkylineUtil.h +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/Skyline/SkylineUtil.h @@ -25,6 +25,8 @@ #ifndef EIGEN_SKYLINEUTIL_H #define EIGEN_SKYLINEUTIL_H +namespace Eigen { + #ifdef NDEBUG #define EIGEN_DBG_SKYLINE(X) #else @@ -97,5 +99,6 @@ template class eval } // end namespace internal +} // end namespace Eigen #endif // EIGEN_SKYLINEUTIL_H diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/SparseExtra/BlockOfDynamicSparseMatrix.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/SparseExtra/BlockOfDynamicSparseMatrix.h new file mode 100644 index 000000000..0cc6e3a06 --- /dev/null +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/SparseExtra/BlockOfDynamicSparseMatrix.h @@ -0,0 +1,129 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2008-2009 Gael Guennebaud +// +// Eigen is free software; you can redistribute it and/or +// modify it under the terms of the GNU Lesser General Public +// License as published by the Free Software Foundation; either +// version 3 of the License, or (at your option) any later version. +// +// Alternatively, you can redistribute it and/or +// modify it under the terms of the GNU General Public License as +// published by the Free Software Foundation; either version 2 of +// the License, or (at your option) any later version. +// +// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY +// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the +// GNU General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public +// License and a copy of the GNU General Public License along with +// Eigen. If not, see . + +#ifndef EIGEN_SPARSE_BLOCKFORDYNAMICMATRIX_H +#define EIGEN_SPARSE_BLOCKFORDYNAMICMATRIX_H + +namespace Eigen { + +/*************************************************************************** +* specialisation for DynamicSparseMatrix +***************************************************************************/ + +template +class SparseInnerVectorSet, Size> + : public SparseMatrixBase, Size> > +{ + typedef DynamicSparseMatrix<_Scalar, _Options, _Index> MatrixType; + public: + + enum { IsRowMajor = internal::traits::IsRowMajor }; + + EIGEN_SPARSE_PUBLIC_INTERFACE(SparseInnerVectorSet) + class InnerIterator: public MatrixType::InnerIterator + { + public: + inline InnerIterator(const SparseInnerVectorSet& xpr, Index outer) + : MatrixType::InnerIterator(xpr.m_matrix, xpr.m_outerStart + outer), m_outer(outer) + {} + inline Index row() const { return IsRowMajor ? m_outer : this->index(); } + inline Index col() const { return IsRowMajor ? this->index() : m_outer; } + protected: + Index m_outer; + }; + + inline SparseInnerVectorSet(const MatrixType& matrix, Index outerStart, Index outerSize) + : m_matrix(matrix), m_outerStart(outerStart), m_outerSize(outerSize) + { + eigen_assert( (outerStart>=0) && ((outerStart+outerSize)<=matrix.outerSize()) ); + } + + inline SparseInnerVectorSet(const MatrixType& matrix, Index outer) + : m_matrix(matrix), m_outerStart(outer), m_outerSize(Size) + { + eigen_assert(Size!=Dynamic); + eigen_assert( (outer>=0) && (outer + inline SparseInnerVectorSet& operator=(const SparseMatrixBase& other) + { + if (IsRowMajor != ((OtherDerived::Flags&RowMajorBit)==RowMajorBit)) + { + // need to transpose => perform a block evaluation followed by a big swap + DynamicSparseMatrix aux(other); + *this = aux.markAsRValue(); + } + else + { + // evaluate/copy vector per vector + for (Index j=0; j aux(other.innerVector(j)); + m_matrix.const_cast_derived()._data()[m_outerStart+j].swap(aux._data()); + } + } + return *this; + } + + inline SparseInnerVectorSet& operator=(const SparseInnerVectorSet& other) + { + return operator=(other); + } + + Index nonZeros() const + { + Index count = 0; + for (Index j=0; j0); + return m_matrix.data()[m_outerStart].vale(m_matrix.data()[m_outerStart].size()-1); + } + +// template +// inline SparseInnerVectorSet& operator=(const SparseMatrixBase& other) +// { +// return *this; +// } + + EIGEN_STRONG_INLINE Index rows() const { return IsRowMajor ? m_outerSize.value() : m_matrix.rows(); } + EIGEN_STRONG_INLINE Index cols() const { return IsRowMajor ? m_matrix.cols() : m_outerSize.value(); } + + protected: + + const typename MatrixType::Nested m_matrix; + Index m_outerStart; + const internal::variable_if_dynamic m_outerSize; + +}; + +} // end namespace Eigen + +#endif // EIGEN_SPARSE_BLOCKFORDYNAMICMATRIX_H diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/SparseExtra/CholmodSupportLegacy.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/SparseExtra/CholmodSupportLegacy.h deleted file mode 100644 index 676cd8574..000000000 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/SparseExtra/CholmodSupportLegacy.h +++ /dev/null @@ -1,517 +0,0 @@ -// This file is part of Eigen, a lightweight C++ template library -// for linear algebra. -// -// Copyright (C) 2008-2009 Gael Guennebaud -// -// Eigen is free software; you can redistribute it and/or -// modify it under the terms of the GNU Lesser General Public -// License as published by the Free Software Foundation; either -// version 3 of the License, or (at your option) any later version. -// -// Alternatively, you can redistribute it and/or -// modify it under the terms of the GNU General Public License as -// published by the Free Software Foundation; either version 2 of -// the License, or (at your option) any later version. -// -// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY -// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS -// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the -// GNU General Public License for more details. -// -// You should have received a copy of the GNU Lesser General Public -// License and a copy of the GNU General Public License along with -// Eigen. If not, see . - -#ifndef EIGEN_CHOLMODSUPPORT_LEGACY_H -#define EIGEN_CHOLMODSUPPORT_LEGACY_H - -namespace internal { - -template -void cholmod_configure_matrix_legacy(CholmodType& mat) -{ - if (internal::is_same::value) - { - mat.xtype = CHOLMOD_REAL; - mat.dtype = CHOLMOD_SINGLE; - } - else if (internal::is_same::value) - { - mat.xtype = CHOLMOD_REAL; - mat.dtype = CHOLMOD_DOUBLE; - } - else if (internal::is_same >::value) - { - mat.xtype = CHOLMOD_COMPLEX; - mat.dtype = CHOLMOD_SINGLE; - } - else if (internal::is_same >::value) - { - mat.xtype = CHOLMOD_COMPLEX; - mat.dtype = CHOLMOD_DOUBLE; - } - else - { - eigen_assert(false && "Scalar type not supported by CHOLMOD"); - } -} - -template -cholmod_sparse cholmod_map_eigen_to_sparse(_MatrixType& mat) -{ - typedef typename _MatrixType::Scalar Scalar; - cholmod_sparse res; - res.nzmax = mat.nonZeros(); - res.nrow = mat.rows();; - res.ncol = mat.cols(); - res.p = mat._outerIndexPtr(); - res.i = mat._innerIndexPtr(); - res.x = mat._valuePtr(); - res.xtype = CHOLMOD_REAL; - res.itype = CHOLMOD_INT; - res.sorted = 1; - res.packed = 1; - res.dtype = 0; - res.stype = -1; - - internal::cholmod_configure_matrix_legacy(res); - - - if (_MatrixType::Flags & SelfAdjoint) - { - if (_MatrixType::Flags & Upper) - res.stype = 1; - else if (_MatrixType::Flags & Lower) - res.stype = -1; - else - res.stype = 0; - } - else - res.stype = -1; // by default we consider the lower part - - return res; -} - -template -cholmod_dense cholmod_map_eigen_to_dense(MatrixBase& mat) -{ - EIGEN_STATIC_ASSERT((internal::traits::Flags&RowMajorBit)==0,THIS_METHOD_IS_ONLY_FOR_COLUMN_MAJOR_MATRICES); - typedef typename Derived::Scalar Scalar; - - cholmod_dense res; - res.nrow = mat.rows(); - res.ncol = mat.cols(); - res.nzmax = res.nrow * res.ncol; - res.d = Derived::IsVectorAtCompileTime ? mat.derived().size() : mat.derived().outerStride(); - res.x = mat.derived().data(); - res.z = 0; - - internal::cholmod_configure_matrix_legacy(res); - - return res; -} - -template -MappedSparseMatrix map_cholmod_sparse_to_eigen(cholmod_sparse& cm) -{ - return MappedSparseMatrix - (cm.nrow, cm.ncol, reinterpret_cast(cm.p)[cm.ncol], - reinterpret_cast(cm.p), reinterpret_cast(cm.i),reinterpret_cast(cm.x) ); -} - -} // namespace internal - -template -class SparseLLT<_MatrixType, Cholmod> : public SparseLLT<_MatrixType> -{ - protected: - typedef SparseLLT<_MatrixType> Base; - typedef typename Base::Scalar Scalar; - typedef typename Base::RealScalar RealScalar; - typedef typename Base::CholMatrixType CholMatrixType; - using Base::MatrixLIsDirty; - using Base::SupernodalFactorIsDirty; - using Base::m_flags; - using Base::m_matrix; - using Base::m_status; - - public: - typedef _MatrixType MatrixType; - typedef typename MatrixType::Index Index; - - SparseLLT(int flags = 0) - : Base(flags), m_cholmodFactor(0) - { - cholmod_start(&m_cholmod); - } - - SparseLLT(const MatrixType& matrix, int flags = 0) - : Base(flags), m_cholmodFactor(0) - { - cholmod_start(&m_cholmod); - compute(matrix); - } - - ~SparseLLT() - { - if (m_cholmodFactor) - cholmod_free_factor(&m_cholmodFactor, &m_cholmod); - cholmod_finish(&m_cholmod); - } - - inline const CholMatrixType& matrixL() const; - - template - bool solveInPlace(MatrixBase &b) const; - - template - inline const internal::solve_retval, Rhs> - solve(const MatrixBase& b) const - { - eigen_assert(true && "SparseLLT is not initialized."); - return internal::solve_retval, Rhs>(*this, b.derived()); - } - - void compute(const MatrixType& matrix); - - inline Index cols() const { return m_matrix.cols(); } - inline Index rows() const { return m_matrix.rows(); } - - inline const cholmod_factor* cholmodFactor() const - { return m_cholmodFactor; } - - inline cholmod_common* cholmodCommon() const - { return &m_cholmod; } - - bool succeeded() const; - - protected: - mutable cholmod_common m_cholmod; - cholmod_factor* m_cholmodFactor; -}; - - -namespace internal { - -template - struct solve_retval, Rhs> - : solve_retval_base, Rhs> -{ - typedef SparseLLT<_MatrixType, Cholmod> SpLLTDecType; - EIGEN_MAKE_SOLVE_HELPERS(SpLLTDecType,Rhs) - - template void evalTo(Dest& dst) const - { - //Index size = dec().cholmodFactor()->n; - eigen_assert((Index)dec().cholmodFactor()->n==rhs().rows()); - - cholmod_factor* cholmodFactor = const_cast(dec().cholmodFactor()); - cholmod_common* cholmodCommon = const_cast(dec().cholmodCommon()); - // this uses Eigen's triangular sparse solver - // if (m_status & MatrixLIsDirty) - // matrixL(); - // Base::solveInPlace(b); - // as long as our own triangular sparse solver is not fully optimal, - // let's use CHOLMOD's one: - cholmod_dense cdb = internal::cholmod_map_eigen_to_dense(rhs().const_cast_derived()); - cholmod_dense* x = cholmod_solve(CHOLMOD_A, cholmodFactor, &cdb, cholmodCommon); - - dst = Matrix::Map(reinterpret_cast(x->x), rhs().rows()); - - cholmod_free_dense(&x, cholmodCommon); - - } - -}; - -} // namespace internal - - - -template -void SparseLLT<_MatrixType,Cholmod>::compute(const _MatrixType& a) -{ - if (m_cholmodFactor) - { - cholmod_free_factor(&m_cholmodFactor, &m_cholmod); - m_cholmodFactor = 0; - } - - cholmod_sparse A = internal::cholmod_map_eigen_to_sparse(const_cast<_MatrixType&>(a)); -// m_cholmod.supernodal = CHOLMOD_AUTO; - // TODO -// if (m_flags&IncompleteFactorization) -// { -// m_cholmod.nmethods = 1; -// m_cholmod.method[0].ordering = CHOLMOD_NATURAL; -// m_cholmod.postorder = 0; -// } -// else -// { -// m_cholmod.nmethods = 1; -// m_cholmod.method[0].ordering = CHOLMOD_NATURAL; -// m_cholmod.postorder = 0; -// } -// m_cholmod.final_ll = 1; - m_cholmodFactor = cholmod_analyze(&A, &m_cholmod); - cholmod_factorize(&A, m_cholmodFactor, &m_cholmod); - - this->m_status = (this->m_status & ~Base::SupernodalFactorIsDirty) | Base::MatrixLIsDirty; -} - - -// TODO -template -bool SparseLLT<_MatrixType,Cholmod>::succeeded() const -{ return true; } - - - -template -inline const typename SparseLLT<_MatrixType,Cholmod>::CholMatrixType& -SparseLLT<_MatrixType,Cholmod>::matrixL() const -{ - if (this->m_status & Base::MatrixLIsDirty) - { - eigen_assert(!(this->m_status & Base::SupernodalFactorIsDirty)); - - cholmod_sparse* cmRes = cholmod_factor_to_sparse(m_cholmodFactor, &m_cholmod); - const_cast(this->m_matrix) = - internal::map_cholmod_sparse_to_eigen(*cmRes); - free(cmRes); - - this->m_status = (this->m_status & ~Base::MatrixLIsDirty); - } - return this->m_matrix; -} - - - - -template -template -bool SparseLLT<_MatrixType,Cholmod>::solveInPlace(MatrixBase &b) const -{ - //Index size = m_cholmodFactor->n; - eigen_assert((Index)m_cholmodFactor->n==b.rows()); - - // this uses Eigen's triangular sparse solver - // if (m_status & MatrixLIsDirty) - // matrixL(); - // Base::solveInPlace(b); - // as long as our own triangular sparse solver is not fully optimal, - // let's use CHOLMOD's one: - cholmod_dense cdb = internal::cholmod_map_eigen_to_dense(b); - - cholmod_dense* x = cholmod_solve(CHOLMOD_A, m_cholmodFactor, &cdb, &m_cholmod); - eigen_assert(x && "Eigen: cholmod_solve failed."); - - b = Matrix::Map(reinterpret_cast(x->x),b.rows()); - cholmod_free_dense(&x, &m_cholmod); - return true; -} - - - - - - - - - - - -template -class SparseLDLT<_MatrixType,Cholmod> : public SparseLDLT<_MatrixType> -{ - protected: - typedef SparseLDLT<_MatrixType> Base; - typedef typename Base::Scalar Scalar; - typedef typename Base::RealScalar RealScalar; - using Base::MatrixLIsDirty; - using Base::SupernodalFactorIsDirty; - using Base::m_flags; - using Base::m_matrix; - using Base::m_status; - - public: - typedef _MatrixType MatrixType; - typedef typename MatrixType::Index Index; - - SparseLDLT(int flags = 0) - : Base(flags), m_cholmodFactor(0) - { - cholmod_start(&m_cholmod); - } - - SparseLDLT(const _MatrixType& matrix, int flags = 0) - : Base(flags), m_cholmodFactor(0) - { - cholmod_start(&m_cholmod); - compute(matrix); - } - - ~SparseLDLT() - { - if (m_cholmodFactor) - cholmod_free_factor(&m_cholmodFactor, &m_cholmod); - cholmod_finish(&m_cholmod); - } - - inline const typename Base::CholMatrixType& matrixL(void) const; - - template - void solveInPlace(MatrixBase &b) const; - - template - inline const internal::solve_retval, Rhs> - solve(const MatrixBase& b) const - { - eigen_assert(true && "SparseLDLT is not initialized."); - return internal::solve_retval, Rhs>(*this, b.derived()); - } - - void compute(const _MatrixType& matrix); - - inline Index cols() const { return m_matrix.cols(); } - inline Index rows() const { return m_matrix.rows(); } - - inline const cholmod_factor* cholmodFactor() const - { return m_cholmodFactor; } - - inline cholmod_common* cholmodCommon() const - { return &m_cholmod; } - - bool succeeded() const; - - protected: - mutable cholmod_common m_cholmod; - cholmod_factor* m_cholmodFactor; -}; - - - -namespace internal { - -template - struct solve_retval, Rhs> - : solve_retval_base, Rhs> -{ - typedef SparseLDLT<_MatrixType, Cholmod> SpLDLTDecType; - EIGEN_MAKE_SOLVE_HELPERS(SpLDLTDecType,Rhs) - - template void evalTo(Dest& dst) const - { - //Index size = dec().cholmodFactor()->n; - eigen_assert((Index)dec().cholmodFactor()->n==rhs().rows()); - - cholmod_factor* cholmodFactor = const_cast(dec().cholmodFactor()); - cholmod_common* cholmodCommon = const_cast(dec().cholmodCommon()); - // this uses Eigen's triangular sparse solver - // if (m_status & MatrixLIsDirty) - // matrixL(); - // Base::solveInPlace(b); - // as long as our own triangular sparse solver is not fully optimal, - // let's use CHOLMOD's one: - cholmod_dense cdb = internal::cholmod_map_eigen_to_dense(rhs().const_cast_derived()); - cholmod_dense* x = cholmod_solve(CHOLMOD_LDLt, cholmodFactor, &cdb, cholmodCommon); - - dst = Matrix::Map(reinterpret_cast(x->x), rhs().rows()); - cholmod_free_dense(&x, cholmodCommon); - - } - -}; - - -} // namespace internal - -template -void SparseLDLT<_MatrixType,Cholmod>::compute(const _MatrixType& a) -{ - if (m_cholmodFactor) - { - cholmod_free_factor(&m_cholmodFactor, &m_cholmod); - m_cholmodFactor = 0; - } - - cholmod_sparse A = internal::cholmod_map_eigen_to_sparse(const_cast<_MatrixType&>(a)); - - //m_cholmod.supernodal = CHOLMOD_AUTO; - m_cholmod.supernodal = CHOLMOD_SIMPLICIAL; - //m_cholmod.supernodal = CHOLMOD_SUPERNODAL; - // TODO - if (this->m_flags & IncompleteFactorization) - { - m_cholmod.nmethods = 1; - //m_cholmod.method[0].ordering = CHOLMOD_NATURAL; - m_cholmod.method[0].ordering = CHOLMOD_COLAMD; - m_cholmod.postorder = 1; - } - else - { - m_cholmod.nmethods = 1; - m_cholmod.method[0].ordering = CHOLMOD_NATURAL; - m_cholmod.postorder = 0; - } - m_cholmod.final_ll = 0; - m_cholmodFactor = cholmod_analyze(&A, &m_cholmod); - cholmod_factorize(&A, m_cholmodFactor, &m_cholmod); - - this->m_status = (this->m_status & ~Base::SupernodalFactorIsDirty) | Base::MatrixLIsDirty; -} - - -// TODO -template -bool SparseLDLT<_MatrixType,Cholmod>::succeeded() const -{ return true; } - - -template -inline const typename SparseLDLT<_MatrixType>::CholMatrixType& -SparseLDLT<_MatrixType,Cholmod>::matrixL() const -{ - if (this->m_status & Base::MatrixLIsDirty) - { - eigen_assert(!(this->m_status & Base::SupernodalFactorIsDirty)); - - cholmod_sparse* cmRes = cholmod_factor_to_sparse(m_cholmodFactor, &m_cholmod); - const_cast(this->m_matrix) = MappedSparseMatrix(*cmRes); - free(cmRes); - - this->m_status = (this->m_status & ~Base::MatrixLIsDirty); - } - return this->m_matrix; -} - - - - - - -template -template -void SparseLDLT<_MatrixType,Cholmod>::solveInPlace(MatrixBase &b) const -{ - //Index size = m_cholmodFactor->n; - eigen_assert((Index)m_cholmodFactor->n == b.rows()); - - // this uses Eigen's triangular sparse solver - // if (m_status & MatrixLIsDirty) - // matrixL(); - // Base::solveInPlace(b); - // as long as our own triangular sparse solver is not fully optimal, - // let's use CHOLMOD's one: - cholmod_dense cdb = internal::cholmod_map_eigen_to_dense(b); - cholmod_dense* x = cholmod_solve(CHOLMOD_A, m_cholmodFactor, &cdb, &m_cholmod); - b = Matrix::Map(reinterpret_cast(x->x),b.rows()); - cholmod_free_dense(&x, &m_cholmod); -} - - - - - - -#endif // EIGEN_CHOLMODSUPPORT_LEGACY_H diff --git a/gtsam/3rdparty/Eigen/Eigen/src/Sparse/DynamicSparseMatrix.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/SparseExtra/DynamicSparseMatrix.h similarity index 87% rename from gtsam/3rdparty/Eigen/Eigen/src/Sparse/DynamicSparseMatrix.h rename to gtsam/3rdparty/Eigen/unsupported/Eigen/src/SparseExtra/DynamicSparseMatrix.h index 93e75f4c6..151d46538 100644 --- a/gtsam/3rdparty/Eigen/Eigen/src/Sparse/DynamicSparseMatrix.h +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/SparseExtra/DynamicSparseMatrix.h @@ -25,7 +25,11 @@ #ifndef EIGEN_DYNAMIC_SPARSEMATRIX_H #define EIGEN_DYNAMIC_SPARSEMATRIX_H -/** \class DynamicSparseMatrix +namespace Eigen { + +/** \deprecated use a SparseMatrix in an uncompressed mode + * + * \class DynamicSparseMatrix * * \brief A sparse matrix class designed for matrix assembly purpose * @@ -64,7 +68,7 @@ struct traits > } template -class DynamicSparseMatrix + class DynamicSparseMatrix : public SparseMatrixBase > { public: @@ -84,7 +88,7 @@ class DynamicSparseMatrix typedef DynamicSparseMatrix TransposedSparseMatrix; Index m_innerSize; - std::vector > m_data; + std::vector > m_data; public: @@ -94,8 +98,8 @@ class DynamicSparseMatrix inline Index outerSize() const { return static_cast(m_data.size()); } inline Index innerNonZeros(Index j) const { return m_data[j].size(); } - std::vector >& _data() { return m_data; } - const std::vector >& _data() const { return m_data; } + std::vector >& _data() { return m_data; } + const std::vector >& _data() const { return m_data; } /** \returns the coefficient value at given position \a row, \a col * This operation involes a log(rho*outer_size) binary search. @@ -119,6 +123,7 @@ class DynamicSparseMatrix } class InnerIterator; + class ReverseInnerIterator; void setZero() { @@ -232,20 +237,23 @@ class DynamicSparseMatrix } } - inline DynamicSparseMatrix() + /** The class DynamicSparseMatrix is deprectaed */ + EIGEN_DEPRECATED inline DynamicSparseMatrix() : m_innerSize(0), m_data(0) { eigen_assert(innerSize()==0 && outerSize()==0); } - inline DynamicSparseMatrix(Index rows, Index cols) + /** The class DynamicSparseMatrix is deprectaed */ + EIGEN_DEPRECATED inline DynamicSparseMatrix(Index rows, Index cols) : m_innerSize(0) { resize(rows, cols); } + /** The class DynamicSparseMatrix is deprectaed */ template - explicit inline DynamicSparseMatrix(const SparseMatrixBase& other) + EIGEN_DEPRECATED explicit inline DynamicSparseMatrix(const SparseMatrixBase& other) : m_innerSize(0) { Base::operator=(other.derived()); @@ -325,12 +333,12 @@ class DynamicSparseMatrix # ifdef EIGEN_DYNAMICSPARSEMATRIX_PLUGIN # include EIGEN_DYNAMICSPARSEMATRIX_PLUGIN # endif -}; + }; template -class DynamicSparseMatrix::InnerIterator : public SparseVector::InnerIterator +class DynamicSparseMatrix::InnerIterator : public SparseVector::InnerIterator { - typedef typename SparseVector::InnerIterator Base; + typedef typename SparseVector::InnerIterator Base; public: InnerIterator(const DynamicSparseMatrix& mat, Index outer) : Base(mat.m_data[outer]), m_outer(outer) @@ -343,4 +351,22 @@ class DynamicSparseMatrix::InnerIterator : public Sparse const Index m_outer; }; +template +class DynamicSparseMatrix::ReverseInnerIterator : public SparseVector::ReverseInnerIterator +{ + typedef typename SparseVector::ReverseInnerIterator Base; + public: + ReverseInnerIterator(const DynamicSparseMatrix& mat, Index outer) + : Base(mat.m_data[outer]), m_outer(outer) + {} + + inline Index row() const { return IsRowMajor ? m_outer : Base::index(); } + inline Index col() const { return IsRowMajor ? Base::index() : m_outer; } + + protected: + const Index m_outer; +}; + +} // end namespace Eigen + #endif // EIGEN_DYNAMIC_SPARSEMATRIX_H diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/SparseExtra/MarketIO.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/SparseExtra/MarketIO.h new file mode 100644 index 000000000..9cfe1d9f5 --- /dev/null +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/SparseExtra/MarketIO.h @@ -0,0 +1,288 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2011 Gael Guennebaud +// Copyright (C) 2012 Desire NUENTSA WAKAM +// +// Eigen is free software; you can redistribute it and/or +// modify it under the terms of the GNU Lesser General Public +// License as published by the Free Software Foundation; either +// version 3 of the License, or (at your option) any later version. +// +// Alternatively, you can redistribute it and/or +// modify it under the terms of the GNU General Public License as +// published by the Free Software Foundation; either version 2 of +// the License, or (at your option) any later version. +// +// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY +// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the +// GNU General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public +// License and a copy of the GNU General Public License along with +// Eigen. If not, see . + +#ifndef EIGEN_SPARSE_MARKET_IO_H +#define EIGEN_SPARSE_MARKET_IO_H + +#include + +namespace Eigen { + +namespace internal +{ + template + inline bool GetMarketLine (std::stringstream& line, int& M, int& N, int& i, int& j, Scalar& value) + { + line >> i >> j >> value; + i--; + j--; + if(i>=0 && j>=0 && i + inline bool GetMarketLine (std::stringstream& line, int& M, int& N, int& i, int& j, std::complex& value) + { + Scalar valR, valI; + line >> i >> j >> valR >> valI; + i--; + j--; + if(i>=0 && j>=0 && i(valR, valI); + return true; + } + else + return false; + } + + template + inline void GetVectorElt (const std::string& line, RealScalar& val) + { + std::istringstream newline(line); + newline >> val; + } + + template + inline void GetVectorElt (const std::string& line, std::complex& val) + { + RealScalar valR, valI; + std::istringstream newline(line); + newline >> valR >> valI; + val = std::complex(valR, valI); + } + + template + inline void putMarketHeader(std::string& header,int sym) + { + header= "%%MatrixMarket matrix coordinate "; + if(internal::is_same >::value || internal::is_same >::value) + { + header += " complex"; + if(sym == Symmetric) header += " symmetric"; + else if (sym == SelfAdjoint) header += " Hermitian"; + else header += " general"; + } + else + { + header += " real"; + if(sym == Symmetric) header += " symmetric"; + else header += " general"; + } + } + + template + inline void PutMatrixElt(Scalar value, int row, int col, std::ofstream& out) + { + out << row << " "<< col << " " << value << "\n"; + } + template + inline void PutMatrixElt(std::complex value, int row, int col, std::ofstream& out) + { + out << row << " " << col << " " << value.real() << " " << value.imag() << "\n"; + } + + + template + inline void putVectorElt(Scalar value, std::ofstream& out) + { + out << value << "\n"; + } + template + inline void putVectorElt(std::complex value, std::ofstream& out) + { + out << value.real << " " << value.imag()<< "\n"; + } + +} // end namepsace internal + +inline bool getMarketHeader(const std::string& filename, int& sym, bool& iscomplex, bool& isvector) +{ + sym = 0; + isvector = false; + std::ifstream in(filename.c_str(),std::ios::in); + if(!in) + return false; + + std::string line; + // The matrix header is always the first line in the file + std::getline(in, line); assert(in.good()); + + std::stringstream fmtline(line); + std::string substr[5]; + fmtline>> substr[0] >> substr[1] >> substr[2] >> substr[3] >> substr[4]; + if(substr[2].compare("array") == 0) isvector = true; + if(substr[3].compare("complex") == 0) iscomplex = true; + if(substr[4].compare("symmetric") == 0) sym = Symmetric; + else if (substr[4].compare("Hermitian") == 0) sym = SelfAdjoint; + + return true; +} + +template +bool loadMarket(SparseMatrixType& mat, const std::string& filename) +{ + typedef typename SparseMatrixType::Scalar Scalar; + std::ifstream input(filename.c_str(),std::ios::in); + if(!input) + return false; + + const int maxBuffersize = 2048; + char buffer[maxBuffersize]; + + bool readsizes = false; + + typedef Triplet T; + std::vector elements; + + int M(-1), N(-1), NNZ(-1); + int count = 0; + while(input.getline(buffer, maxBuffersize)) + { + // skip comments + //NOTE An appropriate test should be done on the header to get the symmetry + if(buffer[0]=='%') + continue; + + std::stringstream line(buffer); + + if(!readsizes) + { + line >> M >> N >> NNZ; + if(M > 0 && N > 0 && NNZ > 0) + { + readsizes = true; + std::cout << "sizes: " << M << "," << N << "," << NNZ << "\n"; + mat.resize(M,N); + mat.reserve(NNZ); + } + } + else + { + int i(-1), j(-1); + Scalar value; + if( internal::GetMarketLine(line, M, N, i, j, value) ) + { + ++ count; + elements.push_back(T(i,j,value)); + } + else + std::cerr << "Invalid read: " << i << "," << j << "\n"; + } + } + mat.setFromTriplets(elements.begin(), elements.end()); + if(count!=NNZ) + std::cerr << count << "!=" << NNZ << "\n"; + + input.close(); + return true; +} + +template +bool loadMarketVector(VectorType& vec, const std::string& filename) +{ + typedef typename VectorType::Scalar Scalar; + std::ifstream in(filename.c_str(), std::ios::in); + if(!in) + return false; + + std::string line; + int n(0), col(0); + do + { // Skip comments + std::getline(in, line); assert(in.good()); + } while (line[0] == '%'); + std::istringstream newline(line); + newline >> n >> col; + assert(n>0 && col>0); + vec.resize(n); + int i = 0; + Scalar value; + while ( std::getline(in, line) && (i < n) ){ + internal::GetVectorElt(line, value); + vec(i++) = value; + } + in.close(); + if (i!=n){ + std::cerr<< "Unable to read all elements from file " << filename << "\n"; + return false; + } + return true; +} + +template +bool saveMarket(const SparseMatrixType& mat, const std::string& filename, int sym = 0) +{ + typedef typename SparseMatrixType::Scalar Scalar; + std::ofstream out(filename.c_str(),std::ios::out); + if(!out) + return false; + + out.flags(std::ios_base::scientific); + out.precision(64); + std::string header; + internal::putMarketHeader(header, sym); + out << header << std::endl; + out << mat.rows() << " " << mat.cols() << " " << mat.nonZeros() << "\n"; + int count = 0; + for(int j=0; j +bool saveMarketVector (const VectorType& vec, const std::string& filename) +{ + typedef typename VectorType::Scalar Scalar; + std::ofstream out(filename.c_str(),std::ios::out); + if(!out) + return false; + + out.flags(std::ios_base::scientific); + out.precision(64); + if(internal::is_same >::value || internal::is_same >::value) + out << "%%MatrixMarket matrix array complex general\n"; + else + out << "%%MatrixMarket matrix array real general\n"; + out << vec.size() << " "<< 1 << "\n"; + for (int i=0; i < vec.size(); i++){ + internal::putVectorElt(vec(i), out); + } + out.close(); + return true; +} + +} // end namespace Eigen + +#endif // EIGEN_SPARSE_MARKET_IO_H diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/SparseExtra/MatrixMarketIterator.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/SparseExtra/MatrixMarketIterator.h new file mode 100644 index 000000000..3c34effca --- /dev/null +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/SparseExtra/MatrixMarketIterator.h @@ -0,0 +1,236 @@ + +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2012 Desire NUENTSA WAKAM +// +// Eigen is free software; you can redistribute it and/or +// modify it under the terms of the GNU Lesser General Public +// License as published by the Free Software Foundation; either +// version 3 of the License, or (at your option) any later version. +// +// Alternatively, you can redistribute it and/or +// modify it under the terms of the GNU General Public License as +// published by the Free Software Foundation; either version 2 of +// the License, or (at your option) any later version. +// +// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY +// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the +// GNU General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public +// License and a copy of the GNU General Public License along with +// Eigen. If not, see . + +#ifndef EIGEN_BROWSE_MATRICES_H +#define EIGEN_BROWSE_MATRICES_H + +namespace Eigen { + +enum { + SPD = 0x100, + NonSymmetric = 0x0 +}; + +/** + * @brief Iterator to browse matrices from a specified folder + * + * This is used to load all the matrices from a folder. + * The matrices should be in Matrix Market format + * It is assumed that the matrices are named as matname.mtx + * and matname_SPD.mtx if the matrix is Symmetric and positive definite (or Hermitian) + * The right hand side vectors are loaded as well, if they exist. + * They should be named as matname_b.mtx. + * Note that the right hand side for a SPD matrix is named as matname_SPD_b.mtx + * + * Sometimes a reference solution is available. In this case, it should be named as matname_x.mtx + * + * Sample code + * \code + * + * \endcode + * + * \tparam Scalar The scalar type + */ +template +class MatrixMarketIterator +{ + public: + typedef Matrix VectorType; + typedef SparseMatrix MatrixType; + + public: + MatrixMarketIterator(const std::string folder):m_sym(0),m_isvalid(false),m_matIsLoaded(false),m_hasRhs(false),m_hasrefX(false),m_folder(folder) + { + m_folder_id = opendir(folder.c_str()); + if (!m_folder_id){ + m_isvalid = false; + std::cerr << "The provided Matrix folder could not be opened \n\n"; + abort(); + } + Getnextvalidmatrix(); + } + + ~MatrixMarketIterator() + { + if (m_folder_id) closedir(m_folder_id); + } + + inline MatrixMarketIterator& operator++() + { + m_matIsLoaded = false; + m_hasrefX = false; + m_hasRhs = false; + Getnextvalidmatrix(); + return *this; + } + inline operator bool() const { return m_isvalid;} + + /** Return the sparse matrix corresponding to the current file */ + inline MatrixType& matrix() + { + // Read the matrix + if (m_matIsLoaded) return m_mat; + + std::string matrix_file = m_folder + "/" + m_matname + ".mtx"; + if ( !loadMarket(m_mat, matrix_file)) + { + m_matIsLoaded = false; + return m_mat; + } + m_matIsLoaded = true; + + if (m_sym != NonSymmetric) + { // Store the upper part of the matrix. It is needed by the solvers dealing with nonsymmetric matrices ?? + MatrixType B; + B = m_mat; + m_mat = B.template selfadjointView(); + } + return m_mat; + } + + /** Return the right hand side corresponding to the current matrix. + * If the rhs file is not provided, a random rhs is generated + */ + inline VectorType& rhs() + { + // Get the right hand side + if (m_hasRhs) return m_rhs; + + std::string rhs_file; + rhs_file = m_folder + "/" + m_matname + "_b.mtx"; // The pattern is matname_b.mtx + m_hasRhs = Fileexists(rhs_file); + if (m_hasRhs) + { + m_rhs.resize(m_mat.cols()); + m_hasRhs = loadMarketVector(m_rhs, rhs_file); + } + if (!m_hasRhs) + { + // Generate a random right hand side + if (!m_matIsLoaded) this->matrix(); + m_refX.resize(m_mat.cols()); + m_refX.setRandom(); + m_rhs = m_mat * m_refX; + m_hasrefX = true; + m_hasRhs = true; + } + return m_rhs; + } + + /** Return a reference solution + * If it is not provided and if the right hand side is not available + * then refX is randomly generated such that A*refX = b + * where A and b are the matrix and the rhs. + * Note that when a rhs is provided, refX is not available + */ + inline VectorType& refX() + { + // Check if a reference solution is provided + if (m_hasrefX) return m_refX; + + std::string lhs_file; + lhs_file = m_folder + "/" + m_matname + "_x.mtx"; + m_hasrefX = Fileexists(lhs_file); + if (m_hasrefX) + { + m_refX.resize(m_mat.cols()); + m_hasrefX = loadMarketVector(m_refX, lhs_file); + } + return m_refX; + } + + inline std::string& matname() { return m_matname; } + + inline int sym() { return m_sym; } + + inline bool hasRhs() {return m_hasRhs; } + inline bool hasrefX() {return m_hasrefX; } + + protected: + + inline bool Fileexists(std::string file) + { + std::ifstream file_id(file.c_str()); + if (!file_id.good() ) + { + return false; + } + else + { + file_id.close(); + return true; + } + } + + void Getnextvalidmatrix( ) + { + m_isvalid = false; + // Here, we return with the next valid matrix in the folder + while ( (m_curs_id = readdir(m_folder_id)) != NULL) { + m_isvalid = false; + std::string curfile; + curfile = m_folder + "/" + m_curs_id->d_name; + // Discard if it is a folder + if (m_curs_id->d_type == DT_DIR) continue; //FIXME This may not be available on non BSD systems +// struct stat st_buf; +// stat (curfile.c_str(), &st_buf); +// if (S_ISDIR(st_buf.st_mode)) continue; + + // Determine from the header if it is a matrix or a right hand side + bool isvector,iscomplex; + if(!getMarketHeader(curfile,m_sym,iscomplex,isvector)) continue; + if(isvector) continue; + + // Get the matrix name + std::string filename = m_curs_id->d_name; + m_matname = filename.substr(0, filename.length()-4); + + // Find if the matrix is SPD + size_t found = m_matname.find("SPD"); + if( (found!=std::string::npos) && (m_sym != NonSymmetric) ) + m_sym = SPD; + + m_isvalid = true; + break; + } + } + int m_sym; // Symmetry of the matrix + MatrixType m_mat; // Current matrix + VectorType m_rhs; // Current vector + VectorType m_refX; // The reference solution, if exists + std::string m_matname; // Matrix Name + bool m_isvalid; + bool m_matIsLoaded; // Determine if the matrix has already been loaded from the file + bool m_hasRhs; // The right hand side exists + bool m_hasrefX; // A reference solution is provided + std::string m_folder; + DIR * m_folder_id; + struct dirent *m_curs_id; + +}; + +} // end namespace Eigen + +#endif diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/SparseExtra/RandomSetter.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/SparseExtra/RandomSetter.h index 4ea41af85..9328c60cf 100644 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/SparseExtra/RandomSetter.h +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/SparseExtra/RandomSetter.h @@ -25,6 +25,8 @@ #ifndef EIGEN_RANDOMSETTER_H #define EIGEN_RANDOMSETTER_H +namespace Eigen { + /** Represents a std::map * * \see RandomSetter @@ -180,9 +182,7 @@ class RandomSetter enum { SwapStorage = 1 - MapTraits::IsSorted, TargetRowMajor = (SparseMatrixType::Flags & RowMajorBit) ? 1 : 0, - SetterRowMajor = SwapStorage ? 1-TargetRowMajor : TargetRowMajor, - IsUpper = SparseMatrixType::Flags & Upper, - IsLower = SparseMatrixType::Flags & Lower + SetterRowMajor = SwapStorage ? 1-TargetRowMajor : TargetRowMajor }; public: @@ -227,6 +227,7 @@ class RandomSetter if (!SwapStorage) // also means the map is sorted { mp_target->setZero(); + mp_target->makeCompressed(); mp_target->reserve(nonZeros()); Index prevOuter = -1; for (Index k=0; kouterSize(); ++j) { Index tmp = positions[j]; - mp_target->_outerIndexPtr()[j] = count; + mp_target->outerIndexPtr()[j] = count; positions[j] = count; count += tmp; } - mp_target->_outerIndexPtr()[mp_target->outerSize()] = count; + mp_target->makeCompressed(); + mp_target->outerIndexPtr()[mp_target->outerSize()] = count; mp_target->resizeNonZeros(count); // pass 2 for (Index k=0; k_outerIndexPtr()[outer]; + Index posStart = mp_target->outerIndexPtr()[outer]; Index i = (positions[outer]++) - 1; - while ( (i >= posStart) && (mp_target->_innerIndexPtr()[i] > inner) ) + while ( (i >= posStart) && (mp_target->innerIndexPtr()[i] > inner) ) { - mp_target->_valuePtr()[i+1] = mp_target->_valuePtr()[i]; - mp_target->_innerIndexPtr()[i+1] = mp_target->_innerIndexPtr()[i]; + mp_target->valuePtr()[i+1] = mp_target->valuePtr()[i]; + mp_target->innerIndexPtr()[i+1] = mp_target->innerIndexPtr()[i]; --i; } - mp_target->_innerIndexPtr()[i+1] = inner; - mp_target->_valuePtr()[i+1] = it->second.value; + mp_target->innerIndexPtr()[i+1] = inner; + mp_target->valuePtr()[i+1] = it->second.value; } } } @@ -305,8 +307,6 @@ class RandomSetter /** \returns a reference to the coefficient at given coordinates \a row, \a col */ Scalar& operator() (Index row, Index col) { - eigen_assert(((!IsUpper) || (row<=col)) && "Invalid access to an upper triangular matrix"); - eigen_assert(((!IsLower) || (col<=row)) && "Invalid access to an upper triangular matrix"); const Index outer = SetterRowMajor ? row : col; const Index inner = SetterRowMajor ? col : row; const Index outerMajor = outer >> OuterPacketBits; // index of the packet/map @@ -337,4 +337,6 @@ class RandomSetter unsigned char m_keyBitsOffset; }; +} // end namespace Eigen + #endif // EIGEN_RANDOMSETTER_H diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/SparseExtra/SimplicialCholesky.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/SparseExtra/SimplicialCholesky.h deleted file mode 100644 index 6af6407c7..000000000 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/SparseExtra/SimplicialCholesky.h +++ /dev/null @@ -1,477 +0,0 @@ -// This file is part of Eigen, a lightweight C++ template library -// for linear algebra. -// -// Copyright (C) 2008-2010 Gael Guennebaud -// -// Eigen is free software; you can redistribute it and/or -// modify it under the terms of the GNU Lesser General Public -// License as published by the Free Software Foundation; either -// version 3 of the License, or (at your option) any later version. -// -// Alternatively, you can redistribute it and/or -// modify it under the terms of the GNU General Public License as -// published by the Free Software Foundation; either version 2 of -// the License, or (at your option) any later version. -// -// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY -// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS -// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the -// GNU General Public License for more details. -// -// You should have received a copy of the GNU Lesser General Public -// License and a copy of the GNU General Public License along with -// Eigen. If not, see . - -/* - -NOTE: the _symbolic, and _numeric functions has been adapted from - the LDL library: - -LDL Copyright (c) 2005 by Timothy A. Davis. All Rights Reserved. - -LDL License: - - Your use or distribution of LDL or any modified version of - LDL implies that you agree to this License. - - This library is free software; you can redistribute it and/or - modify it under the terms of the GNU Lesser General Public - License as published by the Free Software Foundation; either - version 2.1 of the License, or (at your option) any later version. - - This library is distributed in the hope that it will be useful, - but WITHOUT ANY WARRANTY; without even the implied warranty of - MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU - Lesser General Public License for more details. - - You should have received a copy of the GNU Lesser General Public - License along with this library; if not, write to the Free Software - Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 - USA - - Permission is hereby granted to use or copy this program under the - terms of the GNU LGPL, provided that the Copyright, this License, - and the Availability of the original version is retained on all copies. - User documentation of any code that uses this code or any modified - version of this code must cite the Copyright, this License, the - Availability note, and "Used by permission." Permission to modify - the code and to distribute modified code is granted, provided the - Copyright, this License, and the Availability note are retained, - and a notice that the code was modified is included. - */ - -#ifndef EIGEN_SIMPLICIAL_CHOLESKY_H -#define EIGEN_SIMPLICIAL_CHOLESKY_H - -enum SimplicialCholeskyMode { - SimplicialCholeskyLLt, - SimplicialCholeskyLDLt -}; - -/** \brief A direct sparse Cholesky factorization - * - * This class allows to solve for A.X = B sparse linear problems via a LL^T or LDL^T Cholesky factorization. - * The sparse matrix A must be selfadjoint and positive definite. The vectors or matrices - * X and B can be either dense or sparse. - * - * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<> - * \tparam _UpLo the triangular part that will be used for the computations. It can be Lower - * or Upper. Default is Lower. - * - */ -template -class SimplicialCholesky -{ - public: - typedef _MatrixType MatrixType; - enum { UpLo = _UpLo }; - typedef typename MatrixType::Scalar Scalar; - typedef typename MatrixType::RealScalar RealScalar; - typedef typename MatrixType::Index Index; - typedef SparseMatrix CholMatrixType; - typedef Matrix VectorType; - - public: - - SimplicialCholesky() - : m_info(Success), m_isInitialized(false), m_LDLt(true) - {} - - SimplicialCholesky(const MatrixType& matrix) - : m_info(Success), m_isInitialized(false), m_LDLt(true) - { - compute(matrix); - } - - ~SimplicialCholesky() - { - } - - inline Index cols() const { return m_matrix.cols(); } - inline Index rows() const { return m_matrix.rows(); } - - SimplicialCholesky& setMode(SimplicialCholeskyMode mode) - { - switch(mode) - { - case SimplicialCholeskyLLt: - m_LDLt = false; - break; - case SimplicialCholeskyLDLt: - m_LDLt = true; - break; - default: - break; - } - - return *this; - } - - /** \brief Reports whether previous computation was successful. - * - * \returns \c Success if computation was succesful, - * \c NumericalIssue if the matrix.appears to be negative. - */ - ComputationInfo info() const - { - eigen_assert(m_isInitialized && "Decomposition is not initialized."); - return m_info; - } - - /** Computes the sparse Cholesky decomposition of \a matrix */ - SimplicialCholesky& compute(const MatrixType& matrix) - { - analyzePattern(matrix); - factorize(matrix); - return *this; - } - - /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A. - * - * \sa compute() - */ - template - inline const internal::solve_retval - solve(const MatrixBase& b) const - { - eigen_assert(m_isInitialized && "SimplicialCholesky is not initialized."); - eigen_assert(rows()==b.rows() - && "SimplicialCholesky::solve(): invalid number of rows of the right hand side matrix b"); - return internal::solve_retval(*this, b.derived()); - } - - /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A. - * - * \sa compute() - */ -// template -// inline const internal::sparse_solve_retval -// solve(const SparseMatrixBase& b) const -// { -// eigen_assert(m_isInitialized && "SimplicialCholesky is not initialized."); -// eigen_assert(rows()==b.rows() -// && "SimplicialCholesky::solve(): invalid number of rows of the right hand side matrix b"); -// return internal::sparse_solve_retval(*this, b.derived()); -// } - - /** Performs a symbolic decomposition on the sparcity of \a matrix. - * - * This function is particularly useful when solving for several problems having the same structure. - * - * \sa factorize() - */ - void analyzePattern(const MatrixType& a); - - - /** Performs a numeric decomposition of \a matrix - * - * The given matrix must has the same sparcity than the matrix on which the symbolic decomposition has been performed. - * - * \sa analyzePattern() - */ - void factorize(const MatrixType& a); - - /** \returns the permutation P - * \sa permutationPinv() */ - const PermutationMatrix& permutationP() const - { return m_P; } - - /** \returns the inverse P^-1 of the permutation P - * \sa permutationP() */ - const PermutationMatrix& permutationPinv() const - { return m_Pinv; } - - #ifndef EIGEN_PARSED_BY_DOXYGEN - /** \internal */ - template - void _solve(const MatrixBase &b, MatrixBase &dest) const - { - eigen_assert(m_factorizationIsOk && "The decomposition is not in a valid state for solving, you must first call either compute() or symbolic()/numeric()"); - eigen_assert(m_matrix.rows()==b.rows()); - - if(m_info!=Success) - return; - - if(m_P.size()>0) - dest = m_Pinv * b; - else - dest = b; - - if(m_LDLt) - { - if(m_matrix.nonZeros()>0) // otherwise L==I - m_matrix.template triangularView().solveInPlace(dest); - - dest = m_diag.asDiagonal().inverse() * dest; - - if (m_matrix.nonZeros()>0) // otherwise L==I - m_matrix.adjoint().template triangularView().solveInPlace(dest); - } - else - { - if(m_matrix.nonZeros()>0) // otherwise L==I - m_matrix.template triangularView().solveInPlace(dest); - - if (m_matrix.nonZeros()>0) // otherwise L==I - m_matrix.adjoint().template triangularView().solveInPlace(dest); - } - - if(m_P.size()>0) - dest = m_P * dest; - } - - /** \internal */ - /* - template - void _solve(const SparseMatrix &b, SparseMatrix &dest) const - { - // TODO - } - */ - #endif // EIGEN_PARSED_BY_DOXYGEN - - template - void dumpMemory(Stream& s) - { - int total = 0; - s << " L: " << ((total+=(m_matrix.cols()+1) * sizeof(int) + m_matrix.nonZeros()*(sizeof(int)+sizeof(Scalar))) >> 20) << "Mb" << "\n"; - s << " diag: " << ((total+=m_diag.size() * sizeof(Scalar)) >> 20) << "Mb" << "\n"; - s << " tree: " << ((total+=m_parent.size() * sizeof(int)) >> 20) << "Mb" << "\n"; - s << " nonzeros: " << ((total+=m_nonZerosPerCol.size() * sizeof(int)) >> 20) << "Mb" << "\n"; - s << " perm: " << ((total+=m_P.size() * sizeof(int)) >> 20) << "Mb" << "\n"; - s << " perm^-1: " << ((total+=m_Pinv.size() * sizeof(int)) >> 20) << "Mb" << "\n"; - s << " TOTAL: " << (total>> 20) << "Mb" << "\n"; - } - - protected: - /** keeps off-diagonal entries; drops diagonal entries */ - struct keep_diag { - inline bool operator() (const Index& row, const Index& col, const Scalar&) const - { - return row!=col; - } - }; - - mutable ComputationInfo m_info; - bool m_isInitialized; - bool m_factorizationIsOk; - bool m_analysisIsOk; - bool m_LDLt; - - CholMatrixType m_matrix; - VectorType m_diag; // the diagonal coefficients in case of a LDLt decomposition - VectorXi m_parent; // elimination tree - VectorXi m_nonZerosPerCol; - PermutationMatrix m_P; // the permutation - PermutationMatrix m_Pinv; // the inverse permutation -}; - -template -void SimplicialCholesky<_MatrixType,_UpLo>::analyzePattern(const MatrixType& a) -{ - eigen_assert(a.rows()==a.cols()); - const Index size = a.rows(); - m_matrix.resize(size, size); - m_parent.resize(size); - m_nonZerosPerCol.resize(size); - - ei_declare_aligned_stack_constructed_variable(Index, tags, size, 0); - - // TODO allows to configure the permutation - { - CholMatrixType C; - C = a.template selfadjointView(); - // remove diagonal entries: - C.prune(keep_diag()); - internal::minimum_degree_ordering(C, m_P); - } - - if(m_P.size()>0) - m_Pinv = m_P.inverse(); - else - m_Pinv.resize(0); - - SparseMatrix ap(size,size); - ap.template selfadjointView() = a.template selfadjointView().twistedBy(m_Pinv); - - for(Index k = 0; k < size; ++k) - { - /* L(k,:) pattern: all nodes reachable in etree from nz in A(0:k-1,k) */ - m_parent[k] = -1; /* parent of k is not yet known */ - tags[k] = k; /* mark node k as visited */ - m_nonZerosPerCol[k] = 0; /* count of nonzeros in column k of L */ - for(typename CholMatrixType::InnerIterator it(ap,k); it; ++it) - { - Index i = it.index(); - if(i < k) - { - /* follow path from i to root of etree, stop at flagged node */ - for(; tags[i] != k; i = m_parent[i]) - { - /* find parent of i if not yet determined */ - if (m_parent[i] == -1) - m_parent[i] = k; - m_nonZerosPerCol[i]++; /* L (k,i) is nonzero */ - tags[i] = k; /* mark i as visited */ - } - } - } - } - - /* construct Lp index array from m_nonZerosPerCol column counts */ - Index* Lp = m_matrix._outerIndexPtr(); - Lp[0] = 0; - for(Index k = 0; k < size; ++k) - Lp[k+1] = Lp[k] + m_nonZerosPerCol[k] + (m_LDLt ? 0 : 1); - - m_matrix.resizeNonZeros(Lp[size]); - - m_isInitialized = true; - m_info = Success; - m_analysisIsOk = true; - m_factorizationIsOk = false; -} - - -template -void SimplicialCholesky<_MatrixType,_UpLo>::factorize(const MatrixType& a) -{ - eigen_assert(m_analysisIsOk && "You must first call analyzePattern()"); - eigen_assert(a.rows()==a.cols()); - const Index size = a.rows(); - eigen_assert(m_parent.size()==size); - eigen_assert(m_nonZerosPerCol.size()==size); - - const Index* Lp = m_matrix._outerIndexPtr(); - Index* Li = m_matrix._innerIndexPtr(); - Scalar* Lx = m_matrix._valuePtr(); - - ei_declare_aligned_stack_constructed_variable(Scalar, y, size, 0); - ei_declare_aligned_stack_constructed_variable(Index, pattern, size, 0); - ei_declare_aligned_stack_constructed_variable(Index, tags, size, 0); - - SparseMatrix ap(size,size); - ap.template selfadjointView() = a.template selfadjointView().twistedBy(m_Pinv); - - bool ok = true; - m_diag.resize(m_LDLt ? size : 0); - - for(Index k = 0; k < size; ++k) - { - // compute nonzero pattern of kth row of L, in topological order - y[k] = 0.0; // Y(0:k) is now all zero - Index top = size; // stack for pattern is empty - tags[k] = k; // mark node k as visited - m_nonZerosPerCol[k] = 0; // count of nonzeros in column k of L - for(typename MatrixType::InnerIterator it(ap,k); it; ++it) - { - Index i = it.index(); - if(i <= k) - { - y[i] += internal::conj(it.value()); /* scatter A(i,k) into Y (sum duplicates) */ - Index len; - for(len = 0; tags[i] != k; i = m_parent[i]) - { - pattern[len++] = i; /* L(k,i) is nonzero */ - tags[i] = k; /* mark i as visited */ - } - while(len > 0) - pattern[--top] = pattern[--len]; - } - } - - /* compute numerical values kth row of L (a sparse triangular solve) */ - Scalar d = y[k]; // get D(k,k) and clear Y(k) - y[k] = 0.0; - for(; top < size; ++top) - { - Index i = pattern[top]; /* pattern[top:n-1] is pattern of L(:,k) */ - Scalar yi = y[i]; /* get and clear Y(i) */ - y[i] = 0.0; - - /* the nonzero entry L(k,i) */ - Scalar l_ki; - if(m_LDLt) - l_ki = yi / m_diag[i]; - else - yi = l_ki = yi / Lx[Lp[i]]; - - Index p2 = Lp[i] + m_nonZerosPerCol[i]; - Index p; - for(p = Lp[i] + (m_LDLt ? 0 : 1); p < p2; ++p) - y[Li[p]] -= internal::conj(Lx[p]) * yi; - d -= l_ki * internal::conj(yi); - Li[p] = k; /* store L(k,i) in column form of L */ - Lx[p] = l_ki; - ++m_nonZerosPerCol[i]; /* increment count of nonzeros in col i */ - } - if(m_LDLt) - m_diag[k] = d; - else - { - Index p = Lp[k]+m_nonZerosPerCol[k]++; - Li[p] = k ; /* store L(k,k) = sqrt (d) in column k */ - Lx[p] = internal::sqrt(d) ; - } - if(d == Scalar(0)) - { - ok = false; /* failure, D(k,k) is zero */ - break; - } - } - - m_info = ok ? Success : NumericalIssue; - m_factorizationIsOk = true; -} - -namespace internal { - -template -struct solve_retval, Rhs> - : solve_retval_base, Rhs> -{ - typedef SimplicialCholesky<_MatrixType,_UpLo> Dec; - EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs) - - template void evalTo(Dest& dst) const - { - dec()._solve(rhs(),dst); - } -}; - -template -struct sparse_solve_retval, Rhs> - : sparse_solve_retval_base, Rhs> -{ - typedef SimplicialCholesky<_MatrixType,_UpLo> Dec; - EIGEN_MAKE_SPARSE_SOLVE_HELPERS(Dec,Rhs) - - template void evalTo(Dest& dst) const - { - dec()._solve(rhs(),dst); - } -}; - -} - -#endif // EIGEN_SIMPLICIAL_CHOLESKY_H diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/SparseExtra/SparseLDLTLegacy.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/SparseExtra/SparseLDLTLegacy.h deleted file mode 100644 index 14283c117..000000000 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/SparseExtra/SparseLDLTLegacy.h +++ /dev/null @@ -1,414 +0,0 @@ -// This file is part of Eigen, a lightweight C++ template library -// for linear algebra. -// -// Copyright (C) 2008 Gael Guennebaud -// -// Eigen is free software; you can redistribute it and/or -// modify it under the terms of the GNU Lesser General Public -// License as published by the Free Software Foundation; either -// version 3 of the License, or (at your option) any later version. -// -// Alternatively, you can redistribute it and/or -// modify it under the terms of the GNU General Public License as -// published by the Free Software Foundation; either version 2 of -// the License, or (at your option) any later version. -// -// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY -// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS -// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the -// GNU General Public License for more details. -// -// You should have received a copy of the GNU Lesser General Public -// License and a copy of the GNU General Public License along with -// Eigen. If not, see . - -/* - -NOTE: the _symbolic, and _numeric functions has been adapted from - the LDL library: - -LDL Copyright (c) 2005 by Timothy A. Davis. All Rights Reserved. - -LDL License: - - Your use or distribution of LDL or any modified version of - LDL implies that you agree to this License. - - This library is free software; you can redistribute it and/or - modify it under the terms of the GNU Lesser General Public - License as published by the Free Software Foundation; either - version 2.1 of the License, or (at your option) any later version. - - This library is distributed in the hope that it will be useful, - but WITHOUT ANY WARRANTY; without even the implied warranty of - MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU - Lesser General Public License for more details. - - You should have received a copy of the GNU Lesser General Public - License along with this library; if not, write to the Free Software - Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 - USA - - Permission is hereby granted to use or copy this program under the - terms of the GNU LGPL, provided that the Copyright, this License, - and the Availability of the original version is retained on all copies. - User documentation of any code that uses this code or any modified - version of this code must cite the Copyright, this License, the - Availability note, and "Used by permission." Permission to modify - the code and to distribute modified code is granted, provided the - Copyright, this License, and the Availability note are retained, - and a notice that the code was modified is included. - */ - -#ifndef EIGEN_SPARSELDLT_LEGACY_H -#define EIGEN_SPARSELDLT_LEGACY_H - -/** \ingroup Sparse_Module - * - * \class SparseLDLT - * - * \brief LDLT Cholesky decomposition of a sparse matrix and associated features - * - * \param MatrixType the type of the matrix of which we are computing the LDLT Cholesky decomposition - * - * \warning the upper triangular part has to be specified. The rest of the matrix is not used. The input matrix must be column major. - * - * \sa class LDLT, class LDLT - */ -template -class SparseLDLT -{ - protected: - typedef typename _MatrixType::Scalar Scalar; - typedef typename NumTraits::Real RealScalar; - - typedef Matrix VectorType; - - enum { - SupernodalFactorIsDirty = 0x10000, - MatrixLIsDirty = 0x20000 - }; - - public: - typedef SparseMatrix CholMatrixType; - typedef _MatrixType MatrixType; - typedef typename MatrixType::Index Index; - - - /** Creates a dummy LDLT factorization object with flags \a flags. */ - SparseLDLT(int flags = 0) - : m_flags(flags), m_status(0) - { - eigen_assert((MatrixType::Flags&RowMajorBit)==0); - m_precision = RealScalar(0.1) * Eigen::NumTraits::dummy_precision(); - } - - /** Creates a LDLT object and compute the respective factorization of \a matrix using - * flags \a flags. */ - SparseLDLT(const MatrixType& matrix, int flags = 0) - : m_matrix(matrix.rows(), matrix.cols()), m_flags(flags), m_status(0) - { - eigen_assert((MatrixType::Flags&RowMajorBit)==0); - m_precision = RealScalar(0.1) * Eigen::NumTraits::dummy_precision(); - compute(matrix); - } - - /** Sets the relative threshold value used to prune zero coefficients during the decomposition. - * - * Setting a value greater than zero speeds up computation, and yields to an imcomplete - * factorization with fewer non zero coefficients. Such approximate factors are especially - * useful to initialize an iterative solver. - * - * \warning if precision is greater that zero, the LDLT factorization is not guaranteed to succeed - * even if the matrix is positive definite. - * - * Note that the exact meaning of this parameter might depends on the actual - * backend. Moreover, not all backends support this feature. - * - * \sa precision() */ - void setPrecision(RealScalar v) { m_precision = v; } - - /** \returns the current precision. - * - * \sa setPrecision() */ - RealScalar precision() const { return m_precision; } - - /** Sets the flags. Possible values are: - * - CompleteFactorization - * - IncompleteFactorization - * - MemoryEfficient (hint to use the memory most efficient method offered by the backend) - * - SupernodalMultifrontal (implies a complete factorization if supported by the backend, - * overloads the MemoryEfficient flags) - * - SupernodalLeftLooking (implies a complete factorization if supported by the backend, - * overloads the MemoryEfficient flags) - * - * \sa flags() */ - void settags(int f) { m_flags = f; } - /** \returns the current flags */ - int flags() const { return m_flags; } - - /** Computes/re-computes the LDLT factorization */ - void compute(const MatrixType& matrix); - - /** Perform a symbolic factorization */ - void _symbolic(const MatrixType& matrix); - /** Perform the actual factorization using the previously - * computed symbolic factorization */ - bool _numeric(const MatrixType& matrix); - - /** \returns the lower triangular matrix L */ - inline const CholMatrixType& matrixL(void) const { return m_matrix; } - - /** \returns the coefficients of the diagonal matrix D */ - inline VectorType vectorD(void) const { return m_diag; } - - template - bool solveInPlace(MatrixBase &b) const; - - template - inline const internal::solve_retval, Rhs> - solve(const MatrixBase& b) const - { - eigen_assert(true && "SparseLDLT is not initialized."); - return internal::solve_retval, Rhs>(*this, b.derived()); - } - - inline Index cols() const { return m_matrix.cols(); } - inline Index rows() const { return m_matrix.rows(); } - - inline const VectorType& diag() const { return m_diag; } - - /** \returns true if the factorization succeeded */ - inline bool succeeded(void) const { return m_succeeded; } - - protected: - CholMatrixType m_matrix; - VectorType m_diag; - VectorXi m_parent; // elimination tree - VectorXi m_nonZerosPerCol; -// VectorXi m_w; // workspace - PermutationMatrix m_P; - PermutationMatrix m_Pinv; - RealScalar m_precision; - int m_flags; - mutable int m_status; - bool m_succeeded; -}; - -namespace internal { - -template -struct solve_retval, Rhs> - : solve_retval_base, Rhs> -{ - typedef SparseLDLT<_MatrixType> SpLDLTDecType; - EIGEN_MAKE_SOLVE_HELPERS(SpLDLTDecType,Rhs) - - template void evalTo(Dest& dst) const - { - //Index size = dec().matrixL().rows(); - eigen_assert(dec().matrixL().rows()==rhs().rows()); - - Rhs b(rhs().rows(), rhs().cols()); - b = rhs(); - - if (dec().matrixL().nonZeros()>0) // otherwise L==I - dec().matrixL().template triangularView().solveInPlace(b); - - b = b.cwiseQuotient(dec().diag()); - if (dec().matrixL().nonZeros()>0) // otherwise L==I - dec().matrixL().adjoint().template triangularView().solveInPlace(b); - - dst = b; - - } - -}; - -} // end namespace internal - -/** Computes / recomputes the LDLT decomposition of matrix \a a - * using the default algorithm. - */ -template -void SparseLDLT<_MatrixType,Backend>::compute(const _MatrixType& a) -{ - _symbolic(a); - m_succeeded = _numeric(a); -} - -template -void SparseLDLT<_MatrixType,Backend>::_symbolic(const _MatrixType& a) -{ - assert(a.rows()==a.cols()); - const Index size = a.rows(); - m_matrix.resize(size, size); - m_parent.resize(size); - m_nonZerosPerCol.resize(size); - - ei_declare_aligned_stack_constructed_variable(Index, tags, size, 0); - - const Index* Ap = a._outerIndexPtr(); - const Index* Ai = a._innerIndexPtr(); - Index* Lp = m_matrix._outerIndexPtr(); - - const Index* P = 0; - Index* Pinv = 0; - - if(P) - { - m_P.indices() = VectorXi::Map(P,size); - m_Pinv = m_P.inverse(); - Pinv = m_Pinv.indices().data(); - } - else - { - m_P.resize(0); - m_Pinv.resize(0); - } - - for (Index k = 0; k < size; ++k) - { - /* L(k,:) pattern: all nodes reachable in etree from nz in A(0:k-1,k) */ - m_parent[k] = -1; /* parent of k is not yet known */ - tags[k] = k; /* mark node k as visited */ - m_nonZerosPerCol[k] = 0; /* count of nonzeros in column k of L */ - Index kk = P ? P[k] : k; /* kth original, or permuted, column */ - Index p2 = Ap[kk+1]; - for (Index p = Ap[kk]; p < p2; ++p) - { - /* A (i,k) is nonzero (original or permuted A) */ - Index i = Pinv ? Pinv[Ai[p]] : Ai[p]; - if (i < k) - { - /* follow path from i to root of etree, stop at flagged node */ - for (; tags[i] != k; i = m_parent[i]) - { - /* find parent of i if not yet determined */ - if (m_parent[i] == -1) - m_parent[i] = k; - ++m_nonZerosPerCol[i]; /* L (k,i) is nonzero */ - tags[i] = k; /* mark i as visited */ - } - } - } - } - /* construct Lp index array from m_nonZerosPerCol column counts */ - Lp[0] = 0; - for (Index k = 0; k < size; ++k) - Lp[k+1] = Lp[k] + m_nonZerosPerCol[k]; - - m_matrix.resizeNonZeros(Lp[size]); -} - -template -bool SparseLDLT<_MatrixType,Backend>::_numeric(const _MatrixType& a) -{ - assert(a.rows()==a.cols()); - const Index size = a.rows(); - assert(m_parent.size()==size); - assert(m_nonZerosPerCol.size()==size); - - const Index* Ap = a._outerIndexPtr(); - const Index* Ai = a._innerIndexPtr(); - const Scalar* Ax = a._valuePtr(); - const Index* Lp = m_matrix._outerIndexPtr(); - Index* Li = m_matrix._innerIndexPtr(); - Scalar* Lx = m_matrix._valuePtr(); - m_diag.resize(size); - - ei_declare_aligned_stack_constructed_variable(Scalar, y, size, 0); - ei_declare_aligned_stack_constructed_variable(Index, pattern, size, 0); - ei_declare_aligned_stack_constructed_variable(Index, tags, size, 0); - - Index* P = 0; - Index* Pinv = 0; - - if(m_P.size()==size) - { - P = m_P.indices().data(); - Pinv = m_Pinv.indices().data(); - } - - bool ok = true; - - for (Index k = 0; k < size; ++k) - { - /* compute nonzero pattern of kth row of L, in topological order */ - y[k] = 0.0; /* Y(0:k) is now all zero */ - Index top = size; /* stack for pattern is empty */ - tags[k] = k; /* mark node k as visited */ - m_nonZerosPerCol[k] = 0; /* count of nonzeros in column k of L */ - Index kk = (P) ? (P[k]) : (k); /* kth original, or permuted, column */ - Index p2 = Ap[kk+1]; - for (Index p = Ap[kk]; p < p2; ++p) - { - Index i = Pinv ? Pinv[Ai[p]] : Ai[p]; /* get A(i,k) */ - if (i <= k) - { - y[i] += internal::conj(Ax[p]); /* scatter A(i,k) into Y (sum duplicates) */ - Index len; - for (len = 0; tags[i] != k; i = m_parent[i]) - { - pattern[len++] = i; /* L(k,i) is nonzero */ - tags[i] = k; /* mark i as visited */ - } - while (len > 0) - pattern[--top] = pattern[--len]; - } - } - - /* compute numerical values kth row of L (a sparse triangular solve) */ - m_diag[k] = y[k]; /* get D(k,k) and clear Y(k) */ - y[k] = 0.0; - for (; top < size; ++top) - { - Index i = pattern[top]; /* pattern[top:n-1] is pattern of L(:,k) */ - Scalar yi = (y[i]); /* get and clear Y(i) */ - y[i] = 0.0; - Index p2 = Lp[i] + m_nonZerosPerCol[i]; - Index p; - for (p = Lp[i]; p < p2; ++p) - y[Li[p]] -= internal::conj(Lx[p]) * (yi); - Scalar l_ki = yi / m_diag[i]; /* the nonzero entry L(k,i) */ - m_diag[k] -= l_ki * internal::conj(yi); - Li[p] = k; /* store L(k,i) in column form of L */ - Lx[p] = (l_ki); - ++m_nonZerosPerCol[i]; /* increment count of nonzeros in col i */ - } - if (m_diag[k] == 0.0) - { - ok = false; /* failure, D(k,k) is zero */ - break; - } - } - - return ok; /* success, diagonal of D is all nonzero */ -} - -/** Computes b = L^-T D^-1 L^-1 b */ -template -template -bool SparseLDLT<_MatrixType, Backend>::solveInPlace(MatrixBase &b) const -{ - //Index size = m_matrix.rows(); - eigen_assert(m_matrix.rows()==b.rows()); - if (!m_succeeded) - return false; - - if(m_P.size()>0) - b = m_Pinv * b; - - if (m_matrix.nonZeros()>0) // otherwise L==I - m_matrix.template triangularView().solveInPlace(b); - b = b.cwiseQuotient(m_diag); - if (m_matrix.nonZeros()>0) // otherwise L==I - m_matrix.adjoint().template triangularView().solveInPlace(b); - - if(m_P.size()>0) - b = m_P * b; - - return true; -} - -#endif // EIGEN_SPARSELDLT_LEGACY_H diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/SparseExtra/SparseLLT.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/SparseExtra/SparseLLT.h deleted file mode 100644 index ac042217b..000000000 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/SparseExtra/SparseLLT.h +++ /dev/null @@ -1,245 +0,0 @@ -// This file is part of Eigen, a lightweight C++ template library -// for linear algebra. -// -// Copyright (C) 2008 Gael Guennebaud -// -// Eigen is free software; you can redistribute it and/or -// modify it under the terms of the GNU Lesser General Public -// License as published by the Free Software Foundation; either -// version 3 of the License, or (at your option) any later version. -// -// Alternatively, you can redistribute it and/or -// modify it under the terms of the GNU General Public License as -// published by the Free Software Foundation; either version 2 of -// the License, or (at your option) any later version. -// -// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY -// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS -// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the -// GNU General Public License for more details. -// -// You should have received a copy of the GNU Lesser General Public -// License and a copy of the GNU General Public License along with -// Eigen. If not, see . - -#ifndef EIGEN_SPARSELLT_H -#define EIGEN_SPARSELLT_H - -/** \ingroup Sparse_Module - * - * \class SparseLLT - * - * \brief LLT Cholesky decomposition of a sparse matrix and associated features - * - * \param MatrixType the type of the matrix of which we are computing the LLT Cholesky decomposition - * - * \sa class LLT, class LDLT - */ -template -class SparseLLT -{ - protected: - typedef typename _MatrixType::Scalar Scalar; - typedef typename NumTraits::Real RealScalar; - - enum { - SupernodalFactorIsDirty = 0x10000, - MatrixLIsDirty = 0x20000 - }; - - public: - typedef SparseMatrix CholMatrixType; - typedef _MatrixType MatrixType; - typedef typename MatrixType::Index Index; - - /** Creates a dummy LLT factorization object with flags \a flags. */ - SparseLLT(int flags = 0) - : m_flags(flags), m_status(0) - { - m_precision = RealScalar(0.1) * Eigen::NumTraits::dummy_precision(); - } - - /** Creates a LLT object and compute the respective factorization of \a matrix using - * flags \a flags. */ - SparseLLT(const MatrixType& matrix, int flags = 0) - : m_matrix(matrix.rows(), matrix.cols()), m_flags(flags), m_status(0) - { - m_precision = RealScalar(0.1) * Eigen::NumTraits::dummy_precision(); - compute(matrix); - } - - /** Sets the relative threshold value used to prune zero coefficients during the decomposition. - * - * Setting a value greater than zero speeds up computation, and yields to an imcomplete - * factorization with fewer non zero coefficients. Such approximate factors are especially - * useful to initialize an iterative solver. - * - * \warning if precision is greater that zero, the LLT factorization is not guaranteed to succeed - * even if the matrix is positive definite. - * - * Note that the exact meaning of this parameter might depends on the actual - * backend. Moreover, not all backends support this feature. - * - * \sa precision() */ - void setPrecision(RealScalar v) { m_precision = v; } - - /** \returns the current precision. - * - * \sa setPrecision() */ - RealScalar precision() const { return m_precision; } - - /** Sets the flags. Possible values are: - * - CompleteFactorization - * - IncompleteFactorization - * - MemoryEfficient (hint to use the memory most efficient method offered by the backend) - * - SupernodalMultifrontal (implies a complete factorization if supported by the backend, - * overloads the MemoryEfficient flags) - * - SupernodalLeftLooking (implies a complete factorization if supported by the backend, - * overloads the MemoryEfficient flags) - * - * \sa flags() */ - void setFlags(int f) { m_flags = f; } - /** \returns the current flags */ - int flags() const { return m_flags; } - - /** Computes/re-computes the LLT factorization */ - void compute(const MatrixType& matrix); - - /** \returns the lower triangular matrix L */ - inline const CholMatrixType& matrixL(void) const { return m_matrix; } - - template - bool solveInPlace(MatrixBase &b) const; - - template - inline const internal::solve_retval, Rhs> - solve(const MatrixBase& b) const - { - eigen_assert(true && "SparseLLT is not initialized."); - return internal::solve_retval, Rhs>(*this, b.derived()); - } - - inline Index cols() const { return m_matrix.cols(); } - inline Index rows() const { return m_matrix.rows(); } - - /** \returns true if the factorization succeeded */ - inline bool succeeded(void) const { return m_succeeded; } - - protected: - CholMatrixType m_matrix; - RealScalar m_precision; - int m_flags; - mutable int m_status; - bool m_succeeded; -}; - - -namespace internal { - -template -struct solve_retval, Rhs> - : solve_retval_base, Rhs> -{ - typedef SparseLLT<_MatrixType> SpLLTDecType; - EIGEN_MAKE_SOLVE_HELPERS(SpLLTDecType,Rhs) - - template void evalTo(Dest& dst) const - { - const Index size = dec().matrixL().rows(); - eigen_assert(size==rhs().rows()); - - Rhs b(rhs().rows(), rhs().cols()); - b = rhs(); - - dec().matrixL().template triangularView().solveInPlace(b); - dec().matrixL().adjoint().template triangularView().solveInPlace(b); - - dst = b; - - } - -}; - -} // end namespace internal - - -/** Computes / recomputes the LLT decomposition of matrix \a a - * using the default algorithm. - */ -template -void SparseLLT<_MatrixType,Backend>::compute(const _MatrixType& a) -{ - assert(a.rows()==a.cols()); - const Index size = a.rows(); - m_matrix.resize(size, size); - - // allocate a temporary vector for accumulations - AmbiVector tempVector(size); - RealScalar density = a.nonZeros()/RealScalar(size*size); - - // TODO estimate the number of non zeros - m_matrix.setZero(); - m_matrix.reserve(a.nonZeros()*2); - for (Index j = 0; j < size; ++j) - { - Scalar x = internal::real(a.coeff(j,j)); - - // TODO better estimate of the density ! - tempVector.init(density>0.001? IsDense : IsSparse); - tempVector.setBounds(j+1,size); - tempVector.setZero(); - // init with current matrix a - { - typename _MatrixType::InnerIterator it(a,j); - eigen_assert(it.index()==j && - "matrix must has non zero diagonal entries and only the lower triangular part must be stored"); - ++it; // skip diagonal element - for (; it; ++it) - tempVector.coeffRef(it.index()) = it.value(); - } - for (Index k=0; k::Iterator it(tempVector, m_precision*rx); it; ++it) - { - // FIXME use insertBack - m_matrix.insert(it.index(), j) = it.value() * y; - } - } - m_matrix.finalize(); -} - -/** Computes b = L^-T L^-1 b */ -template -template -bool SparseLLT<_MatrixType, Backend>::solveInPlace(MatrixBase &b) const -{ - const Index size = m_matrix.rows(); - eigen_assert(size==b.rows()); - - m_matrix.template triangularView().solveInPlace(b); - m_matrix.adjoint().template triangularView().solveInPlace(b); - - return true; -} - -#endif // EIGEN_SPARSELLT_H diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/SparseExtra/SparseLU.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/SparseExtra/SparseLU.h deleted file mode 100644 index 3d10dbbee..000000000 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/SparseExtra/SparseLU.h +++ /dev/null @@ -1,163 +0,0 @@ -// This file is part of Eigen, a lightweight C++ template library -// for linear algebra. -// -// Copyright (C) 2008 Gael Guennebaud -// -// Eigen is free software; you can redistribute it and/or -// modify it under the terms of the GNU Lesser General Public -// License as published by the Free Software Foundation; either -// version 3 of the License, or (at your option) any later version. -// -// Alternatively, you can redistribute it and/or -// modify it under the terms of the GNU General Public License as -// published by the Free Software Foundation; either version 2 of -// the License, or (at your option) any later version. -// -// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY -// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS -// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the -// GNU General Public License for more details. -// -// You should have received a copy of the GNU Lesser General Public -// License and a copy of the GNU General Public License along with -// Eigen. If not, see . - -#ifndef EIGEN_SPARSELU_H -#define EIGEN_SPARSELU_H - -enum { - SvNoTrans = 0, - SvTranspose = 1, - SvAdjoint = 2 -}; - -/** \ingroup Sparse_Module - * - * \class SparseLU - * - * \brief LU decomposition of a sparse matrix and associated features - * - * \param _MatrixType the type of the matrix of which we are computing the LU factorization - * - * \sa class FullPivLU, class SparseLLT - */ -template -class SparseLU - { - protected: - typedef typename _MatrixType::Scalar Scalar; - typedef typename NumTraits::Real RealScalar; - typedef SparseMatrix LUMatrixType; - - enum { - MatrixLUIsDirty = 0x10000 - }; - - public: - typedef _MatrixType MatrixType; - - /** Creates a dummy LU factorization object with flags \a flags. */ - SparseLU(int flags = 0) - : m_flags(flags), m_status(0) - { - m_precision = RealScalar(0.1) * Eigen::NumTraits::dummy_precision(); - } - - /** Creates a LU object and compute the respective factorization of \a matrix using - * flags \a flags. */ - SparseLU(const _MatrixType& matrix, int flags = 0) - : /*m_matrix(matrix.rows(), matrix.cols()),*/ m_flags(flags), m_status(0) - { - m_precision = RealScalar(0.1) * Eigen::NumTraits::dummy_precision(); - compute(matrix); - } - - /** Sets the relative threshold value used to prune zero coefficients during the decomposition. - * - * Setting a value greater than zero speeds up computation, and yields to an imcomplete - * factorization with fewer non zero coefficients. Such approximate factors are especially - * useful to initialize an iterative solver. - * - * Note that the exact meaning of this parameter might depends on the actual - * backend. Moreover, not all backends support this feature. - * - * \sa precision() */ - void setPrecision(RealScalar v) { m_precision = v; } - - /** \returns the current precision. - * - * \sa setPrecision() */ - RealScalar precision() const { return m_precision; } - - /** Sets the flags. Possible values are: - * - CompleteFactorization - * - IncompleteFactorization - * - MemoryEfficient - * - one of the ordering methods - * - etc... - * - * \sa flags() */ - void setFlags(int f) { m_flags = f; } - /** \returns the current flags */ - int flags() const { return m_flags; } - - void setOrderingMethod(int m) - { - eigen_assert( (m&~OrderingMask) == 0 && m!=0 && "invalid ordering method"); - m_flags = m_flags&~OrderingMask | m&OrderingMask; - } - - int orderingMethod() const - { - return m_flags&OrderingMask; - } - - /** Computes/re-computes the LU factorization */ - void compute(const _MatrixType& matrix); - - /** \returns the lower triangular matrix L */ - //inline const _MatrixType& matrixL() const { return m_matrixL; } - - /** \returns the upper triangular matrix U */ - //inline const _MatrixType& matrixU() const { return m_matrixU; } - - template - bool solve(const MatrixBase &b, MatrixBase* x, - const int transposed = SvNoTrans) const; - - /** \returns true if the factorization succeeded */ - inline bool succeeded(void) const { return m_succeeded; } - - protected: - RealScalar m_precision; - int m_flags; - mutable int m_status; - bool m_succeeded; -}; - -/** Computes / recomputes the LU decomposition of matrix \a a - * using the default algorithm. - */ -template -void SparseLU<_MatrixType,Backend>::compute(const _MatrixType& ) -{ - eigen_assert(false && "not implemented yet"); -} - -/** Computes *x = U^-1 L^-1 b - * - * If \a transpose is set to SvTranspose or SvAdjoint, the solution - * of the transposed/adjoint system is computed instead. - * - * Not all backends implement the solution of the transposed or - * adjoint system. - */ -template -template -bool SparseLU<_MatrixType,Backend>::solve(const MatrixBase &, MatrixBase* , const int ) const -{ - eigen_assert(false && "not implemented yet"); - return false; -} - -#endif // EIGEN_SPARSELU_H diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/SparseExtra/SuperLUSupport.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/SparseExtra/SuperLUSupport.h deleted file mode 100644 index bb7312190..000000000 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/SparseExtra/SuperLUSupport.h +++ /dev/null @@ -1,667 +0,0 @@ -// This file is part of Eigen, a lightweight C++ template library -// for linear algebra. -// -// Copyright (C) 2008-2009 Gael Guennebaud -// -// Eigen is free software; you can redistribute it and/or -// modify it under the terms of the GNU Lesser General Public -// License as published by the Free Software Foundation; either -// version 3 of the License, or (at your option) any later version. -// -// Alternatively, you can redistribute it and/or -// modify it under the terms of the GNU General Public License as -// published by the Free Software Foundation; either version 2 of -// the License, or (at your option) any later version. -// -// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY -// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS -// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the -// GNU General Public License for more details. -// -// You should have received a copy of the GNU Lesser General Public -// License and a copy of the GNU General Public License along with -// Eigen. If not, see . - -#ifndef EIGEN_SUPERLUSUPPORT_H -#define EIGEN_SUPERLUSUPPORT_H - -#define DECL_GSSVX(PREFIX,FLOATTYPE,KEYTYPE) \ - extern "C" { \ - typedef struct { FLOATTYPE for_lu; FLOATTYPE total_needed; int expansions; } PREFIX##mem_usage_t; \ - extern void PREFIX##gssvx(superlu_options_t *, SuperMatrix *, int *, int *, int *, \ - char *, FLOATTYPE *, FLOATTYPE *, SuperMatrix *, SuperMatrix *, \ - void *, int, SuperMatrix *, SuperMatrix *, \ - FLOATTYPE *, FLOATTYPE *, FLOATTYPE *, FLOATTYPE *, \ - PREFIX##mem_usage_t *, SuperLUStat_t *, int *); \ - } \ - inline float SuperLU_gssvx(superlu_options_t *options, SuperMatrix *A, \ - int *perm_c, int *perm_r, int *etree, char *equed, \ - FLOATTYPE *R, FLOATTYPE *C, SuperMatrix *L, \ - SuperMatrix *U, void *work, int lwork, \ - SuperMatrix *B, SuperMatrix *X, \ - FLOATTYPE *recip_pivot_growth, \ - FLOATTYPE *rcond, FLOATTYPE *ferr, FLOATTYPE *berr, \ - SuperLUStat_t *stats, int *info, KEYTYPE) { \ - PREFIX##mem_usage_t mem_usage; \ - PREFIX##gssvx(options, A, perm_c, perm_r, etree, equed, R, C, L, \ - U, work, lwork, B, X, recip_pivot_growth, rcond, \ - ferr, berr, &mem_usage, stats, info); \ - return mem_usage.for_lu; /* bytes used by the factor storage */ \ - } - -DECL_GSSVX(s,float,float) -DECL_GSSVX(c,float,std::complex) -DECL_GSSVX(d,double,double) -DECL_GSSVX(z,double,std::complex) - -#ifdef MILU_ALPHA -#define EIGEN_SUPERLU_HAS_ILU -#endif - -#ifdef EIGEN_SUPERLU_HAS_ILU - -// similarly for the incomplete factorization using gsisx -#define DECL_GSISX(PREFIX,FLOATTYPE,KEYTYPE) \ - extern "C" { \ - extern void PREFIX##gsisx(superlu_options_t *, SuperMatrix *, int *, int *, int *, \ - char *, FLOATTYPE *, FLOATTYPE *, SuperMatrix *, SuperMatrix *, \ - void *, int, SuperMatrix *, SuperMatrix *, FLOATTYPE *, FLOATTYPE *, \ - PREFIX##mem_usage_t *, SuperLUStat_t *, int *); \ - } \ - inline float SuperLU_gsisx(superlu_options_t *options, SuperMatrix *A, \ - int *perm_c, int *perm_r, int *etree, char *equed, \ - FLOATTYPE *R, FLOATTYPE *C, SuperMatrix *L, \ - SuperMatrix *U, void *work, int lwork, \ - SuperMatrix *B, SuperMatrix *X, \ - FLOATTYPE *recip_pivot_growth, \ - FLOATTYPE *rcond, \ - SuperLUStat_t *stats, int *info, KEYTYPE) { \ - PREFIX##mem_usage_t mem_usage; \ - PREFIX##gsisx(options, A, perm_c, perm_r, etree, equed, R, C, L, \ - U, work, lwork, B, X, recip_pivot_growth, rcond, \ - &mem_usage, stats, info); \ - return mem_usage.for_lu; /* bytes used by the factor storage */ \ - } - -DECL_GSISX(s,float,float) -DECL_GSISX(c,float,std::complex) -DECL_GSISX(d,double,double) -DECL_GSISX(z,double,std::complex) - -#endif - -template -struct SluMatrixMapHelper; - -/** \internal - * - * A wrapper class for SuperLU matrices. It supports only compressed sparse matrices - * and dense matrices. Supernodal and other fancy format are not supported by this wrapper. - * - * This wrapper class mainly aims to avoids the need of dynamic allocation of the storage structure. - */ -struct SluMatrix : SuperMatrix -{ - SluMatrix() - { - Store = &storage; - } - - SluMatrix(const SluMatrix& other) - : SuperMatrix(other) - { - Store = &storage; - storage = other.storage; - } - - SluMatrix& operator=(const SluMatrix& other) - { - SuperMatrix::operator=(static_cast(other)); - Store = &storage; - storage = other.storage; - return *this; - } - - struct - { - union {int nnz;int lda;}; - void *values; - int *innerInd; - int *outerInd; - } storage; - - void setStorageType(Stype_t t) - { - Stype = t; - if (t==SLU_NC || t==SLU_NR || t==SLU_DN) - Store = &storage; - else - { - eigen_assert(false && "storage type not supported"); - Store = 0; - } - } - - template - void setScalarType() - { - if (internal::is_same::value) - Dtype = SLU_S; - else if (internal::is_same::value) - Dtype = SLU_D; - else if (internal::is_same >::value) - Dtype = SLU_C; - else if (internal::is_same >::value) - Dtype = SLU_Z; - else - { - eigen_assert(false && "Scalar type not supported by SuperLU"); - } - } - - template - static SluMatrix Map(Matrix& mat) - { - typedef Matrix MatrixType; - eigen_assert( ((Options&RowMajor)!=RowMajor) && "row-major dense matrices is not supported by SuperLU"); - SluMatrix res; - res.setStorageType(SLU_DN); - res.setScalarType(); - res.Mtype = SLU_GE; - - res.nrow = mat.rows(); - res.ncol = mat.cols(); - - res.storage.lda = MatrixType::IsVectorAtCompileTime ? mat.size() : mat.outerStride(); - res.storage.values = mat.data(); - return res; - } - - template - static SluMatrix Map(SparseMatrixBase& mat) - { - SluMatrix res; - if ((MatrixType::Flags&RowMajorBit)==RowMajorBit) - { - res.setStorageType(SLU_NR); - res.nrow = mat.cols(); - res.ncol = mat.rows(); - } - else - { - res.setStorageType(SLU_NC); - res.nrow = mat.rows(); - res.ncol = mat.cols(); - } - - res.Mtype = SLU_GE; - - res.storage.nnz = mat.nonZeros(); - res.storage.values = mat.derived()._valuePtr(); - res.storage.innerInd = mat.derived()._innerIndexPtr(); - res.storage.outerInd = mat.derived()._outerIndexPtr(); - - res.setScalarType(); - - // FIXME the following is not very accurate - if (MatrixType::Flags & Upper) - res.Mtype = SLU_TRU; - if (MatrixType::Flags & Lower) - res.Mtype = SLU_TRL; - if (MatrixType::Flags & SelfAdjoint) - eigen_assert(false && "SelfAdjoint matrix shape not supported by SuperLU"); - return res; - } -}; - -template -struct SluMatrixMapHelper > -{ - typedef Matrix MatrixType; - static void run(MatrixType& mat, SluMatrix& res) - { - eigen_assert( ((Options&RowMajor)!=RowMajor) && "row-major dense matrices is not supported by SuperLU"); - res.setStorageType(SLU_DN); - res.setScalarType(); - res.Mtype = SLU_GE; - - res.nrow = mat.rows(); - res.ncol = mat.cols(); - - res.storage.lda = mat.outerStride(); - res.storage.values = mat.data(); - } -}; - -template -struct SluMatrixMapHelper > -{ - typedef Derived MatrixType; - static void run(MatrixType& mat, SluMatrix& res) - { - if ((MatrixType::Flags&RowMajorBit)==RowMajorBit) - { - res.setStorageType(SLU_NR); - res.nrow = mat.cols(); - res.ncol = mat.rows(); - } - else - { - res.setStorageType(SLU_NC); - res.nrow = mat.rows(); - res.ncol = mat.cols(); - } - - res.Mtype = SLU_GE; - - res.storage.nnz = mat.nonZeros(); - res.storage.values = mat._valuePtr(); - res.storage.innerInd = mat._innerIndexPtr(); - res.storage.outerInd = mat._outerIndexPtr(); - - res.setScalarType(); - - // FIXME the following is not very accurate - if (MatrixType::Flags & Upper) - res.Mtype = SLU_TRU; - if (MatrixType::Flags & Lower) - res.Mtype = SLU_TRL; - if (MatrixType::Flags & SelfAdjoint) - eigen_assert(false && "SelfAdjoint matrix shape not supported by SuperLU"); - } -}; - -namespace internal { - -template -SluMatrix asSluMatrix(MatrixType& mat) -{ - return SluMatrix::Map(mat); -} - -/** View a Super LU matrix as an Eigen expression */ -template -MappedSparseMatrix map_superlu(SluMatrix& sluMat) -{ - eigen_assert((Flags&RowMajor)==RowMajor && sluMat.Stype == SLU_NR - || (Flags&ColMajor)==ColMajor && sluMat.Stype == SLU_NC); - - Index outerSize = (Flags&RowMajor)==RowMajor ? sluMat.ncol : sluMat.nrow; - - return MappedSparseMatrix( - sluMat.nrow, sluMat.ncol, sluMat.storage.outerInd[outerSize], - sluMat.storage.outerInd, sluMat.storage.innerInd, reinterpret_cast(sluMat.storage.values) ); -} - -} // end namespace internal - -template -class SparseLU : public SparseLU -{ - protected: - typedef SparseLU Base; - typedef typename Base::Scalar Scalar; - typedef typename Base::RealScalar RealScalar; - typedef Matrix Vector; - typedef Matrix IntRowVectorType; - typedef Matrix IntColVectorType; - typedef SparseMatrix LMatrixType; - typedef SparseMatrix UMatrixType; - using Base::m_flags; - using Base::m_status; - - public: - - SparseLU(int flags = NaturalOrdering) - : Base(flags) - { - } - - SparseLU(const MatrixType& matrix, int flags = NaturalOrdering) - : Base(flags) - { - compute(matrix); - } - - ~SparseLU() - { - Destroy_SuperNode_Matrix(&m_sluL); - Destroy_CompCol_Matrix(&m_sluU); - } - - inline const LMatrixType& matrixL() const - { - if (m_extractedDataAreDirty) extractData(); - return m_l; - } - - inline const UMatrixType& matrixU() const - { - if (m_extractedDataAreDirty) extractData(); - return m_u; - } - - inline const IntColVectorType& permutationP() const - { - if (m_extractedDataAreDirty) extractData(); - return m_p; - } - - inline const IntRowVectorType& permutationQ() const - { - if (m_extractedDataAreDirty) extractData(); - return m_q; - } - - Scalar determinant() const; - - template - bool solve(const MatrixBase &b, MatrixBase* x, const int transposed = SvNoTrans) const; - - void compute(const MatrixType& matrix); - - protected: - - void extractData() const; - - protected: - // cached data to reduce reallocation, etc. - mutable LMatrixType m_l; - mutable UMatrixType m_u; - mutable IntColVectorType m_p; - mutable IntRowVectorType m_q; - - mutable SparseMatrix m_matrix; - mutable SluMatrix m_sluA; - mutable SuperMatrix m_sluL, m_sluU; - mutable SluMatrix m_sluB, m_sluX; - mutable SuperLUStat_t m_sluStat; - mutable superlu_options_t m_sluOptions; - mutable std::vector m_sluEtree; - mutable std::vector m_sluRscale, m_sluCscale; - mutable std::vector m_sluFerr, m_sluBerr; - mutable char m_sluEqued; - mutable bool m_extractedDataAreDirty; -}; - -template -void SparseLU::compute(const MatrixType& a) -{ - const int size = a.rows(); - m_matrix = a; - - set_default_options(&m_sluOptions); - m_sluOptions.ColPerm = NATURAL; - m_sluOptions.PrintStat = NO; - m_sluOptions.ConditionNumber = NO; - m_sluOptions.Trans = NOTRANS; - // m_sluOptions.Equil = NO; - - switch (Base::orderingMethod()) - { - case NaturalOrdering : m_sluOptions.ColPerm = NATURAL; break; - case MinimumDegree_AT_PLUS_A : m_sluOptions.ColPerm = MMD_AT_PLUS_A; break; - case MinimumDegree_ATA : m_sluOptions.ColPerm = MMD_ATA; break; - case ColApproxMinimumDegree : m_sluOptions.ColPerm = COLAMD; break; - default: - //std::cerr << "Eigen: ordering method \"" << Base::orderingMethod() << "\" not supported by the SuperLU backend\n"; - m_sluOptions.ColPerm = NATURAL; - }; - - m_sluA = internal::asSluMatrix(m_matrix); - memset(&m_sluL,0,sizeof m_sluL); - memset(&m_sluU,0,sizeof m_sluU); - //m_sluEqued = 'B'; - int info = 0; - - m_p.resize(size); - m_q.resize(size); - m_sluRscale.resize(size); - m_sluCscale.resize(size); - m_sluEtree.resize(size); - - RealScalar recip_pivot_gross, rcond; - RealScalar ferr, berr; - - // set empty B and X - m_sluB.setStorageType(SLU_DN); - m_sluB.setScalarType(); - m_sluB.Mtype = SLU_GE; - m_sluB.storage.values = 0; - m_sluB.nrow = m_sluB.ncol = 0; - m_sluB.storage.lda = size; - m_sluX = m_sluB; - - StatInit(&m_sluStat); - if (m_flags&IncompleteFactorization) - { - #ifdef EIGEN_SUPERLU_HAS_ILU - ilu_set_default_options(&m_sluOptions); - - // no attempt to preserve column sum - m_sluOptions.ILU_MILU = SILU; - - // only basic ILU(k) support -- no direct control over memory consumption - // better to use ILU_DropRule = DROP_BASIC | DROP_AREA - // and set ILU_FillFactor to max memory growth - m_sluOptions.ILU_DropRule = DROP_BASIC; - m_sluOptions.ILU_DropTol = Base::m_precision; - - SuperLU_gsisx(&m_sluOptions, &m_sluA, m_q.data(), m_p.data(), &m_sluEtree[0], - &m_sluEqued, &m_sluRscale[0], &m_sluCscale[0], - &m_sluL, &m_sluU, - NULL, 0, - &m_sluB, &m_sluX, - &recip_pivot_gross, &rcond, - &m_sluStat, &info, Scalar()); - #else - //std::cerr << "Incomplete factorization is only available in SuperLU v4\n"; - Base::m_succeeded = false; - return; - #endif - } - else - { - SuperLU_gssvx(&m_sluOptions, &m_sluA, m_q.data(), m_p.data(), &m_sluEtree[0], - &m_sluEqued, &m_sluRscale[0], &m_sluCscale[0], - &m_sluL, &m_sluU, - NULL, 0, - &m_sluB, &m_sluX, - &recip_pivot_gross, &rcond, - &ferr, &berr, - &m_sluStat, &info, Scalar()); - } - StatFree(&m_sluStat); - - m_extractedDataAreDirty = true; - - // FIXME how to better check for errors ??? - Base::m_succeeded = (info == 0); -} - -template -template -bool SparseLU::solve(const MatrixBase &b, - MatrixBase *x, const int transposed) const -{ - const int size = m_matrix.rows(); - const int rhsCols = b.cols(); - eigen_assert(size==b.rows()); - - switch (transposed) { - case SvNoTrans : m_sluOptions.Trans = NOTRANS; break; - case SvTranspose : m_sluOptions.Trans = TRANS; break; - case SvAdjoint : m_sluOptions.Trans = CONJ; break; - default: - //std::cerr << "Eigen: transposition option \"" << transposed << "\" not supported by the SuperLU backend\n"; - m_sluOptions.Trans = NOTRANS; - } - - m_sluOptions.Fact = FACTORED; - m_sluOptions.IterRefine = NOREFINE; - - m_sluFerr.resize(rhsCols); - m_sluBerr.resize(rhsCols); - m_sluB = SluMatrix::Map(b.const_cast_derived()); - m_sluX = SluMatrix::Map(x->derived()); - - StatInit(&m_sluStat); - int info = 0; - RealScalar recip_pivot_gross, rcond; - - if (m_flags&IncompleteFactorization) - { - #ifdef EIGEN_SUPERLU_HAS_ILU - SuperLU_gsisx(&m_sluOptions, &m_sluA, m_q.data(), m_p.data(), &m_sluEtree[0], - &m_sluEqued, &m_sluRscale[0], &m_sluCscale[0], - &m_sluL, &m_sluU, - NULL, 0, - &m_sluB, &m_sluX, - &recip_pivot_gross, &rcond, - &m_sluStat, &info, Scalar()); - #else - //std::cerr << "Incomplete factorization is only available in SuperLU v4\n"; - return false; - #endif - } - else - { - SuperLU_gssvx( - &m_sluOptions, &m_sluA, - m_q.data(), m_p.data(), - &m_sluEtree[0], &m_sluEqued, - &m_sluRscale[0], &m_sluCscale[0], - &m_sluL, &m_sluU, - NULL, 0, - &m_sluB, &m_sluX, - &recip_pivot_gross, &rcond, - &m_sluFerr[0], &m_sluBerr[0], - &m_sluStat, &info, Scalar()); - } - StatFree(&m_sluStat); - - // reset to previous state - m_sluOptions.Trans = NOTRANS; - return info==0; -} - -// -// the code of this extractData() function has been adapted from the SuperLU's Matlab support code, -// -// Copyright (c) 1994 by Xerox Corporation. All rights reserved. -// -// THIS MATERIAL IS PROVIDED AS IS, WITH ABSOLUTELY NO WARRANTY -// EXPRESSED OR IMPLIED. ANY USE IS AT YOUR OWN RISK. -// -template -void SparseLU::extractData() const -{ - if (m_extractedDataAreDirty) - { - int upper; - int fsupc, istart, nsupr; - int lastl = 0, lastu = 0; - SCformat *Lstore = static_cast(m_sluL.Store); - NCformat *Ustore = static_cast(m_sluU.Store); - Scalar *SNptr; - - const int size = m_matrix.rows(); - m_l.resize(size,size); - m_l.resizeNonZeros(Lstore->nnz); - m_u.resize(size,size); - m_u.resizeNonZeros(Ustore->nnz); - - int* Lcol = m_l._outerIndexPtr(); - int* Lrow = m_l._innerIndexPtr(); - Scalar* Lval = m_l._valuePtr(); - - int* Ucol = m_u._outerIndexPtr(); - int* Urow = m_u._innerIndexPtr(); - Scalar* Uval = m_u._valuePtr(); - - Ucol[0] = 0; - Ucol[0] = 0; - - /* for each supernode */ - for (int k = 0; k <= Lstore->nsuper; ++k) - { - fsupc = L_FST_SUPC(k); - istart = L_SUB_START(fsupc); - nsupr = L_SUB_START(fsupc+1) - istart; - upper = 1; - - /* for each column in the supernode */ - for (int j = fsupc; j < L_FST_SUPC(k+1); ++j) - { - SNptr = &((Scalar*)Lstore->nzval)[L_NZ_START(j)]; - - /* Extract U */ - for (int i = U_NZ_START(j); i < U_NZ_START(j+1); ++i) - { - Uval[lastu] = ((Scalar*)Ustore->nzval)[i]; - /* Matlab doesn't like explicit zero. */ - if (Uval[lastu] != 0.0) - Urow[lastu++] = U_SUB(i); - } - for (int i = 0; i < upper; ++i) - { - /* upper triangle in the supernode */ - Uval[lastu] = SNptr[i]; - /* Matlab doesn't like explicit zero. */ - if (Uval[lastu] != 0.0) - Urow[lastu++] = L_SUB(istart+i); - } - Ucol[j+1] = lastu; - - /* Extract L */ - Lval[lastl] = 1.0; /* unit diagonal */ - Lrow[lastl++] = L_SUB(istart + upper - 1); - for (int i = upper; i < nsupr; ++i) - { - Lval[lastl] = SNptr[i]; - /* Matlab doesn't like explicit zero. */ - if (Lval[lastl] != 0.0) - Lrow[lastl++] = L_SUB(istart+i); - } - Lcol[j+1] = lastl; - - ++upper; - } /* for j ... */ - - } /* for k ... */ - - // squeeze the matrices : - m_l.resizeNonZeros(lastl); - m_u.resizeNonZeros(lastu); - - m_extractedDataAreDirty = false; - } -} - -template -typename SparseLU::Scalar SparseLU::determinant() const -{ - assert((!NumTraits::IsComplex) && "This function is not implemented for complex yet"); - if (m_extractedDataAreDirty) - extractData(); - - // TODO this code could be moved to the default/base backend - // FIXME perhaps we have to take into account the scale factors m_sluRscale and m_sluCscale ??? - Scalar det = Scalar(1); - for (int j=0; j 0) - { - int lastId = m_u._outerIndexPtr()[j+1]-1; - eigen_assert(m_u._innerIndexPtr()[lastId]<=j); - if (m_u._innerIndexPtr()[lastId]==j) - { - det *= m_u._valuePtr()[lastId]; - } - } -// std::cout << m_sluRscale[j] << " " << m_sluCscale[j] << " \n"; - } - return det; -} - -#endif // EIGEN_SUPERLUSUPPORT_H diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/SparseExtra/UmfPackSupport.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/SparseExtra/UmfPackSupport.h deleted file mode 100644 index beb18f6cd..000000000 --- a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/SparseExtra/UmfPackSupport.h +++ /dev/null @@ -1,350 +0,0 @@ -// This file is part of Eigen, a lightweight C++ template library -// for linear algebra. -// -// Copyright (C) 2008-2009 Gael Guennebaud -// -// Eigen is free software; you can redistribute it and/or -// modify it under the terms of the GNU Lesser General Public -// License as published by the Free Software Foundation; either -// version 3 of the License, or (at your option) any later version. -// -// Alternatively, you can redistribute it and/or -// modify it under the terms of the GNU General Public License as -// published by the Free Software Foundation; either version 2 of -// the License, or (at your option) any later version. -// -// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY -// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS -// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the -// GNU General Public License for more details. -// -// You should have received a copy of the GNU Lesser General Public -// License and a copy of the GNU General Public License along with -// Eigen. If not, see . - -#ifndef EIGEN_UMFPACKSUPPORT_H -#define EIGEN_UMFPACKSUPPORT_H - -/* TODO extract L, extract U, compute det, etc... */ - -// generic double/complex wrapper functions: - -inline void umfpack_free_numeric(void **Numeric, double) -{ umfpack_di_free_numeric(Numeric); } - -inline void umfpack_free_numeric(void **Numeric, std::complex) -{ umfpack_zi_free_numeric(Numeric); } - -inline void umfpack_free_symbolic(void **Symbolic, double) -{ umfpack_di_free_symbolic(Symbolic); } - -inline void umfpack_free_symbolic(void **Symbolic, std::complex) -{ umfpack_zi_free_symbolic(Symbolic); } - -inline int umfpack_symbolic(int n_row,int n_col, - const int Ap[], const int Ai[], const double Ax[], void **Symbolic, - const double Control [UMFPACK_CONTROL], double Info [UMFPACK_INFO]) -{ - return umfpack_di_symbolic(n_row,n_col,Ap,Ai,Ax,Symbolic,Control,Info); -} - -inline int umfpack_symbolic(int n_row,int n_col, - const int Ap[], const int Ai[], const std::complex Ax[], void **Symbolic, - const double Control [UMFPACK_CONTROL], double Info [UMFPACK_INFO]) -{ - return umfpack_zi_symbolic(n_row,n_col,Ap,Ai,&internal::real_ref(Ax[0]),0,Symbolic,Control,Info); -} - -inline int umfpack_numeric( const int Ap[], const int Ai[], const double Ax[], - void *Symbolic, void **Numeric, - const double Control[UMFPACK_CONTROL],double Info [UMFPACK_INFO]) -{ - return umfpack_di_numeric(Ap,Ai,Ax,Symbolic,Numeric,Control,Info); -} - -inline int umfpack_numeric( const int Ap[], const int Ai[], const std::complex Ax[], - void *Symbolic, void **Numeric, - const double Control[UMFPACK_CONTROL],double Info [UMFPACK_INFO]) -{ - return umfpack_zi_numeric(Ap,Ai,&internal::real_ref(Ax[0]),0,Symbolic,Numeric,Control,Info); -} - -inline int umfpack_solve( int sys, const int Ap[], const int Ai[], const double Ax[], - double X[], const double B[], void *Numeric, - const double Control[UMFPACK_CONTROL], double Info[UMFPACK_INFO]) -{ - return umfpack_di_solve(sys,Ap,Ai,Ax,X,B,Numeric,Control,Info); -} - -inline int umfpack_solve( int sys, const int Ap[], const int Ai[], const std::complex Ax[], - std::complex X[], const std::complex B[], void *Numeric, - const double Control[UMFPACK_CONTROL], double Info[UMFPACK_INFO]) -{ - return umfpack_zi_solve(sys,Ap,Ai,&internal::real_ref(Ax[0]),0,&internal::real_ref(X[0]),0,&internal::real_ref(B[0]),0,Numeric,Control,Info); -} - -inline int umfpack_get_lunz(int *lnz, int *unz, int *n_row, int *n_col, int *nz_udiag, void *Numeric, double) -{ - return umfpack_di_get_lunz(lnz,unz,n_row,n_col,nz_udiag,Numeric); -} - -inline int umfpack_get_lunz(int *lnz, int *unz, int *n_row, int *n_col, int *nz_udiag, void *Numeric, std::complex) -{ - return umfpack_zi_get_lunz(lnz,unz,n_row,n_col,nz_udiag,Numeric); -} - -inline int umfpack_get_numeric(int Lp[], int Lj[], double Lx[], int Up[], int Ui[], double Ux[], - int P[], int Q[], double Dx[], int *do_recip, double Rs[], void *Numeric) -{ - return umfpack_di_get_numeric(Lp,Lj,Lx,Up,Ui,Ux,P,Q,Dx,do_recip,Rs,Numeric); -} - -inline int umfpack_get_numeric(int Lp[], int Lj[], std::complex Lx[], int Up[], int Ui[], std::complex Ux[], - int P[], int Q[], std::complex Dx[], int *do_recip, double Rs[], void *Numeric) -{ - double& lx0_real = internal::real_ref(Lx[0]); - double& ux0_real = internal::real_ref(Ux[0]); - double& dx0_real = internal::real_ref(Dx[0]); - return umfpack_zi_get_numeric(Lp,Lj,Lx?&lx0_real:0,0,Up,Ui,Ux?&ux0_real:0,0,P,Q, - Dx?&dx0_real:0,0,do_recip,Rs,Numeric); -} - -inline int umfpack_get_determinant(double *Mx, double *Ex, void *NumericHandle, double User_Info [UMFPACK_INFO]) -{ - return umfpack_di_get_determinant(Mx,Ex,NumericHandle,User_Info); -} - -inline int umfpack_get_determinant(std::complex *Mx, double *Ex, void *NumericHandle, double User_Info [UMFPACK_INFO]) -{ - double& mx_real = internal::real_ref(*Mx); - return umfpack_zi_get_determinant(&mx_real,0,Ex,NumericHandle,User_Info); -} - - -template -class SparseLU<_MatrixType,UmfPack> : public SparseLU<_MatrixType> -{ - protected: - typedef SparseLU<_MatrixType> Base; - typedef typename Base::Scalar Scalar; - typedef typename Base::RealScalar RealScalar; - typedef Matrix Vector; - typedef Matrix IntRowVectorType; - typedef Matrix IntColVectorType; - typedef SparseMatrix LMatrixType; - typedef SparseMatrix UMatrixType; - using Base::m_flags; - using Base::m_status; - - public: - typedef _MatrixType MatrixType; - typedef typename MatrixType::Index Index; - - SparseLU(int flags = NaturalOrdering) - : Base(flags), m_numeric(0) - { - } - - SparseLU(const MatrixType& matrix, int flags = NaturalOrdering) - : Base(flags), m_numeric(0) - { - compute(matrix); - } - - ~SparseLU() - { - if (m_numeric) - umfpack_free_numeric(&m_numeric,Scalar()); - } - - inline const LMatrixType& matrixL() const - { - if (m_extractedDataAreDirty) extractData(); - return m_l; - } - - inline const UMatrixType& matrixU() const - { - if (m_extractedDataAreDirty) extractData(); - return m_u; - } - - inline const IntColVectorType& permutationP() const - { - if (m_extractedDataAreDirty) extractData(); - return m_p; - } - - inline const IntRowVectorType& permutationQ() const - { - if (m_extractedDataAreDirty) extractData(); - return m_q; - } - - Scalar determinant() const; - - template - bool solve(const MatrixBase &b, MatrixBase* x) const; - - template - inline const internal::solve_retval, Rhs> - solve(const MatrixBase& b) const - { - eigen_assert(true && "SparseLU is not initialized."); - return internal::solve_retval, Rhs>(*this, b.derived()); - } - - void compute(const MatrixType& matrix); - - inline Index cols() const { return m_matrixRef->cols(); } - inline Index rows() const { return m_matrixRef->rows(); } - - inline const MatrixType& matrixLU() const - { - //eigen_assert(m_isInitialized && "LU is not initialized."); - return *m_matrixRef; - } - - const void* numeric() const - { - return m_numeric; - } - - protected: - - void extractData() const; - - protected: - // cached data: - void* m_numeric; - const MatrixType* m_matrixRef; - mutable LMatrixType m_l; - mutable UMatrixType m_u; - mutable IntColVectorType m_p; - mutable IntRowVectorType m_q; - mutable bool m_extractedDataAreDirty; -}; - -namespace internal { - -template - struct solve_retval, Rhs> - : solve_retval_base, Rhs> -{ - typedef SparseLU<_MatrixType, UmfPack> SpLUDecType; - EIGEN_MAKE_SOLVE_HELPERS(SpLUDecType,Rhs) - - template void evalTo(Dest& dst) const - { - const int rhsCols = rhs().cols(); - - eigen_assert((Rhs::Flags&RowMajorBit)==0 && "UmfPack backend does not support non col-major rhs yet"); - eigen_assert((Dest::Flags&RowMajorBit)==0 && "UmfPack backend does not support non col-major result yet"); - - void* numeric = const_cast(dec().numeric()); - - EIGEN_UNUSED int errorCode = 0; - for (int j=0; j -void SparseLU::compute(const MatrixType& a) -{ - typedef typename MatrixType::Index Index; - const Index rows = a.rows(); - const Index cols = a.cols(); - eigen_assert((MatrixType::Flags&RowMajorBit)==0 && "Row major matrices are not supported yet"); - - m_matrixRef = &a; - - if (m_numeric) - umfpack_free_numeric(&m_numeric,Scalar()); - - void* symbolic; - int errorCode = 0; - errorCode = umfpack_symbolic(rows, cols, a._outerIndexPtr(), a._innerIndexPtr(), a._valuePtr(), - &symbolic, 0, 0); - if (errorCode==0) - errorCode = umfpack_numeric(a._outerIndexPtr(), a._innerIndexPtr(), a._valuePtr(), - symbolic, &m_numeric, 0, 0); - - umfpack_free_symbolic(&symbolic,Scalar()); - - m_extractedDataAreDirty = true; - - Base::m_succeeded = (errorCode==0); -} - -template -void SparseLU::extractData() const -{ - if (m_extractedDataAreDirty) - { - // get size of the data - int lnz, unz, rows, cols, nz_udiag; - umfpack_get_lunz(&lnz, &unz, &rows, &cols, &nz_udiag, m_numeric, Scalar()); - - // allocate data - m_l.resize(rows,(std::min)(rows,cols)); - m_l.resizeNonZeros(lnz); - - m_u.resize((std::min)(rows,cols),cols); - m_u.resizeNonZeros(unz); - - m_p.resize(rows); - m_q.resize(cols); - - // extract - umfpack_get_numeric(m_l._outerIndexPtr(), m_l._innerIndexPtr(), m_l._valuePtr(), - m_u._outerIndexPtr(), m_u._innerIndexPtr(), m_u._valuePtr(), - m_p.data(), m_q.data(), 0, 0, 0, m_numeric); - - m_extractedDataAreDirty = false; - } -} - -template -typename SparseLU::Scalar SparseLU::determinant() const -{ - Scalar det; - umfpack_get_determinant(&det, 0, m_numeric, 0); - return det; -} - -template -template -bool SparseLU::solve(const MatrixBase &b, MatrixBase *x) const -{ - //const int size = m_matrix.rows(); - const int rhsCols = b.cols(); -// eigen_assert(size==b.rows()); - eigen_assert((BDerived::Flags&RowMajorBit)==0 && "UmfPack backend does not support non col-major rhs yet"); - eigen_assert((XDerived::Flags&RowMajorBit)==0 && "UmfPack backend does not support non col-major result yet"); - - int errorCode; - for (int j=0; j_outerIndexPtr(), m_matrixRef->_innerIndexPtr(), m_matrixRef->_valuePtr(), - &x->col(j).coeffRef(0), &b.const_cast_derived().col(j).coeffRef(0), m_numeric, 0, 0); - if (errorCode!=0) - return false; - } -// errorCode = umfpack_di_solve(UMFPACK_A, -// m_matrixRef._outerIndexPtr(), m_matrixRef._innerIndexPtr(), m_matrixRef._valuePtr(), -// x->derived().data(), b.derived().data(), m_numeric, 0, 0); - - return true; -} - -#endif // EIGEN_UMFPACKSUPPORT_H diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/Splines/CMakeLists.txt b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/Splines/CMakeLists.txt new file mode 100644 index 000000000..55c6271e9 --- /dev/null +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/Splines/CMakeLists.txt @@ -0,0 +1,6 @@ +FILE(GLOB Eigen_Splines_SRCS "*.h") + +INSTALL(FILES + ${Eigen_Splines_SRCS} + DESTINATION ${INCLUDE_INSTALL_DIR}/unsupported/Eigen/src/Splines COMPONENT Devel + ) diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/Splines/Spline.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/Splines/Spline.h new file mode 100644 index 000000000..4c06453f7 --- /dev/null +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/Splines/Spline.h @@ -0,0 +1,479 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 20010-2011 Hauke Heibel +// +// Eigen is free software; you can redistribute it and/or +// modify it under the terms of the GNU Lesser General Public +// License as published by the Free Software Foundation; either +// version 3 of the License, or (at your option) any later version. +// +// Alternatively, you can redistribute it and/or +// modify it under the terms of the GNU General Public License as +// published by the Free Software Foundation; either version 2 of +// the License, or (at your option) any later version. +// +// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY +// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the +// GNU General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public +// License and a copy of the GNU General Public License along with +// Eigen. If not, see . + +#ifndef EIGEN_SPLINE_H +#define EIGEN_SPLINE_H + +#include "SplineFwd.h" + +namespace Eigen +{ + /** + * \ingroup Splines_Module + * \class Spline class + * \brief A class representing multi-dimensional spline curves. + * + * The class represents B-splines with non-uniform knot vectors. Each control + * point of the B-spline is associated with a basis function + * \f{align*} + * C(u) & = \sum_{i=0}^{n}N_{i,p}(u)P_i + * \f} + * + * \tparam _Scalar The underlying data type (typically float or double) + * \tparam _Dim The curve dimension (e.g. 2 or 3) + * \tparam _Degree Per default set to Dynamic; could be set to the actual desired + * degree for optimization purposes (would result in stack allocation + * of several temporary variables). + **/ + template + class Spline + { + public: + typedef _Scalar Scalar; /*!< The spline curve's scalar type. */ + enum { Dimension = _Dim /*!< The spline curve's dimension. */ }; + enum { Degree = _Degree /*!< The spline curve's degree. */ }; + + /** \brief The point type the spline is representing. */ + typedef typename SplineTraits::PointType PointType; + + /** \brief The data type used to store knot vectors. */ + typedef typename SplineTraits::KnotVectorType KnotVectorType; + + /** \brief The data type used to store non-zero basis functions. */ + typedef typename SplineTraits::BasisVectorType BasisVectorType; + + /** \brief The data type representing the spline's control points. */ + typedef typename SplineTraits::ControlPointVectorType ControlPointVectorType; + + /** + * \brief Creates a spline from a knot vector and control points. + * \param knots The spline's knot vector. + * \param ctrls The spline's control point vector. + **/ + template + Spline(const OtherVectorType& knots, const OtherArrayType& ctrls) : m_knots(knots), m_ctrls(ctrls) {} + + /** + * \brief Copy constructor for splines. + * \param spline The input spline. + **/ + template + Spline(const Spline& spline) : + m_knots(spline.knots()), m_ctrls(spline.ctrls()) {} + + /** + * \brief Returns the knots of the underlying spline. + **/ + const KnotVectorType& knots() const { return m_knots; } + + /** + * \brief Returns the knots of the underlying spline. + **/ + const ControlPointVectorType& ctrls() const { return m_ctrls; } + + /** + * \brief Returns the spline value at a given site \f$u\f$. + * + * The function returns + * \f{align*} + * C(u) & = \sum_{i=0}^{n}N_{i,p}P_i + * \f} + * + * \param u Parameter \f$u \in [0;1]\f$ at which the spline is evaluated. + * \return The spline value at the given location \f$u\f$. + **/ + PointType operator()(Scalar u) const; + + /** + * \brief Evaluation of spline derivatives of up-to given order. + * + * The function returns + * \f{align*} + * \frac{d^i}{du^i}C(u) & = \sum_{i=0}^{n} \frac{d^i}{du^i} N_{i,p}(u)P_i + * \f} + * for i ranging between 0 and order. + * + * \param u Parameter \f$u \in [0;1]\f$ at which the spline derivative is evaluated. + * \param order The order up to which the derivatives are computed. + **/ + typename SplineTraits::DerivativeType + derivatives(Scalar u, DenseIndex order) const; + + /** + * \copydoc Spline::derivatives + * Using the template version of this function is more efficieent since + * temporary objects are allocated on the stack whenever this is possible. + **/ + template + typename SplineTraits::DerivativeType + derivatives(Scalar u, DenseIndex order = DerivativeOrder) const; + + /** + * \brief Computes the non-zero basis functions at the given site. + * + * Splines have local support and a point from their image is defined + * by exactly \f$p+1\f$ control points \f$P_i\f$ where \f$p\f$ is the + * spline degree. + * + * This function computes the \f$p+1\f$ non-zero basis function values + * for a given parameter value \f$u\f$. It returns + * \f{align*}{ + * N_{i,p}(u), \hdots, N_{i+p+1,p}(u) + * \f} + * + * \param u Parameter \f$u \in [0;1]\f$ at which the non-zero basis functions + * are computed. + **/ + typename SplineTraits::BasisVectorType + basisFunctions(Scalar u) const; + + /** + * \brief Computes the non-zero spline basis function derivatives up to given order. + * + * The function computes + * \f{align*}{ + * \frac{d^i}{du^i} N_{i,p}(u), \hdots, \frac{d^i}{du^i} N_{i+p+1,p}(u) + * \f} + * with i ranging from 0 up to the specified order. + * + * \param u Parameter \f$u \in [0;1]\f$ at which the non-zero basis function + * derivatives are computed. + * \param order The order up to which the basis function derivatives are computes. + **/ + typename SplineTraits::BasisDerivativeType + basisFunctionDerivatives(Scalar u, DenseIndex order) const; + + /** + * \copydoc Spline::basisFunctionDerivatives + * Using the template version of this function is more efficieent since + * temporary objects are allocated on the stack whenever this is possible. + **/ + template + typename SplineTraits::BasisDerivativeType + basisFunctionDerivatives(Scalar u, DenseIndex order = DerivativeOrder) const; + + /** + * \brief Returns the spline degree. + **/ + DenseIndex degree() const; + + /** + * \brief Returns the span within the knot vector in which u is falling. + * \param u The site for which the span is determined. + **/ + DenseIndex span(Scalar u) const; + + /** + * \brief Computes the spang within the provided knot vector in which u is falling. + **/ + static DenseIndex Span(typename SplineTraits::Scalar u, DenseIndex degree, const typename SplineTraits::KnotVectorType& knots); + + /** + * \brief Returns the spline's non-zero basis functions. + * + * The function computes and returns + * \f{align*}{ + * N_{i,p}(u), \hdots, N_{i+p+1,p}(u) + * \f} + * + * \param u The site at which the basis functions are computed. + * \param degree The degree of the underlying spline. + * \param knots The underlying spline's knot vector. + **/ + static BasisVectorType BasisFunctions(Scalar u, DenseIndex degree, const KnotVectorType& knots); + + + private: + KnotVectorType m_knots; /*!< Knot vector. */ + ControlPointVectorType m_ctrls; /*!< Control points. */ + }; + + template + DenseIndex Spline<_Scalar, _Dim, _Degree>::Span( + typename SplineTraits< Spline<_Scalar, _Dim, _Degree> >::Scalar u, + DenseIndex degree, + const typename SplineTraits< Spline<_Scalar, _Dim, _Degree> >::KnotVectorType& knots) + { + // Piegl & Tiller, "The NURBS Book", A2.1 (p. 68) + if (u <= knots(0)) return degree; + const Scalar* pos = std::upper_bound(knots.data()+degree-1, knots.data()+knots.size()-degree-1, u); + return static_cast( std::distance(knots.data(), pos) - 1 ); + } + + template + typename Spline<_Scalar, _Dim, _Degree>::BasisVectorType + Spline<_Scalar, _Dim, _Degree>::BasisFunctions( + typename Spline<_Scalar, _Dim, _Degree>::Scalar u, + DenseIndex degree, + const typename Spline<_Scalar, _Dim, _Degree>::KnotVectorType& knots) + { + typedef typename Spline<_Scalar, _Dim, _Degree>::BasisVectorType BasisVectorType; + + const DenseIndex p = degree; + const DenseIndex i = Spline::Span(u, degree, knots); + + const KnotVectorType& U = knots; + + BasisVectorType left(p+1); left(0) = Scalar(0); + BasisVectorType right(p+1); right(0) = Scalar(0); + + VectorBlock(left,1,p) = u - VectorBlock(U,i+1-p,p).reverse(); + VectorBlock(right,1,p) = VectorBlock(U,i+1,p) - u; + + BasisVectorType N(1,p+1); + N(0) = Scalar(1); + for (DenseIndex j=1; j<=p; ++j) + { + Scalar saved = Scalar(0); + for (DenseIndex r=0; r + DenseIndex Spline<_Scalar, _Dim, _Degree>::degree() const + { + if (_Degree == Dynamic) + return m_knots.size() - m_ctrls.cols() - 1; + else + return _Degree; + } + + template + DenseIndex Spline<_Scalar, _Dim, _Degree>::span(Scalar u) const + { + return Spline::Span(u, degree(), knots()); + } + + template + typename Spline<_Scalar, _Dim, _Degree>::PointType Spline<_Scalar, _Dim, _Degree>::operator()(Scalar u) const + { + enum { Order = SplineTraits::OrderAtCompileTime }; + + const DenseIndex span = this->span(u); + const DenseIndex p = degree(); + const BasisVectorType basis_funcs = basisFunctions(u); + + const Replicate ctrl_weights(basis_funcs); + const Block ctrl_pts(ctrls(),0,span-p,Dimension,p+1); + return (ctrl_weights * ctrl_pts).rowwise().sum(); + } + + /* --------------------------------------------------------------------------------------------- */ + + template + void derivativesImpl(const SplineType& spline, typename SplineType::Scalar u, DenseIndex order, DerivativeType& der) + { + enum { Dimension = SplineTraits::Dimension }; + enum { Order = SplineTraits::OrderAtCompileTime }; + enum { DerivativeOrder = DerivativeType::ColsAtCompileTime }; + + typedef typename SplineTraits::Scalar Scalar; + + typedef typename SplineTraits::BasisVectorType BasisVectorType; + typedef typename SplineTraits::ControlPointVectorType ControlPointVectorType; + + typedef typename SplineTraits::BasisDerivativeType BasisDerivativeType; + typedef typename BasisDerivativeType::ConstRowXpr BasisDerivativeRowXpr; + + const DenseIndex p = spline.degree(); + const DenseIndex span = spline.span(u); + + const DenseIndex n = (std::min)(p, order); + + der.resize(Dimension,n+1); + + // Retrieve the basis function derivatives up to the desired order... + const BasisDerivativeType basis_func_ders = spline.template basisFunctionDerivatives(u, n+1); + + // ... and perform the linear combinations of the control points. + for (DenseIndex der_order=0; der_order ctrl_weights( basis_func_ders.row(der_order) ); + const Block ctrl_pts(spline.ctrls(),0,span-p,Dimension,p+1); + der.col(der_order) = (ctrl_weights * ctrl_pts).rowwise().sum(); + } + } + + template + typename SplineTraits< Spline<_Scalar, _Dim, _Degree> >::DerivativeType + Spline<_Scalar, _Dim, _Degree>::derivatives(Scalar u, DenseIndex order) const + { + typename SplineTraits< Spline >::DerivativeType res; + derivativesImpl(*this, u, order, res); + return res; + } + + template + template + typename SplineTraits< Spline<_Scalar, _Dim, _Degree>, DerivativeOrder >::DerivativeType + Spline<_Scalar, _Dim, _Degree>::derivatives(Scalar u, DenseIndex order) const + { + typename SplineTraits< Spline, DerivativeOrder >::DerivativeType res; + derivativesImpl(*this, u, order, res); + return res; + } + + template + typename SplineTraits< Spline<_Scalar, _Dim, _Degree> >::BasisVectorType + Spline<_Scalar, _Dim, _Degree>::basisFunctions(Scalar u) const + { + return Spline::BasisFunctions(u, degree(), knots()); + } + + /* --------------------------------------------------------------------------------------------- */ + + template + void basisFunctionDerivativesImpl(const SplineType& spline, typename SplineType::Scalar u, DenseIndex order, DerivativeType& N_) + { + enum { Order = SplineTraits::OrderAtCompileTime }; + + typedef typename SplineTraits::Scalar Scalar; + typedef typename SplineTraits::BasisVectorType BasisVectorType; + typedef typename SplineTraits::KnotVectorType KnotVectorType; + typedef typename SplineTraits::ControlPointVectorType ControlPointVectorType; + + const KnotVectorType& U = spline.knots(); + + const DenseIndex p = spline.degree(); + const DenseIndex span = spline.span(u); + + const DenseIndex n = (std::min)(p, order); + + N_.resize(n+1, p+1); + + BasisVectorType left = BasisVectorType::Zero(p+1); + BasisVectorType right = BasisVectorType::Zero(p+1); + + Matrix ndu(p+1,p+1); + + double saved, temp; + + ndu(0,0) = 1.0; + + DenseIndex j; + for (j=1; j<=p; ++j) + { + left[j] = u-U[span+1-j]; + right[j] = U[span+j]-u; + saved = 0.0; + + for (DenseIndex r=0; r(saved+right[r+1] * temp); + saved = left[j-r] * temp; + } + + ndu(j,j) = static_cast(saved); + } + + for (j = p; j>=0; --j) + N_(0,j) = ndu(j,p); + + // Compute the derivatives + DerivativeType a(n+1,p+1); + DenseIndex r=0; + for (; r<=p; ++r) + { + DenseIndex s1,s2; + s1 = 0; s2 = 1; // alternate rows in array a + a(0,0) = 1.0; + + // Compute the k-th derivative + for (DenseIndex k=1; k<=static_cast(n); ++k) + { + double d = 0.0; + DenseIndex rk,pk,j1,j2; + rk = r-k; pk = p-k; + + if (r>=k) + { + a(s2,0) = a(s1,0)/ndu(pk+1,rk); + d = a(s2,0)*ndu(rk,pk); + } + + if (rk>=-1) j1 = 1; + else j1 = -rk; + + if (r-1 <= pk) j2 = k-1; + else j2 = p-r; + + for (j=j1; j<=j2; ++j) + { + a(s2,j) = (a(s1,j)-a(s1,j-1))/ndu(pk+1,rk+j); + d += a(s2,j)*ndu(rk+j,pk); + } + + if (r<=pk) + { + a(s2,k) = -a(s1,k-1)/ndu(pk+1,r); + d += a(s2,k)*ndu(r,pk); + } + + N_(k,r) = static_cast(d); + j = s1; s1 = s2; s2 = j; // Switch rows + } + } + + /* Multiply through by the correct factors */ + /* (Eq. [2.9]) */ + r = p; + for (DenseIndex k=1; k<=static_cast(n); ++k) + { + for (DenseIndex j=p; j>=0; --j) N_(k,j) *= r; + r *= p-k; + } + } + + template + typename SplineTraits< Spline<_Scalar, _Dim, _Degree> >::BasisDerivativeType + Spline<_Scalar, _Dim, _Degree>::basisFunctionDerivatives(Scalar u, DenseIndex order) const + { + typename SplineTraits< Spline >::BasisDerivativeType der; + basisFunctionDerivativesImpl(*this, u, order, der); + return der; + } + + template + template + typename SplineTraits< Spline<_Scalar, _Dim, _Degree>, DerivativeOrder >::BasisDerivativeType + Spline<_Scalar, _Dim, _Degree>::basisFunctionDerivatives(Scalar u, DenseIndex order) const + { + typename SplineTraits< Spline, DerivativeOrder >::BasisDerivativeType der; + basisFunctionDerivativesImpl(*this, u, order, der); + return der; + } +} + +#endif // EIGEN_SPLINE_H diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/Splines/SplineFitting.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/Splines/SplineFitting.h new file mode 100644 index 000000000..3e8abbbce --- /dev/null +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/Splines/SplineFitting.h @@ -0,0 +1,174 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 20010-2011 Hauke Heibel +// +// Eigen is free software; you can redistribute it and/or +// modify it under the terms of the GNU Lesser General Public +// License as published by the Free Software Foundation; either +// version 3 of the License, or (at your option) any later version. +// +// Alternatively, you can redistribute it and/or +// modify it under the terms of the GNU General Public License as +// published by the Free Software Foundation; either version 2 of +// the License, or (at your option) any later version. +// +// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY +// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the +// GNU General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public +// License and a copy of the GNU General Public License along with +// Eigen. If not, see . + +#ifndef EIGEN_SPLINE_FITTING_H +#define EIGEN_SPLINE_FITTING_H + +#include + +#include "SplineFwd.h" + +#include + +namespace Eigen +{ + /** + * \brief Computes knot averages. + * \ingroup Splines_Module + * + * The knots are computed as + * \f{align*} + * u_0 & = \hdots = u_p = 0 \\ + * u_{m-p} & = \hdots = u_{m} = 1 \\ + * u_{j+p} & = \frac{1}{p}\sum_{i=j}^{j+p-1}\bar{u}_i \quad\quad j=1,\hdots,n-p + * \f} + * where \f$p\f$ is the degree and \f$m+1\f$ the number knots + * of the desired interpolating spline. + * + * \param[in] parameters The input parameters. During interpolation one for each data point. + * \param[in] degree The spline degree which is used during the interpolation. + * \param[out] knots The output knot vector. + * + * \sa Les Piegl and Wayne Tiller, The NURBS book (2nd ed.), 1997, 9.2.1 Global Curve Interpolation to Point Data + **/ + template + void KnotAveraging(const KnotVectorType& parameters, DenseIndex degree, KnotVectorType& knots) + { + typedef typename KnotVectorType::Scalar Scalar; + + knots.resize(parameters.size()+degree+1); + + for (DenseIndex j=1; j + void ChordLengths(const PointArrayType& pts, KnotVectorType& chord_lengths) + { + typedef typename KnotVectorType::Scalar Scalar; + + const DenseIndex n = pts.cols(); + + // 1. compute the column-wise norms + chord_lengths.resize(pts.cols()); + chord_lengths[0] = 0; + chord_lengths.rightCols(n-1) = (pts.array().leftCols(n-1) - pts.array().rightCols(n-1)).matrix().colwise().norm(); + + // 2. compute the partial sums + std::partial_sum(chord_lengths.data(), chord_lengths.data()+n, chord_lengths.data()); + + // 3. normalize the data + chord_lengths /= chord_lengths(n-1); + chord_lengths(n-1) = Scalar(1); + } + + /** + * \brief Spline fitting methods. + * \ingroup Splines_Module + **/ + template + struct SplineFitting + { + typedef typename SplineType::KnotVectorType KnotVectorType; + + /** + * \brief Fits an interpolating Spline to the given data points. + * + * \param pts The points for which an interpolating spline will be computed. + * \param degree The degree of the interpolating spline. + * + * \returns A spline interpolating the initially provided points. + **/ + template + static SplineType Interpolate(const PointArrayType& pts, DenseIndex degree); + + /** + * \brief Fits an interpolating Spline to the given data points. + * + * \param pts The points for which an interpolating spline will be computed. + * \param degree The degree of the interpolating spline. + * \param knot_parameters The knot parameters for the interpolation. + * + * \returns A spline interpolating the initially provided points. + **/ + template + static SplineType Interpolate(const PointArrayType& pts, DenseIndex degree, const KnotVectorType& knot_parameters); + }; + + template + template + SplineType SplineFitting::Interpolate(const PointArrayType& pts, DenseIndex degree, const KnotVectorType& knot_parameters) + { + typedef typename SplineType::KnotVectorType::Scalar Scalar; + typedef typename SplineType::BasisVectorType BasisVectorType; + typedef typename SplineType::ControlPointVectorType ControlPointVectorType; + + typedef Matrix MatrixType; + + KnotVectorType knots; + KnotAveraging(knot_parameters, degree, knots); + + DenseIndex n = pts.cols(); + MatrixType A = MatrixType::Zero(n,n); + for (DenseIndex i=1; i qr(A); + + // Here, we are creating a temporary due to an Eigen issue. + ControlPointVectorType ctrls = qr.solve(MatrixType(pts.transpose())).transpose(); + + return SplineType(knots, ctrls); + } + + template + template + SplineType SplineFitting::Interpolate(const PointArrayType& pts, DenseIndex degree) + { + KnotVectorType chord_lengths; // knot parameters + ChordLengths(pts, chord_lengths); + return Interpolate(pts, degree, chord_lengths); + } +} + +#endif // EIGEN_SPLINE_FITTING_H diff --git a/gtsam/3rdparty/Eigen/unsupported/Eigen/src/Splines/SplineFwd.h b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/Splines/SplineFwd.h new file mode 100644 index 000000000..0119115a6 --- /dev/null +++ b/gtsam/3rdparty/Eigen/unsupported/Eigen/src/Splines/SplineFwd.h @@ -0,0 +1,101 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 20010-2011 Hauke Heibel +// +// Eigen is free software; you can redistribute it and/or +// modify it under the terms of the GNU Lesser General Public +// License as published by the Free Software Foundation; either +// version 3 of the License, or (at your option) any later version. +// +// Alternatively, you can redistribute it and/or +// modify it under the terms of the GNU General Public License as +// published by the Free Software Foundation; either version 2 of +// the License, or (at your option) any later version. +// +// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY +// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the +// GNU General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public +// License and a copy of the GNU General Public License along with +// Eigen. If not, see . + +#ifndef EIGEN_SPLINES_FWD_H +#define EIGEN_SPLINES_FWD_H + +#include + +namespace Eigen +{ + template class Spline; + + template < typename SplineType, int DerivativeOrder = Dynamic > struct SplineTraits {}; + + /** + * \ingroup Splines_Module + * \brief Compile-time attributes of the Spline class for Dynamic degree. + **/ + template + struct SplineTraits< Spline<_Scalar, _Dim, _Degree>, Dynamic > + { + typedef _Scalar Scalar; /*!< The spline curve's scalar type. */ + enum { Dimension = _Dim /*!< The spline curve's dimension. */ }; + enum { Degree = _Degree /*!< The spline curve's degree. */ }; + + enum { OrderAtCompileTime = _Degree==Dynamic ? Dynamic : _Degree+1 /*!< The spline curve's order at compile-time. */ }; + enum { NumOfDerivativesAtCompileTime = OrderAtCompileTime /*!< The number of derivatives defined for the current spline. */ }; + + /** \brief The data type used to store non-zero basis functions. */ + typedef Array BasisVectorType; + + /** \brief The data type used to store the values of the basis function derivatives. */ + typedef Array BasisDerivativeType; + + /** \brief The data type used to store the spline's derivative values. */ + typedef Array DerivativeType; + + /** \brief The point type the spline is representing. */ + typedef Array PointType; + + /** \brief The data type used to store knot vectors. */ + typedef Array KnotVectorType; + + /** \brief The data type representing the spline's control points. */ + typedef Array ControlPointVectorType; + }; + + /** + * \ingroup Splines_Module + * \brief Compile-time attributes of the Spline class for fixed degree. + * + * The traits class inherits all attributes from the SplineTraits of Dynamic degree. + **/ + template < typename _Scalar, int _Dim, int _Degree, int _DerivativeOrder > + struct SplineTraits< Spline<_Scalar, _Dim, _Degree>, _DerivativeOrder > : public SplineTraits< Spline<_Scalar, _Dim, _Degree> > + { + enum { OrderAtCompileTime = _Degree==Dynamic ? Dynamic : _Degree+1 /*!< The spline curve's order at compile-time. */ }; + enum { NumOfDerivativesAtCompileTime = _DerivativeOrder==Dynamic ? Dynamic : _DerivativeOrder+1 /*!< The number of derivatives defined for the current spline. */ }; + + /** \brief The data type used to store the values of the basis function derivatives. */ + typedef Array<_Scalar,Dynamic,Dynamic,RowMajor,NumOfDerivativesAtCompileTime,OrderAtCompileTime> BasisDerivativeType; + + /** \brief The data type used to store the spline's derivative values. */ + typedef Array<_Scalar,_Dim,Dynamic,ColMajor,_Dim,NumOfDerivativesAtCompileTime> DerivativeType; + }; + + /** \brief 2D float B-spline with dynamic degree. */ + typedef Spline Spline2f; + + /** \brief 3D float B-spline with dynamic degree. */ + typedef Spline Spline3f; + + /** \brief 2D double B-spline with dynamic degree. */ + typedef Spline Spline2d; + + /** \brief 3D double B-spline with dynamic degree. */ + typedef Spline Spline3d; +} + +#endif // EIGEN_SPLINES_FWD_H diff --git a/gtsam/3rdparty/Eigen/unsupported/doc/Doxyfile.in b/gtsam/3rdparty/Eigen/unsupported/doc/Doxyfile.in index 7d5f24b4e..1facf2985 100644 --- a/gtsam/3rdparty/Eigen/unsupported/doc/Doxyfile.in +++ b/gtsam/3rdparty/Eigen/unsupported/doc/Doxyfile.in @@ -203,7 +203,6 @@ ALIASES = "only_for_vectors=This is only for vectors (either row- "svd_module=This is defined in the %SVD module. \code #include \endcode" \ "geometry_module=This is defined in the %Geometry module. \code #include \endcode" \ "label=\bug" \ - "redstar=*" \ "nonstableyet=\warning This is not considered to be part of the stable public API yet. Changes may happen in future releases. See \ref Experimental \"Experimental parts of Eigen\"" # Set the OPTIMIZE_OUTPUT_FOR_C tag to YES if your project consists of C @@ -576,13 +575,14 @@ FILE_PATTERNS = * # should be searched for input files as well. Possible values are YES and NO. # If left blank NO is used. -RECURSIVE = NO +RECURSIVE = YES # The EXCLUDE tag can be used to specify files and/or directories that should # excluded from the INPUT source files. This way you can easily exclude a # subdirectory from a directory tree whose root is specified with the INPUT tag. -EXCLUDE = +EXCLUDE = "${Eigen_SOURCE_DIR}/unsupported/doc/examples" \ + "${Eigen_SOURCE_DIR}/unsupported/doc/snippets" # The EXCLUDE_SYMLINKS tag can be used select whether or not files or # directories that are symbolic links (a Unix filesystem feature) are excluded @@ -958,7 +958,8 @@ PAPER_TYPE = a4wide # The EXTRA_PACKAGES tag can be to specify one or more names of LaTeX # packages that should be included in the LaTeX output. -EXTRA_PACKAGES = amssymb +EXTRA_PACKAGES = amssymb \ + amsmath # The LATEX_HEADER tag can be used to specify a personal LaTeX header for # the generated latex document. The header should contain everything until diff --git a/gtsam/3rdparty/Eigen/unsupported/doc/examples/MatrixLogarithm.cpp b/gtsam/3rdparty/Eigen/unsupported/doc/examples/MatrixLogarithm.cpp new file mode 100644 index 000000000..8c5d97054 --- /dev/null +++ b/gtsam/3rdparty/Eigen/unsupported/doc/examples/MatrixLogarithm.cpp @@ -0,0 +1,15 @@ +#include +#include + +using namespace Eigen; + +int main() +{ + using std::sqrt; + MatrixXd A(3,3); + A << 0.5*sqrt(2), -0.5*sqrt(2), 0, + 0.5*sqrt(2), 0.5*sqrt(2), 0, + 0, 0, 1; + std::cout << "The matrix A is:\n" << A << "\n\n"; + std::cout << "The matrix logarithm of A is:\n" << A.log() << "\n"; +} diff --git a/gtsam/3rdparty/Eigen/unsupported/doc/examples/MatrixSquareRoot.cpp b/gtsam/3rdparty/Eigen/unsupported/doc/examples/MatrixSquareRoot.cpp new file mode 100644 index 000000000..88e7557d7 --- /dev/null +++ b/gtsam/3rdparty/Eigen/unsupported/doc/examples/MatrixSquareRoot.cpp @@ -0,0 +1,16 @@ +#include +#include + +using namespace Eigen; + +int main() +{ + const double pi = std::acos(-1.0); + + MatrixXd A(2,2); + A << cos(pi/3), -sin(pi/3), + sin(pi/3), cos(pi/3); + std::cout << "The matrix A is:\n" << A << "\n\n"; + std::cout << "The matrix square root of A is:\n" << A.sqrt() << "\n\n"; + std::cout << "The square of the last matrix is:\n" << A.sqrt() * A.sqrt() << "\n"; +} diff --git a/gtsam/3rdparty/Eigen/unsupported/test/BVH.cpp b/gtsam/3rdparty/Eigen/unsupported/test/BVH.cpp index e77e84b6d..3f9d108de 100644 --- a/gtsam/3rdparty/Eigen/unsupported/test/BVH.cpp +++ b/gtsam/3rdparty/Eigen/unsupported/test/BVH.cpp @@ -24,9 +24,15 @@ #include "main.h" #include +#include #include -inline double SQR(double x) { return x * x; } +namespace Eigen { + +template AlignedBox bounding_box(const Matrix &v) { return AlignedBox(v); } + +} + template struct Ball @@ -41,16 +47,10 @@ EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF_VECTORIZABLE_FIXED_SIZE(double, Dim) VectorType center; double radius; }; - -namespace Eigen { -namespace internal { - -template AlignedBox bounding_box(const Matrix &v) { return AlignedBox(v); } template AlignedBox bounding_box(const Ball &b) { return AlignedBox(b.center.array() - b.radius, b.center.array() + b.radius); } -} // end namespace internal -} +inline double SQR(double x) { return x * x; } template struct BallPointStuff //this class provides functions to be both an intersector and a minimizer, both for a ball and a point and for two trees diff --git a/gtsam/3rdparty/Eigen/unsupported/test/CMakeLists.txt b/gtsam/3rdparty/Eigen/unsupported/test/CMakeLists.txt index f8c0ff486..b34b151b1 100644 --- a/gtsam/3rdparty/Eigen/unsupported/test/CMakeLists.txt +++ b/gtsam/3rdparty/Eigen/unsupported/test/CMakeLists.txt @@ -1,47 +1,6 @@ -include_directories(../../test ../../unsupported ../../Eigen) - -set(SPARSE_LIBS "") - -# configure blas/lapack -if(CMAKE_Fortran_COMPILER_WORKS) - set(BLAS_FOUND TRUE) - set(LAPACK_FOUND TRUE) - set(BLAS_LIBRARIES eigen_blas_static) - set(LAPACK_LIBRARIES eigen_lapack_static) -else() - # TODO search for default blas/lapack -endif() - -find_package(Cholmod) -if(CHOLMOD_FOUND AND BLAS_FOUND AND LAPACK_FOUND) - add_definitions("-DEIGEN_CHOLMOD_SUPPORT") - include_directories(${CHOLMOD_INCLUDES}) - set(SPARSE_LIBS ${SPARSE_LIBS} ${CHOLMOD_LIBRARIES} ${BLAS_LIBRARIES} ${LAPACK_LIBRARIES}) - ei_add_property(EIGEN_TESTED_BACKENDS "Cholmod, ") -else() - ei_add_property(EIGEN_MISSING_BACKENDS "Cholmod, ") -endif() - -find_package(Umfpack) -if(UMFPACK_FOUND AND BLAS_FOUND) - add_definitions("-DEIGEN_UMFPACK_SUPPORT") - include_directories(${UMFPACK_INCLUDES}) - set(SPARSE_LIBS ${SPARSE_LIBS} ${UMFPACK_LIBRARIES} ${BLAS_LIBRARIES}) - ei_add_property(EIGEN_TESTED_BACKENDS "UmfPack, ") -else() - ei_add_property(EIGEN_MISSING_BACKENDS "UmfPack, ") -endif() - -find_package(SuperLU) -if(SUPERLU_FOUND AND BLAS_FOUND) - add_definitions("-DEIGEN_SUPERLU_SUPPORT") - include_directories(${SUPERLU_INCLUDES}) - set(SPARSE_LIBS ${SPARSE_LIBS} ${SUPERLU_LIBRARIES} ${BLAS_LIBRARIES}) - ei_add_property(EIGEN_TESTED_BACKENDS "SuperLU, ") -else() - ei_add_property(EIGEN_MISSING_BACKENDS "SuperLU, ") -endif() +include_directories(../../test ../../unsupported ../../Eigen + ${CMAKE_CURRENT_BINARY_DIR}/../../test) find_package(GoogleHash) if(GOOGLEHASH_FOUND) @@ -74,6 +33,7 @@ endif() ei_add_test(matrix_exponential) ei_add_test(matrix_function) +ei_add_test(matrix_square_root) ei_add_test(alignedvector3) ei_add_test(FFT) @@ -88,18 +48,16 @@ else() ei_add_property(EIGEN_MISSING_BACKENDS "MPFR C++, ") endif() -ei_add_test(sparse_llt "" "${SPARSE_LIBS}") -ei_add_test(sparse_ldlt "" "${SPARSE_LIBS}") -ei_add_test(sparse_lu "" "${SPARSE_LIBS}") ei_add_test(sparse_extra "" "") find_package(FFTW) if(FFTW_FOUND) ei_add_property(EIGEN_TESTED_BACKENDS "fftw, ") + include_directories( ${FFTW_INCLUDES} ) if(FFTWL_LIB) - ei_add_test(FFTW "-DEIGEN_FFTW_DEFAULT -DEIGEN_HAS_FFTWL" "fftw3;fftw3f;fftw3l" ) + ei_add_test(FFTW "-DEIGEN_FFTW_DEFAULT -DEIGEN_HAS_FFTWL" "${FFTW_LIBRARIES}" ) else() - ei_add_test(FFTW "-DEIGEN_FFTW_DEFAULT " "fftw3;fftw3f" ) + ei_add_test(FFTW "-DEIGEN_FFTW_DEFAULT" "${FFTW_LIBRARIES}" ) endif() else() ei_add_property(EIGEN_MISSING_BACKENDS "fftw, ") @@ -121,18 +79,9 @@ else() ei_add_property(EIGEN_MISSING_BACKENDS "OpenGL, ") endif() -find_package(GSL) -if(GSL_FOUND AND GSL_VERSION_MINOR LESS 9) - set(GSL_FOUND "") -endif(GSL_FOUND AND GSL_VERSION_MINOR LESS 9) -if(GSL_FOUND) - add_definitions("-DHAS_GSL" ${GSL_DEFINITIONS}) - include_directories(${GSL_INCLUDE_DIR}) - ei_add_property(EIGEN_TESTED_BACKENDS "GSL, ") -else(GSL_FOUND) - ei_add_property(EIGEN_MISSING_BACKENDS "GSL, ") - set(GSL_LIBRARIES " ") -endif(GSL_FOUND) - -ei_add_test(polynomialsolver " " "${GSL_LIBRARIES}" ) +ei_add_test(polynomialsolver) ei_add_test(polynomialutils) +ei_add_test(kronecker_product) +ei_add_test(splines) +ei_add_test(gmres) + diff --git a/gtsam/3rdparty/Eigen/unsupported/test/autodiff.cpp b/gtsam/3rdparty/Eigen/unsupported/test/autodiff.cpp index a32d85829..7ce4b4dee 100644 --- a/gtsam/3rdparty/Eigen/unsupported/test/autodiff.cpp +++ b/gtsam/3rdparty/Eigen/unsupported/test/autodiff.cpp @@ -28,13 +28,21 @@ template EIGEN_DONT_INLINE Scalar foo(const Scalar& x, const Scalar& y) { + using namespace std; // return x+std::sin(y); EIGEN_ASM_COMMENT("mybegin"); - return static_cast(x*2 - std::pow(x,2) + 2*std::sqrt(y*y) - 4 * std::sin(x) + 2 * std::cos(y) - std::exp(-0.5*x*x)); + return static_cast(x*2 - pow(x,2) + 2*sqrt(y*y) - 4 * sin(x) + 2 * cos(y) - exp(-0.5*x*x)); //return x+2*y*x;//x*2 -std::pow(x,2);//(2*y/x);// - y*2; EIGEN_ASM_COMMENT("myend"); } +template +EIGEN_DONT_INLINE typename Vector::Scalar foo(const Vector& p) +{ + typedef typename Vector::Scalar Scalar; + return (p-Vector(Scalar(-1),Scalar(1.))).norm() + (p.array() * p.array()).sum() + p.dot(p); +} + template struct TestFunc1 { @@ -140,9 +148,23 @@ void test_autodiff_scalar() typedef AutoDiffScalar AD; AD ax(1,Vector2f::UnitX()); AD ay(2,Vector2f::UnitY()); - foo(ax,ay); - std::cerr << foo(ax,ay).value() << " <> " - << foo(ax,ay).derivatives().transpose() << "\n\n"; + AD res = foo(ax,ay); + std::cerr << res.value() << " <> " + << res.derivatives().transpose() << "\n\n"; +} + +void test_autodiff_vector() +{ + std::cerr << foo(Vector2f(1,2)) << "\n"; + typedef AutoDiffScalar AD; + typedef Matrix VectorAD; + VectorAD p(AD(1),AD(-1)); + p.x().derivatives() = Vector2f::UnitX(); + p.y().derivatives() = Vector2f::UnitY(); + + AD res = foo(p); + std::cerr << res.value() << " <> " + << res.derivatives().transpose() << "\n\n"; } void test_autodiff_jacobian() @@ -159,6 +181,7 @@ void test_autodiff_jacobian() void test_autodiff() { test_autodiff_scalar(); - test_autodiff_jacobian(); + test_autodiff_vector(); +// test_autodiff_jacobian(); } diff --git a/gtsam/3rdparty/Eigen/unsupported/test/forward_adolc.cpp b/gtsam/3rdparty/Eigen/unsupported/test/forward_adolc.cpp index 1971d883b..07959a668 100644 --- a/gtsam/3rdparty/Eigen/unsupported/test/forward_adolc.cpp +++ b/gtsam/3rdparty/Eigen/unsupported/test/forward_adolc.cpp @@ -23,11 +23,20 @@ // Eigen. If not, see . #include "main.h" +#include + #define NUMBER_DIRECTIONS 16 #include int adtl::ADOLC_numDir; +template +EIGEN_DONT_INLINE typename Vector::Scalar foo(const Vector& p) +{ + typedef typename Vector::Scalar Scalar; + return (p-Vector(Scalar(-1),Scalar(1.))).norm() + (p.array().sqrt().abs() * p.array().sin()).sum() + p.dot(p); +} + template struct TestFunc1 { @@ -138,4 +147,12 @@ void test_forward_adolc() CALL_SUBTEST(( adolc_forward_jacobian(TestFunc1()) )); CALL_SUBTEST(( adolc_forward_jacobian(TestFunc1(3,3)) )); } + + { + // simple instanciation tests + Matrix x; + foo(x); + Matrix A(4,4);; + A.selfadjointView().eigenvalues(); + } } diff --git a/gtsam/3rdparty/Eigen/unsupported/test/gmres.cpp b/gtsam/3rdparty/Eigen/unsupported/test/gmres.cpp new file mode 100644 index 000000000..30ebe8979 --- /dev/null +++ b/gtsam/3rdparty/Eigen/unsupported/test/gmres.cpp @@ -0,0 +1,48 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2011 Gael Guennebaud +// Copyright (C) 2012 Kolja Brix +// +// Eigen is free software; you can redistribute it and/or +// modify it under the terms of the GNU Lesser General Public +// License as published by the Free Software Foundation; either +// version 3 of the License, or (at your option) any later version. +// +// Alternatively, you can redistribute it and/or +// modify it under the terms of the GNU General Public License as +// published by the Free Software Foundation; either version 2 of +// the License, or (at your option) any later version. +// +// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY +// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the +// GNU General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public +// License and a copy of the GNU General Public License along with +// Eigen. If not, see . + +#include "../../test/sparse_solver.h" +#include + +template void test_gmres_T() +{ + GMRES, DiagonalPreconditioner > gmres_colmajor_diag; + GMRES, IdentityPreconditioner > gmres_colmajor_I; + GMRES, IncompleteLUT > gmres_colmajor_ilut; + //GMRES, SSORPreconditioner > gmres_colmajor_ssor; + + CALL_SUBTEST( check_sparse_square_solving(gmres_colmajor_diag) ); +// CALL_SUBTEST( check_sparse_square_solving(gmres_colmajor_I) ); + CALL_SUBTEST( check_sparse_square_solving(gmres_colmajor_ilut) ); + //CALL_SUBTEST( check_sparse_square_solving(gmres_colmajor_ssor) ); +} + +void test_gmres() +{ + for(int i = 0; i < g_repeat; i++) { + CALL_SUBTEST_1(test_gmres_T()); + CALL_SUBTEST_2(test_gmres_T >()); + } +} diff --git a/gtsam/3rdparty/Eigen/unsupported/test/kronecker_product.cpp b/gtsam/3rdparty/Eigen/unsupported/test/kronecker_product.cpp new file mode 100644 index 000000000..3c7a6629f --- /dev/null +++ b/gtsam/3rdparty/Eigen/unsupported/test/kronecker_product.cpp @@ -0,0 +1,194 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2011 Kolja Brix +// Copyright (C) 2011 Andreas Platen +// +// Eigen is free software; you can redistribute it and/or +// modify it under the terms of the GNU Lesser General Public +// License as published by the Free Software Foundation; either +// version 3 of the License, or (at your option) any later version. +// +// Alternatively, you can redistribute it and/or +// modify it under the terms of the GNU General Public License as +// published by the Free Software Foundation; either version 2 of +// the License, or (at your option) any later version. +// +// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY +// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the +// GNU General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public +// License and a copy of the GNU General Public License along with +// Eigen. If not, see . + + +#include "sparse.h" +#include +#include + + +template +void check_dimension(const MatrixType& ab, const unsigned int rows, const unsigned int cols) +{ + VERIFY_IS_EQUAL(ab.rows(), rows); + VERIFY_IS_EQUAL(ab.cols(), cols); +} + + +template +void check_kronecker_product(const MatrixType& ab) +{ + VERIFY_IS_EQUAL(ab.rows(), 6); + VERIFY_IS_EQUAL(ab.cols(), 6); + VERIFY_IS_EQUAL(ab.nonZeros(), 36); + VERIFY_IS_APPROX(ab.coeff(0,0), -0.4017367630386106); + VERIFY_IS_APPROX(ab.coeff(0,1), 0.1056863433932735); + VERIFY_IS_APPROX(ab.coeff(0,2), -0.7255206194554212); + VERIFY_IS_APPROX(ab.coeff(0,3), 0.1908653336744706); + VERIFY_IS_APPROX(ab.coeff(0,4), 0.350864567234111); + VERIFY_IS_APPROX(ab.coeff(0,5), -0.0923032108308013); + VERIFY_IS_APPROX(ab.coeff(1,0), 0.415417514804677); + VERIFY_IS_APPROX(ab.coeff(1,1), -0.2369227701722048); + VERIFY_IS_APPROX(ab.coeff(1,2), 0.7502275131458511); + VERIFY_IS_APPROX(ab.coeff(1,3), -0.4278731019742696); + VERIFY_IS_APPROX(ab.coeff(1,4), -0.3628129162264507); + VERIFY_IS_APPROX(ab.coeff(1,5), 0.2069210808481275); + VERIFY_IS_APPROX(ab.coeff(2,0), 0.05465890160863986); + VERIFY_IS_APPROX(ab.coeff(2,1), -0.2634092511419858); + VERIFY_IS_APPROX(ab.coeff(2,2), 0.09871180285793758); + VERIFY_IS_APPROX(ab.coeff(2,3), -0.4757066334017702); + VERIFY_IS_APPROX(ab.coeff(2,4), -0.04773740823058334); + VERIFY_IS_APPROX(ab.coeff(2,5), 0.2300535609645254); + VERIFY_IS_APPROX(ab.coeff(3,0), -0.8172945853260133); + VERIFY_IS_APPROX(ab.coeff(3,1), 0.2150086428359221); + VERIFY_IS_APPROX(ab.coeff(3,2), 0.5825113847292743); + VERIFY_IS_APPROX(ab.coeff(3,3), -0.1532433770097174); + VERIFY_IS_APPROX(ab.coeff(3,4), -0.329383387282399); + VERIFY_IS_APPROX(ab.coeff(3,5), 0.08665207912033064); + VERIFY_IS_APPROX(ab.coeff(4,0), 0.8451267514863225); + VERIFY_IS_APPROX(ab.coeff(4,1), -0.481996458918977); + VERIFY_IS_APPROX(ab.coeff(4,2), -0.6023482390791535); + VERIFY_IS_APPROX(ab.coeff(4,3), 0.3435339347164565); + VERIFY_IS_APPROX(ab.coeff(4,4), 0.3406002157428891); + VERIFY_IS_APPROX(ab.coeff(4,5), -0.1942526344200915); + VERIFY_IS_APPROX(ab.coeff(5,0), 0.1111982482925399); + VERIFY_IS_APPROX(ab.coeff(5,1), -0.5358806424754169); + VERIFY_IS_APPROX(ab.coeff(5,2), -0.07925446559335647); + VERIFY_IS_APPROX(ab.coeff(5,3), 0.3819388757769038); + VERIFY_IS_APPROX(ab.coeff(5,4), 0.04481475387219876); + VERIFY_IS_APPROX(ab.coeff(5,5), -0.2159688616158057); +} + + +template +void check_sparse_kronecker_product(const MatrixType& ab) +{ + VERIFY_IS_EQUAL(ab.rows(), 12); + VERIFY_IS_EQUAL(ab.cols(), 10); + VERIFY_IS_EQUAL(ab.nonZeros(), 3*2); + VERIFY_IS_APPROX(ab.coeff(3,0), -0.04); + VERIFY_IS_APPROX(ab.coeff(5,1), 0.05); + VERIFY_IS_APPROX(ab.coeff(0,6), -0.08); + VERIFY_IS_APPROX(ab.coeff(2,7), 0.10); + VERIFY_IS_APPROX(ab.coeff(6,8), 0.12); + VERIFY_IS_APPROX(ab.coeff(8,9), -0.15); +} + + +void test_kronecker_product() +{ + // DM = dense matrix; SM = sparse matrix + Matrix DM_a; + MatrixXd DM_b(3,2); + SparseMatrix SM_a(2,3); + SparseMatrix SM_b(3,2); + SM_a.insert(0,0) = DM_a(0,0) = -0.4461540300782201; + SM_a.insert(0,1) = DM_a(0,1) = -0.8057364375283049; + SM_a.insert(0,2) = DM_a(0,2) = 0.3896572459516341; + SM_a.insert(1,0) = DM_a(1,0) = -0.9076572187376921; + SM_a.insert(1,1) = DM_a(1,1) = 0.6469156566545853; + SM_a.insert(1,2) = DM_a(1,2) = -0.3658010398782789; + SM_b.insert(0,0) = DM_b(0,0) = 0.9004440976767099; + SM_b.insert(0,1) = DM_b(0,1) = -0.2368830858139832; + SM_b.insert(1,0) = DM_b(1,0) = -0.9311078389941825; + SM_b.insert(1,1) = DM_b(1,1) = 0.5310335762980047; + SM_b.insert(2,0) = DM_b(2,0) = -0.1225112806872035; + SM_b.insert(2,1) = DM_b(2,1) = 0.5903998022741264; + SparseMatrix SM_row_a(SM_a), SM_row_b(SM_b); + + // test kroneckerProduct(DM_block,DM,DM_fixedSize) + Matrix DM_fix_ab; + DM_fix_ab(0,0)=37.0; + kroneckerProduct(DM_a.block(0,0,2,3),DM_b,DM_fix_ab); + CALL_SUBTEST(check_kronecker_product(DM_fix_ab)); + + // test kroneckerProduct(DM,DM,DM_block) + MatrixXd DM_block_ab(10,15); + DM_block_ab(0,0)=37.0; + kroneckerProduct(DM_a,DM_b,DM_block_ab.block(2,5,6,6)); + CALL_SUBTEST(check_kronecker_product(DM_block_ab.block(2,5,6,6))); + + // test kroneckerProduct(DM,DM,DM) + MatrixXd DM_ab(1,5); + DM_ab(0,0)=37.0; + kroneckerProduct(DM_a,DM_b,DM_ab); + CALL_SUBTEST(check_kronecker_product(DM_ab)); + + // test kroneckerProduct(SM,DM,SM) + SparseMatrix SM_ab(1,20); + SM_ab.insert(0,0)=37.0; + kroneckerProduct(SM_a,DM_b,SM_ab); + CALL_SUBTEST(check_kronecker_product(SM_ab)); + SparseMatrix SM_ab2(10,3); + SM_ab2.insert(0,0)=37.0; + kroneckerProduct(SM_a,DM_b,SM_ab2); + CALL_SUBTEST(check_kronecker_product(SM_ab2)); + + // test kroneckerProduct(DM,SM,SM) + SM_ab.insert(0,0)=37.0; + kroneckerProduct(DM_a,SM_b,SM_ab); + CALL_SUBTEST(check_kronecker_product(SM_ab)); + SM_ab2.insert(0,0)=37.0; + kroneckerProduct(DM_a,SM_b,SM_ab2); + CALL_SUBTEST(check_kronecker_product(SM_ab2)); + + // test kroneckerProduct(SM,SM,SM) + SM_ab.resize(2,33); + SM_ab.insert(0,0)=37.0; + kroneckerProduct(SM_a,SM_b,SM_ab); + CALL_SUBTEST(check_kronecker_product(SM_ab)); + SM_ab2.resize(5,11); + SM_ab2.insert(0,0)=37.0; + kroneckerProduct(SM_a,SM_b,SM_ab2); + CALL_SUBTEST(check_kronecker_product(SM_ab2)); + + // test kroneckerProduct(SM,SM,SM) with sparse pattern + SM_a.resize(4,5); + SM_b.resize(3,2); + SM_a.resizeNonZeros(0); + SM_b.resizeNonZeros(0); + SM_a.insert(1,0) = -0.1; + SM_a.insert(0,3) = -0.2; + SM_a.insert(2,4) = 0.3; + SM_a.finalize(); + SM_b.insert(0,0) = 0.4; + SM_b.insert(2,1) = -0.5; + SM_b.finalize(); + SM_ab.resize(1,1); + SM_ab.insert(0,0)=37.0; + kroneckerProduct(SM_a,SM_b,SM_ab); + CALL_SUBTEST(check_sparse_kronecker_product(SM_ab)); + + // test dimension of result of kroneckerProduct(DM,DM,DM) + MatrixXd DM_a2(2,1); + MatrixXd DM_b2(5,4); + MatrixXd DM_ab2; + kroneckerProduct(DM_a2,DM_b2,DM_ab2); + CALL_SUBTEST(check_dimension(DM_ab2,2*5,1*4)); + DM_a2.resize(10,9); + DM_b2.resize(4,8); + kroneckerProduct(DM_a2,DM_b2,DM_ab2); + CALL_SUBTEST(check_dimension(DM_ab2,10*4,9*8)); +} diff --git a/gtsam/3rdparty/Eigen/unsupported/test/matrix_exponential.cpp b/gtsam/3rdparty/Eigen/unsupported/test/matrix_exponential.cpp index 996b42a7f..26403c4e6 100644 --- a/gtsam/3rdparty/Eigen/unsupported/test/matrix_exponential.cpp +++ b/gtsam/3rdparty/Eigen/unsupported/test/matrix_exponential.cpp @@ -55,7 +55,7 @@ void test2dRotation(double tol) for (int i=0; i<=20; i++) { angle = static_cast(pow(10, i / 5. - 2)); - B << cos(angle), sin(angle), -sin(angle), cos(angle); + B << std::cos(angle), std::sin(angle), -std::sin(angle), std::cos(angle); C = (angle*A).matrixFunction(expfn); std::cout << "test2dRotation: i = " << i << " error funm = " << relerr(C, B); @@ -146,8 +146,10 @@ void test_matrix_exponential() { CALL_SUBTEST_2(test2dRotation(1e-13)); CALL_SUBTEST_1(test2dRotation(2e-5)); // was 1e-5, relaxed for clang 2.8 / linux / x86-64 + CALL_SUBTEST_8(test2dRotation(1e-13)); CALL_SUBTEST_2(test2dHyperbolicRotation(1e-14)); CALL_SUBTEST_1(test2dHyperbolicRotation(1e-5)); + CALL_SUBTEST_8(test2dHyperbolicRotation(1e-14)); CALL_SUBTEST_6(testPascal(1e-6)); CALL_SUBTEST_5(testPascal(1e-15)); CALL_SUBTEST_2(randomTest(Matrix2d(), 1e-13)); @@ -158,4 +160,5 @@ void test_matrix_exponential() CALL_SUBTEST_5(randomTest(Matrix3cf(), 1e-4)); CALL_SUBTEST_1(randomTest(Matrix4f(), 1e-4)); CALL_SUBTEST_6(randomTest(MatrixXf(8,8), 1e-4)); + CALL_SUBTEST_9(randomTest(Matrix(7,7), 1e-13)); } diff --git a/gtsam/3rdparty/Eigen/unsupported/test/matrix_function.cpp b/gtsam/3rdparty/Eigen/unsupported/test/matrix_function.cpp index 04167abfb..c2ca5d5f1 100644 --- a/gtsam/3rdparty/Eigen/unsupported/test/matrix_function.cpp +++ b/gtsam/3rdparty/Eigen/unsupported/test/matrix_function.cpp @@ -120,6 +120,26 @@ void testMatrixExponential(const MatrixType& A) VERIFY_IS_APPROX(A.exp(), A.matrixFunction(StdStemFunctions::exp)); } +template +void testMatrixLogarithm(const MatrixType& A) +{ + typedef typename internal::traits::Scalar Scalar; + typedef typename NumTraits::Real RealScalar; + typedef std::complex ComplexScalar; + + MatrixType scaledA; + RealScalar maxImagPartOfSpectrum = A.eigenvalues().imag().cwiseAbs().maxCoeff(); + if (maxImagPartOfSpectrum >= 0.9 * M_PI) + scaledA = A * 0.9 * M_PI / maxImagPartOfSpectrum; + else + scaledA = A; + + // identity X.exp().log() = X only holds if Im(lambda) < pi for all eigenvalues of X + MatrixType expA = scaledA.exp(); + MatrixType logExpA = expA.log(); + VERIFY_IS_APPROX(logExpA, scaledA); +} + template void testHyperbolicFunctions(const MatrixType& A) { @@ -157,6 +177,7 @@ template void testMatrix(const MatrixType& A) { testMatrixExponential(A); + testMatrixLogarithm(A); testHyperbolicFunctions(A); testGonioFunctions(A); } diff --git a/gtsam/3rdparty/Eigen/unsupported/test/matrix_square_root.cpp b/gtsam/3rdparty/Eigen/unsupported/test/matrix_square_root.cpp new file mode 100644 index 000000000..8e701aac6 --- /dev/null +++ b/gtsam/3rdparty/Eigen/unsupported/test/matrix_square_root.cpp @@ -0,0 +1,77 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2011 Jitse Niesen +// +// Eigen is free software; you can redistribute it and/or +// modify it under the terms of the GNU Lesser General Public +// License as published by the Free Software Foundation; either +// version 3 of the License, or (at your option) any later version. +// +// Alternatively, you can redistribute it and/or +// modify it under the terms of the GNU General Public License as +// published by the Free Software Foundation; either version 2 of +// the License, or (at your option) any later version. +// +// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY +// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the +// GNU General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public +// License and a copy of the GNU General Public License along with +// Eigen. If not, see . + +#include "main.h" +#include + +template ::Scalar>::IsComplex> +struct generateTestMatrix; + +// for real matrices, make sure none of the eigenvalues are negative +template +struct generateTestMatrix +{ + static void run(MatrixType& result, typename MatrixType::Index size) + { + MatrixType mat = MatrixType::Random(size, size); + EigenSolver es(mat); + typename EigenSolver::EigenvalueType eivals = es.eigenvalues(); + for (typename MatrixType::Index i = 0; i < size; ++i) { + if (eivals(i).imag() == 0 && eivals(i).real() < 0) + eivals(i) = -eivals(i); + } + result = (es.eigenvectors() * eivals.asDiagonal() * es.eigenvectors().inverse()).real(); + } +}; + +// for complex matrices, any matrix is fine +template +struct generateTestMatrix +{ + static void run(MatrixType& result, typename MatrixType::Index size) + { + result = MatrixType::Random(size, size); + } +}; + +template +void testMatrixSqrt(const MatrixType& m) +{ + MatrixType A; + generateTestMatrix::run(A, m.rows()); + MatrixType sqrtA = A.sqrt(); + VERIFY_IS_APPROX(sqrtA * sqrtA, A); +} + +void test_matrix_square_root() +{ + for (int i = 0; i < g_repeat; i++) { + CALL_SUBTEST_1(testMatrixSqrt(Matrix3cf())); + CALL_SUBTEST_2(testMatrixSqrt(MatrixXcd(12,12))); + CALL_SUBTEST_3(testMatrixSqrt(Matrix4f())); + CALL_SUBTEST_4(testMatrixSqrt(Matrix(9, 9))); + CALL_SUBTEST_5(testMatrixSqrt(Matrix())); + CALL_SUBTEST_5(testMatrixSqrt(Matrix,1,1>())); + } +} diff --git a/gtsam/3rdparty/Eigen/unsupported/test/mpreal/dlmalloc.c b/gtsam/3rdparty/Eigen/unsupported/test/mpreal/dlmalloc.c index a2c03b533..7ce8feb07 100755 --- a/gtsam/3rdparty/Eigen/unsupported/test/mpreal/dlmalloc.c +++ b/gtsam/3rdparty/Eigen/unsupported/test/mpreal/dlmalloc.c @@ -1267,7 +1267,7 @@ int mspace_mallopt(int, int); #endif /* MSPACES */ #ifdef __cplusplus -}; /* end of extern "C" */ +} /* end of extern "C" */ #endif /* __cplusplus */ /* diff --git a/gtsam/3rdparty/Eigen/unsupported/test/mpreal/mpreal.cpp b/gtsam/3rdparty/Eigen/unsupported/test/mpreal/mpreal.cpp index 373f23b12..5c23544ef 100644 --- a/gtsam/3rdparty/Eigen/unsupported/test/mpreal/mpreal.cpp +++ b/gtsam/3rdparty/Eigen/unsupported/test/mpreal/mpreal.cpp @@ -3,14 +3,15 @@ Project homepage: http://www.holoborodko.com/pavel/ Contact e-mail: pavel@holoborodko.com - Copyright (c) 2008-2010 Pavel Holoborodko + Copyright (c) 2008-2011 Pavel Holoborodko Core Developers: Pavel Holoborodko, Dmitriy Gubanov, Konstantin Holoborodko. Contributors: Brian Gladman, Helmut Jarausch, Fokko Beekhof, Ulrich Mutze, - Heinz van Saanen, Pere Constans, Peter van Hoof. + Heinz van Saanen, Pere Constans, Peter van Hoof, Gael Guennebaud, + Tsai Chia Cheng, Alexei Zubanov. **************************************************************************** This library is free software; you can redistribute it and/or @@ -27,31 +28,21 @@ License along with this library; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA + **************************************************************************** **************************************************************************** Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: - + 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. - + 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. - - 3. Redistributions of any form whatsoever must retain the following - acknowledgment: - " - This product includes software developed by Pavel Holoborodko - Web: http://www.holoborodko.com/pavel/ - e-mail: pavel@holoborodko.com - " - 4. This software cannot be, by any means, used for any commercial - purpose without the prior permission of the copyright holder. - - Any of the above conditions can be waived if you get permission from - the copyright holder. + 3. The name of the author may be used to endorse or promote products + derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE AUTHOR AND CONTRIBUTORS ``AS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE @@ -66,9 +57,11 @@ SUCH DAMAGE. */ #include -#include #include "mpreal.h" + +#if defined (MPREAL_HAVE_CUSTOM_MPFR_MALLOC) #include "dlmalloc.h" +#endif using std::ws; using std::cerr; @@ -79,62 +72,107 @@ using std::istream; namespace mpfr{ -mp_rnd_t mpreal::default_rnd = mpfr_get_default_rounding_mode(); -mp_prec_t mpreal::default_prec = mpfr_get_default_prec(); +mp_rnd_t mpreal::default_rnd = MPFR_RNDN; //(mpfr_get_default_rounding_mode)(); +mp_prec_t mpreal::default_prec = 64; //(mpfr_get_default_prec)(); int mpreal::default_base = 10; int mpreal::double_bits = -1; + +#if defined (MPREAL_HAVE_CUSTOM_MPFR_MALLOC) bool mpreal::is_custom_malloc = false; +#endif // Default constructor: creates mp number and initializes it to 0. mpreal::mpreal() { + +#if defined (MPREAL_HAVE_CUSTOM_MPFR_MALLOC) set_custom_malloc(); +#endif + mpfr_init2(mp,default_prec); mpfr_set_ui(mp,0,default_rnd); + + MPREAL_MSVC_DEBUGVIEW_CODE; } mpreal::mpreal(const mpreal& u) { + +#if defined (MPREAL_HAVE_CUSTOM_MPFR_MALLOC) set_custom_malloc(); +#endif + mpfr_init2(mp,mpfr_get_prec(u.mp)); mpfr_set(mp,u.mp,default_rnd); + + MPREAL_MSVC_DEBUGVIEW_CODE; } mpreal::mpreal(const mpfr_t u) { + +#if defined (MPREAL_HAVE_CUSTOM_MPFR_MALLOC) set_custom_malloc(); +#endif + mpfr_init2(mp,mpfr_get_prec(u)); mpfr_set(mp,u,default_rnd); + + MPREAL_MSVC_DEBUGVIEW_CODE; } mpreal::mpreal(const mpf_t u) { + +#if defined (MPREAL_HAVE_CUSTOM_MPFR_MALLOC) set_custom_malloc(); - mpfr_init2(mp,mpf_get_prec(u)); +#endif + + mpfr_init2(mp,(mp_prec_t) mpf_get_prec(u)); // (gmp: mp_bitcnt_t) unsigned long -> long (mpfr: mp_prec_t) mpfr_set_f(mp,u,default_rnd); + + MPREAL_MSVC_DEBUGVIEW_CODE; } mpreal::mpreal(const mpz_t u, mp_prec_t prec, mp_rnd_t mode) { + +#if defined (MPREAL_HAVE_CUSTOM_MPFR_MALLOC) set_custom_malloc(); +#endif + mpfr_init2(mp,prec); mpfr_set_z(mp,u,mode); + + MPREAL_MSVC_DEBUGVIEW_CODE; } mpreal::mpreal(const mpq_t u, mp_prec_t prec, mp_rnd_t mode) { + +#if defined (MPREAL_HAVE_CUSTOM_MPFR_MALLOC) set_custom_malloc(); +#endif + mpfr_init2(mp,prec); mpfr_set_q(mp,u,mode); + + MPREAL_MSVC_DEBUGVIEW_CODE; } mpreal::mpreal(const double u, mp_prec_t prec, mp_rnd_t mode) { + +#if defined (MPREAL_HAVE_CUSTOM_MPFR_MALLOC) set_custom_malloc(); +#endif + if(double_bits == -1 || fits_in_bits(u, double_bits)) { mpfr_init2(mp,prec); mpfr_set_d(mp,u,mode); + + MPREAL_MSVC_DEBUGVIEW_CODE; } else throw conversion_overflow(); @@ -142,51 +180,121 @@ mpreal::mpreal(const double u, mp_prec_t prec, mp_rnd_t mode) mpreal::mpreal(const long double u, mp_prec_t prec, mp_rnd_t mode) { + +#if defined (MPREAL_HAVE_CUSTOM_MPFR_MALLOC) set_custom_malloc(); +#endif + mpfr_init2(mp,prec); mpfr_set_ld(mp,u,mode); + + MPREAL_MSVC_DEBUGVIEW_CODE; } mpreal::mpreal(const unsigned long int u, mp_prec_t prec, mp_rnd_t mode) { + +#if defined (MPREAL_HAVE_CUSTOM_MPFR_MALLOC) set_custom_malloc(); +#endif + mpfr_init2(mp,prec); mpfr_set_ui(mp,u,mode); + + MPREAL_MSVC_DEBUGVIEW_CODE; } mpreal::mpreal(const unsigned int u, mp_prec_t prec, mp_rnd_t mode) { + +#if defined (MPREAL_HAVE_CUSTOM_MPFR_MALLOC) set_custom_malloc(); +#endif + mpfr_init2(mp,prec); mpfr_set_ui(mp,u,mode); + + MPREAL_MSVC_DEBUGVIEW_CODE; } mpreal::mpreal(const long int u, mp_prec_t prec, mp_rnd_t mode) { + +#if defined (MPREAL_HAVE_CUSTOM_MPFR_MALLOC) set_custom_malloc(); +#endif + mpfr_init2(mp,prec); mpfr_set_si(mp,u,mode); + + MPREAL_MSVC_DEBUGVIEW_CODE; } mpreal::mpreal(const int u, mp_prec_t prec, mp_rnd_t mode) { + +#if defined (MPREAL_HAVE_CUSTOM_MPFR_MALLOC) set_custom_malloc(); +#endif + mpfr_init2(mp,prec); mpfr_set_si(mp,u,mode); + + MPREAL_MSVC_DEBUGVIEW_CODE; } +#if defined (MPREAL_HAVE_INT64_SUPPORT) +mpreal::mpreal(const uint64_t u, mp_prec_t prec, mp_rnd_t mode) +{ + +#if defined (MPREAL_HAVE_CUSTOM_MPFR_MALLOC) + set_custom_malloc(); +#endif + + mpfr_init2(mp,prec); + mpfr_set_uj(mp, u, mode); + + MPREAL_MSVC_DEBUGVIEW_CODE; +} + +mpreal::mpreal(const int64_t u, mp_prec_t prec, mp_rnd_t mode) +{ + +#if defined (MPREAL_HAVE_CUSTOM_MPFR_MALLOC) + set_custom_malloc(); +#endif + + mpfr_init2(mp,prec); + mpfr_set_sj(mp, u, mode); + + MPREAL_MSVC_DEBUGVIEW_CODE; +} +#endif + mpreal::mpreal(const char* s, mp_prec_t prec, int base, mp_rnd_t mode) { + +#if defined (MPREAL_HAVE_CUSTOM_MPFR_MALLOC) set_custom_malloc(); +#endif + mpfr_init2(mp,prec); mpfr_set_str(mp, s, base, mode); + + MPREAL_MSVC_DEBUGVIEW_CODE; } mpreal::mpreal(const std::string& s, mp_prec_t prec, int base, mp_rnd_t mode) { + +#if defined (MPREAL_HAVE_CUSTOM_MPFR_MALLOC) set_custom_malloc(); +#endif + mpfr_init2(mp,prec); mpfr_set_str(mp, s.c_str(), base, mode); + + MPREAL_MSVC_DEBUGVIEW_CODE; } mpreal::~mpreal() @@ -198,18 +306,22 @@ mpreal::~mpreal() mpreal& mpreal::operator=(const char* s) { mpfr_t t; - + +#if defined (MPREAL_HAVE_CUSTOM_MPFR_MALLOC) set_custom_malloc(); +#endif if(0==mpfr_init_set_str(t,s,default_base,default_rnd)) { - // We will rewrite mp anyway, so use flash it and resize - mpfr_set_prec(mp,mpfr_get_prec(t)); //<- added 01.04.2011 + // We will rewrite mp anyway, so flash it and resize + mpfr_set_prec(mp,mpfr_get_prec(t)); mpfr_set(mp,t,mpreal::default_rnd); mpfr_clear(t); + + MPREAL_MSVC_DEBUGVIEW_CODE; + }else{ mpfr_clear(t); - // cerr<<"fail to convert string"<xp?yp:xp); - - mpfr_hypot(a.mp, x.mp, y.mp, rnd_mode); - - return a; -} - const mpreal sum (const mpreal tab[], unsigned long int n, mp_rnd_t rnd_mode) { mpreal x; @@ -288,21 +385,6 @@ const mpreal sum (const mpreal tab[], unsigned long int n, mp_rnd_t rnd_mode) return x; } -const mpreal remainder (const mpreal& x, const mpreal& y, mp_rnd_t rnd_mode) -{ - mpreal a; - mp_prec_t yp, xp; - - yp = y.get_prec(); - xp = x.get_prec(); - - a.set_prec(yp>xp?yp:xp); - - mpfr_remainder(a.mp, x.mp, y.mp, rnd_mode); - - return a; -} - const mpreal remquo (long* q, const mpreal& x, const mpreal& y, mp_rnd_t rnd_mode) { mpreal a; @@ -319,36 +401,71 @@ const mpreal remquo (long* q, const mpreal& x, const mpreal& y, mp_rnd_t rnd_mod } template -std::string to_string(T t, std::ios_base & (*f)(std::ios_base&)) +std::string toString(T t, std::ios_base & (*f)(std::ios_base&)) { std::ostringstream oss; oss << f << t; return oss.str(); } -mpreal::operator std::string() const +#if (MPFR_VERSION >= MPFR_VERSION_NUM(2,4,0)) + +std::string mpreal::toString(const std::string& format) const { - return to_string(); + char *s = NULL; + string out; + + if( !format.empty() ) + { + if(!(mpfr_asprintf(&s,format.c_str(),mp) < 0)) + { + out = std::string(s); + + mpfr_free_str(s); + } + } + + return out; } -std::string mpreal::to_string(size_t n, int b, mp_rnd_t mode) const +#endif + +std::string mpreal::toString(int n, int b, mp_rnd_t mode) const { - char *s, *ns = NULL; + (void)b; + (void)mode; +#if (MPFR_VERSION >= MPFR_VERSION_NUM(2,4,0)) + + // Use MPFR native function for output + char format[128]; + int digits; + + digits = n > 0 ? n : bits2digits(mpfr_get_prec(mp)); + + sprintf(format,"%%.%dRNg",digits); // Default format + + return toString(std::string(format)); + +#else + + char *s, *ns = NULL; size_t slen, nslen; mp_exp_t exp; string out; - + +#if defined (MPREAL_HAVE_CUSTOM_MPFR_MALLOC) set_custom_malloc(); - +#endif + if(mpfr_inf_p(mp)) { - if(mpfr_sgn(mp)>0) return "+@Inf@"; - else return "-@Inf@"; + if(mpfr_sgn(mp)>0) return "+Inf"; + else return "-Inf"; } if(mpfr_zero_p(mp)) return "0"; - if(mpfr_nan_p(mp)) return "@NaN@"; - + if(mpfr_nan_p(mp)) return "NaN"; + s = mpfr_get_str(NULL,&exp,b,0,mp,mode); ns = mpfr_get_str(NULL,&exp,b,n,mp,mode); @@ -419,8 +536,8 @@ std::string mpreal::to_string(size_t n, int b, mp_rnd_t mode) const // Make final string if(--exp) { - if(exp>0) out += "e+"+mpfr::to_string(exp,std::dec); - else out += "e"+mpfr::to_string(exp,std::dec); + if(exp>0) out += "e+"+mpfr::toString(exp,std::dec); + else out += "e"+mpfr::toString(exp,std::dec); } } @@ -429,79 +546,52 @@ std::string mpreal::to_string(size_t n, int b, mp_rnd_t mode) const }else{ return "conversion error!"; } +#endif } + ////////////////////////////////////////////////////////////////////////// // I/O ostream& operator<<(ostream& os, const mpreal& v) { - return os<(os.precision())); + return os<(os.precision())); } istream& operator>>(istream &is, mpreal& v) { - char c; - string s = ""; - mpfr_t t; - - mpreal::set_custom_malloc(); - - if(is.good()) - { - is>>ws; - while ((c = is.get())!=EOF) - { - if(c ==' ' || c == '\t' || c == '\n' || c == '\r') - { - is.putback(c); - break; - } - s += c; - } - - if(s.size() != 0) - { - // Protect current value from alternation in case of input error - // so some error handling(roll back) procedure can be used - - if(0==mpfr_init_set_str(t,s.c_str(),mpreal::default_base,mpreal::default_rnd)) - { - mpfr_set(v.mp,t,mpreal::default_rnd); - mpfr_clear(t); - - }else{ - mpfr_clear(t); - cerr<<"error reading from istream"<> tmp; + mpfr_set_str(v.mp, tmp.c_str(),mpreal::default_base,mpreal::default_rnd); return is; } -// Optimized dynamic memory allocation/(re-)deallocation. -void * mpreal::mpreal_allocate(size_t alloc_size) -{ - return(dlmalloc(alloc_size)); -} -void * mpreal::mpreal_reallocate(void *ptr, size_t /*old_size*/, size_t new_size) -{ - return(dlrealloc(ptr,new_size)); -} - -void mpreal::mpreal_free(void *ptr, size_t /*size*/) -{ - dlfree(ptr); -} - -inline void mpreal::set_custom_malloc(void) -{ - if(!is_custom_malloc) +#if defined (MPREAL_HAVE_CUSTOM_MPFR_MALLOC) + // Optimized dynamic memory allocation/(re-)deallocation. + void * mpreal::mpreal_allocate(size_t alloc_size) { - mp_set_memory_functions(mpreal_allocate,mpreal_reallocate,mpreal_free); - is_custom_malloc = true; + return(dlmalloc(alloc_size)); } -} + + void * mpreal::mpreal_reallocate(void *ptr, size_t old_size, size_t new_size) + { + return(dlrealloc(ptr,new_size)); + } + + void mpreal::mpreal_free(void *ptr, size_t size) + { + dlfree(ptr); + } + + inline void mpreal::set_custom_malloc(void) + { + if(!is_custom_malloc) + { + mp_set_memory_functions(mpreal_allocate,mpreal_reallocate,mpreal_free); + is_custom_malloc = true; + } + } +#endif + } diff --git a/gtsam/3rdparty/Eigen/unsupported/test/mpreal/mpreal.h b/gtsam/3rdparty/Eigen/unsupported/test/mpreal/mpreal.h index 96f474640..c640af947 100644 --- a/gtsam/3rdparty/Eigen/unsupported/test/mpreal/mpreal.h +++ b/gtsam/3rdparty/Eigen/unsupported/test/mpreal/mpreal.h @@ -1,16 +1,17 @@ /* - Multi-precision real number class. C++ interface fo MPFR library. + Multi-precision real number class. C++ interface for MPFR library. Project homepage: http://www.holoborodko.com/pavel/ Contact e-mail: pavel@holoborodko.com - Copyright (c) 2008-2010 Pavel Holoborodko + Copyright (c) 2008-2012 Pavel Holoborodko Core Developers: Pavel Holoborodko, Dmitriy Gubanov, Konstantin Holoborodko. Contributors: Brian Gladman, Helmut Jarausch, Fokko Beekhof, Ulrich Mutze, - Heinz van Saanen, Pere Constans, Peter van Hoof. + Heinz van Saanen, Pere Constans, Peter van Hoof, Gael Guennebaud, + Tsai Chia Cheng, Alexei Zubanov. **************************************************************************** This library is free software; you can redistribute it and/or @@ -39,19 +40,8 @@ notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. - 3. Redistributions of any form whatsoever must retain the following - acknowledgment: - " - This product includes software developed by Pavel Holoborodko - Web: http://www.holoborodko.com/pavel/ - e-mail: pavel@holoborodko.com - " - - 4. This software cannot be, by any means, used for any commercial - purpose without the prior permission of the copyright holder. - - Any of the above conditions can be waived if you get permission from - the copyright holder. + 3. The name of the author may be used to endorse or promote products + derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE AUTHOR AND CONTRIBUTORS ``AS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE @@ -66,8 +56,8 @@ SUCH DAMAGE. */ -#ifndef __MP_REAL_H__ -#define __MP_REAL_H__ +#ifndef __MPREAL_H__ +#define __MPREAL_H__ #include #include @@ -76,22 +66,65 @@ #include #include -#include +// Options +#define MPREAL_HAVE_INT64_SUPPORT // int64_t support: available only for MSVC 2010 & GCC +#define MPREAL_HAVE_MSVC_DEBUGVIEW // Enable Debugger Visualizer (valid only for MSVC in "Debug" builds) // Detect compiler using signatures from http://predef.sourceforge.net/ #if defined(__GNUC__) && defined(__INTEL_COMPILER) #define IsInf(x) isinf(x) // Intel ICC compiler on Linux +#elif defined(_MSC_VER) // Microsoft Visual C++ + #define IsInf(x) (!_finite(x)) + #elif defined(__GNUC__) #define IsInf(x) std::isinf(x) // GNU C/C++ -#elif defined(_MSC_VER) - #define IsInf(x) (!_finite(x)) // Microsoft Visual C++ - #else #define IsInf(x) std::isinf(x) // Unknown compiler, just hope for C99 conformance #endif +#if defined(MPREAL_HAVE_INT64_SUPPORT) + + #define MPFR_USE_INTMAX_T // should be defined before mpfr.h + + #if defined(_MSC_VER) // is available only in msvc2010! + #if (_MSC_VER >= 1600) + #include + #else // MPFR relies on intmax_t which is available only in msvc2010 + #undef MPREAL_HAVE_INT64_SUPPORT // Besides, MPFR - MPIR have to be compiled with msvc2010 + #undef MPFR_USE_INTMAX_T // Since we cannot detect this, disable x64 by default + // Someone should change this manually if needed. + #endif + #endif + + #if defined (__MINGW32__) || defined(__MINGW64__) + #include // equivalent to msvc2010 + #elif defined (__GNUC__) + #if defined(__amd64__) || defined(__amd64) || defined(__x86_64__) || defined(__x86_64) + #undef MPREAL_HAVE_INT64_SUPPORT // remove all shaman dances for x64 builds since + #undef MPFR_USE_INTMAX_T // GCC already support x64 as of "long int" is 64-bit integer, nothing left to do + #else + #include // use int64_t, uint64_t otherwise. + #endif + #endif + +#endif + +#if defined(MPREAL_HAVE_MSVC_DEBUGVIEW) && defined(_MSC_VER) && defined(_DEBUG) +#define MPREAL_MSVC_DEBUGVIEW_CODE DebugView = toString() + #define MPREAL_MSVC_DEBUGVIEW_DATA std::string DebugView +#else + #define MPREAL_MSVC_DEBUGVIEW_CODE + #define MPREAL_MSVC_DEBUGVIEW_DATA +#endif + +#include + +#if (MPFR_VERSION < MPFR_VERSION_NUM(3,0,0)) + #include // needed for random() +#endif + namespace mpfr { class mpreal { @@ -99,19 +132,17 @@ private: mpfr_t mp; public: - static mp_rnd_t default_rnd; - static mp_prec_t default_prec; - static int default_base; - static int double_bits; - + static mp_rnd_t default_rnd; + static mp_prec_t default_prec; + static int default_base; + static int double_bits; + public: // Constructors && type conversion mpreal(); mpreal(const mpreal& u); - mpreal(const mpfr_t u); mpreal(const mpf_t u); - mpreal(const mpz_t u, mp_prec_t prec = default_prec, mp_rnd_t mode = default_rnd); mpreal(const mpq_t u, mp_prec_t prec = default_prec, mp_rnd_t mode = default_rnd); mpreal(const double u, mp_prec_t prec = default_prec, mp_rnd_t mode = default_rnd); @@ -120,6 +151,12 @@ public: mpreal(const unsigned int u, mp_prec_t prec = default_prec, mp_rnd_t mode = default_rnd); mpreal(const long int u, mp_prec_t prec = default_prec, mp_rnd_t mode = default_rnd); mpreal(const int u, mp_prec_t prec = default_prec, mp_rnd_t mode = default_rnd); + +#if defined (MPREAL_HAVE_INT64_SUPPORT) + mpreal(const uint64_t u, mp_prec_t prec = default_prec, mp_rnd_t mode = default_rnd); + mpreal(const int64_t u, mp_prec_t prec = default_prec, mp_rnd_t mode = default_rnd); +#endif + mpreal(const char* s, mp_prec_t prec = default_prec, int base = default_base, mp_rnd_t mode = default_rnd); mpreal(const std::string& s, mp_prec_t prec = default_prec, int base = default_base, mp_rnd_t mode = default_rnd); @@ -155,6 +192,18 @@ public: mpreal& operator+=(const unsigned int u); mpreal& operator+=(const long int u); mpreal& operator+=(const int u); + +#if defined (MPREAL_HAVE_INT64_SUPPORT) + mpreal& operator+=(const int64_t u); + mpreal& operator+=(const uint64_t u); + mpreal& operator-=(const int64_t u); + mpreal& operator-=(const uint64_t u); + mpreal& operator*=(const int64_t u); + mpreal& operator*=(const uint64_t u); + mpreal& operator/=(const int64_t u); + mpreal& operator/=(const uint64_t u); +#endif + const mpreal operator+() const; mpreal& operator++ (); const mpreal operator++ (int); @@ -225,29 +274,49 @@ public: friend bool operator == (const mpreal& a, const mpreal& b); friend bool operator != (const mpreal& a, const mpreal& b); + // Optimized specializations for boolean operators + friend bool operator == (const mpreal& a, const unsigned long int b); + friend bool operator == (const mpreal& a, const unsigned int b); + friend bool operator == (const mpreal& a, const long int b); + friend bool operator == (const mpreal& a, const int b); + friend bool operator == (const mpreal& a, const long double b); + friend bool operator == (const mpreal& a, const double b); + // Type Conversion operators - inline operator long double() const; - inline operator double() const; - inline operator float() const; - inline operator unsigned long() const; - inline operator unsigned int() const; - inline operator long() const; - inline operator int() const; - operator std::string() const; - inline operator mpfr_ptr(); + long toLong() const; + unsigned long toULong() const; + double toDouble() const; + long double toLDouble() const; + +#if defined (MPREAL_HAVE_INT64_SUPPORT) + int64_t toInt64() const; + uint64_t toUInt64() const; +#endif + + // Get raw pointers + ::mpfr_ptr mpfr_ptr(); + ::mpfr_srcptr mpfr_srcptr() const; + + // Convert mpreal to string with n significant digits in base b + // n = 0 -> convert with the maximum available digits + std::string toString(int n = 0, int b = default_base, mp_rnd_t mode = default_rnd) const; + +#if (MPFR_VERSION >= MPFR_VERSION_NUM(2,4,0)) + std::string toString(const std::string& format) const; +#endif // Math Functions - friend const mpreal sqr(const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); + friend const mpreal sqr (const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); friend const mpreal sqrt(const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); friend const mpreal sqrt(const unsigned long int v, mp_rnd_t rnd_mode = mpreal::default_rnd); friend const mpreal cbrt(const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); friend const mpreal root(const mpreal& v, unsigned long int k, mp_rnd_t rnd_mode = mpreal::default_rnd); - friend const mpreal pow(const mpreal& a, const mpreal& b, mp_rnd_t rnd_mode = mpreal::default_rnd); - friend const mpreal pow(const mpreal& a, const mpz_t b, mp_rnd_t rnd_mode = mpreal::default_rnd); - friend const mpreal pow(const mpreal& a, const unsigned long int b, mp_rnd_t rnd_mode = mpreal::default_rnd); - friend const mpreal pow(const mpreal& a, const long int b, mp_rnd_t rnd_mode = mpreal::default_rnd); - friend const mpreal pow(const unsigned long int a, const mpreal& b, mp_rnd_t rnd_mode = mpreal::default_rnd); - friend const mpreal pow(const unsigned long int a, const unsigned long int b, mp_rnd_t rnd_mode = mpreal::default_rnd); + friend const mpreal pow (const mpreal& a, const mpreal& b, mp_rnd_t rnd_mode = mpreal::default_rnd); + friend const mpreal pow (const mpreal& a, const mpz_t b, mp_rnd_t rnd_mode = mpreal::default_rnd); + friend const mpreal pow (const mpreal& a, const unsigned long int b, mp_rnd_t rnd_mode = mpreal::default_rnd); + friend const mpreal pow (const mpreal& a, const long int b, mp_rnd_t rnd_mode = mpreal::default_rnd); + friend const mpreal pow (const unsigned long int a, const mpreal& b, mp_rnd_t rnd_mode = mpreal::default_rnd); + friend const mpreal pow (const unsigned long int a, const unsigned long int b, mp_rnd_t rnd_mode = mpreal::default_rnd); friend const mpreal fabs(const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); friend const mpreal abs(const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); @@ -264,8 +333,8 @@ public: friend const mpreal exp (const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); friend const mpreal exp2 (const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); friend const mpreal exp10(const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); - friend const mpreal log1p (const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); - friend const mpreal expm1 (const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); + friend const mpreal log1p(const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); + friend const mpreal expm1(const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); friend const mpreal cos(const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); friend const mpreal sin(const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); @@ -279,15 +348,23 @@ public: friend const mpreal asin (const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); friend const mpreal atan (const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); friend const mpreal atan2 (const mpreal& y, const mpreal& x, mp_rnd_t rnd_mode = mpreal::default_rnd); + friend const mpreal acot (const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); + friend const mpreal asec (const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); + friend const mpreal acsc (const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); + friend const mpreal cosh (const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); friend const mpreal sinh (const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); friend const mpreal tanh (const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); friend const mpreal sech (const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); friend const mpreal csch (const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); friend const mpreal coth (const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); - friend const mpreal acosh (const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); - friend const mpreal asinh (const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); - friend const mpreal atanh (const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); + friend const mpreal acosh (const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); + friend const mpreal asinh (const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); + friend const mpreal atanh (const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); + friend const mpreal acoth (const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); + friend const mpreal asech (const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); + friend const mpreal acsch (const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); + friend const mpreal hypot (const mpreal& x, const mpreal& y, mp_rnd_t rnd_mode = mpreal::default_rnd); friend const mpreal fac_ui (unsigned long int v, mp_prec_t prec = mpreal::default_prec, mp_rnd_t rnd_mode = mpreal::default_rnd); @@ -299,12 +376,12 @@ public: friend const mpreal zeta (const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); friend const mpreal erf (const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); friend const mpreal erfc (const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); - friend const mpreal _j0 (const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); - friend const mpreal _j1 (const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); - friend const mpreal _jn (long n, const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); - friend const mpreal _y0 (const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); - friend const mpreal _y1 (const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); - friend const mpreal _yn (long n, const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); + friend const mpreal besselj0 (const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); + friend const mpreal besselj1 (const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); + friend const mpreal besseljn (long n, const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); + friend const mpreal bessely0 (const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); + friend const mpreal bessely1 (const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); + friend const mpreal besselyn (long n, const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); friend const mpreal fma (const mpreal& v1, const mpreal& v2, const mpreal& v3, mp_rnd_t rnd_mode = mpreal::default_rnd); friend const mpreal fms (const mpreal& v1, const mpreal& v2, const mpreal& v3, mp_rnd_t rnd_mode = mpreal::default_rnd); friend const mpreal agm (const mpreal& v1, const mpreal& v2, mp_rnd_t rnd_mode = mpreal::default_rnd); @@ -324,9 +401,15 @@ public: friend const mpreal digamma(const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); friend const mpreal ai(const mpreal& v, mp_rnd_t rnd_mode = mpreal::default_rnd); friend const mpreal urandom (gmp_randstate_t& state,mp_rnd_t rnd_mode = mpreal::default_rnd); // use gmp_randinit_default() to init state, gmp_randclear() to clear - friend bool _isregular(const mpreal& v); + friend bool isregular(const mpreal& v); #endif - + + // Uniformly distributed random number generation in [0,1] using + // Mersenne-Twister algorithm by default. + // Use parameter to setup seed, e.g.: random((unsigned)time(NULL)) + // Check urandom() for more precise control. + friend const mpreal random(unsigned int seed = 0); + // Exponent and mantissa manipulation friend const mpreal frexp(const mpreal& v, mp_exp_t* exp); friend const mpreal ldexp(const mpreal& v, mp_exp_t exp); @@ -376,22 +459,27 @@ public: #endif // Instance Checkers - friend bool _isnan(const mpreal& v); - friend bool _isinf(const mpreal& v); - friend bool _isnum(const mpreal& v); - friend bool _iszero(const mpreal& v); - friend bool _isint(const mpreal& v); + friend bool isnan (const mpreal& v); + friend bool isinf (const mpreal& v); + friend bool isfinite(const mpreal& v); + + friend bool isnum(const mpreal& v); + friend bool iszero(const mpreal& v); + friend bool isint(const mpreal& v); // Set/Get instance properties inline mp_prec_t get_prec() const; - inline void set_prec(mp_prec_t prec, mp_rnd_t rnd_mode = default_rnd); // Change precision with rounding mode - - // Set mpreal to +-inf, NaN - void set_inf(int sign = +1); - void set_nan(); + inline void set_prec(mp_prec_t prec, mp_rnd_t rnd_mode = default_rnd); // Change precision with rounding mode - // sign = -1 or +1 - void set_sign(int sign, mp_rnd_t rnd_mode = default_rnd); + // Aliases for get_prec(), set_prec() - needed for compatibility with std::complex interface + inline mpreal& setPrecision(int Precision, mp_rnd_t RoundingMode = (mpfr_get_default_rounding_mode)()); + inline int getPrecision() const; + + // Set mpreal to +/- inf, NaN, +/-0 + mpreal& setInf (int Sign = +1); + mpreal& setNan (); + mpreal& setZero (int Sign = +1); + mpreal& setSign (int Sign, mp_rnd_t RoundingMode = (mpfr_get_default_rounding_mode)()); //Exponent mp_exp_t get_exp(); @@ -411,36 +499,25 @@ public: static int get_double_bits(); static void set_default_rnd(mp_rnd_t rnd_mode); static mp_rnd_t get_default_rnd(); - static mp_exp_t get_emin (void); - static mp_exp_t get_emax (void); - static mp_exp_t get_emin_min (void); - static mp_exp_t get_emin_max (void); - static mp_exp_t get_emax_min (void); - static mp_exp_t get_emax_max (void); - static int set_emin (mp_exp_t exp); - static int set_emax (mp_exp_t exp); + static mp_exp_t get_emin (void); + static mp_exp_t get_emax (void); + static mp_exp_t get_emin_min (void); + static mp_exp_t get_emin_max (void); + static mp_exp_t get_emax_min (void); + static mp_exp_t get_emax_max (void); + static int set_emin (mp_exp_t exp); + static int set_emax (mp_exp_t exp); - // Get/Set conversions - // Convert mpreal to string with n significant digits in base b - // n = 0 -> convert with the maximum available digits - std::string to_string(size_t n = 0, int b = default_base, mp_rnd_t mode = default_rnd) const; - // Efficient swapping of two mpreal values friend void swap(mpreal& x, mpreal& y); //Min Max - macros is evil. Needed for systems which defines max and min globally as macros (e.g. Windows) //Hope that globally defined macros use > < operations only - #ifndef max - friend const mpreal max(const mpreal& x, const mpreal& y); - #endif - - #ifndef min - friend const mpreal min(const mpreal& x, const mpreal& y); - #endif - friend const mpreal fmax(const mpreal& x, const mpreal& y, mp_rnd_t rnd_mode = default_rnd); friend const mpreal fmin(const mpreal& x, const mpreal& y, mp_rnd_t rnd_mode = default_rnd); +#if defined (MPREAL_HAVE_CUSTOM_MPFR_MALLOC) + private: // Optimized dynamic memory allocation/(re-)deallocation. static bool is_custom_malloc; @@ -448,6 +525,20 @@ private: static void *mpreal_reallocate (void *ptr, size_t old_size, size_t new_size); static void mpreal_free (void *ptr, size_t size); inline static void set_custom_malloc (void); + +#endif + + +private: + // Human friendly Debug Preview in Visual Studio. + // Put one of these lines: + // + // mpfr::mpreal= ; Show value only + // mpfr::mpreal=, bits ; Show value & precision + // + // at the beginning of + // [Visual Studio Installation Folder]\Common7\Packages\Debugger\autoexp.dat + MPREAL_MSVC_DEBUGVIEW_DATA }; ////////////////////////////////////////////////////////////////////////// @@ -457,190 +548,63 @@ public: std::string why() { return "inexact conversion from floating point"; } }; -////////////////////////////////////////////////////////////////////////// +namespace internal{ + + // Use SFINAE to restrict arithmetic operations instantiation only for numeric types + // This is needed for smooth integration with libraries based on expression templates + template struct result_type {}; + + template <> struct result_type {typedef mpreal type;}; + template <> struct result_type {typedef mpreal type;}; + template <> struct result_type {typedef mpreal type;}; + template <> struct result_type {typedef mpreal type;}; + template <> struct result_type {typedef mpreal type;}; + template <> struct result_type {typedef mpreal type;}; + template <> struct result_type {typedef mpreal type;}; + template <> struct result_type {typedef mpreal type;}; + template <> struct result_type {typedef mpreal type;}; + +#if defined (MPREAL_HAVE_INT64_SUPPORT) + template <> struct result_type {typedef mpreal type;}; + template <> struct result_type {typedef mpreal type;}; +#endif +} + // + Addition -const mpreal operator+(const mpreal& a, const mpreal& b); +template +inline const typename internal::result_type::type + operator+(const mpreal& lhs, const Rhs& rhs){ return mpreal(lhs) += rhs; } -// + Fast specialized addition - implemented through fast += operations -const mpreal operator+(const mpreal& a, const mpz_t b); -const mpreal operator+(const mpreal& a, const mpq_t b); -const mpreal operator+(const mpreal& a, const long double b); -const mpreal operator+(const mpreal& a, const double b); -const mpreal operator+(const mpreal& a, const unsigned long int b); -const mpreal operator+(const mpreal& a, const unsigned int b); -const mpreal operator+(const mpreal& a, const long int b); -const mpreal operator+(const mpreal& a, const int b); -const mpreal operator+(const mpreal& a, const char* b); -const mpreal operator+(const char* a, const mpreal& b); -const std::string operator+(const mpreal& a, const std::string b); -const std::string operator+(const std::string a, const mpreal& b); +template +inline const typename internal::result_type::type + operator+(const Lhs& lhs, const mpreal& rhs){ return mpreal(rhs) += lhs; } -const mpreal operator+(const mpz_t b, const mpreal& a); -const mpreal operator+(const mpq_t b, const mpreal& a); -const mpreal operator+(const long double b, const mpreal& a); -const mpreal operator+(const double b, const mpreal& a); -const mpreal operator+(const unsigned long int b, const mpreal& a); -const mpreal operator+(const unsigned int b, const mpreal& a); -const mpreal operator+(const long int b, const mpreal& a); -const mpreal operator+(const int b, const mpreal& a); - -////////////////////////////////////////////////////////////////////////// // - Subtraction -const mpreal operator-(const mpreal& a, const mpreal& b); +template +inline const typename internal::result_type::type + operator-(const mpreal& lhs, const Rhs& rhs){ return mpreal(lhs) -= rhs; } -// - Fast specialized subtraction - implemented through fast -= operations -const mpreal operator-(const mpreal& a, const mpz_t b); -const mpreal operator-(const mpreal& a, const mpq_t b); -const mpreal operator-(const mpreal& a, const long double b); -const mpreal operator-(const mpreal& a, const double b); -const mpreal operator-(const mpreal& a, const unsigned long int b); -const mpreal operator-(const mpreal& a, const unsigned int b); -const mpreal operator-(const mpreal& a, const long int b); -const mpreal operator-(const mpreal& a, const int b); -const mpreal operator-(const mpreal& a, const char* b); -const mpreal operator-(const char* a, const mpreal& b); +template +inline const typename internal::result_type::type + operator-(const Lhs& lhs, const mpreal& rhs){ return mpreal(lhs) -= rhs; } -const mpreal operator-(const mpz_t b, const mpreal& a); -const mpreal operator-(const mpq_t b, const mpreal& a); -const mpreal operator-(const long double b, const mpreal& a); -//const mpreal operator-(const double b, const mpreal& a); - -////////////////////////////////////////////////////////////////////////// // * Multiplication -const mpreal operator*(const mpreal& a, const mpreal& b); +template +inline const typename internal::result_type::type + operator*(const mpreal& lhs, const Rhs& rhs){ return mpreal(lhs) *= rhs; } -// * Fast specialized multiplication - implemented through fast *= operations -const mpreal operator*(const mpreal& a, const mpz_t b); -const mpreal operator*(const mpreal& a, const mpq_t b); -const mpreal operator*(const mpreal& a, const long double b); -const mpreal operator*(const mpreal& a, const double b); -const mpreal operator*(const mpreal& a, const unsigned long int b); -const mpreal operator*(const mpreal& a, const unsigned int b); -const mpreal operator*(const mpreal& a, const long int b); -const mpreal operator*(const mpreal& a, const int b); +template +inline const typename internal::result_type::type + operator*(const Lhs& lhs, const mpreal& rhs){ return mpreal(rhs) *= lhs; } -const mpreal operator*(const mpz_t b, const mpreal& a); -const mpreal operator*(const mpq_t b, const mpreal& a); -const mpreal operator*(const long double b, const mpreal& a); -const mpreal operator*(const double b, const mpreal& a); -const mpreal operator*(const unsigned long int b, const mpreal& a); -const mpreal operator*(const unsigned int b, const mpreal& a); -const mpreal operator*(const long int b, const mpreal& a); -const mpreal operator*(const int b, const mpreal& a); - -////////////////////////////////////////////////////////////////////////// // / Division -const mpreal operator/(const mpreal& a, const mpreal& b); +template +inline const typename internal::result_type::type + operator/(const mpreal& lhs, const Rhs& rhs){ return mpreal(lhs) /= rhs; } -// / Fast specialized division - implemented through fast /= operations -const mpreal operator/(const mpreal& a, const mpz_t b); -const mpreal operator/(const mpreal& a, const mpq_t b); -const mpreal operator/(const mpreal& a, const long double b); -const mpreal operator/(const mpreal& a, const double b); -const mpreal operator/(const mpreal& a, const unsigned long int b); -const mpreal operator/(const mpreal& a, const unsigned int b); -const mpreal operator/(const mpreal& a, const long int b); -const mpreal operator/(const mpreal& a, const int b); - -const mpreal operator/(const long double b, const mpreal& a); - -////////////////////////////////////////////////////////////////////////// -// Shifts operators - Multiplication/Division by a power of 2 -const mpreal operator<<(const mpreal& v, const unsigned long int k); -const mpreal operator<<(const mpreal& v, const unsigned int k); -const mpreal operator<<(const mpreal& v, const long int k); -const mpreal operator<<(const mpreal& v, const int k); - -const mpreal operator>>(const mpreal& v, const unsigned long int k); -const mpreal operator>>(const mpreal& v, const unsigned int k); -const mpreal operator>>(const mpreal& v, const long int k); -const mpreal operator>>(const mpreal& v, const int k); - -////////////////////////////////////////////////////////////////////////// -// Boolean operators -bool operator < (const mpreal& a, const unsigned long int b); -bool operator < (const mpreal& a, const unsigned int b); -bool operator < (const mpreal& a, const long int b); -bool operator < (const mpreal& a, const int b); -bool operator < (const mpreal& a, const long double b); -bool operator < (const mpreal& a, const double b); - -bool operator < (const unsigned long int a,const mpreal& b); -bool operator < (const unsigned int a, const mpreal& b); -bool operator < (const long int a, const mpreal& b); -bool operator < (const int a, const mpreal& b); -bool operator < (const long double a, const mpreal& b); -bool operator < (const double a, const mpreal& b); - -bool operator > (const mpreal& a, const unsigned long int b); -bool operator > (const mpreal& a, const unsigned int b); -bool operator > (const mpreal& a, const long int b); -bool operator > (const mpreal& a, const int b); -bool operator > (const mpreal& a, const long double b); -bool operator > (const mpreal& a, const double b); - -bool operator > (const unsigned long int a,const mpreal& b); -bool operator > (const unsigned int a, const mpreal& b); -bool operator > (const long int a, const mpreal& b); -bool operator > (const int a, const mpreal& b); -bool operator > (const long double a, const mpreal& b); -bool operator > (const double a, const mpreal& b); - -bool operator >= (const mpreal& a, const unsigned long int b); -bool operator >= (const mpreal& a, const unsigned int b); -bool operator >= (const mpreal& a, const long int b); -bool operator >= (const mpreal& a, const int b); -bool operator >= (const mpreal& a, const long double b); -bool operator >= (const mpreal& a, const double b); - -bool operator >= (const unsigned long int a,const mpreal& b); -bool operator >= (const unsigned int a, const mpreal& b); -bool operator >= (const long int a, const mpreal& b); -bool operator >= (const int a, const mpreal& b); -bool operator >= (const long double a, const mpreal& b); -bool operator >= (const double a, const mpreal& b); - -bool operator <= (const mpreal& a, const unsigned long int b); -bool operator <= (const mpreal& a, const unsigned int b); -bool operator <= (const mpreal& a, const long int b); -bool operator <= (const mpreal& a, const int b); -bool operator <= (const mpreal& a, const long double b); -bool operator <= (const mpreal& a, const double b); - -bool operator <= (const unsigned long int a,const mpreal& b); -bool operator <= (const unsigned int a, const mpreal& b); -bool operator <= (const long int a, const mpreal& b); -bool operator <= (const int a, const mpreal& b); -bool operator <= (const long double a, const mpreal& b); -bool operator <= (const double a, const mpreal& b); - -bool operator == (const mpreal& a, const unsigned long int b); -bool operator == (const mpreal& a, const unsigned int b); -bool operator == (const mpreal& a, const long int b); -bool operator == (const mpreal& a, const int b); -bool operator == (const mpreal& a, const long double b); -bool operator == (const mpreal& a, const double b); - -bool operator == (const unsigned long int a,const mpreal& b); -bool operator == (const unsigned int a, const mpreal& b); -bool operator == (const long int a, const mpreal& b); -bool operator == (const int a, const mpreal& b); -bool operator == (const long double a, const mpreal& b); -bool operator == (const double a, const mpreal& b); - -bool operator != (const mpreal& a, const unsigned long int b); -bool operator != (const mpreal& a, const unsigned int b); -bool operator != (const mpreal& a, const long int b); -bool operator != (const mpreal& a, const int b); -bool operator != (const mpreal& a, const long double b); -bool operator != (const mpreal& a, const double b); - -bool operator != (const unsigned long int a,const mpreal& b); -bool operator != (const unsigned int a, const mpreal& b); -bool operator != (const long int a, const mpreal& b); -bool operator != (const int a, const mpreal& b); -bool operator != (const long double a, const mpreal& b); -bool operator != (const double a, const mpreal& b); +template +inline const typename internal::result_type::type + operator/(const Lhs& lhs, const mpreal& rhs){ return mpreal(lhs) /= rhs; } ////////////////////////////////////////////////////////////////////////// // sqrt @@ -704,22 +668,45 @@ const mpreal pow(const double a, const int b, mp_rnd_t rnd_mode = mpreal::defaul ////////////////////////////////////////////////////////////////////////// // Estimate machine epsilon for the given precision -inline const mpreal machine_epsilon(mp_prec_t prec = mpreal::default_prec); -inline const mpreal mpreal_min(mp_prec_t prec = mpreal::default_prec); -inline const mpreal mpreal_max(mp_prec_t prec = mpreal::default_prec); +// Returns smallest eps such that 1.0 + eps != 1.0 +inline const mpreal machine_epsilon(mp_prec_t prec = mpreal::get_default_prec()); + +// Returns the positive distance from abs(x) to the next larger in magnitude floating point number of the same precision as x +inline const mpreal machine_epsilon(const mpreal& x); + +inline const mpreal mpreal_min(mp_prec_t prec = mpreal::get_default_prec()); +inline const mpreal mpreal_max(mp_prec_t prec = mpreal::get_default_prec()); +inline bool isEqualFuzzy(const mpreal& a, const mpreal& b, const mpreal& eps); +inline bool isEqualUlps(const mpreal& a, const mpreal& b, int maxUlps); ////////////////////////////////////////////////////////////////////////// -// Implementation of inline functions +// Bits - decimal digits relation +// bits = ceil(digits*log[2](10)) +// digits = floor(bits*log[10](2)) + +inline mp_prec_t digits2bits(int d); +inline int bits2digits(mp_prec_t b); + +////////////////////////////////////////////////////////////////////////// +// min, max +const mpreal (max)(const mpreal& x, const mpreal& y); +const mpreal (min)(const mpreal& x, const mpreal& y); + +////////////////////////////////////////////////////////////////////////// +// Implementation ////////////////////////////////////////////////////////////////////////// ////////////////////////////////////////////////////////////////////////// // Operators - Assignment inline mpreal& mpreal::operator=(const mpreal& v) { - if (this!= &v) + if (this != &v) { - mpfr_set_prec(mp,mpfr_get_prec(v.mp)); + mpfr_clear(mp); + mpfr_init2(mp,mpfr_get_prec(v.mp)); mpfr_set(mp,v.mp,default_rnd); + + MPREAL_MSVC_DEBUGVIEW_CODE; } return *this; } @@ -727,24 +714,32 @@ inline mpreal& mpreal::operator=(const mpreal& v) inline mpreal& mpreal::operator=(const mpf_t v) { mpfr_set_f(mp,v,default_rnd); + + MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } inline mpreal& mpreal::operator=(const mpz_t v) { mpfr_set_z(mp,v,default_rnd); + + MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } inline mpreal& mpreal::operator=(const mpq_t v) { mpfr_set_q(mp,v,default_rnd); + + MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } inline mpreal& mpreal::operator=(const long double v) { mpfr_set_ld(mp,v,default_rnd); + + MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } @@ -753,6 +748,8 @@ inline mpreal& mpreal::operator=(const double v) if(double_bits == -1 || fits_in_bits(v, double_bits)) { mpfr_set_d(mp,v,default_rnd); + + MPREAL_MSVC_DEBUGVIEW_CODE; } else throw conversion_overflow(); @@ -763,24 +760,32 @@ inline mpreal& mpreal::operator=(const double v) inline mpreal& mpreal::operator=(const unsigned long int v) { mpfr_set_ui(mp,v,default_rnd); + + MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } inline mpreal& mpreal::operator=(const unsigned int v) { mpfr_set_ui(mp,v,default_rnd); + + MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } inline mpreal& mpreal::operator=(const long int v) { mpfr_set_si(mp,v,default_rnd); + + MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } inline mpreal& mpreal::operator=(const int v) { mpfr_set_si(mp,v,default_rnd); + + MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } @@ -789,70 +794,90 @@ inline mpreal& mpreal::operator=(const int v) inline mpreal& mpreal::operator+=(const mpreal& v) { mpfr_add(mp,mp,v.mp,default_rnd); + MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } inline mpreal& mpreal::operator+=(const mpf_t u) { *this += mpreal(u); + MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } inline mpreal& mpreal::operator+=(const mpz_t u) { mpfr_add_z(mp,mp,u,default_rnd); + MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } inline mpreal& mpreal::operator+=(const mpq_t u) { mpfr_add_q(mp,mp,u,default_rnd); + MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } inline mpreal& mpreal::operator+= (const long double u) { - return *this += mpreal(u); + *this += mpreal(u); + MPREAL_MSVC_DEBUGVIEW_CODE; + return *this; } inline mpreal& mpreal::operator+= (const double u) { #if (MPFR_VERSION >= MPFR_VERSION_NUM(2,4,0)) mpfr_add_d(mp,mp,u,default_rnd); - return *this; #else - return *this += mpreal(u); + *this += mpreal(u); #endif + + MPREAL_MSVC_DEBUGVIEW_CODE; + return *this; } inline mpreal& mpreal::operator+=(const unsigned long int u) { mpfr_add_ui(mp,mp,u,default_rnd); + MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } inline mpreal& mpreal::operator+=(const unsigned int u) { mpfr_add_ui(mp,mp,u,default_rnd); + MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } inline mpreal& mpreal::operator+=(const long int u) { mpfr_add_si(mp,mp,u,default_rnd); + MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } inline mpreal& mpreal::operator+=(const int u) { mpfr_add_si(mp,mp,u,default_rnd); + MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } -inline const mpreal mpreal::operator+()const -{ - return mpreal(*this); -} +#if defined (MPREAL_HAVE_INT64_SUPPORT) +inline mpreal& mpreal::operator+=(const int64_t u){ *this += mpreal(u); MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } +inline mpreal& mpreal::operator+=(const uint64_t u){ *this += mpreal(u); MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } +inline mpreal& mpreal::operator-=(const int64_t u){ *this -= mpreal(u); MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } +inline mpreal& mpreal::operator-=(const uint64_t u){ *this -= mpreal(u); MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } +inline mpreal& mpreal::operator*=(const int64_t u){ *this *= mpreal(u); MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } +inline mpreal& mpreal::operator*=(const uint64_t u){ *this *= mpreal(u); MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } +inline mpreal& mpreal::operator/=(const int64_t u){ *this /= mpreal(u); MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } +inline mpreal& mpreal::operator/=(const uint64_t u){ *this /= mpreal(u); MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } +#endif + +inline const mpreal mpreal::operator+()const { return mpreal(*this); } inline const mpreal operator+(const mpreal& a, const mpreal& b) { @@ -861,111 +886,9 @@ inline const mpreal operator+(const mpreal& a, const mpreal& b) else return mpreal(b) += a; } -inline const std::string operator+(const mpreal& a, const std::string b) -{ - return (std::string)a+b; -} - -inline const std::string operator+(const std::string a, const mpreal& b) -{ - return a+(std::string)b; -} - -inline const mpreal operator+(const mpreal& a, const mpz_t b) -{ - return mpreal(a) += b; -} - -inline const mpreal operator+(const mpreal& a, const char* b) -{ - return a+mpreal(b); -} - -inline const mpreal operator+(const char* a, const mpreal& b) -{ - return mpreal(a)+b; - -} - -inline const mpreal operator+(const mpreal& a, const mpq_t b) -{ - return mpreal(a) += b; -} - -inline const mpreal operator+(const mpreal& a, const long double b) -{ - return mpreal(a) += b; -} - -inline const mpreal operator+(const mpreal& a, const double b) -{ - return mpreal(a) += b; -} - -inline const mpreal operator+(const mpreal& a, const unsigned long int b) -{ - return mpreal(a) += b; -} - -inline const mpreal operator+(const mpreal& a, const unsigned int b) -{ - return mpreal(a) += b; -} - -inline const mpreal operator+(const mpreal& a, const long int b) -{ - return mpreal(a) += b; -} - -inline const mpreal operator+(const mpreal& a, const int b) -{ - return mpreal(a) += b; -} - -inline const mpreal operator+(const mpz_t b, const mpreal& a) -{ - return mpreal(a) += b; -} - -inline const mpreal operator+(const mpq_t b, const mpreal& a) -{ - return mpreal(a) += b; -} - -inline const mpreal operator+(const long double b, const mpreal& a) -{ - return mpreal(a) += b; -} - -inline const mpreal operator+(const double b, const mpreal& a) -{ - return mpreal(a) += b; -} - -inline const mpreal operator+(const unsigned long int b, const mpreal& a) -{ - return mpreal(a) += b; -} - -inline const mpreal operator+(const unsigned int b, const mpreal& a) -{ - return mpreal(a) += b; -} - -inline const mpreal operator+(const long int b, const mpreal& a) -{ - return mpreal(a) += b; -} - -inline const mpreal operator+(const int b, const mpreal& a) -{ - return mpreal(a) += b; -} - inline mpreal& mpreal::operator++() { - *this += 1; - return *this; + return *this += 1; } inline const mpreal mpreal::operator++ (int) @@ -977,8 +900,7 @@ inline const mpreal mpreal::operator++ (int) inline mpreal& mpreal::operator--() { - *this -= 1; - return *this; + return *this -= 1; } inline const mpreal mpreal::operator-- (int) @@ -993,57 +915,68 @@ inline const mpreal mpreal::operator-- (int) inline mpreal& mpreal::operator-= (const mpreal& v) { mpfr_sub(mp,mp,v.mp,default_rnd); + MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } inline mpreal& mpreal::operator-=(const mpz_t v) { mpfr_sub_z(mp,mp,v,default_rnd); + MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } inline mpreal& mpreal::operator-=(const mpq_t v) { mpfr_sub_q(mp,mp,v,default_rnd); + MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } inline mpreal& mpreal::operator-=(const long double v) { - return *this -= mpreal(v); + *this -= mpreal(v); + MPREAL_MSVC_DEBUGVIEW_CODE; + return *this; } inline mpreal& mpreal::operator-=(const double v) { #if (MPFR_VERSION >= MPFR_VERSION_NUM(2,4,0)) mpfr_sub_d(mp,mp,v,default_rnd); - return *this; #else - return *this -= mpreal(v); + *this -= mpreal(v); #endif + + MPREAL_MSVC_DEBUGVIEW_CODE; + return *this; } inline mpreal& mpreal::operator-=(const unsigned long int v) { mpfr_sub_ui(mp,mp,v,default_rnd); + MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } inline mpreal& mpreal::operator-=(const unsigned int v) { mpfr_sub_ui(mp,mp,v,default_rnd); + MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } inline mpreal& mpreal::operator-=(const long int v) { mpfr_sub_si(mp,mp,v,default_rnd); + MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } inline mpreal& mpreal::operator-=(const int v) { mpfr_sub_si(mp,mp,v,default_rnd); + MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } @@ -1057,63 +990,14 @@ inline const mpreal mpreal::operator-()const inline const mpreal operator-(const mpreal& a, const mpreal& b) { // prec(a-b) = max(prec(a),prec(b)) - if(a.get_prec()>b.get_prec()) return mpreal(a) -= b; - else return -(mpreal(b) -= a); -} - -inline const mpreal operator-(const mpreal& a, const mpz_t b) -{ - return mpreal(a) -= b; -} - -inline const mpreal operator-(const mpreal& a, const mpq_t b) -{ - return mpreal(a) -= b; -} - -inline const mpreal operator-(const mpreal& a, const long double b) -{ - return mpreal(a) -= b; -} - -inline const mpreal operator-(const mpreal& a, const double b) -{ - return mpreal(a) -= b; -} - -inline const mpreal operator-(const mpreal& a, const unsigned long int b) -{ - return mpreal(a) -= b; -} - -inline const mpreal operator-(const mpreal& a, const unsigned int b) -{ - return mpreal(a) -= b; -} - -inline const mpreal operator-(const mpreal& a, const long int b) -{ - return mpreal(a) -= b; -} - -inline const mpreal operator-(const mpreal& a, const int b) -{ - return mpreal(a) -= b; -} - -inline const mpreal operator-(const mpz_t b, const mpreal& a) -{ - return -(mpreal(a) -= b); -} - -inline const mpreal operator-(const mpq_t b, const mpreal& a) -{ - return -(mpreal(a) -= b); -} - -inline const mpreal operator-(const long double b, const mpreal& a) -{ - return -(mpreal(a) -= b); + if(a.getPrecision() >= b.getPrecision()) + { + return mpreal(a) -= b; + }else{ + mpreal x(a); + x.setPrecision(b.getPrecision()); + return x -= b; + } } inline const mpreal operator-(const double b, const mpreal& a) @@ -1123,7 +1007,7 @@ inline const mpreal operator-(const double b, const mpreal& a) mpfr_d_sub(x.mp,b,a.mp,mpreal::default_rnd); return x; #else - return -(mpreal(a) -= b); + return mpreal(b) -= a; #endif } @@ -1155,160 +1039,81 @@ inline const mpreal operator-(const int b, const mpreal& a) return x; } -inline const mpreal operator-(const mpreal& a, const char* b) -{ - return a-mpreal(b); -} - -inline const mpreal operator-(const char* a, const mpreal& b) -{ - return mpreal(a)-b; -} - ////////////////////////////////////////////////////////////////////////// // * Multiplication inline mpreal& mpreal::operator*= (const mpreal& v) { mpfr_mul(mp,mp,v.mp,default_rnd); + MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } inline mpreal& mpreal::operator*=(const mpz_t v) { mpfr_mul_z(mp,mp,v,default_rnd); + MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } inline mpreal& mpreal::operator*=(const mpq_t v) { mpfr_mul_q(mp,mp,v,default_rnd); + MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } inline mpreal& mpreal::operator*=(const long double v) { - return *this *= mpreal(v); + *this *= mpreal(v); + MPREAL_MSVC_DEBUGVIEW_CODE; + return *this; } inline mpreal& mpreal::operator*=(const double v) { #if (MPFR_VERSION >= MPFR_VERSION_NUM(2,4,0)) mpfr_mul_d(mp,mp,v,default_rnd); - return *this; #else - return *this *= mpreal(v); + *this *= mpreal(v); #endif + + MPREAL_MSVC_DEBUGVIEW_CODE; + return *this; } inline mpreal& mpreal::operator*=(const unsigned long int v) { mpfr_mul_ui(mp,mp,v,default_rnd); + MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } inline mpreal& mpreal::operator*=(const unsigned int v) { mpfr_mul_ui(mp,mp,v,default_rnd); + MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } inline mpreal& mpreal::operator*=(const long int v) { mpfr_mul_si(mp,mp,v,default_rnd); + MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } inline mpreal& mpreal::operator*=(const int v) { mpfr_mul_si(mp,mp,v,default_rnd); + MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } inline const mpreal operator*(const mpreal& a, const mpreal& b) { // prec(a*b) = max(prec(a),prec(b)) - if(a.get_prec()>b.get_prec()) return mpreal(a) *= b; - else return mpreal(b) *= a; -} - -inline const mpreal operator*(const mpreal& a, const mpz_t b) -{ - return mpreal(a) *= b; -} - -inline const mpreal operator*(const mpreal& a, const mpq_t b) -{ - return mpreal(a) *= b; -} - -inline const mpreal operator*(const mpreal& a, const long double b) -{ - return mpreal(a) *= b; -} - -inline const mpreal operator*(const mpreal& a, const double b) -{ - return mpreal(a) *= b; -} - -inline const mpreal operator*(const mpreal& a, const unsigned long int b) -{ - return mpreal(a) *= b; -} - -inline const mpreal operator*(const mpreal& a, const unsigned int b) -{ - return mpreal(a) *= b; -} - -inline const mpreal operator*(const mpreal& a, const long int b) -{ - return mpreal(a) *= b; -} - -inline const mpreal operator*(const mpreal& a, const int b) -{ - return mpreal(a) *= b; -} - -inline const mpreal operator*(const mpz_t b, const mpreal& a) -{ - return mpreal(a) *= b; -} - -inline const mpreal operator*(const mpq_t b, const mpreal& a) -{ - return mpreal(a) *= b; -} - -inline const mpreal operator*(const long double b, const mpreal& a) -{ - return mpreal(a) *= b; -} - -inline const mpreal operator*(const double b, const mpreal& a) -{ - return mpreal(a) *= b; -} - -inline const mpreal operator*(const unsigned long int b, const mpreal& a) -{ - return mpreal(a) *= b; -} - -inline const mpreal operator*(const unsigned int b, const mpreal& a) -{ - return mpreal(a) *= b; -} - -inline const mpreal operator*(const long int b, const mpreal& a) -{ - return mpreal(a) *= b; -} - -inline const mpreal operator*(const int b, const mpreal& a) -{ - return mpreal(a) *= b; + if(a.getPrecision() >= b.getPrecision()) return mpreal(a) *= b; + else return mpreal(b) *= a; } ////////////////////////////////////////////////////////////////////////// @@ -1316,112 +1121,82 @@ inline const mpreal operator*(const int b, const mpreal& a) inline mpreal& mpreal::operator/=(const mpreal& v) { mpfr_div(mp,mp,v.mp,default_rnd); + MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } inline mpreal& mpreal::operator/=(const mpz_t v) { mpfr_div_z(mp,mp,v,default_rnd); + MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } inline mpreal& mpreal::operator/=(const mpq_t v) { mpfr_div_q(mp,mp,v,default_rnd); + MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } inline mpreal& mpreal::operator/=(const long double v) { - return *this /= mpreal(v); + *this /= mpreal(v); + MPREAL_MSVC_DEBUGVIEW_CODE; + return *this; } inline mpreal& mpreal::operator/=(const double v) { #if (MPFR_VERSION >= MPFR_VERSION_NUM(2,4,0)) mpfr_div_d(mp,mp,v,default_rnd); - return *this; #else - return *this /= mpreal(v); + *this /= mpreal(v); #endif + MPREAL_MSVC_DEBUGVIEW_CODE; + return *this; } inline mpreal& mpreal::operator/=(const unsigned long int v) { mpfr_div_ui(mp,mp,v,default_rnd); + MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } inline mpreal& mpreal::operator/=(const unsigned int v) { mpfr_div_ui(mp,mp,v,default_rnd); + MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } inline mpreal& mpreal::operator/=(const long int v) { mpfr_div_si(mp,mp,v,default_rnd); + MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } inline mpreal& mpreal::operator/=(const int v) { mpfr_div_si(mp,mp,v,default_rnd); + MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } inline const mpreal operator/(const mpreal& a, const mpreal& b) { - mpreal x(a); - mp_prec_t pb; - mp_prec_t pa; - // prec(a/b) = max(prec(a),prec(b)) - pa = a.get_prec(); - pb = b.get_prec(); - if(pb>pa) x.set_prec(pb); + if(a.getPrecision() >= b.getPrecision()) + { + return mpreal(a) /= b; + }else{ - return x /= b; -} - -inline const mpreal operator/(const mpreal& a, const mpz_t b) -{ - return mpreal(a) /= b; -} - -inline const mpreal operator/(const mpreal& a, const mpq_t b) -{ - return mpreal(a) /= b; -} - -inline const mpreal operator/(const mpreal& a, const long double b) -{ - return mpreal(a) /= b; -} - -inline const mpreal operator/(const mpreal& a, const double b) -{ - return mpreal(a) /= b; -} - -inline const mpreal operator/(const mpreal& a, const unsigned long int b) -{ - return mpreal(a) /= b; -} - -inline const mpreal operator/(const mpreal& a, const unsigned int b) -{ - return mpreal(a) /= b; -} - -inline const mpreal operator/(const mpreal& a, const long int b) -{ - return mpreal(a) /= b; -} - -inline const mpreal operator/(const mpreal& a, const int b) -{ - return mpreal(a) /= b; + mpreal x(a); + x.setPrecision(b.getPrecision()); + return x /= b; + } } inline const mpreal operator/(const unsigned long int b, const mpreal& a) @@ -1452,12 +1227,6 @@ inline const mpreal operator/(const int b, const mpreal& a) return x; } -inline const mpreal operator/(const long double b, const mpreal& a) -{ - mpreal x(b); - return x/a; -} - inline const mpreal operator/(const double b, const mpreal& a) { #if (MPFR_VERSION >= MPFR_VERSION_NUM(2,4,0)) @@ -1465,8 +1234,7 @@ inline const mpreal operator/(const double b, const mpreal& a) mpfr_d_div(x.mp,b,a.mp,mpreal::default_rnd); return x; #else - mpreal x(b); - return x/a; + return mpreal(b) /= a; #endif } @@ -1475,48 +1243,56 @@ inline const mpreal operator/(const double b, const mpreal& a) inline mpreal& mpreal::operator<<=(const unsigned long int u) { mpfr_mul_2ui(mp,mp,u,default_rnd); + MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } inline mpreal& mpreal::operator<<=(const unsigned int u) { mpfr_mul_2ui(mp,mp,static_cast(u),default_rnd); + MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } inline mpreal& mpreal::operator<<=(const long int u) { mpfr_mul_2si(mp,mp,u,default_rnd); + MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } inline mpreal& mpreal::operator<<=(const int u) { mpfr_mul_2si(mp,mp,static_cast(u),default_rnd); + MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } inline mpreal& mpreal::operator>>=(const unsigned long int u) { mpfr_div_2ui(mp,mp,u,default_rnd); + MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } inline mpreal& mpreal::operator>>=(const unsigned int u) { mpfr_div_2ui(mp,mp,static_cast(u),default_rnd); + MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } inline mpreal& mpreal::operator>>=(const long int u) { mpfr_div_2si(mp,mp,u,default_rnd); + MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } inline mpreal& mpreal::operator>>=(const int u) { mpfr_div_2si(mp,mp,static_cast(u),default_rnd); + MPREAL_MSVC_DEBUGVIEW_CODE; return *this; } @@ -1592,468 +1368,67 @@ inline const mpreal div_2si(const mpreal& v, long int k, mp_rnd_t rnd_mode) ////////////////////////////////////////////////////////////////////////// //Boolean operators -inline bool operator > (const mpreal& a, const mpreal& b) -{ - return (mpfr_greater_p(a.mp,b.mp)!=0); -} - -inline bool operator > (const mpreal& a, const unsigned long int b) -{ - return a>mpreal(b); -} - -inline bool operator > (const mpreal& a, const unsigned int b) -{ - return a>mpreal(b); -} - -inline bool operator > (const mpreal& a, const long int b) -{ - return a>mpreal(b); -} - -inline bool operator > (const mpreal& a, const int b) -{ - return a>mpreal(b); -} - -inline bool operator > (const mpreal& a, const long double b) -{ - return a>mpreal(b); -} - -inline bool operator > (const mpreal& a, const double b) -{ - return a>mpreal(b); -} - -inline bool operator > (const unsigned long int a, const mpreal& b) -{ - return mpreal(a)>b; -} - -inline bool operator > (const unsigned int a, const mpreal& b) -{ - return mpreal(a)>b; -} - -inline bool operator > (const long int a, const mpreal& b) -{ - return mpreal(a)>b; -} - -inline bool operator > (const int a, const mpreal& b) -{ - return mpreal(a)>b; -} - -inline bool operator > (const long double a, const mpreal& b) -{ - return mpreal(a)>b; -} - -inline bool operator > (const double a, const mpreal& b) -{ - return mpreal(a)>b; -} - -inline bool operator >= (const mpreal& a, const mpreal& b) -{ - return (mpfr_greaterequal_p(a.mp,b.mp)!=0); -} - -inline bool operator >= (const mpreal& a, const unsigned long int b) -{ - return a>=mpreal(b); -} - -inline bool operator >= (const mpreal& a, const unsigned int b) -{ - return a>=mpreal(b); -} - -inline bool operator >= (const mpreal& a, const long int b) -{ - return a>=mpreal(b); -} - -inline bool operator >= (const mpreal& a, const int b) -{ - return a>=mpreal(b); -} - -inline bool operator >= (const mpreal& a, const long double b) -{ - return a>=mpreal(b); -} - -inline bool operator >= (const mpreal& a, const double b) -{ - return a>=mpreal(b); -} - -inline bool operator >= (const unsigned long int a,const mpreal& b) -{ - return mpreal(a)>=b; -} - -inline bool operator >= (const unsigned int a, const mpreal& b) -{ - return mpreal(a)>=b; -} - -inline bool operator >= (const long int a, const mpreal& b) -{ - return mpreal(a)>=b; -} - -inline bool operator >= (const int a, const mpreal& b) -{ - return mpreal(a)>=b; -} - -inline bool operator >= (const long double a, const mpreal& b) -{ - return mpreal(a)>=b; -} - -inline bool operator >= (const double a, const mpreal& b) -{ - return mpreal(a)>=b; -} - -inline bool operator < (const mpreal& a, const mpreal& b) -{ - return (mpfr_less_p(a.mp,b.mp)!=0); -} - -inline bool operator < (const mpreal& a, const unsigned long int b) -{ - return a (const mpreal& a, const mpreal& b){ return (mpfr_greater_p(a.mp,b.mp) !=0); } +inline bool operator >= (const mpreal& a, const mpreal& b){ return (mpfr_greaterequal_p(a.mp,b.mp) !=0); } +inline bool operator < (const mpreal& a, const mpreal& b){ return (mpfr_less_p(a.mp,b.mp) !=0); } +inline bool operator <= (const mpreal& a, const mpreal& b){ return (mpfr_lessequal_p(a.mp,b.mp) !=0); } +inline bool operator == (const mpreal& a, const mpreal& b){ return (mpfr_equal_p(a.mp,b.mp) !=0); } +inline bool operator != (const mpreal& a, const mpreal& b){ return (mpfr_lessgreater_p(a.mp,b.mp) !=0); } + +inline bool operator == (const mpreal& a, const unsigned long int b ){ return (mpfr_cmp_ui(a.mp,b) == 0); } +inline bool operator == (const mpreal& a, const unsigned int b ){ return (mpfr_cmp_ui(a.mp,b) == 0); } +inline bool operator == (const mpreal& a, const long int b ){ return (mpfr_cmp_si(a.mp,b) == 0); } +inline bool operator == (const mpreal& a, const int b ){ return (mpfr_cmp_si(a.mp,b) == 0); } +inline bool operator == (const mpreal& a, const long double b ){ return (mpfr_cmp_ld(a.mp,b) == 0); } +inline bool operator == (const mpreal& a, const double b ){ return (mpfr_cmp_d(a.mp,b) == 0); } + + +inline bool isnan (const mpreal& v){ return (mpfr_nan_p(v.mp) != 0); } +inline bool isinf (const mpreal& v){ return (mpfr_inf_p(v.mp) != 0); } +inline bool isfinite(const mpreal& v){ return (mpfr_number_p(v.mp) != 0); } +inline bool iszero (const mpreal& v){ return (mpfr_zero_p(v.mp) != 0); } +inline bool isint (const mpreal& v){ return (mpfr_integer_p(v.mp) != 0); } #if (MPFR_VERSION >= MPFR_VERSION_NUM(3,0,0)) -inline bool _isregular(const mpreal& v) -{ - return (mpfr_regular_p(v.mp)); -} -#endif // MPFR 3.0.0 Specifics +inline bool isregular(const mpreal& v){ return (mpfr_regular_p(v.mp));} +#endif ////////////////////////////////////////////////////////////////////////// // Type Converters -inline mpreal::operator double() const +inline long mpreal::toLong() const { return mpfr_get_si(mp,GMP_RNDZ); } +inline unsigned long mpreal::toULong() const { return mpfr_get_ui(mp,GMP_RNDZ); } +inline double mpreal::toDouble() const { return mpfr_get_d(mp,default_rnd); } +inline long double mpreal::toLDouble() const { return mpfr_get_ld(mp,default_rnd); } + +#if defined (MPREAL_HAVE_INT64_SUPPORT) +inline int64_t mpreal::toInt64() const{ return mpfr_get_sj(mp,GMP_RNDZ); } +inline uint64_t mpreal::toUInt64() const{ return mpfr_get_uj(mp,GMP_RNDZ); } +#endif + +inline ::mpfr_ptr mpreal::mpfr_ptr() { return mp; } +inline ::mpfr_srcptr mpreal::mpfr_srcptr() const { return const_cast< ::mpfr_srcptr >(mp); } + +////////////////////////////////////////////////////////////////////////// +// Bits - decimal digits relation +// bits = ceil(digits*log[2](10)) +// digits = floor(bits*log[10](2)) + +inline mp_prec_t digits2bits(int d) { - return mpfr_get_d(mp,default_rnd); + const double LOG2_10 = 3.3219280948873624; + + d = 10>d?10:d; + + return (mp_prec_t)std::ceil((d)*LOG2_10); } -inline mpreal::operator float() const +inline int bits2digits(mp_prec_t b) { - return (float)mpfr_get_d(mp,default_rnd); -} + const double LOG10_2 = 0.30102999566398119; -inline mpreal::operator long double() const -{ - return mpfr_get_ld(mp,default_rnd); -} + b = 34>b?34:b; -inline mpreal::operator unsigned long() const -{ - return mpfr_get_ui(mp,GMP_RNDZ); -} - -inline mpreal::operator unsigned int() const -{ - return static_cast(mpfr_get_ui(mp,GMP_RNDZ)); -} - -inline mpreal::operator long() const -{ - return mpfr_get_si(mp,GMP_RNDZ); -} - -inline mpreal::operator int() const -{ - return static_cast(mpfr_get_si(mp,GMP_RNDZ)); -} - -inline mpreal::operator mpfr_ptr() -{ - return mp; + return (int)std::floor((b)*LOG10_2); } ////////////////////////////////////////////////////////////////////////// @@ -2064,9 +1439,44 @@ inline int sgn(const mpreal& v) return (r>0?-1:1); } -inline void mpreal::set_sign(int sign, mp_rnd_t rnd_mode) +inline mpreal& mpreal::setSign(int sign, mp_rnd_t RoundingMode) { - mpfr_setsign(mp,mp,(sign<0?1:0),rnd_mode); + mpfr_setsign(mp,mp,(sign<0?1:0),RoundingMode); + MPREAL_MSVC_DEBUGVIEW_CODE; + return *this; +} + +inline int mpreal::getPrecision() const +{ + return mpfr_get_prec(mp); +} + +inline mpreal& mpreal::setPrecision(int Precision, mp_rnd_t RoundingMode) +{ + mpfr_prec_round(mp,Precision, RoundingMode); + MPREAL_MSVC_DEBUGVIEW_CODE; + return *this; +} + +inline mpreal& mpreal::setInf(int sign) +{ + mpfr_set_inf(mp,sign); + MPREAL_MSVC_DEBUGVIEW_CODE; + return *this; +} + +inline mpreal& mpreal::setNan() +{ + mpfr_set_nan(mp); + MPREAL_MSVC_DEBUGVIEW_CODE; + return *this; +} + +inline mpreal& mpreal::setZero(int sign) +{ + mpfr_set_zero(mp,sign); + MPREAL_MSVC_DEBUGVIEW_CODE; + return *this; } inline mp_prec_t mpreal::get_prec() const @@ -2077,16 +1487,7 @@ inline mp_prec_t mpreal::get_prec() const inline void mpreal::set_prec(mp_prec_t prec, mp_rnd_t rnd_mode) { mpfr_prec_round(mp,prec,rnd_mode); -} - -inline void mpreal::set_inf(int sign) -{ - mpfr_set_inf(mp,sign); -} - -inline void mpreal::set_nan() -{ - mpfr_set_nan(mp); + MPREAL_MSVC_DEBUGVIEW_CODE; } inline mp_exp_t mpreal::get_exp () @@ -2096,7 +1497,9 @@ inline mp_exp_t mpreal::get_exp () inline int mpreal::set_exp (mp_exp_t e) { - return mpfr_set_exp(mp,e); + int x = mpfr_set_exp(mp, e); + MPREAL_MSVC_DEBUGVIEW_CODE; + return x; } inline const mpreal frexp(const mpreal& v, mp_exp_t* exp) @@ -2120,16 +1523,24 @@ inline const mpreal machine_epsilon(mp_prec_t prec) { // the smallest eps such that 1.0+eps != 1.0 // depends (of cause) on the precision - mpreal x(1,prec); - return nextabove(x)-x; + return machine_epsilon(mpreal(1,prec)); +} + +inline const mpreal machine_epsilon(const mpreal& x) +{ + if( x < 0) + { + return nextabove(-x)+x; + }else{ + return nextabove(x)-x; + } } inline const mpreal mpreal_min(mp_prec_t prec) { // min = 1/2*2^emin = 2^(emin-1) - - mpreal x(1,prec); - return x <<= mpreal::get_emin()-1; + + return mpreal(1,prec) << mpreal::get_emin()-1; } inline const mpreal mpreal_max(mp_prec_t prec) @@ -2138,8 +1549,25 @@ inline const mpreal mpreal_max(mp_prec_t prec) // and use emax-1 to prevent value to be +inf // max = 2^(emax-1) - mpreal x(1,prec); - return x <<= mpreal::get_emax()-1; + return mpreal(1,prec) << mpreal::get_emax()-1; +} + +inline bool isEqualUlps(const mpreal& a, const mpreal& b, int maxUlps) +{ + /* + maxUlps - a and b can be apart by maxUlps binary numbers. + */ + return abs(a - b) <= machine_epsilon((max)(abs(a), abs(b))) * maxUlps; +} + +inline bool isEqualFuzzy(const mpreal& a, const mpreal& b, const mpreal& eps) +{ + return abs(a - b) <= (min)(abs(a), abs(b)) * eps; +} + +inline bool isEqualFuzzy(const mpreal& a, const mpreal& b) +{ + return isEqualFuzzy(a,b,machine_epsilon((std::min)(abs(a), abs(b)))); } inline const mpreal modf(const mpreal& v, mpreal& n) @@ -2159,7 +1587,9 @@ inline int mpreal::check_range (int t, mp_rnd_t rnd_mode) inline int mpreal::subnormalize (int t,mp_rnd_t rnd_mode) { - return mpfr_subnormalize(mp,t,rnd_mode); + int r = mpfr_subnormalize(mp,t,rnd_mode); + MPREAL_MSVC_DEBUGVIEW_CODE; + return r; } inline mp_exp_t mpreal::get_emin (void) @@ -2234,13 +1664,13 @@ inline const mpreal sqrt(const unsigned int v, mp_rnd_t rnd_mode) inline const mpreal sqrt(const long int v, mp_rnd_t rnd_mode) { if (v>=0) return sqrt(static_cast(v),rnd_mode); - else return mpreal(); // NaN + else return mpreal().setNan(); // NaN } inline const mpreal sqrt(const int v, mp_rnd_t rnd_mode) { if (v>=0) return sqrt(static_cast(v),rnd_mode); - else return mpreal(); // NaN + else return mpreal().setNan(); // NaN } inline const mpreal sqrt(const long double v, mp_rnd_t rnd_mode) @@ -2403,6 +1833,36 @@ inline const mpreal atan (const mpreal& v, mp_rnd_t rnd_mode) return x; } +inline const mpreal acot (const mpreal& v, mp_rnd_t rnd_mode) +{ + return atan(1/v, rnd_mode); +} + +inline const mpreal asec (const mpreal& v, mp_rnd_t rnd_mode) +{ + return acos(1/v, rnd_mode); +} + +inline const mpreal acsc (const mpreal& v, mp_rnd_t rnd_mode) +{ + return asin(1/v, rnd_mode); +} + +inline const mpreal acoth (const mpreal& v, mp_rnd_t rnd_mode) +{ + return atanh(1/v, rnd_mode); +} + +inline const mpreal asech (const mpreal& v, mp_rnd_t rnd_mode) +{ + return acosh(1/v, rnd_mode); +} + +inline const mpreal acsch (const mpreal& v, mp_rnd_t rnd_mode) +{ + return asinh(1/v, rnd_mode); +} + inline const mpreal atan2 (const mpreal& y, const mpreal& x, mp_rnd_t rnd_mode) { mpreal a; @@ -2481,6 +1941,36 @@ inline const mpreal atanh (const mpreal& v, mp_rnd_t rnd_mode) return x; } +inline const mpreal hypot (const mpreal& x, const mpreal& y, mp_rnd_t rnd_mode) +{ + mpreal a; + mp_prec_t yp, xp; + + yp = y.get_prec(); + xp = x.get_prec(); + + a.set_prec(yp>xp?yp:xp); + + mpfr_hypot(a.mp, x.mp, y.mp, rnd_mode); + + return a; +} + +inline const mpreal remainder (const mpreal& x, const mpreal& y, mp_rnd_t rnd_mode) +{ + mpreal a; + mp_prec_t yp, xp; + + yp = y.get_prec(); + xp = x.get_prec(); + + a.set_prec(yp>xp?yp:xp); + + mpfr_remainder(a.mp, x.mp, y.mp, rnd_mode); + + return a; +} + inline const mpreal fac_ui (unsigned long int v, mp_prec_t prec, mp_rnd_t rnd_mode) { mpreal x(0,prec); @@ -2509,11 +1999,15 @@ inline const mpreal eint (const mpreal& v, mp_rnd_t rnd_mode) return x; } -inline const mpreal gamma (const mpreal& v, mp_rnd_t rnd_mode) +inline const mpreal gamma (const mpreal& x, mp_rnd_t rnd_mode) { - mpreal x(v); - mpfr_gamma(x.mp,v.mp,rnd_mode); - return x; + mpreal FunctionValue(x); + + // x < 0: gamma(-x) = -pi/(x * gamma(x) * sin(pi*x)) + + mpfr_gamma(FunctionValue.mp, x.mp, rnd_mode); + + return FunctionValue; } inline const mpreal lngamma (const mpreal& v, mp_rnd_t rnd_mode) @@ -2557,42 +2051,42 @@ inline const mpreal erfc (const mpreal& v, mp_rnd_t rnd_mode) return x; } -inline const mpreal _j0 (const mpreal& v, mp_rnd_t rnd_mode) +inline const mpreal besselj0 (const mpreal& v, mp_rnd_t rnd_mode) { mpreal x(v); mpfr_j0(x.mp,v.mp,rnd_mode); return x; } -inline const mpreal _j1 (const mpreal& v, mp_rnd_t rnd_mode) +inline const mpreal besselj1 (const mpreal& v, mp_rnd_t rnd_mode) { mpreal x(v); mpfr_j1(x.mp,v.mp,rnd_mode); return x; } -inline const mpreal _jn (long n, const mpreal& v, mp_rnd_t rnd_mode) +inline const mpreal besseljn (long n, const mpreal& v, mp_rnd_t rnd_mode) { mpreal x(v); mpfr_jn(x.mp,n,v.mp,rnd_mode); return x; } -inline const mpreal _y0 (const mpreal& v, mp_rnd_t rnd_mode) +inline const mpreal bessely0 (const mpreal& v, mp_rnd_t rnd_mode) { mpreal x(v); mpfr_y0(x.mp,v.mp,rnd_mode); return x; } -inline const mpreal _y1 (const mpreal& v, mp_rnd_t rnd_mode) +inline const mpreal bessely1 (const mpreal& v, mp_rnd_t rnd_mode) { mpreal x(v); mpfr_y1(x.mp,v.mp,rnd_mode); return x; } -inline const mpreal _yn (long n, const mpreal& v, mp_rnd_t rnd_mode) +inline const mpreal besselyn (long n, const mpreal& v, mp_rnd_t rnd_mode) { mpreal x(v); mpfr_yn(x.mp,n,v.mp,rnd_mode); @@ -2780,7 +2274,6 @@ inline void swap(mpreal& a, mpreal& b) mpfr_swap(a.mp,b.mp); } - inline const mpreal (max)(const mpreal& x, const mpreal& y) { return (x>y?x:y); @@ -2835,7 +2328,7 @@ inline const mpreal urandomb (gmp_randstate_t& state) #if (MPFR_VERSION >= MPFR_VERSION_NUM(3,0,0)) // use gmp_randinit_default() to init state, gmp_randclear() to clear -inline const mpreal urandom (gmp_randstate_t& state,mp_rnd_t rnd_mode) +inline const mpreal urandom (gmp_randstate_t& state, mp_rnd_t rnd_mode) { mpreal x; mpfr_urandom(x.mp,state,rnd_mode); @@ -2852,6 +2345,34 @@ inline const mpreal random2 (mp_size_t size, mp_exp_t exp) } #endif +// Uniformly distributed random number generation +// a = random(seed); <- initialization & first random number generation +// a = random(); <- next random numbers generation +// seed != 0 +inline const mpreal random(unsigned int seed) +{ + +#if (MPFR_VERSION >= MPFR_VERSION_NUM(3,0,0)) + static gmp_randstate_t state; + static bool isFirstTime = true; + + if(isFirstTime) + { + gmp_randinit_default(state); + gmp_randseed_ui(state,0); + isFirstTime = false; + } + + if(seed != 0) gmp_randseed_ui(state,seed); + + return mpfr::urandom(state); +#else + if(seed != 0) std::srand(seed); + return mpfr::mpreal(std::rand()/(double)RAND_MAX); +#endif + +} + ////////////////////////////////////////////////////////////////////////// // Set/Get global properties inline void mpreal::set_default_prec(mp_prec_t prec) @@ -2862,7 +2383,7 @@ inline void mpreal::set_default_prec(mp_prec_t prec) inline mp_prec_t mpreal::get_default_prec() { - return mpfr_get_default_prec(); + return (mpfr_get_default_prec)(); } inline void mpreal::set_default_base(int base) @@ -2883,7 +2404,7 @@ inline void mpreal::set_default_rnd(mp_rnd_t rnd_mode) inline mp_rnd_t mpreal::get_default_rnd() { - return mpfr_get_default_rounding_mode(); + return static_cast((mpfr_get_default_rounding_mode)()); } inline void mpreal::set_double_bits(int dbits) @@ -3197,8 +2718,7 @@ inline const mpreal pow(const double a, const int b, mp_rnd_t rnd_mode) { return pow(mpreal(a),static_cast(b),rnd_mode); // mpfr_pow_si } - -} +} // End of mpfr namespace // Explicit specialization of std::swap for mpreal numbers // Thus standard algorithms will use efficient version of swap (due to Koenig lookup) @@ -3212,4 +2732,4 @@ namespace std } } -#endif /* __MP_REAL_H__ */ +#endif /* __MPREAL_H__ */ diff --git a/gtsam/3rdparty/Eigen/unsupported/test/mpreal_support.cpp b/gtsam/3rdparty/Eigen/unsupported/test/mpreal_support.cpp index 53d388821..551af9db8 100644 --- a/gtsam/3rdparty/Eigen/unsupported/test/mpreal_support.cpp +++ b/gtsam/3rdparty/Eigen/unsupported/test/mpreal_support.cpp @@ -2,6 +2,7 @@ #include #include #include +#include using namespace mpfr; using namespace std; @@ -24,6 +25,15 @@ void test_mpreal_support() MatrixXmp B = MatrixXmp::Random(s,s); MatrixXmp S = A.adjoint() * A; MatrixXmp X; + + // Basic stuffs + VERIFY_IS_APPROX(A.real(), A); + VERIFY(Eigen::internal::isApprox(A.array().abs2().sum(), A.squaredNorm())); + VERIFY_IS_APPROX(A.array().exp(), exp(A.array())); + VERIFY_IS_APPROX(A.array().abs2().sqrt(), A.array().abs()); + VERIFY_IS_APPROX(A.array().sin(), sin(A.array())); + VERIFY_IS_APPROX(A.array().cos(), cos(A.array())); + // Cholesky X = S.selfadjointView().llt().solve(B); @@ -39,6 +49,13 @@ void test_mpreal_support() VERIFY_IS_APPROX((S.selfadjointView() * eig.eigenvectors()), eig.eigenvectors() * eig.eigenvalues().asDiagonal()); } + + { + MatrixXmp A(8,3); A.setRandom(); + // test output (interesting things happen in this code) + std::stringstream stream; + stream << A; + } } extern "C" { diff --git a/gtsam/3rdparty/Eigen/unsupported/test/polynomialsolver.cpp b/gtsam/3rdparty/Eigen/unsupported/test/polynomialsolver.cpp index 54b6657c9..28e034179 100644 --- a/gtsam/3rdparty/Eigen/unsupported/test/polynomialsolver.cpp +++ b/gtsam/3rdparty/Eigen/unsupported/test/polynomialsolver.cpp @@ -27,10 +27,6 @@ #include #include -#ifdef HAS_GSL -#include "gsl_helper.h" -#endif - using namespace std; namespace Eigen { @@ -73,32 +69,6 @@ bool aux_evalSolver( const POLYNOMIAL& pols, SOLVER& psolve ) cerr << endl; } - #ifdef HAS_GSL - if (internal::is_same< Scalar, double>::value) - { - typedef GslTraits Gsl; - RootsType gslRoots(deg); - Gsl::eigen_poly_solve( pols, gslRoots ); - EvalRootsType gslEvr( deg ); - for( int i=0; i() ); - if( !evalToZero ) - { - if( !gslEvalToZero ){ - cerr << "GSL also failed" << endl; } - else{ - cerr << "GSL did NOT failed" << endl; } - cerr << "GSL roots found: " << gslRoots.transpose() << endl; - cerr << "Abs value of the polynomial at the GSL roots: " << gslEvr.transpose() << endl; - cerr << endl; - } - } - #endif //< HAS_GSL - - std::vector rootModuli( roots.size() ); Map< EvalRootsType > aux( &rootModuli[0], roots.size() ); aux = roots.array().abs(); diff --git a/gtsam/3rdparty/Eigen/unsupported/test/sparse_extra.cpp b/gtsam/3rdparty/Eigen/unsupported/test/sparse_extra.cpp index b1fd481e8..6c5c888ae 100644 --- a/gtsam/3rdparty/Eigen/unsupported/test/sparse_extra.cpp +++ b/gtsam/3rdparty/Eigen/unsupported/test/sparse_extra.cpp @@ -22,7 +22,11 @@ // License and a copy of the GNU General Public License along with // Eigen. If not, see . -#include "sparse.h" + +// import basic and product tests for deprectaed DynamicSparseMatrix +#define EIGEN_NO_DEPRECATED_WARNING +#include "sparse_basic.cpp" +#include "sparse_product.cpp" #include template @@ -145,10 +149,16 @@ template void sparse_extra(const SparseMatrixType& re void test_sparse_extra() { for(int i = 0; i < g_repeat; i++) { + int s = Eigen::internal::random(1,50); CALL_SUBTEST_1( sparse_extra(SparseMatrix(8, 8)) ); - CALL_SUBTEST_2( sparse_extra(SparseMatrix >(16, 16)) ); - CALL_SUBTEST_1( sparse_extra(SparseMatrix(33, 33)) ); + CALL_SUBTEST_2( sparse_extra(SparseMatrix >(s, s)) ); + CALL_SUBTEST_1( sparse_extra(SparseMatrix(s, s)) ); - CALL_SUBTEST_3( sparse_extra(DynamicSparseMatrix(8, 8)) ); + CALL_SUBTEST_3( sparse_extra(DynamicSparseMatrix(s, s)) ); +// CALL_SUBTEST_3(( sparse_basic(DynamicSparseMatrix(s, s)) )); +// CALL_SUBTEST_3(( sparse_basic(DynamicSparseMatrix(s, s)) )); + + CALL_SUBTEST_3( (sparse_product >()) ); + CALL_SUBTEST_3( (sparse_product >()) ); } } diff --git a/gtsam/3rdparty/Eigen/unsupported/test/sparse_ldlt.cpp b/gtsam/3rdparty/Eigen/unsupported/test/sparse_ldlt.cpp deleted file mode 100644 index 03a26bcd2..000000000 --- a/gtsam/3rdparty/Eigen/unsupported/test/sparse_ldlt.cpp +++ /dev/null @@ -1,175 +0,0 @@ -// This file is part of Eigen, a lightweight C++ template library -// for linear algebra. -// -// Copyright (C) 2008-2010 Gael Guennebaud -// -// Eigen is free software; you can redistribute it and/or -// modify it under the terms of the GNU Lesser General Public -// License as published by the Free Software Foundation; either -// version 3 of the License, or (at your option) any later version. -// -// Alternatively, you can redistribute it and/or -// modify it under the terms of the GNU General Public License as -// published by the Free Software Foundation; either version 2 of -// the License, or (at your option) any later version. -// -// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY -// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS -// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the -// GNU General Public License for more details. -// -// You should have received a copy of the GNU Lesser General Public -// License and a copy of the GNU General Public License along with -// Eigen. If not, see . - -#include "sparse.h" -#include - -#ifdef EIGEN_CHOLMOD_SUPPORT -#include -#endif - -template void sparse_ldlt(int rows, int cols) -{ - static bool odd = true; - odd = !odd; - double density = (std::max)(8./(rows*cols), 0.01); - typedef Matrix DenseMatrix; - typedef Matrix DenseVector; - - SparseMatrix m2(rows, cols); - DenseMatrix refMat2(rows, cols); - - DenseVector b = DenseVector::Random(cols); - DenseVector refX(cols), x(cols); - - initSparse(density, refMat2, m2, ForceNonZeroDiag|MakeUpperTriangular, 0, 0); - - SparseMatrix m3 = m2 * m2.adjoint(), m3_lo(rows,rows), m3_up(rows,rows); - DenseMatrix refMat3 = refMat2 * refMat2.adjoint(); - - refX = refMat3.template selfadjointView().ldlt().solve(b); - typedef SparseMatrix SparseSelfAdjointMatrix; - x = b; - SparseLDLT ldlt(m3); - if (ldlt.succeeded()) - ldlt.solveInPlace(x); - else - std::cerr << "warning LDLT failed\n"; - - VERIFY_IS_APPROX(refMat3.template selfadjointView() * x, b); - VERIFY(refX.isApprox(x,test_precision()) && "LDLT: default"); - -#ifdef EIGEN_CHOLMOD_SUPPORT - { - x = b; - SparseLDLT ldlt2(m3); - if (ldlt2.succeeded()) - { - ldlt2.solveInPlace(x); - VERIFY_IS_APPROX(refMat3.template selfadjointView() * x, b); - VERIFY(refX.isApprox(x,test_precision()) && "LDLT: cholmod solveInPlace"); - - x = ldlt2.solve(b); - VERIFY_IS_APPROX(refMat3.template selfadjointView() * x, b); - VERIFY(refX.isApprox(x,test_precision()) && "LDLT: cholmod solve"); - } - else - std::cerr << "warning LDLT failed\n"; - } -#endif - - // new Simplicial LLT - - - // new API - { - SparseMatrix m2(rows, cols); - DenseMatrix refMat2(rows, cols); - - DenseVector b = DenseVector::Random(cols); - DenseVector ref_x(cols), x(cols); - DenseMatrix B = DenseMatrix::Random(rows,cols); - DenseMatrix ref_X(rows,cols), X(rows,cols); - - initSparse(density, refMat2, m2, ForceNonZeroDiag|MakeLowerTriangular, 0, 0); - - for(int i=0; i m3 = m2 * m2.adjoint(), m3_lo(rows,rows), m3_up(rows,rows); - DenseMatrix refMat3 = refMat2 * refMat2.adjoint(); - - m3_lo.template selfadjointView().rankUpdate(m2,0); - m3_up.template selfadjointView().rankUpdate(m2,0); - - // with a single vector as the rhs - ref_x = refMat3.template selfadjointView().llt().solve(b); - - x = SimplicialCholesky, Lower>().setMode(odd ? SimplicialCholeskyLLt : SimplicialCholeskyLDLt).compute(m3).solve(b); - VERIFY(ref_x.isApprox(x,test_precision()) && "SimplicialCholesky: solve, full storage, lower, single dense rhs"); - - x = SimplicialCholesky, Upper>().setMode(odd ? SimplicialCholeskyLLt : SimplicialCholeskyLDLt).compute(m3).solve(b); - VERIFY(ref_x.isApprox(x,test_precision()) && "SimplicialCholesky: solve, full storage, upper, single dense rhs"); - - x = SimplicialCholesky, Lower>(m3_lo).solve(b); - VERIFY(ref_x.isApprox(x,test_precision()) && "SimplicialCholesky: solve, lower only, single dense rhs"); - - x = SimplicialCholesky, Upper>(m3_up).solve(b); - VERIFY(ref_x.isApprox(x,test_precision()) && "SimplicialCholesky: solve, upper only, single dense rhs"); - - - // with multiple rhs - ref_X = refMat3.template selfadjointView().llt().solve(B); - - X = SimplicialCholesky, Lower>().setMode(odd ? SimplicialCholeskyLLt : SimplicialCholeskyLDLt).compute(m3).solve(B); - VERIFY(ref_X.isApprox(X,test_precision()) && "SimplicialCholesky: solve, full storage, lower, multiple dense rhs"); - - X = SimplicialCholesky, Upper>().setMode(odd ? SimplicialCholeskyLLt : SimplicialCholeskyLDLt).compute(m3).solve(B); - VERIFY(ref_X.isApprox(X,test_precision()) && "SimplicialCholesky: solve, full storage, upper, multiple dense rhs"); - - - // with a sparse rhs -// SparseMatrix spB(rows,cols), spX(rows,cols); -// B.diagonal().array() += 1; -// spB = B.sparseView(0.5,1); -// -// ref_X = refMat3.template selfadjointView().llt().solve(DenseMatrix(spB)); -// -// spX = SimplicialCholesky, Lower>(m3).solve(spB); -// VERIFY(ref_X.isApprox(spX.toDense(),test_precision()) && "LLT: cholmod solve, multiple sparse rhs"); -// -// spX = SimplicialCholesky, Upper>(m3).solve(spB); -// VERIFY(ref_X.isApprox(spX.toDense(),test_precision()) && "LLT: cholmod solve, multiple sparse rhs"); - } - - - -// for(int i=0; i().ldlt().solve(b); -// typedef SparseMatrix SparseSelfAdjointMatrix; -// x = b; -// SparseLDLT ldlt(m2); -// if (ldlt.succeeded()) -// ldlt.solveInPlace(x); -// else -// std::cerr << "warning LDLT failed\n"; -// -// VERIFY_IS_APPROX(refMat2.template selfadjointView() * x, b); -// VERIFY(refX.isApprox(x,test_precision()) && "LDLT: default"); - - -} - -void test_sparse_ldlt() -{ - for(int i = 0; i < g_repeat; i++) { - CALL_SUBTEST_1(sparse_ldlt(8, 8) ); - int s = internal::random(1,300); - CALL_SUBTEST_2(sparse_ldlt >(s,s) ); - CALL_SUBTEST_1(sparse_ldlt(s,s) ); - } -} diff --git a/gtsam/3rdparty/Eigen/unsupported/test/sparse_llt.cpp b/gtsam/3rdparty/Eigen/unsupported/test/sparse_llt.cpp deleted file mode 100644 index 5f8a7ce36..000000000 --- a/gtsam/3rdparty/Eigen/unsupported/test/sparse_llt.cpp +++ /dev/null @@ -1,140 +0,0 @@ -// This file is part of Eigen, a lightweight C++ template library -// for linear algebra. -// -// Copyright (C) 2008-2010 Gael Guennebaud -// -// Eigen is free software; you can redistribute it and/or -// modify it under the terms of the GNU Lesser General Public -// License as published by the Free Software Foundation; either -// version 3 of the License, or (at your option) any later version. -// -// Alternatively, you can redistribute it and/or -// modify it under the terms of the GNU General Public License as -// published by the Free Software Foundation; either version 2 of -// the License, or (at your option) any later version. -// -// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY -// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS -// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the -// GNU General Public License for more details. -// -// You should have received a copy of the GNU Lesser General Public -// License and a copy of the GNU General Public License along with -// Eigen. If not, see . - -#include "sparse.h" -#include - -#ifdef EIGEN_CHOLMOD_SUPPORT -#include -#endif - -template void sparse_llt(int rows, int cols) -{ - double density = (std::max)(8./(rows*cols), 0.01); - typedef Matrix DenseMatrix; - typedef Matrix DenseVector; - - // TODO fix the issue with complex (see SparseLLT::solveInPlace) - SparseMatrix m2(rows, cols); - DenseMatrix refMat2(rows, cols); - - DenseVector b = DenseVector::Random(cols); - DenseVector ref_x(cols), x(cols); - DenseMatrix B = DenseMatrix::Random(rows,cols); - DenseMatrix ref_X(rows,cols), X(rows,cols); - - initSparse(density, refMat2, m2, ForceNonZeroDiag|MakeLowerTriangular, 0, 0); - - for(int i=0; i().llt().solve(b); - if (!NumTraits::IsComplex) - { - x = b; - SparseLLT > (m2).solveInPlace(x); - VERIFY(ref_x.isApprox(x,test_precision()) && "LLT: default"); - } - -#ifdef EIGEN_CHOLMOD_SUPPORT - // legacy API - { - // Cholmod, as configured in CholmodSupport.h, only supports self-adjoint matrices - SparseMatrix m3 = m2.adjoint()*m2; - DenseMatrix refMat3 = refMat2.adjoint()*refMat2; - - ref_x = refMat3.template selfadjointView().llt().solve(b); - - x = b; - SparseLLT, Cholmod>(m3).solveInPlace(x); - VERIFY((m3*x).isApprox(b,test_precision()) && "LLT legacy: cholmod solveInPlace"); - - x = SparseLLT, Cholmod>(m3).solve(b); - VERIFY(ref_x.isApprox(x,test_precision()) && "LLT legacy: cholmod solve"); - } - - // new API - { - // Cholmod, as configured in CholmodSupport.h, only supports self-adjoint matrices - SparseMatrix m3 = m2 * m2.adjoint(), m3_lo(rows,rows), m3_up(rows,rows); - DenseMatrix refMat3 = refMat2 * refMat2.adjoint(); - - m3_lo.template selfadjointView().rankUpdate(m2,0); - m3_up.template selfadjointView().rankUpdate(m2,0); - - // with a single vector as the rhs - ref_x = refMat3.template selfadjointView().llt().solve(b); - - x = CholmodDecomposition, Lower>(m3).solve(b); - VERIFY(ref_x.isApprox(x,test_precision()) && "LLT: cholmod solve, single dense rhs"); - - x = CholmodDecomposition, Upper>(m3).solve(b); - VERIFY(ref_x.isApprox(x,test_precision()) && "LLT: cholmod solve, single dense rhs"); - - x = CholmodDecomposition, Lower>(m3_lo).solve(b); - VERIFY(ref_x.isApprox(x,test_precision()) && "LLT: cholmod solve, single dense rhs"); - - x = CholmodDecomposition, Upper>(m3_up).solve(b); - VERIFY(ref_x.isApprox(x,test_precision()) && "LLT: cholmod solve, single dense rhs"); - - - // with multiple rhs - ref_X = refMat3.template selfadjointView().llt().solve(B); - - #ifndef EIGEN_DEFAULT_TO_ROW_MAJOR - // TODO make sure the API is properly documented about this fact - X = CholmodDecomposition, Lower>(m3).solve(B); - VERIFY(ref_X.isApprox(X,test_precision()) && "LLT: cholmod solve, multiple dense rhs"); - - X = CholmodDecomposition, Upper>(m3).solve(B); - VERIFY(ref_X.isApprox(X,test_precision()) && "LLT: cholmod solve, multiple dense rhs"); - #endif - - - // with a sparse rhs - SparseMatrix spB(rows,cols), spX(rows,cols); - B.diagonal().array() += 1; - spB = B.sparseView(0.5,1); - - ref_X = refMat3.template selfadjointView().llt().solve(DenseMatrix(spB)); - - spX = CholmodDecomposition, Lower>(m3).solve(spB); - VERIFY(ref_X.isApprox(spX.toDense(),test_precision()) && "LLT: cholmod solve, multiple sparse rhs"); - - spX = CholmodDecomposition, Upper>(m3).solve(spB); - VERIFY(ref_X.isApprox(spX.toDense(),test_precision()) && "LLT: cholmod solve, multiple sparse rhs"); - } -#endif - -} - -void test_sparse_llt() -{ - for(int i = 0; i < g_repeat; i++) { - CALL_SUBTEST_1(sparse_llt(8, 8) ); - int s = internal::random(1,300); - CALL_SUBTEST_2(sparse_llt >(s,s) ); - CALL_SUBTEST_1(sparse_llt(s,s) ); - } -} diff --git a/gtsam/3rdparty/Eigen/unsupported/test/sparse_lu.cpp b/gtsam/3rdparty/Eigen/unsupported/test/sparse_lu.cpp deleted file mode 100644 index d58e85a0a..000000000 --- a/gtsam/3rdparty/Eigen/unsupported/test/sparse_lu.cpp +++ /dev/null @@ -1,113 +0,0 @@ -// This file is part of Eigen, a lightweight C++ template library -// for linear algebra. -// -// Copyright (C) 2008-2010 Gael Guennebaud -// -// Eigen is free software; you can redistribute it and/or -// modify it under the terms of the GNU Lesser General Public -// License as published by the Free Software Foundation; either -// version 3 of the License, or (at your option) any later version. -// -// Alternatively, you can redistribute it and/or -// modify it under the terms of the GNU General Public License as -// published by the Free Software Foundation; either version 2 of -// the License, or (at your option) any later version. -// -// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY -// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS -// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the -// GNU General Public License for more details. -// -// You should have received a copy of the GNU Lesser General Public -// License and a copy of the GNU General Public License along with -// Eigen. If not, see . - -#include "sparse.h" -#include - -#ifdef EIGEN_UMFPACK_SUPPORT -#include -#endif - -#ifdef EIGEN_SUPERLU_SUPPORT -#include -#endif - -template void sparse_lu(int rows, int cols) -{ - double density = (std::max)(8./(rows*cols), 0.01); - typedef Matrix DenseMatrix; - typedef Matrix DenseVector; - - DenseVector vec1 = DenseVector::Random(rows); - - std::vector zeroCoords; - std::vector nonzeroCoords; - - SparseMatrix m2(rows, cols); - DenseMatrix refMat2(rows, cols); - - DenseVector b = DenseVector::Random(cols); - DenseVector refX(cols), x(cols); - - initSparse(density, refMat2, m2, ForceNonZeroDiag, &zeroCoords, &nonzeroCoords); - - FullPivLU refLu(refMat2); - refX = refLu.solve(b); - #if defined(EIGEN_SUPERLU_SUPPORT) || defined(EIGEN_UMFPACK_SUPPORT) - Scalar refDet = refLu.determinant(); - #endif - x.setZero(); - // // SparseLU > (m2).solve(b,&x); - // // VERIFY(refX.isApprox(x,test_precision()) && "LU: default"); - - #ifdef EIGEN_UMFPACK_SUPPORT - { - // check solve - x.setZero(); - SparseLU,UmfPack> lu(m2); - VERIFY(lu.succeeded() && "umfpack LU decomposition failed"); - VERIFY(lu.solve(b,&x) && "umfpack LU solving failed"); - VERIFY(refX.isApprox(x,test_precision()) && "LU: umfpack"); - VERIFY_IS_APPROX(refDet,lu.determinant()); - // TODO check the extracted data - //std::cerr << slu.matrixL() << "\n"; - } - #endif - - #ifdef EIGEN_SUPERLU_SUPPORT - { - x.setZero(); - SparseLU,SuperLU> slu(m2); - if (slu.succeeded()) - { - if (slu.solve(b,&x)) { - VERIFY(refX.isApprox(x,test_precision()) && "LU: SuperLU"); - } - // std::cerr << refDet << " == " << slu.determinant() << "\n"; - if (slu.solve(b, &x, SvTranspose)) { - VERIFY(b.isApprox(m2.transpose() * x, test_precision())); - } - - if (slu.solve(b, &x, SvAdjoint)) { - VERIFY(b.isApprox(m2.adjoint() * x, test_precision())); - } - - if (!NumTraits::IsComplex) { - VERIFY_IS_APPROX(refDet,slu.determinant()); // FIXME det is not very stable for complex - } - } - } - #endif - -} - -void test_sparse_lu() -{ - for(int i = 0; i < g_repeat; i++) { - CALL_SUBTEST_1(sparse_lu(8, 8) ); - int s = internal::random(1,300); - CALL_SUBTEST_2(sparse_lu >(s,s) ); - CALL_SUBTEST_1(sparse_lu(s,s) ); - } -} diff --git a/gtsam/3rdparty/Eigen/unsupported/test/splines.cpp b/gtsam/3rdparty/Eigen/unsupported/test/splines.cpp new file mode 100644 index 000000000..fe98bf183 --- /dev/null +++ b/gtsam/3rdparty/Eigen/unsupported/test/splines.cpp @@ -0,0 +1,255 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2010-2011 Hauke Heibel +// +// Eigen is free software; you can redistribute it and/or +// modify it under the terms of the GNU Lesser General Public +// License as published by the Free Software Foundation; either +// version 3 of the License, or (at your option) any later version. +// +// Alternatively, you can redistribute it and/or +// modify it under the terms of the GNU General Public License as +// published by the Free Software Foundation; either version 2 of +// the License, or (at your option) any later version. +// +// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY +// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the +// GNU General Public License for more details. +// +// You should have received a copy of the GNU Lesser General Public +// License and a copy of the GNU General Public License along with +// Eigen. If not, see . + +#include "main.h" + +#include + +// lets do some explicit instantiations and thus +// force the compilation of all spline functions... +template class Spline; +template class Spline; + +template class Spline; +template class Spline; +template class Spline; +template class Spline; + +template class Spline; +template class Spline; + +template class Spline; +template class Spline; +template class Spline; +template class Spline; + +Spline closed_spline2d() +{ + RowVectorXd knots(12); + knots << 0, + 0, + 0, + 0, + 0.867193179093898, + 1.660330955342408, + 2.605084834823134, + 3.484154586374428, + 4.252699478956276, + 4.252699478956276, + 4.252699478956276, + 4.252699478956276; + + MatrixXd ctrls(8,2); + ctrls << -0.370967741935484, 0.236842105263158, + -0.231401860693277, 0.442245185027632, + 0.344361228532831, 0.773369994120753, + 0.828990216203802, 0.106550882647595, + 0.407270163678382, -1.043452922172848, + -0.488467813584053, -0.390098582530090, + -0.494657189446427, 0.054804824897884, + -0.370967741935484, 0.236842105263158; + ctrls.transposeInPlace(); + + return Spline(knots, ctrls); +} + +/* create a reference spline */ +Spline spline3d() +{ + RowVectorXd knots(11); + knots << 0, + 0, + 0, + 0.118997681558377, + 0.162611735194631, + 0.498364051982143, + 0.655098003973841, + 0.679702676853675, + 1.000000000000000, + 1.000000000000000, + 1.000000000000000; + + MatrixXd ctrls(8,3); + ctrls << 0.959743958516081, 0.340385726666133, 0.585267750979777, + 0.223811939491137, 0.751267059305653, 0.255095115459269, + 0.505957051665142, 0.699076722656686, 0.890903252535799, + 0.959291425205444, 0.547215529963803, 0.138624442828679, + 0.149294005559057, 0.257508254123736, 0.840717255983663, + 0.254282178971531, 0.814284826068816, 0.243524968724989, + 0.929263623187228, 0.349983765984809, 0.196595250431208, + 0.251083857976031, 0.616044676146639, 0.473288848902729; + ctrls.transposeInPlace(); + + return Spline(knots, ctrls); +} + +/* compares evaluations against known results */ +void eval_spline3d() +{ + Spline3d spline = spline3d(); + + RowVectorXd u(10); + u << 0.351659507062997, + 0.830828627896291, + 0.585264091152724, + 0.549723608291140, + 0.917193663829810, + 0.285839018820374, + 0.757200229110721, + 0.753729094278495, + 0.380445846975357, + 0.567821640725221; + + MatrixXd pts(10,3); + pts << 0.707620811535916, 0.510258911240815, 0.417485437023409, + 0.603422256426978, 0.529498282727551, 0.270351549348981, + 0.228364197569334, 0.423745615677815, 0.637687289287490, + 0.275556796335168, 0.350856706427970, 0.684295784598905, + 0.514519311047655, 0.525077224890754, 0.351628308305896, + 0.724152914315666, 0.574461155457304, 0.469860285484058, + 0.529365063753288, 0.613328702656816, 0.237837040141739, + 0.522469395136878, 0.619099658652895, 0.237139665242069, + 0.677357023849552, 0.480655768435853, 0.422227610314397, + 0.247046593173758, 0.380604672404750, 0.670065791405019; + pts.transposeInPlace(); + + for (int i=0; i::Interpolate(points,3); + + for (Eigen::DenseIndex i=0; i::Interpolate(points,3,chord_lengths); + + for (Eigen::DenseIndex i=0; i #include -#include +#include using namespace std; diff --git a/gtsam_unstable/base/DSFVector.h b/gtsam/base/DSFVector.h similarity index 99% rename from gtsam_unstable/base/DSFVector.h rename to gtsam/base/DSFVector.h index 17e897032..3940723c4 100644 --- a/gtsam_unstable/base/DSFVector.h +++ b/gtsam/base/DSFVector.h @@ -27,7 +27,7 @@ namespace gtsam { /** * A fast implementation of disjoint set forests that uses vector as underly data structure. - * @ingroup base + * @addtogroup base */ class DSFVector { diff --git a/gtsam/base/DerivedValue.h b/gtsam/base/DerivedValue.h index 1919f9540..2dc6f3d67 100644 --- a/gtsam/base/DerivedValue.h +++ b/gtsam/base/DerivedValue.h @@ -10,14 +10,13 @@ * -------------------------------------------------------------------------- */ /* - * DerivedValue.h - * - * Created on: Jan 26, 2012 - * Author: thduynguyen + * @file DerivedValue.h + * @date Jan 26, 2012 + * @author Duy Nguyen Ta */ #pragma once - +#include #include #include @@ -25,9 +24,6 @@ namespace gtsam { template class DerivedValue : public Value { -private: - /// Fake Tag struct for singleton pool allocator. In fact, it is never used! - struct PoolTag { }; protected: DerivedValue() {} @@ -38,7 +34,8 @@ public: /** * Create a duplicate object returned as a pointer to the generic Value interface. - * For the sake of performance, this function use singleton pool allocator instead of the normal heap allocator + * For the sake of performance, this function use singleton pool allocator instead of the normal heap allocator. + * The result must be deleted with Value::deallocate_, not with the 'delete' operator. */ virtual Value* clone_() const { void *place = boost::singleton_pool::malloc(); @@ -50,10 +47,17 @@ public: * Destroy and deallocate this object, only if it was originally allocated using clone_(). */ virtual void deallocate_() const { - this->~Value(); - boost::singleton_pool::free((void*)this); + this->~DerivedValue(); // Virtual destructor cleans up the derived object + boost::singleton_pool::free((void*)this); // Release memory from pool } + /** + * Clone this value (normal clone on the heap, delete with 'delete' operator) + */ + virtual boost::shared_ptr clone() const { + return boost::make_shared(static_cast(*this)); + } + /// equals implementing generic Value interface virtual bool equals_(const Value& p, double tol = 1e-9) const { // Cast the base class Value pointer to a derived class pointer @@ -112,6 +116,10 @@ protected: return *this; } +private: + /// Fake Tag struct for singleton pool allocator. In fact, it is never used! + struct PoolTag { }; + }; } /* namespace gtsam */ diff --git a/gtsam/base/FastList.h b/gtsam/base/FastList.h index 60452357f..aa1ab24e8 100644 --- a/gtsam/base/FastList.h +++ b/gtsam/base/FastList.h @@ -31,7 +31,7 @@ namespace gtsam { * convenience to avoid having lengthy types in the code. Through timing, * we've seen that the fast_pool_allocator can lead to speedups of several * percent. - * @ingroup base + * @addtogroup base */ template class FastList: public std::list > { @@ -50,9 +50,18 @@ public: /** Copy constructor from another FastList */ FastList(const FastList& x) : Base(x) {} - /** Copy constructor from the base map class */ + /** Copy constructor from the base list class */ FastList(const Base& x) : Base(x) {} + /** Copy constructor from a standard STL container */ + FastList(const std::list& x) { + // This if statement works around a bug in boost pool allocator and/or + // STL vector where if the size is zero, the pool allocator will allocate + // huge amounts of memory. + if(x.size() > 0) + Base::assign(x.begin(), x.end()); + } + private: /** Serialization function */ friend class boost::serialization::access; diff --git a/gtsam/base/FastMap.h b/gtsam/base/FastMap.h index c9fe30646..ab448de07 100644 --- a/gtsam/base/FastMap.h +++ b/gtsam/base/FastMap.h @@ -31,7 +31,7 @@ namespace gtsam { * convenience to avoid having lengthy types in the code. Through timing, * we've seen that the fast_pool_allocator can lead to speedups of several * percent. - * @ingroup base + * @addtogroup base */ template class FastMap : public std::map, boost::fast_pool_allocator > > { diff --git a/gtsam/base/FastSet.h b/gtsam/base/FastSet.h index 6abd7efb8..123a8bb31 100644 --- a/gtsam/base/FastSet.h +++ b/gtsam/base/FastSet.h @@ -42,7 +42,7 @@ struct FastSetTestableHelper; * fast_pool_allocator instead of the default STL allocator. This is just a * convenience to avoid having lengthy types in the code. Through timing, * we've seen that the fast_pool_allocator can lead to speedups of several %. - * @ingroup base + * @addtogroup base */ template class FastSet: public std::set, boost::fast_pool_allocator > { @@ -66,11 +66,20 @@ public: Base(x) { } - /** Copy constructor from the base map class */ + /** Copy constructor from the base set class */ FastSet(const Base& x) : Base(x) { } + /** Copy constructor from a standard STL container */ + FastSet(const std::set& x) { + // This if statement works around a bug in boost pool allocator and/or + // STL vector where if the size is zero, the pool allocator will allocate + // huge amounts of memory. + if(x.size() > 0) + Base::insert(x.begin(), x.end()); + } + /** Print to implement Testable */ void print(const std::string& str = "") const { FastSetTestableHelper::print(*this, str); } diff --git a/gtsam/base/FastVector.h b/gtsam/base/FastVector.h index 18af63006..33bc5cb7c 100644 --- a/gtsam/base/FastVector.h +++ b/gtsam/base/FastVector.h @@ -23,6 +23,9 @@ #include #include +#include +#include + namespace gtsam { /** @@ -30,7 +33,7 @@ namespace gtsam { * pool_allocator instead of the default STL allocator. This is just a * convenience to avoid having lengthy types in the code. Through timing, * we've seen that the pool_allocator can lead to speedups of several % - * @ingroup base + * @addtogroup base */ template class FastVector: public std::vector > { @@ -58,9 +61,21 @@ public: Base::assign(first, last); } - /** Copy constructor from another FastSet */ + /** Copy constructor from another FastVector */ FastVector(const FastVector& x) : Base(x) {} + /** Copy constructor from a FastList */ + FastVector(const FastList& x) { + if(x.size() > 0) + Base::assign(x.begin(), x.end()); + } + + /** Copy constructor from a FastSet */ + FastVector(const FastSet& x) { + if(x.size() > 0) + Base::assign(x.begin(), x.end()); + } + /** Copy constructor from the base class */ FastVector(const Base& x) : Base(x) {} @@ -73,6 +88,11 @@ public: Base::assign(x.begin(), x.end()); } + /** Conversion to a standard STL container */ + operator std::vector() const { + return std::vector(this->begin(), this->end()); + } + private: /** Serialization function */ friend class boost::serialization::access; diff --git a/gtsam/base/LieMatrix.cpp b/gtsam/base/LieMatrix.cpp new file mode 100644 index 000000000..332401689 --- /dev/null +++ b/gtsam/base/LieMatrix.cpp @@ -0,0 +1,36 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file LieMatrix.cpp + * @brief A wrapper around Matrix providing Lie compatibility + * @author Richard Roberts and Alex Cunningham + */ + +#include + +namespace gtsam { + + /* ************************************************************************* */ + LieMatrix::LieMatrix(size_t m, size_t n, ...) + : Matrix(m,n) { + va_list ap; + va_start(ap, n); + for(size_t i = 0; i < m; ++i) { + for(size_t j = 0; j < n; ++j) { + double value = va_arg(ap, double); + (*this)(i,j) = value; + } + } + va_end(ap); + } + +} \ No newline at end of file diff --git a/gtsam/base/LieMatrix.h b/gtsam/base/LieMatrix.h new file mode 100644 index 000000000..5844e8201 --- /dev/null +++ b/gtsam/base/LieMatrix.h @@ -0,0 +1,153 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file LieMatrix.h + * @brief A wrapper around Matrix providing Lie compatibility + * @author Richard Roberts and Alex Cunningham + */ + +#pragma once + +#include + +#include +#include +#include +#include + +namespace gtsam { + +/** + * LieVector is a wrapper around vector to allow it to be a Lie type + */ +struct LieMatrix : public Matrix, public DerivedValue { + + /** default constructor - should be unnecessary */ + LieMatrix() {} + + /** initialize from a normal matrix */ + LieMatrix(const Matrix& v) : Matrix(v) {} + + /** initialize from a fixed size normal vector */ + template + LieMatrix(const Eigen::Matrix& v) : Matrix(v) {} + + /** constructor with size and initial data, row order ! */ + LieMatrix(size_t m, size_t n, const double* const data) : + Matrix(Eigen::Map(data, m, n)) {} + + /** Specify arguments directly, as in Matrix_() - always force these to be doubles */ + LieMatrix(size_t m, size_t n, ...); + + /** get the underlying vector */ + inline Matrix matrix() const { + return static_cast(*this); + } + + /** print @param s optional string naming the object */ + inline void print(const std::string& name="") const { + gtsam::print(matrix(), name); + } + + /** equality up to tolerance */ + inline bool equals(const LieMatrix& expected, double tol=1e-5) const { + return gtsam::equal_with_abs_tol(matrix(), expected.matrix(), tol); + } + + // Manifold requirements + + /** Returns dimensionality of the tangent space */ + inline size_t dim() const { return this->size(); } + + /** Update the LieMatrix with a tangent space update. The elements of the + * tangent space vector correspond to the matrix entries arranged in + * *row-major* order. */ + inline LieMatrix retract(const Vector& v) const { + if(v.size() != this->rows() * this->cols()) + throw std::invalid_argument("LieMatrix::retract called with Vector of incorrect size"); + return LieMatrix(*this + Eigen::Map(&v(0), this->cols(), this->rows()).transpose()); + } + + /** @return the local coordinates of another object. The elements of the + * tangent space vector correspond to the matrix entries arranged in + * *row-major* order. */ + inline Vector localCoordinates(const LieMatrix& t2) const { + Vector result(this->rows() * this->cols()); + Eigen::Map(&result(0), this->cols(), this->rows()).transpose() = + (t2 - *this); + return result; + } + + // Group requirements + + /** identity - NOTE: no known size at compile time - so zero length */ + inline static LieMatrix identity() { + throw std::runtime_error("LieMatrix::identity(): Don't use this function"); + return LieMatrix(); + } + + // Note: Manually specifying the 'gtsam' namespace for the optional Matrix arguments + // This is a work-around for linux g++ 4.6.1 that incorrectly selects the Eigen::Matrix class + // instead of the gtsam::Matrix class. This is related to deriving this class from an Eigen Vector + // as the other geometry objects (Point3, Rot3, etc.) have this problem + /** compose with another object */ + inline LieMatrix compose(const LieMatrix& p, + boost::optional H1=boost::none, + boost::optional H2=boost::none) const { + if(H1) *H1 = eye(dim()); + if(H2) *H2 = eye(p.dim()); + + return LieMatrix(*this + p); + } + + /** between operation */ + inline LieMatrix between(const LieMatrix& l2, + boost::optional H1=boost::none, + boost::optional H2=boost::none) const { + if(H1) *H1 = -eye(dim()); + if(H2) *H2 = eye(l2.dim()); + return LieMatrix(l2 - *this); + } + + /** invert the object and yield a new one */ + inline LieMatrix inverse(boost::optional H=boost::none) const { + if(H) *H = -eye(dim()); + + return LieMatrix(-(*this)); + } + + // Lie functions + + /** Expmap around identity */ + static inline LieMatrix Expmap(const Vector& v) { + throw std::runtime_error("LieMatrix::Expmap(): Don't use this function"); + return LieMatrix(v); } + + /** Logmap around identity - just returns with default cast back */ + static inline Vector Logmap(const LieMatrix& p) { + return Eigen::Map(&p(0,0), p.dim()); } + +private: + + // Serialization function + friend class boost::serialization::access; + template + void serialize(Archive & ar, const unsigned int version) { + ar & boost::serialization::make_nvp("LieMatrix", + boost::serialization::base_object(*this)); + ar & boost::serialization::make_nvp("Matrix", + boost::serialization::base_object(*this)); + + } + +}; +} // \namespace gtsam diff --git a/gtsam/base/LieScalar.h b/gtsam/base/LieScalar.h index 505f06921..3721492ec 100644 --- a/gtsam/base/LieScalar.h +++ b/gtsam/base/LieScalar.h @@ -31,12 +31,15 @@ namespace gtsam { LieScalar() : d_(0.0) {} /** wrap a double */ - LieScalar(double d) : d_(d) {} + explicit LieScalar(double d) : d_(d) {} /** access the underlying value */ double value() const { return d_; } - /** print @param s optional string naming the object */ + /** Automatic conversion to underlying value */ + operator double() const { return d_; } + + /** print @param name optional string naming the object */ inline void print(const std::string& name="") const { std::cout << name << ": " << d_ << std::endl; } diff --git a/gtsam/base/LieVector.cpp b/gtsam/base/LieVector.cpp index 876c8fa6e..d5ae5d504 100644 --- a/gtsam/base/LieVector.cpp +++ b/gtsam/base/LieVector.cpp @@ -15,7 +15,7 @@ * @author Alex Cunningham */ -#include +#include #include using namespace std; diff --git a/gtsam/base/LieVector.h b/gtsam/base/LieVector.h index 82455e173..916730fd3 100644 --- a/gtsam/base/LieVector.h +++ b/gtsam/base/LieVector.h @@ -52,7 +52,7 @@ struct LieVector : public Vector, public DerivedValue { return static_cast(*this); } - /** print @param s optional string naming the object */ + /** print @param name optional string naming the object */ inline void print(const std::string& name="") const { gtsam::print(vector(), name); } @@ -119,5 +119,17 @@ struct LieVector : public Vector, public DerivedValue { /** Logmap around identity - just returns with default cast back */ static inline Vector Logmap(const LieVector& p) { return p; } +private: + + // Serialization function + friend class boost::serialization::access; + template + void serialize(Archive & ar, const unsigned int version) { + ar & boost::serialization::make_nvp("LieVector", + boost::serialization::base_object(*this)); + ar & boost::serialization::make_nvp("Vector", + boost::serialization::base_object(*this)); + } + }; } // \namespace gtsam diff --git a/gtsam/base/Matrix.cpp b/gtsam/base/Matrix.cpp index 849dc3f5a..1369f13b8 100644 --- a/gtsam/base/Matrix.cpp +++ b/gtsam/base/Matrix.cpp @@ -15,9 +15,11 @@ * @author Christian Potthast */ +#include #include #include #include +#include #include #include @@ -25,8 +27,8 @@ #include #include -#include -#include +#include +#include #include #include #include @@ -235,8 +237,41 @@ void save(const Matrix& A, const string &s, const string& filename) { } /* ************************************************************************* */ -void insertSub(Matrix& big, const Matrix& small, size_t i, size_t j) { - big.block(i, j, small.rows(), small.cols()) = small; +istream& operator>>(istream& inputStream, Matrix& destinationMatrix) { + string line; + FastList > coeffs; + bool first = true; + size_t width = 0; + size_t height = 0; + while(getline(inputStream, line)) { + // Read coefficients from file + coeffs.push_back(vector()); + if(!first) + coeffs.back().reserve(width); + stringstream lineStream(line); + std::copy(istream_iterator(lineStream), istream_iterator(), + back_insert_iterator >(coeffs.back())); + if(first) + width = coeffs.back().size(); + if(coeffs.back().size() != width) + throw runtime_error("Error reading matrix from input stream, inconsistent numbers of elements in rows"); + ++ height; + } + + // Copy coefficients to matrix + destinationMatrix.resize(height, width); + int row = 0; + BOOST_FOREACH(const vector& rowVec, coeffs) { + destinationMatrix.row(row) = Eigen::Map(&rowVec[0], width); + ++ row; + } + + return inputStream; +} + +/* ************************************************************************* */ +void insertSub(Matrix& fullMatrix, const Matrix& subMatrix, size_t i, size_t j) { + fullMatrix.block(i, j, subMatrix.rows(), subMatrix.cols()) = subMatrix; } /* ************************************************************************* */ @@ -647,31 +682,21 @@ void svd(const Matrix& A, Matrix& U, Vector& S, Matrix& V) { boost::tuple DLT(const Matrix& A, double rank_tol) { // Check size of A - int m = A.rows(), n = A.cols(); - if (m < n) throw invalid_argument( - "DLT: m svd(A, Eigen::ComputeFullV); + Vector s = svd.singularValues(); + Matrix V = svd.matrixV(); // Find rank int rank = 0; - for (int j = 0; j < n; j++) - if (S(j) > rank_tol) rank++; - // Find minimum singular value and corresponding column index - int min_j = n - 1; - double min_S = S(min_j); - for (int j = 0; j < n - 1; j++) - if (S(j) < min_S) { - min_j = j; - min_S = S(j); - } + for (int j = 0; j < m; j++) + if (s(j) > rank_tol) rank++; - // Return rank, minimum singular value, and corresponding column of V - return boost::tuple(rank, min_S, Vector(column(V, min_j))); + // Return rank, error, and corresponding column of V + double error = m

(rank, error, Vector(column(V, p-1))); } /* ************************************************************************* */ diff --git a/gtsam/base/Matrix.h b/gtsam/base/Matrix.h index 3a70d9b76..e6a40f727 100644 --- a/gtsam/base/Matrix.h +++ b/gtsam/base/Matrix.h @@ -26,6 +26,7 @@ #include #include #include +#include /** * Matrix is a typedef in the gtsam namespace @@ -66,11 +67,30 @@ inline Matrix Matrix_(const Vector& v) { return Matrix_(v.size(),1,v);} */ Matrix Matrix_(size_t m, size_t n, ...); +// Matlab-like syntax + /** - * MATLAB like constructors + * Creates an zeros matrix, with matlab-like syntax + * + * Note: if assigning a block (created from an Eigen block() function) of a matrix to zeros, + * don't use this function, instead use ".setZero(m,n)" to avoid an Eigen error. */ Matrix zeros(size_t m, size_t n); + +/** + * Creates an identity matrix, with matlab-like syntax + * + * Note: if assigning a block (created from an Eigen block() function) of a matrix to identity, + * don't use this function, instead use ".setIdentity(m,n)" to avoid an Eigen error. + */ Matrix eye(size_t m, size_t n); + +/** + * Creates a square identity matrix, with matlab-like syntax + * + * Note: if assigning a block (created from an Eigen block() function) of a matrix to identity, + * don't use this function, instead use ".setIdentity(m)" to avoid an Eigen error. + */ inline Matrix eye( size_t m ) { return eye(m,m); } Matrix diag(const Vector& v); @@ -87,7 +107,7 @@ bool equal_with_abs_tol(const Eigen::DenseBase& A, const Eigen::DenseBas for(size_t i=0; i tol) return false; @@ -182,6 +202,13 @@ void print(const Matrix& A, const std::string& s = "", std::ostream& stream = st */ void save(const Matrix& A, const std::string &s, const std::string& filename); +/** + * Read a matrix from an input stream, such as a file. Entries can be either + * tab-, space-, or comma-separated, similar to the format read by the MATLAB + * dlmread command. + */ +std::istream& operator>>(std::istream& inputStream, Matrix& destinationMatrix); + /** * extract submatrix, slice semantics, i.e. range = [i1,i2[ excluding i2 * @param A matrix @@ -200,17 +227,17 @@ Eigen::Block sub(const MATRIX& A, size_t i1, size_t i2, size_t j1, /** * insert a submatrix IN PLACE at a specified location in a larger matrix * NOTE: there is no size checking - * @param large matrix to be updated - * @param small matrix to be inserted + * @param fullMatrix matrix to be updated + * @param subMatrix matrix to be inserted * @param i is the row of the upper left corner insert location * @param j is the column of the upper left corner insert location */ -void insertSub(Matrix& big, const Matrix& small, size_t i, size_t j); +void insertSub(Matrix& fullMatrix, const Matrix& subMatrix, size_t i, size_t j); /** * Extracts a column view from a matrix that avoids a copy - * @param matrix to extract column from - * @param index of the column + * @param A matrix to extract column from + * @param j index of the column * @return a const view of the matrix */ template @@ -220,8 +247,8 @@ const typename MATRIX::ConstColXpr column(const MATRIX& A, size_t j) { /** * Extracts a row view from a matrix that avoids a copy - * @param matrix to extract row from - * @param index of the row + * @param A matrix to extract row from + * @param j index of the row * @return a const view of the matrix */ template @@ -285,7 +312,7 @@ std::pair qr(const Matrix& A); * @param clear_below_diagonal enables zeroing out below diagonal */ template -void inplace_QR(MATRIX& A, bool clear_below_diagonal=true) { +void inplace_QR(MATRIX& A) { size_t rows = A.rows(); size_t cols = A.cols(); size_t size = std::min(rows,cols); @@ -354,7 +381,7 @@ Vector backSubstituteUpper(const Vector& b, const Matrix& U, bool unit=false); * @param unit, set true if unit triangular * @return the solution x of L*x=b */ -Vector backSubstituteLower(const Matrix& L, const Vector& d, bool unit=false); +Vector backSubstituteLower(const Matrix& L, const Vector& b, bool unit=false); /** * create a matrix by stacking other matrices diff --git a/gtsam/base/Testable.h b/gtsam/base/Testable.h index bcc6c8957..009d286db 100644 --- a/gtsam/base/Testable.h +++ b/gtsam/base/Testable.h @@ -46,7 +46,7 @@ namespace gtsam { * tests and in generic algorithms. * * See macros for details on using this structure - * @ingroup base + * @addtogroup base * @tparam T is the type this constrains to be testable - assumes print() and equals() */ template diff --git a/gtsam/base/TestableAssertions.h b/gtsam/base/TestableAssertions.h index dad1c6d20..00ab79d30 100644 --- a/gtsam/base/TestableAssertions.h +++ b/gtsam/base/TestableAssertions.h @@ -30,7 +30,7 @@ namespace gtsam { /** * Equals testing for basic types */ -bool assert_equal(const Index& expected, const Index& actual, double tol = 0.0) { +inline bool assert_equal(const Index& expected, const Index& actual, double tol = 0.0) { if(expected != actual) { std::cout << "Not equal:\nexpected: " << expected << "\nactual: " << actual << std::endl; return false; @@ -81,7 +81,7 @@ bool assert_equal(const V& expected, const boost::optional& actual, do /** * Version of assert_equals to work with vectors - * @DEPRECIATED: use container equals instead + * \deprecated: use container equals instead */ template bool assert_equal(const std::vector& expected, const std::vector& actual, double tol = 1e-9) { @@ -327,7 +327,7 @@ bool assert_container_equality(const V& expected, const V& actual) { /** * Compare strings for unit tests */ -bool assert_equal(const std::string& expected, const std::string& actual) { +inline bool assert_equal(const std::string& expected, const std::string& actual) { if (expected == actual) return true; printf("Not equal:\n"); diff --git a/gtsam/base/Value.h b/gtsam/base/Value.h index 394a11e72..8b19a6532 100644 --- a/gtsam/base/Value.h +++ b/gtsam/base/Value.h @@ -101,12 +101,15 @@ namespace gtsam { class Value { public: - /** Allocate and construct a clone of this value */ + /** Clone this value in a special memory pool, must be deleted with Value::deallocate_, *not* with the 'delete' operator. */ virtual Value* clone_() const = 0; /** Deallocate a raw pointer of this value */ virtual void deallocate_() const = 0; + /** Clone this value (normal clone on the heap, delete with 'delete' operator) */ + virtual boost::shared_ptr clone() const = 0; + /** Compare this Value with another for equality. */ virtual bool equals_(const Value& other, double tol = 1e-9) const = 0; diff --git a/gtsam/base/Vector.cpp b/gtsam/base/Vector.cpp index 27b56830c..a7e8f2769 100644 --- a/gtsam/base/Vector.cpp +++ b/gtsam/base/Vector.cpp @@ -16,30 +16,27 @@ * @author Frank Dellaert */ -#include +#include #include #include #include #include #include #include +#include #include #include -#include - -#ifdef WIN32 -#include -#endif - -#include -#include +#include #include +#include + +//#ifdef WIN32 +//#include +//#endif using namespace std; -boost::minstd_rand generator(42u); - namespace gtsam { /* ************************************************************************* */ @@ -55,11 +52,11 @@ void odprintf_(const char *format, ostream& stream, ...) { #endif va_end(args); -#ifdef WIN32 - OutputDebugString(buf); -#else +//#ifdef WIN32 +// OutputDebugString(buf); +//#else stream << buf; -#endif +//#endif } /* ************************************************************************* */ @@ -76,11 +73,11 @@ void odprintf(const char *format, ...) { #endif va_end(args); -#ifdef WIN32 - OutputDebugString(buf); -#else +//#ifdef WIN32 +// OutputDebugString(buf); +//#else cout << buf; -#endif +//#endif } /* ************************************************************************* */ @@ -169,7 +166,7 @@ bool equal_with_abs_tol(const Vector& vec1, const Vector& vec2, double tol) { if (vec1.size()!=vec2.size()) return false; size_t m = vec1.size(); for(size_t i=0; i tol) return false; @@ -182,7 +179,7 @@ bool equal_with_abs_tol(const SubVector& vec1, const SubVector& vec2, double tol if (vec1.size()!=vec2.size()) return false; size_t m = vec1.size(); for(size_t i=0; i tol) return false; @@ -250,8 +247,8 @@ ConstSubVector sub(const Vector &v, size_t i1, size_t i2) { } /* ************************************************************************* */ -void subInsert(Vector& big, const Vector& small, size_t i) { - big.segment(i, small.size()) = small; +void subInsert(Vector& fullVector, const Vector& subVector, size_t i) { + fullVector.segment(i, subVector.size()) = subVector; } /* ************************************************************************* */ @@ -431,19 +428,6 @@ Vector concatVectors(size_t nrVectors, ...) return concatVectors(vs); } -/* ************************************************************************* */ -Vector rand_vector_norm(size_t dim, double mean, double sigma) -{ - boost::normal_distribution norm_dist(mean, sigma); - boost::variate_generator > norm(generator, norm_dist); - - Vector v(dim); - for(int i = 0; i #include -#include -#include - -/** - * Static random number generator - needs to maintain a state - * over time, hence the static generator. Be careful in - * cases where multiple processes (as is frequently the case with - * multi-robot scenarios) are using the sample() facilities - * in NoiseModel, as they will each have the same seed. - */ -// FIXME: make this go away - use the Sampler class instead -extern boost::minstd_rand generator; +#include +#include +#include namespace gtsam { @@ -72,8 +63,8 @@ Vector Vector_(const std::vector& data); /** * Create vector initialized to a constant value - * @param size - * @param constant value + * @param n is the size of the vector + * @param value is a constant value to insert into the vector */ Vector repeat(size_t n, double value); @@ -81,7 +72,7 @@ Vector repeat(size_t n, double value); * Create basis vector of dimension n, * with a constant in spot i * @param n is the size of the vector - * @param index of the one + * @param i index of the one * @param value is the value to insert into the vector * @return delta vector */ @@ -91,20 +82,20 @@ Vector delta(size_t n, size_t i, double value); * Create basis vector of dimension n, * with one in spot i * @param n is the size of the vector - * @param index of the one + * @param i index of the one * @return basis vector */ inline Vector basis(size_t n, size_t i) { return delta(n, i, 1.0); } /** * Create zero vector - * @param size + * @param n size */ inline Vector zero(size_t n) { return Vector::Zero(n);} /** * Create vector initialized to ones - * @param size + * @param n size */ inline Vector ones(size_t n) { return Vector::Ones(n); } @@ -208,11 +199,11 @@ ConstSubVector sub(const Vector &v, size_t i1, size_t i2); /** * Inserts a subvector into a vector IN PLACE - * @param big is the vector to be changed - * @param small is the vector to insert + * @param fullVector is the vector to be changed + * @param subVector is the vector to insert * @param i is the index where the subvector should be inserted */ -void subInsert(Vector& big, const Vector& small, size_t i); +void subInsert(Vector& fullVector, const Vector& subVector, size_t i); /** * elementwise multiplication @@ -248,35 +239,35 @@ double sum(const Vector &a); /** * Calculates L2 norm for a vector * modeled after boost.ublas for compatibility - * @param vector + * @param v vector * @return the L2 norm */ double norm_2(const Vector& v); /** - * elementwise reciprocal of vector elements + * Elementwise reciprocal of vector elements * @param a vector * @return [1/a(i)] */ Vector reciprocal(const Vector &a); /** - * elementwise sqrt of vector elements - * @param a vector + * Elementwise sqrt of vector elements + * @param v is a vector * @return [sqrt(a(i))] */ Vector esqrt(const Vector& v); /** - * absolut values of vector elements - * @param a vector + * Absolute values of vector elements + * @param v is a vector * @return [abs(a(i))] */ Vector abs(const Vector& v); /** - * return the max element of a vector - * @param a vector + * Return the max element of a vector + * @param a is a vector * @return max(a) */ double max(const Vector &a); @@ -299,13 +290,13 @@ inline double inner_prod(const V1 &a, const V2& b) { /** * BLAS Level 1 scal: x <- alpha*x - * @DEPRECIATED: use operators instead + * \deprecated: use operators instead */ inline void scal(double alpha, Vector& x) { x *= alpha; } /** * BLAS Level 1 axpy: y <- alpha*x + y - * @DEPRECIATED: use operators instead + * \deprecated: use operators instead */ template inline void axpy(double alpha, const V1& x, V2& y) { @@ -357,20 +348,6 @@ Vector concatVectors(const std::list& vs); */ Vector concatVectors(size_t nrVectors, ...); -/** - * random vector - */ -Vector rand_vector_norm(size_t dim, double mean = 0, double sigma = 1); - -/** - * Sets the generator to use a different seed value. - * Default argument resets the RNG - * @param seed is the new seed - */ -inline void seedRNG(unsigned int seed = 42u) { - generator.seed(seed); -} - } // namespace gtsam #include diff --git a/gtsam/base/blockMatrices.h b/gtsam/base/blockMatrices.h index a1baecd76..c0bc95a50 100644 --- a/gtsam/base/blockMatrices.h +++ b/gtsam/base/blockMatrices.h @@ -40,7 +40,7 @@ template class SymmetricBlockView; * all rows, rowEnd() should be set to the number of rows in the matrix (i.e. * one after the last true row index). * - * @ingroup base + * @addtogroup base */ template class VerticalBlockView { @@ -330,7 +330,7 @@ private: * change the apparent matrix view. firstBlock() determines the block that * appears to have index 0 for all operations (except re-setting firstBlock()). * - * @ingroup base + * @addtogroup base */ template class SymmetricBlockView { diff --git a/gtsam/base/cholesky.cpp b/gtsam/base/cholesky.cpp index 66bbbde55..e941082ae 100644 --- a/gtsam/base/cholesky.cpp +++ b/gtsam/base/cholesky.cpp @@ -24,7 +24,7 @@ #include #include -#include +#include using namespace std; @@ -33,19 +33,23 @@ namespace gtsam { static const double negativePivotThreshold = -1e-1; static const double zeroPivotThreshold = 1e-6; static const double underconstrainedPrior = 1e-5; - static const bool dampUnderconstrained = false; + static const int underconstrainedExponentDifference = 12; /* ************************************************************************* */ -static inline bool choleskyStep(Matrix& ATA, size_t k, size_t order) { +static inline int choleskyStep(Matrix& ATA, size_t k, size_t order) { + + const bool debug = ISDEBUG("choleskyCareful"); // Get pivot value double alpha = ATA(k,k); // Correct negative pivots from round-off error if(alpha < negativePivotThreshold) { - cout << "pivot = " << alpha << endl; - print(ATA, "Partially-factorized matrix: "); - throw(CarefulCholeskyNegativeMatrixException()); + if(debug) { + cout << "pivot = " << alpha << endl; + print(ATA, "Partially-factorized matrix: "); + } + return -1; } else if(alpha < 0.0) alpha = 0.0; @@ -68,14 +72,14 @@ static inline bool choleskyStep(Matrix& ATA, size_t k, size_t order) { // ATA.bottomRightCorner(order-(k+1), order-(k+1)).selfadjointView() // .rankUpdate(V.adjoint(), -1); } - - return true; + return 1; } else { // For zero pivots, add the underconstrained variable prior ATA(k,k) = underconstrainedPrior; for(size_t j=k+1; j choleskyCareful(Matrix& ATA, int order) { // Negative order means factor the entire matrix if(order < 0) - order = n; + order = int(n); assert(size_t(order) <= n); // The index of the row after the last non-zero row of the square-root factor size_t maxrank = 0; - bool fullRank = true; + bool success = true; // Factor row-by-row for(size_t k = 0; k < size_t(order); ++k) { - if(choleskyStep(ATA, k, size_t(order))) { + int stepResult = choleskyStep(ATA, k, size_t(order)); + if(stepResult == 1) { if(debug) cout << "choleskyCareful: Factored through " << k << endl; if(debug) print(ATA, "ATA: "); maxrank = k+1; - } else { - fullRank = false; - if(debug) cout << "choleskyCareful: Skipping " << k << endl; - } + } else if(stepResult == -1) { + success = false; + break; + } /* else if(stepResult == 0) Found zero pivot */ } - return make_pair(maxrank, fullRank); + return make_pair(maxrank, success); } /* ************************************************************************* */ -void choleskyPartial(Matrix& ABC, size_t nFrontal) { +bool choleskyPartial(Matrix& ABC, size_t nFrontal) { const bool debug = ISDEBUG("choleskyPartial"); @@ -127,9 +132,8 @@ void choleskyPartial(Matrix& ABC, size_t nFrontal) { // Compute Cholesky factorization of A, overwrites A. tic(1, "lld"); - ABC.block(0,0,nFrontal,nFrontal).triangularView() = - ABC.block(0,0,nFrontal,nFrontal).selfadjointView().llt().matrixU(); - assert(ABC.topLeftCorner(nFrontal,nFrontal).triangularView().toDenseMatrix().unaryExpr(&isfinite).all()); + Eigen::LLT llt = ABC.block(0,0,nFrontal,nFrontal).selfadjointView().llt(); + ABC.block(0,0,nFrontal,nFrontal).triangularView() = llt.matrixU(); toc(1, "lld"); if(debug) cout << "R:\n" << Eigen::MatrixXd(ABC.topLeftCorner(nFrontal,nFrontal).triangularView()) << endl; @@ -140,7 +144,6 @@ void choleskyPartial(Matrix& ABC, size_t nFrontal) { ABC.topLeftCorner(nFrontal,nFrontal).triangularView().transpose().solveInPlace( ABC.topRightCorner(nFrontal, n-nFrontal)); } - assert(ABC.topRightCorner(nFrontal, n-nFrontal).unaryExpr(&isfinite).all()); if(debug) cout << "S:\n" << ABC.topRightCorner(nFrontal, n-nFrontal) << endl; toc(2, "compute S"); @@ -150,9 +153,29 @@ void choleskyPartial(Matrix& ABC, size_t nFrontal) { if(n - nFrontal > 0) ABC.bottomRightCorner(n-nFrontal,n-nFrontal).selfadjointView().rankUpdate( ABC.topRightCorner(nFrontal, n-nFrontal).transpose(), -1.0); - assert(ABC.bottomRightCorner(n-nFrontal,n-nFrontal).selfadjointView().toDenseMatrix().unaryExpr(&isfinite).all()); if(debug) cout << "L:\n" << Eigen::MatrixXd(ABC.bottomRightCorner(n-nFrontal,n-nFrontal).selfadjointView()) << endl; toc(3, "compute L"); + + // Check last diagonal element - Eigen does not check it + bool ok; + if(llt.info() == Eigen::Success) { + if(nFrontal >= 2) { + int exp2, exp1; + (void)frexp(ABC(nFrontal-2, nFrontal-2), &exp2); + (void)frexp(ABC(nFrontal-1, nFrontal-1), &exp1); + ok = (exp2 - exp1 < underconstrainedExponentDifference); + } else if(nFrontal == 1) { + int exp1; + (void)frexp(ABC(0,0), &exp1); + ok = (exp1 > -underconstrainedExponentDifference); + } else { + ok = true; + } + } else { + ok = false; + } + + return ok; } } diff --git a/gtsam/base/cholesky.h b/gtsam/base/cholesky.h index 50d3b24a8..8b1073107 100644 --- a/gtsam/base/cholesky.h +++ b/gtsam/base/cholesky.h @@ -22,45 +22,6 @@ namespace gtsam { -/** - * An exception indicating an attempt to factor a negative or indefinite matrix. - * If detailed exceptions are enabled, then the \c detail member will contain - * the matrices leading to the problem, see documentation for - * NegativeMatrixException::Detail. - */ -struct NegativeMatrixException : public std::exception { - /// Detail for NegativeMatrixException - struct Detail { - Matrix A; ///< The original matrix attempted to factor - Matrix U; ///< The produced upper-triangular factor - Matrix D; ///< The produced diagonal factor - Detail(const Matrix& _A, const Matrix& _U, const Matrix& _D) /**< Detail constructor */ : A(_A), U(_U), D(_D) {} - void print(const std::string& str = "") const { - std::cout << str << "\n"; - gtsam::print(A, " A: "); - gtsam::print(U, " U: "); - gtsam::print(D, " D: "); - } - }; - const boost::shared_ptr detail; ///< Detail - NegativeMatrixException() /**< Constructor with no detail */ {} - NegativeMatrixException(const Detail& _detail) /**< Constructor with detail */ : detail(new Detail(_detail)) {} - NegativeMatrixException(const boost::shared_ptr& _detail) /**< Constructor with detail */ : detail(_detail) {} - virtual ~NegativeMatrixException() throw() {} -}; - -/** - * An exception indicating an attempt to factor a negative or indefinite matrix. - * If detailed exceptions are enabled, then the \c detail member will contain - * the matrices leading to the problem, see documentation for - * CarefulCholeskyNegativeMatrixException::Detail. - */ -struct CarefulCholeskyNegativeMatrixException : public std::exception { - CarefulCholeskyNegativeMatrixException() throw() {} - virtual ~CarefulCholeskyNegativeMatrixException() throw() {} - const char* what() const throw() { return "The matrix was found to be non-positive-semidefinite when factoring with careful Cholesky."; } -}; - /** * "Careful" Cholesky computes the positive square-root of a positive symmetric * semi-definite matrix (i.e. that may be rank-deficient). Unlike standard @@ -70,6 +31,10 @@ struct CarefulCholeskyNegativeMatrixException : public std::exception { * non-zero row in the computed factor, so that it may be truncated to an * upper-trapazoidal matrix. * + * The second element of the return value is \c true if the matrix was factored + * successfully, or \c false if it was non-positive-semidefinite (i.e. + * indefinite or negative-(semi-)definite. + * * Note that this returned index is the rank of the matrix if and only if all * of the zero-rows of the factor occur after any non-zero rows. This is * (always?) the case during elimination of a fully-constrained least-squares @@ -77,6 +42,8 @@ struct CarefulCholeskyNegativeMatrixException : public std::exception { * * The optional order argument specifies the size of the square upper-left * submatrix to operate on, ignoring the rest of the matrix. + * + * */ std::pair choleskyCareful(Matrix& ATA, int order = -1); @@ -87,8 +54,11 @@ std::pair choleskyCareful(Matrix& ATA, int order = -1); * [B' C] * nFrontal determines the split between A, B, and C, with A being of size * nFrontal x nFrontal. + * + * @return \c true if the decomposition is successful, \c false if \c A was + * not positive-definite. */ -void choleskyPartial(Matrix& ABC, size_t nFrontal); +bool choleskyPartial(Matrix& ABC, size_t nFrontal); } diff --git a/gtsam/base/tests/testCholesky.cpp b/gtsam/base/tests/testCholesky.cpp index 63fdec810..8e8da7a70 100644 --- a/gtsam/base/tests/testCholesky.cpp +++ b/gtsam/base/tests/testCholesky.cpp @@ -81,7 +81,47 @@ TEST(cholesky, BadScalingSVD) { double expectedCondition = 1e40; double actualCondition = S(0) / S(1); - DOUBLES_EQUAL(expectedCondition, actualCondition, 1e-41); + DOUBLES_EQUAL(expectedCondition, actualCondition, 1e30); +} + +/* ************************************************************************* */ +TEST(cholesky, underconstrained) { + Matrix L(6,6); L << + 1, 0, 0, 0, 0, 0, + 1.11177808157954, 1.06204809504665, 0.507342638873381, 1.34953401829486, 1, 0, + 0.155864888199928, 1.10933048588373, 0.501255576961674, 1, 0, 0, + 1.12108665967793, 1.01584408366945, 1, 0, 0, 0, + 0.776164062474843, 0.117617236580373, -0.0236628691347294, 0.814118199972143, 0.694309975328922, 1, + 0.1197220685104, 1, 0, 0, 0, 0; + Matrix D1(6,6); D1 << + 0.814723686393179, 0, 0, 0, 0, 0, + 0, 0.811780089277421, 0, 0, 0, 0, + 0, 0, 1.82596950680844, 0, 0, 0, + 0, 0, 0, 0.240287537694585, 0, 0, + 0, 0, 0, 0, 1.34342584865901, 0, + 0, 0, 0, 0, 0, 1e-12; + Matrix D2(6,6); D2 << + 0.814723686393179, 0, 0, 0, 0, 0, + 0, 0.811780089277421, 0, 0, 0, 0, + 0, 0, 1.82596950680844, 0, 0, 0, + 0, 0, 0, 0.240287537694585, 0, 0, + 0, 0, 0, 0, 0, 0, + 0, 0, 0, 0, 0, 0; + Matrix D3(6,6); D3 << + 0.814723686393179, 0, 0, 0, 0, 0, + 0, 0.811780089277421, 0, 0, 0, 0, + 0, 0, 1.82596950680844, 0, 0, 0, + 0, 0, 0, 0.240287537694585, 0, 0, + 0, 0, 0, 0, -0.5, 0, + 0, 0, 0, 0, 0, -0.6; + + Matrix A1 = L * D1 * L.transpose(); + Matrix A2 = L * D2 * L.transpose(); + Matrix A3 = L * D3 * L.transpose(); + + LONGS_EQUAL(long(false), long(choleskyPartial(A1, 6))); + LONGS_EQUAL(long(false), long(choleskyPartial(A2, 6))); + LONGS_EQUAL(long(false), long(choleskyPartial(A3, 6))); } /* ************************************************************************* */ diff --git a/gtsam_unstable/base/tests/testDSFVector.cpp b/gtsam/base/tests/testDSFVector.cpp similarity index 99% rename from gtsam_unstable/base/tests/testDSFVector.cpp rename to gtsam/base/tests/testDSFVector.cpp index 8997559f5..c0b72f1a0 100644 --- a/gtsam_unstable/base/tests/testDSFVector.cpp +++ b/gtsam/base/tests/testDSFVector.cpp @@ -24,7 +24,7 @@ using namespace boost::assign; #include -#include +#include using namespace std; using namespace gtsam; diff --git a/gtsam/base/tests/testDebug.cpp b/gtsam/base/tests/testDebug.cpp index f399dcb3b..81e4f039b 100644 --- a/gtsam/base/tests/testDebug.cpp +++ b/gtsam/base/tests/testDebug.cpp @@ -17,6 +17,7 @@ #include +#undef NDEBUG #define NDEBUG #undef GTSAM_ENABLE_DEBUG #include diff --git a/gtsam/base/tests/testLieMatrix.cpp b/gtsam/base/tests/testLieMatrix.cpp new file mode 100644 index 000000000..aad28563c --- /dev/null +++ b/gtsam/base/tests/testLieMatrix.cpp @@ -0,0 +1,70 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file testLieMatrix.cpp + * @author Richard Roberts + */ + +#include + +#include +#include +#include + +using namespace gtsam; + +GTSAM_CONCEPT_TESTABLE_INST(LieMatrix) +GTSAM_CONCEPT_LIE_INST(LieMatrix) + +/* ************************************************************************* */ +TEST( LieMatrix, construction ) { + Matrix m = Matrix_(2,2, 1.0, 2.0, 3.0, 4.0); + LieMatrix lie1(m), lie2(m); + + EXPECT(lie1.dim() == 4); + EXPECT(assert_equal(m, lie1.matrix())); + EXPECT(assert_equal(lie1, lie2)); +} + +/* ************************************************************************* */ +TEST( LieMatrix, other_constructors ) { + Matrix init = Matrix_(2,2, 10.0, 20.0, 30.0, 40.0); + LieMatrix exp(init); + LieMatrix a(2,2,10.0,20.0,30.0,40.0); + double data[] = {10,30,20,40}; + LieMatrix b(2,2,data); + EXPECT(assert_equal(exp, a)); + EXPECT(assert_equal(exp, b)); + EXPECT(assert_equal(b, a)); +} + +/* ************************************************************************* */ +TEST(LieMatrix, retract) { + LieMatrix init(2,2, 1.0,2.0,3.0,4.0); + Vector update = Vector_(4, 3.0, 4.0, 6.0, 7.0); + + LieMatrix expected(2,2, 4.0, 6.0, 9.0, 11.0); + LieMatrix actual = init.retract(update); + + EXPECT(assert_equal(expected, actual)); + + LieMatrix expectedUpdate = update; + LieMatrix actualUpdate = init.localCoordinates(actual); + + EXPECT(assert_equal(expectedUpdate, actualUpdate)); +} + +/* ************************************************************************* */ +int main() { TestResult tr; return TestRegistry::runAllTests(tr); } +/* ************************************************************************* */ + + diff --git a/gtsam/base/tests/testMatrix.cpp b/gtsam/base/tests/testMatrix.cpp index ad6742613..56be42c02 100644 --- a/gtsam/base/tests/testMatrix.cpp +++ b/gtsam/base/tests/testMatrix.cpp @@ -17,6 +17,7 @@ **/ #include +#include #include #include #include @@ -261,6 +262,26 @@ TEST( matrix, insert_sub ) EXPECT(assert_equal(expected, big)); } +/* ************************************************************************* */ +TEST( matrix, stream_read ) { + Matrix expected = Matrix_(3,4, + 1.1, 2.3, 4.2, 7.6, + -0.3, -8e-2, 5.1, 9.0, + 1.2, 3.4, 4.5, 6.7); + + string matrixAsString = + "1.1 2.3 4.2 7.6\n" + "-0.3 -8e-2 5.1 9.0\n\r" // Test extra spaces and windows newlines + "1.2 \t 3.4 4.5 6.7"; // Test tab as separator + + stringstream asStream(matrixAsString, ios::in); + + Matrix actual; + asStream >> actual; + + EXPECT(assert_equal(expected, actual)); +} + /* ************************************************************************* */ TEST( matrix, scale_columns ) { @@ -1052,32 +1073,55 @@ TEST( matrix, svd3 ) /* ************************************************************************* */ TEST( matrix, svd4 ) { - Matrix U, V; - Vector s; + Matrix U, V; + Vector s; - Matrix A = Matrix_(3,2, - 0.8147, 0.9134, - 0.9058, 0.6324, - 0.1270, 0.0975); + Matrix A = Matrix_(3,2, + 0.8147, 0.9134, + 0.9058, 0.6324, + 0.1270, 0.0975); - Matrix expectedU = Matrix_(3,2, - 0.7397, 0.6724, - 0.6659, -0.7370, - 0.0970, -0.0689); + Matrix expectedU = Matrix_(3,2, + 0.7397, 0.6724, + 0.6659, -0.7370, + 0.0970, -0.0689); - Vector expected_s = Vector_(2, 1.6455, 0.1910); + Vector expected_s = Vector_(2, 1.6455, 0.1910); - Matrix expectedV = Matrix_(2,2, - 0.7403, -0.6723, - 0.6723, 0.7403); + Matrix expectedV = Matrix_(2,2, + 0.7403, -0.6723, + 0.6723, 0.7403); - svd(A, U, s, V); - Matrix reconstructed = U * diag(s) * trans(V); + svd(A, U, s, V); + Matrix reconstructed = U * diag(s) * trans(V); - EXPECT(assert_equal(A, reconstructed, 1e-4)); - EXPECT(assert_equal(expectedU,U, 1e-3)); - EXPECT(assert_equal(expected_s,s, 1e-4)); - EXPECT(assert_equal(expectedV,V, 1e-4)); + EXPECT(assert_equal(A, reconstructed, 1e-4)); + EXPECT(assert_equal(expectedU,U, 1e-3)); + EXPECT(assert_equal(expected_s,s, 1e-4)); + EXPECT(assert_equal(expectedV,V, 1e-4)); +} + +/* ************************************************************************* */ +TEST( matrix, DLT ) +{ + Matrix A = Matrix_(8,9, + 0.21, -0.42, -10.71, 0.18, -0.36, -9.18, -0.61, 1.22, 31.11, + 0.44, -0.66, -15.84, 0.34, -0.51, -12.24, -1.64, 2.46, 59.04, + 0.69, -8.28, -12.19, -0.48, 5.76, 8.48, -1.89, 22.68, 33.39, + 0.96, -8.4, -17.76, -0.6, 5.25, 11.1, -3.36, 29.4, 62.16, + 1.25, 0.3, 2.75, -3.5, -0.84, -7.7, 16.25, 3.9, 35.75, + 1.56, 0.42, 4.56, -3.38, -0.91, -9.88, 22.36, 6.02, 65.36, + 1.89, 2.24, 3.99, 3.24, 3.84, 6.84, 18.09, 21.44, 38.19, + 2.24, 2.48, 6.24, 3.08, 3.41, 8.58, 24.64, 27.28, 68.64 + ); + int rank; + double error; + Vector actual; + boost::tie(rank,error,actual) = DLT(A); + Vector expected = Vector_(9, -0.0, 0.2357, 0.4714, -0.2357, 0.0, - 0.4714,-0.4714, 0.4714, 0.0); + EXPECT_LONGS_EQUAL(8,rank); + EXPECT_DOUBLES_EQUAL(0,error,1e-8); + EXPECT(assert_equal(expected, actual, 1e-4)); } /* ************************************************************************* */ diff --git a/gtsam/base/tests/testVector.cpp b/gtsam/base/tests/testVector.cpp index 8b8757027..b8bb0333b 100644 --- a/gtsam/base/tests/testVector.cpp +++ b/gtsam/base/tests/testVector.cpp @@ -251,7 +251,7 @@ TEST( TestVector, axpy ) /* ************************************************************************* */ TEST( TestVector, equals ) { - Vector v1 = Vector_(1, 0.0/0.0); //testing nan + Vector v1 = Vector_(1, 0.0/std::numeric_limits::quiet_NaN()); //testing nan Vector v2 = Vector_(1, 1.0); double tol = 1.; EXPECT(!equal_with_abs_tol(v1, v2, tol)); @@ -297,27 +297,6 @@ TEST( TestVector, linear_dependent3 ) EXPECT(!linear_dependent(v1, v2)); } -/* ************************************************************************* */ -TEST( TestVector, random ) -{ - // Assumes seed not previously reset during this test - seedRNG(); - Vector v1_42 = rand_vector_norm(5); - - // verify that resetting the RNG produces the same value - seedRNG(); - Vector v2_42 = rand_vector_norm(5); - - EXPECT(assert_equal(v1_42, v2_42, 1e-6)); - - // verify that different seed produces a different value - seedRNG(41u); - - Vector v3_41 = rand_vector_norm(5); - - EXPECT(assert_inequal(v1_42, v3_41, 1e-6)); -} - /* ************************************************************************* */ int main() { TestResult tr; return TestRegistry::runAllTests(tr); } /* ************************************************************************* */ diff --git a/gtsam/base/tests/timeVirtual.cpp b/gtsam/base/tests/timeVirtual.cpp index a61ce7b77..697a219b1 100644 --- a/gtsam/base/tests/timeVirtual.cpp +++ b/gtsam/base/tests/timeVirtual.cpp @@ -87,13 +87,13 @@ int main(int argc, char *argv[]) { tic_("shared plain alloc, dealloc"); for(size_t i=0; i obj(new Plain(i)); + boost::shared_ptr obj(new Plain(i)); } toc_("shared plain alloc, dealloc"); tic_("shared virtual alloc, dealloc"); for(size_t i=0; i obj(new Virtual(i)); + boost::shared_ptr obj(new Virtual(i)); } toc_("shared virtual alloc, dealloc"); @@ -130,14 +130,14 @@ int main(int argc, char *argv[]) { tic_("shared plain alloc, dealloc, call"); for(size_t i=0; i obj(new Plain(i)); + boost::shared_ptr obj(new Plain(i)); obj->setData(i+1); } toc_("shared plain alloc, dealloc, call"); tic_("shared virtual alloc, dealloc, call"); for(size_t i=0; i obj(new Virtual(i)); + boost::shared_ptr obj(new Virtual(i)); obj->setData(i+1); } toc_("shared virtual alloc, dealloc, call"); diff --git a/gtsam/base/timing.cpp b/gtsam/base/timing.cpp index 1388c2f18..162a1306f 100644 --- a/gtsam/base/timing.cpp +++ b/gtsam/base/timing.cpp @@ -20,7 +20,6 @@ #include #include #include -#include #include #include #include @@ -31,7 +30,9 @@ boost::shared_ptr timingRoot(new TimingOutline("Total")); boost::weak_ptr timingCurrent(timingRoot); +#ifdef ENABLE_OLD_TIMING Timing timing; +#endif std::string timingPrefix; /* ************************************************************************* */ @@ -48,7 +49,7 @@ void TimingOutline::add(size_t usecs) { /* ************************************************************************* */ TimingOutline::TimingOutline(const std::string& label) : - t_(0), t2_(0.0), tIt_(0), tMax_(0), tMin_(0), n_(0), label_(label), timerActive_(false) {} + t_(0), t2_(0.0), tIt_(0), tMax_(0), tMin_(0), n_(0), label_(label) {} /* ************************************************************************* */ size_t TimingOutline::time() const { @@ -151,18 +152,28 @@ const boost::shared_ptr& TimingOutline::child(size_t child, const /* ************************************************************************* */ void TimingOutline::tic() { +#ifdef GTSAM_USING_NEW_BOOST_TIMERS + assert(timer_.is_stopped()); + timer_.start(); +#else assert(!timerActive_); - timerActive_ = true; - gettimeofday(&t0_, NULL); + timer_.restart(); + *timerActive_ = true; +#endif } /* ************************************************************************* */ void TimingOutline::toc() { - struct timeval t; - gettimeofday(&t, NULL); - assert(timerActive_); - add(t.tv_sec*1000000 + t.tv_usec - (t0_.tv_sec*1000000 + t0_.tv_usec)); - timerActive_ = false; +#ifdef GTSAM_USING_NEW_BOOST_TIMERS + assert(!timer_.is_stopped()); + timer_.stop(); + add((timer_.elapsed().user + timer_.elapsed().system) / 1000); +#else + assert(timerActive_); + double elapsed = timer_.elapsed(); + add(size_t(elapsed * 1000000.0)); + *timerActive_ = false; +#endif } /* ************************************************************************* */ @@ -196,7 +207,7 @@ void toc_(size_t id) { != current->parent_.lock()->children_.end()) std::cout << "gtsam timing: Incorrect ID passed to toc, expected " << std::find(current->parent_.lock()->children_.begin(), current->parent_.lock()->children_.end(), current) - current->parent_.lock()->children_.begin() - << ", got " << id << std::endl; + << " \"" << current->label_ << "\", got " << id << std::endl; else std::cout << "gtsam timing: Incorrect ID passed to toc, id " << id << " does not exist" << std::endl; timingRoot->print(); @@ -231,6 +242,8 @@ void toc_(size_t id, const std::string& label) { toc_(id); } +#ifdef ENABLE_OLD_TIMING + /* ************************************************************************* */ // Timing class implementation void Timing::print() { @@ -260,3 +273,5 @@ void ticPop_(const std::string& prefix, const std::string& id) { else timingPrefix.resize(timingPrefix.size() - prefix.size() - 1); } + +#endif diff --git a/gtsam/base/timing.h b/gtsam/base/timing.h index 94498c3b3..8eb99f577 100644 --- a/gtsam/base/timing.h +++ b/gtsam/base/timing.h @@ -1,202 +1,224 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) - - * See LICENSE for the license information - - * -------------------------------------------------------------------------- */ - -/** - * @file timing.h - * @brief Timing utilities - * @author Richard Roberts, Michael Kaess - * @date Oct 5, 2010 - */ -#pragma once - -#include -#include -#include -#include -#include - -class TimingOutline; -extern boost::shared_ptr timingRoot; -extern boost::weak_ptr timingCurrent; - -class TimingOutline { -protected: - size_t t_; - double t2_ ; /* cache the \sum t_i^2 */ - size_t tIt_; - size_t tMax_; - size_t tMin_; - size_t n_; - std::string label_; - - boost::weak_ptr parent_; - std::vector > children_; - struct timeval t0_; - bool timerActive_; - - void add(size_t usecs); - -public: - - TimingOutline(const std::string& label); - - size_t time() const; - - void print(const std::string& outline = "") const; - - void print2(const std::string& outline = "", const double parentTotal = -1.0) const; - - const boost::shared_ptr& child(size_t child, const std::string& label, const boost::weak_ptr& thisPtr); - - void tic(); - - void toc(); - - void finishedIteration(); - - friend class AutoTimer; - friend void toc_(size_t id); - friend void toc_(size_t id, const std::string& label); -}; // \TimingOutline - -void tic_(size_t id, const std::string& label); - -void toc_(size_t id); - -void toc_(size_t id, const std::string& label); - -inline void tictoc_finishedIteration_() { - timingRoot->finishedIteration(); -} - -#ifdef ENABLE_TIMING -inline void tic(size_t id, const std::string& label) { tic_(id, label); } -inline void toc(size_t id) { toc_(id); } -inline void toc(size_t id, const std::string& label) { toc_(id, label); } -inline void tictoc_finishedIteration() { tictoc_finishedIteration_(); } -#else -inline void tic(size_t, const char*) {} -inline void toc(size_t) {} -inline void toc(size_t, const char*) {} -inline void tictoc_finishedIteration() {} -#endif - -// simple class for accumulating execution timing information by name -class Timing; -extern Timing timing; -extern std::string timingPrefix; - -double _tic(); -double _toc(double t); -double tic(const std::string& id); -double toc(const std::string& id); -void ticPush(const std::string& id); -void ticPop(const std::string& id); -void tictoc_print(); -void tictoc_finishedIteration(); - -/** These underscore versions work evening when ENABLE_TIMING is not defined */ -double _tic_(); -double _toc_(double t); -double tic_(const std::string& id); -double toc_(const std::string& id); -void ticPush_(const std::string& id); -void ticPop_(const std::string& id); -void tictoc_print_(); -void tictoc_finishedIteration_(); - - - -// simple class for accumulating execution timing information by name -class Timing { - class Stats { - public: - std::string label; - double t0; - double t; - double t_max; - double t_min; - int n; - }; - std::map stats; -public: - void add_t0(const std::string& id, double t0) { - stats[id].t0 = t0; - } - double get_t0(const std::string& id) { - return stats[id].t0; - } - void add_dt(const std::string& id, double dt) { - Stats& s = stats[id]; - s.t += dt; - s.n++; - if (s.n==1 || s.t_max < dt) s.t_max = dt; - if (s.n==1 || s.t_min > dt) s.t_min = dt; - } - void print(); - - double time(const std::string& id) { - Stats& s = stats[id]; - return s.t; - } -}; - -double _tic_(); -inline double _toc_(double t) { - double s = _tic_(); - return (std::max(0., s-t)); -} -inline double tic_(const std::string& id) { - double t0 = _tic_(); - timing.add_t0(timingPrefix + " " + id, t0); - return t0; -} -inline double toc_(const std::string& id) { - std::string comb(timingPrefix + " " + id); - double dt = _toc_(timing.get_t0(comb)); - timing.add_dt(comb, dt); - return dt; -} -inline void ticPush_(const std::string& prefix, const std::string& id) { - if(timingPrefix.size() > 0) - timingPrefix += "."; - timingPrefix += prefix; - tic_(id); -} -void ticPop_(const std::string& prefix, const std::string& id); - -inline void tictoc_print_() { - timing.print(); - timingRoot->print(); -} - -/* print mean and standard deviation */ -inline void tictoc_print2_() { - timingRoot->print2(); -} - -#ifdef ENABLE_TIMING -inline double _tic() { return _tic_(); } -inline double _toc(double t) { return _toc_(t); } -inline double tic(const std::string& id) { return tic_(id); } -inline double toc(const std::string& id) { return toc_(id); } -inline void ticPush(const std::string& prefix, const std::string& id) { ticPush_(prefix, id); } -inline void ticPop(const std::string& prefix, const std::string& id) { ticPop_(prefix, id); } -inline void tictoc_print() { tictoc_print_(); } -#else -inline double _tic() {return 0.;} -inline double _toc(double) {return 0.;} -inline double tic(const std::string&) {return 0.;} -inline double toc(const std::string&) {return 0.;} -inline void ticPush(const std::string&, const std::string&) {} -inline void ticPop(const std::string&, const std::string&) {} -inline void tictoc_print() {} -#endif +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file timing.h + * @brief Timing utilities + * @author Richard Roberts, Michael Kaess + * @date Oct 5, 2010 + */ +#pragma once + +#include +#include +#include +#include +#include +#include + +// Enabling the new Boost timers introduces dependencies on other Boost +// libraries so this is disabled for now until we modify the build scripts +// to link each component or MATLAB wrapper with only the libraries it needs. +#if 0 +#if BOOST_VERSION >= 104800 +#define GTSAM_USING_NEW_BOOST_TIMERS +#endif +#endif + +#ifdef GTSAM_USING_NEW_BOOST_TIMERS +#include +#else +#include +#endif + +class TimingOutline; +extern boost::shared_ptr timingRoot; +extern boost::weak_ptr timingCurrent; + +class TimingOutline { +protected: + size_t t_; + double t2_ ; /* cache the \sum t_i^2 */ + size_t tIt_; + size_t tMax_; + size_t tMin_; + size_t n_; + std::string label_; + + boost::weak_ptr parent_; + std::vector > children_; +#ifdef GTSAM_USING_NEW_BOOST_TIMERS + boost::timer::cpu_timer timer_; +#else + boost::timer timer_; + gtsam::ValueWithDefault timerActive_; +#endif + + void add(size_t usecs); + +public: + + TimingOutline(const std::string& label); + + size_t time() const; + + void print(const std::string& outline = "") const; + + void print2(const std::string& outline = "", const double parentTotal = -1.0) const; + + const boost::shared_ptr& child(size_t child, const std::string& label, const boost::weak_ptr& thisPtr); + + void tic(); + + void toc(); + + void finishedIteration(); + + friend class AutoTimer; + friend void toc_(size_t id); + friend void toc_(size_t id, const std::string& label); +}; // \TimingOutline + +void tic_(size_t id, const std::string& label); + +void toc_(size_t id); + +void toc_(size_t id, const std::string& label); + +inline void tictoc_finishedIteration_() { + timingRoot->finishedIteration(); +} + +inline void tictoc_print_() { + timingRoot->print(); +} + +/* print mean and standard deviation */ +inline void tictoc_print2_() { + timingRoot->print2(); +} + +#ifdef ENABLE_TIMING +inline void tic(size_t id, const std::string& label) { tic_(id, label); } +inline void toc(size_t id) { toc_(id); } +inline void toc(size_t id, const std::string& label) { toc_(id, label); } +inline void tictoc_finishedIteration() { tictoc_finishedIteration_(); } +inline void tictoc_print() { tictoc_print_(); } +#else +inline void tic(size_t, const char*) {} +inline void toc(size_t) {} +inline void toc(size_t, const char*) {} +inline void tictoc_finishedIteration() {} +inline void tictoc_print() {} +#endif + + +#ifdef ENABLE_OLD_TIMING + +// simple class for accumulating execution timing information by name +class Timing; +extern Timing timing; +extern std::string timingPrefix; + +double _tic(); +double _toc(double t); +double tic(const std::string& id); +double toc(const std::string& id); +void ticPush(const std::string& id); +void ticPop(const std::string& id); +void tictoc_finishedIteration(); + +/** These underscore versions work evening when ENABLE_TIMING is not defined */ +double _tic_(); +double _toc_(double t); +double tic_(const std::string& id); +double toc_(const std::string& id); +void ticPush_(const std::string& id); +void ticPop_(const std::string& id); +void tictoc_finishedIteration_(); + + + +// simple class for accumulating execution timing information by name +class Timing { + class Stats { + public: + std::string label; + double t0; + double t; + double t_max; + double t_min; + int n; + }; + std::map stats; +public: + void add_t0(const std::string& id, double t0) { + stats[id].t0 = t0; + } + double get_t0(const std::string& id) { + return stats[id].t0; + } + void add_dt(const std::string& id, double dt) { + Stats& s = stats[id]; + s.t += dt; + s.n++; + if (s.n==1 || s.t_max < dt) s.t_max = dt; + if (s.n==1 || s.t_min > dt) s.t_min = dt; + } + void print(); + + double time(const std::string& id) { + Stats& s = stats[id]; + return s.t; + } +}; + +double _tic_(); +inline double _toc_(double t) { + double s = _tic_(); + return (std::max(0., s-t)); +} +inline double tic_(const std::string& id) { + double t0 = _tic_(); + timing.add_t0(timingPrefix + " " + id, t0); + return t0; +} +inline double toc_(const std::string& id) { + std::string comb(timingPrefix + " " + id); + double dt = _toc_(timing.get_t0(comb)); + timing.add_dt(comb, dt); + return dt; +} +inline void ticPush_(const std::string& prefix, const std::string& id) { + if(timingPrefix.size() > 0) + timingPrefix += "."; + timingPrefix += prefix; + tic_(id); +} +void ticPop_(const std::string& prefix, const std::string& id); + +#ifdef ENABLE_TIMING +inline double _tic() { return _tic_(); } +inline double _toc(double t) { return _toc_(t); } +inline double tic(const std::string& id) { return tic_(id); } +inline double toc(const std::string& id) { return toc_(id); } +inline void ticPush(const std::string& prefix, const std::string& id) { ticPush_(prefix, id); } +inline void ticPop(const std::string& prefix, const std::string& id) { ticPop_(prefix, id); } +#else +inline double _tic() {return 0.;} +inline double _toc(double) {return 0.;} +inline double tic(const std::string&) {return 0.;} +inline double toc(const std::string&) {return 0.;} +inline void ticPush(const std::string&, const std::string&) {} +inline void ticPop(const std::string&, const std::string&) {} +#endif + +#endif diff --git a/gtsam/base/types.cpp b/gtsam/base/types.cpp new file mode 100644 index 000000000..ea4db72c8 --- /dev/null +++ b/gtsam/base/types.cpp @@ -0,0 +1,30 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file types.h + * @brief Typedefs for easier changing of types + * @author Richard Roberts + * @date Aug 21, 2010 + * @addtogroup base + */ + +#include + +#include + +namespace gtsam { + + std::string _defaultIndexFormatter(Index j) { + return boost::lexical_cast(j); + } + +} \ No newline at end of file diff --git a/gtsam/base/types.h b/gtsam/base/types.h index b6c5617a5..a42c2acc5 100644 --- a/gtsam/base/types.h +++ b/gtsam/base/types.h @@ -14,18 +14,30 @@ * @brief Typedefs for easier changing of types * @author Richard Roberts * @date Aug 21, 2010 - * @defgroup base + * @addtogroup base */ #pragma once -#include +#include + +#include +#include namespace gtsam { /// Integer variable index type typedef size_t Index; + /** A function to convert indices to strings, for example by translating back + * to a nonlinear key and then to a Symbol. */ + typedef boost::function IndexFormatter; + + std::string _defaultIndexFormatter(Index j); + + /** The default IndexFormatter outputs the index */ + static const IndexFormatter DefaultIndexFormatter = &_defaultIndexFormatter; + /** * Helper class that uses templates to select between two types based on * whether TEST_TYPE is const or not. @@ -71,3 +83,35 @@ namespace gtsam { } +#ifdef _MSC_VER + +// Define some common g++ functions and macros that MSVC does not have + +#include +namespace std { + using boost::math::isfinite; + using boost::math::isnan; + using boost::math::isinf; +} + +#include +#ifndef M_PI +#define M_PI (boost::math::constants::pi()) +#endif +#ifndef M_PI_2 +#define M_PI_2 (boost::math::constants::pi() / 2.0) +#endif +#ifndef M_PI_4 +#define M_PI_4 (boost::math::constants::pi() / 4.0) +#endif + +#endif + +#ifdef min +#undef min +#endif + +#ifdef max +#undef max +#endif + diff --git a/gtsam/discrete/Assignment.h b/gtsam/discrete/Assignment.h index 06e2ac137..f6decc359 100644 --- a/gtsam/discrete/Assignment.h +++ b/gtsam/discrete/Assignment.h @@ -20,8 +20,10 @@ #include #include +#include #include + namespace gtsam { /** @@ -29,7 +31,7 @@ namespace gtsam { * Assigns to each label a value. Implemented as a simple map. * A discrete factor takes an Assignment and returns a value. */ - template + template class Assignment: public std::map { public: void print(const std::string& s = "Assignment: ") const { @@ -42,6 +44,44 @@ namespace gtsam { bool equals(const Assignment& other, double tol = 1e-9) const { return (*this == other); } - }; + }; //Assignment + + + /** + * @brief Get Cartesian product consisting all possible configurations + * @param vector list of keys (label,cardinality) pairs. + * @return vector list of all possible value assignments + * + * This function returns a vector of Assignment values for all possible + * (Cartesian product) configurations of set of Keys which are nothing + * but (Label,cardinality) pairs. This function should NOT be called for + * more than a small number of variables and cardinalities. E.g. For 6 + * variables with each having cardinalities 4, we get 4096 possible + * configurations!! + */ + template + std::vector > cartesianProduct( + const std::vector >& keys) { + std::vector > allPossValues; + Assignment values; + typedef std::pair DiscreteKey; + BOOST_FOREACH(const DiscreteKey& key, keys) + values[key.first] = 0; //Initialize from 0 + while (1) { + allPossValues.push_back(values); + size_t j = 0; + for (j = 0; j < keys.size(); j++) { + L idx = keys[j].first; + values[idx]++; + if (values[idx] < keys[j].second) + break; + //Wrap condition + values[idx] = 0; + } + if (j == keys.size()) + break; + } + return allPossValues; + } } // namespace gtsam diff --git a/gtsam/discrete/DecisionTree-inl.h b/gtsam/discrete/DecisionTree-inl.h index 1fa750ace..057f014bf 100644 --- a/gtsam/discrete/DecisionTree-inl.h +++ b/gtsam/discrete/DecisionTree-inl.h @@ -27,6 +27,7 @@ #include #include #include +using boost::assign::operator+=; #include #include @@ -37,8 +38,6 @@ namespace gtsam { - using namespace boost::assign; - /*********************************************************************************/ // Node /*********************************************************************************/ @@ -81,7 +80,7 @@ namespace gtsam { bool equals(const Node& q, double tol) const { const Leaf* other = dynamic_cast (&q); if (!other) return false; - return fabs(this->constant_ - other->constant_) < tol; + return fabs(double(this->constant_ - other->constant_)) < tol; } /** print */ diff --git a/gtsam/discrete/DecisionTreeFactor.cpp b/gtsam/discrete/DecisionTreeFactor.cpp index 23b761b3b..bb83cec16 100644 --- a/gtsam/discrete/DecisionTreeFactor.cpp +++ b/gtsam/discrete/DecisionTreeFactor.cpp @@ -22,6 +22,7 @@ #include #include +#include using namespace std; @@ -48,10 +49,11 @@ namespace gtsam { } /* ************************************************************************* */ - void DecisionTreeFactor::print(const string& s) const { - cout << s << ":\n"; - IndexFactor::print("IndexFactor:"); - Potentials::print("Potentials:"); + void DecisionTreeFactor::print(const string& s, + const IndexFormatter& formatter) const { + cout << s; + IndexFactor::print("IndexFactor:",formatter); + Potentials::print("Potentials:",formatter); } /* ************************************************************************* */ @@ -94,8 +96,7 @@ namespace gtsam { Index j = keys()[i]; dkeys.push_back(DiscreteKey(j,cardinality(j))); } - shared_ptr f(new DecisionTreeFactor(dkeys, result)); - return f; + return boost::make_shared(dkeys, result); } /* ************************************************************************* */ diff --git a/gtsam/discrete/DecisionTreeFactor.h b/gtsam/discrete/DecisionTreeFactor.h index c63e59517..64f37c174 100644 --- a/gtsam/discrete/DecisionTreeFactor.h +++ b/gtsam/discrete/DecisionTreeFactor.h @@ -72,7 +72,8 @@ namespace gtsam { bool equals(const DecisionTreeFactor& other, double tol = 1e-9) const; // print - void print(const std::string& s = "DecisionTreeFactor: ") const; + virtual void print(const std::string& s = "DecisionTreeFactor:\n", + const IndexFormatter& formatter = DefaultIndexFormatter) const; /// @} /// @name Standard Interface @@ -94,7 +95,7 @@ namespace gtsam { } /// Convert into a decisiontree - virtual operator DecisionTreeFactor() const { + virtual DecisionTreeFactor toDecisionTreeFactor() const { return *this; } @@ -127,6 +128,18 @@ namespace gtsam { */ shared_ptr combine(size_t nrFrontals, ADT::Binary op) const; + /** + * @brief Permutes the keys in Potentials and DiscreteFactor + * + * This re-implements the permuteWithInverse() in both Potentials + * and DiscreteFactor by doing both of them together. + */ + + void permuteWithInverse(const Permutation& inversePermutation){ + DiscreteFactor::permuteWithInverse(inversePermutation); + Potentials::permuteWithInverse(inversePermutation); + } + /// @} }; // DecisionTreeFactor diff --git a/gtsam/discrete/DiscreteConditional.cpp b/gtsam/discrete/DiscreteConditional.cpp index 73649dce6..029873d2c 100644 --- a/gtsam/discrete/DiscreteConditional.cpp +++ b/gtsam/discrete/DiscreteConditional.cpp @@ -46,9 +46,9 @@ namespace gtsam { const DecisionTreeFactor& marginal) : IndexConditional(joint.keys(), joint.size() - marginal.size()), Potentials( ISDEBUG("DiscreteConditional::COUNT") ? joint : joint / marginal) { - assert(nrFrontals() == 1); +// assert(nrFrontals() == 1); if (ISDEBUG("DiscreteConditional::DiscreteConditional")) cout - << (firstFrontalKey()) << endl; + << (firstFrontalKey()) << endl; //TODO Print all keys } /* ******************************************************************************** */ @@ -66,7 +66,7 @@ namespace gtsam { Index j = (key); size_t value = parentsValues.at(j); pFS = pFS.choose(j, value); - } catch (exception& e) { + } catch (exception&) { throw runtime_error( "DiscreteConditional::choose: parent value missing"); }; @@ -75,10 +75,44 @@ namespace gtsam { /* ******************************************************************************** */ void DiscreteConditional::solveInPlace(Values& values) const { - assert(nrFrontals() == 1); - Index j = (firstFrontalKey()); - size_t mpe = solve(values); // Solve for variable - values[j] = mpe; // store result in partial solution +// OLD +// assert(nrFrontals() == 1); +// Index j = (firstFrontalKey()); +// size_t mpe = solve(values); // Solve for variable +// values[j] = mpe; // store result in partial solution +// OLD + + // TODO: is this really the fastest way? I think it is. + + //The following is to make make adjustment for nFrontals \neq 1 + ADT pFS = choose(values); // P(F|S=parentsValues) + + // Initialize + Values mpe; + double maxP = 0; + + DiscreteKeys keys; + BOOST_FOREACH(Index idx, frontals()) { + DiscreteKey dk(idx,cardinality(idx)); + keys & dk; + } + // Get all Possible Configurations + vector allPosbValues = cartesianProduct(keys); + + // Find the MPE + BOOST_FOREACH(Values& frontalVals, allPosbValues) { + double pValueS = pFS(frontalVals); // P(F=value|S=parentsValues) + // Update MPE solution if better + if (pValueS > maxP) { + maxP = pValueS; + mpe = frontalVals; + } + } + + //set values (inPlace) to mpe + BOOST_FOREACH(Index j, frontals()) { + values[j] = mpe[j]; + } } /* ******************************************************************************** */ @@ -155,7 +189,14 @@ namespace gtsam { return sampled; return 0; - } + } + + /* ******************************************************************************** */ + void DiscreteConditional::permuteWithInverse(const Permutation& inversePermutation){ + IndexConditional::permuteWithInverse(inversePermutation); + Potentials::permuteWithInverse(inversePermutation); + } + /* ******************************************************************************** */ diff --git a/gtsam/discrete/DiscreteConditional.h b/gtsam/discrete/DiscreteConditional.h index f6603c195..e05bfd669 100644 --- a/gtsam/discrete/DiscreteConditional.h +++ b/gtsam/discrete/DiscreteConditional.h @@ -63,9 +63,11 @@ namespace gtsam { /// @{ /** GTSAM-style print */ - void print(const std::string& s = "Discrete Conditional: ") const { + void print(const std::string& s = "Discrete Conditional: ", + const IndexFormatter& formatter + =DefaultIndexFormatter) const { std::cout << s << std::endl; - IndexConditional::print(s); + IndexConditional::print(s, formatter); Potentials::print(s); } @@ -89,14 +91,14 @@ namespace gtsam { /** * solve a conditional - * @param parentsAssignment Known values of the parents + * @param parentsValues Known values of the parents * @return MPE value of the child (1 frontal variable). */ size_t solve(const Values& parentsValues) const; /** * sample - * @param parentsAssignment Known values of the parents + * @param parentsValues Known values of the parents * @return sample from conditional */ size_t sample(const Values& parentsValues) const; @@ -111,6 +113,11 @@ namespace gtsam { /// sample in place, stores result in partial solution void sampleInPlace(Values& parentsValues) const; + /** + * Permutes both IndexConditional and Potentials. + */ + void permuteWithInverse(const Permutation& inversePermutation); + /// @} }; diff --git a/gtsam/discrete/DiscreteFactor.h b/gtsam/discrete/DiscreteFactor.h index 8152ff726..9b1130bae 100644 --- a/gtsam/discrete/DiscreteFactor.h +++ b/gtsam/discrete/DiscreteFactor.h @@ -82,8 +82,10 @@ namespace gtsam { /// @{ // print - virtual void print(const std::string& s = "DiscreteFactor") const { - IndexFactor::print(s); + virtual void print(const std::string& s = "DiscreteFactor\n", + const IndexFormatter& formatter + =DefaultIndexFormatter) const { + IndexFactor::print(s,formatter); } /// @} @@ -96,7 +98,15 @@ namespace gtsam { /// Multiply in a DecisionTreeFactor and return the result as DecisionTreeFactor virtual DecisionTreeFactor operator*(const DecisionTreeFactor&) const = 0; - virtual operator DecisionTreeFactor() const = 0; + virtual DecisionTreeFactor toDecisionTreeFactor() const = 0; + + /** + * Permutes the factor, but for efficiency requires the permutation + * to already be inverted. + */ + virtual void permuteWithInverse(const Permutation& inversePermutation){ + IndexFactor::permuteWithInverse(inversePermutation); + } /// @} }; diff --git a/gtsam/discrete/DiscreteFactorGraph.cpp b/gtsam/discrete/DiscreteFactorGraph.cpp index f5fc7533d..f3c89721b 100644 --- a/gtsam/discrete/DiscreteFactorGraph.cpp +++ b/gtsam/discrete/DiscreteFactorGraph.cpp @@ -24,69 +24,84 @@ namespace gtsam { -// Explicitly instantiate so we don't have to include everywhere -template class FactorGraph ; -template class EliminationTree ; + // Explicitly instantiate so we don't have to include everywhere + template class FactorGraph ; + template class EliminationTree ; -/* ************************************************************************* */ -DiscreteFactorGraph::DiscreteFactorGraph() { -} + /* ************************************************************************* */ + DiscreteFactorGraph::DiscreteFactorGraph() { + } -/* ************************************************************************* */ -DiscreteFactorGraph::DiscreteFactorGraph( - const BayesNet& bayesNet) : - FactorGraph(bayesNet) { -} + /* ************************************************************************* */ + DiscreteFactorGraph::DiscreteFactorGraph( + const BayesNet& bayesNet) : + FactorGraph(bayesNet) { + } -/* ************************************************************************* */ -FastSet DiscreteFactorGraph::keys() const { - FastSet keys; - BOOST_FOREACH(const sharedFactor& factor, *this) - if (factor) keys.insert(factor->begin(), factor->end()); - return keys; -} + /* ************************************************************************* */ + FastSet DiscreteFactorGraph::keys() const { + FastSet keys; + BOOST_FOREACH(const sharedFactor& factor, *this) + if (factor) keys.insert(factor->begin(), factor->end()); + return keys; + } -/* ************************************************************************* */ -DecisionTreeFactor DiscreteFactorGraph::product() const { - DecisionTreeFactor result; - BOOST_FOREACH(const sharedFactor& factor, *this) - if (factor) result = (*factor) * result; - return result; -} + /* ************************************************************************* */ + DecisionTreeFactor DiscreteFactorGraph::product() const { + DecisionTreeFactor result; + BOOST_FOREACH(const sharedFactor& factor, *this) + if (factor) result = (*factor) * result; + return result; + } -/* ************************************************************************* */ -double DiscreteFactorGraph::operator()( - const DiscreteFactor::Values &values) const { - double product = 1.0; - BOOST_FOREACH( const sharedFactor& factor, factors_ ) - product *= (*factor)(values); - return product; -} + /* ************************************************************************* */ + double DiscreteFactorGraph::operator()( + const DiscreteFactor::Values &values) const { + double product = 1.0; + BOOST_FOREACH( const sharedFactor& factor, factors_ ) + product *= (*factor)(values); + return product; + } -/* ************************************************************************* */ -pair // -EliminateDiscrete(const FactorGraph& factors, size_t num) { + /* ************************************************************************* */ + void DiscreteFactorGraph::print(const std::string& s, + const IndexFormatter& formatter) const { + std::cout << s << std::endl; + std::cout << "size: " << size() << std::endl; + for (size_t i = 0; i < factors_.size(); i++) { + std::stringstream ss; + ss << "factor " << i << ": "; + if (factors_[i] != NULL) factors_[i]->print(ss.str(), formatter); + } + } - // PRODUCT: multiply all factors - tic(1, "product"); - DecisionTreeFactor product; - BOOST_FOREACH(const DiscreteFactor::shared_ptr& factor, factors) - product = (*factor) * product; - toc(1, "product"); + /* ************************************************************************* */ + std::pair // + EliminateDiscrete(const FactorGraph& factors, size_t num) { - // sum out frontals, this is the factor on the separator - tic(2, "sum"); - DecisionTreeFactor::shared_ptr sum = product.sum(num); - toc(2, "sum"); + // PRODUCT: multiply all factors + tic(1, "product"); + DecisionTreeFactor product; + BOOST_FOREACH(const DiscreteFactor::shared_ptr& factor, factors){ + product = (*factor) * product; + } - // now divide product/sum to get conditional - tic(3, "divide"); - DiscreteConditional::shared_ptr cond(new DiscreteConditional(product, *sum)); - toc(3, "divide"); - tictoc_finishedIteration(); + toc(1, "product"); + + // sum out frontals, this is the factor on the separator + tic(2, "sum"); + DecisionTreeFactor::shared_ptr sum = product.sum(num); + toc(2, "sum"); + + // now divide product/sum to get conditional + tic(3, "divide"); + DiscreteConditional::shared_ptr cond(new DiscreteConditional(product, *sum)); + toc(3, "divide"); + tictoc_finishedIteration(); + + return std::make_pair(cond, sum); + } - return make_pair(cond, sum); -} /* ************************************************************************* */ } // namespace diff --git a/gtsam/discrete/DiscreteFactorGraph.h b/gtsam/discrete/DiscreteFactorGraph.h index eefdfaf1d..0f399abdd 100644 --- a/gtsam/discrete/DiscreteFactorGraph.h +++ b/gtsam/discrete/DiscreteFactorGraph.h @@ -77,16 +77,8 @@ public: double operator()(const DiscreteFactor::Values & values) const; /// print - void print(const std::string& s = "DiscreteFactorGraph") const { - std::cout << s << std::endl; - std::cout << "size: " << size() << std::endl; - for (size_t i = 0; i < factors_.size(); i++) { - std::stringstream ss; - ss << "factor " << i << ": "; - if (factors_[i] != NULL) factors_[i]->print(ss.str()); - } - } - + void print(const std::string& s = "DiscreteFactorGraph", + const IndexFormatter& formatter =DefaultIndexFormatter) const; }; // DiscreteFactorGraph diff --git a/gtsam/discrete/DiscreteMarginals.h b/gtsam/discrete/DiscreteMarginals.h new file mode 100644 index 000000000..1e89286a8 --- /dev/null +++ b/gtsam/discrete/DiscreteMarginals.h @@ -0,0 +1,78 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file DiscreteMarginals.h + * @brief A class for computing marginals in a DiscreteFactorGraph + * @author Abhijit Kundu + * @author Richard Roberts + * @author Frank Dellaert + * @date June 4, 2012 + */ + +#pragma once + +#include +#include +#include + +namespace gtsam { + + /** + * A class for computing marginals of variables in a DiscreteFactorGraph + */ + class DiscreteMarginals { + + protected: + + BayesTree bayesTree_; + + public: + + /** Construct a marginals class. + * @param graph The factor graph defining the full joint density on all variables. + */ + DiscreteMarginals(const DiscreteFactorGraph& graph) { + typedef JunctionTree DiscreteJT; + GenericMultifrontalSolver solver(graph); + bayesTree_ = *solver.eliminate(&EliminateDiscrete); + } + + /** Compute the marginal of a single variable */ + DiscreteFactor::shared_ptr operator()(Index variable) const { + // Compute marginal + DiscreteFactor::shared_ptr marginalFactor; + marginalFactor = bayesTree_.marginalFactor(variable, &EliminateDiscrete); + return marginalFactor; + } + + /** Compute the marginal of a single variable + * @param key DiscreteKey of the Variable + * @return Vector of marginal probabilities + */ + Vector marginalProbabilities(const DiscreteKey& key) const { + // Compute marginal + DiscreteFactor::shared_ptr marginalFactor; + marginalFactor = bayesTree_.marginalFactor(key.first, &EliminateDiscrete); + + //Create result + Vector vResult(key.second); + for (size_t state = 0; state < key.second ; ++ state) { + DiscreteFactor::Values values; + values[key.first] = state; + vResult(state) = (*marginalFactor)(values); + } + return vResult; + } + + }; + +} /* namespace gtsam */ diff --git a/gtsam/discrete/DiscreteSequentialSolver.cpp b/gtsam/discrete/DiscreteSequentialSolver.cpp index 1ca00875a..e4bc502c8 100644 --- a/gtsam/discrete/DiscreteSequentialSolver.cpp +++ b/gtsam/discrete/DiscreteSequentialSolver.cpp @@ -52,6 +52,24 @@ namespace gtsam { return solution; } + + /* ************************************************************************* */ + Vector DiscreteSequentialSolver::marginalProbabilities( + const DiscreteKey& key) const { + // Compute marginal + DiscreteFactor::shared_ptr marginalFactor; + marginalFactor = Base::marginalFactor(key.first, &EliminateDiscrete); + + //Create result + Vector vResult(key.second); + for (size_t state = 0; state < key.second; ++state) { + DiscreteFactor::Values values; + values[key.first] = state; + vResult(state) = (*marginalFactor)(values); + } + return vResult; + } + /* ************************************************************************* */ } diff --git a/gtsam/discrete/DiscreteSequentialSolver.h b/gtsam/discrete/DiscreteSequentialSolver.h index c453f5b96..6adb32ef6 100644 --- a/gtsam/discrete/DiscreteSequentialSolver.h +++ b/gtsam/discrete/DiscreteSequentialSolver.h @@ -74,7 +74,6 @@ namespace gtsam { return Base::eliminate(&EliminateDiscrete); } -#ifdef BROKEN /** * Compute the marginal joint over a set of variables, by integrating out * all of the other variables. This function returns the result as a factor @@ -94,7 +93,13 @@ namespace gtsam { DiscreteFactor::shared_ptr marginalFactor(Index j) const { return Base::marginalFactor(j, &EliminateDiscrete); } -#endif + + /** + * Compute the marginal density over a variable, by integrating out + * all of the other variables. This function returns the result as a + * Vector of the probability values. + */ + Vector marginalProbabilities(const DiscreteKey& key) const; /** * Compute the MPE solution of the DiscreteFactorGraph. This diff --git a/gtsam/discrete/Potentials.cpp b/gtsam/discrete/Potentials.cpp index ac6ecde10..2a2260d97 100644 --- a/gtsam/discrete/Potentials.cpp +++ b/gtsam/discrete/Potentials.cpp @@ -51,14 +51,37 @@ namespace gtsam { } /* ************************************************************************* */ - void Potentials::print(const string&s) const { + void Potentials::print(const string& s, + const IndexFormatter& formatter) const { cout << s << "\n Cardinalities: "; BOOST_FOREACH(const DiscreteKey& key, cardinalities_) - cout << key.first << "=" << key.second << " "; + cout << formatter(key.first) << "=" << formatter(key.second) << " "; cout << endl; ADT::print(" "); } /* ************************************************************************* */ + void Potentials::permuteWithInverse(const Permutation& permutation) { + // Permute the _cardinalities (TODO: Inefficient Consider Improving) + DiscreteKeys keys; + map ordering; + + // Get the orginal keys from cardinalities_ + BOOST_FOREACH(const DiscreteKey& key, cardinalities_) + keys & key; + + // Perform Permutation + BOOST_FOREACH(DiscreteKey& key, keys) { + ordering[key.first] = permutation[key.first]; + key.first = ordering[key.first]; + } + + // Change *this + AlgebraicDecisionTree permuted((*this), ordering); + *this = permuted; + cardinalities_ = keys.cardinalities(); + } + + /* ************************************************************************* */ } // namespace gtsam diff --git a/gtsam/discrete/Potentials.h b/gtsam/discrete/Potentials.h index 8a8c2e3bc..3ca222b5f 100644 --- a/gtsam/discrete/Potentials.h +++ b/gtsam/discrete/Potentials.h @@ -20,6 +20,7 @@ #include #include #include +#include #include #include @@ -64,10 +65,20 @@ namespace gtsam { // Testable bool equals(const Potentials& other, double tol = 1e-9) const; - void print(const std::string& s = "Potentials: ") const; + void print(const std::string& s = "Potentials: ", + const IndexFormatter& formatter = DefaultIndexFormatter) const; size_t cardinality(Index j) const { return cardinalities_.at(j);} + /** + * @brief Permutes the keys in Potentials + * + * This permutes the Indices and performs necessary re-ordering of ADD. + * This is virtual so that derived types e.g. DecisionTreeFactor can + * re-implement it. + */ + virtual void permuteWithInverse(const Permutation& inversePermutation); + }; // Potentials } // namespace gtsam diff --git a/gtsam/discrete/Signature.cpp b/gtsam/discrete/Signature.cpp index ee7c1e59a..76ccad9db 100644 --- a/gtsam/discrete/Signature.cpp +++ b/gtsam/discrete/Signature.cpp @@ -21,18 +21,15 @@ #include "Signature.h" -#ifdef BOOST_HAVE_PARSER #include // for parsing #include // for qi::_val -#endif namespace gtsam { using namespace std; - -#ifdef BOOST_HAVE_PARSER namespace qi = boost::spirit::qi; + namespace ph = boost::phoenix; // parser for strings of form "99/1 80/20" etc... namespace parser { @@ -85,9 +82,9 @@ namespace gtsam { // check for OR, AND on whole phrase It f = spec.begin(), l = spec.end(); if (qi::parse(f, l, - qi::lit("OR")[ref(table) = logic(false, true, true, true)]) || + qi::lit("OR")[ph::ref(table) = logic(false, true, true, true)]) || qi::parse(f, l, - qi::lit("AND")[ref(table) = logic(false, false, false, true)])) + qi::lit("AND")[ph::ref(table) = logic(false, false, false, true)])) return true; // tokenize into separate rows @@ -97,9 +94,9 @@ namespace gtsam { Signature::Row values; It tf = token.begin(), tl = token.end(); bool r = qi::parse(tf, tl, - qi::double_[push_back(ref(values), qi::_1)] >> +("/" >> qi::double_[push_back(ref(values), qi::_1)]) | - qi::lit("T")[ref(values) = T] | - qi::lit("F")[ref(values) = F] ); + qi::double_[push_back(ph::ref(values), qi::_1)] >> +("/" >> qi::double_[push_back(ph::ref(values), qi::_1)]) | + qi::lit("T")[ph::ref(values) = T] | + qi::lit("F")[ph::ref(values) = F] ); if (!r) return false; table.push_back(values); @@ -108,7 +105,6 @@ namespace gtsam { return true; } } // \namespace parser -#endif ostream& operator <<(ostream &os, const Signature::Row &row) { os << row[0]; @@ -168,7 +164,6 @@ namespace gtsam { Signature& Signature::operator=(const string& spec) { spec_.reset(spec); -#ifdef BOOST_HAVE_PARSER Table table; // NOTE: using simpler parse function to ensure boost back compatibility // parser::It f = spec.begin(), l = spec.end(); @@ -180,7 +175,6 @@ namespace gtsam { normalize(row); table_.reset(table); } -#endif return *this; } diff --git a/gtsam/discrete/Signature.h b/gtsam/discrete/Signature.h index 873365c24..937bd6e1b 100644 --- a/gtsam/discrete/Signature.h +++ b/gtsam/discrete/Signature.h @@ -22,11 +22,6 @@ #include #include -#include // for checking whether we are using boost 1.40 -#if BOOST_VERSION >= 104200 -#define BOOST_HAVE_PARSER -#endif - namespace gtsam { /** diff --git a/gtsam/discrete/tests/testAlgebraicDecisionTree.cpp b/gtsam/discrete/tests/testAlgebraicDecisionTree.cpp index bfeacb8e4..8ab3b6a14 100644 --- a/gtsam/discrete/tests/testAlgebraicDecisionTree.cpp +++ b/gtsam/discrete/tests/testAlgebraicDecisionTree.cpp @@ -23,10 +23,6 @@ #include #include // for convert only #define DISABLE_TIMING -#include // for checking whether we are using boost 1.40 -#if BOOST_VERSION >= 104200 -#define BOOST_HAVE_PARSER -#endif #include #include @@ -150,7 +146,6 @@ TEST(ADT, joint) { DiscreteKey A(0, 2), S(1, 2), T(2, 2), L(3, 2), B(4, 2), E(5, 2), X(6, 2), D(7, 2); -#ifdef BOOST_HAVE_PARSER resetCounts(); ADT pA = create(A % "99/1"); ADT pS = create(S % "50/50"); @@ -193,7 +188,6 @@ TEST(ADT, joint) EXPECT(assert_equal(pA, fAa)); ADT fAb = pASTL.combine(S, &add_).combine(T, &add_).combine(L, &add_); EXPECT(assert_equal(pA, fAb)); -#endif } /* ************************************************************************* */ @@ -203,7 +197,6 @@ TEST(ADT, inference) DiscreteKey A(0,2), D(1,2),// B(2,2), L(3,2), E(4,2), S(5,2), T(6,2), X(7,2); -#ifdef BOOST_HAVE_PARSER resetCounts(); ADT pA = create(A % "99/1"); ADT pS = create(S % "50/50"); @@ -247,7 +240,6 @@ TEST(ADT, inference) dot(marginal, "Joint-Sum-ADBL"); EXPECT_LONGS_EQUAL(161, adds); printCounts("Asia sum"); -#endif } /* ************************************************************************* */ @@ -255,7 +247,6 @@ TEST(ADT, factor_graph) { DiscreteKey B(0,2), L(1,2), E(2,2), S(3,2), T(4,2), X(5,2); -#ifdef BOOST_HAVE_PARSER resetCounts(); ADT pS = create(S % "50/50"); ADT pT = create(T % "95/5"); @@ -334,7 +325,6 @@ TEST(ADT, factor_graph) fB = fB.combine(L, &add_); dot(fB, "Eliminate-10-fB"); printCounts("Eliminate L"); -#endif } /* ************************************************************************* */ @@ -360,7 +350,6 @@ TEST(ADT, equality_noparser) } /* ************************************************************************* */ -#ifdef BOOST_HAVE_PARSER // test equality TEST(ADT, equality_parser) { @@ -376,7 +365,6 @@ TEST(ADT, equality_parser) ADT pAB2 = apply(pB, pA1, &mul); EXPECT(pAB2 == pAB1); } -#endif /* ******************************************************************************** */ // Factor graph construction diff --git a/gtsam/discrete/tests/testDecisionTree.cpp b/gtsam/discrete/tests/testDecisionTree.cpp index f67df51a8..1dfcd3057 100644 --- a/gtsam/discrete/tests/testDecisionTree.cpp +++ b/gtsam/discrete/tests/testDecisionTree.cpp @@ -41,6 +41,9 @@ void dot(const T&f, const string& filename) { #define DOT(x)(dot(x,#x)) +struct Crazy { int a; double b; }; +typedef DecisionTree CrazyDecisionTree; // check that DecisionTree is actually generic (as it pretends to be) + /* ******************************************************************************** */ // Test string labels and int range /* ******************************************************************************** */ diff --git a/gtsam/discrete/tests/testDiscreteBayesNet.cpp b/gtsam/discrete/tests/testDiscreteBayesNet.cpp index bc07d57ca..63f225c35 100644 --- a/gtsam/discrete/tests/testDiscreteBayesNet.cpp +++ b/gtsam/discrete/tests/testDiscreteBayesNet.cpp @@ -25,10 +25,6 @@ #include using namespace boost::assign; -#include // for checking whether we are using boost 1.40 -#if BOOST_VERSION >= 104200 -#define BOOST_HAVE_PARSER -#endif #include @@ -44,7 +40,6 @@ TEST(DiscreteBayesNet, Asia) DiscreteKey A(0,2), S(4,2), T(3,2), L(6,2), B(7,2), E(5,2), X(2,2), D(1,2); // TODO: make a version that doesn't use the parser -#ifdef BOOST_HAVE_PARSER add_front(asia, A % "99/1"); add_front(asia, S % "50/50"); @@ -104,7 +99,6 @@ TEST(DiscreteBayesNet, Asia) S.first, 1)(E.first, 0)(L.first, 0)(B.first, 1); DiscreteFactor::sharedValues actualSample = sample(*chordal2); EXPECT(assert_equal(expectedSample, *actualSample)); -#endif } /* ************************************************************************* */ @@ -114,7 +108,6 @@ TEST_UNSAFE(DiscreteBayesNet, Sugar) DiscreteBayesNet bn; -#ifdef BOOST_HAVE_PARSER // test some mistakes // add(bn, D); // add(bn, D | E); @@ -127,7 +120,6 @@ TEST_UNSAFE(DiscreteBayesNet, Sugar) // // try multivalued add(bn, C % "1/1/2"); add(bn, C | S = "1/1/2 5/2/3"); -#endif } /* ************************************************************************* */ diff --git a/gtsam/discrete/tests/testDiscreteConditional.cpp b/gtsam/discrete/tests/testDiscreteConditional.cpp index c11dddef5..8af23e4f8 100644 --- a/gtsam/discrete/tests/testDiscreteConditional.cpp +++ b/gtsam/discrete/tests/testDiscreteConditional.cpp @@ -24,10 +24,6 @@ using namespace boost::assign; #include #include #include -#include // for checking whether we are using boost 1.40 -#if BOOST_VERSION >= 104200 -#define BOOST_HAVE_PARSER -#endif using namespace std; using namespace gtsam; @@ -37,17 +33,31 @@ TEST( DiscreteConditionalTest, constructors) { DiscreteKey X(0, 2), Y(2, 3), Z(1, 2); // watch ordering ! -#ifdef BOOST_HAVE_PARSER DiscreteConditional::shared_ptr expected1 = // boost::make_shared(X | Y = "1/1 2/3 1/4"); -#else + EXPECT(expected1); + DecisionTreeFactor f1(X & Y, "0.5 0.4 0.2 0.5 0.6 0.8"); + DiscreteConditional actual1(1, f1); + EXPECT(assert_equal(*expected1, actual1, 1e-9)); + + DecisionTreeFactor f2(X & Y & Z, + "0.2 0.5 0.3 0.6 0.4 0.7 0.25 0.55 0.35 0.65 0.45 0.75"); + DiscreteConditional actual2(1, f2); + DecisionTreeFactor::shared_ptr actual2factor = actual2.toFactor(); +// EXPECT(assert_equal(f2, *actual2factor, 1e-9)); +} + +/* ************************************************************************* */ +TEST( DiscreteConditionalTest, constructors_alt_interface) +{ + DiscreteKey X(0, 2), Y(2, 3), Z(1, 2); // watch ordering ! + Signature::Table table; Signature::Row r1, r2, r3; r1 += 1.0, 1.0; r2 += 2.0, 3.0; r3 += 1.0, 4.0; table += r1, r2, r3; DiscreteConditional::shared_ptr expected1 = // boost::make_shared(X | Y = table); -#endif EXPECT(expected1); DecisionTreeFactor f1(X & Y, "0.5 0.4 0.2 0.5 0.6 0.8"); DiscreteConditional actual1(1, f1); @@ -63,7 +73,6 @@ TEST( DiscreteConditionalTest, constructors) /* ************************************************************************* */ TEST( DiscreteConditionalTest, constructors2) { -#ifdef BOOST_HAVE_PARSER // Declare keys and ordering DiscreteKey C(0,2), B(1,2); DecisionTreeFactor expected(C & B, "0.8 0.75 0.2 0.25"); @@ -71,13 +80,11 @@ TEST( DiscreteConditionalTest, constructors2) DiscreteConditional actual(signature); DecisionTreeFactor::shared_ptr actualFactor = actual.toFactor(); EXPECT(assert_equal(expected, *actualFactor)); -#endif - } +} /* ************************************************************************* */ TEST( DiscreteConditionalTest, constructors3) { -#ifdef BOOST_HAVE_PARSER // Declare keys and ordering DiscreteKey C(0,2), B(1,2), A(2,2); DecisionTreeFactor expected(C & B & A, "0.8 0.5 0.5 0.2 0.2 0.5 0.5 0.8"); @@ -85,13 +92,9 @@ TEST( DiscreteConditionalTest, constructors3) DiscreteConditional actual(signature); DecisionTreeFactor::shared_ptr actualFactor = actual.toFactor(); EXPECT(assert_equal(expected, *actualFactor)); -#endif } /* ************************************************************************* */ -int main() { - TestResult tr; - return TestRegistry::runAllTests(tr); -} +int main() { TestResult tr; return TestRegistry::runAllTests(tr); } /* ************************************************************************* */ diff --git a/gtsam/discrete/tests/testDiscreteFactorGraph.cpp b/gtsam/discrete/tests/testDiscreteFactorGraph.cpp index f3ca4b59e..8fdbc5870 100644 --- a/gtsam/discrete/tests/testDiscreteFactorGraph.cpp +++ b/gtsam/discrete/tests/testDiscreteFactorGraph.cpp @@ -10,8 +10,7 @@ * -------------------------------------------------------------------------- */ /* - * testDiscreteFactorGraph.cpp - * + * @file testDiscreteFactorGraph.cpp * @date Feb 14, 2011 * @author Duy-Nguyen Ta */ @@ -25,10 +24,6 @@ #include using namespace boost::assign; -#include // for checking whether we are using boost 1.40 -#if BOOST_VERSION >= 104200 -#define BOOST_HAVE_PARSER -#endif using namespace std; using namespace gtsam; @@ -137,7 +132,6 @@ TEST( DiscreteFactorGraph, test) boost::tie(conditional, newFactor) =// EliminateDiscrete(graph, 1); -#ifdef BOOST_HAVE_PARSER // Check Bayes net CHECK(conditional); DiscreteBayesNet expected; @@ -174,7 +168,6 @@ TEST( DiscreteFactorGraph, test) insert(expectedValues)(0, 0)(1, 0)(2, 0); DiscreteFactor::sharedValues actualValues = solver.optimize(); EXPECT(assert_equal(expectedValues, *actualValues)); -#endif } /* ************************************************************************* */ diff --git a/gtsam/discrete/tests/testDiscreteMarginals.cpp b/gtsam/discrete/tests/testDiscreteMarginals.cpp new file mode 100644 index 000000000..7f2b7b1b1 --- /dev/null +++ b/gtsam/discrete/tests/testDiscreteMarginals.cpp @@ -0,0 +1,105 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/* + * @file testDiscreteMarginals.cpp + * @date Jun 7, 2012 + * @author Abhijit Kundu + * @author Richard Roberts + * @author Frank Dellaert + */ + +#include +#include + +using namespace std; +using namespace gtsam; + +/* ************************************************************************* */ + +TEST_UNSAFE( DiscreteMarginals, UGM_small ) { + size_t nrStates = 2; + DiscreteKey Cathy(1, nrStates), Heather(2, nrStates), Mark(3, nrStates), + Allison(4, nrStates); + DiscreteFactorGraph graph; + + // add node potentials + graph.add(Cathy, "1 3"); + graph.add(Heather, "9 1"); + graph.add(Mark, "1 3"); + graph.add(Allison, "9 1"); + + // add edge potentials + graph.add(Cathy & Heather, "2 1 1 2"); + graph.add(Heather & Mark, "2 1 1 2"); + graph.add(Mark & Allison, "2 1 1 2"); + + DiscreteMarginals marginals(graph); + DiscreteFactor::shared_ptr actualC = marginals(Cathy.first); + DiscreteFactor::Values values; + + values[Cathy.first] = 0; + EXPECT_DOUBLES_EQUAL( 0.359631, (*actualC)(values), 1e-6); + + Vector actualCvector = marginals.marginalProbabilities(Cathy); + EXPECT(assert_equal(Vector_(2, 0.359631, 0.640369), actualCvector, 1e-6)); + + actualCvector = marginals.marginalProbabilities(Mark); + EXPECT(assert_equal(Vector_(2, 0.48628, 0.51372), actualCvector, 1e-6)); +} + +TEST_UNSAFE( DiscreteMarginals, UGM_chain ) { + + const int nrNodes = 10; + const size_t nrStates = 7; + + // define variables + vector nodes; + for (int i = 0; i < nrNodes; i++) { + DiscreteKey dk(i, nrStates); + nodes.push_back(dk); + } + + // create graph + DiscreteFactorGraph graph; + + // add node potentials + graph.add(nodes[0], ".3 .6 .1 0 0 0 0"); + for (int i = 1; i < nrNodes; i++) + graph.add(nodes[i], "1 1 1 1 1 1 1"); + + const std::string edgePotential = ".08 .9 .01 0 0 0 .01 " + ".03 .95 .01 0 0 0 .01 " + ".06 .06 .75 .05 .05 .02 .01 " + "0 0 0 .3 .6 .09 .01 " + "0 0 0 .02 .95 .02 .01 " + "0 0 0 .01 .01 .97 .01 " + "0 0 0 0 0 0 1"; + + // add edge potentials + for (int i = 0; i < nrNodes - 1; i++) + graph.add(nodes[i] & nodes[i + 1], edgePotential); + + DiscreteMarginals marginals(graph); + DiscreteFactor::shared_ptr actualC = marginals(nodes[2].first); + DiscreteFactor::Values values; + + values[nodes[2].first] = 0; + EXPECT_DOUBLES_EQUAL( 0.03426, (*actualC)(values), 1e-4); +} + +/* ************************************************************************* */ +int main() { + TestResult tr; + return TestRegistry::runAllTests(tr); +} +/* ************************************************************************* */ + diff --git a/gtsam/discrete/tests/testSignature.cpp b/gtsam/discrete/tests/testSignature.cpp index 66b1c61b3..bf4aabb7f 100644 --- a/gtsam/discrete/tests/testSignature.cpp +++ b/gtsam/discrete/tests/testSignature.cpp @@ -28,7 +28,6 @@ using namespace boost::assign; DiscreteKey X(0,2), Y(1,3), Z(2,2); -#ifdef BOOST_HAVE_PARSER /* ************************************************************************* */ TEST(testSignature, simple_conditional) { Signature sig(X | Y = "1/1 2/3 1/4"); @@ -43,7 +42,6 @@ TEST(testSignature, simple_conditional) { vector actCpt = sig.cpt(); EXPECT_LONGS_EQUAL(6, actCpt.size()); } -#endif /* ************************************************************************* */ TEST(testSignature, simple_conditional_nonparser) { diff --git a/gtsam/geometry/Cal3Bundler.h b/gtsam/geometry/Cal3Bundler.h index 259a07c9b..7825e677e 100644 --- a/gtsam/geometry/Cal3Bundler.h +++ b/gtsam/geometry/Cal3Bundler.h @@ -25,7 +25,7 @@ namespace gtsam { /** * @brief Calibration used by Bundler - * @ingroup geometry + * @addtogroup geometry * \nosubgrouping */ class Cal3Bundler : public DerivedValue { diff --git a/gtsam/geometry/Cal3DS2.cpp b/gtsam/geometry/Cal3DS2.cpp index dcb6d6d54..66f8d99a7 100644 --- a/gtsam/geometry/Cal3DS2.cpp +++ b/gtsam/geometry/Cal3DS2.cpp @@ -23,13 +23,6 @@ namespace gtsam { -/* ************************************************************************* */ -Cal3DS2::Cal3DS2():fx_(1), fy_(1), s_(0), u0_(0), v0_(0), k1_(0), k2_(0), k3_(0), k4_(0){} - -/* ************************************************************************* */ -Cal3DS2::Cal3DS2(double fx, double fy, double s, double u0, double v0, double k1, double k2, double k3, double k4) : - fx_(fx), fy_(fy), s_(s), u0_(u0), v0_(v0), k1_(k1), k2_(k2), k3_(k3), k4_(k4) {} - /* ************************************************************************* */ Cal3DS2::Cal3DS2(const Vector &v): fx_(v[0]), fy_(v[1]), s_(v[2]), u0_(v[3]), v0_(v[4]), k1_(v[5]), k2_(v[6]), k3_(v[7]), k4_(v[8]){} @@ -37,14 +30,11 @@ Cal3DS2::Cal3DS2(const Vector &v): /* ************************************************************************* */ Matrix Cal3DS2::K() const { return Matrix_(3,3, fx_, s_, u0_, 0.0, fy_, v0_, 0.0, 0.0, 1.0); } -/* ************************************************************************* */ -Vector Cal3DS2::k() const { return Vector_(4, k1_, k2_, k3_, k4_); } - /* ************************************************************************* */ Vector Cal3DS2::vector() const { return Vector_(9, fx_, fy_, s_, u0_, v0_, k1_, k2_, k3_, k4_) ; } /* ************************************************************************* */ -void Cal3DS2::print(const std::string& s) const { gtsam::print(K(), s + ".K") ; gtsam::print(k(), s + ".k") ; } +void Cal3DS2::print(const std::string& s) const { gtsam::print(K(), s + ".K") ; gtsam::print(Vector(k()), s + ".k") ; } /* ************************************************************************* */ bool Cal3DS2::equals(const Cal3DS2& K, double tol) const { @@ -78,6 +68,36 @@ Point2 Cal3DS2::uncalibrate(const Point2& p, return Point2(fx_* x2 + s_ * y2 + u0_, fy_ * y2 + v0_) ; } +/* ************************************************************************* */ +Point2 Cal3DS2::calibrate(const Point2& pi, const double tol) const { + // Use the following fixed point iteration to invert the radial distortion. + // pn_{t+1} = (inv(K)*pi - dp(pn_{t})) / g(pn_{t}) + + const Point2 invKPi ((1 / fx_) * (pi.x() - u0_ - (s_ / fy_) * (pi.y() - v0_)), + (1 / fy_) * (pi.y() - v0_)); + + // initialize by ignoring the distortion at all, might be problematic for pixels around boundary + Point2 pn = invKPi; + + // iterate until the uncalibrate is close to the actual pixel coordinate + const int maxIterations = 10; + int iteration; + for ( iteration = 0 ; iteration < maxIterations ; ++iteration ) { + if ( uncalibrate(pn).dist(pi) <= tol ) break; + const double x = pn.x(), y = pn.y(), xy = x*y, xx = x*x, yy = y*y ; + const double r = xx + yy ; + const double g = (1+k1_*r+k2_*r*r) ; + const double dx = 2*k3_*xy + k4_*(r+2*xx) ; + const double dy = 2*k4_*xy + k3_*(r+2*yy) ; + pn = (invKPi - Point2(dx,dy))/g ; + } + + if ( iteration >= maxIterations ) + throw std::runtime_error("Cal3DS2::calibrate fails to converge. need a better initialization"); + + return pn; +} + /* ************************************************************************* */ Matrix Cal3DS2::D2d_intrinsic(const Point2& p) const { //const double fx = fx_, fy = fy_, s = s_ ; diff --git a/gtsam/geometry/Cal3DS2.h b/gtsam/geometry/Cal3DS2.h index 9b94eccb5..fc5918f28 100644 --- a/gtsam/geometry/Cal3DS2.h +++ b/gtsam/geometry/Cal3DS2.h @@ -25,7 +25,7 @@ namespace gtsam { /** * @brief Calibration of a camera with radial distortion - * @ingroup geometry + * @addtogroup geometry * \nosubgrouping */ class Cal3DS2 : public DerivedValue { @@ -34,7 +34,7 @@ private: double fx_, fy_, s_, u0_, v0_ ; // focal length, skew and principal point double k1_, k2_ ; // radial 2nd-order and 4th-order - double k3_, k4_ ; // tagential distortion + double k3_, k4_ ; // tangential distortion // K = [ fx s u0 ; 0 fy v0 ; 0 0 1 ] // r = Pn.x^2 + Pn.y^2 @@ -44,17 +44,18 @@ private: public: Matrix K() const ; - Vector k() const ; + Eigen::Vector4d k() const { return Eigen::Vector4d(k1_, k2_, k3_, k4_); } Vector vector() const ; /// @name Standard Constructors /// @{ /// Default Constructor with only unit focal length - Cal3DS2(); + Cal3DS2() : fx_(1), fy_(1), s_(0), u0_(0), v0_(0), k1_(0), k2_(0), k3_(0), k4_(0) {} Cal3DS2(double fx, double fy, double s, double u0, double v0, - double k1, double k2, double k3, double k4) ; + double k1, double k2, double k3 = 0.0, double k4 = 0.0) : + fx_(fx), fy_(fy), s_(s), u0_(u0), v0_(v0), k1_(k1), k2_(k2), k3_(k3), k4_(k4) {} /// @} /// @name Advanced Constructors @@ -76,31 +77,49 @@ public: /// @name Standard Interface /// @{ - ///TODO: comment + /// focal length x + inline double fx() const { return fx_;} + + /// focal length x + inline double fy() const { return fy_;} + + /// skew + inline double skew() const { return s_;} + + /// image center in x + inline double px() const { return u0_;} + + /// image center in y + inline double py() const { return v0_;} + + /// Convert ideal point p (in intrinsic coordinates) into pixel coordinates Point2 uncalibrate(const Point2& p, boost::optional H1 = boost::none, boost::optional H2 = boost::none) const ; - ///TODO: comment + /// Conver a pixel coordinate to ideal coordinate + Point2 calibrate(const Point2& p, const double tol=1e-5) const; + + /// Derivative of uncalibrate wrpt intrinsic coordinates Matrix D2d_intrinsic(const Point2& p) const ; - ///TODO: comment + /// Derivative of uncalibrate wrpt the calibration parameters Matrix D2d_calibration(const Point2& p) const ; /// @} /// @name Manifold /// @{ - ///TODO: comment + /// Given delta vector, update calibration Cal3DS2 retract(const Vector& d) const ; - ///TODO: comment + /// Given a different calibration, calculate update to obtain it Vector localCoordinates(const Cal3DS2& T2) const ; - ///TODO: comment + /// Return dimensions of calibration manifold object virtual size_t dim() const { return 9 ; } //TODO: make a final dimension variable (also, usually size_t in other classes e.g. Pose2) - ///TODO: comment + /// Return dimensions of calibration manifold object static size_t Dim() { return 9; } //TODO: make a final dimension variable private: diff --git a/gtsam/geometry/Cal3_S2.cpp b/gtsam/geometry/Cal3_S2.cpp index 709e03493..88115929a 100644 --- a/gtsam/geometry/Cal3_S2.cpp +++ b/gtsam/geometry/Cal3_S2.cpp @@ -15,12 +15,12 @@ * @author Frank Dellaert */ +#include + #include #include #include -#include - namespace gtsam { using namespace std; @@ -51,7 +51,11 @@ namespace gtsam { } /* ************************************************************************* */ + void Cal3_S2::print(const std::string& s) const { + gtsam::print(matrix(), s); + } + /* ************************************************************************* */ bool Cal3_S2::equals(const Cal3_S2& K, double tol) const { if (fabs(fx_ - K.fx_) > tol) return false; if (fabs(fy_ - K.fy_) > tol) return false; diff --git a/gtsam/geometry/Cal3_S2.h b/gtsam/geometry/Cal3_S2.h index 021b1e366..3c88aaeb2 100644 --- a/gtsam/geometry/Cal3_S2.h +++ b/gtsam/geometry/Cal3_S2.h @@ -16,7 +16,7 @@ */ /** - * @defgroup geometry + * @addtogroup geometry */ #pragma once @@ -28,7 +28,7 @@ namespace gtsam { /** * @brief The most common 5DOF 3D->2D calibration - * @ingroup geometry + * @addtogroup geometry * \nosubgrouping */ class Cal3_S2 : public DerivedValue { @@ -75,9 +75,7 @@ namespace gtsam { /// @{ /// print with optional string - void print(const std::string& s = "") const { - gtsam::print(matrix(), s); - } + void print(const std::string& s = "Cal3_S2") const; /// Check if equal up to specified tolerance bool equals(const Cal3_S2& K, double tol = 10e-9) const; @@ -138,8 +136,8 @@ namespace gtsam { /// convert image coordinates uv to intrinsic coordinates xy Point2 calibrate(const Point2& p) const { const double u = p.x(), v = p.y(); - return Point2((1 / fx_) * (u - u0_ - (s_ / fy_) * (v - v0_)), (1 / fy_) - * (v - v0_)); + return Point2((1 / fx_) * (u - u0_ - (s_ / fy_) * (v - v0_)), + (1 / fy_) * (v - v0_)); } /// @} diff --git a/gtsam/geometry/Cal3_S2Stereo.h b/gtsam/geometry/Cal3_S2Stereo.h index 7bbafd7d5..3a945e8cd 100644 --- a/gtsam/geometry/Cal3_S2Stereo.h +++ b/gtsam/geometry/Cal3_S2Stereo.h @@ -23,11 +23,13 @@ namespace gtsam { /** * @brief The most common 5DOF 3D->2D calibration, stereo version - * @ingroup geometry + * @addtogroup geometry * \nosubgrouping */ - class Cal3_S2Stereo: public Cal3_S2 { + class Cal3_S2Stereo { private: + + Cal3_S2 K_; double b_; public: @@ -39,12 +41,12 @@ namespace gtsam { /// default calibration leaves coordinates unchanged Cal3_S2Stereo() : - Cal3_S2(1, 1, 0, 0, 0), b_(1.0) { + K_(1, 1, 0, 0, 0), b_(1.0) { } /// constructor from doubles Cal3_S2Stereo(double fx, double fy, double s, double u0, double v0, double b) : - Cal3_S2(fx, fy, s, u0, v0), b_(b) { + K_(fx, fy, s, u0, v0), b_(b) { } /// @} @@ -52,23 +54,45 @@ namespace gtsam { /// @{ void print(const std::string& s = "") const { - gtsam::print(matrix(), s); - std::cout << "Baseline: " << b_ << std::endl; + K_.print(s+"K: "); + std::cout << s << "Baseline: " << b_ << std::endl; } - /// @} + /// Check if equal up to specified tolerance + bool equals(const Cal3_S2Stereo& other, double tol = 10e-9) const { + if (fabs(b_ - other.b_) > tol) return false; + return K_.equals(other.K_,tol); + } + + /// @} /// @name Standard Interface /// @{ - //TODO: remove? -// /** -// * Check if equal up to specified tolerance -// */ -// bool equals(const Cal3_S2& K, double tol = 10e-9) const; + /// return calibration, same for left and right + const Cal3_S2& calibration() const { return K_;} + /// return calibration matrix K, same for left and right + Matrix matrix() const { return K_.matrix();} + /// focal length x + inline double fx() const { return K_.fx();} - ///TODO: comment + /// focal length x + inline double fy() const { return K_.fy();} + + /// skew + inline double skew() const { return K_.skew();} + + /// image center in x + inline double px() const { return K_.px();} + + /// image center in y + inline double py() const { return K_.py();} + + /// return the principal point + Point2 principalPoint() const { return K_.principalPoint();} + + /// return baseline inline double baseline() const { return b_; } /// @} @@ -81,10 +105,8 @@ namespace gtsam { template void serialize(Archive & ar, const unsigned int version) { - ar & boost::serialization::make_nvp("Cal3_S2Stereo", - boost::serialization::base_object(*this)); + ar & BOOST_SERIALIZATION_NVP(K_); ar & BOOST_SERIALIZATION_NVP(b_); - ar & BOOST_SERIALIZATION_BASE_OBJECT_NVP(Cal3_S2); } /// @} diff --git a/gtsam/geometry/CalibratedCamera.cpp b/gtsam/geometry/CalibratedCamera.cpp index fa27f2f71..25a4bc57b 100644 --- a/gtsam/geometry/CalibratedCamera.cpp +++ b/gtsam/geometry/CalibratedCamera.cpp @@ -47,7 +47,7 @@ Point3 CalibratedCamera::backproject_from_camera(const Point2& p, const double s } /* ************************************************************************* */ -CalibratedCamera CalibratedCamera::level(const Pose2& pose2, double height) { +CalibratedCamera CalibratedCamera::Level(const Pose2& pose2, double height) { double st = sin(pose2.theta()), ct = cos(pose2.theta()); Point3 x(st, -ct, 0), y(0, 0, -1), z(ct, st, 0); Rot3 wRc(x, y, z); diff --git a/gtsam/geometry/CalibratedCamera.h b/gtsam/geometry/CalibratedCamera.h index 04296eba1..6a52f7cb5 100644 --- a/gtsam/geometry/CalibratedCamera.h +++ b/gtsam/geometry/CalibratedCamera.h @@ -33,7 +33,7 @@ namespace gtsam { * A Calibrated camera class [R|-R't], calibration K=I. * If calibration is known, it is more computationally efficient * to calibrate the measurements rather than try to predict in pixels. - * @ingroup geometry + * @addtogroup geometry * \nosubgrouping */ class CalibratedCamera : public DerivedValue { @@ -94,9 +94,10 @@ namespace gtsam { /** * Create a level camera at the given 2D pose and height * @param pose2 specifies the location and viewing direction + * @param height specifies the height of the camera (along the positive Z-axis) * (theta 0 = looking in direction of positive X axis) */ - static CalibratedCamera level(const Pose2& pose2, double height); + static CalibratedCamera Level(const Pose2& pose2, double height); /// @} /// @name Manifold @@ -126,8 +127,9 @@ namespace gtsam { /** * This function receives the camera pose and the landmark location and * returns the location the point is supposed to appear in the image - * @param camera the CalibratedCamera * @param point a 3D point to be projected + * @param D_intrinsic_pose the optionally computed Jacobian with respect to pose + * @param D_intrinsic_point the optionally computed Jacobian with respect to the 3D point * @return the intrinsic coordinates of the projected point */ Point2 project(const Point3& point, @@ -150,6 +152,8 @@ namespace gtsam { /** * Calculate range to a landmark * @param point 3D location of landmark + * @param H1 optionally computed Jacobian with respect to pose + * @param H2 optionally computed Jacobian with respect to the 3D point * @return range (double) */ double range(const Point3& point, @@ -160,6 +164,8 @@ namespace gtsam { /** * Calculate range to another pose * @param pose Other SO(3) pose + * @param H1 optionally computed Jacobian with respect to pose + * @param H2 optionally computed Jacobian with respect to the 3D point * @return range (double) */ double range(const Pose3& pose, @@ -170,6 +176,8 @@ namespace gtsam { /** * Calculate range to another camera * @param camera Other camera + * @param H1 optionally computed Jacobian with respect to pose + * @param H2 optionally computed Jacobian with respect to the 3D point * @return range (double) */ double range(const CalibratedCamera& camera, diff --git a/gtsam/geometry/PinholeCamera.h b/gtsam/geometry/PinholeCamera.h index 943409b4b..8ec300ac6 100644 --- a/gtsam/geometry/PinholeCamera.h +++ b/gtsam/geometry/PinholeCamera.h @@ -33,14 +33,14 @@ namespace gtsam { /** * A pinhole camera class that has a Pose3 and a Calibration. - * @ingroup geometry + * @addtogroup geometry * \nosubgrouping */ template class PinholeCamera : public DerivedValue > { private: Pose3 pose_; - Calibration k_; + Calibration K_; public: @@ -54,23 +54,82 @@ namespace gtsam { explicit PinholeCamera(const Pose3& pose):pose_(pose){} /** constructor with pose and calibration */ - PinholeCamera(const Pose3& pose, const Calibration& k):pose_(pose),k_(k) {} + PinholeCamera(const Pose3& pose, const Calibration& K):pose_(pose),K_(K) {} - /** alternative constructor with pose and calibration */ - PinholeCamera(const Calibration& k, const Pose3& pose):pose_(pose),k_(k) {} + /// @} + /// @name Named Constructors + /// @{ + + /** + * Create a level camera at the given 2D pose and height + * @param K the calibration + * @param pose2 specifies the location and viewing direction + * (theta 0 = looking in direction of positive X axis) + * @param height camera height + */ + static PinholeCamera Level(const Calibration &K, const Pose2& pose2, double height) { + const double st = sin(pose2.theta()), ct = cos(pose2.theta()); + const Point3 x(st, -ct, 0), y(0, 0, -1), z(ct, st, 0); + const Rot3 wRc(x, y, z); + const Point3 t(pose2.x(), pose2.y(), height); + const Pose3 pose3(wRc, t); + return PinholeCamera(pose3, K); + } + + /// PinholeCamera::level with default calibration + static PinholeCamera Level(const Pose2& pose2, double height) { + return PinholeCamera::Level(Calibration(), pose2, height); + } + + /** + * Create a camera at the given eye position looking at a target point in the scene + * with the specified up direction vector. + * @param eye specifies the camera position + * @param target the point to look at + * @param upVector specifies the camera up direction vector, + * doesn't need to be on the image plane nor orthogonal to the viewing axis + * @param K optional calibration parameter + */ + static PinholeCamera Lookat(const Point3& eye, const Point3& target, const Point3& upVector, const Calibration& K = Calibration()) { + Point3 zc = target-eye; + zc = zc/zc.norm(); + Point3 xc = (-upVector).cross(zc); // minus upVector since yc is pointing down + xc = xc/xc.norm(); + Point3 yc = zc.cross(xc); + Pose3 pose3(Rot3(xc,yc,zc), eye); + return PinholeCamera(pose3, K); + } /// @} /// @name Advanced Constructors /// @{ - explicit PinholeCamera(const Vector &v){ + explicit PinholeCamera(const Vector &v) { pose_ = Pose3::Expmap(v.head(Pose3::Dim())); - if ( v.size() > Pose3::Dim()) { - k_ = Calibration(v.tail(Calibration::Dim())); + if (v.size() > Pose3::Dim()) { + K_ = Calibration(v.tail(Calibration::Dim())); } } - PinholeCamera(const Vector &v, const Vector &k) : pose_(Pose3::Expmap(v)),k_(k){} + PinholeCamera(const Vector &v, const Vector &K) : + pose_(Pose3::Expmap(v)), K_(K) { + } + + /// @} + /// @name Testable + /// @{ + + /// assert equality up to a tolerance + bool equals (const PinholeCamera &camera, double tol = 1e-9) const { + return pose_.equals(camera.pose(), tol) && + K_.equals(camera.calibration(), tol) ; + } + + /// print + void print(const std::string& s = "PinholeCamera") const { + pose_.print(s+".pose"); + K_.print(s+".calibration"); + } /// @} /// @name Standard Interface @@ -85,35 +144,23 @@ namespace gtsam { inline const Pose3& pose() const { return pose_; } /// return calibration - inline Calibration& calibration() { return k_; } + inline Calibration& calibration() { return K_; } /// return calibration - inline const Calibration& calibration() const { return k_; } + inline const Calibration& calibration() const { return K_; } - /// compose two cameras + /// @} + /// @name Group ?? Frank says this might not make sense + /// @{ + + /// compose two cameras: TODO Frank says this might not make sense inline const PinholeCamera compose(const Pose3 &c) const { - return PinholeCamera( pose_ * c, k_ ) ; + return PinholeCamera( pose_ * c, K_ ) ; } - /// inverse + /// compose two cameras: TODO Frank says this might not make sense inline const PinholeCamera inverse() const { - return PinholeCamera( pose_.inverse(), k_ ) ; - } - - /// @} - /// @name Testable - /// @{ - - /// assert equality up to a tolerance - bool equals (const PinholeCamera &camera, double tol = 1e-9) const { - return pose_.equals(camera.pose(), tol) && - k_.equals(camera.calibration(), tol) ; - } - - /// print - void print(const std::string& s = "") const { - pose_.print("pose3"); - k_.print("calibration"); + return PinholeCamera( pose_.inverse(), K_ ) ; } /// @} @@ -137,39 +184,21 @@ namespace gtsam { return d; } - /// Lie group dimensionality - inline size_t dim() const { return pose_.dim() + k_.dim(); } + /// Manifold dimension + inline size_t dim() const { return pose_.dim() + K_.dim(); } - /// Lie group dimensionality + /// Manifold dimension inline static size_t Dim() { return Pose3::Dim() + Calibration::Dim(); } - /** - * Create a level camera at the given 2D pose and height - * @param pose2 specifies the location and viewing direction - * (theta 0 = looking in direction of positive X axis) - */ - static PinholeCamera level(const Pose2& pose2, double height) { - return PinholeCamera::level(Calibration(), pose2, height); - } - - static PinholeCamera level(const Calibration &K, const Pose2& pose2, double height) { - const double st = sin(pose2.theta()), ct = cos(pose2.theta()); - const Point3 x(st, -ct, 0), y(0, 0, -1), z(ct, st, 0); - const Rot3 wRc(x, y, z); - const Point3 t(pose2.x(), pose2.y(), height); - const Pose3 pose3(wRc, t); - return PinholeCamera(pose3, K); - } - /// @} /// @name Transformations and measurement functions /// @{ /** - * projects a 3-dimensional point in camera coordinates into the - * camera and returns a 2-dimensional point, no calibration applied - * With optional 2by3 derivative - */ + * projects a 3-dimensional point in camera coordinates into the + * camera and returns a 2-dimensional point, no calibration applied + * With optional 2by3 derivative + */ inline static Point2 project_to_camera(const Point3& P, boost::optional H1 = boost::none){ if (H1) { @@ -183,7 +212,7 @@ namespace gtsam { inline std::pair projectSafe(const Point3& pw) const { const Point3 pc = pose_.transform_to(pw) ; const Point2 pn = project_to_camera(pc) ; - return std::make_pair(k_.uncalibrate(pn), pc.z()>0); + return std::make_pair(K_.uncalibrate(pn), pc.z()>0); } /** project a point from world coordinate to the image @@ -201,7 +230,7 @@ namespace gtsam { const Point3 pc = pose_.transform_to(pw) ; if ( pc.z() <= 0 ) throw CheiralityException(); const Point2 pn = project_to_camera(pc) ; - return k_.uncalibrate(pn); + return K_.uncalibrate(pn); } // world to camera coordinate @@ -215,7 +244,7 @@ namespace gtsam { // uncalibration Matrix Hk, Hi; // 2*2 - const Point2 pi = k_.uncalibrate(pn, Hk, Hi); + const Point2 pi = K_.uncalibrate(pn, Hk, Hi); // chain the jacobian matrices const Matrix tmp = Hi*Hn ; @@ -238,7 +267,7 @@ namespace gtsam { const Point3 pc = pose_.transform_to(pw) ; if ( pc.z() <= 0 ) throw CheiralityException(); const Point2 pn = project_to_camera(pc) ; - return k_.uncalibrate(pn); + return K_.uncalibrate(pn); } Matrix Htmp1, Htmp2, Htmp3; @@ -252,23 +281,18 @@ namespace gtsam { return pi; } - /** - * backproject a 2-dimensional point to a 3-dimension point - */ - - inline Point3 backproject(const Point2& pi, const double scale) const { - const Point2 pn = k_.calibrate(pi); - const Point3 pc(pn.x()*scale, pn.y()*scale, scale); + /// backproject a 2-dimensional point to a 3-dimensional point at given depth + inline Point3 backproject(const Point2& p, double depth) const { + const Point2 pn = K_.calibrate(p); + const Point3 pc(pn.x()*depth, pn.y()*depth, depth); return pose_.transform_from(pc); } - inline Point3 backproject_from_camera(const Point2& pi, const double scale) const { - return backproject(pi, scale); - } - /** * Calculate range to a landmark * @param point 3D location of landmark + * @param H1 the optionally computed Jacobian with respect to pose + * @param H2 the optionally computed Jacobian with respect to the landmark * @return range (double) */ double range(const Point3& point, @@ -278,8 +302,8 @@ namespace gtsam { if(H1) { // Add columns of zeros to Jacobian for calibration Matrix& H1r(*H1); - H1r.conservativeResize(Eigen::NoChange, pose_.dim() + k_.dim()); - H1r.block(0, pose_.dim(), 1, k_.dim()) = Matrix::Zero(1, k_.dim()); + H1r.conservativeResize(Eigen::NoChange, pose_.dim() + K_.dim()); + H1r.block(0, pose_.dim(), 1, K_.dim()) = Matrix::Zero(1, K_.dim()); } return result; } @@ -287,6 +311,8 @@ namespace gtsam { /** * Calculate range to another pose * @param pose Other SO(3) pose + * @param H1 the optionally computed Jacobian with respect to pose + * @param H2 the optionally computed Jacobian with respect to the landmark * @return range (double) */ double range(const Pose3& pose, @@ -296,8 +322,8 @@ namespace gtsam { if(H1) { // Add columns of zeros to Jacobian for calibration Matrix& H1r(*H1); - H1r.conservativeResize(Eigen::NoChange, pose_.dim() + k_.dim()); - H1r.block(0, pose_.dim(), 1, k_.dim()) = Matrix::Zero(1, k_.dim()); + H1r.conservativeResize(Eigen::NoChange, pose_.dim() + K_.dim()); + H1r.block(0, pose_.dim(), 1, K_.dim()) = Matrix::Zero(1, K_.dim()); } return result; } @@ -305,6 +331,8 @@ namespace gtsam { /** * Calculate range to another camera * @param camera Other camera + * @param H1 the optionally computed Jacobian with respect to pose + * @param H2 the optionally computed Jacobian with respect to the landmark * @return range (double) */ template @@ -315,8 +343,8 @@ namespace gtsam { if(H1) { // Add columns of zeros to Jacobian for calibration Matrix& H1r(*H1); - H1r.conservativeResize(Eigen::NoChange, pose_.dim() + k_.dim()); - H1r.block(0, pose_.dim(), 1, k_.dim()) = Matrix::Zero(1, k_.dim()); + H1r.conservativeResize(Eigen::NoChange, pose_.dim() + K_.dim()); + H1r.block(0, pose_.dim(), 1, K_.dim()) = Matrix::Zero(1, K_.dim()); } if(H2) { // Add columns of zeros to Jacobian for calibration @@ -330,6 +358,8 @@ namespace gtsam { /** * Calculate range to another camera * @param camera Other camera + * @param H1 the optionally computed Jacobian with respect to pose + * @param H2 the optionally computed Jacobian with respect to the landmark * @return range (double) */ double range(const CalibratedCamera& camera, @@ -349,7 +379,7 @@ private: void serialize(Archive & ar, const unsigned int version) { ar & BOOST_SERIALIZATION_BASE_OBJECT_NVP(Value); ar & BOOST_SERIALIZATION_NVP(pose_); - ar & BOOST_SERIALIZATION_NVP(k_); + ar & BOOST_SERIALIZATION_NVP(K_); } /// @} }; diff --git a/gtsam/geometry/Point2.h b/gtsam/geometry/Point2.h index fe7792733..af5b1fbcd 100644 --- a/gtsam/geometry/Point2.h +++ b/gtsam/geometry/Point2.h @@ -29,7 +29,7 @@ namespace gtsam { * A 2D point * Complies with the Testable Concept * Functional, so no set functions: once created, a point is constant. - * @ingroup geometry + * @addtogroup geometry * \nosubgrouping */ class Point2 : public DerivedValue { @@ -58,7 +58,12 @@ public: /// @{ /// construct from 2D vector - Point2(const Vector& v) : x_(v(0)), y_(v(1)) { assert(v.size() == 2); } + Point2(const Vector& v) { + if(v.size() != 2) + throw std::invalid_argument("Point2 constructor from Vector requires that the Vector have dimension 2"); + x_ = v(0); + y_ = v(1); + } /// @} /// @name Testable diff --git a/gtsam/geometry/Point3.h b/gtsam/geometry/Point3.h index 9eeb748db..3e7423c0a 100644 --- a/gtsam/geometry/Point3.h +++ b/gtsam/geometry/Point3.h @@ -21,6 +21,7 @@ #pragma once +#include #include #include @@ -31,7 +32,7 @@ namespace gtsam { /** * A 3D point - * @ingroup geometry + * @addtogroup geometry * \nosubgrouping */ class Point3 : public DerivedValue { @@ -47,21 +48,24 @@ namespace gtsam { /// @name Standard Constructors /// @{ - ///TODO: comment + /// Default constructor creates a zero-Point3 Point3(): x_(0), y_(0), z_(0) {} - ///TODO: comment - Point3(const Point3 &p) : x_(p.x_), y_(p.y_), z_(p.z_) {} - - ///TODO: comment + /// Construct from x, y, and z coordinates Point3(double x, double y, double z): x_(x), y_(y), z_(z) {} /// @} /// @name Advanced Constructors /// @{ - ///TODO: comment - Point3(const Vector& v) : x_(v(0)), y_(v(1)), z_(v(2)) {} + /// Construct from 3-element vector + Point3(const Vector& v) { + if(v.size() != 3) + throw std::invalid_argument("Point3 constructor from Vector requires that the Vector have dimension 3"); + x_ = v(0); + y_ = v(1); + z_ = v(2); + } /// @} /// @name Testable @@ -150,7 +154,7 @@ namespace gtsam { /** distance between two points */ double dist(const Point3& p2) const { - return sqrt(pow(x()-p2.x(),2.0) + pow(y()-p2.y(),2.0) + pow(z()-p2.z(),2.0)); + return std::sqrt(pow(x()-p2.x(),2.0) + pow(y()-p2.y(),2.0) + pow(z()-p2.z(),2.0)); } /** Distance of the point from the origin */ diff --git a/gtsam/geometry/Pose2.cpp b/gtsam/geometry/Pose2.cpp index a15929c67..fa02ecfb8 100644 --- a/gtsam/geometry/Pose2.cpp +++ b/gtsam/geometry/Pose2.cpp @@ -20,6 +20,8 @@ #include #include #include +#include +#include using namespace std; @@ -44,7 +46,7 @@ Matrix Pose2::matrix() const { /* ************************************************************************* */ void Pose2::print(const string& s) const { - cout << s << "(" << t_.x() << ", " << t_.y() << ", " << r_.theta() << ")" << endl; + cout << s << setprecision(2) << "(" << t_.x() << ", " << t_.y() << ", " << r_.theta() << ")" << endl; } /* ************************************************************************* */ @@ -106,7 +108,7 @@ Vector Pose2::localCoordinates(const Pose2& p2) const { /* ************************************************************************* */ // Calculate Adjoint map // Ad_pose is 3*3 matrix that when applied to twist xi, returns Ad_pose(xi) -Matrix Pose2::AdjointMap() const { +Matrix Pose2::adjointMap() const { double c = r_.c(), s = r_.s(), x = t_.x(), y = t_.y(); return Matrix_(3,3, c, -s, y, @@ -117,7 +119,7 @@ Matrix Pose2::AdjointMap() const { /* ************************************************************************* */ Pose2 Pose2::inverse(boost::optional H1) const { - if (H1) *H1 = -AdjointMap(); + if (H1) *H1 = -adjointMap(); return Pose2(r_.inverse(), r_.unrotate(Point2(-t_.x(), -t_.y()))); } @@ -140,7 +142,7 @@ Point2 Pose2::transform_to(const Point2& point, Pose2 Pose2::compose(const Pose2& p2, boost::optional H1, boost::optional H2) const { // TODO: inline and reuse? - if(H1) *H1 = p2.inverse().AdjointMap(); + if(H1) *H1 = p2.inverse().adjointMap(); if(H2) *H2 = I3; return (*this)*p2; } diff --git a/gtsam/geometry/Pose2.h b/gtsam/geometry/Pose2.h index 877eb93a1..d091ddac8 100644 --- a/gtsam/geometry/Pose2.h +++ b/gtsam/geometry/Pose2.h @@ -30,7 +30,7 @@ namespace gtsam { /** * A 2D pose (Point2,Rot2) - * @ingroup geometry + * @addtogroup geometry * \nosubgrouping */ class Pose2 : public DerivedValue { @@ -158,10 +158,10 @@ public: * Calculate Adjoint map * Ad_pose is 3*3 matrix that when applied to twist xi, returns Ad_pose(xi) */ - Matrix AdjointMap() const; - inline Vector Adjoint(const Vector& xi) const { + Matrix adjointMap() const; + inline Vector adjoint(const Vector& xi) const { assert(xi.size() == 3); - return AdjointMap()*xi; + return adjointMap()*xi; } /** @@ -226,7 +226,7 @@ public: /** * Calculate bearing to a landmark * @param point 2D location of landmark - * @return 2D rotation \in SO(2) + * @return 2D rotation \f$ \in SO(2) \f$ */ Rot2 bearing(const Point2& point, boost::optional H1=boost::none, @@ -235,7 +235,7 @@ public: /** * Calculate bearing to another pose * @param point SO(2) location of other pose - * @return 2D rotation \in SO(2) + * @return 2D rotation \f$ \in SO(2) \f$ */ Rot2 bearing(const Pose2& point, boost::optional H1=boost::none, @@ -259,12 +259,26 @@ public: boost::optional H1=boost::none, boost::optional H2=boost::none) const; -private: - /// @} /// @name Advanced Interface /// @{ + /** + * Return the start and end indices (inclusive) of the translation component of the + * exponential map parameterization + * @return a pair of [start, end] indices into the tangent space vector + */ + inline static std::pair translationInterval() { return std::make_pair(0, 1); } + + /** + * Return the start and end indices (inclusive) of the rotation component of the + * exponential map parameterization + * @return a pair of [start, end] indices into the tangent space vector + */ + static std::pair rotationInterval() { return std::make_pair(2, 2); } + +private: + // Serialization function friend class boost::serialization::access; template diff --git a/gtsam/geometry/Pose3.cpp b/gtsam/geometry/Pose3.cpp index 59e5ceef5..be9869030 100644 --- a/gtsam/geometry/Pose3.cpp +++ b/gtsam/geometry/Pose3.cpp @@ -55,8 +55,9 @@ namespace gtsam { /* ************************************************************************* */ void Pose3::print(const string& s) const { - R_.print(s + ".R"); - t_.print(s + ".t"); + cout << s; + R_.print("R:\n"); + t_.print("t: "); } /* ************************************************************************* */ diff --git a/gtsam/geometry/Pose3.h b/gtsam/geometry/Pose3.h index 9cfe7ba37..dfae2d7a2 100644 --- a/gtsam/geometry/Pose3.h +++ b/gtsam/geometry/Pose3.h @@ -32,7 +32,7 @@ namespace gtsam { /** * A 3D pose (R,t) : (Rot3,Point3) - * @ingroup geometry + * @addtogroup geometry * \nosubgrouping */ class Pose3 : public DerivedValue { @@ -228,6 +228,20 @@ namespace gtsam { /// @name Advanced Interface /// @{ + /** + * Return the start and end indices (inclusive) of the translation component of the + * exponential map parameterization + * @return a pair of [start, end] indices into the tangent space vector + */ + inline static std::pair translationInterval() { return std::make_pair(3, 5); } + + /** + * Return the start and end indices (inclusive) of the rotation component of the + * exponential map parameterization + * @return a pair of [start, end] indices into the tangent space vector + */ + static std::pair rotationInterval() { return std::make_pair(0, 2); } + private: /** Serialization function */ friend class boost::serialization::access; diff --git a/gtsam/geometry/Rot2.h b/gtsam/geometry/Rot2.h index 8e33794e4..9e5e6fddc 100644 --- a/gtsam/geometry/Rot2.h +++ b/gtsam/geometry/Rot2.h @@ -28,7 +28,7 @@ namespace gtsam { /** * Rotation matrix * NOTE: the angle theta is in radians unless explicitly stated - * @ingroup geometry + * @addtogroup geometry * \nosubgrouping */ class Rot2 : public DerivedValue { @@ -83,9 +83,9 @@ namespace gtsam { /** * Named constructor with derivative * Calculate relative bearing to a landmark in local coordinate frame - * @param point 2D location of landmark + * @param d 2D location of landmark * @param H optional reference for Jacobian - * @return 2D rotation \in SO(2) + * @return 2D rotation \f$ \in SO(2) \f$ */ static Rot2 relativeBearing(const Point2& d, boost::optional H = boost::none); diff --git a/gtsam/geometry/Rot3.h b/gtsam/geometry/Rot3.h index 93e276de7..e3aaa6d32 100644 --- a/gtsam/geometry/Rot3.h +++ b/gtsam/geometry/Rot3.h @@ -48,7 +48,7 @@ namespace gtsam { * @brief A 3D rotation represented as a rotation matrix if the preprocessor * symbol GTSAM_DEFAULT_QUATERNIONS is not defined, or as a quaternion if it * is defined. - * @ingroup geometry + * @addtogroup geometry * \nosubgrouping */ class Rot3 : public DerivedValue { @@ -104,10 +104,10 @@ namespace gtsam { /// Rotation around X axis as in http://en.wikipedia.org/wiki/Rotation_matrix, counterclockwise when looking from unchanging axis. static Rot3 Rx(double t); - /// Rotation around X axis as in http://en.wikipedia.org/wiki/Rotation_matrix, counterclockwise when looking from unchanging axis. + /// Rotation around Y axis as in http://en.wikipedia.org/wiki/Rotation_matrix, counterclockwise when looking from unchanging axis. static Rot3 Ry(double t); - /// Rotation around X axis as in http://en.wikipedia.org/wiki/Rotation_matrix, counterclockwise when looking from unchanging axis. + /// Rotation around Z axis as in http://en.wikipedia.org/wiki/Rotation_matrix, counterclockwise when looking from unchanging axis. static Rot3 Rz(double t); /// Rotations around Z, Y, then X axes as in http://en.wikipedia.org/wiki/Rotation_matrix, counterclockwise when looking from unchanging axis. @@ -119,31 +119,17 @@ namespace gtsam { return RzRyRx(xyz(0), xyz(1), xyz(2)); } - /** - * Positive yaw is to right (as in aircraft heading). - * Tait-Bryan system from Spatial Reference Model (SRM) (x,y,z) = (roll,pitch,yaw) - * as described in http://www.sedris.org/wg8home/Documents/WG80462.pdf. - * Assumes vehicle coordinate frame X forward, Y right, Z down. - */ + /// Positive yaw is to right (as in aircraft heading). See ypr static Rot3 yaw (double t) { return Rz(t); } - /** - * Positive pitch is up (increasing aircraft altitude). - * Tait-Bryan system from Spatial Reference Model (SRM) (x,y,z) = (roll,pitch,yaw) - * as described in http://www.sedris.org/wg8home/Documents/WG80462.pdf. - * Assumes vehicle coordinate frame X forward, Y right, Z down. - */ + /// Positive pitch is up (increasing aircraft altitude).See ypr static Rot3 pitch(double t) { return Ry(t); } - /** - * Positive roll is to right (increasing yaw in aircraft). - * Tait-Bryan system from Spatial Reference Model (SRM) (x,y,z) = (roll,pitch,yaw) - * as described in http://www.sedris.org/wg8home/Documents/WG80462.pdf. - * Assumes vehicle coordinate frame X forward, Y right, Z down. - */ + //// Positive roll is to right (increasing yaw in aircraft). static Rot3 roll (double t) { return Rx(t); } - /** Returns rotation nRb from body to nav frame. + /** + * Returns rotation nRb from body to nav frame. * Positive yaw is to right (as in aircraft heading). * Positive pitch is up (increasing aircraft altitude). * Positive roll is to right (increasing yaw in aircraft). @@ -394,7 +380,7 @@ namespace gtsam { * such that A = R*Q = R*Qz'*Qy'*Qx'. When A is a rotation matrix, R will * be the identity and Q is a yaw-pitch-roll decomposition of A. * The implementation uses Givens rotations and is based on Hartley-Zisserman. - * @param a 3 by 3 matrix A=RQ + * @param A 3 by 3 matrix A=RQ * @return an upper triangular matrix R * @return a vector [thetax, thetay, thetaz] in radians. */ diff --git a/gtsam/geometry/SimpleCamera.cpp b/gtsam/geometry/SimpleCamera.cpp new file mode 100644 index 000000000..d441716cb --- /dev/null +++ b/gtsam/geometry/SimpleCamera.cpp @@ -0,0 +1,49 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file SimpleCamera.cpp + * @brief A simple camera class with a Cal3_S2 calibration + * @date June 30, 2012 + * @author Frank Dellaert + */ + +#include +#include + +namespace gtsam { + + SimpleCamera simpleCamera(const Matrix& P) { + + // P = [A|a] = s K cRw [I|-T], with s the unknown scale + Matrix A = P.topLeftCorner(3, 3); + Vector a = P.col(3); + + // do RQ decomposition to get s*K and cRw angles + Matrix sK; + Vector xyz; + boost::tie(sK, xyz) = RQ(A); + + // Recover scale factor s and K + double s = sK(2, 2); + Matrix K = sK / s; + + // Recover cRw itself, and its inverse + Rot3 cRw = Rot3::RzRyRx(xyz); + Rot3 wRc = cRw.inverse(); + + // Now, recover T from a = - s K cRw T = - A T + Vector T = -(A.inverse() * a); + return SimpleCamera(Pose3(wRc, T), + Cal3_S2(K(0, 0), K(1, 1), K(0, 1), K(0, 2), K(1, 2))); + } + +} diff --git a/gtsam/geometry/SimpleCamera.h b/gtsam/geometry/SimpleCamera.h index d3b0cdbdc..abe42f1a0 100644 --- a/gtsam/geometry/SimpleCamera.h +++ b/gtsam/geometry/SimpleCamera.h @@ -22,5 +22,10 @@ #include namespace gtsam { + + /// A simple camera class with a Cal3_S2 calibration typedef PinholeCamera SimpleCamera; + + /// Recover camera from 3*4 camera matrix + SimpleCamera simpleCamera(const Matrix& P); } diff --git a/gtsam/geometry/StereoCamera.h b/gtsam/geometry/StereoCamera.h index f5e07e66c..140ab1bdf 100644 --- a/gtsam/geometry/StereoCamera.h +++ b/gtsam/geometry/StereoCamera.h @@ -28,15 +28,19 @@ namespace gtsam { /** * A stereo camera class, parameterize by left camera pose and stereo calibration - * @ingroup geometry + * @addtogroup geometry */ -class StereoCamera { +class StereoCamera : public DerivedValue { private: Pose3 leftCamPose_; Cal3_S2Stereo::shared_ptr K_; public: + + /// @name Standard Constructors + /// @{ + StereoCamera() { } @@ -46,6 +50,54 @@ public: return K_; } + /// @} + /// @name Testable + /// @{ + + void print(const std::string& s = "") const { + leftCamPose_.print(s + ".camera."); + K_->print(s + ".calibration."); + } + + bool equals(const StereoCamera &camera, double tol = 1e-9) const { + return leftCamPose_.equals(camera.leftCamPose_, tol) && K_->equals( + *camera.K_, tol); + } + + /// @} + /// @name Manifold + /// @{ + + /** Dimensionality of the tangent space */ + inline size_t dim() const { + return 6; + } + + /** Dimensionality of the tangent space */ + static inline size_t Dim() { + return 6; + } + + /// Updates a with tangent space delta + inline StereoCamera retract(const Vector& v) const { + return StereoCamera(pose().retract(v), K_); + } + + /// Local coordinates of manifold neighborhood around current value + inline Vector localCoordinates(const StereoCamera& t2) const { + return Vector(leftCamPose_.localCoordinates(t2.leftCamPose_)); + } + + Pose3 between(const StereoCamera &camera, + boost::optional H1=boost::none, + boost::optional H2=boost::none) const { + return leftCamPose_.between(camera.pose(), H1, H2); + } + + /// @} + /// @name Standard Interface + /// @{ + const Pose3& pose() const { return leftCamPose_; } @@ -71,16 +123,6 @@ public: return project(point, H1, H2); } - /* - * backproject using left camera calibration, up to scale only - * i.e. does not rely on baseline - */ - Point3 backproject(const Point2& projection, const double scale) const { - Point2 intrinsic = K_->calibrate(projection); - Point3 cameraPoint = Point3(intrinsic.x() * scale, intrinsic.y() * scale, scale);; - return pose().transform_from(cameraPoint); - } - Point3 backproject(const StereoPoint2& z) const { Vector measured = z.vector(); double Z = K_->baseline()*K_->fx()/(measured[0]-measured[1]); @@ -90,40 +132,7 @@ public: return world_point; } - /** Dimensionality of the tangent space */ - inline size_t dim() const { - return 6; - } - - /** Dimensionality of the tangent space */ - static inline size_t Dim() { - return 6; - } - - bool equals(const StereoCamera &camera, double tol = 1e-9) const { - return leftCamPose_.equals(camera.leftCamPose_, tol) && K_->equals( - *camera.K_, tol); - } - - // Manifold requirements - use existing expmap/logmap - inline StereoCamera retract(const Vector& v) const { - return StereoCamera(pose().retract(v), K_); - } - - inline Vector localCoordinates(const StereoCamera& t2) const { - return Vector(leftCamPose_.localCoordinates(t2.leftCamPose_)); - } - - Pose3 between(const StereoCamera &camera, - boost::optional H1=boost::none, - boost::optional H2=boost::none) const { - return leftCamPose_.between(camera.pose(), H1, H2); - } - - void print(const std::string& s = "") const { - leftCamPose_.print(s + ".camera."); - K_->print(s + ".calibration."); - } + /// @} private: /** utility functions */ @@ -132,7 +141,9 @@ private: friend class boost::serialization::access; template void serialize(Archive & ar, const unsigned int version) { - ar & BOOST_SERIALIZATION_NVP(leftCamPose_); + ar & boost::serialization::make_nvp("StereoCamera", + boost::serialization::base_object(*this)); + ar & BOOST_SERIALIZATION_NVP(leftCamPose_); ar & BOOST_SERIALIZATION_NVP(K_); } diff --git a/gtsam/geometry/StereoPoint2.h b/gtsam/geometry/StereoPoint2.h index 43701e4e8..6bfdefe26 100644 --- a/gtsam/geometry/StereoPoint2.h +++ b/gtsam/geometry/StereoPoint2.h @@ -25,7 +25,7 @@ namespace gtsam { /** * A 2D stereo point, v will be same for rectified images - * @ingroup geometry + * @addtogroup geometry * \nosubgrouping */ class StereoPoint2 : public DerivedValue { @@ -119,6 +119,11 @@ namespace gtsam { return p.vector(); } + /** The difference between another point and this point */ + inline StereoPoint2 between(const StereoPoint2& p2) const { + return gtsam::between_default(*this, p2); + } + /// @} /// @name Standard Interface /// @{ @@ -133,11 +138,6 @@ namespace gtsam { return Point2(uL_, v_); } - ///TODO comment - inline StereoPoint2 between(const StereoPoint2& p2) const { - return gtsam::between_default(*this, p2); - } - private: /// @} diff --git a/gtsam/geometry/Tensor1.h b/gtsam/geometry/Tensor1.h deleted file mode 100644 index 685166b53..000000000 --- a/gtsam/geometry/Tensor1.h +++ /dev/null @@ -1,85 +0,0 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) - - * See LICENSE for the license information - - * -------------------------------------------------------------------------- */ - -/** - * @file Tensor1.h - * @brief Rank 1 tensors based on http://www.gps.caltech.edu/~walter/FTensor/FTensor.pdf - * @date Feb 10, 2010 - * @author Frank Dellaert - */ - -#pragma once -#include - -namespace tensors { - - /** - * A rank 1 tensor. Actually stores data. - * @ingroup tensors - * \nosubgrouping - */ - template - class Tensor1 { - double T[N]; ///< Storage - - public: - - /// @name Standard Constructors - /// @{ - - /** default constructor */ - Tensor1() { - } - - /** construct from data */ - Tensor1(const double* data) { - for (int i = 0; i < N; i++) - T[i] = data[i]; - } - - /** construct from expression */ - template - Tensor1(const Tensor1Expression >& a) { - for (int i = 0; i < N; i++) - T[i] = a(i); - } - - /// @} - /// @name Standard Interface - /// @{ - - /** return data */ - inline int dim() const { - return N; - } - - /** return data */ - inline const double& operator()(int i) const { - return T[i]; - } - - /** return data */ - inline double& operator()(int i) { - return T[i]; - } - - /// return an expression associated with an index - template Tensor1Expression > operator()( - Index index) const { - return Tensor1Expression >(*this); - } - - /// @} - - }; -// Tensor1 - -}// namespace tensors diff --git a/gtsam/geometry/Tensor1Expression.h b/gtsam/geometry/Tensor1Expression.h deleted file mode 100644 index 4e43fff58..000000000 --- a/gtsam/geometry/Tensor1Expression.h +++ /dev/null @@ -1,181 +0,0 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) - - * See LICENSE for the license information - - * -------------------------------------------------------------------------- */ - -/** - * @file Tensor1Expression.h - * @brief Tensor expression templates based on http://www.gps.caltech.edu/~walter/FTensor/FTensor.pdf - * @date Feb 10, 2010 - * @author Frank Dellaert - */ - -#pragma once - -#include -#include -#include -#include - -namespace tensors { - - /** - * Templated class to provide a rank 1 tensor interface to a class. - * This class does not store any data but the result of an expression. - * It is associated with an index. - * @ingroup tensors - * \nosubgrouping - */ - template class Tensor1Expression { - - private: - - A iter; - - typedef Tensor1Expression This; - - /** Helper class for multiplying with a double */ - class TimesDouble_ { - A iter; - const double s; - public: - /// Constructor - TimesDouble_(const A &a, double s_) : - iter(a), s(s_) { - } - /// Element access - inline double operator()(int i) const { - return iter(i) * s; - } - }; - - public: - - /// @name Standard Constructors - /// @{ - - /** constructor */ - Tensor1Expression(const A &a) : - iter(a) { - } - - /// @} - /// @name Testable - /// @{ - - /** Print */ - void print(const std::string s = "") const { - std::cout << s << "{"; - std::cout << (*this)(0); - for (int i = 1; i < I::dim; i++) - std::cout << ", "<< (*this)(i); - std::cout << "}" << std::endl; - } - - /// equality - template - bool equals(const Tensor1Expression & q, double tol) const { - for (int i = 0; i < I::dim; i++) - if (fabs((*this)(i) - q(i)) > tol) return false; - return true; - } - - /// @} - /// @name Standard Interface - /// @{ - - /** norm */ - double norm() const { - double sumsqr = 0.0; - for (int i = 0; i < I::dim; i++) - sumsqr += iter(i) * iter(i); - return sqrt(sumsqr); - } - - /// test equivalence - template - bool equivalent(const Tensor1Expression & q, double tol = 1e-9) const { - return ((*this) * (1.0 / norm())).equals(q * (1.0 / q.norm()), tol) - || ((*this) * (-1.0 / norm())).equals(q * (1.0 / q.norm()), tol); - } - - /** Check if two expressions are equal */ - template - bool operator==(const Tensor1Expression& e) const { - for (int i = 0; i < I::dim; i++) - if (iter(i) != e(i)) return false; - return true; - } - - /** element access */ - double operator()(int i) const { - return iter(i); - } - - /** mutliply with a double. */ - inline Tensor1Expression operator*(double s) const { - return TimesDouble_(iter, s); - } - - /** Class for contracting two rank 1 tensor expressions, yielding a double. */ - template - inline double operator*(const Tensor1Expression &b) const { - double sum = 0.0; - for (int i = 0; i < I::dim; i++) - sum += (*this)(i) * b(i); - return sum; - } - - }; // Tensor1Expression - - /// @} - /// @name Advanced Interface - /// @{ - - /** Print a rank 1 expression */ - template - void print(const Tensor1Expression& T, const std::string s = "") { - T.print(s); - } - - /** norm */ - template - double norm(const Tensor1Expression& T) { - return T.norm(); - } - - /** - * This template works for any two expressions - */ - template - bool assert_equality(const Tensor1Expression& expected, - const Tensor1Expression& actual, double tol = 1e-9) { - if (actual.equals(expected, tol)) return true; - std::cout << "Not equal:\n"; - expected.print("expected:\n"); - actual.print("actual:\n"); - return false; - } - - /** - * This template works for any two expressions - */ - template - bool assert_equivalent(const Tensor1Expression& expected, - const Tensor1Expression& actual, double tol = 1e-9) { - if (actual.equivalent(expected, tol)) return true; - std::cout << "Not equal:\n"; - expected.print("expected:\n"); - actual.print("actual:\n"); - return false; - } - - /// @} - -} // namespace tensors diff --git a/gtsam/geometry/Tensor2.h b/gtsam/geometry/Tensor2.h deleted file mode 100644 index 12fd1509f..000000000 --- a/gtsam/geometry/Tensor2.h +++ /dev/null @@ -1,84 +0,0 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) - - * See LICENSE for the license information - - * -------------------------------------------------------------------------- */ - -/** - * @file Tensor2.h - * @brief Rank 2 Tensor based on http://www.gps.caltech.edu/~walter/FTensor/FTensor.pdf - * @date Feb 10, 2010 - * @author Frank Dellaert - */ - -#pragma once -#include - -namespace tensors { - -/** - * Rank 2 Tensor - * @ingroup tensors - * \nosubgrouping - */ -template -class Tensor2 { -protected: - Tensor1 T[N2]; ///< Storage - -public: - - /// @name Standard Constructors - /// @{ - - /** default constructor */ - Tensor2() { - } - - /// construct from data - expressed in row major form - Tensor2(const double data[N2][N1]) { - for (int j = 0; j < N2; j++) - T[j] = Tensor1 (data[j]); - } - - /** construct from expression */ - template - Tensor2(const Tensor2Expression , Index >& a) { - for (int j = 0; j < N2; j++) - T[j] = a(j); - } - - /// @} - /// @name Standard Interface - /// @{ - - /** dimension - TODO: is this right for anything other than 3x3? */ - size_t dim() const {return N1 * N2;} - - /// const element access - const double & operator()(int i, int j) const { - return T[j](i); - } - - /// element access - double & operator()(int i, int j) { - return T[j](i); - } - - /** convert to expression */ - template Tensor2Expression , Index< - N2, J> > operator()(Index i, Index j) const { - return Tensor2Expression , Index > (*this); - } - - /// @} - -}; - -} // namespace tensors - diff --git a/gtsam/geometry/Tensor2Expression.h b/gtsam/geometry/Tensor2Expression.h deleted file mode 100644 index 6c953a5aa..000000000 --- a/gtsam/geometry/Tensor2Expression.h +++ /dev/null @@ -1,310 +0,0 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) - - * See LICENSE for the license information - - * -------------------------------------------------------------------------- */ - -/** - * @file Tensor2Expression.h - * @brief Tensor expression templates based on http://www.gps.caltech.edu/~walter/FTensor/FTensor.pdf - * @date Feb 10, 2010 - * @author Frank Dellaert - */ - -#pragma once - -#include -#include -#include - -namespace tensors { - - /** - * Templated class to hold a rank 2 tensor expression. - * @ingroup tensors - * \nosubgrouping - */ - template class Tensor2Expression { - - private: - - A iter; - - typedef Tensor2Expression This; - - /** Helper class for instantiating one index */ - class FixJ_ { - const int j; - const A iter; - public: - FixJ_(int j_, const A &a) : - j(j_), iter(a) { - } - double operator()(int i) const { - return iter(i, j); - } - }; - - /** Helper class for swapping indices */ - class Swap_ { - const A iter; - public: - /// Constructor - Swap_(const A &a) : - iter(a) { - } - /// Element access - double operator()(int j, int i) const { - return iter(i, j); - } - }; - - /** Helper class for multiplying with a double */ - class TimesDouble_ { - A iter; - const double s; - public: - /// Constructor - TimesDouble_(const A &a, double s_) : - iter(a), s(s_) { - } - /// Element access - inline double operator()(int i, int j) const { - return iter(i, j) * s; - } - }; - - /** Helper class for contracting index I with rank 1 tensor */ - template class ITimesRank1_ { - const This a; - const Tensor1Expression b; - public: - /// Constructor - ITimesRank1_(const This &a_, const Tensor1Expression &b_) : - a(a_), b(b_) { - } - /// Element access - double operator()(int j) const { - double sum = 0.0; - for (int i = 0; i < I::dim; i++) - sum += a(i, j) * b(i); - return sum; - } - }; - - /** Helper class for contracting index J with rank 1 tensor */ - template class JTimesRank1_ { - const This a; - const Tensor1Expression b; - public: - /// Constructor - JTimesRank1_(const This &a_, const Tensor1Expression &b_) : - a(a_), b(b_) { - } - /// Element access - double operator()(int i) const { - double sum = 0.0; - for (int j = 0; j < J::dim; j++) - sum += a(i, j) * b(j); - return sum; - } - }; - - /** Helper class for contracting index I with rank 2 tensor */ - template class ITimesRank2_ { - const This a; - const Tensor2Expression b; - public: - /// Constructor - ITimesRank2_(const This &a_, const Tensor2Expression &b_) : - a(a_), b(b_) { - } - /// Element access - double operator()(int j, int k) const { - double sum = 0.0; - for (int i = 0; i < I::dim; i++) - sum += a(i, j) * b(i, k); - return sum; - } - }; - - public: - - /// @name Standard Constructors - /// @{ - - /** constructor */ - Tensor2Expression(const A &a) : - iter(a) { - } - - /// @} - /// @name Testable - /// @{ - - /** Print */ - void print(const std::string& s = "Tensor2:") const { - std::cout << s << "{"; - (*this)(0).print(); - for (int j = 1; j < J::dim; j++) { - std::cout << ","; - (*this)(j).print(""); - } - std::cout << "}" << std::endl; - } - - /// test equality - template - bool equals(const Tensor2Expression & q, double tol) const { - for (int j = 0; j < J::dim; j++) - if (!(*this)(j).equals(q(j), tol)) - return false; - return true; - } - - /// @} - /// @name Standard Interface - /// @{ - - /** norm */ - double norm() const { - double sumsqr = 0.0; - for (int i = 0; i < I::dim; i++) - for (int j = 0; j < J::dim; j++) - sumsqr += iter(i, j) * iter(i, j); - return sqrt(sumsqr); - } - - /// test equivalence - template - bool equivalent(const Tensor2Expression & q, double tol) const { - return ((*this) * (1.0 / norm())).equals(q * (1.0 / q.norm()), tol) - || ((*this) * (-1.0 / norm())).equals(q * (1.0 / q.norm()), tol); - } - - /** element access */ - double operator()(int i, int j) const { - return iter(i, j); - } - - /** swap indices */ - typedef Tensor2Expression Swapped; - /// Return Swap_ helper class - Swapped swap() { - return Swap_(iter); - } - - /** mutliply with a double. */ - inline Tensor2Expression operator*(double s) const { - return TimesDouble_(iter, s); - } - - /** Fix a single index */ - Tensor1Expression operator()(int j) const { - return FixJ_(j, iter); - } - - /** Check if two expressions are equal */ - template - bool operator==(const Tensor2Expression& T) const { - for (int i = 0; i < I::dim; i++) - for (int j = 0; j < J::dim; j++) - if (iter(i, j) != T(i, j)) - return false; - return true; - } - - /// @} - /// @name Advanced Interface - /// @{ - - /** c(j) = a(i,j)*b(i) */ - template - inline Tensor1Expression, J> operator*( - const Tensor1Expression& p) { - return ITimesRank1_(*this, p); - } - - /** c(i) = a(i,j)*b(j) */ - template - inline Tensor1Expression, I> operator*( - const Tensor1Expression &p) { - return JTimesRank1_(*this, p); - } - - /** c(j,k) = a(i,j)*T(i,k) */ - template - inline Tensor2Expression , J, K> operator*( - const Tensor2Expression& p) { - return ITimesRank2_(*this, p); - } - - }; - // Tensor2Expression - - /** Print */ - template - void print(const Tensor2Expression& T, const std::string& s = - "Tensor2:") { - T.print(s); - } - - /** Helper class for multiplying two covariant tensors */ - template class Rank1Rank1_ { - const Tensor1Expression iterA; - const Tensor1Expression iterB; - public: - /// Constructor - Rank1Rank1_(const Tensor1Expression &a, - const Tensor1Expression &b) : - iterA(a), iterB(b) { - } - /// element access - double operator()(int i, int j) const { - return iterA(i) * iterB(j); - } - }; - - /** Multiplying two different indices yields an outer product */ - template - inline Tensor2Expression , I, J> operator*( - const Tensor1Expression &a, const Tensor1Expression &b) { - return Rank1Rank1_(a, b); - } - - /** - * This template works for any two expressions - */ - template - bool assert_equality(const Tensor2Expression& expected, - const Tensor2Expression& actual, double tol = 1e-9) { - if (actual.equals(expected, tol)) - return true; - std::cout << "Not equal:\n"; - expected.print("expected:\n"); - actual.print("actual:\n"); - return false; - } - - /** - * This template works for any two expressions - */ - template - bool assert_equivalent(const Tensor2Expression& expected, - const Tensor2Expression& actual, double tol = 1e-9) { - if (actual.equivalent(expected, tol)) - return true; - std::cout << "Not equal:\n"; - expected.print("expected:\n"); - actual.print("actual:\n"); - return false; - } - - /// @} - -} // namespace tensors diff --git a/gtsam/geometry/Tensor3.h b/gtsam/geometry/Tensor3.h deleted file mode 100644 index 78cdcb9f2..000000000 --- a/gtsam/geometry/Tensor3.h +++ /dev/null @@ -1,106 +0,0 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) - - * See LICENSE for the license information - - * -------------------------------------------------------------------------- */ - -/** - * @file Tensor3.h - * @brief Rank 3 tensors based on http://www.gps.caltech.edu/~walter/FTensor/FTensor.pdf - * @date Feb 10, 2010 - * @author: Frank Dellaert - */ - -#pragma once -#include - -namespace tensors { - - /** - * Rank 3 Tensor - * @ingroup tensors - * \nosubgrouping - */ - template - class Tensor3 { - Tensor2 T[N3]; ///< Storage - - public: - - /// @name Standard Constructors - /// @{ - - /** default constructor */ - Tensor3() { - } - - /** construct from data */ - Tensor3(const double data[N3][N2][N1]) { - for (int k = 0; k < N3; k++) - T[k] = data[k]; - } - - /// @} - /// @name Advanced Constructors - /// @{ - - /** construct from expression */ - template - Tensor3(const Tensor3Expression , Index , Index >& a) { - for (int k = 0; k < N3; k++) - T[k] = a(k); - } - - /// @} - /// @name Standard Interface - /// @{ - - /// element access - double operator()(int i, int j, int k) const { - return T[k](i, j); - } - - /** convert to expression */ - template Tensor3Expression , - Index , Index > operator()(const Index& i, - const Index& j, const Index& k) { - return Tensor3Expression , Index , Index > (*this); - } - - /** convert to expression */ - template Tensor3Expression , - Index , Index > operator()(const Index& i, - const Index& j, const Index& k) const { - return Tensor3Expression , Index , Index > (*this); - } - }; // Tensor3 - - /** Rank 3 permutation tensor */ - struct Eta3 { - - /** calculate value. TODO: wasteful to actually use this */ - double operator()(int i, int j, int k) const { - return ((j - i) * (k - i) * (k - j)) / 2; - } - - /** create expression */ - template Tensor3Expression , - Index<3, J> , Index<3, K> > operator()(const Index<3, I>& i, - const Index<3, J>& j, const Index<3, K>& k) const { - return Tensor3Expression , Index<3, J> , Index<3, K> > ( - *this); - } - - }; // Eta - - /// @} - -} // namespace tensors diff --git a/gtsam/geometry/Tensor3Expression.h b/gtsam/geometry/Tensor3Expression.h deleted file mode 100644 index 0356caa6f..000000000 --- a/gtsam/geometry/Tensor3Expression.h +++ /dev/null @@ -1,194 +0,0 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) - - * See LICENSE for the license information - - * -------------------------------------------------------------------------- */ - -/** - * @file Tensor3Expression.h - * @brief Tensor expression templates based on http://www.gps.caltech.edu/~walter/FTensor/FTensor.pdf - * @date Feb 10, 2010 - * @author Frank Dellaert - */ - -#pragma once - -#include -#include - -namespace tensors { - - /** - * templated class to interface to an object A as a rank 3 tensor - * @ingroup tensors - * \nosubgrouping - */ - template class Tensor3Expression { - A iter; - - typedef Tensor3Expression This; - - /** Helper class for instantiating one index */ - class FixK_ { - const int k; - const A iter; - public: - FixK_(int k_, const A &a) : - k(k_), iter(a) { - } - double operator()(int i, int j) const { - return iter(i, j, k); - } - }; - - /** Helper class for contracting rank3 and rank1 tensor */ - template class TimesRank1_ { - typedef Tensor1Expression Rank1; - const This T; - const Rank1 t; - public: - TimesRank1_(const This &a, const Rank1 &b) : - T(a), t(b) { - } - double operator()(int j, int k) const { - double sum = 0.0; - for (int i = 0; i < I::dim; i++) - sum += T(i, j, k) * t(i); - return sum; - } - }; - - public: - - /// @name Standard Constructors - /// @{ - - /** constructor */ - Tensor3Expression(const A &a) : - iter(a) { - } - - /// @} - /// @name Standard Interface - /// @{ - - /** Print */ - void print(const std::string& s = "Tensor3:") const { - std::cout << s << "{"; - (*this)(0).print(""); - for (int k = 1; k < K::dim; k++) { - std::cout << ","; - (*this)(k).print(""); - } - std::cout << "}" << std::endl; - } - - /// test equality - template - bool equals(const Tensor3Expression & q, double tol) const { - for (int k = 0; k < K::dim; k++) - if (!(*this)(k).equals(q(k), tol)) return false; - return true; - } - - /** element access */ - double operator()(int i, int j, int k) const { - return iter(i, j, k); - } - - /** Fix a single index */ - Tensor2Expression operator()(int k) const { - return FixK_(k, iter); - } - - /** Contracting with rank1 tensor */ - template - inline Tensor2Expression , J, K> operator*( - const Tensor1Expression &b) const { - return TimesRank1_ (*this, b); - } - - }; // Tensor3Expression - - /// @} - /// @name Advanced Interface - /// @{ - - /** Print */ - template - void print(const Tensor3Expression& T, const std::string& s = - "Tensor3:") { - T.print(s); - } - - /** Helper class for outer product of rank2 and rank1 tensor */ - template - class Rank2Rank1_ { - typedef Tensor2Expression Rank2; - typedef Tensor1Expression Rank1; - const Rank2 iterA; - const Rank1 iterB; - public: - /// Constructor - Rank2Rank1_(const Rank2 &a, const Rank1 &b) : - iterA(a), iterB(b) { - } - /// Element access - double operator()(int i, int j, int k) const { - return iterA(i, j) * iterB(k); - } - }; - - /** outer product of rank2 and rank1 tensor */ - template - inline Tensor3Expression , I, J, K> operator*( - const Tensor2Expression& a, const Tensor1Expression &b) { - return Rank2Rank1_ (a, b); - } - - /** Helper class for outer product of rank1 and rank2 tensor */ - template - class Rank1Rank2_ { - typedef Tensor1Expression Rank1; - typedef Tensor2Expression Rank2; - const Rank1 iterA; - const Rank2 iterB; - public: - /// Constructor - Rank1Rank2_(const Rank1 &a, const Rank2 &b) : - iterA(a), iterB(b) { - } - /// Element access - double operator()(int i, int j, int k) const { - return iterA(i) * iterB(j, k); - } - }; - - /** outer product of rank2 and rank1 tensor */ - template - inline Tensor3Expression , I, J, K> operator*( - const Tensor1Expression& a, const Tensor2Expression &b) { - return Rank1Rank2_ (a, b); - } - - /** - * This template works for any two expressions - */ - template - bool assert_equality(const Tensor3Expression& expected, - const Tensor3Expression& actual, double tol = 1e-9) { - if (actual.equals(expected, tol)) return true; - std::cout << "Not equal:\n"; - expected.print("expected:\n"); - actual.print("actual:\n"); - return false; - } - - /// @} - -} // namespace tensors diff --git a/gtsam/geometry/Tensor4.h b/gtsam/geometry/Tensor4.h deleted file mode 100644 index 26a52750c..000000000 --- a/gtsam/geometry/Tensor4.h +++ /dev/null @@ -1,58 +0,0 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) - - * See LICENSE for the license information - - * -------------------------------------------------------------------------- */ - -/** - * @file Tensor4.h - * @brief Rank 4 tensors based on http://www.gps.caltech.edu/~walter/FTensor/FTensor.pdf - * @date Feb 12, 2010 - * @author Frank Dellaert - */ - -#pragma once -#include - -namespace tensors { - - /** - * Rank 4 Tensor - * @ingroup tensors - * \nosubgrouping - */ - template - class Tensor4 { - - private: - - Tensor3 T[N4]; ///< Storage - - public: - - /// @name Standard Constructors - /// @{ - - /** default constructor */ - Tensor4() { - } - - /// @} - /// @name Standard Interface - /// @{ - - /// element access - double operator()(int i, int j, int k, int l) const { - return T[l](i, j, k); - } - - /// @} - - }; // Tensor4 - -} // namespace tensors diff --git a/gtsam/geometry/Tensor5.h b/gtsam/geometry/Tensor5.h deleted file mode 100644 index e12f7d2fb..000000000 --- a/gtsam/geometry/Tensor5.h +++ /dev/null @@ -1,75 +0,0 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) - - * See LICENSE for the license information - - * -------------------------------------------------------------------------- */ - -/** - * @file Tensor5.h - * @brief Rank 5 tensors based on http://www.gps.caltech.edu/~walter/FTensor/FTensor.pdf - * @date Feb 12, 2010 - * @author Frank Dellaert - */ - -#pragma once -#include - -namespace tensors { - - /** - * Rank 5 Tensor - * @ingroup tensors - * \nosubgrouping - */ - template - class Tensor5 { - - private: - - Tensor4 T[N5]; ///< Storage - - public: - - /// @name Standard Constructors - /// @{ - - /** default constructor */ - Tensor5() { - } - - /// @} - /// @name Standard Interface - /// @{ - - /** construct from expression */ - template - Tensor5(const Tensor5Expression , Index , Index , Index , Index >& a) { - for (int m = 0; m < N5; m++) - T[m] = a(m); - } - - /// element access - double operator()(int i, int j, int k, int l, int m) const { - return T[m](i, j, k, l); - } - - /** convert to expression */ - template Tensor5Expression , Index , Index , Index , - Index > operator()(Index i, Index j, - Index k, Index l, Index m) { - return Tensor5Expression , Index , Index , Index , Index > (*this); - } - - /// @} - - }; // Tensor5 - -} // namespace tensors diff --git a/gtsam/geometry/Tensor5Expression.h b/gtsam/geometry/Tensor5Expression.h deleted file mode 100644 index e9f0e852a..000000000 --- a/gtsam/geometry/Tensor5Expression.h +++ /dev/null @@ -1,135 +0,0 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) - - * See LICENSE for the license information - - * -------------------------------------------------------------------------- */ - -/** - * @file Tensor5Expression.h - * @brief Tensor expression templates based on http://www.gps.caltech.edu/~walter/FTensor/FTensor.pdf - * @date Feb 10, 2010 - * @author Frank Dellaert - */ - -#pragma once - -#include -#include - -namespace tensors { - - /** - * templated class to interface to an object A as a rank 5 tensor - * @ingroup tensors - * \nosubgrouping - */ - template class Tensor5Expression { - A iter; - - typedef Tensor5Expression This; - - /** Helper class for swapping indices 3 and 4 :-) */ - class Swap34_ { - const A iter; - public: - /// Constructor - Swap34_(const A &a) : - iter(a) { - } - /// swapping element access - double operator()(int i, int j, int k, int l, int m) const { - return iter(i, j, l, k, m); - } - }; - - public: - - /// @name Standard Constructors - /// @{ - - /** constructor */ - Tensor5Expression(const A &a) : - iter(a) { - } - - /// @} - /// @name Standard Interface - /// @{ - - /** Print */ - void print(const std::string& s = "Tensor5:") const { - std::cout << s << std::endl; - for (int m = 0; m < M::dim; m++) - for (int l = 0; l < L::dim; l++) - for (int k = 0; k < K::dim; k++) { - std::cout << "(m,l,k) = (" << m << "," << l << "," << k << ")" - << std::endl; - for (int j = 0; j < J::dim; j++) { - for (int i = 0; i < I::dim; i++) - std::cout << " " << (*this)(i, j, k, l, m); - std::cout << std::endl; - } - } - std::cout << std::endl; - } - - /** swap indices */ - typedef Tensor5Expression Swapped; - /// create Swap34_ helper class - Swapped swap34() { - return Swap34_(iter); - } - - /** element access */ - double operator()(int i, int j, int k, int l, int m) const { - return iter(i, j, k, l, m); - } - - }; - // Tensor5Expression - - /// @} - /// @name Advanced Interface - /// @{ - - /** Print */ - template - void print(const Tensor5Expression& T, - const std::string& s = "Tensor5:") { - T.print(s); - } - - /** Helper class for outer product of rank3 and rank2 tensor */ - template - class Rank3Rank2_ { - typedef Tensor3Expression Rank3; - typedef Tensor2Expression Rank2; - const Rank3 iterA; - const Rank2 iterB; - public: - /// Constructor - Rank3Rank2_(const Rank3 &a, const Rank2 &b) : - iterA(a), iterB(b) { - } - /// Element access - double operator()(int i, int j, int k, int l, int m) const { - return iterA(i, j, k) * iterB(l, m); - } - }; - - /** outer product of rank2 and rank1 tensor */ - template - inline Tensor5Expression , I, J, K, L, M> operator*( - const Tensor3Expression& a, - const Tensor2Expression &b) { - return Rank3Rank2_(a, b); - } - - /// @} - -} // namespace tensors diff --git a/gtsam/geometry/concepts.h b/gtsam/geometry/concepts.h index 3000530e5..bde16ee6e 100644 --- a/gtsam/geometry/concepts.h +++ b/gtsam/geometry/concepts.h @@ -49,6 +49,14 @@ private: static Translation checkTranslationMemberAccess(const POSE& p) { return p.translation(); } + + static std::pair checkTranslationInterval() { + return POSE::translationInterval(); + } + + static std::pair checkRotationInterval() { + return POSE::rotationInterval(); + } }; /** diff --git a/gtsam/geometry/projectiveGeometry.cpp b/gtsam/geometry/projectiveGeometry.cpp deleted file mode 100644 index 31c975c43..000000000 --- a/gtsam/geometry/projectiveGeometry.cpp +++ /dev/null @@ -1,71 +0,0 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) - - * See LICENSE for the license information - - * -------------------------------------------------------------------------- */ - -/** - * @file projectiveGeometry.cpp - * @brief Projective geometry, implemented using tensor library - * @date Feb 12, 2010 - * @author: Frank Dellaert - */ - -#include -#include - -#include -#include - -namespace gtsam { - - using namespace std; - using namespace tensors; - - /* ************************************************************************* */ - Point2h point2h(double x, double y, double w) { - double data[3]; - data[0] = x; - data[1] = y; - data[2] = w; - return data; - } - - /* ************************************************************************* */ - Line2h line2h(double a, double b, double c) { - double data[3]; - data[0] = a; - data[1] = b; - data[2] = c; - return data; - } - - /* ************************************************************************* */ - Point3h point3h(double X, double Y, double Z, double W) { - double data[4]; - data[0] = X; - data[1] = Y; - data[2] = Z; - data[3] = W; - return data; - } - - /* ************************************************************************* */ - Plane3h plane3h(double a, double b, double c, double d) { - double data[4]; - data[0] = a; - data[1] = b; - data[2] = c; - data[3] = d; - return data; - } - - - /* ************************************************************************* */ - -} // namespace gtsam diff --git a/gtsam/geometry/projectiveGeometry.h b/gtsam/geometry/projectiveGeometry.h deleted file mode 100644 index cfad515ac..000000000 --- a/gtsam/geometry/projectiveGeometry.h +++ /dev/null @@ -1,124 +0,0 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) - - * See LICENSE for the license information - - * -------------------------------------------------------------------------- */ - -/** - * @file projectiveGeometry.h - * @brief Projective geometry, implemented using tensor library - * @date Feb 12, 2010 - * @author Frank Dellaert - */ - -#pragma once - -#include -#include - -namespace gtsam { - - /** - * 2D Point in homogeneous coordinates - * @ingroup geometry - */ - typedef tensors::Tensor1<3> Point2h; - Point2h point2h(double x, double y, double w); ///< create Point2h - - /** - * 2D Line in homogeneous coordinates - * @ingroup geometry - */ - typedef tensors::Tensor1<3> Line2h; - Line2h line2h(double a, double b, double c); ///< create Line2h - - /** - * 2D (homegeneous) Point correspondence - * @ingroup geometry - */ - struct Correspondence { - Point2h first; ///< First point - Point2h second; ///< Second point - - /// Create a correspondence pair - Correspondence(const Point2h &p1, const Point2h &p2) : - first(p1), second(p2) { - } - /// Swap points - Correspondence swap() const { - return Correspondence(second, first); - } - /// print - void print() { - tensors::Index<3, 'i'> i; - tensors::print(first(i), "first :"); - tensors::print(second(i), "second:"); - } - }; - - /** - * 2D-2D Homography - * @ingroup geometry - */ - typedef tensors::Tensor2<3, 3> Homography2; - - /** - * Fundamental Matrix - * @ingroup geometry - */ - typedef tensors::Tensor2<3, 3> FundamentalMatrix; - - /** - * Triplet of (homogeneous) 2D points - * @ingroup geometry - */ - struct Triplet { - Point2h first; ///< First point - Point2h second; ///< Second point - Point2h third; ///< Third point - - /// Create a Triplet correspondence - Triplet(const Point2h &p1, const Point2h &p2, const Point2h &p3) : - first(p1), second(p2), third(p3) { - } - /// print - void print() { - tensors::Index<3, 'i'> i; - tensors::print(first(i), "first :"); - tensors::print(second(i), "second:"); - tensors::print(third(i), "third :"); - } - }; - - /** - * Trifocal Tensor - * @ingroup geometry - */ - typedef tensors::Tensor3<3, 3, 3> TrifocalTensor; - - /** - * 3D Point in homogeneous coordinates - * @ingroup geometry - */ - typedef tensors::Tensor1<4> Point3h; - Point3h point3h(double X, double Y, double Z, double W); ///< create Point3h - - /** - * 3D Plane in homogeneous coordinates - * @ingroup geometry - */ - typedef tensors::Tensor1<4> Plane3h; - Plane3h plane3h(double a, double b, double c, double d); ///< create Plane3h - - /** - * 3D to 2D projective camera - * @ingroup geometry - */ - typedef tensors::Tensor2<3, 4> ProjectiveCamera; - -} // namespace gtsam diff --git a/gtsam/geometry/tensorInterface.h b/gtsam/geometry/tensorInterface.h deleted file mode 100644 index 61212e2c9..000000000 --- a/gtsam/geometry/tensorInterface.h +++ /dev/null @@ -1,108 +0,0 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) - - * See LICENSE for the license information - - * -------------------------------------------------------------------------- */ - -/** - * @file tensorInterface.h - * @brief Interfacing tensors template library and gtsam - * @date Feb 12, 2010 - * @author Frank Dellaert - */ - -#pragma once - -#include -#include - -namespace gtsam { - - /** Reshape rank 2 tensor into Matrix */ - template - Matrix reshape(const tensors::Tensor2Expression& T, int m, int n) { - if (m * n != I::dim * J::dim) throw std::invalid_argument( - "reshape: incompatible dimensions"); - MatrixRowMajor M(m, n); - size_t t = 0; - for (int j = 0; j < J::dim; j++) - for (int i = 0; i < I::dim; i++) - M.data()[t++] = T(i, j); - return Matrix(M); - } - - /** Reshape rank 2 tensor into Vector */ - template - Vector toVector(const tensors::Tensor2Expression& T) { - Vector v(I::dim * J::dim); - size_t t = 0; - for (int j = 0; j < J::dim; j++) - for (int i = 0; i < I::dim; i++) - v(t++) = T(i, j); - return v; - } - - /** Reshape Vector into rank 2 tensor */ - template - tensors::Tensor2 reshape2(const Vector& v) { - if (v.size() != N1 * N2) throw std::invalid_argument( - "reshape2: incompatible dimensions"); - double data[N2][N1]; - int t = 0; - for (int j = 0; j < N2; j++) - for (int i = 0; i < N1; i++) - data[j][i] = v(t++); - return tensors::Tensor2(data); - } - - /** Reshape rank 3 tensor into Matrix */ - template - Matrix reshape(const tensors::Tensor3Expression& T, int m, int n) { - if (m * n != I::dim * J::dim * K::dim) throw std::invalid_argument( - "reshape: incompatible dimensions"); - Matrix M(m, n); - int t = 0; - for (int k = 0; k < K::dim; k++) - for (int i = 0; i < I::dim; i++) - for (int j = 0; j < J::dim; j++) - M.data()[t++] = T(i, j, k); - return M; - } - - /** Reshape Vector into rank 3 tensor */ - template - tensors::Tensor3 reshape3(const Vector& v) { - if (v.size() != N1 * N2 * N3) throw std::invalid_argument( - "reshape3: incompatible dimensions"); - double data[N3][N2][N1]; - int t = 0; - for (int k = 0; k < N3; k++) - for (int j = 0; j < N2; j++) - for (int i = 0; i < N1; i++) - data[k][j][i] = v(t++); - return tensors::Tensor3(data); - } - - /** Reshape rank 5 tensor into Matrix */ - template - Matrix reshape(const tensors::Tensor5Expression& T, int m, - int n) { - if (m * n != I::dim * J::dim * K::dim * L::dim * M::dim) throw std::invalid_argument( - "reshape: incompatible dimensions"); - Matrix R(m, n); - int t = 0; - for (int m = 0; m < M::dim; m++) - for (int l = 0; l < L::dim; l++) - for (int k = 0; k < K::dim; k++) - for (int i = 0; i < I::dim; i++) - for (int j = 0; j < J::dim; j++) - R.data()[t++] = T(i, j, k, l, m); - return R; - } - -} // namespace gtsam diff --git a/gtsam/geometry/tensors.h b/gtsam/geometry/tensors.h deleted file mode 100644 index 1441a7823..000000000 --- a/gtsam/geometry/tensors.h +++ /dev/null @@ -1,45 +0,0 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) - - * See LICENSE for the license information - - * -------------------------------------------------------------------------- */ - -/** - * @file tensors.h - * @brief Tensor expression templates based on http://www.gps.caltech.edu/~walter/FTensor/FTensor.pdf - * @date Feb 10, 2010 - * @author Frank Dellaert - * @defgroup tensors - */ - -#pragma once - -namespace tensors { - - /** index */ - template struct Index { - static const int dim = Dim; ///< dimension - }; - -} // namespace tensors - -// Expression templates -#include -#include -#include -// Tensor4 not needed so far -#include - -// Actual tensor classes -#include -#include -#include -#include -#include - - diff --git a/gtsam/geometry/tests/testCal3Bundler.cpp b/gtsam/geometry/tests/testCal3Bundler.cpp index bb1bd861d..e354796fa 100644 --- a/gtsam/geometry/tests/testCal3Bundler.cpp +++ b/gtsam/geometry/tests/testCal3Bundler.cpp @@ -25,8 +25,8 @@ using namespace gtsam; GTSAM_CONCEPT_TESTABLE_INST(Cal3Bundler) GTSAM_CONCEPT_MANIFOLD_INST(Cal3Bundler) -Cal3Bundler K(500, 1e-3, 1e-3); -Point2 p(2,3); +static Cal3Bundler K(500, 1e-3, 1e-3); +static Point2 p(2,3); /* ************************************************************************* */ TEST( Cal3Bundler, calibrate) diff --git a/gtsam/geometry/tests/testCal3DS2.cpp b/gtsam/geometry/tests/testCal3DS2.cpp index 4c79a447b..c73ae1182 100644 --- a/gtsam/geometry/tests/testCal3DS2.cpp +++ b/gtsam/geometry/tests/testCal3DS2.cpp @@ -25,11 +25,11 @@ using namespace gtsam; GTSAM_CONCEPT_TESTABLE_INST(Cal3DS2) GTSAM_CONCEPT_MANIFOLD_INST(Cal3DS2) -Cal3DS2 K(500, 100, 0.1, 320, 240, 1e-3, 2.0*1e-3, 3.0*1e-3, 4.0*1e-3); -Point2 p(2,3); +static Cal3DS2 K(500, 100, 0.1, 320, 240, 1e-3, 2.0*1e-3, 3.0*1e-3, 4.0*1e-3); +static Point2 p(2,3); /* ************************************************************************* */ -TEST( Cal3DS2, calibrate) +TEST( Cal3DS2, uncalibrate) { Vector k = K.k() ; double r = p.x()*p.x() + p.y()*p.y() ; @@ -43,6 +43,14 @@ TEST( Cal3DS2, calibrate) CHECK(assert_equal(q,p_i)); } +TEST( Cal3DS2, calibrate ) +{ + Point2 pn(0.5, 0.5); + Point2 pi = K.uncalibrate(pn); + Point2 pn_hat = K.calibrate(pi); + CHECK( pn.equals(pn_hat, 1e-5)); +} + Point2 uncalibrate_(const Cal3DS2& k, const Point2& pt) { return k.uncalibrate(pt); } /* ************************************************************************* */ diff --git a/gtsam/geometry/tests/testCal3_S2.cpp b/gtsam/geometry/tests/testCal3_S2.cpp index fd82557a3..8995a3a14 100644 --- a/gtsam/geometry/tests/testCal3_S2.cpp +++ b/gtsam/geometry/tests/testCal3_S2.cpp @@ -24,8 +24,8 @@ using namespace gtsam; GTSAM_CONCEPT_TESTABLE_INST(Cal3_S2) GTSAM_CONCEPT_MANIFOLD_INST(Cal3_S2) -Cal3_S2 K(500, 500, 0.1, 640 / 2, 480 / 2); -Point2 p(1, -2); +static Cal3_S2 K(500, 500, 0.1, 640 / 2, 480 / 2); +static Point2 p(1, -2); /* ************************************************************************* */ TEST( Cal3_S2, easy_constructor) diff --git a/gtsam/geometry/tests/testCalibratedCamera.cpp b/gtsam/geometry/tests/testCalibratedCamera.cpp index 5bb1ebe65..57ccc0260 100644 --- a/gtsam/geometry/tests/testCalibratedCamera.cpp +++ b/gtsam/geometry/tests/testCalibratedCamera.cpp @@ -27,19 +27,19 @@ using namespace gtsam; GTSAM_CONCEPT_MANIFOLD_INST(CalibratedCamera) -const Pose3 pose1(Matrix_(3,3, +static const Pose3 pose1(Matrix_(3,3, 1., 0., 0., 0.,-1., 0., 0., 0.,-1. ), Point3(0,0,0.5)); -const CalibratedCamera camera(pose1); +static const CalibratedCamera camera(pose1); -const Point3 point1(-0.08,-0.08, 0.0); -const Point3 point2(-0.08, 0.08, 0.0); -const Point3 point3( 0.08, 0.08, 0.0); -const Point3 point4( 0.08,-0.08, 0.0); +static const Point3 point1(-0.08,-0.08, 0.0); +static const Point3 point2(-0.08, 0.08, 0.0); +static const Point3 point3( 0.08, 0.08, 0.0); +static const Point3 point4( 0.08,-0.08, 0.0); /* ************************************************************************* */ TEST( CalibratedCamera, constructor) @@ -52,7 +52,7 @@ TEST( CalibratedCamera, level1) { // Create a level camera, looking in X-direction Pose2 pose2(0.1,0.2,0); - CalibratedCamera camera = CalibratedCamera::level(pose2, 0.3); + CalibratedCamera camera = CalibratedCamera::Level(pose2, 0.3); // expected Point3 x(0,-1,0),y(0,0,-1),z(1,0,0); @@ -65,8 +65,8 @@ TEST( CalibratedCamera, level1) TEST( CalibratedCamera, level2) { // Create a level camera, looking in Y-direction - Pose2 pose2(0.4,0.3,M_PI_2); - CalibratedCamera camera = CalibratedCamera::level(pose2, 0.1); + Pose2 pose2(0.4,0.3,M_PI/2.0); + CalibratedCamera camera = CalibratedCamera::Level(pose2, 0.1); // expected Point3 x(1,0,0),y(0,0,-1),z(0,1,0); @@ -95,7 +95,7 @@ TEST( CalibratedCamera, Dproject_to_camera1) { } /* ************************************************************************* */ -Point2 project2(const Pose3& pose, const Point3& point) { +static Point2 project2(const Pose3& pose, const Point3& point) { return CalibratedCamera(pose).project(point); } diff --git a/gtsam/geometry/tests/testFundamental.cpp b/gtsam/geometry/tests/testFundamental.cpp deleted file mode 100644 index 297b36036..000000000 --- a/gtsam/geometry/tests/testFundamental.cpp +++ /dev/null @@ -1,73 +0,0 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) - - * See LICENSE for the license information - - * -------------------------------------------------------------------------- */ - -/** - * @file testFundamental.cpp - * @brief try tensor expressions based on http://www.gps.caltech.edu/~walter/FTensor/FTensor.pdf - * @date Feb 13, 2010 - * @author: Frank Dellaert - */ - -#include -#include -#include // for operator += -using namespace boost::assign; - -#include - -#include -#include -#include - -using namespace std; -using namespace gtsam; -using namespace tensors; - -/* ************************************************************************* */ -// Indices - -Index<3, 'a'> a; -Index<3, 'b'> b; - -Index<4, 'A'> A; -Index<4, 'B'> B; - -/* ************************************************************************* */ -TEST( Tensors, FundamentalMatrix) -{ - double f[3][3] = { { 1, 0, 0 }, { 1, 2, 3 }, { 1, 2, 3 } }; - FundamentalMatrix F(f); - - Point2h p = point2h(1, 2, 3); // point p in view one - Point2h q = point2h(14, -1, 0); // point q in view two - - // points p and q are in correspondence - CHECK(F(a,b)*p(a)*q(b) == 0) - - // in detail, l1(b)*q(b)==0 - Line2h l1 = line2h(1, 14, 14); - CHECK(F(a,b)*p(a) == l1(b)) - CHECK(l1(b)*q(b) == 0); // q is on line l1 - - // and l2(a)*p(a)==0 - Line2h l2 = line2h(13, -2, -3); - CHECK(F(a,b)*q(b) == l2(a)) - CHECK(l2(a)*p(a) == 0); // p is on line l2 -} - - -/* ************************************************************************* */ -int main() { - TestResult tr; - return TestRegistry::runAllTests(tr); -} -/* ************************************************************************* */ - diff --git a/gtsam/geometry/tests/testHomography2.cpp b/gtsam/geometry/tests/testHomography2.cpp deleted file mode 100644 index 417d41977..000000000 --- a/gtsam/geometry/tests/testHomography2.cpp +++ /dev/null @@ -1,188 +0,0 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) - - * See LICENSE for the license information - - * -------------------------------------------------------------------------- */ - -/** - * @file testHomography2.cpp - * @brief Test and estimate 2D homographies - * @date Feb 13, 2010 - * @author Frank Dellaert - */ - -#include -#include -#include // for operator += -using namespace boost::assign; - -#include - -#include -#include -#include -#include -#include - -using namespace std; -using namespace gtsam; -using namespace tensors; - -/* ************************************************************************* */ -// Indices - -Index<3, 'a'> a, _a; -Index<3, 'b'> b, _b; -Index<3, 'c'> c, _c; - -/* ************************************************************************* */ -TEST( Homography2, RealImages) -{ - // 4 point correspondences MATLAB from the floor of bt001.png and bt002.png - Correspondence p1(point2h(216.841, 443.220, 1), point2h(213.528, 414.671, 1)); - Correspondence p2(point2h(252.119, 363.481, 1), point2h(244.614, 348.842, 1)); - Correspondence p3(point2h(316.614, 414.768, 1), point2h(303.128, 390.000, 1)); - Correspondence p4(point2h(324.165, 465.463, 1), point2h(308.614, 431.129, 1)); - - // Homography obtained using MATLAB code - double h[3][3] = { { 0.9075, 0.0031, -0 }, { -0.1165, 0.8288, -0.0004 }, { - 30.8472, 16.0449, 1 } }; - Homography2 H(h); - - // CHECK whether they are equivalent - CHECK(assert_equivalent(p1.second(b),H(b,a)*p1.first(a),0.05)) - CHECK(assert_equivalent(p2.second(b),H(b,a)*p2.first(a),0.05)) - CHECK(assert_equivalent(p3.second(b),H(b,a)*p3.first(a),0.05)) - CHECK(assert_equivalent(p4.second(b),H(b,a)*p4.first(a),0.05)) -} - -/* ************************************************************************* */ -// Homography test case -// 4 trivial correspondences of a translating square -Correspondence p1(point2h(0, 0, 1), point2h(4, 5, 1)); -Correspondence p2(point2h(1, 0, 1), point2h(5, 5, 1)); -Correspondence p3(point2h(1, 1, 1), point2h(5, 6, 1)); -Correspondence p4(point2h(0, 1, 1), point2h(4, 6, 1)); - -double h[3][3] = { { 1, 0, 4 }, { 0, 1, 5 }, { 0, 0, 1 } }; -Homography2 H(h); - -/* ************************************************************************* */ -TEST( Homography2, TestCase) -{ - // Check homography - list correspondences; - correspondences += p1, p2, p3, p4; - BOOST_FOREACH(const Correspondence& p, correspondences) - CHECK(assert_equality(p.second(b),H(_a,b) * p.first(a))) - - // Check a line - Line2h l1 = line2h(1, 0, -1); // in a - Line2h l2 = line2h(1, 0, -5); // x==5 in b - CHECK(assert_equality(l1(a), H(a,b)*l2(b))) -} - -/* ************************************************************************* */ -/** - * Computes the homography H(I,_T) from template to image - * given the pose tEc of the camera in the template coordinate frame. - * Assumption is Z is normal to the template, template texture in X-Y plane. - */ -Homography2 patchH(const Pose3& tEc) { - Pose3 cEt = tEc.inverse(); - Rot3 cRt = cEt.rotation(); - Point3 r1 = cRt.r1(), r2 = cRt.r2(), t = cEt.translation(); - - // TODO cleanup !!!! - // column 1 - double H11 = r1.x(); - double H21 = r1.y(); - double H31 = r1.z(); - // column 2 - double H12 = r2.x(); - double H22 = r2.y(); - double H32 = r2.z(); - // column 3 - double H13 = t.x(); - double H23 = t.y(); - double H33 = t.z(); - double data2[3][3] = { { H11, H21, H31 }, { H12, H22, H32 }, - { H13, H23, H33 } }; - return Homography2(data2); -} - -/* ************************************************************************* */ -namespace gtsam { -// size_t dim(const tensors::Tensor2<3, 3>& H) {return 9;} - Vector toVector(const tensors::Tensor2<3, 3>& H) { - Index<3, 'T'> _T; // covariant 2D template - Index<3, 'C'> I; // contravariant 2D camera - return toVector(H(I,_T)); - } - Vector localCoordinates(const tensors::Tensor2<3, 3>& A, const tensors::Tensor2<3, 3>& B) { - return toVector(A)-toVector(B); // TODO correct order ? - } -} - -#include - -/* ************************************************************************* */ -TEST( Homography2, patchH) -{ - Index<3, 'T'> _T; // covariant 2D template - Index<3, 'C'> I; // contravariant 2D camera - - // data[_T][I] - double data1[3][3] = {{1,0,0},{0,-1,0},{0,0,10}}; - Homography2 expected(data1); - - // camera rotation, looking in negative Z - Rot3 gRc(Point3(1,0,0),Point3(0,-1,0),Point3(0,0,-1)); - Point3 gTc(0,0,10); // Camera location, out on the Z axis - Pose3 gEc(gRc,gTc); // Camera pose - - Homography2 actual = patchH(gEc); - -// GTSAM_PRINT(expected(I,_T)); -// GTSAM_PRINT(actual(I,_T)); - CHECK(assert_equality(expected(I,_T),actual(I,_T))); - - // FIXME: this doesn't appear to be tested, and requires that Tensor2 be a Lie object -// Matrix D = numericalDerivative11(patchH, gEc); -// print(D,"D"); -} - -/* ************************************************************************* */ -TEST( Homography2, patchH2) -{ - Index<3, 'T'> _T; // covariant 2D template - Index<3, 'C'> I; // contravariant 2D camera - - // data[_T][I] - double data1[3][3] = {{1,0,0},{0,-1,0},{0,0,10}}; - Homography2 expected(data1); - - // camera rotation, looking in negative Z - Rot3 gRc(Point3(1,0,0),Point3(0,-1,0),Point3(0,0,-1)); - Point3 gTc(0,0,10); // Camera location, out on the Z axis - Pose3 gEc(gRc,gTc); // Camera pose - - Homography2 actual = patchH(gEc); - -// GTSAM_PRINT(expected(I,_T)); -// GTSAM_PRINT(actual(I,_T)); - CHECK(assert_equality(expected(I,_T),actual(I,_T))); -} - -/* ************************************************************************* */ -int main() { - TestResult tr; - return TestRegistry::runAllTests(tr); -} -/* ************************************************************************* */ - diff --git a/gtsam/geometry/tests/testPoint2.cpp b/gtsam/geometry/tests/testPoint2.cpp index 3416361cd..f7fee0418 100644 --- a/gtsam/geometry/tests/testPoint2.cpp +++ b/gtsam/geometry/tests/testPoint2.cpp @@ -72,7 +72,7 @@ TEST( Point2, arithmetic) /* ************************************************************************* */ TEST( Point2, norm) { - Point2 p0(cos(5), sin(5)); + Point2 p0(cos(5.0), sin(5.0)); DOUBLES_EQUAL(1,p0.norm(),1e-6); Point2 p1(4, 5), p2(1, 1); DOUBLES_EQUAL( 5,p1.dist(p2),1e-6); @@ -85,7 +85,7 @@ TEST( Point2, unit) Point2 p0(10.0, 0.0), p1(0.0,-10.0), p2(10.0, 10.0); EXPECT(assert_equal(Point2(1.0, 0.0), p0.unit(), 1e-6)); EXPECT(assert_equal(Point2(0.0,-1.0), p1.unit(), 1e-6)); - EXPECT(assert_equal(Point2(sqrt(2)/2.0, sqrt(2)/2.0), p2.unit(), 1e-6)); + EXPECT(assert_equal(Point2(sqrt(2.0)/2.0, sqrt(2.0)/2.0), p2.unit(), 1e-6)); } /* ************************************************************************* */ diff --git a/gtsam/geometry/tests/testPoint3.cpp b/gtsam/geometry/tests/testPoint3.cpp index c7e25f7a9..492d65e42 100644 --- a/gtsam/geometry/tests/testPoint3.cpp +++ b/gtsam/geometry/tests/testPoint3.cpp @@ -23,7 +23,7 @@ using namespace gtsam; GTSAM_CONCEPT_TESTABLE_INST(Point3) GTSAM_CONCEPT_LIE_INST(Point3) -Point3 P(0.2,0.7,-2); +static Point3 P(0.2,0.7,-2); /* ************************************************************************* */ TEST(Point3, Lie) { diff --git a/gtsam/geometry/tests/testPose2.cpp b/gtsam/geometry/tests/testPose2.cpp index 14e529613..a79371e63 100644 --- a/gtsam/geometry/tests/testPose2.cpp +++ b/gtsam/geometry/tests/testPose2.cpp @@ -44,14 +44,14 @@ TEST(Pose2, constructors) { Pose2 pose(0,p); Pose2 origin; assert_equal(pose,origin); - Pose2 t(M_PI_2+0.018, Point2(1.015, 2.01)); + Pose2 t(M_PI/2.0+0.018, Point2(1.015, 2.01)); EXPECT(assert_equal(t,Pose2(t.matrix()))); } /* ************************************************************************* */ TEST(Pose2, manifold) { - Pose2 t1(M_PI_2, Point2(1, 2)); - Pose2 t2(M_PI_2+0.018, Point2(1.015, 2.01)); + Pose2 t1(M_PI/2.0, Point2(1, 2)); + Pose2 t2(M_PI/2.0+0.018, Point2(1.015, 2.01)); Pose2 origin; Vector d12 = t1.localCoordinates(t2); EXPECT(assert_equal(t2, t1.retract(d12))); @@ -63,11 +63,11 @@ TEST(Pose2, manifold) { /* ************************************************************************* */ TEST(Pose2, retract) { - Pose2 pose(M_PI_2, Point2(1, 2)); + Pose2 pose(M_PI/2.0, Point2(1, 2)); #ifdef SLOW_BUT_CORRECT_EXPMAP Pose2 expected(1.00811, 2.01528, 2.5608); #else - Pose2 expected(M_PI_2+0.99, Point2(1.015, 2.01)); + Pose2 expected(M_PI/2.0+0.99, Point2(1.015, 2.01)); #endif Pose2 actual = pose.retract(Vector_(3, 0.01, -0.015, 0.99)); EXPECT(assert_equal(expected, actual, 1e-5)); @@ -75,7 +75,7 @@ TEST(Pose2, retract) { /* ************************************************************************* */ TEST(Pose2, expmap) { - Pose2 pose(M_PI_2, Point2(1, 2)); + Pose2 pose(M_PI/2.0, Point2(1, 2)); Pose2 expected(1.00811, 2.01528, 2.5608); Pose2 actual = expmap_default(pose, Vector_(3, 0.01, -0.015, 0.99)); EXPECT(assert_equal(expected, actual, 1e-5)); @@ -83,7 +83,7 @@ TEST(Pose2, expmap) { /* ************************************************************************* */ TEST(Pose2, expmap2) { - Pose2 pose(M_PI_2, Point2(1, 2)); + Pose2 pose(M_PI/2.0, Point2(1, 2)); Pose2 expected(1.00811, 2.01528, 2.5608); Pose2 actual = expmap_default(pose, Vector_(3, 0.01, -0.015, 0.99)); EXPECT(assert_equal(expected, actual, 1e-5)); @@ -110,11 +110,11 @@ TEST(Pose2, expmap3) { /* ************************************************************************* */ TEST(Pose2, expmap0) { - Pose2 pose(M_PI_2, Point2(1, 2)); + Pose2 pose(M_PI/2.0, Point2(1, 2)); //#ifdef SLOW_BUT_CORRECT_EXPMAP Pose2 expected(1.01491, 2.01013, 1.5888); //#else -// Pose2 expected(M_PI_2+0.018, Point2(1.015, 2.01)); +// Pose2 expected(M_PI/2.0+0.018, Point2(1.015, 2.01)); //#endif Pose2 actual = pose * (Pose2::Expmap(Vector_(3, 0.01, -0.015, 0.018))); EXPECT(assert_equal(expected, actual, 1e-5)); @@ -122,7 +122,7 @@ TEST(Pose2, expmap0) { /* ************************************************************************* */ TEST(Pose2, expmap0_full) { - Pose2 pose(M_PI_2, Point2(1, 2)); + Pose2 pose(M_PI/2.0, Point2(1, 2)); Pose2 expected(1.01491, 2.01013, 1.5888); Pose2 actual = pose * Pose2::Expmap(Vector_(3, 0.01, -0.015, 0.018)); EXPECT(assert_equal(expected, actual, 1e-5)); @@ -130,7 +130,7 @@ TEST(Pose2, expmap0_full) { /* ************************************************************************* */ TEST(Pose2, expmap0_full2) { - Pose2 pose(M_PI_2, Point2(1, 2)); + Pose2 pose(M_PI/2.0, Point2(1, 2)); Pose2 expected(1.01491, 2.01013, 1.5888); Pose2 actual = pose * Pose2::Expmap(Vector_(3, 0.01, -0.015, 0.018)); EXPECT(assert_equal(expected, actual, 1e-5)); @@ -156,7 +156,7 @@ TEST(Pose3, expmap_c) #endif /* ************************************************************************* */ -TEST(Pose3, expmap_c_full) +TEST(Pose2, expmap_c_full) { double w=0.3; Vector xi = Vector_(3, 0.0, w, w); @@ -170,8 +170,8 @@ TEST(Pose3, expmap_c_full) /* ************************************************************************* */ TEST(Pose2, logmap) { - Pose2 pose0(M_PI_2, Point2(1, 2)); - Pose2 pose(M_PI_2+0.018, Point2(1.015, 2.01)); + Pose2 pose0(M_PI/2.0, Point2(1, 2)); + Pose2 pose(M_PI/2.0+0.018, Point2(1.015, 2.01)); #ifdef SLOW_BUT_CORRECT_EXPMAP Vector expected = Vector_(3, 0.00986473, -0.0150896, 0.018); #else @@ -183,21 +183,21 @@ TEST(Pose2, logmap) { /* ************************************************************************* */ TEST(Pose2, logmap_full) { - Pose2 pose0(M_PI_2, Point2(1, 2)); - Pose2 pose(M_PI_2+0.018, Point2(1.015, 2.01)); + Pose2 pose0(M_PI/2.0, Point2(1, 2)); + Pose2 pose(M_PI/2.0+0.018, Point2(1.015, 2.01)); Vector expected = Vector_(3, 0.00986473, -0.0150896, 0.018); Vector actual = logmap_default(pose0, pose); EXPECT(assert_equal(expected, actual, 1e-5)); } /* ************************************************************************* */ -Point2 transform_to_proxy(const Pose2& pose, const Point2& point) { +static Point2 transform_to_proxy(const Pose2& pose, const Point2& point) { return pose.transform_to(point); } TEST( Pose2, transform_to ) { - Pose2 pose(M_PI_2, Point2(1,2)); // robot at (1,2) looking towards y + Pose2 pose(M_PI/2.0, Point2(1,2)); // robot at (1,2) looking towards y Point2 point(-1,4); // landmark at (-1,4) // expected @@ -220,13 +220,13 @@ TEST( Pose2, transform_to ) } /* ************************************************************************* */ -Point2 transform_from_proxy(const Pose2& pose, const Point2& point) { +static Point2 transform_from_proxy(const Pose2& pose, const Point2& point) { return pose.transform_from(point); } TEST (Pose2, transform_from) { - Pose2 pose(1., 0., M_PI_2); + Pose2 pose(1., 0., M_PI/2.0); Point2 pt(2., 1.); Matrix H1, H2; Point2 actual = pose.transform_from(pt, H1, H2); @@ -326,7 +326,7 @@ TEST(Pose2, compose_c) TEST(Pose2, inverse ) { Point2 origin, t(1,2); - Pose2 gTl(M_PI_2, t); // robot at (1,2) looking towards y + Pose2 gTl(M_PI/2.0, t); // robot at (1,2) looking towards y Pose2 identity, lTg = gTl.inverse(); EXPECT(assert_equal(identity,lTg.compose(gTl))); @@ -362,7 +362,7 @@ Matrix matrix(const Pose2& gTl) { TEST( Pose2, matrix ) { Point2 origin, t(1,2); - Pose2 gTl(M_PI_2, t); // robot at (1,2) looking towards y + Pose2 gTl(M_PI/2.0, t); // robot at (1,2) looking towards y Matrix gMl = matrix(gTl); EXPECT(assert_equal(Matrix_(3,3, 0.0, -1.0, 1.0, @@ -393,7 +393,7 @@ TEST( Pose2, matrix ) /* ************************************************************************* */ TEST( Pose2, compose_matrix ) { - Pose2 gT1(M_PI_2, Point2(1,2)); // robot at (1,2) looking towards y + Pose2 gT1(M_PI/2.0, Point2(1,2)); // robot at (1,2) looking towards y Pose2 _1T2(M_PI, Point2(-1,4)); // local robot at (-1,4) loooking at negative x Matrix gM1(matrix(gT1)),_1M2(matrix(_1T2)); EXPECT(assert_equal(gM1*_1M2,matrix(gT1.compose(_1T2)))); // RIGHT DOES NOT @@ -407,11 +407,11 @@ TEST( Pose2, between ) // ^ // // *--0--*--* - Pose2 gT1(M_PI_2, Point2(1,2)); // robot at (1,2) looking towards y + Pose2 gT1(M_PI/2.0, Point2(1,2)); // robot at (1,2) looking towards y Pose2 gT2(M_PI, Point2(-1,4)); // robot at (-1,4) loooking at negative x Matrix actualH1,actualH2; - Pose2 expected(M_PI_2, Point2(2,2)); + Pose2 expected(M_PI/2.0, Point2(2,2)); Pose2 actual1 = gT1.between(gT2); Pose2 actual2 = gT1.between(gT2,actualH1,actualH2); EXPECT(assert_equal(expected,actual1)); @@ -426,7 +426,7 @@ TEST( Pose2, between ) EXPECT(assert_equal(expectedH1,actualH1)); EXPECT(assert_equal(numericalH1,actualH1)); // Assert H1 = -AdjointMap(between(p2,p1)) as in doc/math.lyx - EXPECT(assert_equal(-gT2.between(gT1).AdjointMap(),actualH1)); + EXPECT(assert_equal(-gT2.between(gT1).adjointMap(),actualH1)); Matrix expectedH2 = Matrix_(3,3, 1.0, 0.0, 0.0, @@ -443,7 +443,7 @@ TEST( Pose2, between ) // reverse situation for extra test TEST( Pose2, between2 ) { - Pose2 p2(M_PI_2, Point2(1,2)); // robot at (1,2) looking towards y + Pose2 p2(M_PI/2.0, Point2(1,2)); // robot at (1,2) looking towards y Pose2 p1(M_PI, Point2(-1,4)); // robot at (-1,4) loooking at negative x Matrix actualH1,actualH2; @@ -472,7 +472,7 @@ TEST(Pose2, members) /* ************************************************************************* */ // some shared test values -Pose2 x1, x2(1, 1, 0), x3(1, 1, M_PI_4); +Pose2 x1, x2(1, 1, 0), x3(1, 1, M_PI/4.0); Point2 l1(1, 0), l2(1, 1), l3(2, 2), l4(1, 3); /* ************************************************************************* */ @@ -488,11 +488,11 @@ TEST( Pose2, bearing ) EXPECT(assert_equal(Rot2(),x1.bearing(l1))); // establish bearing is indeed 45 degrees - EXPECT(assert_equal(Rot2::fromAngle(M_PI_4),x1.bearing(l2))); + EXPECT(assert_equal(Rot2::fromAngle(M_PI/4.0),x1.bearing(l2))); // establish bearing is indeed 45 degrees even if shifted Rot2 actual23 = x2.bearing(l3, actualH1, actualH2); - EXPECT(assert_equal(Rot2::fromAngle(M_PI_4),actual23)); + EXPECT(assert_equal(Rot2::fromAngle(M_PI/4.0),actual23)); // Check numerical derivatives expectedH1 = numericalDerivative21(bearing_proxy, x2, l3); @@ -502,7 +502,7 @@ TEST( Pose2, bearing ) // establish bearing is indeed 45 degrees even if rotated Rot2 actual34 = x3.bearing(l4, actualH1, actualH2); - EXPECT(assert_equal(Rot2::fromAngle(M_PI_4),actual34)); + EXPECT(assert_equal(Rot2::fromAngle(M_PI/4.0),actual34)); // Check numerical derivatives expectedH1 = numericalDerivative21(bearing_proxy, x3, l4); @@ -518,7 +518,7 @@ Rot2 bearing_pose_proxy(const Pose2& pose, const Pose2& pt) { TEST( Pose2, bearing_pose ) { - Pose2 xl1(1, 0, M_PI_2), xl2(1, 1, M_PI), xl3(2.0, 2.0,-M_PI_2), xl4(1, 3, 0); + Pose2 xl1(1, 0, M_PI/2.0), xl2(1, 1, M_PI), xl3(2.0, 2.0,-M_PI/2.0), xl4(1, 3, 0); Matrix expectedH1, actualH1, expectedH2, actualH2; @@ -526,11 +526,11 @@ TEST( Pose2, bearing_pose ) EXPECT(assert_equal(Rot2(),x1.bearing(xl1))); // establish bearing is indeed 45 degrees - EXPECT(assert_equal(Rot2::fromAngle(M_PI_4),x1.bearing(xl2))); + EXPECT(assert_equal(Rot2::fromAngle(M_PI/4.0),x1.bearing(xl2))); // establish bearing is indeed 45 degrees even if shifted Rot2 actual23 = x2.bearing(xl3, actualH1, actualH2); - EXPECT(assert_equal(Rot2::fromAngle(M_PI_4),actual23)); + EXPECT(assert_equal(Rot2::fromAngle(M_PI/4.0),actual23)); // Check numerical derivatives expectedH1 = numericalDerivative21(bearing_pose_proxy, x2, xl3); @@ -540,7 +540,7 @@ TEST( Pose2, bearing_pose ) // establish bearing is indeed 45 degrees even if rotated Rot2 actual34 = x3.bearing(xl4, actualH1, actualH2); - EXPECT(assert_equal(Rot2::fromAngle(M_PI_4),actual34)); + EXPECT(assert_equal(Rot2::fromAngle(M_PI/4.0),actual34)); // Check numerical derivatives expectedH1 = numericalDerivative21(bearing_pose_proxy, x3, xl4); @@ -561,11 +561,11 @@ TEST( Pose2, range ) EXPECT_DOUBLES_EQUAL(1,x1.range(l1),1e-9); // establish range is indeed 45 degrees - EXPECT_DOUBLES_EQUAL(sqrt(2),x1.range(l2),1e-9); + EXPECT_DOUBLES_EQUAL(sqrt(2.0),x1.range(l2),1e-9); // Another pair double actual23 = x2.range(l3, actualH1, actualH2); - EXPECT_DOUBLES_EQUAL(sqrt(2),actual23,1e-9); + EXPECT_DOUBLES_EQUAL(sqrt(2.0),actual23,1e-9); // Check numerical derivatives expectedH1 = numericalDerivative21(range_proxy, x2, l3); @@ -590,7 +590,7 @@ LieVector range_pose_proxy(const Pose2& pose, const Pose2& point) { } TEST( Pose2, range_pose ) { - Pose2 xl1(1, 0, M_PI_2), xl2(1, 1, M_PI), xl3(2.0, 2.0,-M_PI_2), xl4(1, 3, 0); + Pose2 xl1(1, 0, M_PI/2.0), xl2(1, 1, M_PI), xl3(2.0, 2.0,-M_PI/2.0), xl4(1, 3, 0); Matrix expectedH1, actualH1, expectedH2, actualH2; @@ -598,11 +598,11 @@ TEST( Pose2, range_pose ) EXPECT_DOUBLES_EQUAL(1,x1.range(xl1),1e-9); // establish range is indeed 45 degrees - EXPECT_DOUBLES_EQUAL(sqrt(2),x1.range(xl2),1e-9); + EXPECT_DOUBLES_EQUAL(sqrt(2.0),x1.range(xl2),1e-9); // Another pair double actual23 = x2.range(xl3, actualH1, actualH2); - EXPECT_DOUBLES_EQUAL(sqrt(2),actual23,1e-9); + EXPECT_DOUBLES_EQUAL(sqrt(2.0),actual23,1e-9); // Check numerical derivatives expectedH1 = numericalDerivative21(range_pose_proxy, x2, xl3); @@ -637,7 +637,7 @@ TEST(Pose2, align_1) { TEST(Pose2, align_2) { Point2 t(20,10); - Rot2 R = Rot2::fromAngle(M_PI_2); + Rot2 R = Rot2::fromAngle(M_PI/2.0); Pose2 expected(R, t); vector correspondences; diff --git a/gtsam/geometry/tests/testPose3.cpp b/gtsam/geometry/tests/testPose3.cpp index eb2d410f8..4ec1c6aee 100644 --- a/gtsam/geometry/tests/testPose3.cpp +++ b/gtsam/geometry/tests/testPose3.cpp @@ -535,7 +535,7 @@ TEST( Pose3, between ) /* ************************************************************************* */ // some shared test values - pulled from equivalent test in Pose2 Point3 l1(1, 0, 0), l2(1, 1, 0), l3(2, 2, 0), l4(1, 4,-4); -Pose3 x1, x2(Rot3::ypr(0.0, 0.0, 0.0), l2), x3(Rot3::ypr(M_PI_4, 0.0, 0.0), l2); +Pose3 x1, x2(Rot3::ypr(0.0, 0.0, 0.0), l2), x3(Rot3::ypr(M_PI/4.0, 0.0, 0.0), l2); Pose3 xl1(Rot3::ypr(0.0, 0.0, 0.0), Point3(1, 0, 0)), xl2(Rot3::ypr(0.0, 1.0, 0.0), Point3(1, 1, 0)), @@ -554,11 +554,11 @@ TEST( Pose3, range ) EXPECT_DOUBLES_EQUAL(1,x1.range(l1),1e-9); // establish range is indeed sqrt2 - EXPECT_DOUBLES_EQUAL(sqrt(2),x1.range(l2),1e-9); + EXPECT_DOUBLES_EQUAL(sqrt(2.0),x1.range(l2),1e-9); // Another pair double actual23 = x2.range(l3, actualH1, actualH2); - EXPECT_DOUBLES_EQUAL(sqrt(2),actual23,1e-9); + EXPECT_DOUBLES_EQUAL(sqrt(2.0),actual23,1e-9); // Check numerical derivatives expectedH1 = numericalDerivative21(range_proxy, x2, l3); @@ -589,11 +589,11 @@ TEST( Pose3, range_pose ) EXPECT_DOUBLES_EQUAL(1,x1.range(xl1),1e-9); // establish range is indeed sqrt2 - EXPECT_DOUBLES_EQUAL(sqrt(2),x1.range(xl2),1e-9); + EXPECT_DOUBLES_EQUAL(sqrt(2.0),x1.range(xl2),1e-9); // Another pair double actual23 = x2.range(xl3, actualH1, actualH2); - EXPECT_DOUBLES_EQUAL(sqrt(2),actual23,1e-9); + EXPECT_DOUBLES_EQUAL(sqrt(2.0),actual23,1e-9); // Check numerical derivatives expectedH1 = numericalDerivative21(range_pose_proxy, x2, xl3); @@ -619,7 +619,7 @@ TEST( Pose3, unicycle ) Vector x_step = delta(6,3,1.0); EXPECT(assert_equal(Pose3(Rot3::ypr(0,0,0), l1), expmap_default(x1, x_step), tol)); EXPECT(assert_equal(Pose3(Rot3::ypr(0,0,0), Point3(2,1,0)), expmap_default(x2, x_step), tol)); - EXPECT(assert_equal(Pose3(Rot3::ypr(M_PI_4,0,0), Point3(2,2,0)), expmap_default(x3, sqrt(2) * x_step), tol)); + EXPECT(assert_equal(Pose3(Rot3::ypr(M_PI/4.0,0,0), Point3(2,2,0)), expmap_default(x3, sqrt(2.0) * x_step), tol)); } /* ************************************************************************* */ diff --git a/gtsam/geometry/tests/testRot2.cpp b/gtsam/geometry/tests/testRot2.cpp index e23224898..acf385fab 100644 --- a/gtsam/geometry/tests/testRot2.cpp +++ b/gtsam/geometry/tests/testRot2.cpp @@ -43,7 +43,7 @@ TEST( Rot2, constructors_and_angle) TEST( Rot2, unit) { EXPECT(assert_equal(Point2(1.0, 0.0), Rot2::fromAngle(0).unit())); - EXPECT(assert_equal(Point2(0.0, 1.0), Rot2::fromAngle(M_PI_2).unit())); + EXPECT(assert_equal(Point2(0.0, 1.0), Rot2::fromAngle(M_PI/2.0).unit())); } /* ************************************************************************* */ @@ -94,9 +94,9 @@ TEST( Rot2, expmap) /* ************************************************************************* */ TEST(Rot2, logmap) { - Rot2 rot0(Rot2::fromAngle(M_PI_2)); + Rot2 rot0(Rot2::fromAngle(M_PI/2.0)); Rot2 rot(Rot2::fromAngle(M_PI)); - Vector expected = Vector_(1, M_PI_2); + Vector expected = Vector_(1, M_PI/2.0); Vector actual = rot0.localCoordinates(rot); CHECK(assert_equal(expected, actual)); } @@ -146,7 +146,7 @@ TEST( Rot2, relativeBearing ) // establish relativeBearing is indeed 45 degrees Rot2 actual2 = Rot2::relativeBearing(l2, actualH); - CHECK(assert_equal(Rot2::fromAngle(M_PI_4),actual2)); + CHECK(assert_equal(Rot2::fromAngle(M_PI/4.0),actual2)); // Check numerical derivative expectedH = numericalDerivative11(relativeBearing_, l2); diff --git a/gtsam/geometry/tests/testRot3M.cpp b/gtsam/geometry/tests/testRot3M.cpp index a5047f14b..449ed9cd7 100644 --- a/gtsam/geometry/tests/testRot3M.cpp +++ b/gtsam/geometry/tests/testRot3M.cpp @@ -31,9 +31,9 @@ using namespace std; using namespace gtsam; -Rot3 R = Rot3::rodriguez(0.1, 0.4, 0.2); -Point3 P(0.2, 0.7, -2.0); -double error = 1e-9, epsilon = 0.001; +static Rot3 R = Rot3::rodriguez(0.1, 0.4, 0.2); +static Point3 P(0.2, 0.7, -2.0); +static double error = 1e-9, epsilon = 0.001; static const Matrix I3 = eye(3); /* ************************************************************************* */ @@ -131,7 +131,7 @@ TEST( Rot3, rodriguez3) TEST( Rot3, rodriguez4) { Vector axis = Vector_(3,0.,0.,1.); // rotation around Z - double angle = M_PI_2; + double angle = M_PI/2.0; Rot3 actual = Rot3::rodriguez(axis, angle); double c=cos(angle),s=sin(angle); Rot3 expected(c,-s, 0, diff --git a/gtsam/geometry/tests/testRot3Q.cpp b/gtsam/geometry/tests/testRot3Q.cpp index 02056eb2d..7268eed55 100644 --- a/gtsam/geometry/tests/testRot3Q.cpp +++ b/gtsam/geometry/tests/testRot3Q.cpp @@ -27,9 +27,9 @@ using namespace gtsam; -Rot3 R = Rot3::rodriguez(0.1, 0.4, 0.2); -Point3 P(0.2, 0.7, -2.0); -double error = 1e-9, epsilon = 0.001; +static Rot3 R = Rot3::rodriguez(0.1, 0.4, 0.2); +static Point3 P(0.2, 0.7, -2.0); +static double error = 1e-9, epsilon = 0.001; /* ************************************************************************* */ TEST( Rot3, constructor) diff --git a/gtsam/geometry/tests/testSerializationGeometry.cpp b/gtsam/geometry/tests/testSerializationGeometry.cpp index c1fba6b2c..17a0b1eca 100644 --- a/gtsam/geometry/tests/testSerializationGeometry.cpp +++ b/gtsam/geometry/tests/testSerializationGeometry.cpp @@ -36,37 +36,20 @@ using namespace gtsam; using namespace gtsam::serializationTestHelpers; /* ************************************************************************* */ -// Export all classes derived from Value -BOOST_CLASS_EXPORT(gtsam::Cal3_S2) -BOOST_CLASS_EXPORT(gtsam::Cal3_S2Stereo) -BOOST_CLASS_EXPORT(gtsam::Cal3Bundler) -BOOST_CLASS_EXPORT(gtsam::CalibratedCamera) -BOOST_CLASS_EXPORT(gtsam::Point2) -BOOST_CLASS_EXPORT(gtsam::Point3) -BOOST_CLASS_EXPORT(gtsam::Pose2) -BOOST_CLASS_EXPORT(gtsam::Pose3) -BOOST_CLASS_EXPORT(gtsam::Rot2) -BOOST_CLASS_EXPORT(gtsam::Rot3) -BOOST_CLASS_EXPORT(gtsam::PinholeCamera) -BOOST_CLASS_EXPORT(gtsam::PinholeCamera) -BOOST_CLASS_EXPORT(gtsam::PinholeCamera) -BOOST_CLASS_EXPORT(gtsam::StereoPoint2) +static Point3 pt3(1.0, 2.0, 3.0); +static Rot3 rt3 = Rot3::RzRyRx(1.0, 3.0, 2.0); +static Pose3 pose3(rt3, pt3); -/* ************************************************************************* */ -Point3 pt3(1.0, 2.0, 3.0); -Rot3 rt3 = Rot3::RzRyRx(1.0, 3.0, 2.0); -Pose3 pose3(rt3, pt3); +static Cal3_S2 cal1(1.0, 2.0, 0.3, 0.1, 0.5); +static Cal3DS2 cal2(1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0); +static Cal3Bundler cal3(1.0, 2.0, 3.0); +static Cal3_S2Stereo cal4(1.0, 2.0, 3.0, 4.0, 5.0, 6.0); +static Cal3_S2Stereo::shared_ptr cal4ptr(new Cal3_S2Stereo(cal4)); +static CalibratedCamera cal5(Pose3(rt3, pt3)); -Cal3_S2 cal1(1.0, 2.0, 0.3, 0.1, 0.5); -Cal3DS2 cal2(1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0); -Cal3Bundler cal3(1.0, 2.0, 3.0); -Cal3_S2Stereo cal4(1.0, 2.0, 3.0, 4.0, 5.0, 6.0); -Cal3_S2Stereo::shared_ptr cal4ptr(new Cal3_S2Stereo(cal4)); -CalibratedCamera cal5(Pose3(rt3, pt3)); - -PinholeCamera cam1(pose3, cal1); -StereoCamera cam2(pose3, cal4ptr); -StereoPoint2 spt(1.0, 2.0, 3.0); +static PinholeCamera cam1(pose3, cal1); +static StereoCamera cam2(pose3, cal4ptr); +static StereoPoint2 spt(1.0, 2.0, 3.0); /* ************************************************************************* */ TEST (Serialization, text_geometry) { diff --git a/gtsam/geometry/tests/testSimpleCamera.cpp b/gtsam/geometry/tests/testSimpleCamera.cpp index b3df0d8f8..5e8918215 100644 --- a/gtsam/geometry/tests/testSimpleCamera.cpp +++ b/gtsam/geometry/tests/testSimpleCamera.cpp @@ -26,21 +26,21 @@ using namespace std; using namespace gtsam; -const Cal3_S2 K(625, 625, 0, 0, 0); +static const Cal3_S2 K(625, 625, 0, 0, 0); -const Pose3 pose1(Matrix_(3,3, +static const Pose3 pose1(Matrix_(3,3, 1., 0., 0., 0.,-1., 0., 0., 0.,-1. ), Point3(0,0,0.5)); -const SimpleCamera camera(K, pose1); +static const SimpleCamera camera(pose1, K); -const Point3 point1(-0.08,-0.08, 0.0); -const Point3 point2(-0.08, 0.08, 0.0); -const Point3 point3( 0.08, 0.08, 0.0); -const Point3 point4( 0.08,-0.08, 0.0); +static const Point3 point1(-0.08,-0.08, 0.0); +static const Point3 point2(-0.08, 0.08, 0.0); +static const Point3 point3( 0.08, 0.08, 0.0); +static const Point3 point4( 0.08,-0.08, 0.0); /* ************************************************************************* */ TEST( SimpleCamera, constructor) @@ -53,8 +53,8 @@ TEST( SimpleCamera, constructor) TEST( SimpleCamera, level2) { // Create a level camera, looking in Y-direction - Pose2 pose2(0.4,0.3,M_PI_2); - SimpleCamera camera = SimpleCamera::level(K, pose2, 0.1); + Pose2 pose2(0.4,0.3,M_PI/2.0); + SimpleCamera camera = SimpleCamera::Level(K, pose2, 0.1); // expected Point3 x(1,0,0),y(0,0,-1),z(0,1,0); @@ -63,6 +63,26 @@ TEST( SimpleCamera, level2) CHECK(assert_equal( camera.pose(), expected)); } +/* ************************************************************************* */ +TEST( SimpleCamera, lookat) +{ + // Create a level camera, looking in Y-direction + Point3 C(10.0,0.0,0.0); + SimpleCamera camera = SimpleCamera::Lookat(C, Point3(), Point3(0.0,0.0,1.0)); + + // expected + Point3 xc(0,1,0),yc(0,0,-1),zc(-1,0,0); + Pose3 expected(Rot3(xc,yc,zc),C); + CHECK(assert_equal( camera.pose(), expected)); + + Point3 C2(30.0,0.0,10.0); + SimpleCamera camera2 = SimpleCamera::Lookat(C2, Point3(), Point3(0.0,0.0,1.0)); + + Matrix R = camera2.pose().rotation().matrix(); + Matrix I = trans(R)*R; + CHECK(assert_equal(I, eye(3))); +} + /* ************************************************************************* */ TEST( SimpleCamera, project) { @@ -86,7 +106,7 @@ TEST( SimpleCamera, backproject2) { Point3 origin; Rot3 rot(1., 0., 0., 0., 0., 1., 0., -1., 0.); // a camera looking down - SimpleCamera camera(K, Pose3(rot, origin)); + SimpleCamera camera(Pose3(rot, origin), K); Point3 actual = camera.backproject(Point2(), 1.); Point3 expected(0., 1., 0.); @@ -98,8 +118,8 @@ TEST( SimpleCamera, backproject2) } /* ************************************************************************* */ -Point2 project2(const Pose3& pose, const Point3& point) { - return SimpleCamera(K,pose).project(point); +static Point2 project2(const Pose3& pose, const Point3& point) { + return SimpleCamera(pose,K).project(point); } TEST( SimpleCamera, Dproject_point_pose) @@ -113,6 +133,26 @@ TEST( SimpleCamera, Dproject_point_pose) CHECK(assert_equal(Dpoint, numerical_point,1e-7)); } +/* ************************************************************************* */ +TEST( SimpleCamera, simpleCamera) +{ + Cal3_S2 K(468.2,427.2,91.2,300,200); + Rot3 R( + 0.41380,0.90915,0.04708, + -0.57338,0.22011,0.78917, + 0.70711,-0.35355,0.61237); + Point3 T(1000,2000,1500); + SimpleCamera expected(Pose3(R.inverse(),T),K); + // H&Z example, 2nd edition, page 163 + Matrix P = Matrix_(3,4, + 3.53553e2, 3.39645e2, 2.77744e2, -1.44946e6, + -1.03528e2, 2.33212e1, 4.59607e2, -6.32525e5, + 7.07107e-1, -3.53553e-1,6.12372e-1, -9.18559e2); + SimpleCamera actual = simpleCamera(P); + // Note precision of numbers given in book + CHECK(assert_equal(expected, actual,1e-1)); +} + /* ************************************************************************* */ int main() { TestResult tr; return TestRegistry::runAllTests(tr); } /* ************************************************************************* */ diff --git a/gtsam/geometry/tests/testStereoCamera.cpp b/gtsam/geometry/tests/testStereoCamera.cpp index 2446ff122..29a8344d4 100644 --- a/gtsam/geometry/tests/testStereoCamera.cpp +++ b/gtsam/geometry/tests/testStereoCamera.cpp @@ -74,21 +74,21 @@ TEST( StereoCamera, project) /* ************************************************************************* */ -Pose3 camera1(Matrix_(3,3, +static Pose3 camera1(Matrix_(3,3, 1., 0., 0., 0.,-1., 0., 0., 0.,-1. ), Point3(0,0,6.25)); -Cal3_S2Stereo::shared_ptr K(new Cal3_S2Stereo(1500, 1500, 0, 320, 240, 0.5)); -StereoCamera stereoCam(Pose3(), K); +static Cal3_S2Stereo::shared_ptr K(new Cal3_S2Stereo(1500, 1500, 0, 320, 240, 0.5)); +static StereoCamera stereoCam(Pose3(), K); // point X Y Z in meters -Point3 p(0, 0, 5); +static Point3 p(0, 0, 5); /* ************************************************************************* */ -StereoPoint2 project_(const StereoCamera& cam, const Point3& point) { return cam.project(point); } +static StereoPoint2 project_(const StereoCamera& cam, const Point3& point) { return cam.project(point); } TEST( StereoCamera, Dproject_stereo_pose) { Matrix expected = numericalDerivative21(project_,stereoCam, p); diff --git a/gtsam/geometry/tests/testTensors.cpp b/gtsam/geometry/tests/testTensors.cpp deleted file mode 100644 index 755b274a6..000000000 --- a/gtsam/geometry/tests/testTensors.cpp +++ /dev/null @@ -1,240 +0,0 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) - - * See LICENSE for the license information - - * -------------------------------------------------------------------------- */ - -/** - * @file testTensors.cpp - * @brief try tensor expressions based on http://www.gps.caltech.edu/~walter/FTensor/FTensor.pdf - * @date Feb 9, 2010 - * @author Frank Dellaert - */ - -#include -#include -#include // for operator += -using namespace boost::assign; - -#include - -#include -#include -#include - -using namespace std; -using namespace gtsam; -using namespace tensors; - -/* ************************************************************************* */ -// Indices - -Index<3, 'a'> a, _a; -Index<3, 'b'> b, _b; -Index<3, 'c'> c, _c; - -Index<4, 'A'> A; -Index<4, 'B'> B; - -/* ************************************************************************* */ -// Tensor1 -/* ************************************************************************* */ -TEST(Tensor1, Basics) -{ - // you can create 1-tensors corresponding to 2D homogeneous points - // using the function point2h in projectiveGeometry.* - Point2h p = point2h(1, 2, 3), q = point2h(2, 4, 6); - - // equality tests always take tensor expressions, not tensors themselves - // the difference is that a tensor expression has indices - CHECK(p(a)==p(a)) - CHECK(assert_equality(p(a),p(a))) - CHECK(assert_equality(p(a)*2,q(a))) - CHECK(assert_equivalent(p(a),q(a))) // projectively equivalent - - // and you can take a norm, typically for normalization to the sphere - DOUBLES_EQUAL(sqrt(14),norm(p(a)),1e-9) -} - -/* ************************************************************************* */ -TEST( Tensor1, Incidence2D) -{ - // 2D lines are created with line2h - Line2h l = line2h(-13, 5, 1); - Point2h p = point2h(1, 2, 3), q = point2h(2, 5, 1); - - // Incidence between a line and a point is checked with simple contraction - // It does not matter which index you use, but it has to be of dimension 3 - DOUBLES_EQUAL(l(a)*p(a),0,1e-9) - DOUBLES_EQUAL(l(b)*q(b),0,1e-9) - DOUBLES_EQUAL(p(a)*l(a),0,1e-9) - DOUBLES_EQUAL(q(a)*l(a),0,1e-9) -} - -/* ************************************************************************* */ -TEST( Tensor1, Incidence3D) -{ - // similar constructs exist for 3D points and planes - Plane3h pi = plane3h(0, 1, 0, -2); - Point3h P = point3h(0, 2, 0, 1), Q = point3h(1, 2, 0, 1); - - // Incidence is checked similarly - DOUBLES_EQUAL(pi(A)*P(A),0,1e-9) - DOUBLES_EQUAL(pi(A)*Q(A),0,1e-9) - DOUBLES_EQUAL(P(A)*pi(A),0,1e-9) - DOUBLES_EQUAL(Q(A)*pi(A),0,1e-9) -} - -/* ************************************************************************* */ -// Tensor2 -/* ************************************************************************* */ -TEST( Tensor2, Outer33) -{ - Line2h l1 = line2h(1, 2, 3), l2 = line2h(1, 3, 5); - - // We can also create tensors directly from data - double data[3][3] = { { 1, 2, 3 }, { 3, 6, 9 }, {5, 10, 15} }; - Tensor2<3, 3> expected(data); - // in this case expected(0) == {1,2,3} - Line2h l0 = expected(a,b)(0); - CHECK(l0(a) == l1(a)) - - // And we create rank 2 tensors from the outer product of two rank 1 tensors - CHECK(expected(a,b) == l1(a) * l2(b)) - - // swap just swaps how you access a tensor, but note the data is the same - CHECK(assert_equality(expected(a,b).swap(), l2(b) * l1(a))); -} - -/* ************************************************************************* */ -TEST( Tensor2, AnotherOuter33) -{ - // first cube point from testFundamental, projected in left and right -// Point2h p = point2h(0, -1, 2), q = point2h(-2, -1, 2); -// print(p(a)*q(b)); -// print(p(b)*q(a)); -// print(q(a)*p(b)); -// print(q(b)*p(a)); -} - -/* ************************************************************************* */ -TEST( Tensor2, Outer34) -{ - Line2h l = line2h(1, 2, 3); - Plane3h pi = plane3h(1, 3, 5, 7); - double - data[4][3] = { { 1, 2, 3 }, { 3, 6, 9 }, { 5, 10, 15 }, { 7, 14, 21 } }; - Tensor2<3, 4> expected(data); - CHECK(assert_equality(expected(a,B),l(a) * pi(B))) - CHECK(assert_equality(expected(a,B).swap(),pi(B) * l(a))) -} - -/* ************************************************************************* */ -TEST( Tensor2, SpecialContract) -{ - double data[3][3] = { { 1, 2, 3 }, { 2, 4, 6 }, { 3, 6, 9 } }; - Tensor2<3, 3> S(data), T(data); - //print(S(a, b) * T(a, c)); // contract a -> b,c - // S(a,0)*T(a,0) = [1 2 3] . [1 2 3] = 14 - // S(a,0)*T(a,2) = [1 2 3] . [3 6 9] = 3+12+27 = 42 - double data2[3][3] = { { 14, 28, 42 }, { 28, 56, 84 }, { 42, 84, 126 } }; - Tensor2<3, 3> expected(data2); - CHECK(assert_equality(expected(b,c), S(a, b) * T(a, c))); -} - -/* ************************************************************************* */ -TEST( Tensor2, ProjectiveCamera) -{ - Point2h p = point2h(1 + 2, 2, 5); - Point3h P = point3h(1, 2, 5, 1); - double data[4][3] = { { 1, 0, 0 }, { 0, 1, 0 }, { 0, 0, 1 }, { 2, 0, 0 } }; - ProjectiveCamera M(data); - CHECK(assert_equality(p(a),M(a,A)*P(A))) -} - -/* ************************************************************************* */ -namespace camera { - // to specify the tensor M(a,A), we need to give four 2D points - double data[4][3] = { { 1, 2, 3 }, { 4, 5, 6 }, { 7, 8, 9 }, { 10, 11, 12 } }; - ProjectiveCamera M(data); - Matrix matrix = Matrix_(4,3,1.,2.,3.,4.,5.,6.,7.,8.,9.,10.,11.,12.); - Vector vector = Vector_( 12,1.,2.,3.,4.,5.,6.,7.,8.,9.,10.,11.,12.); -} - -/* ************************************************************************* */ -TEST( Tensor2, reshape ) -{ - // it is annoying that a camera can only be reshaped to a 4*3 -// print(camera::M(a,A)); - Matrix actual = reshape(camera::M(a,A),4,3); - EQUALITY(camera::matrix,actual); -} - -/* ************************************************************************* */ -TEST( Tensor2, toVector ) -{ - // Vectors are created with the leftmost indices iterating the fastest - Vector actual = toVector(camera::M(a,A)); - CHECK(assert_equal(camera::vector,actual)); -} - -/* ************************************************************************* */ -TEST( Tensor2, reshape2 ) -{ - Tensor2<3,4> actual = reshape2<3,4>(camera::vector); - CHECK(assert_equality(camera::M(a,A),actual(a,A))); -} - -/* ************************************************************************* */ -TEST( Tensor2, reshape_33_to_9 ) -{ - double data[3][3] = { { 1, 2, 3 }, { 4, 5, 6 }, { 7, 8, 9 } }; - FundamentalMatrix F(data); - Matrix matrix = Matrix_(1,9,1.,2.,3.,4.,5.,6.,7.,8.,9.); - Matrix actual = reshape(F(a,b),1,9); - EQUALITY(matrix,actual); - Vector v = Vector_( 9,1.,2.,3.,4.,5.,6.,7.,8.,9.); - CHECK(assert_equality(F(a,b),reshape2<3, 3> (v)(a,b))); -} - -/* ************************************************************************* */ -// Tensor3 -/* ************************************************************************* */ -TEST( Tensor3, Join) -{ - Line2h l = line2h(-13, 5, 1); - Point2h p = point2h(1, 2, 3), q = point2h(2, 5, 1); - - // join points into line - Eta3 e; - CHECK(assert_equality(e(a, b, c) * p(a) * q(b), l(c))) -} - -/* ************************************************************************* */ -TEST( Tensor5, Outer32) -{ - double t[3][3][3] = { { { 0, 0, 3 }, { 0, 8, -125 }, { -3, 125, 1 } }, { { 0, - 0, 3 }, { 0, 8, -125 }, { -3, 125, 1 } }, { { 0, 0, 3 }, { 0, 8, -125 }, - { -3, 125, 1 } } }; - TrifocalTensor T(t); - - double data[3][3] = { { 0, 0, 3 }, { 0, 8, -125 }, { -3, 125, 1 } }; - FundamentalMatrix F(data); - - //Index<3, 'd'> d, _d; - //Index<3, 'e'> e, _e; - //print(T(_a,b,c)*F(_d,_e)); -} - -/* ************************************************************************* */ -int main() { - TestResult tr; - return TestRegistry::runAllTests(tr); -} -/* ************************************************************************* */ - diff --git a/gtsam/inference/BayesNet-inl.h b/gtsam/inference/BayesNet-inl.h index 7ff8fc076..c306cb39d 100644 --- a/gtsam/inference/BayesNet-inl.h +++ b/gtsam/inference/BayesNet-inl.h @@ -19,57 +19,80 @@ #include -#include -#include #include #include #include -#include -#include #include // for += -using namespace boost::assign; +using boost::assign::operator+=; -using namespace std; +#include +#include +#include namespace gtsam { /* ************************************************************************* */ template - void BayesNet::print(const string& s) const { - cout << s << ":\n"; - BOOST_REVERSE_FOREACH(sharedConditional conditional,conditionals_) - conditional->print(); - } - - /* ************************************************************************* */ - template - bool BayesNet::equals(const BayesNet& cbn, double tol) const { - if(size() != cbn.size()) return false; - return equal(conditionals_.begin(),conditionals_.end(),cbn.conditionals_.begin(),equals_star(tol)); - } - - /* ************************************************************************* */ - template - typename BayesNet::const_iterator BayesNet::find(Index key) const { - for(const_iterator it = begin(); it != end(); ++it) - if(std::find((*it)->beginFrontals(), (*it)->endFrontals(), key) != (*it)->endFrontals()) - return it; - return end(); + void BayesNet::print(const std::string& s, + const IndexFormatter& formatter) const { + std::cout << s; + BOOST_REVERSE_FOREACH(sharedConditional conditional, conditionals_) + conditional->print("Conditional", formatter); } /* ************************************************************************* */ template - typename BayesNet::iterator BayesNet::find(Index key) { - for(iterator it = begin(); it != end(); ++it) - if(std::find((*it)->beginFrontals(), (*it)->endFrontals(), key) != (*it)->endFrontals()) + void BayesNet::printStats(const std::string& s) const { + + const size_t n = conditionals_.size(); + size_t max_size = 0; + size_t total = 0; + BOOST_REVERSE_FOREACH(sharedConditional conditional, conditionals_) { + max_size = std::max(max_size, conditional->size()); + total += conditional->size(); + } + std::cout << s + << "maximum conditional size = " << max_size << std::endl + << "average conditional size = " << total / n << std::endl + << "density = " << 100.0 * total / (double) (n*(n+1)/2) << " %" << std::endl; + } + + /* ************************************************************************* */ + template + bool BayesNet::equals(const BayesNet& cbn, double tol) const { + if (size() != cbn.size()) + return false; + return std::equal(conditionals_.begin(), conditionals_.end(), + cbn.conditionals_.begin(), equals_star(tol)); + } + + /* ************************************************************************* */ + template + typename BayesNet::const_iterator BayesNet::find( + Index key) const { + for (const_iterator it = begin(); it != end(); ++it) + if (std::find((*it)->beginFrontals(), (*it)->endFrontals(), key) + != (*it)->endFrontals()) return it; return end(); } /* ************************************************************************* */ template - void BayesNet::permuteWithInverse(const Permutation& inversePermutation) { + typename BayesNet::iterator BayesNet::find( + Index key) { + for (iterator it = begin(); it != end(); ++it) + if (std::find((*it)->beginFrontals(), (*it)->endFrontals(), key) + != (*it)->endFrontals()) + return it; + return end(); + } + + /* ************************************************************************* */ + template + void BayesNet::permuteWithInverse( + const Permutation& inversePermutation) { BOOST_FOREACH(sharedConditional conditional, conditionals_) { conditional->permuteWithInverse(inversePermutation); } @@ -77,52 +100,54 @@ namespace gtsam { /* ************************************************************************* */ template - bool BayesNet::permuteSeparatorWithInverse(const Permutation& inversePermutation) { + bool BayesNet::permuteSeparatorWithInverse( + const Permutation& inversePermutation) { bool separatorChanged = false; BOOST_FOREACH(sharedConditional conditional, conditionals_) { - if(conditional->permuteSeparatorWithInverse(inversePermutation)) + if (conditional->permuteSeparatorWithInverse(inversePermutation)) separatorChanged = true; } return separatorChanged; } - /* ************************************************************************* */ - template - void BayesNet::push_back(const BayesNet bn) { - BOOST_FOREACH(sharedConditional conditional,bn.conditionals_) - push_back(conditional); - } - - /* ************************************************************************* */ - template - void BayesNet::push_front(const BayesNet bn) { - BOOST_FOREACH(sharedConditional conditional,bn.conditionals_) - push_front(conditional); - } + /* ************************************************************************* */ + template + void BayesNet::push_back(const BayesNet bn) { + BOOST_FOREACH(sharedConditional conditional,bn.conditionals_) + push_back(conditional); + } /* ************************************************************************* */ template - void BayesNet::popLeaf(iterator conditional) { + void BayesNet::push_front(const BayesNet bn) { + BOOST_FOREACH(sharedConditional conditional,bn.conditionals_) + push_front(conditional); + } + + /* ************************************************************************* */ + template + void BayesNet::popLeaf(iterator conditional) { #ifndef NDEBUG BOOST_FOREACH(typename CONDITIONAL::shared_ptr checkConditional, conditionals_) { BOOST_FOREACH(Index key, (*conditional)->frontals()) { if(std::find(checkConditional->beginParents(), checkConditional->endParents(), key) != checkConditional->endParents()) - throw std::invalid_argument( - "Debug mode exception: in BayesNet::popLeaf, the requested conditional is not a leaf."); + throw std::invalid_argument( + "Debug mode exception: in BayesNet::popLeaf, the requested conditional is not a leaf."); } } #endif conditionals_.erase(conditional); - } + } - /* ************************************************************************* */ - template - FastList BayesNet::ordering() const { - FastList ord; - BOOST_FOREACH(sharedConditional conditional,conditionals_) - ord.insert(ord.begin(), conditional->beginFrontals(), conditional->endFrontals()); - return ord; - } + /* ************************************************************************* */ + template + FastList BayesNet::ordering() const { + FastList ord; + BOOST_FOREACH(sharedConditional conditional,conditionals_) + ord.insert(ord.begin(), conditional->beginFrontals(), + conditional->endFrontals()); + return ord; + } // /* ************************************************************************* */ // template @@ -139,21 +164,22 @@ namespace gtsam { // of.close(); // } // - /* ************************************************************************* */ + /* ************************************************************************* */ - template - typename BayesNet::sharedConditional - BayesNet::operator[](Index key) const { - BOOST_FOREACH(typename CONDITIONAL::shared_ptr conditional, conditionals_) { - typename CONDITIONAL::const_iterator it = std::find(conditional->beginFrontals(), conditional->endFrontals(), key); - if (it!=conditional->endFrontals()) { + template + typename BayesNet::sharedConditional BayesNet::operator[]( + Index key) const { + BOOST_FOREACH(typename CONDITIONAL::shared_ptr conditional, conditionals_) { + typename CONDITIONAL::const_iterator it = std::find( + conditional->beginFrontals(), conditional->endFrontals(), key); + if (it != conditional->endFrontals()) { return conditional; } - } - throw(invalid_argument((boost::format( - "BayesNet::operator['%1%']: not found") % key).str())); - } + } + throw(std::invalid_argument( + (boost::format("BayesNet::operator['%1%']: not found") % key).str())); + } - /* ************************************************************************* */ +/* ************************************************************************* */ } // namespace gtsam diff --git a/gtsam/inference/BayesNet.h b/gtsam/inference/BayesNet.h index 0f78a15e3..67d59c48d 100644 --- a/gtsam/inference/BayesNet.h +++ b/gtsam/inference/BayesNet.h @@ -10,7 +10,7 @@ * -------------------------------------------------------------------------- */ /** - * @file BayesNet + * @file BayesNet.h * @brief Bayes network * @author Frank Dellaert */ @@ -23,6 +23,7 @@ #include #include #include +#include #include #include @@ -48,6 +49,7 @@ public: typedef typename boost::shared_ptr > shared_ptr; /** We store shared pointers to Conditional densities */ + typedef typename CONDITIONAL::KeyType KeyType; typedef typename boost::shared_ptr sharedConditional; typedef typename boost::shared_ptr const_sharedConditional; typedef typename std::list Conditionals; @@ -88,7 +90,11 @@ public: /// @{ /** print */ - void print(const std::string& s = "") const; + void print(const std::string& s = "", + const IndexFormatter& formatter = DefaultIndexFormatter) const; + + /** print statistics */ + void printStats(const std::string& s = "") const; /** check equality */ bool equals(const BayesNet& other, double tol = 1e-9) const; diff --git a/gtsam/inference/BayesTree-inl.h b/gtsam/inference/BayesTree-inl.h index 95b070739..3d5276be8 100644 --- a/gtsam/inference/BayesTree-inl.h +++ b/gtsam/inference/BayesTree-inl.h @@ -10,7 +10,7 @@ * -------------------------------------------------------------------------- */ /** - * @file BayesTree.cpp + * @file BayesTree-inl.h * @brief Bayes Tree is a tree of cliques of a Bayes Chain * @author Frank Dellaert * @author Michael Kaess @@ -26,22 +26,17 @@ #include #include +#include #include #include #include #include // for operator += +using boost::assign::operator+=; #include -#include -#include -#include -using namespace boost::assign; -namespace lam = boost::lambda; namespace gtsam { - using namespace std; - /* ************************************************************************* */ template typename BayesTree::CliqueData @@ -51,9 +46,9 @@ namespace gtsam { return data; } + /* ************************************************************************* */ template - void BayesTree::getCliqueData(CliqueData& data, - BayesTree::sharedClique clique) const { + void BayesTree::getCliqueData(CliqueData& data, sharedClique clique) const { data.conditionalSizes.push_back((*clique)->nrFrontals()); data.separatorSizes.push_back((*clique)->nrParents()); BOOST_FOREACH(sharedClique c, clique->children_) { @@ -63,29 +58,28 @@ namespace gtsam { /* ************************************************************************* */ template - void BayesTree::saveGraph(const std::string &s) const { - if (!root_.get()) throw invalid_argument("the root of bayes tree has not been initialized!"); - ofstream of(s.c_str()); + void BayesTree::saveGraph(const std::string &s, const IndexFormatter& indexFormatter) const { + if (!root_.get()) throw std::invalid_argument("the root of Bayes tree has not been initialized!"); + std::ofstream of(s.c_str()); of<< "digraph G{\n"; - saveGraph(of, root_); + saveGraph(of, root_, indexFormatter); of<<"}"; of.close(); } + /* ************************************************************************* */ template - void BayesTree::saveGraph(ostream &s, - BayesTree::sharedClique clique, - int parentnum) const { + void BayesTree::saveGraph(std::ostream &s, sharedClique clique, const IndexFormatter& indexFormatter, int parentnum) const { static int num = 0; bool first = true; std::stringstream out; out << num; - string parent = out.str(); + std::string parent = out.str(); parent += "[label=\""; - BOOST_FOREACH(boost::shared_ptr c, clique->conditionals_) { + BOOST_FOREACH(Index index, clique->conditional_->frontals()) { if(!first) parent += ","; first = false; - parent += (string(c->key())).c_str(); + parent += indexFormatter(index); } if( clique != root_){ @@ -94,9 +88,9 @@ namespace gtsam { } first = true; - BOOST_FOREACH(Index sep, clique->separator_) { + BOOST_FOREACH(Index sep, clique->conditional_->parents()) { if(!first) parent += ","; first = false; - parent += (boost::format("%1%")%sep).str(); + parent += indexFormatter(sep); } parent += "\"];\n"; s << parent; @@ -104,11 +98,22 @@ namespace gtsam { BOOST_FOREACH(sharedClique c, clique->children_) { num++; - saveGraph(s, c, parentnum); + saveGraph(s, c, indexFormatter, parentnum); } } + /* ************************************************************************* */ + template + void BayesTree::CliqueStats::print(const std::string& s) const { + std::cout << s + <<"avg Conditional Size: " << avgConditionalSize << std::endl + << "max Conditional Size: " << maxConditionalSize << std::endl + << "avg Separator Size: " << avgSeparatorSize << std::endl + << "max Separator Size: " << maxSeparatorSize << std::endl; + } + + /* ************************************************************************* */ template typename BayesTree::CliqueStats BayesTree::CliqueData::getStats() const { @@ -137,10 +142,10 @@ namespace gtsam { /* ************************************************************************* */ template - void BayesTree::Cliques::print(const std::string& s) const { - cout << s << ":\n"; + void BayesTree::Cliques::print(const std::string& s, const IndexFormatter& indexFormatter) const { + std::cout << s << ":\n"; BOOST_FOREACH(sharedClique clique, *this) - clique->printTree(); + clique->printTree("", indexFormatter); } /* ************************************************************************* */ @@ -162,8 +167,8 @@ namespace gtsam { template void BayesTree::addClique(const sharedClique& clique, const sharedClique& parent_clique) { nodes_.resize(std::max((*clique)->lastFrontalKey()+1, nodes_.size())); - BOOST_FOREACH(Index key, (*clique)->frontals()) - nodes_[key] = clique; + BOOST_FOREACH(Index j, (*clique)->frontals()) + nodes_[j] = clique; if (parent_clique != NULL) { clique->parent_ = parent_clique; parent_clique->children_.push_back(clique); @@ -177,11 +182,11 @@ namespace gtsam { /* ************************************************************************* */ template typename BayesTree::sharedClique BayesTree::addClique( - const sharedConditional& conditional, list& child_cliques) { + const sharedConditional& conditional, std::list& child_cliques) { sharedClique new_clique(new Clique(conditional)); nodes_.resize(std::max(conditional->lastFrontalKey()+1, nodes_.size())); - BOOST_FOREACH(Index key, conditional->frontals()) - nodes_[key] = new_clique; + BOOST_FOREACH(Index j, conditional->frontals()) + nodes_[j] = new_clique; new_clique->children_ = child_cliques; BOOST_FOREACH(sharedClique& child, child_cliques) child->parent_ = new_clique; @@ -205,13 +210,13 @@ namespace gtsam { #endif if(debug) conditional->print("Adding conditional "); if(debug) clique->print("To clique "); - Index key = conditional->lastFrontalKey(); - bayesTree.nodes_.resize(std::max(key+1, bayesTree.nodes_.size())); - bayesTree.nodes_[key] = clique; - FastVector newKeys((*clique)->size() + 1); - newKeys[0] = key; - std::copy((*clique)->begin(), (*clique)->end(), newKeys.begin()+1); - clique->conditional_ = CONDITIONAL::FromKeys(newKeys, (*clique)->nrFrontals() + 1); + Index j = conditional->lastFrontalKey(); + bayesTree.nodes_.resize(std::max(j+1, bayesTree.nodes_.size())); + bayesTree.nodes_[j] = clique; + FastVector newIndices((*clique)->size() + 1); + newIndices[0] = j; + std::copy((*clique)->begin(), (*clique)->end(), newIndices.begin()+1); + clique->conditional_ = CONDITIONAL::FromKeys(newIndices, (*clique)->nrFrontals() + 1); if(debug) clique->print("Expanded clique is "); clique->assertInvariants(); } @@ -229,8 +234,8 @@ namespace gtsam { BOOST_FOREACH(sharedClique child, clique->children_) child->parent_ = typename Clique::weak_ptr(); - BOOST_FOREACH(Index key, (*clique->conditional())) { - nodes_[key].reset(); + BOOST_FOREACH(Index j, (*clique->conditional())) { + nodes_[j].reset(); } } @@ -292,10 +297,10 @@ namespace gtsam { template BayesTree::BayesTree(const BayesNet& bayesNet, std::list > subtrees) { if (bayesNet.size() == 0) - throw invalid_argument("BayesTree::insert: empty bayes net!"); + throw std::invalid_argument("BayesTree::insert: empty bayes net!"); // get the roots of child subtrees and merge their nodes_ - list childRoots; + std::list childRoots; typedef BayesTree Tree; BOOST_FOREACH(const Tree& subtree, subtrees) { nodes_.insert(subtree.nodes_.begin(), subtree.nodes_.end()); @@ -331,14 +336,14 @@ namespace gtsam { /* ************************************************************************* */ template - void BayesTree::print(const string& s) const { + void BayesTree::print(const std::string& s, const IndexFormatter& indexFormatter) const { if (root_.use_count() == 0) { - printf("WARNING: BayesTree.print encountered a forest...\n"); + std::cout << "WARNING: BayesTree.print encountered a forest..." << std::endl; return; } - cout << s << ": clique size == " << size() << ", node size == " << nodes_.size() << endl; + std::cout << s << ": clique size == " << size() << ", node size == " << nodes_.size() << std::endl; if (nodes_.empty()) return; - root_->printTree(""); + root_->printTree("", indexFormatter); } /* ************************************************************************* */ @@ -374,14 +379,14 @@ namespace gtsam { { static const bool debug = false; - // get key and parents + // get indices and parents const typename CONDITIONAL::Parents& parents = conditional->parents(); if(debug) conditional->print("Adding conditional "); // if no parents, start a new root clique if (parents.empty()) { - if(debug) cout << "No parents so making root" << endl; + if(debug) std::cout << "No parents so making root" << std::endl; bayesTree.root_ = bayesTree.addClique(conditional); return; } @@ -389,15 +394,15 @@ namespace gtsam { // otherwise, find the parent clique by using the index data structure // to find the lowest-ordered parent Index parentRepresentative = bayesTree.findParentClique(parents); - if(debug) cout << "First-eliminated parent is " << parentRepresentative << ", have " << bayesTree.nodes_.size() << " nodes." << endl; + if(debug) std::cout << "First-eliminated parent is " << parentRepresentative << ", have " << bayesTree.nodes_.size() << " nodes." << std::endl; sharedClique parent_clique = bayesTree[parentRepresentative]; if(debug) parent_clique->print("Parent clique is "); // if the parents and parent clique have the same size, add to parent clique if ((*parent_clique)->size() == size_t(parents.size())) { - if(debug) cout << "Adding to parent clique" << endl; + if(debug) std::cout << "Adding to parent clique" << std::endl; #ifndef NDEBUG - // Debug check that the parent keys of the new conditional match the keys + // Debug check that the parent indices of the new conditional match the indices // currently in the clique. // list::const_iterator parent = parents.begin(); // typename Clique::const_iterator cond = parent_clique->begin(); @@ -410,7 +415,7 @@ namespace gtsam { #endif addToCliqueFront(bayesTree, conditional, parent_clique); } else { - if(debug) cout << "Starting new clique" << endl; + if(debug) std::cout << "Starting new clique" << std::endl; // otherwise, start a new clique and add it to the tree bayesTree.addClique(conditional,parent_clique); } @@ -420,10 +425,10 @@ namespace gtsam { //TODO: remove this function after removing TSAM.cpp template typename BayesTree::sharedClique BayesTree::insert( - const sharedConditional& clique, list& children, bool isRootClique) { + const sharedConditional& clique, std::list& children, bool isRootClique) { if (clique->nrFrontals() == 0) - throw invalid_argument("BayesTree::insert: empty clique!"); + throw std::invalid_argument("BayesTree::insert: empty clique!"); // create a new clique and add all the conditionals to the clique sharedClique new_clique = addClique(clique, children); @@ -436,7 +441,7 @@ namespace gtsam { template void BayesTree::fillNodesIndex(const sharedClique& subtree) { // Add each frontal variable of this root node - BOOST_FOREACH(const Index& key, subtree->conditional()->frontals()) { nodes_[key] = subtree; } + BOOST_FOREACH(const Index& j, subtree->conditional()->frontals()) { nodes_[j] = subtree; } // Fill index for each child typedef typename BayesTree::sharedClique sharedClique; BOOST_FOREACH(const sharedClique& child, subtree->children_) { @@ -475,26 +480,26 @@ namespace gtsam { /* ************************************************************************* */ template typename CONDITIONAL::FactorType::shared_ptr BayesTree::marginalFactor( - Index key, Eliminate function) const { + Index j, Eliminate function) const { - // get clique containing key - sharedClique clique = (*this)[key]; + // get clique containing Index j + sharedClique clique = (*this)[j]; // calculate or retrieve its marginal FactorGraph cliqueMarginal = clique->marginal(root_,function); return GenericSequentialSolver(cliqueMarginal).marginalFactor( - key, function); + j, function); } /* ************************************************************************* */ template typename BayesNet::shared_ptr BayesTree::marginalBayesNet( - Index key, Eliminate function) const { + Index j, Eliminate function) const { // calculate marginal as a factor graph FactorGraph fg; - fg.push_back(this->marginalFactor(key,function)); + fg.push_back(this->marginalFactor(j,function)); // eliminate factor graph marginal to a Bayes net return GenericSequentialSolver(fg).eliminate(function); @@ -505,28 +510,28 @@ namespace gtsam { /* ************************************************************************* */ template typename FactorGraph::shared_ptr - BayesTree::joint(Index key1, Index key2, Eliminate function) const { + BayesTree::joint(Index j1, Index j2, Eliminate function) const { // get clique C1 and C2 - sharedClique C1 = (*this)[key1], C2 = (*this)[key2]; + sharedClique C1 = (*this)[j1], C2 = (*this)[j2]; // calculate joint FactorGraph p_C1C2(C1->joint(C2, root_, function)); // eliminate remaining factor graph to get requested joint - vector key12(2); key12[0] = key1; key12[1] = key2; + std::vector j12(2); j12[0] = j1; j12[1] = j2; GenericSequentialSolver solver(p_C1C2); - return solver.jointFactorGraph(key12,function); + return solver.jointFactorGraph(j12,function); } /* ************************************************************************* */ template typename BayesNet::shared_ptr BayesTree::jointBayesNet( - Index key1, Index key2, Eliminate function) const { + Index j1, Index j2, Eliminate function) const { // eliminate factor graph marginal to a Bayes net return GenericSequentialSolver ( - *this->joint(key1, key2, function)).eliminate(function); + *this->joint(j1, j2, function)).eliminate(function); } /* ************************************************************************* */ @@ -564,22 +569,27 @@ namespace gtsam { /* ************************************************************************* */ template - template - void BayesTree::removeTop(const CONTAINER& keys, + template + void BayesTree::removeTop(const CONTAINER& keys, BayesNet& bn, typename BayesTree::Cliques& orphans) { // process each key of the new factor - BOOST_FOREACH(const Index& key, keys) { + BOOST_FOREACH(const Index& j, keys) { // get the clique - if(key < nodes_.size()) { - const sharedClique& clique(nodes_[key]); + if(j < nodes_.size()) { + const sharedClique& clique(nodes_[j]); if(clique) { // remove path from clique to root this->removePath(clique, bn, orphans); } } } + + // Delete cachedShorcuts for each orphan subtree + //TODO: Consider Improving + BOOST_FOREACH(sharedClique& orphan, orphans) + orphan->deleteCachedShorcuts(); } /* ************************************************************************* */ diff --git a/gtsam/inference/BayesTree.h b/gtsam/inference/BayesTree.h index a9ed53ee9..1e87ca141 100644 --- a/gtsam/inference/BayesTree.h +++ b/gtsam/inference/BayesTree.h @@ -10,7 +10,7 @@ * -------------------------------------------------------------------------- */ /** - * @file BayesTree + * @file BayesTree.h * @brief Bayes Tree is a tree of cliques of a Bayes Chain * @author Frank Dellaert */ @@ -25,6 +25,7 @@ #include #include #include +#include #include #include @@ -46,7 +47,7 @@ namespace gtsam { * @tparam CLIQUE The type of the clique data structure, defaults to BayesTreeClique, normally do not change this * as it is only used when developing special versions of BayesTree, e.g. for ISAM2. * - * \ingroup Multifrontal + * \addtogroup Multifrontal * \nosubgrouping */ template > @@ -69,7 +70,8 @@ namespace gtsam { // A convenience class for a list of shared cliques struct Cliques : public std::list { - void print(const std::string& s = "Cliques") const; + void print(const std::string& s = "Cliques", + const IndexFormatter& indexFormatter = DefaultIndexFormatter) const; bool equals(const Cliques& other, double tol = 1e-9) const; }; @@ -79,6 +81,7 @@ namespace gtsam { std::size_t maxConditionalSize; double avgSeparatorSize; std::size_t maxSeparatorSize; + void print(const std::string& s = "") const ; }; /** store all the sizes */ @@ -88,55 +91,18 @@ namespace gtsam { CliqueStats getStats() const; }; - /** Map from keys to Clique */ + /** Map from indices to Clique */ typedef std::deque Nodes; protected: - /** Map from keys to Clique */ - Nodes nodes_; + /** Map from indices to Clique */ + Nodes nodes_; - /** private helper method for saving the Tree to a text file in GraphViz format */ - void saveGraph(std::ostream &s, sharedClique clique, - int parentnum = 0) const; + /** Root clique */ + sharedClique root_; - /** Gather data on a single clique */ - void getCliqueData(CliqueData& stats, sharedClique clique) const; - - /** Root clique */ - sharedClique root_; - - /** remove a clique: warning, can result in a forest */ - void removeClique(sharedClique clique); - - /** add a clique (top down) */ - sharedClique addClique(const sharedConditional& conditional, const sharedClique& parent_clique = sharedClique()); - - /** add a clique (top down) */ - void addClique(const sharedClique& clique, const sharedClique& parent_clique = sharedClique()); - - /** add a clique (bottom up) */ - sharedClique addClique(const sharedConditional& conditional, std::list& child_cliques); - - /** - * Add a conditional to the front of a clique, i.e. a conditional whose - * parents are already in the clique or its separators. This function does - * not check for this condition, it just updates the data structures. - */ - static void addToCliqueFront(BayesTree& bayesTree, - const sharedConditional& conditional, const sharedClique& clique); - - /** Fill the nodes index for a subtree */ - void fillNodesIndex(const sharedClique& subtree); - - /** Helper function to build a non-symbolic tree (e.g. Gaussian) using a - * symbolic tree, used in the BT(BN) constructor. - */ - void recursiveTreeBuild(const boost::shared_ptr >& symbolic, - const std::vector >& conditionals, - const typename BayesTree::sharedClique& parent); - - public: + public: /// @name Standard Constructors /// @{ @@ -174,14 +140,13 @@ namespace gtsam { bool equals(const BayesTree& other, double tol = 1e-9) const; /** print */ - void print(const std::string& s = "") const; + void print(const std::string& s = "", + const IndexFormatter& indexFormatter = DefaultIndexFormatter ) const; /// @} /// @name Standard Interface /// @{ - public: - /** * Find parent clique of a conditional. It will look at all parents and * return the one with the lowest index in the ordering. @@ -198,41 +163,41 @@ namespace gtsam { } /** return nodes */ - Nodes nodes() const { return nodes_; } + const Nodes& nodes() const { return nodes_; } /** return root clique */ const sharedClique& root() const { return root_; } - /** find the clique to which key belongs */ - sharedClique operator[](Index key) const { - return nodes_.at(key); + /** find the clique that contains the variable with Index j */ + sharedClique operator[](Index j) const { + return nodes_.at(j); } /** Gather data on all cliques */ CliqueData getCliqueData() const; /** return marginal on any variable */ - typename FactorType::shared_ptr marginalFactor(Index key, Eliminate function) const; + typename FactorType::shared_ptr marginalFactor(Index j, Eliminate function) const; /** * return marginal on any variable, as a Bayes Net * NOTE: this function calls marginal, and then eliminates it into a Bayes Net * This is more expensive than the above function */ - typename BayesNet::shared_ptr marginalBayesNet(Index key, Eliminate function) const; + typename BayesNet::shared_ptr marginalBayesNet(Index j, Eliminate function) const; /** return joint on two variables */ - typename FactorGraph::shared_ptr joint(Index key1, Index key2, Eliminate function) const; + typename FactorGraph::shared_ptr joint(Index j1, Index j2, Eliminate function) const; /** return joint on two variables as a BayesNet */ - typename BayesNet::shared_ptr jointBayesNet(Index key1, Index key2, Eliminate function) const; + typename BayesNet::shared_ptr jointBayesNet(Index j1, Index j2, Eliminate function) const; /** * Read only with side effects */ /** saves the Tree to a text file in GraphViz format */ - void saveGraph(const std::string& s) const; + void saveGraph(const std::string& s, const IndexFormatter& indexFormatter = DefaultIndexFormatter ) const; /// @} /// @name Advanced Interface @@ -241,6 +206,9 @@ namespace gtsam { /** Access the root clique (non-const version) */ sharedClique& root() { return root_; } + /** Access the nodes (non-cost version) */ + Nodes& nodes() { return nodes_; } + /** Remove all nodes */ void clear(); @@ -251,11 +219,11 @@ namespace gtsam { void removePath(sharedClique clique, BayesNet& bn, Cliques& orphans); /** - * Given a list of keys, turn "contaminated" part of the tree back into a factor graph. + * Given a list of indices, turn "contaminated" part of the tree back into a factor graph. * Factors and orphans are added to the in/out arguments. */ template - void removeTop(const CONTAINER& keys, BayesNet& bn, Cliques& orphans); + void removeTop(const CONTAINER& indices, BayesNet& bn, Cliques& orphans); /** * Hang a new subtree off of the existing tree. This finds the appropriate @@ -280,6 +248,46 @@ namespace gtsam { sharedClique insert(const sharedConditional& clique, std::list& children, bool isRootClique = false); + + protected: + + /** private helper method for saving the Tree to a text file in GraphViz format */ + void saveGraph(std::ostream &s, sharedClique clique, const IndexFormatter& indexFormatter, + int parentnum = 0) const; + + /** Gather data on a single clique */ + void getCliqueData(CliqueData& stats, sharedClique clique) const; + + /** remove a clique: warning, can result in a forest */ + void removeClique(sharedClique clique); + + /** add a clique (top down) */ + sharedClique addClique(const sharedConditional& conditional, const sharedClique& parent_clique = sharedClique()); + + /** add a clique (top down) */ + void addClique(const sharedClique& clique, const sharedClique& parent_clique = sharedClique()); + + /** add a clique (bottom up) */ + sharedClique addClique(const sharedConditional& conditional, std::list& child_cliques); + + /** + * Add a conditional to the front of a clique, i.e. a conditional whose + * parents are already in the clique or its separators. This function does + * not check for this condition, it just updates the data structures. + */ + static void addToCliqueFront(BayesTree& bayesTree, + const sharedConditional& conditional, const sharedClique& clique); + + /** Fill the nodes index for a subtree */ + void fillNodesIndex(const sharedClique& subtree); + + /** Helper function to build a non-symbolic tree (e.g. Gaussian) using a + * symbolic tree, used in the BT(BN) constructor. + */ + void recursiveTreeBuild(const boost::shared_ptr >& symbolic, + const std::vector >& conditionals, + const typename BayesTree::sharedClique& parent); + private: /** deep copy to another tree */ diff --git a/gtsam/inference/BayesTreeCliqueBase-inl.h b/gtsam/inference/BayesTreeCliqueBase-inl.h index dfc8864f7..344f845ac 100644 --- a/gtsam/inference/BayesTreeCliqueBase-inl.h +++ b/gtsam/inference/BayesTreeCliqueBase-inl.h @@ -10,7 +10,7 @@ * -------------------------------------------------------------------------- */ /** - * @file BayesTreeCliqueBase + * @file BayesTreeCliqueBase-inl.h * @brief Base class for cliques of a BayesTree * @author Richard Roberts and Frank Dellaert */ @@ -50,8 +50,8 @@ namespace gtsam { /* ************************************************************************* */ template - void BayesTreeCliqueBase::print(const std::string& s) const { - conditional_->print(s); + void BayesTreeCliqueBase::print(const std::string& s, const IndexFormatter& indexFormatter) const { + conditional_->print(s, indexFormatter); } /* ************************************************************************* */ @@ -65,10 +65,10 @@ namespace gtsam { /* ************************************************************************* */ template - void BayesTreeCliqueBase::printTree(const std::string& indent) const { - asDerived(this)->print(indent); + void BayesTreeCliqueBase::printTree(const std::string& indent, const IndexFormatter& indexFormatter) const { + asDerived(this)->print(indent, indexFormatter); BOOST_FOREACH(const derived_ptr& child, children_) - child->printTree(indent+" "); + child->printTree(indent+" ", indexFormatter); } /* ************************************************************************* */ @@ -108,98 +108,106 @@ namespace gtsam { // P(Sp|R) as \int P(Fp|Sp) P(Sp|R), where Fp are the frontal nodes in p /* ************************************************************************* */ template - BayesNet BayesTreeCliqueBase::shortcut(derived_ptr R, Eliminate function) { + BayesNet BayesTreeCliqueBase::shortcut( + derived_ptr R, Eliminate function) const{ - static const bool debug = false; + static const bool debug = false; - // A first base case is when this clique or its parent is the root, - // in which case we return an empty Bayes net. + BayesNet p_S_R; //shortcut P(S|R) This is empty now - derived_ptr parent(parent_.lock()); + //Check if the ShortCut already exists + if(!cachedShortcut_){ - if (R.get()==this || parent==R) { - BayesNet empty; - return empty; - } + // A first base case is when this clique or its parent is the root, + // in which case we return an empty Bayes net. - // The root conditional - FactorGraph p_R(BayesNet(R->conditional())); + derived_ptr parent(parent_.lock()); + if (R.get() != this && parent != R) { - // The parent clique has a ConditionalType for each frontal node in Fp - // so we can obtain P(Fp|Sp) in factor graph form - FactorGraph p_Fp_Sp(BayesNet(parent->conditional())); + // The root conditional + FactorGraph p_R(BayesNet(R->conditional())); - // If not the base case, obtain the parent shortcut P(Sp|R) as factors - FactorGraph p_Sp_R(parent->shortcut(R, function)); + // The parent clique has a ConditionalType for each frontal node in Fp + // so we can obtain P(Fp|Sp) in factor graph form + FactorGraph p_Fp_Sp(BayesNet(parent->conditional())); - // now combine P(Cp|R) = P(Fp|Sp) * P(Sp|R) - FactorGraph p_Cp_R; - p_Cp_R.push_back(p_R); - p_Cp_R.push_back(p_Fp_Sp); - p_Cp_R.push_back(p_Sp_R); + // If not the base case, obtain the parent shortcut P(Sp|R) as factors + FactorGraph p_Sp_R(parent->shortcut(R, function)); - // Eliminate into a Bayes net with ordering designed to integrate out - // any variables not in *our* separator. Variables to integrate out must be - // eliminated first hence the desired ordering is [Cp\S S]. - // However, an added wrinkle is that Cp might overlap with the root. - // Keys corresponding to the root should not be added to the ordering at all. + // now combine P(Cp|R) = P(Fp|Sp) * P(Sp|R) + FactorGraph p_Cp_R; + p_Cp_R.push_back(p_R); + p_Cp_R.push_back(p_Fp_Sp); + p_Cp_R.push_back(p_Sp_R); - if(debug) { - p_R.print("p_R: "); - p_Fp_Sp.print("p_Fp_Sp: "); - p_Sp_R.print("p_Sp_R: "); - } + // Eliminate into a Bayes net with ordering designed to integrate out + // any variables not in *our* separator. Variables to integrate out must be + // eliminated first hence the desired ordering is [Cp\S S]. + // However, an added wrinkle is that Cp might overlap with the root. + // Keys corresponding to the root should not be added to the ordering at all. - // We want to factor into a conditional of the clique variables given the - // root and the marginal on the root, integrating out all other variables. - // The integrands include any parents of this clique and the variables of - // the parent clique. - FastSet variablesAtBack; - FastSet separator; - size_t uniqueRootVariables = 0; - BOOST_FOREACH(const Index separatorIndex, this->conditional()->parents()) { - variablesAtBack.insert(separatorIndex); - separator.insert(separatorIndex); - if(debug) std::cout << "At back (this): " << separatorIndex << std::endl; - } - BOOST_FOREACH(const Index key, R->conditional()->keys()) { - if(variablesAtBack.insert(key).second) - ++ uniqueRootVariables; - if(debug) std::cout << "At back (root): " << key << std::endl; - } + if(debug) { + p_R.print("p_R: "); + p_Fp_Sp.print("p_Fp_Sp: "); + p_Sp_R.print("p_Sp_R: "); + } - Permutation toBack = Permutation::PushToBack( - std::vector(variablesAtBack.begin(), variablesAtBack.end()), - R->conditional()->lastFrontalKey() + 1); - Permutation::shared_ptr toBackInverse(toBack.inverse()); - BOOST_FOREACH(const typename FactorType::shared_ptr& factor, p_Cp_R) { - factor->permuteWithInverse(*toBackInverse); } - typename BayesNet::shared_ptr eliminated(EliminationTree< - FactorType>::Create(p_Cp_R)->eliminate(function)); + // We want to factor into a conditional of the clique variables given the + // root and the marginal on the root, integrating out all other variables. + // The integrands include any parents of this clique and the variables of + // the parent clique. + FastSet variablesAtBack; + FastSet separator; + size_t uniqueRootVariables = 0; + BOOST_FOREACH(const Index separatorIndex, this->conditional()->parents()) { + variablesAtBack.insert(separatorIndex); + separator.insert(separatorIndex); + if(debug) std::cout << "At back (this): " << separatorIndex << std::endl; + } + BOOST_FOREACH(const Index key, R->conditional()->keys()) { + if(variablesAtBack.insert(key).second) + ++ uniqueRootVariables; + if(debug) std::cout << "At back (root): " << key << std::endl; + } - // Take only the conditionals for p(S|R). We check for each variable being - // in the separator set because if some separator variables overlap with - // root variables, we cannot rely on the number of root variables, and also - // want to include those variables in the conditional. - BayesNet p_S_R; - BOOST_REVERSE_FOREACH(typename ConditionalType::shared_ptr conditional, *eliminated) { - assert(conditional->nrFrontals() == 1); - if(separator.find(toBack[conditional->firstFrontalKey()]) != separator.end()) { - if(debug) - conditional->print("Taking C|R conditional: "); - p_S_R.push_front(conditional); - } - if(p_S_R.size() == separator.size()) - break; - } + Permutation toBack = Permutation::PushToBack( + std::vector(variablesAtBack.begin(), variablesAtBack.end()), + R->conditional()->lastFrontalKey() + 1); + Permutation::shared_ptr toBackInverse(toBack.inverse()); + BOOST_FOREACH(const typename FactorType::shared_ptr& factor, p_Cp_R) { + factor->permuteWithInverse(*toBackInverse); } + typename BayesNet::shared_ptr eliminated(EliminationTree< + FactorType>::Create(p_Cp_R)->eliminate(function)); - // Undo the permutation - if(debug) toBack.print("toBack: "); - p_S_R.permuteWithInverse(toBack); + // Take only the conditionals for p(S|R). We check for each variable being + // in the separator set because if some separator variables overlap with + // root variables, we cannot rely on the number of root variables, and also + // want to include those variables in the conditional. + BOOST_REVERSE_FOREACH(typename ConditionalType::shared_ptr conditional, *eliminated) { + assert(conditional->nrFrontals() == 1); + if(separator.find(toBack[conditional->firstFrontalKey()]) != separator.end()) { + if(debug) + conditional->print("Taking C|R conditional: "); + p_S_R.push_front(conditional); + } + if(p_S_R.size() == separator.size()) + break; + } - // return the parent shortcut P(Sp|R) - assertInvariants(); - return p_S_R; + // Undo the permutation + if(debug) toBack.print("toBack: "); + p_S_R.permuteWithInverse(toBack); + } + + cachedShortcut_ = p_S_R; + } + else + p_S_R = *cachedShortcut_; // return the cached version + + assertInvariants(); + + // return the shortcut P(S|R) + return p_S_R; } /* ************************************************************************* */ @@ -210,7 +218,7 @@ namespace gtsam { /* ************************************************************************* */ template FactorGraph::FactorType> BayesTreeCliqueBase::marginal( - derived_ptr R, Eliminate function) { + derived_ptr R, Eliminate function) const{ // If we are the root, just return this root // NOTE: immediately cast to a factor graph BayesNet bn(R->conditional()); @@ -231,7 +239,7 @@ namespace gtsam { /* ************************************************************************* */ template FactorGraph::FactorType> BayesTreeCliqueBase::joint( - derived_ptr C2, derived_ptr R, Eliminate function) { + derived_ptr C2, derived_ptr R, Eliminate function) const { // For now, assume neither is the root // Combine P(F1|S1), P(S1|R), P(F2|S2), P(S2|R), and P(R) @@ -257,4 +265,22 @@ namespace gtsam { return *solver.jointFactorGraph(keys12vector, function); } + /* ************************************************************************* */ + template + void BayesTreeCliqueBase::deleteCachedShorcuts() { + + // When a shortcut is requested, all of the shortcuts between it and the + // root are also generated. So, if this clique's cached shortcut is set, + // recursively call over all child cliques. Otherwise, it is unnecessary. + if(cachedShortcut_) { + BOOST_FOREACH(derived_ptr& child, children_) { + child->deleteCachedShorcuts(); + } + + //Delete CachedShortcut for this clique + this->resetCachedShortcut(); + } + + } + } diff --git a/gtsam/inference/BayesTreeCliqueBase.h b/gtsam/inference/BayesTreeCliqueBase.h index 194b616b7..a2fb8feef 100644 --- a/gtsam/inference/BayesTreeCliqueBase.h +++ b/gtsam/inference/BayesTreeCliqueBase.h @@ -10,7 +10,7 @@ * -------------------------------------------------------------------------- */ /** - * @file BayesTreeCliqueBase + * @file BayesTreeCliqueBase.h * @brief Base class for cliques of a BayesTree * @author Richard Roberts and Frank Dellaert */ @@ -75,6 +75,9 @@ namespace gtsam { /// @} + /// This stores the Cached Shortcut value + mutable boost::optional > cachedShortcut_; + public: sharedConditional conditional_; derived_weak_ptr parent_; @@ -90,10 +93,10 @@ namespace gtsam { } /** print this node */ - void print(const std::string& s = "") const; + void print(const std::string& s = "", const IndexFormatter& indexFormatter = DefaultIndexFormatter ) const; /** print this node and entire subtree below it */ - void printTree(const std::string& indent="") const; + void printTree(const std::string& indent="", const IndexFormatter& indexFormatter = DefaultIndexFormatter ) const; /// @} /// @name Standard Interface @@ -111,9 +114,12 @@ namespace gtsam { /** The arrow operator accesses the conditional */ const ConditionalType* operator->() const { return conditional_.get(); } - ///TODO: comment + /** return the const reference of children */ const std::list& children() const { return children_; } + /** return a shared_ptr to the parent clique */ + derived_ptr parent() const { return parent_.lock(); } + /// @} /// @name Advanced Interface /// @{ @@ -121,7 +127,7 @@ namespace gtsam { /** The arrow operator accesses the conditional */ ConditionalType* operator->() { return conditional_.get(); } - /** return the const reference of children */ + /** return the reference of children non-const version*/ std::list& children() { return children_; } /** Construct shared_ptr from a conditional, leaving parent and child pointers uninitialized */ @@ -130,7 +136,7 @@ namespace gtsam { /** Construct shared_ptr from a FactorGraph::EliminationResult. In this class * the conditional part is kept and the factor part is ignored, but in derived clique * types, such as ISAM2Clique, the factor part is kept as a cached factor. - * @param An elimination result, which is a pair + * @param result An elimination result, which is a pair */ static derived_ptr Create(const std::pair >& result) { return boost::make_shared(result); } @@ -150,14 +156,22 @@ namespace gtsam { bool permuteSeparatorWithInverse(const Permutation& inversePermutation); /** return the conditional P(S|Root) on the separator given the root */ - // TODO: create a cached version - BayesNet shortcut(derived_ptr root, Eliminate function); + BayesNet shortcut(derived_ptr root, Eliminate function) const; /** return the marginal P(C) of the clique */ - FactorGraph marginal(derived_ptr root, Eliminate function); + FactorGraph marginal(derived_ptr root, Eliminate function) const; /** return the joint P(C1,C2), where C1==this. TODO: not a method? */ - FactorGraph joint(derived_ptr C2, derived_ptr root, Eliminate function); + FactorGraph joint(derived_ptr C2, derived_ptr root, Eliminate function) const; + + /** + * This deletes the cached shortcuts of all cliques (subtree) below this clique. + * This is performed when the bayes tree is modified. + */ + void deleteCachedShorcuts(); + + /** return cached shortcut of the clique */ + const boost::optional > cachedShortcut() const { return cachedShortcut_; } friend class BayesTree; @@ -166,6 +180,9 @@ namespace gtsam { ///TODO: comment void assertInvariants() const; + /// Reset the computed shortcut of this clique. Used by friend BayesTree + void resetCachedShortcut() { cachedShortcut_ = boost::none; } + private: /** Cliques cannot be copied except by the clone() method, which does not diff --git a/gtsam/inference/ClusterTree-inl.h b/gtsam/inference/ClusterTree-inl.h index 0f1f823af..3b8deb316 100644 --- a/gtsam/inference/ClusterTree-inl.h +++ b/gtsam/inference/ClusterTree-inl.h @@ -26,8 +26,6 @@ namespace gtsam { - using namespace std; - /* ************************************************************************* * * Cluster * ************************************************************************* */ @@ -58,13 +56,13 @@ namespace gtsam { /* ************************************************************************* */ template - bool ClusterTree::Cluster::equals(const ClusterTree::Cluster& other) const { + bool ClusterTree::Cluster::equals(const Cluster& other) const { if (frontal != other.frontal) return false; if (separator != other.separator) return false; if (children_.size() != other.children_.size()) return false; - typename list::const_iterator it1 = children_.begin(); - typename list::const_iterator it2 = other.children_.begin(); + typename std::list::const_iterator it1 = children_.begin(); + typename std::list::const_iterator it2 = other.children_.begin(); for (; it1 != children_.end(); it1++, it2++) if (!(*it1)->equals(**it2)) return false; @@ -73,31 +71,34 @@ namespace gtsam { /* ************************************************************************* */ template - void ClusterTree::Cluster::print(const string& indent) const { - cout << indent; + void ClusterTree::Cluster::print(const std::string& indent, + const IndexFormatter& formatter) const { + std::cout << indent; BOOST_FOREACH(const Index key, frontal) - cout << key << " "; - cout << ": "; + std::cout << formatter(key) << " "; + std::cout << ": "; BOOST_FOREACH(const Index key, separator) - cout << key << " "; - cout << endl; + std::cout << key << " "; + std::cout << std::endl; } /* ************************************************************************* */ template - void ClusterTree::Cluster::printTree(const string& indent) const { - print(indent); + void ClusterTree::Cluster::printTree(const std::string& indent, + const IndexFormatter& formatter) const { + print(indent, formatter); BOOST_FOREACH(const shared_ptr& child, children_) - child->printTree(indent + " "); + child->printTree(indent + " ", formatter); } /* ************************************************************************* * * ClusterTree * ************************************************************************* */ template - void ClusterTree::print(const string& str) const { - cout << str << endl; - if (root_) root_->printTree(""); + void ClusterTree::print(const std::string& str, + const IndexFormatter& formatter) const { + std::cout << str << std::endl; + if (root_) root_->printTree("", formatter); } /* ************************************************************************* */ diff --git a/gtsam/inference/ClusterTree.h b/gtsam/inference/ClusterTree.h index c5301f030..276ef374d 100644 --- a/gtsam/inference/ClusterTree.h +++ b/gtsam/inference/ClusterTree.h @@ -25,6 +25,7 @@ #include #include +#include #include @@ -32,12 +33,15 @@ namespace gtsam { /** * A cluster-tree is associated with a factor graph and is defined as in Koller-Friedman: - * each node k represents a subset C_k \sub X, and the tree is family preserving, in that - * each factor f_i is associated with a single cluster and scope(f_i) \sub C_k. + * each node k represents a subset \f$ C_k \sub X \f$, and the tree is family preserving, in that + * each factor \f$ f_i \f$ is associated with a single cluster and \f$ scope(f_i) \sub C_k \f$. * \nosubgrouping */ template class ClusterTree { + public: + // Access to factor types + typedef typename FG::KeyType KeyType; protected: @@ -74,10 +78,10 @@ namespace gtsam { Cluster(FRONTALIT firstFrontal, FRONTALIT lastFrontal, SEPARATORIT firstSeparator, SEPARATORIT lastSeparator); /// print - void print(const std::string& indent) const; + void print(const std::string& indent, const IndexFormatter& formatter = DefaultIndexFormatter) const; /// print the enire tree - void printTree(const std::string& indent) const; + void printTree(const std::string& indent, const IndexFormatter& formatter = DefaultIndexFormatter) const; /// check equality bool equals(const Cluster& other) const; @@ -123,7 +127,7 @@ namespace gtsam { /// @{ /// print the object - void print(const std::string& str="") const; + void print(const std::string& str="", const IndexFormatter& formatter = DefaultIndexFormatter) const; /** check equality */ bool equals(const ClusterTree& other, double tol = 1e-9) const; diff --git a/gtsam/inference/Conditional.h b/gtsam/inference/Conditional.h index 0b5fca660..8363c1800 100644 --- a/gtsam/inference/Conditional.h +++ b/gtsam/inference/Conditional.h @@ -23,6 +23,7 @@ #include // for noncopyable #include #include +#include #include #include @@ -98,13 +99,16 @@ public: Conditional(KeyType key) : FactorType(key), nrFrontals_(1) { assertInvariants(); } /** Single parent */ - Conditional(KeyType key, KeyType parent) : FactorType(key, parent), nrFrontals_(1) { assertInvariants(); } + Conditional(KeyType key, KeyType parent) + : FactorType(key, parent), nrFrontals_(1) { assertInvariants(); } /** Two parents */ - Conditional(KeyType key, KeyType parent1, KeyType parent2) : FactorType(key, parent1, parent2), nrFrontals_(1) { assertInvariants(); } + Conditional(KeyType key, KeyType parent1, KeyType parent2) + : FactorType(key, parent1, parent2), nrFrontals_(1) { assertInvariants(); } /** Three parents */ - Conditional(KeyType key, KeyType parent1, KeyType parent2, KeyType parent3) : FactorType(key, parent1, parent2, parent3), nrFrontals_(1) { assertInvariants(); } + Conditional(KeyType key, KeyType parent1, KeyType parent2, KeyType parent3) + : FactorType(key, parent1, parent2, parent3), nrFrontals_(1) { assertInvariants(); } /// @} /// @name Advanced Constructors @@ -126,8 +130,8 @@ public: /// @name Testable /// @{ - /** print */ - void print(const std::string& s = "Conditional") const; + /** print with optional formatter */ + void print(const std::string& s = "Conditional", const IndexFormatter& formatter = DefaultIndexFormatter) const; /** check equality */ template @@ -196,12 +200,12 @@ private: /* ************************************************************************* */ template -void Conditional::print(const std::string& s) const { +void Conditional::print(const std::string& s, const IndexFormatter& formatter) const { std::cout << s << " P("; - BOOST_FOREACH(KeyType key, frontals()) std::cout << " " << key; - if (nrParents()>0) std::cout << " |"; - BOOST_FOREACH(KeyType parent, parents()) std::cout << " " << parent; - std::cout << ")" << std::endl; + BOOST_FOREACH(KeyType key, frontals()) std::cout << " " << formatter(key); + if (nrParents()>0) std::cout << " |"; + BOOST_FOREACH(KeyType parent, parents()) std::cout << " " << formatter(parent); + std::cout << ")" << std::endl; } } // gtsam diff --git a/gtsam/inference/EliminationTree-inl.h b/gtsam/inference/EliminationTree-inl.h index 488911127..2e977aa4b 100644 --- a/gtsam/inference/EliminationTree-inl.h +++ b/gtsam/inference/EliminationTree-inl.h @@ -10,7 +10,7 @@ * -------------------------------------------------------------------------- */ /** - * @file EliminationTree.cpp + * @file EliminationTree-inl.h * @author Frank Dellaert * @date Oct 13, 2010 */ @@ -24,14 +24,12 @@ #include #include -#include #include + #include #include #include -using namespace std; - namespace gtsam { /* ************************************************************************* */ @@ -41,7 +39,7 @@ typename EliminationTree::sharedFactor EliminationTree::eliminat static const bool debug = false; - if(debug) cout << "ETree: eliminating " << this->key_ << endl; + if(debug) std::cout << "ETree: eliminating " << this->key_ << std::endl; // Create the list of factors to be eliminated, initially empty, and reserve space FactorGraph factors; @@ -60,7 +58,7 @@ typename EliminationTree::sharedFactor EliminationTree::eliminat eliminated(function(factors, 1)); conditionals[this->key_] = eliminated.first; - if(debug) cout << "Eliminated " << this->key_ << " to get:\n"; + if(debug) std::cout << "Eliminated " << this->key_ << " to get:\n"; if(debug) eliminated.first->print("Conditional: "); if(debug) eliminated.second->print("Factor: "); @@ -69,17 +67,17 @@ typename EliminationTree::sharedFactor EliminationTree::eliminat /* ************************************************************************* */ template -vector EliminationTree::ComputeParents(const VariableIndex& structure) { +std::vector EliminationTree::ComputeParents(const VariableIndex& structure) { // Number of factors and variables const size_t m = structure.nFactors(); const size_t n = structure.size(); - static const Index none = numeric_limits::max(); + static const Index none = std::numeric_limits::max(); // Allocate result parent vector and vector of last factor columns - vector parents(n, none); - vector prevCol(m, none); + std::vector parents(n, none); + std::vector prevCol(m, none); // for column j \in 1 to n do for (Index j = 0; j < n; j++) { @@ -111,17 +109,17 @@ typename EliminationTree::shared_ptr EliminationTree::Create( tic(1, "ET ComputeParents"); // Compute the tree structure - vector parents(ComputeParents(structure)); + std::vector parents(ComputeParents(structure)); toc(1, "ET ComputeParents"); // Number of variables const size_t n = structure.size(); - static const Index none = numeric_limits::max(); + static const Index none = std::numeric_limits::max(); // Create tree structure tic(2, "assemble tree"); - vector trees(n); + std::vector trees(n); for (Index k = 1; k <= n; k++) { Index j = n - k; // Start at the last variable and loop down to 0 trees[j].reset(new EliminationTree(j)); // Create a new node on this variable @@ -134,7 +132,7 @@ typename EliminationTree::shared_ptr EliminationTree::Create( // Hang factors in right places tic(3, "hang factors"); - BOOST_FOREACH(const typename DERIVEDFACTOR::shared_ptr& derivedFactor, factorGraph) { + BOOST_FOREACH(const typename boost::shared_ptr& derivedFactor, factorGraph) { // Here we upwards-cast to the factor type of this EliminationTree. This // allows performing symbolic elimination on, for example, GaussianFactors. if(derivedFactor) { @@ -168,12 +166,13 @@ EliminationTree::Create(const FactorGraph& factorGraph) { /* ************************************************************************* */ template -void EliminationTree::print(const std::string& name) const { - cout << name << " (" << key_ << ")" << endl; +void EliminationTree::print(const std::string& name, + const IndexFormatter& formatter) const { + std::cout << name << " (" << formatter(key_) << ")" << std::endl; BOOST_FOREACH(const sharedFactor& factor, factors_) { - factor->print(name + " "); } + factor->print(name + " ", formatter); } BOOST_FOREACH(const shared_ptr& child, subTrees_) { - child->print(name + " "); } + child->print(name + " ", formatter); } } /* ************************************************************************* */ diff --git a/gtsam/inference/EliminationTree.h b/gtsam/inference/EliminationTree.h index 0b01f0586..f2b0c1eaf 100644 --- a/gtsam/inference/EliminationTree.h +++ b/gtsam/inference/EliminationTree.h @@ -52,8 +52,10 @@ public: typedef EliminationTree This; ///< This class typedef boost::shared_ptr shared_ptr; ///< Shared pointer to this class - typedef typename FACTOR::shared_ptr sharedFactor; ///< Shared pointer to a factor + typedef typename boost::shared_ptr sharedFactor; ///< Shared pointer to a factor typedef gtsam::BayesNet BayesNet; ///< The BayesNet corresponding to FACTOR + typedef FACTOR Factor; + typedef typename FACTOR::KeyType KeyType; /** Typedef for an eliminate subroutine */ typedef typename FactorGraph::Eliminate Eliminate; @@ -67,43 +69,15 @@ private: typedef FastList SubTrees; typedef std::vector Conditionals; - Index key_; ///< index associated with root + Index key_; ///< index associated with root // FIXME: doesn't this require that "Index" is the type of keys in the generic factor? Factors factors_; ///< factors associated with root SubTrees subTrees_; ///< sub-trees +public: + /// @name Standard Constructors /// @{ - /** default constructor, private, as you should use Create below */ - EliminationTree(Index key = 0) : key_(key) {} - - /// @} - /// @name Advanced Interface - /// @{ - - /** - * Static internal function to build a vector of parent pointers using the - * algorithm of Gilbert et al., 2001, BIT. - */ - static std::vector ComputeParents(const VariableIndex& structure); - - /** add a factor, for Create use only */ - void add(const sharedFactor& factor) { factors_.push_back(factor); } - - /** add a subtree, for Create use only */ - void add(const shared_ptr& child) { subTrees_.push_back(child); } - - /** - * Recursive routine that eliminates the factors arranged in an elimination tree - * @param Conditionals is a vector of shared pointers that will be modified in place - */ - sharedFactor eliminate_(Eliminate function, Conditionals& conditionals) const; - - /// Allow access to constructor and add methods for testing purposes - friend class ::EliminationTreeTester; - -public: - /** * Named constructor to build the elimination tree of a factor graph using * pre-computed column structure. @@ -141,13 +115,40 @@ public: /// @{ /** Print the tree to cout */ - void print(const std::string& name = "EliminationTree: ") const; + void print(const std::string& name = "EliminationTree: ", + const IndexFormatter& formatter = DefaultIndexFormatter) const; /** Test whether the tree is equal to another */ bool equals(const EliminationTree& other, double tol = 1e-9) const; /// @} +private: + + /** default constructor, private, as you should use Create below */ + EliminationTree(Index key = 0) : key_(key) {} + + /** + * Static internal function to build a vector of parent pointers using the + * algorithm of Gilbert et al., 2001, BIT. + */ + static std::vector ComputeParents(const VariableIndex& structure); + + /** add a factor, for Create use only */ + void add(const sharedFactor& factor) { factors_.push_back(factor); } + + /** add a subtree, for Create use only */ + void add(const shared_ptr& child) { subTrees_.push_back(child); } + + /** + * Recursive routine that eliminates the factors arranged in an elimination tree + * @param Conditionals is a vector of shared pointers that will be modified in place + */ + sharedFactor eliminate_(Eliminate function, Conditionals& conditionals) const; + + /// Allow access to constructor and add methods for testing purposes + friend class ::EliminationTreeTester; + }; @@ -157,7 +158,7 @@ public: * disconnected graphs, a workaround is to create zero-information factors to * bridge the disconnects. To do this, create any factor type (e.g. * BetweenFactor or RangeFactor) with the noise model - * \ref sharedPrecision(dim, 0.0), where \c dim is the appropriate + * sharedPrecision(dim, 0.0), where \c dim is the appropriate * dimensionality for that factor. */ struct DisconnectedGraphException : public std::exception { @@ -166,7 +167,12 @@ struct DisconnectedGraphException : public std::exception { /// Returns the string "Attempting to eliminate a disconnected graph - this is not currently possible in gtsam." virtual const char* what() const throw() { - return "Attempting to eliminate a disconnected graph - this is not currently possible in gtsam."; } + return + "Attempting to eliminate a disconnected graph - this is not currently possible in\n" + "GTSAM. You may add \"empty\" BetweenFactor's to join disconnected graphs, these\n" + "will affect the symbolic structure and solving complexity of the graph but not\n" + "the solution. To do this, create BetweenFactor's with zero-precision noise\n" + "models, i.e. noiseModel::Isotropic::Precision(n, 0.0);\n"; } }; } diff --git a/gtsam/inference/Factor-inl.h b/gtsam/inference/Factor-inl.h index d9fb1e0de..b2099aa3e 100644 --- a/gtsam/inference/Factor-inl.h +++ b/gtsam/inference/Factor-inl.h @@ -56,12 +56,19 @@ namespace gtsam { /* ************************************************************************* */ template - void Factor::print(const std::string& s) const { - std::cout << s << " "; - BOOST_FOREACH(KEY key, keys_) std::cout << " " << key; - std::cout << std::endl; + void Factor::print(const std::string& s, + const IndexFormatter& formatter) const { + printKeys(s,formatter); } + /* ************************************************************************* */ + template + void Factor::printKeys(const std::string& s, const IndexFormatter& formatter) const { + std::cout << s << " "; + BOOST_FOREACH(KEY key, keys_) std::cout << " " << formatter(key); + std::cout << std::endl; + } + /* ************************************************************************* */ template bool Factor::equals(const This& other, double tol) const { diff --git a/gtsam/inference/Factor.h b/gtsam/inference/Factor.h index 87c1f3860..4c31664d7 100644 --- a/gtsam/inference/Factor.h +++ b/gtsam/inference/Factor.h @@ -25,6 +25,9 @@ #include #include #include +#include +#include +#include #include namespace gtsam { @@ -36,7 +39,7 @@ template class Conditional; * which will be the type used to label variables. Key types currently in use * in gtsam are Index with symbolic (IndexFactor, SymbolicFactorGraph) and * Gaussian factors (GaussianFactor, JacobianFactor, HessianFactor, GaussianFactorGraph), - * and Symbol with nonlinear factors (NonlinearFactor, NonlinearFactorGraph). + * and Key with nonlinear factors (NonlinearFactor, NonlinearFactorGraph). * though currently only IndexFactor and IndexConditional derive from this * class, using Index keys. This class does not store any data other than its * keys. Derived classes store data such as matrices and probability tables. @@ -45,7 +48,7 @@ template class Conditional; * typedefs to refer to the associated conditional and shared_ptr types of the * derived class. See IndexFactor, JacobianFactor, etc. for examples. * - * This class is \bold{not} virtual for performance reasons - derived symbolic classes, + * This class is \b not virtual for performance reasons - derived symbolic classes, * IndexFactor and IndexConditional, need to be created and destroyed quickly * during symbolic elimination. GaussianFactor and NonlinearFactor are virtual. * \nosubgrouping @@ -78,15 +81,6 @@ protected: /// The keys involved in this factor std::vector keys_; - friend class JacobianFactor; - friend class HessianFactor; - -protected: - - /// Internal consistency check that is run frequently when in debug mode. - /// If NDEBUG is defined, this is empty and optimized out. - void assertInvariants() const; - public: /// @name Standard Constructors @@ -190,7 +184,12 @@ public: /// @{ /// print - void print(const std::string& s = "Factor") const; + void print(const std::string& s = "Factor", + const IndexFormatter& formatter = DefaultIndexFormatter) const; + + /// print only keys + void printKeys(const std::string& s = "Factor", + const IndexFormatter& formatter = DefaultIndexFormatter) const; /// check equality bool equals(const This& other, double tol = 1e-9) const; @@ -208,9 +207,15 @@ public: iterator begin() { return keys_.begin(); } ///TODO: comment iterator end() { return keys_.end(); } ///TODO: comment +protected: + friend class JacobianFactor; + friend class HessianFactor; + + /// Internal consistency check that is run frequently when in debug mode. + /// If NDEBUG is defined, this is empty and optimized out. + void assertInvariants() const; private: - /** Serialization function */ friend class boost::serialization::access; template diff --git a/gtsam/inference/FactorGraph-inl.h b/gtsam/inference/FactorGraph-inl.h index ea92cb791..04490dbc6 100644 --- a/gtsam/inference/FactorGraph-inl.h +++ b/gtsam/inference/FactorGraph-inl.h @@ -23,38 +23,46 @@ #pragma once #include +#include #include #include #include -#include #include #include #include #include #include -#include - -using namespace std; namespace gtsam { + /* ************************************************************************* */ + template + template + FactorGraph::FactorGraph(const BayesNet& bayesNet) { + factors_.reserve(bayesNet.size()); + BOOST_FOREACH(const typename CONDITIONAL::shared_ptr& cond, bayesNet) { + this->push_back(cond->toFactor()); + } + } + /* ************************************************************************* */ template - void FactorGraph::print(const string& s) const { - cout << s << endl; - cout << "size: " << size() << endl; + void FactorGraph::print(const std::string& s, + const IndexFormatter& formatter) const { + std::cout << s << std::endl; + std::cout << "size: " << size() << std::endl; for (size_t i = 0; i < factors_.size(); i++) { - stringstream ss; + std::stringstream ss; ss << "factor " << i << ": "; - if (factors_[i] != NULL) factors_[i]->print(ss.str()); + if (factors_[i] != NULL) factors_[i]->print(ss.str(), formatter); } } /* ************************************************************************* */ template - bool FactorGraph::equals(const FactorGraph& fg, double tol) const { + bool FactorGraph::equals(const This& fg, double tol) const { /** check whether the two factor graphs have the same number of factors_ */ if (factors_.size() != fg.size()) return false; @@ -78,10 +86,61 @@ namespace gtsam { return size_; } + /* ************************************************************************* */ + template + std::pair::sharedConditional, FactorGraph > + FactorGraph::eliminateFrontals(size_t nFrontals, const Eliminate& eliminate) const + { + // Build variable index + VariableIndex variableIndex(*this); + + // Find first variable + Index firstIndex = 0; + while(firstIndex < variableIndex.size() && variableIndex[firstIndex].empty()) + ++ firstIndex; + + // Check that number of variables is in bounds + if(firstIndex + nFrontals > variableIndex.size()) + throw std::invalid_argument("Requested to eliminate more frontal variables than exist in the factor graph."); + + // Get set of involved factors + FastSet involvedFactorIs; + for(Index j = firstIndex; j < firstIndex + nFrontals; ++j) { + BOOST_FOREACH(size_t i, variableIndex[j]) { + involvedFactorIs.insert(i); + } + } + + // Separate factors into involved and remaining + FactorGraph involvedFactors; + FactorGraph remainingFactors; + FastSet::const_iterator involvedFactorIsIt = involvedFactorIs.begin(); + for(size_t i = 0; i < this->size(); ++i) { + if(involvedFactorIsIt != involvedFactorIs.end() && *involvedFactorIsIt == i) { + // If the current factor is involved, add it to involved and increment involved iterator + involvedFactors.push_back((*this)[i]); + ++ involvedFactorIsIt; + } else { + // If not involved, add to remaining + remainingFactors.push_back((*this)[i]); + } + } + + // Do dense elimination on the involved factors + typename FactorGraph::EliminationResult eliminationResult = + eliminate(involvedFactors, nFrontals); + + // Add the remaining factor back into the factor graph + remainingFactors.push_back(eliminationResult.second); + + // Return the eliminated factor and remaining factor graph + return std::make_pair(eliminationResult.first, remainingFactors); + } + /* ************************************************************************* */ template void FactorGraph::replace(size_t index, sharedFactor factor) { - if (index >= factors_.size()) throw invalid_argument(boost::str( + if (index >= factors_.size()) throw std::invalid_argument(boost::str( boost::format("Factor graph does not contain a factor with index %d.") % index)); // Replace the factor @@ -101,30 +160,34 @@ namespace gtsam { } /* ************************************************************************* */ - template - typename DERIVED::shared_ptr Combine(const FactorGraph& factors, - const FastMap >& variableSlots) { - typedef const pair > KeySlotPair; - return typename DERIVED::shared_ptr(new DERIVED( - boost::make_transform_iterator(variableSlots.begin(), boost::bind(&KeySlotPair::first, _1)), - boost::make_transform_iterator(variableSlots.end(), boost::bind(&KeySlotPair::first, _1)))); + template + typename DERIVEDFACTOR::shared_ptr Combine(const FactorGraph& factors, + const FastMap >& variableSlots) { + + typedef const std::pair > KeySlotPair; + // Local functional for getting keys out of key-value pairs + struct Local { static KEY FirstOf(const KeySlotPair& pr) { return pr.first; } }; + + return typename DERIVEDFACTOR::shared_ptr(new DERIVEDFACTOR( + boost::make_transform_iterator(variableSlots.begin(), &Local::FirstOf), + boost::make_transform_iterator(variableSlots.end(), &Local::FirstOf))); } /* ************************************************************************* */ + // Recursive function to add factors in cliques to vector of factors_io template void _FactorGraph_BayesTree_adder( - vector::sharedFactor>& factors, + std::vector >& factors_io, const typename BayesTree::sharedClique& clique) { if(clique) { // Add factor from this clique - factors.push_back((*clique)->toFactor()); + factors_io.push_back((*clique)->toFactor()); // Traverse children typedef typename BayesTree::sharedClique sharedClique; - BOOST_FOREACH(const sharedClique& child, clique->children()) { - _FactorGraph_BayesTree_adder(factors, child); - } + BOOST_FOREACH(const sharedClique& child, clique->children()) + _FactorGraph_BayesTree_adder(factors_io, child); } } diff --git a/gtsam/inference/FactorGraph.h b/gtsam/inference/FactorGraph.h index 33cdd02a1..ed3e7d952 100644 --- a/gtsam/inference/FactorGraph.h +++ b/gtsam/inference/FactorGraph.h @@ -21,14 +21,13 @@ #pragma once -#include -#include -#include - #include #include #include +#include +#include + namespace gtsam { // Forward declarations @@ -41,30 +40,28 @@ template class BayesTree; */ template class FactorGraph { + public: - typedef FACTOR FactorType; - typedef typename FACTOR::KeyType KeyType; - typedef boost::shared_ptr > shared_ptr; - typedef typename boost::shared_ptr sharedFactor; + + typedef FACTOR FactorType; ///< factor type + typedef typename FACTOR::KeyType KeyType; ///< type of Keys we use to index factors with + typedef boost::shared_ptr sharedFactor; ///< Shared pointer to a factor + typedef boost::shared_ptr sharedConditional; ///< Shared pointer to a conditional + + typedef FactorGraph This; ///< Typedef for this class + typedef boost::shared_ptr shared_ptr; ///< Shared pointer for this class typedef typename std::vector::iterator iterator; typedef typename std::vector::const_iterator const_iterator; - /** typedef for elimination result */ - typedef std::pair< - boost::shared_ptr, - typename FACTOR::shared_ptr> EliminationResult; + /** typedef for elimination result */ + typedef std::pair EliminationResult; - /** typedef for an eliminate subroutine */ - typedef boost::function&, size_t)> Eliminate; - - /** Typedef for the result of factorization */ - typedef std::pair< - boost::shared_ptr, - FactorGraph > FactorizationResult; + /** typedef for an eliminate subroutine */ + typedef boost::function Eliminate; protected: - /** concept check */ + /** concept check, makes sure FACTOR defines print and equals */ GTSAM_CONCEPT_TESTABLE_TYPE(FACTOR) /** Collection of factors */ @@ -82,7 +79,11 @@ template class BayesTree; /// @name Advanced Constructors /// @{ - /** convert from Bayes net */ + /** + * @brief Constructor from a Bayes net + * @param bayesNet the Bayes net to convert, type CONDITIONAL must yield compatible factor + * @return a factor graph with all the conditionals, as factors + */ template FactorGraph(const BayesNet& bayesNet); @@ -113,7 +114,7 @@ template class BayesTree; } /** push back many factors */ - void push_back(const FactorGraph& factors) { + void push_back(const This& factors) { factors_.insert(end(), factors.begin(), factors.end()); } @@ -123,19 +124,25 @@ template class BayesTree; factors_.insert(end(), firstFactor, lastFactor); } - /** push back many factors stored in a vector*/ + /** + * @brief Add a vector of derived factors + * @param factors to add + */ template - void push_back(const std::vector >& factors); + void push_back(const std::vector >& factors) { + factors_.insert(end(), factors.begin(), factors.end()); + } /// @} /// @name Testable /// @{ /** print out graph */ - void print(const std::string& s = "FactorGraph") const; + void print(const std::string& s = "FactorGraph", + const IndexFormatter& formatter = DefaultIndexFormatter) const; /** Check equality */ - bool equals(const FactorGraph& fg, double tol = 1e-9) const; + bool equals(const This& fg, double tol = 1e-9) const; /// @} /// @name Standard Interface @@ -151,8 +158,10 @@ template class BayesTree; operator const std::vector&() const { return factors_; } /** Get a specific factor by index */ - const sharedFactor operator[](size_t i) const { assert(i class BayesTree; /** Get the last factor */ sharedFactor back() const { return factors_.back(); } + /** Eliminate the first \c n frontal variables, returning the resulting + * conditional and remaining factor graph - this is very inefficient for + * eliminating all variables, to do that use EliminationTree or + * JunctionTree. + */ + std::pair > eliminateFrontals(size_t nFrontals, const Eliminate& eliminate) const; + /// @} /// @name Modifying Factor Graphs (imperative, discouraged) /// @{ @@ -192,39 +208,6 @@ template class BayesTree; /** return the number valid factors */ size_t nrFactors() const; - /** dynamic_cast the factor pointers down or up the class hierarchy */ - template - typename RELATED::shared_ptr dynamicCastFactors() const { - typename RELATED::shared_ptr ret(new RELATED); - ret->reserve(this->size()); - BOOST_FOREACH(const sharedFactor& factor, *this) { - typename RELATED::FactorType::shared_ptr castedFactor(boost::dynamic_pointer_cast(factor)); - if(castedFactor) - ret->push_back(castedFactor); - else - throw std::invalid_argument("In FactorGraph::dynamic_factor_cast(), dynamic_cast failed, meaning an invalid cast was requested."); - } - return ret; - } - - /** - * dynamic_cast factor pointers if possible, otherwise convert with a - * constructor of the target type. - */ - template - typename TARGET::shared_ptr convertCastFactors() const { - typename TARGET::shared_ptr ret(new TARGET); - ret->reserve(this->size()); - BOOST_FOREACH(const sharedFactor& factor, *this) { - typename TARGET::FactorType::shared_ptr castedFactor(boost::dynamic_pointer_cast(factor)); - if(castedFactor) - ret->push_back(castedFactor); - else - ret->push_back(typename TARGET::FactorType::shared_ptr(new typename TARGET::FactorType(*factor))); - } - return ret; - } - private: /** Serialization function */ @@ -239,44 +222,19 @@ template class BayesTree; }; // FactorGraph /** Create a combined joint factor (new style for EliminationTree). */ - template - typename DERIVED::shared_ptr Combine(const FactorGraph& factors, + template + typename DERIVEDFACTOR::shared_ptr Combine(const FactorGraph& factors, const FastMap >& variableSlots); /** * static function that combines two factor graphs - * @param const &fg1 Linear factor graph - * @param const &fg2 Linear factor graph + * @param fg1 Linear factor graph + * @param fg2 Linear factor graph * @return a new combined factor graph */ template FACTORGRAPH combine(const FACTORGRAPH& fg1, const FACTORGRAPH& fg2); - /* - * These functions are defined here because they are templated on an - * additional parameter. Putting them in the -inl.h file would mean these - * would have to be explicitly instantiated for any possible derived factor - * type. - */ - - /* ************************************************************************* */ - template - template - FactorGraph::FactorGraph(const BayesNet& bayesNet) { - factors_.reserve(bayesNet.size()); - BOOST_FOREACH(const typename CONDITIONAL::shared_ptr& cond, bayesNet) { - this->push_back(cond->toFactor()); - } - } - - /* ************************************************************************* */ - template - template - void FactorGraph::push_back(const std::vector >& factors) { - BOOST_FOREACH(const boost::shared_ptr& factor, factors) - this->push_back(factor); - } - } // namespace gtsam #include diff --git a/gtsam/inference/GenericMultifrontalSolver-inl.h b/gtsam/inference/GenericMultifrontalSolver-inl.h index 652db02ca..39cda6771 100644 --- a/gtsam/inference/GenericMultifrontalSolver-inl.h +++ b/gtsam/inference/GenericMultifrontalSolver-inl.h @@ -21,8 +21,6 @@ #include #include -using namespace std; - namespace gtsam { /* ************************************************************************* */ @@ -36,28 +34,45 @@ namespace gtsam { /* ************************************************************************* */ template GenericMultifrontalSolver::GenericMultifrontalSolver( - const typename FactorGraph::shared_ptr& graph, + const sharedGraph& graph, const VariableIndex::shared_ptr& variableIndex) : structure_(variableIndex), junctionTree_(new JT(*graph, *structure_)) { } + /* ************************************************************************* */ + template + void GenericMultifrontalSolver::print(const std::string& s) const { + this->structure_->print(s + " structure:\n"); + this->junctionTree_->print(s + " jtree:"); + } + + /* ************************************************************************* */ + template + bool GenericMultifrontalSolver::equals( + const GenericMultifrontalSolver& expected, double tol) const { + if (!this->structure_->equals(*expected.structure_, tol)) return false; + if (!this->junctionTree_->equals(*expected.junctionTree_, tol)) return false; + return true; + } + /* ************************************************************************* */ template - void GenericMultifrontalSolver::replaceFactors( - const typename FactorGraph::shared_ptr& graph) { + void GenericMultifrontalSolver::replaceFactors(const sharedGraph& graph) { junctionTree_.reset(new JT(*graph, *structure_)); } /* ************************************************************************* */ - template - typename BayesTree::shared_ptr GenericMultifrontalSolver::eliminate( - typename FactorGraph::Eliminate function) const { + template + typename BayesTree::shared_ptr + GenericMultifrontalSolver::eliminate(Eliminate function) const { // eliminate junction tree, returns pointer to root - typename BayesTree::sharedClique root = junctionTree_->eliminate(function); + typename BayesTree::sharedClique + root = junctionTree_->eliminate(function); // create an empty Bayes tree and insert root clique - typename BayesTree::shared_ptr bayesTree(new BayesTree); + typename BayesTree::shared_ptr + bayesTree(new BayesTree); bayesTree->insert(root); // return the Bayes tree @@ -69,9 +84,10 @@ namespace gtsam { typename FactorGraph::shared_ptr GenericMultifrontalSolver::jointFactorGraph( const std::vector& js, Eliminate function) const { - // We currently have code written only for computing the + // FIXME: joint for arbitrary sets of variables not present + // TODO: develop and implement theory for shortcuts of more than two variables - if (js.size() != 2) throw domain_error( + if (js.size() != 2) throw std::domain_error( "*MultifrontalSolver::joint(js) currently can only compute joint marginals\n" "for exactly two variables. You can call marginal to compute the\n" "marginal for one variable. *SequentialSolver::joint(js) can compute the\n" @@ -82,7 +98,7 @@ namespace gtsam { /* ************************************************************************* */ template - typename F::shared_ptr GenericMultifrontalSolver::marginalFactor( + typename boost::shared_ptr GenericMultifrontalSolver::marginalFactor( Index j, Eliminate function) const { return eliminate(function)->marginalFactor(j, function); } diff --git a/gtsam/inference/GenericMultifrontalSolver.h b/gtsam/inference/GenericMultifrontalSolver.h index 5d6cc74ef..2d50b2ec1 100644 --- a/gtsam/inference/GenericMultifrontalSolver.h +++ b/gtsam/inference/GenericMultifrontalSolver.h @@ -72,7 +72,17 @@ namespace gtsam { GenericMultifrontalSolver(const sharedGraph& factorGraph, const VariableIndex::shared_ptr& variableIndex); - /// @} + /// @} + /// @name Testable + /// @{ + + /** Print to cout */ + void print(const std::string& name = "GenericMultifrontalSolver: ") const; + + /** Test whether is equal to another */ + bool equals(const GenericMultifrontalSolver& other, double tol = 1e-9) const; + + /// @} /// @name Standard Interface /// @{ @@ -102,7 +112,7 @@ namespace gtsam { * Compute the marginal density over a variable, by integrating out * all of the other variables. This function returns the result as a factor. */ - typename FACTOR::shared_ptr marginalFactor(Index j, + typename boost::shared_ptr marginalFactor(Index j, Eliminate function) const; /// @} diff --git a/gtsam/inference/GenericSequentialSolver-inl.h b/gtsam/inference/GenericSequentialSolver-inl.h index b2629566b..368aae831 100644 --- a/gtsam/inference/GenericSequentialSolver-inl.h +++ b/gtsam/inference/GenericSequentialSolver-inl.h @@ -41,7 +41,7 @@ namespace gtsam { template GenericSequentialSolver::GenericSequentialSolver( const sharedFactorGraph& factorGraph, - const VariableIndex::shared_ptr& variableIndex) : + const boost::shared_ptr& variableIndex) : factors_(factorGraph), structure_(variableIndex), eliminationTree_(EliminationTree::Create(*factors_, *structure_)) { } @@ -88,43 +88,43 @@ namespace gtsam { GenericSequentialSolver::jointFactorGraph( const std::vector& js, Eliminate function) const { - // Compute a COLAMD permutation with the marginal variable constrained to the end. + // Compute a COLAMD permutation with the marginal variables constrained to the end. Permutation::shared_ptr permutation(inference::PermutationCOLAMD(*structure_, js)); Permutation::shared_ptr permutationInverse(permutation->inverse()); // Permute the factors - NOTE that this permutes the original factors, not // copies. Other parts of the code may hold shared_ptr's to these factors so // we must undo the permutation before returning. - BOOST_FOREACH(const typename FACTOR::shared_ptr& factor, *factors_) - if (factor) factor->permuteWithInverse(*permutationInverse); + BOOST_FOREACH(const typename boost::shared_ptr& factor, *factors_) + if (factor) factor->permuteWithInverse(*permutationInverse); // Eliminate all variables typename BayesNet::shared_ptr bayesNet(EliminationTree::Create(*factors_)->eliminate(function)); // Undo the permuation on the original factors and on the structure. - BOOST_FOREACH(const typename FACTOR::shared_ptr& factor, *factors_) - if (factor) factor->permuteWithInverse(*permutation); + BOOST_FOREACH(const typename boost::shared_ptr& factor, *factors_) + if (factor) factor->permuteWithInverse(*permutation); // Take the joint marginal from the Bayes net. sharedFactorGraph joint(new FactorGraph ); joint->reserve(js.size()); typename BayesNet::const_reverse_iterator - conditional = bayesNet->rbegin(); + conditional = bayesNet->rbegin(); for (size_t i = 0; i < js.size(); ++i) joint->push_back((*(conditional++))->toFactor()); // Undo the permutation on the eliminated joint marginal factors - BOOST_FOREACH(const typename FACTOR::shared_ptr& factor, *joint) - factor->permuteWithInverse(*permutation); + BOOST_FOREACH(const typename boost::shared_ptr& factor, *joint) + factor->permuteWithInverse(*permutation); return joint; } /* ************************************************************************* */ template - typename FACTOR::shared_ptr // + typename boost::shared_ptr // GenericSequentialSolver::marginalFactor(Index j, Eliminate function) const { // Create a container for the one variable index std::vector js(1); diff --git a/gtsam/inference/GenericSequentialSolver.h b/gtsam/inference/GenericSequentialSolver.h index 5486b3280..5b4d4b41e 100644 --- a/gtsam/inference/GenericSequentialSolver.h +++ b/gtsam/inference/GenericSequentialSolver.h @@ -130,7 +130,7 @@ namespace gtsam { * Compute the marginal Gaussian density over a variable, by integrating out * all of the other variables. This function returns the result as a factor. */ - typename FACTOR::shared_ptr marginalFactor(Index j, Eliminate function) const; + typename boost::shared_ptr marginalFactor(Index j, Eliminate function) const; /// @} diff --git a/gtsam/inference/ISAM-inl.h b/gtsam/inference/ISAM-inl.h index 5d72f396c..c1252f1b0 100644 --- a/gtsam/inference/ISAM-inl.h +++ b/gtsam/inference/ISAM-inl.h @@ -19,7 +19,6 @@ #include #include // for operator += -using namespace boost::assign; #include #include @@ -27,8 +26,6 @@ using namespace boost::assign; namespace gtsam { - using namespace std; - /* ************************************************************************* */ template ISAM::ISAM() : BayesTree() {} diff --git a/gtsam/inference/IndexFactor.cpp b/gtsam/inference/IndexFactor.cpp index f74aa4ff5..b04338d5b 100644 --- a/gtsam/inference/IndexFactor.cpp +++ b/gtsam/inference/IndexFactor.cpp @@ -58,7 +58,7 @@ namespace gtsam { /* ************************************************************************* */ void IndexFactor::permuteWithInverse(const Permutation& inversePermutation) { BOOST_FOREACH(Index& key, keys()) - key = inversePermutation[key]; + key = inversePermutation[key]; assertInvariants(); } /* ************************************************************************* */ diff --git a/gtsam/inference/IndexFactor.h b/gtsam/inference/IndexFactor.h index 9b2d39727..8ab5a880a 100644 --- a/gtsam/inference/IndexFactor.h +++ b/gtsam/inference/IndexFactor.h @@ -98,6 +98,18 @@ namespace gtsam { assertInvariants(); } + /** Construct 5-way factor */ + IndexFactor(Index j1, Index j2, Index j3, Index j4, Index j5) : + Base(j1, j2, j3, j4, j5) { + assertInvariants(); + } + + /** Construct 6-way factor */ + IndexFactor(Index j1, Index j2, Index j3, Index j4, Index j5, Index j6) : + Base(j1, j2, j3, j4, j5, j6) { + assertInvariants(); + } + /// @} /// @name Advanced Constructors /// @{ diff --git a/gtsam/inference/JunctionTree-inl.h b/gtsam/inference/JunctionTree-inl.h index ad8b389ab..1d647ef88 100644 --- a/gtsam/inference/JunctionTree-inl.h +++ b/gtsam/inference/JunctionTree-inl.h @@ -19,19 +19,15 @@ #pragma once -#include #include #include #include +#include #include -#include -#include namespace gtsam { - using namespace std; - /* ************************************************************************* */ template void JunctionTree::construct(const FG& fg, const VariableIndex& variableIndex) { @@ -72,7 +68,7 @@ namespace gtsam { /* ************************************************************************* */ template typename JunctionTree::sharedClique JunctionTree::distributeFactors( - const FG& fg, const typename SymbolicBayesTree::sharedClique& bayesClique) { + const FG& fg, const SymbolicBayesTree::sharedClique& bayesClique) { // Build "target" index. This is an index for each variable of the factors // that involve this variable as their *lowest-ordered* variable. For each @@ -83,7 +79,7 @@ namespace gtsam { // Two stages - first build an array of the lowest-ordered variable in each // factor and find the last variable to be eliminated. - vector lowestOrdered(fg.size(), numeric_limits::max()); + std::vector lowestOrdered(fg.size(), std::numeric_limits::max()); Index maxVar = 0; for(size_t i=0; i > targets(maxVar+1); + std::vector > targets(maxVar+1); for(size_t i=0; i::max()) + if(lowestOrdered[i] != std::numeric_limits::max()) targets[lowestOrdered[i]].push_back(i); // Now call the recursive distributeFactors @@ -145,7 +141,7 @@ namespace gtsam { /* ************************************************************************* */ template - pair::BTClique::shared_ptr, + std::pair::BTClique::shared_ptr, typename FG::sharedFactor> JunctionTree::eliminateOneClique( typename FG::Eliminate function, const boost::shared_ptr& current) const { @@ -155,9 +151,9 @@ namespace gtsam { fg.push_back(*current); // add the local factors // receive the factors from the child and its clique point - list children; + std::list children; BOOST_FOREACH(const boost::shared_ptr& child, current->children()) { - pair tree_factor( + std::pair tree_factor( eliminateOneClique(function, child)); children.push_back(tree_factor.first); fg.push_back(tree_factor.second); @@ -185,7 +181,7 @@ namespace gtsam { } toc(3, "Update tree"); - return make_pair(new_clique, eliminated.second); + return std::make_pair(new_clique, eliminated.second); } /* ************************************************************************* */ @@ -194,9 +190,9 @@ namespace gtsam { typename FG::Eliminate function) const { if (this->root()) { tic(2, "JT eliminate"); - pair ret = + std::pair ret = this->eliminateOneClique(function, this->root()); - if (ret.second->size() != 0) throw runtime_error( + if (ret.second->size() != 0) throw std::runtime_error( "JuntionTree::eliminate: elimination failed because of factors left over!"); toc(2, "JT eliminate"); return ret.first; diff --git a/gtsam/inference/JunctionTree.h b/gtsam/inference/JunctionTree.h index 33a9aa5e4..4ff55d19b 100644 --- a/gtsam/inference/JunctionTree.h +++ b/gtsam/inference/JunctionTree.h @@ -47,7 +47,7 @@ namespace gtsam { * except that in the JunctionTree, at each node multiple variables are eliminated at a time. * * - * \ingroup Multifrontal + * \addtogroup Multifrontal * \nosubgrouping */ template::Clique> @@ -108,7 +108,7 @@ namespace gtsam { JunctionTree(const FG& factorGraph); /** Construct from a factor graph and pre-computed variable index. - * @param factorGraph The factor graph for which to build the junction tree + * @param fg The factor graph for which to build the junction tree * @param structure The set of factors involving each variable. If this is not * precomputed, you can call the JunctionTree(const FG&) * constructor instead. diff --git a/gtsam/inference/Permutation.h b/gtsam/inference/Permutation.h index dc3aa669a..4e32b1f52 100644 --- a/gtsam/inference/Permutation.h +++ b/gtsam/inference/Permutation.h @@ -26,7 +26,7 @@ namespace gtsam { -/** + /** * A permutation reorders variables, for example to reduce fill-in during * elimination. To save computation, the permutation can be applied to * the necessary data structures only once, then multiple computations @@ -36,10 +36,9 @@ namespace gtsam { * that linearized factor graphs are already correctly ordered and need * not be permuted. * - * For convenience, there is also a helper class "Permuted" that transforms - * arguments supplied through the square-bracket [] operator through the - * permutation. Note that this helper class stores a reference to the original - * container. + * Permutations can be considered to a 1-1 mapping from an original set of indices + * to a different set of indices. Permutations can be composed and inverted + * in order to create new indexing for a structure. * \nosubgrouping */ class Permutation { @@ -82,11 +81,25 @@ public: /// @{ /** - * Permute the given variable, i.e. determine it's new index after the - * permutation. + * Return the new index of the supplied variable after the permutation */ Index operator[](Index variable) const { check(variable); return rangeIndices_[variable]; } + /** + * Return the new index of the supplied variable after the permutation. This version allows modification. + */ + Index& operator[](Index variable) { check(variable); return rangeIndices_[variable]; } + + /** + * Return the new index of the supplied variable after the permutation. Synonym for operator[](Index). + */ + Index at(Index variable) const { return operator[](variable); } + + /** + * Return the new index of the supplied variable after the permutation. This version allows modification. Synonym for operator[](Index). + */ + Index& at(Index variable) { return operator[](variable); } + /** * The number of variables in the range of this permutation, i.e. the output * space. @@ -115,8 +128,8 @@ public: static Permutation PullToFront(const std::vector& toFront, size_t size, bool filterDuplicates = false); /** - * Create a permutation that pulls the given variables to the front while - * pushing the rest to the back. + * Create a permutation that pushes the given variables to the back while + * pulling the rest to the front. */ static Permutation PushToBack(const std::vector& toBack, size_t size, bool filterDuplicates = false); @@ -133,18 +146,25 @@ public: */ Permutation::shared_ptr inverse() const; - const_iterator begin() const { return rangeIndices_.begin(); } /// + void applyToCollection(OUTPUT_COLLECTION& output, const INPUT_COLLECTION& input) const { + for(size_t i = 0; i < output.size(); ++i) output[i] = input[(*this)[i]]; } /// @} /// @name Advanced Interface /// @{ - /** - * TODO: comment - */ - Index& operator[](Index variable) { check(variable); return rangeIndices_[variable]; } /** * A partial permutation, reorders the variables selected by selector through @@ -153,8 +173,8 @@ public: */ Permutation::shared_ptr partialPermutation(const Permutation& selector, const Permutation& partialPermutation) const; - iterator begin() { return rangeIndices_.begin(); } /// permuted(permutation, container); - * permuted[index1]; - * permuted[index2]; - * which is equivalent to: - * container[permutation[index1]]; - * container[permutation[index2]]; - * but more concise. - */ -template -class Permuted { - Permutation permutation_; - CONTAINER& container_; -public: - typedef typename CONTAINER::iterator::value_type value_type; - - /** Construct as a permuted view on the Container. The permutation is copied - * but only a reference to the container is stored. - */ - Permuted(const Permutation& permutation, CONTAINER& container) : permutation_(permutation), container_(container) {} - - /** Construct as a view on the Container with an identity permutation. Only - * a reference to the container is stored. - */ - Permuted(CONTAINER& container) : permutation_(Permutation::Identity(container.size())), container_(container) {} - - /** Print */ - void print(const std::string& str = "") const { - std::cout << str; - permutation_.print(" permutation: "); - container_.print(" container: "); - } - - /** Access the container through the permutation */ - value_type& operator[](size_t index) { return container_[permutation_[index]]; } - - /** Access the container through the permutation (const version) */ - const value_type& operator[](size_t index) const { return container_[permutation_[index]]; } - - /** Assignment operator for cloning in ISAM2 */ - Permuted operator=(const Permuted& other) { - permutation_ = other.permutation_; - container_ = other.container_; - return *this; - } - - /** Permute this view by applying a permutation to the underlying permutation */ - void permute(const Permutation& permutation) { assert(permutation.size() == this->size()); permutation_ = *permutation_.permute(permutation); } - - /** Access the underlying container */ - CONTAINER* operator->() { return &container_; } - - /** Access the underlying container (const version) */ - const CONTAINER* operator->() const { return &container_; } - - /** Size of the underlying container */ - size_t size() const { return container_.size(); } - - /** Access to the underlying container */ - CONTAINER& container() { return container_; } - - /** Access to the underlying container (const version) */ - const CONTAINER& container() const { return container_; } - - /** Access the underlying permutation */ - Permutation& permutation() { return permutation_; } - const Permutation& permutation() const { return permutation_; } -}; - - } diff --git a/gtsam/inference/SymbolicFactorGraph.cpp b/gtsam/inference/SymbolicFactorGraph.cpp index 2d5190f45..ff7a91ca6 100644 --- a/gtsam/inference/SymbolicFactorGraph.cpp +++ b/gtsam/inference/SymbolicFactorGraph.cpp @@ -15,43 +15,43 @@ * @author Frank Dellaert */ -#include - #include #include #include #include +#include + namespace gtsam { using namespace std; /* ************************************************************************* */ - SymbolicFactorGraph::SymbolicFactorGraph(const BayesNet& bayesNet) : + SymbolicFactorGraph::SymbolicFactorGraph(const SymbolicBayesNet& bayesNet) : FactorGraph(bayesNet) {} - /* ************************************************************************* */ + /* ************************************************************************* */ + SymbolicFactorGraph::SymbolicFactorGraph(const SymbolicBayesTree& bayesTree) : + FactorGraph(bayesTree) {} + + /* ************************************************************************* */ void SymbolicFactorGraph::push_factor(Index key) { - boost::shared_ptr factor(new IndexFactor(key)); - push_back(factor); + push_back(boost::make_shared(key)); } /** Push back binary factor */ void SymbolicFactorGraph::push_factor(Index key1, Index key2) { - boost::shared_ptr factor(new IndexFactor(key1,key2)); - push_back(factor); + push_back(boost::make_shared(key1,key2)); } /** Push back ternary factor */ void SymbolicFactorGraph::push_factor(Index key1, Index key2, Index key3) { - boost::shared_ptr factor(new IndexFactor(key1,key2,key3)); - push_back(factor); + push_back(boost::make_shared(key1,key2,key3)); } /** Push back 4-way factor */ void SymbolicFactorGraph::push_factor(Index key1, Index key2, Index key3, Index key4) { - boost::shared_ptr factor(new IndexFactor(key1,key2,key3,key4)); - push_back(factor); + push_back(boost::make_shared(key1,key2,key3,key4)); } /* ************************************************************************* */ @@ -63,12 +63,18 @@ namespace gtsam { return keys; } + /* ************************************************************************* */ + std::pair + SymbolicFactorGraph::eliminateFrontals(size_t nFrontals) const + { + return FactorGraph::eliminateFrontals(nFrontals, EliminateSymbolic); + } + /* ************************************************************************* */ IndexFactor::shared_ptr CombineSymbolic( const FactorGraph& factors, const FastMap >& variableSlots) { - IndexFactor::shared_ptr combined(Combine (factors, - variableSlots)); + vector >& variableSlots) { + IndexFactor::shared_ptr combined(Combine (factors, variableSlots)); // combined->assertInvariants(); return combined; } @@ -85,12 +91,9 @@ namespace gtsam { if (keys.size() < 1) throw invalid_argument( "IndexFactor::CombineAndEliminate called on factors with no variables."); - pair result; - std::vector newKeys(keys.begin(),keys.end()); - result.first.reset(new IndexConditional(newKeys, nrFrontals)); - result.second.reset(new IndexFactor(newKeys.begin()+nrFrontals, newKeys.end())); - - return result; + vector newKeys(keys.begin(), keys.end()); + return make_pair(boost::make_shared(newKeys, nrFrontals), + boost::make_shared(newKeys.begin() + nrFrontals, newKeys.end())); } /* ************************************************************************* */ diff --git a/gtsam/inference/SymbolicFactorGraph.h b/gtsam/inference/SymbolicFactorGraph.h index 4da2baf13..1b20ac239 100644 --- a/gtsam/inference/SymbolicFactorGraph.h +++ b/gtsam/inference/SymbolicFactorGraph.h @@ -23,12 +23,14 @@ namespace gtsam { template class EliminationTree; } namespace gtsam { template class BayesNet; } +namespace gtsam { template class BayesTree; } namespace gtsam { class IndexConditional; } namespace gtsam { + typedef EliminationTree SymbolicEliminationTree; typedef BayesNet SymbolicBayesNet; - typedef EliminationTree SymbolicEliminationTree; + typedef BayesTree SymbolicBayesTree; /** Symbolic IndexFactor Graph * \nosubgrouping @@ -45,13 +47,25 @@ namespace gtsam { } /** Construct from a BayesNet */ - SymbolicFactorGraph(const BayesNet& bayesNet); + SymbolicFactorGraph(const SymbolicBayesNet& bayesNet); + + /** Construct from a BayesTree */ + SymbolicFactorGraph(const SymbolicBayesTree& bayesTree); /** * Construct from a factor graph of any type */ template SymbolicFactorGraph(const FactorGraph& fg); + + /** Eliminate the first \c n frontal variables, returning the resulting + * conditional and remaining factor graph - this is very inefficient for + * eliminating all variables, to do that use EliminationTree or + * JunctionTree. Note that this version simply calls + * FactorGraph::eliminateFrontals with EliminateSymbolic + * as the eliminate function argument. + */ + std::pair eliminateFrontals(size_t nFrontals) const; /// @} /// @name Standard Interface @@ -63,6 +77,8 @@ namespace gtsam { */ FastSet keys() const; + + /// @} /// @name Advanced Interface /// @{ @@ -82,9 +98,8 @@ namespace gtsam { }; /** Create a combined joint factor (new style for EliminationTree). */ - IndexFactor::shared_ptr CombineSymbolic( - const FactorGraph& factors, const FastMap >& variableSlots); + IndexFactor::shared_ptr CombineSymbolic(const FactorGraph& factors, + const FastMap >& variableSlots); /** * CombineAndEliminate provides symbolic elimination. diff --git a/gtsam/inference/SymbolicMultifrontalSolver.h b/gtsam/inference/SymbolicMultifrontalSolver.h index 35b253c31..802b10d72 100644 --- a/gtsam/inference/SymbolicMultifrontalSolver.h +++ b/gtsam/inference/SymbolicMultifrontalSolver.h @@ -22,7 +22,50 @@ namespace gtsam { -// The base class provides all of the needed functionality -typedef GenericMultifrontalSolver > > SymbolicMultifrontalSolver; + class SymbolicMultifrontalSolver : GenericMultifrontalSolver > > { + + protected: + typedef GenericMultifrontalSolver > > Base; + + public: + /** + * Construct the solver for a factor graph. This builds the junction + * tree, which does the symbolic elimination, identifies the cliques, + * and distributes all the factors to the right cliques. + */ + SymbolicMultifrontalSolver(const SymbolicFactorGraph& factorGraph) : Base(factorGraph) {}; + + /** + * Construct the solver with a shared pointer to a factor graph and to a + * VariableIndex. The solver will store these pointers, so this constructor + * is the fastest. + */ + SymbolicMultifrontalSolver(const SymbolicFactorGraph::shared_ptr& factorGraph, + const VariableIndex::shared_ptr& variableIndex) : Base(factorGraph, variableIndex) {}; + + /** Print to cout */ + void print(const std::string& name = "SymbolicMultifrontalSolver: ") const { Base::print(name); }; + + /** Test whether is equal to another */ + bool equals(const SymbolicMultifrontalSolver& other, double tol = 1e-9) const { return Base::equals(other, tol); }; + + /** + * Eliminate the factor graph sequentially. Uses a column elimination tree + * to recursively eliminate. + */ + SymbolicBayesTree::shared_ptr eliminate() const { return Base::eliminate(&EliminateSymbolic); }; + + /** + * Compute the marginal joint over a set of variables, by integrating out + * all of the other variables. Returns the result as a factor graph. + */ + SymbolicFactorGraph::shared_ptr jointFactorGraph(const std::vector& js) const { return Base::jointFactorGraph(js, &EliminateSymbolic); }; + + /** + * Compute the marginal Gaussian density over a variable, by integrating out + * all of the other variables. This function returns the result as a factor. + */ + IndexFactor::shared_ptr marginalFactor(Index j) const { return Base::marginalFactor(j, &EliminateSymbolic); }; + }; } diff --git a/gtsam/inference/SymbolicSequentialSolver.h b/gtsam/inference/SymbolicSequentialSolver.h index d6e21e88e..c114261f0 100644 --- a/gtsam/inference/SymbolicSequentialSolver.h +++ b/gtsam/inference/SymbolicSequentialSolver.h @@ -21,8 +21,51 @@ namespace gtsam { -// The base class provides all of the needed functionality -typedef GenericSequentialSolver SymbolicSequentialSolver; + class SymbolicSequentialSolver : GenericSequentialSolver { + + protected: + typedef GenericSequentialSolver Base; + + public: + /** + * Construct the solver for a factor graph. This builds the junction + * tree, which does the symbolic elimination, identifies the cliques, + * and distributes all the factors to the right cliques. + */ + SymbolicSequentialSolver(const SymbolicFactorGraph& factorGraph) : Base(factorGraph) {}; + + /** + * Construct the solver with a shared pointer to a factor graph and to a + * VariableIndex. The solver will store these pointers, so this constructor + * is the fastest. + */ + SymbolicSequentialSolver(const SymbolicFactorGraph::shared_ptr& factorGraph, + const VariableIndex::shared_ptr& variableIndex) : Base(factorGraph, variableIndex) {}; + + /** Print to cout */ + void print(const std::string& name = "SymbolicSequentialSolver: ") const { Base::print(name); }; + + /** Test whether is equal to another */ + bool equals(const SymbolicSequentialSolver& other, double tol = 1e-9) const { return Base::equals(other, tol); }; + + /** + * Eliminate the factor graph sequentially. Uses a column elimination tree + * to recursively eliminate. + */ + SymbolicBayesNet::shared_ptr eliminate() const { return Base::eliminate(&EliminateSymbolic); }; + + /** + * Compute the marginal joint over a set of variables, by integrating out + * all of the other variables. Returns the result as a factor graph. + */ + SymbolicFactorGraph::shared_ptr jointFactorGraph(const std::vector& js) const { return Base::jointFactorGraph(js, &EliminateSymbolic); }; + + /** + * Compute the marginal Gaussian density over a variable, by integrating out + * all of the other variables. This function returns the result as a factor. + */ + IndexFactor::shared_ptr marginalFactor(Index j) const { return Base::marginalFactor(j, &EliminateSymbolic); }; + }; } diff --git a/gtsam/inference/VariableIndex.cpp b/gtsam/inference/VariableIndex.cpp index c7ef90e9f..b24e2f5fc 100644 --- a/gtsam/inference/VariableIndex.cpp +++ b/gtsam/inference/VariableIndex.cpp @@ -18,37 +18,12 @@ #include #include +#include namespace gtsam { using namespace std; -/* ************************************************************************* */ -VariableIndex::VariableIndex(const VariableIndex& other) : - index_(indexUnpermuted_) { - *this = other; -} - -/* ************************************************************************* */ -VariableIndex& VariableIndex::operator=(const VariableIndex& rhs) { - index_ = rhs.index_; - nFactors_ = rhs.nFactors_; - nEntries_ = rhs.nEntries_; - return *this; -} - -/* ************************************************************************* */ -void VariableIndex::permute(const Permutation& permutation) { -#ifndef NDEBUG - // Assert that the permutation does not leave behind any non-empty variables, - // otherwise the nFactors and nEntries counts would be incorrect. - for(Index j=0; jindex_.size(); ++j) - if(find(permutation.begin(), permutation.end(), j) == permutation.end()) - assert(this->operator[](j).empty()); -#endif - index_.permute(permutation); -} - /* ************************************************************************* */ bool VariableIndex::equals(const VariableIndex& other, double tol) const { if(this->nEntries_ == other.nEntries_ && this->nFactors_ == other.nFactors_) { @@ -66,17 +41,13 @@ bool VariableIndex::equals(const VariableIndex& other, double tol) const { /* ************************************************************************* */ void VariableIndex::print(const string& str) const { - cout << str << "\n"; + cout << str; cout << "nEntries = " << nEntries() << ", nFactors = " << nFactors() << "\n"; - Index var = 0; - BOOST_FOREACH(const Factors& variable, index_.container()) { - Permutation::const_iterator rvar = find(index_.permutation().begin(), index_.permutation().end(), var); - assert(rvar != index_.permutation().end()); - cout << "var " << (rvar-index_.permutation().begin()) << ":"; - BOOST_FOREACH(const size_t factor, variable) + for(Index var = 0; var < size(); ++var) { + cout << "var " << var << ":"; + BOOST_FOREACH(const size_t factor, index_[var]) cout << " " << factor; cout << "\n"; - ++ var; } cout << flush; } @@ -85,7 +56,7 @@ void VariableIndex::print(const string& str) const { void VariableIndex::outputMetisFormat(ostream& os) const { os << size() << " " << nFactors() << "\n"; // run over variables, which will be hyper-edges. - BOOST_FOREACH(const Factors& variable, index_.container()) { + BOOST_FOREACH(const Factors& variable, index_) { // every variable is a hyper-edge covering its factors BOOST_FOREACH(const size_t factor, variable) os << (factor+1) << " "; // base 1 @@ -94,4 +65,26 @@ void VariableIndex::outputMetisFormat(ostream& os) const { os << flush; } +/* ************************************************************************* */ +void VariableIndex::permuteInPlace(const Permutation& permutation) { + // Create new index and move references to data into it in permuted order + deque newIndex(this->size()); + for(Index i = 0; i < newIndex.size(); ++i) + newIndex[i].swap(this->index_[permutation[i]]); + + // Move reference to entire index into the VariableIndex + index_.swap(newIndex); +} + +/* ************************************************************************* */ +void VariableIndex::removeUnusedAtEnd(size_t nToRemove) { +#ifndef NDEBUG + for(size_t i = this->size() - nToRemove; i < this->size(); ++i) + if(!(*this)[i].empty()) + throw std::invalid_argument("Attempting to remove non-empty variables with VariableIndex::removeUnusedAtEnd()"); +#endif + + index_.resize(this->size() - nToRemove); +} + } diff --git a/gtsam/inference/VariableIndex.h b/gtsam/inference/VariableIndex.h index c9efc6b22..d747d1122 100644 --- a/gtsam/inference/VariableIndex.h +++ b/gtsam/inference/VariableIndex.h @@ -18,20 +18,23 @@ #pragma once #include +#include #include #include #include -#include +#include namespace gtsam { + class Permutation; + /** * The VariableIndex class computes and stores the block column structure of a * factor graph. The factor graph stores a collection of factors, each of * which involves a set of variables. In contrast, the VariableIndex is built * from a factor graph prior to elimination, and stores the list of factors - * that involve each variable. This information is stored as a vector of + * that involve each variable. This information is stored as a deque of * lists of factor indices. * \nosubgrouping */ @@ -44,8 +47,7 @@ public: typedef Factors::const_iterator Factor_const_iterator; protected: - std::vector indexUnpermuted_; - Permuted > index_; // Permuted view of indexUnpermuted. + std::deque index_; size_t nFactors_; // Number of factors in the original factor graph. size_t nEntries_; // Sum of involved variable counts of each factor. @@ -55,7 +57,7 @@ public: /// @{ /** Default constructor, creates an empty VariableIndex */ - VariableIndex() : index_(indexUnpermuted_), nFactors_(0), nEntries_(0) {} + VariableIndex() : nFactors_(0), nEntries_(0) {} /** * Create a VariableIndex that computes and stores the block column structure @@ -70,16 +72,6 @@ public: */ template VariableIndex(const FactorGraph& factorGraph); - /** - * Copy constructor - */ - VariableIndex(const VariableIndex& other); - - /** - * Assignment operator - */ - VariableIndex& operator=(const VariableIndex& rhs); - /// @} /// @name Standard Interface /// @{ @@ -120,9 +112,6 @@ public: /// @name Advanced Interface /// @{ - /** Access a list of factors by variable */ - Factors& operator[](Index variable) { checkVar(variable); return index_[variable]; } - /** * Augment the variable index with new factors. This can be used when * solving problems incrementally. @@ -131,17 +120,25 @@ public: /** * Remove entries corresponding to the specified factors. + * NOTE: We intentionally do not decrement nFactors_ because the factor + * indices need to remain consistent. Removing factors from a factor graph + * does not shift the indices of other factors. Also, we keep nFactors_ + * one greater than the highest-numbered factor referenced in a VariableIndex. + * * @param indices The indices of the factors to remove, which must match \c factors * @param factors The factors being removed, which must symbolically correspond * exactly to the factors with the specified \c indices that were added. */ template void remove(const CONTAINER& indices, const FactorGraph& factors); - /** - * Apply a variable permutation. Does not rearrange data, just permutes - * future lookups by variable. - */ - void permute(const Permutation& permutation); + /// Permute the variables in the VariableIndex according to the given permutation + void permuteInPlace(const Permutation& permutation); + + /** Remove unused empty variables at the end of the ordering (in debug mode + * verifies they are empty). + * @param nToRemove The number of unused variables at the end to remove + */ + void removeUnusedAtEnd(size_t nToRemove); protected: Factor_iterator factorsBegin(Index variable) { checkVar(variable); return index_[variable].begin(); } /// void fill(const FactorGraph& factorGraph); /// @} @@ -183,7 +180,7 @@ void VariableIndex::fill(const FactorGraph& factorGraph) { /* ************************************************************************* */ template VariableIndex::VariableIndex(const FactorGraph& factorGraph) : - index_(indexUnpermuted_), nFactors_(0), nEntries_(0) { + nFactors_(0), nEntries_(0) { // If the factor graph is empty, return an empty index because inside this // if block we assume at least one factor. @@ -200,8 +197,7 @@ VariableIndex::VariableIndex(const FactorGraph& factorGraph) : } // Allocate array - index_.container().resize(maxVar+1); - index_.permutation() = Permutation::Identity(maxVar+1); + index_.resize(maxVar+1); fill(factorGraph); } @@ -210,7 +206,7 @@ VariableIndex::VariableIndex(const FactorGraph& factorGraph) : /* ************************************************************************* */ template VariableIndex::VariableIndex(const FactorGraph& factorGraph, Index nVariables) : - indexUnpermuted_(nVariables), index_(indexUnpermuted_), nFactors_(0), nEntries_(0) { + index_(nVariables), nFactors_(0), nEntries_(0) { fill(factorGraph); } @@ -232,11 +228,7 @@ void VariableIndex::augment(const FactorGraph& factors) { } // Allocate index - Index originalSize = index_.size(); - index_.container().resize(std::max(index_.size(), maxVar+1)); - index_.permutation().resize(index_.container().size()); - for(Index var=originalSize; var void VariableIndex::remove(const CONTAINER& indices, const FactorGraph& factors) { + // NOTE: We intentionally do not decrement nFactors_ because the factor + // indices need to remain consistent. Removing factors from a factor graph + // does not shift the indices of other factors. Also, we keep nFactors_ + // one greater than the highest-numbered factor referenced in a VariableIndex. for(size_t fi=0; fikeys().size(); ++ji) { diff --git a/gtsam/inference/VariableSlots.h b/gtsam/inference/VariableSlots.h index 551993db4..2533a7411 100644 --- a/gtsam/inference/VariableSlots.h +++ b/gtsam/inference/VariableSlots.h @@ -48,10 +48,6 @@ namespace gtsam { * variable index 3), row-block 2 (also meaning component factor 2), comes from * column-block 0 of component factor 2. * - * Note that in the case of GaussianFactor, the rows of the combined factor are - * further sorted so that the column-block position of the first structural - * non-zero increases monotonically through the rows. This additional process - * is not performed by this class. * \nosubgrouping */ diff --git a/gtsam/inference/graph-inl.h b/gtsam/inference/graph-inl.h index d8395942a..ff65147cc 100644 --- a/gtsam/inference/graph-inl.h +++ b/gtsam/inference/graph-inl.h @@ -10,9 +10,9 @@ * -------------------------------------------------------------------------- */ /* - * graph-inl.h + * @file graph-inl.h * @brief Graph algorithm using boost library - * @author: Kai Ni + * @author Kai Ni */ #pragma once @@ -24,8 +24,6 @@ #include -using namespace std; - #define FOREACH_PAIR( KEY, VAL, COL) BOOST_FOREACH (boost::tie(KEY,VAL),COL) namespace gtsam { @@ -44,7 +42,7 @@ public: /* ************************************************************************* */ template -list predecessorMap2Keys(const PredecessorMap& p_map) { +std::list predecessorMap2Keys(const PredecessorMap& p_map) { typedef typename SGraph::Vertex SVertex; @@ -66,13 +64,13 @@ SDGraph toBoostGraph(const G& graph) { // convert the factor graph to boost graph SDGraph g; typedef typename boost::graph_traits >::vertex_descriptor BoostVertex; - map key2vertex; + std::map key2vertex; BoostVertex v1, v2; typename G::const_iterator itFactor; for(itFactor=graph.begin(); itFactor!=graph.end(); itFactor++) { if ((*itFactor)->keys().size() > 2) - throw(invalid_argument("toBoostGraph: only support factors with at most two keys")); + throw(std::invalid_argument("toBoostGraph: only support factors with at most two keys")); if ((*itFactor)->keys().size() == 1) continue; @@ -104,24 +102,24 @@ SDGraph toBoostGraph(const G& graph) { /* ************************************************************************* */ template -boost::tuple > +boost::tuple > predecessorMap2Graph(const PredecessorMap& p_map) { G g; - map key2vertex; + std::map key2vertex; V v1, v2, root; KEY child, parent; bool foundRoot = false; FOREACH_PAIR(child, parent, p_map) { if (key2vertex.find(child) == key2vertex.end()) { v1 = add_vertex(child, g); - key2vertex.insert(make_pair(child, v1)); + key2vertex.insert(std::make_pair(child, v1)); } else v1 = key2vertex[child]; if (key2vertex.find(parent) == key2vertex.end()) { v2 = add_vertex(parent, g); - key2vertex.insert(make_pair(parent, v2)); + key2vertex.insert(std::make_pair(parent, v2)); } else v2 = key2vertex[parent]; @@ -133,7 +131,7 @@ predecessorMap2Graph(const PredecessorMap& p_map) { } if (!foundRoot) - throw invalid_argument("predecessorMap2Graph: invalid predecessor map!"); + throw std::invalid_argument("predecessorMap2Graph: invalid predecessor map!"); else return boost::tuple >(g, root, key2vertex); } @@ -173,7 +171,7 @@ boost::shared_ptr composePoses(const G& graph, const PredecessorMap PoseGraph g; PoseVertex root; - map key2vertex; + std::map key2vertex; boost::tie(g, root, key2vertex) = predecessorMap2Graph(tree); @@ -183,7 +181,7 @@ boost::shared_ptr composePoses(const G& graph, const PredecessorMap BOOST_FOREACH(typename G::sharedFactor nl_factor, graph) { if (nl_factor->keys().size() > 2) - throw invalid_argument("composePoses: only support factors with at most two keys"); + throw std::invalid_argument("composePoses: only support factors with at most two keys"); // e.g. in pose2graph, nonlinear factor needs to be converted to pose2factor boost::shared_ptr factor = boost::dynamic_pointer_cast(nl_factor); @@ -196,9 +194,9 @@ boost::shared_ptr composePoses(const G& graph, const PredecessorMap PoseVertex v2 = key2vertex.find(key2)->second; POSE l1Xl2 = factor->measured(); - tie(edge12, found1) = boost::edge(v1, v2, g); - tie(edge21, found2) = boost::edge(v2, v1, g); - if (found1 && found2) throw invalid_argument ("composePoses: invalid spanning tree"); + boost::tie(edge12, found1) = boost::edge(v1, v2, g); + boost::tie(edge21, found2) = boost::edge(v2, v1, g); + if (found1 && found2) throw std::invalid_argument ("composePoses: invalid spanning tree"); if (!found1 && !found2) continue; if (found1) boost::put(boost::edge_weight, g, edge12, l1Xl2); @@ -225,13 +223,13 @@ PredecessorMap findMinimumSpanningTree(const G& fg) { SDGraph g = gtsam::toBoostGraph(fg); // find minimum spanning tree - vector::Vertex> p_map(boost::num_vertices(g)); + std::vector::Vertex> p_map(boost::num_vertices(g)); prim_minimum_spanning_tree(g, &p_map[0]); // convert edge to string pairs PredecessorMap tree; typename SDGraph::vertex_iterator itVertex = boost::vertices(g).first; - typename vector::Vertex>::iterator vi; + typename std::vector::Vertex>::iterator vi; for (vi = p_map.begin(); vi != p_map.end(); itVertex++, vi++) { KEY key = boost::get(boost::vertex_name, g, *itVertex); KEY parent = boost::get(boost::vertex_name, g, *vi); @@ -250,7 +248,7 @@ void split(const G& g, const PredecessorMap& tree, G& Ab1, G& Ab2) { BOOST_FOREACH(const F& factor, g) { if (factor->keys().size() > 2) - throw(invalid_argument("split: only support factors with at most two keys")); + throw(std::invalid_argument("split: only support factors with at most two keys")); if (factor->keys().size() == 1) { Ab1.push_back(factor); diff --git a/gtsam/inference/graph.h b/gtsam/inference/graph.h index 98d41940b..88ab5d0e8 100644 --- a/gtsam/inference/graph.h +++ b/gtsam/inference/graph.h @@ -108,3 +108,5 @@ namespace gtsam { } // namespace gtsam + +#include diff --git a/gtsam/inference/inference-inl.h b/gtsam/inference/inference-inl.h index 02e78e8e9..c17f947d1 100644 --- a/gtsam/inference/inference-inl.h +++ b/gtsam/inference/inference-inl.h @@ -31,7 +31,8 @@ namespace inference { /* ************************************************************************* */ template -Permutation::shared_ptr PermutationCOLAMD(const VariableIndex& variableIndex, const CONSTRAINED& constrainLast) { +Permutation::shared_ptr PermutationCOLAMD( + const VariableIndex& variableIndex, const CONSTRAINED& constrainLast) { std::vector cmember(variableIndex.size(), 0); @@ -47,6 +48,22 @@ Permutation::shared_ptr PermutationCOLAMD(const VariableIndex& variableIndex, co return PermutationCOLAMD_(variableIndex, cmember); } +/* ************************************************************************* */ +template +Permutation::shared_ptr PermutationCOLAMDGrouped( + const VariableIndex& variableIndex, const CONSTRAINED_MAP& constraints) { + std::vector cmember(variableIndex.size(), 0); + + typedef typename CONSTRAINED_MAP::value_type constraint_pair; + BOOST_FOREACH(const constraint_pair& p, constraints) { + assert(p.first < variableIndex.size()); + // FIXME: check that no groups are skipped + cmember[p.first] = p.second; + } + + return PermutationCOLAMD_(variableIndex, cmember); +} + /* ************************************************************************* */ inline Permutation::shared_ptr PermutationCOLAMD(const VariableIndex& variableIndex) { std::vector cmember(variableIndex.size(), 0); @@ -55,10 +72,14 @@ inline Permutation::shared_ptr PermutationCOLAMD(const VariableIndex& variableIn /* ************************************************************************* */ template -typename Graph::FactorizationResult eliminate(const Graph& factorGraph, const std::vector& variables, - const typename Graph::Eliminate& eliminateFcn, boost::optional variableIndex_) { +std::pair eliminate( + const Graph& factorGraph, + const std::vector& variables, + const typename Graph::Eliminate& eliminateFcn, + boost::optional variableIndex_) { - const VariableIndex& variableIndex = variableIndex_ ? *variableIndex_ : VariableIndex(factorGraph); + const VariableIndex& variableIndex = + variableIndex_ ? *variableIndex_ : VariableIndex(factorGraph); // First find the involved factors Graph involvedFactors; @@ -108,13 +129,11 @@ typename Graph::FactorizationResult eliminate(const Graph& factorGraph, const st if(remainingFactor->size() != 0) remainingGraph.push_back(remainingFactor); - return typename Graph::FactorizationResult(conditional, remainingGraph); + return std::make_pair(conditional, remainingGraph); -} - - -} - -} +} // eliminate + +} // namespace inference +} // namespace gtsam diff --git a/gtsam/inference/inference.cpp b/gtsam/inference/inference.cpp index 9b7252030..3cddc4cfc 100644 --- a/gtsam/inference/inference.cpp +++ b/gtsam/inference/inference.cpp @@ -10,9 +10,10 @@ * -------------------------------------------------------------------------- */ /** - * @file inference-inl.h + * @file inference.cpp * @brief inference definitions - * @author Frank Dellaert, Richard Roberts + * @author Frank Dellaert + * @author Richard Roberts */ #include @@ -28,9 +29,9 @@ using namespace std; namespace gtsam { - namespace inference { +/* ************************************************************************* */ Permutation::shared_ptr PermutationCOLAMD_(const VariableIndex& variableIndex, std::vector& cmember) { size_t nEntries = variableIndex.nEntries(), nFactors = variableIndex.nFactors(), nVars = variableIndex.size(); // Convert to compressed column major format colamd wants it in (== MATLAB format!) @@ -92,6 +93,6 @@ Permutation::shared_ptr PermutationCOLAMD_(const VariableIndex& variableIndex, s return permutation; } -} - -} +/* ************************************************************************* */ +} // \namespace inference +} // \namespace gtsam diff --git a/gtsam/inference/inference.h b/gtsam/inference/inference.h index d87720b5a..7ba268789 100644 --- a/gtsam/inference/inference.h +++ b/gtsam/inference/inference.h @@ -13,7 +13,8 @@ * @file inference.h * @brief Contains *generic* inference algorithms that convert between templated * graphical models, i.e., factor graphs, Bayes nets, and Bayes trees - * @author Frank Dellaert, Richard Roberts + * @author Frank Dellaert + * @author Richard Roberts */ #pragma once @@ -28,53 +29,85 @@ namespace gtsam { -namespace inference { + namespace inference { -/** - * Compute a permutation (variable ordering) using colamd - */ -Permutation::shared_ptr PermutationCOLAMD(const VariableIndex& variableIndex); + /** + * Compute a permutation (variable ordering) using colamd + */ + Permutation::shared_ptr PermutationCOLAMD( + const VariableIndex& variableIndex); -/** - * Compute a permutation (variable ordering) using constrained colamd - */ -template -Permutation::shared_ptr PermutationCOLAMD(const VariableIndex& variableIndex, const CONSTRAINED& constrainLast); + /** + * Compute a permutation (variable ordering) using constrained colamd to move + * a set of variables to the end of the ordering + * @param variableIndex is the variable index lookup from a graph + * @param constrainlast is a vector of keys that should be constrained + * @tparam constrainLast is a std::vector (or similar structure) + */ + template + Permutation::shared_ptr PermutationCOLAMD( + const VariableIndex& variableIndex, const CONSTRAINED& constrainLast); -/** - * Compute a CCOLAMD permutation using the constraint groups in cmember. - */ -Permutation::shared_ptr PermutationCOLAMD_(const VariableIndex& variableIndex, std::vector& cmember); + /** + * Compute a permutation of variable ordering using constrained colamd to + * move variables to the end in groups (0 = unconstrained, higher numbers at + * the end). + * @param variableIndex is the variable index lookup from a graph + * @param constraintMap is a map from variable index -> group number for constrained variables + * @tparam CONSTRAINED_MAP is an associative structure (like std::map), from size_t->int + */ + template + Permutation::shared_ptr PermutationCOLAMDGrouped( + const VariableIndex& variableIndex, const CONSTRAINED_MAP& constraints); -/** Factor the factor graph into a conditional and a remaining factor graph. - * Given the factor graph \f$ f(X) \f$, and \c variables to factorize out - * \f$ V \f$, this function factorizes into \f$ f(X) = f(V;Y)f(Y) \f$, where - * \f$ Y := X\V \f$ are the remaining variables. If \f$ f(X) = p(X) \f$ is - * a probability density or likelihood, the factorization produces a - * conditional probability density and a marginal \f$ p(X) = p(V|Y)p(Y) \f$. - * - * For efficiency, this function treats the variables to eliminate - * \c variables as fully-connected, so produces a dense (fully-connected) - * conditional on all of the variables in \c variables, instead of a sparse - * BayesNet. If the variables are not fully-connected, it is more efficient - * to sequentially factorize multiple times. - */ -template -typename Graph::FactorizationResult eliminate(const Graph& factorGraph, const std::vector& variables, - const typename Graph::Eliminate& eliminateFcn, boost::optional variableIndex = boost::none); + /** + * Compute a CCOLAMD permutation using the constraint groups in cmember. + * The format for cmember is a part of ccolamd. + * + * @param variableIndex is the variable structure from a graph + * @param cmember is the constraint group list for each variable, where + * 0 is the default, unconstrained group, and higher numbers move further to + * the back of the list + * + * AGC: does cmember change? + */ + Permutation::shared_ptr PermutationCOLAMD_( + const VariableIndex& variableIndex, std::vector& cmember); -/** Eliminate a single variable, by calling - * eliminate(const Graph&, const std::vector&, const typename Graph::Eliminate&, boost::optional) - */ -template -typename Graph::FactorizationResult eliminateOne(const Graph& factorGraph, typename Graph::KeyType variable, - const typename Graph::Eliminate& eliminateFcn, boost::optional variableIndex = boost::none) { - std::vector variables(1, variable); - return eliminate(factorGraph, variables, eliminateFcn, variableIndex); -} + /** Factor the factor graph into a conditional and a remaining factor graph. + * Given the factor graph \f$ f(X) \f$, and \c variables to factorize out + * \f$ V \f$, this function factorizes into \f$ f(X) = f(V;Y)f(Y) \f$, where + * \f$ Y := X\V \f$ are the remaining variables. If \f$ f(X) = p(X) \f$ is + * a probability density or likelihood, the factorization produces a + * conditional probability density and a marginal \f$ p(X) = p(V|Y)p(Y) \f$. + * + * For efficiency, this function treats the variables to eliminate + * \c variables as fully-connected, so produces a dense (fully-connected) + * conditional on all of the variables in \c variables, instead of a sparse + * BayesNet. If the variables are not fully-connected, it is more efficient + * to sequentially factorize multiple times. + */ + template + std::pair eliminate( + const Graph& factorGraph, + const std::vector& variables, + const typename Graph::Eliminate& eliminateFcn, + boost::optional variableIndex = boost::none); -} + /** Eliminate a single variable, by calling + * eliminate(const Graph&, const std::vector&, const typename Graph::Eliminate&, boost::optional) + */ + template + std::pair eliminateOne( + const Graph& factorGraph, typename Graph::KeyType variable, + const typename Graph::Eliminate& eliminateFcn, + boost::optional variableIndex = boost::none) { + std::vector variables(1, variable); + return eliminate(factorGraph, variables, eliminateFcn, variableIndex); + } -} // namespace gtsam + } // \namespace inference + +} // \namespace gtsam #include diff --git a/gtsam/inference/tests/testBayesTree.cpp b/gtsam/inference/tests/testBayesTree.cpp index 71021ef70..b99364092 100644 --- a/gtsam/inference/tests/testBayesTree.cpp +++ b/gtsam/inference/tests/testBayesTree.cpp @@ -30,10 +30,9 @@ using namespace boost::assign; #include #include +using namespace std; using namespace gtsam; -typedef BayesTree SymbolicBayesTree; - ///* ************************************************************************* */ //// SLAM example from RSS sqrtSAM paper static const Index _x3_=0, _x2_=1; @@ -61,7 +60,7 @@ static const Index _x3_=0, _x2_=1; /* ************************************************************************* */ // Conditionals for ASIA example from the tutorial with A and D evidence static const Index _X_=0, _T_=1, _S_=2, _E_=3, _L_=4, _B_=5; -IndexConditional::shared_ptr +static IndexConditional::shared_ptr B(new IndexConditional(_B_)), L(new IndexConditional(_L_, _B_)), E(new IndexConditional(_E_, _L_, _B_)), @@ -70,11 +69,11 @@ IndexConditional::shared_ptr X(new IndexConditional(_X_, _E_)); // Cliques -IndexConditional::shared_ptr +static IndexConditional::shared_ptr ELB(IndexConditional::FromKeys(cref_list_of<3>(_E_)(_L_)(_B_), 3)); // Bayes Tree for Asia example -SymbolicBayesTree createAsiaSymbolicBayesTree() { +static SymbolicBayesTree createAsiaSymbolicBayesTree() { SymbolicBayesTree bayesTree; // Ordering asiaOrdering; asiaOrdering += _X_, _T_, _S_, _E_, _L_, _B_; SymbolicBayesTree::insert(bayesTree, B); @@ -239,6 +238,76 @@ TEST( BayesTree, removePath3 ) CHECK(assert_equal(expectedOrphans, orphans)); } +void getAllCliques(const SymbolicBayesTree::sharedClique& subtree, SymbolicBayesTree::Cliques& cliques) { + // Check if subtree exists + if (subtree) { + cliques.push_back(subtree); + // Recursive call over all child cliques + BOOST_FOREACH(SymbolicBayesTree::sharedClique& childClique, subtree->children()) { + getAllCliques(childClique,cliques); + } + } +} + +/* ************************************************************************* */ +TEST( BayesTree, shortcutCheck ) +{ + const Index _A_=6, _B_=5, _C_=4, _D_=3, _E_=2, _F_=1, _G_=0; + IndexConditional::shared_ptr + A(new IndexConditional(_A_)), + B(new IndexConditional(_B_, _A_)), + C(new IndexConditional(_C_, _A_)), + D(new IndexConditional(_D_, _C_)), + E(new IndexConditional(_E_, _B_)), + F(new IndexConditional(_F_, _E_)), + G(new IndexConditional(_G_, _F_)); + SymbolicBayesTree bayesTree; +// Ordering ord; ord += _A_,_B_,_C_,_D_,_E_,_F_; + SymbolicBayesTree::insert(bayesTree, A); + SymbolicBayesTree::insert(bayesTree, B); + SymbolicBayesTree::insert(bayesTree, C); + SymbolicBayesTree::insert(bayesTree, D); + SymbolicBayesTree::insert(bayesTree, E); + SymbolicBayesTree::insert(bayesTree, F); + SymbolicBayesTree::insert(bayesTree, G); + + //bayesTree.print("BayesTree"); + //bayesTree.saveGraph("BT1.dot"); + + SymbolicBayesTree::sharedClique rootClique= bayesTree.root(); + //rootClique->printTree(); + SymbolicBayesTree::Cliques allCliques; + getAllCliques(rootClique,allCliques); + + BayesNet bn; + BOOST_FOREACH(SymbolicBayesTree::sharedClique& clique, allCliques) { + //clique->print("Clique#"); + bn = clique->shortcut(rootClique, &EliminateSymbolic); + //bn.print("Shortcut:\n"); + //cout << endl; + } + + // Check if all the cached shortcuts are cleared + rootClique->deleteCachedShorcuts(); + BOOST_FOREACH(SymbolicBayesTree::sharedClique& clique, allCliques) { + bool notCleared = clique->cachedShortcut(); + CHECK( notCleared == false); + } + +// BOOST_FOREACH(SymbolicBayesTree::sharedClique& clique, allCliques) { +// clique->print("Clique#"); +// if(clique->cachedShortcut()){ +// bn = clique->cachedShortcut().get(); +// bn.print("Shortcut:\n"); +// } +// else +// cout << "Not Initialized" << endl; +// cout << endl; +// } +} + + + /* ************************************************************************* */ TEST( BayesTree, removeTop ) { diff --git a/gtsam/inference/tests/testEliminationTree.cpp b/gtsam/inference/tests/testEliminationTree.cpp index 0ec8b2266..c1df6e98e 100644 --- a/gtsam/inference/tests/testEliminationTree.cpp +++ b/gtsam/inference/tests/testEliminationTree.cpp @@ -101,8 +101,7 @@ TEST(EliminationTree, eliminate ) fg.push_factor(3, 4); // eliminate - SymbolicBayesNet actual = *SymbolicSequentialSolver(fg).eliminate( - &EliminateSymbolic); + SymbolicBayesNet actual = *SymbolicSequentialSolver(fg).eliminate(); CHECK(assert_equal(expected,actual)); } diff --git a/gtsam/inference/tests/testFactorGraph.cpp b/gtsam/inference/tests/testFactorGraph.cpp index 8669329bb..bfbe716d4 100644 --- a/gtsam/inference/tests/testFactorGraph.cpp +++ b/gtsam/inference/tests/testFactorGraph.cpp @@ -21,80 +21,43 @@ #include #include #include // for operator += +#include using namespace boost::assign; #include +#include #include using namespace std; using namespace gtsam; -typedef boost::shared_ptr shared; - -///* ************************************************************************* */ -// SL-FIX TEST( FactorGraph, splitMinimumSpanningTree ) -//{ -// SymbolicFactorGraph G; -// G.push_factor("x1", "x2"); -// G.push_factor("x1", "x3"); -// G.push_factor("x1", "x4"); -// G.push_factor("x2", "x3"); -// G.push_factor("x2", "x4"); -// G.push_factor("x3", "x4"); -// -// SymbolicFactorGraph T, C; -// boost::tie(T, C) = G.splitMinimumSpanningTree(); -// -// SymbolicFactorGraph expectedT, expectedC; -// expectedT.push_factor("x1", "x2"); -// expectedT.push_factor("x1", "x3"); -// expectedT.push_factor("x1", "x4"); -// expectedC.push_factor("x2", "x3"); -// expectedC.push_factor("x2", "x4"); -// expectedC.push_factor("x3", "x4"); -// CHECK(assert_equal(expectedT,T)); -// CHECK(assert_equal(expectedC,C)); -//} - -///* ************************************************************************* */ -///** -// * x1 - x2 - x3 - x4 - x5 -// * | | / | -// * l1 l2 l3 -// */ -// SL-FIX TEST( FactorGraph, removeSingletons ) -//{ -// SymbolicFactorGraph G; -// G.push_factor("x1", "x2"); -// G.push_factor("x2", "x3"); -// G.push_factor("x3", "x4"); -// G.push_factor("x4", "x5"); -// G.push_factor("x2", "l1"); -// G.push_factor("x3", "l2"); -// G.push_factor("x4", "l2"); -// G.push_factor("x4", "l3"); -// -// SymbolicFactorGraph singletonGraph; -// set singletons; -// boost::tie(singletonGraph, singletons) = G.removeSingletons(); -// -// set singletons_excepted; singletons_excepted += "x1", "x2", "x5", "l1", "l3"; -// CHECK(singletons_excepted == singletons); -// -// SymbolicFactorGraph singletonGraph_excepted; -// singletonGraph_excepted.push_factor("x2", "l1"); -// singletonGraph_excepted.push_factor("x4", "l3"); -// singletonGraph_excepted.push_factor("x1", "x2"); -// singletonGraph_excepted.push_factor("x4", "x5"); -// singletonGraph_excepted.push_factor("x2", "x3"); -// CHECK(singletonGraph_excepted.equals(singletonGraph)); -//} - /* ************************************************************************* */ -TEST(FactorGraph, dynamic_factor_cast) { - FactorGraph fg; - fg.dynamicCastFactors >(); +TEST(FactorGraph, eliminateFrontals) { + + SymbolicFactorGraph sfgOrig; + sfgOrig.push_factor(0,1); + sfgOrig.push_factor(0,2); + sfgOrig.push_factor(1,3); + sfgOrig.push_factor(1,4); + sfgOrig.push_factor(2,3); + sfgOrig.push_factor(4,5); + + IndexConditional::shared_ptr actualCond; + SymbolicFactorGraph actualSfg; + boost::tie(actualCond, actualSfg) = sfgOrig.eliminateFrontals(2); + + vector condIndices; + condIndices += 0,1,2,3,4; + IndexConditional expectedCond(condIndices, 2); + + SymbolicFactorGraph expectedSfg; + expectedSfg.push_factor(2,3); + expectedSfg.push_factor(4,5); + expectedSfg.push_factor(2,3,4); + + EXPECT(assert_equal(expectedSfg, actualSfg)); + EXPECT(assert_equal(expectedCond, *actualCond)); } /* ************************************************************************* */ diff --git a/gtsam/inference/tests/testISAM.cpp b/gtsam/inference/tests/testISAM.cpp index 8fdc78fc0..18cf66723 100644 --- a/gtsam/inference/tests/testISAM.cpp +++ b/gtsam/inference/tests/testISAM.cpp @@ -34,7 +34,7 @@ typedef ISAM SymbolicISAM; /* ************************************************************************* */ // Some numbers that should be consistent among all smoother tests -double sigmax1 = 0.786153, sigmax2 = 0.687131, sigmax3 = 0.671512, sigmax4 = +static double sigmax1 = 0.786153, sigmax2 = 0.687131, sigmax3 = 0.671512, sigmax4 = 0.669534, sigmax5 = sigmax3, sigmax6 = sigmax2, sigmax7 = sigmax1; /* ************************************************************************* */ diff --git a/gtsam/inference/tests/testInference.cpp b/gtsam/inference/tests/testInference.cpp index 41c33a456..b25703cb6 100644 --- a/gtsam/inference/tests/testInference.cpp +++ b/gtsam/inference/tests/testInference.cpp @@ -11,8 +11,8 @@ /** * @file testInference.cpp - * @brief * @author Richard Roberts + * @author Alex Cunningham * @date Dec 6, 2010 */ @@ -35,8 +35,84 @@ TEST(inference, UnobservedVariables) { VariableIndex variableIndex(sfg); - Permutation::shared_ptr colamd(inference::PermutationCOLAMD(variableIndex)); + // Computes a permutation with known variables first, skipped variables last + // Actual 0 1 3 5 2 4 + Permutation::shared_ptr actual(inference::PermutationCOLAMD(variableIndex)); + Permutation expected(6); + expected[0] = 0; + expected[1] = 1; + expected[2] = 3; + expected[3] = 5; + expected[4] = 2; + expected[5] = 4; + EXPECT(assert_equal(expected, *actual)); +} + +/* ************************************************************************* */ +TEST(inference, constrained_ordering) { + SymbolicFactorGraph sfg; + + // create graph with wanted variable set = 2, 4 + sfg.push_factor(0,1); + sfg.push_factor(1,2); + sfg.push_factor(2,3); + sfg.push_factor(3,4); + sfg.push_factor(4,5); + + VariableIndex variableIndex(sfg); + + // unconstrained version + Permutation::shared_ptr actUnconstrained(inference::PermutationCOLAMD(variableIndex)); + Permutation expUnconstrained = Permutation::Identity(6); + EXPECT(assert_equal(expUnconstrained, *actUnconstrained)); + + // constrained version - push one set to the end + std::vector constrainLast; + constrainLast.push_back(2); + constrainLast.push_back(4); + Permutation::shared_ptr actConstrained(inference::PermutationCOLAMD(variableIndex, constrainLast)); + Permutation expConstrained(6); + expConstrained[0] = 0; + expConstrained[1] = 1; + expConstrained[2] = 5; + expConstrained[3] = 3; + expConstrained[4] = 4; + expConstrained[5] = 2; + EXPECT(assert_equal(expConstrained, *actConstrained)); +} + +/* ************************************************************************* */ +TEST(inference, grouped_constrained_ordering) { + SymbolicFactorGraph sfg; + + // create graph with constrained groups: + // 1: 2, 4 + // 2: 5 + sfg.push_factor(0,1); + sfg.push_factor(1,2); + sfg.push_factor(2,3); + sfg.push_factor(3,4); + sfg.push_factor(4,5); + + VariableIndex variableIndex(sfg); + + // constrained version - push one set to the end + FastMap constraints; + constraints[2] = 1; + constraints[4] = 1; + constraints[5] = 2; + + Permutation::shared_ptr actConstrained(inference::PermutationCOLAMDGrouped(variableIndex, constraints)); + Permutation expConstrained(6); + expConstrained[0] = 0; + expConstrained[1] = 1; + expConstrained[2] = 3; + expConstrained[3] = 2; + expConstrained[4] = 4; + expConstrained[5] = 5; + EXPECT(assert_equal(expConstrained, *actConstrained)); } /* ************************************************************************* */ int main() { TestResult tr; return TestRegistry::runAllTests(tr); } +/* ************************************************************************* */ diff --git a/gtsam/inference/tests/testJunctionTree.cpp b/gtsam/inference/tests/testJunctionTree.cpp index 16309abda..e9694eda3 100644 --- a/gtsam/inference/tests/testJunctionTree.cpp +++ b/gtsam/inference/tests/testJunctionTree.cpp @@ -35,7 +35,6 @@ using namespace gtsam; using namespace std; typedef JunctionTree SymbolicJunctionTree; -typedef BayesTree SymbolicBayesTree; /* ************************************************************************* * * x1 - x2 - x3 - x4 @@ -83,8 +82,7 @@ TEST( JunctionTree, eliminate) SymbolicJunctionTree jt(fg); SymbolicBayesTree::sharedClique actual = jt.eliminate(&EliminateSymbolic); - BayesNet bn(*SymbolicSequentialSolver(fg).eliminate( - &EliminateSymbolic)); + BayesNet bn(*SymbolicSequentialSolver(fg).eliminate()); SymbolicBayesTree expected(bn); // cout << "BT from JT:\n"; diff --git a/gtsam/inference/tests/testSymbolicBayesNet.cpp b/gtsam/inference/tests/testSymbolicBayesNet.cpp index 20abb6a71..06b1bded9 100644 --- a/gtsam/inference/tests/testSymbolicBayesNet.cpp +++ b/gtsam/inference/tests/testSymbolicBayesNet.cpp @@ -35,7 +35,7 @@ static const Index _C_ = 3; static const Index _D_ = 4; static const Index _E_ = 5; -IndexConditional::shared_ptr +static IndexConditional::shared_ptr B(new IndexConditional(_B_)), L(new IndexConditional(_L_, _B_)); diff --git a/gtsam/inference/tests/testVariableIndex.cpp b/gtsam/inference/tests/testVariableIndex.cpp index a990a5a87..412b3fa04 100644 --- a/gtsam/inference/tests/testVariableIndex.cpp +++ b/gtsam/inference/tests/testVariableIndex.cpp @@ -22,6 +22,7 @@ #include #include +using namespace std; using namespace gtsam; /* ************************************************************************* */ @@ -43,7 +44,9 @@ TEST(VariableIndex, augment) { VariableIndex actual(fg1); actual.augment(fg2); - CHECK(assert_equal(expected, actual)); + LONGS_EQUAL(16, actual.nEntries()); + LONGS_EQUAL(8, actual.nFactors()); + EXPECT(assert_equal(expected, actual)); } /* ************************************************************************* */ diff --git a/gtsam/linear/ConjugateGradientSolver.h b/gtsam/linear/ConjugateGradientSolver.h new file mode 100644 index 000000000..a89d7a10c --- /dev/null +++ b/gtsam/linear/ConjugateGradientSolver.h @@ -0,0 +1,76 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +#pragma once + +#include + +namespace gtsam { + +/** + * parameters for the conjugate gradient method + */ + +class ConjugateGradientParameters : public IterativeOptimizationParameters { +public: + typedef IterativeOptimizationParameters Base; + typedef boost::shared_ptr shared_ptr; + + size_t minIterations_; ///< minimum number of cg iterations + size_t maxIterations_; ///< maximum number of cg iterations + size_t reset_; ///< number of iterations before reset + double epsilon_rel_; ///< threshold for relative error decrease + double epsilon_abs_; ///< threshold for absolute error decrease + + ConjugateGradientParameters() + : minIterations_(1), maxIterations_(500), reset_(501), epsilon_rel_(1e-3), epsilon_abs_(1e-3){} + + ConjugateGradientParameters(size_t minIterations, size_t maxIterations, size_t reset, double epsilon_rel, double epsilon_abs) + : minIterations_(minIterations), maxIterations_(maxIterations), reset_(reset), epsilon_rel_(epsilon_rel), epsilon_abs_(epsilon_abs){} + + ConjugateGradientParameters(const ConjugateGradientParameters &p) + : Base(p), minIterations_(p.minIterations_), maxIterations_(p.maxIterations_), reset_(p.reset_), epsilon_rel_(p.epsilon_rel_), epsilon_abs_(p.epsilon_abs_) {} + + /* general interface */ + inline size_t minIterations() const { return minIterations_; } + inline size_t maxIterations() const { return maxIterations_; } + inline size_t reset() const { return reset_; } + inline double epsilon() const { return epsilon_rel_; } + inline double epsilon_rel() const { return epsilon_rel_; } + inline double epsilon_abs() const { return epsilon_abs_; } + + inline size_t getMinIterations() const { return minIterations_; } + inline size_t getMaxIterations() const { return maxIterations_; } + inline size_t getReset() const { return reset_; } + inline double getEpsilon() const { return epsilon_rel_; } + inline double getEpsilon_rel() const { return epsilon_rel_; } + inline double getEpsilon_abs() const { return epsilon_abs_; } + + inline void setMinIterations(size_t value) { minIterations_ = value; } + inline void setMaxIterations(size_t value) { maxIterations_ = value; } + inline void setReset(size_t value) { reset_ = value; } + inline void setEpsilon(double value) { epsilon_rel_ = value; } + inline void setEpsilon_rel(double value) { epsilon_rel_ = value; } + inline void setEpsilon_abs(double value) { epsilon_abs_ = value; } + + virtual void print(const std::string &s="") const { + Base::print(); + std::cout << "ConjugateGradientParameters: " + << "minIter = " << minIterations_ + << ", maxIter = " << maxIterations_ + << ", resetIter = " << reset_ + << ", eps_rel = " << epsilon_rel_ + << ", eps_abs = " << epsilon_abs_ + << std::endl; + } +}; + +} diff --git a/gtsam/linear/Errors.cpp b/gtsam/linear/Errors.cpp index 71d0cc003..65a52cce1 100644 --- a/gtsam/linear/Errors.cpp +++ b/gtsam/linear/Errors.cpp @@ -17,7 +17,6 @@ * @author Christian Potthast */ -#include #include #include @@ -56,7 +55,6 @@ struct equalsVector : public std::binary_function +#include +#include +#include +#include + #include +#include #include -#include -#include -#include - -#include +#include using namespace std; using namespace gtsam; - // trick from some reading group #define FOREACH_PAIR( KEY, VAL, COL) BOOST_FOREACH (boost::tie(KEY,VAL),COL) #define REVERSE_FOREACH_PAIR( KEY, VAL, COL) BOOST_REVERSE_FOREACH (boost::tie(KEY,VAL),COL) @@ -99,6 +99,24 @@ void optimizeInPlace(const GaussianBayesNet& bn, VectorValues& x) { } } +/* ************************************************************************* */ +VectorValues backSubstitute(const GaussianBayesNet& bn, const VectorValues& input) { + VectorValues output = input; + BOOST_REVERSE_FOREACH(const boost::shared_ptr cg, bn) { + const Index key = *(cg->beginFrontals()); + Vector xS = internal::extractVectorValuesSlices(output, cg->beginParents(), cg->endParents()); + xS = input[key] - cg->get_S() * xS; + output[key] = cg->get_R().triangularView().solve(xS); + } + + BOOST_FOREACH(const boost::shared_ptr cg, bn) { + cg->scaleFrontalsBySigma(output); + } + + return output; +} + + /* ************************************************************************* */ // gy=inv(L)*gx by solving L*gy=gx. // gy=inv(R'*inv(Sigma))*gx @@ -224,12 +242,12 @@ double determinant(const GaussianBayesNet& bayesNet) { /* ************************************************************************* */ VectorValues gradient(const GaussianBayesNet& bayesNet, const VectorValues& x0) { - return gradient(FactorGraph(bayesNet), x0); + return gradient(GaussianFactorGraph(bayesNet), x0); } /* ************************************************************************* */ void gradientAtZero(const GaussianBayesNet& bayesNet, VectorValues& g) { - gradientAtZero(FactorGraph(bayesNet), g); + gradientAtZero(GaussianFactorGraph(bayesNet), g); } /* ************************************************************************* */ diff --git a/gtsam/linear/GaussianBayesNet.h b/gtsam/linear/GaussianBayesNet.h index 8c6e72357..fb179da92 100644 --- a/gtsam/linear/GaussianBayesNet.h +++ b/gtsam/linear/GaussianBayesNet.h @@ -106,6 +106,12 @@ namespace gtsam { * */ void optimizeGradientSearchInPlace(const GaussianBayesNet& bn, VectorValues& grad); + /** + * Backsubstitute + * gy=inv(R*inv(Sigma))*gx + */ + VectorValues backSubstitute(const GaussianBayesNet& bn, const VectorValues& gx); + /** * Transpose Backsubstitute * gy=inv(L)*gx by solving L*gy=gx. diff --git a/gtsam/linear/GaussianBayesTree-inl.h b/gtsam/linear/GaussianBayesTree-inl.h index 4972b13bf..4e398ef7f 100644 --- a/gtsam/linear/GaussianBayesTree-inl.h +++ b/gtsam/linear/GaussianBayesTree-inl.h @@ -10,7 +10,7 @@ * -------------------------------------------------------------------------- */ /** - * @file GaussianBayesTree.cpp + * @file GaussianBayesTree-inl.h * @brief Gaussian Bayes Tree, the result of eliminating a GaussianJunctionTree * @brief GaussianBayesTree * @author Frank Dellaert diff --git a/gtsam/linear/GaussianBayesTree.cpp b/gtsam/linear/GaussianBayesTree.cpp index ae76d958e..04cb4a25a 100644 --- a/gtsam/linear/GaussianBayesTree.cpp +++ b/gtsam/linear/GaussianBayesTree.cpp @@ -18,7 +18,7 @@ */ #include -#include +#include namespace gtsam { @@ -35,27 +35,27 @@ void optimizeInPlace(const GaussianBayesTree& bayesTree, VectorValues& result) { } /* ************************************************************************* */ -VectorValues optimizeGradientSearch(const GaussianBayesTree& Rd) { +VectorValues optimizeGradientSearch(const GaussianBayesTree& bayesTree) { tic(0, "Allocate VectorValues"); - VectorValues grad = *allocateVectorValues(Rd); + VectorValues grad = *allocateVectorValues(bayesTree); toc(0, "Allocate VectorValues"); - optimizeGradientSearchInPlace(Rd, grad); + optimizeGradientSearchInPlace(bayesTree, grad); return grad; } /* ************************************************************************* */ -void optimizeGradientSearchInPlace(const GaussianBayesTree& Rd, VectorValues& grad) { +void optimizeGradientSearchInPlace(const GaussianBayesTree& bayesTree, VectorValues& grad) { tic(1, "Compute Gradient"); // Compute gradient (call gradientAtZero function, which is defined for various linear systems) - gradientAtZero(Rd, grad); + gradientAtZero(bayesTree, grad); double gradientSqNorm = grad.dot(grad); toc(1, "Compute Gradient"); tic(2, "Compute R*g"); // Compute R * g - FactorGraph Rd_jfg(Rd); + FactorGraph Rd_jfg(bayesTree); Errors Rg = Rd_jfg * grad; toc(2, "Compute R*g"); diff --git a/gtsam/linear/GaussianBayesTree.h b/gtsam/linear/GaussianBayesTree.h index 8b581351c..91480d43a 100644 --- a/gtsam/linear/GaussianBayesTree.h +++ b/gtsam/linear/GaussianBayesTree.h @@ -25,13 +25,14 @@ namespace gtsam { +/// A Bayes Tree representing a Gaussian density typedef BayesTree GaussianBayesTree; /// optimize the BayesTree, starting from the root VectorValues optimize(const GaussianBayesTree& bayesTree); /// recursively optimize this conditional and all subtrees -void optimizeInPlace(const GaussianBayesTree& clique, VectorValues& result); +void optimizeInPlace(const GaussianBayesTree& bayesTree, VectorValues& result); namespace internal { template @@ -63,10 +64,10 @@ void optimizeInPlace(const typename BAYESTREE::sharedClique& clique, VectorValue * * \f[ \delta x = \hat\alpha g = \frac{-g^T g}{(R g)^T(R g)} \f] */ -VectorValues optimizeGradientSearch(const GaussianBayesTree& bn); +VectorValues optimizeGradientSearch(const GaussianBayesTree& bayesTree); /** In-place version of optimizeGradientSearch requiring pre-allocated VectorValues \c x */ -void optimizeGradientSearchInPlace(const GaussianBayesTree& bn, VectorValues& grad); +void optimizeGradientSearchInPlace(const GaussianBayesTree& bayesTree, VectorValues& grad); /** * Compute the gradient of the energy function, diff --git a/gtsam/linear/GaussianConditional.cpp b/gtsam/linear/GaussianConditional.cpp index de459a00f..b35bffd3c 100644 --- a/gtsam/linear/GaussianConditional.cpp +++ b/gtsam/linear/GaussianConditional.cpp @@ -17,8 +17,10 @@ #include #include +#include #include +#include #include #include #include @@ -73,7 +75,7 @@ GaussianConditional::GaussianConditional(Index key, const Vector& d, const Matri const Matrix& R, const list >& parents, const Vector& sigmas) : IndexConditional(key, GetKeys(parents.size(), parents.begin(), parents.end())), rsd_(matrix_), sigmas_(sigmas) { assert(R.rows() <= R.cols()); - size_t dims[1+parents.size()+1]; + size_t* dims = (size_t*)alloca(sizeof(size_t)*(1+parents.size()+1)); // FIXME: alloca is bad, just ask Google. dims[0] = R.cols(); size_t j=1; std::list >::const_iterator parent=parents.begin(); @@ -95,7 +97,7 @@ GaussianConditional::GaussianConditional(const std::list Index_Matrix; BOOST_FOREACH(const Index_Matrix& term, terms) { @@ -129,16 +131,16 @@ GaussianConditional& GaussianConditional::operator=(const GaussianConditional& r } /* ************************************************************************* */ -void GaussianConditional::print(const string &s) const +void GaussianConditional::print(const string &s, const IndexFormatter& formatter) const { cout << s << ": density on "; for(const_iterator it = beginFrontals(); it != endFrontals(); ++it) { - cout << (boost::format("[%1%]")%(*it)).str() << " "; + cout << (boost::format("[%1%]")%(formatter(*it))).str() << " "; } cout << endl; gtsam::print(Matrix(get_R()),"R"); for(const_iterator it = beginParents() ; it != endParents() ; ++it ) { - gtsam::print(Matrix(get_S(it)), (boost::format("A[%1%]")%(*it)).str()); + gtsam::print(Matrix(get_S(it)), (boost::format("A[%1%]")%(formatter(*it))).str()); } gtsam::print(Vector(get_d()),"d"); gtsam::print(sigmas_,"sigmas"); @@ -182,41 +184,34 @@ JacobianFactor::shared_ptr GaussianConditional::toFactor() const { return JacobianFactor::shared_ptr(new JacobianFactor(*this)); } -/* ************************************************************************* */ -template -inline static void doSolveInPlace(const GaussianConditional& conditional, VALUES& x) { - - // Helper function to solve-in-place on a VectorValues or Permuted, - // called by GaussianConditional::solveInPlace(VectorValues&) and by - // GaussianConditional::solveInPlace(Permuted&). - - static const bool debug = false; - if(debug) conditional.print("Solving conditional in place"); - Vector xS = internal::extractVectorValuesSlices(x, conditional.beginParents(), conditional.endParents()); - xS = conditional.get_d() - conditional.get_S() * xS; - Vector soln = conditional.get_R().triangularView().solve(xS); - if(debug) { - gtsam::print(Matrix(conditional.get_R()), "Calling backSubstituteUpper on "); - gtsam::print(soln, "full back-substitution solution: "); - } - internal::writeVectorValuesSlices(soln, x, conditional.beginFrontals(), conditional.endFrontals()); -} - /* ************************************************************************* */ void GaussianConditional::solveInPlace(VectorValues& x) const { - doSolveInPlace(*this, x); // Call helper version above -} + static const bool debug = false; + if(debug) this->print("Solving conditional in place"); + Vector xS = internal::extractVectorValuesSlices(x, this->beginParents(), this->endParents()); + xS = this->get_d() - this->get_S() * xS; + Vector soln = this->get_R().triangularView().solve(xS); -/* ************************************************************************* */ -void GaussianConditional::solveInPlace(Permuted& x) const { - doSolveInPlace(*this, x); // Call helper version above + // Check for indeterminant solution + if(soln.unaryExpr(!boost::lambda::bind(ptr_fun(isfinite), boost::lambda::_1)).any()) + throw IndeterminantLinearSystemException(this->keys().front()); + + if(debug) { + gtsam::print(Matrix(this->get_R()), "Calling backSubstituteUpper on "); + gtsam::print(soln, "full back-substitution solution: "); + } + internal::writeVectorValuesSlices(soln, x, this->beginFrontals(), this->endFrontals()); } /* ************************************************************************* */ void GaussianConditional::solveTransposeInPlace(VectorValues& gy) const { Vector frontalVec = internal::extractVectorValuesSlices(gy, beginFrontals(), endFrontals()); - // TODO: verify permutation frontalVec = gtsam::backSubstituteUpper(frontalVec,Matrix(get_R())); + + // Check for indeterminant solution + if(frontalVec.unaryExpr(!boost::lambda::bind(ptr_fun(isfinite), boost::lambda::_1)).any()) + throw IndeterminantLinearSystemException(this->keys().front()); + GaussianConditional::const_iterator it; for (it = beginParents(); it!= endParents(); it++) { const Index i = *it; diff --git a/gtsam/linear/GaussianConditional.h b/gtsam/linear/GaussianConditional.h index 2f91a6115..cde4f266f 100644 --- a/gtsam/linear/GaussianConditional.h +++ b/gtsam/linear/GaussianConditional.h @@ -80,7 +80,7 @@ public: GaussianConditional(); /** constructor */ - GaussianConditional(Index key); + explicit GaussianConditional(Index key); /** constructor with no parents * |Rx-d| @@ -138,7 +138,8 @@ public: GaussianConditional& operator=(const GaussianConditional& rhs); /** print */ - void print(const std::string& = "GaussianConditional") const; + void print(const std::string& = "GaussianConditional", + const IndexFormatter& formatter = DefaultIndexFormatter) const; /** equals function */ bool equals(const GaussianConditional &cg, double tol = 1e-9) const; @@ -195,23 +196,6 @@ public: */ void solveInPlace(VectorValues& x) const; - /** - * Solves a conditional Gaussian and writes the solution into the entries of - * \c x for each frontal variable of the conditional (version for permuted - * VectorValues). The parents are assumed to have already been solved in - * and their values are read from \c x. This function works for multiple - * frontal variables. - * - * Given the Gaussian conditional with log likelihood \f$ |R x_f - (d - S x_s)|^2, - * where \f$ f \f$ are the frontal variables and \f$ s \f$ are the separator - * variables of this conditional, this solve function computes - * \f$ x_f = R^{-1} (d - S x_s) \f$ using back-substitution. - * - * @param x VectorValues structure with solved parents \f$ x_s \f$, and into which the - * solution \f$ x_f \f$ will be written. - */ - void solveInPlace(Permuted& x) const; - // functions for transpose backsubstitution /** diff --git a/gtsam/linear/GaussianDensity.cpp b/gtsam/linear/GaussianDensity.cpp index 97e42d9ba..c8fc4c21a 100644 --- a/gtsam/linear/GaussianDensity.cpp +++ b/gtsam/linear/GaussianDensity.cpp @@ -23,11 +23,11 @@ using namespace std; namespace gtsam { /* ************************************************************************* */ - void GaussianDensity::print(const string &s) const + void GaussianDensity::print(const string &s, const IndexFormatter& formatter) const { cout << s << ": density on "; for(const_iterator it = beginFrontals(); it != endFrontals(); ++it) - cout << (boost::format("[%1%]")%(*it)).str() << " "; + cout << (boost::format("[%1%]")%(formatter(*it))).str() << " "; cout << endl; gtsam::print(Matrix(get_R()),"R"); gtsam::print(Vector(get_d()),"d"); diff --git a/gtsam/linear/GaussianDensity.h b/gtsam/linear/GaussianDensity.h index 2c13e847c..4d4f673f9 100644 --- a/gtsam/linear/GaussianDensity.h +++ b/gtsam/linear/GaussianDensity.h @@ -54,7 +54,8 @@ namespace gtsam { } /// print - void print(const std::string& = "GaussianDensity") const; + void print(const std::string& = "GaussianDensity", + const IndexFormatter& formatter =DefaultIndexFormatter) const; /// Mean \f$ \mu = R^{-1} d \f$ Vector mean() const; diff --git a/gtsam/linear/GaussianFactor.h b/gtsam/linear/GaussianFactor.h index 3fdad19c6..0d435ce17 100644 --- a/gtsam/linear/GaussianFactor.h +++ b/gtsam/linear/GaussianFactor.h @@ -20,8 +20,11 @@ #pragma once +#include #include +#include + #include #include @@ -80,7 +83,9 @@ namespace gtsam { typedef boost::shared_ptr shared_ptr; // Implementing Testable interface - virtual void print(const std::string& s = "") const = 0; + virtual void print(const std::string& s = "", + const IndexFormatter& formatter = DefaultIndexFormatter) const = 0; + virtual bool equals(const GaussianFactor& lf, double tol = 1e-9) const = 0; virtual double error(const VectorValues& c) const = 0; /** 0.5*(A*x-b)'*D*(A*x-b) */ @@ -88,6 +93,16 @@ namespace gtsam { /** Return the dimension of the variable pointed to by the given key iterator */ virtual size_t getDim(const_iterator variable) const = 0; + /** Return the augmented information matrix represented by this GaussianFactor. + * The augmented information matrix contains the information matrix with an + * additional column holding the information vector, and an additional row + * holding the transpose of the information vector. The lower-right entry + * contains the constant error term (when \f$ \delta x = 0 \f$). The + * augmented information matrix is described in more detail in HessianFactor, + * which in fact stores an augmented information matrix. + */ + virtual Matrix computeInformation() const = 0; + /** Clone a factor (make a deep copy) */ virtual GaussianFactor::shared_ptr clone() const = 0; @@ -96,7 +111,16 @@ namespace gtsam { * to already be inverted. This acts just as a change-of-name for each * variable. The order of the variables within the factor is not changed. */ - virtual void permuteWithInverse(const Permutation& inversePermutation) { IndexFactor::permuteWithInverse(inversePermutation); } + virtual void permuteWithInverse(const Permutation& inversePermutation) { + IndexFactor::permuteWithInverse(inversePermutation); + } + + /** + * Construct the corresponding anti-factor to negate information + * stored stored in this factor. + * @return a HessianFactor with negated Hessian matrices + */ + virtual GaussianFactor::shared_ptr negate() const = 0; private: /** Serialization function */ diff --git a/gtsam/linear/GaussianFactorGraph.cpp b/gtsam/linear/GaussianFactorGraph.cpp index 853cf26ba..222f025a0 100644 --- a/gtsam/linear/GaussianFactorGraph.cpp +++ b/gtsam/linear/GaussianFactorGraph.cpp @@ -47,6 +47,13 @@ namespace gtsam { return keys; } + /* ************************************************************************* */ + std::pair + GaussianFactorGraph::eliminateFrontals(size_t nFrontals) const + { + return FactorGraph::eliminateFrontals(nFrontals, EliminateQR); + } + /* ************************************************************************* */ void GaussianFactorGraph::permuteWithInverse( const Permutation& inversePermutation) { @@ -159,16 +166,33 @@ namespace gtsam { } /* ************************************************************************* */ - Matrix GaussianFactorGraph::denseJacobian() const { + Matrix GaussianFactorGraph::augmentedJacobian() const { + // Convert to Jacobians + FactorGraph jfg; + jfg.reserve(this->size()); + BOOST_FOREACH(const sharedFactor& factor, *this) { + if(boost::shared_ptr jf = + boost::dynamic_pointer_cast(factor)) + jfg.push_back(jf); + else + jfg.push_back(boost::make_shared(*factor)); + } // combine all factors - JacobianFactor combined(*CombineJacobians(*convertCastFactors > (), VariableSlots(*this))); + JacobianFactor combined(*CombineJacobians(jfg, VariableSlots(*this))); return combined.matrix_augmented(); } + /* ************************************************************************* */ + std::pair GaussianFactorGraph::jacobian() const { + Matrix augmented = augmentedJacobian(); + return make_pair( + augmented.leftCols(augmented.cols()-1), + augmented.col(augmented.cols()-1)); + } + /* ************************************************************************* */ // Helper functions for Combine - static boost::tuple, size_t, size_t> countDims(const std::vector& factors, const VariableSlots& variableSlots) { + static boost::tuple, size_t, size_t> countDims(const FactorGraph& factors, const VariableSlots& variableSlots) { #ifndef NDEBUG vector varDims(variableSlots.size(), numeric_limits::max()); #else @@ -231,20 +255,6 @@ break; } toc(1, "countDims"); - if (debug) cout << "Sort rows" << endl; - tic(2, "sort rows"); - vector rowSources; - rowSources.reserve(m); - bool anyConstrained = false; - for (size_t sourceFactorI = 0; sourceFactorI < factors.size(); ++sourceFactorI) { - const JacobianFactor& sourceFactor(*factors[sourceFactorI]); - sourceFactor.collectInfo(sourceFactorI, rowSources); - if (sourceFactor.isConstrained()) anyConstrained = true; - } - assert(rowSources.size() == m); - std::sort(rowSources.begin(), rowSources.end()); - toc(2, "sort rows"); - if (debug) cout << "Allocate new factor" << endl; tic(3, "allocate"); JacobianFactor::shared_ptr combined(new JacobianFactor()); @@ -252,36 +262,47 @@ break; Vector sigmas(m); toc(3, "allocate"); - if (debug) cout << "Copy rows" << endl; - tic(4, "copy rows"); + if (debug) cout << "Copy blocks" << endl; + tic(4, "copy blocks"); + // Loop over slots in combined factor Index combinedSlot = 0; BOOST_FOREACH(const VariableSlots::value_type& varslot, variableSlots) { - for (size_t row = 0; row < m; ++row) { - const JacobianFactor::_RowSource& info(rowSources[row]); - const JacobianFactor& source(*factors[info.factorI]); - size_t sourceRow = info.factorRowI; - Index sourceSlot = varslot.second[info.factorI]; - combined->copyRow(source, sourceRow, sourceSlot, row, combinedSlot); + JacobianFactor::ABlock destSlot(combined->getA(combined->begin()+combinedSlot)); + // Loop over source factors + size_t nextRow = 0; + for(size_t factorI = 0; factorI < factors.size(); ++factorI) { + // Slot in source factor + const Index sourceSlot = varslot.second[factorI]; + const size_t sourceRows = factors[factorI]->rows(); + JacobianFactor::ABlock::RowsBlockXpr destBlock(destSlot.middleRows(nextRow, sourceRows)); + // Copy if exists in source factor, otherwise set zero + if(sourceSlot != numeric_limits::max()) + destBlock = factors[factorI]->getA(factors[factorI]->begin()+sourceSlot); + else + destBlock.setZero(); + nextRow += sourceRows; } ++combinedSlot; } - toc(4, "copy rows"); + toc(4, "copy blocks"); - if (debug) cout << "Copy rhs (b), sigma, and firstNonzeroBlocks" << endl; + if (debug) cout << "Copy rhs (b) and sigma" << endl; tic(5, "copy vectors"); - for (size_t row = 0; row < m; ++row) { - const JacobianFactor::_RowSource& info(rowSources[row]); - const JacobianFactor& source(*factors[info.factorI]); - const size_t sourceRow = info.factorRowI; - combined->getb()(row) = source.getb()(sourceRow); - sigmas(row) = source.get_model()->sigmas()(sourceRow); + bool anyConstrained = false; + // Loop over source factors + size_t nextRow = 0; + for(size_t factorI = 0; factorI < factors.size(); ++factorI) { + const size_t sourceRows = factors[factorI]->rows(); + combined->getb().segment(nextRow, sourceRows) = factors[factorI]->getb(); + sigmas.segment(nextRow, sourceRows) = factors[factorI]->get_model()->sigmas(); + if (factors[factorI]->isConstrained()) anyConstrained = true; + nextRow += sourceRows; } - combined->copyFNZ(m, variableSlots.size(),rowSources); toc(5, "copy vectors"); if (debug) cout << "Create noise model from sigmas" << endl; tic(6, "noise model"); - combined->setModel( anyConstrained,sigmas); + combined->setModel(anyConstrained, sigmas); toc(6, "noise model"); if (debug) cout << "Assert Invariants" << endl; @@ -304,9 +325,7 @@ break; } /* ************************************************************************* */ - static - FastMap findScatterAndDims - (const FactorGraph& factors) { + static FastMap findScatterAndDims(const FactorGraph& factors) { const bool debug = ISDEBUG("findScatterAndDims"); @@ -336,7 +355,7 @@ break; } /* ************************************************************************* */ - Matrix GaussianFactorGraph::denseHessian() const { + Matrix GaussianFactorGraph::augmentedHessian() const { Scatter scatter = findScatterAndDims(*this); @@ -354,6 +373,14 @@ break; return result; } + /* ************************************************************************* */ + std::pair GaussianFactorGraph::hessian() const { + Matrix augmented = augmentedHessian(); + return make_pair( + augmented.topLeftCorner(augmented.rows()-1, augmented.rows()-1), + augmented.col(augmented.rows()-1).head(augmented.rows()-1)); + } + /* ************************************************************************* */ GaussianFactorGraph::EliminationResult EliminateCholesky(const FactorGraph< GaussianFactor>& factors, size_t nrFrontals) { @@ -377,22 +404,14 @@ break; // Form Ab' * Ab tic(3, "combine"); - HessianFactor::shared_ptr // - combinedFactor(new HessianFactor(factors, dimensions, scatter)); + HessianFactor::shared_ptr combinedFactor(new HessianFactor(factors, dimensions, scatter)); toc(3, "combine"); // Do Cholesky, note that after this, the lower triangle still contains // some untouched non-zeros that should be zero. We zero them while // extracting submatrices next. tic(4, "partial Cholesky"); - try { - combinedFactor->partialCholesky(nrFrontals); - } catch - (std::exception &ex) { // catch exception from Cholesky - combinedFactor->print("combinedFactor"); - string reason = "EliminateCholesky failed while trying to eliminate the combined factor"; - throw invalid_argument(reason); - } + combinedFactor->partialCholesky(nrFrontals); toc(4, "partial Cholesky"); @@ -494,67 +513,134 @@ break; return EliminateQR(factors, nrFrontals); else { GaussianFactorGraph::EliminationResult ret; -#ifdef NDEBUG - static const bool diag = false; -#else - static const bool diag = !ISDEBUG("NoCholeskyDiagnostics"); -#endif - if (!diag) { - tic(2, "EliminateCholesky"); - ret = EliminateCholesky(factors, nrFrontals); - toc(2, "EliminateCholesky"); - } else { - try { - tic(2, "EliminateCholesky"); - ret = EliminateCholesky(factors, nrFrontals); - toc(2, "EliminateCholesky"); - } catch (const exception& e) { - cout << "Exception in EliminateCholesky: " << e.what() << endl; - SETDEBUG("EliminateCholesky", true); - SETDEBUG("updateATA", true); - SETDEBUG("JacobianFactor::eliminate", true); - SETDEBUG("JacobianFactor::Combine", true); - SETDEBUG("choleskyPartial", true); - factors.print("Combining factors: "); - EliminateCholesky(factors, nrFrontals); - throw; - } - } - - const bool checkCholesky = ISDEBUG("EliminateGaussian Check Cholesky"); - if (checkCholesky) { - GaussianFactorGraph::EliminationResult expected; - FactorGraph jacobians = convertToJacobians(factors); - try { - // Compare with QR - expected = EliminateJacobians(jacobians, nrFrontals); - } catch (...) { - cout << "Exception in QR" << endl; - throw; - } - - H actual_factor(*ret.second); - H expected_factor(*expected.second); - if (!assert_equal(*expected.first, *ret.first, 100.0) - || !assert_equal(expected_factor, actual_factor, 1.0)) { - cout << "Cholesky and QR do not agree" << endl; - - SETDEBUG("EliminateCholesky", true); - SETDEBUG("updateATA", true); - SETDEBUG("JacobianFactor::eliminate", true); - SETDEBUG("JacobianFactor::Combine", true); - jacobians.print("Jacobian Factors: "); - EliminateJacobians(jacobians, nrFrontals); - EliminateCholesky(factors, nrFrontals); - factors.print("Combining factors: "); - - throw runtime_error("Cholesky and QR do not agree"); - } - } - + tic(2, "EliminateCholesky"); + ret = EliminateCholesky(factors, nrFrontals); + toc(2, "EliminateCholesky"); return ret; } } // \EliminatePreferCholesky + + + /* ************************************************************************* */ + static JacobianFactor::shared_ptr convertToJacobianFactorPtr(const GaussianFactor::shared_ptr &gf) { + JacobianFactor::shared_ptr result = boost::dynamic_pointer_cast(gf); + if( !result ) { + result = boost::make_shared(*gf); // Convert any non-Jacobian factors to Jacobians (e.g. Hessian -> Jacobian with Cholesky) + } + return result; + } + + /* ************************************************************************* */ + Errors operator*(const GaussianFactorGraph& fg, const VectorValues& x) { + Errors e; + BOOST_FOREACH(const GaussianFactor::shared_ptr& Ai_G, fg) { + JacobianFactor::shared_ptr Ai = convertToJacobianFactorPtr(Ai_G); + e.push_back((*Ai)*x); + } + return e; + } + + /* ************************************************************************* */ + void multiplyInPlace(const GaussianFactorGraph& fg, const VectorValues& x, Errors& e) { + multiplyInPlace(fg,x,e.begin()); + } + + /* ************************************************************************* */ + void multiplyInPlace(const GaussianFactorGraph& fg, const VectorValues& x, const Errors::iterator& e) { + Errors::iterator ei = e; + BOOST_FOREACH(const GaussianFactor::shared_ptr& Ai_G, fg) { + JacobianFactor::shared_ptr Ai = convertToJacobianFactorPtr(Ai_G); + *ei = (*Ai)*x; + ei++; + } + } + + /* ************************************************************************* */ + // x += alpha*A'*e + void transposeMultiplyAdd(const GaussianFactorGraph& fg, double alpha, const Errors& e, VectorValues& x) { + // For each factor add the gradient contribution + Errors::const_iterator ei = e.begin(); + BOOST_FOREACH(const GaussianFactor::shared_ptr& Ai_G, fg) { + JacobianFactor::shared_ptr Ai = convertToJacobianFactorPtr(Ai_G); + Ai->transposeMultiplyAdd(alpha,*(ei++),x); + } + } + + /* ************************************************************************* */ + VectorValues gradient(const GaussianFactorGraph& fg, const VectorValues& x0) { + // It is crucial for performance to make a zero-valued clone of x + VectorValues g = VectorValues::Zero(x0); + Errors e; + BOOST_FOREACH(const GaussianFactor::shared_ptr& Ai_G, fg) { + JacobianFactor::shared_ptr Ai = convertToJacobianFactorPtr(Ai_G); + e.push_back(Ai->error_vector(x0)); + } + transposeMultiplyAdd(fg, 1.0, e, g); + return g; + } + + /* ************************************************************************* */ + void gradientAtZero(const GaussianFactorGraph& fg, VectorValues& g) { + // Zero-out the gradient + g.setZero(); + Errors e; + BOOST_FOREACH(const GaussianFactor::shared_ptr& Ai_G, fg) { + JacobianFactor::shared_ptr Ai = convertToJacobianFactorPtr(Ai_G); + e.push_back(-Ai->getb()); + } + transposeMultiplyAdd(fg, 1.0, e, g); + } + + /* ************************************************************************* */ + void residual(const GaussianFactorGraph& fg, const VectorValues &x, VectorValues &r) { + Index i = 0 ; + BOOST_FOREACH(const GaussianFactor::shared_ptr& Ai_G, fg) { + JacobianFactor::shared_ptr Ai = convertToJacobianFactorPtr(Ai_G); + r[i] = Ai->getb(); + i++; + } + VectorValues Ax = VectorValues::SameStructure(r); + multiply(fg,x,Ax); + axpy(-1.0,Ax,r); + } + + /* ************************************************************************* */ + void multiply(const GaussianFactorGraph& fg, const VectorValues &x, VectorValues &r) { + r.vector() = Vector::Zero(r.dim()); + Index i = 0; + BOOST_FOREACH(const GaussianFactor::shared_ptr& Ai_G, fg) { + JacobianFactor::shared_ptr Ai = convertToJacobianFactorPtr(Ai_G); + SubVector &y = r[i]; + for(JacobianFactor::const_iterator j = Ai->begin(); j != Ai->end(); ++j) { + y += Ai->getA(j) * x[*j]; + } + ++i; + } + } + + /* ************************************************************************* */ + void transposeMultiply(const GaussianFactorGraph& fg, const VectorValues &r, VectorValues &x) { + x.vector() = Vector::Zero(x.dim()); + Index i = 0; + BOOST_FOREACH(const GaussianFactor::shared_ptr& Ai_G, fg) { + JacobianFactor::shared_ptr Ai = convertToJacobianFactorPtr(Ai_G); + for(JacobianFactor::const_iterator j = Ai->begin(); j != Ai->end(); ++j) { + x[*j] += Ai->getA(j).transpose() * r[i]; + } + ++i; + } + } + + /* ************************************************************************* */ + boost::shared_ptr gaussianErrors_(const GaussianFactorGraph& fg, const VectorValues& x) { + boost::shared_ptr e(new Errors); + BOOST_FOREACH(const GaussianFactor::shared_ptr& Ai_G, fg) { + JacobianFactor::shared_ptr Ai = convertToJacobianFactorPtr(Ai_G); + e->push_back(Ai->error_vector(x)); + } + return e; + } + } // namespace gtsam diff --git a/gtsam/linear/GaussianFactorGraph.h b/gtsam/linear/GaussianFactorGraph.h index 1f66b5b4c..5e6e792be 100644 --- a/gtsam/linear/GaussianFactorGraph.h +++ b/gtsam/linear/GaussianFactorGraph.h @@ -31,26 +31,6 @@ namespace gtsam { - class SharedDiagonal; - - /** return A*x-b - * \todo Make this a member function - affects SubgraphPreconditioner */ - template - Errors gaussianErrors(const FactorGraph& fg, const VectorValues& x) { - return *gaussianErrors_(fg, x); - } - - /** shared pointer version - * \todo Make this a member function - affects SubgraphPreconditioner */ - template - boost::shared_ptr gaussianErrors_(const FactorGraph& fg, const VectorValues& x) { - boost::shared_ptr e(new Errors); - BOOST_FOREACH(const typename FACTOR::shared_ptr& factor, fg) { - e->push_back(factor->error_vector(x)); - } - return e; - } - /** * A Linear Factor Graph is a factor graph where all factors are Gaussian, i.e. * Factor == GaussianFactor @@ -85,32 +65,32 @@ namespace gtsam { push_back(fg); } - /** Add a Jacobian factor */ - void add(const boost::shared_ptr& factor) { - factors_.push_back(boost::shared_ptr(factor)); + /** Add a factor by value - makes a copy */ + void add(const GaussianFactor& factor) { + factors_.push_back(factor.clone()); } - /** Add a Hessian factor */ - void add(const boost::shared_ptr& factor) { - factors_.push_back(boost::shared_ptr(factor)); + /** Add a factor by pointer - stores pointer without copying the factor */ + void add(const sharedFactor& factor) { + factors_.push_back(factor); } /** Add a null factor */ void add(const Vector& b) { - add(JacobianFactor::shared_ptr(new JacobianFactor(b))); + add(JacobianFactor(b)); } /** Add a unary factor */ void add(Index key1, const Matrix& A1, const Vector& b, const SharedDiagonal& model) { - add(JacobianFactor::shared_ptr(new JacobianFactor(key1,A1,b,model))); + add(JacobianFactor(key1,A1,b,model)); } /** Add a binary factor */ void add(Index key1, const Matrix& A1, Index key2, const Matrix& A2, const Vector& b, const SharedDiagonal& model) { - add(JacobianFactor::shared_ptr(new JacobianFactor(key1,A1,key2,A2,b,model))); + add(JacobianFactor(key1,A1,key2,A2,b,model)); } /** Add a ternary factor */ @@ -118,13 +98,13 @@ namespace gtsam { Index key2, const Matrix& A2, Index key3, const Matrix& A3, const Vector& b, const SharedDiagonal& model) { - add(JacobianFactor::shared_ptr(new JacobianFactor(key1,A1,key2,A2,key3,A3,b,model))); + add(JacobianFactor(key1,A1,key2,A2,key3,A3,b,model)); } /** Add an n-ary factor */ void add(const std::vector > &terms, const Vector &b, const SharedDiagonal& model) { - add(JacobianFactor::shared_ptr(new JacobianFactor(terms,b,model))); + add(JacobianFactor(terms,b,model)); } /** @@ -134,6 +114,16 @@ namespace gtsam { typedef FastSet Keys; Keys keys() const; + + /** Eliminate the first \c n frontal variables, returning the resulting + * conditional and remaining factor graph - this is very inefficient for + * eliminating all variables, to do that use EliminationTree or + * JunctionTree. Note that this version simply calls + * FactorGraph::eliminateFrontals with EliminateQR as the + * eliminate function argument. + */ + std::pair eliminateFrontals(size_t nFrontals) const; + /** Permute the variables in the factors */ void permuteWithInverse(const Permutation& inversePermutation); @@ -151,9 +141,9 @@ namespace gtsam { } /** - * static function that combines two factor graphs - * @param const &lfg1 Linear factor graph - * @param const &lfg2 Linear factor graph + * Static function that combines two factor graphs. + * @param lfg1 Linear factor graph + * @param lfg2 Linear factor graph * @return a new combined factor graph */ static GaussianFactorGraph combine2(const GaussianFactorGraph& lfg1, @@ -180,15 +170,43 @@ namespace gtsam { Matrix sparseJacobian_() const; /** - * Return a dense \f$ m \times n \f$ Jacobian matrix, augmented with b - * with standard deviations are baked into A and b + * Return a dense \f$ [ \;A\;b\; ] \in \mathbb{R}^{m \times n+1} \f$ + * Jacobian matrix, augmented with b with the noise models baked + * into A and b. The negative log-likelihood is + * \f$ \frac{1}{2} \Vert Ax-b \Vert^2 \f$. See also + * GaussianFactorGraph::jacobian and GaussianFactorGraph::sparseJacobian. */ - Matrix denseJacobian() const; + Matrix augmentedJacobian() const; + + /** + * Return the dense Jacobian \f$ A \f$ and right-hand-side \f$ b \f$, + * with the noise models baked into A and b. The negative log-likelihood + * is \f$ \frac{1}{2} \Vert Ax-b \Vert^2 \f$. See also + * GaussianFactorGraph::augmentedJacobian and + * GaussianFactorGraph::sparseJacobian. + */ + std::pair jacobian() const; /** - * Return a dense \f$ n \times n \f$ Hessian matrix, augmented with \f$ A^T b \f$ + * Return a dense \f$ \Lambda \in \mathbb{R}^{n+1 \times n+1} \f$ Hessian + * matrix, augmented with the information vector \f$ \eta \f$. The + * augmented Hessian is + \f[ \left[ \begin{array}{ccc} + \Lambda & \eta \\ + \eta^T & c + \end{array} \right] \f] + and the negative log-likelihood is + \f$ \frac{1}{2} x^T \Lambda x + \eta^T x + c \f$. */ - Matrix denseHessian() const; + Matrix augmentedHessian() const; + + /** + * Return the dense Hessian \f$ \Lambda \f$ and information vector + * \f$ \eta \f$, with the noise models baked in. The negative log-likelihood + * is \frac{1}{2} x^T \Lambda x + \eta^T x + c. See also + * GaussianFactorGraph::augmentedHessian. + */ + std::pair hessian() const; private: /** Serialization function */ @@ -202,7 +220,7 @@ namespace gtsam { /** * Combine and eliminate several factors. - * \ingroup LinearSolving + * \addtogroup LinearSolving */ JacobianFactor::shared_ptr CombineJacobians( const FactorGraph& factors, @@ -223,7 +241,7 @@ namespace gtsam { * @param nrFrontals Number of frontal variables to eliminate. * @return The conditional and remaining factor - * \ingroup LinearSolving + * \addtogroup LinearSolving */ GaussianFactorGraph::EliminationResult EliminateJacobians(const FactorGraph< JacobianFactor>& factors, size_t nrFrontals = 1); @@ -238,7 +256,7 @@ namespace gtsam { * @param nrFrontals Number of frontal variables to eliminate. * @return The conditional and remaining factor - * \ingroup LinearSolving + * \addtogroup LinearSolving */ GaussianFactorGraph::EliminationResult EliminateQR(const FactorGraph< GaussianFactor>& factors, size_t nrFrontals = 1); @@ -260,7 +278,7 @@ namespace gtsam { * @param nrFrontals Number of frontal variables to eliminate. * @return The conditional and remaining factor - * \ingroup LinearSolving + * \addtogroup LinearSolving */ GaussianFactorGraph::EliminationResult EliminatePreferCholesky(const FactorGraph< GaussianFactor>& factors, size_t nrFrontals = 1); @@ -281,9 +299,59 @@ namespace gtsam { * @param nrFrontals Number of frontal variables to eliminate. * @return The conditional and remaining factor - * \ingroup LinearSolving + * \addtogroup LinearSolving */ GaussianFactorGraph::EliminationResult EliminateCholesky(const FactorGraph< GaussianFactor>& factors, size_t nrFrontals = 1); + /****** Linear Algebra Opeations ******/ + + /** return A*x */ + Errors operator*(const GaussianFactorGraph& fg, const VectorValues& x); + + /** In-place version e <- A*x that overwrites e. */ + void multiplyInPlace(const GaussianFactorGraph& fg, const VectorValues& x, Errors& e); + + /** In-place version e <- A*x that takes an iterator. */ + void multiplyInPlace(const GaussianFactorGraph& fg, const VectorValues& x, const Errors::iterator& e); + + /** x += alpha*A'*e */ + void transposeMultiplyAdd(const GaussianFactorGraph& fg, double alpha, const Errors& e, VectorValues& x); + + /** + * Compute the gradient of the energy function, + * \f$ \nabla_{x=x_0} \left\Vert \Sigma^{-1} A x - b \right\Vert^2 \f$, + * centered around \f$ x = x_0 \f$. + * The gradient is \f$ A^T(Ax-b) \f$. + * @param fg The Jacobian factor graph $(A,b)$ + * @param x0 The center about which to compute the gradient + * @return The gradient as a VectorValues + */ + VectorValues gradient(const GaussianFactorGraph& fg, const VectorValues& x0); + + /** + * Compute the gradient of the energy function, + * \f$ \nabla_{x=0} \left\Vert \Sigma^{-1} A x - b \right\Vert^2 \f$, + * centered around zero. + * The gradient is \f$ A^T(Ax-b) \f$. + * @param fg The Jacobian factor graph $(A,b)$ + * @param [output] g A VectorValues to store the gradient, which must be preallocated, see allocateVectorValues + * @return The gradient as a VectorValues + */ + void gradientAtZero(const GaussianFactorGraph& fg, VectorValues& g); + + /* matrix-vector operations */ + void residual(const GaussianFactorGraph& fg, const VectorValues &x, VectorValues &r); + void multiply(const GaussianFactorGraph& fg, const VectorValues &x, VectorValues &r); + void transposeMultiply(const GaussianFactorGraph& fg, const VectorValues &r, VectorValues &x); + + /** shared pointer version + * \todo Make this a member function - affects SubgraphPreconditioner */ + boost::shared_ptr gaussianErrors_(const GaussianFactorGraph& fg, const VectorValues& x); + + /** return A*x-b + * \todo Make this a member function - affects SubgraphPreconditioner */ + inline Errors gaussianErrors(const GaussianFactorGraph& fg, const VectorValues& x) { + return *gaussianErrors_(fg, x); } + } // namespace gtsam diff --git a/gtsam/linear/GaussianISAM.cpp b/gtsam/linear/GaussianISAM.cpp index 6207d6ac7..f78d8b3c3 100644 --- a/gtsam/linear/GaussianISAM.cpp +++ b/gtsam/linear/GaussianISAM.cpp @@ -10,7 +10,7 @@ * -------------------------------------------------------------------------- */ /** - * @file GaussianISAM + * @file GaussianISAM.cpp * @brief Linear ISAM only * @author Michael Kaess */ diff --git a/gtsam/linear/GaussianISAM.h b/gtsam/linear/GaussianISAM.h index af96d5317..2f35845b8 100644 --- a/gtsam/linear/GaussianISAM.h +++ b/gtsam/linear/GaussianISAM.h @@ -10,7 +10,7 @@ * -------------------------------------------------------------------------- */ /** - * @file GaussianISAM + * @file GaussianISAM.h * @brief Linear ISAM only * @author Michael Kaess */ @@ -48,20 +48,8 @@ public: /** Override update_internal to also keep track of variable dimensions. */ template void update_internal(const FACTORGRAPH& newFactors, Cliques& orphans) { - - Super::update_internal(newFactors, orphans, &EliminateQR); - - // update dimensions - BOOST_FOREACH(const typename FACTORGRAPH::sharedFactor& factor, newFactors) { - for(typename FACTORGRAPH::FactorType::const_iterator key = factor->begin(); key != factor->end(); ++key) { - if(*key >= dims_.size()) - dims_.resize(*key + 1); - if(dims_[*key] == 0) - dims_[*key] = factor->getDim(key); - else - assert(dims_[*key] == factor->getDim(key)); - } - } + Super::update_internal(newFactors, orphans, &EliminateQR); // TODO: why does this force QR? + update_dimensions(newFactors); } template @@ -70,11 +58,29 @@ public: this->update_internal(newFactors, orphans); } + template + inline void update_dimensions(const FACTORGRAPH& newFactors) { + BOOST_FOREACH(const typename FACTORGRAPH::sharedFactor& factor, newFactors) { + for(typename FACTORGRAPH::FactorType::const_iterator key = factor->begin(); key != factor->end(); ++key) { + if(*key >= dims_.size()) + dims_.resize(*key + 1); + if(dims_[*key] == 0) + dims_[*key] = factor->getDim(key); + else + assert(dims_[*key] == factor->getDim(key)); + } + } + } + void clear() { Super::clear(); dims_.clear(); } + // access + const Dims& dims() const { return dims_; } ///< Const access to dimensions structure + Dims& dims() { return dims_; } ///< non-const access to dimensions structure (advanced interface) + friend VectorValues optimize(const GaussianISAM&); /** return marginal on any variable as a factor, Bayes net, or mean/cov */ diff --git a/gtsam/linear/GaussianJunctionTree.h b/gtsam/linear/GaussianJunctionTree.h index 3d4227b93..b97998a12 100644 --- a/gtsam/linear/GaussianJunctionTree.h +++ b/gtsam/linear/GaussianJunctionTree.h @@ -35,7 +35,7 @@ namespace gtsam { * create a BayesTree. In both cases, you need to provide a basic * GaussianFactorGraph::Eliminate function that will be used to * - * \ingroup Multifrontal + * \addtogroup Multifrontal */ class GaussianJunctionTree: public JunctionTree { diff --git a/gtsam/linear/GaussianMultifrontalSolver.h b/gtsam/linear/GaussianMultifrontalSolver.h index 6adde1aa5..322aacfc6 100644 --- a/gtsam/linear/GaussianMultifrontalSolver.h +++ b/gtsam/linear/GaussianMultifrontalSolver.h @@ -100,6 +100,8 @@ public: * Compute the marginal joint over a set of variables, by integrating out * all of the other variables. This function returns the result as a factor * graph. + * + * NOTE: This function is limited to computing a joint on 2 variables */ GaussianFactorGraph::shared_ptr jointFactorGraph(const std::vector& js) const; @@ -116,7 +118,7 @@ public: * all of the other variables. This function returns the result as a mean * vector and covariance matrix. Compared to marginalCanonical, which * returns a GaussianConditional, this function back-substitutes the R factor - * to obtain the mean, then computes \Sigma = (R^T * R)^-1. + * to obtain the mean, then computes \f$ \Sigma = (R^T * R)^{-1} \f$. */ Matrix marginalCovariance(Index j) const; diff --git a/gtsam/linear/GaussianSequentialSolver.cpp b/gtsam/linear/GaussianSequentialSolver.cpp index b83926647..d3ff3146c 100644 --- a/gtsam/linear/GaussianSequentialSolver.cpp +++ b/gtsam/linear/GaussianSequentialSolver.cpp @@ -10,7 +10,7 @@ * -------------------------------------------------------------------------- */ /** - * @file SequentialSolver.cpp + * @file GaussianSequentialSolver.cpp * @author Richard Roberts * @date Oct 19, 2010 */ diff --git a/gtsam/linear/GaussianSequentialSolver.h b/gtsam/linear/GaussianSequentialSolver.h index 2fad97867..8fd8e2dbb 100644 --- a/gtsam/linear/GaussianSequentialSolver.h +++ b/gtsam/linear/GaussianSequentialSolver.h @@ -10,7 +10,7 @@ * -------------------------------------------------------------------------- */ /** - * @file SequentialSolver.h + * @file GaussianSequentialSolver.h * @brief Solves a GaussianFactorGraph (i.e. a sparse linear system) using sequential variable elimination. * @author Richard Roberts * @date Oct 19, 2010 @@ -115,7 +115,7 @@ public: * all of the other variables. This function returns the result as a mean * vector and covariance matrix. Compared to marginalCanonical, which * returns a GaussianConditional, this function back-substitutes the R factor - * to obtain the mean, then computes \Sigma = (R^T * R)^-1. + * to obtain the mean, then computes \f$ \Sigma = (R^T * R)^{-1} \f$. */ Matrix marginalCovariance(Index j) const; diff --git a/gtsam/linear/HessianFactor.cpp b/gtsam/linear/HessianFactor.cpp index b1f829005..e152738fb 100644 --- a/gtsam/linear/HessianFactor.cpp +++ b/gtsam/linear/HessianFactor.cpp @@ -28,6 +28,7 @@ #include #include #include +#include #include #include #include @@ -47,13 +48,7 @@ string SlotEntry::toString() const { /* ************************************************************************* */ void HessianFactor::assertInvariants() const { -#ifndef NDEBUG - // Check for non-finite values - for(size_t i=0; i<(size_t) matrix_.rows(); ++i) - for(size_t j=i; j<(size_t) matrix_.cols(); ++j) - if(!isfinite(matrix_(i,j))) - throw invalid_argument("HessianFactor contains non-finite matrix entries."); -#endif + GaussianFactor::assertInvariants(); // The base class checks for unique keys } /* ************************************************************************* */ @@ -188,7 +183,7 @@ HessianFactor::HessianFactor(const std::vector& js, const std::vector& factors, if (debug) cout << "Combining " << factors.size() << " factors" << endl; BOOST_FOREACH(const GaussianFactor::shared_ptr& factor, factors) { - shared_ptr hessian(boost::dynamic_pointer_cast(factor)); - if (hessian) - updateATA(*hessian, scatter); - else { - JacobianFactor::shared_ptr jacobianFactor(boost::dynamic_pointer_cast(factor)); - if (jacobianFactor) + if(factor) { + if(shared_ptr hessian = boost::dynamic_pointer_cast(factor)) + updateATA(*hessian, scatter); + else if(JacobianFactor::shared_ptr jacobianFactor = boost::dynamic_pointer_cast(factor)) updateATA(*jacobianFactor, scatter); else throw invalid_argument("GaussianFactor is neither Hessian nor Jacobian"); @@ -292,11 +285,11 @@ HessianFactor& HessianFactor::operator=(const HessianFactor& rhs) { } /* ************************************************************************* */ -void HessianFactor::print(const std::string& s) const { +void HessianFactor::print(const std::string& s, const IndexFormatter& formatter) const { cout << s << "\n"; cout << " keys: "; for(const_iterator key=this->begin(); key!=this->end(); ++key) - cout << *key << "(" << this->getDim(key) << ") "; + cout << formatter(*key) << "(" << this->getDim(key) << ") "; cout << "\n"; gtsam::print(Matrix(info_.range(0,info_.nBlocks(), 0,info_.nBlocks()).selfadjointView()), "Ab^T * Ab: "); } @@ -315,13 +308,8 @@ bool HessianFactor::equals(const GaussianFactor& lf, double tol) const { } /* ************************************************************************* */ -double HessianFactor::constantTerm() const { - return info_(this->size(), this->size())(0,0); -} - -/* ************************************************************************* */ -HessianFactor::constColumn HessianFactor::linearTerm() const { - return info_.rangeColumn(0, this->size(), this->size(), 0); +Matrix HessianFactor::computeInformation() const { + return info_.full().selfadjointView(); } /* ************************************************************************* */ @@ -345,7 +333,7 @@ void HessianFactor::updateATA(const HessianFactor& update, const Scatter& scatte // First build an array of slots tic(1, "slots"); - size_t slots[update.size()]; + size_t* slots = (size_t*)alloca(sizeof(size_t)*update.size()); // FIXME: alloca is bad, just ask Google. size_t slot = 0; BOOST_FOREACH(Index j, update) { slots[slot] = scatter.find(j)->second.slot; @@ -360,7 +348,6 @@ void HessianFactor::updateATA(const HessianFactor& update, const Scatter& scatte // Apply updates to the upper triangle tic(3, "update"); - assert(this->info_.nBlocks() - 1 == scatter.size()); for(size_t j2=0; j2info_.nBlocks()-1 : slots[j2]; for(size_t j1=0; j1<=j2; ++j1) { @@ -399,7 +386,7 @@ void HessianFactor::updateATA(const JacobianFactor& update, const Scatter& scatt // First build an array of slots tic(1, "slots"); - size_t slots[update.size()]; + size_t* slots = (size_t*)alloca(sizeof(size_t)*update.size()); // FIXME: alloca is bad, just ask Google. size_t slot = 0; BOOST_FOREACH(Index j, update) { slots[slot] = scatter.find(j)->second.slot; @@ -437,7 +424,6 @@ void HessianFactor::updateATA(const JacobianFactor& update, const Scatter& scatt // Apply updates to the upper triangle tic(3, "update"); - assert(this->info_.nBlocks() - 1 == scatter.size()); for(size_t j2=0; j2info_.nBlocks()-1 : slots[j2]; for(size_t j1=0; j1<=j2; ++j1) { @@ -468,7 +454,8 @@ void HessianFactor::updateATA(const JacobianFactor& update, const Scatter& scatt /* ************************************************************************* */ void HessianFactor::partialCholesky(size_t nrFrontals) { - choleskyPartial(matrix_, info_.offset(nrFrontals)); + if(!choleskyPartial(matrix_, info_.offset(nrFrontals))) + throw IndeterminantLinearSystemException(this->keys().front()); } /* ************************************************************************* */ @@ -506,4 +493,24 @@ GaussianConditional::shared_ptr HessianFactor::splitEliminatedFactor(size_t nrFr return conditional; } +/* ************************************************************************* */ +GaussianFactor::shared_ptr HessianFactor::negate() const { + // Copy Hessian Blocks from Hessian factor and invert + std::vector js; + std::vector Gs; + std::vector gs; + double f; + js.insert(js.end(), begin(), end()); + for(size_t i = 0; i < js.size(); ++i){ + for(size_t j = i; j < js.size(); ++j){ + Gs.push_back( -info(begin()+i, begin()+j) ); + } + gs.push_back( -linearTerm(begin()+i) ); + } + f = -constantTerm(); + + // Create the Anti-Hessian Factor from the negated blocks + return HessianFactor::shared_ptr(new HessianFactor(js, Gs, gs, f)); +} + } // gtsam diff --git a/gtsam/linear/HessianFactor.h b/gtsam/linear/HessianFactor.h index d6ff23159..9e4ed2074 100644 --- a/gtsam/linear/HessianFactor.h +++ b/gtsam/linear/HessianFactor.h @@ -1,309 +1,366 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) - - * See LICENSE for the license information - - * -------------------------------------------------------------------------- */ - -/** - * @file HessianFactor.h - * @brief Contains the HessianFactor class, a general quadratic factor - * @author Richard Roberts - * @date Dec 8, 2010 - */ - -#pragma once - -#include -#include -#include - -// Forward declarations for friend unit tests -class ConversionConstructorHessianFactorTest; -class Constructor1HessianFactorTest; -class Constructor1bHessianFactorTest; -class combineHessianFactorTest; - - -namespace gtsam { - - // Forward declarations - class JacobianFactor; - class SharedDiagonal; - class GaussianConditional; - template class BayesNet; - - // Definition of Scatter, which is an intermediate data structure used when - // building a HessianFactor incrementally, to get the keys in the right - // order. - struct SlotEntry { - size_t slot; - size_t dimension; - SlotEntry(size_t _slot, size_t _dimension) - : slot(_slot), dimension(_dimension) {} - std::string toString() const; - }; - typedef FastMap Scatter; - - /** - * @brief A Gaussian factor using the canonical parameters (information form) - * - * HessianFactor implements a general quadratic factor of the form - * \f[ E(x) = 0.5 x^T G x - x^T g + 0.5 f \f] - * that stores the matrix \f$ G \f$, the vector \f$ g \f$, and the constant term \f$ f \f$. - * - * When \f$ G \f$ is positive semidefinite, this factor represents a Gaussian, - * in which case \f$ G \f$ is the information matrix \f$ \Lambda \f$, - * \f$ g \f$ is the information vector \f$ \eta \f$, and \f$ f \f$ is the residual - * sum-square-error at the mean, when \f$ x = \mu \f$. - * - * Indeed, the negative log-likelihood of a Gaussian is (up to a constant) - * @f$ E(x) = 0.5(x-\mu)^T P^{-1} (x-\mu) @f$ - * with @f$ \mu @f$ the mean and @f$ P @f$ the covariance matrix. Expanding the product we get - * @f[ - * E(x) = 0.5 x^T P^{-1} x - x^T P^{-1} \mu + 0.5 \mu^T P^{-1} \mu - * @f] - * We define the Information matrix (or Hessian) @f$ \Lambda = P^{-1} @f$ - * and the information vector @f$ \eta = P^{-1} \mu = \Lambda \mu @f$ - * to arrive at the canonical form of the Gaussian: - * @f[ - * E(x) = 0.5 x^T \Lambda x - x^T \eta + 0.5 \mu^T \Lambda \mu - * @f] - * - * This factor is one of the factors that can be in a GaussianFactorGraph. - * It may be returned from NonlinearFactor::linearize(), but is also - * used internally to store the Hessian during Cholesky elimination. - * - * This can represent a quadratic factor with characteristics that cannot be - * represented using a JacobianFactor (which has the form - * \f$ E(x) = \Vert Ax - b \Vert^2 \f$ and stores the Jacobian \f$ A \f$ - * and error vector \f$ b \f$, i.e. is a sum-of-squares factor). For example, - * a HessianFactor need not be positive semidefinite, it can be indefinite or - * even negative semidefinite. - * - * If a HessianFactor is indefinite or negative semi-definite, then in order - * for solving the linear system to be possible, - * the Hessian of the full system must be positive definite (i.e. when all - * small Hessians are combined, the result must be positive definite). If - * this is not the case, an error will occur during elimination. - * - * This class stores G, g, and f as an augmented matrix HessianFactor::matrix_. - * The upper-left n x n blocks of HessianFactor::matrix_ store the upper-right - * triangle of G, the upper-right-most column of length n of HessianFactor::matrix_ - * stores g, and the lower-right entry of HessianFactor::matrix_ stores f, i.e. - * \code - HessianFactor::matrix_ = [ G11 G12 G13 ... g1 - 0 G22 G23 ... g2 - 0 0 G33 ... g3 - : : : : - 0 0 0 ... f ] - \endcode - Blocks can be accessed as follows: - \code - G11 = info(begin(), begin()); - G12 = info(begin(), begin()+1); - G23 = info(begin()+1, begin()+2); - g2 = linearTerm(begin()+1); - f = constantTerm(); - ....... - \endcode - */ - class HessianFactor : public GaussianFactor { - protected: - typedef Matrix InfoMatrix; ///< The full augmented Hessian - typedef SymmetricBlockView BlockInfo; ///< A blockwise view of the Hessian - typedef GaussianFactor Base; ///< Typedef to base class - - InfoMatrix matrix_; ///< The full augmented information matrix, s.t. the quadratic error is 0.5*[x -1]'*H*[x -1] - BlockInfo info_; ///< The block view of the full information matrix. - - /** Update the factor by adding the information from the JacobianFactor - * (used internally during elimination). - * @param update The JacobianFactor containing the new information to add - * @param scatter A mapping from variable index to slot index in this HessianFactor - */ - void updateATA(const JacobianFactor& update, const Scatter& scatter); - - /** Update the factor by adding the information from the HessianFactor - * (used internally during elimination). - * @param update The HessianFactor containing the new information to add - * @param scatter A mapping from variable index to slot index in this HessianFactor - */ - void updateATA(const HessianFactor& update, const Scatter& scatter); - - public: - - typedef boost::shared_ptr shared_ptr; ///< A shared_ptr to this - typedef BlockInfo::Block Block; ///< A block from the Hessian matrix - typedef BlockInfo::constBlock constBlock; ///< A block from the Hessian matrix (const version) - typedef BlockInfo::Column Column; ///< A column containing the linear term h - typedef BlockInfo::constColumn constColumn; ///< A column containing the linear term h (const version) - - /** Copy constructor */ - HessianFactor(const HessianFactor& gf); - - /** default constructor for I/O */ - HessianFactor(); - - /** Construct a unary factor. G is the quadratic term (Hessian matrix), g - * the linear term (a vector), and f the constant term. The quadratic - * error is: - * 0.5*(f - 2*x'*g + x'*G*x) - */ - HessianFactor(Index j, const Matrix& G, const Vector& g, double f); - - /** Construct a unary factor, given a mean and covariance matrix. - * error is 0.5*(x-mu)'*inv(Sigma)*(x-mu) - */ - HessianFactor(Index j, const Vector& mu, const Matrix& Sigma); - - /** Construct a binary factor. Gxx are the upper-triangle blocks of the - * quadratic term (the Hessian matrix), gx the pieces of the linear vector - * term, and f the constant term. - * JacobianFactor error is \f[ 0.5* (Ax-b)' M (Ax-b) = 0.5*x'A'MAx - x'A'Mb + 0.5*b'Mb \f] - * HessianFactor error is \f[ 0.5*(x'Gx - 2x'g + f) = 0.5*x'Gx - x'*g + 0.5*f \f] - * So, with \f$ A = [A1 A2] \f$ and \f$ G=A*'M*A = [A1';A2']*M*[A1 A2] \f$ we have - \code - n1*n1 G11 = A1'*M*A1 - n1*n2 G12 = A1'*M*A2 - n2*n2 G22 = A2'*M*A2 - n1*1 g1 = A1'*M*b - n2*1 g2 = A2'*M*b - 1*1 f = b'*M*b - \endcode - */ - HessianFactor(Index j1, Index j2, - const Matrix& G11, const Matrix& G12, const Vector& g1, - const Matrix& G22, const Vector& g2, double f); - - /** Construct a ternary factor. Gxx are the upper-triangle blocks of the - * quadratic term (the Hessian matrix), gx the pieces of the linear vector - * term, and f the constant term. - */ - HessianFactor(Index j1, Index j2, Index j3, - const Matrix& G11, const Matrix& G12, const Matrix& G13, const Vector& g1, - const Matrix& G22, const Matrix& G23, const Vector& g2, - const Matrix& G33, const Vector& g3, double f); - - /** Construct an n-way factor. Gs contains the upper-triangle blocks of the - * quadratic term (the Hessian matrix) provided in row-order, gs the pieces - * of the linear vector term, and f the constant term. - */ - HessianFactor(const std::vector& js, const std::vector& Gs, - const std::vector& gs, double f); - - /** Construct from Conditional Gaussian */ - HessianFactor(const GaussianConditional& cg); - - /** Convert from a JacobianFactor (computes A^T * A) or HessianFactor */ - HessianFactor(const GaussianFactor& factor); - - /** Special constructor used in EliminateCholesky which combines the given factors */ - HessianFactor(const FactorGraph& factors, - const std::vector& dimensions, const Scatter& scatter); - - /** Destructor */ - virtual ~HessianFactor() {} - - /** Aassignment operator */ - HessianFactor& operator=(const HessianFactor& rhs); - - /** Clone this JacobianFactor */ - virtual GaussianFactor::shared_ptr clone() const { - return boost::static_pointer_cast( - shared_ptr(new HessianFactor(*this))); - } - - /** Print the factor for debugging and testing (implementing Testable) */ - virtual void print(const std::string& s = "") const; - - /** Compare to another factor for testing (implementing Testable) */ - virtual bool equals(const GaussianFactor& lf, double tol = 1e-9) const; - - /** Evaluate the factor error f(x), see above. */ - virtual double error(const VectorValues& c) const; /** 0.5*[x -1]'*H*[x -1] (also see constructor documentation) */ - - /** Return the dimension of the variable pointed to by the given key iterator - * todo: Remove this in favor of keeping track of dimensions with variables? - * @param variable An iterator pointing to the slot in this factor. You can - * use, for example, begin() + 2 to get the 3rd variable in this factor. - */ - virtual size_t getDim(const_iterator variable) const { return info_(variable-this->begin(), 0).rows(); } - - /** Return the number of columns and rows of the Hessian matrix */ - size_t rows() const { return info_.rows(); } - - /** Return a view of the block at (j1,j2) of the upper-triangular part of the - * information matrix \f$ H \f$, no data is copied. See HessianFactor class documentation - * above to explain that only the upper-triangular part of the information matrix is stored - * and returned by this function. - * @param j1 Which block row to get, as an iterator pointing to the slot in this factor. You can - * use, for example, begin() + 2 to get the 3rd variable in this factor. - * @param j2 Which block column to get, as an iterator pointing to the slot in this factor. You can - * use, for example, begin() + 2 to get the 3rd variable in this factor. - * @return A view of the requested block, not a copy. - */ - constBlock info(const_iterator j1, const_iterator j2) const { return info_(j1-begin(), j2-begin()); } - - /** Return the upper-triangular part of the full *augmented* information matrix, - * as described above. See HessianFactor class documentation above to explain that only the - * upper-triangular part of the information matrix is stored and returned by this function. - */ - constBlock info() const { return info_.full(); } - - /** Return the constant term \f$ f \f$ as described above - * @return The constant term \f$ f \f$ - */ - double constantTerm() const; - - /** Return the part of linear term \f$ g \f$ as described above corresponding to the requested variable. - * @param j Which block row to get, as an iterator pointing to the slot in this factor. You can - * use, for example, begin() + 2 to get the 3rd variable in this factor. - * @return The linear term \f$ g \f$ */ - constColumn linearTerm(const_iterator j) const { return info_.column(j-begin(), size(), 0); } - - /** Return the complete linear term \f$ g \f$ as described above. - * @return The linear term \f$ g \f$ */ - constColumn linearTerm() const; - - // Friend unit test classes - friend class ::ConversionConstructorHessianFactorTest; - friend class ::Constructor1HessianFactorTest; - friend class ::Constructor1bHessianFactorTest; - friend class ::combineHessianFactorTest; - - // Friend JacobianFactor for conversion - friend class JacobianFactor; - - // used in eliminateCholesky: - - /** - * Do Cholesky. Note that after this, the lower triangle still contains - * some untouched non-zeros that should be zero. We zero them while - * extracting submatrices in splitEliminatedFactor. Frank says :-( - */ - void partialCholesky(size_t nrFrontals); - - /** split partially eliminated factor */ - boost::shared_ptr splitEliminatedFactor(size_t nrFrontals); - - /** assert invariants */ - void assertInvariants() const; - - private: - /** Serialization function */ - friend class boost::serialization::access; - template - void serialize(ARCHIVE & ar, const unsigned int version) { - ar & BOOST_SERIALIZATION_BASE_OBJECT_NVP(GaussianFactor); - ar & BOOST_SERIALIZATION_NVP(info_); - ar & BOOST_SERIALIZATION_NVP(matrix_); - } - }; - -} - +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file HessianFactor.h + * @brief Contains the HessianFactor class, a general quadratic factor + * @author Richard Roberts + * @date Dec 8, 2010 + */ + +#pragma once + +#include +#include +#include + +// Forward declarations for friend unit tests +class ConversionConstructorHessianFactorTest; +class Constructor1HessianFactorTest; +class Constructor1bHessianFactorTest; +class combineHessianFactorTest; + + +namespace gtsam { + + // Forward declarations + class JacobianFactor; + class GaussianConditional; + template class BayesNet; + + // Definition of Scatter, which is an intermediate data structure used when + // building a HessianFactor incrementally, to get the keys in the right + // order. + struct SlotEntry { + size_t slot; + size_t dimension; + SlotEntry(size_t _slot, size_t _dimension) + : slot(_slot), dimension(_dimension) {} + std::string toString() const; + }; + typedef FastMap Scatter; + + /** + * @brief A Gaussian factor using the canonical parameters (information form) + * + * HessianFactor implements a general quadratic factor of the form + * \f[ E(x) = 0.5 x^T G x - x^T g + 0.5 f \f] + * that stores the matrix \f$ G \f$, the vector \f$ g \f$, and the constant term \f$ f \f$. + * + * When \f$ G \f$ is positive semidefinite, this factor represents a Gaussian, + * in which case \f$ G \f$ is the information matrix \f$ \Lambda \f$, + * \f$ g \f$ is the information vector \f$ \eta \f$, and \f$ f \f$ is the residual + * sum-square-error at the mean, when \f$ x = \mu \f$. + * + * Indeed, the negative log-likelihood of a Gaussian is (up to a constant) + * @f$ E(x) = 0.5(x-\mu)^T P^{-1} (x-\mu) @f$ + * with @f$ \mu @f$ the mean and @f$ P @f$ the covariance matrix. Expanding the product we get + * @f[ + * E(x) = 0.5 x^T P^{-1} x - x^T P^{-1} \mu + 0.5 \mu^T P^{-1} \mu + * @f] + * We define the Information matrix (or Hessian) @f$ \Lambda = P^{-1} @f$ + * and the information vector @f$ \eta = P^{-1} \mu = \Lambda \mu @f$ + * to arrive at the canonical form of the Gaussian: + * @f[ + * E(x) = 0.5 x^T \Lambda x - x^T \eta + 0.5 \mu^T \Lambda \mu + * @f] + * + * This factor is one of the factors that can be in a GaussianFactorGraph. + * It may be returned from NonlinearFactor::linearize(), but is also + * used internally to store the Hessian during Cholesky elimination. + * + * This can represent a quadratic factor with characteristics that cannot be + * represented using a JacobianFactor (which has the form + * \f$ E(x) = \Vert Ax - b \Vert^2 \f$ and stores the Jacobian \f$ A \f$ + * and error vector \f$ b \f$, i.e. is a sum-of-squares factor). For example, + * a HessianFactor need not be positive semidefinite, it can be indefinite or + * even negative semidefinite. + * + * If a HessianFactor is indefinite or negative semi-definite, then in order + * for solving the linear system to be possible, + * the Hessian of the full system must be positive definite (i.e. when all + * small Hessians are combined, the result must be positive definite). If + * this is not the case, an error will occur during elimination. + * + * This class stores G, g, and f as an augmented matrix HessianFactor::matrix_. + * The upper-left n x n blocks of HessianFactor::matrix_ store the upper-right + * triangle of G, the upper-right-most column of length n of HessianFactor::matrix_ + * stores g, and the lower-right entry of HessianFactor::matrix_ stores f, i.e. + * \code + HessianFactor::matrix_ = [ G11 G12 G13 ... g1 + 0 G22 G23 ... g2 + 0 0 G33 ... g3 + : : : : + 0 0 0 ... f ] + \endcode + Blocks can be accessed as follows: + \code + G11 = info(begin(), begin()); + G12 = info(begin(), begin()+1); + G23 = info(begin()+1, begin()+2); + g2 = linearTerm(begin()+1); + f = constantTerm(); + ....... + \endcode + */ + class HessianFactor : public GaussianFactor { + protected: + typedef Matrix InfoMatrix; ///< The full augmented Hessian + typedef SymmetricBlockView BlockInfo; ///< A blockwise view of the Hessian + typedef GaussianFactor Base; ///< Typedef to base class + + InfoMatrix matrix_; ///< The full augmented information matrix, s.t. the quadratic error is 0.5*[x -1]'*H*[x -1] + BlockInfo info_; ///< The block view of the full information matrix. + + public: + + typedef boost::shared_ptr shared_ptr; ///< A shared_ptr to this + typedef BlockInfo::Block Block; ///< A block from the Hessian matrix + typedef BlockInfo::constBlock constBlock; ///< A block from the Hessian matrix (const version) + typedef BlockInfo::Column Column; ///< A column containing the linear term h + typedef BlockInfo::constColumn constColumn; ///< A column containing the linear term h (const version) + + /** Copy constructor */ + HessianFactor(const HessianFactor& gf); + + /** default constructor for I/O */ + HessianFactor(); + + /** Construct a unary factor. G is the quadratic term (Hessian matrix), g + * the linear term (a vector), and f the constant term. The quadratic + * error is: + * 0.5*(f - 2*x'*g + x'*G*x) + */ + HessianFactor(Index j, const Matrix& G, const Vector& g, double f); + + /** Construct a unary factor, given a mean and covariance matrix. + * error is 0.5*(x-mu)'*inv(Sigma)*(x-mu) + */ + HessianFactor(Index j, const Vector& mu, const Matrix& Sigma); + + /** Construct a binary factor. Gxx are the upper-triangle blocks of the + * quadratic term (the Hessian matrix), gx the pieces of the linear vector + * term, and f the constant term. + * JacobianFactor error is \f[ 0.5* (Ax-b)' M (Ax-b) = 0.5*x'A'MAx - x'A'Mb + 0.5*b'Mb \f] + * HessianFactor error is \f[ 0.5*(x'Gx - 2x'g + f) = 0.5*x'Gx - x'*g + 0.5*f \f] + * So, with \f$ A = [A1 A2] \f$ and \f$ G=A*'M*A = [A1';A2']*M*[A1 A2] \f$ we have + \code + n1*n1 G11 = A1'*M*A1 + n1*n2 G12 = A1'*M*A2 + n2*n2 G22 = A2'*M*A2 + n1*1 g1 = A1'*M*b + n2*1 g2 = A2'*M*b + 1*1 f = b'*M*b + \endcode + */ + HessianFactor(Index j1, Index j2, + const Matrix& G11, const Matrix& G12, const Vector& g1, + const Matrix& G22, const Vector& g2, double f); + + /** Construct a ternary factor. Gxx are the upper-triangle blocks of the + * quadratic term (the Hessian matrix), gx the pieces of the linear vector + * term, and f the constant term. + */ + HessianFactor(Index j1, Index j2, Index j3, + const Matrix& G11, const Matrix& G12, const Matrix& G13, const Vector& g1, + const Matrix& G22, const Matrix& G23, const Vector& g2, + const Matrix& G33, const Vector& g3, double f); + + /** Construct an n-way factor. Gs contains the upper-triangle blocks of the + * quadratic term (the Hessian matrix) provided in row-order, gs the pieces + * of the linear vector term, and f the constant term. + */ + HessianFactor(const std::vector& js, const std::vector& Gs, + const std::vector& gs, double f); + + /** Construct from Conditional Gaussian */ + explicit HessianFactor(const GaussianConditional& cg); + + /** Convert from a JacobianFactor (computes A^T * A) or HessianFactor */ + explicit HessianFactor(const GaussianFactor& factor); + + /** Special constructor used in EliminateCholesky which combines the given factors */ + HessianFactor(const FactorGraph& factors, + const std::vector& dimensions, const Scatter& scatter); + + /** Destructor */ + virtual ~HessianFactor() {} + + /** Aassignment operator */ + HessianFactor& operator=(const HessianFactor& rhs); + + /** Clone this JacobianFactor */ + virtual GaussianFactor::shared_ptr clone() const { + return boost::static_pointer_cast( + shared_ptr(new HessianFactor(*this))); + } + + /** Print the factor for debugging and testing (implementing Testable) */ + virtual void print(const std::string& s = "", + const IndexFormatter& formatter = DefaultIndexFormatter) const; + + /** Compare to another factor for testing (implementing Testable) */ + virtual bool equals(const GaussianFactor& lf, double tol = 1e-9) const; + + /** Evaluate the factor error f(x), see above. */ + virtual double error(const VectorValues& c) const; /** 0.5*[x -1]'*H*[x -1] (also see constructor documentation) */ + + /** Return the dimension of the variable pointed to by the given key iterator + * todo: Remove this in favor of keeping track of dimensions with variables? + * @param variable An iterator pointing to the slot in this factor. You can + * use, for example, begin() + 2 to get the 3rd variable in this factor. + */ + virtual size_t getDim(const_iterator variable) const { return info_(variable-this->begin(), 0).rows(); } + + /** Return the number of columns and rows of the Hessian matrix */ + size_t rows() const { return info_.rows(); } + + /** + * Construct the corresponding anti-factor to negate information + * stored stored in this factor. + * @return a HessianFactor with negated Hessian matrices + */ + virtual GaussianFactor::shared_ptr negate() const; + + /** Return a view of the block at (j1,j2) of the upper-triangular part of the + * information matrix \f$ H \f$, no data is copied. See HessianFactor class documentation + * above to explain that only the upper-triangular part of the information matrix is stored + * and returned by this function. + * @param j1 Which block row to get, as an iterator pointing to the slot in this factor. You can + * use, for example, begin() + 2 to get the 3rd variable in this factor. + * @param j2 Which block column to get, as an iterator pointing to the slot in this factor. You can + * use, for example, begin() + 2 to get the 3rd variable in this factor. + * @return A view of the requested block, not a copy. + */ + constBlock info(const_iterator j1, const_iterator j2) const { return info_(j1-begin(), j2-begin()); } + + /** Return a view of the block at (j1,j2) of the upper-triangular part of the + * information matrix \f$ H \f$, no data is copied. See HessianFactor class documentation + * above to explain that only the upper-triangular part of the information matrix is stored + * and returned by this function. + * @param j1 Which block row to get, as an iterator pointing to the slot in this factor. You can + * use, for example, begin() + 2 to get the 3rd variable in this factor. + * @param j2 Which block column to get, as an iterator pointing to the slot in this factor. You can + * use, for example, begin() + 2 to get the 3rd variable in this factor. + * @return A view of the requested block, not a copy. + */ + Block info(iterator j1, iterator j2) { return info_(j1-begin(), j2-begin()); } + + /** Return the upper-triangular part of the full *augmented* information matrix, + * as described above. See HessianFactor class documentation above to explain that only the + * upper-triangular part of the information matrix is stored and returned by this function. + */ + constBlock info() const { return info_.full(); } + + /** Return the upper-triangular part of the full *augmented* information matrix, + * as described above. See HessianFactor class documentation above to explain that only the + * upper-triangular part of the information matrix is stored and returned by this function. + */ + Block info() { return info_.full(); } + + /** Return the constant term \f$ f \f$ as described above + * @return The constant term \f$ f \f$ + */ + double constantTerm() const { return info_(this->size(), this->size())(0,0); } + + /** Return the constant term \f$ f \f$ as described above + * @return The constant term \f$ f \f$ + */ + double& constantTerm() { return info_(this->size(), this->size())(0,0); } + + /** Return the part of linear term \f$ g \f$ as described above corresponding to the requested variable. + * @param j Which block row to get, as an iterator pointing to the slot in this factor. You can + * use, for example, begin() + 2 to get the 3rd variable in this factor. + * @return The linear term \f$ g \f$ */ + constColumn linearTerm(const_iterator j) const { return info_.column(j-begin(), size(), 0); } + + /** Return the part of linear term \f$ g \f$ as described above corresponding to the requested variable. + * @param j Which block row to get, as an iterator pointing to the slot in this factor. You can + * use, for example, begin() + 2 to get the 3rd variable in this factor. + * @return The linear term \f$ g \f$ */ + Column linearTerm(iterator j) { return info_.column(j-begin(), size(), 0); } + + /** Return the complete linear term \f$ g \f$ as described above. + * @return The linear term \f$ g \f$ */ + constColumn linearTerm() const { return info_.rangeColumn(0, this->size(), this->size(), 0); } + + /** Return the complete linear term \f$ g \f$ as described above. + * @return The linear term \f$ g \f$ */ + Column linearTerm() { return info_.rangeColumn(0, this->size(), this->size(), 0); } + + /** Return the augmented information matrix represented by this GaussianFactor. + * The augmented information matrix contains the information matrix with an + * additional column holding the information vector, and an additional row + * holding the transpose of the information vector. The lower-right entry + * contains the constant error term (when \f$ \delta x = 0 \f$). The + * augmented information matrix is described in more detail in HessianFactor, + * which in fact stores an augmented information matrix. + * + * For HessianFactor, this is the same as info() except that this function + * returns a complete symmetric matrix whereas info() returns a matrix where + * only the upper triangle is valid, but should be interpreted as symmetric. + * This is because info() returns only a reference to the internal + * representation of the augmented information matrix, which stores only the + * upper triangle. + */ + virtual Matrix computeInformation() const; + + // Friend unit test classes + friend class ::ConversionConstructorHessianFactorTest; + friend class ::Constructor1HessianFactorTest; + friend class ::Constructor1bHessianFactorTest; + friend class ::combineHessianFactorTest; + + // Friend JacobianFactor for conversion + friend class JacobianFactor; + + // used in eliminateCholesky: + + /** + * Do Cholesky. Note that after this, the lower triangle still contains + * some untouched non-zeros that should be zero. We zero them while + * extracting submatrices in splitEliminatedFactor. Frank says :-( + */ + void partialCholesky(size_t nrFrontals); + + /** split partially eliminated factor */ + boost::shared_ptr splitEliminatedFactor(size_t nrFrontals); + + /** Update the factor by adding the information from the JacobianFactor + * (used internally during elimination). + * @param update The JacobianFactor containing the new information to add + * @param scatter A mapping from variable index to slot index in this HessianFactor + */ + void updateATA(const JacobianFactor& update, const Scatter& scatter); + + /** Update the factor by adding the information from the HessianFactor + * (used internally during elimination). + * @param update The HessianFactor containing the new information to add + * @param scatter A mapping from variable index to slot index in this HessianFactor + */ + void updateATA(const HessianFactor& update, const Scatter& scatter); + + /** assert invariants */ + void assertInvariants() const; + + private: + /** Serialization function */ + friend class boost::serialization::access; + template + void serialize(ARCHIVE & ar, const unsigned int version) { + ar & BOOST_SERIALIZATION_BASE_OBJECT_NVP(GaussianFactor); + ar & BOOST_SERIALIZATION_NVP(info_); + ar & BOOST_SERIALIZATION_NVP(matrix_); + } + }; + +} + diff --git a/gtsam/linear/IterativeOptimizationParameters.h b/gtsam/linear/IterativeOptimizationParameters.h deleted file mode 100644 index b38f6ab1a..000000000 --- a/gtsam/linear/IterativeOptimizationParameters.h +++ /dev/null @@ -1,232 +0,0 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) - - * See LICENSE for the license information - - * -------------------------------------------------------------------------- */ - -/** - * @file IterativeOptimizationParameters.h - * @date Oct 22, 2010 - * @author Yong-Dian Jian - */ - -#pragma once - -#include -#include -#include - -namespace gtsam { - -/* parameters for combinatorial preconditioner */ -struct CombinatorialParameters { - - enum Group { /* group of variables */ - BLOCK = 0, /* utilize the inherent block structure */ - SCALAR /* break the block variables into scalars */ - } group_; - - enum Type { /* subgraph specification */ - JACOBI = 0, /* block diagonal */ - SPTREE, /* spanning tree */ - GSP, /* gspn, n = 0: all factors, n = 1: all unary factors, n = 2: spanning tree, etc .. */ - KOUTIS, /* implement Koutis2011Focs */ - } type_; - - enum Weight { /* how to weigh the graph edges */ - EQUAL = 0, /* 0: every block edge has equal weight */ - RHS_2NORM, /* 1: use the 2-norm of the rhs */ - LHS_FNORM, /* 2: use the frobenius norm of the lhs */ - RAW, /* 3: use raw scalar weight for the scalar case */ - } weight_ ; - - int complexity_;/* a parameter for the subgraph complexity */ - int hessian_; /* 0: do nothing, 1: use whole block hessian */ - - CombinatorialParameters(): group_(BLOCK), type_(JACOBI), weight_(EQUAL), complexity_(0), hessian_(1) {} - CombinatorialParameters(Group group, Type type, Weight weight, int complexity, int hessian) - : group_(group), type_(type), weight_(weight), complexity_(complexity), hessian_(hessian) {} - - inline Group group() const { return group_; } - inline Type type() const { return type_; } - inline Weight weight() const { return weight_; } - inline int complexity() const { return complexity_; } - inline int hessian() const { return hessian_; } - - inline bool isScalar() const { return group_ == SCALAR; } - inline bool isBlock() const { return group_ == BLOCK; } - inline bool isStatic() const { return (type_ == JACOBI || weight_ == EQUAL) ? true : false;} - inline bool isDynamic() const { return !isStatic(); } - - inline void print() const { - - const std::string groupStr[2] = {"block", "scalar"}; - const std::string typeStr[4] = {"jacobi", "sptree", "gsp", "koutis"}; - const std::string weightStr[4] = {"equal", "rhs-2norm", "lhs-form", "raw"}; - - std::cout << "CombinatorialParameters: " - << "group = " << groupStr[group_] - << ", type = " << typeStr[type_] - << ", weight = " << weightStr[weight_] - << ", complexity = " << complexity_ - << ", hessian = " << hessian_ << std::endl; - } -}; - -/* parameters for the preconditioner */ -struct PreconditionerParameters { - - typedef boost::shared_ptr shared_ptr; - - enum Kernel { /* Preconditioner Kernel */ - GTSAM = 0, /* Jacobian Factor Graph of GTSAM */ - CHOLMOD /* Cholmod Sparse */ - } kernel_ ; - - enum Type { /* preconditioner type */ - Combinatorial = 0 /* combinatorial preconditioner */ - } type_; - - CombinatorialParameters combinatorial_; - - enum Verbosity { SILENT = 0, COMPLEXITY = 1, ERROR = 2} verbosity_ ; /* Verbosity */ - - PreconditionerParameters(): kernel_(CHOLMOD), type_(Combinatorial), verbosity_(SILENT) {} - PreconditionerParameters(Kernel kernel, const CombinatorialParameters &combinatorial, Verbosity verbosity) - : kernel_(kernel), type_(Combinatorial), combinatorial_(combinatorial), verbosity_(verbosity) {} - - /* general interface */ - inline Kernel kernel() const { return kernel_; } - inline Type type() const { return type_; } - inline const CombinatorialParameters & combinatorial() const { return combinatorial_; } - inline Verbosity verbosity() const { return verbosity_; } - - - void print() const { - const std::string kernelStr[2] = {"gtsam", "cholmod"}; - const std::string typeStr[1] = {"combinatorial"}; - - std::cout << "PreconditionerParameters: " - << "kernel = " << kernelStr[kernel_] - << ", type = " << typeStr[type_] << std::endl; - combinatorial_.print(); - } -}; - -/* parameters for the conjugate gradient method */ -struct ConjugateGradientParameters { - - size_t minIterations_; /* minimum number of cg iterations */ - size_t maxIterations_; /* maximum number of cg iterations */ - size_t reset_; /* number of iterations before reset */ - double epsilon_rel_; /* threshold for relative error decrease */ - double epsilon_abs_; /* threshold for absolute error decrease */ - - enum BLASKernel { /* Matrix Operation Kernel */ - GTSAM = 0, /* Jacobian Factor Graph of GTSAM */ - SBM, /* Sparse Block Matrix */ - SBM_MT /* Sparse Block Matrix Multithreaded */ - } blas_kernel_; - - size_t degree_; /* the maximum degree of the vertices to be eliminated before doing cg */ - - enum Verbosity { SILENT = 0, COMPLEXITY = 1, ERROR = 2} verbosity_ ; /* Verbosity */ - - ConjugateGradientParameters() - : minIterations_(1), maxIterations_(500), reset_(501), epsilon_rel_(1e-3), epsilon_abs_(1e-3), - blas_kernel_(GTSAM), degree_(0), verbosity_(SILENT) {} - - ConjugateGradientParameters(size_t minIterations, size_t maxIterations, size_t reset, - double epsilon_rel, double epsilon_abs, BLASKernel blas = GTSAM, size_t degree = 0, Verbosity verbosity = SILENT) - : minIterations_(minIterations), maxIterations_(maxIterations), reset_(reset), - epsilon_rel_(epsilon_rel), epsilon_abs_(epsilon_abs), blas_kernel_(blas), degree_(degree), verbosity_(verbosity) {} - - /* general interface */ - inline size_t minIterations() const { return minIterations_; } - inline size_t maxIterations() const { return maxIterations_; } - inline size_t reset() const { return reset_; } - inline double epsilon() const { return epsilon_rel_; } - inline double epsilon_rel() const { return epsilon_rel_; } - inline double epsilon_abs() const { return epsilon_abs_; } - inline BLASKernel blas_kernel() const { return blas_kernel_; } - inline size_t degree() const { return degree_; } - inline Verbosity verbosity() const { return verbosity_; } - - void print() const { - const std::string blasStr[4] = {"gtsam", "sbm", "sbm-mt"}; - std::cout << "ConjugateGradientParameters: " - << "blas = " << blasStr[blas_kernel_] - << ", minIter = " << minIterations_ - << ", maxIter = " << maxIterations_ - << ", resetIter = " << reset_ - << ", eps_rel = " << epsilon_rel_ - << ", eps_abs = " << epsilon_abs_ - << ", degree = " << degree_ - << std::endl; - } -}; - -/* parameters for iterative linear solvers */ -struct IterativeOptimizationParameters { - -public: - - typedef boost::shared_ptr shared_ptr; - - PreconditionerParameters preconditioner_; - ConjugateGradientParameters cg_; - enum Kernel { PCG = 0 /*, PCGPlus*/, LSPCG } kernel_ ; /* Iterative Method Kernel */ - enum Verbosity { SILENT = 0, COMPLEXITY = 1, ERROR = 2} verbosity_ ; /* Verbosity */ - -public: - - IterativeOptimizationParameters() - : preconditioner_(), cg_(), kernel_(PCG), verbosity_(SILENT) {} - - IterativeOptimizationParameters(const IterativeOptimizationParameters &p) : - preconditioner_(p.preconditioner_), cg_(p.cg_), kernel_(p.kernel_), verbosity_(p.verbosity_) {} - - IterativeOptimizationParameters( - const PreconditionerParameters &p, const ConjugateGradientParameters &c, Kernel kernel = PCG, Verbosity verbosity = SILENT) - : preconditioner_(p), cg_(c), kernel_(kernel), verbosity_(verbosity) {} - - /* general interface */ - inline Kernel kernel() const { return kernel_; } - inline Verbosity verbosity() const { return verbosity_; } - - /* utility */ - inline const PreconditionerParameters& preconditioner() const { return preconditioner_; } - inline const ConjugateGradientParameters& cg() const { return cg_; } - - /* interface to preconditioner parameters */ - inline PreconditionerParameters::Kernel preconditioner_kernel() const { return preconditioner_.kernel(); } - inline PreconditionerParameters::Type type() const { return preconditioner_.type(); } - - /* interface to cg parameters */ - inline size_t minIterations() const { return cg_.minIterations(); } - inline size_t maxIterations() const { return cg_.maxIterations(); } - inline size_t reset() const { return cg_.reset(); } - inline double epsilon() const { return cg_.epsilon_rel(); } - inline double epsilon_rel() const { return cg_.epsilon_rel(); } - inline double epsilon_abs() const { return cg_.epsilon_abs(); } - inline size_t degree() const { return cg_.degree(); } - inline ConjugateGradientParameters::BLASKernel blas_kernel() const { return cg_.blas_kernel(); } - - void print(const std::string &s="") const { - const std::string kernelStr[2] = {"pcg", "lspcg"}; - std::cout << s << std::endl - << "IterativeOptimizationParameters: " - << "kernel = " << kernelStr[kernel_] << std::endl; - cg_.print(); - preconditioner_.print(); - - } - -}; - -} diff --git a/gtsam/linear/IterativeSolver.cpp b/gtsam/linear/IterativeSolver.cpp new file mode 100644 index 000000000..2bba3e12b --- /dev/null +++ b/gtsam/linear/IterativeSolver.cpp @@ -0,0 +1,50 @@ +/** + * @file IterativeSolver.cpp + * @brief + * @date Sep 3, 2012 + * @author Yong-Dian Jian + */ + +#include +#include +#include + +namespace gtsam { + +std::string IterativeOptimizationParameters::getKernel() const { return kernelTranslator(kernel_); } +std::string IterativeOptimizationParameters::getVerbosity() const { return verbosityTranslator(verbosity_); } +void IterativeOptimizationParameters::setKernel(const std::string &src) { kernel_ = kernelTranslator(src); } +void IterativeOptimizationParameters::setVerbosity(const std::string &src) { verbosity_ = verbosityTranslator(src); } + +IterativeOptimizationParameters::Kernel IterativeOptimizationParameters::kernelTranslator(const std::string &src) { + std::string s = src; boost::algorithm::to_upper(s); + if (s == "CG") return IterativeOptimizationParameters::CG; + /* default is cg */ + else return IterativeOptimizationParameters::CG; +} + +IterativeOptimizationParameters::Verbosity IterativeOptimizationParameters::verbosityTranslator(const std::string &src) { + std::string s = src; boost::algorithm::to_upper(s); + if (s == "SILENT") return IterativeOptimizationParameters::SILENT; + else if (s == "COMPLEXITY") return IterativeOptimizationParameters::COMPLEXITY; + else if (s == "ERROR") return IterativeOptimizationParameters::ERROR; + /* default is default */ + else return IterativeOptimizationParameters::SILENT; +} + +std::string IterativeOptimizationParameters::kernelTranslator(IterativeOptimizationParameters::Kernel k) { + if ( k == CG ) return "CG"; + else return "UNKNOWN"; +} + +std::string IterativeOptimizationParameters::verbosityTranslator(IterativeOptimizationParameters::Verbosity verbosity) { + if (verbosity == SILENT) return "SILENT"; + else if (verbosity == COMPLEXITY) return "COMPLEXITY"; + else if (verbosity == ERROR) return "ERROR"; + else return "UNKNOWN"; +} + + +} + + diff --git a/gtsam/linear/IterativeSolver.h b/gtsam/linear/IterativeSolver.h index 7b1c1e630..7946874bb 100644 --- a/gtsam/linear/IterativeSolver.h +++ b/gtsam/linear/IterativeSolver.h @@ -9,44 +9,67 @@ * -------------------------------------------------------------------------- */ -/** - * @file IterativeSolver.h - * @date Oct 24, 2010 - * @author Yong-Dian Jian - * @brief Base Class for all iterative solvers of linear systems - */ - #pragma once -#include +#include #include -#include +#include namespace gtsam { -class IterativeSolver { + /** + * parameters for iterative linear solvers + */ + class IterativeOptimizationParameters { -public: + public: - typedef boost::shared_ptr shared_ptr; - typedef IterativeOptimizationParameters Parameters; + typedef boost::shared_ptr shared_ptr; + enum Kernel { CG = 0 } kernel_ ; ///< Iterative Method Kernel + enum Verbosity { SILENT = 0, COMPLEXITY, ERROR } verbosity_; -protected: + public: - Parameters::shared_ptr parameters_ ; + IterativeOptimizationParameters(const IterativeOptimizationParameters &p) + : kernel_(p.kernel_), verbosity_(p.verbosity_) {} -public: + IterativeOptimizationParameters(const Kernel kernel = CG, const Verbosity verbosity = SILENT) + : kernel_(kernel), verbosity_(verbosity) {} - IterativeSolver(): parameters_(new Parameters()) {} - IterativeSolver(const IterativeSolver &solver) : parameters_(solver.parameters_) {} - IterativeSolver(const Parameters::shared_ptr& parameters) : parameters_(parameters) {} - IterativeSolver(const Parameters ¶meters) : parameters_(new Parameters(parameters)) {} + virtual ~IterativeOptimizationParameters() {} - virtual ~IterativeSolver() {} + /* general interface */ + inline Kernel kernel() const { return kernel_; } + inline Verbosity verbosity() const { return verbosity_; } - virtual VectorValues::shared_ptr optimize () = 0; + /* matlab interface */ + std::string getKernel() const ; + std::string getVerbosity() const; + void setKernel(const std::string &s) ; + void setVerbosity(const std::string &s) ; - Parameters::shared_ptr parameters() { return parameters_ ; } -}; + void print() const { + std::cout << "IterativeOptimizationParameters: " + << "kernel = " << kernelTranslator(kernel_) + << ", verbosity = " << verbosityTranslator(verbosity_) << std::endl; + } + + static Kernel kernelTranslator(const std::string &s); + static Verbosity verbosityTranslator(const std::string &s); + static std::string kernelTranslator(Kernel k); + static std::string verbosityTranslator(Verbosity v); + }; + + class IterativeSolver { + public: + typedef boost::shared_ptr shared_ptr; + IterativeSolver() {} + virtual ~IterativeSolver() {} + + /* interface to the nonlinear optimizer */ + virtual VectorValues optimize () = 0; + /* update interface to the nonlinear optimizer */ + virtual void replaceFactors(const GaussianFactorGraph::shared_ptr &factorGraph, const double lambda) {} + }; } diff --git a/gtsam/linear/JacobianFactor.cpp b/gtsam/linear/JacobianFactor.cpp index e2facec40..759be4948 100644 --- a/gtsam/linear/JacobianFactor.cpp +++ b/gtsam/linear/JacobianFactor.cpp @@ -15,6 +15,7 @@ * @date Dec 8, 2010 */ +#include #include #include #include @@ -29,15 +30,16 @@ #include #include #include -#include -#include +#include +//#include +//#include #include #include #include using namespace std; -using namespace boost::lambda; +//using namespace boost::lambda; namespace gtsam { @@ -46,40 +48,48 @@ namespace gtsam { #ifndef NDEBUG GaussianFactor::assertInvariants(); // The base class checks for unique keys assert((size() == 0 && Ab_.rows() == 0 && Ab_.nBlocks() == 0) || size()+1 == Ab_.nBlocks()); - assert(firstNonzeroBlocks_.size() == Ab_.rows()); - for(size_t i=0; i(&gf)) + *this = JacobianFactor(*rhs); + else if(const HessianFactor* rhs = dynamic_cast(&gf)) + *this = JacobianFactor(*rhs); + else + throw std::invalid_argument("In JacobianFactor(const GaussianFactor& rhs), rhs is neither a JacobianFactor nor a HessianFactor"); + assertInvariants(); + } + /* ************************************************************************* */ JacobianFactor::JacobianFactor() : Ab_(matrix_) { assertInvariants(); } /* ************************************************************************* */ - JacobianFactor::JacobianFactor(const Vector& b_in) : firstNonzeroBlocks_(b_in.size(), 0), Ab_(matrix_) { + JacobianFactor::JacobianFactor(const Vector& b_in) : Ab_(matrix_) { size_t dims[] = { 1 }; Ab_.copyStructureFrom(BlockAb(matrix_, dims, dims+1, b_in.size())); getb() = b_in; + model_ = noiseModel::Unit::Create(this->rows()); assertInvariants(); } /* ************************************************************************* */ JacobianFactor::JacobianFactor(Index i1, const Matrix& A1, const Vector& b, const SharedDiagonal& model) : - GaussianFactor(i1), model_(model), firstNonzeroBlocks_(b.size(), 0), Ab_(matrix_) { + GaussianFactor(i1), model_(model), Ab_(matrix_) { + + if(model->dim() != (size_t) b.size()) + throw InvalidNoiseModel(b.size(), model->dim()); + size_t dims[] = { A1.cols(), 1}; Ab_.copyStructureFrom(BlockAb(matrix_, dims, dims+2, b.size())); Ab_(0) = A1; @@ -90,7 +100,11 @@ namespace gtsam { /* ************************************************************************* */ JacobianFactor::JacobianFactor(Index i1, const Matrix& A1, Index i2, const Matrix& A2, const Vector& b, const SharedDiagonal& model) : - GaussianFactor(i1,i2), model_(model), firstNonzeroBlocks_(b.size(), 0), Ab_(matrix_) { + GaussianFactor(i1,i2), model_(model), Ab_(matrix_) { + + if(model->dim() != (size_t) b.size()) + throw InvalidNoiseModel(b.size(), model->dim()); + size_t dims[] = { A1.cols(), A2.cols(), 1}; Ab_.copyStructureFrom(BlockAb(matrix_, dims, dims+3, b.size())); Ab_(0) = A1; @@ -102,7 +116,11 @@ namespace gtsam { /* ************************************************************************* */ JacobianFactor::JacobianFactor(Index i1, const Matrix& A1, Index i2, const Matrix& A2, Index i3, const Matrix& A3, const Vector& b, const SharedDiagonal& model) : - GaussianFactor(i1,i2,i3), model_(model), firstNonzeroBlocks_(b.size(), 0), Ab_(matrix_) { + GaussianFactor(i1,i2,i3), model_(model), Ab_(matrix_) { + + if(model->dim() != (size_t) b.size()) + throw InvalidNoiseModel(b.size(), model->dim()); + size_t dims[] = { A1.cols(), A2.cols(), A3.cols(), 1}; Ab_.copyStructureFrom(BlockAb(matrix_, dims, dims+4, b.size())); Ab_(0) = A1; @@ -116,9 +134,13 @@ namespace gtsam { JacobianFactor::JacobianFactor(const std::vector > &terms, const Vector &b, const SharedDiagonal& model) : GaussianFactor(GetKeys(terms.size(), terms.begin(), terms.end())), - model_(model), firstNonzeroBlocks_(b.size(), 0), Ab_(matrix_) + model_(model), Ab_(matrix_) { - size_t dims[terms.size()+1]; + + if(model->dim() != (size_t) b.size()) + throw InvalidNoiseModel(b.size(), model->dim()); + + size_t* dims = (size_t*)alloca(sizeof(size_t)*(terms.size()+1)); // FIXME: alloca is bad, just ask Google. for(size_t j=0; j > &terms, const Vector &b, const SharedDiagonal& model) : GaussianFactor(GetKeys(terms.size(), terms.begin(), terms.end())), - model_(model), firstNonzeroBlocks_(b.size(), 0), Ab_(matrix_) + model_(model), Ab_(matrix_) { - size_t dims[terms.size()+1]; + + if(model->dim() != (size_t) b.size()) + throw InvalidNoiseModel(b.size(), model->dim()); + + size_t* dims=(size_t*)alloca(sizeof(size_t)*(terms.size()+1)); // FIXME: alloca is bad, just ask Google. size_t j=0; std::list >::const_iterator term=terms.begin(); for(; term!=terms.end(); ++term,++j) @@ -150,9 +176,11 @@ namespace gtsam { } /* ************************************************************************* */ - JacobianFactor::JacobianFactor(const GaussianConditional& cg) : GaussianFactor(cg), model_(noiseModel::Diagonal::Sigmas(cg.get_sigmas(), true)), Ab_(matrix_) { + JacobianFactor::JacobianFactor(const GaussianConditional& cg) : + GaussianFactor(cg), + model_(noiseModel::Diagonal::Sigmas(cg.get_sigmas(), true)), + Ab_(matrix_) { Ab_.assignNoalias(cg.rsd_); - firstNonzeroBlocks_.resize(cg.get_d().size(), 0); // set sigmas from precisions assertInvariants(); } @@ -160,18 +188,16 @@ namespace gtsam { JacobianFactor::JacobianFactor(const HessianFactor& factor) : Ab_(matrix_) { keys_ = factor.keys_; Ab_.assignNoalias(factor.info_); + + // Do Cholesky to get a Jacobian size_t maxrank; - try { - maxrank = choleskyCareful(matrix_).first; - } catch(const CarefulCholeskyNegativeMatrixException& e) { - cout << - "Attempting to convert a HessianFactor to a JacobianFactor, but for this\n" - "HessianFactor it is not possible because either the Hessian is negative or\n" - "indefinite, or the quadratic error function it describes becomes negative for\n" - "some values. Here is the HessianFactor on which this conversion was attempted:\n"; - factor.print(""); - throw; - } + bool success; + boost::tie(maxrank, success) = choleskyCareful(matrix_); + + // Check for indefinite system + if(!success) + throw IndeterminantLinearSystemException(factor.keys().front()); + // Zero out lower triangle matrix_.topRows(maxrank).triangularView() = Matrix::Zero(maxrank, matrix_.cols()); @@ -179,23 +205,6 @@ namespace gtsam { Ab_.rowEnd() = maxrank; model_ = noiseModel::Unit::Create(maxrank); - firstNonzeroBlocks_.resize(this->rows(), 0); - - // Sort keys - set vars; - for(size_t j=0; jBase::operator=(rhs); // Copy keys model_ = rhs.model_; // Copy noise model - firstNonzeroBlocks_ = rhs.firstNonzeroBlocks_; // Copy staircase pattern Ab_.assignNoalias(rhs.Ab_); // Copy matrix and block structure assertInvariants(); return *this; } /* ************************************************************************* */ - void JacobianFactor::print(const string& s) const { + void JacobianFactor::print(const string& s, const IndexFormatter& formatter) const { cout << s << "\n"; if (empty()) { cout << " empty, keys: "; - BOOST_FOREACH(const Index& key, keys()) { cout << key << " "; } + BOOST_FOREACH(const Index& key, keys()) { cout << formatter(key) << " "; } cout << endl; } else { for(const_iterator key=begin(); key!=end(); ++key) - cout << boost::format("A[%1%]=\n")%*key << getA(key) << endl; + cout << boost::format("A[%1%]=\n")%formatter(*key) << getA(key) << endl; cout << "b=" << getb() << endl; model_->print("model"); } @@ -271,6 +279,12 @@ namespace gtsam { return 0.5 * weighted.dot(weighted); } + /* ************************************************************************* */ + Matrix JacobianFactor::computeInformation() const { + Matrix AbWhitened = Ab_.full(); + model_->WhitenInPlace(AbWhitened); + return AbWhitened.transpose() * AbWhitened; + } /* ************************************************************************* */ Vector JacobianFactor::operator*(const VectorValues& x) const { @@ -284,7 +298,6 @@ namespace gtsam { return model_->whiten(Ax); } - /* ************************************************************************* */ void JacobianFactor::transposeMultiplyAdd(double alpha, const Vector& e, VectorValues& x) const { @@ -345,11 +358,68 @@ namespace gtsam { return result; } + /* ************************************************************************* */ + GaussianFactor::shared_ptr JacobianFactor::negate() const { + HessianFactor hessian(*this); + return hessian.negate(); + } + /* ************************************************************************* */ GaussianConditional::shared_ptr JacobianFactor::eliminateFirst() { return this->eliminate(1); } + /* ************************************************************************* */ + GaussianConditional::shared_ptr JacobianFactor::splitConditional(size_t nrFrontals) { + assert(Ab_.rowStart() == 0 && Ab_.rowEnd() == (size_t) matrix_.rows() && Ab_.firstBlock() == 0); + assert(size() >= nrFrontals); + assertInvariants(); + + const bool debug = ISDEBUG("JacobianFactor::splitConditional"); + + if(debug) cout << "Eliminating " << nrFrontals << " frontal variables" << endl; + if(debug) this->print("Splitting JacobianFactor: "); + + size_t frontalDim = Ab_.range(0,nrFrontals).cols(); + + // Check for singular factor + if(model_->dim() < frontalDim) + throw IndeterminantLinearSystemException(this->keys().front()); + + // Extract conditional + tic(3, "cond Rd"); + + // Restrict the matrix to be in the first nrFrontals variables + Ab_.rowEnd() = Ab_.rowStart() + frontalDim; + const Eigen::VectorBlock sigmas = model_->sigmas().segment(Ab_.rowStart(), Ab_.rowEnd()-Ab_.rowStart()); + GaussianConditional::shared_ptr conditional(new GaussianConditional(begin(), end(), nrFrontals, Ab_, sigmas)); + if(debug) conditional->print("Extracted conditional: "); + Ab_.rowStart() += frontalDim; + Ab_.firstBlock() += nrFrontals; + toc(3, "cond Rd"); + + if(debug) conditional->print("Extracted conditional: "); + + tic(4, "remaining factor"); + // Take lower-right block of Ab to get the new factor + Ab_.rowEnd() = model_->dim(); + keys_.erase(begin(), begin() + nrFrontals); + // Set sigmas with the right model + if (model_->isConstrained()) + model_ = noiseModel::Constrained::MixedSigmas(sub(model_->sigmas(), frontalDim, model_->dim())); + else + model_ = noiseModel::Diagonal::Sigmas(sub(model_->sigmas(), frontalDim, model_->dim())); + if(debug) this->print("Eliminated factor: "); + assert(Ab_.rows() <= Ab_.cols()-1); + toc(4, "remaining factor"); + + if(debug) print("Eliminated factor: "); + + assertInvariants(); + + return conditional; + } + /* ************************************************************************* */ GaussianConditional::shared_ptr JacobianFactor::eliminate(size_t nrFrontals) { @@ -361,34 +431,6 @@ namespace gtsam { if(debug) cout << "Eliminating " << nrFrontals << " frontal variables" << endl; if(debug) this->print("Eliminating JacobianFactor: "); - - // NOTE: stairs are not currently used in the Eigen QR implementation - // add this back if DenseQR is ever reimplemented -// tic(1, "stairs"); -// // Translate the left-most nonzero column indices into top-most zero row indices -// vector firstZeroRows(Ab_.cols()); -// { -// size_t lastNonzeroRow = 0; -// vector::iterator firstZeroRowsIt = firstZeroRows.begin(); -// for(size_t var=0; varrows() && firstNonzeroBlocks_[lastNonzeroRow] <= var) -// ++ lastNonzeroRow; -// fill(firstZeroRowsIt, firstZeroRowsIt+Ab_(var).cols(), lastNonzeroRow); -// firstZeroRowsIt += Ab_(var).cols(); -// } -// assert(firstZeroRowsIt+1 == firstZeroRows.end()); -// *firstZeroRowsIt = this->rows(); -// } -// toc(1, "stairs"); - -// #ifndef NDEBUG -// for(size_t col=0; colprint("QR result noise model: "); - // Check for singular factor - if(noiseModel->dim() < frontalDim) { - throw domain_error((boost::format( - "JacobianFactor is singular in variable %1%, discovered while attempting\n" - "to eliminate this variable.") % front()).str()); - } - - // Extract conditionals - tic(3, "cond Rd"); - GaussianConditional::shared_ptr conditionals(new GaussianConditional()); - - // Restrict the matrix to be in the first nrFrontals variables - Ab_.rowEnd() = Ab_.rowStart() + frontalDim; - const Eigen::VectorBlock sigmas = noiseModel->sigmas().segment(Ab_.rowStart(), Ab_.rowEnd()-Ab_.rowStart()); - conditionals = boost::make_shared(begin(), end(), nrFrontals, Ab_, sigmas); - if(debug) conditionals->print("Extracted conditional: "); - Ab_.rowStart() += frontalDim; - Ab_.firstBlock() += nrFrontals; - toc(3, "cond Rd"); - - if(debug) conditionals->print("Extracted conditionals: "); - - tic(4, "remaining factor"); - // Take lower-right block of Ab to get the new factor - Ab_.rowEnd() = noiseModel->dim(); - keys_.erase(begin(), begin() + nrFrontals); - // Set sigmas with the right model - if (noiseModel->isConstrained()) - model_ = noiseModel::Constrained::MixedSigmas(sub(noiseModel->sigmas(), frontalDim, noiseModel->dim())); - else - model_ = noiseModel::Diagonal::Sigmas(sub(noiseModel->sigmas(), frontalDim, noiseModel->dim())); - if(debug) this->print("Eliminated factor: "); - assert(Ab_.rows() <= Ab_.cols()-1); - toc(4, "remaining factor"); - - // todo SL: deal with "dead" pivot columns!!! - tic(5, "rowstarts"); - size_t varpos = 0; - firstNonzeroBlocks_.resize(this->rows()); - for(size_t row=0; row& rowSources) const { - assertInvariants(); - for (size_t row = 0; row < rows(); ++row) { - Index firstNonzeroVar; - if (firstNonzeroBlocks_[row] < size()) { - firstNonzeroVar = keys_[firstNonzeroBlocks_[row]]; - } else if (firstNonzeroBlocks_[row] == size()) { - firstNonzeroVar = back() + 1; - } else { - assert(false); - } - rowSources.push_back(_RowSource(firstNonzeroVar, index, row)); - } - } - /* ************************************************************************* */ void JacobianFactor::allocate(const VariableSlots& variableSlots, vector< size_t>& varDims, size_t m) { keys_.resize(variableSlots.size()); std::transform(variableSlots.begin(), variableSlots.end(), begin(), - bind(&VariableSlots::const_iterator::value_type::first, - boost::lambda::_1)); + boost::bind(&VariableSlots::const_iterator::value_type::first, _1)); varDims.push_back(1); Ab_.copyStructureFrom(BlockAb(matrix_, varDims.begin(), varDims.end(), m)); - firstNonzeroBlocks_.resize(m); - } - - /* ************************************************************************* */ - void JacobianFactor::copyRow(const JacobianFactor& source, Index sourceRow, - size_t sourceSlot, size_t row, Index slot) { - ABlock combinedBlock = Ab_(slot); - if (sourceSlot != numeric_limits::max()) { - if (source.firstNonzeroBlocks_[sourceRow] <= sourceSlot) { - const constABlock sourceBlock(source.Ab_(sourceSlot)); - combinedBlock.row(row).noalias() = sourceBlock.row(sourceRow); - } else { - combinedBlock.row(row).setZero(); - } - } else { - combinedBlock.row(row).setZero(); - } - } - - /* ************************************************************************* */ - void JacobianFactor::copyFNZ(size_t m, size_t n, - vector<_RowSource>& rowSources) { - Index i = 0; - for (size_t row = 0; row < m; ++row) { - while (i < n && rowSources[row].firstNonzeroVar > keys_[i]) - ++i; - firstNonzeroBlocks_[row] = i; - } } /* ************************************************************************* */ void JacobianFactor::setModel(bool anyConstrained, const Vector& sigmas) { + if((size_t) sigmas.size() != this->rows()) + throw InvalidNoiseModel(this->rows(), sigmas.size()); if (anyConstrained) model_ = noiseModel::Constrained::MixedSigmas(sigmas); else @@ -531,97 +479,14 @@ namespace gtsam { } /* ************************************************************************* */ - Errors operator*(const FactorGraph& fg, const VectorValues& x) { - Errors e; - BOOST_FOREACH(const JacobianFactor::shared_ptr& Ai, fg) { - e.push_back((*Ai)*x); - } - return e; - } - - /* ************************************************************************* */ - void multiplyInPlace(const FactorGraph& fg, const VectorValues& x, Errors& e) { - multiplyInPlace(fg,x,e.begin()); - } - - /* ************************************************************************* */ - void multiplyInPlace(const FactorGraph& fg, const VectorValues& x, const Errors::iterator& e) { - Errors::iterator ei = e; - BOOST_FOREACH(const JacobianFactor::shared_ptr& Ai, fg) { - *ei = (*Ai)*x; - ei++; - } - } - - - /* ************************************************************************* */ - // x += alpha*A'*e - void transposeMultiplyAdd(const FactorGraph& fg, double alpha, const Errors& e, VectorValues& x) { - // For each factor add the gradient contribution - Errors::const_iterator ei = e.begin(); - BOOST_FOREACH(const JacobianFactor::shared_ptr& Ai, fg) { - Ai->transposeMultiplyAdd(alpha,*(ei++),x); - } - } - - /* ************************************************************************* */ - VectorValues gradient(const FactorGraph& fg, const VectorValues& x0) { - // It is crucial for performance to make a zero-valued clone of x - VectorValues g = VectorValues::Zero(x0); - Errors e; - BOOST_FOREACH(const JacobianFactor::shared_ptr& factor, fg) { - e.push_back(factor->error_vector(x0)); - } - transposeMultiplyAdd(fg, 1.0, e, g); - return g; - } - - /* ************************************************************************* */ - void gradientAtZero(const FactorGraph& fg, VectorValues& g) { - // Zero-out the gradient - g.setZero(); - Errors e; - BOOST_FOREACH(const JacobianFactor::shared_ptr& factor, fg) { - e.push_back(-factor->getb()); - } - transposeMultiplyAdd(fg, 1.0, e, g); - } - - /* ************************************************************************* */ - void residual(const FactorGraph& fg, const VectorValues &x, VectorValues &r) { - Index i = 0 ; - BOOST_FOREACH(const JacobianFactor::shared_ptr& factor, fg) { - r[i] = factor->getb(); - i++; - } - VectorValues Ax = VectorValues::SameStructure(r); - multiply(fg,x,Ax); - axpy(-1.0,Ax,r); - } - - /* ************************************************************************* */ - void multiply(const FactorGraph& fg, const VectorValues &x, VectorValues &r) { - r.vector() = Vector::Zero(r.dim()); - Index i = 0; - BOOST_FOREACH(const JacobianFactor::shared_ptr& factor, fg) { - SubVector &y = r[i]; - for(JacobianFactor::const_iterator j = factor->begin(); j != factor->end(); ++j) { - y += factor->getA(j) * x[*j]; - } - ++i; - } - } - - /* ************************************************************************* */ - void transposeMultiply(const FactorGraph& fg, const VectorValues &r, VectorValues &x) { - x.vector() = Vector::Zero(x.dim()); - Index i = 0; - BOOST_FOREACH(const JacobianFactor::shared_ptr& factor, fg) { - for(JacobianFactor::const_iterator j = factor->begin(); j != factor->end(); ++j) { - x[*j] += factor->getA(j).transpose() * r[i]; - } - ++i; - } + const char* JacobianFactor::InvalidNoiseModel::what() const throw() { + if(description_.empty()) + description_ = (boost::format( + "A JacobianFactor was attempted to be constructed or modified to use a\n" + "noise model of incompatible dimension. The JacobianFactor has\n" + "dimensionality (i.e. length of error vector) %d but the provided noise\n" + "model has dimensionality %d.") % factorDims % noiseModelDims).str(); + return description_.c_str(); } } diff --git a/gtsam/linear/JacobianFactor.h b/gtsam/linear/JacobianFactor.h index b5a2dd500..f2bd9c75d 100644 --- a/gtsam/linear/JacobianFactor.h +++ b/gtsam/linear/JacobianFactor.h @@ -19,7 +19,7 @@ #include #include #include -#include +#include #include #include #include @@ -78,14 +78,11 @@ namespace gtsam { * \f[ E(x) = \frac{1}{2} (A_1 x_{j1} + A_2 x_{j2} - b)^T \Sigma^{-1} (A_1 x_{j1} + A_2 x_{j2} - b) . \f] */ class JacobianFactor : public GaussianFactor { - public: - typedef Matrix AbMatrix; - typedef VerticalBlockView BlockAb; - protected: + typedef Matrix AbMatrix; + typedef VerticalBlockView BlockAb; - SharedDiagonal model_; // Gaussian noise model with diagonal covariance matrix - std::vector firstNonzeroBlocks_; + noiseModel::Diagonal::shared_ptr model_; // Gaussian noise model with diagonal covariance matrix AbMatrix matrix_; // the full matrix corresponding to the factor BlockAb Ab_; // the block view of the full matrix typedef GaussianFactor Base; // typedef to base @@ -97,11 +94,12 @@ namespace gtsam { typedef BlockAb::Column BVector; typedef BlockAb::constColumn constBVector; - public: - /** Copy constructor */ JacobianFactor(const JacobianFactor& gf); + /** Convert from other GaussianFactor */ + JacobianFactor(const GaussianFactor& gf); + /** default constructor for I/O */ JacobianFactor(); @@ -148,13 +146,31 @@ namespace gtsam { } // Implementing Testable interface - virtual void print(const std::string& s = "") const; + virtual void print(const std::string& s = "", + const IndexFormatter& formatter = DefaultIndexFormatter) const; virtual bool equals(const GaussianFactor& lf, double tol = 1e-9) const; Vector unweighted_error(const VectorValues& c) const; /** (A*x-b) */ Vector error_vector(const VectorValues& c) const; /** (A*x-b)/sigma */ virtual double error(const VectorValues& c) const; /** 0.5*(A*x-b)'*D*(A*x-b) */ + /** Return the augmented information matrix represented by this GaussianFactor. + * The augmented information matrix contains the information matrix with an + * additional column holding the information vector, and an additional row + * holding the transpose of the information vector. The lower-right entry + * contains the constant error term (when \f$ \delta x = 0 \f$). The + * augmented information matrix is described in more detail in HessianFactor, + * which in fact stores an augmented information matrix. + */ + virtual Matrix computeInformation() const; + + /** + * Construct the corresponding anti-factor to negate information + * stored stored in this factor. + * @return a HessianFactor with negated Hessian matrices + */ + virtual GaussianFactor::shared_ptr negate() const; + /** Check if the factor contains no information, i.e. zero rows. This does * not necessarily mean that the factor involves no variables (to check for * involving no variables use keys().empty()). @@ -224,7 +240,6 @@ namespace gtsam { /** * Return (dense) matrix associated with factor * The returned system is an augmented matrix: [A b] - * @param ordering of variables needed for matrix column order * @param set weight to use whitening to bake in weights */ Matrix matrix_augmented(bool weight = true) const; @@ -251,41 +266,43 @@ namespace gtsam { /** return a multi-frontal conditional. It's actually a chordal Bayesnet */ boost::shared_ptr eliminate(size_t nrFrontals = 1); - /* Used by ::CombineJacobians for sorting */ - struct _RowSource { - size_t firstNonzeroVar; - size_t factorI; - size_t factorRowI; - _RowSource(size_t _firstNonzeroVar, size_t _factorI, size_t _factorRowI) : - firstNonzeroVar(_firstNonzeroVar), factorI(_factorI), factorRowI(_factorRowI) {} - bool operator<(const _RowSource& o) const { - return firstNonzeroVar < o.firstNonzeroVar; - } - }; + /** + * splits a pre-factorized factor into a conditional, and changes the current + * factor to be the remaining component. Performs same operation as eliminate(), + * but without running QR. + */ + boost::shared_ptr splitConditional(size_t nrFrontals = 1); // following methods all used in CombineJacobians: // Many imperative, perhaps all need to be combined in constructor - /** Collect information on Jacobian rows */ - void collectInfo(size_t index, std::vector<_RowSource>& rowSources) const; - /** allocate space */ void allocate(const VariableSlots& variableSlots, std::vector& varDims, size_t m); - /** copy a slot from source */ - void copyRow(const JacobianFactor& source, - Index sourceRow, size_t sourceSlot, size_t row, Index slot); - - /** copy firstNonzeroBlocks structure */ - void copyFNZ(size_t m, size_t n, std::vector<_RowSource>& rowSources); - /** set noiseModel correctly */ void setModel(bool anyConstrained, const Vector& sigmas); /** Assert invariants after elimination */ void assertInvariants() const; + /** An exception indicating that the noise model dimension passed into the + * JacobianFactor has a different dimensionality than the factor. */ + class InvalidNoiseModel : std::exception { + public: + const size_t factorDims; ///< The dimensionality of the factor + const size_t noiseModelDims; ///< The dimensionality of the noise model + + InvalidNoiseModel(size_t factorDims, size_t noiseModelDims) : + factorDims(factorDims), noiseModelDims(noiseModelDims) {} + virtual ~InvalidNoiseModel() throw() {} + + virtual const char* what() const throw(); + + private: + mutable std::string description_; + }; + private: // Friend HessianFactor to facilitate conversion constructors @@ -301,52 +318,11 @@ namespace gtsam { template void serialize(ARCHIVE & ar, const unsigned int version) { ar & BOOST_SERIALIZATION_BASE_OBJECT_NVP(GaussianFactor); - ar & BOOST_SERIALIZATION_NVP(firstNonzeroBlocks_); ar & BOOST_SERIALIZATION_NVP(Ab_); ar & BOOST_SERIALIZATION_NVP(model_); ar & BOOST_SERIALIZATION_NVP(matrix_); } - }; // JacobianFactor - /** return A*x */ - Errors operator*(const FactorGraph& fg, const VectorValues& x); - - /* In-place version e <- A*x that overwrites e. */ - void multiplyInPlace(const FactorGraph& fg, const VectorValues& x, Errors& e); - - /* In-place version e <- A*x that takes an iterator. */ - void multiplyInPlace(const FactorGraph& fg, const VectorValues& x, const Errors::iterator& e); - - /** x += alpha*A'*e */ - void transposeMultiplyAdd(const FactorGraph& fg, double alpha, const Errors& e, VectorValues& x); - - /** - * Compute the gradient of the energy function, - * \f$ \nabla_{x=x_0} \left\Vert \Sigma^{-1} A x - b \right\Vert^2 \f$, - * centered around \f$ x = x_0 \f$. - * The gradient is \f$ A^T(Ax-b) \f$. - * @param fg The Jacobian factor graph $(A,b)$ - * @param x0 The center about which to compute the gradient - * @return The gradient as a VectorValues - */ - VectorValues gradient(const FactorGraph& fg, const VectorValues& x0); - - /** - * Compute the gradient of the energy function, - * \f$ \nabla_{x=0} \left\Vert \Sigma^{-1} A x - b \right\Vert^2 \f$, - * centered around zero. - * The gradient is \f$ A^T(Ax-b) \f$. - * @param fg The Jacobian factor graph $(A,b)$ - * @param [output] g A VectorValues to store the gradient, which must be preallocated, see allocateVectorValues - * @return The gradient as a VectorValues - */ - void gradientAtZero(const FactorGraph& fg, VectorValues& g); - - // matrix-vector operations - void residual(const FactorGraph& fg, const VectorValues &x, VectorValues &r); - void multiply(const FactorGraph& fg, const VectorValues &x, VectorValues &r); - void transposeMultiply(const FactorGraph& fg, const VectorValues &r, VectorValues &x); - } // gtsam diff --git a/gtsam/linear/KalmanFilter.cpp b/gtsam/linear/KalmanFilter.cpp index 0df9d99ce..987191254 100644 --- a/gtsam/linear/KalmanFilter.cpp +++ b/gtsam/linear/KalmanFilter.cpp @@ -23,7 +23,6 @@ #include #include #include -#include #include #include diff --git a/gtsam/linear/KalmanFilter.h b/gtsam/linear/KalmanFilter.h index b74a0db7d..df4cd1d65 100644 --- a/gtsam/linear/KalmanFilter.h +++ b/gtsam/linear/KalmanFilter.h @@ -10,17 +10,17 @@ * -------------------------------------------------------------------------- */ /** - * @file testKalmanFilter.cpp - * - * Simple linear Kalman filter. - * Implemented using factor graphs, i.e., does Cholesky-based SRIF, really. - * + * @file KalmanFilter.h + * @brief Simple linear Kalman filter. Implemented using factor graphs, i.e., does Cholesky-based SRIF, really. * @date Sep 3, 2011 * @author Stephen Williams * @author Frank Dellaert */ +#pragma once + #include +#include #ifndef KALMANFILTER_DEFAULT_FACTORIZATION #define KALMANFILTER_DEFAULT_FACTORIZATION QR @@ -28,9 +28,6 @@ namespace gtsam { - class SharedDiagonal; - class SharedGaussian; - /** * Kalman Filter class * diff --git a/gtsam/linear/NoiseModel.cpp b/gtsam/linear/NoiseModel.cpp index b6472061f..7479c2141 100644 --- a/gtsam/linear/NoiseModel.cpp +++ b/gtsam/linear/NoiseModel.cpp @@ -27,9 +27,7 @@ #include #include -#include #include -#include static double inf = std::numeric_limits::infinity(); using namespace std; @@ -125,7 +123,7 @@ SharedDiagonal Gaussian::QR(Matrix& Ab) const { if(debug) gtsam::print(Ab, "Whitened Ab: "); // Eigen QR - much faster than older householder approach - inplace_QR(Ab, false); + inplace_QR(Ab); // hand-coded householder implementation // TODO: necessary to isolate last column? @@ -134,35 +132,6 @@ SharedDiagonal Gaussian::QR(Matrix& Ab) const { return Unit::Create(maxRank); } -/* ************************************************************************* */ -SharedDiagonal Gaussian::Cholesky(Matrix& Ab, size_t nFrontals) const { - // get size(A) and maxRank - // TODO: really no rank problems ? - - // pre-whiten everything (cheaply if possible) - tic("Cholesky: 1 whiten"); - WhitenInPlace(Ab); - toc("Cholesky: 1 whiten"); - - // Form A'*A (todo: this is probably less efficient than possible) - tic("Cholesky: 2 A' * A"); - Ab = Ab.transpose() * Ab; - toc("Cholesky: 2 A' * A"); - - // Use Cholesky to factor Ab - tic("Cholesky: 3 careful"); - size_t maxrank = choleskyCareful(Ab).first; - toc("Cholesky: 3 careful"); - - // Due to numerical error the rank could appear to be more than the number - // of variables. The important part is that it does not includes the - // augmented b column. - if(maxrank == (size_t) Ab.cols()) - -- maxrank; - - return Unit::Create(maxrank); -} - void Gaussian::WhitenSystem(vector& A, Vector& b) const { BOOST_FOREACH(Matrix& Aj, A) { WhitenInPlace(Aj); } whitenInPlace(b); @@ -226,7 +195,7 @@ Diagonal::shared_ptr Diagonal::Sigmas(const Vector& sigmas, bool smart) { /* ************************************************************************* */ void Diagonal::print(const string& name) const { - gtsam::print(sigmas_, name + ": diagonal sigmas"); + gtsam::print(sigmas_, name + "diagonal sigmas"); } /* ************************************************************************* */ @@ -261,18 +230,6 @@ void Diagonal::WhitenInPlace(Matrix& H) const { vector_scale_inplace(invsigmas(), H); } -/* ************************************************************************* */ -Vector Diagonal::sample() const { - Vector result(dim_); - for (size_t i = 0; i < dim_; i++) { - typedef boost::normal_distribution Normal; - Normal dist(0.0, this->sigmas_(i)); - boost::variate_generator norm(generator, dist); - result(i) = norm(); - } - return result; -} - /* ************************************************************************* */ // Constrained /* ************************************************************************* */ @@ -290,8 +247,8 @@ Constrained::shared_ptr Constrained::MixedSigmas(const Vector& mu, const Vector& /* ************************************************************************* */ void Constrained::print(const std::string& name) const { - gtsam::print(sigmas_, name + ": constrained sigmas"); - gtsam::print(mu_, name + ": constrained mu"); + gtsam::print(sigmas_, name + "constrained sigmas"); + gtsam::print(mu_, name + "constrained mu"); } /* ************************************************************************* */ @@ -428,6 +385,12 @@ SharedDiagonal Constrained::QR(Matrix& Ab) const { /* ************************************************************************* */ // Isotropic +/* ************************************************************************* */ +Isotropic::shared_ptr Isotropic::Sigma(size_t dim, double sigma, bool smart) { + if (smart && fabs(sigma-1.0)<1e-9) return Unit::Create(dim); + return shared_ptr(new Isotropic(dim, sigma)); +} + /* ************************************************************************* */ Isotropic::shared_ptr Isotropic::Variance(size_t dim, double variance, bool smart) { if (smart && fabs(variance-1.0)<1e-9) return Unit::Create(dim); @@ -436,7 +399,7 @@ Isotropic::shared_ptr Isotropic::Variance(size_t dim, double variance, bool smar /* ************************************************************************* */ void Isotropic::print(const string& name) const { - cout << name << ": isotropic sigma " << " " << sigma_ << endl; + cout << name << "isotropic sigma " << " " << sigma_ << endl; } /* ************************************************************************* */ @@ -464,23 +427,11 @@ void Isotropic::WhitenInPlace(Matrix& H) const { H *= invsigma_; } -/* ************************************************************************* */ -// faster version -Vector Isotropic::sample() const { - typedef boost::normal_distribution Normal; - Normal dist(0.0, this->sigma_); - boost::variate_generator norm(generator, dist); - Vector result(dim_); - for (size_t i = 0; i < dim_; i++) - result(i) = norm(); - return result; -} - /* ************************************************************************* */ // Unit /* ************************************************************************* */ void Unit::print(const std::string& name) const { - cout << name << ": unit (" << dim_ << ") " << endl; + cout << name << "unit (" << dim_ << ") " << endl; } /* ************************************************************************* */ @@ -583,7 +534,7 @@ void Base::reweight(Matrix &A1, Matrix &A2, Matrix &A3, Vector &error) const { /* ************************************************************************* */ void Null::print(const std::string &s="") const -{ cout << s << ": null ()" << endl; } +{ cout << s << "null ()" << endl; } Null::shared_ptr Null::Create() { return shared_ptr(new Null()); } @@ -604,7 +555,7 @@ double Fair::weight(const double &error) const { return 1.0 / (1.0 + fabs(error)/c_); } void Fair::print(const std::string &s="") const -{ cout << s << ": fair (" << c_ << ")" << endl; } +{ cout << s << "fair (" << c_ << ")" << endl; } bool Fair::equals(const Base &expected, const double tol) const { const Fair* p = dynamic_cast (&expected); @@ -632,7 +583,7 @@ double Huber::weight(const double &error) const { } void Huber::print(const std::string &s="") const { - cout << s << ": huber (" << k_ << ")" << endl; + cout << s << "huber (" << k_ << ")" << endl; } bool Huber::equals(const Base &expected, const double tol) const { diff --git a/gtsam/linear/NoiseModel.h b/gtsam/linear/NoiseModel.h index b6cf4deac..8588c738b 100644 --- a/gtsam/linear/NoiseModel.h +++ b/gtsam/linear/NoiseModel.h @@ -19,15 +19,17 @@ #pragma once #include +#include +#include #include +#include namespace gtsam { - class SharedDiagonal; // forward declare - /// All noise models live in the noiseModel namespace namespace noiseModel { + // Forward declaration class Gaussian; class Diagonal; class Constrained; @@ -111,6 +113,8 @@ namespace gtsam { * as indeed * |y|^2 = y'*y = x'*R'*R*x * Various derived classes are available that are more efficient. + * The named constructors return a shared_ptr because, when the smart flag is true, + * the underlying object might be a derived class such as Diagonal. */ class Gaussian: public Base { @@ -145,7 +149,6 @@ namespace gtsam { /** * A Gaussian noise model created by specifying a square root information matrix. - * @param smart, check if can be simplified to derived class */ static shared_ptr SqrtInformation(const Matrix& R) { return shared_ptr(new Gaussian(R.rows(),R)); @@ -153,9 +156,10 @@ namespace gtsam { /** * A Gaussian noise model created by specifying a covariance matrix. - * @param smart, check if can be simplified to derived class + * @param covariance The square covariance Matrix + * @param smart check if can be simplified to derived class */ - static shared_ptr Covariance(const Matrix& covariance, bool smart=false); + static shared_ptr Covariance(const Matrix& covariance, bool smart = true); virtual void print(const std::string& name) const; virtual bool equals(const Base& expected, double tol=1e-9) const; @@ -197,13 +201,7 @@ namespace gtsam { * @param Ab is the m*(n+1) augmented system matrix [A b] * @return in-place QR factorization [R d]. Below-diagonal is undefined !!!!! */ - virtual SharedDiagonal QR(Matrix& Ab) const; - - /** - * Cholesky factorization - * FIXME: this is never used anywhere - */ - virtual SharedDiagonal Cholesky(Matrix& Ab, size_t nFrontals) const; + virtual boost::shared_ptr QR(Matrix& Ab) const; /** * Return R itself, but note that Whiten(H) is cheaper than R*H @@ -261,21 +259,22 @@ namespace gtsam { * A diagonal noise model created by specifying a Vector of sigmas, i.e. * standard devations, the diagonal of the square root covariance matrix. */ - static shared_ptr Sigmas(const Vector& sigmas, bool smart=false); + static shared_ptr Sigmas(const Vector& sigmas, bool smart = true); /** * A diagonal noise model created by specifying a Vector of variances, i.e. * i.e. the diagonal of the covariance matrix. - * @param smart, check if can be simplified to derived class + * @param variances A vector containing the variances of this noise model + * @param smart check if can be simplified to derived class */ - static shared_ptr Variances(const Vector& variances, bool smart = false); + static shared_ptr Variances(const Vector& variances, bool smart = true); /** * A diagonal noise model created by specifying a Vector of precisions, i.e. * i.e. the diagonal of the information matrix, i.e., weights */ - static shared_ptr Precisions(const Vector& precisions) { - return Variances(reciprocal(precisions)); + static shared_ptr Precisions(const Vector& precisions, bool smart = true) { + return Variances(reciprocal(precisions), smart); } virtual void print(const std::string& name) const; @@ -296,11 +295,6 @@ namespace gtsam { Vector invsigmas() const; double invsigma(size_t i) const; - /** - * generate random variate - */ - virtual Vector sample() const; - /** * Return R itself, but note that Whiten(H) is cheaper than R*H */ @@ -368,13 +362,13 @@ namespace gtsam { * standard devations, some of which might be zero */ static shared_ptr MixedSigmas(const Vector& mu, const Vector& sigmas, - bool smart = false); + bool smart = true); /** * A diagonal noise model created by specifying a Vector of * standard devations, some of which might be zero */ - static shared_ptr MixedSigmas(const Vector& sigmas, bool smart = false) { + static shared_ptr MixedSigmas(const Vector& sigmas, bool smart = true) { return MixedSigmas(repeat(sigmas.size(), 1000.0), sigmas, smart); } @@ -383,7 +377,7 @@ namespace gtsam { * standard devations, some of which might be zero */ static shared_ptr MixedSigmas(double m, const Vector& sigmas, - bool smart = false) { + bool smart = true) { return MixedSigmas(repeat(sigmas.size(), m), sigmas, smart); } @@ -445,7 +439,7 @@ namespace gtsam { /** * Apply QR factorization to the system [A b], taking into account constraints */ - virtual SharedDiagonal QR(Matrix& Ab) const; + virtual Diagonal::shared_ptr QR(Matrix& Ab) const; /** * Check constrained is always true @@ -496,21 +490,21 @@ namespace gtsam { /** * An isotropic noise model created by specifying a standard devation sigma */ - static shared_ptr Sigma(size_t dim, double sigma) { - return shared_ptr(new Isotropic(dim, sigma)); - } + static shared_ptr Sigma(size_t dim, double sigma, bool smart = true); /** * An isotropic noise model created by specifying a variance = sigma^2. - * @param smart, check if can be simplified to derived class + * @param dim The dimension of this noise model + * @param variance The variance of this noise model + * @param smart check if can be simplified to derived class */ - static shared_ptr Variance(size_t dim, double variance, bool smart = false); + static shared_ptr Variance(size_t dim, double variance, bool smart = true); /** * An isotropic noise model created by specifying a precision */ - static shared_ptr Precision(size_t dim, double precision) { - return Variance(dim, 1.0/precision); + static shared_ptr Precision(size_t dim, double precision, bool smart = true) { + return Variance(dim, 1.0/precision, smart); } virtual void print(const std::string& name) const; @@ -525,11 +519,6 @@ namespace gtsam { */ inline double sigma() const { return sigma_; } - /** - * generate random variate - */ - virtual Vector sample() const; - private: /** Serialization function */ friend class boost::serialization::access; @@ -609,7 +598,7 @@ namespace gtsam { virtual bool equals(const Base& expected, const double tol=1e-8) const = 0; inline double sqrtWeight(const double &error) const - { return sqrt(weight(error)); } + { return std::sqrt(weight(error)); } /** produce a weight vector according to an error vector and the implemented * robust function */ @@ -728,6 +717,13 @@ namespace gtsam { } // namespace noiseModel + /** Note, deliberately not in noiseModel namespace. + * Deprecated. Only for compatibility with previous version. + */ + typedef noiseModel::Base::shared_ptr SharedNoiseModel; + typedef noiseModel::Gaussian::shared_ptr SharedGaussian; + typedef noiseModel::Diagonal::shared_ptr SharedDiagonal; + } // namespace gtsam diff --git a/gtsam/linear/Sampler.cpp b/gtsam/linear/Sampler.cpp index 058533104..6031440bd 100644 --- a/gtsam/linear/Sampler.cpp +++ b/gtsam/linear/Sampler.cpp @@ -18,27 +18,32 @@ #include #include - namespace gtsam { /* ************************************************************************* */ -Sampler::Sampler(const SharedDiagonal& model, int32_t seed) - : sigmas_(model->sigmas()), generator_(static_cast(seed)) +Sampler::Sampler(const noiseModel::Diagonal::shared_ptr& model, int32_t seed) + : model_(model), generator_(static_cast(seed)) { } /* ************************************************************************* */ Sampler::Sampler(const Vector& sigmas, int32_t seed) - : sigmas_(sigmas), generator_(static_cast(seed)) +: model_(noiseModel::Diagonal::Sigmas(sigmas, true)), generator_(static_cast(seed)) { } /* ************************************************************************* */ -Vector Sampler::sample() { - size_t d = dim(); +Sampler::Sampler(int32_t seed) +: generator_(static_cast(seed)) +{ +} + +/* ************************************************************************* */ +Vector Sampler::sampleDiagonal(const Vector& sigmas) { + size_t d = sigmas.size(); Vector result(d); for (size_t i = 0; i < d; i++) { - double sigma = sigmas_(i); + double sigma = sigmas(i); // handle constrained case separately if (sigma == 0.0) { @@ -53,4 +58,19 @@ Vector Sampler::sample() { return result; } +/* ************************************************************************* */ +Vector Sampler::sample() { + assert(model_.get()); + const Vector& sigmas = model_->sigmas(); + return sampleDiagonal(sigmas); +} + +/* ************************************************************************* */ +Vector Sampler::sampleNewModel(const noiseModel::Diagonal::shared_ptr& model) { + assert(model.get()); + const Vector& sigmas = model->sigmas(); + return sampleDiagonal(sigmas); +} +/* ************************************************************************* */ + } // \namespace gtsam diff --git a/gtsam/linear/Sampler.h b/gtsam/linear/Sampler.h index 53b59a9ea..3f6fee7ca 100644 --- a/gtsam/linear/Sampler.h +++ b/gtsam/linear/Sampler.h @@ -10,15 +10,17 @@ * -------------------------------------------------------------------------- */ /** - * @file Sampler.h * @brief sampling that can be parameterized using a NoiseModel to generate samples from + * @file Sampler.h * the given distribution * @author Alex Cunningham */ #pragma once -#include +#include + +#include namespace gtsam { @@ -31,8 +33,8 @@ namespace gtsam { */ class Sampler { protected: - /** sigmas from the noise model */ - Vector sigmas_; + /** noiseModel created at generation */ + noiseModel::Diagonal::shared_ptr model_; /** generator */ boost::minstd_rand generator_; @@ -46,7 +48,7 @@ public: * * NOTE: do not use zero as a seed, it will break the generator */ - Sampler(const SharedDiagonal& model, int32_t seed = 42u); + Sampler(const noiseModel::Diagonal::shared_ptr& model, int32_t seed = 42u); /** * Create a sampler for a distribution specified by a vector of sigmas directly @@ -55,9 +57,17 @@ public: */ Sampler(const Vector& sigmas, int32_t seed = 42u); + /** + * Create a sampler without a given noisemodel - pass in to sample + * + * NOTE: do not use zero as a seed, it will break the generator + */ + Sampler(int32_t seed = 42u); + /** access functions */ - size_t dim() const { return sigmas_.size(); } - Vector sigmas() const { return sigmas_; } + size_t dim() const { assert(model_.get()); return model_->dim(); } + Vector sigmas() const { assert(model_.get()); return model_->sigmas(); } + const noiseModel::Diagonal::shared_ptr& model() const { return model_; } /** * sample from distribution @@ -65,6 +75,19 @@ public: */ Vector sample(); + /** + * Sample from noisemodel passed in as an argument, + * can be used without having initialized a model for the system. + * + * NOTE: not const due to need to update the underlying generator + */ + Vector sampleNewModel(const noiseModel::Diagonal::shared_ptr& model); + +protected: + + /** given sigmas for a diagonal model, returns a sample */ + Vector sampleDiagonal(const Vector& sigmas); + }; -} +} // \namespace gtsam diff --git a/gtsam/linear/SharedDiagonal.h b/gtsam/linear/SharedDiagonal.h deleted file mode 100644 index 8a7e101a2..000000000 --- a/gtsam/linear/SharedDiagonal.h +++ /dev/null @@ -1,81 +0,0 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) - - * See LICENSE for the license information - - * -------------------------------------------------------------------------- */ - -/** - * @file SharedDiagonal.h - * @brief Class that wraps a shared noise model with diagonal covariance - * @author Frank Dellaert - * @date Jan 22, 2010 - */ - -#pragma once - -#include - -namespace gtsam { // note, deliberately not in noiseModel namespace - - // A useful convenience class to refer to a shared Diagonal model - // There are (somewhat dangerous) constructors from Vector and pair - // that call Sigmas and Sigma, respectively. - class SharedDiagonal: public noiseModel::Diagonal::shared_ptr { - public: - SharedDiagonal() { - } - SharedDiagonal(const noiseModel::Diagonal::shared_ptr& p) : - noiseModel::Diagonal::shared_ptr(p) { - } - SharedDiagonal(const noiseModel::Constrained::shared_ptr& p) : - noiseModel::Diagonal::shared_ptr(p) { - } - SharedDiagonal(const noiseModel::Isotropic::shared_ptr& p) : - noiseModel::Diagonal::shared_ptr(p) { - } - SharedDiagonal(const noiseModel::Unit::shared_ptr& p) : - noiseModel::Diagonal::shared_ptr(p) { - } - SharedDiagonal(const Vector& sigmas) : - noiseModel::Diagonal::shared_ptr(noiseModel::Diagonal::Sigmas(sigmas)) { - } - - /// Print - inline void print(const std::string &s) const { (*this)->print(s); } - - /// Generate a sample - inline Vector sample() const { return (*this)->sample(); } - - /** Serialization function */ - friend class boost::serialization::access; - template - void serialize(ARCHIVE & ar, const unsigned int version) { - ar & boost::serialization::make_nvp("SharedDiagonal", - boost::serialization::base_object(*this)); - } - }; - - // TODO: make these the ones really used in unit tests - inline SharedDiagonal sharedSigmas(const Vector& sigmas) { - return noiseModel::Diagonal::Sigmas(sigmas); - } - inline SharedDiagonal sharedSigma(size_t dim, double sigma) { - return noiseModel::Isotropic::Sigma(dim, sigma); - } - inline SharedDiagonal sharedPrecisions(const Vector& precisions) { - return noiseModel::Diagonal::Precisions(precisions); - } - inline SharedDiagonal sharedPrecision(size_t dim, double precision) { - return noiseModel::Isotropic::Precision(dim, precision); - } - inline SharedDiagonal sharedUnit(size_t dim) { - return noiseModel::Unit::Create(dim); - } - -} - diff --git a/gtsam/linear/SharedGaussian.h b/gtsam/linear/SharedGaussian.h deleted file mode 100644 index a3154bac1..000000000 --- a/gtsam/linear/SharedGaussian.h +++ /dev/null @@ -1,70 +0,0 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) - - * See LICENSE for the license information - - * -------------------------------------------------------------------------- */ - -/** - * @file SharedGaussian.h - * @brief Class that wraps a shared Gaussian noise model - * @author Frank Dellaert - * @date Jan 22, 2010 - */ - -#pragma once - -#include -#include - -namespace gtsam { // note, deliberately not in noiseModel namespace - - /** - * A useful convenience class to refer to a shared Gaussian model - * Also needed to make noise models in matlab - */ - class SharedGaussian: public SharedNoiseModel { - public: - - typedef SharedNoiseModel Base; - - SharedGaussian() {} - SharedGaussian(const noiseModel::Gaussian::shared_ptr& p) : Base(p) {} - SharedGaussian(const noiseModel::Diagonal::shared_ptr& p) : Base(p) {} - SharedGaussian(const noiseModel::Constrained::shared_ptr& p) : Base(p) {} - SharedGaussian(const noiseModel::Isotropic::shared_ptr& p) : Base(p) {} - SharedGaussian(const noiseModel::Unit::shared_ptr& p) : Base(p) {} - - // Define GTSAM_MAGIC_GAUSSIAN to have access to slightly - // dangerous and non-shared (inefficient, wasteful) noise models. - // Intended to be used only in tests (if you must) and the MATLAB wrapper -#ifdef GTSAM_MAGIC_GAUSSIAN - SharedGaussian(const Matrix& covariance) - : Base(noiseModel::Gaussian::Covariance(covariance)) {} - SharedGaussian(const Vector& sigmas) - : Base(noiseModel::Diagonal::Sigmas(sigmas)) {} -#endif - -// Define GTSAM_DANGEROUS_GAUSSIAN to have access to bug-prone fixed dimension Gaussians -// Not intended for human use, only for backwards compatibility of old unit tests -#ifdef GTSAM_DANGEROUS_GAUSSIAN - SharedGaussian(const double& s) : - Base(noiseModel::Isotropic::Sigma(GTSAM_DANGEROUS_GAUSSIAN, s)) {} -#endif - - /// Print - inline void print(const std::string &s) const { (*this)->print(s); } - - /** Serialization function */ - friend class boost::serialization::access; - template - void serialize(ARCHIVE & ar, const unsigned int version) { - ar & boost::serialization::make_nvp("SharedGaussian", - boost::serialization::base_object(*this)); - } - }; -} diff --git a/gtsam/linear/SharedNoiseModel.h b/gtsam/linear/SharedNoiseModel.h deleted file mode 100644 index 1d66e3495..000000000 --- a/gtsam/linear/SharedNoiseModel.h +++ /dev/null @@ -1,89 +0,0 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) - - * See LICENSE for the license information - - * -------------------------------------------------------------------------- */ - -#pragma once - -#include - -namespace gtsam { // note, deliberately not in noiseModel namespace - - struct SharedNoiseModel: public noiseModel::Base::shared_ptr { - - typedef noiseModel::Base::shared_ptr Base; - - SharedNoiseModel() {} - SharedNoiseModel(const noiseModel::Robust::shared_ptr& p): Base(p) {} - SharedNoiseModel(const noiseModel::Gaussian::shared_ptr& p): Base(p) {} - SharedNoiseModel(const noiseModel::Diagonal::shared_ptr& p): Base(p) {} - SharedNoiseModel(const noiseModel::Constrained::shared_ptr& p): Base(p) {} - SharedNoiseModel(const noiseModel::Isotropic::shared_ptr& p): Base(p) {} - SharedNoiseModel(const noiseModel::Unit::shared_ptr& p): Base(p) {} - - #ifdef GTSAM_MAGIC_GAUSSIAN - SharedNoiseModel(const Matrix& covariance) : - Base(boost::static_pointer_cast( - noiseModel::Gaussian::Covariance(covariance))) {} - - SharedNoiseModel(const Vector& sigmas) : - Base(boost::static_pointer_cast( - noiseModel::Diagonal::Sigmas(sigmas))) {} - #endif - - // Define GTSAM_DANGEROUS_GAUSSIAN to have access to bug-prone fixed dimension Gaussians - // Not intended for human use, only for backwards compatibility of old unit tests - #ifdef GTSAM_DANGEROUS_GAUSSIAN - SharedNoiseModel(const double& s) : - Base(boost::static_pointer_cast( - noiseModel::Isotropic::Sigma(GTSAM_DANGEROUS_GAUSSIAN, s))) {} - #endif - - /// Print - inline void print(const std::string &s) const { (*this)->print(s); } - - // Static syntactic sugar functions to create noisemodels directly - // These should only be used with the Matlab interface - static inline SharedNoiseModel Sigmas(const Vector& sigmas, bool smart=false) { - return noiseModel::Diagonal::Sigmas(sigmas, smart); - } - - static inline SharedNoiseModel Sigma(size_t dim, double sigma) { - return noiseModel::Isotropic::Sigma(dim, sigma); - } - - static inline SharedNoiseModel Precisions(const Vector& precisions) { - return noiseModel::Diagonal::Precisions(precisions); - } - - static inline SharedNoiseModel Precision(size_t dim, double precision) { - return noiseModel::Isotropic::Precision(dim, precision); - } - - static inline SharedNoiseModel Unit(size_t dim) { - return noiseModel::Unit::Create(dim); - } - - static inline SharedNoiseModel SqrtInformation(const Matrix& R) { - return noiseModel::Gaussian::SqrtInformation(R); - } - - static inline SharedNoiseModel Covariance(const Matrix& covariance, bool smart=false) { - return noiseModel::Gaussian::Covariance(covariance, smart); - } - - /** Serialization function */ - friend class boost::serialization::access; - template - void serialize(ARCHIVE & ar, const unsigned int version) { - ar & boost::serialization::make_nvp("SharedNoiseModel", - boost::serialization::base_object(*this)); - } - }; -} diff --git a/gtsam/linear/SubgraphPreconditioner.cpp b/gtsam/linear/SubgraphPreconditioner.cpp new file mode 100644 index 000000000..8b5a3708f --- /dev/null +++ b/gtsam/linear/SubgraphPreconditioner.cpp @@ -0,0 +1,139 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file SubgraphPreconditioner.cpp + * @date Dec 31, 2009 + * @author: Frank Dellaert + */ + +#include +#include +#include + +using namespace std; + +namespace gtsam { + + /* ************************************************************************* */ + static GaussianFactorGraph::shared_ptr convertToJacobianFactors(const GaussianFactorGraph &gfg) { + GaussianFactorGraph::shared_ptr result(new GaussianFactorGraph()); + BOOST_FOREACH(const GaussianFactor::shared_ptr &gf, gfg) { + JacobianFactor::shared_ptr jf = boost::dynamic_pointer_cast(gf); + if( !jf ) { + jf = boost::make_shared(*gf); // Convert any non-Jacobian factors to Jacobians (e.g. Hessian -> Jacobian with Cholesky) + } + result->push_back(jf); + } + return result; + } + + /* ************************************************************************* */ + SubgraphPreconditioner::SubgraphPreconditioner(const sharedFG& Ab2, + const sharedBayesNet& Rc1, const sharedValues& xbar) : + Ab2_(convertToJacobianFactors(*Ab2)), Rc1_(Rc1), xbar_(xbar), b2bar_(new Errors(-gaussianErrors(*Ab2_,*xbar))) { + } + + /* ************************************************************************* */ + // x = xbar + inv(R1)*y + VectorValues SubgraphPreconditioner::x(const VectorValues& y) const { + return *xbar_ + gtsam::backSubstitute(*Rc1_, y); + } + + /* ************************************************************************* */ + double error(const SubgraphPreconditioner& sp, const VectorValues& y) { + Errors e(y); + VectorValues x = sp.x(y); + Errors e2 = gaussianErrors(*sp.Ab2(),x); + return 0.5 * (dot(e, e) + dot(e2,e2)); + } + + /* ************************************************************************* */ + // gradient is y + inv(R1')*A2'*(A2*inv(R1)*y-b2bar), + VectorValues gradient(const SubgraphPreconditioner& sp, const VectorValues& y) { + VectorValues x = gtsam::backSubstitute(*sp.Rc1(), y); /* inv(R1)*y */ + Errors e = (*sp.Ab2()*x - *sp.b2bar()); /* (A2*inv(R1)*y-b2bar) */ + VectorValues v = VectorValues::Zero(x); + transposeMultiplyAdd(*sp.Ab2(), 1.0, e, v); /* A2'*(A2*inv(R1)*y-b2bar) */ + return y + gtsam::backSubstituteTranspose(*sp.Rc1(), v); + } + + /* ************************************************************************* */ + // Apply operator A, A*y = [I;A2*inv(R1)]*y = [y; A2*inv(R1)*y] + Errors operator*(const SubgraphPreconditioner& sp, const VectorValues& y) { + + Errors e(y); + VectorValues x = gtsam::backSubstitute(*sp.Rc1(), y); /* x=inv(R1)*y */ + Errors e2 = *sp.Ab2() * x; /* A2*x */ + e.splice(e.end(), e2); + return e; + } + + /* ************************************************************************* */ + // In-place version that overwrites e + void multiplyInPlace(const SubgraphPreconditioner& sp, const VectorValues& y, Errors& e) { + + Errors::iterator ei = e.begin(); + for ( Index i = 0 ; i < y.size() ; ++i, ++ei ) { + *ei = y[i]; + } + + // Add A2 contribution + VectorValues x = gtsam::backSubstitute(*sp.Rc1(), y); // x=inv(R1)*y + gtsam::multiplyInPlace(*sp.Ab2(), x, ei); // use iterator version + } + + /* ************************************************************************* */ + // Apply operator A', A'*e = [I inv(R1')*A2']*e = e1 + inv(R1')*A2'*e2 + VectorValues operator^(const SubgraphPreconditioner& sp, const Errors& e) { + + Errors::const_iterator it = e.begin(); + VectorValues y = sp.zero(); + for ( Index i = 0 ; i < y.size() ; ++i, ++it ) + y[i] = *it ; + sp.transposeMultiplyAdd2(1.0,it,e.end(),y); + return y; + } + + /* ************************************************************************* */ + // y += alpha*A'*e + void transposeMultiplyAdd + (const SubgraphPreconditioner& sp, double alpha, const Errors& e, VectorValues& y) { + + Errors::const_iterator it = e.begin(); + for ( Index i = 0 ; i < y.size() ; ++i, ++it ) { + const Vector& ei = *it; + axpy(alpha, ei, y[i]); + } + sp.transposeMultiplyAdd2(alpha, it, e.end(), y); + } + + /* ************************************************************************* */ + // y += alpha*inv(R1')*A2'*e2 + void SubgraphPreconditioner::transposeMultiplyAdd2 (double alpha, + Errors::const_iterator it, Errors::const_iterator end, VectorValues& y) const { + + // create e2 with what's left of e + // TODO can we avoid creating e2 by passing iterator to transposeMultiplyAdd ? + Errors e2; + while (it != end) e2.push_back(*(it++)); + + VectorValues x = VectorValues::Zero(y); // x = 0 + gtsam::transposeMultiplyAdd(*Ab2_,1.0,e2,x); // x += A2'*e2 + axpy(alpha, gtsam::backSubstituteTranspose(*Rc1_, x), y); // y += alpha*inv(R1')*x + } + + /* ************************************************************************* */ + void SubgraphPreconditioner::print(const std::string& s) const { + cout << s << endl; + Ab2_->print(); + } +} // nsamespace gtsam diff --git a/gtsam/linear/SubgraphPreconditioner.h b/gtsam/linear/SubgraphPreconditioner.h new file mode 100644 index 000000000..f266928d7 --- /dev/null +++ b/gtsam/linear/SubgraphPreconditioner.h @@ -0,0 +1,117 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file SubgraphPreconditioner.h + * @date Dec 31, 2009 + * @author Frank Dellaert + */ + +#pragma once + +#include +#include +#include + +namespace gtsam { + + /** + * Subgraph conditioner class, as explained in the RSS 2010 submission. + * Starting with a graph A*x=b, we split it in two systems A1*x=b1 and A2*x=b2 + * We solve R1*x=c1, and make the substitution y=R1*x-c1. + * To use the class, give the Bayes Net R1*x=c1 and Graph A2*x=b2. + * Then solve for yhat using CG, and solve for xhat = system.x(yhat). + */ + class SubgraphPreconditioner { + + public: + typedef boost::shared_ptr shared_ptr; + typedef boost::shared_ptr sharedBayesNet; + typedef boost::shared_ptr sharedFG; + typedef boost::shared_ptr sharedValues; + typedef boost::shared_ptr sharedErrors; + + private: + sharedFG Ab2_; + sharedBayesNet Rc1_; + sharedValues xbar_; ///< A1 \ b1 + sharedErrors b2bar_; ///< A2*xbar - b2 + + public: + + SubgraphPreconditioner(); + + /** + * Constructor + * @param Ab2: the Graph A2*x=b2 + * @param Rc1: the Bayes Net R1*x=c1 + * @param xbar: the solution to R1*x=c1 + */ + SubgraphPreconditioner(const sharedFG& Ab2, const sharedBayesNet& Rc1, const sharedValues& xbar); + + /** Access Ab2 */ + const sharedFG& Ab2() const { return Ab2_; } + + /** Access Rc1 */ + const sharedBayesNet& Rc1() const { return Rc1_; } + + /** Access b2bar */ + const sharedErrors b2bar() const { return b2bar_; } + + /** + * Add zero-mean i.i.d. Gaussian prior terms to each variable + * @param sigma Standard deviation of Gaussian + */ +// SubgraphPreconditioner add_priors(double sigma) const; + + /* x = xbar + inv(R1)*y */ + VectorValues x(const VectorValues& y) const; + + /* A zero VectorValues with the structure of xbar */ + VectorValues zero() const { + VectorValues V(VectorValues::Zero(*xbar_)); + return V ; + } + + /** + * Add constraint part of the error only + * y += alpha*inv(R1')*A2'*e2 + * Takes a range indicating e2 !!!! + */ + void transposeMultiplyAdd2(double alpha, Errors::const_iterator begin, + Errors::const_iterator end, VectorValues& y) const; + + /** print the object */ + void print(const std::string& s = "SubgraphPreconditioner") const; + }; + + /* error, given y */ + double error(const SubgraphPreconditioner& sp, const VectorValues& y); + + /** gradient = y + inv(R1')*A2'*(A2*inv(R1)*y-b2bar) */ + VectorValues gradient(const SubgraphPreconditioner& sp, const VectorValues& y); + + /** Apply operator A */ + Errors operator*(const SubgraphPreconditioner& sp, const VectorValues& y); + + /** Apply operator A in place: needs e allocated already */ + void multiplyInPlace(const SubgraphPreconditioner& sp, const VectorValues& y, Errors& e); + + /** Apply operator A' */ + VectorValues operator^(const SubgraphPreconditioner& sp, const Errors& e); + + /** + * Add A'*e to y + * y += alpha*A'*[e1;e2] = [alpha*e1; alpha*inv(R1')*A2'*e2] + */ + void transposeMultiplyAdd(const SubgraphPreconditioner& sp, double alpha, const Errors& e, VectorValues& y); + +} // namespace gtsam diff --git a/gtsam/linear/SubgraphSolver.cpp b/gtsam/linear/SubgraphSolver.cpp new file mode 100644 index 000000000..9986fb76c --- /dev/null +++ b/gtsam/linear/SubgraphSolver.cpp @@ -0,0 +1,137 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +using namespace std; + +namespace gtsam { + +/**************************************************************************************************/ +SubgraphSolver::SubgraphSolver(const GaussianFactorGraph &gfg, const Parameters ¶meters) + : parameters_(parameters) +{ + initialize(gfg); +} + +/**************************************************************************************************/ +SubgraphSolver::SubgraphSolver(const GaussianFactorGraph::shared_ptr &jfg, const Parameters ¶meters) + : parameters_(parameters) +{ + initialize(*jfg); +} + +/**************************************************************************************************/ +SubgraphSolver::SubgraphSolver(const GaussianFactorGraph &Ab1, const GaussianFactorGraph &Ab2, const Parameters ¶meters) + : parameters_(parameters) { + + GaussianBayesNet::shared_ptr Rc1 = EliminationTree::Create(Ab1)->eliminate(&EliminateQR); + initialize(Rc1, boost::make_shared(Ab2)); +} + +/**************************************************************************************************/ +SubgraphSolver::SubgraphSolver(const GaussianFactorGraph::shared_ptr &Ab1, + const GaussianFactorGraph::shared_ptr &Ab2, const Parameters ¶meters) + : parameters_(parameters) { + + GaussianBayesNet::shared_ptr Rc1 = EliminationTree::Create(*Ab1)->eliminate(&EliminateQR); + initialize(Rc1, Ab2); +} + +/**************************************************************************************************/ +SubgraphSolver::SubgraphSolver(const GaussianBayesNet::shared_ptr &Rc1, const GaussianFactorGraph &Ab2, + const Parameters ¶meters) : parameters_(parameters) +{ + initialize(Rc1, boost::make_shared(Ab2)); +} + +/**************************************************************************************************/ +SubgraphSolver::SubgraphSolver(const GaussianBayesNet::shared_ptr &Rc1, + const GaussianFactorGraph::shared_ptr &Ab2, const Parameters ¶meters) : parameters_(parameters) +{ + initialize(Rc1, Ab2); +} + +VectorValues SubgraphSolver::optimize() { + VectorValues ybar = conjugateGradients(*pc_, pc_->zero(), parameters_); + return pc_->x(ybar); +} + +void SubgraphSolver::initialize(const GaussianFactorGraph &jfg) +{ + GaussianFactorGraph::shared_ptr Ab1 = boost::make_shared(), + Ab2 = boost::make_shared(); + + boost::tie(Ab1, Ab2) = splitGraph(jfg) ; + if (parameters_.verbosity()) + cout << "Split A into (A1) " << Ab1->size() << " and (A2) " << Ab2->size() << " factors" << endl; + + GaussianBayesNet::shared_ptr Rc1 = EliminationTree::Create(*Ab1)->eliminate(&EliminateQR); + VectorValues::shared_ptr xbar(new VectorValues(gtsam::optimize(*Rc1))); + pc_ = boost::make_shared(Ab2, Rc1, xbar); +} + +void SubgraphSolver::initialize(const GaussianBayesNet::shared_ptr &Rc1, const GaussianFactorGraph::shared_ptr &Ab2) +{ + VectorValues::shared_ptr xbar(new VectorValues(gtsam::optimize(*Rc1))); + pc_ = boost::make_shared(Ab2, Rc1, xbar); +} + +boost::tuple +SubgraphSolver::splitGraph(const GaussianFactorGraph &jfg) { + + const VariableIndex index(jfg); + const size_t n = index.size(); + DSFVector D(n); + + GaussianFactorGraph::shared_ptr At(new GaussianFactorGraph()); + GaussianFactorGraph::shared_ptr Ac( new GaussianFactorGraph()); + + size_t t = 0; + BOOST_FOREACH ( const GaussianFactor::shared_ptr &gf, jfg ) { + + if ( gf->keys().size() > 2 ) { + throw runtime_error("SubgraphSolver::splitGraph the graph is not simple, sanity check failed "); + } + + bool augment = false ; + + /* check whether this factor should be augmented to the "tree" graph */ + if ( gf->keys().size() == 1 ) augment = true; + else { + const Index u = gf->keys()[0], v = gf->keys()[1], + u_root = D.findSet(u), v_root = D.findSet(v); + if ( u_root != v_root ) { + t++; augment = true ; + D.makeUnionInPlace(u_root, v_root); + } + } + if ( augment ) At->push_back(gf); + else Ac->push_back(gf); + } + + return boost::tie(At, Ac); +} + +} // \namespace gtsam diff --git a/gtsam/linear/SubgraphSolver.h b/gtsam/linear/SubgraphSolver.h new file mode 100644 index 000000000..fe968d486 --- /dev/null +++ b/gtsam/linear/SubgraphSolver.h @@ -0,0 +1,87 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +#pragma once + +#include +#include +#include +#include +#include + +namespace gtsam { + +class SubgraphSolverParameters : public ConjugateGradientParameters { +public: + typedef ConjugateGradientParameters Base; + SubgraphSolverParameters() : Base() {} + virtual void print(const std::string &s="") const { Base::print(s); } +}; + +/** + * This class implements the SPCG solver presented in Dellaert et al in IROS'10. + * + * Given a linear least-squares problem \f$ f(x) = |A x - b|^2 \f$. We split the problem into + * \f$ f(x) = |A_t - b_t|^2 + |A_c - b_c|^2 \f$ where \f$ A_t \f$ denotes the "tree" part, and \f$ A_c \f$ denotes the "constraint" part. + * \f$ A_t \f$ is factorized into \f$ Q_t R_t \f$, and we compute \f$ c_t = Q_t^{-1} b_t \f$, and \f$ x_t = R_t^{-1} c_t \f$ accordingly. + * Then we solve a reparametrized problem \f$ f(y) = |y|^2 + |A_c R_t^{-1} y - \bar{b_y}|^2 \f$, where \f$ y = R_t(x - x_t) \f$, and \f$ \bar{b_y} = (b_c - A_c x_t) \f$ + * + * In the matrix form, it is equivalent to solving \f$ [A_c R_t^{-1} ; I ] y = [\bar{b_y} ; 0] \f$. We can solve it + * with the least-squares variation of the conjugate gradient method. + * + * To use it in nonlinear optimization, please see the following example + * + * LevenbergMarquardtParams parameters; + * parameters.linearSolverType = SuccessiveLinearizationParams::CONJUGATE_GRADIENT; + * parameters.iterativeParams = boost::make_shared(); + * LevenbergMarquardtOptimizer optimizer(graph, initialEstimate, parameters); + * Values result = optimizer.optimize(); + * + * \nosubgrouping + */ + +class SubgraphSolver : public IterativeSolver { + +public: + typedef SubgraphSolverParameters Parameters; + +protected: + Parameters parameters_; + SubgraphPreconditioner::shared_ptr pc_; ///< preconditioner object + +public: + /* Given a gaussian factor graph, split it into a spanning tree (A1) + others (A2) for SPCG */ + SubgraphSolver(const GaussianFactorGraph &A, const Parameters ¶meters); + SubgraphSolver(const GaussianFactorGraph::shared_ptr &A, const Parameters ¶meters); + + /* The user specify the subgraph part and the constraint part, may throw exception if A1 is underdetermined */ + SubgraphSolver(const GaussianFactorGraph &Ab1, const GaussianFactorGraph &Ab2, const Parameters ¶meters); + SubgraphSolver(const GaussianFactorGraph::shared_ptr &Ab1, const GaussianFactorGraph::shared_ptr &Ab2, const Parameters ¶meters); + + /* The same as above, but the A1 is solved before */ + SubgraphSolver(const GaussianBayesNet::shared_ptr &Rc1, const GaussianFactorGraph &Ab2, const Parameters ¶meters); + SubgraphSolver(const GaussianBayesNet::shared_ptr &Rc1, const GaussianFactorGraph::shared_ptr &Ab2, const Parameters ¶meters); + + virtual ~SubgraphSolver() {} + virtual VectorValues optimize () ; + +protected: + + void initialize(const GaussianFactorGraph &jfg); + void initialize(const GaussianBayesNet::shared_ptr &Rc1, const GaussianFactorGraph::shared_ptr &Ab2); + + boost::tuple + splitGraph(const GaussianFactorGraph &gfg) ; +}; + +} // namespace gtsam + + diff --git a/gtsam/linear/VectorValues.cpp b/gtsam/linear/VectorValues.cpp index a0af31c70..fd7f2757c 100644 --- a/gtsam/linear/VectorValues.cpp +++ b/gtsam/linear/VectorValues.cpp @@ -17,10 +17,12 @@ */ #include +#include #include using namespace std; -using namespace gtsam; + +namespace gtsam { /* ************************************************************************* */ VectorValues::VectorValues(const VectorValues& other) { @@ -43,6 +45,14 @@ VectorValues VectorValues::Zero(const VectorValues& x) { return cloned; } +/* ************************************************************************* */ +vector VectorValues::dims() const { + std::vector result(this->size()); + for(Index j = 0; j < this->size(); ++j) + result[j] = this->dim(j); + return result; +} + /* ************************************************************************* */ void VectorValues::insert(Index j, const Vector& value) { // Make sure j does not already exist @@ -77,10 +87,10 @@ void VectorValues::insert(Index j, const Vector& value) { } /* ************************************************************************* */ -void VectorValues::print(const std::string& str) const { +void VectorValues::print(const std::string& str, const IndexFormatter& formatter) const { std::cout << str << ": " << size() << " elements\n"; for (Index var = 0; var < size(); ++var) - std::cout << " " << var << ": \n" << operator[](var) << "\n"; + std::cout << " " << formatter(var) << ": \n" << operator[](var) << "\n"; std::cout.flush(); } @@ -151,6 +161,14 @@ VectorValues VectorValues::operator+(const VectorValues& c) const { return result; } +/* ************************************************************************* */ +VectorValues VectorValues::operator-(const VectorValues& c) const { + assert(this->hasSameStructure(c)); + VectorValues result(SameStructure(c)); + result.values_ = this->values_ - c.values_; + return result; +} + /* ************************************************************************* */ void VectorValues::operator+=(const VectorValues& c) { assert(this->hasSameStructure(c)); @@ -158,20 +176,30 @@ void VectorValues::operator+=(const VectorValues& c) { } /* ************************************************************************* */ -VectorValues& VectorValues::operator=(const Permuted& rhs) { - if(this->size() != rhs.size()) - throw std::invalid_argument("VectorValues assignment from Permuted requires pre-allocation, see documentation."); - for(size_t j=0; jsize(); ++j) { - if(exists(j)) { - SubVector& l(this->at(j)); - const SubVector& r(rhs[j]); - if(l.rows() != r.rows()) - throw std::invalid_argument("VectorValues assignment from Permuted requires pre-allocation, see documentation."); - l = r; - } else { - if(rhs.container().exists(rhs.permutation()[j])) - throw std::invalid_argument("VectorValues assignment from Permuted requires pre-allocation, see documentation."); - } - } - return *this; +VectorValues VectorValues::permute(const Permutation& permutation) const { + // Create result and allocate space + VectorValues lhs; + lhs.values_.resize(this->dim()); + lhs.maps_.reserve(this->size()); + + // Copy values from this VectorValues to the permuted VectorValues + size_t lhsPos = 0; + for(size_t i = 0; i < this->size(); ++i) { + // Map the next LHS subvector to the next slice of the LHS vector + lhs.maps_.push_back(SubVector(lhs.values_, lhsPos, this->at(permutation[i]).size())); + // Copy the data from the RHS subvector to the LHS subvector + lhs.maps_[i] = this->at(permutation[i]); + // Increment lhs position + lhsPos += lhs.maps_[i].size(); + } + + return lhs; } + +/* ************************************************************************* */ +void VectorValues::swap(VectorValues& other) { + this->values_.swap(other.values_); + this->maps_.swap(other.maps_); +} + +} \ No newline at end of file diff --git a/gtsam/linear/VectorValues.h b/gtsam/linear/VectorValues.h index 7939b486d..9fad99223 100644 --- a/gtsam/linear/VectorValues.h +++ b/gtsam/linear/VectorValues.h @@ -19,14 +19,18 @@ #include #include -#include +#include #include #include #include +#include namespace gtsam { + // Forward declarations + class Permutation; + /** * This class represents a collection of vector-valued variables associated * each with a unique integer index. It is typically used to store the variables @@ -130,6 +134,9 @@ namespace gtsam { /** Return the summed dimensionality of all variables. */ size_t dim() const { return values_.rows(); } + /** Return the dimension of each vector in this container */ + std::vector dims() const; + /** Check whether a variable with index \c j exists. */ bool exists(Index j) const { return j < size() && maps_[j].rows() > 0; } @@ -147,7 +154,7 @@ namespace gtsam { /** Insert a vector \c value with index \c j. * Causes reallocation. Can be used to insert values in any order, but - * throws an invalid_argument exception if the index \j is already used. + * throws an invalid_argument exception if the index \c j is already used. * @param value The vector to be inserted. * @param j The index with which the value will be associated. */ @@ -158,23 +165,24 @@ namespace gtsam { iterator begin() { chk(); return maps_.begin(); } ///< Iterator over variables const_iterator begin() const { chk(); return maps_.begin(); } ///< Iterator over variables - iterator end() { chk(); return maps_.end(); } ///< Iterator over variables + iterator end() { chk(); return maps_.end(); } ///< Iterator over variables const_iterator end() const { chk(); return maps_.end(); } ///< Iterator over variables - reverse_iterator rbegin() { chk(); return maps_.rbegin(); } ///< Reverse iterator over variables + reverse_iterator rbegin() { chk(); return maps_.rbegin(); } ///< Reverse iterator over variables const_reverse_iterator rbegin() const { chk(); return maps_.rbegin(); } ///< Reverse iterator over variables - reverse_iterator rend() { chk(); return maps_.rend(); } ///< Reverse iterator over variables + reverse_iterator rend() { chk(); return maps_.rend(); } ///< Reverse iterator over variables const_reverse_iterator rend() const { chk(); return maps_.rend(); } ///< Reverse iterator over variables /** print required by Testable for unit testing */ - void print(const std::string& str = "VectorValues: ") const; + void print(const std::string& str = "VectorValues: ", + const IndexFormatter& formatter =DefaultIndexFormatter) const; /** equals required by Testable for unit testing */ bool equals(const VectorValues& x, double tol = 1e-9) const; - /// @} + /// @{ /// \anchor AdvancedConstructors /// @name Advanced Constructors - /// @{ + /// @} /** Construct from a container of variable dimensions (in variable order), without initializing any values. */ template @@ -262,22 +270,39 @@ namespace gtsam { return gtsam::dot(this->values_, V.values_); } + /** Vector L2 norm */ + inline double norm() const { + return this->vector().norm(); + } + /** * + operator does element-wise addition. Both VectorValues must have the * same structure (checked when NDEBUG is not defined). */ VectorValues operator+(const VectorValues& c) const; + /** + * + operator does element-wise subtraction. Both VectorValues must have the + * same structure (checked when NDEBUG is not defined). + */ + VectorValues operator-(const VectorValues& c) const; + /** * += operator does element-wise addition. Both VectorValues must have the * same structure (checked when NDEBUG is not defined). */ void operator+=(const VectorValues& c); - /** Assignment operator from Permuted, requires the dimensions - * of the assignee to already be properly pre-allocated. - */ - VectorValues& operator=(const Permuted& rhs); + /** + * Permute the entries of this VectorValues, returns a new VectorValues as + * the result. + */ + VectorValues permute(const Permutation& permutation) const; + + /** + * Swap the data in this VectorValues with another. + */ + void swap(VectorValues& other); /// @} @@ -296,6 +321,16 @@ namespace gtsam { void copyStructureFrom(const VectorValues& other); public: + + /** + * scale a vector by a scalar + */ + friend VectorValues operator*(const double a, const VectorValues &V) { + VectorValues result(VectorValues::SameStructure(V)); + result.values_ = a * V.values_; + return result; + } + /// TODO: linear algebra interface seems to have been added for SPCG. friend size_t dim(const VectorValues& V) { return V.dim(); @@ -384,7 +419,7 @@ namespace gtsam { maps_.reserve(maps_.size() + dimensions.size()); BOOST_FOREACH(size_t dim, dimensions) { maps_.push_back(values_.segment(varStart, dim)); - varStart += dim; // varStart is continued from first for loop + varStart += (int)dim; // varStart is continued from first for loop } } diff --git a/gtsam/linear/iterative-inl.h b/gtsam/linear/iterative-inl.h index 02048d3df..5cc0841b0 100644 --- a/gtsam/linear/iterative-inl.h +++ b/gtsam/linear/iterative-inl.h @@ -18,12 +18,9 @@ #pragma once -#include - -#include #include - -using namespace std; +#include +#include namespace gtsam { @@ -32,13 +29,13 @@ namespace gtsam { template struct CGState { - typedef IterativeOptimizationParameters Parameters; + typedef ConjugateGradientParameters Parameters; const Parameters ¶meters_; - int k; - bool steepest; - V g, d; - double gamma, threshold; + int k; ///< iteration + bool steepest; ///< flag to indicate we are doing steepest descent + V g, d; ///< gradient g and search direction d for CG + double gamma, threshold; ///< gamma (squared L2 norm of g) and convergence threshold E Ad; /* ************************************************************************* */ @@ -53,7 +50,7 @@ namespace gtsam { // init gamma and calculate threshold gamma = dot(g,g) ; - threshold = ::max(parameters_.epsilon_abs(), parameters_.epsilon() * parameters_.epsilon() * gamma); + threshold = std::max(parameters_.epsilon_abs(), parameters_.epsilon() * parameters_.epsilon() * gamma); // Allocate and calculate A*d for first iteration if (gamma > parameters_.epsilon_abs()) Ad = Ab * d; @@ -62,10 +59,10 @@ namespace gtsam { /* ************************************************************************* */ // print void print(const V& x) { - cout << "iteration = " << k << endl; + std::cout << "iteration = " << k << std::endl; gtsam::print(x,"x"); gtsam::print(g, "g"); - cout << "dotg = " << gamma << endl; + std::cout << "dotg = " << gamma << std::endl; gtsam::print(d, "d"); gtsam::print(Ad, "Ad"); } @@ -82,6 +79,7 @@ namespace gtsam { /* ************************************************************************* */ // take a step, return true if converged bool step(const S& Ab, V& x) { + if ((++k) >= ((int)parameters_.maxIterations())) return true; //----------------------------------> @@ -94,9 +92,12 @@ namespace gtsam { // check for convergence double new_gamma = dot(g, g); - if (parameters_.verbosity() != IterativeOptimizationParameters::SILENT) - cout << "iteration " << k << ": alpha = " << alpha - << ", dotg = " << new_gamma << endl; + + if (parameters_.verbosity() != ConjugateGradientParameters::SILENT) + std::cout << "iteration " << k << ": alpha = " << alpha + << ", dotg = " << new_gamma + << std::endl; + if (new_gamma < threshold) return true; // calculate new search direction @@ -121,22 +122,20 @@ namespace gtsam { // conjugate gradient method. // S: linear system, V: step vector, E: errors template - V conjugateGradients( - const S& Ab, - V x, - const IterativeOptimizationParameters ¶meters, - bool steepest = false) { + V conjugateGradients(const S& Ab, V x, const ConjugateGradientParameters ¶meters, bool steepest) { CGState state(Ab, x, parameters, steepest); - if (parameters.verbosity() != IterativeOptimizationParameters::SILENT) - cout << "CG: epsilon = " << parameters.epsilon() - << ", maxIterations = " << parameters.maxIterations() - << ", ||g0||^2 = " << state.gamma - << ", threshold = " << state.threshold << endl; + + if (parameters.verbosity() != ConjugateGradientParameters::SILENT) + std::cout << "CG: epsilon = " << parameters.epsilon() + << ", maxIterations = " << parameters.maxIterations() + << ", ||g0||^2 = " << state.gamma + << ", threshold = " << state.threshold + << std::endl; if ( state.gamma < state.threshold ) { - if (parameters.verbosity() != IterativeOptimizationParameters::SILENT) - cout << "||g0||^2 < threshold, exiting immediately !" << endl; + if (parameters.verbosity() != ConjugateGradientParameters::SILENT) + std::cout << "||g0||^2 < threshold, exiting immediately !" << std::endl; return x; } diff --git a/gtsam/linear/iterative.cpp b/gtsam/linear/iterative.cpp index c431e0c82..07d4de865 100644 --- a/gtsam/linear/iterative.cpp +++ b/gtsam/linear/iterative.cpp @@ -15,55 +15,64 @@ * @author Frank Dellaert * @date Dec 28, 2009 */ -#include +#include #include #include #include -#include -#include +#include + +#include using namespace std; namespace gtsam { - /* ************************************************************************* */ - void System::print (const string& s) const { - cout << s << endl; - gtsam::print(A_, "A"); - gtsam::print(b_, "b"); - } + /* ************************************************************************* */ + void System::print(const string& s) const { + cout << s << endl; + gtsam::print(A_, "A"); + gtsam::print(b_, "b"); + } - /* ************************************************************************* */ + /* ************************************************************************* */ - Vector steepestDescent(const System& Ab, const Vector& x, const IterativeOptimizationParameters & parameters) { - return conjugateGradients (Ab, x, parameters, true); - } + Vector steepestDescent(const System& Ab, const Vector& x, + const ConjugateGradientParameters & parameters) { + return conjugateGradients(Ab, x, parameters, true); + } - Vector conjugateGradientDescent(const System& Ab, const Vector& x, const IterativeOptimizationParameters & parameters) { - return conjugateGradients (Ab, x, parameters); - } + Vector conjugateGradientDescent(const System& Ab, const Vector& x, + const ConjugateGradientParameters & parameters) { + return conjugateGradients(Ab, x, parameters); + } - /* ************************************************************************* */ - Vector steepestDescent(const Matrix& A, const Vector& b, const Vector& x, const IterativeOptimizationParameters & parameters) { - System Ab(A, b); - return conjugateGradients (Ab, x, parameters, true); - } + /* ************************************************************************* */ + Vector steepestDescent(const Matrix& A, const Vector& b, const Vector& x, + const ConjugateGradientParameters & parameters) { + System Ab(A, b); + return conjugateGradients(Ab, x, parameters, true); + } - Vector conjugateGradientDescent(const Matrix& A, const Vector& b, const Vector& x, const IterativeOptimizationParameters & parameters) { - System Ab(A, b); - return conjugateGradients (Ab, x, parameters); - } + Vector conjugateGradientDescent(const Matrix& A, const Vector& b, + const Vector& x, const ConjugateGradientParameters & parameters) { + System Ab(A, b); + return conjugateGradients(Ab, x, parameters); + } - /* ************************************************************************* */ - VectorValues steepestDescent(const FactorGraph& fg, const VectorValues& x, const IterativeOptimizationParameters & parameters) { - return conjugateGradients, VectorValues, Errors> (fg, x, parameters, true); - } + /* ************************************************************************* */ + VectorValues steepestDescent(const GaussianFactorGraph& fg, + const VectorValues& x, const ConjugateGradientParameters & parameters) { + return conjugateGradients( + fg, x, parameters, true); + } - VectorValues conjugateGradientDescent(const FactorGraph& fg, const VectorValues& x, const IterativeOptimizationParameters & parameters) { - return conjugateGradients, VectorValues, Errors> (fg, x, parameters); - } + VectorValues conjugateGradientDescent(const GaussianFactorGraph& fg, + const VectorValues& x, const ConjugateGradientParameters & parameters) { + return conjugateGradients( + fg, x, parameters); + } - /* ************************************************************************* */ +/* ************************************************************************* */ } // namespace gtsam diff --git a/gtsam/linear/iterative.h b/gtsam/linear/iterative.h index 2e6f77f10..0eb04bf49 100644 --- a/gtsam/linear/iterative.h +++ b/gtsam/linear/iterative.h @@ -1,6 +1,6 @@ /* ---------------------------------------------------------------------------- - * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * GTSAM Copyright 2010, Georgia Tech Research Corporation, * Atlanta, Georgia 30332-0415 * All Rights Reserved * Authors: Frank Dellaert, et al. (see THANKS for the full author list) @@ -20,7 +20,7 @@ #include #include -#include +#include namespace gtsam { @@ -31,19 +31,18 @@ namespace gtsam { * "Vector" class E needs dot(v,v) * @param Ab, the "system" that needs to be solved, examples below * @param x is the initial estimate - * @param epsilon determines the convergence criterion: norm(g) - V conjugateGradients(const S& Ab, V x, bool verbose, double epsilon, - size_t maxIterations, bool steepest = false); + template + V conjugateGradients(const S& Ab, V x, + const ConjugateGradientParameters ¶meters, bool steepest = false); /** * Helper class encapsulating the combined system |Ax-b_|^2 * Needed to run Conjugate Gradients on matrices * */ class System { + private: const Matrix& A_; const Vector& b_; @@ -105,7 +104,7 @@ namespace gtsam { Vector conjugateGradientDescent( const System& Ab, const Vector& x, - const IterativeOptimizationParameters & parameters); + const ConjugateGradientParameters & parameters); /** convenience calls using matrices, will create System class internally: */ @@ -116,7 +115,7 @@ namespace gtsam { const Matrix& A, const Vector& b, const Vector& x, - const IterativeOptimizationParameters & parameters); + const ConjugateGradientParameters & parameters); /** * Method of conjugate gradients (CG), Matrix version @@ -125,25 +124,26 @@ namespace gtsam { const Matrix& A, const Vector& b, const Vector& x, - const IterativeOptimizationParameters & parameters); - - class GaussianFactorGraph; + const ConjugateGradientParameters & parameters); /** * Method of steepest gradients, Gaussian Factor Graph version - * */ + */ VectorValues steepestDescent( const GaussianFactorGraph& fg, const VectorValues& x, - const IterativeOptimizationParameters & parameters); + const ConjugateGradientParameters & parameters); /** * Method of conjugate gradients (CG), Gaussian Factor Graph version - * */ + */ VectorValues conjugateGradientDescent( const GaussianFactorGraph& fg, const VectorValues& x, - const IterativeOptimizationParameters & parameters); + const ConjugateGradientParameters & parameters); } // namespace gtsam + +#include + diff --git a/gtsam/linear/linearExceptions.h b/gtsam/linear/linearExceptions.h new file mode 100644 index 000000000..5e90f57b3 --- /dev/null +++ b/gtsam/linear/linearExceptions.h @@ -0,0 +1,180 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file linearExceptions.h + * @brief Exceptions that may be thrown by linear solver components + * @author Richard Roberts + * @date Aug 17, 2012 + */ +#pragma once + +#include +#include +#include + +namespace gtsam { + + /** + Thrown when a linear system is ill-posed. The most common cause for this + error is having underconstrained variables. Mathematically, the system is + either underdetermined, or its quadratic error function is concave in some + directions. + + Examples of situations causing this error are: + - A landmark observed by two cameras with a very small baseline will have + high uncertainty in its distance from the cameras but low uncertainty + in its bearing, creating a poorly-conditioned system. + - A landmark observed by only a single ProjectionFactor, RangeFactor, or + BearingFactor (the landmark is not completely constrained). + - An overall scale or rigid transformation ambiguity, for example missing + a prior or hard constraint on the first pose, or missing a scale + constraint between the first two cameras (in structure-from-motion). + + Mathematically, the following conditions cause this problem: + - Underdetermined system: This occurs when the variables are not + completely constrained by factors. Even if all variables are involved + in factors, the variables can still be numerically underconstrained, + (for example, if a landmark is observed by only one ProjectionFactor). + Mathematically in this case, the rank of the linear Jacobian or Hessian + is less than the number of scalars in the system. + - Indefinite system: This condition occurs when the system Hessian is + indefinite, i.e. non-positive-semidefinite. Note that this condition + can also indicate an underdetermined system, but when solving with + Cholesky, accumulation of numerical errors can cause the system to + become indefinite (have some negative eigenvalues) even if it is in + reality positive semi-definite (has some near-zero positive + eigenvalues). Alternatively, if the system contains some + HessianFactor's with negative eigenvalues, these can create a truly + indefinite system, whose quadratic error function has negative + curvature in some directions. + - Poorly-conditioned system: A system that is positive-definite (has a + unique solution) but is numerically ill-conditioned can accumulate + numerical errors during solving that cause the system to become + indefinite later during the elimination process. Note that poorly- + conditioned systems will usually have inaccurate solutions, even if + they do not always trigger this error. Systems with almost- + unconstrained variables or vastly different measurement uncertainties + or variable units can be poorly-conditioned. + + Resolving this problem: + - This exception contains the variable at which the problem was + discovered (IndeterminantLinearSystemException::nearbyVariable()). + Note, however, that this is not necessarily the variable where the + problem originates. For example, in the case that a prior on the + first camera was forgotten, it may only be another camera or landmark + where the problem can be detected. Where the problem is detected + depends on the graph structure and variable elimination ordering. + - MATLAB (or similar software) is a useful tool to diagnose this problem. + Use GaussianFactorGraph::sparseJacobian_(), + GaussianFactorGraph::sparseJacobian() + GaussianFactorGraph::denseJacobian(), and + GaussianFactorGraph::denseHessian() to output the linear graph in + matrix format. If using the MATLAB wrapper, the returned matrices can + be immediately inspected and analyzed using standard methods. If not + using the MATLAB wrapper, the output of these functions may be written + to text files and then loaded into MATLAB. + - When outputting linear graphs as Jacobian matrices, rows are ordered in + the same order as factors in the graph, which each factor occupying the + number of rows indicated by its JacobianFactor::rows() function. Each + column appears in elimination ordering, as in the Ordering class. Each + variable occupies the number of columns indicated by the + JacobianFactor::getDim() function. + - When outputting linear graphs as Hessian matrices, rows and columns are + ordered in elimination order and occupy scalars in the same way as + described for Jacobian columns in the previous bullet. + */ + class IndeterminantLinearSystemException : public std::exception { + Index j_; + mutable std::string what_; + public: + IndeterminantLinearSystemException(Index j) throw() : j_(j) {} + virtual ~IndeterminantLinearSystemException() throw() {} + Index nearbyVariable() const { return j_; } + virtual const char* what() const throw() { + if(what_.empty()) + what_ = +"\nIndeterminant linear system detected while working near variable with\n" +"index " + boost::lexical_cast(j_) + " in ordering.\n" +"\n\ +Thrown when a linear system is ill-posed. The most common cause for this\n\ +error is having underconstrained variables. Mathematically, the system is\n\ +either underdetermined, or its quadratic error function is concave in some\n\ +directions.\n\ +\n\ +Examples of situations causing this error are:\n\ +- A landmark observed by two cameras with a very small baseline will have\n\ + high uncertainty in its distance from the cameras but low uncertainty\n\ + in its bearing, creating a poorly-conditioned system.\n\ +- A landmark observed by only a single ProjectionFactor, RangeFactor, or\n\ + BearingFactor (the landmark is not completely constrained).\n\ +- An overall scale or rigid transformation ambiguity, for example missing\n\ + a prior or hard constraint on the first pose, or missing a scale\n\ + constraint between the first two cameras (in structure-from-motion).\n\ +\n\ +Mathematically, the following conditions cause this problem:\n\ +- Underdetermined system: This occurs when the variables are not\n\ + completely constrained by factors. Even if all variables are involved\n\ + in factors, the variables can still be numerically underconstrained,\n\ + (for example, if a landmark is observed by only one ProjectionFactor).\n\ + Mathematically in this case, the rank of the linear Jacobian or Hessian\n\ + is less than the number of scalars in the system.\n\ +- Indefinite system: This condition occurs when the system Hessian is\n\ + indefinite, i.e. non-positive-semidefinite. Note that this condition\n\ + can also indicate an underdetermined system, but when solving with\n\ + Cholesky, accumulation of numerical errors can cause the system to\n\ + become indefinite (have some negative eigenvalues) even if it is in\n\ + reality positive semi-definite (has some near-zero positive\n\ + eigenvalues). Alternatively, if the system contains some\n\ + HessianFactor's with negative eigenvalues, these can create a truly\n\ + indefinite system, whose quadratic error function has negative\n\ + curvature in some directions.\n\ +- Poorly-conditioned system: A system that is positive-definite (has a\n\ + unique solution) but is numerically ill-conditioned can accumulate\n\ + numerical errors during solving that cause the system to become\n\ + indefinite later during the elimination process. Note that poorly-\n\ + conditioned systems will usually have inaccurate solutions, even if\n\ + they do not always trigger this error. Systems with almost-\n\ + unconstrained variables or vastly different measurement uncertainties\n\ + or variable units can be poorly-conditioned.\n\ +\n\ +Resolving this problem:\n\ +- This exception contains the variable at which the problem was\n\ + discovered (IndeterminantLinearSystemException::nearbyVariable()).\n\ + Note, however, that this is not necessarily the variable where the\n\ + problem originates. For example, in the case that a prior on the\n\ + first camera was forgotten, it may only be another camera or landmark\n\ + where the problem can be detected. Where the problem is detected\n\ + depends on the graph structure and variable elimination ordering.\n\ +- MATLAB (or similar software) is a useful tool to diagnose this problem.\n\ + Use GaussianFactorGraph::sparseJacobian_(),\n\ + GaussianFactorGraph::sparseJacobian()\n\ + GaussianFactorGraph::denseJacobian(), and\n\ + GaussianFactorGraph::denseHessian() to output the linear graph in\n\ + matrix format. If using the MATLAB wrapper, the returned matrices can\n\ + be immediately inspected and analyzed using standard methods. If not\n\ + using the MATLAB wrapper, the output of these functions may be written\n\ + to text files and then loaded into MATLAB.\n\ +- When outputting linear graphs as Jacobian matrices, rows are ordered in\n\ + the same order as factors in the graph, which each factor occupying the\n\ + number of rows indicated by its JacobianFactor::rows() function. Each\n\ + column appears in elimination ordering, as in the Ordering class. Each\n\ + variable occupies the number of columns indicated by the\n\ + JacobianFactor::getDim() function.\n\ +- When outputting linear graphs as Hessian matrices, rows and columns are\n\ + ordered in elimination order and occupy scalars in the same way as\n\ + described for Jacobian columns in the previous bullet.\ +"; + return what_.c_str(); + } + }; + +} diff --git a/gtsam/linear/tests/testGaussianConditional.cpp b/gtsam/linear/tests/testGaussianConditional.cpp index 93030b598..8b0c5e239 100644 --- a/gtsam/linear/tests/testGaussianConditional.cpp +++ b/gtsam/linear/tests/testGaussianConditional.cpp @@ -267,55 +267,6 @@ TEST( GaussianConditional, solve_multifrontal ) } -/* ************************************************************************* */ -TEST( GaussianConditional, solve_multifrontal_permuted ) -{ - // create full system, 3 variables, 2 frontals, all 2 dim - Matrix full_matrix = Matrix_(4, 7, - 1.0, 0.0, 2.0, 0.0, 3.0, 0.0, 0.1, - 0.0, 1.0, 0.0, 2.0, 0.0, 3.0, 0.2, - 0.0, 0.0, 3.0, 0.0, 4.0, 0.0, 0.3, - 0.0, 0.0, 0.0, 3.0, 0.0, 4.0, 0.4); - - // 3 variables, all dim=2 - vector dims; dims += 2, 2, 2, 1; - GaussianConditional::rsd_type matrices(full_matrix, dims.begin(), dims.end()); - Vector sigmas = ones(4); - vector cgdims; cgdims += _x_, _x1_, _l1_; - GaussianConditional cg(cgdims.begin(), cgdims.end(), 2, matrices, sigmas); - - EXPECT(assert_equal(Vector_(4, 0.1, 0.2, 0.3, 0.4), cg.get_d())); - - // partial solution - Vector sl1 = Vector_(2, 9.0, 10.0); - - // elimination order; _x_, _x1_, _l1_ - VectorValues actualUnpermuted(vector(3, 2)); - Permutation permutation(3); - permutation[0] = 2; - permutation[1] = 0; - permutation[2] = 1; - Permuted actual(permutation, actualUnpermuted); - actual[_x_] = Vector_(2, 0.1, 0.2); // rhs - actual[_x1_] = Vector_(2, 0.3, 0.4); // rhs - actual[_l1_] = sl1; // parent - - VectorValues expectedUnpermuted(vector(3, 2)); - Permuted expected(permutation, expectedUnpermuted); - expected[_x_] = Vector_(2, -3.1,-3.4); - expected[_x1_] = Vector_(2, -11.9,-13.2); - expected[_l1_] = sl1; - - // verify indices/size - EXPECT_LONGS_EQUAL(3, cg.size()); - EXPECT_LONGS_EQUAL(4, cg.dim()); - - // solve and verify - cg.solveInPlace(actual); - EXPECT(assert_equal(expected.container(), actual.container(), tol)); - -} - /* ************************************************************************* */ TEST( GaussianConditional, solveTranspose ) { static const Index _y_=1; diff --git a/gtsam/linear/tests/testGaussianFactorGraph.cpp b/gtsam/linear/tests/testGaussianFactorGraph.cpp index 34009f856..cb835a76a 100644 --- a/gtsam/linear/tests/testGaussianFactorGraph.cpp +++ b/gtsam/linear/tests/testGaussianFactorGraph.cpp @@ -36,7 +36,7 @@ static const Index _x0_=0, _x1_=1, _x2_=2, _x3_=3, _x4_=4, _x_=5, _y_=6, _l1_=7, #endif static SharedDiagonal - sigma0_1 = sharedSigma(2,0.1), sigma_02 = sharedSigma(2,0.2), + sigma0_1 = noiseModel::Isotropic::Sigma(2,0.1), sigma_02 = noiseModel::Isotropic::Sigma(2,0.2), constraintModel = noiseModel::Constrained::All(2); /* ************************************************************************* */ @@ -50,10 +50,8 @@ TEST(GaussianFactorGraph, initialization) { fg.add(0, -5*eye(2), 2, 5*eye(2), Vector_(2, 0.0, 1.0), unit2); fg.add(1, -5*eye(2), 2, 5*eye(2), Vector_(2, -1.0, 1.5), unit2); - FactorGraph graph = *fg.dynamicCastFactors >(); - - EXPECT_LONGS_EQUAL(4, graph.size()); - JacobianFactor factor = *graph[0]; + EXPECT_LONGS_EQUAL(4, fg.size()); + JacobianFactor factor = *boost::dynamic_pointer_cast(fg[0]); // Test sparse, which takes a vector and returns a matrix, used in MATLAB // Note that this the augmented vector and the RHS is in column 7 @@ -155,14 +153,20 @@ TEST(GaussianFactorGraph, Combine2) gfg.add(0, A10, 1, A11, b1, noiseModel::Diagonal::Sigmas(s1, true)); gfg.add(1, A21, b2, noiseModel::Diagonal::Sigmas(s2, true)); - JacobianFactor actual = *CombineJacobians(*gfg.dynamicCastFactors > (), VariableSlots(gfg)); + // Convert to Jacobians, inefficient copy of all factors instead of selectively converting only Hessians + FactorGraph jacobians; + BOOST_FOREACH(const GaussianFactorGraph::sharedFactor& factor, gfg) { + jacobians.push_back(boost::make_shared(*factor)); + } + + // Combine Jacobians into a single dense factor + JacobianFactor actual = *CombineJacobians(jacobians, VariableSlots(gfg)); Matrix zero3x3 = zeros(3,3); - Matrix A0 = gtsam::stack(3, &A10, &zero3x3, &zero3x3); - Matrix A1 = gtsam::stack(3, &A11, &A01, &A21); - Vector b = gtsam::concatVectors(3, &b1, &b0, &b2); - Vector sigmas = gtsam::concatVectors(3, &s1, &s0, &s2); + Matrix A0 = gtsam::stack(3, &zero3x3, &A10, &zero3x3); + Matrix A1 = gtsam::stack(3, &A01, &A11, &A21); + Vector b = gtsam::concatVectors(3, &b0, &b1, &b2); + Vector sigmas = gtsam::concatVectors(3, &s0, &s1, &s2); JacobianFactor expected(0, A0, 1, A1, b, noiseModel::Diagonal::Sigmas(sigmas, true)); @@ -213,8 +217,7 @@ TEST(GaussianFactor, CombineAndEliminate) GaussianConditional::shared_ptr actualBN; GaussianFactor::shared_ptr actualFactor; - boost::tie(actualBN, actualFactor) = // - EliminateQR(*gfg.dynamicCastFactors > (), 1); + boost::tie(actualBN, actualFactor) = EliminateQR(gfg, 1); JacobianFactor::shared_ptr actualJacobian = boost::dynamic_pointer_cast< JacobianFactor>(actualFactor); @@ -231,26 +234,26 @@ TEST( NonlinearFactorGraph, combine2){ A11(1,0) = 0; A11(1,1) = 1; Vector b(2); b(0) = 2; b(1) = -1; - JacobianFactor::shared_ptr f1(new JacobianFactor(_x1_, A11, b*sigma1, sharedSigma(2,sigma1))); + JacobianFactor::shared_ptr f1(new JacobianFactor(_x1_, A11, b*sigma1, noiseModel::Isotropic::Sigma(2,sigma1))); double sigma2 = 0.5; A11(0,0) = 1; A11(0,1) = 0; A11(1,0) = 0; A11(1,1) = -1; b(0) = 4 ; b(1) = -5; - JacobianFactor::shared_ptr f2(new JacobianFactor(_x1_, A11, b*sigma2, sharedSigma(2,sigma2))); + JacobianFactor::shared_ptr f2(new JacobianFactor(_x1_, A11, b*sigma2, noiseModel::Isotropic::Sigma(2,sigma2))); double sigma3 = 0.25; A11(0,0) = 1; A11(0,1) = 0; A11(1,0) = 0; A11(1,1) = -1; b(0) = 3 ; b(1) = -88; - JacobianFactor::shared_ptr f3(new JacobianFactor(_x1_, A11, b*sigma3, sharedSigma(2,sigma3))); + JacobianFactor::shared_ptr f3(new JacobianFactor(_x1_, A11, b*sigma3, noiseModel::Isotropic::Sigma(2,sigma3))); // TODO: find a real sigma value for this example double sigma4 = 0.1; A11(0,0) = 6; A11(0,1) = 0; A11(1,0) = 0; A11(1,1) = 7; b(0) = 5 ; b(1) = -6; - JacobianFactor::shared_ptr f4(new JacobianFactor(_x1_, A11*sigma4, b*sigma4, sharedSigma(2,sigma4))); + JacobianFactor::shared_ptr f4(new JacobianFactor(_x1_, A11*sigma4, b*sigma4, noiseModel::Isotropic::Sigma(2,sigma4))); vector lfg; lfg.push_back(f1); @@ -283,7 +286,7 @@ TEST( NonlinearFactorGraph, combine2){ TEST(GaussianFactor, linearFactorN){ Matrix I = eye(2); vector f; - SharedDiagonal model = sharedSigma(2,1.0); + SharedDiagonal model = noiseModel::Isotropic::Sigma(2,1.0); f.push_back(JacobianFactor::shared_ptr(new JacobianFactor(_x1_, I, Vector_(2, 10.0, 5.0), model))); f.push_back(JacobianFactor::shared_ptr(new JacobianFactor(_x1_, -10 * I, @@ -371,7 +374,7 @@ TEST(GaussianFactor, eliminateFrontals) make_pair( 9, Matrix(Ab.block(0, 6, 4, 2))), make_pair(11, Matrix(Ab.block(0, 8, 4, 2))); Vector b1 = Ab.col(10).segment(0, 4); - JacobianFactor::shared_ptr factor1(new JacobianFactor(terms1, b1, sharedSigma(4, 0.5))); + JacobianFactor::shared_ptr factor1(new JacobianFactor(terms1, b1, noiseModel::Isotropic::Sigma(4, 0.5))); // Create second factor list > terms2; @@ -381,7 +384,7 @@ TEST(GaussianFactor, eliminateFrontals) make_pair(9, Matrix(Ab.block(4, 6, 4, 2))), make_pair(11,Matrix(Ab.block(4, 8, 4, 2))); Vector b2 = Ab.col(10).segment(4, 4); - JacobianFactor::shared_ptr factor2(new JacobianFactor(terms2, b2, sharedSigma(4, 0.5))); + JacobianFactor::shared_ptr factor2(new JacobianFactor(terms2, b2, noiseModel::Isotropic::Sigma(4, 0.5))); // Create third factor list > terms3; @@ -390,14 +393,14 @@ TEST(GaussianFactor, eliminateFrontals) make_pair(9, Matrix(Ab.block(8, 6, 4, 2))), make_pair(11,Matrix(Ab.block(8, 8, 4, 2))); Vector b3 = Ab.col(10).segment(8, 4); - JacobianFactor::shared_ptr factor3(new JacobianFactor(terms3, b3, sharedSigma(4, 0.5))); + JacobianFactor::shared_ptr factor3(new JacobianFactor(terms3, b3, noiseModel::Isotropic::Sigma(4, 0.5))); // Create fourth factor list > terms4; terms4 += make_pair(11, Matrix(Ab.block(12, 8, 2, 2))); Vector b4 = Ab.col(10).segment(12, 2); - JacobianFactor::shared_ptr factor4(new JacobianFactor(terms4, b4, sharedSigma(2, 0.5))); + JacobianFactor::shared_ptr factor4(new JacobianFactor(terms4, b4, noiseModel::Isotropic::Sigma(2, 0.5))); // Create factor graph GaussianFactorGraph factors; @@ -407,12 +410,17 @@ TEST(GaussianFactor, eliminateFrontals) factors.push_back(factor4); // extract the dense matrix for the graph - Matrix actualDense = factors.denseJacobian(); + Matrix actualDense = factors.augmentedJacobian(); EXPECT(assert_equal(2.0 * Ab, actualDense)); + // Convert to Jacobians, inefficient copy of all factors instead of selectively converting only Hessians + FactorGraph jacobians; + BOOST_FOREACH(const GaussianFactorGraph::sharedFactor& factor, factors) { + jacobians.push_back(boost::make_shared(*factor)); + } + // Create combined factor - JacobianFactor combined(*CombineJacobians(*factors.dynamicCastFactors > (), VariableSlots(factors))); + JacobianFactor combined(*CombineJacobians(jacobians, VariableSlots(factors))); // Copies factors as they will be eliminated in place JacobianFactor actualFactor_QR = combined; @@ -546,13 +554,13 @@ TEST(GaussianFactor, permuteWithInverse) inversePermutation[4] = 1; inversePermutation[5] = 0; - JacobianFactor actual(1, A1, 3, A2, 5, A3, b, sharedSigma(2, 1.0)); + JacobianFactor actual(1, A1, 3, A2, 5, A3, b, noiseModel::Isotropic::Sigma(2, 1.0)); GaussianFactorGraph actualFG; actualFG.push_back(JacobianFactor::shared_ptr(new JacobianFactor(actual))); VariableIndex actualIndex(actualFG); actual.permuteWithInverse(inversePermutation); // actualIndex.permute(*inversePermutation.inverse()); - JacobianFactor expected(4, A1, 2, A2, 0, A3, b, sharedSigma(2, 1.0)); + JacobianFactor expected(4, A1, 2, A2, 0, A3, b, noiseModel::Isotropic::Sigma(2, 1.0)); GaussianFactorGraph expectedFG; expectedFG.push_back(JacobianFactor::shared_ptr(new JacobianFactor(expected))); // GaussianVariableIndex expectedIndex(expectedFG); @@ -601,7 +609,7 @@ TEST(GaussianFactorGraph, sparseJacobian) { 4., 6.,32.).transpose(); GaussianFactorGraph gfg; - SharedDiagonal model = sharedSigma(2, 0.5); + SharedDiagonal model = noiseModel::Isotropic::Sigma(2, 0.5); gfg.add(0, Matrix_(2,3, 1., 2., 3., 5., 6., 7.), Vector_(2, 4., 8.), model); gfg.add(0, Matrix_(2,3, 9.,10., 0., 0., 0., 0.), 1, Matrix_(2,2, 11., 12., 14., 15.), Vector_(2, 13.,16.), model); @@ -611,7 +619,7 @@ TEST(GaussianFactorGraph, sparseJacobian) { } /* ************************************************************************* */ -TEST(GaussianFactorGraph, denseHessian) { +TEST(GaussianFactorGraph, matrices) { // Create factor graph: // x1 x2 x3 x4 x5 b // 1 2 3 0 0 4 @@ -620,7 +628,7 @@ TEST(GaussianFactorGraph, denseHessian) { // 0 0 0 14 15 16 GaussianFactorGraph gfg; - SharedDiagonal model = sharedUnit(2); + SharedDiagonal model = noiseModel::Unit::Create(2); gfg.add(0, Matrix_(2,3, 1., 2., 3., 5., 6., 7.), Vector_(2, 4., 8.), model); gfg.add(0, Matrix_(2,3, 9.,10., 0., 0., 0., 0.), 1, Matrix_(2,2, 11., 12., 14., 15.), Vector_(2, 13.,16.), model); @@ -631,9 +639,24 @@ TEST(GaussianFactorGraph, denseHessian) { 9,10, 0,11,12,13, 0, 0, 0,14,15,16; + Matrix expectedJacobian = jacobian; Matrix expectedHessian = jacobian.transpose() * jacobian; - Matrix actualHessian = gfg.denseHessian(); + Matrix expectedA = jacobian.leftCols(jacobian.cols()-1); + Vector expectedb = jacobian.col(jacobian.cols()-1); + Matrix expectedL = expectedA.transpose() * expectedA; + Vector expectedeta = expectedA.transpose() * expectedb; + + Matrix actualJacobian = gfg.augmentedJacobian(); + Matrix actualHessian = gfg.augmentedHessian(); + Matrix actualA; Vector actualb; boost::tie(actualA,actualb) = gfg.jacobian(); + Matrix actualL; Vector actualeta; boost::tie(actualL,actualeta) = gfg.hessian(); + + EXPECT(assert_equal(expectedJacobian, actualJacobian)); EXPECT(assert_equal(expectedHessian, actualHessian)); + EXPECT(assert_equal(expectedA, actualA)); + EXPECT(assert_equal(expectedb, actualb)); + EXPECT(assert_equal(expectedL, actualL)); + EXPECT(assert_equal(expectedeta, actualeta)); } /* ************************************************************************* */ diff --git a/gtsam/linear/tests/testGaussianJunctionTree.cpp b/gtsam/linear/tests/testGaussianJunctionTree.cpp index a10f80a4d..c4ddc360b 100644 --- a/gtsam/linear/tests/testGaussianJunctionTree.cpp +++ b/gtsam/linear/tests/testGaussianJunctionTree.cpp @@ -35,10 +35,10 @@ using namespace gtsam; static const Index x2=0, x1=1, x3=2, x4=3; -GaussianFactorGraph createChain() { +static GaussianFactorGraph createChain() { typedef GaussianFactorGraph::sharedFactor Factor; - SharedDiagonal model(Vector_(1, 0.5)); + SharedDiagonal model = noiseModel::Isotropic::Sigma(1, 0.5); Factor factor1(new JacobianFactor(x2, Matrix_(1,1,1.), x1, Matrix_(1,1,1.), Vector_(1,1.), model)); Factor factor2(new JacobianFactor(x2, Matrix_(1,1,1.), x3, Matrix_(1,1,1.), Vector_(1,1.), model)); Factor factor3(new JacobianFactor(x3, Matrix_(1,1,1.), x4, Matrix_(1,1,1.), Vector_(1,1.), model)); diff --git a/gtsam/linear/tests/testHessianFactor.cpp b/gtsam/linear/tests/testHessianFactor.cpp index 59873862a..9c2adcffa 100644 --- a/gtsam/linear/tests/testHessianFactor.cpp +++ b/gtsam/linear/tests/testHessianFactor.cpp @@ -93,7 +93,7 @@ TEST(HessianFactor, ConversionConstructor) { vector > meas; meas.push_back(make_pair(0, Ax2)); meas.push_back(make_pair(1, Al1x1)); - JacobianFactor combined(meas, b2, sigmas); + JacobianFactor combined(meas, b2, noiseModel::Diagonal::Sigmas(sigmas)); HessianFactor actual(combined); @@ -414,10 +414,20 @@ TEST_UNSAFE(HessianFactor, CombineAndEliminate) // create expected Hessian after elimination HessianFactor expectedCholeskyFactor(expectedFactor); - GaussianFactorGraph::EliminationResult actualCholesky = EliminateCholesky( - *gfg.convertCastFactors > (), 1); - HessianFactor::shared_ptr actualFactor = boost::dynamic_pointer_cast< - HessianFactor>(actualCholesky.second); + // Convert all factors to hessians + FactorGraph hessians; + BOOST_FOREACH(const GaussianFactorGraph::sharedFactor& factor, gfg) { + if(boost::shared_ptr hf = boost::dynamic_pointer_cast(factor)) + hessians.push_back(hf); + else if(boost::shared_ptr jf = boost::dynamic_pointer_cast(factor)) + hessians.push_back(boost::make_shared(*jf)); + else + CHECK(false); + } + + // Eliminate + GaussianFactorGraph::EliminationResult actualCholesky = EliminateCholesky(gfg, 1); + HessianFactor::shared_ptr actualFactor = boost::dynamic_pointer_cast(actualCholesky.second); EXPECT(assert_equal(*expectedBN, *actualCholesky.first, 1e-6)); EXPECT(assert_equal(expectedCholeskyFactor, *actualFactor, 1e-6)); @@ -458,7 +468,7 @@ TEST(HessianFactor, eliminate2 ) vector > meas; meas.push_back(make_pair(0, Ax2)); meas.push_back(make_pair(1, Al1x1)); - JacobianFactor combined(meas, b2, sigmas); + JacobianFactor combined(meas, b2, noiseModel::Diagonal::Sigmas(sigmas)); // eliminate the combined factor HessianFactor::shared_ptr combinedLF_Chol(new HessianFactor(combined)); @@ -492,7 +502,7 @@ TEST(HessianFactor, eliminate2 ) 0.00, 1.00, +0.00, -1.00 )/sigma; Vector b1 = Vector_(2,0.0,0.894427); - JacobianFactor expectedLF(1, Bl1x1, b1, repeat(2,1.0)); + JacobianFactor expectedLF(1, Bl1x1, b1, noiseModel::Isotropic::Sigma(2,1.0)); EXPECT(assert_equal(HessianFactor(expectedLF), *actualFactor, 1.5e-3)); } diff --git a/gtsam/linear/tests/testJacobianFactor.cpp b/gtsam/linear/tests/testJacobianFactor.cpp index 0d46807b6..9b6071935 100644 --- a/gtsam/linear/tests/testJacobianFactor.cpp +++ b/gtsam/linear/tests/testJacobianFactor.cpp @@ -26,11 +26,9 @@ using namespace std; using namespace gtsam; -static const Index _x0_=0, _x1_=1, _x2_=2, _x3_=3, _x4_=4, _x_=5, _y_=6, _l1_=7, _l11_=8; +static const Index _x0_=0, _x1_=1, _x2_=2, _x_=5, _y_=6, _l11_=8; -static SharedDiagonal - sigma0_1 = sharedSigma(2,0.1), sigma_02 = sharedSigma(2,0.2), - constraintModel = noiseModel::Constrained::All(2); +static SharedDiagonal constraintModel = noiseModel::Constrained::All(2); /* ************************************************************************* */ TEST(JacobianFactor, constructor) @@ -76,7 +74,7 @@ TEST(JacobianFactor, constructor2) JacobianFactor construct() { Matrix A = Matrix_(2,2, 1.,2.,3.,4.); Vector b = Vector_(2, 1.0, 2.0); - SharedDiagonal s = sharedSigmas(Vector_(2, 3.0, 4.0)); + SharedDiagonal s = noiseModel::Diagonal::Sigmas(Vector_(2, 3.0, 4.0)); JacobianFactor::shared_ptr shared( new JacobianFactor(0, A, b, s)); return *shared; @@ -86,7 +84,7 @@ TEST(JacobianFactor, return_value) { Matrix A = Matrix_(2,2, 1.,2.,3.,4.); Vector b = Vector_(2, 1.0, 2.0); - SharedDiagonal s = sharedSigmas(Vector_(2, 3.0, 4.0)); + SharedDiagonal s = noiseModel::Diagonal::Sigmas(Vector_(2, 3.0, 4.0)); JacobianFactor copied = construct(); EXPECT(assert_equal(b, copied.getb())); EXPECT(assert_equal(*s, *copied.get_model())); @@ -107,7 +105,7 @@ TEST(JabobianFactor, Hessian_conversion) { 1.2530, 2.1508, -0.8779, -1.8755, 0, 2.5858, 0.4789, -2.3943).finished(), (Vector(2) << -6.2929, -5.7941).finished(), - sharedUnit(2)); + noiseModel::Unit::Create(2)); JacobianFactor actual(hessian); @@ -140,6 +138,8 @@ TEST(JacobianFactor, error) { #ifdef BROKEN TEST(JacobianFactor, operators ) { + SharedDiagonal sigma0_1 = noiseModel::Isotropic::Sigma(2,0.1); + Matrix I = eye(2); Vector b = Vector_(2,0.2,-0.1); JacobianFactor lf(_x1_, -I, _x2_, I, b, sigma0_1); @@ -202,7 +202,7 @@ TEST(JacobianFactor, eliminate2 ) vector > meas; meas.push_back(make_pair(_x2_, Ax2)); meas.push_back(make_pair(_l11_, Al1x1)); - JacobianFactor combined(meas, b2, sigmas); + JacobianFactor combined(meas, b2, noiseModel::Diagonal::Sigmas(sigmas)); // eliminate the combined factor GaussianConditional::shared_ptr actualCG_QR; @@ -236,7 +236,7 @@ TEST(JacobianFactor, eliminate2 ) 0.00, 1.00, +0.00, -1.00 )/sigma; Vector b1 = Vector_(2,0.0,0.894427); - JacobianFactor expectedLF(_l11_, Bl1x1, b1, repeat(2,1.0)); + JacobianFactor expectedLF(_l11_, Bl1x1, b1, noiseModel::Isotropic::Sigma(2,1.0)); EXPECT(assert_equal(expectedLF,*actualLF_QR,1e-3)); } @@ -304,7 +304,7 @@ TEST(JacobianFactor, CONSTRUCTOR_GaussianConditional ) // Call the constructor we are testing ! JacobianFactor actualLF(*CG); - JacobianFactor expectedLF(_x2_,R11,_l11_,S12,d, sigmas); + JacobianFactor expectedLF(_x2_,R11,_l11_,S12,d, noiseModel::Diagonal::Sigmas(sigmas)); EXPECT(assert_equal(expectedLF,actualLF,1e-5)); } diff --git a/gtsam/linear/tests/testJacobianFactorGraph.cpp b/gtsam/linear/tests/testJacobianFactorGraph.cpp new file mode 100644 index 000000000..07dda4652 --- /dev/null +++ b/gtsam/linear/tests/testJacobianFactorGraph.cpp @@ -0,0 +1,92 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file testJacobianFactorGraph.cpp + * @brief Unit tests for GaussianFactorGraph + * @author Yong Dian Jian + **/ + +#include +#include + + +///* ************************************************************************* */ +//TEST( GaussianFactorGraph, gradient ) +//{ +// GaussianFactorGraph fg = createGaussianFactorGraph(); +// +// // Construct expected gradient +// VectorValues expected; +// +// // 2*f(x) = 100*(x1+c[X(1)])^2 + 100*(x2-x1-[0.2;-0.1])^2 + 25*(l1-x1-[0.0;0.2])^2 + 25*(l1-x2-[-0.2;0.3])^2 +// // worked out: df/dx1 = 100*[0.1;0.1] + 100*[0.2;-0.1]) + 25*[0.0;0.2] = [10+20;10-10+5] = [30;5] +// expected.insert(L(1),Vector_(2, 5.0,-12.5)); +// expected.insert(X(1),Vector_(2, 30.0, 5.0)); +// expected.insert(X(2),Vector_(2,-25.0, 17.5)); +// +// // Check the gradient at delta=0 +// VectorValues zero = createZeroDelta(); +// VectorValues actual = fg.gradient(zero); +// EXPECT(assert_equal(expected,actual)); +// +// // Check it numerically for good measure +// Vector numerical_g = numericalGradient(error,zero,0.001); +// EXPECT(assert_equal(Vector_(6,5.0,-12.5,30.0,5.0,-25.0,17.5),numerical_g)); +// +// // Check the gradient at the solution (should be zero) +// Ordering ord; +// ord += X(2),L(1),X(1); +// GaussianFactorGraph fg2 = createGaussianFactorGraph(); +// VectorValues solution = fg2.optimize(ord); // destructive +// VectorValues actual2 = fg.gradient(solution); +// EXPECT(assert_equal(zero,actual2)); +//} + +///* ************************************************************************* */ +//TEST( GaussianFactorGraph, transposeMultiplication ) +//{ +// // create an ordering +// Ordering ord; ord += X(2),L(1),X(1); +// +// GaussianFactorGraph A = createGaussianFactorGraph(ord); +// Errors e; +// e += Vector_(2, 0.0, 0.0); +// e += Vector_(2,15.0, 0.0); +// e += Vector_(2, 0.0,-5.0); +// e += Vector_(2,-7.5,-5.0); +// +// VectorValues expected = createZeroDelta(ord), actual = A ^ e; +// expected[ord[L(1)]] = Vector_(2, -37.5,-50.0); +// expected[ord[X(1)]] = Vector_(2,-150.0, 25.0); +// expected[ord[X(2)]] = Vector_(2, 187.5, 25.0); +// EXPECT(assert_equal(expected,actual)); +//} + +///* ************************************************************************* */ +//TEST( GaussianFactorGraph, rhs ) +//{ +// // create an ordering +// Ordering ord; ord += X(2),L(1),X(1); +// +// GaussianFactorGraph Ab = createGaussianFactorGraph(ord); +// Errors expected = createZeroDelta(ord), actual = Ab.rhs(); +// expected.push_back(Vector_(2,-1.0,-1.0)); +// expected.push_back(Vector_(2, 2.0,-1.0)); +// expected.push_back(Vector_(2, 0.0, 1.0)); +// expected.push_back(Vector_(2,-1.0, 1.5)); +// EXPECT(assert_equal(expected,actual)); +//} + + +/* ************************************************************************* */ +int main() { TestResult tr; return TestRegistry::runAllTests(tr);} +/* ************************************************************************* */ diff --git a/gtsam/linear/tests/testKalmanFilter.cpp b/gtsam/linear/tests/testKalmanFilter.cpp index ca50c12e9..b45ac6a7b 100644 --- a/gtsam/linear/tests/testKalmanFilter.cpp +++ b/gtsam/linear/tests/testKalmanFilter.cpp @@ -18,8 +18,7 @@ */ #include -#include -#include +#include #include #include diff --git a/gtsam/linear/tests/testNoiseModel.cpp b/gtsam/linear/tests/testNoiseModel.cpp index 6ca0ccd81..224395051 100644 --- a/gtsam/linear/tests/testNoiseModel.cpp +++ b/gtsam/linear/tests/testNoiseModel.cpp @@ -25,8 +25,6 @@ using namespace boost::assign; #include #include #include -#include -#include using namespace std; using namespace gtsam; @@ -131,15 +129,6 @@ TEST(NoiseModel, equals) EXPECT(assert_inequal(*i1,*i2)); } -/* ************************************************************************* */ -TEST(NoiseModel, sample) -{ - Vector s = Vector_(3,1.0,2.0,3.0); - SharedDiagonal model = sharedSigmas(s); - Vector v = model->sample(); - // no check as no way yet to set random seed -} - // TODO enable test once a mechanism for smart constraints exists ///* ************************************************************************* */ //TEST(NoiseModel, ConstrainedSmart ) @@ -258,18 +247,6 @@ TEST( NoiseModel, QR ) EXPECT(linear_dependent(expectedRd2,Ab2,1e-6)); // Ab was modified in place !!! } -/* ************************************************************************* */ -TEST(NoiseModel, Cholesky) -{ - SharedDiagonal expected = noiseModel::Unit::Create(4); - Matrix Ab = exampleQR::Ab; // otherwise overwritten ! - SharedDiagonal actual = exampleQR::diagonal->Cholesky(Ab, 4); - EXPECT(assert_equal(*expected,*actual)); - // Ab was modified in place !!! - Matrix actualRd = Ab.block(0, 0, actual->dim(), Ab.cols()).triangularView(); - EXPECT(linear_dependent(exampleQR::Rd,actualRd,1e-4)); -} - /* ************************************************************************* */ TEST(NoiseModel, QRNan ) { @@ -288,8 +265,8 @@ TEST(NoiseModel, QRNan ) TEST(NoiseModel, SmartCovariance ) { bool smart = true; - SharedGaussian expected = Unit::Create(3); - SharedGaussian actual = Gaussian::Covariance(eye(3), smart); + gtsam::SharedGaussian expected = Unit::Create(3); + gtsam::SharedGaussian actual = Gaussian::Covariance(eye(3), smart); EXPECT(assert_equal(*expected,*actual)); } @@ -306,7 +283,7 @@ TEST(NoiseModel, ScalarOrVector ) TEST(NoiseModel, WhitenInPlace) { Vector sigmas = Vector_(3, 0.1, 0.1, 0.1); - SharedDiagonal model(sigmas); + SharedDiagonal model = Diagonal::Sigmas(sigmas); Matrix A = eye(3); model->WhitenInPlace(A); Matrix expected = eye(3) * 10; @@ -346,8 +323,5 @@ TEST(NoiseModel, robustNoise) } /* ************************************************************************* */ -int main() { - TestResult tr; - return TestRegistry::runAllTests(tr); -} +int main() { TestResult tr; return TestRegistry::runAllTests(tr); } /* ************************************************************************* */ diff --git a/gtsam/linear/tests/testSampler.cpp b/gtsam/linear/tests/testSampler.cpp index e01788b65..ffb546e40 100644 --- a/gtsam/linear/tests/testSampler.cpp +++ b/gtsam/linear/tests/testSampler.cpp @@ -25,7 +25,7 @@ const double tol = 1e-5; /* ************************************************************************* */ TEST(testSampler, basic) { Vector sigmas = Vector_(3, 1.0, 0.1, 0.0); - SharedDiagonal model = noiseModel::Diagonal::Sigmas(sigmas); + noiseModel::Diagonal::shared_ptr model = noiseModel::Diagonal::Sigmas(sigmas); char seed = 'A'; Sampler sampler1(model, seed), sampler2(model, 1), sampler3(model, 1); EXPECT(assert_equal(sigmas, sampler1.sigmas())); diff --git a/gtsam/linear/tests/testSerializationLinear.cpp b/gtsam/linear/tests/testSerializationLinear.cpp index 8082d3626..e8a53c504 100644 --- a/gtsam/linear/tests/testSerializationLinear.cpp +++ b/gtsam/linear/tests/testSerializationLinear.cpp @@ -22,9 +22,6 @@ #include #include #include -#include -#include -#include #include #include @@ -50,11 +47,11 @@ BOOST_CLASS_EXPORT_GUID(gtsam::SharedDiagonal, "gtsam_SharedDiagonal"); /* ************************************************************************* */ // example noise models -noiseModel::Diagonal::shared_ptr diag3 = noiseModel::Diagonal::Sigmas(Vector_(3, 0.1, 0.2, 0.3)); -noiseModel::Gaussian::shared_ptr gaussian3 = noiseModel::Gaussian::SqrtInformation(2.0 * eye(3,3)); -noiseModel::Isotropic::shared_ptr iso3 = noiseModel::Isotropic::Sigma(3, 0.2); -noiseModel::Constrained::shared_ptr constrained3 = noiseModel::Constrained::MixedSigmas(Vector_(3, 0.0, 0.0, 0.1)); -noiseModel::Unit::shared_ptr unit3 = noiseModel::Unit::Create(3); +static noiseModel::Diagonal::shared_ptr diag3 = noiseModel::Diagonal::Sigmas(Vector_(3, 0.1, 0.2, 0.3)); +static noiseModel::Gaussian::shared_ptr gaussian3 = noiseModel::Gaussian::SqrtInformation(2.0 * eye(3,3)); +static noiseModel::Isotropic::shared_ptr iso3 = noiseModel::Isotropic::Sigma(3, 0.2); +static noiseModel::Constrained::shared_ptr constrained3 = noiseModel::Constrained::MixedSigmas(Vector_(3, 0.0, 0.0, 0.1)); +static noiseModel::Unit::shared_ptr unit3 = noiseModel::Unit::Create(3); /* ************************************************************************* */ TEST (Serialization, noiseModels) { diff --git a/gtsam/linear/tests/testVectorValues.cpp b/gtsam/linear/tests/testVectorValues.cpp index a92b81ddc..17230854a 100644 --- a/gtsam/linear/tests/testVectorValues.cpp +++ b/gtsam/linear/tests/testVectorValues.cpp @@ -421,52 +421,31 @@ TEST(VectorValues, hasSameStructure) { EXPECT(!v1.hasSameStructure(VectorValues())); } + /* ************************************************************************* */ -TEST(VectorValues, permuted_combined) { - Vector v1 = Vector_(3, 1.0,2.0,3.0); - Vector v2 = Vector_(2, 4.0,5.0); - Vector v3 = Vector_(4, 6.0,7.0,8.0,9.0); +TEST(VectorValues, permute) { - vector dims(3); dims[0]=3; dims[1]=2; dims[2]=4; - VectorValues combined(dims); - combined[0] = v1; - combined[1] = v2; - combined[2] = v3; + VectorValues original; + original.insert(0, Vector_(1, 1.0)); + original.insert(1, Vector_(2, 2.0, 3.0)); + original.insert(2, Vector_(2, 4.0, 5.0)); + original.insert(3, Vector_(2, 6.0, 7.0)); - Permutation perm1(3); - perm1[0] = 1; - perm1[1] = 2; - perm1[2] = 0; + VectorValues expected; + expected.insert(0, Vector_(2, 4.0, 5.0)); // from 2 + expected.insert(1, Vector_(1, 1.0)); // from 0 + expected.insert(2, Vector_(2, 6.0, 7.0)); // from 3 + expected.insert(3, Vector_(2, 2.0, 3.0)); // from 1 - Permutation perm2(3); - perm2[0] = 1; - perm2[1] = 2; - perm2[2] = 0; + Permutation permutation(4); + permutation[0] = 2; + permutation[1] = 0; + permutation[2] = 3; + permutation[3] = 1; - Permuted permuted1(combined); - CHECK(assert_equal(v1, permuted1[0])) - CHECK(assert_equal(v2, permuted1[1])) - CHECK(assert_equal(v3, permuted1[2])) + VectorValues actual = original.permute(permutation); - permuted1.permute(perm1); - CHECK(assert_equal(v1, permuted1[2])) - CHECK(assert_equal(v2, permuted1[0])) - CHECK(assert_equal(v3, permuted1[1])) - - permuted1.permute(perm2); - CHECK(assert_equal(v1, permuted1[1])) - CHECK(assert_equal(v2, permuted1[2])) - CHECK(assert_equal(v3, permuted1[0])) - - Permuted permuted2(perm1, combined); - CHECK(assert_equal(v1, permuted2[2])) - CHECK(assert_equal(v2, permuted2[0])) - CHECK(assert_equal(v3, permuted2[1])) - - permuted2.permute(perm2); - CHECK(assert_equal(v1, permuted2[1])) - CHECK(assert_equal(v2, permuted2[2])) - CHECK(assert_equal(v3, permuted2[0])) + EXPECT(assert_equal(expected, actual)); } /* ************************************************************************* */ diff --git a/gtsam/linear/tests/timeFactorOverhead.cpp b/gtsam/linear/tests/timeFactorOverhead.cpp index a843efd84..5ca4ceb59 100644 --- a/gtsam/linear/tests/timeFactorOverhead.cpp +++ b/gtsam/linear/tests/timeFactorOverhead.cpp @@ -60,7 +60,7 @@ int main(int argc, char *argv[]) { blockGfgs.reserve(nTrials); for(size_t trial=0; trial combGfgs; for(size_t trial=0; trial > terms; terms.reserve(varsPerBlock); diff --git a/gtsam/mainpage.dox b/gtsam/mainpage.dox index e81fc1f65..db42b1277 100644 --- a/gtsam/mainpage.dox +++ b/gtsam/mainpage.dox @@ -9,9 +9,9 @@ namespace gtsam { \section new_factor_variable_types Creating new factor and variable types GTSAM comes with a set of variable and factor types typically used in SFM and -SLAM. Geometry variables such as points and poses are in the \ref geometry +SLAM. Geometry variables such as points and poses are in the geometry subdirectory and module. Factors such as BetweenFactor and BearingFactor are in -the \ref gtsam/slam directory. +the gtsam/slam directory. To use GTSAM to solve your own problems, you will often have to create new factor types, which derive either from NonlinearFactor or NoiseModelFactor, or one of their derived types. Here is an outline of the options: diff --git a/gtsam/nonlinear/DoglegOptimizer.cpp b/gtsam/nonlinear/DoglegOptimizer.cpp index 84090d666..e3f4e4dcd 100644 --- a/gtsam/nonlinear/DoglegOptimizer.cpp +++ b/gtsam/nonlinear/DoglegOptimizer.cpp @@ -13,7 +13,7 @@ * @file DoglegOptimizer.cpp * @brief * @author Richard Roberts - * @created Feb 26, 2012 + * @date Feb 26, 2012 */ #include @@ -22,10 +22,33 @@ #include #include +#include + using namespace std; namespace gtsam { +/* ************************************************************************* */ +DoglegParams::VerbosityDL DoglegParams::verbosityDLTranslator(const std::string &verbosityDL) const { + std::string s = verbosityDL; boost::algorithm::to_upper(s); + if (s == "SILENT") return DoglegParams::SILENT; + if (s == "VERBOSE") return DoglegParams::VERBOSE; + + /* default is silent */ + return DoglegParams::SILENT; +} + +/* ************************************************************************* */ +std::string DoglegParams::verbosityDLTranslator(VerbosityDL verbosityDL) const { + std::string s; + switch (verbosityDL) { + case DoglegParams::SILENT: s = "SILENT"; break; + case DoglegParams::VERBOSE: s = "VERBOSE"; break; + default: s = "UNDEFINED"; break; + } + return s; +} + /* ************************************************************************* */ void DoglegOptimizer::iterate(void) { @@ -33,25 +56,25 @@ void DoglegOptimizer::iterate(void) { const Ordering& ordering = *params_.ordering; GaussianFactorGraph::shared_ptr linear = graph_.linearize(state_.values, ordering); - // Get elimination method - GaussianFactorGraph::Eliminate eliminationMethod = params_.getEliminationFunction(); - // Pull out parameters we'll use const bool dlVerbose = (params_.verbosityDL > DoglegParams::SILENT); // Do Dogleg iteration with either Multifrontal or Sequential elimination DoglegOptimizerImpl::IterationResult result; - if(params_.elimination == DoglegParams::MULTIFRONTAL) { + if ( params_.isMultifrontal() ) { GaussianBayesTree bt; - bt.insert(GaussianJunctionTree(*linear).eliminate(eliminationMethod)); + bt.insert(GaussianJunctionTree(*linear).eliminate(params_.getEliminationFunction())); result = DoglegOptimizerImpl::Iterate(state_.Delta, DoglegOptimizerImpl::ONE_STEP_PER_ITERATION, bt, graph_, state_.values, ordering, state_.error, dlVerbose); - - } else if(params_.elimination == DoglegParams::SEQUENTIAL) { - GaussianBayesNet::shared_ptr bn = EliminationTree::Create(*linear)->eliminate(eliminationMethod); + } + else if ( params_.isSequential() ) { + GaussianBayesNet::shared_ptr bn = EliminationTree::Create(*linear)->eliminate(params_.getEliminationFunction()); result = DoglegOptimizerImpl::Iterate(state_.Delta, DoglegOptimizerImpl::ONE_STEP_PER_ITERATION, *bn, graph_, state_.values, ordering, state_.error, dlVerbose); - - } else { + } + else if ( params_.isCG() ) { + throw runtime_error("todo: "); + } + else { throw runtime_error("Optimization parameter is invalid: DoglegParams::elimination"); } diff --git a/gtsam/nonlinear/DoglegOptimizer.h b/gtsam/nonlinear/DoglegOptimizer.h index 7edb43ca9..71551dce1 100644 --- a/gtsam/nonlinear/DoglegOptimizer.h +++ b/gtsam/nonlinear/DoglegOptimizer.h @@ -13,7 +13,7 @@ * @file DoglegOptimizer.h * @brief * @author Richard Roberts - * @created Feb 26, 2012 + * @date Feb 26, 2012 */ #pragma once @@ -50,6 +50,16 @@ public: std::cout << " deltaInitial: " << deltaInitial << "\n"; std::cout.flush(); } + + double getDeltaInitial() const { return deltaInitial; } + std::string getVerbosityDL() const { return verbosityDLTranslator(verbosityDL); } + + void setDeltaInitial(double deltaInitial) { this->deltaInitial = deltaInitial; } + void setVerbosityDL(const std::string& verbosityDL) { this->verbosityDL = verbosityDLTranslator(verbosityDL); } + +private: + VerbosityDL verbosityDLTranslator(const std::string& verbosityDL) const; + std::string verbosityDLTranslator(VerbosityDL verbosityDL) const; }; /** @@ -57,7 +67,6 @@ public: */ class DoglegState : public NonlinearOptimizerState { public: - double Delta; DoglegState() {} @@ -76,8 +85,11 @@ protected: */ class DoglegOptimizer : public NonlinearOptimizer { -public: +protected: + DoglegParams params_; + DoglegState state_; +public: typedef boost::shared_ptr shared_ptr; /// @name Standard interface @@ -101,7 +113,6 @@ public: * copies the objects. * @param graph The nonlinear factor graph to optimize * @param initialValues The initial variable assignments - * @param params The optimization parameters */ DoglegOptimizer(const NonlinearFactorGraph& graph, const Values& initialValues, const Ordering& ordering) : NonlinearOptimizer(graph) { @@ -129,14 +140,11 @@ public: const DoglegState& state() const { return state_; } /** Access the current trust region radius Delta */ - double Delta() const { return state_.Delta; } + double getDelta() const { return state_.Delta; } /// @} protected: - DoglegParams params_; - DoglegState state_; - /** Access the parameters (base class version) */ virtual const NonlinearOptimizerParams& _params() const { return params_; } diff --git a/gtsam/nonlinear/DoglegOptimizerImpl.cpp b/gtsam/nonlinear/DoglegOptimizerImpl.cpp index 480d76f6a..b46fc6a3f 100644 --- a/gtsam/nonlinear/DoglegOptimizerImpl.cpp +++ b/gtsam/nonlinear/DoglegOptimizerImpl.cpp @@ -15,8 +15,11 @@ * @author Richard Roberts */ +#include #include +using namespace std; + namespace gtsam { /* ************************************************************************* */ VectorValues DoglegOptimizerImpl::ComputeDoglegPoint( @@ -27,12 +30,12 @@ VectorValues DoglegOptimizerImpl::ComputeDoglegPoint( double DeltaSq = Delta*Delta; double x_u_norm_sq = dx_u.vector().squaredNorm(); double x_n_norm_sq = dx_n.vector().squaredNorm(); - if(verbose) cout << "Steepest descent magnitude " << sqrt(x_u_norm_sq) << ", Newton's method magnitude " << sqrt(x_n_norm_sq) << endl; + if(verbose) cout << "Steepest descent magnitude " << std::sqrt(x_u_norm_sq) << ", Newton's method magnitude " << std::sqrt(x_n_norm_sq) << endl; if(DeltaSq < x_u_norm_sq) { // Trust region is smaller than steepest descent update VectorValues x_d = VectorValues::SameStructure(dx_u); - x_d.vector() = dx_u.vector() * sqrt(DeltaSq / x_u_norm_sq); - if(verbose) cout << "In steepest descent region with fraction " << sqrt(DeltaSq / x_u_norm_sq) << " of steepest descent magnitude" << endl; + x_d.vector() = dx_u.vector() * std::sqrt(DeltaSq / x_u_norm_sq); + if(verbose) cout << "In steepest descent region with fraction " << std::sqrt(DeltaSq / x_u_norm_sq) << " of steepest descent magnitude" << endl; return x_d; } else if(DeltaSq < x_n_norm_sq) { // Trust region boundary is between steepest descent point and Newton's method point @@ -59,7 +62,7 @@ VectorValues DoglegOptimizerImpl::ComputeBlend(double Delta, const VectorValues& const double a = uu - 2.*un + nn; const double b = 2. * (un - uu); const double c = uu - Delta*Delta; - double sqrt_b_m4ac = sqrt(b*b - 4*a*c); + double sqrt_b_m4ac = std::sqrt(b*b - 4*a*c); // Compute blending parameter double tau1 = (-b + sqrt_b_m4ac) / (2.*a); diff --git a/gtsam/nonlinear/DoglegOptimizerImpl.h b/gtsam/nonlinear/DoglegOptimizerImpl.h index 03951babf..fa2179afa 100644 --- a/gtsam/nonlinear/DoglegOptimizerImpl.h +++ b/gtsam/nonlinear/DoglegOptimizerImpl.h @@ -61,6 +61,7 @@ struct DoglegOptimizerImpl { */ enum TrustRegionAdaptationMode { SEARCH_EACH_ITERATION, + SEARCH_REDUCE_ONLY, ONE_STEP_PER_ITERATION }; @@ -72,7 +73,7 @@ struct DoglegOptimizerImpl { * * The update is computed using a quadratic approximation \f$ M(\delta x) \f$ * of an original nonlinear error function (a NonlinearFactorGraph) \f$ f(x) \f$. - * The quadratic approximation is represented as a GaussianBayesNet \bayesNet, which is + * The quadratic approximation is represented as a GaussianBayesNet \f$ \bayesNet \f$, which is * obtained by eliminating a GaussianFactorGraph resulting from linearizing * the nonlinear factor graph \f$ f(x) \f$. Thus, \f$ M(\delta x) \f$ is * \f[ @@ -93,8 +94,8 @@ struct DoglegOptimizerImpl { * @param Rd The Bayes' net or tree as described above. * @param f The original nonlinear factor graph with which to evaluate the * accuracy of \f$ M(\delta x) \f$ to adjust \f$ \Delta \f$. - * @param x0 The linearization point about which \bayesNet was created - * @param ordering The variable ordering used to create \bayesNet + * @param x0 The linearization point about which \f$ \bayesNet \f$ was created + * @param ordering The variable ordering used to create\f$ \bayesNet \f$ * @param f_error The result of f.error(x0). * @return A DoglegIterationResult containing the new \c Delta, the linear * update \c dx_d, and the resulting nonlinear error \c f_error. @@ -111,7 +112,7 @@ struct DoglegOptimizerImpl { * * The update is computed using a quadratic approximation \f$ M(\delta x) \f$ * of an original nonlinear error function (a NonlinearFactorGraph) \f$ f(x) \f$. - * The quadratic approximation is represented as a GaussianBayesNet \bayesNet, which is + * The quadratic approximation is represented as a GaussianBayesNet \f$ \bayesNet \f$, which is * obtained by eliminating a GaussianFactorGraph resulting from linearizing * the nonlinear factor graph \f$ f(x) \f$. Thus, \f$ M(\delta x) \f$ is * \f[ @@ -134,8 +135,8 @@ struct DoglegOptimizerImpl { * \f$ \| (1-\tau)\delta x_u + \tau\delta x_n \| = \Delta \f$, where \f$ \Delta \f$ * is the trust region radius. * @param Delta Trust region radius - * @param xu Steepest descent minimizer - * @param xn Newton's method minimizer + * @param x_u Steepest descent minimizer + * @param x_n Newton's method minimizer */ static VectorValues ComputeBlend(double Delta, const VectorValues& x_u, const VectorValues& x_n, const bool verbose=false); }; @@ -176,7 +177,7 @@ typename DoglegOptimizerImpl::IterationResult DoglegOptimizerImpl::Iterate( result.dx_d = ComputeDoglegPoint(Delta, dx_u, dx_n, verbose); toc(3, "Dog leg point"); - if(verbose) cout << "Delta = " << Delta << ", dx_d_norm = " << result.dx_d.vector().norm() << endl; + if(verbose) std::cout << "Delta = " << Delta << ", dx_d_norm = " << result.dx_d.vector().norm() << std::endl; tic(4, "retract"); // Compute expmapped solution @@ -193,8 +194,8 @@ typename DoglegOptimizerImpl::IterationResult DoglegOptimizerImpl::Iterate( const double new_M_error = jfg.error(result.dx_d); toc(6, "decrease in M"); - if(verbose) cout << setprecision(15) << "f error: " << f_error << " -> " << result.f_error << endl; - if(verbose) cout << setprecision(15) << "M error: " << M_error << " -> " << new_M_error << endl; + if(verbose) std::cout << std::setprecision(15) << "f error: " << f_error << " -> " << result.f_error << std::endl; + if(verbose) std::cout << std::setprecision(15) << "M error: " << M_error << " -> " << new_M_error << std::endl; tic(7, "adjust Delta"); // Compute gain ratio. Here we take advantage of the invariant that the @@ -203,14 +204,14 @@ typename DoglegOptimizerImpl::IterationResult DoglegOptimizerImpl::Iterate( 0.5 : (f_error - result.f_error) / (M_error - new_M_error); - if(verbose) cout << setprecision(15) << "rho = " << rho << endl; + if(verbose) std::cout << std::setprecision(15) << "rho = " << rho << std::endl; if(rho >= 0.75) { // M agrees very well with f, so try to increase lambda const double dx_d_norm = result.dx_d.vector().norm(); const double newDelta = std::max(Delta, 3.0 * dx_d_norm); // Compute new Delta - if(mode == ONE_STEP_PER_ITERATION) + if(mode == ONE_STEP_PER_ITERATION || mode == SEARCH_REDUCE_ONLY) stay = false; // If not searching, just return with the new Delta else if(mode == SEARCH_EACH_ITERATION) { if(newDelta == Delta || lastAction == DECREASED_DELTA) @@ -231,13 +232,17 @@ typename DoglegOptimizerImpl::IterationResult DoglegOptimizerImpl::Iterate( } else if(0.25 > rho && rho >= 0.0) { // M does not agree well with f, decrease Delta until it does double newDelta; - if(Delta > 1e-5) + bool hitMinimumDelta; + if(Delta > 1e-5) { newDelta = 0.5 * Delta; - else + hitMinimumDelta = false; + } else { newDelta = Delta; - if(mode == ONE_STEP_PER_ITERATION || lastAction == INCREASED_DELTA || newDelta == Delta) + hitMinimumDelta = true; + } + if(mode == ONE_STEP_PER_ITERATION || /* mode == SEARCH_EACH_ITERATION && */ lastAction == INCREASED_DELTA || hitMinimumDelta) stay = false; // If not searching, just return with the new smaller delta - else if(mode == SEARCH_EACH_ITERATION) { + else if(mode == SEARCH_EACH_ITERATION || mode == SEARCH_REDUCE_ONLY) { stay = true; lastAction = DECREASED_DELTA; } else { @@ -246,14 +251,18 @@ typename DoglegOptimizerImpl::IterationResult DoglegOptimizerImpl::Iterate( Delta = newDelta; // Update Delta from new Delta } else { - // f actually increased, so keep decreasing Delta until f does not decrease + // f actually increased, so keep decreasing Delta until f does not decrease. + // NOTE: NaN and Inf solutions also will fall into this case, so that we + // decrease Delta if the solution becomes undetermined. assert(0.0 > rho); if(Delta > 1e-5) { Delta *= 0.5; stay = true; lastAction = DECREASED_DELTA; } else { - if(verbose) cout << "Warning: Dog leg stopping because cannot decrease error with minimum Delta" << endl; + if(verbose) std::cout << "Warning: Dog leg stopping because cannot decrease error with minimum Delta" << std::endl; + result.dx_d.setZero(); // Set delta to zero - don't allow error to increase + result.f_error = f_error; stay = false; } } diff --git a/gtsam/nonlinear/ExtendedKalmanFilter.h b/gtsam/nonlinear/ExtendedKalmanFilter.h index 353439d98..ebca4899c 100644 --- a/gtsam/nonlinear/ExtendedKalmanFilter.h +++ b/gtsam/nonlinear/ExtendedKalmanFilter.h @@ -90,3 +90,5 @@ namespace gtsam { }; } // namespace + +#include diff --git a/gtsam/nonlinear/GaussNewtonOptimizer.cpp b/gtsam/nonlinear/GaussNewtonOptimizer.cpp index 8e2b20859..05ba56a21 100644 --- a/gtsam/nonlinear/GaussNewtonOptimizer.cpp +++ b/gtsam/nonlinear/GaussNewtonOptimizer.cpp @@ -13,11 +13,9 @@ * @file GaussNewtonOptimizer.cpp * @brief * @author Richard Roberts - * @created Feb 26, 2012 + * @date Feb 26, 2012 */ -#include -#include #include using namespace std; @@ -32,17 +30,8 @@ void GaussNewtonOptimizer::iterate() { // Linearize graph GaussianFactorGraph::shared_ptr linear = graph_.linearize(current.values, *params_.ordering); - // Optimize - VectorValues delta; - { - GaussianFactorGraph::Eliminate eliminationMethod = params_.getEliminationFunction(); - if(params_.elimination == GaussNewtonParams::MULTIFRONTAL) - delta = GaussianJunctionTree(*linear).optimize(eliminationMethod); - else if(params_.elimination == GaussNewtonParams::SEQUENTIAL) - delta = gtsam::optimize(*EliminationTree::Create(*linear)->eliminate(eliminationMethod)); - else - throw runtime_error("Optimization parameter is invalid: GaussNewtonParams::elimination"); - } + // Solve Factor Graph + const VectorValues delta = solveGaussianFactorGraph(*linear, params_); // Maybe show output if(params_.verbosity >= NonlinearOptimizerParams::DELTA) delta.print("delta"); diff --git a/gtsam/nonlinear/GaussNewtonOptimizer.h b/gtsam/nonlinear/GaussNewtonOptimizer.h index 39b64b667..b68ac4fc5 100644 --- a/gtsam/nonlinear/GaussNewtonOptimizer.h +++ b/gtsam/nonlinear/GaussNewtonOptimizer.h @@ -13,7 +13,7 @@ * @file GaussNewtonOptimizer.h * @brief * @author Richard Roberts - * @created Feb 26, 2012 + * @date Feb 26, 2012 */ #pragma once @@ -43,8 +43,11 @@ protected: */ class GaussNewtonOptimizer : public NonlinearOptimizer { -public: +protected: + GaussNewtonParams params_; + GaussNewtonState state_; +public: /// @name Standard interface /// @{ @@ -66,7 +69,6 @@ public: * copies the objects. * @param graph The nonlinear factor graph to optimize * @param initialValues The initial variable assignments - * @param params The optimization parameters */ GaussNewtonOptimizer(const NonlinearFactorGraph& graph, const Values& initialValues, const Ordering& ordering) : NonlinearOptimizer(graph), state_(graph, initialValues) { @@ -95,10 +97,6 @@ public: /// @} protected: - - GaussNewtonParams params_; - GaussNewtonState state_; - /** Access the parameters (base class version) */ virtual const NonlinearOptimizerParams& _params() const { return params_; } diff --git a/gtsam/nonlinear/ISAM2-impl.cpp b/gtsam/nonlinear/ISAM2-impl.cpp index 8fe117e34..f3b27b138 100644 --- a/gtsam/nonlinear/ISAM2-impl.cpp +++ b/gtsam/nonlinear/ISAM2-impl.cpp @@ -12,21 +12,26 @@ /** * @file ISAM2-impl.cpp * @brief Incremental update functionality (ISAM2) for BayesTree, with fluid relinearization. - * @author Michael Kaess, Richard Roberts + * @author Michael Kaess + * @author Richard Roberts */ +#include +#include // for selective linearization thresholds +#include +#include #include #include -#include -#include + +using namespace std; namespace gtsam { /* ************************************************************************* */ void ISAM2::Impl::AddVariables( - const Values& newTheta, Values& theta, Permuted& delta, - Permuted& deltaNewton, Permuted& deltaGradSearch, vector& replacedKeys, - Ordering& ordering, Base::Nodes& nodes, const KeyFormatter& keyFormatter) { + const Values& newTheta, Values& theta, VectorValues& delta, + VectorValues& deltaNewton, VectorValues& deltaGradSearch, vector& replacedKeys, + Ordering& ordering, const KeyFormatter& keyFormatter) { const bool debug = ISDEBUG("ISAM2 AddVariables"); theta.insert(newTheta); @@ -35,34 +40,91 @@ void ISAM2::Impl::AddVariables( std::vector dims(newTheta.dims(*newTheta.orderingArbitrary())); if(debug) cout << "New variables have total dimensionality " << accumulate(dims.begin(), dims.end(), 0) << endl; const size_t newDim = accumulate(dims.begin(), dims.end(), 0); - const size_t originalDim = delta->dim(); - const size_t originalnVars = delta->size(); - delta.container().append(dims); - delta.container().vector().segment(originalDim, newDim).operator=(Vector::Zero(newDim)); - delta.permutation().resize(originalnVars + newTheta.size()); - deltaNewton.container().append(dims); - deltaNewton.container().vector().segment(originalDim, newDim).operator=(Vector::Zero(newDim)); - deltaNewton.permutation().resize(originalnVars + newTheta.size()); - deltaGradSearch.container().append(dims); - deltaGradSearch.container().vector().segment(originalDim, newDim).operator=(Vector::Zero(newDim)); - deltaGradSearch.permutation().resize(originalnVars + newTheta.size()); + const size_t originalDim = delta.dim(); + const size_t originalnVars = delta.size(); + delta.append(dims); + delta.vector().segment(originalDim, newDim).operator=(Vector::Zero(newDim)); + deltaNewton.append(dims); + deltaNewton.vector().segment(originalDim, newDim).operator=(Vector::Zero(newDim)); + deltaGradSearch.append(dims); + deltaGradSearch.vector().segment(originalDim, newDim).operator=(Vector::Zero(newDim)); { Index nextVar = originalnVars; BOOST_FOREACH(const Values::ConstKeyValuePair& key_value, newTheta) { - delta.permutation()[nextVar] = nextVar; - deltaNewton.permutation()[nextVar] = nextVar; - deltaGradSearch.permutation()[nextVar] = nextVar; ordering.insert(key_value.key, nextVar); if(debug) cout << "Adding variable " << keyFormatter(key_value.key) << " with order " << nextVar << endl; ++ nextVar; } - assert(delta.permutation().size() == delta.container().size()); assert(ordering.nVars() == delta.size()); assert(ordering.size() == delta.size()); } - assert(ordering.nVars() >= nodes.size()); replacedKeys.resize(ordering.nVars(), false); - nodes.resize(ordering.nVars()); +} + +/* ************************************************************************* */ +void ISAM2::Impl::RemoveVariables(const FastSet& unusedKeys, const ISAM2Clique::shared_ptr& root, + Values& theta, VariableIndex& variableIndex, + VectorValues& delta, VectorValues& deltaNewton, VectorValues& deltaGradSearch, + std::vector& replacedKeys, Ordering& ordering, Base::Nodes& nodes, + GaussianFactorGraph& linearFactors) { + + // Get indices of unused keys + vector unusedIndices; unusedIndices.reserve(unusedKeys.size()); + BOOST_FOREACH(Key key, unusedKeys) { unusedIndices.push_back(ordering[key]); } + + // Create a permutation that shifts the unused variables to the end + Permutation unusedToEnd = Permutation::PushToBack(unusedIndices, delta.size()); + Permutation unusedToEndInverse = *unusedToEnd.inverse(); + + // Use the permutation to remove unused variables while shifting all the others to take up the space + variableIndex.permuteInPlace(unusedToEnd); + variableIndex.removeUnusedAtEnd(unusedIndices.size()); + { + // Create a vector of variable dimensions with the unused ones removed + // by applying the unusedToEnd permutation to the original vector of + // variable dimensions. We only allocate space in the shifted dims + // vector for the used variables, so that the unused ones are dropped + // when the permutation is applied. + vector originalDims = delta.dims(); + vector dims(delta.size() - unusedIndices.size()); + unusedToEnd.applyToCollection(dims, originalDims); + + // Copy from the old data structures to new ones, only iterating up to + // the number of used variables, and applying the unusedToEnd permutation + // in order to remove the unused variables. + VectorValues newDelta(dims); + VectorValues newDeltaNewton(dims); + VectorValues newDeltaGradSearch(dims); + std::vector newReplacedKeys(replacedKeys.size() - unusedIndices.size()); + Base::Nodes newNodes(replacedKeys.size() - unusedIndices.size()); + + for(size_t j = 0; j < dims.size(); ++j) { + newDelta[j] = delta[unusedToEnd[j]]; + newDeltaNewton[j] = deltaNewton[unusedToEnd[j]]; + newDeltaGradSearch[j] = deltaGradSearch[unusedToEnd[j]]; + newReplacedKeys[j] = replacedKeys[unusedToEnd[j]]; + newNodes[j] = nodes[unusedToEnd[j]]; + } + + // Swap the new data structures with the outputs of this function + delta.swap(newDelta); + deltaNewton.swap(newDeltaNewton); + deltaGradSearch.swap(newDeltaGradSearch); + replacedKeys.swap(newReplacedKeys); + nodes.swap(newNodes); + } + + // Reorder and remove from ordering and solution + ordering.permuteWithInverse(unusedToEndInverse); + BOOST_REVERSE_FOREACH(Key key, unusedKeys) { + ordering.pop_back(key); + theta.erase(key); + } + + // Finally, permute references to variables + if(root) + root->permuteWithInverse(unusedToEndInverse); + linearFactors.permuteWithInverse(unusedToEndInverse); } /* ************************************************************************* */ @@ -77,7 +139,7 @@ FastSet ISAM2::Impl::IndicesFromFactors(const Ordering& ordering, const N } /* ************************************************************************* */ -FastSet ISAM2::Impl::CheckRelinearization(const Permuted& delta, const Ordering& ordering, +FastSet ISAM2::Impl::CheckRelinearizationFull(const VectorValues& delta, const Ordering& ordering, const ISAM2Params::RelinearizationThreshold& relinearizeThreshold, const KeyFormatter& keyFormatter) { FastSet relinKeys; @@ -104,6 +166,77 @@ FastSet ISAM2::Impl::CheckRelinearization(const Permuted& d return relinKeys; } +/* ************************************************************************* */ +void CheckRelinearizationRecursiveDouble(FastSet& relinKeys, double threshold, const VectorValues& delta, const ISAM2Clique::shared_ptr& clique) { + + // Check the current clique for relinearization + bool relinearize = false; + BOOST_FOREACH(Index var, clique->conditional()->keys()) { + double maxDelta = delta[var].lpNorm(); + if(maxDelta >= threshold) { + relinKeys.insert(var); + relinearize = true; + } + } + + // If this node was relinearized, also check its children + if(relinearize) { + BOOST_FOREACH(const ISAM2Clique::shared_ptr& child, clique->children()) { + CheckRelinearizationRecursiveDouble(relinKeys, threshold, delta, child); + } + } +} + +/* ************************************************************************* */ +void CheckRelinearizationRecursiveMap(FastSet& relinKeys, const FastMap& thresholds, const VectorValues& delta, const Ordering::InvertedMap& decoder, const ISAM2Clique::shared_ptr& clique) { + + // Check the current clique for relinearization + bool relinearize = false; + BOOST_FOREACH(Index var, clique->conditional()->keys()) { + + // Lookup the key associated with this index + Key key = decoder.at(var); + + // Find the threshold for this variable type + const Vector& threshold = thresholds.find(Symbol(key).chr())->second; + + // Verify the threshold vector matches the actual variable size + if(threshold.rows() != delta[var].rows()) + throw std::invalid_argument("Relinearization threshold vector dimensionality passed into iSAM2 parameters does not match actual variable dimensionality"); + + // Check for relinearization + if((delta[var].array().abs() > threshold.array()).any()) { + relinKeys.insert(var); + relinearize = true; + } + } + + // If this node was relinearized, also check its children + if(relinearize) { + BOOST_FOREACH(const ISAM2Clique::shared_ptr& child, clique->children()) { + CheckRelinearizationRecursiveMap(relinKeys, thresholds, delta, decoder, child); + } + } +} + +/* ************************************************************************* */ +FastSet ISAM2::Impl::CheckRelinearizationPartial(const ISAM2Clique::shared_ptr& root, const VectorValues& delta, const Ordering& ordering, + const ISAM2Params::RelinearizationThreshold& relinearizeThreshold, const KeyFormatter& keyFormatter) { + + FastSet relinKeys; + + if(root) { + if(relinearizeThreshold.type() == typeid(double)) { + CheckRelinearizationRecursiveDouble(relinKeys, boost::get(relinearizeThreshold), delta, root); + } else if(relinearizeThreshold.type() == typeid(FastMap)) { + Ordering::InvertedMap decoder = ordering.invert(); + CheckRelinearizationRecursiveMap(relinKeys, boost::get >(relinearizeThreshold), delta, decoder, root); + } + } + + return relinKeys; +} + /* ************************************************************************* */ void ISAM2::Impl::FindAll(ISAM2Clique::shared_ptr clique, FastSet& keys, const vector& markedMask) { static const bool debug = false; @@ -125,13 +258,13 @@ void ISAM2::Impl::FindAll(ISAM2Clique::shared_ptr clique, FastSet& keys, } /* ************************************************************************* */ -void ISAM2::Impl::ExpmapMasked(Values& values, const Permuted& delta, const Ordering& ordering, - const vector& mask, boost::optional&> invalidateIfDebug, const KeyFormatter& keyFormatter) { +void ISAM2::Impl::ExpmapMasked(Values& values, const VectorValues& delta, const Ordering& ordering, + const vector& mask, boost::optional invalidateIfDebug, const KeyFormatter& keyFormatter) { // If debugging, invalidate if requested, otherwise do not invalidate. // Invalidating means setting expmapped entries to Inf, to trigger assertions // if we try to re-use them. #ifdef NDEBUG - invalidateIfDebug = boost::optional&>(); + invalidateIfDebug = boost::none; #endif assert(values.size() == ordering.nVars()); @@ -149,7 +282,7 @@ void ISAM2::Impl::ExpmapMasked(Values& values, const Permuted& del cout << " " << keyFormatter(key_value->key) << " (j = " << var << "), delta = " << delta[var].transpose() << endl; } assert(delta[var].size() == (int)key_value->value.dim()); - assert(delta[var].unaryExpr(&isfinite).all()); + assert(delta[var].unaryExpr(ptr_fun(isfinite)).all()); if(mask[var]) { Value* retracted = key_value->value.retract_(delta[var]); key_value->value = *retracted; @@ -228,7 +361,7 @@ ISAM2::Impl::PartialSolve(GaussianFactorGraph& factors, toc(4,"ccolamd permutations"); tic(5,"permute affected variable index"); - affectedFactorsIndex.permute(*affectedColamd); + affectedFactorsIndex.permuteInPlace(*affectedColamd); toc(5,"permute affected variable index"); tic(6,"permute affected factors"); @@ -278,25 +411,13 @@ inline static void optimizeInPlace(const boost::shared_ptr& clique, } /* ************************************************************************* */ -size_t ISAM2::Impl::UpdateDelta(const boost::shared_ptr& root, std::vector& replacedKeys, Permuted& delta, double wildfireThreshold) { +size_t ISAM2::Impl::UpdateDelta(const boost::shared_ptr& root, std::vector& replacedKeys, VectorValues& delta, double wildfireThreshold) { size_t lastBacksubVariableCount; if (wildfireThreshold <= 0.0) { // Threshold is zero or less, so do a full recalculation - // Collect dimensions and allocate new VectorValues - vector dims(delta.size()); - for(size_t j=0; jdim(j); - VectorValues newDelta(dims); - - // Optimize full solution delta - internal::optimizeInPlace(root, newDelta); - - // Copy solution into delta - delta.permutation() = Permutation::Identity(delta.size()); - delta.container() = newDelta; - + internal::optimizeInPlace(root, delta); lastBacksubVariableCount = delta.size(); } else { @@ -304,8 +425,8 @@ size_t ISAM2::Impl::UpdateDelta(const boost::shared_ptr& root, std: lastBacksubVariableCount = optimizeWildfire(root, wildfireThreshold, replacedKeys, delta); // modifies delta_ #ifndef NDEBUG - for(size_t j=0; j).all()); + for(size_t j=0; j)).all()); #endif } @@ -318,7 +439,7 @@ size_t ISAM2::Impl::UpdateDelta(const boost::shared_ptr& root, std: /* ************************************************************************* */ namespace internal { void updateDoglegDeltas(const boost::shared_ptr& clique, std::vector& replacedKeys, - const VectorValues& grad, Permuted& deltaNewton, Permuted& RgProd, size_t& varsUpdated) { + const VectorValues& grad, VectorValues& deltaNewton, VectorValues& RgProd, size_t& varsUpdated) { // Check if any frontal or separator keys were recalculated, if so, we need // update deltas and recurse to children, but if not, we do not need to @@ -357,7 +478,7 @@ void updateDoglegDeltas(const boost::shared_ptr& clique, std::vecto /* ************************************************************************* */ size_t ISAM2::Impl::UpdateDoglegDeltas(const ISAM2& isam, double wildfireThreshold, std::vector& replacedKeys, - Permuted& deltaNewton, Permuted& RgProd) { + VectorValues& deltaNewton, VectorValues& RgProd) { // Get gradient VectorValues grad = *allocateVectorValues(isam); diff --git a/gtsam/nonlinear/ISAM2-impl.h b/gtsam/nonlinear/ISAM2-impl.h index 34573f0c5..b873c87bf 100644 --- a/gtsam/nonlinear/ISAM2-impl.h +++ b/gtsam/nonlinear/ISAM2-impl.h @@ -22,8 +22,6 @@ namespace gtsam { -using namespace std; - struct ISAM2::Impl { struct PartialSolveResult { @@ -48,9 +46,17 @@ struct ISAM2::Impl { * @param nodes Current BayesTree::Nodes index to be augmented with slots for new variables * @param keyFormatter Formatter for printing nonlinear keys during debugging */ - static void AddVariables(const Values& newTheta, Values& theta, Permuted& delta, - Permuted& deltaNewton, Permuted& deltaGradSearch, vector& replacedKeys, - Ordering& ordering, Base::Nodes& nodes, const KeyFormatter& keyFormatter = DefaultKeyFormatter); + static void AddVariables(const Values& newTheta, Values& theta, VectorValues& delta, + VectorValues& deltaNewton, VectorValues& deltaGradSearch, std::vector& replacedKeys, + Ordering& ordering, const KeyFormatter& keyFormatter = DefaultKeyFormatter); + + /** + * Remove variables from the ISAM2 system. + */ + static void RemoveVariables(const FastSet& unusedKeys, const ISAM2Clique::shared_ptr& root, + Values& theta, VariableIndex& variableIndex, VectorValues& delta, VectorValues& deltaNewton, + VectorValues& deltaGradSearch, std::vector& replacedKeys, Ordering& ordering, Base::Nodes& nodes, + GaussianFactorGraph& linearFactors); /** * Extract the set of variable indices from a NonlinearFactorGraph. For each Symbol @@ -70,7 +76,21 @@ struct ISAM2::Impl { * @return The set of variable indices in delta whose magnitude is greater than or * equal to relinearizeThreshold */ - static FastSet CheckRelinearization(const Permuted& delta, const Ordering& ordering, + static FastSet CheckRelinearizationFull(const VectorValues& delta, const Ordering& ordering, + const ISAM2Params::RelinearizationThreshold& relinearizeThreshold, const KeyFormatter& keyFormatter = DefaultKeyFormatter); + + /** + * Find the set of variables to be relinearized according to relinearizeThreshold. + * This check is performed recursively, starting at the top of the tree. Once a + * variable in the tree does not need to be relinearized, no further checks in + * that branch are performed. This is an approximation of the Full version, designed + * to save time at the expense of accuracy. + * @param delta The linear delta to check against the threshold + * @param keyFormatter Formatter for printing nonlinear keys during debugging + * @return The set of variable indices in delta whose magnitude is greater than or + * equal to relinearizeThreshold + */ + static FastSet CheckRelinearizationPartial(const ISAM2Clique::shared_ptr& root, const VectorValues& delta, const Ordering& ordering, const ISAM2Params::RelinearizationThreshold& relinearizeThreshold, const KeyFormatter& keyFormatter = DefaultKeyFormatter); /** @@ -88,12 +108,12 @@ struct ISAM2::Impl { * * Alternatively could we trace up towards the root for each variable here? */ - static void FindAll(ISAM2Clique::shared_ptr clique, FastSet& keys, const vector& markedMask); + static void FindAll(ISAM2Clique::shared_ptr clique, FastSet& keys, const std::vector& markedMask); /** * Apply expmap to the given values, but only for indices appearing in * \c markedRelinMask. Values are expmapped in-place. - * \param [in][out] values The value to expmap in-place + * \param [in, out] values The value to expmap in-place * \param delta The linear delta with which to expmap * \param ordering The ordering * \param mask Mask on linear indices, only \c true entries are expmapped @@ -103,9 +123,9 @@ struct ISAM2::Impl { * recalculate its delta. * @param keyFormatter Formatter for printing nonlinear keys during debugging */ - static void ExpmapMasked(Values& values, const Permuted& delta, + static void ExpmapMasked(Values& values, const VectorValues& delta, const Ordering& ordering, const std::vector& mask, - boost::optional&> invalidateIfDebug = boost::optional&>(), + boost::optional invalidateIfDebug = boost::none, const KeyFormatter& keyFormatter = DefaultKeyFormatter); /** @@ -125,10 +145,10 @@ struct ISAM2::Impl { static PartialSolveResult PartialSolve(GaussianFactorGraph& factors, const FastSet& keys, const ReorderingMode& reorderingMode, bool useQR); - static size_t UpdateDelta(const boost::shared_ptr& root, std::vector& replacedKeys, Permuted& delta, double wildfireThreshold); + static size_t UpdateDelta(const boost::shared_ptr& root, std::vector& replacedKeys, VectorValues& delta, double wildfireThreshold); static size_t UpdateDoglegDeltas(const ISAM2& isam, double wildfireThreshold, std::vector& replacedKeys, - Permuted& deltaNewton, Permuted& RgProd); + VectorValues& deltaNewton, VectorValues& RgProd); }; diff --git a/gtsam/nonlinear/ISAM2-inl.h b/gtsam/nonlinear/ISAM2-inl.h index 04395069c..ba0071b51 100644 --- a/gtsam/nonlinear/ISAM2-inl.h +++ b/gtsam/nonlinear/ISAM2-inl.h @@ -23,12 +23,8 @@ #include #include -#include - namespace gtsam { -using namespace std; - /* ************************************************************************* */ template VALUE ISAM2::calculateEstimate(Key key) const { @@ -41,7 +37,7 @@ VALUE ISAM2::calculateEstimate(Key key) const { namespace internal { template void optimizeWildfire(const boost::shared_ptr& clique, double threshold, - vector& changed, const vector& replaced, Permuted& delta, int& count) { + std::vector& changed, const std::vector& replaced, VectorValues& delta, int& count) { // if none of the variables in this clique (frontal and separator!) changed // significantly, then by the running intersection property, none of the // cliques in the children need to be processed @@ -70,7 +66,7 @@ void optimizeWildfire(const boost::shared_ptr& clique, double threshold, if(recalculate) { // Temporary copy of the original values, to check how much they change - vector originalValues((*clique)->nrFrontals()); + std::vector originalValues((*clique)->nrFrontals()); GaussianConditional::const_iterator it; for(it = (*clique)->beginFrontals(); it!=(*clique)->endFrontals(); it++) { originalValues[it - (*clique)->beginFrontals()] = delta[*it]; @@ -118,8 +114,8 @@ void optimizeWildfire(const boost::shared_ptr& clique, double threshold, /* ************************************************************************* */ template -int optimizeWildfire(const boost::shared_ptr& root, double threshold, const vector& keys, Permuted& delta) { - vector changed(keys.size(), false); +int optimizeWildfire(const boost::shared_ptr& root, double threshold, const std::vector& keys, VectorValues& delta) { + std::vector changed(keys.size(), false); int count = 0; // starting from the root, call optimize on each conditional if(root) diff --git a/gtsam/nonlinear/ISAM2.cpp b/gtsam/nonlinear/ISAM2.cpp index bae2252d6..081910e8c 100644 --- a/gtsam/nonlinear/ISAM2.cpp +++ b/gtsam/nonlinear/ISAM2.cpp @@ -20,12 +20,14 @@ using namespace boost::assign; #include #include +#include #include #include #include #include #include +#include #include #include @@ -38,9 +40,50 @@ using namespace std; static const bool disableReordering = false; static const double batchThreshold = 0.65; +/* ************************************************************************* */ +std::string ISAM2DoglegParams::adaptationModeTranslator(const DoglegOptimizerImpl::TrustRegionAdaptationMode& adaptationMode) const { + std::string s; + switch (adaptationMode) { + case DoglegOptimizerImpl::SEARCH_EACH_ITERATION: s = "SEARCH_EACH_ITERATION"; break; + case DoglegOptimizerImpl::ONE_STEP_PER_ITERATION: s = "ONE_STEP_PER_ITERATION"; break; + default: s = "UNDEFINED"; break; + } + return s; +} + +/* ************************************************************************* */ +DoglegOptimizerImpl::TrustRegionAdaptationMode ISAM2DoglegParams::adaptationModeTranslator(const std::string& adaptationMode) const { + std::string s = adaptationMode; boost::algorithm::to_upper(s); + if (s == "SEARCH_EACH_ITERATION") return DoglegOptimizerImpl::SEARCH_EACH_ITERATION; + if (s == "ONE_STEP_PER_ITERATION") return DoglegOptimizerImpl::ONE_STEP_PER_ITERATION; + + /* default is SEARCH_EACH_ITERATION */ + return DoglegOptimizerImpl::SEARCH_EACH_ITERATION; +} + +/* ************************************************************************* */ +ISAM2Params::Factorization ISAM2Params::factorizationTranslator(const std::string& str) const { + std::string s = str; boost::algorithm::to_upper(s); + if (s == "QR") return ISAM2Params::QR; + if (s == "CHOLESKY") return ISAM2Params::CHOLESKY; + + /* default is CHOLESKY */ + return ISAM2Params::CHOLESKY; +} + +/* ************************************************************************* */ +std::string ISAM2Params::factorizationTranslator(const ISAM2Params::Factorization& value) const { + std::string s; + switch (value) { + case ISAM2Params::QR: s = "QR"; break; + case ISAM2Params::CHOLESKY: s = "CHOLESKY"; break; + default: s = "UNDEFINED"; break; + } + return s; +} + /* ************************************************************************* */ ISAM2::ISAM2(const ISAM2Params& params): - delta_(deltaUnpermuted_), deltaNewton_(deltaNewtonUnpermuted_), RgProd_(RgProdUnpermuted_), deltaDoglegUptodate_(true), deltaUptodate_(true), params_(params) { if(params_.optimizationParams.type() == typeid(ISAM2DoglegParams)) doglegDelta_ = boost::get(params_.optimizationParams).initialDelta; @@ -48,15 +91,13 @@ ISAM2::ISAM2(const ISAM2Params& params): /* ************************************************************************* */ ISAM2::ISAM2(): - delta_(deltaUnpermuted_), deltaNewton_(deltaNewtonUnpermuted_), RgProd_(RgProdUnpermuted_), deltaDoglegUptodate_(true), deltaUptodate_(true) { if(params_.optimizationParams.type() == typeid(ISAM2DoglegParams)) doglegDelta_ = boost::get(params_.optimizationParams).initialDelta; } /* ************************************************************************* */ -ISAM2::ISAM2(const ISAM2& other): - delta_(deltaUnpermuted_), deltaNewton_(deltaNewtonUnpermuted_), RgProd_(RgProdUnpermuted_) { +ISAM2::ISAM2(const ISAM2& other) { *this = other; } @@ -88,9 +129,6 @@ ISAM2& ISAM2::operator=(const ISAM2& rhs) { params_ = rhs.params_; doglegDelta_ = rhs.doglegDelta_; -#ifndef NDEBUG - lastRelinVariables_ = rhs.lastRelinVariables_; -#endif lastAffectedVariableCount = rhs.lastAffectedVariableCount; lastAffectedFactorCount = rhs.lastAffectedFactorCount; lastAffectedCliqueCount = rhs.lastAffectedCliqueCount; @@ -205,8 +243,8 @@ GaussianFactorGraph ISAM2::getCachedBoundaryFactors(Cliques& orphans) { return cachedBoundary; } -boost::shared_ptr > ISAM2::recalculate( - const FastSet& markedKeys, const FastSet& relinKeys, const FastVector& observedKeys, +boost::shared_ptr > ISAM2::recalculate(const FastSet& markedKeys, + const FastSet& relinKeys, const FastVector& observedKeys, const FastSet& unusedIndices, const boost::optional >& constrainKeys, ISAM2Result& result) { // TODO: new factors are linearized twice, the newFactors passed in are not used. @@ -307,12 +345,12 @@ boost::shared_ptr > ISAM2::recalculate( // Reorder tic(2,"permute global variable index"); - variableIndex_.permute(*colamd); + variableIndex_.permuteInPlace(*colamd); toc(2,"permute global variable index"); tic(3,"permute delta"); - delta_.permute(*colamd); - deltaNewton_.permute(*colamd); - RgProd_.permute(*colamd); + delta_ = delta_.permute(*colamd); + deltaNewton_ = deltaNewton_.permute(*colamd); + RgProd_ = RgProd_.permute(*colamd); toc(3,"permute delta"); tic(4,"permute ordering"); ordering_.permuteWithInverse(*colamdInverse); @@ -320,11 +358,13 @@ boost::shared_ptr > ISAM2::recalculate( toc(1,"reorder"); tic(2,"linearize"); - linearFactors_ = *nonlinearFactors_.linearize(theta_, ordering_); + GaussianFactorGraph linearized = *nonlinearFactors_.linearize(theta_, ordering_); + if(params_.cacheLinearizedFactors) + linearFactors_ = linearized; toc(2,"linearize"); tic(5,"eliminate"); - JunctionTree jt(linearFactors_, variableIndex_); + JunctionTree jt(linearized, variableIndex_); sharedClique newRoot; if(params_.factorization == ISAM2Params::CHOLESKY) newRoot = jt.eliminate(EliminatePreferCholesky); @@ -343,12 +383,12 @@ boost::shared_ptr > ISAM2::recalculate( lastAffectedMarkedCount = markedKeys.size(); lastAffectedVariableCount = affectedKeysSet->size(); - lastAffectedFactorCount = linearFactors_.size(); + lastAffectedFactorCount = linearized.size(); // Reeliminated keys for detailed results if(params_.enableDetailedResults) { BOOST_FOREACH(Key key, theta_.keys()) { - result.detail->variableStatus[key].isReeliminated = true; + result.detail->variableStatus[key].isReeliminated = true; } } @@ -372,7 +412,7 @@ boost::shared_ptr > ISAM2::recalculate( // Reeliminated keys for detailed results if(params_.enableDetailedResults) { BOOST_FOREACH(Index index, affectedAndNewKeys) { - result.detail->variableStatus[inverseOrdering_->at(index)].isReeliminated = true; + result.detail->variableStatus[inverseOrdering_->at(index)].isReeliminated = true; } } @@ -419,8 +459,12 @@ boost::shared_ptr > ISAM2::recalculate( reorderingMode.constrainedKeys = FastMap(); BOOST_FOREACH(Index var, observedKeys) { reorderingMode.constrainedKeys->insert(make_pair(var, 1)); } } + FastSet affectedUsedKeys = *affectedKeysSet; // Remove unused keys from the set we pass to PartialSolve + BOOST_FOREACH(Index unused, unusedIndices) { + affectedUsedKeys.erase(unused); + } Impl::PartialSolveResult partialSolveResult = - Impl::PartialSolve(factors, *affectedKeysSet, reorderingMode, (params_.factorization == ISAM2Params::QR)); + Impl::PartialSolve(factors, affectedUsedKeys, reorderingMode, (params_.factorization == ISAM2Params::QR)); toc(2,"PartialSolve"); // We now need to permute everything according this partial reordering: the @@ -428,12 +472,12 @@ boost::shared_ptr > ISAM2::recalculate( // re-eliminate. The reordered variables are also mentioned in the // orphans and the leftover cached factors. tic(3,"permute global variable index"); - variableIndex_.permute(partialSolveResult.fullReordering); + variableIndex_.permuteInPlace(partialSolveResult.fullReordering); toc(3,"permute global variable index"); tic(4,"permute delta"); - delta_.permute(partialSolveResult.fullReordering); - deltaNewton_.permute(partialSolveResult.fullReordering); - RgProd_.permute(partialSolveResult.fullReordering); + delta_ = delta_.permute(partialSolveResult.fullReordering); + deltaNewton_ = deltaNewton_.permute(partialSolveResult.fullReordering); + RgProd_ = RgProd_.permute(partialSolveResult.fullReordering); toc(4,"permute delta"); tic(5,"permute ordering"); ordering_.permuteWithInverse(partialSolveResult.fullReorderingInverse); @@ -485,7 +529,7 @@ boost::shared_ptr > ISAM2::recalculate( // Root clique variables for detailed results if(params_.enableDetailedResults) { BOOST_FOREACH(Index index, this->root()->conditional()->frontals()) { - result.detail->variableStatus[inverseOrdering_->at(index)].inRootClique = true; + result.detail->variableStatus[inverseOrdering_->at(index)].inRootClique = true; } } @@ -541,15 +585,38 @@ ISAM2Result ISAM2::update( BOOST_FOREACH(size_t index, removeFactorIndices) { removeFactors.push_back(nonlinearFactors_[index]); nonlinearFactors_.remove(index); + if(params_.cacheLinearizedFactors) + linearFactors_.remove(index); } // Remove removed factors from the variable index so we do not attempt to relinearize them variableIndex_.remove(removeFactorIndices, *removeFactors.symbolic(ordering_)); + + // Compute unused keys and indices + FastSet unusedKeys; + FastSet unusedIndices; + { + // Get keys from removed factors and new factors, and compute unused keys, + // i.e., keys that are empty now and do not appear in the new factors. + FastSet removedAndEmpty; + BOOST_FOREACH(Key key, removeFactors.keys()) { + if(variableIndex_[ordering_[key]].empty()) + removedAndEmpty.insert(removedAndEmpty.end(), key); + } + FastSet newFactorSymbKeys = newFactors.keys(); + std::set_difference(removedAndEmpty.begin(), removedAndEmpty.end(), + newFactorSymbKeys.begin(), newFactorSymbKeys.end(), std::inserter(unusedKeys, unusedKeys.end())); + + // Get indices for unused keys + BOOST_FOREACH(Key key, unusedKeys) { + unusedIndices.insert(unusedIndices.end(), ordering_[key]); + } + } toc(1,"push_back factors"); tic(2,"add new variables"); // 2. Initialize any new variables \Theta_{new} and add \Theta:=\Theta\cup\Theta_{new}. - Impl::AddVariables(newTheta, theta_, delta_, deltaNewton_, RgProd_, deltaReplacedMask_, ordering_, Base::nodes_); + Impl::AddVariables(newTheta, theta_, delta_, deltaNewton_, RgProd_, deltaReplacedMask_, ordering_); // New keys for detailed results if(params_.enableDetailedResults) { inverseOrdering_ = ordering_.invert(); @@ -569,16 +636,21 @@ ISAM2Result ISAM2::update( FastSet markedRemoveKeys = Impl::IndicesFromFactors(ordering_, removeFactors); // Get keys involved in removed factors markedKeys.insert(markedRemoveKeys.begin(), markedRemoveKeys.end()); // Add to the overall set of marked keys } - // Observed keys for detailed results + + // Observed keys for detailed results if(params_.enableDetailedResults) { BOOST_FOREACH(Index index, markedKeys) { - result.detail->variableStatus[inverseOrdering_->at(index)].isObserved = true; + result.detail->variableStatus[inverseOrdering_->at(index)].isObserved = true; } } // NOTE: we use assign instead of the iterator constructor here because this // is a vector of size_t, so the constructor unintentionally resolves to // vector(size_t count, Index value) instead of the iterator constructor. - FastVector observedKeys; observedKeys.assign(markedKeys.begin(), markedKeys.end()); // Make a copy of these, as we'll soon add to them + FastVector observedKeys; observedKeys.reserve(markedKeys.size()); + BOOST_FOREACH(Index index, markedKeys) { + if(unusedIndices.find(index) == unusedIndices.end()) // Only add if not unused + observedKeys.push_back(index); // Make a copy of these, as we'll soon add to them + } toc(4,"gather involved keys"); // Check relinearization if we're at the nth step, or we are using a looser loop relin threshold @@ -587,8 +659,11 @@ ISAM2Result ISAM2::update( tic(5,"gather relinearize keys"); vector markedRelinMask(ordering_.nVars(), false); // 4. Mark keys in \Delta above threshold \beta: J=\{\Delta_{j}\in\Delta|\Delta_{j}\geq\beta\}. - relinKeys = Impl::CheckRelinearization(delta_, ordering_, params_.relinearizeThreshold); - if(disableReordering) relinKeys = Impl::CheckRelinearization(delta_, ordering_, 0.0); // This is used for debugging + if(params_.enablePartialRelinearizationCheck) + relinKeys = Impl::CheckRelinearizationPartial(root_, delta_, ordering_, params_.relinearizeThreshold); + else + relinKeys = Impl::CheckRelinearizationFull(delta_, ordering_, params_.relinearizeThreshold); + if(disableReordering) relinKeys = Impl::CheckRelinearizationFull(delta_, ordering_, 0.0); // This is used for debugging // Above relin threshold keys for detailed results if(params_.enableDetailedResults) { @@ -626,15 +701,8 @@ ISAM2Result ISAM2::update( toc(7,"expmap"); result.variablesRelinearized = markedKeys.size(); - -#ifndef NDEBUG - lastRelinVariables_ = markedRelinMask; -#endif } else { result.variablesRelinearized = 0; -#ifndef NDEBUG - lastRelinVariables_ = vector(ordering_.nVars(), false); -#endif } tic(8,"linearize new"); @@ -668,7 +736,7 @@ ISAM2Result ISAM2::update( } boost::shared_ptr > replacedKeys; if(!markedKeys.empty() || !observedKeys.empty()) - replacedKeys = recalculate(markedKeys, relinKeys, observedKeys, constrainedIndices, result); + replacedKeys = recalculate(markedKeys, relinKeys, observedKeys, unusedIndices, constrainedIndices, result); // Update replaced keys mask (accumulates until back-substitution takes place) if(replacedKeys) { @@ -676,19 +744,23 @@ ISAM2Result ISAM2::update( deltaReplacedMask_[var] = true; } } toc(9,"recalculate"); - //tic(9,"solve"); - // 9. Solve - if(debug) delta_.print("delta_: "); - //toc(9,"solve"); - + // After the top of the tree has been redone and may have index gaps from + // unused keys, condense the indices to remove gaps by rearranging indices + // in all data structures. + if(!unusedKeys.empty()) { + tic(10,"remove variables"); + Impl::RemoveVariables(unusedKeys, root_, theta_, variableIndex_, delta_, deltaNewton_, RgProd_, + deltaReplacedMask_, ordering_, Base::nodes_, linearFactors_); + toc(10,"remove variables"); + } result.cliques = this->nodes().size(); deltaDoglegUptodate_ = false; deltaUptodate_ = false; - tic(10,"evaluate error after"); + tic(11,"evaluate error after"); if(params_.evaluateNonlinearError) result.errorAfter.reset(nonlinearFactors_.error(calculateEstimate())); - toc(10,"evaluate error after"); + toc(11,"evaluate error after"); return result; } @@ -719,8 +791,7 @@ void ISAM2::updateDelta(bool forceFullSolve) const { tic(2, "Copy dx_d"); // Update Delta and linear step doglegDelta_ = doglegResult.Delta; - delta_.permutation() = Permutation::Identity(delta_.size()); // Dogleg solves for the full delta so there is no permutation - delta_.container() = doglegResult.dx_d; // Copy the VectorValues containing with the linear solution + delta_ = doglegResult.dx_d; // Copy the VectorValues containing with the linear solution toc(2, "Copy dx_d"); } @@ -732,10 +803,10 @@ Values ISAM2::calculateEstimate() const { // We use ExpmapMasked here instead of regular expmap because the former // handles Permuted tic(1, "Copy Values"); - Values ret(theta_); - toc(1, "Copy Values"); - tic(2, "getDelta"); - const Permuted& delta(getDelta()); + Values ret(theta_); + toc(1, "Copy Values"); + tic(2, "getDelta"); + const VectorValues& delta(getDelta()); toc(2, "getDelta"); tic(3, "Expmap"); vector mask(ordering_.nVars(), true); @@ -752,7 +823,7 @@ Values ISAM2::calculateBestEstimate() const { } /* ************************************************************************* */ -const Permuted& ISAM2::getDelta() const { +const VectorValues& ISAM2::getDelta() const { if(!deltaUptodate_) updateDelta(); return delta_; @@ -825,7 +896,7 @@ void optimizeGradientSearchInPlace(const ISAM2& isam, VectorValues& grad) { tic(3, "Compute minimizing step size"); // Compute minimizing step size - double RgNormSq = isam.RgProd_.container().vector().squaredNorm(); + double RgNormSq = isam.RgProd_.vector().squaredNorm(); double step = -gradientSqNorm / RgNormSq; toc(3, "Compute minimizing step size"); diff --git a/gtsam/nonlinear/ISAM2.h b/gtsam/nonlinear/ISAM2.h index 30f0b14d2..1cea78837 100644 --- a/gtsam/nonlinear/ISAM2.h +++ b/gtsam/nonlinear/ISAM2.h @@ -28,11 +28,7 @@ namespace gtsam { /** - * @defgroup ISAM2 - */ - -/** - * @ingroup ISAM2 + * @addtogroup ISAM2 * Parameters for ISAM2 using Gauss-Newton optimization. Either this class or * ISAM2DoglegParams should be specified as the optimizationParams in * ISAM2Params, which should in turn be passed to ISAM2(const ISAM2Params&). @@ -44,10 +40,19 @@ struct ISAM2GaussNewtonParams { ISAM2GaussNewtonParams( double _wildfireThreshold = 0.001 ///< see ISAM2GaussNewtonParams public variables, ISAM2GaussNewtonParams::wildfireThreshold ) : wildfireThreshold(_wildfireThreshold) {} + + void print(const std::string str = "") const { + std::cout << str << "type: ISAM2GaussNewtonParams\n"; + std::cout << str << "wildfireThreshold: " << wildfireThreshold << "\n"; + std::cout.flush(); + } + + double getWildfireThreshold() const { return wildfireThreshold; } + void setWildfireThreshold(double wildfireThreshold) { this->wildfireThreshold = wildfireThreshold; } }; /** - * @ingroup ISAM2 + * @addtogroup ISAM2 * Parameters for ISAM2 using Dogleg optimization. Either this class or * ISAM2GaussNewtonParams should be specified as the optimizationParams in * ISAM2Params, which should in turn be passed to ISAM2(const ISAM2Params&). @@ -66,12 +71,35 @@ struct ISAM2DoglegParams { bool _verbose = false ///< see ISAM2DoglegParams::verbose ) : initialDelta(_initialDelta), wildfireThreshold(_wildfireThreshold), adaptationMode(_adaptationMode), verbose(_verbose) {} + + void print(const std::string str = "") const { + std::cout << str << "type: ISAM2DoglegParams\n"; + std::cout << str << "initialDelta: " << initialDelta << "\n"; + std::cout << str << "wildfireThreshold: " << wildfireThreshold << "\n"; + std::cout << str << "adaptationMode: " << adaptationModeTranslator(adaptationMode) << "\n"; + std::cout.flush(); + } + + double getInitialDelta() const { return initialDelta; } + double getWildfireThreshold() const { return wildfireThreshold; } + std::string getAdaptationMode() const { return adaptationModeTranslator(adaptationMode); }; + bool isVerbose() const { return verbose; }; + + void setInitialDelta(double initialDelta) { this->initialDelta = initialDelta; } + void setWildfireThreshold(double wildfireThreshold) { this->wildfireThreshold = wildfireThreshold; } + void setAdaptationMode(const std::string& adaptationMode) { this->adaptationMode = adaptationModeTranslator(adaptationMode); } + void setVerbose(bool verbose) { this->verbose = verbose; }; + + std::string adaptationModeTranslator(const DoglegOptimizerImpl::TrustRegionAdaptationMode& adaptationMode) const; + DoglegOptimizerImpl::TrustRegionAdaptationMode adaptationModeTranslator(const std::string& adaptationMode) const; }; /** - * @ingroup ISAM2 + * @addtogroup ISAM2 * Parameters for the ISAM2 algorithm. Default parameter values are listed below. */ +typedef FastMap ISAM2ThresholdMap; +typedef ISAM2ThresholdMap::value_type ISAM2ThresholdMapValue; struct ISAM2Params { typedef boost::variant OptimizationParams; ///< Either ISAM2GaussNewtonParams or ISAM2DoglegParams typedef boost::variant > RelinearizationThreshold; ///< Either a constant relinearization threshold or a per-variable-type set of thresholds @@ -94,8 +122,8 @@ struct ISAM2Params { * entries would be added with: * \code FastMap thresholds; - thresholds[PoseKey::chr()] = Vector_(6, 0.1, 0.1, 0.1, 0.5, 0.5, 0.5); // 0.1 rad rotation threshold, 0.5 m translation threshold - thresholds[PointKey::chr()] = Vector_(3, 1.0, 1.0, 1.0); // 1.0 m landmark position threshold + thresholds['x'] = Vector_(6, 0.1, 0.1, 0.1, 0.5, 0.5, 0.5); // 0.1 rad rotation threshold, 0.5 m translation threshold + thresholds['l'] = Vector_(3, 1.0, 1.0, 1.0); // 1.0 m landmark position threshold params.relinearizeThreshold = thresholds; \endcode */ @@ -112,7 +140,7 @@ struct ISAM2Params { * Cholesky is faster but potentially numerically unstable for poorly-conditioned problems, which can occur when * uncertainty is very low in some variables (or dimensions of variables) and very high in others. QR is * slower but more numerically stable in poorly-conditioned problems. We suggest using the default of Cholesky - * unless gtsam sometimes throws NegativeMatrixException when your problem's Hessian is actually positive + * unless gtsam sometimes throws IndefiniteLinearSystemException when your problem's Hessian is actually positive * definite. For positive definite problems, numerical error accumulation can cause the problem to become * numerically negative or indefinite as solving proceeds, especially when using Cholesky. */ @@ -129,6 +157,13 @@ struct ISAM2Params { bool enableDetailedResults; ///< Whether to compute and return ISAM2Result::detailedResults, this can increase running time (default: false) + /** Check variables for relinearization in tree-order, stopping the check once a variable does not need to be relinearized (default: false). + * This can improve speed by only checking a small part of the top of the tree. However, variables below the check cut-off can accumulate + * significant deltas without triggering relinearization. This is particularly useful in exploration scenarios where real-time performance + * is desired over correctness. Use with caution. + */ + bool enablePartialRelinearizationCheck; + /** Specify parameters as constructor arguments */ ISAM2Params( OptimizationParams _optimizationParams = ISAM2GaussNewtonParams(), ///< see ISAM2Params::optimizationParams @@ -143,11 +178,65 @@ struct ISAM2Params { relinearizeSkip(_relinearizeSkip), enableRelinearization(_enableRelinearization), evaluateNonlinearError(_evaluateNonlinearError), factorization(_factorization), cacheLinearizedFactors(_cacheLinearizedFactors), keyFormatter(_keyFormatter), - enableDetailedResults(false) {} + enableDetailedResults(false), enablePartialRelinearizationCheck(false) {} + + void print(const std::string& str = "") const { + std::cout << str << "\n"; + if(optimizationParams.type() == typeid(ISAM2GaussNewtonParams)) + boost::get(optimizationParams).print("optimizationParams: "); + else if(optimizationParams.type() == typeid(ISAM2DoglegParams)) + boost::get(optimizationParams).print("optimizationParams: "); + else + std::cout << "optimizationParams: " << "{unknown type}" << "\n"; + if(relinearizeThreshold.type() == typeid(double)) + std::cout << "relinearizeThreshold: " << boost::get(relinearizeThreshold) << "\n"; + else + { + std::cout << "relinearizeThreshold: " << "{mapped}" << "\n"; + BOOST_FOREACH(const ISAM2ThresholdMapValue& value, boost::get(relinearizeThreshold)) { + std::cout << " '" << value.first << "' -> [" << value.second.transpose() << " ]\n"; + } + } + std::cout << "relinearizeSkip: " << relinearizeSkip << "\n"; + std::cout << "enableRelinearization: " << enableRelinearization << "\n"; + std::cout << "evaluateNonlinearError: " << evaluateNonlinearError << "\n"; + std::cout << "factorization: " << factorizationTranslator(factorization) << "\n"; + std::cout << "cacheLinearizedFactors: " << cacheLinearizedFactors << "\n"; + std::cout << "enableDetailedResults: " << enableDetailedResults << "\n"; + std::cout << "enablePartialRelinearizationCheck: " << enablePartialRelinearizationCheck << "\n"; + std::cout.flush(); + } + + /** Getters and Setters for all properties */ + OptimizationParams getOptimizationParams() const { return this->optimizationParams; } + RelinearizationThreshold getRelinearizeThreshold() const { return relinearizeThreshold; } + int getRelinearizeSkip() const { return relinearizeSkip; } + bool isEnableRelinearization() const { return enableRelinearization; } + bool isEvaluateNonlinearError() const { return evaluateNonlinearError; } + std::string getFactorization() const { return factorizationTranslator(factorization); } + bool isCacheLinearizedFactors() const { return cacheLinearizedFactors; } + KeyFormatter getKeyFormatter() const { return keyFormatter; } + bool isEnableDetailedResults() const { return enableDetailedResults; } + bool isEnablePartialRelinearizationCheck() const { return enablePartialRelinearizationCheck; } + + void setOptimizationParams(OptimizationParams optimizationParams) { this->optimizationParams = optimizationParams; } + void setRelinearizeThreshold(RelinearizationThreshold relinearizeThreshold) { this->relinearizeThreshold = relinearizeThreshold; } + void setRelinearizeSkip(int relinearizeSkip) { this->relinearizeSkip = relinearizeSkip; } + void setEnableRelinearization(bool enableRelinearization) { this->enableRelinearization = enableRelinearization; } + void setEvaluateNonlinearError(bool evaluateNonlinearError) { this->evaluateNonlinearError = evaluateNonlinearError; } + void setFactorization(const std::string& factorization) { this->factorization = factorizationTranslator(factorization); } + void setCacheLinearizedFactors(bool cacheLinearizedFactors) { this->cacheLinearizedFactors = cacheLinearizedFactors; } + void setKeyFormatter(KeyFormatter keyFormatter) { this->keyFormatter = keyFormatter; } + void setEnableDetailedResults(bool enableDetailedResults) { this->enableDetailedResults = enableDetailedResults; } + void setEnablePartialRelinearizationCheck(bool enablePartialRelinearizationCheck) { this->enablePartialRelinearizationCheck = enablePartialRelinearizationCheck; } + + Factorization factorizationTranslator(const std::string& str) const; + std::string factorizationTranslator(const Factorization& value) const; }; + /** - * @ingroup ISAM2 + * @addtogroup ISAM2 * This struct is returned from ISAM2::update() and contains information about * the update that is useful for determining whether the solution is * converging, and about how much work was required for the update. See member @@ -203,7 +292,7 @@ struct ISAM2Result { * factors passed as \c newFactors to ISAM2::update(). These indices may be * used later to refer to the factors in order to remove them. */ - FastVector newFactorsIndices; + std::vector newFactorsIndices; /** A struct holding detailed results, which must be enabled with * ISAM2Params::enableDetailedResults. @@ -234,10 +323,24 @@ struct ISAM2Result { /** Detailed results, if enabled by ISAM2Params::enableDetailedResults. See * Detail for information about the results data stored here. */ boost::optional detail; + + + void print(const std::string str = "") const { + std::cout << str << " Reelimintated: " << variablesReeliminated << " Relinearized: " << variablesRelinearized << " Cliques: " << cliques << std::endl; + } + + /** Getters and Setters */ + size_t getVariablesRelinearized() const { return variablesRelinearized; }; + size_t getVariablesReeliminated() const { return variablesReeliminated; }; + size_t getCliques() const { return cliques; }; }; -struct ISAM2Clique : public BayesTreeCliqueBase { - +/** + * Specialized Clique structure for ISAM2, incorporating caching and gradient contribution + * TODO: more documentation + */ +class ISAM2Clique : public BayesTreeCliqueBase { +public: typedef ISAM2Clique This; typedef BayesTreeCliqueBase Base; typedef boost::shared_ptr shared_ptr; @@ -250,11 +353,12 @@ struct ISAM2Clique : public BayesTreeCliqueBase >& result) : - Base(result.first), cachedFactor_(result.second), gradientContribution_(result.first->get_R().cols() + result.first->get_S().cols()) { + Base(result.first), cachedFactor_(result.second), + gradientContribution_(result.first->get_R().cols() + result.first->get_S().cols()) { // Compute gradient contribution const ConditionalType& conditional(*result.first); // Rewrite -(R * P')'*d as -(d' * R * P')' for computational speed reasons @@ -264,7 +368,7 @@ struct ISAM2Clique : public BayesTreeCliqueBaseclone() : Base::FactorType::shared_ptr()))); copy->gradientContribution_ = gradientContribution_; @@ -272,22 +376,26 @@ struct ISAM2Clique : public BayesTreeCliqueBaseequals(*other.cachedFactor_, tol))); + return Base::equals(other) && + ((!cachedFactor_ && !other.cachedFactor_) + || (cachedFactor_ && other.cachedFactor_ + && cachedFactor_->equals(*other.cachedFactor_, tol))); } /** print this node */ - void print(const std::string& s = "") const { - Base::print(s); + void print(const std::string& s = "", + const IndexFormatter& formatter = DefaultIndexFormatter) const { + Base::print(s,formatter); if(cachedFactor_) - cachedFactor_->print(s + "Cached: "); + cachedFactor_->print(s + "Cached: ", formatter); else - cout << s << "Cached empty" << endl; + std::cout << s << "Cached empty" << std::endl; if(gradientContribution_.rows() != 0) gtsam::print(gradientContribution_, "Gradient contribution: "); } @@ -304,6 +412,7 @@ struct ISAM2Clique : public BayesTreeCliqueBase @@ -312,10 +421,10 @@ private: ar & BOOST_SERIALIZATION_NVP(cachedFactor_); ar & BOOST_SERIALIZATION_NVP(gradientContribution_); } -}; +}; // \struct ISAM2Clique /** - * @ingroup ISAM2 + * @addtogroup ISAM2 * Implementation of the full ISAM2 algorithm for incremental nonlinear optimization. * * The typical cycle of using this class to create an instance by providing ISAM2Params @@ -334,26 +443,16 @@ protected: /** VariableIndex lets us look up factors by involved variable and keeps track of dimensions */ VariableIndex variableIndex_; - /** The linear delta from the last linear solution, an update to the estimate in theta */ - VectorValues deltaUnpermuted_; + /** The linear delta from the last linear solution, an update to the estimate in theta + * + * This is \c mutable because it is a "cached" variable - it is not updated + * until either requested with getDelta() or calculateEstimate(), or needed + * during update() to evaluate whether to relinearize variables. + */ + mutable VectorValues delta_; - /** The permutation through which the deltaUnpermuted_ is - * referenced. - * - * Permuting Vector entries would be slow, so for performance we - * instead maintain this permutation through which we access the linear delta - * indirectly - * - * This is \c mutable because it is a "cached" variable - it is not updated - * until either requested with getDelta() or calculateEstimate(), or needed - * during update() to evaluate whether to relinearize variables. - */ - mutable Permuted delta_; - - VectorValues deltaNewtonUnpermuted_; - mutable Permuted deltaNewton_; - VectorValues RgProdUnpermuted_; - mutable Permuted RgProd_; + mutable VectorValues deltaNewton_; + mutable VectorValues RgProd_; mutable bool deltaDoglegUptodate_; /** Indicates whether the current delta is up-to-date, only used @@ -400,11 +499,6 @@ protected: /** The inverse ordering, only used for creating ISAM2Result::DetailedResults */ boost::optional inverseOrdering_; -private: -#ifndef NDEBUG - std::vector lastRelinVariables_; -#endif - public: typedef ISAM2 This; ///< This class @@ -446,6 +540,8 @@ public: * @param force_relinearize Relinearize any variables whose delta magnitude is sufficiently * large (Params::relinearizeThreshold), regardless of the relinearization interval * (Params::relinearizeSkip). + * @param constrainedKeys is an optional map of keys to group labels, such that a variable can + * be constrained to a particular grouping in the BayesTree * @return An ISAM2Result struct containing information about the update */ ISAM2Result update(const NonlinearFactorGraph& newFactors = NonlinearFactorGraph(), const Values& newTheta = Values(), @@ -454,7 +550,7 @@ public: bool force_relinearize = false); /** Access the current linearization point */ - const Values& getLinearizationPoint() const {return theta_;} + const Values& getLinearizationPoint() const { return theta_; } /** Compute an estimate from the incomplete linear delta computed during the last update. * This delta is incomplete because it was not updated below wildfire_threshold. If only @@ -482,7 +578,7 @@ public: Values calculateBestEstimate() const; /** Access the current delta, computed during the last call to update */ - const Permuted& getDelta() const; + const VectorValues& getDelta() const; /** Access the set of nonlinear factors */ const NonlinearFactorGraph& getFactorsUnsafe() const { return nonlinearFactors_; } @@ -490,6 +586,9 @@ public: /** Access the current ordering */ const Ordering& getOrdering() const { return ordering_; } + /** Access the nonlinear variable index */ + const VariableIndex& getVariableIndex() const { return variableIndex_; } + size_t lastAffectedVariableCount; size_t lastAffectedFactorCount; size_t lastAffectedCliqueCount; @@ -497,7 +596,10 @@ public: mutable size_t lastBacksubVariableCount; size_t lastNnzTop; - ISAM2Params params() const { return params_; } + const ISAM2Params& params() const { return params_; } + + /** prints out clique statistics */ + void printStats() const { getCliqueData().getStats().print(); } //@} @@ -508,8 +610,7 @@ private: GaussianFactorGraph getCachedBoundaryFactors(Cliques& orphans); boost::shared_ptr > recalculate(const FastSet& markedKeys, const FastSet& relinKeys, - const FastVector& observedKeys, - const boost::optional >& constrainKeys, ISAM2Result& result); + const FastVector& observedKeys, const FastSet& unusedIndices, const boost::optional >& constrainKeys, ISAM2Result& result); // void linear_update(const GaussianFactorGraph& newFactors); void updateDelta(bool forceFullSolve = false) const; @@ -537,7 +638,7 @@ void optimizeInPlace(const ISAM2& isam, VectorValues& delta); /// @return The number of variables that were solved for template int optimizeWildfire(const boost::shared_ptr& root, - double threshold, const std::vector& replaced, Permuted& delta); + double threshold, const std::vector& replaced, VectorValues& delta); /** * Optimize along the gradient direction, with a closed-form computation to diff --git a/gtsam/nonlinear/Key.h b/gtsam/nonlinear/Key.h index 65a65c6d4..ab63fda6d 100644 --- a/gtsam/nonlinear/Key.h +++ b/gtsam/nonlinear/Key.h @@ -20,6 +20,10 @@ #include #include +#include +#include +#include + namespace gtsam { /// Integer nonlinear key type @@ -36,5 +40,10 @@ namespace gtsam { /// and Symbol keys. static const KeyFormatter DefaultKeyFormatter = &_defaultKeyFormatter; + /// Useful typedefs for operations with Values - allow for matlab interfaces + typedef FastList KeyList; + typedef FastVector KeyVector; + typedef FastSet KeySet; + } diff --git a/gtsam/nonlinear/LevenbergMarquardtOptimizer.cpp b/gtsam/nonlinear/LevenbergMarquardtOptimizer.cpp index 1b19cfe75..a77cac35a 100644 --- a/gtsam/nonlinear/LevenbergMarquardtOptimizer.cpp +++ b/gtsam/nonlinear/LevenbergMarquardtOptimizer.cpp @@ -13,28 +13,67 @@ * @file LevenbergMarquardtOptimizer.cpp * @brief * @author Richard Roberts - * @created Feb 26, 2012 + * @date Feb 26, 2012 */ -#include +#include -#include // For NegativeMatrixException -#include -#include +#include +#include +#include + +#include +#include using namespace std; namespace gtsam { +/* ************************************************************************* */ +LevenbergMarquardtParams::VerbosityLM LevenbergMarquardtParams::verbosityLMTranslator(const std::string &src) const { + std::string s = src; boost::algorithm::to_upper(s); + if (s == "SILENT") return LevenbergMarquardtParams::SILENT; + if (s == "LAMBDA") return LevenbergMarquardtParams::LAMBDA; + if (s == "TRYLAMBDA") return LevenbergMarquardtParams::TRYLAMBDA; + if (s == "TRYCONFIG") return LevenbergMarquardtParams::TRYCONFIG; + if (s == "TRYDELTA") return LevenbergMarquardtParams::TRYDELTA; + if (s == "DAMPED") return LevenbergMarquardtParams::DAMPED; + + /* default is silent */ + return LevenbergMarquardtParams::SILENT; +} + +/* ************************************************************************* */ +std::string LevenbergMarquardtParams::verbosityLMTranslator(VerbosityLM value) const { + std::string s; + switch (value) { + case LevenbergMarquardtParams::SILENT: s = "SILENT" ; break; + case LevenbergMarquardtParams::LAMBDA: s = "LAMBDA" ; break; + case LevenbergMarquardtParams::TRYLAMBDA: s = "TRYLAMBDA" ; break; + case LevenbergMarquardtParams::TRYCONFIG: s = "TRYCONFIG" ; break; + case LevenbergMarquardtParams::TRYDELTA: s = "TRYDELTA" ; break; + case LevenbergMarquardtParams::DAMPED: s = "DAMPED" ; break; + default: s = "UNDEFINED" ; break; + } + return s; +} + +/* ************************************************************************* */ +void LevenbergMarquardtParams::print(const std::string& str) const { + SuccessiveLinearizationParams::print(str); + std::cout << " lambdaInitial: " << lambdaInitial << "\n"; + std::cout << " lambdaFactor: " << lambdaFactor << "\n"; + std::cout << " lambdaUpperBound: " << lambdaUpperBound << "\n"; + std::cout << " verbosityLM: " << verbosityLMTranslator(verbosityLM) << "\n"; + std::cout.flush(); +} + /* ************************************************************************* */ void LevenbergMarquardtOptimizer::iterate() { // Linearize graph GaussianFactorGraph::shared_ptr linear = graph_.linearize(state_.values, *params_.ordering); - // Get elimination method - GaussianFactorGraph::Eliminate eliminationMethod = params_.getEliminationFunction(); - // Pull out parameters we'll use const NonlinearOptimizerParams::Verbosity nloVerbosity = params_.verbosity; const LevenbergMarquardtParams::VerbosityLM lmVerbosity = params_.verbosityLM; @@ -48,7 +87,7 @@ void LevenbergMarquardtOptimizer::iterate() { // TODO: replace this dampening with a backsubstitution approach GaussianFactorGraph dampedSystem(*linear); { - double sigma = 1.0 / sqrt(state_.lambda); + double sigma = 1.0 / std::sqrt(state_.lambda); dampedSystem.reserve(dampedSystem.size() + dimensions_.size()); // for each of the variables, add a prior for(Index j=0; j::Create(dampedSystem)->eliminate(eliminationMethod)); - else - throw runtime_error("Optimization parameter is invalid: LevenbergMarquardtParams::elimination"); + // Solve Damped Gaussian Factor Graph + const VectorValues delta = solveGaussianFactorGraph(dampedSystem, params_); if (lmVerbosity >= LevenbergMarquardtParams::TRYLAMBDA) cout << "linear delta norm = " << delta.vector().norm() << endl; if (lmVerbosity >= LevenbergMarquardtParams::TRYDELTA) delta.print("delta"); @@ -102,7 +134,7 @@ void LevenbergMarquardtOptimizer::iterate() { state_.lambda *= params_.lambdaFactor; } } - } catch(const NegativeMatrixException& e) { + } catch(const IndeterminantLinearSystemException& e) { if(lmVerbosity >= LevenbergMarquardtParams::LAMBDA) cout << "Negative matrix, increasing lambda" << endl; // Either we're not cautious, or the same lambda was worse than the current error. diff --git a/gtsam/nonlinear/LevenbergMarquardtOptimizer.h b/gtsam/nonlinear/LevenbergMarquardtOptimizer.h index c1fe55c26..62d05839d 100644 --- a/gtsam/nonlinear/LevenbergMarquardtOptimizer.h +++ b/gtsam/nonlinear/LevenbergMarquardtOptimizer.h @@ -13,7 +13,7 @@ * @file LevenbergMarquardtOptimizer.h * @brief * @author Richard Roberts - * @created Feb 26, 2012 + * @date Feb 26, 2012 */ #pragma once @@ -30,10 +30,11 @@ class LevenbergMarquardtOptimizer; * all of those parameters. */ class LevenbergMarquardtParams : public SuccessiveLinearizationParams { + public: /** See LevenbergMarquardtParams::lmVerbosity */ enum VerbosityLM { - SILENT, + SILENT = 0, LAMBDA, TRYLAMBDA, TRYCONFIG, @@ -46,26 +47,32 @@ public: double lambdaUpperBound; ///< The maximum lambda to try before assuming the optimization has failed (default: 1e5) VerbosityLM verbosityLM; ///< The verbosity level for Levenberg-Marquardt (default: SILENT), see also NonlinearOptimizerParams::verbosity - LevenbergMarquardtParams() : - lambdaInitial(1e-5), lambdaFactor(10.0), lambdaUpperBound(1e5), verbosityLM(SILENT) {} - + LevenbergMarquardtParams() : lambdaInitial(1e-5), lambdaFactor(10.0), lambdaUpperBound(1e5), verbosityLM(SILENT) {} virtual ~LevenbergMarquardtParams() {} - virtual void print(const std::string& str = "") const { - SuccessiveLinearizationParams::print(str); - std::cout << " lambdaInitial: " << lambdaInitial << "\n"; - std::cout << " lambdaFactor: " << lambdaFactor << "\n"; - std::cout << " lambdaUpperBound: " << lambdaUpperBound << "\n"; - std::cout.flush(); - } + virtual void print(const std::string& str = "") const; + + inline double getlambdaInitial() const { return lambdaInitial; } + inline double getlambdaFactor() const { return lambdaFactor; } + inline double getlambdaUpperBound() const { return lambdaUpperBound; } + inline std::string getVerbosityLM() const { return verbosityLMTranslator(verbosityLM); } + + inline void setlambdaInitial(double value) { lambdaInitial = value; } + inline void setlambdaFactor(double value) { lambdaFactor = value; } + inline void setlambdaUpperBound(double value) { lambdaUpperBound = value; } + inline void setVerbosityLM(const std::string &s) { verbosityLM = verbosityLMTranslator(s); } + +private: + VerbosityLM verbosityLMTranslator(const std::string &s) const; + std::string verbosityLMTranslator(VerbosityLM value) const; }; /** * State for LevenbergMarquardtOptimizer */ class LevenbergMarquardtState : public NonlinearOptimizerState { -public: +public: double lambda; LevenbergMarquardtState() {} @@ -73,10 +80,10 @@ public: virtual ~LevenbergMarquardtState() {} protected: - LevenbergMarquardtState(const NonlinearFactorGraph& graph, const Values& initialValues, const LevenbergMarquardtParams& params, unsigned int iterations = 0) : - NonlinearOptimizerState(graph, initialValues, iterations), lambda(params.lambdaInitial) {} + LevenbergMarquardtState(const NonlinearFactorGraph& graph, const Values& initialValues, const LevenbergMarquardtParams& params, unsigned int iterations = 0) : + NonlinearOptimizerState(graph, initialValues, iterations), lambda(params.lambdaInitial) {} - friend class LevenbergMarquardtOptimizer; + friend class LevenbergMarquardtOptimizer; }; /** @@ -84,8 +91,12 @@ protected: */ class LevenbergMarquardtOptimizer : public NonlinearOptimizer { -public: +protected: + LevenbergMarquardtParams params_; ///< LM parameters + LevenbergMarquardtState state_; ///< optimization state + std::vector dimensions_; ///< undocumented +public: typedef boost::shared_ptr shared_ptr; /// @name Standard interface @@ -110,16 +121,21 @@ public: * copies the objects. * @param graph The nonlinear factor graph to optimize * @param initialValues The initial variable assignments - * @param params The optimization parameters */ LevenbergMarquardtOptimizer(const NonlinearFactorGraph& graph, const Values& initialValues, const Ordering& ordering) : NonlinearOptimizer(graph), dimensions_(initialValues.dims(ordering)) { params_.ordering = ordering; state_ = LevenbergMarquardtState(graph, initialValues, params_); } - /** Access the current damping value */ + /// Access the current damping value double lambda() const { return state_.lambda; } + /// print + virtual void print(const std::string& str = "") const { + std::cout << str << "LevenbergMarquardtOptimizer" << std::endl; + this->params_.print(" parameters:\n"); + } + /// @} /// @name Advanced interface @@ -143,23 +159,18 @@ public: /// @} protected: + /** Access the parameters (base class version) */ + virtual const NonlinearOptimizerParams& _params() const { return params_; } - LevenbergMarquardtParams params_; - LevenbergMarquardtState state_; - std::vector dimensions_; + /** Access the state (base class version) */ + virtual const NonlinearOptimizerState& _state() const { return state_; } - /** Access the parameters (base class version) */ - virtual const NonlinearOptimizerParams& _params() const { return params_; } - - /** Access the state (base class version) */ - virtual const NonlinearOptimizerState& _state() const { return state_; } - - /** Internal function for computing a COLAMD ordering if no ordering is specified */ - LevenbergMarquardtParams ensureHasOrdering(LevenbergMarquardtParams params, const NonlinearFactorGraph& graph, const Values& values) const { - if(!params.ordering) - params.ordering = *graph.orderingCOLAMD(values); - return params; - } + /** Internal function for computing a COLAMD ordering if no ordering is specified */ + LevenbergMarquardtParams ensureHasOrdering(LevenbergMarquardtParams params, const NonlinearFactorGraph& graph, const Values& values) const { + if(!params.ordering) + params.ordering = *graph.orderingCOLAMD(values); + return params; + } }; } diff --git a/gtsam/nonlinear/Marginals.cpp b/gtsam/nonlinear/Marginals.cpp index 34d620bc2..c3078ea76 100644 --- a/gtsam/nonlinear/Marginals.cpp +++ b/gtsam/nonlinear/Marginals.cpp @@ -21,6 +21,8 @@ #include #include +using namespace std; + namespace gtsam { /* ************************************************************************* */ @@ -43,6 +45,14 @@ Marginals::Marginals(const NonlinearFactorGraph& graph, const Values& solution, bayesTree_ = *GaussianMultifrontalSolver(graph_, true).eliminate(); } +/* ************************************************************************* */ +void Marginals::print(const std::string& str, const KeyFormatter& keyFormatter) const { + ordering_.print(str+"Ordering: ", keyFormatter); + graph_.print(str+"Graph: "); + values_.print(str+"Solution: ", keyFormatter); + bayesTree_.print(str+"Bayes Tree: "); +} + /* ************************************************************************* */ Matrix Marginals::marginalCovariance(Key variable) const { return marginalInformation(variable).inverse(); @@ -61,16 +71,22 @@ Matrix Marginals::marginalInformation(Key variable) const { marginalFactor = bayesTree_.marginalFactor(index, EliminateQR); // Get information matrix (only store upper-right triangle) - if(typeid(*marginalFactor) == typeid(JacobianFactor)) { - JacobianFactor::constABlock A = static_cast(*marginalFactor).getA(); - return A.transpose() * A; // Compute A'A - } else if(typeid(*marginalFactor) == typeid(HessianFactor)) { - const HessianFactor& hessian = static_cast(*marginalFactor); - const size_t dim = hessian.getDim(hessian.begin()); - return hessian.info().topLeftCorner(dim,dim).selfadjointView(); // Take the non-augmented part of the information matrix - } else { - throw runtime_error("Internal error: Marginals::marginalInformation expected either a JacobianFactor or HessianFactor"); - } + Matrix info = marginalFactor->computeInformation(); + const int dim = info.rows() - 1; + return info.topLeftCorner(dim,dim); // Take the non-augmented part of the information matrix +} + +/* ************************************************************************* */ +JointMarginal::JointMarginal(const JointMarginal& other) : + blockView_(fullMatrix_) { + *this = other; +} + +/* ************************************************************************* */ +JointMarginal& JointMarginal::operator=(const JointMarginal& rhs) { + indices_ = rhs.indices_; + blockView_.assignNoalias(rhs.blockView_); + return *this; } /* ************************************************************************* */ @@ -94,11 +110,11 @@ JointMarginal Marginals::jointMarginalInformation(const std::vector& variab return JointMarginal(info, dims, indices); } else { - // Convert keys to linear indices + // Obtain requested variables as ordered indices vector indices(variables.size()); for(size_t i=0; i& variab jointFG = *GaussianSequentialSolver(graph_, true).jointFactorGraph(indices); } - // Conversion from variable keys to position in factor graph variables, + // Build map from variable keys to position in factor graph variables, // which are sorted in index order. Ordering variableConversion; { + // First build map from index to key FastMap usedIndices; for(size_t i=0; i Index_Key; BOOST_FOREACH(const Index_Key& index_key, usedIndices) { @@ -129,15 +147,30 @@ JointMarginal Marginals::jointMarginalInformation(const std::vector& variab // Get dimensions from factor graph std::vector dims(indices.size(), 0); - for(size_t i = 0; i < variables.size(); ++i) - dims[i] = values_.at(variables[i]).dim(); + BOOST_FOREACH(Key key, variables) { + dims[variableConversion[key]] = values_.at(key).dim(); + } // Get information matrix - Matrix augmentedInfo = jointFG.denseHessian(); + Matrix augmentedInfo = jointFG.augmentedHessian(); Matrix info = augmentedInfo.topLeftCorner(augmentedInfo.rows()-1, augmentedInfo.cols()-1); return JointMarginal(info, dims, variableConversion); } } +/* ************************************************************************* */ +void JointMarginal::print(const std::string& s, const KeyFormatter& formatter) const { + cout << s << "Joint marginal on keys "; + bool first = true; + BOOST_FOREACH(const Ordering::value_type& key_index, indices_) { + if(!first) + cout << ", "; + else + first = false; + cout << formatter(key_index.first); + } + cout << ". Use 'at' or 'operator()' to query matrix blocks." << endl; +} + } /* namespace gtsam */ diff --git a/gtsam/nonlinear/Marginals.h b/gtsam/nonlinear/Marginals.h index 77bccdfd2..302c686e8 100644 --- a/gtsam/nonlinear/Marginals.h +++ b/gtsam/nonlinear/Marginals.h @@ -40,6 +40,16 @@ public: QR }; +protected: + + GaussianFactorGraph graph_; + Ordering ordering_; + Values values_; + Factorization factorization_; + GaussianBayesTree bayesTree_; + +public: + /** Construct a marginals class. * @param graph The factor graph defining the full joint density on all variables. * @param solution The linearization point about which to compute Gaussian marginals (usually the MLE as obtained from a NonlinearOptimizer). @@ -47,6 +57,9 @@ public: */ Marginals(const NonlinearFactorGraph& graph, const Values& solution, Factorization factorization = CHOLESKY); + /** print */ + void print(const std::string& str = "Marginals: ", const KeyFormatter& keyFormatter = DefaultKeyFormatter) const; + /** Compute the marginal covariance of a single variable */ Matrix marginalCovariance(Key variable) const; @@ -60,14 +73,6 @@ public: /** Compute the joint marginal information of several variables */ JointMarginal jointMarginalInformation(const std::vector& variables) const; - -protected: - - GaussianFactorGraph graph_; - Values values_; - Ordering ordering_; - Factorization factorization_; - GaussianBayesTree bayesTree_; }; /** @@ -76,7 +81,12 @@ protected: class JointMarginal { protected: - typedef SymmetricBlockView BlockView; + + typedef SymmetricBlockView BlockView; + + Matrix fullMatrix_; + BlockView blockView_; + Ordering indices_; public: /** A block view of the joint marginal - this stores a reference to the @@ -102,15 +112,32 @@ public: Block operator()(Key iVariable, Key jVariable) const { return blockView_(indices_[iVariable], indices_[jVariable]); } + /** Synonym for operator() */ + Block at(Key iVariable, Key jVariable) const { + return (*this)(iVariable, jVariable); } + + /** The full, dense covariance/information matrix of the joint marginal. This returns + * a reference to the JointMarginal object, so the JointMarginal object must be kept + * in scope while this view is needed. Otherwise assign this block object to a Matrix + * to store it. + */ + const Matrix& fullMatrix() const { return fullMatrix_; } + + /** Copy constructor */ + JointMarginal(const JointMarginal& other); + + /** Assignment operator */ + JointMarginal& operator=(const JointMarginal& rhs); + + /** Print */ + void print(const std::string& s = "", const KeyFormatter& formatter = DefaultKeyFormatter) const; + protected: - Matrix fullMatrix_; - BlockView blockView_; - Ordering indices_; + JointMarginal(const Matrix& fullMatrix, const std::vector& dims, const Ordering& indices) : + fullMatrix_(fullMatrix), blockView_(fullMatrix_, dims.begin(), dims.end()), indices_(indices) {} - JointMarginal(const Matrix& fullMatrix, const std::vector& dims, const Ordering& indices) : - fullMatrix_(fullMatrix), blockView_(fullMatrix_, dims.begin(), dims.end()), indices_(indices) {} + friend class Marginals; - friend class Marginals; }; } /* namespace gtsam */ diff --git a/gtsam/nonlinear/NonlinearConjugateGradientOptimizer.cpp b/gtsam/nonlinear/NonlinearConjugateGradientOptimizer.cpp new file mode 100644 index 000000000..da14d8982 --- /dev/null +++ b/gtsam/nonlinear/NonlinearConjugateGradientOptimizer.cpp @@ -0,0 +1,64 @@ +/** + * @file GradientDescentOptimizer.cpp + * @brief + * @author ydjian + * @date Jun 11, 2012 + */ + +#include +#include +#include +#include +#include + +#include + +using namespace std; + +namespace gtsam { + +/* Return the gradient vector of a nonlinear factor given a linearization point and a variable ordering + * Can be moved to NonlinearFactorGraph.h if desired */ +void gradientInPlace(const NonlinearFactorGraph &nfg, const Values &values, const Ordering &ordering, VectorValues &g) { + // Linearize graph + GaussianFactorGraph::shared_ptr linear = nfg.linearize(values, ordering); + FactorGraph jfg; jfg.reserve(linear->size()); + BOOST_FOREACH(const GaussianFactorGraph::sharedFactor& factor, *linear) { + if(boost::shared_ptr jf = boost::dynamic_pointer_cast(factor)) + jfg.push_back((jf)); + else + jfg.push_back(boost::make_shared(*factor)); + } + // compute the gradient direction + gradientAtZero(jfg, g); +} + +double NonlinearConjugateGradientOptimizer::System::error(const State &state) const { + return graph_.error(state); +} + +NonlinearConjugateGradientOptimizer::System::Gradient NonlinearConjugateGradientOptimizer::System::gradient(const State &state) const { + Gradient result = state.zeroVectors(ordering_); + gradientInPlace(graph_, state, ordering_, result); + return result; +} +NonlinearConjugateGradientOptimizer::System::State NonlinearConjugateGradientOptimizer::System::advance(const State ¤t, const double alpha, const Gradient &g) const { + Gradient step = g; + step.vector() *= alpha; + return current.retract(step, ordering_); +} + +void NonlinearConjugateGradientOptimizer::iterate() { + size_t dummy ; + boost::tie(state_.values, dummy) = nonlinearConjugateGradient(System(graph_, *ordering_), state_.values, params_, true /* single iterations */); + ++state_.iterations; + state_.error = graph_.error(state_.values); +} + +const Values& NonlinearConjugateGradientOptimizer::optimize() { + boost::tie(state_.values, state_.iterations) = nonlinearConjugateGradient(System(graph_, *ordering_), state_.values, params_, false /* up to convergent */); + state_.error = graph_.error(state_.values); + return state_.values; +} + +} /* namespace gtsam */ diff --git a/gtsam/nonlinear/NonlinearConjugateGradientOptimizer.h b/gtsam/nonlinear/NonlinearConjugateGradientOptimizer.h new file mode 100644 index 000000000..5bac11f5e --- /dev/null +++ b/gtsam/nonlinear/NonlinearConjugateGradientOptimizer.h @@ -0,0 +1,193 @@ +/** + * @file GradientDescentOptimizer.cpp + * @brief + * @author Yong-Dian Jian + * @date Jun 11, 2012 + */ + +#pragma once + +#include +#include +#include + +namespace gtsam { + +/** An implementation of the nonlinear cg method using the template below */ +class NonlinearConjugateGradientState : public NonlinearOptimizerState { +public: + typedef NonlinearOptimizerState Base; + NonlinearConjugateGradientState(const NonlinearFactorGraph& graph, const Values& values) + : Base(graph, values) {} +}; + +class NonlinearConjugateGradientOptimizer : public NonlinearOptimizer { + /* a class for the nonlinearConjugateGradient template */ + class System { + public: + typedef Values State; + typedef VectorValues Gradient; + typedef NonlinearOptimizerParams Parameters; + + protected: + const NonlinearFactorGraph &graph_; + const Ordering &ordering_; + + public: + System(const NonlinearFactorGraph &graph, const Ordering &ordering): graph_(graph), ordering_(ordering) {} + double error(const State &state) const ; + Gradient gradient(const State &state) const ; + State advance(const State ¤t, const double alpha, const Gradient &g) const ; + }; + +public: + typedef NonlinearOptimizer Base; + typedef NonlinearConjugateGradientState States; + typedef NonlinearOptimizerParams Parameters; + typedef boost::shared_ptr shared_ptr; + +protected: + States state_; + Parameters params_; + Ordering::shared_ptr ordering_; + VectorValues::shared_ptr gradient_; + +public: + + NonlinearConjugateGradientOptimizer(const NonlinearFactorGraph& graph, const Values& initialValues, + const Parameters& params = Parameters()) + : Base(graph), state_(graph, initialValues), params_(params), ordering_(initialValues.orderingArbitrary()), + gradient_(new VectorValues(initialValues.zeroVectors(*ordering_))){} + + virtual ~NonlinearConjugateGradientOptimizer() {} + virtual void iterate(); + virtual const Values& optimize (); + virtual const NonlinearOptimizerState& _state() const { return state_; } + virtual const NonlinearOptimizerParams& _params() const { return params_; } +}; + +/** Implement the golden-section line search algorithm */ +template +double lineSearch(const S &system, const V currentValues, const W &gradient) { + + /* normalize it such that it becomes a unit vector */ + const double g = gradient.norm(); + + // perform the golden section search algorithm to decide the the optimal step size + // detail refer to http://en.wikipedia.org/wiki/Golden_section_search + const double phi = 0.5*(1.0+std::sqrt(5.0)), resphi = 2.0 - phi, tau = 1e-5; + double minStep = -1.0/g, maxStep = 0, + newStep = minStep + (maxStep-minStep) / (phi+1.0) ; + + V newValues = system.advance(currentValues, newStep, gradient); + double newError = system.error(newValues); + + while (true) { + const bool flag = (maxStep - newStep > newStep - minStep) ? true : false ; + const double testStep = flag ? + newStep + resphi * (maxStep - newStep) : newStep - resphi * (newStep - minStep); + + if ( (maxStep- minStep) < tau * (std::fabs(testStep) + std::fabs(newStep)) ) { + return 0.5*(minStep+maxStep); + } + + const V testValues = system.advance(currentValues, testStep, gradient); + const double testError = system.error(testValues); + + // update the working range + if ( testError >= newError ) { + if ( flag ) maxStep = testStep; + else minStep = testStep; + } + else { + if ( flag ) { + minStep = newStep; + newStep = testStep; + newError = testError; + } + else { + maxStep = newStep; + newStep = testStep; + newError = testError; + } + } + } + return 0.0; +} + +/** + * Implement the nonlinear conjugate gradient method using the Polak-Ribieve formula suggested in + * http://en.wikipedia.org/wiki/Nonlinear_conjugate_gradient_method. + * + * The S (system) class requires three member functions: error(state), gradient(state) and + * advance(state, step-size, direction). The V class denotes the state or the solution. + * + * The last parameter is a switch between gradient-descent and conjugate gradient + */ +template +boost::tuple nonlinearConjugateGradient(const S &system, const V &initial, const NonlinearOptimizerParams ¶ms, const bool singleIteration, const bool gradientDescent = false) { + + // GTSAM_CONCEPT_MANIFOLD_TYPE(V); + + Index iteration = 0; + + // check if we're already close enough + double currentError = system.error(initial); + if(currentError <= params.errorTol) { + if (params.verbosity >= NonlinearOptimizerParams::ERROR){ + std::cout << "Exiting, as error = " << currentError << " < " << params.errorTol << std::endl; + } + return boost::tie(initial, iteration); + } + + V currentValues = initial; + typename S::Gradient currentGradient = system.gradient(currentValues), prevGradient, + direction = currentGradient; + + /* do one step of gradient descent */ + V prevValues = currentValues; double prevError = currentError; + double alpha = lineSearch(system, currentValues, direction); + currentValues = system.advance(prevValues, alpha, direction); + currentError = system.error(currentValues); + + // Maybe show output + if (params.verbosity >= NonlinearOptimizerParams::ERROR) std::cout << "Initial error: " << currentError << std::endl; + + // Iterative loop + do { + if ( gradientDescent == true) { + direction = system.gradient(currentValues); + } + else { + prevGradient = currentGradient; + currentGradient = system.gradient(currentValues); + const double beta = std::max(0.0, currentGradient.dot(currentGradient-prevGradient)/currentGradient.dot(currentGradient)); + direction = currentGradient + (beta*direction); + } + + alpha = lineSearch(system, currentValues, direction); + + prevValues = currentValues; prevError = currentError; + + currentValues = system.advance(prevValues, alpha, direction); + currentError = system.error(currentValues); + + // Maybe show output + if(params.verbosity >= NonlinearOptimizerParams::ERROR) std::cout << "currentError: " << currentError << std::endl; + } while( ++iteration < params.maxIterations && + !singleIteration && + !checkConvergence(params.relativeErrorTol, params.absoluteErrorTol, params.errorTol, prevError, currentError, params.verbosity)); + + // Printing if verbose + if (params.verbosity >= NonlinearOptimizerParams::ERROR && iteration >= params.maxIterations) + std::cout << "nonlinearConjugateGradient: Terminating because reached maximum iterations" << std::endl; + + return boost::tie(currentValues, iteration); +} + + + + + + +} diff --git a/gtsam/nonlinear/NonlinearEquality.h b/gtsam/nonlinear/NonlinearEquality.h index a1c685668..e4a628b85 100644 --- a/gtsam/nonlinear/NonlinearEquality.h +++ b/gtsam/nonlinear/NonlinearEquality.h @@ -109,8 +109,8 @@ namespace gtsam { /// @{ virtual void print(const std::string& s = "", const KeyFormatter& keyFormatter = DefaultKeyFormatter) const { - std::cout << "Constraint: " << s << " on [" << keyFormatter(this->key()) << "]\n"; - gtsam::print(feasible_,"Feasible Point"); + std::cout << s << "Constraint: on [" << keyFormatter(this->key()) << "]\n"; + gtsam::print(feasible_,"Feasible Point:\n"); std::cout << "Variable Dimension: " << feasible_.dim() << std::endl; } @@ -161,6 +161,11 @@ namespace gtsam { return GaussianFactor::shared_ptr(new JacobianFactor(ordering[this->key()], A, b, model)); } + /// @return a deep copy of this factor + virtual gtsam::NonlinearFactor::shared_ptr clone() const { + return boost::static_pointer_cast( + gtsam::NonlinearFactor::shared_ptr(new This(*this))); } + /// @} private: @@ -190,6 +195,7 @@ namespace gtsam { protected: typedef NoiseModelFactor1 Base; + typedef NonlinearEquality1 This; /** default constructor to allow for serialization */ NonlinearEquality1() {} @@ -209,6 +215,11 @@ namespace gtsam { virtual ~NonlinearEquality1() {} + /// @return a deep copy of this factor + virtual gtsam::NonlinearFactor::shared_ptr clone() const { + return boost::static_pointer_cast( + gtsam::NonlinearFactor::shared_ptr(new This(*this))); } + /** g(x) with optional derivative */ Vector evaluateError(const X& x1, boost::optional H = boost::none) const { if (H) (*H) = eye(x1.dim()); @@ -248,6 +259,7 @@ namespace gtsam { protected: typedef NoiseModelFactor2 Base; + typedef NonlinearEquality2 This; GTSAM_CONCEPT_MANIFOLD_TYPE(X); @@ -263,6 +275,11 @@ namespace gtsam { : Base(noiseModel::Constrained::All(X::Dim(), fabs(mu)), key1, key2) {} virtual ~NonlinearEquality2() {} + /// @return a deep copy of this factor + virtual gtsam::NonlinearFactor::shared_ptr clone() const { + return boost::static_pointer_cast( + gtsam::NonlinearFactor::shared_ptr(new This(*this))); } + /** g(x) with optional derivative2 */ Vector evaluateError(const X& x1, const X& x2, boost::optional H1 = boost::none, diff --git a/gtsam/nonlinear/NonlinearFactor.h b/gtsam/nonlinear/NonlinearFactor.h index bf19555bf..ad10b3ee0 100644 --- a/gtsam/nonlinear/NonlinearFactor.h +++ b/gtsam/nonlinear/NonlinearFactor.h @@ -10,8 +10,8 @@ * -------------------------------------------------------------------------- */ /** - * @file NoiseModelFactor.h - * @brief Non-linear factor class + * @file NonlinearFactor.h + * @brief Non-linear factor base classes * @author Frank Dellaert * @author Richard Roberts */ @@ -28,12 +28,20 @@ #include #include -#include +#include #include #include #include -#include + +/** + * Macro to add a standard clone function to a derived factor + * @deprecated: will go away shortly - just add the clone function directly + */ +#define ADD_CLONE_NONLINEAR_FACTOR(Derived) \ + virtual gtsam::NonlinearFactor::shared_ptr clone() const { \ + return boost::static_pointer_cast( \ + gtsam::NonlinearFactor::shared_ptr(new Derived(*this))); } namespace gtsam { @@ -91,9 +99,9 @@ public: /** print */ virtual void print(const std::string& s = "", const KeyFormatter& keyFormatter = DefaultKeyFormatter) const { - std::cout << s << "keys = { "; + std::cout << s << " keys = { "; BOOST_FOREACH(Key key, this->keys()) { std::cout << keyFormatter(key) << " "; } - std::cout << "}" << endl; + std::cout << "}" << std::endl; } /** Check if two factors are equal */ @@ -111,7 +119,7 @@ public: /** * Calculate the error of the factor - * This is typically equal to log-likelihood, e.g. 0.5(h(x)-z)^2/sigma^2 in case of Gaussian. + * This is typically equal to log-likelihood, e.g. \f$ 0.5(h(x)-z)^2/sigma^2 \f$ in case of Gaussian. * You can override this for systems with unusual noise models. */ virtual double error(const Values& c) const = 0; @@ -146,6 +154,45 @@ public: return IndexFactor::shared_ptr(new IndexFactor(indices)); } + /** + * Creates a shared_ptr clone of the factor - needs to be specialized to allow + * for subclasses + * + * By default, throws exception if subclass does not implement the function. + */ + virtual shared_ptr clone() const { + // TODO: choose better exception to throw here + throw std::runtime_error("NonlinearFactor::clone(): Attempting to clone factor with no clone() implemented!"); + return shared_ptr(); + } + + /** + * Creates a shared_ptr clone of the factor with different keys using + * a map from old->new keys + */ + shared_ptr rekey(const std::map& rekey_mapping) const { + shared_ptr new_factor = clone(); + for (size_t i=0; isize(); ++i) { + Key& cur_key = new_factor->keys()[i]; + std::map::const_iterator mapping = rekey_mapping.find(cur_key); + if (mapping != rekey_mapping.end()) + cur_key = mapping->second; + } + return new_factor; + } + + /** + * Clones a factor and fully replaces its keys + * @param new_keys is the full replacement set of keys + */ + shared_ptr rekey(const std::vector& new_keys) const { + assert(new_keys.size() == this->keys().size()); + shared_ptr new_factor = clone(); + new_factor->keys() = new_keys; + return new_factor; + } + + }; // \class NonlinearFactor /* ************************************************************************* */ @@ -182,7 +229,6 @@ public: /** * Constructor - * @param keys The variables involved in this factor */ template NoiseModelFactor(const SharedNoiseModel& noiseModel, ITERATOR beginKeys, ITERATOR endKeys) @@ -333,14 +379,14 @@ public: /** * Constructor - * @param z measurement - * @param key by which to look up X value in Values + * @param key1 by which to look up X value in Values */ NoiseModelFactor1(const SharedNoiseModel& noiseModel, Key key1) : Base(noiseModel, key1) {} /** Calls the 1-key specific version of evaluateError, which is pure virtual - * so must be implemented in the derived class. */ + * so must be implemented in the derived class. + */ virtual Vector unwhitenedError(const Values& x, boost::optional&> H = boost::none) const { if(this->active(x)) { const X& x1 = x.at(keys_[0]); diff --git a/gtsam/nonlinear/NonlinearFactorGraph.cpp b/gtsam/nonlinear/NonlinearFactorGraph.cpp index 2400ea996..969e40677 100644 --- a/gtsam/nonlinear/NonlinearFactorGraph.cpp +++ b/gtsam/nonlinear/NonlinearFactorGraph.cpp @@ -27,112 +27,161 @@ using namespace std; namespace gtsam { - /* ************************************************************************* */ - double NonlinearFactorGraph::probPrime(const Values& c) const { - return exp(-0.5 * error(c)); +/* ************************************************************************* */ +double NonlinearFactorGraph::probPrime(const Values& c) const { + return exp(-0.5 * error(c)); +} + +/* ************************************************************************* */ +void NonlinearFactorGraph::print(const std::string& str, const KeyFormatter& keyFormatter) const { + cout << str << "size: " << size() << endl; + for (size_t i = 0; i < factors_.size(); i++) { + stringstream ss; + ss << "factor " << i << ": "; + if (factors_[i] != NULL) factors_[i]->print(ss.str(), keyFormatter); } +} - /* ************************************************************************* */ - void NonlinearFactorGraph::print(const std::string& str, const KeyFormatter& keyFormatter) const { - cout << str << "size: " << size() << endl; - for (size_t i = 0; i < factors_.size(); i++) { - stringstream ss; - ss << "factor " << i << ": "; - if (factors_[i] != NULL) factors_[i]->print(ss.str(), keyFormatter); - } +/* ************************************************************************* */ +double NonlinearFactorGraph::error(const Values& c) const { + double total_error = 0.; + // iterate over all the factors_ to accumulate the log probabilities + BOOST_FOREACH(const sharedFactor& factor, this->factors_) { + if(factor) + total_error += factor->error(c); } + return total_error; +} - /* ************************************************************************* */ - double NonlinearFactorGraph::error(const Values& c) const { - double total_error = 0.; - // iterate over all the factors_ to accumulate the log probabilities - BOOST_FOREACH(const sharedFactor& factor, this->factors_) { - if(factor) - total_error += factor->error(c); - } - return total_error; +/* ************************************************************************* */ +FastSet NonlinearFactorGraph::keys() const { + FastSet keys; + BOOST_FOREACH(const sharedFactor& factor, this->factors_) { + if(factor) + keys.insert(factor->begin(), factor->end()); } + return keys; +} - /* ************************************************************************* */ - std::set NonlinearFactorGraph::keys() const { - std::set keys; - BOOST_FOREACH(const sharedFactor& factor, this->factors_) { - if(factor) - keys.insert(factor->begin(), factor->end()); - } - return keys; - } - - /* ************************************************************************* */ - Ordering::shared_ptr NonlinearFactorGraph::orderingCOLAMD( - const Values& config) const { - - // Create symbolic graph and initial (iterator) ordering - SymbolicFactorGraph::shared_ptr symbolic; - Ordering::shared_ptr ordering; - boost::tie(symbolic, ordering) = this->symbolic(config); - - // Compute the VariableIndex (column-wise index) - VariableIndex variableIndex(*symbolic, ordering->size()); - if (config.size() != variableIndex.size()) throw std::runtime_error( - "orderingCOLAMD: some variables in the graph are not constrained!"); - - // Compute a fill-reducing ordering with COLAMD - Permutation::shared_ptr colamdPerm(inference::PermutationCOLAMD( - variableIndex)); - - // Permute the Ordering with the COLAMD ordering - ordering->permuteWithInverse(*colamdPerm->inverse()); - - // Return the Ordering and VariableIndex to be re-used during linearization - // and elimination - return ordering; - } - - /* ************************************************************************* */ - SymbolicFactorGraph::shared_ptr NonlinearFactorGraph::symbolic(const Ordering& ordering) const { - // Generate the symbolic factor graph - SymbolicFactorGraph::shared_ptr symbolicfg(new SymbolicFactorGraph); - symbolicfg->reserve(this->size()); - - BOOST_FOREACH(const sharedFactor& factor, this->factors_) { - if(factor) - symbolicfg->push_back(factor->symbolic(ordering)); - else - symbolicfg->push_back(SymbolicFactorGraph::sharedFactor()); - } - - return symbolicfg; - } - - /* ************************************************************************* */ - pair NonlinearFactorGraph::symbolic( +/* ************************************************************************* */ +Ordering::shared_ptr NonlinearFactorGraph::orderingCOLAMD( const Values& config) const { - // Generate an initial key ordering in iterator order - Ordering::shared_ptr ordering(config.orderingArbitrary()); - return make_pair(symbolic(*ordering), ordering); + + // Create symbolic graph and initial (iterator) ordering + SymbolicFactorGraph::shared_ptr symbolic; + Ordering::shared_ptr ordering; + boost::tie(symbolic, ordering) = this->symbolic(config); + + // Compute the VariableIndex (column-wise index) + VariableIndex variableIndex(*symbolic, ordering->size()); + if (config.size() != variableIndex.size()) throw std::runtime_error( + "orderingCOLAMD: some variables in the graph are not constrained!"); + + // Compute a fill-reducing ordering with COLAMD + Permutation::shared_ptr colamdPerm(inference::PermutationCOLAMD( + variableIndex)); + + // Permute the Ordering with the COLAMD ordering + ordering->permuteWithInverse(*colamdPerm->inverse()); + return ordering; +} + +/* ************************************************************************* */ +Ordering::shared_ptr NonlinearFactorGraph::orderingCOLAMDConstrained(const Values& config, + const std::map& constraints) const { + // Create symbolic graph and initial (iterator) ordering + SymbolicFactorGraph::shared_ptr symbolic; + Ordering::shared_ptr ordering; + boost::tie(symbolic, ordering) = this->symbolic(config); + + // Compute the VariableIndex (column-wise index) + VariableIndex variableIndex(*symbolic, ordering->size()); + if (config.size() != variableIndex.size()) throw std::runtime_error( + "orderingCOLAMD: some variables in the graph are not constrained!"); + + // Create a constraint list with correct indices + typedef std::map::value_type constraint_type; + std::map index_constraints; + BOOST_FOREACH(const constraint_type& p, constraints) + index_constraints[ordering->at(p.first)] = p.second; + + // Compute a constrained fill-reducing ordering with COLAMD + Permutation::shared_ptr colamdPerm(inference::PermutationCOLAMDGrouped( + variableIndex, index_constraints)); + + // Permute the Ordering with the COLAMD ordering + ordering->permuteWithInverse(*colamdPerm->inverse()); + return ordering; +} + +/* ************************************************************************* */ +SymbolicFactorGraph::shared_ptr NonlinearFactorGraph::symbolic(const Ordering& ordering) const { + // Generate the symbolic factor graph + SymbolicFactorGraph::shared_ptr symbolicfg(new SymbolicFactorGraph); + symbolicfg->reserve(this->size()); + + BOOST_FOREACH(const sharedFactor& factor, this->factors_) { + if(factor) + symbolicfg->push_back(factor->symbolic(ordering)); + else + symbolicfg->push_back(SymbolicFactorGraph::sharedFactor()); } - /* ************************************************************************* */ - GaussianFactorGraph::shared_ptr NonlinearFactorGraph::linearize( - const Values& config, const Ordering& ordering) const { + return symbolicfg; +} - // create an empty linear FG - GaussianFactorGraph::shared_ptr linearFG(new GaussianFactorGraph); - linearFG->reserve(this->size()); +/* ************************************************************************* */ +pair NonlinearFactorGraph::symbolic( + const Values& config) const { + // Generate an initial key ordering in iterator order + Ordering::shared_ptr ordering(config.orderingArbitrary()); + return make_pair(symbolic(*ordering), ordering); +} - // linearize all factors - BOOST_FOREACH(const sharedFactor& factor, this->factors_) { - if(factor) { - GaussianFactor::shared_ptr lf = factor->linearize(config, ordering); - if (lf) linearFG->push_back(lf); - } else - linearFG->push_back(GaussianFactor::shared_ptr()); - } +/* ************************************************************************* */ +GaussianFactorGraph::shared_ptr NonlinearFactorGraph::linearize( + const Values& config, const Ordering& ordering) const { - return linearFG; + // create an empty linear FG + GaussianFactorGraph::shared_ptr linearFG(new GaussianFactorGraph); + linearFG->reserve(this->size()); + + // linearize all factors + BOOST_FOREACH(const sharedFactor& factor, this->factors_) { + if(factor) { + GaussianFactor::shared_ptr lf = factor->linearize(config, ordering); + if (lf) linearFG->push_back(lf); + } else + linearFG->push_back(GaussianFactor::shared_ptr()); } + return linearFG; +} + +/* ************************************************************************* */ +NonlinearFactorGraph NonlinearFactorGraph::clone() const { + NonlinearFactorGraph result; + BOOST_FOREACH(const sharedFactor& f, *this) { + if (f) + result.push_back(f->clone()); + else + result.push_back(sharedFactor()); // Passes on null factors so indices remain valid + } + return result; +} + +/* ************************************************************************* */ +NonlinearFactorGraph NonlinearFactorGraph::rekey(const std::map& rekey_mapping) const { + NonlinearFactorGraph result; + BOOST_FOREACH(const sharedFactor& f, *this) { + if (f) + result.push_back(f->rekey(rekey_mapping)); + else + result.push_back(sharedFactor()); + } + return result; +} + /* ************************************************************************* */ } // namespace gtsam diff --git a/gtsam/nonlinear/NonlinearFactorGraph.h b/gtsam/nonlinear/NonlinearFactorGraph.h index 3caeec680..f7ebb42bc 100644 --- a/gtsam/nonlinear/NonlinearFactorGraph.h +++ b/gtsam/nonlinear/NonlinearFactorGraph.h @@ -46,18 +46,23 @@ namespace gtsam { /** print just calls base class */ void print(const std::string& str = "NonlinearFactorGraph: ", const KeyFormatter& keyFormatter = DefaultKeyFormatter) const; - /** return keys in some random order */ - std::set keys() const; + /** return keys as an ordered set - ordering is by key value */ + FastSet keys() const; - /** unnormalized error */ + /** unnormalized error, \f$ 0.5 \sum_i (h_i(X_i)-z)^2/\sigma^2 \f$ in the most common case */ double error(const Values& c) const; /** Unnormalized probability. O(n) */ double probPrime(const Values& c) const; - template - void add(const F& factor) { - this->push_back(boost::shared_ptr(new F(factor))); + /// Add a factor by value - copies the factor object + void add(const NonlinearFactor& factor) { + this->push_back(factor.clone()); + } + + /// Add a factor by pointer - stores pointer without copying factor object + void add(const sharedFactor& factor) { + this->push_back(factor); } /** @@ -75,18 +80,43 @@ namespace gtsam { symbolic(const Values& config) const; /** - * Compute a fill-reducing ordering using COLAMD. This returns the - * ordering and a VariableIndex, which can later be re-used to save - * computation. + * Compute a fill-reducing ordering using COLAMD. */ Ordering::shared_ptr orderingCOLAMD(const Values& config) const; + /** + * Compute a fill-reducing ordering with constraints using CCOLAMD + * + * @param constraints is a map of Key->group, where 0 is unconstrained, and higher + * group numbers are further back in the ordering. Only keys with nonzero group + * indices need to appear in the constraints, unconstrained is assumed for all + * other variables + */ + Ordering::shared_ptr orderingCOLAMDConstrained(const Values& config, + const std::map& constraints) const; + /** * linearize a nonlinear factor graph */ boost::shared_ptr linearize(const Values& config, const Ordering& ordering) const; + /** + * Clone() performs a deep-copy of the graph, including all of the factors + */ + NonlinearFactorGraph clone() const; + + /** + * Rekey() performs a deep-copy of all of the factors, and changes + * keys according to a mapping. + * + * Keys not specified in the mapping will remain unchanged. + * + * @param rekey_mapping is a map of old->new keys + * @result a cloned graph with updated keys + */ + NonlinearFactorGraph rekey(const std::map& rekey_mapping) const; + private: /** Serialization function */ diff --git a/gtsam/nonlinear/NonlinearISAM-inl.h b/gtsam/nonlinear/NonlinearISAM.cpp similarity index 59% rename from gtsam/nonlinear/NonlinearISAM-inl.h rename to gtsam/nonlinear/NonlinearISAM.cpp index e054ecacb..b2135fedd 100644 --- a/gtsam/nonlinear/NonlinearISAM-inl.h +++ b/gtsam/nonlinear/NonlinearISAM.cpp @@ -15,22 +15,28 @@ * @author Viorela Ila and Richard Roberts */ -#pragma once - -#include - -#include +#include #include #include #include +#include + +#include + using namespace std; -using namespace gtsam; + +namespace gtsam { + /* ************************************************************************* */ -template -void NonlinearISAM::update(const Factors& newFactors, +void NonlinearISAM::saveGraph(const string& s, const KeyFormatter& keyFormatter) const { + isam_.saveGraph(s, OrderingIndexFormatter(ordering_, keyFormatter)); +} + +/* ************************************************************************* */ +void NonlinearISAM::update(const NonlinearFactorGraph& newFactors, const Values& initialValues) { if(newFactors.size() > 0) { @@ -48,13 +54,13 @@ void NonlinearISAM::update(const Factors& newFactors, linPoint_.insert(initialValues); // Augment ordering + // TODO: allow for ordering constraints within the new variables // FIXME: should just loop over new values - BOOST_FOREACH(const typename Factors::sharedFactor& factor, newFactors) + BOOST_FOREACH(const NonlinearFactorGraph::sharedFactor& factor, newFactors) BOOST_FOREACH(Key key, factor->keys()) ordering_.tryInsert(key, ordering_.nVars()); // will do nothing if already present - boost::shared_ptr linearizedNewFactors( - newFactors.linearize(linPoint_, ordering_)->template dynamicCastFactors()); + boost::shared_ptr linearizedNewFactors = newFactors.linearize(linPoint_, ordering_); // Update ISAM isam_.update(*linearizedNewFactors); @@ -62,8 +68,7 @@ void NonlinearISAM::update(const Factors& newFactors, } /* ************************************************************************* */ -template -void NonlinearISAM::reorder_relinearize() { +void NonlinearISAM::reorder_relinearize() { // cout << "Reordering, relinearizing..." << endl; @@ -74,11 +79,12 @@ void NonlinearISAM::reorder_relinearize() { isam_.clear(); // Compute an ordering + // TODO: allow for constrained ordering here ordering_ = *factors_.orderingCOLAMD(newLinPoint); // Create a linear factor graph at the new linearization point - boost::shared_ptr gfg( - factors_.linearize(newLinPoint, ordering_)->template dynamicCastFactors()); + // TODO: decouple relinearization and reordering to avoid + boost::shared_ptr gfg = factors_.linearize(newLinPoint, ordering_); // Just recreate the whole BayesTree isam_.update(*gfg); @@ -89,8 +95,7 @@ void NonlinearISAM::reorder_relinearize() { } /* ************************************************************************* */ -template -Values NonlinearISAM::estimate() const { +Values NonlinearISAM::estimate() const { if(isam_.size() > 0) return linPoint_.retract(optimize(isam_), ordering_); else @@ -98,18 +103,24 @@ Values NonlinearISAM::estimate() const { } /* ************************************************************************* */ -template -Matrix NonlinearISAM::marginalCovariance(Key key) const { +Matrix NonlinearISAM::marginalCovariance(Key key) const { return isam_.marginalCovariance(ordering_[key]); } /* ************************************************************************* */ -template -void NonlinearISAM::print(const std::string& s) const { - cout << "ISAM - " << s << ":" << endl; - cout << " ReorderInterval: " << reorderInterval_ << " Current Count: " << reorderCounter_ << endl; - isam_.print("GaussianISAM"); - linPoint_.print("Linearization Point"); - ordering_.print("System Ordering"); - factors_.print("Nonlinear Graph"); +void NonlinearISAM::print(const string& s, const KeyFormatter& keyFormatter) const { + cout << s << "ReorderInterval: " << reorderInterval_ << " Current Count: " << reorderCounter_ << endl; + isam_.print("GaussianISAM:\n"); + linPoint_.print("Linearization Point:\n", keyFormatter); + ordering_.print("System Ordering:\n", keyFormatter); + factors_.print("Nonlinear Graph:\n", keyFormatter); } + +/* ************************************************************************* */ +void NonlinearISAM::printStats() const { + isam_.getCliqueData().getStats().print(); +} + +/* ************************************************************************* */ + +}///\ namespace gtsam diff --git a/gtsam/nonlinear/NonlinearISAM.h b/gtsam/nonlinear/NonlinearISAM.h index 16547770b..fc2f69f55 100644 --- a/gtsam/nonlinear/NonlinearISAM.h +++ b/gtsam/nonlinear/NonlinearISAM.h @@ -24,12 +24,7 @@ namespace gtsam { /** * Wrapper class to manage ISAM in a nonlinear context */ -template class NonlinearISAM { -public: - - typedef GRAPH Factors; - protected: /** The internal iSAM object */ @@ -42,7 +37,7 @@ protected: gtsam::Ordering ordering_; /** The original factors, used when relinearizing */ - Factors factors_; + NonlinearFactorGraph factors_; /** The reordering interval and counter */ int reorderInterval_; @@ -84,21 +79,27 @@ public: const gtsam::Ordering& getOrdering() const { return ordering_; } /** get underlying nonlinear graph */ - const Factors& getFactorsUnsafe() const { return factors_; } + const NonlinearFactorGraph& getFactorsUnsafe() const { return factors_; } /** get counters */ int reorderInterval() const { return reorderInterval_; } /// diff --git a/gtsam/nonlinear/NonlinearOptimizer.cpp b/gtsam/nonlinear/NonlinearOptimizer.cpp index 76d1fe573..2312a9f88 100644 --- a/gtsam/nonlinear/NonlinearOptimizer.cpp +++ b/gtsam/nonlinear/NonlinearOptimizer.cpp @@ -19,11 +19,49 @@ #include #include #include - +#include using namespace std; namespace gtsam { +/* ************************************************************************* */ +NonlinearOptimizerParams::Verbosity NonlinearOptimizerParams::verbosityTranslator(const std::string &src) const { + std::string s = src; boost::algorithm::to_upper(s); + if (s == "SILENT") return NonlinearOptimizerParams::SILENT; + if (s == "ERROR") return NonlinearOptimizerParams::ERROR; + if (s == "VALUES") return NonlinearOptimizerParams::VALUES; + if (s == "DELTA") return NonlinearOptimizerParams::DELTA; + if (s == "LINEAR") return NonlinearOptimizerParams::LINEAR; + + /* default is silent */ + return NonlinearOptimizerParams::SILENT; +} + +/* ************************************************************************* */ +std::string NonlinearOptimizerParams::verbosityTranslator(Verbosity value) const { + std::string s; + switch (value) { + case NonlinearOptimizerParams::SILENT: s = "SILENT"; break; + case NonlinearOptimizerParams::ERROR: s = "ERROR"; break; + case NonlinearOptimizerParams::VALUES: s = "VALUES"; break; + case NonlinearOptimizerParams::DELTA: s = "DELTA"; break; + case NonlinearOptimizerParams::LINEAR: s = "LINEAR"; break; + default: s = "UNDEFINED"; break; + } + return s; +} + +/* ************************************************************************* */ +void NonlinearOptimizerParams::print(const std::string& str) const { + std::cout << str << "\n"; + std::cout << "relative decrease threshold: " << relativeErrorTol << "\n"; + std::cout << "absolute decrease threshold: " << absoluteErrorTol << "\n"; + std::cout << " total error threshold: " << errorTol << "\n"; + std::cout << " maximum iterations: " << maxIterations << "\n"; + std::cout << " verbosity: " << verbosityTranslator(verbosity) << "\n"; + std::cout.flush(); +} + /* ************************************************************************* */ void NonlinearOptimizer::defaultOptimize() { @@ -64,12 +102,24 @@ void NonlinearOptimizer::defaultOptimize() { cout << "Terminating because reached maximum iterations" << endl; } +/* ************************************************************************* */ +const Values& NonlinearOptimizer::optimizeSafely() { + static const Values empty; + try { + defaultOptimize(); + return values(); + } catch (...) { + // uncaught exception, returning empty result + return empty; + } +} + /* ************************************************************************* */ bool checkConvergence(double relativeErrorTreshold, double absoluteErrorTreshold, double errorThreshold, double currentError, double newError, NonlinearOptimizerParams::Verbosity verbosity) { - if ( verbosity >= 2 ) { + if ( verbosity >= NonlinearOptimizerParams::ERROR ) { if ( newError <= errorThreshold ) cout << "errorThreshold: " << newError << " < " << errorThreshold << endl; else @@ -80,7 +130,7 @@ bool checkConvergence(double relativeErrorTreshold, double absoluteErrorTreshold // check if diverges double absoluteDecrease = currentError - newError; - if (verbosity >= 2) { + if (verbosity >= NonlinearOptimizerParams::ERROR) { if (absoluteDecrease <= absoluteErrorTreshold) cout << "absoluteDecrease: " << setprecision(12) << absoluteDecrease << " < " << absoluteErrorTreshold << endl; else @@ -89,7 +139,7 @@ bool checkConvergence(double relativeErrorTreshold, double absoluteErrorTreshold // calculate relative error decrease and update currentError double relativeDecrease = absoluteDecrease / currentError; - if (verbosity >= 2) { + if (verbosity >= NonlinearOptimizerParams::ERROR) { if (relativeDecrease <= relativeErrorTreshold) cout << "relativeDecrease: " << setprecision(12) << relativeDecrease << " < " << relativeErrorTreshold << endl; else @@ -97,7 +147,7 @@ bool checkConvergence(double relativeErrorTreshold, double absoluteErrorTreshold } bool converged = (relativeErrorTreshold && (relativeDecrease <= relativeErrorTreshold)) || (absoluteDecrease <= absoluteErrorTreshold); - if (verbosity >= 1 && converged) { + if (verbosity >= NonlinearOptimizerParams::ERROR && converged) { if(absoluteDecrease >= 0.0) cout << "converged" << endl; else @@ -105,6 +155,7 @@ bool checkConvergence(double relativeErrorTreshold, double absoluteErrorTreshold } return converged; } +/* ************************************************************************* */ } diff --git a/gtsam/nonlinear/NonlinearOptimizer.h b/gtsam/nonlinear/NonlinearOptimizer.h index 388058ac0..488d3d832 100644 --- a/gtsam/nonlinear/NonlinearOptimizer.h +++ b/gtsam/nonlinear/NonlinearOptimizer.h @@ -45,21 +45,28 @@ public: Verbosity verbosity; ///< The printing verbosity during optimization (default SILENT) NonlinearOptimizerParams() : - maxIterations(100.0), relativeErrorTol(1e-5), absoluteErrorTol(1e-5), + maxIterations(100), relativeErrorTol(1e-5), absoluteErrorTol(1e-5), errorTol(0.0), verbosity(SILENT) {} - virtual void print(const std::string& str = "") const { - std::cout << str << "\n"; - std::cout << "relative decrease threshold: " << relativeErrorTol << "\n"; - std::cout << "absolute decrease threshold: " << absoluteErrorTol << "\n"; - std::cout << " total error threshold: " << errorTol << "\n"; - std::cout << " maximum iterations: " << maxIterations << "\n"; - std::cout << " verbosity level: " << verbosity << std::endl; - } - virtual ~NonlinearOptimizerParams() {} -}; + virtual void print(const std::string& str = "") const ; + size_t getMaxIterations() const { return maxIterations; } + double getRelativeErrorTol() const { return relativeErrorTol; } + double getAbsoluteErrorTol() const { return absoluteErrorTol; } + double getErrorTol() const { return errorTol; } + std::string getVerbosity() const { return verbosityTranslator(verbosity); } + + void setMaxIterations(size_t value) { maxIterations = value; } + void setRelativeErrorTol(double value) { relativeErrorTol = value; } + void setAbsoluteErrorTol(double value) { absoluteErrorTol = value; } + void setErrorTol(double value) { errorTol = value ; } + void setVerbosity(const std::string &src) { verbosity = verbosityTranslator(src); } + +private: + Verbosity verbosityTranslator(const std::string &s) const; + std::string verbosityTranslator(Verbosity value) const; +}; /** * Base class for a nonlinear optimization state, including the current estimate @@ -169,8 +176,10 @@ Values::const_shared_ptr result = DoglegOptimizer(graph, initialValues, params). */ class NonlinearOptimizer { -public: +protected: + NonlinearFactorGraph graph_; +public: /** A shared pointer to this class */ typedef boost::shared_ptr shared_ptr; @@ -188,10 +197,21 @@ public: */ virtual const Values& optimize() { defaultOptimize(); return values(); } + /** + * Optimize, but return empty result if any uncaught exception is thrown + * Intended for MATLAB. In C++, use above and catch exceptions. + * No message is printed: it is up to the caller to check the result + * @param optimizer a non-linear optimizer + */ + const Values& optimizeSafely(); + + /// return error double error() const { return _state().error; } + /// return number of iterations unsigned int iterations() const { return _state().iterations; } + /// return values const Values& values() const { return _state().values; } /// @} @@ -210,10 +230,7 @@ public: /// @} -protected: - - NonlinearFactorGraph graph_; - +protected: /** A default implementation of the optimization loop, which calls iterate() * until checkConvergence returns true. */ @@ -229,7 +246,7 @@ protected: }; /** Check whether the relative error decrease is less than relativeErrorTreshold, - * the absolute error decrease is less than absoluteErrorTreshold, or + * the absolute error decrease is less than absoluteErrorTreshold, or * the error itself is less than errorThreshold. */ bool checkConvergence(double relativeErrorTreshold, diff --git a/gtsam/nonlinear/Ordering.cpp b/gtsam/nonlinear/Ordering.cpp index 14be537d3..b445af506 100644 --- a/gtsam/nonlinear/Ordering.cpp +++ b/gtsam/nonlinear/Ordering.cpp @@ -41,13 +41,27 @@ void Ordering::permuteWithInverse(const Permutation& inversePermutation) { /* ************************************************************************* */ void Ordering::print(const string& str, const KeyFormatter& keyFormatter) const { - cout << str << " "; - BOOST_FOREACH(const Ordering::value_type& key_order, *this) { - if(key_order != *begin()) - cout << ", "; - cout << keyFormatter(key_order.first) << ":" << key_order.second; - } - cout << endl; + cout << str; + // Print ordering in index order + Ordering::InvertedMap inverted = this->invert(); + // Print the ordering with varsPerLine ordering entries printed on each line, + // for compactness. + static const size_t varsPerLine = 10; + bool endedOnNewline = false; + BOOST_FOREACH(const Ordering::InvertedMap::value_type& index_key, inverted) { + if(index_key.first % varsPerLine != 0) + cout << ", "; + cout << index_key.first << ":" << keyFormatter(index_key.second); + if(index_key.first % varsPerLine == varsPerLine - 1) { + cout << "\n"; + endedOnNewline = true; + } else { + endedOnNewline = false; + } + } + if(!endedOnNewline) + cout << "\n"; + cout.flush(); } /* ************************************************************************* */ diff --git a/gtsam/nonlinear/Ordering.h b/gtsam/nonlinear/Ordering.h index e2837a1ca..c6881fbde 100644 --- a/gtsam/nonlinear/Ordering.h +++ b/gtsam/nonlinear/Ordering.h @@ -17,14 +17,14 @@ #pragma once -#include -#include +#include #include -#include +#include #include #include #include +#include namespace gtsam { @@ -93,7 +93,8 @@ public: /// behavior of std::map) Index& operator[](Key key) { iterator i=order_.find(key); - if(i == order_.end()) throw std::out_of_range(std::string("Attempting to access a key from an ordering that does not contain that key")); + if(i == order_.end()) throw std::out_of_range( + std::string("Attempting to access a key from an ordering that does not contain that key:") + DefaultKeyFormatter(key)); else return i->second; } /// Access the index for the requested key, throws std::out_of_range if the @@ -101,7 +102,8 @@ public: /// behavior of std::map) Index operator[](Key key) const { const_iterator i=order_.find(key); - if(i == order_.end()) throw std::out_of_range(std::string("Attempting to access a key from an ordering that does not contain that key")); + if(i == order_.end()) throw std::out_of_range( + std::string("Attempting to access a key from an ordering that does not contain that key:") + DefaultKeyFormatter(key)); else return i->second; } /** Returns an iterator pointing to the symbol/index pair with the requested, @@ -153,7 +155,7 @@ public: iterator end() { return order_.end(); } /// Test if the key exists in the ordering. - bool exists(Key key) const { return order_.count(key); } + bool exists(Key key) const { return order_.count(key) > 0; } ///TODO: comment std::pair tryInsert(Key key, Index order) { return tryInsert(std::make_pair(key,order)); } @@ -215,7 +217,7 @@ public: /// @{ /** print (from Testable) for testing and debugging */ - void print(const std::string& str = "Ordering:", const KeyFormatter& keyFormatter = DefaultKeyFormatter) const; + void print(const std::string& str = "Ordering:\n", const KeyFormatter& keyFormatter = DefaultKeyFormatter) const; /** equals (from Testable) for testing and debugging */ bool equals(const Ordering& rhs, double tol = 0.0) const; @@ -231,7 +233,10 @@ private: ar & BOOST_SERIALIZATION_NVP(order_); ar & BOOST_SERIALIZATION_NVP(nVars_); } -}; +}; // \class Ordering + +// typedef for use with matlab +typedef Ordering::InvertedMap InvertedOrdering; /** * @class Unordered @@ -256,5 +261,17 @@ public: bool equals(const Unordered &t, double tol=0) const; }; -} +// Create an index formatter that looks up the Key in an inverse ordering, then +// formats the key using the provided key formatter, used in saveGraph. +struct OrderingIndexFormatter { + Ordering::InvertedMap inverseOrdering; + const KeyFormatter& keyFormatter; + OrderingIndexFormatter(const Ordering& ordering, const KeyFormatter& keyFormatter) : + inverseOrdering(ordering.invert()), keyFormatter(keyFormatter) {} + std::string operator()(Index index) { + return keyFormatter(inverseOrdering.at(index)); + } +}; + +} // \namespace gtsam diff --git a/gtsam/nonlinear/SuccessiveLinearizationOptimizer.cpp b/gtsam/nonlinear/SuccessiveLinearizationOptimizer.cpp new file mode 100644 index 000000000..fec460b08 --- /dev/null +++ b/gtsam/nonlinear/SuccessiveLinearizationOptimizer.cpp @@ -0,0 +1,80 @@ +/** + * @file SuccessiveLinearizationOptimizer.cpp + * @brief + * @date Jul 24, 2012 + * @author Yong-Dian Jian + */ + +#include +#include +#include +#include +#include +#include +#include + +namespace gtsam { + +void SuccessiveLinearizationParams::setIterativeParams(const SubgraphSolverParameters ¶ms) { + iterativeParams = boost::make_shared(params); +} + +void SuccessiveLinearizationParams::print(const std::string& str) const { + NonlinearOptimizerParams::print(str); + switch ( linearSolverType ) { + case MULTIFRONTAL_CHOLESKY: + std::cout << " linear solver type: MULTIFRONTAL CHOLESKY\n"; + break; + case MULTIFRONTAL_QR: + std::cout << " linear solver type: MULTIFRONTAL QR\n"; + break; + case SEQUENTIAL_CHOLESKY: + std::cout << " linear solver type: SEQUENTIAL CHOLESKY\n"; + break; + case SEQUENTIAL_QR: + std::cout << " linear solver type: SEQUENTIAL QR\n"; + break; + case CHOLMOD: + std::cout << " linear solver type: CHOLMOD\n"; + break; + case CONJUGATE_GRADIENT: + std::cout << " linear solver type: CONJUGATE GRADIENT\n"; + break; + default: + std::cout << " linear solver type: (invalid)\n"; + break; + } + + if(ordering) + std::cout << " ordering: custom\n"; + else + std::cout << " ordering: COLAMD\n"; + + std::cout.flush(); +} + +VectorValues solveGaussianFactorGraph(const GaussianFactorGraph &gfg, const SuccessiveLinearizationParams ¶ms) { + VectorValues delta; + if ( params.isMultifrontal() ) { + delta = GaussianJunctionTree(gfg).optimize(params.getEliminationFunction()); + } + else if ( params.isSequential() ) { + delta = gtsam::optimize(*EliminationTree::Create(gfg)->eliminate(params.getEliminationFunction())); + } + else if ( params.isCG() ) { + if ( !params.iterativeParams ) throw std::runtime_error("solveGaussianFactorGraph: cg parameter has to be assigned ..."); + if ( boost::dynamic_pointer_cast(params.iterativeParams) ) { + SubgraphSolver solver (gfg, *boost::dynamic_pointer_cast(params.iterativeParams)); + delta = solver.optimize(); + } + else { + throw std::runtime_error("solveGaussianFactorGraph: special cg parameter type is not handled in LM solver ..."); + } + } + else { + throw std::runtime_error("solveGaussianFactorGraph: Optimization parameter is invalid"); + } + return delta; +} + +} diff --git a/gtsam/nonlinear/SuccessiveLinearizationOptimizer.h b/gtsam/nonlinear/SuccessiveLinearizationOptimizer.h index f17e01d49..d422c09a9 100644 --- a/gtsam/nonlinear/SuccessiveLinearizationOptimizer.h +++ b/gtsam/nonlinear/SuccessiveLinearizationOptimizer.h @@ -19,64 +19,88 @@ #pragma once #include +#include namespace gtsam { class SuccessiveLinearizationParams : public NonlinearOptimizerParams { public: - /** See SuccessiveLinearizationParams::elimination */ - enum Elimination { - MULTIFRONTAL, - SEQUENTIAL + /** See SuccessiveLinearizationParams::linearSolverType */ + enum LinearSolverType { + MULTIFRONTAL_CHOLESKY, + MULTIFRONTAL_QR, + SEQUENTIAL_CHOLESKY, + SEQUENTIAL_QR, + CONJUGATE_GRADIENT, /* Experimental Flag */ + CHOLMOD, /* Experimental Flag */ }; - /** See SuccessiveLinearizationParams::factorization */ - enum Factorization { - CHOLESKY, - QR, - }; - - Elimination elimination; ///< The elimination algorithm to use (default: MULTIFRONTAL) - Factorization factorization; ///< The numerical factorization (default: Cholesky) + LinearSolverType linearSolverType; ///< The type of linear solver to use in the nonlinear optimizer boost::optional ordering; ///< The variable elimination ordering, or empty to use COLAMD (default: empty) + IterativeOptimizationParameters::shared_ptr iterativeParams; ///< The container for iterativeOptimization parameters. used in CG Solvers. - SuccessiveLinearizationParams() : - elimination(MULTIFRONTAL), factorization(CHOLESKY) {} - + SuccessiveLinearizationParams() : linearSolverType(MULTIFRONTAL_CHOLESKY) {} virtual ~SuccessiveLinearizationParams() {} - virtual void print(const std::string& str = "") const { - NonlinearOptimizerParams::print(str); - if(elimination == MULTIFRONTAL) - std::cout << " elimination method: MULTIFRONTAL\n"; - else if(elimination == SEQUENTIAL) - std::cout << " elimination method: SEQUENTIAL\n"; - else - std::cout << " elimination method: (invalid)\n"; + inline bool isMultifrontal() const { + return (linearSolverType == MULTIFRONTAL_CHOLESKY) || (linearSolverType == MULTIFRONTAL_QR); } - if(factorization == CHOLESKY) - std::cout << " factorization method: CHOLESKY\n"; - else if(factorization == QR) - std::cout << " factorization method: QR\n"; - else - std::cout << " factorization method: (invalid)\n"; + inline bool isSequential() const { + return (linearSolverType == SEQUENTIAL_CHOLESKY) || (linearSolverType == SEQUENTIAL_QR); } - if(ordering) - std::cout << " ordering: custom\n"; - else - std::cout << " ordering: COLAMD\n"; + inline bool isCholmod() const { return (linearSolverType == CHOLMOD); } - std::cout.flush(); - } + inline bool isCG() const { return (linearSolverType == CONJUGATE_GRADIENT); } + + virtual void print(const std::string& str) const; GaussianFactorGraph::Eliminate getEliminationFunction() const { - if(factorization == SuccessiveLinearizationParams::CHOLESKY) + switch (linearSolverType) { + case MULTIFRONTAL_CHOLESKY: + case SEQUENTIAL_CHOLESKY: return EliminatePreferCholesky; - else if(factorization == SuccessiveLinearizationParams::QR) + + case MULTIFRONTAL_QR: + case SEQUENTIAL_QR: return EliminateQR; - else - throw runtime_error("Nonlinear optimization parameter \"factorization\" is invalid"); + + default: + throw std::runtime_error("Nonlinear optimization parameter \"factorization\" is invalid"); + return EliminateQR; + break; + } } + + std::string getLinearSolverType() const { return linearSolverTranslator(linearSolverType); } + + void setLinearSolverType(const std::string& solver) { linearSolverType = linearSolverTranslator(solver); } + void setIterativeParams(const SubgraphSolverParameters ¶ms); + void setOrdering(const Ordering& ordering) { this->ordering = ordering; } + +private: + std::string linearSolverTranslator(LinearSolverType linearSolverType) const { + switch(linearSolverType) { + case MULTIFRONTAL_CHOLESKY: return "MULTIFRONTAL_CHOLESKY"; + case MULTIFRONTAL_QR: return "MULTIFRONTAL_QR"; + case SEQUENTIAL_CHOLESKY: return "SEQUENTIAL_CHOLESKY"; + case SEQUENTIAL_QR: return "SEQUENTIAL_QR"; + case CONJUGATE_GRADIENT: return "CONJUGATE_GRADIENT"; + case CHOLMOD: return "CHOLMOD"; + default: throw std::invalid_argument("Unknown linear solver type in SuccessiveLinearizationOptimizer"); + } + } + LinearSolverType linearSolverTranslator(const std::string& linearSolverType) const { + if(linearSolverType == "MULTIFRONTAL_CHOLESKY") return MULTIFRONTAL_CHOLESKY; + if(linearSolverType == "MULTIFRONTAL_QR") return MULTIFRONTAL_QR; + if(linearSolverType == "SEQUENTIAL_CHOLESKY") return SEQUENTIAL_CHOLESKY; + if(linearSolverType == "SEQUENTIAL_QR") return SEQUENTIAL_QR; + if(linearSolverType == "CONJUGATE_GRADIENT") return CONJUGATE_GRADIENT; + if(linearSolverType == "CHOLMOD") return CHOLMOD; + throw std::invalid_argument("Unknown linear solver type in SuccessiveLinearizationOptimizer"); + } }; +/* a wrapper for solving a GaussianFactorGraph according to the parameters */ +VectorValues solveGaussianFactorGraph(const GaussianFactorGraph &gfg, const SuccessiveLinearizationParams ¶ms) ; + } /* namespace gtsam */ diff --git a/gtsam/nonlinear/Symbol.cpp b/gtsam/nonlinear/Symbol.cpp new file mode 100644 index 000000000..19cf78eb5 --- /dev/null +++ b/gtsam/nonlinear/Symbol.cpp @@ -0,0 +1,74 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file Symbol.cpp + * @date June 9, 2012 + * @author: Frank Dellaert + * @author: Richard Roberts + */ + +#include + +#include +#include +#include +#include +#include +#include + +#include +#include +#include + +namespace gtsam { + +static const size_t keyBits = sizeof(Key) * 8; +static const size_t chrBits = sizeof(unsigned char) * 8; +static const size_t indexBits = keyBits - chrBits; +static const Key chrMask = Key(UCHAR_MAX) << indexBits; // For some reason, std::numeric_limits::max() fails +static const Key indexMask = ~chrMask; + +Symbol::Symbol(Key key) { + c_ = (unsigned char) ((key & chrMask) >> indexBits); + j_ = key & indexMask; +} + +Key Symbol::key() const { + if (j_ > indexMask) { + boost::format msg("Symbol index is too large, j=%d, indexMask=%d"); + msg % j_ % indexMask; + throw std::invalid_argument(msg.str()); + } + Key key = (Key(c_) << indexBits) | j_; + return key; +} + +void Symbol::print(const std::string& s) const { + std::cout << s << (std::string) (*this) << std::endl; +} + +bool Symbol::equals(const Symbol& expected, double tol) const { + return (*this) == expected; +} + +Symbol::operator std::string() const { + return str(boost::format("%c%d") % c_ % j_); +} + +boost::function Symbol::ChrTest(unsigned char c) { + namespace bl = boost::lambda; + return bl::bind(&Symbol::chr, bl::bind(bl::constructor(), bl::_1)) + == c; +} + +} // namespace gtsam + diff --git a/gtsam/nonlinear/Symbol.h b/gtsam/nonlinear/Symbol.h index f671a4b30..c128b1105 100644 --- a/gtsam/nonlinear/Symbol.h +++ b/gtsam/nonlinear/Symbol.h @@ -18,17 +18,8 @@ #pragma once -#include -#include -#include -#include -#include -#include -#include -#include -#include - #include +#include namespace gtsam { @@ -44,6 +35,7 @@ protected: size_t j_; public: + /** Default constructor */ Symbol() : c_(0), j_(0) { @@ -60,36 +52,19 @@ public: } /** Constructor that decodes an integer Key */ - Symbol(Key key) { - const size_t keyBits = sizeof(Key) * 8; - const size_t chrBits = sizeof(unsigned char) * 8; - const size_t indexBits = keyBits - chrBits; - const Key chrMask = Key(std::numeric_limits::max()) << indexBits; - const Key indexMask = ~chrMask; - c_ = (unsigned char)((key & chrMask) >> indexBits); - j_ = key & indexMask; - } + Symbol(Key key); + + /** return Key (integer) representation */ + Key key() const; /** Cast to integer */ - operator Key() const { - const size_t keyBits = sizeof(Key) * 8; - const size_t chrBits = sizeof(unsigned char) * 8; - const size_t indexBits = keyBits - chrBits; - const Key chrMask = Key(std::numeric_limits::max()) << indexBits; - const Key indexMask = ~chrMask; - if(j_ > indexMask) - throw std::invalid_argument("Symbol index is too large"); - Key key = (Key(c_) << indexBits) | j_; - return key; - } + operator Key() const { return key(); } - // Testable Requirements - void print(const std::string& s = "") const { - std::cout << s << ": " << (std::string) (*this) << std::endl; - } - bool equals(const Symbol& expected, double tol = 0.0) const { - return (*this) == expected; - } + /// Print + void print(const std::string& s = "") const; + + /// Check equality + bool equals(const Symbol& expected, double tol = 0.0) const; /** Retrieve key character */ unsigned char chr() const { @@ -102,23 +77,29 @@ public: } /** Create a string from the key */ - operator std::string() const { - return str(boost::format("%c%d") % c_ % j_); - } + operator std::string() const; /** Comparison for use in maps */ bool operator<(const Symbol& comp) const { return c_ < comp.c_ || (comp.c_ == c_ && j_ < comp.j_); } + + /** Comparison for use in maps */ bool operator==(const Symbol& comp) const { return comp.c_ == c_ && comp.j_ == j_; } + + /** Comparison for use in maps */ bool operator==(Key comp) const { return comp == (Key)(*this); } + + /** Comparison for use in maps */ bool operator!=(const Symbol& comp) const { return comp.c_ != c_ || comp.j_ != j_; } + + /** Comparison for use in maps */ bool operator!=(Key comp) const { return comp != (Key)(*this); } @@ -128,10 +109,7 @@ public: * Values::filter() function to retrieve all key-value pairs with the * requested character. */ - static boost::function ChrTest(unsigned char c) { - namespace bl = boost::lambda; - return bl::bind(&Symbol::chr, bl::bind(bl::constructor(), bl::_1)) == c; - } + static boost::function ChrTest(unsigned char c); private: @@ -144,6 +122,15 @@ private: } }; +/** Create a symbol key from a character and index, i.e. x5. */ +inline Key symbol(unsigned char c, size_t j) { return (Key)Symbol(c,j); } + +/** Return the character portion of a symbol key. */ +inline unsigned char symbolChr(Key key) { return Symbol(key).chr(); } + +/** Return the index portion of a symbol key. */ +inline size_t symbolIndex(Key key) { return Symbol(key).index(); } + namespace symbol_shorthand { inline Key A(size_t j) { return Symbol('a', j); } inline Key B(size_t j) { return Symbol('b', j); } diff --git a/gtsam/nonlinear/Values-inl.h b/gtsam/nonlinear/Values-inl.h index 40e95188e..3aec3e7b2 100644 --- a/gtsam/nonlinear/Values-inl.h +++ b/gtsam/nonlinear/Values-inl.h @@ -40,6 +40,187 @@ namespace gtsam { ValueCloneAllocator() {} }; + /* ************************************************************************* */ + template + struct _ValuesKeyValuePair { + const Key key; ///< The key + ValueType& value; ///< The value + + _ValuesKeyValuePair(Key _key, ValueType& _value) : key(_key), value(_value) {} + }; + + /* ************************************************************************* */ + template + struct _ValuesConstKeyValuePair { + const Key key; ///< The key + const ValueType& value; ///< The value + + _ValuesConstKeyValuePair(Key _key, const ValueType& _value) : key(_key), value(_value) {} + _ValuesConstKeyValuePair(const _ValuesKeyValuePair& rhs) : key(rhs.key), value(rhs.value) {} + }; + + /* ************************************************************************* */ + template + class Values::Filtered { + public: + /** A key-value pair, with the value a specific derived Value type. */ + typedef _ValuesKeyValuePair KeyValuePair; + typedef _ValuesConstKeyValuePair ConstKeyValuePair; + typedef KeyValuePair value_type; + + typedef + boost::transform_iterator< + KeyValuePair(*)(Values::KeyValuePair), + boost::filter_iterator< + boost::function, + Values::iterator> > + iterator; + + typedef iterator const_iterator; + + typedef + boost::transform_iterator< + ConstKeyValuePair(*)(Values::ConstKeyValuePair), + boost::filter_iterator< + boost::function, + Values::const_iterator> > + const_const_iterator; + + iterator begin() { return begin_; } + iterator end() { return end_; } + const_iterator begin() const { return begin_; } + const_iterator end() const { return end_; } + const_const_iterator beginConst() const { return constBegin_; } + const_const_iterator endConst() const { return constEnd_; } + + /** Returns the number of values in this view */ + size_t size() const { + size_t i = 0; + for (const_const_iterator it = beginConst(); it != endConst(); ++it) + ++i; + return i; + } + + private: + Filtered(const boost::function& filter, Values& values) : + begin_(boost::make_transform_iterator( + boost::make_filter_iterator( + filter, values.begin(), values.end()), + &castHelper)), + end_(boost::make_transform_iterator( + boost::make_filter_iterator( + filter, values.end(), values.end()), + &castHelper)), + constBegin_(boost::make_transform_iterator( + boost::make_filter_iterator( + filter, ((const Values&)values).begin(), ((const Values&)values).end()), + &castHelper)), + constEnd_(boost::make_transform_iterator( + boost::make_filter_iterator( + filter, ((const Values&)values).end(), ((const Values&)values).end()), + &castHelper)) {} + + friend class Values; + iterator begin_; + iterator end_; + const_const_iterator constBegin_; + const_const_iterator constEnd_; + }; + + /* ************************************************************************* */ + template + class Values::ConstFiltered { + public: + /** A const key-value pair, with the value a specific derived Value type. */ + typedef _ValuesConstKeyValuePair KeyValuePair; + typedef KeyValuePair value_type; + + typedef typename Filtered::const_const_iterator iterator; + typedef typename Filtered::const_const_iterator const_iterator; + + /** Conversion from Filtered to ConstFiltered */ + ConstFiltered(const Filtered& rhs) : + begin_(rhs.beginConst()), + end_(rhs.endConst()) {} + + iterator begin() { return begin_; } + iterator end() { return end_; } + const_iterator begin() const { return begin_; } + const_iterator end() const { return end_; } + + /** Returns the number of values in this view */ + size_t size() const { + size_t i = 0; + for (const_iterator it = begin(); it != end(); ++it) + ++i; + return i; + } + + FastList keys() const { + FastList result; + for(const_iterator it = begin(); it != end(); ++it) + result.push_back(it->key); + return result; + } + + private: + friend class Values; + const_iterator begin_; + const_iterator end_; + ConstFiltered(const boost::function& filter, const Values& values) { + // We remove the const from values to create a non-const Filtered + // view, then pull the const_iterators out of it. + const Filtered filtered(filter, const_cast(values)); + begin_ = filtered.beginConst(); + end_ = filtered.endConst(); + } + }; + + /* ************************************************************************* */ + /** Constructor from a Filtered view copies out all values */ + template + Values::Values(const Values::Filtered& view) { + BOOST_FOREACH(const typename Filtered::KeyValuePair& key_value, view) { + Key key = key_value.key; + insert(key, key_value.value); + } + } + + /* ************************************************************************* */ + template + Values::Values(const Values::ConstFiltered& view) { + BOOST_FOREACH(const typename ConstFiltered::KeyValuePair& key_value, view) { + Key key = key_value.key; + insert(key, key_value.value); + } + } + + /* ************************************************************************* */ + Values::Filtered + inline Values::filter(const boost::function& filterFcn) { + return filter(filterFcn); + } + + /* ************************************************************************* */ + template + Values::Filtered + Values::filter(const boost::function& filterFcn) { + return Filtered(boost::bind(&filterHelper, filterFcn, _1), *this); + } + + /* ************************************************************************* */ + Values::ConstFiltered + inline Values::filter(const boost::function& filterFcn) const { + return filter(filterFcn); + } + + /* ************************************************************************* */ + template + Values::ConstFiltered + Values::filter(const boost::function& filterFcn) const { + return ConstFiltered(boost::bind(&filterHelper, filterFcn, _1), *this); + } + /* ************************************************************************* */ template const ValueType& Values::at(Key j) const { diff --git a/gtsam/nonlinear/Values.cpp b/gtsam/nonlinear/Values.cpp index c3d3bd8df..eab37ff17 100644 --- a/gtsam/nonlinear/Values.cpp +++ b/gtsam/nonlinear/Values.cpp @@ -41,9 +41,9 @@ namespace gtsam { /* ************************************************************************* */ void Values::print(const string& str, const KeyFormatter& keyFormatter) const { - cout << str << "Values with " << size() << " values:\n" << endl; + cout << str << "Values with " << size() << " values:" << endl; for(const_iterator key_value = begin(); key_value != end(); ++key_value) { - cout << " " << keyFormatter(key_value->key) << ": "; + cout << "Value " << keyFormatter(key_value->key) << ": "; key_value->value.print(""); } } @@ -90,7 +90,15 @@ namespace gtsam { /* ************************************************************************* */ VectorValues Values::localCoordinates(const Values& cp, const Ordering& ordering) const { VectorValues result(this->dims(ordering)); - localCoordinates(cp, ordering, result); + if(this->size() != cp.size()) + throw DynamicValuesMismatched(); + for(const_iterator it1=this->begin(), it2=cp.begin(); it1!=this->end(); ++it1, ++it2) { + if(it1->key != it2->key) + throw DynamicValuesMismatched(); // If keys do not match + // Will throw a dynamic_cast exception if types do not match + // NOTE: this is separate from localCoordinates(cp, ordering, result) due to at() vs. insert + result.at(ordering[it1->key]) = it1->value.localCoordinates_(it2->value); + } return result; } @@ -120,7 +128,7 @@ namespace gtsam { /* ************************************************************************* */ void Values::insert(Key j, const Value& val) { Key key = j; // Non-const duplicate to deal with non-const insert argument - std::pair insertResult = values_.insert(key, val.clone_()); + std::pair insertResult = values_.insert(key, val.clone_()); if(!insertResult.second) throw ValuesKeyAlreadyExists(j); } @@ -165,10 +173,8 @@ namespace gtsam { /* ************************************************************************* */ FastList Values::keys() const { FastList result; - for(const_iterator key_value = begin(); key_value != end(); ++key_value) { + for(const_iterator key_value = begin(); key_value != end(); ++key_value) result.push_back(key_value->key); - cout << result.back() << endl; - } return result; } diff --git a/gtsam/nonlinear/Values.h b/gtsam/nonlinear/Values.h index 4af8e5a3e..25bd3dc2e 100644 --- a/gtsam/nonlinear/Values.h +++ b/gtsam/nonlinear/Values.h @@ -24,8 +24,11 @@ #pragma once -#include -#include +#include +#include +#include +#include +#include #include #include @@ -35,20 +38,18 @@ #include #include #include -#include -#include -#include -#include -#include +#include +#include namespace gtsam { - // Forward declarations + // Forward declarations / utilities class ValueCloneAllocator; class ValueAutomaticCasting; + template static bool _truePredicate(const T&) { return true; } -/** + /** * A non-templated config holding any types of Manifold-group elements. A * values structure is a map from keys to values. It is used to specify the * value of a bunch of variables in a factor graph. A Values is a values @@ -122,133 +123,13 @@ namespace gtsam { typedef KeyValuePair value_type; - private: - template - struct _KeyValuePair { - const Key key; ///< The key - ValueType& value; ///< The value - - _KeyValuePair(Key _key, ValueType& _value) : key(_key), value(_value) {} - }; - - template - struct _ConstKeyValuePair { - const Key key; ///< The key - const ValueType& value; ///< The value - - _ConstKeyValuePair(Key _key, const ValueType& _value) : key(_key), value(_value) {} - _ConstKeyValuePair(const _KeyValuePair& rhs) : key(rhs.key), value(rhs.value) {} - }; - - public: - + /** A filtered view of a Values, returned from Values::filter. */ template - class Filtered { - public: - /** A key-value pair, with the value a specific derived Value type. */ - typedef _KeyValuePair KeyValuePair; - typedef _ConstKeyValuePair ConstKeyValuePair; - typedef KeyValuePair value_type; - - typedef - boost::transform_iterator< - KeyValuePair(*)(Values::KeyValuePair), - boost::filter_iterator< - boost::function, - Values::iterator> > - iterator; - - typedef iterator const_iterator; - - typedef - boost::transform_iterator< - ConstKeyValuePair(*)(Values::ConstKeyValuePair), - boost::filter_iterator< - boost::function, - Values::const_iterator> > - const_const_iterator; - - iterator begin() { return begin_; } - iterator end() { return end_; } - const_iterator begin() const { return begin_; } - const_iterator end() const { return end_; } - const_const_iterator beginConst() const { return constBegin_; } - const_const_iterator endConst() const { return constEnd_; } - - /** Returns the number of values in this view */ - size_t size() const { - size_t i = 0; - for (const_const_iterator it = beginConst(); it != endConst(); ++it) - ++i; - return i; - } - - private: - Filtered(const boost::function& filter, Values& values) : - begin_(boost::make_transform_iterator( - boost::make_filter_iterator( - filter, values.begin(), values.end()), - &castHelper)), - end_(boost::make_transform_iterator( - boost::make_filter_iterator( - filter, values.end(), values.end()), - &castHelper)), - constBegin_(boost::make_transform_iterator( - boost::make_filter_iterator( - filter, ((const Values&)values).begin(), ((const Values&)values).end()), - &castHelper)), - constEnd_(boost::make_transform_iterator( - boost::make_filter_iterator( - filter, ((const Values&)values).end(), ((const Values&)values).end()), - &castHelper)) {} - - friend class Values; - iterator begin_; - iterator end_; - const_const_iterator constBegin_; - const_const_iterator constEnd_; - }; + class Filtered; + /** A filtered view of a const Values, returned from Values::filter. */ template - class ConstFiltered { - public: - /** A const key-value pair, with the value a specific derived Value type. */ - typedef _ConstKeyValuePair KeyValuePair; - typedef KeyValuePair value_type; - - typedef typename Filtered::const_const_iterator iterator; - typedef typename Filtered::const_const_iterator const_iterator; - - /** Conversion from Filtered to ConstFiltered */ - ConstFiltered(const Filtered& rhs) : - begin_(rhs.beginConst()), - end_(rhs.endConst()) {} - - iterator begin() { return begin_; } - iterator end() { return end_; } - const_iterator begin() const { return begin_; } - const_iterator end() const { return end_; } - - /** Returns the number of values in this view */ - size_t size() const { - size_t i = 0; - for (const_iterator it = begin(); it != end(); ++it) - ++i; - return i; - } - - private: - friend class Values; - const_iterator begin_; - const_iterator end_; - ConstFiltered(const boost::function& filter, const Values& values) { - // We remove the const from values to create a non-const Filtered - // view, then pull the const_iterators out of it. - const Filtered filtered(filter, const_cast(values)); - begin_ = filtered.beginConst(); - end_ = filtered.endConst(); - } - }; + class ConstFiltered; /** Default constructor creates an empty Values class */ Values() {} @@ -258,21 +139,11 @@ namespace gtsam { /** Constructor from a Filtered view copies out all values */ template - Values(const Filtered& view) { - BOOST_FOREACH(const typename Filtered::KeyValuePair& key_value, view) { - Key key = key_value.key; - insert(key, key_value.value); - } - } + Values(const Filtered& view); - /** Constructor from Const Filtered view */ + /** Constructor from a Filtered or ConstFiltered view */ template - Values(const ConstFiltered& view) { - BOOST_FOREACH(const typename ConstFiltered::KeyValuePair& key_value, view) { - Key key = key_value.key; - insert(key, key_value.value); - } - } + Values(const ConstFiltered& view); /// @name Testable /// @{ @@ -323,13 +194,6 @@ namespace gtsam { /** Get a zero VectorValues of the correct structure */ VectorValues zeroVectors(const Ordering& ordering) const; - private: - static ConstKeyValuePair make_const_deref_pair(const KeyValueMap::const_iterator::value_type& key_value) { - return ConstKeyValuePair(key_value.first, *key_value.second); } - static KeyValuePair make_deref_pair(const KeyValueMap::iterator::value_type& key_value) { - return KeyValuePair(key_value.first, *key_value.second); } - - public: const_iterator begin() const { return boost::make_transform_iterator(values_.begin(), &make_const_deref_pair); } const_iterator end() const { return boost::make_transform_iterator(values_.end(), &make_const_deref_pair); } iterator begin() { return boost::make_transform_iterator(values_.begin(), &make_deref_pair); } @@ -348,7 +212,7 @@ namespace gtsam { /** Get a delta config about a linearization point c0 (*this) */ VectorValues localCoordinates(const Values& cp, const Ordering& ordering) const; - /** Get a delta config about a linearization point c0 (*this) */ + /** Get a delta config about a linearization point c0 (*this) - assumes uninitialized delta */ void localCoordinates(const Values& cp, const Ordering& ordering, VectorValues& delta) const; ///@} @@ -372,7 +236,7 @@ namespace gtsam { * Returns a set of keys in the config * Note: by construction, the list is ordered */ - FastList keys() const; + KeyList keys() const; /** Replace all keys and variables */ Values& operator=(const Values& rhs); @@ -402,7 +266,7 @@ namespace gtsam { * When iterating over the filtered view, only the key-value pairs * with a key causing \c filterFcn to return \c true are visited. Because * the object Filtered returned from filter() is only a - * view the original Values object must not be deallocated or + * view the original Values object must not be deallocated or * go out of scope as long as the view is needed. * @param filterFcn The function that determines which key-value pairs are * included in the filtered view, for which this function returns \c true @@ -411,9 +275,7 @@ namespace gtsam { * the original Values class. */ Filtered - filter(const boost::function& filterFcn) { - return filter(filterFcn); - } + filter(const boost::function& filterFcn); /** * Return a filtered view of this Values class, without copying any data. @@ -421,7 +283,7 @@ namespace gtsam { * template argument \c ValueType and whose key causes the function argument * \c filterFcn to return true are visited when iterating over the filtered * view. Because the object Filtered returned from filter() is only - * a view the original Values object must not be deallocated or + * a view the original Values object must not be deallocated or * go out of scope as long as the view is needed. * @tparam ValueType The type that the value in a key-value pair must match * to be included in the filtered view. Currently, base classes are not @@ -436,16 +298,14 @@ namespace gtsam { */ template Filtered - filter(const boost::function& filterFcn = (boost::lambda::_1, true)) { - return Filtered(boost::bind(&filterHelper, filterFcn, _1), *this); - } + filter(const boost::function& filterFcn = &_truePredicate); /** * Return a filtered view of this Values class, without copying any data. * When iterating over the filtered view, only the key-value pairs * with a key causing \c filterFcn to return \c true are visited. Because * the object Filtered returned from filter() is only a - * view the original Values object must not be deallocated or + * view the original Values object must not be deallocated or * go out of scope as long as the view is needed. * @param filterFcn The function that determines which key-value pairs are * included in the filtered view, for which this function returns \c true @@ -454,9 +314,7 @@ namespace gtsam { * the original Values class. */ ConstFiltered - filter(const boost::function& filterFcn) const { - return filter(filterFcn); - } + filter(const boost::function& filterFcn) const; /** * Return a filtered view of this Values class, without copying any data. @@ -464,7 +322,7 @@ namespace gtsam { * template argument \c ValueType and whose key causes the function argument * \c filterFcn to return true are visited when iterating over the filtered * view. Because the object Filtered returned from filter() is only - * a view the original Values object must not be deallocated or + * a view the original Values object must not be deallocated or * go out of scope as long as the view is needed. * @tparam ValueType The type that the value in a key-value pair must match * to be included in the filtered view. Currently, base classes are not @@ -478,9 +336,7 @@ namespace gtsam { */ template ConstFiltered - filter(const boost::function& filterFcn = (boost::lambda::_1, true)) const { - return ConstFiltered(boost::bind(&filterHelper, filterFcn, _1), *this); - } + filter(const boost::function& filterFcn = &_truePredicate) const; private: // Filters based on ValueType (if not Value) and also based on the user- @@ -505,6 +361,12 @@ namespace gtsam { ar & BOOST_SERIALIZATION_NVP(values_); } + static ConstKeyValuePair make_const_deref_pair(const KeyValueMap::const_iterator::value_type& key_value) { + return ConstKeyValuePair(key_value.first, *key_value.second); } + + static KeyValuePair make_deref_pair(const KeyValueMap::iterator::value_type& key_value) { + return KeyValuePair(key_value.first, *key_value.second); } + }; /* ************************************************************************* */ @@ -516,13 +378,13 @@ namespace gtsam { mutable std::string message_; public: - /// Construct with the key-value pair attemped to be added + /// Construct with the key-value pair attempted to be added ValuesKeyAlreadyExists(Key key) throw() : key_(key) {} virtual ~ValuesKeyAlreadyExists() throw() {} - /// The duplicate key that was attemped to be added + /// The duplicate key that was attempted to be added Key key() const throw() { return key_; } /// The message to be displayed to the user diff --git a/gtsam/nonlinear/WhiteNoiseFactor.h b/gtsam/nonlinear/WhiteNoiseFactor.h index f5fb7fae1..163633115 100644 --- a/gtsam/nonlinear/WhiteNoiseFactor.h +++ b/gtsam/nonlinear/WhiteNoiseFactor.h @@ -51,7 +51,7 @@ namespace gtsam { public: - /** @brief negative log likelihood as a function of mean \mu and precision \tau + /** @brief negative log likelihood as a function of mean \f$ \mu \f$ and precision \f$ \tau \f$ * @f[ * f(z, \tau, \mu) * = -\log \left( \frac{\sqrt{\tau}}{\sqrt{2\pi}} \exp(-0.5\tau(z-\mu)^2) \right) @@ -163,6 +163,11 @@ namespace gtsam { return linearize(z_, u, p, j1, j2); } + /// @return a deep copy of this factor + virtual gtsam::NonlinearFactor::shared_ptr clone() const { + return boost::static_pointer_cast( + gtsam::NonlinearFactor::shared_ptr(new This(*this))); } + /// @} }; diff --git a/gtsam/nonlinear/tests/testKey.cpp b/gtsam/nonlinear/tests/testKey.cpp index 54a2e504a..ee9734af5 100644 --- a/gtsam/nonlinear/tests/testKey.cpp +++ b/gtsam/nonlinear/tests/testKey.cpp @@ -21,17 +21,19 @@ using namespace boost::assign; #include #include #include - + using namespace std; using namespace gtsam; +Key aKey = gtsam::symbol_shorthand::X(4); + /* ************************************************************************* */ TEST(Key, KeySymbolConversion) { - Symbol expected('j', 4); - Key key(expected); + Symbol original('j', 4); + Key key(original); + EXPECT(assert_equal(key, original.key())) Symbol actual(key); - - EXPECT(assert_equal(expected, actual)) + EXPECT(assert_equal(original, actual)) } /* ************************************************************************* */ diff --git a/gtsam/nonlinear/tests/testOrdering.cpp b/gtsam/nonlinear/tests/testOrdering.cpp index f57e3281a..d89c04d3c 100644 --- a/gtsam/nonlinear/tests/testOrdering.cpp +++ b/gtsam/nonlinear/tests/testOrdering.cpp @@ -14,9 +14,10 @@ * @author Alex Cunningham */ -#include -#include #include +#include +#include +#include using namespace std; using namespace gtsam; @@ -43,8 +44,11 @@ TEST( testOrdering, simple_modifications ) { CHECK_EXCEPTION(ordering.pop_back(x1), std::invalid_argument); // reassemble back make the ordering 1, 2, 4, 3 - ordering.push_back(x4); - ordering.push_back(x3); + EXPECT_LONGS_EQUAL(2, ordering.push_back(x4)); + EXPECT_LONGS_EQUAL(3, ordering.push_back(x3)); + + EXPECT_LONGS_EQUAL(2, ordering[x4]); + EXPECT_LONGS_EQUAL(3, ordering[x3]); // verify Ordering expectedFinal; diff --git a/gtsam/nonlinear/tests/testSerializationNonlinear.cpp b/gtsam/nonlinear/tests/testSerializationNonlinear.cpp index 120a9fa94..57e2c0a34 100644 --- a/gtsam/nonlinear/tests/testSerializationNonlinear.cpp +++ b/gtsam/nonlinear/tests/testSerializationNonlinear.cpp @@ -16,11 +16,12 @@ * @date Feb 7, 2012 */ +#include +#include #include #include #include #include -#include #include #include @@ -46,13 +47,13 @@ typedef PinholeCamera PinholeCal3DS2; typedef PinholeCamera PinholeCal3Bundler; /* ************************************************************************* */ -Point3 pt3(1.0, 2.0, 3.0); -Rot3 rt3 = Rot3::RzRyRx(1.0, 3.0, 2.0); -Pose3 pose3(rt3, pt3); +static Point3 pt3(1.0, 2.0, 3.0); +static Rot3 rt3 = Rot3::RzRyRx(1.0, 3.0, 2.0); +static Pose3 pose3(rt3, pt3); -Cal3_S2 cal1(1.0, 2.0, 0.3, 0.1, 0.5); -Cal3DS2 cal2(1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0); -Cal3Bundler cal3(1.0, 2.0, 3.0); +static Cal3_S2 cal1(1.0, 2.0, 0.3, 0.1, 0.5); +static Cal3DS2 cal2(1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0); +static Cal3Bundler cal3(1.0, 2.0, 3.0); TEST (Serialization, TemplatedValues) { Values values; diff --git a/gtsam/nonlinear/tests/testValues.cpp b/gtsam/nonlinear/tests/testValues.cpp index 6ccd3b083..ffef740a6 100644 --- a/gtsam/nonlinear/tests/testValues.cpp +++ b/gtsam/nonlinear/tests/testValues.cpp @@ -10,28 +10,54 @@ * -------------------------------------------------------------------------- */ /** - * @file testDynamicValues.cpp + * @file testValues.cpp * @author Richard Roberts */ -#include -#include -#include -#include // for operator += -using namespace boost::assign; - +#include +#include +#include +#include #include #include #include -#include -#include -#include + +#include +#include // for operator += +using namespace boost::assign; +#include +#include using namespace gtsam; using namespace std; static double inf = std::numeric_limits::infinity(); -const Key key1(Symbol('v',1)), key2(Symbol('v',2)), key3(Symbol('v',3)), key4(Symbol('v',4)); +// Convenience for named keys +using symbol_shorthand::X; +using symbol_shorthand::L; + +const Symbol key1('v',1), key2('v',2), key3('v',3), key4('v',4); + + +class TestValueData { +public: + static int ConstructorCount; + static int DestructorCount; + TestValueData(const TestValueData& other) { cout << "Copy constructor" << endl; ++ ConstructorCount; } + TestValueData() { cout << "Default constructor" << endl; ++ ConstructorCount; } + ~TestValueData() { cout << "Destructor" << endl; ++ DestructorCount; } +}; +int TestValueData::ConstructorCount = 0; +int TestValueData::DestructorCount = 0; +class TestValue : public DerivedValue { + TestValueData data_; +public: + virtual void print(const std::string& str = "") const {} + bool equals(const TestValue& other, double tol = 1e-9) const { return true; } + virtual size_t dim() const { return 0; } + TestValue retract(const Vector&) const { return TestValue(); } + Vector localCoordinates(const TestValue&) const { return Vector(); } +}; /* ************************************************************************* */ TEST( Values, equals1 ) @@ -208,6 +234,24 @@ TEST(Values, expmap_d) CHECK(config0.equals(config0)); } +/* ************************************************************************* */ +TEST(Values, localCoordinates) +{ + Values valuesA; + valuesA.insert(key1, LieVector(3, 1.0, 2.0, 3.0)); + valuesA.insert(key2, LieVector(3, 5.0, 6.0, 7.0)); + + Ordering ordering = *valuesA.orderingArbitrary(); + + VectorValues expDelta = valuesA.zeroVectors(ordering); +// expDelta.at(ordering[key1]) = Vector_(3, 0.1, 0.2, 0.3); +// expDelta.at(ordering[key2]) = Vector_(3, 0.4, 0.5, 0.6); + + Values valuesB = valuesA.retract(expDelta, ordering); + + EXPECT(assert_equal(expDelta, valuesA.localCoordinates(valuesB, ordering))); +} + /* ************************************************************************* */ TEST(Values, extract_keys) { @@ -332,9 +376,9 @@ TEST(Values, Symbol_filter) { Pose3 pose3(Pose2(0.3, 0.7, 0.9)); Values values; - values.insert(Symbol('x',0), pose0); + values.insert(X(0), pose0); values.insert(Symbol('y',1), pose1); - values.insert(Symbol('x',2), pose2); + values.insert(X(2), pose2); values.insert(Symbol('y',3), pose3); int i = 0; @@ -353,6 +397,26 @@ TEST(Values, Symbol_filter) { LONGS_EQUAL(2, i); } +/* ************************************************************************* */ +TEST(Values, Destructors) { + // Check that Value destructors are called when Values container is deleted + { + Values values; + { + TestValue value1; + TestValue value2; + LONGS_EQUAL(2, TestValueData::ConstructorCount); + LONGS_EQUAL(0, TestValueData::DestructorCount); + values.insert(0, value1); + values.insert(1, value2); + } + LONGS_EQUAL(4, TestValueData::ConstructorCount); + LONGS_EQUAL(2, TestValueData::DestructorCount); + } + LONGS_EQUAL(4, TestValueData::ConstructorCount); + LONGS_EQUAL(4, TestValueData::DestructorCount); +} + /* ************************************************************************* */ int main() { TestResult tr; return TestRegistry::runAllTests(tr); } /* ************************************************************************* */ diff --git a/gtsam/slam/AntiFactor.h b/gtsam/slam/AntiFactor.h index 633360fed..b5e77b578 100644 --- a/gtsam/slam/AntiFactor.h +++ b/gtsam/slam/AntiFactor.h @@ -26,6 +26,7 @@ namespace gtsam { * A class for downdating an existing factor from a graph. The AntiFactor returns the same * linearized Hessian matrices of the original factor, but with the opposite sign. This effectively * cancels out any affects of the original factor during optimization." + * @addtogroup SLAM */ class AntiFactor: public NonlinearFactor { @@ -50,6 +51,11 @@ namespace gtsam { virtual ~AntiFactor() {} + /// @return a deep copy of this factor + virtual gtsam::NonlinearFactor::shared_ptr clone() const { + return boost::static_pointer_cast( + gtsam::NonlinearFactor::shared_ptr(new This(*this))); } + /** implement functions needed for Testable */ /** print */ @@ -94,30 +100,8 @@ namespace gtsam { // Generate the linearized factor from the contained nonlinear factor GaussianFactor::shared_ptr gaussianFactor = factor_->linearize(c, ordering); - // Cast the GaussianFactor to a Hessian - HessianFactor::shared_ptr hessianFactor = boost::dynamic_pointer_cast(gaussianFactor); - - // If the cast fails, convert it to a Hessian - if(!hessianFactor){ - hessianFactor = HessianFactor::shared_ptr(new HessianFactor(*gaussianFactor)); - } - - // Copy Hessian Blocks from Hessian factor and invert - std::vector js; - std::vector Gs; - std::vector gs; - double f; - js.insert(js.end(), hessianFactor->begin(), hessianFactor->end()); - for(size_t i = 0; i < js.size(); ++i){ - for(size_t j = i; j < js.size(); ++j){ - Gs.push_back( -hessianFactor->info(hessianFactor->begin()+i, hessianFactor->begin()+j) ); - } - gs.push_back( -hessianFactor->linearTerm(hessianFactor->begin()+i) ); - } - f = -hessianFactor->constantTerm(); - - // Create the Anti-Hessian Factor from the negated blocks - return HessianFactor::shared_ptr(new HessianFactor(js, Gs, gs, f)); + // return the negated version of the factor + return gaussianFactor->negate(); } diff --git a/gtsam/slam/BearingFactor.h b/gtsam/slam/BearingFactor.h index 7c208436a..86a6e159c 100644 --- a/gtsam/slam/BearingFactor.h +++ b/gtsam/slam/BearingFactor.h @@ -24,13 +24,14 @@ namespace gtsam { /** * Binary factor for a bearing measurement + * @addtogroup SLAM */ - template + template class BearingFactor: public NoiseModelFactor2 { private: typedef POSE Pose; - typedef typename Pose::Rotation Rot; + typedef ROTATION Rot; typedef POINT Point; typedef BearingFactor This; @@ -55,6 +56,11 @@ namespace gtsam { virtual ~BearingFactor() {} + /// @return a deep copy of this factor + virtual gtsam::NonlinearFactor::shared_ptr clone() const { + return boost::static_pointer_cast( + gtsam::NonlinearFactor::shared_ptr(new This(*this))); } + /** h(x)-z -> between(z,h(x)) for Rot2 manifold */ Vector evaluateError(const Pose& pose, const Point& point, boost::optional H1, boost::optional H2) const { @@ -73,6 +79,13 @@ namespace gtsam { return e != NULL && Base::equals(*e, tol) && this->measured_.equals(e->measured_, tol); } + /** print contents */ + void print(const std::string& s="", const KeyFormatter& keyFormatter = DefaultKeyFormatter) const { + std::cout << s << "BearingFactor, bearing = "; + measured_.print(); + Base::print("", keyFormatter); + } + private: /** Serialization function */ diff --git a/gtsam/slam/BearingRangeFactor.h b/gtsam/slam/BearingRangeFactor.h index 4c170c811..d701054f9 100644 --- a/gtsam/slam/BearingRangeFactor.h +++ b/gtsam/slam/BearingRangeFactor.h @@ -26,13 +26,14 @@ namespace gtsam { /** * Binary factor for a bearing measurement + * @addtogroup SLAM */ - template + template class BearingRangeFactor: public NoiseModelFactor2 { private: typedef POSE Pose; - typedef typename POSE::Rotation Rot; + typedef ROTATION Rot; typedef POINT Point; typedef BearingRangeFactor This; @@ -57,14 +58,19 @@ namespace gtsam { virtual ~BearingRangeFactor() {} + /// @return a deep copy of this factor + virtual gtsam::NonlinearFactor::shared_ptr clone() const { + return boost::static_pointer_cast( + gtsam::NonlinearFactor::shared_ptr(new This(*this))); } + /** Print */ virtual void print(const std::string& s = "", const KeyFormatter& keyFormatter = DefaultKeyFormatter) const { - std::cout << s << ": BearingRangeFactor(" + std::cout << s << "BearingRangeFactor(" << keyFormatter(this->key1()) << "," << keyFormatter(this->key2()) << ")\n"; - measuredBearing_.print(" measured bearing"); - std::cout << " measured range: " << measuredRange_ << std::endl; - this->noiseModel_->print(" noise model"); + measuredBearing_.print("measured bearing: "); + std::cout << "measured range: " << measuredRange_ << std::endl; + this->noiseModel_->print("noise model:\n"); } /** equals */ diff --git a/gtsam/slam/BetweenFactor.h b/gtsam/slam/BetweenFactor.h index 2df0b98de..14314ceb7 100644 --- a/gtsam/slam/BetweenFactor.h +++ b/gtsam/slam/BetweenFactor.h @@ -27,6 +27,7 @@ namespace gtsam { /** * A class for a measurement predicted by "between(config[key1],config[key2])" * @tparam VALUE the Value type + * @addtogroup SLAM */ template class BetweenFactor: public NoiseModelFactor2 { @@ -62,6 +63,11 @@ namespace gtsam { virtual ~BetweenFactor() {} + /// @return a deep copy of this factor + virtual gtsam::NonlinearFactor::shared_ptr clone() const { + return boost::static_pointer_cast( + gtsam::NonlinearFactor::shared_ptr(new This(*this))); } + /** implement functions needed for Testable */ /** print */ @@ -69,8 +75,8 @@ namespace gtsam { std::cout << s << "BetweenFactor(" << keyFormatter(this->key1()) << "," << keyFormatter(this->key2()) << ")\n"; - measured_.print(" measured"); - this->noiseModel_->print(" noise model"); + measured_.print(" measured: "); + this->noiseModel_->print(" noise model: "); } /** equals */ diff --git a/gtsam/slam/BoundingConstraint.h b/gtsam/slam/BoundingConstraint.h index 0032d9a05..43d3802c0 100644 --- a/gtsam/slam/BoundingConstraint.h +++ b/gtsam/slam/BoundingConstraint.h @@ -27,6 +27,7 @@ namespace gtsam { * greater/less than a fixed threshold. The function * will need to have its value function implemented to return * a scalar for comparison. + * @addtogroup SLAM */ template struct BoundingConstraint1: public NoiseModelFactor1 { diff --git a/gtsam/slam/GeneralSFMFactor.h b/gtsam/slam/GeneralSFMFactor.h index 4f1f48958..3f3ae5a52 100644 --- a/gtsam/slam/GeneralSFMFactor.h +++ b/gtsam/slam/GeneralSFMFactor.h @@ -20,18 +20,21 @@ #pragma once -#include #include - +#include +#include +#include +#include namespace gtsam { /** - * Non-linear factor for a constraint derived from a 2D measurement. The calibration is unknown here compared to GenericProjectionFactor + * Non-linear factor for a constraint derived from a 2D measurement. + * The calibration is unknown here compared to GenericProjectionFactor + * @addtogroup SLAM */ template - class GeneralSFMFactor: - public NoiseModelFactor2 { + class GeneralSFMFactor: public NoiseModelFactor2 { protected: Point2 measured_; ///< the 2D measurement @@ -47,10 +50,10 @@ namespace gtsam { /** * Constructor - * @param z is the 2 dimensional location of point in image (the measurement) + * @param measured is the 2 dimensional location of point in image (the measurement) * @param model is the standard deviation of the measurements - * @param i is basically the frame number - * @param j is the index of the landmark + * @param cameraKey is the index of the camera + * @param landmarkKey is the index of the landmark */ GeneralSFMFactor(const Point2& measured, const SharedNoiseModel& model, Key cameraKey, Key landmarkKey) : Base(model, cameraKey, landmarkKey), measured_(measured) {} @@ -61,9 +64,15 @@ namespace gtsam { virtual ~GeneralSFMFactor() {} ///< destructor + /// @return a deep copy of this factor + virtual gtsam::NonlinearFactor::shared_ptr clone() const { + return boost::static_pointer_cast( + gtsam::NonlinearFactor::shared_ptr(new This(*this))); } + /** * print * @param s optional string naming the factor + * @param keyFormatter optional formatter for printing out Symbols */ void print(const std::string& s = "SFMFactor", const KeyFormatter& keyFormatter = DefaultKeyFormatter) const { Base::print(s, keyFormatter); @@ -91,8 +100,8 @@ namespace gtsam { if (H2) *H2 = zeros(2, point.dim()); // cout << e.what() << ": Landmark "<< this->key2_.index() // << " behind Camera " << this->key1_.index() << endl; - return zero(2); } + return zero(2); } /** return the measured */ @@ -105,8 +114,103 @@ namespace gtsam { friend class boost::serialization::access; template void serialize(Archive & ar, const unsigned int version) { + ar & boost::serialization::make_nvp("NoiseModelFactor2", + boost::serialization::base_object(*this)); ar & BOOST_SERIALIZATION_NVP(measured_); } }; + /** + * Non-linear factor for a constraint derived from a 2D measurement. + * Compared to GeneralSFMFactor, it is a ternary-factor because the calibration is isolated from camera.. + */ + template + class GeneralSFMFactor2: public NoiseModelFactor3 { + protected: + Point2 measured_; ///< the 2D measurement + + public: + + typedef GeneralSFMFactor2 This; + typedef PinholeCamera Camera; ///< typedef for camera type + typedef NoiseModelFactor3 Base; ///< typedef for the base class + typedef Point2 Measurement; ///< typedef for the measurement + + // shorthand for a smart pointer to a factor + typedef boost::shared_ptr shared_ptr; + + /** + * Constructor + * @param measured is the 2 dimensional location of point in image (the measurement) + * @param model is the standard deviation of the measurements + * @param poseKey is the index of the camera + * @param landmarkKey is the index of the landmark + * @param calibKey is the index of the calibration + */ + GeneralSFMFactor2(const Point2& measured, const SharedNoiseModel& model, Key poseKey, Key landmarkKey, Key calibKey) : + Base(model, poseKey, landmarkKey, calibKey), measured_(measured) {} + GeneralSFMFactor2():measured_(0.0,0.0) {} ///< default constructor + + virtual ~GeneralSFMFactor2() {} ///< destructor + + /// @return a deep copy of this factor + virtual gtsam::NonlinearFactor::shared_ptr clone() const { + return boost::static_pointer_cast( + gtsam::NonlinearFactor::shared_ptr(new This(*this))); } + + /** + * print + * @param s optional string naming the factor + * @param keyFormatter optional formatter useful for printing Symbols + */ + void print(const std::string& s = "SFMFactor2", const KeyFormatter& keyFormatter = DefaultKeyFormatter) const { + Base::print(s, keyFormatter); + measured_.print(s + ".z"); + } + + /** + * equals + */ + bool equals(const NonlinearFactor &p, double tol = 1e-9) const { + const This* e = dynamic_cast(&p); + return e && Base::equals(p, tol) && this->measured_.equals(e->measured_, tol) ; + } + + /** h(x)-z */ + Vector evaluateError(const Pose3& pose3, const Point3& point, const CALIBRATION &calib, + boost::optional H1=boost::none, + boost::optional H2=boost::none, + boost::optional H3=boost::none) const + { + try { + Camera camera(pose3,calib); + Point2 reprojError(camera.project(point, H1, H2, H3) - measured_); + return reprojError.vector(); + } + catch( CheiralityException& e) { + if (H1) *H1 = zeros(2, pose3.dim()); + if (H2) *H2 = zeros(2, point.dim()); + if (H3) *H3 = zeros(2, calib.dim()); + } + return zero(2); + } + + /** return the measured */ + inline const Point2 measured() const { + return measured_; + } + + private: + /** Serialization function */ + friend class boost::serialization::access; + template + void serialize(Archive & ar, const unsigned int version) { + ar & boost::serialization::make_nvp("NoiseModelFactor3", + boost::serialization::base_object(*this)); + ar & BOOST_SERIALIZATION_NVP(measured_); + } + }; + + + } //namespace diff --git a/gtsam/slam/PriorFactor.h b/gtsam/slam/PriorFactor.h index 2ab011bf5..5bd0ee76f 100644 --- a/gtsam/slam/PriorFactor.h +++ b/gtsam/slam/PriorFactor.h @@ -22,6 +22,7 @@ namespace gtsam { /** * A class for a soft prior on any Value type + * @addtogroup SLAM */ template class PriorFactor: public NoiseModelFactor1 { @@ -56,13 +57,18 @@ namespace gtsam { Base(model, key), prior_(prior) { } + /// @return a deep copy of this factor + virtual gtsam::NonlinearFactor::shared_ptr clone() const { + return boost::static_pointer_cast( + gtsam::NonlinearFactor::shared_ptr(new This(*this))); } + /** implement functions needed for Testable */ /** print */ virtual void print(const std::string& s, const KeyFormatter& keyFormatter = DefaultKeyFormatter) const { - std::cout << s << "PriorFactor(" << keyFormatter(this->key()) << ")\n"; - prior_.print(" prior"); - this->noiseModel_->print(" noise model"); + std::cout << s << "PriorFactor on " << keyFormatter(this->key()) << "\n"; + prior_.print(" prior mean: "); + this->noiseModel_->print(" noise model: "); } /** equals */ diff --git a/gtsam/slam/ProjectionFactor.h b/gtsam/slam/ProjectionFactor.h index d5e9048e5..79796e6c3 100644 --- a/gtsam/slam/ProjectionFactor.h +++ b/gtsam/slam/ProjectionFactor.h @@ -28,14 +28,15 @@ namespace gtsam { /** * Non-linear factor for a constraint derived from a 2D measurement. The calibration is known here. * i.e. the main building block for visual SLAM. + * @addtogroup SLAM */ - template + template class GenericProjectionFactor: public NoiseModelFactor2 { protected: // Keep a copy of measurement and calibration for I/O - Point2 measured_; ///< 2D measurement - boost::shared_ptr K_; ///< shared pointer to calibration object + Point2 measured_; ///< 2D measurement + boost::shared_ptr K_; ///< shared pointer to calibration object public: @@ -43,40 +44,46 @@ namespace gtsam { typedef NoiseModelFactor2 Base; /// shorthand for this class - typedef GenericProjectionFactor This; + typedef GenericProjectionFactor This; /// shorthand for a smart pointer to a factor typedef boost::shared_ptr shared_ptr; /// Default constructor - GenericProjectionFactor() : - K_(new Cal3_S2(444, 555, 666, 777, 888)) { + GenericProjectionFactor() { } /** * Constructor * TODO: Mark argument order standard (keys, measurement, parameters) - * @param z is the 2 dimensional location of point in image (the measurement) + * @param measured is the 2 dimensional location of point in image (the measurement) * @param model is the standard deviation - * @param j_pose is basically the frame number - * @param j_landmark is the index of the landmark + * @param poseKey is the index of the camera + * @param pointKey is the index of the landmark * @param K shared pointer to the constant calibration */ GenericProjectionFactor(const Point2& measured, const SharedNoiseModel& model, - const Key poseKey, Key pointKey, const shared_ptrK& K) : + Key poseKey, Key pointKey, const boost::shared_ptr& K) : Base(model, poseKey, pointKey), measured_(measured), K_(K) { } /** Virtual destructor */ virtual ~GenericProjectionFactor() {} + /// @return a deep copy of this factor + virtual gtsam::NonlinearFactor::shared_ptr clone() const { + return boost::static_pointer_cast( + gtsam::NonlinearFactor::shared_ptr(new This(*this))); } + /** * print * @param s optional string naming the factor + * @param keyFormatter optional formatter useful for printing Symbols */ - void print(const std::string& s = "ProjectionFactor", const KeyFormatter& keyFormatter = DefaultKeyFormatter) const { - Base::print(s, keyFormatter); - measured_.print(s + ".z"); + void print(const std::string& s = "", const KeyFormatter& keyFormatter = DefaultKeyFormatter) const { + std::cout << s << "GenericProjectionFactor, z = "; + measured_.print(); + Base::print("", keyFormatter); } /// equals @@ -89,16 +96,16 @@ namespace gtsam { Vector evaluateError(const Pose3& pose, const Point3& point, boost::optional H1 = boost::none, boost::optional H2 = boost::none) const { try { - SimpleCamera camera(*K_, pose); + PinholeCamera camera(pose, *K_); Point2 reprojectionError(camera.project(point, H1, H2) - measured_); return reprojectionError.vector(); } catch( CheiralityException& e) { if (H1) *H1 = zeros(2,6); if (H2) *H2 = zeros(2,3); - cout << e.what() << ": Landmark "<< DefaultKeyFormatter(this->key2()) << - " moved behind camera " << DefaultKeyFormatter(this->key1()) << endl; - return ones(2) * 2.0 * K_->fx(); + std::cout << e.what() << ": Landmark "<< DefaultKeyFormatter(this->key2()) << + " moved behind camera " << DefaultKeyFormatter(this->key1()) << std::endl; } + return ones(2) * 2.0 * K_->fx(); } /** return the measurement */ @@ -107,7 +114,7 @@ namespace gtsam { } /** return the calibration object */ - inline const Cal3_S2::shared_ptr calibration() const { + inline const boost::shared_ptr calibration() const { return K_; } diff --git a/gtsam/slam/RangeFactor.h b/gtsam/slam/RangeFactor.h index 489f751db..fa4ddb7f2 100644 --- a/gtsam/slam/RangeFactor.h +++ b/gtsam/slam/RangeFactor.h @@ -24,6 +24,7 @@ namespace gtsam { /** * Binary factor for a range measurement + * @addtogroup SLAM */ template class RangeFactor: public NoiseModelFactor2 { @@ -51,6 +52,11 @@ namespace gtsam { virtual ~RangeFactor() {} + /// @return a deep copy of this factor + virtual gtsam::NonlinearFactor::shared_ptr clone() const { + return boost::static_pointer_cast( + gtsam::NonlinearFactor::shared_ptr(new This(*this))); } + /** h(x)-z */ Vector evaluateError(const Pose& pose, const Point& point, boost::optional H1, boost::optional H2) const { double hx = pose.range(point, H1, H2); @@ -70,7 +76,8 @@ namespace gtsam { /** print contents */ void print(const std::string& s="", const KeyFormatter& keyFormatter = DefaultKeyFormatter) const { - Base::print(s + std::string(" range: ") + boost::lexical_cast(measured_), keyFormatter); + std::cout << s << "RangeFactor, range = " << measured_ << std::endl; + Base::print("", keyFormatter); } private: diff --git a/gtsam/slam/StereoFactor.h b/gtsam/slam/StereoFactor.h index ae2deeae3..87cb95d25 100644 --- a/gtsam/slam/StereoFactor.h +++ b/gtsam/slam/StereoFactor.h @@ -18,10 +18,15 @@ #pragma once +#include #include namespace gtsam { +/** + * A Generic Stereo Factor + * @addtogroup SLAM + */ template class GenericStereoFactor: public NoiseModelFactor2 { private: @@ -34,6 +39,7 @@ public: // shorthand for base class type typedef NoiseModelFactor2 Base; ///< typedef for base class + typedef GenericStereoFactor This; ///< typedef for this class (with templates) typedef boost::shared_ptr shared_ptr; ///< typedef for shared pointer to this object typedef POSE CamPose; ///< typedef for Pose Lie Value type @@ -56,9 +62,15 @@ public: virtual ~GenericStereoFactor() {} ///< Virtual destructor + /// @return a deep copy of this factor + virtual gtsam::NonlinearFactor::shared_ptr clone() const { + return boost::static_pointer_cast( + gtsam::NonlinearFactor::shared_ptr(new This(*this))); } + /** * print * @param s optional string naming the factor + * @param keyFormatter optional formatter useful for printing Symbols */ void print(const std::string& s = "", const KeyFormatter& keyFormatter = DefaultKeyFormatter) const { Base::print(s, keyFormatter); @@ -68,7 +80,7 @@ public: /** * equals */ - virtual bool equals(const NonlinearFactor& f, double tol) const { + virtual bool equals(const NonlinearFactor& f, double tol = 1e-9) const { const GenericStereoFactor* p = dynamic_cast (&f); return p && Base::equals(f) && measured_.equals(p->measured_, tol); } @@ -96,6 +108,8 @@ private: friend class boost::serialization::access; template void serialize(Archive & ar, const unsigned int version) { + ar & boost::serialization::make_nvp("NoiseModelFactor2", + boost::serialization::base_object(*this)); ar & BOOST_SERIALIZATION_NVP(measured_); ar & BOOST_SERIALIZATION_NVP(K_); } diff --git a/gtsam/slam/dataset.cpp b/gtsam/slam/dataset.cpp index f45f560a7..4550b418d 100644 --- a/gtsam/slam/dataset.cpp +++ b/gtsam/slam/dataset.cpp @@ -16,72 +16,74 @@ * @brief utility functions for loading datasets */ - #include #include #include +#include + +#include +#include #include +#include +#include using namespace std; -using namespace gtsam; +namespace fs = boost::filesystem; #define LINESIZE 81920 -typedef boost::shared_ptr sharedPose2Graph; -typedef pose2SLAM::Odometry Pose2Factor; ///< Typedef for Constraint class for backwards compatibility - namespace gtsam { +#ifndef MATLAB_MEX_FILE /* ************************************************************************* */ -pair > dataset(const string& dataset, const string& user_path) { - string path = user_path, set = dataset; - boost::optional null_model; - boost::optional identity(noiseModel::Unit::Create(3)); - boost::optional small(noiseModel::Diagonal::Variances( - gtsam::Vector_(3, 0.0001, 0.0001, 0.0003))); +string findExampleDataFile(const string& name) { + // Search source tree and installed location + vector rootsToSearch; + rootsToSearch.push_back(SOURCE_TREE_DATASET_DIR); // Defined by CMake, see gtsam/gtsam/CMakeLists.txt + rootsToSearch.push_back(INSTALLED_DATASET_DIR); // Defined by CMake, see gtsam/gtsam/CMakeLists.txt - if (path.empty()) path = string(getenv("HOME")) + "/data"; - if (set.empty()) set = string(getenv("DATASET")); + // Search for filename as given, and with .graph and .txt extensions + vector namesToSearch; + namesToSearch.push_back(name); + namesToSearch.push_back(name + ".graph"); + namesToSearch.push_back(name + ".txt"); - if (set == "intel") return make_pair(path + "/Intel/intel.graph", null_model); - if (set == "intel-gfs") return make_pair(path + "/Intel/intel.gfs.graph", null_model); - if (set == "Killian-gfs") return make_pair(path + "/Killian/Killian.gfs.graph", null_model); - if (set == "Killian") return make_pair(path + "/Killian/Killian.graph", small); - if (set == "Killian-noised") return make_pair(path + "/Killian/Killian-noised.graph", null_model); - if (set == "3") return make_pair(path + "/TORO/w3-odom.graph", identity); - if (set == "100") return make_pair(path + "/TORO/w100-odom.graph", identity); - if (set == "10K") return make_pair(path + "/TORO/w10000-odom.graph", identity); - if (set == "10K2") return make_pair(path + "/hogman/data/2D/w10000.graph", - noiseModel::Diagonal::Variances(gtsam::Vector_(3, 0.1, 0.1, 0.05))); - if (set == "Eiffel100") return make_pair(path + "/TORO/w100-Eiffel.graph", identity); - if (set == "Eiffel10K") return make_pair(path + "/TORO/w10000-Eiffel.graph", identity); - if (set == "olson") return make_pair(path + "/Olson/olson06icra.graph", null_model); - if (set == "victoria") return make_pair(path + "/VictoriaPark/victoria_park.graph", null_model); - if (set == "beijing") return make_pair(path + "/Beijing/beijingData_trips.graph", null_model); + // Find first name that exists + BOOST_FOREACH(const fs::path& root, rootsToSearch) { + BOOST_FOREACH(const fs::path& name, namesToSearch) { + if(fs::is_regular_file(root / name)) + return (root / name).string(); + } + } - return make_pair("unknown", null_model); + // If we did not return already, then we did not find the file + throw std::invalid_argument( + "gtsam::findExampleDataFile could not find a matching file in\n" + SOURCE_TREE_DATASET_DIR " or\n" + INSTALLED_DATASET_DIR " named\n" + + name + ", " + name + ".graph, or " + name + ".txt"); } +#endif /* ************************************************************************* */ - -pair load2D( - pair > dataset, +pair load2D( + pair > dataset, int maxID, bool addNoise, bool smart) { return load2D(dataset.first, dataset.second, maxID, addNoise, smart); } -pair load2D(const string& filename, - boost::optional model, int maxID, bool addNoise, bool smart) { +/* ************************************************************************* */ +pair load2D( + const string& filename, boost::optional model, int maxID, + bool addNoise, bool smart) { cout << "Will try to read " << filename << endl; ifstream is(filename.c_str()); - if (!is) { - cout << "load2D: can not find the file!"; - exit(-1); - } + if (!is) + throw std::invalid_argument("load2D: can not find the file!"); - Values::shared_ptr poses(new Values); - sharedPose2Graph graph(new pose2SLAM::Graph); + Values::shared_ptr initial(new Values); + NonlinearFactorGraph::shared_ptr graph(new NonlinearFactorGraph); string tag; @@ -94,83 +96,120 @@ pair load2D(const string& filename, double x, y, yaw; is >> id >> x >> y >> yaw; // optional filter - if (maxID && id >= maxID) continue; - poses->insert(pose2SLAM::PoseKey(id), Pose2(x, y, yaw)); + if (maxID && id >= maxID) + continue; + initial->insert(id, Pose2(x, y, yaw)); } is.ignore(LINESIZE, '\n'); } is.clear(); /* clears the end-of-file and error flags */ is.seekg(0, ios::beg); + // Create a sampler with random number generator + Sampler sampler(42u); + // load the factors while (is) { is >> tag; - if ((tag == "EDGE2") || (tag == "EDGE") || (tag == "ODOMETRY")) { - int id1, id2; - double x, y, yaw; + if ((tag == "EDGE2") || (tag == "EDGE") || (tag == "ODOMETRY")) { + int id1, id2; + double x, y, yaw; - is >> id1 >> id2 >> x >> y >> yaw; - Matrix m = eye(3); - is >> m(0, 0) >> m(0, 1) >> m(1, 1) >> m(2, 2) >> m(0, 2) >> m(1, 2); - m(2, 0) = m(0, 2); - m(2, 1) = m(1, 2); - m(1, 0) = m(0, 1); + is >> id1 >> id2 >> x >> y >> yaw; + Matrix m = eye(3); + is >> m(0, 0) >> m(0, 1) >> m(1, 1) >> m(2, 2) >> m(0, 2) >> m(1, 2); + m(2, 0) = m(0, 2); + m(2, 1) = m(1, 2); + m(1, 0) = m(0, 1); - // optional filter - if (maxID && (id1 >= maxID || id2 >= maxID)) continue; + // optional filter + if (maxID && (id1 >= maxID || id2 >= maxID)) + continue; - Pose2 l1Xl2(x, y, yaw); + Pose2 l1Xl2(x, y, yaw); - // SharedNoiseModel noise = noiseModel::Gaussian::Covariance(m, smart); - if (!model) { - Vector variances = Vector_(3,m(0,0),m(1,1),m(2,2)); - model = noiseModel::Diagonal::Variances(variances, smart); - } + // SharedNoiseModel noise = noiseModel::Gaussian::Covariance(m, smart); + if (!model) { + Vector variances = Vector_(3, m(0, 0), m(1, 1), m(2, 2)); + model = noiseModel::Diagonal::Variances(variances, smart); + } - if (addNoise) - l1Xl2 = l1Xl2.retract((*model)->sample()); + if (addNoise) + l1Xl2 = l1Xl2.retract(sampler.sampleNewModel(*model)); - // Insert vertices if pure odometry file - if (!poses->exists(pose2SLAM::PoseKey(id1))) poses->insert(pose2SLAM::PoseKey(id1), Pose2()); - if (!poses->exists(pose2SLAM::PoseKey(id2))) poses->insert(pose2SLAM::PoseKey(id2), poses->at(pose2SLAM::PoseKey(id1)) * l1Xl2); + // Insert vertices if pure odometry file + if (!initial->exists(id1)) + initial->insert(id1, Pose2()); + if (!initial->exists(id2)) + initial->insert(id2, initial->at(id1) * l1Xl2); - pose2SLAM::Graph::sharedFactor factor(new Pose2Factor(pose2SLAM::PoseKey(id1), pose2SLAM::PoseKey(id2), l1Xl2, *model)); - graph->push_back(factor); - } + NonlinearFactor::shared_ptr factor( + new BetweenFactor(id1, id2, l1Xl2, *model)); + graph->push_back(factor); + } + if (tag == "BR") { + int id1, id2; + double bearing, range, bearing_std, range_std; + + is >> id1 >> id2 >> bearing >> range >> bearing_std >> range_std; + + // optional filter + if (maxID && (id1 >= maxID || id2 >= maxID)) + continue; + + noiseModel::Diagonal::shared_ptr measurementNoise = + noiseModel::Diagonal::Sigmas(Vector_(2, bearing_std, range_std)); + graph->add(BearingRangeFactor(id1, id2, bearing, range, measurementNoise)); + + // Insert poses or points if they do not exist yet + if (!initial->exists(id1)) + initial->insert(id1, Pose2()); + if (!initial->exists(id2)) { + Pose2 pose = initial->at(id1); + Point2 local(cos(bearing)*range,sin(bearing)*range); + Point2 global = pose.transform_from(local); + initial->insert(id2, global); + } + } is.ignore(LINESIZE, '\n'); } - cout << "load2D read a graph file with " << poses->size() << " vertices and " - << graph->nrFactors() << " factors" << endl; + cout << "load2D read a graph file with " << initial->size() + << " vertices and " << graph->nrFactors() << " factors" << endl; - return make_pair(graph, poses); + return make_pair(graph, initial); } /* ************************************************************************* */ -void save2D(const pose2SLAM::Graph& graph, const Values& config, const SharedDiagonal model, - const string& filename) { +void save2D(const NonlinearFactorGraph& graph, const Values& config, + const noiseModel::Diagonal::shared_ptr model, const string& filename) { fstream stream(filename.c_str(), fstream::out); // save poses - BOOST_FOREACH(const Values::ConstKeyValuePair& key_value, config) { - const Pose2& pose = dynamic_cast(key_value.value); - stream << "VERTEX2 " << key_value.key << " " << pose.x() << " " << pose.y() << " " << pose.theta() << endl; + BOOST_FOREACH(const Values::ConstKeyValuePair& key_value, config) + { + const Pose2& pose = dynamic_cast(key_value.value); + stream << "VERTEX2 " << key_value.key << " " << pose.x() << " " + << pose.y() << " " << pose.theta() << endl; } // save edges Matrix R = model->R(); - Matrix RR = trans(R)*R;//prod(trans(R),R); - BOOST_FOREACH(boost::shared_ptr factor_, graph) { - boost::shared_ptr factor = boost::dynamic_pointer_cast(factor_); - if (!factor) continue; + Matrix RR = trans(R) * R; //prod(trans(R),R); + BOOST_FOREACH(boost::shared_ptr factor_, graph) + { + boost::shared_ptr > factor = + boost::dynamic_pointer_cast >(factor_); + if (!factor) + continue; Pose2 pose = factor->measured().inverse(); - stream << "EDGE2 " << factor->key2() << " " << factor->key1() - << " " << pose.x() << " " << pose.y() << " " << pose.theta() - << " " << RR(0, 0) << " " << RR(0, 1) << " " << RR(1, 1) << " " << RR(2, 2) - << " " << RR(0, 2) << " " << RR(1, 2) << endl; + stream << "EDGE2 " << factor->key2() << " " << factor->key1() << " " + << pose.x() << " " << pose.y() << " " << pose.theta() << " " + << RR(0, 0) << " " << RR(0, 1) << " " << RR(1, 1) << " " + << RR(2, 2) << " " << RR(0, 2) << " " << RR(1, 2) << endl; } stream.close(); @@ -179,7 +218,8 @@ void save2D(const pose2SLAM::Graph& graph, const Values& config, const SharedDia /* ************************************************************************* */ bool load3D(const string& filename) { ifstream is(filename.c_str()); - if (!is) return false; + if (!is) + return false; while (is) { char buf[LINESIZE]; @@ -216,4 +256,6 @@ bool load3D(const string& filename) { } return true; } -} +/* ************************************************************************* */ + +} // \namespace gtsam diff --git a/gtsam/slam/dataset.h b/gtsam/slam/dataset.h index 5e06e583d..8da3d6ef9 100644 --- a/gtsam/slam/dataset.h +++ b/gtsam/slam/dataset.h @@ -18,43 +18,60 @@ #pragma once +#include +#include #include -#include -namespace gtsam -{ -/** - * Construct dataset filename from short name - * Currently has "Killian" "intel.gfs", "10K", etc... - * @param filename - * @param optional dataset, if empty will try to getenv $DATASET - * @param optional path, if empty will try to getenv $HOME - */ -std::pair > - dataset(const std::string& dataset = "", const std::string& path = ""); +namespace gtsam { -/** - * Load TORO 2D Graph - * @param filename - * @param maxID, if non-zero cut out vertices >= maxID - * @param smart: try to reduce complexity of covariance to cheapest model - */ -std::pair, boost::shared_ptr > load2D( - std::pair > dataset, - int maxID = 0, bool addNoise=false, bool smart=true); -std::pair, boost::shared_ptr > load2D( - const std::string& filename, - boost::optional model = boost::optional(), - int maxID = 0, bool addNoise=false, bool smart=true); +#ifndef MATLAB_MEX_FILE + /** + * Find the full path to an example dataset distributed with gtsam. The name + * may be specified with or without a file extension - if no extension is + * give, this function first looks for the .graph extension, then .txt. We + * first check the gtsam source tree for the file, followed by the installed + * example dataset location. Both the source tree and installed locations + * are obtained from CMake during compilation. + * @return The full path and filename to the requested dataset. + * @throw std::invalid_argument if no matching file could be found using the + * search process described above. + */ + std::string findExampleDataFile(const std::string& name); +#endif -/** save 2d graph */ -void save2D(const pose2SLAM::Graph& graph, const Values& config, const gtsam::SharedDiagonal model, - const std::string& filename); + /** + * Load TORO 2D Graph + * @param dataset/model pair as constructed by [dataset] + * @param maxID if non-zero cut out vertices >= maxID + * @param addNoise add noise to the edges + * @param smart try to reduce complexity of covariance to cheapest model + */ + std::pair load2D( + std::pair > dataset, + int maxID = 0, bool addNoise = false, bool smart = true); -/** - * Load TORO 3D Graph - */ -bool load3D(const std::string& filename); + /** + * Load TORO 2D Graph + * @param filename + * @param model optional noise model to use instead of one specified by file + * @param maxID if non-zero cut out vertices >= maxID + * @param addNoise add noise to the edges + * @param smart try to reduce complexity of covariance to cheapest model + */ + std::pair load2D( + const std::string& filename, + boost::optional model = boost::optional< + noiseModel::Diagonal::shared_ptr>(), int maxID = 0, bool addNoise = false, + bool smart = true); + + /** save 2d graph */ + void save2D(const NonlinearFactorGraph& graph, const Values& config, + const noiseModel::Diagonal::shared_ptr model, const std::string& filename); + + /** + * Load TORO 3D Graph + */ + bool load3D(const std::string& filename); } // namespace gtsam diff --git a/gtsam/slam/planarSLAM.cpp b/gtsam/slam/planarSLAM.cpp deleted file mode 100644 index b5f7b18ef..000000000 --- a/gtsam/slam/planarSLAM.cpp +++ /dev/null @@ -1,68 +0,0 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) - - * See LICENSE for the license information - - * -------------------------------------------------------------------------- */ - -/** - * @file planarSLAM.cpp - * @brief: bearing/range measurements in 2D plane - * @author Frank Dellaert - **/ - -#include -#include - -// Use planarSLAM namespace for specific SLAM instance -namespace planarSLAM { - - /* ************************************************************************* */ - Graph::Graph(const NonlinearFactorGraph& graph) : - NonlinearFactorGraph(graph) {} - - /* ************************************************************************* */ - void Graph::addPrior(Index i, const Pose2& p, const SharedNoiseModel& model) { - sharedFactor factor(new Prior(PoseKey(i), p, model)); - push_back(factor); - } - - /* ************************************************************************* */ - void Graph::addPoseConstraint(Index i, const Pose2& p) { - sharedFactor factor(new Constraint(PoseKey(i), p)); - push_back(factor); - } - - /* ************************************************************************* */ - void Graph::addOdometry(Index i, Index j, const Pose2& odometry, const SharedNoiseModel& model) { - sharedFactor factor(new Odometry(PoseKey(i), PoseKey(j), odometry, model)); - push_back(factor); - } - - /* ************************************************************************* */ - void Graph::addBearing(Index i, Index j, const Rot2& z, const SharedNoiseModel& model) { - sharedFactor factor(new Bearing(PoseKey(i), PointKey(j), z, model)); - push_back(factor); - } - - /* ************************************************************************* */ - void Graph::addRange(Index i, Index j, double z, const SharedNoiseModel& model) { - sharedFactor factor(new Range(PoseKey(i), PointKey(j), z, model)); - push_back(factor); - } - - /* ************************************************************************* */ - void Graph::addBearingRange(Index i, Index j, const Rot2& z1, - double z2, const SharedNoiseModel& model) { - sharedFactor factor(new BearingRange(PoseKey(i), PointKey(j), z1, z2, model)); - push_back(factor); - } - - /* ************************************************************************* */ - -} // planarSLAM - diff --git a/gtsam/slam/planarSLAM.h b/gtsam/slam/planarSLAM.h deleted file mode 100644 index 07e6896e5..000000000 --- a/gtsam/slam/planarSLAM.h +++ /dev/null @@ -1,118 +0,0 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) - - * See LICENSE for the license information - - * -------------------------------------------------------------------------- */ - -/** - * @file planarSLAM.h - * @brief: bearing/range measurements in 2D plane - * @author Frank Dellaert - */ - -#pragma once - -#include -#include -#include -#include -#include -#include -#include -#include -#include - -// Use planarSLAM namespace for specific SLAM instance -namespace planarSLAM { - - using namespace gtsam; - - /// Convenience function for constructing a pose key - inline Symbol PoseKey(Index j) { return Symbol('x', j); } - - /// Convenience function for constructing a pose key - inline Symbol PointKey(Index j) { return Symbol('l', j); } - - /* - * List of typedefs for factors - */ - /// A hard constraint for PoseKeys to enforce particular values - typedef NonlinearEquality Constraint; - /// A prior factor to bias the value of a PoseKey - typedef PriorFactor Prior; - /// A factor between two PoseKeys set with a Pose2 - typedef BetweenFactor Odometry; - /// A factor between a PoseKey and a PointKey to express difference in rotation (set with a Rot2) - typedef BearingFactor Bearing; - /// A factor between a PoseKey and a PointKey to express distance between them (set with a double) - typedef RangeFactor Range; - /// A factor between a PoseKey and a PointKey to express difference in rotation and location - typedef BearingRangeFactor BearingRange; - - /** Values class, using specific PoseKeys and PointKeys - * Mainly as a convenience for MATLAB wrapper, which does not allow for identically named methods - */ - struct Values: public gtsam::Values { - - /// Default constructor - Values() {} - - /// Copy constructor - Values(const gtsam::Values& values) : - gtsam::Values(values) { - } - - /// get a pose - Pose2 pose(Index key) const { return at(PoseKey(key)); } - - /// get a point - Point2 point(Index key) const { return at(PointKey(key)); } - - /// insert a pose - void insertPose(Index key, const Pose2& pose) { insert(PoseKey(key), pose); } - - /// insert a point - void insertPoint(Index key, const Point2& point) { insert(PointKey(key), point); } - }; - - /// Creates a NonlinearFactorGraph with the Values type - struct Graph: public NonlinearFactorGraph { - - /// Default constructor for a NonlinearFactorGraph - Graph(){} - - /// Creates a NonlinearFactorGraph based on another NonlinearFactorGraph - Graph(const NonlinearFactorGraph& graph); - - /// Biases the value of PoseKey key with Pose2 p given a noise model - void addPrior(Index poseKey, const Pose2& pose, const SharedNoiseModel& noiseModel); - - /// Creates a hard constraint to enforce Pose2 p for PoseKey poseKey's value - void addPoseConstraint(Index poseKey, const Pose2& pose); - - /// Creates a factor with a Pose2 between PoseKeys poseKey and pointKey (poseKey.e. an odometry measurement) - void addOdometry(Index poseKey1, Index poseKey2, const Pose2& odometry, const SharedNoiseModel& model); - - /// Creates a factor with a Rot2 between a PoseKey poseKey and PointKey pointKey for difference in rotation - void addBearing(Index poseKey, Index pointKey, const Rot2& bearing, const SharedNoiseModel& model); - - /// Creates a factor with a Rot2 between a PoseKey poseKey and PointKey pointKey for difference in location - void addRange(Index poseKey, Index pointKey, double range, const SharedNoiseModel& model); - - /// Creates a factor with a Rot2 between a PoseKey poseKey and PointKey pointKey for difference in rotation and location - void addBearingRange(Index poseKey, Index pointKey, const Rot2& bearing, double range, const SharedNoiseModel& model); - - /// Optimize - Values optimize(const Values& initialEstimate) { - return LevenbergMarquardtOptimizer(*this, initialEstimate).optimize(); - } - }; - -} // planarSLAM - - diff --git a/gtsam/slam/pose2SLAM.cpp b/gtsam/slam/pose2SLAM.cpp deleted file mode 100644 index e8cbcd7fe..000000000 --- a/gtsam/slam/pose2SLAM.cpp +++ /dev/null @@ -1,55 +0,0 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) - - * See LICENSE for the license information - - * -------------------------------------------------------------------------- */ - -/** - * @file pose2SLAM.cpp - * @brief: Odometry measurements in 2D plane - * @author Frank Dellaert - **/ - -#include - -// Use pose2SLAM namespace for specific SLAM instance - -namespace pose2SLAM { - - /* ************************************************************************* */ - Values circle(size_t n, double R) { - Values x; - double theta = 0, dtheta = 2 * M_PI / n; - for (size_t i = 0; i < n; i++, theta += dtheta) - x.insert(PoseKey(i), Pose2(cos(theta), sin(theta), M_PI_2 + theta)); - return x; - } - - /* ************************************************************************* */ - void Graph::addPrior(Index i, const Pose2& p, - const SharedNoiseModel& model) { - sharedFactor factor(new Prior(PoseKey(i), p, model)); - push_back(factor); - } - - /* ************************************************************************* */ - void Graph::addPoseConstraint(Index i, const Pose2& p) { - sharedFactor factor(new HardConstraint(PoseKey(i), p)); - push_back(factor); - } - - /* ************************************************************************* */ - void Graph::addOdometry(Index i, Index j, const Pose2& z, - const SharedNoiseModel& model) { - sharedFactor factor(new Odometry(PoseKey(i), PoseKey(j), z, model)); - push_back(factor); - } - - /* ************************************************************************* */ - -} // pose2SLAM diff --git a/gtsam/slam/pose2SLAM.h b/gtsam/slam/pose2SLAM.h deleted file mode 100644 index 6dc682f9b..000000000 --- a/gtsam/slam/pose2SLAM.h +++ /dev/null @@ -1,105 +0,0 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) - - * See LICENSE for the license information - - * -------------------------------------------------------------------------- */ - -/** - * @file pose2SLAM.h - * @brief: 2D Pose SLAM - * @author Frank Dellaert - **/ - -#pragma once - -#include -#include -#include -#include -#include -#include -#include -#include - -// Use pose2SLAM namespace for specific SLAM instance -namespace pose2SLAM { - - using namespace gtsam; - - /// Convenience function for constructing a pose key - inline Symbol PoseKey(Index j) { return Symbol('x', j); } - - /// Values class, inherited from Values, using PoseKeys, mainly used as a convenience for MATLAB wrapper - struct Values: public gtsam::Values { - - /// Default constructor - Values() {} - - /// Copy constructor - Values(const gtsam::Values& values) : - gtsam::Values(values) { - } - - // Convenience for MATLAB wrapper, which does not allow for identically named methods - - /// get a pose - Pose2 pose(Index key) const { return at(PoseKey(key)); } - - /// insert a pose - void insertPose(Index key, const Pose2& pose) { insert(PoseKey(key), pose); } - }; - - /** - * Create a circle of n 2D poses tangent to circle of radius R, first pose at (R,0) - * @param n number of poses - * @param R radius of circle - * @param c character to use for keys - * @return circle of n 2D poses - */ - Values circle(size_t n, double R); - - /** - * List of typedefs for factors - */ - - /// A hard constraint to enforce a specific value for a pose - typedef NonlinearEquality HardConstraint; - /// A prior factor on a pose with Pose2 data type. - typedef PriorFactor Prior; - /// A factor to add an odometry measurement between two poses. - typedef BetweenFactor Odometry; - - /// Graph - struct Graph: public NonlinearFactorGraph { - - /// Default constructor for a NonlinearFactorGraph - Graph(){} - - /// Creates a NonlinearFactorGraph based on another NonlinearFactorGraph - Graph(const NonlinearFactorGraph& graph); - - /// Adds a Pose2 prior with a noise model to one of the keys in the nonlinear factor graph - void addPrior(Index i, const Pose2& p, const SharedNoiseModel& model); - - /// Creates a hard constraint for key i with the given Pose2 p. - void addPoseConstraint(Index i, const Pose2& p); - - /// Creates a between factor between keys i and j with a noise model with Pose2 z in the graph - void addOdometry(Index i, Index j, const Pose2& z, - const SharedNoiseModel& model); - - /// Optimize - Values optimize(const Values& initialEstimate) const { - return LevenbergMarquardtOptimizer(*this, initialEstimate).optimize(); - } - }; - -} // pose2SLAM - - - diff --git a/gtsam/slam/pose3SLAM.cpp b/gtsam/slam/pose3SLAM.cpp deleted file mode 100644 index 0ab962f1e..000000000 --- a/gtsam/slam/pose3SLAM.cpp +++ /dev/null @@ -1,64 +0,0 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) - - * See LICENSE for the license information - - * -------------------------------------------------------------------------- */ - -/** - * @file pose3SLAM.cpp - * @brief: bearing/range measurements in 2D plane - * @author Frank Dellaert - **/ - -#include -#include - -// Use pose3SLAM namespace for specific SLAM instance -namespace pose3SLAM { - - /* ************************************************************************* */ - Values circle(size_t n, double radius) { - Values x; - double theta = 0, dtheta = 2 * M_PI / n; - // We use aerospace/navlab convention, X forward, Y right, Z down - // First pose will be at (R,0,0) - // ^y ^ X - // | | - // z-->xZ--> Y (z pointing towards viewer, Z pointing away from viewer) - // Vehicle at p0 is looking towards y axis (X-axis points towards world y) - Rot3 gR0(Point3(0, 1, 0), Point3(1, 0, 0), Point3(0, 0, -1)); - for (size_t i = 0; i < n; i++, theta += dtheta) { - Point3 gti(radius*cos(theta), radius*sin(theta), 0); - Rot3 _0Ri = Rot3::yaw(-theta); // negative yaw goes counterclockwise, with Z down ! - Pose3 gTi(gR0 * _0Ri, gti); - x.insert(PoseKey(i), gTi); - } - return x; - } - - /* ************************************************************************* */ - void Graph::addPrior(Index i, const Pose3& p, const SharedNoiseModel& model) { - sharedFactor factor(new Prior(PoseKey(i), p, model)); - push_back(factor); - } - - /* ************************************************************************* */ - void Graph::addConstraint(Index i, Index j, const Pose3& z, const SharedNoiseModel& model) { - sharedFactor factor(new Constraint(PoseKey(i), PoseKey(j), z, model)); - push_back(factor); - } - - /* ************************************************************************* */ - void Graph::addHardConstraint(Index i, const Pose3& p) { - sharedFactor factor(new HardConstraint(PoseKey(i), p)); - push_back(factor); - } - - /* ************************************************************************* */ - -} // pose3SLAM diff --git a/gtsam/slam/pose3SLAM.h b/gtsam/slam/pose3SLAM.h deleted file mode 100644 index 6b4efbe6c..000000000 --- a/gtsam/slam/pose3SLAM.h +++ /dev/null @@ -1,79 +0,0 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) - - * See LICENSE for the license information - - * -------------------------------------------------------------------------- */ - -/** - * @file pose3SLAM.h - * @brief: 3D Pose SLAM - * @author Frank Dellaert - **/ - -#pragma once - -#include -#include -#include -#include -#include -#include -#include - -/// Use pose3SLAM namespace for specific SLAM instance -namespace pose3SLAM { - - using namespace gtsam; - - /// Convenience function for constructing a pose key - inline Symbol PoseKey(Index j) { return Symbol('x', j); } - - /** - * Create a circle of n 3D poses tangent to circle of radius R, first pose at (R,0) - * @param n number of poses - * @param R radius of circle - * @return circle of n 3D poses - */ - Values circle(size_t n, double R); - - /// A prior factor on Key with Pose3 data type. - typedef PriorFactor Prior; - /// A factor to put constraints between two factors. - typedef BetweenFactor Constraint; - /// A hard constraint would enforce that the given key would have the input value in the results. - typedef NonlinearEquality HardConstraint; - - /// Graph - struct Graph: public NonlinearFactorGraph { - - /// Adds a factor between keys of the same type - void addPrior(Index i, const Pose3& p, const SharedNoiseModel& model); - - /// Creates a between factor between keys i and j with a noise model with Pos3 z in the graph - void addConstraint(Index i, Index j, const Pose3& z, const SharedNoiseModel& model); - - /// Creates a hard constraint for key i with the given Pose3 p. - void addHardConstraint(Index i, const Pose3& p); - - /// Optimize - Values optimize(const Values& initialEstimate) { - return LevenbergMarquardtOptimizer(*this, initialEstimate).optimize(); - } - - }; - -} // pose3SLAM - -/** - * Backwards compatibility - */ -namespace gtsam { - typedef pose3SLAM::Prior Pose3Prior; ///< Typedef for Prior class for backwards compatibility - typedef pose3SLAM::Constraint Pose3Factor; ///< Typedef for Constraint class for backwards compatibility - typedef pose3SLAM::Graph Pose3Graph; ///< Typedef for Graph class for backwards compatibility -} diff --git a/gtsam/slam/tests/testAntiFactor.cpp b/gtsam/slam/tests/testAntiFactor.cpp index 183b0c600..0dd576aed 100644 --- a/gtsam/slam/tests/testAntiFactor.cpp +++ b/gtsam/slam/tests/testAntiFactor.cpp @@ -17,18 +17,18 @@ #include -#include #include -#include +#include +#include #include +#include +#include #include #include using namespace std; using namespace gtsam; -using pose3SLAM::PoseKey; - /* ************************************************************************* */ TEST( AntiFactor, NegativeHessian) { @@ -42,17 +42,17 @@ TEST( AntiFactor, NegativeHessian) // Create a configuration corresponding to the ground truth boost::shared_ptr values(new Values()); - values->insert(PoseKey(1), pose1); - values->insert(PoseKey(2), pose2); + values->insert(1, pose1); + values->insert(2, pose2); // Define an elimination ordering Ordering::shared_ptr ordering(new Ordering()); - ordering->insert(PoseKey(1), 0); - ordering->insert(PoseKey(2), 1); + ordering->insert(1, 0); + ordering->insert(2, 1); // Create a "standard" factor - BetweenFactor::shared_ptr originalFactor(new BetweenFactor(PoseKey(1), PoseKey(2), z, sigma)); + BetweenFactor::shared_ptr originalFactor(new BetweenFactor(1, 2, z, sigma)); // Linearize it into a Jacobian Factor GaussianFactor::shared_ptr originalJacobian = originalFactor->linearize(*values, *ordering); @@ -97,14 +97,14 @@ TEST( AntiFactor, EquivalentBayesNet) Pose3 z(Rot3(), Point3(1, 1, 1)); SharedNoiseModel sigma(noiseModel::Unit::Create(Pose3::Dim())); - boost::shared_ptr graph(new pose3SLAM::Graph()); - graph->addPrior(1, pose1, sigma); - graph->addConstraint(1, 2, pose1.between(pose2), sigma); + NonlinearFactorGraph::shared_ptr graph(new NonlinearFactorGraph()); + graph->add(PriorFactor(1, pose1, sigma)); + graph->add(BetweenFactor(1, 2, pose1.between(pose2), sigma)); // Create a configuration corresponding to the ground truth - boost::shared_ptr values(new Values()); - values->insert(PoseKey(1), pose1); - values->insert(PoseKey(2), pose2); + Values::shared_ptr values(new Values()); + values->insert(1, pose1); + values->insert(2, pose2); // Define an elimination ordering Ordering::shared_ptr ordering = graph->orderingCOLAMD(*values); @@ -117,7 +117,7 @@ TEST( AntiFactor, EquivalentBayesNet) VectorValues expectedDeltas = optimize(*expectedBayesNet); // Add an additional factor between Pose1 and Pose2 - pose3SLAM::Constraint::shared_ptr f1(new pose3SLAM::Constraint(PoseKey(1), PoseKey(2), z, sigma)); + BetweenFactor::shared_ptr f1(new BetweenFactor(1, 2, z, sigma)); graph->push_back(f1); // Add the corresponding AntiFactor between Pose1 and Pose2 diff --git a/gtsam/slam/tests/testDataset.cpp b/gtsam/slam/tests/testDataset.cpp new file mode 100644 index 000000000..aae3fc5da --- /dev/null +++ b/gtsam/slam/tests/testDataset.cpp @@ -0,0 +1,38 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file testDataset.cpp + * @brief Unit test for dataset.cpp + * @author Richard Roberts + */ + +#include + +#include + +#include +#include + +using namespace std; +using namespace gtsam; + +TEST(dataSet, findExampleDataFile) { + const string expected_end = "examples/Data/example.graph"; + const string actual = findExampleDataFile("example"); + string actual_end = actual.substr(actual.size() - expected_end.size(), expected_end.size()); + boost::replace_all(actual_end, "\\", "/"); // Convert directory separators to forward-slash + EXPECT(assert_equal(expected_end, actual_end)); +} + +/* ************************************************************************* */ +int main() { TestResult tr; return TestRegistry::runAllTests(tr); } +/* ************************************************************************* */ diff --git a/gtsam/slam/tests/testGeneralSFMFactor.cpp b/gtsam/slam/tests/testGeneralSFMFactor.cpp index 5b8a217bc..58f06c8d4 100644 --- a/gtsam/slam/tests/testGeneralSFMFactor.cpp +++ b/gtsam/slam/tests/testGeneralSFMFactor.cpp @@ -16,27 +16,32 @@ * @brief unit tests for GeneralSFMFactor */ -#include -#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include #include #include using namespace boost; -#include -#include -#include -#include -#include -#include -#include -#include -#include -#include +#include +#include using namespace std; using namespace gtsam; +// Convenience for named keys +using symbol_shorthand::X; +using symbol_shorthand::L; + typedef PinholeCamera GeneralCamera; typedef GeneralSFMFactor Projection; typedef NonlinearEquality CameraConstraint; @@ -45,22 +50,22 @@ typedef NonlinearEquality Point3Constraint; class Graph: public NonlinearFactorGraph { public: void addMeasurement(int i, int j, const Point2& z, const SharedNoiseModel& model) { - push_back(boost::make_shared(z, model, Symbol('x',i), Symbol('l',j))); + push_back(boost::make_shared(z, model, X(i), L(j))); } void addCameraConstraint(int j, const GeneralCamera& p) { - boost::shared_ptr factor(new CameraConstraint(Symbol('x',j), p)); + boost::shared_ptr factor(new CameraConstraint(X(j), p)); push_back(factor); } void addPoint3Constraint(int j, const Point3& p) { - boost::shared_ptr factor(new Point3Constraint(Symbol('l',j), p)); + boost::shared_ptr factor(new Point3Constraint(L(j), p)); push_back(factor); } }; -double getGaussian() +static double getGaussian() { double S,V1,V2; // Use Box-Muller method to create gauss noise from uniform noise @@ -75,7 +80,7 @@ double getGaussian() return sqrt(-2.0f * (double)log(S) / S) * V1; } -const SharedNoiseModel sigma1(noiseModel::Unit::Create(1)); +static const SharedNoiseModel sigma1(noiseModel::Unit::Create(1)); /* ************************************************************************* */ TEST( GeneralSFMFactor, equals ) @@ -97,46 +102,46 @@ TEST( GeneralSFMFactor, equals ) TEST( GeneralSFMFactor, error ) { Point2 z(3.,0.); const SharedNoiseModel sigma(noiseModel::Unit::Create(1)); - boost::shared_ptr factor(new Projection(z, sigma, Symbol('x',1), Symbol('l',1))); + boost::shared_ptr factor(new Projection(z, sigma, X(1), L(1))); // For the following configuration, the factor predicts 320,240 Values values; Rot3 R; Point3 t1(0,0,-6); Pose3 x1(R,t1); - values.insert(Symbol('x',1), GeneralCamera(x1)); - Point3 l1; values.insert(Symbol('l',1), l1); + values.insert(X(1), GeneralCamera(x1)); + Point3 l1; values.insert(L(1), l1); EXPECT(assert_equal(Vector_(2, -3.0, 0.0), factor->unwhitenedError(values))); } static const double baseline = 5.0 ; /* ************************************************************************* */ -vector genPoint3() { +static vector genPoint3() { const double z = 5; - vector L ; - L.push_back(Point3 (-1.0,-1.0, z)); - L.push_back(Point3 (-1.0, 1.0, z)); - L.push_back(Point3 ( 1.0, 1.0, z)); - L.push_back(Point3 ( 1.0,-1.0, z)); - L.push_back(Point3 (-1.5,-1.5, 1.5*z)); - L.push_back(Point3 (-1.5, 1.5, 1.5*z)); - L.push_back(Point3 ( 1.5, 1.5, 1.5*z)); - L.push_back(Point3 ( 1.5,-1.5, 1.5*z)); - L.push_back(Point3 (-2.0,-2.0, 2*z)); - L.push_back(Point3 (-2.0, 2.0, 2*z)); - L.push_back(Point3 ( 2.0, 2.0, 2*z)); - L.push_back(Point3 ( 2.0,-2.0, 2*z)); - return L ; + vector landmarks ; + landmarks.push_back(Point3 (-1.0,-1.0, z)); + landmarks.push_back(Point3 (-1.0, 1.0, z)); + landmarks.push_back(Point3 ( 1.0, 1.0, z)); + landmarks.push_back(Point3 ( 1.0,-1.0, z)); + landmarks.push_back(Point3 (-1.5,-1.5, 1.5*z)); + landmarks.push_back(Point3 (-1.5, 1.5, 1.5*z)); + landmarks.push_back(Point3 ( 1.5, 1.5, 1.5*z)); + landmarks.push_back(Point3 ( 1.5,-1.5, 1.5*z)); + landmarks.push_back(Point3 (-2.0,-2.0, 2*z)); + landmarks.push_back(Point3 (-2.0, 2.0, 2*z)); + landmarks.push_back(Point3 ( 2.0, 2.0, 2*z)); + landmarks.push_back(Point3 ( 2.0,-2.0, 2*z)); + return landmarks ; } -vector genCameraDefaultCalibration() { +static vector genCameraDefaultCalibration() { vector X ; X.push_back(GeneralCamera(Pose3(eye(3),Point3(-baseline/2.0, 0.0, 0.0)))); X.push_back(GeneralCamera(Pose3(eye(3),Point3( baseline/2.0, 0.0, 0.0)))); return X ; } -vector genCameraVariableCalibration() { +static vector genCameraVariableCalibration() { const Cal3_S2 K(640,480,0.01,320,240); vector X ; X.push_back(GeneralCamera(Pose3(eye(3),Point3(-baseline/2.0, 0.0, 0.0)), K)); @@ -144,10 +149,10 @@ vector genCameraVariableCalibration() { return X ; } -shared_ptr getOrdering(const vector& X, const vector& L) { - shared_ptr ordering(new Ordering); - for ( size_t i = 0 ; i < L.size() ; ++i ) ordering->push_back(Symbol('l', i)) ; - for ( size_t i = 0 ; i < X.size() ; ++i ) ordering->push_back(Symbol('x', i)) ; +static boost::shared_ptr getOrdering(const vector& cameras, const vector& landmarks) { + boost::shared_ptr ordering(new Ordering); + for ( size_t i = 0 ; i < landmarks.size() ; ++i ) ordering->push_back(L(i)) ; + for ( size_t i = 0 ; i < cameras.size() ; ++i ) ordering->push_back(X(i)) ; return ordering ; } @@ -155,37 +160,37 @@ shared_ptr getOrdering(const vector& X, const vector L = genPoint3(); - vector X = genCameraDefaultCalibration(); + vector landmarks = genPoint3(); + vector cameras = genCameraDefaultCalibration(); // add measurement with noise Graph graph; - for ( size_t j = 0 ; j < X.size() ; ++j) { - for ( size_t i = 0 ; i < L.size() ; ++i) { - Point2 pt = X[j].project(L[i]) ; + for ( size_t j = 0 ; j < cameras.size() ; ++j) { + for ( size_t i = 0 ; i < landmarks.size() ; ++i) { + Point2 pt = cameras[j].project(landmarks[i]) ; graph.addMeasurement(j, i, pt, sigma1); } } - const size_t nMeasurements = X.size()*L.size() ; + const size_t nMeasurements = cameras.size()*landmarks.size() ; // add initial const double noise = baseline*0.1; Values values; - for ( size_t i = 0 ; i < X.size() ; ++i ) - values.insert(Symbol('x',i), X[i]) ; + for ( size_t i = 0 ; i < cameras.size() ; ++i ) + values.insert(X(i), cameras[i]) ; - for ( size_t i = 0 ; i < L.size() ; ++i ) { - Point3 pt(L[i].x()+noise*getGaussian(), - L[i].y()+noise*getGaussian(), - L[i].z()+noise*getGaussian()); - values.insert(Symbol('l',i), pt) ; + for ( size_t i = 0 ; i < landmarks.size() ; ++i ) { + Point3 pt(landmarks[i].x()+noise*getGaussian(), + landmarks[i].y()+noise*getGaussian(), + landmarks[i].z()+noise*getGaussian()); + values.insert(L(i), pt) ; } - graph.addCameraConstraint(0, X[0]); + graph.addCameraConstraint(0, cameras[0]); // Create an ordering of the variables - Ordering ordering = *getOrdering(X,L); + Ordering ordering = *getOrdering(cameras,landmarks); LevenbergMarquardtOptimizer optimizer(graph, values, ordering); Values final = optimizer.optimize(); EXPECT(optimizer.error() < 0.5 * 1e-5 * nMeasurements); @@ -193,42 +198,42 @@ TEST( GeneralSFMFactor, optimize_defaultK ) { /* ************************************************************************* */ TEST( GeneralSFMFactor, optimize_varK_SingleMeasurementError ) { - vector L = genPoint3(); - vector X = genCameraVariableCalibration(); + vector landmarks = genPoint3(); + vector cameras = genCameraVariableCalibration(); // add measurement with noise Graph graph; - for ( size_t j = 0 ; j < X.size() ; ++j) { - for ( size_t i = 0 ; i < L.size() ; ++i) { - Point2 pt = X[j].project(L[i]) ; + for ( size_t j = 0 ; j < cameras.size() ; ++j) { + for ( size_t i = 0 ; i < landmarks.size() ; ++i) { + Point2 pt = cameras[j].project(landmarks[i]) ; graph.addMeasurement(j, i, pt, sigma1); } } - const size_t nMeasurements = X.size()*L.size() ; + const size_t nMeasurements = cameras.size()*landmarks.size() ; // add initial const double noise = baseline*0.1; Values values; - for ( size_t i = 0 ; i < X.size() ; ++i ) - values.insert(Symbol('x',i), X[i]) ; + for ( size_t i = 0 ; i < cameras.size() ; ++i ) + values.insert(X(i), cameras[i]) ; // add noise only to the first landmark - for ( size_t i = 0 ; i < L.size() ; ++i ) { + for ( size_t i = 0 ; i < landmarks.size() ; ++i ) { if ( i == 0 ) { - Point3 pt(L[i].x()+noise*getGaussian(), - L[i].y()+noise*getGaussian(), - L[i].z()+noise*getGaussian()); - values.insert(Symbol('l',i), pt) ; + Point3 pt(landmarks[i].x()+noise*getGaussian(), + landmarks[i].y()+noise*getGaussian(), + landmarks[i].z()+noise*getGaussian()); + values.insert(L(i), pt) ; } else { - values.insert(Symbol('l',i), L[i]) ; + values.insert(L(i), landmarks[i]) ; } } - graph.addCameraConstraint(0, X[0]); + graph.addCameraConstraint(0, cameras[0]); const double reproj_error = 1e-5; - Ordering ordering = *getOrdering(X,L); + Ordering ordering = *getOrdering(cameras,landmarks); LevenbergMarquardtOptimizer optimizer(graph, values, ordering); Values final = optimizer.optimize(); EXPECT(optimizer.error() < 0.5 * reproj_error * nMeasurements); @@ -237,39 +242,39 @@ TEST( GeneralSFMFactor, optimize_varK_SingleMeasurementError ) { /* ************************************************************************* */ TEST( GeneralSFMFactor, optimize_varK_FixCameras ) { - vector L = genPoint3(); - vector X = genCameraVariableCalibration(); + vector landmarks = genPoint3(); + vector cameras = genCameraVariableCalibration(); // add measurement with noise const double noise = baseline*0.1; Graph graph; - for ( size_t j = 0 ; j < X.size() ; ++j) { - for ( size_t i = 0 ; i < L.size() ; ++i) { - Point2 pt = X[j].project(L[i]) ; + for ( size_t j = 0 ; j < cameras.size() ; ++j) { + for ( size_t i = 0 ; i < landmarks.size() ; ++i) { + Point2 pt = cameras[j].project(landmarks[i]) ; graph.addMeasurement(j, i, pt, sigma1); } } - const size_t nMeasurements = L.size()*X.size(); + const size_t nMeasurements = landmarks.size()*cameras.size(); Values values; - for ( size_t i = 0 ; i < X.size() ; ++i ) - values.insert(Symbol('x',i), X[i]) ; + for ( size_t i = 0 ; i < cameras.size() ; ++i ) + values.insert(X(i), cameras[i]) ; - for ( size_t i = 0 ; i < L.size() ; ++i ) { - Point3 pt(L[i].x()+noise*getGaussian(), - L[i].y()+noise*getGaussian(), - L[i].z()+noise*getGaussian()); - //Point3 pt(L[i].x(), L[i].y(), L[i].z()); - values.insert(Symbol('l',i), pt) ; + for ( size_t i = 0 ; i < landmarks.size() ; ++i ) { + Point3 pt(landmarks[i].x()+noise*getGaussian(), + landmarks[i].y()+noise*getGaussian(), + landmarks[i].z()+noise*getGaussian()); + //Point3 pt(landmarks[i].x(), landmarks[i].y(), landmarks[i].z()); + values.insert(L(i), pt) ; } - for ( size_t i = 0 ; i < X.size() ; ++i ) - graph.addCameraConstraint(i, X[i]); + for ( size_t i = 0 ; i < cameras.size() ; ++i ) + graph.addCameraConstraint(i, cameras[i]); const double reproj_error = 1e-5 ; - Ordering ordering = *getOrdering(X,L); + Ordering ordering = *getOrdering(cameras,landmarks); LevenbergMarquardtOptimizer optimizer(graph, values, ordering); Values final = optimizer.optimize(); EXPECT(optimizer.error() < 0.5 * reproj_error * nMeasurements); @@ -278,29 +283,29 @@ TEST( GeneralSFMFactor, optimize_varK_FixCameras ) { /* ************************************************************************* */ TEST( GeneralSFMFactor, optimize_varK_FixLandmarks ) { - vector L = genPoint3(); - vector X = genCameraVariableCalibration(); + vector landmarks = genPoint3(); + vector cameras = genCameraVariableCalibration(); // add measurement with noise Graph graph; - for ( size_t j = 0 ; j < X.size() ; ++j) { - for ( size_t i = 0 ; i < L.size() ; ++i) { - Point2 pt = X[j].project(L[i]) ; + for ( size_t j = 0 ; j < cameras.size() ; ++j) { + for ( size_t i = 0 ; i < landmarks.size() ; ++i) { + Point2 pt = cameras[j].project(landmarks[i]) ; graph.addMeasurement(j, i, pt, sigma1); } } - const size_t nMeasurements = L.size()*X.size(); + const size_t nMeasurements = landmarks.size()*cameras.size(); Values values; - for ( size_t i = 0 ; i < X.size() ; ++i ) { + for ( size_t i = 0 ; i < cameras.size() ; ++i ) { const double rot_noise = 1e-5, trans_noise = 1e-3, focal_noise = 1, skew_noise = 1e-5; if ( i == 0 ) { - values.insert(Symbol('x',i), X[i]) ; + values.insert(X(i), cameras[i]) ; } else { @@ -311,22 +316,22 @@ TEST( GeneralSFMFactor, optimize_varK_FixLandmarks ) { skew_noise, // s trans_noise, trans_noise // ux, uy ) ; - values.insert(Symbol('x',i), X[i].retract(delta)) ; + values.insert(X(i), cameras[i].retract(delta)) ; } } - for ( size_t i = 0 ; i < L.size() ; ++i ) { - values.insert(Symbol('l',i), L[i]) ; + for ( size_t i = 0 ; i < landmarks.size() ; ++i ) { + values.insert(L(i), landmarks[i]) ; } - // fix X0 and all landmarks, allow only the X[1] to move - graph.addCameraConstraint(0, X[0]); - for ( size_t i = 0 ; i < L.size() ; ++i ) - graph.addPoint3Constraint(i, L[i]); + // fix X0 and all landmarks, allow only the cameras[1] to move + graph.addCameraConstraint(0, cameras[0]); + for ( size_t i = 0 ; i < landmarks.size() ; ++i ) + graph.addPoint3Constraint(i, landmarks[i]); const double reproj_error = 1e-5 ; - Ordering ordering = *getOrdering(X,L); + Ordering ordering = *getOrdering(cameras,landmarks); LevenbergMarquardtOptimizer optimizer(graph, values, ordering); Values final = optimizer.optimize(); EXPECT(optimizer.error() < 0.5 * reproj_error * nMeasurements); @@ -334,43 +339,43 @@ TEST( GeneralSFMFactor, optimize_varK_FixLandmarks ) { /* ************************************************************************* */ TEST( GeneralSFMFactor, optimize_varK_BA ) { - vector L = genPoint3(); - vector X = genCameraVariableCalibration(); + vector landmarks = genPoint3(); + vector cameras = genCameraVariableCalibration(); // add measurement with noise Graph graph; - for ( size_t j = 0 ; j < X.size() ; ++j) { - for ( size_t i = 0 ; i < L.size() ; ++i) { - Point2 pt = X[j].project(L[i]) ; + for ( size_t j = 0 ; j < cameras.size() ; ++j) { + for ( size_t i = 0 ; i < landmarks.size() ; ++i) { + Point2 pt = cameras[j].project(landmarks[i]) ; graph.addMeasurement(j, i, pt, sigma1); } } - const size_t nMeasurements = X.size()*L.size() ; + const size_t nMeasurements = cameras.size()*landmarks.size() ; // add initial const double noise = baseline*0.1; Values values; - for ( size_t i = 0 ; i < X.size() ; ++i ) - values.insert(Symbol('x',i), X[i]) ; + for ( size_t i = 0 ; i < cameras.size() ; ++i ) + values.insert(X(i), cameras[i]) ; // add noise only to the first landmark - for ( size_t i = 0 ; i < L.size() ; ++i ) { - Point3 pt(L[i].x()+noise*getGaussian(), - L[i].y()+noise*getGaussian(), - L[i].z()+noise*getGaussian()); - values.insert(Symbol('l',i), pt) ; + for ( size_t i = 0 ; i < landmarks.size() ; ++i ) { + Point3 pt(landmarks[i].x()+noise*getGaussian(), + landmarks[i].y()+noise*getGaussian(), + landmarks[i].z()+noise*getGaussian()); + values.insert(L(i), pt) ; } // Constrain position of system with the first camera constrained to the origin - graph.addCameraConstraint(0, X[0]); + graph.addCameraConstraint(0, cameras[0]); // Constrain the scale of the problem with a soft range factor of 1m between the cameras - graph.add(RangeFactor(Symbol('x',0), Symbol('x',1), 2.0, sharedSigma(1, 10.0))); + graph.add(RangeFactor(X(0), X(1), 2.0, noiseModel::Isotropic::Sigma(1, 10.0))); const double reproj_error = 1e-5 ; - Ordering ordering = *getOrdering(X,L); + Ordering ordering = *getOrdering(cameras,landmarks); LevenbergMarquardtOptimizer optimizer(graph, values, ordering); Values final = optimizer.optimize(); EXPECT(optimizer.error() < 0.5 * reproj_error * nMeasurements); @@ -381,17 +386,17 @@ TEST(GeneralSFMFactor, GeneralCameraPoseRange) { // Tests range factor between a GeneralCamera and a Pose3 Graph graph; graph.addCameraConstraint(0, GeneralCamera()); - graph.add(RangeFactor(Symbol('x',0), Symbol('x',1), 2.0, sharedSigma(1, 1.0))); - graph.add(PriorFactor(Symbol('x',1), Pose3(Rot3(), Point3(1.0, 0.0, 0.0)), sharedSigma(6, 1.0))); + graph.add(RangeFactor(X(0), X(1), 2.0, noiseModel::Isotropic::Sigma(1, 1.0))); + graph.add(PriorFactor(X(1), Pose3(Rot3(), Point3(1.0, 0.0, 0.0)), noiseModel::Isotropic::Sigma(6, 1.0))); Values init; - init.insert(Symbol('x',0), GeneralCamera()); - init.insert(Symbol('x',1), Pose3(Rot3(), Point3(1.0,1.0,1.0))); + init.insert(X(0), GeneralCamera()); + init.insert(X(1), Pose3(Rot3(), Point3(1.0,1.0,1.0))); // The optimal value between the 2m range factor and 1m prior is 1.5m Values expected; - expected.insert(Symbol('x',0), GeneralCamera()); - expected.insert(Symbol('x',1), Pose3(Rot3(), Point3(1.5,0.0,0.0))); + expected.insert(X(0), GeneralCamera()); + expected.insert(X(1), Pose3(Rot3(), Point3(1.5,0.0,0.0))); LevenbergMarquardtParams params; params.absoluteErrorTol = 1e-9; @@ -405,17 +410,17 @@ TEST(GeneralSFMFactor, GeneralCameraPoseRange) { TEST(GeneralSFMFactor, CalibratedCameraPoseRange) { // Tests range factor between a CalibratedCamera and a Pose3 NonlinearFactorGraph graph; - graph.add(PriorFactor(Symbol('x',0), CalibratedCamera(), sharedSigma(6, 1.0))); - graph.add(RangeFactor(Symbol('x',0), Symbol('x',1), 2.0, sharedSigma(1, 1.0))); - graph.add(PriorFactor(Symbol('x',1), Pose3(Rot3(), Point3(1.0, 0.0, 0.0)), sharedSigma(6, 1.0))); + graph.add(PriorFactor(X(0), CalibratedCamera(), noiseModel::Isotropic::Sigma(6, 1.0))); + graph.add(RangeFactor(X(0), X(1), 2.0, noiseModel::Isotropic::Sigma(1, 1.0))); + graph.add(PriorFactor(X(1), Pose3(Rot3(), Point3(1.0, 0.0, 0.0)), noiseModel::Isotropic::Sigma(6, 1.0))); Values init; - init.insert(Symbol('x',0), CalibratedCamera()); - init.insert(Symbol('x',1), Pose3(Rot3(), Point3(1.0,1.0,1.0))); + init.insert(X(0), CalibratedCamera()); + init.insert(X(1), Pose3(Rot3(), Point3(1.0,1.0,1.0))); Values expected; - expected.insert(Symbol('x',0), CalibratedCamera(Pose3(Rot3(), Point3(-0.333333333333, 0, 0)))); - expected.insert(Symbol('x',1), Pose3(Rot3(), Point3(1.333333333333, 0, 0))); + expected.insert(X(0), CalibratedCamera(Pose3(Rot3(), Point3(-0.333333333333, 0, 0)))); + expected.insert(X(1), Pose3(Rot3(), Point3(1.333333333333, 0, 0))); LevenbergMarquardtParams params; params.absoluteErrorTol = 1e-9; diff --git a/gtsam/slam/tests/testGeneralSFMFactor_Cal3Bundler.cpp b/gtsam/slam/tests/testGeneralSFMFactor_Cal3Bundler.cpp index 76cf7d180..21f5f2008 100644 --- a/gtsam/slam/tests/testGeneralSFMFactor_Cal3Bundler.cpp +++ b/gtsam/slam/tests/testGeneralSFMFactor_Cal3Bundler.cpp @@ -10,32 +10,38 @@ * -------------------------------------------------------------------------- */ /** - * @file testGeneralSFMFactor.cpp + * @file testGeneralSFMFactor_Cal3Bundler.cpp * @date Dec 27, 2010 * @author nikai * @brief unit tests for GeneralSFMFactor */ -#include -#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include #include #include -using namespace boost; -#include -#include -#include -#include -#include -#include -#include -#include -#include +#include +#include using namespace std; using namespace gtsam; +// Convenience for named keys +using symbol_shorthand::X; +using symbol_shorthand::L; + typedef PinholeCamera GeneralCamera; typedef GeneralSFMFactor Projection; typedef NonlinearEquality CameraConstraint; @@ -45,22 +51,22 @@ typedef NonlinearEquality Point3Constraint; class Graph: public NonlinearFactorGraph { public: void addMeasurement(const int& i, const int& j, const Point2& z, const SharedNoiseModel& model) { - push_back(boost::make_shared(z, model, Symbol('x',i), Symbol('l',j))); + push_back(boost::make_shared(z, model, X(i), L(j))); } void addCameraConstraint(int j, const GeneralCamera& p) { - boost::shared_ptr factor(new CameraConstraint(Symbol('x', j), p)); + boost::shared_ptr factor(new CameraConstraint(X(j), p)); push_back(factor); } void addPoint3Constraint(int j, const Point3& p) { - boost::shared_ptr factor(new Point3Constraint(Symbol('l', j), p)); + boost::shared_ptr factor(new Point3Constraint(L(j), p)); push_back(factor); } }; -double getGaussian() +static double getGaussian() { double S,V1,V2; // Use Box-Muller method to create gauss noise from uniform noise @@ -75,10 +81,10 @@ double getGaussian() return sqrt(-2.0f * (double)log(S) / S) * V1; } -const SharedNoiseModel sigma1(noiseModel::Unit::Create(1)); +static const SharedNoiseModel sigma1(noiseModel::Unit::Create(1)); /* ************************************************************************* */ -TEST( GeneralSFMFactor, equals ) +TEST( GeneralSFMFactor_Cal3Bundler, equals ) { // Create two identical factors and make sure they're equal Vector z = Vector_(2,323.,240.); @@ -94,18 +100,18 @@ TEST( GeneralSFMFactor, equals ) } /* ************************************************************************* */ -TEST( GeneralSFMFactor, error ) { +TEST( GeneralSFMFactor_Cal3Bundler, error ) { Point2 z(3.,0.); const SharedNoiseModel sigma(noiseModel::Unit::Create(1)); boost::shared_ptr - factor(new Projection(z, sigma, Symbol('x',1), Symbol('l',1))); + factor(new Projection(z, sigma, X(1), L(1))); // For the following configuration, the factor predicts 320,240 Values values; Rot3 R; Point3 t1(0,0,-6); Pose3 x1(R,t1); - values.insert(Symbol('x',1), GeneralCamera(x1)); - Point3 l1; values.insert(Symbol('l',1), l1); + values.insert(X(1), GeneralCamera(x1)); + Point3 l1; values.insert(L(1), l1); EXPECT(assert_equal(Vector_(2, -3.0, 0.0), factor->unwhitenedError(values))); } @@ -113,193 +119,193 @@ TEST( GeneralSFMFactor, error ) { static const double baseline = 5.0 ; /* ************************************************************************* */ -vector genPoint3() { +static vector genPoint3() { const double z = 5; - vector L ; - L.push_back(Point3 (-1.0,-1.0, z)); - L.push_back(Point3 (-1.0, 1.0, z)); - L.push_back(Point3 ( 1.0, 1.0, z)); - L.push_back(Point3 ( 1.0,-1.0, z)); - L.push_back(Point3 (-1.5,-1.5, 1.5*z)); - L.push_back(Point3 (-1.5, 1.5, 1.5*z)); - L.push_back(Point3 ( 1.5, 1.5, 1.5*z)); - L.push_back(Point3 ( 1.5,-1.5, 1.5*z)); - L.push_back(Point3 (-2.0,-2.0, 2*z)); - L.push_back(Point3 (-2.0, 2.0, 2*z)); - L.push_back(Point3 ( 2.0, 2.0, 2*z)); - L.push_back(Point3 ( 2.0,-2.0, 2*z)); - return L ; + vector landmarks ; + landmarks.push_back(Point3 (-1.0,-1.0, z)); + landmarks.push_back(Point3 (-1.0, 1.0, z)); + landmarks.push_back(Point3 ( 1.0, 1.0, z)); + landmarks.push_back(Point3 ( 1.0,-1.0, z)); + landmarks.push_back(Point3 (-1.5,-1.5, 1.5*z)); + landmarks.push_back(Point3 (-1.5, 1.5, 1.5*z)); + landmarks.push_back(Point3 ( 1.5, 1.5, 1.5*z)); + landmarks.push_back(Point3 ( 1.5,-1.5, 1.5*z)); + landmarks.push_back(Point3 (-2.0,-2.0, 2*z)); + landmarks.push_back(Point3 (-2.0, 2.0, 2*z)); + landmarks.push_back(Point3 ( 2.0, 2.0, 2*z)); + landmarks.push_back(Point3 ( 2.0,-2.0, 2*z)); + return landmarks ; } -vector genCameraDefaultCalibration() { - vector X ; - X.push_back(GeneralCamera(Pose3(eye(3),Point3(-baseline/2.0, 0.0, 0.0)))); - X.push_back(GeneralCamera(Pose3(eye(3),Point3( baseline/2.0, 0.0, 0.0)))); - return X ; +static vector genCameraDefaultCalibration() { + vector cameras ; + cameras.push_back(GeneralCamera(Pose3(eye(3),Point3(-baseline/2.0, 0.0, 0.0)))); + cameras.push_back(GeneralCamera(Pose3(eye(3),Point3( baseline/2.0, 0.0, 0.0)))); + return cameras ; } -vector genCameraVariableCalibration() { +static vector genCameraVariableCalibration() { const Cal3Bundler K(500,1e-3,1e-3); - vector X ; - X.push_back(GeneralCamera(Pose3(eye(3),Point3(-baseline/2.0, 0.0, 0.0)), K)); - X.push_back(GeneralCamera(Pose3(eye(3),Point3( baseline/2.0, 0.0, 0.0)), K)); - return X ; + vector cameras ; + cameras.push_back(GeneralCamera(Pose3(eye(3),Point3(-baseline/2.0, 0.0, 0.0)), K)); + cameras.push_back(GeneralCamera(Pose3(eye(3),Point3( baseline/2.0, 0.0, 0.0)), K)); + return cameras ; } -shared_ptr getOrdering(const vector& X, const vector& L) { - shared_ptr ordering(new Ordering); - for ( size_t i = 0 ; i < L.size() ; ++i ) ordering->push_back(Symbol('l', i)) ; - for ( size_t i = 0 ; i < X.size() ; ++i ) ordering->push_back(Symbol('x', i)) ; +static boost::shared_ptr getOrdering(const std::vector& cameras, const std::vector& landmarks) { + boost::shared_ptr ordering(new Ordering); + for ( size_t i = 0 ; i < landmarks.size() ; ++i ) ordering->push_back(L(i)) ; + for ( size_t i = 0 ; i < cameras.size() ; ++i ) ordering->push_back(X(i)) ; return ordering ; } /* ************************************************************************* */ -TEST( GeneralSFMFactor, optimize_defaultK ) { +TEST( GeneralSFMFactor_Cal3Bundler, optimize_defaultK ) { - vector L = genPoint3(); - vector X = genCameraDefaultCalibration(); + vector landmarks = genPoint3(); + vector cameras = genCameraDefaultCalibration(); // add measurement with noise Graph graph; - for ( size_t j = 0 ; j < X.size() ; ++j) { - for ( size_t i = 0 ; i < L.size() ; ++i) { - Point2 pt = X[j].project(L[i]) ; + for ( size_t j = 0 ; j < cameras.size() ; ++j) { + for ( size_t i = 0 ; i < landmarks.size() ; ++i) { + Point2 pt = cameras[j].project(landmarks[i]) ; graph.addMeasurement(j, i, pt, sigma1); } } - const size_t nMeasurements = X.size()*L.size() ; + const size_t nMeasurements = cameras.size()*landmarks.size() ; // add initial const double noise = baseline*0.1; Values values; - for ( size_t i = 0 ; i < X.size() ; ++i ) - values.insert(Symbol('x',i), X[i]) ; + for ( size_t i = 0 ; i < cameras.size() ; ++i ) + values.insert(X(i), cameras[i]) ; - for ( size_t i = 0 ; i < L.size() ; ++i ) { - Point3 pt(L[i].x()+noise*getGaussian(), - L[i].y()+noise*getGaussian(), - L[i].z()+noise*getGaussian()); - values.insert(Symbol('l',i), pt) ; + for ( size_t i = 0 ; i < landmarks.size() ; ++i ) { + Point3 pt(landmarks[i].x()+noise*getGaussian(), + landmarks[i].y()+noise*getGaussian(), + landmarks[i].z()+noise*getGaussian()); + values.insert(L(i), pt) ; } - graph.addCameraConstraint(0, X[0]); + graph.addCameraConstraint(0, cameras[0]); // Create an ordering of the variables - Ordering ordering = *getOrdering(X,L); + Ordering ordering = *getOrdering(cameras,landmarks); LevenbergMarquardtOptimizer optimizer(graph, values, ordering); Values final = optimizer.optimize(); EXPECT(optimizer.error() < 0.5 * 1e-5 * nMeasurements); } /* ************************************************************************* */ -TEST( GeneralSFMFactor, optimize_varK_SingleMeasurementError ) { - vector L = genPoint3(); - vector X = genCameraVariableCalibration(); +TEST( GeneralSFMFactor_Cal3Bundler, optimize_varK_SingleMeasurementError ) { + vector landmarks = genPoint3(); + vector cameras = genCameraVariableCalibration(); // add measurement with noise Graph graph; - for ( size_t j = 0 ; j < X.size() ; ++j) { - for ( size_t i = 0 ; i < L.size() ; ++i) { - Point2 pt = X[j].project(L[i]) ; + for ( size_t j = 0 ; j < cameras.size() ; ++j) { + for ( size_t i = 0 ; i < landmarks.size() ; ++i) { + Point2 pt = cameras[j].project(landmarks[i]) ; graph.addMeasurement(j, i, pt, sigma1); } } - const size_t nMeasurements = X.size()*L.size() ; + const size_t nMeasurements = cameras.size()*landmarks.size() ; // add initial const double noise = baseline*0.1; Values values; - for ( size_t i = 0 ; i < X.size() ; ++i ) - values.insert(Symbol('x',i), X[i]) ; + for ( size_t i = 0 ; i < cameras.size() ; ++i ) + values.insert(X(i), cameras[i]) ; // add noise only to the first landmark - for ( size_t i = 0 ; i < L.size() ; ++i ) { + for ( size_t i = 0 ; i < landmarks.size() ; ++i ) { if ( i == 0 ) { - Point3 pt(L[i].x()+noise*getGaussian(), - L[i].y()+noise*getGaussian(), - L[i].z()+noise*getGaussian()); - values.insert(Symbol('l',i), pt) ; + Point3 pt(landmarks[i].x()+noise*getGaussian(), + landmarks[i].y()+noise*getGaussian(), + landmarks[i].z()+noise*getGaussian()); + values.insert(L(i), pt) ; } else { - values.insert(Symbol('l',i), L[i]) ; + values.insert(L(i), landmarks[i]) ; } } - graph.addCameraConstraint(0, X[0]); + graph.addCameraConstraint(0, cameras[0]); const double reproj_error = 1e-5; - Ordering ordering = *getOrdering(X,L); + Ordering ordering = *getOrdering(cameras,landmarks); LevenbergMarquardtOptimizer optimizer(graph, values, ordering); Values final = optimizer.optimize(); EXPECT(optimizer.error() < 0.5 * reproj_error * nMeasurements); } /* ************************************************************************* */ -TEST( GeneralSFMFactor, optimize_varK_FixCameras ) { +TEST( GeneralSFMFactor_Cal3Bundler, optimize_varK_FixCameras ) { - vector L = genPoint3(); - vector X = genCameraVariableCalibration(); + vector landmarks = genPoint3(); + vector cameras = genCameraVariableCalibration(); // add measurement with noise const double noise = baseline*0.1; Graph graph; - for ( size_t j = 0 ; j < X.size() ; ++j) { - for ( size_t i = 0 ; i < L.size() ; ++i) { - Point2 pt = X[j].project(L[i]) ; + for ( size_t j = 0 ; j < cameras.size() ; ++j) { + for ( size_t i = 0 ; i < landmarks.size() ; ++i) { + Point2 pt = cameras[j].project(landmarks[i]) ; graph.addMeasurement(j, i, pt, sigma1); } } - const size_t nMeasurements = L.size()*X.size(); + const size_t nMeasurements = landmarks.size()*cameras.size(); Values values; - for ( size_t i = 0 ; i < X.size() ; ++i ) - values.insert(Symbol('x',i), X[i]) ; + for ( size_t i = 0 ; i < cameras.size() ; ++i ) + values.insert(X(i), cameras[i]) ; - for ( size_t i = 0 ; i < L.size() ; ++i ) { - Point3 pt(L[i].x()+noise*getGaussian(), - L[i].y()+noise*getGaussian(), - L[i].z()+noise*getGaussian()); - //Point3 pt(L[i].x(), L[i].y(), L[i].z()); - values.insert(Symbol('l',i), pt) ; + for ( size_t i = 0 ; i < landmarks.size() ; ++i ) { + Point3 pt(landmarks[i].x()+noise*getGaussian(), + landmarks[i].y()+noise*getGaussian(), + landmarks[i].z()+noise*getGaussian()); + //Point3 pt(landmarks[i].x(), landmarks[i].y(), landmarks[i].z()); + values.insert(L(i), pt) ; } - for ( size_t i = 0 ; i < X.size() ; ++i ) - graph.addCameraConstraint(i, X[i]); + for ( size_t i = 0 ; i < cameras.size() ; ++i ) + graph.addCameraConstraint(i, cameras[i]); const double reproj_error = 1e-5 ; - Ordering ordering = *getOrdering(X,L); + Ordering ordering = *getOrdering(cameras,landmarks); LevenbergMarquardtOptimizer optimizer(graph, values, ordering); Values final = optimizer.optimize(); EXPECT(optimizer.error() < 0.5 * reproj_error * nMeasurements); } /* ************************************************************************* */ -TEST( GeneralSFMFactor, optimize_varK_FixLandmarks ) { +TEST( GeneralSFMFactor_Cal3Bundler, optimize_varK_FixLandmarks ) { - vector L = genPoint3(); - vector X = genCameraVariableCalibration(); + vector landmarks = genPoint3(); + vector cameras = genCameraVariableCalibration(); // add measurement with noise Graph graph; - for ( size_t j = 0 ; j < X.size() ; ++j) { - for ( size_t i = 0 ; i < L.size() ; ++i) { - Point2 pt = X[j].project(L[i]) ; + for ( size_t j = 0 ; j < cameras.size() ; ++j) { + for ( size_t i = 0 ; i < landmarks.size() ; ++i) { + Point2 pt = cameras[j].project(landmarks[i]) ; graph.addMeasurement(j, i, pt, sigma1); } } - const size_t nMeasurements = L.size()*X.size(); + const size_t nMeasurements = landmarks.size()*cameras.size(); Values values; - for ( size_t i = 0 ; i < X.size() ; ++i ) { + for ( size_t i = 0 ; i < cameras.size() ; ++i ) { const double rot_noise = 1e-5, trans_noise = 1e-3, focal_noise = 1, distort_noise = 1e-3; if ( i == 0 ) { - values.insert(Symbol('x',i), X[i]) ; + values.insert(X(i), cameras[i]) ; } else { @@ -308,66 +314,66 @@ TEST( GeneralSFMFactor, optimize_varK_FixLandmarks ) { trans_noise, trans_noise, trans_noise, // translation focal_noise, distort_noise, distort_noise // f, k1, k2 ) ; - values.insert(Symbol('x',i), X[i].retract(delta)) ; + values.insert(X(i), cameras[i].retract(delta)) ; } } - for ( size_t i = 0 ; i < L.size() ; ++i ) { - values.insert(Symbol('l',i), L[i]) ; + for ( size_t i = 0 ; i < landmarks.size() ; ++i ) { + values.insert(L(i), landmarks[i]) ; } - // fix X0 and all landmarks, allow only the X[1] to move - graph.addCameraConstraint(0, X[0]); - for ( size_t i = 0 ; i < L.size() ; ++i ) - graph.addPoint3Constraint(i, L[i]); + // fix X0 and all landmarks, allow only the cameras[1] to move + graph.addCameraConstraint(0, cameras[0]); + for ( size_t i = 0 ; i < landmarks.size() ; ++i ) + graph.addPoint3Constraint(i, landmarks[i]); const double reproj_error = 1e-5 ; - Ordering ordering = *getOrdering(X,L); + Ordering ordering = *getOrdering(cameras,landmarks); LevenbergMarquardtOptimizer optimizer(graph, values, ordering); Values final = optimizer.optimize(); EXPECT(optimizer.error() < 0.5 * reproj_error * nMeasurements); } /* ************************************************************************* */ -TEST( GeneralSFMFactor, optimize_varK_BA ) { - vector L = genPoint3(); - vector X = genCameraVariableCalibration(); +TEST( GeneralSFMFactor_Cal3Bundler, optimize_varK_BA ) { + vector landmarks = genPoint3(); + vector cameras = genCameraVariableCalibration(); // add measurement with noise Graph graph; - for ( size_t j = 0 ; j < X.size() ; ++j) { - for ( size_t i = 0 ; i < L.size() ; ++i) { - Point2 pt = X[j].project(L[i]) ; + for ( size_t j = 0 ; j < cameras.size() ; ++j) { + for ( size_t i = 0 ; i < landmarks.size() ; ++i) { + Point2 pt = cameras[j].project(landmarks[i]) ; graph.addMeasurement(j, i, pt, sigma1); } } - const size_t nMeasurements = X.size()*L.size() ; + const size_t nMeasurements = cameras.size()*landmarks.size() ; // add initial const double noise = baseline*0.1; Values values; - for ( size_t i = 0 ; i < X.size() ; ++i ) - values.insert(Symbol('x',i), X[i]) ; + for ( size_t i = 0 ; i < cameras.size() ; ++i ) + values.insert(X(i), cameras[i]) ; // add noise only to the first landmark - for ( size_t i = 0 ; i < L.size() ; ++i ) { - Point3 pt(L[i].x()+noise*getGaussian(), - L[i].y()+noise*getGaussian(), - L[i].z()+noise*getGaussian()); - values.insert(Symbol('l',i), pt) ; + for ( size_t i = 0 ; i < landmarks.size() ; ++i ) { + Point3 pt(landmarks[i].x()+noise*getGaussian(), + landmarks[i].y()+noise*getGaussian(), + landmarks[i].z()+noise*getGaussian()); + values.insert(L(i), pt) ; } // Constrain position of system with the first camera constrained to the origin - graph.addCameraConstraint(0, X[0]); + graph.addCameraConstraint(0, cameras[0]); // Constrain the scale of the problem with a soft range factor of 1m between the cameras - graph.add(RangeFactor(Symbol('x',0), Symbol('x',1), 2.0, sharedSigma(1, 10.0))); + graph.add(RangeFactor(X(0), X(1), 2.0, noiseModel::Isotropic::Sigma(1, 10.0))); const double reproj_error = 1e-5 ; - Ordering ordering = *getOrdering(X,L); + Ordering ordering = *getOrdering(cameras,landmarks); LevenbergMarquardtOptimizer optimizer(graph, values, ordering); Values final = optimizer.optimize(); EXPECT(optimizer.error() < 0.5 * reproj_error * nMeasurements); diff --git a/gtsam/slam/tests/testPlanarSLAM.cpp b/gtsam/slam/tests/testPlanarSLAM.cpp deleted file mode 100644 index b32bf9a9c..000000000 --- a/gtsam/slam/tests/testPlanarSLAM.cpp +++ /dev/null @@ -1,189 +0,0 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) - - * See LICENSE for the license information - - * -------------------------------------------------------------------------- */ - -/** - * @file testPlanarSLAM.cpp - * @author Frank Dellaert - **/ - -#include -#include - -#include -#include -#include - -using namespace std; -using namespace gtsam; -using namespace planarSLAM; - -// some shared test values -static Pose2 x1, x2(1, 1, 0), x3(1, 1, M_PI_4); -static Point2 l1(1, 0), l2(1, 1), l3(2, 2), l4(1, 3); - -SharedNoiseModel - sigma(noiseModel::Isotropic::Sigma(1,0.1)), - sigma2(noiseModel::Isotropic::Sigma(2,0.1)), - I3(noiseModel::Unit::Create(3)); - -/* ************************************************************************* */ -TEST( planarSLAM, PriorFactor_equals ) -{ - planarSLAM::Prior factor1(PoseKey(2), x1, I3), factor2(PoseKey(2), x2, I3); - EXPECT(assert_equal(factor1, factor1, 1e-5)); - EXPECT(assert_equal(factor2, factor2, 1e-5)); - EXPECT(assert_inequal(factor1, factor2, 1e-5)); -} - -/* ************************************************************************* */ -TEST( planarSLAM, BearingFactor ) -{ - // Create factor - Rot2 z = Rot2::fromAngle(M_PI_4 + 0.1); // h(x) - z = -0.1 - planarSLAM::Bearing factor(PoseKey(2), PointKey(3), z, sigma); - - // create config - planarSLAM::Values c; - c.insert(PoseKey(2), x2); - c.insert(PointKey(3), l3); - - // Check error - Vector actual = factor.unwhitenedError(c); - EXPECT(assert_equal(Vector_(1,-0.1),actual)); -} - -/* ************************************************************************* */ -TEST( planarSLAM, BearingFactor_equals ) -{ - planarSLAM::Bearing - factor1(PoseKey(2), PointKey(3), Rot2::fromAngle(0.1), sigma), - factor2(PoseKey(2), PointKey(3), Rot2::fromAngle(2.3), sigma); - EXPECT(assert_equal(factor1, factor1, 1e-5)); - EXPECT(assert_equal(factor2, factor2, 1e-5)); - EXPECT(assert_inequal(factor1, factor2, 1e-5)); -} - -/* ************************************************************************* */ -TEST( planarSLAM, RangeFactor ) -{ - // Create factor - double z(sqrt(2) - 0.22); // h(x) - z = 0.22 - planarSLAM::Range factor(PoseKey(2), PointKey(3), z, sigma); - - // create config - planarSLAM::Values c; - c.insert(PoseKey(2), x2); - c.insert(PointKey(3), l3); - - // Check error - Vector actual = factor.unwhitenedError(c); - EXPECT(assert_equal(Vector_(1,0.22),actual)); -} - -/* ************************************************************************* */ -TEST( planarSLAM, RangeFactor_equals ) -{ - planarSLAM::Range factor1(PoseKey(2), PointKey(3), 1.2, sigma), factor2(PoseKey(2), PointKey(3), 7.2, sigma); - EXPECT(assert_equal(factor1, factor1, 1e-5)); - EXPECT(assert_equal(factor2, factor2, 1e-5)); - EXPECT(assert_inequal(factor1, factor2, 1e-5)); -} - -/* ************************************************************************* */ -TEST( planarSLAM, BearingRangeFactor ) -{ - // Create factor - Rot2 r = Rot2::fromAngle(M_PI_4 + 0.1); // h(x) - z = -0.1 - double b(sqrt(2) - 0.22); // h(x) - z = 0.22 - planarSLAM::BearingRange factor(PoseKey(2), PointKey(3), r, b, sigma2); - - // create config - planarSLAM::Values c; - c.insert(PoseKey(2), x2); - c.insert(PointKey(3), l3); - - // Check error - Vector actual = factor.unwhitenedError(c); - EXPECT(assert_equal(Vector_(2,-0.1, 0.22),actual)); -} - -/* ************************************************************************* */ -TEST( planarSLAM, BearingRangeFactor_equals ) -{ - planarSLAM::BearingRange - factor1(PoseKey(2), PointKey(3), Rot2::fromAngle(0.1), 7.3, sigma2), - factor2(PoseKey(2), PointKey(3), Rot2::fromAngle(3), 2.0, sigma2); - EXPECT(assert_equal(factor1, factor1, 1e-5)); - EXPECT(assert_equal(factor2, factor2, 1e-5)); - EXPECT(assert_inequal(factor1, factor2, 1e-5)); -} - -/* ************************************************************************* */ -TEST( planarSLAM, BearingRangeFactor_poses ) -{ - typedef BearingRangeFactor PoseBearingRange; - PoseBearingRange actual(PoseKey(2), PoseKey(3), Rot2::fromDegrees(60.0), 12.3, sigma2); -} - -/* ************************************************************************* */ -TEST( planarSLAM, PoseConstraint_equals ) -{ - planarSLAM::Constraint factor1(PoseKey(2), x2), factor2(PoseKey(2), x3); - EXPECT(assert_equal(factor1, factor1, 1e-5)); - EXPECT(assert_equal(factor2, factor2, 1e-5)); - EXPECT(assert_inequal(factor1, factor2, 1e-5)); -} - -/* ************************************************************************* */ -TEST( planarSLAM, constructor ) -{ - // create config - planarSLAM::Values c; - c.insert(PoseKey(2), x2); - c.insert(PoseKey(3), x3); - c.insert(PointKey(3), l3); - - // create graph - planarSLAM::Graph G; - - // Add pose constraint - G.addPoseConstraint(2, x2); // make it feasible :-) - - // Add odometry - G.addOdometry(2, 3, Pose2(0, 0, M_PI_4), I3); - - // Create bearing factor - Rot2 z1 = Rot2::fromAngle(M_PI_4 + 0.1); // h(x) - z = -0.1 - G.addBearing(2, 3, z1, sigma); - - // Create range factor - double z2(sqrt(2) - 0.22); // h(x) - z = 0.22 - G.addRange(2, 3, z2, sigma); - - Vector expected0 = Vector_(3, 0.0, 0.0, 0.0); - Vector expected1 = Vector_(3, 0.0, 0.0, 0.0); - Vector expected2 = Vector_(1, -0.1); - Vector expected3 = Vector_(1, 0.22); - // Get NoiseModelFactors - FactorGraph GNM = - *G.dynamicCastFactors >(); - EXPECT(assert_equal(expected0, GNM[0]->unwhitenedError(c))); - EXPECT(assert_equal(expected1, GNM[1]->unwhitenedError(c))); - EXPECT(assert_equal(expected2, GNM[2]->unwhitenedError(c))); - EXPECT(assert_equal(expected3, GNM[3]->unwhitenedError(c))); -} - -/* ************************************************************************* */ -int main() { - TestResult tr; - return TestRegistry::runAllTests(tr); -} -/* ************************************************************************* */ diff --git a/gtsam/slam/tests/testPose2SLAM.cpp b/gtsam/slam/tests/testPose2SLAM.cpp deleted file mode 100644 index 22c02ab52..000000000 --- a/gtsam/slam/tests/testPose2SLAM.cpp +++ /dev/null @@ -1,561 +0,0 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) - - * See LICENSE for the license information - - * -------------------------------------------------------------------------- */ - -/** - * @file testPose2SLAM.cpp - * @author Frank Dellaert, Viorela Ila - **/ - -#include -#include -#include -#include -using namespace gtsam; - -#include - -#include -#include -using namespace boost; -using namespace boost::assign; - -#include -using namespace std; - -typedef pose2SLAM::Odometry Pose2Factor; -using pose2SLAM::PoseKey; - -// common measurement covariance -static double sx=0.5, sy=0.5,st=0.1; -static noiseModel::Gaussian::shared_ptr covariance( - noiseModel::Gaussian::Covariance(Matrix_(3, 3, - sx*sx, 0.0, 0.0, - 0.0, sy*sy, 0.0, - 0.0, 0.0, st*st - ))); -//static noiseModel::Gaussian::shared_ptr I3(noiseModel::Unit::Create(3)); - -const Key kx0 = Symbol('x',0), kx1 = Symbol('x',1), kx2 = Symbol('x',2), kx3 = Symbol('x',3), kx4 = Symbol('x',4), kx5 = Symbol('x',5), kl1 = Symbol('l',1); - -/* ************************************************************************* */ -// Test constraint, small displacement -Vector f1(const Pose2& pose1, const Pose2& pose2) { - Pose2 z(2.1130913087, 0.468461064817, 0.436332312999); - Pose2Factor constraint(PoseKey(1), PoseKey(2), z, covariance); - return constraint.evaluateError(pose1, pose2); -} - -TEST( Pose2SLAM, constraint1 ) -{ - // create a factor between unknown poses p1 and p2 - Pose2 pose1, pose2(2.1130913087, 0.468461064817, 0.436332312999); - Pose2Factor constraint(PoseKey(1), PoseKey(2), pose2, covariance); - Matrix H1, H2; - Vector actual = constraint.evaluateError(pose1, pose2, H1, H2); - - Matrix numericalH1 = numericalDerivative21(&f1 , pose1, pose2); - EXPECT(assert_equal(numericalH1,H1,5e-3)); - - Matrix numericalH2 = numericalDerivative22(&f1 , pose1, pose2); - EXPECT(assert_equal(numericalH2,H2)); -} - -/* ************************************************************************* */ -// Test constraint, large displacement -Vector f2(const Pose2& pose1, const Pose2& pose2) { - Pose2 z(2,2,M_PI_2); - Pose2Factor constraint(PoseKey(1), PoseKey(2), z, covariance); - return constraint.evaluateError(pose1, pose2); -} - -TEST( Pose2SLAM, constraint2 ) -{ - // create a factor between unknown poses p1 and p2 - Pose2 pose1, pose2(2,2,M_PI_2); - Pose2Factor constraint(PoseKey(1), PoseKey(2), pose2, covariance); - Matrix H1, H2; - Vector actual = constraint.evaluateError(pose1, pose2, H1, H2); - - Matrix numericalH1 = numericalDerivative21(&f2 , pose1, pose2); - EXPECT(assert_equal(numericalH1,H1,5e-3)); - - Matrix numericalH2 = numericalDerivative22(&f2 , pose1, pose2); - EXPECT(assert_equal(numericalH2,H2)); -} - -/* ************************************************************************* */ -TEST( Pose2SLAM, constructor ) -{ - // create a factor between unknown poses p1 and p2 - Pose2 measured(2,2,M_PI_2); - pose2SLAM::Graph graph; - graph.addOdometry(1,2,measured, covariance); - // get the size of the graph - size_t actual = graph.size(); - // verify - size_t expected = 1; - CHECK(actual == expected); -} - -/* ************************************************************************* */ -TEST( Pose2SLAM, linearization ) -{ - // create a factor between unknown poses p1 and p2 - Pose2 measured(2,2,M_PI_2); - Pose2Factor constraint(PoseKey(1), PoseKey(2), measured, covariance); - pose2SLAM::Graph graph; - graph.addOdometry(1,2,measured, covariance); - - // Choose a linearization point - Pose2 p1(1.1,2,M_PI_2); // robot at (1.1,2) looking towards y (ground truth is at 1,2, see testPose2) - Pose2 p2(-1,4.1,M_PI); // robot at (-1,4) looking at negative (ground truth is at 4.1,2) - pose2SLAM::Values config; - config.insert(pose2SLAM::PoseKey(1),p1); - config.insert(pose2SLAM::PoseKey(2),p2); - // Linearize - Ordering ordering(*config.orderingArbitrary()); - boost::shared_ptr > lfg_linearized = graph.linearize(config, ordering); - //lfg_linearized->print("lfg_actual"); - - // the expected linear factor - FactorGraph lfg_expected; - Matrix A1 = Matrix_(3,3, - 0.0,-2.0, -4.2, - 2.0, 0.0, -4.2, - 0.0, 0.0,-10.0); - - Matrix A2 = Matrix_(3,3, - 2.0, 0.0, 0.0, - 0.0, 2.0, 0.0, - 0.0, 0.0, 10.0); - - Vector b = Vector_(3,-0.1/sx,0.1/sy,0.0); - SharedDiagonal probModel1 = noiseModel::Unit::Create(3); - lfg_expected.push_back(JacobianFactor::shared_ptr(new JacobianFactor(ordering[kx1], A1, ordering[kx2], A2, b, probModel1))); - - CHECK(assert_equal(lfg_expected, *lfg_linearized)); -} - -/* ************************************************************************* */ -TEST(Pose2Graph, optimize) { - - // create a Pose graph with one equality constraint and one measurement - pose2SLAM::Graph fg; - fg.addPoseConstraint(0, Pose2(0,0,0)); - fg.addOdometry(0, 1, Pose2(1,2,M_PI_2), covariance); - - // Create initial config - Values initial; - initial.insert(pose2SLAM::PoseKey(0), Pose2(0,0,0)); - initial.insert(pose2SLAM::PoseKey(1), Pose2(0,0,0)); - - // Choose an ordering and optimize - Ordering ordering; - ordering += kx0, kx1; - - LevenbergMarquardtParams params; - params.relativeErrorTol = 1e-15; - params.ordering = ordering; - Values actual = LevenbergMarquardtOptimizer(fg, initial, params).optimize(); - - // Check with expected config - Values expected; - expected.insert(pose2SLAM::PoseKey(0), Pose2(0,0,0)); - expected.insert(pose2SLAM::PoseKey(1), Pose2(1,2,M_PI_2)); - CHECK(assert_equal(expected, actual)); -} - -/* ************************************************************************* */ -// test optimization with 3 poses -TEST(Pose2Graph, optimizeThreePoses) { - - // Create a hexagon of poses - pose2SLAM::Values hexagon = pose2SLAM::circle(3,1.0); - Pose2 p0 = hexagon.pose(0), p1 = hexagon.pose(1); - - // create a Pose graph with one equality constraint and one measurement - pose2SLAM::Graph fg; - fg.addPoseConstraint(0, p0); - Pose2 delta = p0.between(p1); - fg.addOdometry(0, 1, delta, covariance); - fg.addOdometry(1, 2, delta, covariance); - fg.addOdometry(2, 0, delta, covariance); - - // Create initial config - pose2SLAM::Values initial; - initial.insertPose(0, p0); - initial.insertPose(1, hexagon.pose(1).retract(Vector_(3,-0.1, 0.1,-0.1))); - initial.insertPose(2, hexagon.pose(2).retract(Vector_(3, 0.1,-0.1, 0.1))); - - // Choose an ordering - Ordering ordering; - ordering += kx0,kx1,kx2; - - // optimize - LevenbergMarquardtParams params; - params.relativeErrorTol = 1e-15; - params.ordering = ordering; - Values actual = LevenbergMarquardtOptimizer(fg, initial, params).optimize(); - - // Check with ground truth - CHECK(assert_equal((const Values&)hexagon, actual)); -} - -/* ************************************************************************* */ -// test optimization with 6 poses arranged in a hexagon and a loop closure -TEST_UNSAFE(Pose2SLAM, optimizeCircle) { - - // Create a hexagon of poses - pose2SLAM::Values hexagon = pose2SLAM::circle(6,1.0); - Pose2 p0 = hexagon.pose(0), p1 = hexagon.pose(1); - - // create a Pose graph with one equality constraint and one measurement - pose2SLAM::Graph fg; - fg.addPoseConstraint(0, p0); - Pose2 delta = p0.between(p1); - fg.addOdometry(0, 1, delta, covariance); - fg.addOdometry(1,2, delta, covariance); - fg.addOdometry(2,3, delta, covariance); - fg.addOdometry(3,4, delta, covariance); - fg.addOdometry(4,5, delta, covariance); - fg.addOdometry(5, 0, delta, covariance); - - // Create initial config - pose2SLAM::Values initial; - initial.insertPose(0, p0); - initial.insertPose(1, hexagon.pose(1).retract(Vector_(3,-0.1, 0.1,-0.1))); - initial.insertPose(2, hexagon.pose(2).retract(Vector_(3, 0.1,-0.1, 0.1))); - initial.insertPose(3, hexagon.pose(3).retract(Vector_(3,-0.1, 0.1,-0.1))); - initial.insertPose(4, hexagon.pose(4).retract(Vector_(3, 0.1,-0.1, 0.1))); - initial.insertPose(5, hexagon.pose(5).retract(Vector_(3,-0.1, 0.1,-0.1))); - - // Choose an ordering - Ordering ordering; - ordering += kx0,kx1,kx2,kx3,kx4,kx5; - - // optimize - LevenbergMarquardtParams params; - params.relativeErrorTol = 1e-15; - params.ordering = ordering; - Values actual = LevenbergMarquardtOptimizer(fg, initial, params).optimize(); - - // Check with ground truth - CHECK(assert_equal((const Values&)hexagon, actual)); - - // Check loop closure - CHECK(assert_equal(delta, actual.at(PoseKey(5)).between(actual.at(PoseKey(0))))); - -// Pose2SLAMOptimizer myOptimizer("3"); - -// Matrix A1 = myOptimizer.a1(); -// LONGS_EQUAL(3, A1.rows()); -// LONGS_EQUAL(17, A1.cols()); // 7 + 7 + 3 -// -// Matrix A2 = myOptimizer.a2(); -// LONGS_EQUAL(3, A1.rows()); -// LONGS_EQUAL(7, A2.cols()); // 7 -// -// Vector b1 = myOptimizer.b1(); -// LONGS_EQUAL(9, b1.size()); // 3 + 3 + 3 -// -// Vector b2 = myOptimizer.b2(); -// LONGS_EQUAL(3, b2.size()); // 3 -// -// // Here, call matlab to -// // A=[A1;A2], b=[b1;b2] -// // R=qr(A1) -// // call pcg on A,b, with preconditioner R -> get x -// -// Vector x = myOptimizer.optimize(); -// LONGS_EQUAL(9, x.size()); // 3 + 3 + 3 -// -// myOptimizer.update(x); -// -// Values expected; -// expected.insert(0, Pose2(0.,0.,0.)); -// expected.insert(1, Pose2(1.,0.,0.)); -// expected.insert(2, Pose2(2.,0.,0.)); -// -// // Check with ground truth -// CHECK(assert_equal(expected, *myOptimizer.theta())); -} - -/* ************************************************************************* */ -TEST(Pose2Graph, optimize2) { -// Pose2SLAMOptimizer myOptimizer("100"); -// Matrix A1 = myOptimizer.a1(); -// Matrix A2 = myOptimizer.a2(); -// cout << "A1: " << A1.rows() << " " << A1.cols() << endl; -// cout << "A2: " << A2.rows() << " " << A2.cols() << endl; -// -// //cout << "error: " << myOptimizer.error() << endl; -// for(int i = 0; i<10; i++) { -// myOptimizer.linearize(); -// Vector x = myOptimizer.optimize(); -// myOptimizer.update(x); -// } -// //cout << "error: " << myOptimizer.error() << endl; -// CHECK(myOptimizer.error() < 1.); -} - -///* ************************************************************************* */ -// SL-NEEDED? TEST(Pose2SLAM, findMinimumSpanningTree) { -// pose2SLAM::Graph G, T, C; -// G.addConstraint(1, 2, Pose2(0.,0.,0.), I3); -// G.addConstraint(1, 3, Pose2(0.,0.,0.), I3); -// G.addConstraint(2, 3, Pose2(0.,0.,0.), I3); -// -// PredecessorMap tree = -// G.findMinimumSpanningTree(); -// CHECK(tree[1] == 1); -// CHECK(tree[2] == 1); -// CHECK(tree[3] == 1); -//} -// -///* ************************************************************************* */ -// SL-NEEDED? TEST(Pose2SLAM, split) { -// pose2SLAM::Graph G, T, C; -// G.addConstraint(1, 2, Pose2(0.,0.,0.), I3); -// G.addConstraint(1, 3, Pose2(0.,0.,0.), I3); -// G.addConstraint(2, 3, Pose2(0.,0.,0.), I3); -// -// PredecessorMap tree; -// tree.insert(1,2); -// tree.insert(2,2); -// tree.insert(3,2); -// -// G.split(tree, T, C); -// LONGS_EQUAL(2, T.size()); -// LONGS_EQUAL(1, C.size()); -//} - -using namespace pose2SLAM; - -/* ************************************************************************* */ -TEST(Pose2Values, pose2Circle ) -{ - // expected is 4 poses tangent to circle with radius 1m - pose2SLAM::Values expected; - expected.insert(pose2SLAM::PoseKey(0), Pose2( 1, 0, M_PI_2)); - expected.insert(pose2SLAM::PoseKey(1), Pose2( 0, 1, - M_PI )); - expected.insert(pose2SLAM::PoseKey(2), Pose2(-1, 0, - M_PI_2)); - expected.insert(pose2SLAM::PoseKey(3), Pose2( 0, -1, 0 )); - - pose2SLAM::Values actual = pose2SLAM::circle(4,1.0); - CHECK(assert_equal(expected,actual)); -} - -/* ************************************************************************* */ -TEST(Pose2SLAM, expmap ) -{ - // expected is circle shifted to right - pose2SLAM::Values expected; - expected.insert(pose2SLAM::PoseKey(0), Pose2( 1.1, 0, M_PI_2)); - expected.insert(pose2SLAM::PoseKey(1), Pose2( 0.1, 1, - M_PI )); - expected.insert(pose2SLAM::PoseKey(2), Pose2(-0.9, 0, - M_PI_2)); - expected.insert(pose2SLAM::PoseKey(3), Pose2( 0.1, -1, 0 )); - - // Note expmap coordinates are in local coordinates, so shifting to right requires thought !!! - pose2SLAM::Values circle(pose2SLAM::circle(4,1.0)); - Ordering ordering(*circle.orderingArbitrary()); - VectorValues delta(circle.dims(ordering)); - delta[ordering[pose2SLAM::PoseKey(0)]] = Vector_(3, 0.0,-0.1,0.0); - delta[ordering[pose2SLAM::PoseKey(1)]] = Vector_(3, -0.1,0.0,0.0); - delta[ordering[pose2SLAM::PoseKey(2)]] = Vector_(3, 0.0,0.1,0.0); - delta[ordering[pose2SLAM::PoseKey(3)]] = Vector_(3, 0.1,0.0,0.0); - pose2SLAM::Values actual = circle.retract(delta, ordering); - CHECK(assert_equal(expected,actual)); -} - -// Common measurement covariance -static SharedNoiseModel sigmas = sharedSigmas(Vector_(3,sx,sy,st)); - -/* ************************************************************************* */ -// Very simple test establishing Ax-b \approx z-h(x) -TEST( Pose2Prior, error ) -{ - // Choose a linearization point - Pose2 p1(1, 0, 0); // robot at (1,0) - pose2SLAM::Values x0; - x0.insert(PoseKey(1), p1); - - // Create factor - pose2SLAM::Prior factor(PoseKey(1), p1, sigmas); - - // Actual linearization - Ordering ordering(*x0.orderingArbitrary()); - boost::shared_ptr linear = - boost::dynamic_pointer_cast(factor.linearize(x0, ordering)); - - // Check error at x0, i.e. delta = zero ! - VectorValues delta(VectorValues::Zero(x0.dims(ordering))); - delta[ordering[kx1]] = zero(3); - Vector error_at_zero = Vector_(3,0.0,0.0,0.0); - CHECK(assert_equal(error_at_zero,factor.whitenedError(x0))); - CHECK(assert_equal(-error_at_zero,linear->error_vector(delta))); - - // Check error after increasing p2 - VectorValues addition(VectorValues::Zero(x0.dims(ordering))); - addition[ordering[kx1]] = Vector_(3, 0.1, 0.0, 0.0); - VectorValues plus = delta + addition; - pose2SLAM::Values x1 = x0.retract(plus, ordering); - Vector error_at_plus = Vector_(3,0.1/sx,0.0,0.0); // h(x)-z = 0.1 ! - CHECK(assert_equal(error_at_plus,factor.whitenedError(x1))); - CHECK(assert_equal(error_at_plus,linear->error_vector(plus))); -} - -/* ************************************************************************* */ -// common Pose2Prior for tests below -static gtsam::Pose2 priorVal(2,2,M_PI_2); -static pose2SLAM::Prior priorFactor(PoseKey(1), priorVal, sigmas); - -/* ************************************************************************* */ -// The error |A*dx-b| approximates (h(x0+dx)-z) = -error_vector -// Hence i.e., b = approximates z-h(x0) = error_vector(x0) -LieVector hprior(const Pose2& p1) { - return LieVector(sigmas->whiten(priorFactor.evaluateError(p1))); -} - -/* ************************************************************************* */ -TEST( Pose2Prior, linearize ) -{ - // Choose a linearization point at ground truth - pose2SLAM::Values x0; - x0.insertPose(1, priorVal); - - // Actual linearization - Ordering ordering(*x0.orderingArbitrary()); - boost::shared_ptr actual = - boost::dynamic_pointer_cast(priorFactor.linearize(x0, ordering)); - - // Test with numerical derivative - Matrix numericalH = numericalDerivative11(hprior, priorVal); - CHECK(assert_equal(numericalH,actual->getA(actual->find(ordering[kx1])))); -} - -/* ************************************************************************* */ -// Very simple test establishing Ax-b \approx z-h(x) -TEST( Pose2Factor, error ) -{ - // Choose a linearization point - Pose2 p1; // robot at origin - Pose2 p2(1, 0, 0); // robot at (1,0) - pose2SLAM::Values x0; - x0.insertPose(1, p1); - x0.insertPose(2, p2); - - // Create factor - Pose2 z = p1.between(p2); - Pose2Factor factor(PoseKey(1), PoseKey(2), z, covariance); - - // Actual linearization - Ordering ordering(*x0.orderingArbitrary()); - boost::shared_ptr linear = - boost::dynamic_pointer_cast(factor.linearize(x0, ordering)); - - // Check error at x0, i.e. delta = zero ! - VectorValues delta(x0.dims(ordering)); - delta[ordering[kx1]] = zero(3); - delta[ordering[kx2]] = zero(3); - Vector error_at_zero = Vector_(3,0.0,0.0,0.0); - CHECK(assert_equal(error_at_zero,factor.unwhitenedError(x0))); - CHECK(assert_equal(-error_at_zero, linear->error_vector(delta))); - - // Check error after increasing p2 - VectorValues plus = delta; - plus[ordering[kx2]] = Vector_(3, 0.1, 0.0, 0.0); - pose2SLAM::Values x1 = x0.retract(plus, ordering); - Vector error_at_plus = Vector_(3,0.1/sx,0.0,0.0); // h(x)-z = 0.1 ! - CHECK(assert_equal(error_at_plus,factor.whitenedError(x1))); - CHECK(assert_equal(error_at_plus,linear->error_vector(plus))); -} - -/* ************************************************************************* */ -// common Pose2Factor for tests below -static Pose2 measured(2,2,M_PI_2); -static Pose2Factor factor(PoseKey(1),PoseKey(2),measured, covariance); - -/* ************************************************************************* */ -TEST( Pose2Factor, rhs ) -{ - // Choose a linearization point - Pose2 p1(1.1,2,M_PI_2); // robot at (1.1,2) looking towards y (ground truth is at 1,2, see testPose2) - Pose2 p2(-1,4.1,M_PI); // robot at (-1,4.1) looking at negative (ground truth is at -1,4) - pose2SLAM::Values x0; - x0.insert(pose2SLAM::PoseKey(1),p1); - x0.insert(pose2SLAM::PoseKey(2),p2); - - // Actual linearization - Ordering ordering(*x0.orderingArbitrary()); - boost::shared_ptr linear = - boost::dynamic_pointer_cast(factor.linearize(x0, ordering)); - - // Check RHS - Pose2 hx0 = p1.between(p2); - CHECK(assert_equal(Pose2(2.1, 2.1, M_PI_2),hx0)); - Vector expected_b = Vector_(3, -0.1/sx, 0.1/sy, 0.0); - CHECK(assert_equal(expected_b,-factor.whitenedError(x0))); - CHECK(assert_equal(expected_b,linear->getb())); -} - -/* ************************************************************************* */ -// The error |A*dx-b| approximates (h(x0+dx)-z) = -error_vector -// Hence i.e., b = approximates z-h(x0) = error_vector(x0) -LieVector h(const Pose2& p1,const Pose2& p2) { - return LieVector(covariance->whiten(factor.evaluateError(p1,p2))); -} - -/* ************************************************************************* */ -TEST( Pose2Factor, linearize ) -{ - // Choose a linearization point at ground truth - Pose2 p1(1,2,M_PI_2); - Pose2 p2(-1,4,M_PI); - pose2SLAM::Values x0; - x0.insert(pose2SLAM::PoseKey(1),p1); - x0.insert(pose2SLAM::PoseKey(2),p2); - - // expected linearization - Matrix expectedH1 = covariance->Whiten(Matrix_(3,3, - 0.0,-1.0,-2.0, - 1.0, 0.0,-2.0, - 0.0, 0.0,-1.0 - )); - Matrix expectedH2 = covariance->Whiten(Matrix_(3,3, - 1.0, 0.0, 0.0, - 0.0, 1.0, 0.0, - 0.0, 0.0, 1.0 - )); - Vector expected_b = Vector_(3, 0.0, 0.0, 0.0); - - // expected linear factor - Ordering ordering(*x0.orderingArbitrary()); - SharedDiagonal probModel1 = noiseModel::Unit::Create(3); - JacobianFactor expected(ordering[kx1], expectedH1, ordering[kx2], expectedH2, expected_b, probModel1); - - // Actual linearization - boost::shared_ptr actual = - boost::dynamic_pointer_cast(factor.linearize(x0, ordering)); - CHECK(assert_equal(expected,*actual)); - - // Numerical do not work out because BetweenFactor is approximate ? - Matrix numericalH1 = numericalDerivative21(h, p1, p2); - CHECK(assert_equal(expectedH1,numericalH1)); - Matrix numericalH2 = numericalDerivative22(h, p1, p2); - CHECK(assert_equal(expectedH2,numericalH2)); -} - -/* ************************************************************************* */ -int main() { - TestResult tr; - return TestRegistry::runAllTests(tr); -} -/* ************************************************************************* */ diff --git a/gtsam/slam/tests/testPose3SLAM.cpp b/gtsam/slam/tests/testPose3SLAM.cpp deleted file mode 100644 index d4ab3afdb..000000000 --- a/gtsam/slam/tests/testPose3SLAM.cpp +++ /dev/null @@ -1,219 +0,0 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) - - * See LICENSE for the license information - - * -------------------------------------------------------------------------- */ - -/** - * @file testPose3Graph.cpp - * @author Frank Dellaert, Viorela Ila - **/ - -#include - -#include -#include -#include -#include -using namespace boost; -using namespace boost::assign; - -#include - -// TODO: DANGEROUS, create shared pointers -#define GTSAM_MAGIC_GAUSSIAN 6 - -#include -#include -#include - -using namespace std; -using namespace gtsam; -using namespace pose3SLAM; - -// common measurement covariance -static Matrix covariance = eye(6); - -const double tol=1e-5; - -const Key kx0 = Symbol('x',0), kx1 = Symbol('x',1), kx2 = Symbol('x',2), kx3 = Symbol('x',3), kx4 = Symbol('x',4), kx5 = Symbol('x',5); - -/* ************************************************************************* */ -// test optimization with 6 poses arranged in a hexagon and a loop closure -TEST(Pose3Graph, optimizeCircle) { - - // Create a hexagon of poses - double radius = 10; - Values hexagon = pose3SLAM::circle(6,radius); - Pose3 gT0 = hexagon.at(PoseKey(0)), gT1 = hexagon.at(PoseKey(1)); - - // create a Pose graph with one equality constraint and one measurement - pose3SLAM::Graph fg; - fg.addHardConstraint(0, gT0); - Pose3 _0T1 = gT0.between(gT1); // inv(gT0)*gT1 - double theta = M_PI/3.0; - CHECK(assert_equal(Pose3(Rot3::yaw(-theta),Point3(radius*sin(theta),-radius*cos(theta),0)),_0T1)); - fg.addConstraint(0,1, _0T1, covariance); - fg.addConstraint(1,2, _0T1, covariance); - fg.addConstraint(2,3, _0T1, covariance); - fg.addConstraint(3,4, _0T1, covariance); - fg.addConstraint(4,5, _0T1, covariance); - fg.addConstraint(5,0, _0T1, covariance); - - // Create initial config - Values initial; - initial.insert(PoseKey(0), gT0); - initial.insert(PoseKey(1), hexagon.at(PoseKey(1)).retract(Vector_(6,-0.1, 0.1,-0.1,-0.1, 0.1,-0.1))); - initial.insert(PoseKey(2), hexagon.at(PoseKey(2)).retract(Vector_(6, 0.1,-0.1, 0.1, 0.1,-0.1, 0.1))); - initial.insert(PoseKey(3), hexagon.at(PoseKey(3)).retract(Vector_(6,-0.1, 0.1,-0.1,-0.1, 0.1,-0.1))); - initial.insert(PoseKey(4), hexagon.at(PoseKey(4)).retract(Vector_(6, 0.1,-0.1, 0.1, 0.1,-0.1, 0.1))); - initial.insert(PoseKey(5), hexagon.at(PoseKey(5)).retract(Vector_(6,-0.1, 0.1,-0.1,-0.1, 0.1,-0.1))); - - // Choose an ordering and optimize - Ordering ordering; - ordering += kx0,kx1,kx2,kx3,kx4,kx5; - - Values actual = LevenbergMarquardtOptimizer(fg, initial, ordering).optimize(); - - // Check with ground truth - CHECK(assert_equal(hexagon, actual,1e-4)); - - // Check loop closure - CHECK(assert_equal(_0T1, actual.at(PoseKey(5)).between(actual.at(PoseKey(0))),1e-5)); -} - -/* ************************************************************************* */ -TEST(Pose3Graph, partial_prior_height) { - typedef PartialPriorFactor Partial; - - // reference: Pose3 Expmap - (0-2: Rot3) (3-5: Point3) - - // height prior - single element interface - Symbol key = PoseKey(1); - double exp_height = 5.0; - SharedDiagonal model = noiseModel::Unit::Create(1); - Pose3 init(Rot3(), Point3(1.0, 2.0, 3.0)), expected(Rot3(), Point3(1.0, 2.0, exp_height)); - Partial height(key, 5, exp_height, model); - Matrix actA; - EXPECT(assert_equal(Vector_(1,-2.0), height.evaluateError(init, actA), tol)); - Matrix expA = Matrix_(1, 6, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0); - EXPECT(assert_equal(expA, actA)); - - pose3SLAM::Graph graph; - graph.add(height); - - Values values; - values.insert(key, init); - - // linearization - EXPECT_DOUBLES_EQUAL(2.0, height.error(values), tol); - - Values actual = LevenbergMarquardtOptimizer(graph, values).optimize(); - EXPECT(assert_equal(expected, actual.at(key), tol)); - EXPECT_DOUBLES_EQUAL(0.0, graph.error(actual), tol); -} - -/* ************************************************************************* */ -TEST( Pose3Factor, error ) -{ - // Create example - Pose3 t1; // origin - Pose3 t2(Rot3::rodriguez(0.1,0.2,0.3),Point3(0,1,0)); - Pose3 z(Rot3::rodriguez(0.2,0.2,0.3),Point3(0,1.1,0));; - - // Create factor - SharedNoiseModel I6(noiseModel::Unit::Create(6)); - pose3SLAM::Constraint factor(PoseKey(1), PoseKey(2), z, I6); - - // Create config - Values x; - x.insert(PoseKey(1),t1); - x.insert(PoseKey(2),t2); - - // Get error h(x)-z -> localCoordinates(z,h(x)) = localCoordinates(z,between(t1,t2)) - Vector actual = factor.unwhitenedError(x); - Vector expected = z.localCoordinates(t1.between(t2)); - CHECK(assert_equal(expected,actual)); -} - -/* ************************************************************************* */ -TEST(Pose3Graph, partial_prior_xy) { - typedef PartialPriorFactor Partial; - - // XY prior - full mask interface - Symbol key = PoseKey(1); - Vector exp_xy = Vector_(2, 3.0, 4.0); - SharedDiagonal model = noiseModel::Unit::Create(2); - Pose3 init(Rot3(), Point3(1.0,-2.0, 3.0)), expected(Rot3(), Point3(3.0, 4.0, 3.0)); - vector mask; mask += 3, 4; - Partial priorXY(key, mask, exp_xy, model); - Matrix actA; - EXPECT(assert_equal(Vector_(2,-2.0,-6.0), priorXY.evaluateError(init, actA), tol)); - Matrix expA = Matrix_(2, 6, - 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, - 0.0, 0.0, 0.0, 0.0, 1.0, 0.0); - EXPECT(assert_equal(expA, actA)); - - pose3SLAM::Graph graph; - graph.add(priorXY); - - Values values; - values.insert(key, init); - - Values actual = LevenbergMarquardtOptimizer(graph, values).optimize(); - EXPECT(assert_equal(expected, actual.at(key), tol)); - EXPECT_DOUBLES_EQUAL(0.0, graph.error(actual), tol); -} - -// The world coordinate system has z pointing up, y north, x east -// The vehicle has X forward, Y right, Z down -Rot3 R1(Point3( 0, 1, 0), Point3( 1, 0, 0), Point3(0, 0, -1)); -Rot3 R2(Point3(-1, 0, 0), Point3( 0, 1, 0), Point3(0, 0, -1)); -Rot3 R3(Point3( 0,-1, 0), Point3(-1, 0, 0), Point3(0, 0, -1)); -Rot3 R4(Point3( 1, 0, 0), Point3( 0,-1, 0), Point3(0, 0, -1)); - -/* ************************************************************************* */ -TEST( Values, pose3Circle ) -{ - // expected is 4 poses tangent to circle with radius 1m - Values expected; - expected.insert(PoseKey(0), Pose3(R1, Point3( 1, 0, 0))); - expected.insert(PoseKey(1), Pose3(R2, Point3( 0, 1, 0))); - expected.insert(PoseKey(2), Pose3(R3, Point3(-1, 0, 0))); - expected.insert(PoseKey(3), Pose3(R4, Point3( 0,-1, 0))); - - Values actual = pose3SLAM::circle(4,1.0); - CHECK(assert_equal(expected,actual)); -} - -/* ************************************************************************* */ -TEST( Values, expmap ) -{ - Values expected; - expected.insert(PoseKey(0), Pose3(R1, Point3( 1.0, 0.1, 0))); - expected.insert(PoseKey(1), Pose3(R2, Point3(-0.1, 1.0, 0))); - expected.insert(PoseKey(2), Pose3(R3, Point3(-1.0,-0.1, 0))); - expected.insert(PoseKey(3), Pose3(R4, Point3( 0.1,-1.0, 0))); - - Ordering ordering(*expected.orderingArbitrary()); - VectorValues delta(expected.dims(ordering)); - delta.vector() = Vector_(24, - 0.0,0.0,0.0, 0.1, 0.0, 0.0, - 0.0,0.0,0.0, 0.1, 0.0, 0.0, - 0.0,0.0,0.0, 0.1, 0.0, 0.0, - 0.0,0.0,0.0, 0.1, 0.0, 0.0); - Values actual = pose3SLAM::circle(4,1.0).retract(delta, ordering); - CHECK(assert_equal(expected,actual)); -} - -/* ************************************************************************* */ -int main() { - TestResult tr; - return TestRegistry::runAllTests(tr); -} -/* ************************************************************************* */ diff --git a/gtsam/slam/tests/testProjectionFactor.cpp b/gtsam/slam/tests/testProjectionFactor.cpp index 8b4ecbf21..1bda97951 100644 --- a/gtsam/slam/tests/testProjectionFactor.cpp +++ b/gtsam/slam/tests/testProjectionFactor.cpp @@ -16,13 +16,17 @@ * @date Nov 2009 */ +#include +#include +#include +#include +#include +#include +#include #include -#include - using namespace std; using namespace gtsam; -using namespace visualSLAM; // make cube static Point3 @@ -37,23 +41,31 @@ static Cal3_S2 K(fov,w,h); static SharedNoiseModel sigma(noiseModel::Unit::Create(1)); static shared_ptrK sK(new Cal3_S2(K)); -const Key kx1 = Symbol('x',1), kl1 = Symbol('l',1); +// Convenience for named keys +using symbol_shorthand::X; +using symbol_shorthand::L; -// make cameras +typedef GenericProjectionFactor MyProjectionFactor; + +/* ************************************************************************* */ +TEST( ProjectionFactor, nonStandard ) +{ + GenericProjectionFactor f; +} /* ************************************************************************* */ TEST( ProjectionFactor, error ) -{ + { // Create the factor with a measurement that is 3 pixels off in x Point2 z(323.,240.); - int cameraFrameNumber=1, landmarkNumber=1; - boost::shared_ptr - factor(new visualSLAM::ProjectionFactor(z, sigma, PoseKey(cameraFrameNumber), PointKey(landmarkNumber), sK)); + int i=1, j=1; + boost::shared_ptr + factor(new MyProjectionFactor(z, sigma, X(i), L(j), sK)); // For the following values structure, the factor predicts 320,240 Values config; - Rot3 R;Point3 t1(0,0,-6); Pose3 x1(R,t1); config.insert(PoseKey(1), x1); - Point3 l1; config.insert(PointKey(1), l1); + Rot3 R;Point3 t1(0,0,-6); Pose3 x1(R,t1); config.insert(X(1), x1); + Point3 l1; config.insert(L(1), l1); // Point should project to Point2(320.,240.) CHECK(assert_equal(Vector_(2, -3.0, 0.0), factor->unwhitenedError(config))); @@ -61,18 +73,18 @@ TEST( ProjectionFactor, error ) DOUBLES_EQUAL(4.5,factor->error(config),1e-9); // Check linearize - Ordering ordering; ordering += kx1,kl1; + Ordering ordering; ordering += X(1),L(1); Matrix Ax1 = Matrix_(2, 6, 0., -554.256, 0., -92.376, 0., 0., 554.256, 0., 0., 0., -92.376, 0.); Matrix Al1 = Matrix_(2, 3, 92.376, 0., 0., 0., 92.376, 0.); Vector b = Vector_(2,3.,0.); SharedDiagonal probModel1 = noiseModel::Unit::Create(2); - JacobianFactor expected(ordering[kx1], Ax1, ordering[kl1], Al1, b, probModel1); + JacobianFactor expected(ordering[X(1)], Ax1, ordering[L(1)], Al1, b, probModel1); JacobianFactor::shared_ptr actual = boost::dynamic_pointer_cast(factor->linearize(config, ordering)); CHECK(assert_equal(expected,*actual,1e-3)); // linearize graph - visualSLAM::Graph graph; + NonlinearFactorGraph graph; graph.push_back(factor); FactorGraph expected_lfg; expected_lfg.push_back(actual); @@ -81,11 +93,11 @@ TEST( ProjectionFactor, error ) // expmap on a config Values expected_config; - Point3 t2(1,1,-5); Pose3 x2(R,t2); expected_config.insert(PoseKey(1), x2); - Point3 l2(1,2,3); expected_config.insert(PointKey(1), l2); + Point3 t2(1,1,-5); Pose3 x2(R,t2); expected_config.insert(X(1), x2); + Point3 l2(1,2,3); expected_config.insert(L(1), l2); VectorValues delta(expected_config.dims(ordering)); - delta[ordering[kx1]] = Vector_(6, 0.,0.,0., 1.,1.,1.); - delta[ordering[kl1]] = Vector_(3, 1.,2.,3.); + delta[ordering[X(1)]] = Vector_(6, 0.,0.,0., 1.,1.,1.); + delta[ordering[L(1)]] = Vector_(3, 1.,2.,3.); Values actual_config = config.retract(delta, ordering); CHECK(assert_equal(expected_config,actual_config,1e-9)); } @@ -95,12 +107,12 @@ TEST( ProjectionFactor, equals ) { // Create two identical factors and make sure they're equal Vector z = Vector_(2,323.,240.); - int cameraFrameNumber=1, landmarkNumber=1; - boost::shared_ptr - factor1(new visualSLAM::ProjectionFactor(z, sigma, PoseKey(cameraFrameNumber), PointKey(landmarkNumber), sK)); + int i=1, j=1; + boost::shared_ptr + factor1(new MyProjectionFactor(z, sigma, X(i), L(j), sK)); - boost::shared_ptr - factor2(new visualSLAM::ProjectionFactor(z, sigma, PoseKey(cameraFrameNumber), PointKey(landmarkNumber), sK)); + boost::shared_ptr + factor2(new MyProjectionFactor(z, sigma, X(i), L(j), sK)); CHECK(assert_equal(*factor1, *factor2)); } diff --git a/gtsam/slam/tests/testSerializationSLAM.cpp b/gtsam/slam/tests/testSerializationSLAM.cpp deleted file mode 100644 index 9cfb8bb72..000000000 --- a/gtsam/slam/tests/testSerializationSLAM.cpp +++ /dev/null @@ -1,207 +0,0 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) - - * See LICENSE for the license information - - * -------------------------------------------------------------------------- */ - -/** - * @file testSerializationSLAM.cpp - * @brief - * @author Richard Roberts - * @date Feb 7, 2012 - */ - -#include -#include -#include -#include -#include - -#include -#include - -using namespace std; -using namespace gtsam; -using namespace gtsam::serializationTestHelpers; - -/* Create GUIDs for factors */ -/* ************************************************************************* */ -BOOST_CLASS_EXPORT_GUID(gtsam::JacobianFactor, "gtsam::JacobianFactor"); -BOOST_CLASS_EXPORT_GUID(gtsam::HessianFactor , "gtsam::HessianFactor"); - -/* ************************************************************************* */ -// Export Noisemodels -BOOST_CLASS_EXPORT_GUID(gtsam::noiseModel::Constrained, "gtsam_noiseModel_Constrained"); -BOOST_CLASS_EXPORT_GUID(gtsam::noiseModel::Diagonal, "gtsam_noiseModel_Diagonal"); -BOOST_CLASS_EXPORT_GUID(gtsam::noiseModel::Gaussian, "gtsam_noiseModel_Gaussian"); -BOOST_CLASS_EXPORT_GUID(gtsam::noiseModel::Unit, "gtsam_noiseModel_Unit"); -BOOST_CLASS_EXPORT_GUID(gtsam::noiseModel::Isotropic, "gtsam_noiseModel_Isotropic"); - -BOOST_CLASS_EXPORT_GUID(gtsam::SharedNoiseModel, "gtsam_SharedNoiseModel"); -BOOST_CLASS_EXPORT_GUID(gtsam::SharedDiagonal, "gtsam_SharedDiagonal"); - -/* ************************************************************************* */ -TEST (Serialization, smallExample_linear) { - using namespace example; - - Ordering ordering; ordering += Symbol('x',1),Symbol('x',2),Symbol('l',1); - GaussianFactorGraph fg = createGaussianFactorGraph(ordering); - EXPECT(equalsObj(ordering)); - EXPECT(equalsXML(ordering)); - - EXPECT(equalsObj(fg)); - EXPECT(equalsXML(fg)); - - GaussianBayesNet cbn = createSmallGaussianBayesNet(); - EXPECT(equalsObj(cbn)); - EXPECT(equalsXML(cbn)); -} - -/* ************************************************************************* */ -TEST (Serialization, gaussianISAM) { - using namespace example; - Ordering ordering; - GaussianFactorGraph smoother; - boost::tie(smoother, ordering) = createSmoother(7); - BayesTree bayesTree = *GaussianMultifrontalSolver(smoother).eliminate(); - GaussianISAM isam(bayesTree); - - EXPECT(equalsObj(isam)); - EXPECT(equalsXML(isam)); -} - -/* ************************************************************************* */ -/* Create GUIDs for factors in simulated2D */ -BOOST_CLASS_EXPORT_GUID(simulated2D::Prior, "gtsam::simulated2D::Prior" ) -BOOST_CLASS_EXPORT_GUID(simulated2D::Odometry, "gtsam::simulated2D::Odometry" ) -BOOST_CLASS_EXPORT_GUID(simulated2D::Measurement, "gtsam::simulated2D::Measurement") -BOOST_CLASS_EXPORT(gtsam::Point2) - -/* ************************************************************************* */ -TEST (Serialization, smallExample) { - using namespace example; - Graph nfg = createNonlinearFactorGraph(); - Values c1 = createValues(); - EXPECT(equalsObj(nfg)); - EXPECT(equalsXML(nfg)); - - EXPECT(equalsObj(c1)); - EXPECT(equalsXML(c1)); -} - -/* ************************************************************************* */ -/* Create GUIDs for factors */ -BOOST_CLASS_EXPORT_GUID(planarSLAM::Prior, "gtsam::planarSLAM::Prior"); -BOOST_CLASS_EXPORT_GUID(planarSLAM::Bearing, "gtsam::planarSLAM::Bearing"); -BOOST_CLASS_EXPORT_GUID(planarSLAM::Range, "gtsam::planarSLAM::Range"); -BOOST_CLASS_EXPORT_GUID(planarSLAM::BearingRange,"gtsam::planarSLAM::BearingRange"); -BOOST_CLASS_EXPORT_GUID(planarSLAM::Odometry, "gtsam::planarSLAM::Odometry"); -BOOST_CLASS_EXPORT_GUID(planarSLAM::Constraint, "gtsam::planarSLAM::Constraint"); - -BOOST_CLASS_EXPORT(gtsam::Pose2) - -/* ************************************************************************* */ -TEST (Serialization, planar_system) { - using namespace planarSLAM; - planarSLAM::Values values; - values.insert(PointKey(3), Point2(1.0, 2.0)); - values.insert(PoseKey(4), Pose2(1.0, 2.0, 0.3)); - - SharedNoiseModel model1 = noiseModel::Isotropic::Sigma(1, 0.3); - SharedNoiseModel model2 = noiseModel::Isotropic::Sigma(2, 0.3); - SharedNoiseModel model3 = noiseModel::Isotropic::Sigma(3, 0.3); - - Prior prior(PoseKey(3), Pose2(0.1,-0.3, 0.2), model1); - Bearing bearing(PoseKey(3), PointKey(5), Rot2::fromDegrees(0.5), model1); - Range range(PoseKey(2), PointKey(9), 7.0, model1); - BearingRange bearingRange(PoseKey(2), PointKey(3), Rot2::fromDegrees(0.6), 2.0, model2); - Odometry odometry(PoseKey(2), PoseKey(3), Pose2(1.0, 2.0, 0.3), model3); - Constraint constraint(PoseKey(9), Pose2(2.0,-1.0, 0.2)); - - Graph graph; - graph.add(prior); - graph.add(bearing); - graph.add(range); - graph.add(bearingRange); - graph.add(odometry); - graph.add(constraint); - - // text - EXPECT(equalsObj(PoseKey(2))); - EXPECT(equalsObj(PointKey(3))); - EXPECT(equalsObj(values)); - EXPECT(equalsObj(prior)); - EXPECT(equalsObj(bearing)); - EXPECT(equalsObj(bearingRange)); - EXPECT(equalsObj(range)); - EXPECT(equalsObj(odometry)); - EXPECT(equalsObj(constraint)); - EXPECT(equalsObj(graph)); - - // xml - EXPECT(equalsXML(PoseKey(2))); - EXPECT(equalsXML(PointKey(3))); - EXPECT(equalsXML(values)); - EXPECT(equalsXML(prior)); - EXPECT(equalsXML(bearing)); - EXPECT(equalsXML(bearingRange)); - EXPECT(equalsXML(range)); - EXPECT(equalsXML(odometry)); - EXPECT(equalsXML(constraint)); - EXPECT(equalsXML(graph)); -} - -/* ************************************************************************* */ -/* Create GUIDs for factors */ -BOOST_CLASS_EXPORT_GUID(visualSLAM::PoseConstraint, "gtsam::visualSLAM::PoseConstraint"); -BOOST_CLASS_EXPORT_GUID(visualSLAM::PointConstraint, "gtsam::visualSLAM::PointConstraint"); -BOOST_CLASS_EXPORT_GUID(visualSLAM::PosePrior, "gtsam::visualSLAM::PosePrior"); -BOOST_CLASS_EXPORT_GUID(visualSLAM::PointPrior, "gtsam::visualSLAM::PointPrior"); -BOOST_CLASS_EXPORT_GUID(visualSLAM::ProjectionFactor,"gtsam::visualSLAM::ProjectionFactor"); -BOOST_CLASS_EXPORT_GUID(visualSLAM::StereoFactor, "gtsam::visualSLAM::StereoFactor"); - -BOOST_CLASS_EXPORT(gtsam::Pose3) -BOOST_CLASS_EXPORT(gtsam::Point3) - -Point3 pt3(1.0, 2.0, 3.0); -Rot3 rt3 = Rot3::RzRyRx(1.0, 3.0, 2.0); -Pose3 pose3(rt3, pt3); -Cal3_S2 cal1(1.0, 2.0, 0.3, 0.1, 0.5); - -/* ************************************************************************* */ -TEST (Serialization, visual_system) { - using namespace visualSLAM; - Values values; - Symbol x1('x',1), x2('x',2); - Symbol l1('l',1), l2('l',2); - Pose3 pose1 = pose3, pose2 = pose3.inverse(); - Point3 pt1(1.0, 2.0, 3.0), pt2(4.0, 5.0, 6.0); - values.insert(x1, pose1); - values.insert(l1, pt1); - SharedNoiseModel model2 = noiseModel::Isotropic::Sigma(2, 0.3); - SharedNoiseModel model3 = noiseModel::Isotropic::Sigma(3, 0.3); - SharedNoiseModel model6 = noiseModel::Isotropic::Sigma(6, 0.3); - boost::shared_ptr K(new Cal3_S2(cal1)); - - Graph graph; - graph.addMeasurement(Point2(1.0, 2.0), model2, 1, 1, K); - graph.addPointConstraint(1, pt1); - graph.addPointPrior(1, pt2, model3); - graph.addPoseConstraint(1, pose1); - graph.addPosePrior(1, pose2, model6); - - EXPECT(equalsObj(values)); - EXPECT(equalsObj(graph)); - - EXPECT(equalsXML(values)); - EXPECT(equalsXML(graph)); -} - -/* ************************************************************************* */ -int main() { TestResult tr; return TestRegistry::runAllTests(tr); } -/* ************************************************************************* */ diff --git a/gtsam/slam/tests/testStereoFactor.cpp b/gtsam/slam/tests/testStereoFactor.cpp index 25cd6e16f..f6a861354 100644 --- a/gtsam/slam/tests/testStereoFactor.cpp +++ b/gtsam/slam/tests/testStereoFactor.cpp @@ -12,58 +12,59 @@ /** * @file testStereoFactor.cpp * @brief Unit test for StereoFactor - * single camera * @author Chris Beall */ -#include - -#include -#include -#include -#include #include +#include +#include +#include +#include +#include +#include +#include +#include +#include -#include +#include using namespace std; using namespace gtsam; -using namespace boost; -using namespace visualSLAM; -Pose3 camera1(Matrix_(3,3, +static Pose3 camera1(Matrix_(3,3, 1., 0., 0., 0.,-1., 0., 0., 0.,-1. ), Point3(0,0,6.25)); -Cal3_S2Stereo::shared_ptr K(new Cal3_S2Stereo(1500, 1500, 0, 320, 240, 0.5)); -StereoCamera stereoCam(Pose3(), K); +static boost::shared_ptr K(new Cal3_S2Stereo(625, 625, 0, 320, 240, 0.5)); // point X Y Z in meters -Point3 p(0, 0, 5); +static Point3 p(0, 0, 5); static SharedNoiseModel sigma(noiseModel::Unit::Create(1)); +// Convenience for named keys +using symbol_shorthand::X; +using symbol_shorthand::L; + /* ************************************************************************* */ TEST( StereoFactor, singlePoint) { - //Cal3_S2 K(625, 625, 0, 320, 240, 0.5); - boost::shared_ptr K(new Cal3_S2Stereo(625, 625, 0, 320, 240, 0.5)); NonlinearFactorGraph graph; - graph.add(visualSLAM::PoseConstraint(PoseKey(1),camera1)); + graph.add(NonlinearEquality(X(1), camera1)); - StereoPoint2 z14(320,320.0-50, 240); + StereoPoint2 z14(320, 320.0-50, 240); // arguments: measurement, sigma, cam#, measurement #, K, baseline (m) - graph.add(visualSLAM::StereoFactor(z14,sigma, PoseKey(1), PointKey(1), K)); + graph.add(GenericStereoFactor(z14, sigma, X(1), L(1), K)); // Create a configuration corresponding to the ground truth Values values; - values.insert(PoseKey(1), camera1); // add camera at z=6.25m looking towards origin + values.insert(X(1), camera1); // add camera at z=6.25m looking towards origin Point3 l1(0, 0, 0); - values.insert(PointKey(1), l1); // add point at origin; + values.insert(L(1), l1); // add point at origin; GaussNewtonOptimizer optimizer(graph, values); diff --git a/gtsam/slam/tests/testVSLAM.cpp b/gtsam/slam/tests/testVSLAM.cpp deleted file mode 100644 index bb7623954..000000000 --- a/gtsam/slam/tests/testVSLAM.cpp +++ /dev/null @@ -1,214 +0,0 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) - - * See LICENSE for the license information - - * -------------------------------------------------------------------------- */ - -/** - * @file testGraph.cpp - * @brief Unit test for two cameras and four landmarks - * single camera - * @author Chris Beall - * @author Frank Dellaert - * @author Viorela Ila - */ - -#include -#include -using namespace boost; - -#include -#include -#include - -using namespace std; -using namespace gtsam; -using namespace boost; -using namespace visualSLAM; - -static SharedNoiseModel sigma(noiseModel::Unit::Create(1)); - -/* ************************************************************************* */ -Point3 landmark1(-1.0,-1.0, 0.0); -Point3 landmark2(-1.0, 1.0, 0.0); -Point3 landmark3( 1.0, 1.0, 0.0); -Point3 landmark4( 1.0,-1.0, 0.0); - -Pose3 camera1(Matrix_(3,3, - 1., 0., 0., - 0.,-1., 0., - 0., 0.,-1. - ), - Point3(0,0,6.25)); - -Pose3 camera2(Matrix_(3,3, - 1., 0., 0., - 0.,-1., 0., - 0., 0.,-1. - ), - Point3(0,0,5.00)); - -/* ************************************************************************* */ -visualSLAM::Graph testGraph() { - Point2 z11(-100, 100); - Point2 z12(-100,-100); - Point2 z13( 100,-100); - Point2 z14( 100, 100); - Point2 z21(-125, 125); - Point2 z22(-125,-125); - Point2 z23( 125,-125); - Point2 z24( 125, 125); - - shared_ptrK sK(new Cal3_S2(625, 625, 0, 0, 0)); - visualSLAM::Graph g; - g.addMeasurement(z11, sigma, 1, 1, sK); - g.addMeasurement(z12, sigma, 1, 2, sK); - g.addMeasurement(z13, sigma, 1, 3, sK); - g.addMeasurement(z14, sigma, 1, 4, sK); - g.addMeasurement(z21, sigma, 2, 1, sK); - g.addMeasurement(z22, sigma, 2, 2, sK); - g.addMeasurement(z23, sigma, 2, 3, sK); - g.addMeasurement(z24, sigma, 2, 4, sK); - return g; -} - -/* ************************************************************************* */ -TEST( Graph, optimizeLM) -{ - // build a graph - visualSLAM::Graph graph(testGraph()); - // add 3 landmark constraints - graph.addPointConstraint(1, landmark1); - graph.addPointConstraint(2, landmark2); - graph.addPointConstraint(3, landmark3); - - // Create an initial values structure corresponding to the ground truth - Values initialEstimate; - initialEstimate.insert(PoseKey(1), camera1); - initialEstimate.insert(PoseKey(2), camera2); - initialEstimate.insert(PointKey(1), landmark1); - initialEstimate.insert(PointKey(2), landmark2); - initialEstimate.insert(PointKey(3), landmark3); - initialEstimate.insert(PointKey(4), landmark4); - - // Create an ordering of the variables - Ordering ordering; - ordering += PointKey(1),PointKey(2),PointKey(3),PointKey(4),PoseKey(1),PoseKey(2); - - // Create an optimizer and check its error - // We expect the initial to be zero because config is the ground truth - LevenbergMarquardtOptimizer optimizer(graph, initialEstimate, ordering); - DOUBLES_EQUAL(0.0, optimizer.error(), 1e-9); - - // Iterate once, and the config should not have changed because we started - // with the ground truth - optimizer.iterate(); - DOUBLES_EQUAL(0.0, optimizer.error(), 1e-9); - - // check if correct - CHECK(assert_equal(initialEstimate, optimizer.values())); -} - - -/* ************************************************************************* */ -TEST( Graph, optimizeLM2) -{ - // build a graph - visualSLAM::Graph graph(testGraph()); - // add 2 camera constraints - graph.addPoseConstraint(1, camera1); - graph.addPoseConstraint(2, camera2); - - // Create an initial values structure corresponding to the ground truth - Values initialEstimate; - initialEstimate.insert(PoseKey(1), camera1); - initialEstimate.insert(PoseKey(2), camera2); - initialEstimate.insert(PointKey(1), landmark1); - initialEstimate.insert(PointKey(2), landmark2); - initialEstimate.insert(PointKey(3), landmark3); - initialEstimate.insert(PointKey(4), landmark4); - - // Create an ordering of the variables - Ordering ordering; - ordering += PointKey(1),PointKey(2),PointKey(3),PointKey(4),PoseKey(1),PoseKey(2); - - // Create an optimizer and check its error - // We expect the initial to be zero because config is the ground truth - LevenbergMarquardtOptimizer optimizer(graph, initialEstimate, ordering); - DOUBLES_EQUAL(0.0, optimizer.error(), 1e-9); - - // Iterate once, and the config should not have changed because we started - // with the ground truth - optimizer.iterate(); - DOUBLES_EQUAL(0.0, optimizer.error(), 1e-9); - - // check if correct - CHECK(assert_equal(initialEstimate, optimizer.values())); -} - - -/* ************************************************************************* */ -TEST( Graph, CHECK_ORDERING) -{ - // build a graph - visualSLAM::Graph graph = testGraph(); - // add 2 camera constraints - graph.addPoseConstraint(1, camera1); - graph.addPoseConstraint(2, camera2); - - // Create an initial values structure corresponding to the ground truth - Values initialEstimate; - initialEstimate.insert(PoseKey(1), camera1); - initialEstimate.insert(PoseKey(2), camera2); - initialEstimate.insert(PointKey(1), landmark1); - initialEstimate.insert(PointKey(2), landmark2); - initialEstimate.insert(PointKey(3), landmark3); - initialEstimate.insert(PointKey(4), landmark4); - - // Create an optimizer and check its error - // We expect the initial to be zero because config is the ground truth - LevenbergMarquardtOptimizer optimizer(graph, initialEstimate); - DOUBLES_EQUAL(0.0, optimizer.error(), 1e-9); - - // Iterate once, and the config should not have changed because we started - // with the ground truth - optimizer.iterate(); - DOUBLES_EQUAL(0.0, optimizer.error(), 1e-9); - - // check if correct - CHECK(assert_equal(initialEstimate, optimizer.values())); -} - -/* ************************************************************************* */ -TEST( Values, update_with_large_delta) { - // this test ensures that if the update for delta is larger than - // the size of the config, it only updates existing variables - Values init; - init.insert(PoseKey(1), Pose3()); - init.insert(PointKey(1), Point3(1.0, 2.0, 3.0)); - - Values expected; - expected.insert(PoseKey(1), Pose3(Rot3(), Point3(0.1, 0.1, 0.1))); - expected.insert(PointKey(1), Point3(1.1, 2.1, 3.1)); - - Ordering largeOrdering; - Values largeValues = init; - largeValues.insert(PoseKey(2), Pose3()); - largeOrdering += PoseKey(1),PointKey(1),PoseKey(2); - VectorValues delta(largeValues.dims(largeOrdering)); - delta[largeOrdering[PoseKey(1)]] = Vector_(6, 0.0, 0.0, 0.0, 0.1, 0.1, 0.1); - delta[largeOrdering[PointKey(1)]] = Vector_(3, 0.1, 0.1, 0.1); - delta[largeOrdering[PoseKey(2)]] = Vector_(6, 0.0, 0.0, 0.0, 100.1, 4.1, 9.1); - Values actual = init.retract(delta, largeOrdering); - - CHECK(assert_equal(expected,actual)); -} - -/* ************************************************************************* */ -int main() { TestResult tr; return TestRegistry::runAllTests(tr); } -/* ************************************************************************* */ diff --git a/gtsam/slam/visualSLAM.cpp b/gtsam/slam/visualSLAM.cpp deleted file mode 100644 index bc2ee199b..000000000 --- a/gtsam/slam/visualSLAM.cpp +++ /dev/null @@ -1,61 +0,0 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) - - * See LICENSE for the license information - - * -------------------------------------------------------------------------- */ - -/** - * @file visualSLAM.cpp - * @date Jan 14, 2010 - * @author richard - */ - -#include -#include - -namespace visualSLAM { - - /* ************************************************************************* */ - void Graph::addMeasurement(const Point2& measured, const SharedNoiseModel& model, - Index poseKey, Index pointKey, const shared_ptrK& K) { - boost::shared_ptr factor(new ProjectionFactor(measured, model, PoseKey(poseKey), PointKey(pointKey), K)); - push_back(factor); - } - - /* ************************************************************************* */ - void Graph::addPoseConstraint(Index poseKey, const Pose3& p) { - boost::shared_ptr factor(new PoseConstraint(PoseKey(poseKey), p)); - push_back(factor); - } - - /* ************************************************************************* */ - void Graph::addPointConstraint(Index pointKey, const Point3& p) { - boost::shared_ptr factor(new PointConstraint(PointKey(pointKey), p)); - push_back(factor); - } - - /* ************************************************************************* */ - void Graph::addPosePrior(Index poseKey, const Pose3& p, const SharedNoiseModel& model) { - boost::shared_ptr factor(new PosePrior(PoseKey(poseKey), p, model)); - push_back(factor); - } - - /* ************************************************************************* */ - void Graph::addPointPrior(Index pointKey, const Point3& p, const SharedNoiseModel& model) { - boost::shared_ptr factor(new PointPrior(PointKey(pointKey), p, model)); - push_back(factor); - } - - /* ************************************************************************* */ - void Graph::addRangeFactor(Index poseKey, Index pointKey, double range, const SharedNoiseModel& model) { - push_back(boost::shared_ptr(new RangeFactor(PoseKey(poseKey), PointKey(pointKey), range, model))); - } - - /* ************************************************************************* */ - -} diff --git a/gtsam/slam/visualSLAM.h b/gtsam/slam/visualSLAM.h deleted file mode 100644 index 38d3312a7..000000000 --- a/gtsam/slam/visualSLAM.h +++ /dev/null @@ -1,142 +0,0 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) - - * See LICENSE for the license information - - * -------------------------------------------------------------------------- */ - -/** - * @file visualSLAM.h - * @brief Basic typedefs for general VisualSLAM problems. Useful for monocular and stereo systems. - * @date Jan 14, 2010 - * @author Richard Roberts - * @author Chris Beall - */ - -#pragma once - -#include -#include -#include -#include -#include -#include -#include -#include -#include - - -namespace visualSLAM { - - using namespace gtsam; - - /// Convenience function for constructing a pose key - inline Symbol PoseKey(Index j) { return Symbol('x', j); } - - /// Convenience function for constructing a pose key - inline Symbol PointKey(Index j) { return Symbol('l', j); } - - /** - * Typedefs that make up the visualSLAM namespace. - */ - typedef NonlinearEquality PoseConstraint; ///< put a hard constraint on a pose - typedef NonlinearEquality PointConstraint; ///< put a hard constraint on a point - typedef PriorFactor PosePrior; ///< put a soft prior on a Pose - typedef PriorFactor PointPrior; ///< put a soft prior on a point - typedef RangeFactor RangeFactor; ///< put a factor on the range from a pose to a point - - /// monocular and stereo camera typedefs for general use - typedef GenericProjectionFactor ProjectionFactor; - typedef GenericStereoFactor StereoFactor; - - /** - * Non-linear factor graph for vanilla visual SLAM - */ - class Graph: public NonlinearFactorGraph { - - public: - /// shared pointer to this type of graph - typedef boost::shared_ptr shared_graph; - - /// default constructor is empty graph - Graph() { - } - - /// print out graph - void print(const std::string& s = "", const KeyFormatter& keyFormatter = DefaultKeyFormatter) const { - NonlinearFactorGraph::print(s, keyFormatter); - } - - /// check if two graphs are equal - bool equals(const Graph& p, double tol = 1e-9) const { - return NonlinearFactorGraph::equals(p, tol); - } - - /** - * Add a projection factor measurement (monocular) - * @param measured the measurement - * @param model the noise model for the measurement - * @param poseKey variable key for the camera pose - * @param pointKey variable key for the landmark - * @param K shared pointer to calibration object - */ - void addMeasurement(const Point2& measured, const SharedNoiseModel& model, - Index poseKey, Index pointKey, const shared_ptrK& K); - - /** - * Add a constraint on a pose (for now, *must* be satisfied in any Values) - * @param key variable key of the camera pose - * @param p to which pose to constrain it to - */ - void addPoseConstraint(Index poseKey, const Pose3& p = Pose3()); - - /** - * Add a constraint on a point (for now, *must* be satisfied in any Values) - * @param key variable key of the landmark - * @param p point around which soft prior is defined - */ - void addPointConstraint(Index pointKey, const Point3& p = Point3()); - - /** - * Add a prior on a pose - * @param key variable key of the camera pose - * @param p around which soft prior is defined - * @param model uncertainty model of this prior - */ - void addPosePrior(Index poseKey, const Pose3& p = Pose3(), const SharedNoiseModel& model = noiseModel::Unit::Create(6)); - - /** - * Add a prior on a landmark - * @param key variable key of the landmark - * @param p to which point to constrain it to - * @param model uncertainty model of this prior - */ - void addPointPrior(Index pointKey, const Point3& p = Point3(), const SharedNoiseModel& model = noiseModel::Unit::Create(3)); - - /** - * Add a range prior to a landmark - * @param poseKey variable key of the camera pose - * @param pointKey variable key of the landmark - * @param range approximate range to landmark - * @param model uncertainty model of this prior - */ - void addRangeFactor(Index poseKey, Index pointKey, double range, const SharedNoiseModel& model = noiseModel::Unit::Create(1)); - - /** - * Optimize the graph - * @param initialEstimate initial estimate of all variables in the graph - * @param pointKey variable key of the landmark - * @param range approximate range to landmark - * @param model uncertainty model of this prior - */ - Values optimize(const Values& initialEstimate) { - return LevenbergMarquardtOptimizer(*this, initialEstimate).optimize(); - } - - }; // Graph - -} // namespaces diff --git a/gtsam_unstable/CMakeLists.txt b/gtsam_unstable/CMakeLists.txt index f7563f8ff..c38015db9 100644 --- a/gtsam_unstable/CMakeLists.txt +++ b/gtsam_unstable/CMakeLists.txt @@ -2,19 +2,26 @@ # and also build tests set (gtsam_unstable_subdirs base - discrete + geometry + discrete +# linear dynamics - slam + nonlinear + slam ) +add_custom_target(check.unstable COMMAND ${CMAKE_CTEST_COMMAND} --output-on-failure) + # assemble core libaries foreach(subdir ${gtsam_unstable_subdirs}) # Build convenience libraries file(GLOB subdir_srcs "${subdir}/*.cpp") - set(${subdir}_srcs ${subdir_srcs}) - if (GTSAM_BUILD_CONVENIENCE_LIBRARIES) + file(GLOB subdir_headers "${subdir}/*.h") + set(${subdir}_srcs ${subdir_srcs} ${subdir_headers}) + gtsam_assign_source_folders("${${subdir}_srcs}") # Create MSVC structure + if (subdir_srcs AND GTSAM_BUILD_CONVENIENCE_LIBRARIES) message(STATUS "Building Convenience Library: ${subdir}_unstable") - add_library("${subdir}_unstable" STATIC ${subdir_srcs}) + add_library("${subdir}_unstable" STATIC ${${subdir}_srcs}) endif() # Build local library and tests @@ -25,12 +32,17 @@ endforeach(subdir) # assemble gtsam_unstable components set(gtsam_unstable_srcs ${base_srcs} + ${geometry_srcs} ${discrete_srcs} ${dynamics_srcs} - ${slam_srcs} + #${linear_srcs} + ${nonlinear_srcs} + ${slam_srcs} ) -option (GTSAM_UNSTABLE_BUILD_SHARED_LIBRARY "Enable/Disable building of a shared version of gtsam_unstable" ON) +if(NOT MSVC) + option (GTSAM_UNSTABLE_BUILD_SHARED_LIBRARY "Enable/Disable building of a shared version of gtsam_unstable" ON) +endif() # Versions - same as core gtsam library set(gtsam_unstable_version ${GTSAM_VERSION_MAJOR}.${GTSAM_VERSION_MINOR}.${GTSAM_VERSION_PATCH}) @@ -47,7 +59,10 @@ set_target_properties(gtsam_unstable-static PROPERTIES VERSION ${gtsam_unstable_version} SOVERSION ${gtsam_unstable_soversion}) target_link_libraries(gtsam_unstable-static gtsam-static) -install(TARGETS gtsam_unstable-static ARCHIVE DESTINATION lib) +set(gtsam_unstable-lib "gtsam_unstable-static") +install(TARGETS gtsam_unstable-static EXPORT GTSAM-exports ARCHIVE DESTINATION lib) +list(APPEND GTSAM_EXPORTED_TARGETS gtsam_unstable-static) +set(GTSAM_EXPORTED_TARGETS "${GTSAM_EXPORTED_TARGETS}" PARENT_SCOPE) if (GTSAM_UNSTABLE_BUILD_SHARED_LIBRARY) message(STATUS "Building GTSAM_UNSTABLE - shared") @@ -58,39 +73,27 @@ if (GTSAM_UNSTABLE_BUILD_SHARED_LIBRARY) VERSION ${gtsam_unstable_version} SOVERSION ${gtsam_unstable_soversion}) target_link_libraries(gtsam_unstable-shared gtsam-shared) - install(TARGETS gtsam_unstable-shared LIBRARY DESTINATION lib ) + install(TARGETS gtsam_unstable-shared EXPORT GTSAM-exports LIBRARY DESTINATION lib ARCHIVE DESTINATION lib RUNTIME DESTINATION bin) + list(APPEND GTSAM_EXPORTED_TARGETS gtsam_unstable-shared) + set(GTSAM_EXPORTED_TARGETS "${GTSAM_EXPORTED_TARGETS}" PARENT_SCOPE) endif(GTSAM_UNSTABLE_BUILD_SHARED_LIBRARY) # Wrap version for gtsam_unstable -if (GTSAM_BUILD_WRAP) +if (GTSAM_INSTALL_MATLAB_TOOLBOX) # Set up codegen include(GtsamMatlabWrap) - # Wrap codegen - #usage: wrap mexExtension interfacePath moduleName toolboxPath - # mexExtension : OS/CPU-dependent extension for MEX binaries - # interfacePath : *absolute* path to directory of module interface file - # moduleName : the name of the module, interface file must be called moduleName.h - # toolboxPath : the directory in which to generate the wrappers - # [mexFlags] : extra flags for the mex command - # TODO: generate these includes programmatically - set(mexFlags "-I${Boost_INCLUDE_DIR} -I${CMAKE_INSTALL_PREFIX}/include -I${CMAKE_INSTALL_PREFIX}/include/gtsam_unstable -I${CMAKE_INSTALL_PREFIX}/include/gtsam_unstable/dynamics -I${CMAKE_INSTALL_PREFIX}/include/gtsam_unstable/discrete -L${CMAKE_INSTALL_PREFIX}/lib -lgtsam -lgtsam_unstable") - set(toolbox_path ${CMAKE_BINARY_DIR}/wrap/gtsam_unstable) - set(moduleName gtsam_unstable) + # Choose include flags depending on build process + set(MEX_INCLUDE_ROOT ${GTSAM_SOURCE_ROOT_DIR}) + set(MEX_LIB_ROOT ${CMAKE_BINARY_DIR}) + set(GTSAM_LIB_DIR ${MEX_LIB_ROOT}/gtsam) + set(GTSAM_UNSTABLE_LIB_DIR ${MEX_LIB_ROOT}/gtsam_unstable) - find_mexextension() + # Generate, build and install toolbox + set(mexFlags -I${Boost_INCLUDE_DIR} -I${MEX_INCLUDE_ROOT}) - # Code generation command - add_custom_target(wrap_gtsam_unstable ALL COMMAND - ${CMAKE_BINARY_DIR}/wrap/wrap ${GTSAM_MEX_BIN_EXTENSION} ${CMAKE_CURRENT_SOURCE_DIR} ${moduleName} ${toolbox_path} "${mexFlags}" - DEPENDS wrap) - - if (GTSAM_INSTALL_MATLAB_TOOLBOX) - # Primary toolbox files - message(STATUS "Installing Matlab Toolbox to ${GTSAM_TOOLBOX_INSTALL_PATH}") - install(DIRECTORY DESTINATION ${GTSAM_TOOLBOX_INSTALL_PATH}) # make an empty folder - # exploit need for trailing slash to specify a full folder, rather than just its contents to copy - install(DIRECTORY ${toolbox_path} DESTINATION ${GTSAM_TOOLBOX_INSTALL_PATH}) - endif (GTSAM_INSTALL_MATLAB_TOOLBOX) -endif(GTSAM_BUILD_WRAP) + # Macro to handle details of setting up targets + wrap_library(gtsam_unstable "${mexFlags}" "./" gtsam) + +endif(GTSAM_INSTALL_MATLAB_TOOLBOX) diff --git a/gtsam_unstable/base/BTree.h b/gtsam_unstable/base/BTree.h index 2a40465a3..379725a7a 100644 --- a/gtsam_unstable/base/BTree.h +++ b/gtsam_unstable/base/BTree.h @@ -26,7 +26,7 @@ namespace gtsam { /** * @brief Binary tree - * @ingroup base + * @addtogroup base */ template class BTree { diff --git a/gtsam_unstable/base/CMakeLists.txt b/gtsam_unstable/base/CMakeLists.txt index 7e455e9bf..0545cd4c9 100644 --- a/gtsam_unstable/base/CMakeLists.txt +++ b/gtsam_unstable/base/CMakeLists.txt @@ -16,4 +16,4 @@ set (base_excluded_tests "") # Add all tests gtsam_add_subdir_tests(base_unstable "${base_local_libs}" "${base_full_libs}" "${base_excluded_tests}") - +add_dependencies(check.unstable check.base_unstable) diff --git a/gtsam_unstable/base/DSF.h b/gtsam_unstable/base/DSF.h index 5276779b0..0c7cc7399 100644 --- a/gtsam_unstable/base/DSF.h +++ b/gtsam_unstable/base/DSF.h @@ -34,7 +34,7 @@ namespace gtsam { * S = {S_1,S_2,...} of disjoint dynamic sets. Each set is identified by * a representative, which is some member of the set. * - * @ingroup base + * @addtogroup base */ template class DSF : protected BTree { diff --git a/gtsam_unstable/base/Dummy.cpp b/gtsam_unstable/base/Dummy.cpp new file mode 100644 index 000000000..90d71d27e --- /dev/null +++ b/gtsam_unstable/base/Dummy.cpp @@ -0,0 +1,43 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file Dummy.h + * @brief Dummy class for testing MATLAB memory allocation + * @author Andrew Melim + * @author Frank Dellaert + * @date June 14, 2012 + */ + +#include +#include + +namespace gtsam { + +static size_t gDummyCount = 0; + +Dummy::Dummy():id(++gDummyCount) { + std::cout << "Dummy constructor " << id << std::endl; +} + +Dummy::~Dummy() { + std::cout << "Dummy destructor " << id << std::endl; +} + +void Dummy::print(const std::string& s) const { + std::cout << s << "Dummy " << id << std::endl; +} + +unsigned char Dummy::dummyTwoVar(unsigned char a) const { + return a; +} + +} diff --git a/gtsam_unstable/base/Dummy.h b/gtsam_unstable/base/Dummy.h new file mode 100644 index 000000000..0ab344f74 --- /dev/null +++ b/gtsam_unstable/base/Dummy.h @@ -0,0 +1,33 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file Dummy.h + * @brief Dummy class for testing MATLAB memory allocation + * @author Andrew Melim + * @author Frank Dellaert + * @date June 14, 2012 + */ + +#include + +namespace gtsam { + + struct Dummy { + size_t id; + Dummy(); + ~Dummy(); + void print(const std::string& s="") const ; + unsigned char dummyTwoVar(unsigned char a) const ; + }; + +} // namespace gtsam + diff --git a/gtsam_unstable/discrete/AllDiff.cpp b/gtsam_unstable/discrete/AllDiff.cpp index 46efd4499..ac412fa7f 100644 --- a/gtsam_unstable/discrete/AllDiff.cpp +++ b/gtsam_unstable/discrete/AllDiff.cpp @@ -20,10 +20,11 @@ namespace gtsam { } /* ************************************************************************* */ - void AllDiff::print(const std::string& s) const { - std::cout << s << ": AllDiff on "; + void AllDiff::print(const std::string& s, + const IndexFormatter& formatter) const { + std::cout << s << "AllDiff on "; BOOST_FOREACH (Index dkey, keys_) - std::cout << dkey << " "; + std::cout << formatter(dkey) << " "; std::cout << std::endl; } @@ -39,14 +40,14 @@ namespace gtsam { } /* ************************************************************************* */ - AllDiff::operator DecisionTreeFactor() const { + DecisionTreeFactor AllDiff::toDecisionTreeFactor() const { // We will do this by converting the allDif into many BinaryAllDiff constraints DecisionTreeFactor converted; size_t nrKeys = keys_.size(); for (size_t i1 = 0; i1 < nrKeys; i1++) for (size_t i2 = i1 + 1; i2 < nrKeys; i2++) { BinaryAllDiff binary12(discreteKey(i1),discreteKey(i2)); - converted = converted * binary12; + converted = converted * binary12.toDecisionTreeFactor(); } return converted; } @@ -54,7 +55,7 @@ namespace gtsam { /* ************************************************************************* */ DecisionTreeFactor AllDiff::operator*(const DecisionTreeFactor& f) const { // TODO: can we do this more efficiently? - return DecisionTreeFactor(*this) * f; + return toDecisionTreeFactor() * f; } /* ************************************************************************* */ diff --git a/gtsam_unstable/discrete/AllDiff.h b/gtsam_unstable/discrete/AllDiff.h index 4f4e10511..1a560ace2 100644 --- a/gtsam_unstable/discrete/AllDiff.h +++ b/gtsam_unstable/discrete/AllDiff.h @@ -34,13 +34,14 @@ namespace gtsam { AllDiff(const DiscreteKeys& dkeys); // print - virtual void print(const std::string& s = "") const; + virtual void print(const std::string& s = "", + const IndexFormatter& formatter = DefaultIndexFormatter) const; /// Calculate value = expensive ! virtual double operator()(const Values& values) const; /// Convert into a decisiontree, can be *very* expensive ! - virtual operator DecisionTreeFactor() const; + virtual DecisionTreeFactor toDecisionTreeFactor() const; /// Multiply into a decisiontree virtual DecisionTreeFactor operator*(const DecisionTreeFactor& f) const; diff --git a/gtsam_unstable/discrete/BinaryAllDiff.h b/gtsam_unstable/discrete/BinaryAllDiff.h index 04eeba953..9ed2f79f1 100644 --- a/gtsam_unstable/discrete/BinaryAllDiff.h +++ b/gtsam_unstable/discrete/BinaryAllDiff.h @@ -33,9 +33,10 @@ namespace gtsam { } // print - virtual void print(const std::string& s = "") const { - std::cout << s << ": BinaryAllDiff on " << keys_[0] << " and " << keys_[1] - << std::endl; + virtual void print(const std::string& s = "", + const IndexFormatter& formatter = DefaultIndexFormatter) const { + std::cout << s << "BinaryAllDiff on " << formatter(keys_[0]) << " and " + << formatter(keys_[1]) << std::endl; } /// Calculate value @@ -44,7 +45,7 @@ namespace gtsam { } /// Convert into a decisiontree - virtual operator DecisionTreeFactor() const { + virtual DecisionTreeFactor toDecisionTreeFactor() const { DiscreteKeys keys; keys.push_back(DiscreteKey(keys_[0],cardinality0_)); keys.push_back(DiscreteKey(keys_[1],cardinality1_)); @@ -59,7 +60,7 @@ namespace gtsam { /// Multiply into a decisiontree virtual DecisionTreeFactor operator*(const DecisionTreeFactor& f) const { // TODO: can we do this more efficiently? - return DecisionTreeFactor(*this) * f; + return toDecisionTreeFactor() * f; } /* diff --git a/gtsam_unstable/discrete/CMakeLists.txt b/gtsam_unstable/discrete/CMakeLists.txt index b049562a5..ae84426a8 100644 --- a/gtsam_unstable/discrete/CMakeLists.txt +++ b/gtsam_unstable/discrete/CMakeLists.txt @@ -16,16 +16,36 @@ set (discrete_full_libs gtsam_unstable-static) # Exclude tests that don't work -set (discrete_excluded_tests "${CMAKE_CURRENT_SOURCE_DIR}/tests/testScheduler.cpp") +#set (discrete_excluded_tests +#"${CMAKE_CURRENT_SOURCE_DIR}/tests/testScheduler.cpp" +#) + # Add all tests gtsam_add_subdir_tests(discrete_unstable "${discrete_local_libs}" "${discrete_full_libs}" "${discrete_excluded_tests}") +add_dependencies(check.unstable check.discrete_unstable) -# add examples -foreach(example schedulingExample schedulingQuals12) - add_executable(${example} "examples/${example}.cpp") - add_dependencies(${example} gtsam-static gtsam_unstable-static) - target_link_libraries(${example} gtsam-static gtsam_unstable-static) - add_custom_target(${example}.run ${EXECUTABLE_OUTPUT_PATH}${example} ${ARGN}) -endforeach(example) +# List examples to build - comment out here to exclude from compilation +set(discrete_unstable_examples +schedulingExample +schedulingQuals12 +) +if (GTSAM_BUILD_EXAMPLES) + foreach(example ${discrete_unstable_examples}) + add_executable(${example} "examples/${example}.cpp") + + # Disable building during make all/install + if (GTSAM_ENABLE_INSTALL_EXAMPLE_FIX) + set_target_properties(${example} PROPERTIES EXCLUDE_FROM_ALL ON) + endif() + + if(NOT MSVC) + add_dependencies(examples ${example}) + add_custom_target(${example}.run ${EXECUTABLE_OUTPUT_PATH}${example} ${ARGN}) + endif() + + add_dependencies(${example} gtsam-static gtsam_unstable-static) + target_link_libraries(${example} gtsam-static gtsam_unstable-static) + endforeach(example) +endif (GTSAM_BUILD_EXAMPLES) diff --git a/gtsam_unstable/discrete/CSP.cpp b/gtsam_unstable/discrete/CSP.cpp index 4da2f440a..20c0e7617 100644 --- a/gtsam_unstable/discrete/CSP.cpp +++ b/gtsam_unstable/discrete/CSP.cpp @@ -11,6 +11,8 @@ #include #include +using namespace std; + namespace gtsam { /// Find the best total assignment - can be expensive @@ -49,8 +51,9 @@ namespace gtsam { // if not already a singleton if (!domains[v].isSingleton()) { // get the constraint and call its ensureArcConsistency method - Constraint::shared_ptr factor = (*this)[f]; - changed[v] = factor->ensureArcConsistency(v,domains) || changed[v]; + Constraint::shared_ptr constraint = boost::dynamic_pointer_cast((*this)[f]); + if (!constraint) throw runtime_error("CSP:runArcConsistency: non-constraint factor"); + changed[v] = constraint->ensureArcConsistency(v,domains) || changed[v]; } } // f if (changed[v]) anyChange = true; @@ -59,8 +62,8 @@ namespace gtsam { // TODO: Sudoku specific hack if (print) { if (cardinality == 9 && n == 81) { - for (size_t i = 0, v = 0; i < sqrt(n); i++) { - for (size_t j = 0; j < sqrt(n); j++, v++) { + for (size_t i = 0, v = 0; i < (size_t)std::sqrt((double)n); i++) { + for (size_t j = 0; j < (size_t)std::sqrt((double)n); j++, v++) { if (changed[v]) cout << "*"; domains[v].print(); cout << "\t"; @@ -84,8 +87,10 @@ namespace gtsam { // TODO: create a new ordering as we go, to ensure a connected graph // KeyOrdering ordering; // vector dkeys; - BOOST_FOREACH(const Constraint::shared_ptr& factor, factors_) { - Constraint::shared_ptr reduced = factor->partiallyApply(domains); + BOOST_FOREACH(const DiscreteFactor::shared_ptr& f, factors_) { + Constraint::shared_ptr constraint = boost::dynamic_pointer_cast(f); + if (!constraint) throw runtime_error("CSP:runArcConsistency: non-constraint factor"); + Constraint::shared_ptr reduced = constraint->partiallyApply(domains); if (print) reduced->print(); } #endif diff --git a/gtsam_unstable/discrete/CSP.h b/gtsam_unstable/discrete/CSP.h index e2e2a2251..ef4bbc17a 100644 --- a/gtsam_unstable/discrete/CSP.h +++ b/gtsam_unstable/discrete/CSP.h @@ -18,7 +18,7 @@ namespace gtsam { * A specialization of a DiscreteFactorGraph. * It knows about CSP-specific constraints and algorithms */ - class CSP: public FactorGraph { + class CSP: public DiscreteFactorGraph { public: /** A map from keys to values */ @@ -27,30 +27,10 @@ namespace gtsam { typedef boost::shared_ptr sharedValues; public: - /// Constructor - CSP() { - } - template - void add(const DiscreteKey& j, SOURCE table) { - DiscreteKeys keys; - keys.push_back(j); - push_back(boost::make_shared(keys, table)); - } - - template - void add(const DiscreteKey& j1, const DiscreteKey& j2, SOURCE table) { - DiscreteKeys keys; - keys.push_back(j1); - keys.push_back(j2); - push_back(boost::make_shared(keys, table)); - } - - /** add shared discreteFactor immediately from arguments */ - template - void add(const DiscreteKeys& keys, SOURCE table) { - push_back(boost::make_shared(keys, table)); - } +// /// Constructor +// CSP() { +// } /// Add a unary constraint, allowing only a single value void addSingleValue(const DiscreteKey& dkey, size_t value) { @@ -71,19 +51,28 @@ namespace gtsam { push_back(factor); } +// /** return product of all factors as a single factor */ +// DecisionTreeFactor product() const { +// DecisionTreeFactor result; +// BOOST_FOREACH(const sharedFactor& factor, *this) +// if (factor) result = (*factor) * result; +// return result; +// } + /// Find the best total assignment - can be expensive sharedValues optimalAssignment() const; - /* - * Perform loopy belief propagation - * True belief propagation would check for each value in domain - * whether any satisfying separator assignment can be found. - * This corresponds to hyper-arc consistency in CSP speak. - * This can be done by creating a mini-factor graph and search. - * For a nine-by-nine Sudoku, the search tree will be 8+6+6=20 levels deep. - * It will be very expensive to exclude values that way. - */ - // void applyBeliefPropagation(size_t nrIterations = 10) const; +// /* +// * Perform loopy belief propagation +// * True belief propagation would check for each value in domain +// * whether any satisfying separator assignment can be found. +// * This corresponds to hyper-arc consistency in CSP speak. +// * This can be done by creating a mini-factor graph and search. +// * For a nine-by-nine Sudoku, the search tree will be 8+6+6=20 levels deep. +// * It will be very expensive to exclude values that way. +// */ +// void applyBeliefPropagation(size_t nrIterations = 10) const; + /* * Apply arc-consistency ~ Approximate loopy belief propagation * We need to give the domains to a constraint, and it returns @@ -92,7 +81,7 @@ namespace gtsam { */ void runArcConsistency(size_t cardinality, size_t nrIterations = 10, bool print = false) const; - }; + }; // CSP } // gtsam diff --git a/gtsam_unstable/discrete/Domain.cpp b/gtsam_unstable/discrete/Domain.cpp index fd2631cec..dbc05e3f6 100644 --- a/gtsam_unstable/discrete/Domain.cpp +++ b/gtsam_unstable/discrete/Domain.cpp @@ -15,9 +15,10 @@ namespace gtsam { using namespace std; /* ************************************************************************* */ - void Domain::print(const string& s) const { -// cout << s << ": Domain on " << keys_[0] << " (j=" << keys_[0] -// << ") with values"; + void Domain::print(const string& s, + const IndexFormatter& formatter) const { +// cout << s << ": Domain on " << formatter(keys_[0]) << " (j=" << +// formatter(keys_[0]) << ") with values"; // BOOST_FOREACH (size_t v,values_) cout << " " << v; // cout << endl; BOOST_FOREACH (size_t v,values_) cout << v; @@ -29,7 +30,7 @@ namespace gtsam { } /* ************************************************************************* */ - Domain::operator DecisionTreeFactor() const { + DecisionTreeFactor Domain::toDecisionTreeFactor() const { DiscreteKeys keys; keys += DiscreteKey(keys_[0],cardinality_); vector table; @@ -42,7 +43,7 @@ namespace gtsam { /* ************************************************************************* */ DecisionTreeFactor Domain::operator*(const DecisionTreeFactor& f) const { // TODO: can we do this more efficiently? - return DecisionTreeFactor(*this) * f; + return toDecisionTreeFactor() * f; } /* ************************************************************************* */ diff --git a/gtsam_unstable/discrete/Domain.h b/gtsam_unstable/discrete/Domain.h index 50c534f8a..85b35fe8c 100644 --- a/gtsam_unstable/discrete/Domain.h +++ b/gtsam_unstable/discrete/Domain.h @@ -66,7 +66,8 @@ namespace gtsam { } // print - virtual void print(const std::string& s = "") const; + virtual void print(const std::string& s = "", + const IndexFormatter& formatter = DefaultIndexFormatter) const; bool contains(size_t value) const { return values_.count(value)>0; @@ -76,7 +77,7 @@ namespace gtsam { virtual double operator()(const Values& values) const; /// Convert into a decisiontree - virtual operator DecisionTreeFactor() const; + virtual DecisionTreeFactor toDecisionTreeFactor() const; /// Multiply into a decisiontree virtual DecisionTreeFactor operator*(const DecisionTreeFactor& f) const; diff --git a/gtsam_unstable/discrete/Scheduler.cpp b/gtsam_unstable/discrete/Scheduler.cpp index 678ba1580..d551b1f0b 100644 --- a/gtsam_unstable/discrete/Scheduler.cpp +++ b/gtsam_unstable/discrete/Scheduler.cpp @@ -105,7 +105,6 @@ namespace gtsam { /** Add student-specific constraints to the graph */ void Scheduler::addStudentSpecificConstraints(size_t i, boost::optional slot) { -#ifdef BROKEN bool debug = ISDEBUG("Scheduler::buildGraph"); assert(i table; @@ -40,7 +41,7 @@ namespace gtsam { /* ************************************************************************* */ DecisionTreeFactor SingleValue::operator*(const DecisionTreeFactor& f) const { // TODO: can we do this more efficiently? - return DecisionTreeFactor(*this) * f; + return toDecisionTreeFactor() * f; } /* ************************************************************************* */ diff --git a/gtsam_unstable/discrete/SingleValue.h b/gtsam_unstable/discrete/SingleValue.h index 3f7f3011d..1f6e362aa 100644 --- a/gtsam_unstable/discrete/SingleValue.h +++ b/gtsam_unstable/discrete/SingleValue.h @@ -42,13 +42,14 @@ namespace gtsam { } // print - virtual void print(const std::string& s = "") const; + virtual void print(const std::string& s = "", + const IndexFormatter& formatter = DefaultIndexFormatter) const; /// Calculate value virtual double operator()(const Values& values) const; /// Convert into a decisiontree - virtual operator DecisionTreeFactor() const; + virtual DecisionTreeFactor toDecisionTreeFactor() const; /// Multiply into a decisiontree virtual DecisionTreeFactor operator*(const DecisionTreeFactor& f) const; diff --git a/gtsam_unstable/discrete/examples/schedulingExample.cpp b/gtsam_unstable/discrete/examples/schedulingExample.cpp index 485f0ea1c..0f9854007 100644 --- a/gtsam_unstable/discrete/examples/schedulingExample.cpp +++ b/gtsam_unstable/discrete/examples/schedulingExample.cpp @@ -151,9 +151,9 @@ void solveStaged(size_t addMutex = 2) { scheduler.buildGraph(addMutex); // Do EXACT INFERENCE - tic_("eliminate"); + tic_(3,"eliminate"); DiscreteBayesNet::shared_ptr chordal = scheduler.eliminate(); - toc_("eliminate"); + toc_(3,"eliminate"); // find root node DiscreteConditional::shared_ptr root = *(chordal->rbegin()); diff --git a/gtsam_unstable/discrete/examples/schedulingQuals12.cpp b/gtsam_unstable/discrete/examples/schedulingQuals12.cpp index d0fa041c9..4221eb755 100644 --- a/gtsam_unstable/discrete/examples/schedulingQuals12.cpp +++ b/gtsam_unstable/discrete/examples/schedulingQuals12.cpp @@ -178,9 +178,9 @@ void solveStaged(size_t addMutex = 2) { scheduler.buildGraph(addMutex); // Do EXACT INFERENCE - tic_("eliminate"); + tic_(3,"eliminate"); DiscreteBayesNet::shared_ptr chordal = scheduler.eliminate(); - toc_("eliminate"); + toc_(3,"eliminate"); // find root node DiscreteConditional::shared_ptr root = *(chordal->rbegin()); diff --git a/gtsam_unstable/discrete/tests/testCSP.cpp b/gtsam_unstable/discrete/tests/testCSP.cpp index 46bf61240..f446932e2 100644 --- a/gtsam_unstable/discrete/tests/testCSP.cpp +++ b/gtsam_unstable/discrete/tests/testCSP.cpp @@ -7,6 +7,8 @@ #include #include +#include +using boost::assign::insert; #include #include #include @@ -25,12 +27,12 @@ TEST_UNSAFE( BinaryAllDif, allInOne) // Check construction and conversion BinaryAllDiff c1(ID, UT); DecisionTreeFactor f1(ID & UT, "0 1 1 0"); - EXPECT(assert_equal(f1,(DecisionTreeFactor)c1)); + EXPECT(assert_equal(f1,c1.toDecisionTreeFactor())); // Check construction and conversion BinaryAllDiff c2(UT, AZ); DecisionTreeFactor f2(UT & AZ, "0 1 1 0"); - EXPECT(assert_equal(f2,(DecisionTreeFactor)c2)); + EXPECT(assert_equal(f2,c2.toDecisionTreeFactor())); DecisionTreeFactor f3 = f1*f2; EXPECT(assert_equal(f3,c1*f2)); @@ -146,16 +148,16 @@ TEST_UNSAFE( CSP, AllDiff) dkeys += ID,UT,AZ; csp.addAllDiff(dkeys); csp.addSingleValue(AZ,2); - //GTSAM_PRINT(csp); +// GTSAM_PRINT(csp); // Check construction and conversion SingleValue s(AZ,2); DecisionTreeFactor f1(AZ,"0 0 1"); - EXPECT(assert_equal(f1,(DecisionTreeFactor)s)); + EXPECT(assert_equal(f1,s.toDecisionTreeFactor())); // Check construction and conversion AllDiff alldiff(dkeys); - DecisionTreeFactor actual = (DecisionTreeFactor)alldiff; + DecisionTreeFactor actual = alldiff.toDecisionTreeFactor(); // GTSAM_PRINT(actual); // actual.dot("actual"); DecisionTreeFactor f2(ID & AZ & UT, @@ -200,16 +202,16 @@ TEST_UNSAFE( CSP, AllDiff) known[AZ.first] = 2; DiscreteFactor::shared_ptr reduced1 = alldiff.partiallyApply(known); DecisionTreeFactor f3(ID & UT, "0 1 1 1 0 1 1 1 0"); - EXPECT(assert_equal(f3,reduced1->operator DecisionTreeFactor())); + EXPECT(assert_equal(f3,reduced1->toDecisionTreeFactor())); DiscreteFactor::shared_ptr reduced2 = singleValue.partiallyApply(known); DecisionTreeFactor f4(AZ, "0 0 1"); - EXPECT(assert_equal(f4,reduced2->operator DecisionTreeFactor())); + EXPECT(assert_equal(f4,reduced2->toDecisionTreeFactor())); // Parial application, version 2 DiscreteFactor::shared_ptr reduced3 = alldiff.partiallyApply(domains); - EXPECT(assert_equal(f3,reduced3->operator DecisionTreeFactor())); + EXPECT(assert_equal(f3,reduced3->toDecisionTreeFactor())); DiscreteFactor::shared_ptr reduced4 = singleValue.partiallyApply(domains); - EXPECT(assert_equal(f4,reduced4->operator DecisionTreeFactor())); + EXPECT(assert_equal(f4,reduced4->toDecisionTreeFactor())); // full arc-consistency test csp.runArcConsistency(nrColors); diff --git a/gtsam_unstable/discrete/tests/testPlanning.cpp b/gtsam_unstable/discrete/tests/testPlanning.cpp new file mode 100644 index 000000000..2ad1ff9ae --- /dev/null +++ b/gtsam_unstable/discrete/tests/testPlanning.cpp @@ -0,0 +1,37 @@ +/* + * testPlanning.cpp + * @brief develop code for planning example + * @date Feb 13, 2012 + * @author Frank Dellaert + */ + +//#include +#include +#include +#include +#include + +using namespace std; +using namespace gtsam; + +/* ************************************************************************* */ +TEST_UNSAFE(Planner, allInOne) +{ + // A small planning problem + // First variable is location + DiscreteKey location(0,3), + haveRock(1,2), haveSoil(2,2), haveImage(3,2), + commRock(4,2), commSoil(5,2), commImage(6,2); + + // There are 3 actions: + // Drive, communicate, sample +} + + +/* ************************************************************************* */ +int main() { + TestResult tr; + return TestRegistry::runAllTests(tr); +} +/* ************************************************************************* */ + diff --git a/gtsam_unstable/discrete/tests/testScheduler.cpp b/gtsam_unstable/discrete/tests/testScheduler.cpp index bf9273ad6..6559754d5 100644 --- a/gtsam_unstable/discrete/tests/testScheduler.cpp +++ b/gtsam_unstable/discrete/tests/testScheduler.cpp @@ -149,7 +149,7 @@ TEST( schedulingExample, test) /* ************************************************************************* */ TEST( schedulingExample, smallFromFile) { - string path("../../../gtsam_unstable/discrete/examples/"); + string path(TOPSRCDIR "/gtsam_unstable/discrete/examples/"); Scheduler s(2, path + "small.csv"); // add areas diff --git a/gtsam_unstable/discrete/tests/testSudoku.cpp b/gtsam_unstable/discrete/tests/testSudoku.cpp index 1bbac4777..1e4026e7f 100644 --- a/gtsam_unstable/discrete/tests/testSudoku.cpp +++ b/gtsam_unstable/discrete/tests/testSudoku.cpp @@ -7,6 +7,8 @@ #include #include +#include +using boost::assign::insert; #include #include #include @@ -14,6 +16,8 @@ using namespace std; using namespace gtsam; +#define PRINT false + class Sudoku: public CSP { /// sudoku size @@ -73,7 +77,7 @@ public: } // add box constraints - size_t N = sqrt(n), i0 = 0; + size_t N = (size_t)sqrt(double(n)), i0 = 0; for (size_t I = 0; I < N; I++) { size_t j0 = 0; for (size_t J = 0; J < N; J++) { @@ -119,7 +123,7 @@ TEST_UNSAFE( Sudoku, small) 0,1, 0,0); // Do BP - csp.runArcConsistency(4); + csp.runArcConsistency(4,10,PRINT); // optimize and check CSP::sharedValues solution = csp.optimalAssignment(); @@ -150,7 +154,7 @@ TEST_UNSAFE( Sudoku, easy) 5,0,0, 0,3,0, 7,0,0); // Do BP - sudoku.runArcConsistency(4); + sudoku.runArcConsistency(4,10,PRINT); // sudoku.printSolution(); // don't do it } @@ -172,7 +176,7 @@ TEST_UNSAFE( Sudoku, extreme) 0,0,0, 2,7,5, 9,0,0); // Do BP - sudoku.runArcConsistency(9,10,false); + sudoku.runArcConsistency(9,10,PRINT); #ifdef METIS VariableIndex index(sudoku); @@ -201,7 +205,7 @@ TEST_UNSAFE( Sudoku, AJC_3star_Feb8_2012) 0,0,0, 1,0,0, 0,3,7); // Do BP - sudoku.runArcConsistency(9,10,true); + sudoku.runArcConsistency(9,10,PRINT); //sudoku.printSolution(); // don't do it } diff --git a/gtsam_unstable/dynamics/CMakeLists.txt b/gtsam_unstable/dynamics/CMakeLists.txt index 66d0b9ac1..d0d45e0e4 100644 --- a/gtsam_unstable/dynamics/CMakeLists.txt +++ b/gtsam_unstable/dynamics/CMakeLists.txt @@ -23,4 +23,4 @@ set (dynamics_excluded_tests "") # Add all tests gtsam_add_subdir_tests(dynamics_unstable "${dynamics_local_libs}" "${dynamics_full_libs}" "${dynamics_excluded_tests}") - +add_dependencies(check.unstable check.dynamics_unstable) diff --git a/gtsam_unstable/dynamics/DynamicsPriors.h b/gtsam_unstable/dynamics/DynamicsPriors.h index 2d0f9e6a6..ccf7063dc 100644 --- a/gtsam_unstable/dynamics/DynamicsPriors.h +++ b/gtsam_unstable/dynamics/DynamicsPriors.h @@ -9,7 +9,7 @@ #pragma once -#include +#include #include diff --git a/gtsam_unstable/dynamics/FullIMUFactor.h b/gtsam_unstable/dynamics/FullIMUFactor.h index 29b77c661..f42ecc352 100644 --- a/gtsam_unstable/dynamics/FullIMUFactor.h +++ b/gtsam_unstable/dynamics/FullIMUFactor.h @@ -51,9 +51,14 @@ public: virtual ~FullIMUFactor() {} + /// @return a deep copy of this factor + virtual gtsam::NonlinearFactor::shared_ptr clone() const { + return boost::static_pointer_cast( + gtsam::NonlinearFactor::shared_ptr(new This(*this))); } + /** Check if two factors are equal */ virtual bool equals(const NonlinearFactor& e, double tol = 1e-9) const { - const This* const f = dynamic_cast(&e); + const This* const f = dynamic_cast(&e); return f && Base::equals(e) && equal_with_abs_tol(accel_, f->accel_, tol) && equal_with_abs_tol(gyro_, f->gyro_, tol) && @@ -72,8 +77,6 @@ public: const Vector& gyro() const { return gyro_; } const Vector& accel() const { return accel_; } Vector z() const { return concatVectors(2, &accel_, &gyro_); } - const Key& key1() const { return this->key1_; } - const Key& key2() const { return this->key2_; } /** * Error evaluation with optional derivatives - calculates diff --git a/gtsam_unstable/dynamics/IMUFactor.h b/gtsam_unstable/dynamics/IMUFactor.h index 7ded5ef82..9e5651cc9 100644 --- a/gtsam_unstable/dynamics/IMUFactor.h +++ b/gtsam_unstable/dynamics/IMUFactor.h @@ -44,9 +44,14 @@ public: virtual ~IMUFactor() {} + /// @return a deep copy of this factor + virtual gtsam::NonlinearFactor::shared_ptr clone() const { + return boost::static_pointer_cast( + gtsam::NonlinearFactor::shared_ptr(new This(*this))); } + /** Check if two factors are equal */ virtual bool equals(const NonlinearFactor& e, double tol = 1e-9) const { - const This* const f = dynamic_cast(&e); + const This* const f = dynamic_cast(&e); return f && Base::equals(e) && equal_with_abs_tol(accel_, f->accel_, tol) && equal_with_abs_tol(gyro_, f->gyro_, tol) && @@ -65,8 +70,6 @@ public: const Vector& gyro() const { return gyro_; } const Vector& accel() const { return accel_; } Vector z() const { return concatVectors(2, &accel_, &gyro_); } - const Key& key1() const { return this->key1_; } - const Key& key2() const { return this->key2_; } /** * Error evaluation with optional derivatives - calculates diff --git a/gtsam_unstable/dynamics/PoseRTV.cpp b/gtsam_unstable/dynamics/PoseRTV.cpp index 4ab4bcf1d..c10885fc0 100644 --- a/gtsam_unstable/dynamics/PoseRTV.cpp +++ b/gtsam_unstable/dynamics/PoseRTV.cpp @@ -10,7 +10,6 @@ #include #include -#include #include namespace gtsam { @@ -201,7 +200,7 @@ Vector PoseRTV::imuPrediction(const PoseRTV& x2, double dt) const { // rotation rates // just using euler angles based on matlab code // FIXME: this is silly - we shouldn't use differences in Euler angles - Matrix Enb = dynamics::RRTMnb(r1); + Matrix Enb = RRTMnb(r1); Vector euler1 = r1.xyz(), euler2 = r2.xyz(); Vector dR = euler2 - euler1; @@ -258,7 +257,7 @@ PoseRTV PoseRTV::transformed_from(const Pose3& trans, } if (Dtrans) { - *Dtrans = numericalDerivative22(transformed_from_, *this, trans, 1e-6); + *Dtrans = numericalDerivative22(transformed_from_, *this, trans, 1e-8); // // *Dtrans = zeros(9,6); // // directly affecting the pose @@ -276,4 +275,39 @@ PoseRTV PoseRTV::transformed_from(const Pose3& trans, return PoseRTV(newpose, newvel); } +/* ************************************************************************* */ +Matrix PoseRTV::RRTMbn(const Vector& euler) { + assert(euler.size() == 3); + const double s1 = sin(euler(1-1)), c1 = cos(euler(1-1)); + const double t2 = tan(euler(2-1)), c2 = cos(euler(2-1)); + Matrix Ebn(3,3); + Ebn << 1.0, s1 * t2, c1 * t2, + 0.0, c1, -s1, + 0.0, s1 / c2, c1 / c2; + return Ebn; +} + +/* ************************************************************************* */ +Matrix PoseRTV::RRTMbn(const Rot3& att) { + return PoseRTV::RRTMbn(att.rpy()); +} + +/* ************************************************************************* */ +Matrix PoseRTV::RRTMnb(const Vector& euler) { + assert(euler.size() == 3); + Matrix Enb(3,3); + const double s1 = sin(euler(1-1)), c1 = cos(euler(1-1)); + const double s2 = sin(euler(2-1)), c2 = cos(euler(2-1)); + Enb << 1.0, 0.0, -s2, + 0.0, c1, s1*c2, + 0.0, -s1, c1*c2; + return Enb; +} + +/* ************************************************************************* */ +Matrix PoseRTV::RRTMnb(const Rot3& att) { + return PoseRTV::RRTMnb(att.rpy()); +} + +/* ************************************************************************* */ } // \namespace gtsam diff --git a/gtsam_unstable/dynamics/PoseRTV.h b/gtsam_unstable/dynamics/PoseRTV.h index b2e325f53..077756f56 100644 --- a/gtsam_unstable/dynamics/PoseRTV.h +++ b/gtsam_unstable/dynamics/PoseRTV.h @@ -153,6 +153,20 @@ public: boost::optional Dglobal=boost::none, boost::optional Dtrans=boost::none) const; + // Utility functions + + /// RRTMbn - Function computes the rotation rate transformation matrix from + /// body axis rates to euler angle (global) rates + static Matrix RRTMbn(const Vector& euler); + + static Matrix RRTMbn(const Rot3& att); + + /// RRTMnb - Function computes the rotation rate transformation matrix from + /// euler angle rates to body axis rates + static Matrix RRTMnb(const Vector& euler); + + static Matrix RRTMnb(const Rot3& att); + private: /** Serialization function */ friend class boost::serialization::access; diff --git a/gtsam_unstable/dynamics/VelocityConstraint.h b/gtsam_unstable/dynamics/VelocityConstraint.h index a35f09bb7..801bf12cd 100644 --- a/gtsam_unstable/dynamics/VelocityConstraint.h +++ b/gtsam_unstable/dynamics/VelocityConstraint.h @@ -72,6 +72,11 @@ public: virtual ~VelocityConstraint() {} + /// @return a deep copy of this factor + virtual gtsam::NonlinearFactor::shared_ptr clone() const { + return boost::static_pointer_cast( + gtsam::NonlinearFactor::shared_ptr(new VelocityConstraint(*this))); } + /** * Calculates the error for trapezoidal model given */ diff --git a/gtsam_unstable/dynamics/imuSystem.cpp b/gtsam_unstable/dynamics/imuSystem.cpp deleted file mode 100644 index 209615bcc..000000000 --- a/gtsam_unstable/dynamics/imuSystem.cpp +++ /dev/null @@ -1,63 +0,0 @@ -/** - * @file ilm3DSystem.cpp - * @brief Implementations of ilm 3D domain - * @author Alex Cunningham - */ - -#include -#include - -namespace imu { - -using namespace gtsam; - -/* ************************************************************************* */ -void Graph::addPrior(Key key, const PoseRTV& pose, const SharedNoiseModel& noiseModel) { - add(Prior(PoseKey(key), pose, noiseModel)); -} - -/* ************************************************************************* */ -void Graph::addConstraint(Key key, const PoseRTV& pose) { - add(Constraint(PoseKey(key), pose)); -} - -/* ************************************************************************* */ -void Graph::addHeightPrior(Key key, double z, const SharedNoiseModel& noiseModel) { - add(DHeightPrior(PoseKey(key), z, noiseModel)); -} - -/* ************************************************************************* */ -void Graph::addFullIMUMeasurement(Key key1, Key key2, - const Vector& accel, const Vector& gyro, double dt, const SharedNoiseModel& noiseModel) { - add(FullIMUMeasurement(accel, gyro, dt, PoseKey(key1), PoseKey(key2), noiseModel)); -} - -/* ************************************************************************* */ -void Graph::addIMUMeasurement(Key key1, Key key2, - const Vector& accel, const Vector& gyro, double dt, const SharedNoiseModel& noiseModel) { - add(IMUMeasurement(accel, gyro, dt, PoseKey(key1), PoseKey(key2), noiseModel)); -} - -/* ************************************************************************* */ -void Graph::addVelocityConstraint(Key key1, Key key2, double dt, const SharedNoiseModel& noiseModel) { - add(VelocityConstraint(PoseKey(key1), PoseKey(key2), dt, noiseModel)); -} - -/* ************************************************************************* */ -void Graph::addBetween(Key key1, Key key2, const PoseRTV& z, const SharedNoiseModel& noiseModel) { - add(Between(PoseKey(key1), PoseKey(key2), z, noiseModel)); -} - -/* ************************************************************************* */ -void Graph::addRange(Key key1, Key key2, double z, const SharedNoiseModel& noiseModel) { - add(Range(PoseKey(key1), PoseKey(key2), z, noiseModel)); -} - -/* ************************************************************************* */ -Values Graph::optimize(const Values& init) const { - return LevenbergMarquardtOptimizer(*this, init).optimize(); -} -/* ************************************************************************* */ - -} // \namespace imu - diff --git a/gtsam_unstable/dynamics/imuSystem.h b/gtsam_unstable/dynamics/imuSystem.h deleted file mode 100644 index b0bee8873..000000000 --- a/gtsam_unstable/dynamics/imuSystem.h +++ /dev/null @@ -1,88 +0,0 @@ -/** - * @file imuSystem.h - * @brief A 3D Dynamic system domain as a demonstration of IMU factors - * @author Alex Cunningham - */ - -#pragma once - -#include - -#include -#include -#include -#include -#include -#include -#include -#include -#include - -#include -#include -#include -#include -#include - -/** - * This domain focuses on a single class of variables: PoseRTV, which - * models a dynamic pose operating with IMU measurements and assorted priors. - * - * There are also partial priors that constraint certain components of the - * poses, as well as between and range factors to model other between-pose - * information. - */ -namespace imu { - -using namespace gtsam; - -// Values: just poses -inline Symbol PoseKey(Index j) { return Symbol('x', j); } - -struct Values : public gtsam::Values { - typedef gtsam::Values Base; - - Values() {} - Values(const Values& values) : Base(values) {} - Values(const Base& values) : Base(values) {} - - void insertPose(Index key, const PoseRTV& pose) { insert(PoseKey(key), pose); } - PoseRTV pose(Index key) const { return at(PoseKey(key)); } -}; - -// factors -typedef IMUFactor IMUMeasurement; // IMU between measurements -typedef FullIMUFactor FullIMUMeasurement; // Full-state IMU between measurements -typedef BetweenFactor Between; // full odometry (including velocity) -typedef NonlinearEquality Constraint; -typedef PriorFactor Prior; -typedef RangeFactor Range; - -// graph components -struct Graph : public NonlinearFactorGraph { - typedef NonlinearFactorGraph Base; - - Graph() {} - Graph(const Base& graph) : Base(graph) {} - Graph(const Graph& graph) : Base(graph) {} - - // prior factors - void addPrior(size_t key, const PoseRTV& pose, const SharedNoiseModel& noiseModel); - void addConstraint(size_t key, const PoseRTV& pose); - void addHeightPrior(size_t key, double z, const SharedNoiseModel& noiseModel); - - // inertial factors - void addFullIMUMeasurement(size_t key1, size_t key2, const Vector& accel, const Vector& gyro, double dt, const SharedNoiseModel& noiseModel); - void addIMUMeasurement(size_t key1, size_t key2, const Vector& accel, const Vector& gyro, double dt, const SharedNoiseModel& noiseModel); - void addVelocityConstraint(size_t key1, size_t key2, double dt, const SharedNoiseModel& noiseModel); - - // other measurements - void addBetween(size_t key1, size_t key2, const PoseRTV& z, const SharedNoiseModel& noiseModel); - void addRange(size_t key1, size_t key2, double z, const SharedNoiseModel& noiseModel); - - // optimization - Values optimize(const Values& init) const; -}; - -} // \namespace imu - diff --git a/gtsam_unstable/dynamics/imu_examples.h b/gtsam_unstable/dynamics/imu_examples.h deleted file mode 100644 index 90bbc9d8b..000000000 --- a/gtsam_unstable/dynamics/imu_examples.h +++ /dev/null @@ -1,273 +0,0 @@ -/** - * @file imu_examples.h - * @brief Example measurements from ACFR matlab simulation - * @author Alex Cunningham - */ - -#pragma once - -#include -#include - -namespace gtsam { -namespace examples { - -// examples pulled from simulated dataset - -// case pulled from dataset (frame 5000, no noise, flying robot) -namespace frame5000 { -double dt=0.010000; - -// previous frame -gtsam::Point3 posInit( - -34.959663877411039, - -36.312388041359441, - -9.929634578582256); -gtsam::Vector velInit = gtsam::Vector_(3, - -2.325950469365050, - -5.545469040035986, - 0.026939998635121); -gtsam::Vector attInit = gtsam::Vector_(3, - -0.005702574137157, - -0.029956547314287, - 1.625011216344428); - -// IMU measurement (accel (0-2), gyro (3-5)) - from current frame -gtsam::Vector accel = gtsam::Vector_(3, - 1.188806676070333, - -0.183885870345845, - -9.870747316422888); -gtsam::Vector gyro = gtsam::Vector_(3, - 0.0, - 0.026142019158168, - -2.617993877991494); - -// resulting frame -gtsam::Point3 posFinal( - -34.982904302954310, - -36.367693859767584, - -9.929367164045985); -gtsam::Vector velFinal = gtsam::Vector_(3, - -2.324042554327658, - -5.530581840815272, - 0.026741453627181); -gtsam::Vector attFinal = gtsam::Vector_(3, - -0.004918046965288, - -0.029844423605949, - 1.598818460739227); - -PoseRTV init (posInit, gtsam::Rot3::RzRyRx(attInit), velInit); -PoseRTV final(posFinal, gtsam::Rot3::RzRyRx(attFinal), velFinal); -} - -// case pulled from dataset (frame 10000, no noise, flying robot) -namespace frame10000 { -double dt=0.010000; - -// previous frame -gtsam::Point3 posInit( - -30.320731549352189, - -1.988742283760434, - -9.946212692656349); -gtsam::Vector velInit = gtsam::Vector_(3, - -0.094887047280235, - -5.200243574047883, - -0.006106911050672); -gtsam::Vector attInit = gtsam::Vector_(3, - -0.049884854704728, - -0.004630595995732, - -1.952691683647753); - -// IMU measurement (accel (0-2), gyro (3-5)) - from current frame -gtsam::Vector accel = gtsam::Vector_(3, - 0.127512027192321, - 0.508566822495083, - -9.987963604829643); -gtsam::Vector gyro = gtsam::Vector_(3, - 0.0, - 0.004040957322961, - 2.617993877991494); - -// resulting frame -gtsam::Point3 posFinal( - -30.321685191305157, - -2.040760054006146, - -9.946292804391417); -gtsam::Vector velFinal = gtsam::Vector_(3, - -0.095364195297074, - -5.201777024575911, - -0.008011173506779); -gtsam::Vector attFinal = gtsam::Vector_(3, - -0.050005924151669, - -0.003284795837998, - -1.926546047162884); - -PoseRTV init (posInit, gtsam::Rot3::RzRyRx(attInit), velInit); -PoseRTV final(posFinal, gtsam::Rot3::RzRyRx(attFinal), velFinal); -} - -// case pulled from dataset (frame at time 4.00, no noise, flying robot, poses from 3.99 to 4.0) -namespace flying400 { -double dt=0.010000; - -// start pose -// time 3.9900000e+00 -// pos (x,y,z) 1.8226188e+01 -6.7168156e+01 -9.8236334e+00 -// vel (dx,dy,dz) -5.2887267e+00 1.6117880e-01 -2.2665072e-02 -// att (r, p, y) 1.0928413e-02 -2.0811771e-02 2.7206011e+00 - -// previous frame -gtsam::Point3 posInit( - 1.8226188e+01, -6.7168156e+01, -9.8236334e+00); -gtsam::Vector velInit = gtsam::Vector_(3,-5.2887267e+00, 1.6117880e-01, -2.2665072e-02); -gtsam::Vector attInit = gtsam::Vector_(3, 1.0928413e-02, -2.0811771e-02, 2.7206011e+00); - -// time 4.0000000e+00 -// accel 3.4021509e-01 -3.4413998e-01 -9.8822495e+00 -// gyro 0.0000000e+00 1.8161697e-02 -2.6179939e+00 - -// IMU measurement (accel (0-2), gyro (3-5)) - ax, ay, az, r, p, y -gtsam::Vector accel = gtsam::Vector_(3, - 3.4021509e-01, -3.4413998e-01, -9.8822495e+00); -gtsam::Vector gyro = gtsam::Vector_(3, - 0.0000000e+00, 1.8161697e-02, -2.6179939e+00); // original version (possibly r, p, y) - -// final pose -// time 4.0000000e+00 -// pos (x,y,z) 1.8173262e+01 -6.7166500e+01 -9.8238667e+00 -// vel (vx,vy,vz) -5.2926092e+00 1.6559974e-01 -2.3330881e-02 -// att (r, p, y) 1.1473269e-02 -2.0344066e-02 2.6944191e+00 - -// resulting frame -gtsam::Point3 posFinal(1.8173262e+01, -6.7166500e+01, -9.8238667e+00); -gtsam::Vector velFinal = gtsam::Vector_(3,-5.2926092e+00, 1.6559974e-01, -2.3330881e-02); -gtsam::Vector attFinal = gtsam::Vector_(3, 1.1473269e-02, -2.0344066e-02, 2.6944191e+00); - -// full states -PoseRTV init (posInit, gtsam::Rot3::ypr( attInit(2), attInit(1), attInit(0)), velInit); -PoseRTV final(posFinal, gtsam::Rot3::ypr(attFinal(2), attFinal(1), attFinal(0)), velFinal); - -} // \namespace flying400 - -namespace flying650 { -double dt=0.010000; - -// from time 6.49 to 6.50 in robot F2 - - -// frame (6.49) -// 6.4900000e+00 -3.8065039e+01 -6.4788024e+01 -9.8947445e+00 -5.0099274e+00 1.5999675e-01 -1.7762191e-02 -5.7708025e-03 -1.0109000e-02 -3.0465662e+00 -gtsam::Point3 posInit( - -3.8065039e+01, -6.4788024e+01, -9.8947445e+00); -gtsam::Vector velInit = gtsam::Vector_(3,-5.0099274e+00, 1.5999675e-01, -1.7762191e-02); -gtsam::Vector attInit = gtsam::Vector_(3,-5.7708025e-03, -1.0109000e-02, -3.0465662e+00); - -// IMU measurement (accel (0-2), gyro (3-5)) - ax, ay, az, r, p, y -// 6.5000000e+00 -9.2017256e-02 8.6770069e-02 -9.8213017e+00 0.0000000e+00 1.0728860e-02 -2.6179939e+00 -gtsam::Vector accel = gtsam::Vector_(3, - -9.2017256e-02, 8.6770069e-02, -9.8213017e+00); -gtsam::Vector gyro = gtsam::Vector_(3, - 0.0000000e+00, 1.0728860e-02, -2.6179939e+00); // in r,p,y - -// resulting frame (6.50) -// 6.5000000e+00 -3.8115139e+01 -6.4786428e+01 -9.8949233e+00 -5.0099817e+00 1.5966531e-01 -1.7882777e-02 -5.5061386e-03 -1.0152792e-02 -3.0727477e+00 -gtsam::Point3 posFinal(-3.8115139e+01, -6.4786428e+01, -9.8949233e+00); -gtsam::Vector velFinal = gtsam::Vector_(3,-5.0099817e+00, 1.5966531e-01, -1.7882777e-02); -gtsam::Vector attFinal = gtsam::Vector_(3,-5.5061386e-03, -1.0152792e-02, -3.0727477e+00); - -// full states -PoseRTV init (posInit, gtsam::Rot3::ypr( attInit(2), attInit(1), attInit(0)), velInit); -PoseRTV final(posFinal, gtsam::Rot3::ypr(attFinal(2), attFinal(1), attFinal(0)), velFinal); - -} // \namespace flying650 - - -namespace flying39 { -double dt=0.010000; - -// from time 0.38 to 0.39 in robot F1 - -// frame (0.38) -// 3.8000000e-01 3.4204706e+01 -6.7413834e+01 -9.9996055e+00 -2.2484370e-02 -1.3603911e-03 1.5267496e-02 7.9033358e-04 -1.4946656e-02 -3.1174147e+00 -gtsam::Point3 posInit( 3.4204706e+01, -6.7413834e+01, -9.9996055e+00); -gtsam::Vector velInit = gtsam::Vector_(3,-2.2484370e-02, -1.3603911e-03, 1.5267496e-02); -gtsam::Vector attInit = gtsam::Vector_(3, 7.9033358e-04, -1.4946656e-02, -3.1174147e+00); - -// IMU measurement (accel (0-2), gyro (3-5)) - ax, ay, az, r, p, y -// 3.9000000e-01 7.2229967e-01 -9.5790214e-03 -9.3943087e+00 0.0000000e+00 -2.9157400e-01 -2.6179939e+00 -gtsam::Vector accel = gtsam::Vector_(3, 7.2229967e-01, -9.5790214e-03, -9.3943087e+00); -gtsam::Vector gyro = gtsam::Vector_(3, 0.0000000e+00, -2.9157400e-01, -2.6179939e+00); // in r,p,y - -// resulting frame (0.39) -// 3.9000000e-01 3.4204392e+01 -6.7413848e+01 -9.9994098e+00 -3.1382246e-02 -1.3577532e-03 1.9568177e-02 1.1816996e-03 -1.7841704e-02 3.1395854e+00 -gtsam::Point3 posFinal(3.4204392e+01, -6.7413848e+01, -9.9994098e+00); -gtsam::Vector velFinal = gtsam::Vector_(3,-3.1382246e-02, -1.3577532e-03, 1.9568177e-02); -gtsam::Vector attFinal = gtsam::Vector_(3, 1.1816996e-03, -1.7841704e-02, 3.1395854e+00); - -// full states -PoseRTV init (posInit, gtsam::Rot3::ypr( attInit(2), attInit(1), attInit(0)), velInit); -PoseRTV final(posFinal, gtsam::Rot3::ypr(attFinal(2), attFinal(1), attFinal(0)), velFinal); - -} // \namespace flying39 - -namespace ground200 { -double dt=0.010000; - -// from time 2.00 to 2.01 in robot G1 - -// frame (2.00) -// 2.0000000e+00 3.6863524e+01 -8.4874053e+01 0.0000000e+00 -7.9650687e-01 1.8345508e+00 0.0000000e+00 0.0000000e+00 0.0000000e+00 1.9804083e+00 -gtsam::Point3 posInit(3.6863524e+01, -8.4874053e+01, 0.0000000e+00); -gtsam::Vector velInit = gtsam::Vector_(3,-7.9650687e-01, 1.8345508e+00, 0.0000000e+00); -gtsam::Vector attInit = gtsam::Vector_(3, 0.0000000e+00, 0.0000000e+00, 1.9804083e+00); - -// IMU measurement (accel (0-2), gyro (3-5)) - ax, ay, az, r, p, y -// 2.0100000e+00 1.0000000e+00 8.2156504e-15 -9.8100000e+00 0.0000000e+00 0.0000000e+00 0.0000000e+00 -gtsam::Vector accel = gtsam::Vector_(3, - 1.0000000e+00, 8.2156504e-15, -9.8100000e+00); -gtsam::Vector gyro = gtsam::Vector_(3, - 0.0000000e+00, 0.0000000e+00, 0.0000000e+00); // in r,p,y - -// resulting frame (2.01) -// 2.0100000e+00 3.6855519e+01 -8.4855615e+01 0.0000000e+00 -8.0048940e-01 1.8437236e+00 0.0000000e+00 0.0000000e+00 0.0000000e+00 1.9804083e+00 -gtsam::Point3 posFinal(3.6855519e+01, -8.4855615e+01, 0.0000000e+00); -gtsam::Vector velFinal = gtsam::Vector_(3,-8.0048940e-01, 1.8437236e+00, 0.0000000e+00); -gtsam::Vector attFinal = gtsam::Vector_(3, 0.0000000e+00, 0.0000000e+00, 1.9804083e+00); - -// full states -PoseRTV init (posInit, gtsam::Rot3::ypr( attInit(2), attInit(1), attInit(0)), velInit); -PoseRTV final(posFinal, gtsam::Rot3::ypr(attFinal(2), attFinal(1), attFinal(0)), velFinal); - -} // \namespace ground200 - -namespace ground600 { -double dt=0.010000; - -// from time 6.00 to 6.01 in robot G1 - -// frame (6.00) -// 6.0000000e+00 3.0320057e+01 -7.0883904e+01 0.0000000e+00 -4.0020377e+00 2.9972811e+00 0.0000000e+00 0.0000000e+00 0.0000000e+00 2.4987711e+00 -gtsam::Point3 posInit(3.0320057e+01, -7.0883904e+01, 0.0000000e+00); -gtsam::Vector velInit = gtsam::Vector_(3,-4.0020377e+00, 2.9972811e+00, 0.0000000e+00); -gtsam::Vector attInit = gtsam::Vector_(3, 0.0000000e+00, 0.0000000e+00, 2.4987711e+00); - -// IMU measurement (accel (0-2), gyro (3-5)) - ax, ay, az, r, p, y -// 6.0100000e+00 6.1683759e-02 7.8536587e+00 -9.8100000e+00 0.0000000e+00 0.0000000e+00 1.5707963e+00 -gtsam::Vector accel = gtsam::Vector_(3, - 6.1683759e-02, 7.8536587e+00, -9.8100000e+00); -gtsam::Vector gyro = gtsam::Vector_(3, - 0.0000000e+00, 0.0000000e+00, 1.5707963e+00); // in r,p,y - -// resulting frame (6.01) -// 6.0100000e+00 3.0279571e+01 -7.0854564e+01 0.0000000e+00 -4.0486232e+00 2.9340501e+00 0.0000000e+00 0.0000000e+00 0.0000000e+00 2.5144791e+00 -gtsam::Point3 posFinal(3.0279571e+01, -7.0854564e+01, 0.0000000e+00); -gtsam::Vector velFinal = gtsam::Vector_(3,-4.0486232e+00, 2.9340501e+00, 0.0000000e+00); -gtsam::Vector attFinal = gtsam::Vector_(3, 0.0000000e+00, 0.0000000e+00, 2.5144791e+00); - -// full states -PoseRTV init (posInit, gtsam::Rot3::ypr( attInit(2), attInit(1), attInit(0)), velInit); -PoseRTV final(posFinal, gtsam::Rot3::ypr(attFinal(2), attFinal(1), attFinal(0)), velFinal); - -} // \namespace ground600 - -} // \namespace examples -} // \namespace gtsam diff --git a/gtsam_unstable/dynamics/inertialUtils.cpp b/gtsam_unstable/dynamics/inertialUtils.cpp deleted file mode 100644 index 94d99f690..000000000 --- a/gtsam_unstable/dynamics/inertialUtils.cpp +++ /dev/null @@ -1,51 +0,0 @@ -/** - * @file inertialUtils.cpp - * - * @date Nov 28, 2011 - * @author Alex Cunningham - */ - -#include - -namespace gtsam { -namespace dynamics { - -/* ************************************************************************* */ -Matrix RRTMbn(const Vector& euler) { - assert(euler.size() == 3); - const double s1 = sin(euler(1-1)), c1 = cos(euler(1-1)); - const double t2 = tan(euler(2-1)), c2 = cos(euler(2-1)); - Matrix Ebn(3,3); - Ebn << 1.0, s1 * t2, c1 * t2, - 0.0, c1, -s1, - 0.0, s1 / c2, c1 / c2; - return Ebn; -} - -/* ************************************************************************* */ -Matrix RRTMbn(const Rot3& att) { - return RRTMbn(att.rpy()); -} - -/* ************************************************************************* */ -Matrix RRTMnb(const Vector& euler) { - assert(euler.size() == 3); - Matrix Enb(3,3); - const double s1 = sin(euler(1-1)), c1 = cos(euler(1-1)); - const double s2 = sin(euler(2-1)), c2 = cos(euler(2-1)); - Enb << 1.0, 0.0, -s2, - 0.0, c1, s1*c2, - 0.0, -s1, c1*c2; - return Enb; -} - -/* ************************************************************************* */ -Matrix RRTMnb(const Rot3& att) { - return RRTMnb(att.rpy()); -} - -} // \namespace dynamics -} // \namespace gtsam - - - diff --git a/gtsam_unstable/dynamics/inertialUtils.h b/gtsam_unstable/dynamics/inertialUtils.h deleted file mode 100644 index 250ed3abe..000000000 --- a/gtsam_unstable/dynamics/inertialUtils.h +++ /dev/null @@ -1,32 +0,0 @@ -/** - * @file inertialUtils.h - * - * @brief Utility functions for working with dynamic systems - derived from Mitch's matlab code - * This is mostly just syntactic sugar for working with dynamic systems that use - * Euler angles to specify the orientation of a robot. - * - * @date Nov 28, 2011 - * @author Alex Cunningham - */ - -#pragma once - -#include - -namespace gtsam { -namespace dynamics { - -/// RRTMbn - Function computes the rotation rate transformation matrix from -/// body axis rates to euler angle (global) rates -Matrix RRTMbn(const Vector& euler); - -Matrix RRTMbn(const Rot3& att); - -/// RRTMnb - Function computes the rotation rate transformation matrix from -/// euler angle rates to body axis rates -Matrix RRTMnb(const Vector& euler); - -Matrix RRTMnb(const Rot3& att); - -} // \namespace dynamics -} // \namespace gtsam diff --git a/gtsam_unstable/dynamics/tests/testIMUSystem.cpp b/gtsam_unstable/dynamics/tests/testIMUSystem.cpp index ad66b2b60..01c7925b3 100644 --- a/gtsam_unstable/dynamics/tests/testIMUSystem.cpp +++ b/gtsam_unstable/dynamics/tests/testIMUSystem.cpp @@ -3,26 +3,35 @@ * @author Alex Cunningham */ +#include + #include -#include -#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +using namespace std; using namespace gtsam; -using namespace imu; const double tol=1e-5; +static const Key x0 = 0, x1 = 1, x2 = 2, x3 = 3, x4 = 4; static const Vector g = delta(3, 2, -9.81); -Key x1 = PoseKey(1), x2 = PoseKey(2), x3 = PoseKey(3), x4 = PoseKey(4); - /* ************************************************************************* */ TEST(testIMUSystem, instantiations) { // just checking for compilation PoseRTV x1_v; - imu::Values local_values; - Graph graph; gtsam::SharedNoiseModel model1 = gtsam::noiseModel::Unit::Create(1); gtsam::SharedNoiseModel model3 = gtsam::noiseModel::Unit::Create(3); @@ -31,13 +40,13 @@ TEST(testIMUSystem, instantiations) { Vector accel = ones(3), gyro = ones(3); - IMUMeasurement imu(accel, gyro, 0.01, x1, x2, model6); - FullIMUMeasurement full_imu(accel, gyro, 0.01, x1, x2, model9); - Constraint poseHardPrior(x1, x1_v); - Between odom(x1, x2, x1_v, model9); - Range range(x1, x2, 1.0, model1); + IMUFactor imu(accel, gyro, 0.01, x1, x2, model6); + FullIMUFactor full_imu(accel, gyro, 0.01, x1, x2, model9); + NonlinearEquality poseHardPrior(x1, x1_v); + BetweenFactor odom(x1, x2, x1_v, model9); + RangeFactor range(x1, x2, 1.0, model1); VelocityConstraint constraint(x1, x2, 0.1, 10000); - Prior posePrior(x1, x1_v, model9); + PriorFactor posePrior(x1, x1_v, model9); DHeightPrior heightPrior(x1, 0.1, model1); VelocityPrior velPrior(x1, ones(3), model3); } @@ -59,17 +68,17 @@ TEST( testIMUSystem, optimize_chain ) { imu34 = pose3.imuPrediction(pose4, dt); // assemble simple graph with IMU measurements and velocity constraints - Graph graph; - graph.add(Constraint(x1, pose1)); - graph.add(IMUMeasurement(imu12, dt, x1, x2, model)); - graph.add(IMUMeasurement(imu23, dt, x2, x3, model)); - graph.add(IMUMeasurement(imu34, dt, x3, x4, model)); + NonlinearFactorGraph graph; + graph.add(NonlinearEquality(x1, pose1)); + graph.add(IMUFactor(imu12, dt, x1, x2, model)); + graph.add(IMUFactor(imu23, dt, x2, x3, model)); + graph.add(IMUFactor(imu34, dt, x3, x4, model)); graph.add(VelocityConstraint(x1, x2, dt)); graph.add(VelocityConstraint(x2, x3, dt)); graph.add(VelocityConstraint(x3, x4, dt)); // ground truth values - imu::Values true_values; + Values true_values; true_values.insert(x1, pose1); true_values.insert(x2, pose2); true_values.insert(x3, pose3); @@ -79,13 +88,13 @@ TEST( testIMUSystem, optimize_chain ) { EXPECT_DOUBLES_EQUAL(0, graph.error(true_values), 1e-5); // initialize with zero values and optimize - imu::Values values; + Values values; values.insert(x1, PoseRTV()); values.insert(x2, PoseRTV()); values.insert(x3, PoseRTV()); values.insert(x4, PoseRTV()); - imu::Values actual = graph.optimize(values); + Values actual = LevenbergMarquardtOptimizer(graph, values).optimize(); EXPECT(assert_equal(true_values, actual, tol)); } @@ -106,14 +115,14 @@ TEST( testIMUSystem, optimize_chain_fullfactor ) { imu34 = pose3.imuPrediction(pose4, dt); // assemble simple graph with IMU measurements and velocity constraints - Graph graph; - graph.add(Constraint(x1, pose1)); - graph.add(FullIMUMeasurement(imu12, dt, x1, x2, model)); - graph.add(FullIMUMeasurement(imu23, dt, x2, x3, model)); - graph.add(FullIMUMeasurement(imu34, dt, x3, x4, model)); + NonlinearFactorGraph graph; + graph.add(NonlinearEquality(x1, pose1)); + graph.add(FullIMUFactor(imu12, dt, x1, x2, model)); + graph.add(FullIMUFactor(imu23, dt, x2, x3, model)); + graph.add(FullIMUFactor(imu34, dt, x3, x4, model)); // ground truth values - imu::Values true_values; + Values true_values; true_values.insert(x1, pose1); true_values.insert(x2, pose2); true_values.insert(x3, pose3); @@ -123,7 +132,7 @@ TEST( testIMUSystem, optimize_chain_fullfactor ) { EXPECT_DOUBLES_EQUAL(0, graph.error(true_values), 1e-5); // initialize with zero values and optimize - imu::Values values; + Values values; values.insert(x1, PoseRTV()); values.insert(x2, PoseRTV()); values.insert(x3, PoseRTV()); @@ -131,42 +140,10 @@ TEST( testIMUSystem, optimize_chain_fullfactor ) { cout << "Initial Error: " << graph.error(values) << endl; // Initial error is 0.5 - need better prediction model - imu::Values actual = graph.optimize(values); + Values actual = LevenbergMarquardtOptimizer(graph, values).optimize(); // EXPECT(assert_equal(true_values, actual, tol)); // FAIL } -///* ************************************************************************* */ -//TEST( testIMUSystem, imu_factor_basics ) { -// using namespace examples; -// PoseKey x1(1), x2(2); -// SharedDiagonal model = noiseModel::Diagonal::Sigmas(Vector_(6, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6)); -// IMUMeasurement factor(frame5000::accel, frame5000::gyro, frame5000::dt, x1, x2, model); -// -// EXPECT(assert_equal(x1, factor.key1())); -// EXPECT(assert_equal(x2, factor.key2())); -// EXPECT(assert_equal(frame5000::accel, factor.accel(), tol)); -// EXPECT(assert_equal(frame5000::gyro, factor.gyro(), tol)); -// Vector full_meas = concatVectors(2, &frame5000::accel, &frame5000::gyro); -// EXPECT(assert_equal(full_meas, factor.z(), tol)); -//} -// -///* ************************************************************************* */ -//TEST( testIMUSystem, imu_factor_predict_function ) { -// using namespace examples; -// PoseKey x1(1), x2(2); -// SharedDiagonal model = noiseModel::Diagonal::Sigmas(Vector_(6, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6)); -// IMUMeasurement factor(frame5000::accel, frame5000::gyro, frame5000::dt, x1, x2, model); -// -// // verify zero error -// Vector actZeroError = factor.evaluateError(frame5000::init, frame5000::final); -// EXPECT(assert_equal(zero(6), actZeroError, tol)); -// -// // verify nonzero error - z-h(x) -// Vector actError = factor.evaluateError(frame10000::init, frame10000::final); -// Vector meas10k = concatVectors(2, &frame10000::accel, &frame10000::gyro); -// EXPECT(assert_equal(factor.z() - meas10k, actError, tol)); -//} - /* ************************************************************************* */ TEST( testIMUSystem, linear_trajectory) { // create a linear trajectory of poses @@ -178,24 +155,23 @@ TEST( testIMUSystem, linear_trajectory) { Vector gyro = delta(3, 0, 0.1); // constant rotation SharedDiagonal model = noiseModel::Unit::Create(9); - imu::Values true_traj, init_traj; - Graph graph; + Values true_traj, init_traj; + NonlinearFactorGraph graph; - graph.add(Constraint(PoseKey(0), start)); - true_traj.insert(PoseKey(0), start); - init_traj.insert(PoseKey(0), start); + graph.add(NonlinearEquality(x0, start)); + true_traj.insert(x0, start); + init_traj.insert(x0, start); size_t nrPoses = 10; PoseRTV cur_pose = start; for (size_t i=1; i(accel - g, gyro, dt, xA, xB, model)); true_traj.insert(xB, cur_pose); init_traj.insert(xB, PoseRTV()); } // EXPECT_DOUBLES_EQUAL(0, graph.error(true_traj), 1e-5); // FAIL - } /* ************************************************************************* */ diff --git a/gtsam_unstable/dynamics/tests/testInertialUtils.cpp b/gtsam_unstable/dynamics/tests/testInertialUtils.cpp deleted file mode 100644 index 5360aaae8..000000000 --- a/gtsam_unstable/dynamics/tests/testInertialUtils.cpp +++ /dev/null @@ -1,34 +0,0 @@ -/** - * @file testInertialUtils.cpp - * - * @brief Conversions for the utility functions from the matlab implementation - * - * @date Nov 28, 2011 - * @author Alex Cunningham - */ - -#include - -#include - -using namespace gtsam; - -static const double tol = 1e-5; - -/* ************************************************************************* */ -TEST(testInertialUtils, RRTMbn) { - EXPECT(assert_equal(Matrix::Identity(3,3), dynamics::RRTMbn(zero(3)), tol)); - EXPECT(assert_equal(Matrix::Identity(3,3), dynamics::RRTMbn(Rot3()), tol)); - EXPECT(assert_equal(dynamics::RRTMbn(Vector_(3, 0.3, 0.2, 0.1)), dynamics::RRTMbn(Rot3::ypr(0.1, 0.2, 0.3)), tol)); -} - -/* ************************************************************************* */ -TEST(testInertialUtils, RRTMnb) { - EXPECT(assert_equal(Matrix::Identity(3,3), dynamics::RRTMnb(zero(3)), tol)); - EXPECT(assert_equal(Matrix::Identity(3,3), dynamics::RRTMnb(Rot3()), tol)); - EXPECT(assert_equal(dynamics::RRTMnb(Vector_(3, 0.3, 0.2, 0.1)), dynamics::RRTMnb(Rot3::ypr(0.1, 0.2, 0.3)), tol)); -} - -/* ************************************************************************* */ -int main() { TestResult tr; return TestRegistry::runAllTests(tr); } -/* ************************************************************************* */ diff --git a/gtsam_unstable/dynamics/tests/testPoseRTV.cpp b/gtsam_unstable/dynamics/tests/testPoseRTV.cpp index 381971502..1444f69fc 100644 --- a/gtsam_unstable/dynamics/tests/testPoseRTV.cpp +++ b/gtsam_unstable/dynamics/tests/testPoseRTV.cpp @@ -9,7 +9,6 @@ #include #include -#include using namespace gtsam; @@ -119,85 +118,6 @@ TEST( testPoseRTV, dynamics_identities ) { // EXPECT(assert_equal(x4.translation(), x3.imuPrediction(x4, dt).second, tol)); } -///* ************************************************************************* */ -//TEST( testPoseRTV, constant_velocity ) { -// double dt = 1.0; -// PoseRTV init(Rot3(), Point3(1.0, 2.0, 3.0), Vector_(3, 0.5, 0.0, 0.0)); -// PoseRTV final(Rot3(), Point3(1.5, 2.0, 3.0), Vector_(3, 0.5, 0.0, 0.0)); -// -// // constant velocity, so gyro is zero, but accel includes gravity -// Vector accel = delta(3, 2, -9.81), gyro = zero(3); -// -// // perform integration -// PoseRTV actFinal = init.integrate(accel, gyro, dt); -// EXPECT(assert_equal(final, actFinal, tol)); -// -// // perform prediction -// Vector actAccel, actGyro; -// boost::tie(actAccel, actGyro) = init.predict(final, dt); -// EXPECT(assert_equal(accel, actAccel, tol)); -// EXPECT(assert_equal(gyro, actGyro, tol)); -//} -// -///* ************************************************************************* */ -//TEST( testPoseRTV, frame10000_imu ) { -// using namespace examples; -// -// // perform integration -// PoseRTV actFinal = frame10000::init.integrate(frame10000::accel, frame10000::gyro, frame10000::dt); -// EXPECT(assert_equal(frame10000::final, actFinal, tol)); -// -// // perform prediction -// Vector actAccel, actGyro; -// boost::tie(actAccel, actGyro) = frame10000::init.predict(frame10000::final, frame10000::dt); -// EXPECT(assert_equal(frame10000::accel, actAccel, tol)); -// EXPECT(assert_equal(frame10000::gyro, actGyro, tol)); -//} -// -///* ************************************************************************* */ -//TEST( testPoseRTV, frame5000_imu ) { -// using namespace examples; -// -// // perform integration -// PoseRTV actFinal = frame5000::init.integrate(frame5000::accel, frame5000::gyro, frame5000::dt); -// EXPECT(assert_equal(frame5000::final, actFinal, tol)); -// -// // perform prediction -// Vector actAccel, actGyro; -// boost::tie(actAccel, actGyro) = frame5000::init.predict(frame5000::final, frame5000::dt); -// EXPECT(assert_equal(frame5000::accel, actAccel, tol)); -// EXPECT(assert_equal(frame5000::gyro, actGyro, tol)); -//} -// -///* ************************************************************************* */ -//TEST( testPoseRTV, time4_imu ) { -// using namespace examples::flying400; -// -// // perform integration -// PoseRTV actFinal = init.integrate(accel, gyro, dt); -// EXPECT(assert_equal(final, actFinal, tol)); -// -// // perform prediction -// Vector actAccel, actGyro; -// boost::tie(actAccel, actGyro) = init.predict(final, dt); -// EXPECT(assert_equal(accel, actAccel, tol)); -// EXPECT(assert_equal(gyro, actGyro, tol)); -//} -// -///* ************************************************************************* */ -//TEST( testPoseRTV, time65_imu ) { -// using namespace examples::flying650; -// -// // perform integration -// PoseRTV actFinal = init.integrate(accel, gyro, dt); -// EXPECT(assert_equal(final, actFinal, tol)); -// -// // perform prediction -// Vector actAccel, actGyro; -// boost::tie(actAccel, actGyro) = init.predict(final, dt); -// EXPECT(assert_equal(accel, actAccel, tol)); -// EXPECT(assert_equal(gyro, actGyro, tol)); -//} /* ************************************************************************* */ double range_proxy(const PoseRTV& A, const PoseRTV& B) { return A.range(B); } @@ -232,8 +152,8 @@ TEST( testPoseRTV, transformed_from_1 ) { PoseRTV expected(transform.compose(start.pose()), transform.rotation().rotate(V)); EXPECT(assert_equal(expected, actual, tol)); - Matrix numDGlobal = numericalDerivative21(transformed_from_proxy, start, transform, 1e-8); - Matrix numDTrans = numericalDerivative22(transformed_from_proxy, start, transform, 1e-8); + Matrix numDGlobal = numericalDerivative21(transformed_from_proxy, start, transform, 1e-5); // At 1e-8, fails + Matrix numDTrans = numericalDerivative22(transformed_from_proxy, start, transform, 1e-8); // Sensitive to step size EXPECT(assert_equal(numDGlobal, actDGlobal, tol)); EXPECT(assert_equal(numDTrans, actDTrans, tol)); // FIXME: still needs analytic derivative } @@ -251,138 +171,25 @@ TEST( testPoseRTV, transformed_from_2 ) { PoseRTV expected(transform.compose(start.pose()), transform.rotation().rotate(V)); EXPECT(assert_equal(expected, actual, tol)); - Matrix numDGlobal = numericalDerivative21(transformed_from_proxy, start, transform, 1e-8); - Matrix numDTrans = numericalDerivative22(transformed_from_proxy, start, transform, 1e-8); + Matrix numDGlobal = numericalDerivative21(transformed_from_proxy, start, transform, 1e-5); // At 1e-8, fails + Matrix numDTrans = numericalDerivative22(transformed_from_proxy, start, transform, 1e-8); // Sensitive to step size EXPECT(assert_equal(numDGlobal, actDGlobal, tol)); EXPECT(assert_equal(numDTrans, actDTrans, tol)); // FIXME: still needs analytic derivative } /* ************************************************************************* */ -// ground robot maximums -//const static double ground_max_accel = 1.0; // m/s^2 -//const static double ground_mag_vel = 5.0; // m/s - fixed in simulator +TEST(testPoseRTV, RRTMbn) { + EXPECT(assert_equal(Matrix::Identity(3,3), PoseRTV::RRTMbn(zero(3)), tol)); + EXPECT(assert_equal(Matrix::Identity(3,3), PoseRTV::RRTMbn(Rot3()), tol)); + EXPECT(assert_equal(PoseRTV::RRTMbn(Vector_(3, 0.3, 0.2, 0.1)), PoseRTV::RRTMbn(Rot3::ypr(0.1, 0.2, 0.3)), tol)); +} -///* ************************************************************************* */ -//TEST(testPoseRTV, flying_integration650) { -// using namespace examples; -// const PoseRTV &x1 = flying650::init, &x2 = flying650::final; -// Vector accel = flying650::accel, gyro = flying650::gyro; -// double dt = flying650::dt; -// -// // control inputs -// double pitch_rate = gyro(1), -// heading_rate = gyro(2), -// lift_control = 0.0; /// FIXME: need to find this value -// -// PoseRTV actual_x2; -// actual_x2 = x1.flyingDynamics(pitch_rate, heading_rate, lift_control, dt); -// -// // FIXME: enable remaining components when there the lift control value is known -// EXPECT(assert_equal(x2.R(), actual_x2.R(), tol)); -//// EXPECT(assert_equal(x2.t(), actual_x2.t(), tol)); -//// EXPECT(assert_equal(x2.v(), actual_x2.v(), tol)); -//} - -///* ************************************************************************* */ -//TEST(testPoseRTV, imu_prediction650) { -// using namespace examples; -// const PoseRTV &x1 = flying650::init, &x2 = flying650::final; -// Vector accel = flying650::accel, gyro = flying650::gyro; -// double dt = flying650::dt; -// -// // given states, predict the imu measurement and t2 (velocity constraint) -// Vector actual_imu; -// Point3 actual_t2; -// boost::tie(actual_imu, actual_t2) = x1.imuPrediction(x2, dt); -// -// EXPECT(assert_equal(x2.t(), actual_t2, tol)); -// EXPECT(assert_equal(accel, actual_imu.head(3), tol)); -// EXPECT(assert_equal(gyro, actual_imu.tail(3), tol)); -//} -// -///* ************************************************************************* */ -//TEST(testPoseRTV, imu_prediction39) { -// // This case was a known failure case for gyro prediction, returning [9.39091; 0.204952; 625.63] using -// // the general approach for reverse-engineering the gyro updates -// using namespace examples; -// const PoseRTV &x1 = flying39::init, &x2 = flying39::final; -// Vector accel = flying39::accel, gyro = flying39::gyro; -// double dt = flying39::dt; -// -// // given states, predict the imu measurement and t2 (velocity constraint) -// Vector actual_imu; -// Point3 actual_t2; -// boost::tie(actual_imu, actual_t2) = x1.imuPrediction(x2, dt); -// -// EXPECT(assert_equal(x2.t(), actual_t2, tol)); -// EXPECT(assert_equal(accel, actual_imu.head(3), tol)); -// EXPECT(assert_equal(gyro, actual_imu.tail(3), tol)); -//} -// -///* ************************************************************************* */ -//TEST(testPoseRTV, ground_integration200) { -// using namespace examples; -// const PoseRTV &x1 = ground200::init, &x2 = ground200::final; -// Vector accel = ground200::accel, gyro = ground200::gyro; -// double dt = ground200::dt; -// -// // integrates from one pose to the next with known measurements -// // No heading change in this example -// // Hits maximum accel bound in this example -// -// PoseRTV actual_x2; -// actual_x2 = x1.planarDynamics(ground_mag_vel, gyro(2), ground_max_accel, dt); -// -// EXPECT(assert_equal(x2, actual_x2, tol)); -//} -// -///* ************************************************************************* */ -//TEST(testPoseRTV, ground_prediction200) { -// using namespace examples; -// const PoseRTV &x1 = ground200::init, &x2 = ground200::final; -// Vector accel = ground200::accel, gyro = ground200::gyro; -// double dt = ground200::dt; -// -// // given states, predict the imu measurement and t2 (velocity constraint) -// Vector actual_imu; -// Point3 actual_t2; -// boost::tie(actual_imu, actual_t2) = x1.imuPrediction(x2, dt); -// -// EXPECT(assert_equal(x2.t(), actual_t2, tol)); -// EXPECT(assert_equal(accel, actual_imu.head(3), tol)); -// EXPECT(assert_equal(gyro, actual_imu.tail(3), tol)); -//} -// -///* ************************************************************************* */ -//TEST(testPoseRTV, ground_integration600) { -// using namespace examples; -// const PoseRTV &x1 = ground600::init, &x2 = ground600::final; -// Vector accel = ground600::accel, gyro = ground600::gyro; -// double dt = ground600::dt; -// -// // integrates from one pose to the next with known measurements -// PoseRTV actual_x2; -// actual_x2 = x1.planarDynamics(ground_mag_vel, gyro(2), ground_max_accel, dt); -// -// EXPECT(assert_equal(x2, actual_x2, tol)); -//} -// -///* ************************************************************************* */ -//TEST(testPoseRTV, ground_prediction600) { -// using namespace examples; -// const PoseRTV &x1 = ground600::init, &x2 = ground600::final; -// Vector accel = ground600::accel, gyro = ground600::gyro; -// double dt = ground600::dt; -// -// // given states, predict the imu measurement and t2 (velocity constraint) -// Vector actual_imu; -// Point3 actual_t2; -// boost::tie(actual_imu, actual_t2) = x1.imuPrediction(x2, dt); -// -// EXPECT(assert_equal(x2.t(), actual_t2, tol)); -// EXPECT(assert_equal(accel, actual_imu.head(3), tol)); -// EXPECT(assert_equal(gyro, actual_imu.tail(3), tol)); -//} +/* ************************************************************************* */ +TEST(testPoseRTV, RRTMnb) { + EXPECT(assert_equal(Matrix::Identity(3,3), PoseRTV::RRTMnb(zero(3)), tol)); + EXPECT(assert_equal(Matrix::Identity(3,3), PoseRTV::RRTMnb(Rot3()), tol)); + EXPECT(assert_equal(PoseRTV::RRTMnb(Vector_(3, 0.3, 0.2, 0.1)), PoseRTV::RRTMnb(Rot3::ypr(0.1, 0.2, 0.3)), tol)); +} /* ************************************************************************* */ int main() { TestResult tr; return TestRegistry::runAllTests(tr); } diff --git a/gtsam_unstable/dynamics/tests/testVelocityConstraint.cpp b/gtsam_unstable/dynamics/tests/testVelocityConstraint.cpp index eb5950fe7..ea4a3493d 100644 --- a/gtsam_unstable/dynamics/tests/testVelocityConstraint.cpp +++ b/gtsam_unstable/dynamics/tests/testVelocityConstraint.cpp @@ -4,14 +4,14 @@ */ #include -#include + +#include using namespace gtsam; -using namespace imu; const double tol=1e-5; -Key x1 = PoseKey(1), x2 = PoseKey(2); +const Key x1 = 1, x2 = 2; const double dt = 1.0; PoseRTV origin, diff --git a/gtsam_unstable/geometry/CMakeLists.txt b/gtsam_unstable/geometry/CMakeLists.txt new file mode 100644 index 000000000..d6b6a706d --- /dev/null +++ b/gtsam_unstable/geometry/CMakeLists.txt @@ -0,0 +1,22 @@ +# Install headers +file(GLOB geometry_headers "*.h") +install(FILES ${geometry_headers} DESTINATION include/gtsam_unstable/geometry) + +# Components to link tests in this subfolder against +set(geometry_local_libs + #geometry_unstable # No sources currently, so no convenience lib + geometry + base + ccolamd +) + +set (geometry_full_libs + gtsam-static + gtsam_unstable-static) + +# Exclude tests that don't work +set (geometry_excluded_tests "") + +# Add all tests +gtsam_add_subdir_tests(geometry_unstable "${geometry_local_libs}" "${geometry_full_libs}" "${geometry_excluded_tests}") +add_dependencies(check.unstable check.geometry_unstable) diff --git a/gtsam_unstable/geometry/InvDepthCamera3.h b/gtsam_unstable/geometry/InvDepthCamera3.h new file mode 100644 index 000000000..d0b9ccd88 --- /dev/null +++ b/gtsam_unstable/geometry/InvDepthCamera3.h @@ -0,0 +1,179 @@ + +/** + * @file InvDepthCamera3.h + * @brief + * @author Chris Beall + * @date Apr 14, 2012 + */ + +#pragma once + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace gtsam { + +/** + * A pinhole camera class that has a Pose3 and a Calibration. + * @ingroup geometry + * \nosubgrouping + */ +template +class InvDepthCamera3 { +private: + Pose3 pose_; + boost::shared_ptr k_; + +public: + + /// @name Standard Constructors + /// @{ + + /** default constructor */ + InvDepthCamera3() {} + + /** constructor with pose and calibration */ + InvDepthCamera3(const Pose3& pose, const boost::shared_ptr& k) : + pose_(pose),k_(k) {} + + /// @} + /// @name Standard Interface + /// @{ + + virtual ~InvDepthCamera3() {} + + /// return pose + inline Pose3& pose() { return pose_; } + + /// return calibration + inline const boost::shared_ptr& calibration() const { return k_; } + + /// print + void print(const std::string& s = "") const { + pose_.print("pose3"); + k_.print("calibration"); + } + + static gtsam::Point3 invDepthTo3D(const gtsam::LieVector& pw, const gtsam::LieScalar& inv) { + gtsam::Point3 ray_base(pw.vector().segment(0,3)); + double theta = pw(3), phi = pw(4); + double rho = inv.value(); // inverse depth + gtsam::Point3 m(cos(theta)*cos(phi),sin(theta)*cos(phi),sin(phi)); + return ray_base + m/rho; + } + + /** project a point from world InvDepth parameterization to the image + * @param pw is a point in the world coordinate + * @param H1 is the jacobian w.r.t. [pose3 calibration] + * @param H2 is the jacobian w.r.t. inv_depth_landmark + */ + inline gtsam::Point2 project(const gtsam::LieVector& pw, + const gtsam::LieScalar& inv_depth, + boost::optional H1 = boost::none, + boost::optional H2 = boost::none, + boost::optional H3 = boost::none) const { + + gtsam::Point3 ray_base(pw.vector().segment(0,3)); + double theta = pw(3), phi = pw(4); + double rho = inv_depth.value(); // inverse depth + gtsam::Point3 m(cos(theta)*cos(phi),sin(theta)*cos(phi),sin(phi)); + const gtsam::Point3 landmark = ray_base + m/rho; + + gtsam::PinholeCamera camera(pose_, *k_); + + if (!H1 && !H2 && !H3) { + gtsam::Point2 uv= camera.project(landmark); + return uv; + } + else { + gtsam::Matrix J2; + gtsam::Point2 uv= camera.project(landmark,H1, J2); + if (H1) { + *H1 = (*H1) * gtsam::eye(6); + } + + double cos_theta = cos(theta); + double sin_theta = sin(theta); + double cos_phi = cos(phi); + double sin_phi = sin(phi); + double rho2 = rho * rho; + + if (H2) { + double H11 = 1; + double H12 = 0; + double H13 = 0; + double H14 = -cos_phi*sin_theta/rho; + double H15 = -cos_theta*sin_phi/rho; + + double H21 = 0; + double H22 = 1; + double H23 = 0; + double H24 = cos_phi*cos_theta/rho; + double H25 = -sin_phi*sin_theta/rho; + + double H31 = 0; + double H32 = 0; + double H33 = 1; + double H34 = 0; + double H35 = cos_phi/rho; + + *H2 = J2 * gtsam::Matrix_(3,5, + H11, H12, H13, H14, H15, + H21, H22, H23, H24, H25, + H31, H32, H33, H34, H35); + } + if(H3) { + double H16 = -cos_phi*cos_theta/rho2; + double H26 = -cos_phi*sin_theta/rho2; + double H36 = -sin_phi/rho2; + *H3 = J2 * gtsam::Matrix_(3,1, + H16, + H26, + H36); + } + return uv; + } + } + + /** + * backproject a 2-dimensional point to an Inverse Depth landmark + * useful for point initialization + */ + + inline std::pair backproject(const gtsam::Point2& pi, const double depth) const { + const gtsam::Point2 pn = k_->calibrate(pi); + gtsam::Point3 pc(pn.x(), pn.y(), 1.0); + pc = pc/pc.norm(); + gtsam::Point3 pw = pose_.transform_from(pc); + const gtsam::Point3& pt = pose_.translation(); + gtsam::Point3 ray = pw - pt; + double theta = atan2(ray.y(), ray.x()); // longitude + double phi = atan2(ray.z(), sqrt(ray.x()*ray.x()+ray.y()*ray.y())); + return std::make_pair(gtsam::LieVector(5, pt.x(),pt.y(),pt.z(), theta, phi), + gtsam::LieScalar(1./depth)); + } + +private: + + /// @} + /// @name Advanced Interface + /// @{ + + /** Serialization function */ + friend class boost::serialization::access; + template + void serialize(Archive & ar, const unsigned int version) { + ar & BOOST_SERIALIZATION_NVP(pose_); + ar & BOOST_SERIALIZATION_NVP(k_); + } + /// @} +}; // \class InvDepthCamera +} // \namesapce gtsam diff --git a/gtsam_unstable/geometry/tests/testInvDepthCamera3.cpp b/gtsam_unstable/geometry/tests/testInvDepthCamera3.cpp new file mode 100644 index 000000000..a69410e34 --- /dev/null +++ b/gtsam_unstable/geometry/tests/testInvDepthCamera3.cpp @@ -0,0 +1,157 @@ +/* + * testInvDepthFactor.cpp + * + * Created on: Apr 13, 2012 + * Author: cbeall3 + */ + +#include + +#include +#include +#include + +#include + +using namespace std; +using namespace gtsam; + +static Cal3_S2::shared_ptr K(new Cal3_S2(1500, 1200, 0, 640, 480)); +Pose3 level_pose = Pose3(Rot3::ypr(-M_PI/2, 0., -M_PI/2), gtsam::Point3(0,0,1)); +SimpleCamera level_camera(level_pose, *K); + +/* ************************************************************************* */ +TEST( InvDepthFactor, Project1) { + + // landmark 5 meters infront of camera + Point3 landmark(5, 0, 1); + + Point2 expected_uv = level_camera.project(landmark); + + InvDepthCamera3 inv_camera(level_pose, K); + LieVector inv_landmark(5, 1., 0., 1., 0., 0.); + LieScalar inv_depth(1./4); + Point2 actual_uv = inv_camera.project(inv_landmark, inv_depth); + EXPECT(assert_equal(expected_uv, actual_uv)); + EXPECT(assert_equal(Point2(640,480), actual_uv)); +} + +/* ************************************************************************* */ +TEST( InvDepthFactor, Project2) { + + // landmark 1m to the left and 1m up from camera + // inv landmark xyz is same as camera xyz, so depth actually doesn't matter + Point3 landmark(1, 1, 2); + Point2 expected = level_camera.project(landmark); + + InvDepthCamera3 inv_camera(level_pose, K); + LieVector diag_landmark(5, 0., 0., 1., M_PI/4., atan(1.0/sqrt(2.0))); + LieScalar inv_depth(1/sqrt(3.0)); + Point2 actual = inv_camera.project(diag_landmark, inv_depth); + EXPECT(assert_equal(expected, actual)); +} + +/* ************************************************************************* */ +TEST( InvDepthFactor, Project3) { + + // landmark 1m to the left and 1m up from camera + // inv depth landmark xyz at origion + Point3 landmark(1, 1, 2); + Point2 expected = level_camera.project(landmark); + + InvDepthCamera3 inv_camera(level_pose, K); + LieVector diag_landmark(5, 0., 0., 0., M_PI/4., atan(2./sqrt(2.0))); + LieScalar inv_depth( 1./sqrt(1.0+1+4)); + Point2 actual = inv_camera.project(diag_landmark, inv_depth); + EXPECT(assert_equal(expected, actual)); +} + +/* ************************************************************************* */ +TEST( InvDepthFactor, Project4) { + + // landmark 4m to the left and 1m up from camera + // inv depth landmark xyz at origion + Point3 landmark(1, 4, 2); + Point2 expected = level_camera.project(landmark); + + InvDepthCamera3 inv_camera(level_pose, K); + LieVector diag_landmark(5, 0., 0., 0., atan(4.0/1), atan(2./sqrt(1.+16.))); + LieScalar inv_depth(1./sqrt(1.+16.+4.)); + Point2 actual = inv_camera.project(diag_landmark, inv_depth); + EXPECT(assert_equal(expected, actual)); +} + + +/* ************************************************************************* */ +Point2 project_(const Pose3& pose, const LieVector& landmark, const LieScalar& inv_depth) { + return InvDepthCamera3(pose,K).project(landmark, inv_depth); } + +TEST( InvDepthFactor, Dproject_pose) +{ + LieVector landmark(6,0.1,0.2,0.3, 0.1,0.2); + LieScalar inv_depth(1./4); + Matrix expected = numericalDerivative31(project_,level_pose, landmark, inv_depth); + InvDepthCamera3 inv_camera(level_pose,K); + Matrix actual; + Point2 uv = inv_camera.project(landmark, inv_depth, actual, boost::none, boost::none); + EXPECT(assert_equal(expected,actual,1e-6)); +} + +/* ************************************************************************* */ +TEST( InvDepthFactor, Dproject_landmark) +{ + LieVector landmark(5,0.1,0.2,0.3, 0.1,0.2); + LieScalar inv_depth(1./4); + Matrix expected = numericalDerivative32(project_,level_pose, landmark, inv_depth); + InvDepthCamera3 inv_camera(level_pose,K); + Matrix actual; + Point2 uv = inv_camera.project(landmark, inv_depth, boost::none, actual, boost::none); + EXPECT(assert_equal(expected,actual,1e-7)); +} + +/* ************************************************************************* */ +TEST( InvDepthFactor, Dproject_inv_depth) +{ + LieVector landmark(5,0.1,0.2,0.3, 0.1,0.2); + LieScalar inv_depth(1./4); + Matrix expected = numericalDerivative33(project_,level_pose, landmark, inv_depth); + InvDepthCamera3 inv_camera(level_pose,K); + Matrix actual; + Point2 uv = inv_camera.project(landmark, inv_depth, boost::none, boost::none, actual); + EXPECT(assert_equal(expected,actual,1e-7)); +} + +/* ************************************************************************* */ +TEST(InvDepthFactor, backproject) +{ + LieVector expected(5,0.,0.,1., 0.1,0.2); + LieScalar inv_depth(1./4); + InvDepthCamera3 inv_camera(level_pose,K); + Point2 z = inv_camera.project(expected, inv_depth); + + LieVector actual_vec; + LieScalar actual_inv; + boost::tie(actual_vec, actual_inv) = inv_camera.backproject(z, 4); + EXPECT(assert_equal(expected,actual_vec,1e-7)); + EXPECT(assert_equal(inv_depth,actual_inv,1e-7)); +} + +/* ************************************************************************* */ +TEST(InvDepthFactor, backproject2) +{ + // backwards facing camera + LieVector expected(5,-5.,-5.,2., 3., -0.1); + LieScalar inv_depth(1./10); + InvDepthCamera3 inv_camera(Pose3(Rot3::ypr(1.5,0.1, -1.5), Point3(-5, -5, 2)),K); + Point2 z = inv_camera.project(expected, inv_depth); + + LieVector actual_vec; + LieScalar actual_inv; + boost::tie(actual_vec, actual_inv) = inv_camera.backproject(z, 10); + EXPECT(assert_equal(expected,actual_vec,1e-7)); + EXPECT(assert_equal(inv_depth,actual_inv,1e-7)); +} + +/* ************************************************************************* */ +int main() { TestResult tr; return TestRegistry::runAllTests(tr);} +/* ************************************************************************* */ diff --git a/gtsam_unstable/gtsam_unstable.h b/gtsam_unstable/gtsam_unstable.h index 376706e7f..a459925fd 100644 --- a/gtsam_unstable/gtsam_unstable.h +++ b/gtsam_unstable/gtsam_unstable.h @@ -2,17 +2,26 @@ * Matlab toolbox interface definition for gtsam_unstable */ -// Most things are in the gtsam namespace -using namespace gtsam; - // specify the classes from gtsam we are using -class gtsam::Point3; -class gtsam::Rot3; -class gtsam::Pose3; -class gtsam::SharedNoiseModel; +virtual class gtsam::Value; +virtual class gtsam::Point3; +virtual class gtsam::Rot3; +virtual class gtsam::Pose2; +virtual class gtsam::Pose3; +virtual class gtsam::noiseModel::Base; +virtual class gtsam::NonlinearFactor; + +namespace gtsam { + +#include +class Dummy { + Dummy(); + void print(string s) const; + unsigned char dummyTwoVar(unsigned char a) const; +}; #include -class PoseRTV { +virtual class PoseRTV : gtsam::Value { PoseRTV(); PoseRTV(Vector rtv); PoseRTV(const gtsam::Point3& pt, const gtsam::Rot3& rot, const gtsam::Point3& vel); @@ -22,7 +31,7 @@ class PoseRTV { PoseRTV(double roll, double pitch, double yaw, double x, double y, double z, double vx, double vy, double vz); // testable - bool equals(const PoseRTV& other, double tol) const; + bool equals(const gtsam::PoseRTV& other, double tol) const; void print(string s) const; // access @@ -39,58 +48,155 @@ class PoseRTV { // manifold/Lie static size_t Dim(); size_t dim() const; - PoseRTV retract(Vector v) const; - Vector localCoordinates(const PoseRTV& p) const; - static PoseRTV Expmap(Vector v); - static Vector Logmap(const PoseRTV& p); - PoseRTV inverse() const; - PoseRTV compose(const PoseRTV& p) const; - PoseRTV between(const PoseRTV& p) const; + gtsam::PoseRTV retract(Vector v) const; + Vector localCoordinates(const gtsam::PoseRTV& p) const; + static gtsam::PoseRTV Expmap(Vector v); + static Vector Logmap(const gtsam::PoseRTV& p); + gtsam::PoseRTV inverse() const; + gtsam::PoseRTV compose(const gtsam::PoseRTV& p) const; + gtsam::PoseRTV between(const gtsam::PoseRTV& p) const; // measurement - double range(const PoseRTV& other) const; - PoseRTV transformed_from(const gtsam::Pose3& trans) const; + double range(const gtsam::PoseRTV& other) const; + gtsam::PoseRTV transformed_from(const gtsam::Pose3& trans) const; // IMU/dynamics - PoseRTV planarDynamics(double vel_rate, double heading_rate, double max_accel, double dt) const; - PoseRTV flyingDynamics(double pitch_rate, double heading_rate, double lift_control, double dt) const; - PoseRTV generalDynamics(Vector accel, Vector gyro, double dt) const; - Vector imuPrediction(const PoseRTV& x2, double dt) const; - gtsam::Point3 translationIntegration(const PoseRTV& x2, double dt) const; - Vector translationIntegrationVec(const PoseRTV& x2, double dt) const; + gtsam::PoseRTV planarDynamics(double vel_rate, double heading_rate, double max_accel, double dt) const; + gtsam::PoseRTV flyingDynamics(double pitch_rate, double heading_rate, double lift_control, double dt) const; + gtsam::PoseRTV generalDynamics(Vector accel, Vector gyro, double dt) const; + Vector imuPrediction(const gtsam::PoseRTV& x2, double dt) const; + gtsam::Point3 translationIntegration(const gtsam::PoseRTV& x2, double dt) const; + Vector translationIntegrationVec(const gtsam::PoseRTV& x2, double dt) const; }; -#include -namespace imu { -class Values { - Values(); +// Nonlinear factors from gtsam, for our Value types +#include +template +virtual class PriorFactor : gtsam::NonlinearFactor { + PriorFactor(size_t key, const T& prior, const gtsam::noiseModel::Base* noiseModel); +}; + + +#include +template +virtual class BetweenFactor : gtsam::NonlinearFactor { + BetweenFactor(size_t key1, size_t key2, const T& relativePose, const gtsam::noiseModel::Base* noiseModel); +}; + + +#include +template +virtual class RangeFactor : gtsam::NonlinearFactor { + RangeFactor(size_t key1, size_t key2, double measured, const gtsam::noiseModel::Base* noiseModel); +}; + +typedef gtsam::RangeFactor RangeFactorRTV; + + +#include +template +virtual class NonlinearEquality : gtsam::NonlinearFactor { + // Constructor - forces exact evaluation + NonlinearEquality(size_t j, const T& feasible); + // Constructor - allows inexact evaluation + NonlinearEquality(size_t j, const T& feasible, double error_gain); +}; + +#include +template +virtual class IMUFactor : gtsam::NonlinearFactor { + /** Standard constructor */ + IMUFactor(Vector accel, Vector gyro, + double dt, size_t key1, size_t key2, const gtsam::noiseModel::Base* model); + + /** Full IMU vector specification */ + IMUFactor(Vector imu_vector, + double dt, size_t key1, size_t key2, const gtsam::noiseModel::Base* model); + + Vector gyro() const; + Vector accel() const; + Vector z() const; + size_t key1() const; + size_t key2() const; +}; + +#include +template +virtual class FullIMUFactor : gtsam::NonlinearFactor { + /** Standard constructor */ + FullIMUFactor(Vector accel, Vector gyro, + double dt, size_t key1, size_t key2, const gtsam::noiseModel::Base* model); + + /** Single IMU vector - imu = [accel, gyro] */ + FullIMUFactor(Vector imu, + double dt, size_t key1, size_t key2, const gtsam::noiseModel::Base* model); + + Vector gyro() const; + Vector accel() const; + Vector z() const; + size_t key1() const; + size_t key2() const; +}; + + +#include +virtual class DHeightPrior : gtsam::NonlinearFactor { + DHeightPrior(size_t key, double height, const gtsam::noiseModel::Base* model); +}; + + +virtual class DRollPrior : gtsam::NonlinearFactor { + /** allows for explicit roll parameterization - uses canonical coordinate */ + DRollPrior(size_t key, double wx, const gtsam::noiseModel::Base* model); + /** Forces roll to zero */ + DRollPrior(size_t key, const gtsam::noiseModel::Base* model); +}; + + +virtual class VelocityPrior : gtsam::NonlinearFactor { + VelocityPrior(size_t key, Vector vel, const gtsam::noiseModel::Base* model); +}; + + +virtual class DGroundConstraint : gtsam::NonlinearFactor { + // Primary constructor allows for variable height of the "floor" + DGroundConstraint(size_t key, double height, const gtsam::noiseModel::Base* model); + // Fully specify vector - use only for debugging + DGroundConstraint(size_t key, Vector constraint, const gtsam::noiseModel::Base* model); +}; + +//************************************************************************* +// General nonlinear factor types +//************************************************************************* +#include + +#include +template +virtual class PoseTranslationPrior : gtsam::NonlinearFactor { + PoseTranslationPrior(size_t key, const POSE& pose_z, const gtsam::noiseModel::Base* noiseModel); +}; + +typedef gtsam::PoseTranslationPrior PoseTranslationPrior2D; +typedef gtsam::PoseTranslationPrior PoseTranslationPrior3D; + +#include +template +virtual class PoseRotationPrior : gtsam::NonlinearFactor { + PoseRotationPrior(size_t key, const POSE& pose_z, const gtsam::noiseModel::Base* noiseModel); +}; + +typedef gtsam::PoseRotationPrior PoseRotationPrior2D; +typedef gtsam::PoseRotationPrior PoseRotationPrior3D; + +#include +virtual class RelativeElevationFactor: gtsam::NonlinearFactor { + RelativeElevationFactor(); + RelativeElevationFactor(size_t poseKey, size_t pointKey, double measured, + const gtsam::noiseModel::Base* model); + + double measured() const; void print(string s) const; - - void insertPose(size_t key, const PoseRTV& pose); - PoseRTV pose(size_t key) const; }; -class Graph { - Graph(); - void print(string s) const; - - // prior factors - void addPrior(size_t key, const PoseRTV& pose, const gtsam::SharedNoiseModel& noiseModel); - void addConstraint(size_t key, const PoseRTV& pose); - void addHeightPrior(size_t key, double z, const gtsam::SharedNoiseModel& noiseModel); - - // inertial factors - void addFullIMUMeasurement(size_t key1, size_t key2, const Vector& accel, const Vector& gyro, double dt, const gtsam::SharedNoiseModel& noiseModel); - void addIMUMeasurement(size_t key1, size_t key2, const Vector& accel, const Vector& gyro, double dt, const gtsam::SharedNoiseModel& noiseModel); - void addVelocityConstraint(size_t key1, size_t key2, double dt, const gtsam::SharedNoiseModel& noiseModel); - - // other measurements - void addBetween(size_t key1, size_t key2, const PoseRTV& z, const gtsam::SharedNoiseModel& noiseModel); - void addRange(size_t key1, size_t key2, double z, const gtsam::SharedNoiseModel& noiseModel); - - // optimization - imu::Values optimize(const imu::Values& init) const; -}; - -}///\namespace imu +} //\namespace gtsam diff --git a/gtsam_unstable/linear/CMakeLists.txt b/gtsam_unstable/linear/CMakeLists.txt new file mode 100644 index 000000000..d5429a5df --- /dev/null +++ b/gtsam_unstable/linear/CMakeLists.txt @@ -0,0 +1,20 @@ +# Install headers +file(GLOB base_headers "*.h") +install(FILES ${linear_headers} DESTINATION include/gtsam_unstable/linear) + +# Components to link tests in this subfolder against +set(linear_local_libs + linear + linear_unstable + base) + +set (linear_full_libs + gtsam-static + gtsam_unstable-static) + +# Exclude tests that don't work +set (base_excluded_tests "") + +# Add all tests +gtsam_add_subdir_tests(linear_unstable "${linear_local_libs}" "${linear_full_libs}" "${linear_excluded_tests}") +add_dependencies(check.unstable check.linear_unstable) diff --git a/gtsam_unstable/nonlinear/CMakeLists.txt b/gtsam_unstable/nonlinear/CMakeLists.txt new file mode 100644 index 000000000..a815e956d --- /dev/null +++ b/gtsam_unstable/nonlinear/CMakeLists.txt @@ -0,0 +1,25 @@ +# Install headers +file(GLOB nonlinear_headers "*.h") +install(FILES ${nonlinear_headers} DESTINATION include/gtsam_unstable/nonlinear) + +# Components to link tests in this subfolder against +set(nonlinear_local_libs + nonlinear_unstable + nonlinear + linear + inference + geometry + base + ccolamd +) + +set (nonlinear_full_libs + gtsam-static + gtsam_unstable-static) + +# Exclude tests that don't work +set (nonlinear_excluded_tests "") + +# Add all tests +gtsam_add_subdir_tests(nonlinear_unstable "${nonlinear_local_libs}" "${nonlinear_full_libs}" "${nonlinear_excluded_tests}") +add_dependencies(check.unstable check.nonlinear_unstable) diff --git a/gtsam_unstable/nonlinear/LinearContainerFactor.cpp b/gtsam_unstable/nonlinear/LinearContainerFactor.cpp new file mode 100644 index 000000000..b5701fb13 --- /dev/null +++ b/gtsam_unstable/nonlinear/LinearContainerFactor.cpp @@ -0,0 +1,240 @@ +/** + * @file LinearContainerFactor.cpp + * + * @date Jul 6, 2012 + * @author Alex Cunningham + */ + +#include + +#include + +namespace gtsam { + +/* ************************************************************************* */ +void LinearContainerFactor::rekeyFactor(const Ordering& ordering) { + Ordering::InvertedMap invOrdering = ordering.invert(); // TODO: inefficient - make more selective ordering invert + rekeyFactor(invOrdering); +} + +/* ************************************************************************* */ +void LinearContainerFactor::rekeyFactor(const Ordering::InvertedMap& invOrdering) { + BOOST_FOREACH(Index& idx, factor_->keys()) { + Key fullKey = invOrdering.find(idx)->second; + idx = fullKey; + keys_.push_back(fullKey); + } +} + +/* ************************************************************************* */ +void LinearContainerFactor::initializeLinearizationPoint(const Values& linearizationPoint) { + if (!linearizationPoint.empty()) { + linearizationPoint_ = Values(); + BOOST_FOREACH(const gtsam::Key& key, this->keys()) { + linearizationPoint_->insert(key, linearizationPoint.at(key)); + } + } else { + linearizationPoint_ = boost::none; + } +} + +/* ************************************************************************* */ +LinearContainerFactor::LinearContainerFactor(const GaussianFactor::shared_ptr& factor, + const boost::optional& linearizationPoint) +: factor_(factor), linearizationPoint_(linearizationPoint) { + // Extract keys stashed in linear factor + BOOST_FOREACH(const Index& idx, factor_->keys()) + keys_.push_back(idx); +} + +/* ************************************************************************* */ +LinearContainerFactor::LinearContainerFactor( + const JacobianFactor& factor, const Ordering& ordering, + const Values& linearizationPoint) +: factor_(factor.clone()) { + rekeyFactor(ordering); + initializeLinearizationPoint(linearizationPoint); +} + +/* ************************************************************************* */ +LinearContainerFactor::LinearContainerFactor( + const HessianFactor& factor, const Ordering& ordering, + const Values& linearizationPoint) +: factor_(factor.clone()) { + rekeyFactor(ordering); + initializeLinearizationPoint(linearizationPoint); +} + +/* ************************************************************************* */ +LinearContainerFactor::LinearContainerFactor( + const GaussianFactor::shared_ptr& factor, const Ordering& ordering, + const Values& linearizationPoint) +: factor_(factor->clone()) { + rekeyFactor(ordering); + initializeLinearizationPoint(linearizationPoint); +} + +/* ************************************************************************* */ +LinearContainerFactor::LinearContainerFactor( + const GaussianFactor::shared_ptr& factor, + const Values& linearizationPoint) +: factor_(factor->clone()) +{ + // Extract keys stashed in linear factor + BOOST_FOREACH(const Index& idx, factor_->keys()) + keys_.push_back(idx); + initializeLinearizationPoint(linearizationPoint); +} + +/* ************************************************************************* */ +LinearContainerFactor::LinearContainerFactor(const JacobianFactor& factor, + const Ordering::InvertedMap& inverted_ordering, + const Values& linearizationPoint) +: factor_(factor.clone()) { + rekeyFactor(inverted_ordering); + initializeLinearizationPoint(linearizationPoint); +} + +/* ************************************************************************* */ +LinearContainerFactor::LinearContainerFactor(const HessianFactor& factor, + const Ordering::InvertedMap& inverted_ordering, + const Values& linearizationPoint) +: factor_(factor.clone()) { + rekeyFactor(inverted_ordering); + initializeLinearizationPoint(linearizationPoint); +} + +/* ************************************************************************* */ +LinearContainerFactor::LinearContainerFactor( + const GaussianFactor::shared_ptr& factor, + const Ordering::InvertedMap& ordering, + const Values& linearizationPoint) +: factor_(factor->clone()) { + rekeyFactor(ordering); + initializeLinearizationPoint(linearizationPoint); +} + +/* ************************************************************************* */ +void LinearContainerFactor::print(const std::string& s, const KeyFormatter& keyFormatter) const { + Base::print(s+"LinearContainerFactor", keyFormatter); + if (factor_) + factor_->print(" Stored Factor", keyFormatter); + if (linearizationPoint_) + linearizationPoint_->print(" LinearizationPoint", keyFormatter); +} + +/* ************************************************************************* */ +bool LinearContainerFactor::equals(const NonlinearFactor& f, double tol) const { + const LinearContainerFactor* jcf = dynamic_cast(&f); + if (!jcf || !factor_->equals(*jcf->factor_, tol) || !NonlinearFactor::equals(f)) + return false; + if (!linearizationPoint_ && !jcf->linearizationPoint_) + return true; + if (linearizationPoint_ && jcf->linearizationPoint_) + return linearizationPoint_->equals(*jcf->linearizationPoint_, tol); + return false; +} + +/* ************************************************************************* */ +double LinearContainerFactor::error(const Values& c) const { + if (!linearizationPoint_) + return 0; + + // Extract subset of values for comparision + Values csub; + BOOST_FOREACH(const gtsam::Key& key, keys()) + csub.insert(key, c.at(key)); + + // create dummy ordering for evaluation + Ordering ordering = *csub.orderingArbitrary(); + VectorValues delta = linearizationPoint_->localCoordinates(csub, ordering); + + // Change keys on stored factor + BOOST_FOREACH(gtsam::Index& index, factor_->keys()) + index = ordering[index]; + + // compute error + double error = factor_->error(delta); + + // change keys back + factor_->keys() = keys(); + + return error; +} + +/* ************************************************************************* */ +size_t LinearContainerFactor::dim() const { + if (isJacobian()) + return toJacobian()->get_model()->dim(); + else + return 1; // Hessians don't have true dimension +} + +/* ************************************************************************* */ +GaussianFactor::shared_ptr LinearContainerFactor::order(const Ordering& ordering) const { + // clone factor + boost::shared_ptr result = factor_->clone(); + + // rekey + BOOST_FOREACH(Index& key, result->keys()) + key = ordering[key]; + + return result; +} + +/* ************************************************************************* */ +GaussianFactor::shared_ptr LinearContainerFactor::linearize( + const Values& c, const Ordering& ordering) const { + return order(ordering); +} + +/* ************************************************************************* */ +bool LinearContainerFactor::isJacobian() const { + return boost::shared_dynamic_cast(factor_); +} + +/* ************************************************************************* */ +JacobianFactor::shared_ptr LinearContainerFactor::toJacobian() const { + return boost::shared_dynamic_cast(factor_); +} + +/* ************************************************************************* */ +HessianFactor::shared_ptr LinearContainerFactor::toHessian() const { + return boost::shared_dynamic_cast(factor_); +} + +/* ************************************************************************* */ +GaussianFactor::shared_ptr LinearContainerFactor::negate(const Ordering& ordering) const { + GaussianFactor::shared_ptr result = factor_->negate(); + BOOST_FOREACH(Key& key, result->keys()) + key = ordering[key]; + return result; +} + +/* ************************************************************************* */ +NonlinearFactor::shared_ptr LinearContainerFactor::negate() const { + GaussianFactor::shared_ptr antifactor = factor_->negate(); // already has keys in place + return NonlinearFactor::shared_ptr(new LinearContainerFactor(antifactor,linearizationPoint_)); +} + +/* ************************************************************************* */ +NonlinearFactorGraph LinearContainerFactor::convertLinearGraph( + const GaussianFactorGraph& linear_graph, const Ordering& ordering) { + return convertLinearGraph(linear_graph, ordering.invert()); +} + +/* ************************************************************************* */ +NonlinearFactorGraph LinearContainerFactor::convertLinearGraph( + const GaussianFactorGraph& linear_graph, const InvertedOrdering& invOrdering) { + NonlinearFactorGraph result; + BOOST_FOREACH(const GaussianFactor::shared_ptr& f, linear_graph) + if (f) + result.push_back(NonlinearFactorGraph::sharedFactor(new LinearContainerFactor(f, invOrdering))); + return result; +} + +/* ************************************************************************* */ +} // \namespace gtsam + + + diff --git a/gtsam_unstable/nonlinear/LinearContainerFactor.h b/gtsam_unstable/nonlinear/LinearContainerFactor.h new file mode 100644 index 000000000..324556622 --- /dev/null +++ b/gtsam_unstable/nonlinear/LinearContainerFactor.h @@ -0,0 +1,149 @@ +/** + * @file LinearContainerFactor.h + * + * @brief Wrap Jacobian and Hessian linear factors to allow simple injection into a nonlinear graph + * + * @date Jul 6, 2012 + * @author Alex Cunningham + */ + +#pragma once + +#include +#include + +namespace gtsam { + +/** + * Dummy version of a generic linear factor to be injected into a nonlinear factor graph + */ +class LinearContainerFactor : public NonlinearFactor { +protected: + + GaussianFactor::shared_ptr factor_; + boost::optional linearizationPoint_; + + /** direct copy constructor */ + LinearContainerFactor(const GaussianFactor::shared_ptr& factor, + const boost::optional& linearizationPoint); + +public: + + /** Primary constructor: store a linear factor and decode the ordering */ + LinearContainerFactor(const JacobianFactor& factor, const Ordering& ordering, + const Values& linearizationPoint = Values()); + + /** Primary constructor: store a linear factor and decode the ordering */ + LinearContainerFactor(const HessianFactor& factor, const Ordering& ordering, + const Values& linearizationPoint = Values()); + + /** Constructor from shared_ptr */ + LinearContainerFactor(const GaussianFactor::shared_ptr& factor, const Ordering& ordering, + const Values& linearizationPoint = Values()); + + /** Constructor from re-keyed factor: all indices assumed replaced with Key */ + LinearContainerFactor(const GaussianFactor::shared_ptr& factor, + const Values& linearizationPoint = Values()); + + /** Alternate constructor: store a linear factor and decode keys with inverted ordering*/ + LinearContainerFactor(const JacobianFactor& factor, + const Ordering::InvertedMap& inverted_ordering, + const Values& linearizationPoint = Values()); + + /** Alternate constructor: store a linear factor and decode keys with inverted ordering*/ + LinearContainerFactor(const HessianFactor& factor, + const Ordering::InvertedMap& inverted_ordering, + const Values& linearizationPoint = Values()); + + /** Constructor from shared_ptr with inverted ordering*/ + LinearContainerFactor(const GaussianFactor::shared_ptr& factor, + const Ordering::InvertedMap& ordering, + const Values& linearizationPoint = Values()); + + // Access + + const GaussianFactor::shared_ptr& factor() const { return factor_; } + + // Testable + + /** print */ + void print(const std::string& s = "", const KeyFormatter& keyFormatter = gtsam::DefaultKeyFormatter) const; + + /** Check if two factors are equal */ + bool equals(const NonlinearFactor& f, double tol = 1e-9) const; + + // NonlinearFactor + + /** + * Calculate the error of the factor: uses the underlying linear factor to compute ordering + */ + double error(const Values& c) const; + + /** get the dimension of the factor: rows of linear factor */ + size_t dim() const; + + /** Extract the linearization point used in recalculating error */ + const boost::optional& linearizationPoint() const { return linearizationPoint_; } + + /** Apply the ordering to a graph - same as linearize(), but without needing a linearization point */ + GaussianFactor::shared_ptr order(const Ordering& ordering) const; + + /** linearize to a GaussianFactor: values has no effect, just clones/rekeys underlying factor */ + GaussianFactor::shared_ptr linearize(const Values& c, const Ordering& ordering) const; + + /** + * Creates an anti-factor directly and performs rekeying due to ordering + */ + GaussianFactor::shared_ptr negate(const Ordering& ordering) const; + + /** + * Creates the equivalent anti-factor as another LinearContainerFactor, + * so it remains independent of ordering. + */ + NonlinearFactor::shared_ptr negate() const; + + /** + * Creates a shared_ptr clone of the factor - needs to be specialized to allow + * for subclasses + * + * Clones the underlying linear factor + */ + NonlinearFactor::shared_ptr clone() const { + return NonlinearFactor::shared_ptr(new LinearContainerFactor(factor_,linearizationPoint_)); + } + + // casting syntactic sugar + + /** + * Simple check whether this is a Jacobian or Hessian factor + */ + bool isJacobian() const; + + /** Casts to JacobianFactor */ + JacobianFactor::shared_ptr toJacobian() const; + + /** Casts to HessianFactor */ + HessianFactor::shared_ptr toHessian() const; + + /** + * Utility function for converting linear graphs to nonlinear graphs + * consisting of LinearContainerFactors. Two versions are available, using + * either the ordering the linear graph was linearized around, or the inverse ordering. + * If the inverse ordering is present, it will be faster. + */ + static NonlinearFactorGraph convertLinearGraph(const GaussianFactorGraph& linear_graph, + const Ordering& ordering); + + static NonlinearFactorGraph convertLinearGraph(const GaussianFactorGraph& linear_graph, + const InvertedOrdering& invOrdering); + +protected: + void rekeyFactor(const Ordering& ordering); + void rekeyFactor(const Ordering::InvertedMap& invOrdering); + void initializeLinearizationPoint(const Values& linearizationPoint); + +}; // \class LinearContainerFactor + +} // \namespace gtsam + + diff --git a/gtsam_unstable/nonlinear/LinearizedFactor.cpp b/gtsam_unstable/nonlinear/LinearizedFactor.cpp new file mode 100644 index 000000000..3b989be6c --- /dev/null +++ b/gtsam_unstable/nonlinear/LinearizedFactor.cpp @@ -0,0 +1,148 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file LinearizedFactor.cpp + * @brief A dummy factor that allows a linear factor to act as a nonlinear factor + * @author Alex Cunningham + */ + +#include +#include + +#include + +namespace gtsam { + +using namespace std; + +/* ************************************************************************* */ +LinearizedFactor::LinearizedFactor(JacobianFactor::shared_ptr lin_factor, + const KeyLookup& decoder, const Values& lin_points) +: Base(lin_factor->get_model()), b_(lin_factor->getb()), model_(lin_factor->get_model()) { + BOOST_FOREACH(const Index& idx, *lin_factor) { + // find full symbol + KeyLookup::const_iterator decode_it = decoder.find(idx); + if (decode_it == decoder.end()) + throw runtime_error("LinearizedFactor: could not find index in decoder!"); + Key key(decode_it->second); + + // extract linearization point + assert(lin_points.exists(key)); + this->lin_points_.insert(key, lin_points.at(key)); // NOTE: will not overwrite + + // extract Jacobian + Matrix A = lin_factor->getA(lin_factor->find(idx)); + this->matrices_.insert(std::make_pair(key, A)); + + // store keys + this->keys_.push_back(key); + } +} + +/* ************************************************************************* */ +LinearizedFactor::LinearizedFactor(JacobianFactor::shared_ptr lin_factor, + const Ordering& ordering, const Values& lin_points) +: Base(lin_factor->get_model()), b_(lin_factor->getb()), model_(lin_factor->get_model()) { + const KeyLookup decoder = ordering.invert(); + BOOST_FOREACH(const Index& idx, *lin_factor) { + // find full symbol + KeyLookup::const_iterator decode_it = decoder.find(idx); + if (decode_it == decoder.end()) + throw runtime_error("LinearizedFactor: could not find index in decoder!"); + Key key(decode_it->second); + + // extract linearization point + assert(lin_points.exists(key)); + this->lin_points_.insert(key, lin_points.at(key)); // NOTE: will not overwrite + + // extract Jacobian + Matrix A = lin_factor->getA(lin_factor->find(idx)); + this->matrices_.insert(std::make_pair(key, A)); + + // store keys + this->keys_.push_back(key); + } +} + +/* ************************************************************************* */ +Vector LinearizedFactor::unwhitenedError(const Values& c, + boost::optional&> H) const { + // extract the points in the new values + Vector ret = - b_; + + if (H) H->resize(this->size()); + size_t i=0; + BOOST_FOREACH(Key key, this->keys()) { + const Value& newPt = c.at(key); + const Value& linPt = lin_points_.at(key); + Vector d = linPt.localCoordinates_(newPt); + const Matrix& A = matrices_.at(key); + ret += A * d; + if (H) (*H)[i++] = A; + } + + return ret; +} + +/* ************************************************************************* */ +boost::shared_ptr +LinearizedFactor::linearize(const Values& c, const Ordering& ordering) const { + + // sort by varid - only known at linearization time + typedef std::map VarMatrixMap; + VarMatrixMap sorting_terms; + BOOST_FOREACH(const KeyMatrixMap::value_type& p, matrices_) + sorting_terms.insert(std::make_pair(ordering[p.first], p.second)); + + // move into terms + std::vector > terms; + BOOST_FOREACH(const VarMatrixMap::value_type& p, sorting_terms) + terms.push_back(p); + + // compute rhs: adjust current by whitened update + Vector b = unwhitenedError(c) + b_; // remove original b + this->noiseModel_->whitenInPlace(b); + + return boost::shared_ptr(new JacobianFactor(terms, b - b_, model_)); +} + +/* ************************************************************************* */ +void LinearizedFactor::print(const std::string& s, const KeyFormatter& keyFormatter) const { + this->noiseModel_->print(s + std::string(" model")); + BOOST_FOREACH(const KeyMatrixMap::value_type& p, matrices_) { + gtsam::print(p.second, keyFormatter(p.first)); + } + gtsam::print(b_, std::string("b")); + std::cout << " nonlinear keys: "; + BOOST_FOREACH(const Key& key, this->keys()) + cout << keyFormatter(key) << " "; + lin_points_.print("Linearization Point"); +} + +/* ************************************************************************* */ +bool LinearizedFactor::equals(const NonlinearFactor& other, double tol) const { + const LinearizedFactor* e = dynamic_cast(&other); + if (!e || !Base::equals(other, tol) + || !lin_points_.equals(e->lin_points_, tol) + || !equal_with_abs_tol(b_, e->b_, tol) + || !model_->equals(*e->model_, tol) + || matrices_.size() != e->matrices_.size()) + return false; + + KeyMatrixMap::const_iterator map1 = matrices_.begin(), map2 = e->matrices_.begin(); + for (; map1 != matrices_.end() && map2 != e->matrices_.end(); ++map1, ++map2) + if ((map1->first != map2->first) || !equal_with_abs_tol(map1->second, map2->second, tol)) + return false; + return true; +} + +} // \namespace gtsam diff --git a/gtsam_unstable/nonlinear/LinearizedFactor.h b/gtsam_unstable/nonlinear/LinearizedFactor.h new file mode 100644 index 000000000..28102d8fd --- /dev/null +++ b/gtsam_unstable/nonlinear/LinearizedFactor.h @@ -0,0 +1,125 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file LinearizedFactor.h + * @brief A dummy factor that allows a linear factor to act as a nonlinear factor + * @author Alex Cunningham + */ + +#pragma once + +#include +#include +#include + +namespace gtsam { + +/** + * A dummy factor that takes a linearized factor and inserts it into + * a nonlinear graph. + */ +class LinearizedFactor : public gtsam::NoiseModelFactor { + +public: + /** base type */ + typedef gtsam::NoiseModelFactor Base; + typedef LinearizedFactor This; + + /** shared pointer for convenience */ + typedef boost::shared_ptr shared_ptr; + + + /** decoder for keys - avoids the use of a full ordering */ + typedef gtsam::Ordering::InvertedMap KeyLookup; + +protected: + /** hold onto the factor itself */ + // store components of a jacobian factor + typedef std::map KeyMatrixMap; + KeyMatrixMap matrices_; + gtsam::Vector b_; + gtsam::SharedDiagonal model_; /// separate from the noisemodel in NonlinearFactor due to Diagonal/Gaussian + + /** linearization points for error calculation */ + gtsam::Values lin_points_; + + /** default constructor for serialization */ + LinearizedFactor() {} + +public: + + virtual ~LinearizedFactor() {} + + /// @return a deep copy of this factor + virtual gtsam::NonlinearFactor::shared_ptr clone() const { + return boost::static_pointer_cast( + gtsam::NonlinearFactor::shared_ptr(new This(*this))); } + + /** + * Use this constructor with pre-constructed decoders + * @param lin_factor is a gaussian factor with linear keys (no labels baked in) + * @param decoder is a structure to look up the correct keys + * @param values is assumed to have the correct key structure with labels + */ + LinearizedFactor(gtsam::JacobianFactor::shared_ptr lin_factor, + const KeyLookup& decoder, const gtsam::Values& lin_points); + + /** + * Use this constructor with the ordering used to linearize the graph + * @param lin_factor is a gaussian factor with linear keys (no labels baked in) + * @param ordering is the full ordering used to linearize the graph + * @param values is assumed to have the correct key structure with labels + */ + LinearizedFactor(gtsam::JacobianFactor::shared_ptr lin_factor, + const gtsam::Ordering& ordering, const gtsam::Values& lin_points); + + /** Vector of errors, unwhitened, with optional derivatives (ordered by key) */ + virtual gtsam::Vector unwhitenedError(const gtsam::Values& c, + boost::optional&> H = boost::none) const; + + /** + * linearize to a GaussianFactor + * Reimplemented from NoiseModelFactor to directly copy out the + * matrices and only update the RHS b with an updated residual + */ + virtual boost::shared_ptr linearize( + const gtsam::Values& c, const gtsam::Ordering& ordering) const; + + // Testable + + /** print function */ + virtual void print(const std::string& s="", const KeyFormatter& keyFormatter = DefaultKeyFormatter) const; + + /** equals function with optional tolerance */ + virtual bool equals(const NonlinearFactor& other, double tol = 1e-9) const; + + // access functions + + const gtsam::Vector& b() const { return b_; } + inline const gtsam::Values& linearizationPoint() const { return lin_points_; } + +private: + /** Serialization function */ + friend class boost::serialization::access; + template + void serialize(ARCHIVE & ar, const unsigned int version) { + ar & boost::serialization::make_nvp("NonlinearFactor", + boost::serialization::base_object(*this)); + ar & BOOST_SERIALIZATION_NVP(matrices_); + ar & BOOST_SERIALIZATION_NVP(b_); + ar & BOOST_SERIALIZATION_NVP(model_); + ar & BOOST_SERIALIZATION_NVP(lin_points_); + } +}; + +} // \namespace gtsam + diff --git a/gtsam_unstable/nonlinear/tests/testLinearContainerFactor.cpp b/gtsam_unstable/nonlinear/tests/testLinearContainerFactor.cpp new file mode 100644 index 000000000..51f2f73a2 --- /dev/null +++ b/gtsam_unstable/nonlinear/tests/testLinearContainerFactor.cpp @@ -0,0 +1,162 @@ +/** + * @file testLinearContainerFactor.cpp + * + * @date Jul 6, 2012 + * @author Alex Cunningham + */ + +#include + +#include + +#include +#include + +using namespace gtsam; + +const gtsam::noiseModel::Diagonal::shared_ptr diag_model2 = noiseModel::Diagonal::Sigmas(Vector_(2, 1.0, 1.0)); +const double tol = 1e-5; + +gtsam::Key l1 = 101, l2 = 102, x1 = 1, x2 = 2; + +Point2 landmark1(5.0, 1.5), landmark2(7.0, 1.5); +Pose2 poseA1(0.0, 0.0, 0.0), poseA2(2.0, 0.0, 0.0); + +/* ************************************************************************* */ +TEST( testLinearContainerFactor, generic_jacobian_factor ) { + + Ordering initOrdering; initOrdering += x1, x2, l1, l2; + + JacobianFactor expLinFactor1( + initOrdering[l1], + Matrix_(2,2, + 2.74222, -0.0067457, + 0.0, 2.63624), + initOrdering[l2], + Matrix_(2,2, + -0.0455167, -0.0443573, + -0.0222154, -0.102489), + Vector_(2, 0.0277052, + -0.0533393), + diag_model2); + + LinearContainerFactor actFactor1(expLinFactor1, initOrdering); + Values values; + values.insert(l1, landmark1); + values.insert(l2, landmark2); + values.insert(x1, poseA1); + values.insert(x2, poseA2); + + // Check reconstruction from same ordering + GaussianFactor::shared_ptr actLinearizationA = actFactor1.linearize(values, initOrdering); + EXPECT(assert_equal(*expLinFactor1.clone(), *actLinearizationA, tol)); + + // Check reconstruction from new ordering + Ordering newOrdering; newOrdering += x1, l1, x2, l2; + GaussianFactor::shared_ptr actLinearizationB = actFactor1.linearize(values, newOrdering); + + JacobianFactor expLinFactor2( + newOrdering[l1], + Matrix_(2,2, + 2.74222, -0.0067457, + 0.0, 2.63624), + newOrdering[l2], + Matrix_(2,2, + -0.0455167, -0.0443573, + -0.0222154, -0.102489), + Vector_(2, 0.0277052, + -0.0533393), + diag_model2); + + EXPECT(assert_equal(*expLinFactor2.clone(), *actLinearizationB, tol)); +} + +/* ************************************************************************* */ +TEST( testLinearContainerFactor, jacobian_factor_withlinpoints ) { + + Ordering ordering; ordering += x1, x2, l1, l2; + + JacobianFactor expLinFactor( + ordering[l1], + Matrix_(2,2, + 2.74222, -0.0067457, + 0.0, 2.63624), + ordering[l2], + Matrix_(2,2, + -0.0455167, -0.0443573, + -0.0222154, -0.102489), + Vector_(2, 0.0277052, + -0.0533393), + diag_model2); + + Values values; + values.insert(l1, landmark1); + values.insert(l2, landmark2); + values.insert(x1, poseA1); + values.insert(x2, poseA2); + + LinearContainerFactor actFactor(expLinFactor, ordering, values); + LinearContainerFactor actFactorNolin(expLinFactor, ordering); + + EXPECT(assert_equal(actFactor, actFactor, tol)); + EXPECT(assert_inequal(actFactor, actFactorNolin, tol)); + EXPECT(assert_inequal(actFactorNolin, actFactor, tol)); + + // Check contents + Values expLinPoint; + expLinPoint.insert(l1, landmark1); + expLinPoint.insert(l2, landmark2); + CHECK(actFactor.linearizationPoint()); + EXPECT(assert_equal(expLinPoint, *actFactor.linearizationPoint())); + + // Check error evaluation + VectorValues delta = values.zeroVectors(ordering); + delta.at(ordering[l1]) = Vector_(2, 1.0, 2.0); + delta.at(ordering[l2]) = Vector_(2, 3.0, 4.0); + Values noisyValues = values.retract(delta, ordering); + double expError = expLinFactor.error(delta); + EXPECT_DOUBLES_EQUAL(expError, actFactor.error(noisyValues), tol); + EXPECT_DOUBLES_EQUAL(expLinFactor.error(values.zeroVectors(ordering)), actFactor.error(values), tol); +} + +/* ************************************************************************* */ +TEST( testLinearContainerFactor, generic_hessian_factor ) { + Matrix G11 = Matrix_(1,1, 1.0); + Matrix G12 = Matrix_(1,2, 2.0, 4.0); + Matrix G13 = Matrix_(1,3, 3.0, 6.0, 9.0); + + Matrix G22 = Matrix_(2,2, 3.0, 5.0, 0.0, 6.0); + Matrix G23 = Matrix_(2,3, 4.0, 6.0, 8.0, 1.0, 2.0, 4.0); + + Matrix G33 = Matrix_(3,3, 1.0, 2.0, 3.0, 0.0, 5.0, 6.0, 0.0, 0.0, 9.0); + + Vector g1 = Vector_(1, -7.0); + Vector g2 = Vector_(2, -8.0, -9.0); + Vector g3 = Vector_(3, 1.0, 2.0, 3.0); + + double f = 10.0; + + Ordering initOrdering; initOrdering += x1, x2, l1, l2; + HessianFactor initFactor(initOrdering[x1], initOrdering[x2], initOrdering[l1], + G11, G12, G13, g1, G22, G23, g2, G33, g3, f); + + Values values; + values.insert(l1, landmark1); + values.insert(l2, landmark2); + values.insert(x1, poseA1); + values.insert(x2, poseA2); + + LinearContainerFactor actFactor(initFactor, initOrdering); + GaussianFactor::shared_ptr actLinearization1 = actFactor.linearize(values, initOrdering); + EXPECT(assert_equal(*initFactor.clone(), *actLinearization1, tol)); + + Ordering newOrdering; newOrdering += l1, x1, x2, l2; + HessianFactor expLinFactor(newOrdering[x1], newOrdering[x2], newOrdering[l1], + G11, G12, G13, g1, G22, G23, g2, G33, g3, f); + GaussianFactor::shared_ptr actLinearization2 = actFactor.linearize(values, newOrdering); + EXPECT(assert_equal(*expLinFactor.clone(), *actLinearization2, tol)); +} + +/* ************************************************************************* */ +int main() { TestResult tr; return TestRegistry::runAllTests(tr); } +/* ************************************************************************* */ diff --git a/gtsam_unstable/nonlinear/tests/testLinearizedFactor.cpp b/gtsam_unstable/nonlinear/tests/testLinearizedFactor.cpp new file mode 100644 index 000000000..9c0438e49 --- /dev/null +++ b/gtsam_unstable/nonlinear/tests/testLinearizedFactor.cpp @@ -0,0 +1,69 @@ +/** + * @file testLinearizedFactor + * @author Alex Cunningham + */ + +#include +#include +#include +#include +#include + +#include + +using namespace std; +using namespace boost::assign; +using namespace gtsam; + +static const double tol = 1e-5; + +/* ************************************************************************* */ +TEST( testLinearizedFactor, creation ) { + // Create a set of local keys (No robot label) + Key l1 = 11, l2 = 12, + l3 = 13, l4 = 14, + l5 = 15, l6 = 16, + l7 = 17, l8 = 18; + + // creating an ordering to decode the linearized factor + Ordering ordering; + ordering += l1,l2,l3,l4,l5,l6,l7,l8; + + // create a decoder for only the relevant variables + LinearizedFactor::KeyLookup decoder; + decoder[2] = l3; + decoder[4] = l5; + + // create a linear factor + SharedDiagonal model = noiseModel::Unit::Create(2); + JacobianFactor::shared_ptr linear_factor(new JacobianFactor( + ordering[l3], eye(2,2), ordering[l5], 2.0 * eye(2,2), zero(2), model)); + + // create a set of values - build with full set of values + gtsam::Values full_values, exp_values; + full_values.insert(l3, Point2(1.0, 2.0)); + full_values.insert(l5, Point2(4.0, 3.0)); + exp_values = full_values; + full_values.insert(l1, Point2(3.0, 7.0)); + + // create the test LinearizedFactor + // This is called in the constructor of DDFSlot for each linear factor + LinearizedFactor actual1(linear_factor, decoder, full_values); + LinearizedFactor actual2(linear_factor, ordering, full_values); + + EXPECT(assert_equal(actual1, actual2, tol)); + + // Verify the keys + vector expKeys; + expKeys += l3, l5; + EXPECT(assert_container_equality(expKeys, actual1.keys())); + EXPECT(assert_container_equality(expKeys, actual2.keys())); + + // Verify subset of linearization points + EXPECT(assert_equal(exp_values, actual1.linearizationPoint(), tol)); + EXPECT(assert_equal(exp_values, actual2.linearizationPoint(), tol)); +} + +/* ************************************************************************* */ +int main() { TestResult tr; return TestRegistry::runAllTests(tr); } +/* ************************************************************************* */ diff --git a/gtsam_unstable/slam/CMakeLists.txt b/gtsam_unstable/slam/CMakeLists.txt index b0442044f..33cb45df9 100644 --- a/gtsam_unstable/slam/CMakeLists.txt +++ b/gtsam_unstable/slam/CMakeLists.txt @@ -4,7 +4,7 @@ install(FILES ${slam_headers} DESTINATION include/gtsam_unstable/slam) # Components to link tests in this subfolder against set(slam_local_libs - slam_unstable + slam_unstable slam nonlinear linear @@ -23,4 +23,4 @@ set (slam_excluded_tests "") # Add all tests gtsam_add_subdir_tests(slam_unstable "${slam_local_libs}" "${slam_full_libs}" "${slam_excluded_tests}") - +add_dependencies(check.unstable check.slam_unstable) diff --git a/gtsam_unstable/slam/InvDepthFactor3.h b/gtsam_unstable/slam/InvDepthFactor3.h new file mode 100644 index 000000000..f5856f6c8 --- /dev/null +++ b/gtsam_unstable/slam/InvDepthFactor3.h @@ -0,0 +1,116 @@ + +/** + * @file InvDepthFactor3.h + * @brief Inverse Depth Factor + * @author Chris Beall + */ + +#pragma once + +#include +#include +#include + +namespace gtsam { + +/** + * Ternary factor representing a visual measurement that includes inverse depth + */ +template +class InvDepthFactor3: public gtsam::NoiseModelFactor3 { +protected: + + // Keep a copy of measurement and calibration for I/O + gtsam::Point2 measured_; ///< 2D measurement + boost::shared_ptr K_; ///< shared pointer to calibration object + +public: + + /// shorthand for base class type + typedef gtsam::NoiseModelFactor3 Base; + + /// shorthand for this class + typedef InvDepthFactor3 This; + + /// shorthand for a smart pointer to a factor + typedef boost::shared_ptr shared_ptr; + + /// Default constructor + InvDepthFactor3() : K_(new gtsam::Cal3_S2(444, 555, 666, 777, 888)) {} + + /** + * Constructor + * TODO: Mark argument order standard (keys, measurement, parameters) + * @param measured is the 2 dimensional location of point in image (the measurement) + * @param model is the standard deviation + * @param poseKey is the index of the camera pose + * @param pointKey is the index of the landmark + * @param invDepthKey is the index of inverse depth + * @param K shared pointer to the constant calibration + */ + InvDepthFactor3(const gtsam::Point2& measured, const gtsam::SharedNoiseModel& model, + const gtsam::Key poseKey, gtsam::Key pointKey, gtsam::Key invDepthKey, const gtsam::shared_ptrK& K) : + Base(model, poseKey, pointKey, invDepthKey), measured_(measured), K_(K) {} + + /** Virtual destructor */ + virtual ~InvDepthFactor3() {} + + /** + * print + * @param s optional string naming the factor + * @param keyFormatter optional formatter useful for printing Symbols + */ + void print(const std::string& s = "InvDepthFactor3", + const gtsam::KeyFormatter& keyFormatter = gtsam::DefaultKeyFormatter) const { + Base::print(s, keyFormatter); + measured_.print(s + ".z"); + } + + /// equals + virtual bool equals(const gtsam::NonlinearFactor& p, double tol = 1e-9) const { + const This *e = dynamic_cast(&p); + return e && Base::equals(p, tol) && this->measured_.equals(e->measured_, tol) && this->K_->equals(*e->K_, tol); + } + + /// Evaluate error h(x)-z and optionally derivatives + gtsam::Vector evaluateError(const POSE& pose, const gtsam::LieVector& point, const INVDEPTH& invDepth, + boost::optional H1=boost::none, + boost::optional H2=boost::none, + boost::optional H3=boost::none) const { + try { + InvDepthCamera3 camera(pose, K_); + gtsam::Point2 reprojectionError(camera.project(point, invDepth, H1, H2, H3) - measured_); + return reprojectionError.vector(); + } catch( CheiralityException& e) { + if (H1) *H1 = gtsam::zeros(2,6); + if (H2) *H2 = gtsam::zeros(2,5); + if (H3) *H2 = gtsam::zeros(2,1); + std::cout << e.what() << ": Landmark "<< DefaultKeyFormatter(this->key2()) << + " moved behind camera " << DefaultKeyFormatter(this->key1()) << std::endl; + return gtsam::ones(2) * 2.0 * K_->fx(); + } + return gtsam::Vector_(1, 0.0); + } + + /** return the measurement */ + const gtsam::Point2& imagePoint() const { + return measured_; + } + + /** return the calibration object */ + inline const gtsam::Cal3_S2::shared_ptr calibration() const { + return K_; + } + +private: + + /// Serialization function + friend class boost::serialization::access; + template + void serialize(ARCHIVE & ar, const unsigned int version) { + ar & BOOST_SERIALIZATION_BASE_OBJECT_NVP(Base); + ar & BOOST_SERIALIZATION_NVP(measured_); + ar & BOOST_SERIALIZATION_NVP(K_); + } +}; +} // \ namespace gtsam diff --git a/gtsam/slam/PartialPriorFactor.h b/gtsam_unstable/slam/PartialPriorFactor.h similarity index 85% rename from gtsam/slam/PartialPriorFactor.h rename to gtsam_unstable/slam/PartialPriorFactor.h index 4c7069174..f096ed9bc 100644 --- a/gtsam/slam/PartialPriorFactor.h +++ b/gtsam_unstable/slam/PartialPriorFactor.h @@ -18,6 +18,7 @@ #pragma once #include +#include namespace gtsam { @@ -28,15 +29,12 @@ namespace gtsam { * * The prior vector used in this factor is stored in compressed form, such that * it only contains values for measurements that are to be compared, and they are in - * the same order as T::Logmap(). The mask will determine which components to extract + * the same order as VALUE::Logmap(). The mask will determine which components to extract * in the error function. * - * It takes two template parameters: - * Key (typically TypedSymbol) is used to look up T's in a Values - * Values where the T's are stored, typically Values or a TupleValues<...> - * * For practical use, it would be good to subclass this factor and have the class type * construct the mask. + * @tparam VALUE is the type of variable the prior effects */ template class PartialPriorFactor: public NoiseModelFactor1 { @@ -46,12 +44,15 @@ namespace gtsam { protected: + // Concept checks on the variable type - currently requires Lie + GTSAM_CONCEPT_LIE_TYPE(VALUE) + typedef NoiseModelFactor1 Base; typedef PartialPriorFactor This; - Vector prior_; ///< measurement on logmap parameters, in compressed form + Vector prior_; ///< measurement on tangent space parameters, in compressed form std::vector mask_; ///< indices of values to constrain in compressed prior vector - Matrix H_; ///< Constant jacobian - computed at creation + Matrix H_; ///< Constant Jacobian - computed at creation /** default constructor - only use for serialization */ PartialPriorFactor() {} @@ -65,9 +66,6 @@ namespace gtsam { public: - // shorthand for a smart pointer to a factor - typedef typename boost::shared_ptr shared_ptr; - virtual ~PartialPriorFactor() {} /** Single Element Constructor: acts on a single parameter specified by idx */ @@ -86,6 +84,11 @@ namespace gtsam { this->fillH(); } + /// @return a deep copy of this factor + virtual gtsam::NonlinearFactor::shared_ptr clone() const { + return boost::static_pointer_cast( + gtsam::NonlinearFactor::shared_ptr(new This(*this))); } + /** implement functions needed for Testable */ /** print */ @@ -109,6 +112,7 @@ namespace gtsam { if (H) (*H) = H_; // FIXME: this was originally the generic retraction - may not produce same results Vector full_logmap = T::Logmap(p); +// Vector full_logmap = T::identity().localCoordinates(p); // Alternate implementation Vector masked_logmap = zero(this->dim()); for (size_t i=0; i + +namespace gtsam { + +template +class PoseRotationPrior : public NoiseModelFactor1 { +public: + + typedef PoseRotationPrior This; + typedef NoiseModelFactor1 Base; + typedef POSE Pose; + typedef typename POSE::Translation Translation; + typedef typename POSE::Rotation Rotation; + + GTSAM_CONCEPT_POSE_TYPE(Pose) + GTSAM_CONCEPT_GROUP_TYPE(Pose) + GTSAM_CONCEPT_LIE_TYPE(Rotation) + +protected: + + Rotation measured_; + +public: + + /** standard constructor */ + PoseRotationPrior(Key key, const Rotation& rot_z, const SharedNoiseModel& model) + : Base(model, key), measured_(rot_z) {} + + /** Constructor that pulls the translation from an incoming POSE */ + PoseRotationPrior(Key key, const POSE& pose_z, const SharedNoiseModel& model) + : Base(model, key), measured_(pose_z.rotation()) {} + + virtual ~PoseRotationPrior() {} + + // access + const Rotation& measured() const { return measured_; } + + // testable + + /** equals specialized to this factor */ + virtual bool equals(const NonlinearFactor& expected, double tol=1e-9) const { + const This *e = dynamic_cast (&expected); + return e != NULL && Base::equals(*e, tol) && measured_.equals(e->measured_, tol); + } + + /** print contents */ + void print(const std::string& s="", const KeyFormatter& keyFormatter = DefaultKeyFormatter) const { + Base::print(s + "PoseRotationPrior", keyFormatter); + measured_.print("Measured Rotation"); + } + + /** h(x)-z */ + Vector evaluateError(const Pose& pose, boost::optional H = boost::none) const { + const Rotation& newR = pose.rotation(); + const size_t rDim = newR.dim(), xDim = pose.dim(); + if (H) { + *H = gtsam::zeros(rDim, xDim); + if (pose_traits::isRotFirst()) + (*H).leftCols(rDim).setIdentity(rDim, rDim); + else + (*H).rightCols(rDim).setIdentity(rDim, rDim); + } + + return Rotation::Logmap(newR) - Rotation::Logmap(measured_); + } + +private: + + /** Serialization function */ + friend class boost::serialization::access; + template + void serialize(ARCHIVE & ar, const unsigned int version) { + ar & boost::serialization::make_nvp("NoiseModelFactor1", + boost::serialization::base_object(*this)); + ar & BOOST_SERIALIZATION_NVP(measured_); + } +}; + +} // \namespace gtsam + + + + diff --git a/gtsam_unstable/slam/PoseTranslationPrior.h b/gtsam_unstable/slam/PoseTranslationPrior.h new file mode 100644 index 000000000..9fc2bb423 --- /dev/null +++ b/gtsam_unstable/slam/PoseTranslationPrior.h @@ -0,0 +1,119 @@ +/** + * @file PoseTranslationPrior.h + * + * @brief Implements a prior on the translation component of a pose + * + * @date Jun 14, 2012 + * @author Alex Cunningham + */ + +#pragma once + +#include +#include + +namespace gtsam { + +/** simple pose traits for building factors */ +namespace pose_traits { + +/** checks whether parameterization of rotation is before or after translation in Lie algebra */ +template +bool isRotFirst() { + throw std::invalid_argument("PoseTrait: no implementation for this pose type"); + return false; +} + +// Instantiate for common poses +template<> inline bool isRotFirst() { return true; } +template<> inline bool isRotFirst() { return false; } + +} // \namespace pose_traits + +/** + * A prior on the translation part of a pose + */ +template +class PoseTranslationPrior : public NoiseModelFactor1 { +public: + typedef PoseTranslationPrior This; + typedef NoiseModelFactor1 Base; + typedef POSE Pose; + typedef typename POSE::Translation Translation; + typedef typename POSE::Rotation Rotation; + + GTSAM_CONCEPT_POSE_TYPE(Pose) + GTSAM_CONCEPT_GROUP_TYPE(Pose) + GTSAM_CONCEPT_LIE_TYPE(Translation) + +protected: + + Translation measured_; + +public: + + /** standard constructor */ + PoseTranslationPrior(Key key, const Translation& measured, const noiseModel::Base::shared_ptr& model) + : Base(model, key), measured_(measured) { + } + + /** Constructor that pulls the translation from an incoming POSE */ + PoseTranslationPrior(Key key, const POSE& pose_z, const noiseModel::Base::shared_ptr& model) + : Base(model, key), measured_(pose_z.translation()) { + } + + virtual ~PoseTranslationPrior() {} + + const Translation& measured() const { return measured_; } + + /// @return a deep copy of this factor + virtual gtsam::NonlinearFactor::shared_ptr clone() const { + return boost::static_pointer_cast( + gtsam::NonlinearFactor::shared_ptr(new This(*this))); } + + /** h(x)-z */ + Vector evaluateError(const Pose& pose, boost::optional H = boost::none) const { + const Translation& newTrans = pose.translation(); + const Rotation& R = pose.rotation(); + const size_t tDim = newTrans.dim(), xDim = pose.dim(); + if (H) { + *H = gtsam::zeros(tDim, xDim); + if (pose_traits::isRotFirst()) + (*H).rightCols(tDim) = R.matrix(); + else + (*H).leftCols(tDim) = R.matrix(); + } + + return newTrans.vector() - measured_.vector(); + } + + /** equals specialized to this factor */ + virtual bool equals(const NonlinearFactor& expected, double tol=1e-9) const { + const This *e = dynamic_cast (&expected); + return e != NULL && Base::equals(*e, tol) && measured_.equals(e->measured_, tol); + } + + /** print contents */ + void print(const std::string& s="", const KeyFormatter& keyFormatter = DefaultKeyFormatter) const { + Base::print(s + "PoseTranslationPrior", keyFormatter); + measured_.print("Measured Translation"); + } + +private: + + /** Serialization function */ + friend class boost::serialization::access; + template + void serialize(ARCHIVE & ar, const unsigned int version) { + ar & boost::serialization::make_nvp("NoiseModelFactor1", + boost::serialization::base_object(*this)); + ar & BOOST_SERIALIZATION_NVP(measured_); + } + +}; + +} // \namespace gtsam + + + + diff --git a/gtsam_unstable/slam/RelativeElevationFactor.cpp b/gtsam_unstable/slam/RelativeElevationFactor.cpp new file mode 100644 index 000000000..2d0ca7548 --- /dev/null +++ b/gtsam_unstable/slam/RelativeElevationFactor.cpp @@ -0,0 +1,53 @@ +/** + * @file RelativeElevationFactor.cpp + * + * @date Aug 17, 2012 + * @author Alex Cunningham + */ + +#include + +namespace gtsam { + +/* ************************************************************************* */ +RelativeElevationFactor::RelativeElevationFactor(Key poseKey, Key pointKey, double measured, + const SharedNoiseModel& model) +: Base(model, poseKey, pointKey), measured_(measured) +{ +} + +/* ************************************************************************* */ +Vector RelativeElevationFactor::evaluateError(const Pose3& pose, const Point3& point, + boost::optional H1, boost::optional H2) const { + double hx = pose.z() - point.z(); + if (H1) { + *H1 = zeros(1, 6); + // Use bottom row of rotation matrix for derivative of translation + (*H1)(0, 3) = pose.rotation().r1().z(); + (*H1)(0, 4) = pose.rotation().r2().z(); + (*H1)(0, 5) = pose.rotation().r3().z(); + } + + if (H2) { + *H2 = zeros(1, 3); + (*H2)(0, 2) = -1.0; + } + return Vector_(1, hx - measured_); +} + +/* ************************************************************************* */ +bool RelativeElevationFactor::equals(const NonlinearFactor& expected, double tol) const { + const This *e = dynamic_cast (&expected); + return e != NULL && Base::equals(*e, tol) && fabs(this->measured_ - e->measured_) < tol; +} + +/* ************************************************************************* */ +void RelativeElevationFactor::print(const std::string& s, const KeyFormatter& keyFormatter) const { + std::cout << s << "RelativeElevationFactor, relative elevation = " << measured_ << std::endl; + Base::print("", keyFormatter); +} +/* ************************************************************************* */ + +} // \namespace gtsam + + diff --git a/gtsam_unstable/slam/RelativeElevationFactor.h b/gtsam_unstable/slam/RelativeElevationFactor.h new file mode 100644 index 000000000..a0186a9f2 --- /dev/null +++ b/gtsam_unstable/slam/RelativeElevationFactor.h @@ -0,0 +1,77 @@ +/** + * @file RelativeElevationFactor.h + * + * @brief Factor representing a known relative altitude in global frame + * + * @date Aug 17, 2012 + * @author Alex Cunningham + */ + +#pragma once + +#include +#include + +namespace gtsam { + +/** + * Binary factor for a relative elevation. Note that this + * factor takes into account only elevation, and corrects for orientation. + * Unlike a range factor, the relative elevation is signed, and only affects + * the Z coordinate. Measurement function h(pose, pt) = h.z() - pt.z() + * + * Dimension: 1 + * + * TODO: enable use of a Pose3 for the target as well + */ +class RelativeElevationFactor: public NoiseModelFactor2 { +private: + + double measured_; /** measurement */ + + typedef RelativeElevationFactor This; + typedef NoiseModelFactor2 Base; + +public: + + RelativeElevationFactor() : measured_(0.0) {} /* Default constructor */ + + RelativeElevationFactor(Key poseKey, Key pointKey, double measured, + const SharedNoiseModel& model); + + virtual ~RelativeElevationFactor() {} + + /// @return a deep copy of this factor + virtual gtsam::NonlinearFactor::shared_ptr clone() const { + return boost::static_pointer_cast( + gtsam::NonlinearFactor::shared_ptr(new This(*this))); } + + /** h(x)-z */ + Vector evaluateError(const Pose3& pose, const Point3& point, + boost::optional H1 = boost::none, boost::optional H2 = boost::none) const; + + /** return the measured */ + inline double measured() const { return measured_; } + + /** equals specialized to this factor */ + virtual bool equals(const NonlinearFactor& expected, double tol=1e-9) const; + + /** print contents */ + void print(const std::string& s="", const KeyFormatter& keyFormatter = DefaultKeyFormatter) const; + +private: + + /** Serialization function */ + friend class boost::serialization::access; + template + void serialize(ARCHIVE & ar, const unsigned int version) { + ar & boost::serialization::make_nvp("NoiseModelFactor2", + boost::serialization::base_object(*this)); + ar & BOOST_SERIALIZATION_NVP(measured_); + } +}; // RelativeElevationFactor + + +} // \namespace gtsam + + diff --git a/gtsam_unstable/slam/tests/testInvDepthFactor3.cpp b/gtsam_unstable/slam/tests/testInvDepthFactor3.cpp new file mode 100644 index 000000000..5567bc9ce --- /dev/null +++ b/gtsam_unstable/slam/tests/testInvDepthFactor3.cpp @@ -0,0 +1,92 @@ +/* + * testInvDepthFactor.cpp + * + * Created on: Apr 13, 2012 + * Author: cbeall3 + */ + +#include + +#include +#include +#include +#include +#include + +#include + +using namespace std; +using namespace gtsam; + +static Cal3_S2::shared_ptr K(new Cal3_S2(1500, 1200, 0, 640, 480)); +static SharedNoiseModel sigma(noiseModel::Unit::Create(2)); + +Pose3 level_pose = Pose3(Rot3::ypr(-M_PI/2, 0., -M_PI/2), gtsam::Point3(0,0,1)); +SimpleCamera level_camera(level_pose, *K); + +typedef InvDepthFactor3 InverseDepthFactor; +typedef NonlinearEquality PoseConstraint; + +/* ************************************************************************* */ +TEST( InvDepthFactor, optimize) { + + // landmark 5 meters infront of camera + Point3 landmark(5, 0, 1); + + Point2 expected_uv = level_camera.project(landmark); + + InvDepthCamera3 inv_camera(level_pose, K); + LieVector inv_landmark(5, 1., 0., 1., 0., 0.); + LieScalar inv_depth(1./4); + + gtsam::NonlinearFactorGraph graph; + Values initial; + + InverseDepthFactor::shared_ptr factor(new InverseDepthFactor(expected_uv, sigma, + Symbol('x',1), Symbol('l',1), Symbol('d',1), K)); + graph.push_back(factor); + graph.add(PoseConstraint(Symbol('x',1),level_pose)); + initial.insert(Symbol('x',1), level_pose); + initial.insert(Symbol('l',1), inv_landmark); + initial.insert(Symbol('d',1), inv_depth); + + LevenbergMarquardtParams lmParams; + Values result = LevenbergMarquardtOptimizer(graph, initial, lmParams).optimize(); + EXPECT(assert_equal(initial, result, 1e-9)); + + /// Add a second camera + + // add a camera 1 meter to the right + Pose3 right_pose = level_pose * Pose3(Rot3(), Point3(2,0,0)); + SimpleCamera right_camera(right_pose, *K); + + InvDepthCamera3 right_inv_camera(right_pose, K); + + Point3 landmark1(6,0,1); + Point2 right_uv = right_camera.project(landmark1); + + + InverseDepthFactor::shared_ptr factor1(new InverseDepthFactor(right_uv, sigma, + Symbol('x',2), Symbol('l',1),Symbol('d',1),K)); + graph.push_back(factor1); + + graph.add(PoseConstraint(Symbol('x',2),right_pose)); + + initial.insert(Symbol('x',2), right_pose); + + // TODO: need to add priors to make this work with +// Values result2 = optimize(graph, initial, +// NonlinearOptimizationParameters(),MULTIFRONTAL, GN); + + Values result2 = LevenbergMarquardtOptimizer(graph, initial, lmParams).optimize(); + Point3 l1_result2 = InvDepthCamera3::invDepthTo3D( + result2.at(Symbol('l',1)), + result2.at(Symbol('d',1))); + + EXPECT(assert_equal(landmark1, l1_result2, 1e-9)); +} + + +/* ************************************************************************* */ +int main() { TestResult tr; return TestRegistry::runAllTests(tr);} +/* ************************************************************************* */ diff --git a/gtsam_unstable/slam/tests/testPoseRotationPrior.cpp b/gtsam_unstable/slam/tests/testPoseRotationPrior.cpp new file mode 100644 index 000000000..2f60e114a --- /dev/null +++ b/gtsam_unstable/slam/tests/testPoseRotationPrior.cpp @@ -0,0 +1,95 @@ +/** + * @file testPoseRotationPrior.cpp + * + * @brief Tests rotation priors on poses + * + * @date Jun 14, 2012 + * @author Alex Cunningham + */ + +#include + +#include + +#include +#include + +#include + +using namespace gtsam; + +const SharedNoiseModel model1 = noiseModel::Diagonal::Sigmas(Vector_(1, 0.1)); +const SharedNoiseModel model3 = noiseModel::Diagonal::Sigmas(Vector_(3, 0.1, 0.2, 0.3)); + +typedef PoseRotationPrior Pose2RotationPrior; +typedef PoseRotationPrior Pose3RotationPrior; + +const double tol = 1e-5; + +const gtsam::Key poseKey = 1; + +// Pose3 examples +const Point3 point3A(1.0, 2.0, 3.0), point3B(4.0, 6.0, 8.0); +const Rot3 rot3A, rot3B = Rot3::pitch(-M_PI_2), rot3C = Rot3::Expmap(Vector_(3, 0.1, 0.2, 0.3)); + +// Pose2 examples +const Point2 point2A(1.0, 2.0), point2B(4.0, 6.0); +const Rot2 rot2A, rot2B = Rot2::fromAngle(M_PI_2); + +/* ************************************************************************* */ +LieVector evalFactorError3(const Pose3RotationPrior& factor, const Pose3& x) { + return LieVector(factor.evaluateError(x)); +} + +/* ************************************************************************* */ +LieVector evalFactorError2(const Pose2RotationPrior& factor, const Pose2& x) { + return LieVector(factor.evaluateError(x)); +} + +/* ************************************************************************* */ +TEST( testPoseRotationFactor, level3_zero_error ) { + Pose3 pose1(rot3A, point3A); + Pose3RotationPrior factor(poseKey, rot3A, model3); + Matrix actH1; + EXPECT(assert_equal(zero(3), factor.evaluateError(pose1, actH1))); + Matrix expH1 = numericalDerivative11( + boost::bind(evalFactorError3, factor, _1), pose1, 1e-5); + EXPECT(assert_equal(expH1, actH1, tol)); +} + +/* ************************************************************************* */ +TEST( testPoseRotationFactor, level3_error ) { + Pose3 pose1(rot3A, point3A); + Pose3RotationPrior factor(poseKey, rot3C, model3); + Matrix actH1; + EXPECT(assert_equal(Vector_(3,-0.1,-0.2,-0.3), factor.evaluateError(pose1, actH1))); + Matrix expH1 = numericalDerivative11( + boost::bind(evalFactorError3, factor, _1), pose1, 1e-5); + EXPECT(assert_equal(expH1, actH1, tol)); +} + +/* ************************************************************************* */ +TEST( testPoseRotationFactor, level2_zero_error ) { + Pose2 pose1(rot2A, point2A); + Pose2RotationPrior factor(poseKey, rot2A, model1); + Matrix actH1; + EXPECT(assert_equal(zero(1), factor.evaluateError(pose1, actH1))); + Matrix expH1 = numericalDerivative11( + boost::bind(evalFactorError2, factor, _1), pose1, 1e-5); + EXPECT(assert_equal(expH1, actH1, tol)); +} + +/* ************************************************************************* */ +TEST( testPoseRotationFactor, level2_error ) { + Pose2 pose1(rot2A, point2A); + Pose2RotationPrior factor(poseKey, rot2B, model1); + Matrix actH1; + EXPECT(assert_equal(Vector_(1,-M_PI_2), factor.evaluateError(pose1, actH1))); + Matrix expH1 = numericalDerivative11( + boost::bind(evalFactorError2, factor, _1), pose1, 1e-5); + EXPECT(assert_equal(expH1, actH1, tol)); +} + +/* ************************************************************************* */ +int main() { TestResult tr; return TestRegistry::runAllTests(tr); } +/* ************************************************************************* */ diff --git a/gtsam_unstable/slam/tests/testPoseTranslationPrior.cpp b/gtsam_unstable/slam/tests/testPoseTranslationPrior.cpp new file mode 100644 index 000000000..9e11555ee --- /dev/null +++ b/gtsam_unstable/slam/tests/testPoseTranslationPrior.cpp @@ -0,0 +1,136 @@ +/** + * @file testPoseTranslationPrior.cpp + * + * @date Aug 19, 2012 + * @author Alex Cunningham + */ + +#include + +#include +#include +#include + +#include + +using namespace gtsam; + +const SharedNoiseModel model2 = noiseModel::Diagonal::Sigmas(Vector_(2, 0.1, 0.2)); +const SharedNoiseModel model3 = noiseModel::Diagonal::Sigmas(Vector_(3, 0.1, 0.2, 0.3)); + +typedef PoseTranslationPrior Pose2TranslationPrior; +typedef PoseTranslationPrior Pose3TranslationPrior; + +const double tol = 1e-5; + +const gtsam::Key poseKey = 1; + +// Pose3 examples +const Point3 point3A(1.0, 2.0, 3.0), point3B(4.0, 6.0, 8.0); +const Rot3 rot3A, rot3B = Rot3::pitch(-M_PI_2), rot3C = Rot3::RzRyRx(0.1, 0.2, 0.3); + +// Pose2 examples +const Point2 point2A(1.0, 2.0), point2B(4.0, 6.0); +const Rot2 rot2A, rot2B = Rot2::fromAngle(M_PI_2); + +/* ************************************************************************* */ +LieVector evalFactorError3(const Pose3TranslationPrior& factor, const Pose3& x) { + return LieVector(factor.evaluateError(x)); +} + +/* ************************************************************************* */ +LieVector evalFactorError2(const Pose2TranslationPrior& factor, const Pose2& x) { + return LieVector(factor.evaluateError(x)); +} + +/* ************************************************************************* */ +TEST( testPoseTranslationFactor, level3_zero_error ) { + Pose3 pose1(rot3A, point3A); + Pose3TranslationPrior factor(poseKey, point3A, model3); + Matrix actH1; + EXPECT(assert_equal(zero(3), factor.evaluateError(pose1, actH1))); + Matrix expH1 = numericalDerivative11( + boost::bind(evalFactorError3, factor, _1), pose1, 1e-5); + EXPECT(assert_equal(expH1, actH1, tol)); +} + +/* ************************************************************************* */ +TEST( testPoseTranslationFactor, level3_error ) { + Pose3 pose1(rot3A, point3A); + Pose3TranslationPrior factor(poseKey, point3B, model3); + Matrix actH1; + EXPECT(assert_equal(Vector_(3,-3.0,-4.0,-5.0), factor.evaluateError(pose1, actH1))); + Matrix expH1 = numericalDerivative11( + boost::bind(evalFactorError3, factor, _1), pose1, 1e-5); + EXPECT(assert_equal(expH1, actH1, tol)); +} + +/* ************************************************************************* */ +TEST( testPoseTranslationFactor, pitched3_zero_error ) { + Pose3 pose1(rot3B, point3A); + Pose3TranslationPrior factor(poseKey, point3A, model3); + Matrix actH1; + EXPECT(assert_equal(zero(3), factor.evaluateError(pose1, actH1))); + Matrix expH1 = numericalDerivative11( + boost::bind(evalFactorError3, factor, _1), pose1, 1e-5); + EXPECT(assert_equal(expH1, actH1, tol)); +} + +/* ************************************************************************* */ +TEST( testPoseTranslationFactor, pitched3_error ) { + Pose3 pose1(rot3B, point3A); + Pose3TranslationPrior factor(poseKey, point3B, model3); + Matrix actH1; + EXPECT(assert_equal(Vector_(3,-3.0,-4.0,-5.0), factor.evaluateError(pose1, actH1))); + Matrix expH1 = numericalDerivative11( + boost::bind(evalFactorError3, factor, _1), pose1, 1e-5); + EXPECT(assert_equal(expH1, actH1, tol)); +} + +/* ************************************************************************* */ +TEST( testPoseTranslationFactor, smallrot3_zero_error ) { + Pose3 pose1(rot3C, point3A); + Pose3TranslationPrior factor(poseKey, point3A, model3); + Matrix actH1; + EXPECT(assert_equal(zero(3), factor.evaluateError(pose1, actH1))); + Matrix expH1 = numericalDerivative11( + boost::bind(evalFactorError3, factor, _1), pose1, 1e-5); + EXPECT(assert_equal(expH1, actH1, tol)); +} + +/* ************************************************************************* */ +TEST( testPoseTranslationFactor, smallrot3_error ) { + Pose3 pose1(rot3C, point3A); + Pose3TranslationPrior factor(poseKey, point3B, model3); + Matrix actH1; + EXPECT(assert_equal(Vector_(3,-3.0,-4.0,-5.0), factor.evaluateError(pose1, actH1))); + Matrix expH1 = numericalDerivative11( + boost::bind(evalFactorError3, factor, _1), pose1, 1e-5); + EXPECT(assert_equal(expH1, actH1, tol)); +} + +/* ************************************************************************* */ +TEST( testPoseTranslationFactor, level2_zero_error ) { + Pose2 pose1(rot2A, point2A); + Pose2TranslationPrior factor(poseKey, point2A, model2); + Matrix actH1; + EXPECT(assert_equal(zero(2), factor.evaluateError(pose1, actH1))); + Matrix expH1 = numericalDerivative11( + boost::bind(evalFactorError2, factor, _1), pose1, 1e-5); + EXPECT(assert_equal(expH1, actH1, tol)); +} + +/* ************************************************************************* */ +TEST( testPoseTranslationFactor, level2_error ) { + Pose2 pose1(rot2A, point2A); + Pose2TranslationPrior factor(poseKey, point2B, model2); + Matrix actH1; + EXPECT(assert_equal(Vector_(2,-3.0,-4.0), factor.evaluateError(pose1, actH1))); + Matrix expH1 = numericalDerivative11( + boost::bind(evalFactorError2, factor, _1), pose1, 1e-5); + EXPECT(assert_equal(expH1, actH1, tol)); +} + +/* ************************************************************************* */ +int main() { TestResult tr; return TestRegistry::runAllTests(tr); } +/* ************************************************************************* */ diff --git a/gtsam_unstable/slam/tests/testRelativeElevationFactor.cpp b/gtsam_unstable/slam/tests/testRelativeElevationFactor.cpp new file mode 100644 index 000000000..321464c48 --- /dev/null +++ b/gtsam_unstable/slam/tests/testRelativeElevationFactor.cpp @@ -0,0 +1,138 @@ +/** + * @file testRelativeElevationFactor.cpp + * + * @date Aug 17, 2012 + * @author Alex Cunningham + */ + +#include + +#include + +#include + +using namespace gtsam; + +SharedNoiseModel model1 = noiseModel::Unit::Create(1); + +const double tol = 1e-5; + +const Pose3 pose1(Rot3(), Point3(2.0, 3.0, 4.0)); +const Pose3 pose2(Rot3::pitch(-M_PI_2), Point3(2.0, 3.0, 4.0)); +const Pose3 pose3(Rot3::RzRyRx(0.1, 0.2, 0.3), Point3(2.0, 3.0, 4.0)); +const Point3 point1(3.0, 4.0, 2.0); +const gtsam::Key poseKey = 1, pointKey = 2; + +/* ************************************************************************* */ +LieVector evalFactorError(const RelativeElevationFactor& factor, const Pose3& x, const Point3& p) { + return LieVector(factor.evaluateError(x, p)); +} + +/* ************************************************************************* */ +TEST( testRelativeElevationFactor, level_zero_error ) { + // Zero error + double measured = 2.0; + RelativeElevationFactor factor(poseKey, pointKey, measured, model1); + Matrix actH1, actH2; + EXPECT(assert_equal(zero(1), factor.evaluateError(pose1, point1, actH1, actH2))); + Matrix expH1 = numericalDerivative21( + boost::bind(evalFactorError, factor, _1, _2), pose1, point1, 1e-5); + Matrix expH2 = numericalDerivative22( + boost::bind(evalFactorError, factor, _1, _2), pose1, point1, 1e-5); + EXPECT(assert_equal(expH1, actH1, tol)); + EXPECT(assert_equal(expH2, actH2, tol)); +} + +/* ************************************************************************* */ +TEST( testRelativeElevationFactor, level_positive ) { + // Positive meas + double measured = 0.0; + RelativeElevationFactor factor(poseKey, pointKey, measured, model1); + Matrix actH1, actH2; + EXPECT(assert_equal(Vector_(1, 2.0), factor.evaluateError(pose1, point1, actH1, actH2))); + Matrix expH1 = numericalDerivative21( + boost::bind(evalFactorError, factor, _1, _2), pose1, point1, 1e-5); + Matrix expH2 = numericalDerivative22( + boost::bind(evalFactorError, factor, _1, _2), pose1, point1, 1e-5); + EXPECT(assert_equal(expH1, actH1, tol)); + EXPECT(assert_equal(expH2, actH2, tol)); +} + +/* ************************************************************************* */ +TEST( testRelativeElevationFactor, level_negative ) { + // Negative meas + double measured = -1.0; + RelativeElevationFactor factor(poseKey, pointKey, measured, model1); + Matrix actH1, actH2; + EXPECT(assert_equal(Vector_(1, 3.0), factor.evaluateError(pose1, point1, actH1, actH2))); + Matrix expH1 = numericalDerivative21( + boost::bind(evalFactorError, factor, _1, _2), pose1, point1, 1e-5); + Matrix expH2 = numericalDerivative22( + boost::bind(evalFactorError, factor, _1, _2), pose1, point1, 1e-5); + EXPECT(assert_equal(expH1, actH1, tol)); + EXPECT(assert_equal(expH2, actH2, tol)); +} + +/* ************************************************************************* */ +TEST( testRelativeElevationFactor, rotated_zero_error ) { + // Zero error + double measured = 2.0; + RelativeElevationFactor factor(poseKey, pointKey, measured, model1); + Matrix actH1, actH2; + EXPECT(assert_equal(zero(1), factor.evaluateError(pose2, point1, actH1, actH2))); + Matrix expH1 = numericalDerivative21( + boost::bind(evalFactorError, factor, _1, _2), pose2, point1, 1e-5); + Matrix expH2 = numericalDerivative22( + boost::bind(evalFactorError, factor, _1, _2), pose2, point1, 1e-5); + EXPECT(assert_equal(expH1, actH1, tol)); + EXPECT(assert_equal(expH2, actH2, tol)); +} + +/* ************************************************************************* */ +TEST( testRelativeElevationFactor, rotated_positive ) { + // Positive meas + double measured = 0.0; + RelativeElevationFactor factor(poseKey, pointKey, measured, model1); + Matrix actH1, actH2; + EXPECT(assert_equal(Vector_(1, 2.0), factor.evaluateError(pose2, point1, actH1, actH2))); + Matrix expH1 = numericalDerivative21( + boost::bind(evalFactorError, factor, _1, _2), pose2, point1, 1e-5); + Matrix expH2 = numericalDerivative22( + boost::bind(evalFactorError, factor, _1, _2), pose2, point1, 1e-5); + EXPECT(assert_equal(expH1, actH1, tol)); + EXPECT(assert_equal(expH2, actH2, tol)); +} + +/* ************************************************************************* */ +TEST( testRelativeElevationFactor, rotated_negative1 ) { + // Negative meas + double measured = -1.0; + RelativeElevationFactor factor(poseKey, pointKey, measured, model1); + Matrix actH1, actH2; + EXPECT(assert_equal(Vector_(1, 3.0), factor.evaluateError(pose2, point1, actH1, actH2))); + Matrix expH1 = numericalDerivative21( + boost::bind(evalFactorError, factor, _1, _2), pose2, point1, 1e-5); + Matrix expH2 = numericalDerivative22( + boost::bind(evalFactorError, factor, _1, _2), pose2, point1, 1e-5); + EXPECT(assert_equal(expH1, actH1, tol)); + EXPECT(assert_equal(expH2, actH2, tol)); +} + +/* ************************************************************************* */ +TEST( testRelativeElevationFactor, rotated_negative2 ) { + // Negative meas + double measured = -1.0; + RelativeElevationFactor factor(poseKey, pointKey, measured, model1); + Matrix actH1, actH2; + EXPECT(assert_equal(Vector_(1, 3.0), factor.evaluateError(pose3, point1, actH1, actH2))); + Matrix expH1 = numericalDerivative21( + boost::bind(evalFactorError, factor, _1, _2), pose3, point1, 1e-5); + Matrix expH2 = numericalDerivative22( + boost::bind(evalFactorError, factor, _1, _2), pose3, point1, 1e-5); + EXPECT(assert_equal(expH1, actH1, tol)); + EXPECT(assert_equal(expH2, actH2, tol)); +} + +/* ************************************************************************* */ +int main() { TestResult tr; return TestRegistry::runAllTests(tr); } +/* ************************************************************************* */ diff --git a/makedoc.sh b/makedoc.sh deleted file mode 100755 index 5acbd3d87..000000000 --- a/makedoc.sh +++ /dev/null @@ -1,13 +0,0 @@ -#!/bin/sh - -# Add to PATH the default install path for doxygen on Mac OS X - -PATH=$PATH:/Applications/Doxygen.app/Contents/Resources - - -# Run doxygen from the gtsam directory even if this script is run from another -# directory, so that the output 'doc' goes in the gtsam directory. - -GTSAM_DIR=$(dirname "$0") -cd $GTSAM_DIR -doxygen \ No newline at end of file diff --git a/makestats.sh b/makestats.sh new file mode 100644 index 000000000..f1201ddd0 --- /dev/null +++ b/makestats.sh @@ -0,0 +1 @@ +java -jar ~/src/statsvn-0.7.0/statsvn.jar -output-dir stats -exclude "examples/Data/**/*;gtsam/3rdparty/**/*" logfile.log . diff --git a/matlab.h b/matlab.h new file mode 100644 index 000000000..dfc0117e7 --- /dev/null +++ b/matlab.h @@ -0,0 +1,142 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file matlab.h + * @brief Contains *generic* global functions designed particularly for the matlab interface + * @author Stephen Williams + */ + +#pragma once + +#include +#include +#include +#include +#include +#include +#include +#include +#include + +#include + +namespace gtsam { + + namespace utilities { + + /// Extract all Point2 values into a single matrix [x y] + Matrix extractPoint2(const Values& values) { + size_t j=0; + Values::ConstFiltered points = values.filter(); + Matrix result(points.size(),2); + BOOST_FOREACH(const Values::ConstFiltered::KeyValuePair& key_value, points) + result.row(j++) = key_value.value.vector(); + return result; + } + + /// Extract all Point3 values into a single matrix [x y z] + Matrix extractPoint3(const Values& values) { + size_t j=0; + Values::ConstFiltered points = values.filter(); + Matrix result(points.size(),3); + BOOST_FOREACH(const Values::ConstFiltered::KeyValuePair& key_value, points) + result.row(j++) = key_value.value.vector(); + return result; + } + + /// Extract all Pose2 values into a single matrix [x y theta] + Matrix extractPose2(const Values& values) { + size_t j=0; + Values::ConstFiltered poses = values.filter(); + Matrix result(poses.size(),3); + BOOST_FOREACH(const Values::ConstFiltered::KeyValuePair& key_value, poses) + result.row(j++) << key_value.value.x(), key_value.value.y(), key_value.value.theta(); + return result; + } + + /// Extract all Pose3 values into a single matrix [r11 r12 r13 r21 r22 r23 r31 r32 r33 x y z] + Matrix extractPose3(const Values& values) { + size_t j=0; + Values::ConstFiltered poses = values.filter(); + Matrix result(poses.size(),12); + BOOST_FOREACH(const Values::ConstFiltered::KeyValuePair& key_value, poses) { + result.row(j).segment(0, 3) << key_value.value.rotation().matrix().row(0); + result.row(j).segment(3, 3) << key_value.value.rotation().matrix().row(1); + result.row(j).segment(6, 3) << key_value.value.rotation().matrix().row(2); + result.row(j).tail(3) = key_value.value.translation().vector(); + j++; + } + return result; + } + + + /// perturb all Point2 using normally distributed noise + void perturbPoint2(Values& values, double sigma, int32_t seed = 42u) { + noiseModel::Isotropic::shared_ptr model = noiseModel::Isotropic::Sigma(2,sigma); + Sampler sampler(model, seed); + BOOST_FOREACH(const Values::ConstFiltered::KeyValuePair& key_value, values.filter()) { + values.update(key_value.key, key_value.value.retract(sampler.sample())); + } + } + + /// perturb all Point3 using normally distributed noise + void perturbPoint3(Values& values, double sigma, int32_t seed = 42u) { + noiseModel::Isotropic::shared_ptr model = noiseModel::Isotropic::Sigma(3,sigma); + Sampler sampler(model, seed); + BOOST_FOREACH(const Values::ConstFiltered::KeyValuePair& key_value, values.filter()) { + values.update(key_value.key, key_value.value.retract(sampler.sample())); + } + } + + /// insert a number of initial point values by backprojecting + void insertBackprojections(Values& values, const SimpleCamera& camera, const Vector& J, const Matrix& Z, double depth) { + if (Z.rows() != 2) throw std::invalid_argument("insertBackProjections: Z must be 2*K"); + if (Z.cols() != J.size()) throw std::invalid_argument("insertBackProjections: J and Z must have same number of entries"); + for(int k=0;k > + (Point2(Z(0, k), Z(1, k)), model, i, Key(J(k)), K)); + } + } + + /// calculate the errors of all projection factors in a graph + Matrix reprojectionErrors(const NonlinearFactorGraph& graph, const Values& values) { + // first count + size_t K = 0, k=0; + BOOST_FOREACH(const NonlinearFactor::shared_ptr& f, graph) + if (boost::dynamic_pointer_cast >(f)) ++K; + // now fill + Matrix errors(2,K); + BOOST_FOREACH(const NonlinearFactor::shared_ptr& f, graph) { + boost::shared_ptr > p = boost::dynamic_pointer_cast >(f); + if (p) errors.col(k++) = p->unwhitenedError(values); + } + return errors; + } + + } + +} + diff --git a/tests/matlab/CHECK.m b/matlab/+gtsam/CHECK.m similarity index 100% rename from tests/matlab/CHECK.m rename to matlab/+gtsam/CHECK.m diff --git a/matlab/+gtsam/Contents.m b/matlab/+gtsam/Contents.m new file mode 100644 index 000000000..0af19e1c8 --- /dev/null +++ b/matlab/+gtsam/Contents.m @@ -0,0 +1,161 @@ +% GTSAM MATLAB toolbox interface to the Georgia Tech Smoothing and Mapping C++ library +% Version 2.1 08-Sep-2012 +% +%% Basic Utilities +% linear_independent - check whether the rows of two matrices are linear independent +% Permutation - class Permutation, see Doxygen page for details +% +%% General Inference Classes +% IndexConditional - class IndexConditional, see Doxygen page for details +% IndexFactor - class IndexFactor, see Doxygen page for details +% SymbolicBayesNet - class SymbolicBayesNet, see Doxygen page for details +% SymbolicBayesTree - class SymbolicBayesTree, see Doxygen page for details +% SymbolicFactorGraph - class SymbolicFactorGraph, see Doxygen page for details +% SymbolicMultifrontalSolver - class SymbolicMultifrontalSolver, see Doxygen page for details +% SymbolicSequentialSolver - class SymbolicSequentialSolver, see Doxygen page for details +% VariableIndex - class VariableIndex, see Doxygen page for details +% +%% Linear-Gaussian Factor Graphs +% Errors - class Errors, see Doxygen page for details +% GaussianBayesNet - class GaussianBayesNet, see Doxygen page for details +% GaussianConditional - class GaussianConditional, see Doxygen page for details +% GaussianDensity - class GaussianDensity, see Doxygen page for details +% GaussianFactor - class GaussianFactor, see Doxygen page for details +% GaussianFactorGraph - class GaussianFactorGraph, see Doxygen page for details +% GaussianISAM - class GaussianISAM, see Doxygen page for details +% HessianFactor - class HessianFactor, see Doxygen page for details +% JacobianFactor - class JacobianFactor, see Doxygen page for details +% VectorValues - class VectorValues, see Doxygen page for details +% +%% Linear Inference +% GaussianSequentialSolver - class GaussianSequentialSolver, see Doxygen page for details +% IterativeOptimizationParameters - class IterativeOptimizationParameters, see Doxygen page for details +% KalmanFilter - class KalmanFilter, see Doxygen page for details +% SubgraphSolver - class SubgraphSolver, see Doxygen page for details +% SubgraphSolverParameters - class SubgraphSolverParameters, see Doxygen page for details +% SuccessiveLinearizationParams - class SuccessiveLinearizationParams, see Doxygen page for details +% Sampler - class Sampler, see Doxygen page for details +% +%% Nonlinear Factor Graphs +% NonlinearFactor - class NonlinearFactor, see Doxygen page for details +% NonlinearFactorGraph - class NonlinearFactorGraph, see Doxygen page for details +% Ordering - class Ordering, see Doxygen page for details +% Value - class Value, see Doxygen page for details +% Values - class Values, see Doxygen page for details +% +%% Nonlinear Optimization +% ConjugateGradientParameters - class ConjugateGradientParameters, see Doxygen page for details +% DoglegOptimizer - class DoglegOptimizer, see Doxygen page for details +% DoglegParams - class DoglegParams, see Doxygen page for details +% GaussNewtonOptimizer - class GaussNewtonOptimizer, see Doxygen page for details +% GaussNewtonParams - class GaussNewtonParams, see Doxygen page for details +% ISAM2 - class ISAM2, see Doxygen page for details +% ISAM2DoglegParams - class ISAM2DoglegParams, see Doxygen page for details +% ISAM2GaussNewtonParams - class ISAM2GaussNewtonParams, see Doxygen page for details +% ISAM2Params - class ISAM2Params, see Doxygen page for details +% ISAM2Result - class ISAM2Result, see Doxygen page for details +% ISAM2ThresholdMap - class ISAM2ThresholdMap, see Doxygen page for details +% ISAM2ThresholdMapValue - class ISAM2ThresholdMapValue, see Doxygen page for details +% InvertedOrdering - class InvertedOrdering, see Doxygen page for details +% JointMarginal - class JointMarginal, see Doxygen page for details +% KeyList - class KeyList, see Doxygen page for details +% KeySet - class KeySet, see Doxygen page for details +% KeyVector - class KeyVector, see Doxygen page for details +% LevenbergMarquardtOptimizer - class LevenbergMarquardtOptimizer, see Doxygen page for details +% LevenbergMarquardtParams - class LevenbergMarquardtParams, see Doxygen page for details +% Marginals - class Marginals, see Doxygen page for details +% NonlinearISAM - class NonlinearISAM, see Doxygen page for details +% NonlinearOptimizer - class NonlinearOptimizer, see Doxygen page for details +% NonlinearOptimizerParams - class NonlinearOptimizerParams, see Doxygen page for details +% +%% Geometry +% Cal3_S2 - class Cal3_S2, see Doxygen page for details +% Cal3_S2Stereo - class Cal3_S2Stereo, see Doxygen page for details +% Cal3DS2 - class Cal3DS2, see Doxygen page for details +% CalibratedCamera - class CalibratedCamera, see Doxygen page for details +% Point2 - class Point2, see Doxygen page for details +% Point3 - class Point3, see Doxygen page for details +% Pose2 - class Pose2, see Doxygen page for details +% Pose3 - class Pose3, see Doxygen page for details +% Rot2 - class Rot2, see Doxygen page for details +% Rot3 - class Rot3, see Doxygen page for details +% SimpleCamera - class SimpleCamera, see Doxygen page for details +% StereoPoint2 - class StereoPoint2, see Doxygen page for details +% +%% SLAM and SFM +% BearingFactor2D - class BearingFactor2D, see Doxygen page for details +% BearingRangeFactor2D - class BearingRangeFactor2D, see Doxygen page for details +% BetweenFactorLieMatrix - class BetweenFactorLieMatrix, see Doxygen page for details +% BetweenFactorLieScalar - class BetweenFactorLieScalar, see Doxygen page for details +% BetweenFactorLieVector - class BetweenFactorLieVector, see Doxygen page for details +% BetweenFactorPoint2 - class BetweenFactorPoint2, see Doxygen page for details +% BetweenFactorPoint3 - class BetweenFactorPoint3, see Doxygen page for details +% BetweenFactorPose2 - class BetweenFactorPose2, see Doxygen page for details +% BetweenFactorPose3 - class BetweenFactorPose3, see Doxygen page for details +% BetweenFactorRot2 - class BetweenFactorRot2, see Doxygen page for details +% BetweenFactorRot3 - class BetweenFactorRot3, see Doxygen page for details +% GeneralSFMFactor2Cal3_S2 - class GeneralSFMFactor2Cal3_S2, see Doxygen page for details +% GeneralSFMFactorCal3_S2 - class GeneralSFMFactorCal3_S2, see Doxygen page for details +% GenericProjectionFactorCal3_S2 - class GenericProjectionFactorCal3_S2, see Doxygen page for details +% GenericStereoFactor3D - class GenericStereoFactor3D, see Doxygen page for details +% NonlinearEqualityCal3_S2 - class NonlinearEqualityCal3_S2, see Doxygen page for details +% NonlinearEqualityCalibratedCamera - class NonlinearEqualityCalibratedCamera, see Doxygen page for details +% NonlinearEqualityLieMatrix - class NonlinearEqualityLieMatrix, see Doxygen page for details +% NonlinearEqualityLieScalar - class NonlinearEqualityLieScalar, see Doxygen page for details +% NonlinearEqualityLieVector - class NonlinearEqualityLieVector, see Doxygen page for details +% NonlinearEqualityPoint2 - class NonlinearEqualityPoint2, see Doxygen page for details +% NonlinearEqualityPoint3 - class NonlinearEqualityPoint3, see Doxygen page for details +% NonlinearEqualityPose2 - class NonlinearEqualityPose2, see Doxygen page for details +% NonlinearEqualityPose3 - class NonlinearEqualityPose3, see Doxygen page for details +% NonlinearEqualityRot2 - class NonlinearEqualityRot2, see Doxygen page for details +% NonlinearEqualityRot3 - class NonlinearEqualityRot3, see Doxygen page for details +% NonlinearEqualitySimpleCamera - class NonlinearEqualitySimpleCamera, see Doxygen page for details +% NonlinearEqualityStereoPoint2 - class NonlinearEqualityStereoPoint2, see Doxygen page for details +% PriorFactorCal3_S2 - class PriorFactorCal3_S2, see Doxygen page for details +% PriorFactorCalibratedCamera - class PriorFactorCalibratedCamera, see Doxygen page for details +% PriorFactorLieMatrix - class PriorFactorLieMatrix, see Doxygen page for details +% PriorFactorLieScalar - class PriorFactorLieScalar, see Doxygen page for details +% PriorFactorLieVector - class PriorFactorLieVector, see Doxygen page for details +% PriorFactorPoint2 - class PriorFactorPoint2, see Doxygen page for details +% PriorFactorPoint3 - class PriorFactorPoint3, see Doxygen page for details +% PriorFactorPose2 - class PriorFactorPose2, see Doxygen page for details +% PriorFactorPose3 - class PriorFactorPose3, see Doxygen page for details +% PriorFactorRot2 - class PriorFactorRot2, see Doxygen page for details +% PriorFactorRot3 - class PriorFactorRot3, see Doxygen page for details +% PriorFactorSimpleCamera - class PriorFactorSimpleCamera, see Doxygen page for details +% PriorFactorStereoPoint2 - class PriorFactorStereoPoint2, see Doxygen page for details +% RangeFactorCalibratedCamera - class RangeFactorCalibratedCamera, see Doxygen page for details +% RangeFactorCalibratedCameraPoint - class RangeFactorCalibratedCameraPoint, see Doxygen page for details +% RangeFactorPose2 - class RangeFactorPose2, see Doxygen page for details +% RangeFactorPose3 - class RangeFactorPose3, see Doxygen page for details +% RangeFactorPosePoint2 - class RangeFactorPosePoint2, see Doxygen page for details +% RangeFactorPosePoint3 - class RangeFactorPosePoint3, see Doxygen page for details +% RangeFactorSimpleCamera - class RangeFactorSimpleCamera, see Doxygen page for details +% RangeFactorSimpleCameraPoint - class RangeFactorSimpleCameraPoint, see Doxygen page for details +% VisualISAMGenerateData - VisualISAMGenerateData creates data for viusalSLAM::iSAM examples +% VisualISAMInitialize - VisualISAMInitialize initializes visualSLAM::iSAM object and noise parameters +% VisualISAMPlot - VisualISAMPlot plots current state of ISAM2 object +% VisualISAMStep - VisualISAMStep executes one update step of visualSLAM::iSAM object +% +%% MATLAB-only Utilities +% CHECK - throw an error if an assertion fails +% circlePose2 - circlePose2 generates a set of poses in a circle. This function +% circlePose3 - circlePose3 generates a set of poses in a circle. This function +% covarianceEllipse - covarianceEllipse plots a Gaussian as an uncertainty ellipse +% covarianceEllipse3D - covarianceEllipse3D plots a Gaussian as an uncertainty ellipse +% EQUALITY - test equality of two vectors/matrices up to tolerance +% findExampleDataFile - Find a dataset in the examples folder +% load2D - load2D reads a TORO-style 2D pose graph +% load3D - load3D reads a TORO-style 3D pose graph +% plot2DPoints - Plots the Point2's in a values, with optional covariances +% plot2DTrajectory - Plots the Pose2's in a values, with optional covariances +% plot3DPoints - Plots the Point3's in a values, with optional covariances +% plot3DTrajectory - plot3DTrajectory plots a 3D trajectory +% plotCamera - +% plotPoint2 - plotPoint2 shows a Point2, possibly with covariance matrix +% plotPoint3 - Plot a Point3 with an optional covariance matrix +% plotPose2 - plotPose2 shows a Pose2, possibly with covariance matrix +% plotPose3 - plotPose3 shows a Pose, possibly with covariance matrix +% symbol - create a Symbol key +% symbolChr - get character from a symbol key +% symbolIndex - get index from a symbol key diff --git a/matlab/+gtsam/EQUALITY.m b/matlab/+gtsam/EQUALITY.m new file mode 100644 index 000000000..a387e1154 --- /dev/null +++ b/matlab/+gtsam/EQUALITY.m @@ -0,0 +1,19 @@ +function EQUALITY(name,expected,actual,tol) +% test equality of two vectors/matrices up to tolerance + +if nargin<4,tol=1e-9;end + +sameSize = size(expected)==size(actual); +if all(sameSize) + equal = abs(expected-actual)xZ--> Y (z pointing towards viewer, Z pointing away from viewer) +% Vehicle at p0 is looking towards y axis (X-axis points towards world y) + +if nargin<3,symbolChar=0;end +if nargin<2,radius=1.0;end +if nargin<1,numPoses=8;end + +% Force symbolChar to be a single character +symbolChar = char(symbolChar); +symbolChar = symbolChar(1); + +values = gtsam.Values; +theta = 0.0; +dtheta = 2*pi()/numPoses; +for i = 1:numPoses + key = gtsam.symbol(symbolChar, i-1); + pose = gtsam.Pose2(radius*cos(theta), radius*sin(theta), pi()/2 + theta); + values.insert(key, pose); + theta = theta + dtheta; +end diff --git a/matlab/+gtsam/circlePose3.m b/matlab/+gtsam/circlePose3.m new file mode 100644 index 000000000..686bce7cf --- /dev/null +++ b/matlab/+gtsam/circlePose3.m @@ -0,0 +1,33 @@ +function values = circlePose3(numPoses, radius, symbolChar) +% circlePose3 generates a set of poses in a circle. This function +% returns those poses inside a gtsam.Values object, with sequential +% keys starting from 0. An optional character may be provided, which +% will be stored in the msb of each key (i.e. gtsam.Symbol). +% +% We use aerospace/navlab convention, X forward, Y right, Z down +% First pose will be at (R,0,0) +% ^y ^ X +% | | +% z-->xZ--> Y (z pointing towards viewer, Z pointing away from viewer) +% Vehicle at p0 is looking towards y axis (X-axis points towards world y) + +if nargin<3,symbolChar=0;end +if nargin<2,radius=1.0;end +if nargin<1,numPoses=8;end + +% Force symbolChar to be a single character +symbolChar = char(symbolChar); +symbolChar = symbolChar(1); + +values = gtsam.Values; +theta = 0.0; +dtheta = 2*pi()/numPoses; +gRo = gtsam.Rot3([0, 1, 0 ; 1, 0, 0 ; 0, 0, -1]); +for i = 1:numPoses + key = gtsam.symbol(symbolChar, i-1); + gti = gtsam.Point3(radius*cos(theta), radius*sin(theta), 0); + oRi = gtsam.Rot3.Yaw(-theta); % negative yaw goes counterclockwise, with Z down ! + gTi = gtsam.Pose3(gRo.compose(oRi), gti); + values.insert(key, gTi); + theta = theta + dtheta; +end diff --git a/matlab/+gtsam/covarianceEllipse.m b/matlab/+gtsam/covarianceEllipse.m new file mode 100644 index 000000000..7728fc866 --- /dev/null +++ b/matlab/+gtsam/covarianceEllipse.m @@ -0,0 +1,34 @@ +function covarianceEllipse(x,P,color) +% covarianceEllipse plots a Gaussian as an uncertainty ellipse +% Based on Maybeck Vol 1, page 366 +% k=2.296 corresponds to 1 std, 68.26% of all probability +% k=11.82 corresponds to 3 std, 99.74% of all probability +% +% covarianceEllipse(x,P,color) +% it is assumed x and y are the first two components of state x + +[e,s] = eig(P(1:2,1:2)); +s1 = s(1,1); +s2 = s(2,2); +k = 2.296; +[ex,ey] = ellipse( sqrt(s1*k)*e(:,1), sqrt(s2*k)*e(:,2), x(1:2) ); +line(ex,ey,'color',color); + + function [x,y] = ellipse(a,b,c); + % ellipse: return the x and y coordinates for an ellipse + % [x,y] = ellipse(a,b,c); + % a, and b are the axes. c is the center + + global ellipse_x ellipse_y + if ~exist('elipse_x') + q =0:2*pi/25:2*pi; + ellipse_x = cos(q); + ellipse_y = sin(q); + end + + points = a*ellipse_x + b*ellipse_y; + x = c(1) + points(1,:); + y = c(2) + points(2,:); + end + +end \ No newline at end of file diff --git a/matlab/+gtsam/covarianceEllipse3D.m b/matlab/+gtsam/covarianceEllipse3D.m new file mode 100644 index 000000000..9682a9fc1 --- /dev/null +++ b/matlab/+gtsam/covarianceEllipse3D.m @@ -0,0 +1,27 @@ +function covarianceEllipse3D(c,P) +% covarianceEllipse3D plots a Gaussian as an uncertainty ellipse +% Based on Maybeck Vol 1, page 366 +% k=2.296 corresponds to 1 std, 68.26% of all probability +% k=11.82 corresponds to 3 std, 99.74% of all probability +% +% Modified from http://www.mathworks.com/matlabcentral/newsreader/view_thread/42966 + +[e,s] = svd(P); +k = 11.82; +radii = k*sqrt(diag(s)); + +% generate data for "unrotated" ellipsoid +[xc,yc,zc] = ellipsoid(0,0,0,radii(1),radii(2),radii(3),8); + +% rotate data with orientation matrix U and center M +data = kron(e(:,1),xc) + kron(e(:,2),yc) + kron(e(:,3),zc); +n = size(data,2); +x = data(1:n,:)+c(1); +y = data(n+1:2*n,:)+c(2); +z = data(2*n+1:end,:)+c(3); + +% now plot the rotated ellipse +sc = surf(x,y,z,abs(xc)); +shading interp +alpha(0.5) +axis equal \ No newline at end of file diff --git a/matlab/+gtsam/findExampleDataFile.m b/matlab/+gtsam/findExampleDataFile.m new file mode 100644 index 000000000..9c40960b9 --- /dev/null +++ b/matlab/+gtsam/findExampleDataFile.m @@ -0,0 +1,19 @@ +function datafile = findExampleDataFile(datasetName) +%FINDEXAMPLEDATAFILE Find a dataset in the examples folder + +[ myPath, ~, ~ ] = fileparts(mfilename('fullpath')); +searchPath = { ... + fullfile(myPath, [ '../../examples/Data/' datasetName ]) ... + fullfile(myPath, [ '../gtsam_examples/Data/' datasetName ]) }; +datafile = []; +for path = searchPath + if exist(path{:}, 'file') + datafile = path{:}; + end +end +if isempty(datafile) + error([ 'Could not find example data file ' datasetName ]); +end + +end + diff --git a/matlab/+gtsam/load3D.m b/matlab/+gtsam/load3D.m new file mode 100644 index 000000000..94202e0c8 --- /dev/null +++ b/matlab/+gtsam/load3D.m @@ -0,0 +1,58 @@ +function [graph,initial] = load3D(filename,model,successive,N) +% load3D reads a TORO-style 3D pose graph +% cannot read noise model from file yet, uses specified model +% if [successive] is tru, constructs initial estimate from odometry + +import gtsam.* + +if nargin<3, successive=false; end +fid = fopen(filename); +if fid < 0 + error(['load2D: Cannot open file ' filename]); +end + +% scan all lines into a cell array +columns=textscan(fid,'%s','delimiter','\n'); +fclose(fid); +lines=columns{1}; + +% loop over lines and add vertices +graph = NonlinearFactorGraph; +initial = Values; +origin=gtsam.Pose3; +initial.insert(0,origin); +n=size(lines,1); +if nargin<4, N=n;end + +for i=1:n + line_i=lines{i}; + if strcmp('VERTEX3',line_i(1:7)) + v = textscan(line_i,'%s %d %f %f %f %f %f %f',1); + i1=v{2}; + if (~successive && i1i1 + initial.insert(i2,initial.at(i1).compose(dpose)); + else + initial.insert(i1,initial.at(i2).compose(dpose.inverse)); + end + end + end + end + end +end + diff --git a/matlab/+gtsam/plot2DPoints.m b/matlab/+gtsam/plot2DPoints.m new file mode 100644 index 000000000..d4703a5d7 --- /dev/null +++ b/matlab/+gtsam/plot2DPoints.m @@ -0,0 +1,37 @@ +function plot2DPoints(values, linespec, marginals) +%PLOT2DPOINTS Plots the Point2's in a values, with optional covariances +% Finds all the Point2 objects in the given Values object and plots them. +% If a Marginals object is given, this function will also plot marginal +% covariance ellipses for each point. + +import gtsam.* + +if ~exist('linespec', 'var') || isempty(linespec) + linespec = 'g'; +end +haveMarginals = exist('marginals', 'var'); +keys = KeyVector(values.keys); + +holdstate = ishold; +hold on + +% Plot points and covariance matrices +for i = 0:keys.size-1 + key = keys.at(i); + p = values.at(key); + if isa(p, 'gtsam.Point2') + if haveMarginals + P = marginals.marginalCovariance(key); + gtsam.plotPoint2(p, linespec, P); + else + gtsam.plotPoint2(p, linespec); + end + end +end + +if ~holdstate + hold off +end + +end + diff --git a/matlab/+gtsam/plot2DTrajectory.m b/matlab/+gtsam/plot2DTrajectory.m new file mode 100644 index 000000000..329026398 --- /dev/null +++ b/matlab/+gtsam/plot2DTrajectory.m @@ -0,0 +1,54 @@ +function plot2DTrajectory(values, linespec, marginals) +%PLOT2DTRAJECTORY Plots the Pose2's in a values, with optional covariances +% Finds all the Pose2 objects in the given Values object and plots them +% in increasing key order, connecting consecutive poses with a line. If +% a Marginals object is given, this function will also plot marginal +% covariance ellipses for each pose. + +import gtsam.* + +if ~exist('linespec', 'var') || isempty(linespec) + linespec = 'k*-'; +end + +haveMarginals = exist('marginals', 'var'); +keys = KeyVector(values.keys); + +holdstate = ishold; +hold on + +% Plot poses and covariance matrices +lastIndex = []; +for i = 0:keys.size-1 + key = keys.at(i); + x = values.at(key); + if isa(x, 'gtsam.Pose2') + if ~isempty(lastIndex) + % Draw line from last pose then covariance ellipse on top of + % last pose. + lastKey = keys.at(lastIndex); + lastPose = values.at(lastKey); + plot([ x.x; lastPose.x ], [ x.y; lastPose.y ], linespec); + if haveMarginals + P = marginals.marginalCovariance(lastKey); + gtsam.plotPose2(lastPose, 'g', P); + end + end + lastIndex = i; + end +end + +% Draw final covariance ellipse +if ~isempty(lastIndex) && haveMarginals + lastKey = keys.at(lastIndex); + lastPose = values.at(lastKey); + P = marginals.marginalCovariance(lastKey); + gtsam.plotPose2(lastPose, 'g', P); +end + +if ~holdstate + hold off +end + +end + diff --git a/matlab/+gtsam/plot3DPoints.m b/matlab/+gtsam/plot3DPoints.m new file mode 100644 index 000000000..8feab1744 --- /dev/null +++ b/matlab/+gtsam/plot3DPoints.m @@ -0,0 +1,36 @@ +function plot3DPoints(values, linespec, marginals) +%PLOT3DPOINTS Plots the Point3's in a values, with optional covariances +% Finds all the Point3 objects in the given Values object and plots them. +% If a Marginals object is given, this function will also plot marginal +% covariance ellipses for each point. + +import gtsam.* + +if ~exist('linespec', 'var') || isempty(linespec) + linespec = 'g'; +end +haveMarginals = exist('marginals', 'var'); +keys = KeyVector(values.keys); + +holdstate = ishold; +hold on + +% Plot points and covariance matrices +for i = 0:keys.size-1 + key = keys.at(i); + p = values.at(key); + if isa(p, 'gtsam.Point3') + if haveMarginals + P = marginals.marginalCovariance(key); + gtsam.plotPoint3(p, linespec, P); + else + gtsam.plotPoint3(p, linespec); + end + end +end + +if ~holdstate + hold off +end + +end diff --git a/matlab/+gtsam/plot3DTrajectory.m b/matlab/+gtsam/plot3DTrajectory.m new file mode 100644 index 000000000..d24e21297 --- /dev/null +++ b/matlab/+gtsam/plot3DTrajectory.m @@ -0,0 +1,55 @@ +function plot3DTrajectory(values,linespec,frames,scale,marginals) +% plot3DTrajectory plots a 3D trajectory +% plot3DTrajectory(values,linespec,frames,scale,marginals) + +if ~exist('scale','var') || isempty(scale), scale=1; end +if ~exist('frames','var'), scale=[]; end + +import gtsam.* + +haveMarginals = exist('marginals', 'var'); +keys = KeyVector(values.keys); + +holdstate = ishold; +hold on + +% Plot poses and covariance matrices +lastIndex = []; +for i = 0:keys.size-1 + key = keys.at(i); + x = values.at(key); + if isa(x, 'gtsam.Pose3') + if ~isempty(lastIndex) + % Draw line from last pose then covariance ellipse on top of + % last pose. + lastKey = keys.at(lastIndex); + lastPose = values.at(lastKey); + plot3([ x.x; lastPose.x ], [ x.y; lastPose.y ], [ x.z; lastPose.z ], linespec); + if haveMarginals + P = marginals.marginalCovariance(lastKey); + else + P = []; + end + gtsam.plotPose3(lastPose, P, scale); + end + lastIndex = i; + end +end + +% Draw final pose +if ~isempty(lastIndex) + lastKey = keys.at(lastIndex); + lastPose = values.at(lastKey); + if haveMarginals + P = marginals.marginalCovariance(lastKey); + else + P = []; + end + gtsam.plotPose3(lastPose, P, scale); +end + +if ~holdstate + hold off +end + +end \ No newline at end of file diff --git a/matlab/+gtsam/plotCamera.m b/matlab/+gtsam/plotCamera.m new file mode 100644 index 000000000..ba352b757 --- /dev/null +++ b/matlab/+gtsam/plotCamera.m @@ -0,0 +1,18 @@ +function plotCamera(pose, axisLength) + C = pose.translation().vector(); + R = pose.rotation().matrix(); + + xAxis = C+R(:,1)*axisLength; + L = [C xAxis]'; + line(L(:,1),L(:,2),L(:,3),'Color','r'); + + yAxis = C+R(:,2)*axisLength; + L = [C yAxis]'; + line(L(:,1),L(:,2),L(:,3),'Color','g'); + + zAxis = C+R(:,3)*axisLength; + L = [C zAxis]'; + line(L(:,1),L(:,2),L(:,3),'Color','b'); + + axis equal +end \ No newline at end of file diff --git a/matlab/+gtsam/plotPoint2.m b/matlab/+gtsam/plotPoint2.m new file mode 100644 index 000000000..55e476118 --- /dev/null +++ b/matlab/+gtsam/plotPoint2.m @@ -0,0 +1,10 @@ +function plotPoint2(p,color,P) +% plotPoint2 shows a Point2, possibly with covariance matrix +if size(color,2)==1 + plot(p.x,p.y,[color '*']); +else + plot(p.x,p.y,color); +end +if exist('P', 'var') + gtsam.covarianceEllipse([p.x;p.y],P,color(1)); +end \ No newline at end of file diff --git a/matlab/+gtsam/plotPoint3.m b/matlab/+gtsam/plotPoint3.m new file mode 100644 index 000000000..390b44939 --- /dev/null +++ b/matlab/+gtsam/plotPoint3.m @@ -0,0 +1,13 @@ +function plotPoint3(p, color, P) +%PLOTPOINT3 Plot a Point3 with an optional covariance matrix +if size(color,2)==1 + plot3(p.x,p.y,p.z,[color '*']); +else + plot3(p.x,p.y,p.z,color); +end +if exist('P', 'var') + gtsam.covarianceEllipse3D([p.x;p.y;p.z],P); +end + +end + diff --git a/matlab/+gtsam/plotPose2.m b/matlab/+gtsam/plotPose2.m new file mode 100644 index 000000000..799bad48e --- /dev/null +++ b/matlab/+gtsam/plotPose2.m @@ -0,0 +1,13 @@ +function plotPose2(pose,color,P,axisLength) +% plotPose2 shows a Pose2, possibly with covariance matrix +if nargin<4,axisLength=0.1;end + +plot(pose.x,pose.y,[color '*']); +c = cos(pose.theta); +s = sin(pose.theta); +quiver(pose.x,pose.y,c,s,axisLength,color); +if nargin>2 + pPp = P(1:2,1:2); % covariance matrix in pose coordinate frame + gRp = [c -s;s c]; % rotation from pose to global + gtsam.covarianceEllipse([pose.x;pose.y],gRp*pPp*gRp',color); +end \ No newline at end of file diff --git a/matlab/+gtsam/plotPose3.m b/matlab/+gtsam/plotPose3.m new file mode 100644 index 000000000..8c3c7dd76 --- /dev/null +++ b/matlab/+gtsam/plotPose3.m @@ -0,0 +1,31 @@ +function plotPose3(pose, P, axisLength) +% plotPose3 shows a Pose, possibly with covariance matrix +if nargin<3,axisLength=0.1;end + +% get rotation and translation (center) +gRp = pose.rotation().matrix(); % rotation from pose to global +C = pose.translation().vector(); + +if ~isempty(axisLength) + % draw the camera axes + xAxis = C+gRp(:,1)*axisLength; + L = [C xAxis]'; + line(L(:,1),L(:,2),L(:,3),'Color','r'); + + yAxis = C+gRp(:,2)*axisLength; + L = [C yAxis]'; + line(L(:,1),L(:,2),L(:,3),'Color','g'); + + zAxis = C+gRp(:,3)*axisLength; + L = [C zAxis]'; + line(L(:,1),L(:,2),L(:,3),'Color','b'); +end + +% plot the covariance +if (nargin>2) && (~isempty(P)) + pPp = P(4:6,4:6); % covariance matrix in pose coordinate frame + gPp = gRp*pPp*gRp'; % convert the covariance matrix to global coordinate frame + gtsam.covarianceEllipse3D(C,gPp); +end + +end diff --git a/matlab/CMakeLists.txt b/matlab/CMakeLists.txt new file mode 100644 index 000000000..16cfb501a --- /dev/null +++ b/matlab/CMakeLists.txt @@ -0,0 +1,22 @@ +# Install matlab components + +# Tests +message(STATUS "Installing Matlab Toolbox Tests") +install(DIRECTORY "${GTSAM_SOURCE_ROOT_DIR}/matlab/gtsam_tests" DESTINATION "${GTSAM_TOOLBOX_INSTALL_PATH}" FILES_MATCHING PATTERN "*.m" PATTERN ".svn" EXCLUDE) + +# Examples +message(STATUS "Installing Matlab Toolbox Examples") +# Matlab files: *.m and *.fig +install(DIRECTORY "${GTSAM_SOURCE_ROOT_DIR}/matlab/gtsam_examples" DESTINATION "${GTSAM_TOOLBOX_INSTALL_PATH}" FILES_MATCHING PATTERN "*.m" PATTERN "*.fig" PATTERN ".svn" EXCLUDE) + +# Utilities +message(STATUS "Installing Matlab Toolbox Utilities") +install(DIRECTORY "${GTSAM_SOURCE_ROOT_DIR}/matlab/+gtsam" DESTINATION "${GTSAM_TOOLBOX_INSTALL_PATH}" FILES_MATCHING PATTERN "*.m" PATTERN ".svn" EXCLUDE) +install(FILES "${GTSAM_SOURCE_ROOT_DIR}/matlab/README-gtsam-toolbox.txt" DESTINATION "${GTSAM_TOOLBOX_INSTALL_PATH}") + +message(STATUS "Installing Matlab Toolbox Examples (Data)") +# Data files: *.graph and *.txt +file(GLOB matlab_examples_data_graph "${GTSAM_SOURCE_ROOT_DIR}/examples/Data/*.graph") +file(GLOB matlab_examples_data_txt "${GTSAM_SOURCE_ROOT_DIR}/examples/Data/*.txt") +set(matlab_examples_data ${matlab_examples_data_graph} ${matlab_examples_data_txt}) +install(FILES ${matlab_examples_data} DESTINATION ${GTSAM_TOOLBOX_INSTALL_PATH}/gtsam_examples/Data) diff --git a/matlab/README-gtsam-toolbox.txt b/matlab/README-gtsam-toolbox.txt new file mode 100644 index 000000000..6f74f9806 --- /dev/null +++ b/matlab/README-gtsam-toolbox.txt @@ -0,0 +1,76 @@ +================================================================================ +GTSAM - Georgia Tech Smoothing and Mapping Library + +MATLAB wrapper + +http://borg.cc.gatech.edu/projects/gtsam +================================================================================ + +This is the GTSAM MATLAB toolbox, a MATLAB wrapper around the GTSAM C++ +library. + + +---------------------------------------- +Note about newer Ubuntu versions unsupported by MATLAB (later than 10.04) +---------------------------------------- + +If you have a newer Ubuntu system, you must make a small modification to your +MATLAB installation, due to MATLAB being distributed with an old version of +the C++ standard library. Delete or rename all files starting with +'libstdc++' in your MATLAB installation directory, in paths: + + /usr/local/MATLAB/[version]/sys/os/[system]/ + /usr/local/MATLAB/[version]/bin/[system]/ + + +---------------------------------------- +Adding the toolbox to your MATLAB path +---------------------------------------- + +To get started, first add the 'toolbox' folder to your MATLAB path - in the +MATLAB file browser, right-click on the folder and click 'Add to path -> This +folder' (do not add the subfolders to your path). + + +---------------------------------------- +Trying out the examples +---------------------------------------- + +The examples are located in the 'gtsam_examples' subfolder. You may either +run them individually at the MATLAB command line, or open the GTSAM example +GUI by running 'gtsamExamples'. Example: + +>> cd /Users/yourname/toolbox % Change to wherever you installed the toolbox +>> cd gtsam_examples % Change to the examples directory +>> gtsamExamples % Run the GTSAM examples GUI + + +---------------------------------------- +Running the unit tests +---------------------------------------- + +The GTSAM MATLAB toolbox also has a small set of unit tests located in the +gtsam_tests directory. Example: + +>> cd /Users/yourname/toolbox % Change to wherever you installed the toolbox +>> cd gtsam_tests % Change to the examples directory +>> test_gtsam % Run the unit tests +Starting: testJacobianFactor +Starting: testKalmanFilter +Starting: testLocalizationExample +Starting: testOdometryExample +Starting: testPlanarSLAMExample +Starting: testPose2SLAMExample +Starting: testPose3SLAMExample +Starting: testSFMExample +Starting: testStereoVOExample +Starting: testVisualISAMExample +Tests complete! + + +---------------------------------------- +Writing your own code +---------------------------------------- + +Coding for the GTSAM MATLAB toolbox is straightforward and very fast once you +understand a few basic concepts! Please see the manual to get started. diff --git a/matlab/gtsam_examples/LocalizationExample.m b/matlab/gtsam_examples/LocalizationExample.m new file mode 100644 index 000000000..2dcb5341b --- /dev/null +++ b/matlab/gtsam_examples/LocalizationExample.m @@ -0,0 +1,59 @@ +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% GTSAM Copyright 2010, Georgia Tech Research Corporation, +% Atlanta, Georgia 30332-0415 +% All Rights Reserved +% Authors: Frank Dellaert, et al. (see THANKS for the full author list) +% +% See LICENSE for the license information +% +% @brief Example of a simple 2D localization example +% @author Frank Dellaert +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +import gtsam.* + +%% Assumptions +% - Robot poses are facing along the X axis (horizontal, to the right in 2D) +% - The robot moves 2 meters each step +% - The robot is on a grid, moving 2 meters each step + +%% Create the graph (defined in pose2SLAM.h, derived from NonlinearFactorGraph) +graph = NonlinearFactorGraph; + +%% Add two odometry factors +odometry = Pose2(2.0, 0.0, 0.0); % create a measurement for both factors (the same in this case) +odometryNoise = noiseModel.Diagonal.Sigmas([0.2; 0.2; 0.1]); % 20cm std on x,y, 0.1 rad on theta +graph.add(BetweenFactorPose2(1, 2, odometry, odometryNoise)); +graph.add(BetweenFactorPose2(2, 3, odometry, odometryNoise)); + +%% Add three "GPS" measurements +% We use Pose2 Priors here with high variance on theta +priorNoise = noiseModel.Diagonal.Sigmas([0.1; 0.1; 10]); +graph.add(PriorFactorPose2(1, Pose2(0.0, 0.0, 0.0), priorNoise)); +graph.add(PriorFactorPose2(2, Pose2(2.0, 0.0, 0.0), priorNoise)); +graph.add(PriorFactorPose2(3, Pose2(4.0, 0.0, 0.0), priorNoise)); + +%% print +graph.print(sprintf('\nFactor graph:\n')); + +%% Initialize to noisy points +initialEstimate = Values; +initialEstimate.insert(1, Pose2(0.5, 0.0, 0.2)); +initialEstimate.insert(2, Pose2(2.3, 0.1,-0.2)); +initialEstimate.insert(3, Pose2(4.1, 0.1, 0.1)); +initialEstimate.print(sprintf('\nInitial estimate:\n ')); + +%% Optimize using Levenberg-Marquardt optimization with an ordering from colamd +optimizer = LevenbergMarquardtOptimizer(graph, initialEstimate); +result = optimizer.optimizeSafely(); +result.print(sprintf('\nFinal result:\n ')); + +%% Plot trajectory and covariance ellipses +cla; +hold on; + +plot2DTrajectory(result, [], Marginals(graph, result)); + +axis([-0.6 4.8 -1 1]) +axis equal +view(2) diff --git a/matlab/gtsam_examples/OdometryExample.m b/matlab/gtsam_examples/OdometryExample.m new file mode 100644 index 000000000..81d2db676 --- /dev/null +++ b/matlab/gtsam_examples/OdometryExample.m @@ -0,0 +1,57 @@ +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% GTSAM Copyright 2010, Georgia Tech Research Corporation, +% Atlanta, Georgia 30332-0415 +% All Rights Reserved +% Authors: Frank Dellaert, et al. (see THANKS for the full author list) +% +% See LICENSE for the license information +% +% @brief Example of a simple 2D localization example +% @author Frank Dellaert +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +import gtsam.* + +%% Assumptions +% - Robot poses are facing along the X axis (horizontal, to the right in 2D) +% - The robot moves 2 meters each step +% - The robot is on a grid, moving 2 meters each step + +%% Create the graph (defined in pose2SLAM.h, derived from NonlinearFactorGraph) +graph = NonlinearFactorGraph; + +%% Add a Gaussian prior on pose x_1 +priorMean = Pose2(0.0, 0.0, 0.0); % prior mean is at origin +priorNoise = noiseModel.Diagonal.Sigmas([0.3; 0.3; 0.1]); % 30cm std on x,y, 0.1 rad on theta +graph.add(PriorFactorPose2(1, priorMean, priorNoise)); % add directly to graph + +%% Add two odometry factors +odometry = Pose2(2.0, 0.0, 0.0); % create a measurement for both factors (the same in this case) +odometryNoise = noiseModel.Diagonal.Sigmas([0.2; 0.2; 0.1]); % 20cm std on x,y, 0.1 rad on theta +graph.add(BetweenFactorPose2(1, 2, odometry, odometryNoise)); +graph.add(BetweenFactorPose2(2, 3, odometry, odometryNoise)); + +%% print +graph.print(sprintf('\nFactor graph:\n')); + +%% Initialize to noisy points +initialEstimate = Values; +initialEstimate.insert(1, Pose2(0.5, 0.0, 0.2)); +initialEstimate.insert(2, Pose2(2.3, 0.1,-0.2)); +initialEstimate.insert(3, Pose2(4.1, 0.1, 0.1)); +initialEstimate.print(sprintf('\nInitial estimate:\n ')); + +%% Optimize using Levenberg-Marquardt optimization with an ordering from colamd +optimizer = LevenbergMarquardtOptimizer(graph, initialEstimate); +result = optimizer.optimizeSafely(); +result.print(sprintf('\nFinal result:\n ')); + +%% Plot trajectory and covariance ellipses +cla; +hold on; + +plot2DTrajectory(result, [], Marginals(graph, result)); + +axis([-0.6 4.8 -1 1]) +axis equal +view(2) diff --git a/matlab/gtsam_examples/PlanarSLAMExample.m b/matlab/gtsam_examples/PlanarSLAMExample.m new file mode 100644 index 000000000..ef1516017 --- /dev/null +++ b/matlab/gtsam_examples/PlanarSLAMExample.m @@ -0,0 +1,80 @@ +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% GTSAM Copyright 2010, Georgia Tech Research Corporation, +% Atlanta, Georgia 30332-0415 +% All Rights Reserved +% Authors: Frank Dellaert, et al. (see THANKS for the full author list) +% +% See LICENSE for the license information +% +% @brief Simple robotics example using the pre-built planar SLAM domain +% @author Alex Cunningham +% @author Frank Dellaert +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +import gtsam.* + +%% Assumptions +% - All values are axis aligned +% - Robot poses are facing along the X axis (horizontal, to the right in images) +% - We have bearing and range information for measurements +% - We have full odometry for measurements +% - The robot and landmarks are on a grid, moving 2 meters each step +% - Landmarks are 2 meters away from the robot trajectory + +%% Create keys for variables +i1 = symbol('x',1); i2 = symbol('x',2); i3 = symbol('x',3); +j1 = symbol('l',1); j2 = symbol('l',2); + +%% Create graph container and add factors to it +graph = NonlinearFactorGraph; + +%% Add prior +priorMean = Pose2(0.0, 0.0, 0.0); % prior at origin +priorNoise = noiseModel.Diagonal.Sigmas([0.3; 0.3; 0.1]); +graph.add(PriorFactorPose2(i1, priorMean, priorNoise)); + +%% Add odometry +odometry = Pose2(2.0, 0.0, 0.0); +odometryNoise = noiseModel.Diagonal.Sigmas([0.2; 0.2; 0.1]); +graph.add(BetweenFactorPose2(i1, i2, odometry, odometryNoise)); +graph.add(BetweenFactorPose2(i2, i3, odometry, odometryNoise)); + +%% Add bearing/range measurement factors +degrees = pi/180; +brNoise = noiseModel.Diagonal.Sigmas([0.1; 0.2]); +graph.add(BearingRangeFactor2D(i1, j1, Rot2(45*degrees), sqrt(8), brNoise)); +graph.add(BearingRangeFactor2D(i2, j1, Rot2(90*degrees), 2, brNoise)); +graph.add(BearingRangeFactor2D(i3, j2, Rot2(90*degrees), 2, brNoise)); + +% print +graph.print(sprintf('\nFull graph:\n')); + +%% Initialize to noisy points +initialEstimate = Values; +initialEstimate.insert(i1, Pose2(0.5, 0.0, 0.2)); +initialEstimate.insert(i2, Pose2(2.3, 0.1,-0.2)); +initialEstimate.insert(i3, Pose2(4.1, 0.1, 0.1)); +initialEstimate.insert(j1, Point2(1.8, 2.1)); +initialEstimate.insert(j2, Point2(4.1, 1.8)); + +initialEstimate.print(sprintf('\nInitial estimate:\n')); + +%% Optimize using Levenberg-Marquardt optimization with an ordering from colamd +optimizer = LevenbergMarquardtOptimizer(graph, initialEstimate); +result = optimizer.optimizeSafely(); +result.print(sprintf('\nFinal result:\n')); + +%% Plot Covariance Ellipses +cla;hold on + +marginals = Marginals(graph, result); +plot2DTrajectory(result, [], marginals); +plot2DPoints(result, 'b', marginals); + +plot([result.at(i1).x; result.at(j1).x],[result.at(i1).y; result.at(j1).y], 'c-'); +plot([result.at(i2).x; result.at(j1).x],[result.at(i2).y; result.at(j1).y], 'c-'); +plot([result.at(i3).x; result.at(j2).x],[result.at(i3).y; result.at(j2).y], 'c-'); +axis([-0.6 4.8 -1 1]) +axis equal +view(2) + diff --git a/matlab/gtsam_examples/PlanarSLAMExample_graph.m b/matlab/gtsam_examples/PlanarSLAMExample_graph.m new file mode 100644 index 000000000..9ca88e49a --- /dev/null +++ b/matlab/gtsam_examples/PlanarSLAMExample_graph.m @@ -0,0 +1,47 @@ +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% GTSAM Copyright 2010, Georgia Tech Research Corporation, +% Atlanta, Georgia 30332-0415 +% All Rights Reserved +% Authors: Frank Dellaert, et al. (see THANKS for the full author list) +% +% See LICENSE for the license information +% +% @brief Read graph from file and perform GraphSLAM +% @author Frank Dellaert +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +clear + +import gtsam.* + +%% Find data file +datafile = findExampleDataFile('example.graph'); + +%% Initialize graph, initial estimate, and odometry noise +model = noiseModel.Diagonal.Sigmas([0.05; 0.05; 2*pi/180]); +[graph,initial] = load2D(datafile, model); + +%% Add a Gaussian prior on a pose in the middle +priorMean = initial.at(40); +priorNoise = noiseModel.Diagonal.Sigmas([0.1; 0.1; 2*pi/180]); +graph.add(PriorFactorPose2(40, priorMean, priorNoise)); % add directly to graph + +%% Plot Initial Estimate +cla +plot2DTrajectory(initial, 'r-'); axis equal + +%% Optimize using Levenberg-Marquardt optimization with an ordering from colamd +optimizer = LevenbergMarquardtOptimizer(graph, initial); +tic +result = optimizer.optimizeSafely; +toc + +%% Plot Covariance Ellipses +cla;hold on +marginals = Marginals(graph, result); +plot2DTrajectory(result, 'g', marginals); +plot2DPoints(result, 'b', marginals); +axis tight +axis equal +view(2) + diff --git a/matlab/gtsam_examples/PlanarSLAMExample_sampling.m b/matlab/gtsam_examples/PlanarSLAMExample_sampling.m new file mode 100644 index 000000000..327c64d4d --- /dev/null +++ b/matlab/gtsam_examples/PlanarSLAMExample_sampling.m @@ -0,0 +1,74 @@ +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% GTSAM Copyright 2010, Georgia Tech Research Corporation, +% Atlanta, Georgia 30332-0415 +% All Rights Reserved +% Authors: Frank Dellaert, et al. (see THANKS for the full author list) +% +% See LICENSE for the license information +% +% @brief Simple robotics example using the pre-built planar SLAM domain +% @author Alex Cunningham +% @author Frank Dellaert +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +import gtsam.* + +%% Create the same factor graph as in PlanarSLAMExample +i1 = symbol('x',1); i2 = symbol('x',2); i3 = symbol('x',3); +graph = NonlinearFactorGraph; +priorMean = Pose2(0.0, 0.0, 0.0); % prior at origin +priorNoise = noiseModel.Diagonal.Sigmas([0.3; 0.3; 0.1]); +graph.add(PriorFactorPose2(i1, priorMean, priorNoise)); % add directly to graph +odometry = Pose2(2.0, 0.0, 0.0); +odometryNoise = noiseModel.Diagonal.Sigmas([0.2; 0.2; 0.1]); +graph.add(BetweenFactorPose2(i1, i2, odometry, odometryNoise)); +graph.add(BetweenFactorPose2(i2, i3, odometry, odometryNoise)); + +%% Except, for measurements we offer a choice +j1 = symbol('l',1); j2 = symbol('l',2); +degrees = pi/180; +brNoise = noiseModel.Diagonal.Sigmas([0.1; 0.2]); +if 1 + graph.add(BearingRangeFactor2D(i1, j1, Rot2(45*degrees), sqrt(4+4), brNoise)); + graph.add(BearingRangeFactor2D(i2, j1, Rot2(90*degrees), 2, brNoise)); +else + bearingModel = noiseModel.Diagonal.Sigmas(0.1); + graph.add(BearingFactor2D(i1, j1, Rot2(45*degrees), bearingModel)); + graph.add(BearingFactor2D(i2, j1, Rot2(90*degrees), bearingModel)); +end +graph.add(BearingRangeFactor2D(i3, j2, Rot2(90*degrees), 2, brNoise)); + +%% Initialize MCMC sampler with ground truth +sample = Values; +sample.insert(i1, Pose2(0,0,0)); +sample.insert(i2, Pose2(2,0,0)); +sample.insert(i3, Pose2(4,0,0)); +sample.insert(j1, Point2(2,2)); +sample.insert(j2, Point2(4,2)); + +%% Calculate and plot Covariance Ellipses +cla;hold on +marginals = Marginals(graph, sample); + +plot2DTrajectory(sample, [], marginals); +plot2DPoints(sample, [], marginals); + +for j=1:2 + key = symbol('l',j); + point{j} = sample.at(key); + Q{j}=marginals.marginalCovariance(key); + S{j}=chol(Q{j}); % for sampling +end + +plot([sample.at(i1).x; sample.at(j1).x],[sample.at(i1).y; sample.at(j1).y], 'c-'); +plot([sample.at(i2).x; sample.at(j1).x],[sample.at(i2).y; sample.at(j1).y], 'c-'); +plot([sample.at(i3).x; sample.at(j2).x],[sample.at(i3).y; sample.at(j2).y], 'c-'); +view(2); axis auto; axis equal + +%% Do Sampling on point 2 +N=1000; +for s=1:N + delta = S{2}*randn(2,1); + proposedPoint = Point2(point{2}.x+delta(1),point{2}.y+delta(2)); + plotPoint2(proposedPoint,'k.') +end \ No newline at end of file diff --git a/matlab/gtsam_examples/Pose2SLAMExample.m b/matlab/gtsam_examples/Pose2SLAMExample.m new file mode 100644 index 000000000..65ce28dbb --- /dev/null +++ b/matlab/gtsam_examples/Pose2SLAMExample.m @@ -0,0 +1,67 @@ +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% GTSAM Copyright 2010, Georgia Tech Research Corporation, +% Atlanta, Georgia 30332-0415 +% All Rights Reserved +% Authors: Frank Dellaert, et al. (see THANKS for the full author list) +% +% See LICENSE for the license information +% +% @brief Simple robotics example using the pre-built planar SLAM domain +% @author Alex Cunningham +% @author Frank Dellaert +% @author Chris Beall +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +import gtsam.* + +%% Assumptions +% - All values are axis aligned +% - Robot poses are facing along the X axis (horizontal, to the right in images) +% - We have full odometry for measurements +% - The robot is on a grid, moving 2 meters each step + +%% Create graph container and add factors to it +graph = NonlinearFactorGraph; + +%% Add prior +priorNoise = noiseModel.Diagonal.Sigmas([0.3; 0.3; 0.1]); +graph.add(PriorFactorPose2(1, Pose2(0, 0, 0), priorNoise)); % add directly to graph + +%% Add odometry +model = noiseModel.Diagonal.Sigmas([0.2; 0.2; 0.1]); +graph.add(BetweenFactorPose2(1, 2, Pose2(2, 0, 0 ), model)); +graph.add(BetweenFactorPose2(2, 3, Pose2(2, 0, pi/2), model)); +graph.add(BetweenFactorPose2(3, 4, Pose2(2, 0, pi/2), model)); +graph.add(BetweenFactorPose2(4, 5, Pose2(2, 0, pi/2), model)); + +%% Add pose constraint +graph.add(BetweenFactorPose2(5, 2, Pose2(2, 0, pi/2), model)); + +% print +graph.print(sprintf('\nFactor graph:\n')); + +%% Initialize to noisy points +initialEstimate = Values; +initialEstimate.insert(1, Pose2(0.5, 0.0, 0.2 )); +initialEstimate.insert(2, Pose2(2.3, 0.1, -0.2 )); +initialEstimate.insert(3, Pose2(4.1, 0.1, pi/2)); +initialEstimate.insert(4, Pose2(4.0, 2.0, pi )); +initialEstimate.insert(5, Pose2(2.1, 2.1, -pi/2)); +initialEstimate.print(sprintf('\nInitial estimate:\n')); + +%% Optimize using Levenberg-Marquardt optimization with an ordering from colamd +optimizer = LevenbergMarquardtOptimizer(graph, initialEstimate); +result = optimizer.optimizeSafely(); +result.print(sprintf('\nFinal result:\n')); + +%% Plot Covariance Ellipses +cla; +hold on +plot([result.at(5).x;result.at(2).x],[result.at(5).y;result.at(2).y],'r-'); +marginals = Marginals(graph, result); + +plot2DTrajectory(result, [], marginals); +for i=1:5,marginals.marginalCovariance(i),end +axis equal +axis tight +view(2) diff --git a/examples/matlab/Pose2SLAMExample_advanced.m b/matlab/gtsam_examples/Pose2SLAMExample_advanced.m similarity index 54% rename from examples/matlab/Pose2SLAMExample_advanced.m rename to matlab/gtsam_examples/Pose2SLAMExample_advanced.m index 2199def5b..343dee05b 100644 --- a/examples/matlab/Pose2SLAMExample_advanced.m +++ b/matlab/gtsam_examples/Pose2SLAMExample_advanced.m @@ -14,59 +14,55 @@ % @author Can Erdogan %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +import gtsam.* + %% Assumptions % - All values are axis aligned % - Robot poses are facing along the X axis (horizontal, to the right in images) % - We have full odometry for measurements % - The robot is on a grid, moving 2 meters each step -%% Create keys for variables -x1 = 1; x2 = 2; x3 = 3; - %% Create graph container and add factors to it -graph = pose2SLAMGraph; +graph = NonlinearFactorGraph; %% Add prior % gaussian for prior -prior_model = gtsamSharedNoiseModel_Sigmas([0.3; 0.3; 0.1]); -prior_measurement = gtsamPose2(0.0, 0.0, 0.0); % prior at origin -graph.addPrior(x1, prior_measurement, prior_model); % add directly to graph +priorNoise = noiseModel.Diagonal.Sigmas([0.3; 0.3; 0.1]); +priorMean = Pose2(0.0, 0.0, 0.0); % prior at origin +graph.add(PriorFactorPose2(1, priorMean, priorNoise)); % add directly to graph %% Add odometry % general noisemodel for odometry -odom_model = gtsamSharedNoiseModel_Sigmas([0.2; 0.2; 0.1]); -odom_measurement = gtsamPose2(2.0, 0.0, 0.0); % create a measurement for both factors (the same in this case) -graph.addOdometry(x1, x2, odom_measurement, odom_model); -graph.addOdometry(x2, x3, odom_measurement, odom_model); +odometryNoise = noiseModel.Diagonal.Sigmas([0.2; 0.2; 0.1]); +odometry = Pose2(2.0, 0.0, 0.0); % create a measurement for both factors (the same in this case) +graph.add(BetweenFactorPose2(1, 2, odometry, odometryNoise)); +graph.add(BetweenFactorPose2(2, 3, odometry, odometryNoise)); %% Add measurements % general noisemodel for measurements -meas_model = gtsamSharedNoiseModel_Sigmas([0.1; 0.2]); +measurementNoise = noiseModel.Diagonal.Sigmas([0.1; 0.2]); % print graph.print('full graph'); %% Initialize to noisy points -initialEstimate = pose2SLAMValues; -initialEstimate.insertPose(x1, gtsamPose2(0.5, 0.0, 0.2)); -initialEstimate.insertPose(x2, gtsamPose2(2.3, 0.1,-0.2)); -initialEstimate.insertPose(x3, gtsamPose2(4.1, 0.1, 0.1)); +initialEstimate = Values; +initialEstimate.insert(1, Pose2(0.5, 0.0, 0.2)); +initialEstimate.insert(2, Pose2(2.3, 0.1,-0.2)); +initialEstimate.insert(3, Pose2(4.1, 0.1, 0.1)); initialEstimate.print('initial estimate'); %% set up solver, choose ordering and optimize -%params = gtsamNonlinearOptimizationParameters_newDecreaseThresholds(1e-15, 1e-15); -% -%ord = graph.orderingCOLAMD(initialEstimate); -% -%result = pose2SLAMOptimizer(graph,initialEstimate,ord,params); -%result.print('final result'); +params = DoglegParams; +params.setAbsoluteErrorTol(1e-15); +params.setRelativeErrorTol(1e-15); +params.setVerbosity('ERROR'); +params.setVerbosityDL('VERBOSE'); +params.setOrdering(graph.orderingCOLAMD(initialEstimate)); +optimizer = DoglegOptimizer(graph, initialEstimate, params); -% % -% % disp('\\\'); -% % -% % %% Optimize using Levenberg-Marquardt optimization with an ordering from colamd -result = graph.optimize(initialEstimate); +result = optimizer.optimizeSafely(); result.print('final result'); %% Get the corresponding dense matrix @@ -79,4 +75,6 @@ IJS = gfg.sparseJacobian_(); Ab=sparse(IJS(1,:),IJS(2,:),IJS(3,:)); A = Ab(:,1:end-1); b = full(Ab(:,end)); +clf spy(A); +title('Non-zero entries in measurement Jacobian'); diff --git a/matlab/gtsam_examples/Pose2SLAMExample_circle.m b/matlab/gtsam_examples/Pose2SLAMExample_circle.m new file mode 100644 index 000000000..3d2265d76 --- /dev/null +++ b/matlab/gtsam_examples/Pose2SLAMExample_circle.m @@ -0,0 +1,53 @@ +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% GTSAM Copyright 2010, Georgia Tech Research Corporation, +% Atlanta, Georgia 30332-0415 +% All Rights Reserved +% Authors: Frank Dellaert, et al. (see THANKS for the full author list) +% +% See LICENSE for the license information +% +% @brief Read graph from file and perform GraphSLAM +% @author Frank Dellaert +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +import gtsam.* + +%% Create a hexagon of poses +hexagon = circlePose2(6,1.0); +p0 = hexagon.at(0); +p1 = hexagon.at(1); + +%% create a Pose graph with one equality constraint and one measurement +fg = NonlinearFactorGraph; +fg.add(NonlinearEqualityPose2(0, p0)); +delta = p0.between(p1); +covariance = noiseModel.Diagonal.Sigmas([0.05; 0.05; 5*pi/180]); +fg.add(BetweenFactorPose2(0,1, delta, covariance)); +fg.add(BetweenFactorPose2(1,2, delta, covariance)); +fg.add(BetweenFactorPose2(2,3, delta, covariance)); +fg.add(BetweenFactorPose2(3,4, delta, covariance)); +fg.add(BetweenFactorPose2(4,5, delta, covariance)); +fg.add(BetweenFactorPose2(5,0, delta, covariance)); + +%% Create initial config +initial = Values; +initial.insert(0, p0); +initial.insert(1, hexagon.at(1).retract([-0.1, 0.1,-0.1]')); +initial.insert(2, hexagon.at(2).retract([ 0.1,-0.1, 0.1]')); +initial.insert(3, hexagon.at(3).retract([-0.1, 0.1,-0.1]')); +initial.insert(4, hexagon.at(4).retract([ 0.1,-0.1, 0.1]')); +initial.insert(5, hexagon.at(5).retract([-0.1, 0.1,-0.1]')); + +%% Plot Initial Estimate +cla +plot2DTrajectory(initial, 'g*-'); axis equal + +%% optimize +optimizer = DoglegOptimizer(fg, initial); +result = optimizer.optimizeSafely; + +%% Show Result +hold on; plot2DTrajectory(result, 'b*-'); +view(2); +axis([-1.5 1.5 -1.5 1.5]); +result.print(sprintf('\nFinal result:\n')); diff --git a/matlab/gtsam_examples/Pose2SLAMExample_graph.m b/matlab/gtsam_examples/Pose2SLAMExample_graph.m new file mode 100644 index 000000000..eb1b03950 --- /dev/null +++ b/matlab/gtsam_examples/Pose2SLAMExample_graph.m @@ -0,0 +1,48 @@ +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% GTSAM Copyright 2010, Georgia Tech Research Corporation, +% Atlanta, Georgia 30332-0415 +% All Rights Reserved +% Authors: Frank Dellaert, et al. (see THANKS for the full author list) +% +% See LICENSE for the license information +% +% @brief Read graph from file and perform GraphSLAM +% @author Frank Dellaert +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +import gtsam.* + +%% Find data file +datafile = findExampleDataFile('w100-odom.graph'); + +%% Initialize graph, initial estimate, and odometry noise +model = noiseModel.Diagonal.Sigmas([0.05; 0.05; 5*pi/180]); +[graph,initial] = load2D(datafile, model); + +%% Add a Gaussian prior on pose x_1 +priorMean = Pose2(0, 0, 0); % prior mean is at origin +priorNoise = noiseModel.Diagonal.Sigmas([0.01; 0.01; 0.01]); +graph.add(PriorFactorPose2(0, priorMean, priorNoise)); % add directly to graph + +%% Plot Initial Estimate +cla +plot2DTrajectory(initial, 'g-*'); axis equal + +%% Optimize using Levenberg-Marquardt optimization with an ordering from colamd +optimizer = LevenbergMarquardtOptimizer(graph, initial); +tic +result = optimizer.optimizeSafely; +toc +hold on; plot2DTrajectory(result, 'b-*'); + +%% Plot Covariance Ellipses +marginals = Marginals(graph, result); +P={}; +for i=1:result.size()-1 + pose_i = result.at(i); + P{i}=marginals.marginalCovariance(i); + plotPose2(pose_i,'b',P{i}) +end +view(2) +axis tight; axis equal; +% fprintf(1,'%.5f %.5f %.5f\n',P{99}) \ No newline at end of file diff --git a/matlab/gtsam_examples/Pose2SLAMwSPCG.m b/matlab/gtsam_examples/Pose2SLAMwSPCG.m new file mode 100644 index 000000000..67f22fe1d --- /dev/null +++ b/matlab/gtsam_examples/Pose2SLAMwSPCG.m @@ -0,0 +1,64 @@ +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% GTSAM Copyright 2010, Georgia Tech Research Corporation, +% Atlanta, Georgia 30332-0415 +% All Rights Reserved +% Authors: Frank Dellaert, et al. (see THANKS for the full author list) +% +% See LICENSE for the license information +% +% @brief Simple 2D robotics example using the SimpleSPCGSolver +% @author Yong-Dian Jian +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +import gtsam.* + +%% Assumptions +% - All values are axis aligned +% - Robot poses are facing along the X axis (horizontal, to the right in images) +% - We have full odometry for measurements +% - The robot is on a grid, moving 2 meters each step + +%% Create graph container and add factors to it +graph = NonlinearFactorGraph; + +%% Add prior +% gaussian for prior +priorMean = Pose2(0.0, 0.0, 0.0); % prior at origin +priorNoise = noiseModel.Diagonal.Sigmas([0.3; 0.3; 0.1]); +graph.add(PriorFactorPose2(1, priorMean, priorNoise)); % add directly to graph + +%% Add odometry +% general noisemodel for odometry +odometryNoise = noiseModel.Diagonal.Sigmas([0.2; 0.2; 0.1]); +graph.add(BetweenFactorPose2(1, 2, Pose2(2.0, 0.0, 0.0 ), odometryNoise)); +graph.add(BetweenFactorPose2(2, 3, Pose2(2.0, 0.0, pi/2), odometryNoise)); +graph.add(BetweenFactorPose2(3, 4, Pose2(2.0, 0.0, pi/2), odometryNoise)); +graph.add(BetweenFactorPose2(4, 5, Pose2(2.0, 0.0, pi/2), odometryNoise)); + +%% Add pose constraint +model = noiseModel.Diagonal.Sigmas([0.2; 0.2; 0.1]); +graph.add(BetweenFactorPose2(5, 2, Pose2(2.0, 0.0, pi/2), model)); + +% print +graph.print(sprintf('\nFactor graph:\n')); + +%% Initialize to noisy points +initialEstimate = Values; +initialEstimate.insert(1, Pose2(0.5, 0.0, 0.2 )); +initialEstimate.insert(2, Pose2(2.3, 0.1,-0.2 )); +initialEstimate.insert(3, Pose2(4.1, 0.1, pi/2)); +initialEstimate.insert(4, Pose2(4.0, 2.0, pi )); +initialEstimate.insert(5, Pose2(2.1, 2.1,-pi/2)); +initialEstimate.print(sprintf('\nInitial estimate:\n')); + +%% Optimize using Levenberg-Marquardt optimization with SubgraphSolver +params = gtsam.LevenbergMarquardtParams; +subgraphParams = gtsam.SubgraphSolverParameters; +params.setLinearSolverType('CONJUGATE_GRADIENT'); +params.setIterativeParams(subgraphParams); +optimizer = gtsam.LevenbergMarquardtOptimizer(graph, initialEstimate); +result = optimizer.optimize(); +result.print(sprintf('\nFinal result:\n')); + + + diff --git a/matlab/gtsam_examples/Pose3SLAMExample.m b/matlab/gtsam_examples/Pose3SLAMExample.m new file mode 100644 index 000000000..0d2bd237f --- /dev/null +++ b/matlab/gtsam_examples/Pose3SLAMExample.m @@ -0,0 +1,56 @@ +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% GTSAM Copyright 2010, Georgia Tech Research Corporation, +% Atlanta, Georgia 30332-0415 +% All Rights Reserved +% Authors: Frank Dellaert, et al. (see THANKS for the full author list) +% +% See LICENSE for the license information +% +% @brief Read graph from file and perform GraphSLAM +% @author Frank Dellaert +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +import gtsam.* + +%% Create a hexagon of poses +hexagon = circlePose3(6,1.0); +p0 = hexagon.at(0); +p1 = hexagon.at(1); + +%% create a Pose graph with one equality constraint and one measurement +fg = NonlinearFactorGraph; +fg.add(NonlinearEqualityPose3(0, p0)); +delta = p0.between(p1); +covariance = noiseModel.Diagonal.Sigmas([0.05; 0.05; 0.05; 5*pi/180; 5*pi/180; 5*pi/180]); +fg.add(BetweenFactorPose3(0,1, delta, covariance)); +fg.add(BetweenFactorPose3(1,2, delta, covariance)); +fg.add(BetweenFactorPose3(2,3, delta, covariance)); +fg.add(BetweenFactorPose3(3,4, delta, covariance)); +fg.add(BetweenFactorPose3(4,5, delta, covariance)); +fg.add(BetweenFactorPose3(5,0, delta, covariance)); + +%% Create initial config +initial = Values; +s = 0.10; +initial.insert(0, p0); +initial.insert(1, hexagon.at(1).retract(s*randn(6,1))); +initial.insert(2, hexagon.at(2).retract(s*randn(6,1))); +initial.insert(3, hexagon.at(3).retract(s*randn(6,1))); +initial.insert(4, hexagon.at(4).retract(s*randn(6,1))); +initial.insert(5, hexagon.at(5).retract(s*randn(6,1))); + +%% Plot Initial Estimate +cla +plot3DTrajectory(initial, 'g-*'); + +%% optimize +optimizer = DoglegOptimizer(fg, initial); +result = optimizer.optimizeSafely(); + +%% Show Result +hold on; plot3DTrajectory(result, 'b-*', true, 0.3); +axis([-2 2 -2 2 -1 1]); +axis equal +view(-37,40) +colormap hot +result.print(sprintf('\nFinal result:\n')); diff --git a/matlab/gtsam_examples/Pose3SLAMExample_graph.m b/matlab/gtsam_examples/Pose3SLAMExample_graph.m new file mode 100644 index 000000000..f4eb8dd3a --- /dev/null +++ b/matlab/gtsam_examples/Pose3SLAMExample_graph.m @@ -0,0 +1,41 @@ +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% GTSAM Copyright 2010, Georgia Tech Research Corporation, +% Atlanta, Georgia 30332-0415 +% All Rights Reserved +% Authors: Frank Dellaert, et al. (see THANKS for the full author list) +% +% See LICENSE for the license information +% +% @brief Read graph from file and perform GraphSLAM +% @author Frank Dellaert +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +import gtsam.* + +%% Find data file +N = 2500; +% dataset = 'sphere_smallnoise.graph'; +% dataset = 'sphere2500_groundtruth.txt'; +dataset = 'sphere2500.txt'; + +datafile = findExampleDataFile(dataset); + +%% Initialize graph, initial estimate, and odometry noise +model = noiseModel.Diagonal.Sigmas([0.05; 0.05; 0.05; 5*pi/180; 5*pi/180; 5*pi/180]); +[graph,initial]=load3D(datafile,model,true,N); + +%% Plot Initial Estimate +cla +first = initial.at(0); +plot3(first.x(),first.y(),first.z(),'r*'); hold on +plot3DTrajectory(initial,'g-',false); +drawnow; + +%% Read again, now with all constraints, and optimize +graph = load3D(datafile, model, false, N); +graph.add(NonlinearEqualityPose3(0, first)); +optimizer = LevenbergMarquardtOptimizer(graph, initial); +result = optimizer.optimizeSafely(); +plot3DTrajectory(result, 'r-', false); axis equal; + +view(3); axis equal; \ No newline at end of file diff --git a/matlab/gtsam_examples/SBAExample.m b/matlab/gtsam_examples/SBAExample.m new file mode 100644 index 000000000..b0f754044 --- /dev/null +++ b/matlab/gtsam_examples/SBAExample.m @@ -0,0 +1,84 @@ +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% GTSAM Copyright 2010, Georgia Tech Research Corporation, +% Atlanta, Georgia 30332-0415 +% All Rights Reserved +% Authors: Frank Dellaert, et al. (see THANKS for the full author list) +% +% See LICENSE for the license information +% +% @brief An SFM example (adapted from SFMExample.m) optimizing calibration +% @author Yong-Dian Jian +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +import gtsam.* + +%% Assumptions +% - Landmarks as 8 vertices of a cube: (10,10,10) (-10,10,10) etc... +% - Cameras are on a circle around the cube, pointing at the world origin +% - Each camera sees all landmarks. +% - Visual measurements as 2D points are given, corrupted by Gaussian noise. + +% Data Options +options.triangle = false; +options.nrCameras = 10; +options.showImages = false; + +%% Generate data +[data,truth] = VisualISAMGenerateData(options); + +measurementNoiseSigma = 1.0; +pointNoiseSigma = 0.1; +cameraNoiseSigmas = [0.001 0.001 0.001 0.1 0.1 0.1 ... + 0.001*ones(1,5)]'; + +%% Create the graph (defined in visualSLAM.h, derived from NonlinearFactorGraph) +graph = NonlinearFactorGraph; + + +%% Add factors for all measurements +measurementNoise = noiseModel.Isotropic.Sigma(2,measurementNoiseSigma); +for i=1:length(data.Z) + for k=1:length(data.Z{i}) + j = data.J{i}{k}; + graph.add(GeneralSFMFactorCal3_S2(data.Z{i}{k}, measurementNoise, symbol('c',i), symbol('p',j))); + end +end + +%% Add Gaussian priors for a pose and a landmark to constrain the system +cameraPriorNoise = noiseModel.Diagonal.Sigmas(cameraNoiseSigmas); +firstCamera = SimpleCamera(truth.cameras{1}.pose, truth.K); +graph.add(PriorFactorSimpleCamera(symbol('c',1), firstCamera, cameraPriorNoise)); + +pointPriorNoise = noiseModel.Isotropic.Sigma(3,pointNoiseSigma); +graph.add(PriorFactorPoint3(symbol('p',1), truth.points{1}, pointPriorNoise)); + +%% Print the graph +graph.print(sprintf('\nFactor graph:\n')); + + +%% Initialize cameras and points close to ground truth in this example +initialEstimate = Values; +for i=1:size(truth.cameras,2) + pose_i = truth.cameras{i}.pose.retract(0.1*randn(6,1)); + camera_i = SimpleCamera(pose_i, truth.K); + initialEstimate.insert(symbol('c',i), camera_i); +end +for j=1:size(truth.points,2) + point_j = truth.points{j}.retract(0.1*randn(3,1)); + initialEstimate.insert(symbol('p',j), point_j); +end +initialEstimate.print(sprintf('\nInitial estimate:\n ')); + +%% Fine grain optimization, allowing user to iterate step by step +parameters = LevenbergMarquardtParams; +parameters.setlambdaInitial(1.0); +parameters.setVerbosityLM('trylambda'); + +optimizer = LevenbergMarquardtOptimizer(graph, initialEstimate, parameters); + +for i=1:5 + optimizer.iterate(); +end + +result = optimizer.values(); +result.print(sprintf('\nFinal result:\n ')); diff --git a/matlab/gtsam_examples/SFMExample.m b/matlab/gtsam_examples/SFMExample.m new file mode 100644 index 000000000..4115fa6e3 --- /dev/null +++ b/matlab/gtsam_examples/SFMExample.m @@ -0,0 +1,89 @@ +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% GTSAM Copyright 2010, Georgia Tech Research Corporation, +% Atlanta, Georgia 30332-0415 +% All Rights Reserved +% Authors: Frank Dellaert, et al. (see THANKS for the full author list) +% +% See LICENSE for the license information +% +% @brief A structure from motion example +% @author Duy-Nguyen Ta +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +import gtsam.* + +%% Assumptions +% - Landmarks as 8 vertices of a cube: (10,10,10) (-10,10,10) etc... +% - Cameras are on a circle around the cube, pointing at the world origin +% - Each camera sees all landmarks. +% - Visual measurements as 2D points are given, corrupted by Gaussian noise. + +% Data Options +options.triangle = false; +options.nrCameras = 10; +options.showImages = false; + +%% Generate data +[data,truth] = VisualISAMGenerateData(options); + +measurementNoiseSigma = 1.0; +pointNoiseSigma = 0.1; +poseNoiseSigmas = [0.001 0.001 0.001 0.1 0.1 0.1]'; + +%% Create the graph (defined in visualSLAM.h, derived from NonlinearFactorGraph) +graph = NonlinearFactorGraph; + +%% Add factors for all measurements +measurementNoise = noiseModel.Isotropic.Sigma(2,measurementNoiseSigma); +for i=1:length(data.Z) + for k=1:length(data.Z{i}) + j = data.J{i}{k}; + graph.add(GenericProjectionFactorCal3_S2(data.Z{i}{k}, measurementNoise, symbol('x',i), symbol('p',j), data.K)); + end +end + +%% Add Gaussian priors for a pose and a landmark to constrain the system +posePriorNoise = noiseModel.Diagonal.Sigmas(poseNoiseSigmas); +graph.add(PriorFactorPose3(symbol('x',1), truth.cameras{1}.pose, posePriorNoise)); +pointPriorNoise = noiseModel.Isotropic.Sigma(3,pointNoiseSigma); +graph.add(PriorFactorPoint3(symbol('p',1), truth.points{1}, pointPriorNoise)); + +%% Print the graph +graph.print(sprintf('\nFactor graph:\n')); + +%% Initialize cameras and points close to ground truth in this example +initialEstimate = Values; +for i=1:size(truth.cameras,2) + pose_i = truth.cameras{i}.pose.retract(0.1*randn(6,1)); + initialEstimate.insert(symbol('x',i), pose_i); +end +for j=1:size(truth.points,2) + point_j = truth.points{j}.retract(0.1*randn(3,1)); + initialEstimate.insert(symbol('p',j), point_j); +end +initialEstimate.print(sprintf('\nInitial estimate:\n ')); + +%% Fine grain optimization, allowing user to iterate step by step +parameters = LevenbergMarquardtParams; +parameters.setlambdaInitial(1.0); +parameters.setVerbosityLM('trylambda'); + +optimizer = LevenbergMarquardtOptimizer(graph, initialEstimate, parameters); + +for i=1:5 + optimizer.iterate(); +end +result = optimizer.values(); +result.print(sprintf('\nFinal result:\n ')); + +%% Plot results with covariance ellipses +marginals = Marginals(graph, result); +cla +hold on; + +plot3DPoints(result, [], marginals); +plot3DTrajectory(result, '*', 1, 8, marginals); + +axis([-40 40 -40 40 -10 20]);axis equal +view(3) +colormap('hot') diff --git a/matlab/gtsam_examples/StereoVOExample.m b/matlab/gtsam_examples/StereoVOExample.m new file mode 100644 index 000000000..8dbaa1a76 --- /dev/null +++ b/matlab/gtsam_examples/StereoVOExample.m @@ -0,0 +1,75 @@ +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% GTSAM Copyright 2010, Georgia Tech Research Corporation, +% Atlanta, Georgia 30332-0415 +% All Rights Reserved +% Authors: Frank Dellaert, et al. (see THANKS for the full author list) +% +% See LICENSE for the license information +% +% @brief Basic VO Example with 3 landmarks and two cameras +% @author Chris Beall +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +import gtsam.* + +%% Assumptions +% - For simplicity this example is in the camera's coordinate frame +% - X: right, Y: down, Z: forward +% - Pose x1 is at the origin, Pose 2 is 1 meter forward (along Z-axis) +% - x1 is fixed with a constraint, x2 is initialized with noisy values +% - No noise on measurements + +%% Create keys for variables +x1 = symbol('x',1); x2 = symbol('x',2); +l1 = symbol('l',1); l2 = symbol('l',2); l3 = symbol('l',3); + +%% Create graph container and add factors to it +graph = NonlinearFactorGraph; + +%% add a constraint on the starting pose +first_pose = Pose3(); +graph.add(NonlinearEqualityPose3(x1, first_pose)); + +%% Create realistic calibration and measurement noise model +% format: fx fy skew cx cy baseline +K = Cal3_S2Stereo(1000, 1000, 0, 320, 240, 0.2); +stereo_model = noiseModel.Diagonal.Sigmas([1.0; 1.0; 1.0]); + +%% Add measurements +% pose 1 +graph.add(GenericStereoFactor3D(StereoPoint2(520, 480, 440), stereo_model, x1, l1, K)); +graph.add(GenericStereoFactor3D(StereoPoint2(120, 80, 440), stereo_model, x1, l2, K)); +graph.add(GenericStereoFactor3D(StereoPoint2(320, 280, 140), stereo_model, x1, l3, K)); + +%pose 2 +graph.add(GenericStereoFactor3D(StereoPoint2(570, 520, 490), stereo_model, x2, l1, K)); +graph.add(GenericStereoFactor3D(StereoPoint2( 70, 20, 490), stereo_model, x2, l2, K)); +graph.add(GenericStereoFactor3D(StereoPoint2(320, 270, 115), stereo_model, x2, l3, K)); + + +%% Create initial estimate for camera poses and landmarks +initialEstimate = Values; +initialEstimate.insert(x1, first_pose); +% noisy estimate for pose 2 +initialEstimate.insert(x2, Pose3(Rot3(), Point3(0.1,-.1,1.1))); +initialEstimate.insert(l1, Point3( 1, 1, 5)); +initialEstimate.insert(l2, Point3(-1, 1, 5)); +initialEstimate.insert(l3, Point3( 0,-.5, 5)); + +%% optimize +fprintf(1,'Optimizing\n'); tic +optimizer = LevenbergMarquardtOptimizer(graph, initialEstimate); +result = optimizer.optimizeSafely(); +toc + +%% visualize initial trajectory, final trajectory, and final points +cla; hold on; +axis normal +axis([-1.5 1.5 -2 2 -1 6]); +axis equal +view(-38,12) +camup([0;1;0]); + +plot3DTrajectory(initialEstimate, 'r', 1, 0.3); +plot3DTrajectory(result, 'g', 1, 0.3); +plot3DPoints(result); diff --git a/matlab/gtsam_examples/StereoVOExample_large.m b/matlab/gtsam_examples/StereoVOExample_large.m new file mode 100644 index 000000000..b77733abd --- /dev/null +++ b/matlab/gtsam_examples/StereoVOExample_large.m @@ -0,0 +1,76 @@ +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% GTSAM Copyright 2010, Georgia Tech Research Corporation, +% Atlanta, Georgia 30332-0415 +% All Rights Reserved +% Authors: Frank Dellaert, et al. (see THANKS for the full author list) +% +% See LICENSE for the license information +% +% @brief Read Stereo Visual Odometry from file and optimize +% @author Chris Beall +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +import gtsam.* + +%% Load calibration +% format: fx fy skew cx cy baseline +calib = dlmread(findExampleDataFile('VO_calibration.txt')); +K = Cal3_S2Stereo(calib(1), calib(2), calib(3), calib(4), calib(5), calib(6)); +stereo_model = noiseModel.Diagonal.Sigmas([1.0; 1.0; 1.0]); + +%% create empty graph and values +graph = NonlinearFactorGraph; +initial = Values; + + +%% load the initial poses from VO +% row format: camera_id 4x4 pose (row, major) +fprintf(1,'Reading data\n'); +cameras = dlmread(findExampleDataFile('VO_camera_poses_large.txt')); +for i=1:size(cameras,1) + pose = Pose3(reshape(cameras(i,2:17),4,4)'); + initial.insert(symbol('x',cameras(i,1)),pose); +end + +%% load stereo measurements and initialize landmarks +% camera_id landmark_id uL uR v X Y Z +measurements = dlmread(findExampleDataFile('VO_stereo_factors_large.txt')); + +fprintf(1,'Creating Graph\n'); tic +for i=1:size(measurements,1) + sf = measurements(i,:); + graph.add(GenericStereoFactor3D(StereoPoint2(sf(3),sf(4),sf(5)), stereo_model, ... + symbol('x', sf(1)), symbol('l', sf(2)), K)); + + if ~initial.exists(symbol('l',sf(2))) + % 3D landmarks are stored in camera coordinates: transform + % to world coordinates using the respective initial pose + pose = initial.at(symbol('x', sf(1))); + world_point = pose.transform_from(Point3(sf(6),sf(7),sf(8))); + initial.insert(symbol('l',sf(2)), world_point); + end +end +toc + +%% add a constraint on the starting pose +key = symbol('x',1); +first_pose = initial.at(key); +graph.add(NonlinearEqualityPose3(key, first_pose)); + +%% optimize +fprintf(1,'Optimizing\n'); tic +optimizer = LevenbergMarquardtOptimizer(graph, initial); +result = optimizer.optimizeSafely(); +toc + +%% visualize initial trajectory, final trajectory, and final points +cla; hold on; + +plot3DTrajectory(initial, 'r', 1, 0.5); +plot3DTrajectory(result, 'g', 1, 0.5); +plot3DPoints(result); + +axis([-5 20 -20 20 0 100]); +axis equal +view(3) +camup([0;1;0]); diff --git a/matlab/gtsam_examples/VisualISAMDemo.m b/matlab/gtsam_examples/VisualISAMDemo.m new file mode 100644 index 000000000..813d6d2e1 --- /dev/null +++ b/matlab/gtsam_examples/VisualISAMDemo.m @@ -0,0 +1,9 @@ +% VisualISAMDemo: runs VisualSLAM iSAM demo in a GUI +% Authors: Duy Nguyen Ta + +% Make sure global variables are visible on command prompt +% so you can examine how they change as you step through +global options truth data noiseModels isam result frame_i + +% Start GUI +VisualISAM_gui \ No newline at end of file diff --git a/matlab/gtsam_examples/VisualISAMExample.m b/matlab/gtsam_examples/VisualISAMExample.m new file mode 100644 index 000000000..751373b69 --- /dev/null +++ b/matlab/gtsam_examples/VisualISAMExample.m @@ -0,0 +1,50 @@ +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% GTSAM Copyright 2010, Georgia Tech Research Corporation, +% Atlanta, Georgia 30332-0415 +% All Rights Reserved +% Authors: Frank Dellaert, et al. (see THANKS for the full author list) +% +% See LICENSE for the license information +% +% @brief A simple visual SLAM example for structure from motion +% @author Duy-Nguyen Ta +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +import gtsam.* + +% Data Options +options.triangle = false; +options.nrCameras = 20; +options.showImages = false; + +% iSAM Options +options.hardConstraint = false; +options.pointPriors = false; +options.batchInitialization = true; +options.reorderInterval = 10; +options.alwaysRelinearize = false; + +% Display Options +options.saveDotFile = false; +options.printStats = false; +options.drawInterval = 5; +options.cameraInterval = 1; +options.drawTruePoses = false; +options.saveFigures = false; +options.saveDotFiles = false; + +%% Generate data +[data,truth] = VisualISAMGenerateData(options); + +%% Initialize iSAM with the first pose and points +[noiseModels,isam,result,nextPose] = VisualISAMInitialize(data,truth,options); +cla; +VisualISAMPlot(truth, data, isam, result, options) + +%% Main loop for iSAM: stepping through all poses +for frame_i=3:options.nrCameras + [isam,result,nextPose] = VisualISAMStep(data,noiseModels,isam,result,truth,nextPose); + if mod(frame_i,options.drawInterval)==0 + VisualISAMPlot(truth, data, isam, result, options) + end +end diff --git a/matlab/gtsam_examples/VisualISAM_gui.fig b/matlab/gtsam_examples/VisualISAM_gui.fig new file mode 100644 index 000000000..d4d65f565 Binary files /dev/null and b/matlab/gtsam_examples/VisualISAM_gui.fig differ diff --git a/matlab/gtsam_examples/VisualISAM_gui.m b/matlab/gtsam_examples/VisualISAM_gui.m new file mode 100644 index 000000000..4ccde5e53 --- /dev/null +++ b/matlab/gtsam_examples/VisualISAM_gui.m @@ -0,0 +1,268 @@ +function varargout = VisualISAM_gui(varargin) +% VisualISAM_gui: runs VisualSLAM iSAM demo in GUI +% Interface is defined by VisualISAM_gui.fig +% You can run this file directly, but won't have access to globals +% By running ViusalISAMDemo, you see all variables in command prompt +% Authors: Duy Nguyen Ta + +% Last Modified by GUIDE v2.5 13-Jun-2012 23:15:43 + +% Begin initialization code - DO NOT EDIT +gui_Singleton = 1; +gui_State = struct('gui_Name', mfilename, ... + 'gui_Singleton', gui_Singleton, ... + 'gui_OpeningFcn', @VisualISAM_gui_OpeningFcn, ... + 'gui_OutputFcn', @VisualISAM_gui_OutputFcn, ... + 'gui_LayoutFcn', [] , ... + 'gui_Callback', []); +if nargin && ischar(varargin{1}) + gui_State.gui_Callback = str2func(varargin{1}); +end + +if nargout + [varargout{1:nargout}] = gui_mainfcn(gui_State, varargin{:}); +else + gui_mainfcn(gui_State, varargin{:}); +end +% End initialization code - DO NOT EDIT + + +% --- Executes just before VisualISAM_gui is made visible. +function VisualISAM_gui_OpeningFcn(hObject, ~, handles, varargin) +% This function has no output args, see OutputFcn. +% varargin command line arguments to VisualISAM_gui (see VARARGIN) + +% Choose default command line output for VisualISAM_gui +handles.output = hObject; + +% Update handles structure +guidata(hObject, handles); + +% --- Outputs from this function are returned to the command line. +function varargout = VisualISAM_gui_OutputFcn(hObject, ~, handles) +% varargout cell array for returning output args (see VARARGOUT); +% Get default command line output from handles structure +varargout{1} = handles.output; + + +%---------------------------------------------------------- +% Convenient functions +%---------------------------------------------------------- +function showFramei(hObject, handles) +global frame_i +set(handles.frameStatus, 'String', sprintf('Frame: %d',frame_i)); +drawnow +guidata(hObject, handles); + +function showWaiting(handles, status) +set(handles.waitingStatus,'String', status); +drawnow +guidata(handles.waitingStatus, handles); + +function triangle = chooseDataset(handles) +str = cellstr(get(handles.dataset,'String')); +sel = get(handles.dataset,'Value'); +switch str{sel} + case 'triangle' + triangle = true; + case 'cube' + triangle = false; +end + +function initOptions(handles) + +global options + +% Data options +options.triangle = chooseDataset(handles); +options.nrCameras = str2num(get(handles.numCamEdit,'String')); +options.showImages = get(handles.showImagesCB,'Value'); + +% iSAM Options +options.hardConstraint = get(handles.hardConstraintCB,'Value'); +options.pointPriors = get(handles.pointPriorsCB,'Value'); +options.batchInitialization = get(handles.batchInitCB,'Value'); +%options.reorderInterval = str2num(get(handles.reorderIntervalEdit,'String')); +options.alwaysRelinearize = get(handles.alwaysRelinearizeCB,'Value'); + +% Display Options +options.saveDotFile = get(handles.saveGraphCB,'Value'); +options.printStats = get(handles.printStatsCB,'Value'); +options.drawInterval = str2num(get(handles.drawInterval,'String')); +options.cameraInterval = str2num(get(handles.cameraIntervalEdit,'String')); +options.drawTruePoses = get(handles.drawTruePosesCB,'Value'); +options.saveFigures = get(handles.saveFiguresCB,'Value'); +options.saveDotFiles = get(handles.saveGraphsCB,'Value'); + +%---------------------------------------------------------- +% Callback functions for GUI elements +%---------------------------------------------------------- + +% --- Executes during object creation, after setting all properties. +function dataset_CreateFcn(hObject, ~, handles) +% handles empty - handles not created until after all CreateFcns called +% Hint: popupmenu controls usually have a white background on Windows. +% See ISPC and COMPUTER. +if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor')) + set(hObject,'BackgroundColor','white'); +end + +% --- Executes on selection change in dataset. +function dataset_Callback(hObject, ~, handles) +% Hints: contents = cellstr(get(hObject,'String')) returns dataset contents as cell array +% contents{get(hObject,'Value')} returns selected item from dataset + + +% --- Executes during object creation, after setting all properties. +function numCamEdit_CreateFcn(hObject, ~, handles) +% Hint: edit controls usually have a white background on Windows. +if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor')) + set(hObject,'BackgroundColor','white'); +end + +function numCamEdit_Callback(hObject, ~, handles) +% Hints: get(hObject,'String') returns contents of numCamEdit as text +% str2double(get(hObject,'String')) returns contents of numCamEdit as a double + + +% --- Executes on button press in showImagesCB. +function showImagesCB_Callback(hObject, ~, handles) +% Hint: get(hObject,'Value') returns toggle state of showImagesCB + + +% --- Executes on button press in hardConstraintCB. +function hardConstraintCB_Callback(hObject, ~, handles) +% Hint: get(hObject,'Value') returns toggle state of hardConstraintCB + + +% --- Executes on button press in pointPriorsCB. +function pointPriorsCB_Callback(hObject, ~, handles) +% Hint: get(hObject,'Value') returns toggle state of pointPriorsCB + + +% --- Executes during object creation, after setting all properties. +function batchInitCB_CreateFcn(hObject, eventdata, handles) +set(hObject,'Value',1); + +% --- Executes on button press in batchInitCB. +function batchInitCB_Callback(hObject, ~, handles) +% Hint: get(hObject,'Value') returns toggle state of batchInitCB + + +% --- Executes on button press in alwaysRelinearizeCB. +function alwaysRelinearizeCB_Callback(hObject, ~, handles) +% Hint: get(hObject,'Value') returns toggle state of alwaysRelinearizeCB + + +% --- Executes during object creation, after setting all properties. +function reorderIntervalText_CreateFcn(hObject, ~, handles) +% Hint: edit controls usually have a white background on Windows. +if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor')) + set(hObject,'BackgroundColor','white'); +end + + +% --- Executes during object creation, after setting all properties. +function reorderIntervalEdit_CreateFcn(hObject, ~, handles) +% Hint: edit controls usually have a white background on Windows. +if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor')) + set(hObject,'BackgroundColor','white'); +end + + +% --- Executes during object creation, after setting all properties. +function drawInterval_CreateFcn(hObject, ~, handles) +% Hint: edit controls usually have a white background on Windows. +if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor')) + set(hObject,'BackgroundColor','white'); +end + + +function drawInterval_Callback(hObject, ~, handles) +% Hints: get(hObject,'String') returns contents of drawInterval as text +% str2double(get(hObject,'String')) returns contents of drawInterval as a double + + +function cameraIntervalEdit_Callback(hObject, ~, handles) +% Hints: get(hObject,'String') returns contents of cameraIntervalEdit as text +% str2double(get(hObject,'String')) returns contents of cameraIntervalEdit as a double + + +% --- Executes during object creation, after setting all properties. +function cameraIntervalEdit_CreateFcn(hObject, ~, handles) +% Hint: edit controls usually have a white background on Windows. +% See ISPC and COMPUTER. +if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor')) + set(hObject,'BackgroundColor','white'); +end + + +% --- Executes on button press in saveGraphCB. +function saveGraphCB_Callback(hObject, ~, handles) +% Hint: get(hObject,'Value') returns toggle state of saveGraphCB + + +% --- Executes on button press in printStatsCB. +function printStatsCB_Callback(hObject, ~, handles) +% Hint: get(hObject,'Value') returns toggle state of printStatsCB + + +% --- Executes on button press in drawTruePosesCB. +function drawTruePosesCB_Callback(hObject, ~, handles) +% Hint: get(hObject,'Value') returns toggle state of drawTruePosesCB + + +% --- Executes on button press in saveFiguresCB. +function saveFiguresCB_Callback(hObject, ~, handles) +% Hint: get(hObject,'Value') returns toggle state of saveFiguresCB + + +% --- Executes on button press in saveGraphsCB. +function saveGraphsCB_Callback(hObject, ~, handles) +% Hint: get(hObject,'Value') returns toggle state of saveGraphsCB + +% --- Executes on button press in intializeButton. +function intializeButton_Callback(hObject, ~, handles) + +global frame_i truth data noiseModels isam result nextPoseIndex options + +% initialize global options +initOptions(handles) + +% Generate Data +[data,truth] = gtsam.VisualISAMGenerateData(options); + +% Initialize and plot +[noiseModels,isam,result,nextPoseIndex] = gtsam.VisualISAMInitialize(data,truth,options); +cla +gtsam.VisualISAMPlot(truth, data, isam, result, options) +frame_i = 2; +showFramei(hObject, handles) + + +% --- Executes on button press in runButton. +function runButton_Callback(hObject, ~, handles) +global frame_i truth data noiseModels isam result nextPoseIndex options +while (frame_i +#include namespace simulated2D { diff --git a/gtsam/slam/simulated2D.h b/tests/simulated2D.h similarity index 81% rename from gtsam/slam/simulated2D.h rename to tests/simulated2D.h index ca9c0cf15..c5a62bba9 100644 --- a/gtsam/slam/simulated2D.h +++ b/tests/simulated2D.h @@ -30,12 +30,6 @@ namespace simulated2D { // Simulated2D robots have no orientation, just a position - /// Convenience function for constructing a pose key - inline Symbol PoseKey(Index j) { return Symbol('x', j); } - - /// Convenience function for constructing a landmark key - inline Symbol PointKey(Index j) { return Symbol('l', j); } - /** * Custom Values class that holds poses and points, mainly used as a convenience for MATLAB wrapper */ @@ -57,14 +51,14 @@ namespace simulated2D { } /// Insert a pose - void insertPose(Index j, const Point2& p) { - insert(PoseKey(j), p); + void insertPose(Key i, const Point2& p) { + insert(i, p); nrPoses_++; } /// Insert a point - void insertPoint(Index j, const Point2& p) { - insert(PointKey(j), p); + void insertPoint(Key j, const Point2& p) { + insert(j, p); nrPoints_++; } @@ -79,13 +73,13 @@ namespace simulated2D { } /// Return pose i - Point2 pose(Index j) const { - return at(PoseKey(j)); + Point2 pose(Key i) const { + return at(i); } /// Return point j - Point2 point(Index j) const { - return at(PointKey(j)); + Point2 point(Key j) const { + return at(j); } }; @@ -123,6 +117,7 @@ namespace simulated2D { class GenericPrior: public NoiseModelFactor1 { public: typedef NoiseModelFactor1 Base; ///< base class + typedef GenericPrior This; typedef boost::shared_ptr > shared_ptr; typedef VALUE Pose; ///< shortcut to Pose type @@ -138,11 +133,17 @@ namespace simulated2D { return (prior(x, H) - measured_).vector(); } + virtual ~GenericPrior() {} + + /// @return a deep copy of this factor + virtual gtsam::NonlinearFactor::shared_ptr clone() const { + return boost::static_pointer_cast( + gtsam::NonlinearFactor::shared_ptr(new This(*this))); } + private: /// Default constructor - GenericPrior() { - } + GenericPrior() { } /// Serialization function friend class boost::serialization::access; @@ -160,14 +161,15 @@ namespace simulated2D { class GenericOdometry: public NoiseModelFactor2 { public: typedef NoiseModelFactor2 Base; ///< base class + typedef GenericOdometry This; typedef boost::shared_ptr > shared_ptr; typedef VALUE Pose; ///< shortcut to Pose type Pose measured_; ///< odometry measurement /// Create odometry - GenericOdometry(const Pose& measured, const SharedNoiseModel& model, Key key1, Key key2) : - Base(model, key1, key2), measured_(measured) { + GenericOdometry(const Pose& measured, const SharedNoiseModel& model, Key i1, Key i2) : + Base(model, i1, i2), measured_(measured) { } /// Evaluate error and optionally return derivatives @@ -177,11 +179,17 @@ namespace simulated2D { return (odo(x1, x2, H1, H2) - measured_).vector(); } + virtual ~GenericOdometry() {} + + /// @return a deep copy of this factor + virtual gtsam::NonlinearFactor::shared_ptr clone() const { + return boost::static_pointer_cast( + gtsam::NonlinearFactor::shared_ptr(new This(*this))); } + private: /// Default constructor - GenericOdometry() { - } + GenericOdometry() { } /// Serialization function friend class boost::serialization::access; @@ -199,6 +207,7 @@ namespace simulated2D { class GenericMeasurement: public NoiseModelFactor2 { public: typedef NoiseModelFactor2 Base; ///< base class + typedef GenericMeasurement This; typedef boost::shared_ptr > shared_ptr; typedef POSE Pose; ///< shortcut to Pose type typedef LANDMARK Landmark; ///< shortcut to Landmark type @@ -206,8 +215,8 @@ namespace simulated2D { Landmark measured_; ///< Measurement /// Create measurement factor - GenericMeasurement(const Landmark& measured, const SharedNoiseModel& model, Key poseKey, Key landmarkKey) : - Base(model, poseKey, landmarkKey), measured_(measured) { + GenericMeasurement(const Landmark& measured, const SharedNoiseModel& model, Key i, Key j) : + Base(model, i, j), measured_(measured) { } /// Evaluate error and optionally return derivatives @@ -217,11 +226,17 @@ namespace simulated2D { return (mea(x1, x2, H1, H2) - measured_).vector(); } + virtual ~GenericMeasurement() {} + + /// @return a deep copy of this factor + virtual gtsam::NonlinearFactor::shared_ptr clone() const { + return boost::static_pointer_cast( + gtsam::NonlinearFactor::shared_ptr(new This(*this))); } + private: /// Default constructor - GenericMeasurement() { - } + GenericMeasurement() { } /// Serialization function friend class boost::serialization::access; diff --git a/gtsam/slam/simulated2DConstraints.h b/tests/simulated2DConstraints.h similarity index 83% rename from gtsam/slam/simulated2DConstraints.h rename to tests/simulated2DConstraints.h index b44062933..b9f2edcb5 100644 --- a/gtsam/slam/simulated2DConstraints.h +++ b/tests/simulated2DConstraints.h @@ -24,7 +24,7 @@ #include #include #include -#include +#include // \namespace @@ -53,11 +53,17 @@ namespace simulated2D { template struct ScalarCoordConstraint1: public BoundingConstraint1 { typedef BoundingConstraint1 Base; ///< Base class convenience typedef + typedef ScalarCoordConstraint1 This; ///< This class convenience typedef typedef boost::shared_ptr > shared_ptr; ///< boost::shared_ptr convenience typedef typedef VALUE Point; ///< Constrained variable type virtual ~ScalarCoordConstraint1() {} + /// @return a deep copy of this factor + virtual gtsam::NonlinearFactor::shared_ptr clone() const { + return boost::static_pointer_cast( + gtsam::NonlinearFactor::shared_ptr(new This(*this))); } + /** * Constructor for constraint * @param key is the label for the constrained variable @@ -66,8 +72,8 @@ namespace simulated2D { * @param mu is the penalty function gain */ ScalarCoordConstraint1(Key key, double c, - bool isGreaterThan, double mu = 1000.0) : - Base(key, c, isGreaterThan, mu) { + bool isGreaterThan, double mu = 1000.0) : + Base(key, c, isGreaterThan, mu) { } /** @@ -116,10 +122,16 @@ namespace simulated2D { template struct MaxDistanceConstraint : public BoundingConstraint2 { typedef BoundingConstraint2 Base; ///< Base class for factor + typedef MaxDistanceConstraint This; ///< This class for factor typedef VALUE Point; ///< Type of variable constrained virtual ~MaxDistanceConstraint() {} + /// @return a deep copy of this factor + virtual gtsam::NonlinearFactor::shared_ptr clone() const { + return boost::static_pointer_cast( + gtsam::NonlinearFactor::shared_ptr(new This(*this))); } + /** * Primary constructor for factor * @param key1 is the first variable key @@ -157,15 +169,21 @@ namespace simulated2D { */ template struct MinDistanceConstraint : public BoundingConstraint2 { - typedef BoundingConstraint2 Base; ///< Base class for factor - typedef POSE Pose; ///< Type of pose variable constrained - typedef POINT Point; ///< Type of point variable constrained + typedef BoundingConstraint2 Base; ///< Base class for factor + typedef MinDistanceConstraint This; ///< This class for factor + typedef POSE Pose; ///< Type of pose variable constrained + typedef POINT Point; ///< Type of point variable constrained - virtual ~MinDistanceConstraint() {} + virtual ~MinDistanceConstraint() {} - /** - * Primary constructor for factor - * @param key1 is the first variable key + /// @return a deep copy of this factor + virtual gtsam::NonlinearFactor::shared_ptr clone() const { + return boost::static_pointer_cast( + gtsam::NonlinearFactor::shared_ptr(new This(*this))); } + + /** + * Primary constructor for factor + * @param key1 is the first variable key * @param key2 is the second variable key * @param range_bound is the minimum range allowed between the variables * @param mu is the gain for the penalty function diff --git a/gtsam/slam/simulated2DOriented.cpp b/tests/simulated2DOriented.cpp similarity index 96% rename from gtsam/slam/simulated2DOriented.cpp rename to tests/simulated2DOriented.cpp index 947aaddc5..c7d1d8469 100644 --- a/gtsam/slam/simulated2DOriented.cpp +++ b/tests/simulated2DOriented.cpp @@ -15,7 +15,7 @@ * @author Frank Dellaert */ -#include +#include namespace simulated2DOriented { diff --git a/gtsam/slam/simulated2DOriented.h b/tests/simulated2DOriented.h similarity index 80% rename from gtsam/slam/simulated2DOriented.h rename to tests/simulated2DOriented.h index 242aab94b..ef8378fc5 100644 --- a/gtsam/slam/simulated2DOriented.h +++ b/tests/simulated2DOriented.h @@ -19,6 +19,7 @@ #pragma once #include +#include #include #include @@ -27,12 +28,6 @@ namespace simulated2DOriented { using namespace gtsam; - /// Convenience function for constructing a pose key - inline Symbol PoseKey(Index j) { return Symbol('x', j); } - - /// Convenience function for constructing a landmark key - inline Symbol PointKey(Index j) { return Symbol('l', j); } - /// Specialized Values structure with syntactic sugar for /// compatibility with matlab class Values: public gtsam::Values { @@ -40,21 +35,23 @@ namespace simulated2DOriented { public: Values() : nrPoses_(0), nrPoints_(0) {} - void insertPose(Index j, const Pose2& p) { - insert(PoseKey(j), p); + /// insert a pose + void insertPose(Key i, const Pose2& p) { + insert(i, p); nrPoses_++; } - void insertPoint(Index j, const Point2& p) { - insert(PointKey(j), p); + /// insert a landmark + void insertPoint(Key j, const Point2& p) { + insert(j, p); nrPoints_++; } - int nrPoses() const { return nrPoses_; } - int nrPoints() const { return nrPoints_; } + int nrPoses() const { return nrPoses_; } ///< nr of poses + int nrPoints() const { return nrPoints_; } ///< nr of landmarks - Pose2 pose(Index j) const { return at(PoseKey(j)); } - Point2 point(Index j) const { return at(PointKey(j)); } + Pose2 pose(Key i) const { return at(i); } ///< get a pose + Point2 point(Key j) const { return at(j); } ///< get a landmark }; //TODO:: point prior is not implemented right now @@ -102,6 +99,8 @@ namespace simulated2DOriented { struct GenericOdometry: public NoiseModelFactor2 { Pose2 measured_; ///< Between measurement for odometry factor + typedef GenericOdometry This; + /** * Creates an odometry factor between two poses */ @@ -110,6 +109,8 @@ namespace simulated2DOriented { NoiseModelFactor2(model, i1, i2), measured_(measured) { } + virtual ~GenericOdometry() {} + /// Evaluate error and optionally derivative Vector evaluateError(const VALUE& x1, const VALUE& x2, boost::optional H1 = boost::none, @@ -117,6 +118,11 @@ namespace simulated2DOriented { return measured_.localCoordinates(odo(x1, x2, H1, H2)); } + /// @return a deep copy of this factor + virtual gtsam::NonlinearFactor::shared_ptr clone() const { + return boost::static_pointer_cast( + gtsam::NonlinearFactor::shared_ptr(new This(*this))); } + }; typedef GenericOdometry Odometry; diff --git a/gtsam_unstable/slam/simulated3D.cpp b/tests/simulated3D.cpp similarity index 95% rename from gtsam_unstable/slam/simulated3D.cpp rename to tests/simulated3D.cpp index 933d1f194..980b6cabd 100644 --- a/gtsam_unstable/slam/simulated3D.cpp +++ b/tests/simulated3D.cpp @@ -15,7 +15,7 @@ * @author Alex Cunningham **/ -#include +#include namespace gtsam { diff --git a/gtsam_unstable/slam/simulated3D.h b/tests/simulated3D.h similarity index 89% rename from gtsam_unstable/slam/simulated3D.h rename to tests/simulated3D.h index 7b4dfce37..ef79991b8 100644 --- a/gtsam_unstable/slam/simulated3D.h +++ b/tests/simulated3D.h @@ -23,7 +23,6 @@ #include #include #include -#include // \namespace @@ -36,12 +35,6 @@ namespace simulated3D { * the simulated2D domain. */ - /// Convenience function for constructing a pose key - inline Symbol PoseKey(Index j) { return Symbol('x', j); } - - /// Convenience function for constructing a pose key - inline Symbol PointKey(Index j) { return Symbol('l', j); } - /** * Prior on a single pose */ @@ -105,9 +98,8 @@ struct Simulated3DMeasurement: public NoiseModelFactor2 { * @param poseKey is the pose key of the robot * @param pointKey is the point key for the landmark */ - Simulated3DMeasurement(const Point3& measured, const SharedNoiseModel& model, - Key poseKey, Key pointKey) : - NoiseModelFactor2(model, poseKey, pointKey), measured_(measured) {} + Simulated3DMeasurement(const Point3& measured, const SharedNoiseModel& model, Key i, Key j) : + NoiseModelFactor2(model, i, j), measured_(measured) {} /** * Error function with optional derivatives diff --git a/gtsam/slam/smallExample.cpp b/tests/smallExample.cpp similarity index 81% rename from gtsam/slam/smallExample.cpp rename to tests/smallExample.cpp index 170f3ef03..71c8269e9 100644 --- a/gtsam/slam/smallExample.cpp +++ b/tests/smallExample.cpp @@ -17,27 +17,27 @@ * @author Frank dellaert */ -#include -#include +#include +#include +#include +#include +#include +#include + +#include + #include #include +#include +#include + using namespace std; -#include -#include -#include - -// template definitions -#include -#include -#include - namespace gtsam { namespace example { - using simulated2D::PoseKey; - using simulated2D::PointKey; + using namespace gtsam::noiseModel; typedef boost::shared_ptr shared; @@ -49,8 +49,9 @@ namespace example { static const Index _l1_=0, _x1_=1, _x2_=2; static const Index _x_=0, _y_=1, _z_=2; - Key kx(size_t i) { return Symbol('x',i); } - Key kl(size_t i) { return Symbol('l',i); } + // Convenience for named keys + using symbol_shorthand::X; + using symbol_shorthand::L; /* ************************************************************************* */ boost::shared_ptr sharedNonlinearFactorGraph() { @@ -60,22 +61,22 @@ namespace example { // prior on x1 Point2 mu; - shared f1(new simulated2D::Prior(mu, sigma0_1, PoseKey(1))); + shared f1(new simulated2D::Prior(mu, sigma0_1, X(1))); nlfg->push_back(f1); // odometry between x1 and x2 Point2 z2(1.5, 0); - shared f2(new simulated2D::Odometry(z2, sigma0_1, PoseKey(1), PoseKey(2))); + shared f2(new simulated2D::Odometry(z2, sigma0_1, X(1), X(2))); nlfg->push_back(f2); // measurement between x1 and l1 Point2 z3(0, -1); - shared f3(new simulated2D::Measurement(z3, sigma0_2, PoseKey(1), PointKey(1))); + shared f3(new simulated2D::Measurement(z3, sigma0_2, X(1), L(1))); nlfg->push_back(f3); // measurement between x2 and l1 Point2 z4(-1.5, -1.); - shared f4(new simulated2D::Measurement(z4, sigma0_2, PoseKey(2), PointKey(1))); + shared f4(new simulated2D::Measurement(z4, sigma0_2, X(2), L(1))); nlfg->push_back(f4); return nlfg; @@ -89,9 +90,9 @@ namespace example { /* ************************************************************************* */ Values createValues() { Values c; - c.insert(PoseKey(1), Point2(0.0, 0.0)); - c.insert(PoseKey(2), Point2(1.5, 0.0)); - c.insert(PointKey(1), Point2(0.0, -1.0)); + c.insert(X(1), Point2(0.0, 0.0)); + c.insert(X(2), Point2(1.5, 0.0)); + c.insert(L(1), Point2(0.0, -1.0)); return c; } @@ -107,9 +108,9 @@ namespace example { /* ************************************************************************* */ boost::shared_ptr sharedNoisyValues() { boost::shared_ptr c(new Values); - c->insert(PoseKey(1), Point2(0.1, 0.1)); - c->insert(PoseKey(2), Point2(1.4, 0.2)); - c->insert(PointKey(1), Point2(0.1, -1.1)); + c->insert(X(1), Point2(0.1, 0.1)); + c->insert(X(2), Point2(1.4, 0.2)); + c->insert(L(1), Point2(0.1, -1.1)); return c; } @@ -121,41 +122,41 @@ namespace example { /* ************************************************************************* */ VectorValues createCorrectDelta(const Ordering& ordering) { VectorValues c(vector(3,2)); - c[ordering[kl(1)]] = Vector_(2, -0.1, 0.1); - c[ordering[kx(1)]] = Vector_(2, -0.1, -0.1); - c[ordering[kx(2)]] = Vector_(2, 0.1, -0.2); + c[ordering[L(1)]] = Vector_(2, -0.1, 0.1); + c[ordering[X(1)]] = Vector_(2, -0.1, -0.1); + c[ordering[X(2)]] = Vector_(2, 0.1, -0.2); return c; } /* ************************************************************************* */ VectorValues createZeroDelta(const Ordering& ordering) { VectorValues c(vector(3,2)); - c[ordering[kl(1)]] = zero(2); - c[ordering[kx(1)]] = zero(2); - c[ordering[kx(2)]] = zero(2); + c[ordering[L(1)]] = zero(2); + c[ordering[X(1)]] = zero(2); + c[ordering[X(2)]] = zero(2); return c; } /* ************************************************************************* */ - FactorGraph createGaussianFactorGraph(const Ordering& ordering) { + GaussianFactorGraph createGaussianFactorGraph(const Ordering& ordering) { // Create empty graph - GaussianFactorGraph fg; + GaussianFactorGraph fg; SharedDiagonal unit2 = noiseModel::Unit::Create(2); // linearized prior on x1: c[_x1_]+x1=0 i.e. x1=-c[_x1_] - fg.add(ordering[kx(1)], 10*eye(2), -1.0*ones(2), unit2); + fg.push_back(boost::make_shared(ordering[X(1)], 10*eye(2), -1.0*ones(2), unit2)); // odometry between x1 and x2: x2-x1=[0.2;-0.1] - fg.add(ordering[kx(1)], -10*eye(2),ordering[kx(2)], 10*eye(2), Vector_(2, 2.0, -1.0), unit2); + fg.push_back(boost::make_shared(ordering[X(1)], -10*eye(2),ordering[X(2)], 10*eye(2), Vector_(2, 2.0, -1.0), unit2)); // measurement between x1 and l1: l1-x1=[0.0;0.2] - fg.add(ordering[kx(1)], -5*eye(2), ordering[kl(1)], 5*eye(2), Vector_(2, 0.0, 1.0), unit2); + fg.push_back(boost::make_shared(ordering[X(1)], -5*eye(2), ordering[L(1)], 5*eye(2), Vector_(2, 0.0, 1.0), unit2)); // measurement between x2 and l1: l1-x2=[-0.2;0.3] - fg.add(ordering[kx(2)], -5*eye(2), ordering[kl(1)], 5*eye(2), Vector_(2, -1.0, 1.5), unit2); + fg.push_back(boost::make_shared(ordering[X(2)], -5*eye(2), ordering[L(1)], 5*eye(2), Vector_(2, -1.0, 1.5), unit2)); - return *fg.dynamicCastFactors >(); + return fg; } /* ************************************************************************* */ @@ -221,7 +222,7 @@ namespace example { Vector z = Vector_(2, 1.0, 0.0); double sigma = 0.1; boost::shared_ptr factor( - new smallOptimize::UnaryFactor(z, noiseModel::Isotropic::Sigma(2,sigma), PoseKey(1))); + new smallOptimize::UnaryFactor(z, noiseModel::Isotropic::Sigma(2,sigma), X(1))); fg->push_back(factor); return fg; } @@ -239,23 +240,23 @@ namespace example { // prior on x1 Point2 x1(1.0, 0.0); - shared prior(new simulated2D::Prior(x1, sigma1_0, PoseKey(1))); + shared prior(new simulated2D::Prior(x1, sigma1_0, X(1))); nlfg.push_back(prior); - poses.insert(simulated2D::PoseKey(1), x1); + poses.insert(X(1), x1); for (int t = 2; t <= T; t++) { // odometry between x_t and x_{t-1} Point2 odo(1.0, 0.0); - shared odometry(new simulated2D::Odometry(odo, sigma1_0, PoseKey(t - 1), PoseKey(t))); + shared odometry(new simulated2D::Odometry(odo, sigma1_0, X(t - 1), X(t))); nlfg.push_back(odometry); // measurement on x_t is like perfect GPS Point2 xt(t, 0); - shared measurement(new simulated2D::Prior(xt, sigma1_0, PoseKey(t))); + shared measurement(new simulated2D::Prior(xt, sigma1_0, X(t))); nlfg.push_back(measurement); // initial estimate - poses.insert(PoseKey(t), xt); + poses.insert(X(t), xt); } return make_pair(nlfg, poses); @@ -272,7 +273,7 @@ namespace example { } /* ************************************************************************* */ - FactorGraph createSimpleConstraintGraph() { + GaussianFactorGraph createSimpleConstraintGraph() { // create unary factor // prior on _x_, mean = [1,-1], sigma=0.1 Matrix Ax = eye(2); @@ -292,7 +293,7 @@ namespace example { constraintModel)); // construct the graph - FactorGraph fg; + GaussianFactorGraph fg; fg.push_back(f1); fg.push_back(f2); @@ -309,7 +310,7 @@ namespace example { } /* ************************************************************************* */ - FactorGraph createSingleConstraintGraph() { + GaussianFactorGraph createSingleConstraintGraph() { // create unary factor // prior on _x_, mean = [1,-1], sigma=0.1 Matrix Ax = eye(2); @@ -334,7 +335,7 @@ namespace example { constraintModel)); // construct the graph - FactorGraph fg; + GaussianFactorGraph fg; fg.push_back(f1); fg.push_back(f2); @@ -350,7 +351,7 @@ namespace example { } /* ************************************************************************* */ - FactorGraph createMultiConstraintGraph() { + GaussianFactorGraph createMultiConstraintGraph() { // unary factor 1 Matrix A = eye(2); Vector b = Vector_(2, -2.0, 2.0); @@ -395,7 +396,7 @@ namespace example { constraintModel)); // construct the graph - FactorGraph fg; + GaussianFactorGraph fg; fg.push_back(lf1); fg.push_back(lc1); fg.push_back(lc2); @@ -416,24 +417,24 @@ namespace example { /* ************************************************************************* */ // Create key for simulated planar graph Symbol key(int x, int y) { - return PoseKey(1000*x+y); + return X(1000*x+y); } /* ************************************************************************* */ - boost::tuple, Ordering, VectorValues> planarGraph(size_t N) { + boost::tuple planarGraph(size_t N) { // create empty graph NonlinearFactorGraph nlfg; // Create almost hard constraint on x11, sigma=0 will work for PCG not for normal - shared constraint(new simulated2D::Prior(Point2(1.0, 1.0), sharedSigma(2,1e-3), key(1,1))); + shared constraint(new simulated2D::Prior(Point2(1.0, 1.0), Isotropic::Sigma(2,1e-3), key(1,1))); nlfg.push_back(constraint); // Create horizontal constraints, 1...N*(N-1) Point2 z1(1.0, 0.0); // move right for (size_t x = 1; x < N; x++) for (size_t y = 1; y <= N; y++) { - shared f(new simulated2D::Odometry(z1, sharedSigma(2,0.01), key(x, y), key(x + 1, y))); + shared f(new simulated2D::Odometry(z1, Isotropic::Sigma(2,0.01), key(x, y), key(x + 1, y))); nlfg.push_back(f); } @@ -441,7 +442,7 @@ namespace example { Point2 z2(0.0, 1.0); // move up for (size_t x = 1; x <= N; x++) for (size_t y = 1; y < N; y++) { - shared f(new simulated2D::Odometry(z2, sharedSigma(2,0.01), key(x, y), key(x, y + 1))); + shared f(new simulated2D::Odometry(z2, Isotropic::Sigma(2,0.01), key(x, y), key(x, y + 1))); nlfg.push_back(f); } @@ -457,7 +458,8 @@ namespace example { xtrue[ordering[key(x, y)]] = Point2(x,y).vector(); // linearize around zero - return boost::make_tuple(*nlfg.linearize(zeros, ordering), ordering, xtrue); + boost::shared_ptr gfg = nlfg.linearize(zeros, ordering); + return boost::make_tuple(*gfg, xtrue); } /* ************************************************************************* */ @@ -470,9 +472,9 @@ namespace example { } /* ************************************************************************* */ - pair, FactorGraph > splitOffPlanarTree(size_t N, - const FactorGraph& original) { - FactorGraph T, C; + pair splitOffPlanarTree(size_t N, + const GaussianFactorGraph& original) { + GaussianFactorGraph T, C; // Add the x11 constraint to the tree T.push_back(original[0]); diff --git a/gtsam/slam/smallExample.h b/tests/smallExample.h similarity index 87% rename from gtsam/slam/smallExample.h rename to tests/smallExample.h index 96dcbaf09..f87847f24 100644 --- a/gtsam/slam/smallExample.h +++ b/tests/smallExample.h @@ -21,9 +21,9 @@ #pragma once -#include +#include #include -#include +#include namespace gtsam { namespace example { @@ -65,7 +65,7 @@ namespace gtsam { * create a linear factor graph * The non-linear graph above evaluated at NoisyValues */ - FactorGraph createGaussianFactorGraph(const Ordering& ordering); + GaussianFactorGraph createGaussianFactorGraph(const Ordering& ordering); /** * create small Chordal Bayes Net x <- y @@ -99,21 +99,21 @@ namespace gtsam { * Creates a simple constrained graph with one linear factor and * one binary equality constraint that sets x = y */ - FactorGraph createSimpleConstraintGraph(); + GaussianFactorGraph createSimpleConstraintGraph(); VectorValues createSimpleConstraintValues(); /** * Creates a simple constrained graph with one linear factor and * one binary constraint. */ - FactorGraph createSingleConstraintGraph(); + GaussianFactorGraph createSingleConstraintGraph(); VectorValues createSingleConstraintValues(); /** * Creates a constrained graph with a linear factor and two * binary constraints that share a node */ - FactorGraph createMultiConstraintGraph(); + GaussianFactorGraph createMultiConstraintGraph(); VectorValues createMultiConstraintValues(); /* ******************************************************* */ @@ -129,7 +129,7 @@ namespace gtsam { * -x11-x21-x31 * with x11 clamped at (1,1), and others related by 2D odometry. */ - boost::tuple, Ordering, VectorValues> planarGraph(size_t N); + boost::tuple planarGraph(size_t N); /* * Create canonical ordering for planar graph that also works for tree @@ -146,8 +146,8 @@ namespace gtsam { * | * -x11-x21-x31 */ - std::pair, FactorGraph > splitOffPlanarTree( - size_t N, const FactorGraph& original); + std::pair splitOffPlanarTree( + size_t N, const GaussianFactorGraph& original); } // example } // gtsam diff --git a/tests/testBoundingConstraint.cpp b/tests/testBoundingConstraint.cpp index e1b685fc8..128251a23 100644 --- a/tests/testBoundingConstraint.cpp +++ b/tests/testBoundingConstraint.cpp @@ -15,12 +15,13 @@ * @author Alex Cunningham */ -#include - -#include +#include +#include #include #include +#include + namespace iq2D = simulated2D::inequality_constraints; using namespace std; using namespace gtsam; @@ -32,7 +33,7 @@ SharedDiagonal soft_model2_alt = noiseModel::Isotropic::Sigma(2, 0.1); SharedDiagonal hard_model1 = noiseModel::Constrained::All(1); // some simple inequality constraints -Symbol key(simulated2D::PoseKey(1)); +gtsam::Key key = 1; double mu = 10.0; // greater than iq2D::PoseXInequality constraint1(key, 1.0, true, mu); @@ -168,23 +169,22 @@ TEST( testBoundingConstraint, unary_simple_optimization2) { Point2 start_pt(2.0, 3.0); NonlinearFactorGraph graph; - Symbol x1('x',1); - graph.add(iq2D::PoseXInequality(x1, 1.0, false)); - graph.add(iq2D::PoseYInequality(x1, 2.0, false)); - graph.add(simulated2D::Prior(start_pt, soft_model2, x1)); + graph.add(iq2D::PoseXInequality(key, 1.0, false)); + graph.add(iq2D::PoseYInequality(key, 2.0, false)); + graph.add(simulated2D::Prior(start_pt, soft_model2, key)); Values initValues; - initValues.insert(x1, start_pt); + initValues.insert(key, start_pt); Values actual = LevenbergMarquardtOptimizer(graph, initValues).optimize(); Values expected; - expected.insert(x1, goal_pt); + expected.insert(key, goal_pt); CHECK(assert_equal(expected, actual, tol)); } /* ************************************************************************* */ TEST( testBoundingConstraint, MaxDistance_basics) { - Symbol key1('x',1), key2('x',2); + gtsam::Key key1 = 1, key2 = 2; Point2 pt1, pt2(1.0, 0.0), pt3(2.0, 0.0), pt4(3.0, 0.0); iq2D::PoseMaxDistConstraint rangeBound(key1, key2, 2.0, mu); EXPECT_DOUBLES_EQUAL(2.0, rangeBound.threshold(), tol); diff --git a/tests/testDoglegOptimizer.cpp b/tests/testDoglegOptimizer.cpp index b16ac0cdc..6b03b572b 100644 --- a/tests/testDoglegOptimizer.cpp +++ b/tests/testDoglegOptimizer.cpp @@ -15,15 +15,16 @@ * @author Richard Roberts */ -#include -#include -#include +#include +#include +#include #include #include #include -#include -#include -#include +#include +#include + +#include #include #include // for 'list_of()' @@ -31,7 +32,10 @@ using namespace std; using namespace gtsam; -using boost::shared_ptr; + +// Convenience for named keys +using symbol_shorthand::X; +using symbol_shorthand::L; /* ************************************************************************* */ double computeError(const GaussianBayesNet& gbn, const LieVector& values) { @@ -92,7 +96,7 @@ TEST(DoglegOptimizer, ComputeSteepestDescentPoint) { gradientValues.vector() = gradient; // Compute the gradient using dense matrices - Matrix augmentedHessian = GaussianFactorGraph(gbn).denseHessian(); + Matrix augmentedHessian = GaussianFactorGraph(gbn).augmentedHessian(); LONGS_EQUAL(11, augmentedHessian.cols()); VectorValues denseMatrixGradient = *allocateVectorValues(gbn); denseMatrixGradient.vector() = -augmentedHessian.col(10).segment(0,10); @@ -196,7 +200,7 @@ TEST(DoglegOptimizer, BT_BN_equivalency) { GaussianFactorGraph expected(gbn); GaussianFactorGraph actual(bt); - EXPECT(assert_equal(expected.denseJacobian(), actual.denseJacobian())); + EXPECT(assert_equal(expected.augmentedHessian(), actual.augmentedHessian())); } /* ************************************************************************* */ @@ -272,7 +276,7 @@ TEST(DoglegOptimizer, ComputeSteepestDescentPointBT) { gradientValues.vector() = gradient; // Compute the gradient using dense matrices - Matrix augmentedHessian = GaussianFactorGraph(bt).denseHessian(); + Matrix augmentedHessian = GaussianFactorGraph(bt).augmentedHessian(); LONGS_EQUAL(11, augmentedHessian.cols()); VectorValues denseMatrixGradient = *allocateVectorValues(bt); denseMatrixGradient.vector() = -augmentedHessian.col(10).segment(0,10); @@ -381,17 +385,17 @@ TEST(DoglegOptimizer, ComputeDoglegPoint) { /* ************************************************************************* */ TEST(DoglegOptimizer, Iterate) { // really non-linear factor graph - shared_ptr fg(new example::Graph( + boost::shared_ptr fg(new example::Graph( example::createReallyNonlinearFactorGraph())); // config far from minimum Point2 x0(3,0); boost::shared_ptr config(new Values); - config->insert(simulated2D::PoseKey(1), x0); + config->insert(X(1), x0); // ordering - shared_ptr ord(new Ordering()); - ord->push_back(simulated2D::PoseKey(1)); + boost::shared_ptr ord(new Ordering()); + ord->push_back(X(1)); double Delta = 1.0; for(size_t it=0; it<10; ++it) { diff --git a/tests/testExtendedKalmanFilter.cpp b/tests/testExtendedKalmanFilter.cpp index d9e5643a4..c19bcd4c9 100644 --- a/tests/testExtendedKalmanFilter.cpp +++ b/tests/testExtendedKalmanFilter.cpp @@ -14,16 +14,21 @@ * @author Stephen Williams */ -#include - #include #include #include #include +#include #include +#include + using namespace gtsam; +// Convenience for named keys +using symbol_shorthand::X; +using symbol_shorthand::L; + /* ************************************************************************* */ TEST( ExtendedKalmanFilter, linear ) { @@ -409,11 +414,11 @@ TEST( ExtendedKalmanFilter, nonlinear ) { Point2 x_predict, x_update; for(unsigned int i = 0; i < 10; ++i){ // Create motion factor - NonlinearMotionModel motionFactor(Symbol('x',i), Symbol('x',i+1)); + NonlinearMotionModel motionFactor(X(i), X(i+1)); x_predict = ekf.predict(motionFactor); // Create a measurement factor - NonlinearMeasurementModel measurementFactor(Symbol('x',i+1), Vector_(1, z[i])); + NonlinearMeasurementModel measurementFactor(X(i+1), Vector_(1, z[i])); x_update = ekf.update(measurementFactor); EXPECT(assert_equal(expected_predict[i],x_predict, 1e-6)); diff --git a/tests/testGaussianBayesNet.cpp b/tests/testGaussianBayesNet.cpp index 8444dacc3..60af529ec 100644 --- a/tests/testGaussianBayesNet.cpp +++ b/tests/testGaussianBayesNet.cpp @@ -29,7 +29,7 @@ using namespace boost::assign; #include #include #include -#include +#include using namespace std; using namespace gtsam; diff --git a/tests/testGaussianFactor.cpp b/tests/testGaussianFactor.cpp index 2cfb7a076..f5419b7ff 100644 --- a/tests/testGaussianFactor.cpp +++ b/tests/testGaussianFactor.cpp @@ -16,7 +16,14 @@ * @author Frank Dellaert **/ -#include +#include +#include +#include +#include +#include +#include + +#include #include #include // for operator += @@ -24,28 +31,25 @@ #include // for insert using namespace boost::assign; -#include - -#include -#include -#include -#include -#include +#include using namespace std; using namespace gtsam; -using namespace example; -using namespace boost; + +// Convenience for named keys +using symbol_shorthand::X; +using symbol_shorthand::L; static SharedDiagonal - sigma0_1 = sharedSigma(2,0.1), sigma_02 = sharedSigma(2,0.2), + sigma0_1 = noiseModel::Isotropic::Sigma(2,0.1), sigma_02 = noiseModel::Isotropic::Sigma(2,0.2), constraintModel = noiseModel::Constrained::All(2); -const Key kx1 = Symbol('x',1), kx2 = Symbol('x',2), kl1 = Symbol('l',1); +//const Key kx1 = X(1), kx2 = X(2), kl1 = L(1); // FIXME: throws exception /* ************************************************************************* */ TEST( GaussianFactor, linearFactor ) { + const Key kx1 = X(1), kx2 = X(2), kl1 = L(1); Ordering ordering; ordering += kx1,kx2,kl1; Matrix I = eye(2); @@ -53,48 +57,23 @@ TEST( GaussianFactor, linearFactor ) JacobianFactor expected(ordering[kx1], -10*I,ordering[kx2], 10*I, b, noiseModel::Unit::Create(2)); // create a small linear factor graph - FactorGraph fg = createGaussianFactorGraph(ordering); + GaussianFactorGraph fg = example::createGaussianFactorGraph(ordering); // get the factor kf2 from the factor graph - JacobianFactor::shared_ptr lf = fg[1]; + JacobianFactor::shared_ptr lf = + boost::dynamic_pointer_cast(fg[1]); // check if the two factors are the same EXPECT(assert_equal(expected,*lf)); } -///* ************************************************************************* */ -// SL-FIX TEST( GaussianFactor, keys ) -//{ -// // get the factor kf2 from the small linear factor graph -// Ordering ordering; ordering += kx1,kx2,kl1; -// GaussianFactorGraph fg = createGaussianFactorGraph(ordering); -// GaussianFactor::shared_ptr lf = fg[1]; -// list expected; -// expected.push_back(kx1); -// expected.push_back(kx2); -// EXPECT(lf->keys() == expected); -//} - -///* ************************************************************************* */ -// SL-FIX TEST( GaussianFactor, dimensions ) -//{ -// // get the factor kf2 from the small linear factor graph -// Ordering ordering; ordering += kx1,kx2,kl1; -// GaussianFactorGraph fg = createGaussianFactorGraph(ordering); -// -// // Check a single factor -// Dimensions expected; -// insert(expected)(kx1, 2)(kx2, 2); -// Dimensions actual = fg[1]->dimensions(); -// EXPECT(expected==actual); -//} - /* ************************************************************************* */ TEST( GaussianFactor, getDim ) { + const Key kx1 = X(1), kx2 = X(2), kl1 = L(1); // get a factor Ordering ordering; ordering += kx1,kx2,kl1; - GaussianFactorGraph fg = createGaussianFactorGraph(ordering); + GaussianFactorGraph fg = example::createGaussianFactorGraph(ordering); GaussianFactor::shared_ptr factor = fg[0]; // get the size of a variable @@ -105,74 +84,19 @@ TEST( GaussianFactor, getDim ) EXPECT_LONGS_EQUAL(expected, actual); } -///* ************************************************************************* */ -// SL-FIX TEST( GaussianFactor, combine ) -//{ -// // create a small linear factor graph -// Ordering ordering; ordering += kx1,kx2,kl1; -// GaussianFactorGraph fg = createGaussianFactorGraph(ordering); -// -// // get two factors from it and insert the factors into a vector -// vector lfg; -// lfg.push_back(fg[4 - 1]); -// lfg.push_back(fg[2 - 1]); -// -// // combine in a factor -// GaussianFactor combined(lfg); -// -// // sigmas -// double sigma2 = 0.1; -// double sigma4 = 0.2; -// Vector sigmas = Vector_(4, sigma4, sigma4, sigma2, sigma2); -// -// // the expected combined linear factor -// Matrix Ax2 = Matrix_(4, 2, // x2 -// -5., 0., -// +0., -5., -// 10., 0., -// +0., 10.); -// -// Matrix Al1 = Matrix_(4, 2, // l1 -// 5., 0., -// 0., 5., -// 0., 0., -// 0., 0.); -// -// Matrix Ax1 = Matrix_(4, 2, // x1 -// 0.00, 0., // f4 -// 0.00, 0., // f4 -// -10., 0., // f2 -// 0.00, -10. // f2 -// ); -// -// // the RHS -// Vector b2(4); -// b2(0) = -1.0; -// b2(1) = 1.5; -// b2(2) = 2.0; -// b2(3) = -1.0; -// -// // use general constructor for making arbitrary factors -// vector > meas; -// meas.push_back(make_pair(kx2, Ax2)); -// meas.push_back(make_pair(kl1, Al1)); -// meas.push_back(make_pair(kx1, Ax1)); -// GaussianFactor expected(meas, b2, noiseModel::Diagonal::Sigmas(ones(4))); -// EXPECT(assert_equal(expected,combined)); -//} - /* ************************************************************************* */ TEST( GaussianFactor, error ) { + const Key kx1 = X(1), kx2 = X(2), kl1 = L(1); // create a small linear factor graph Ordering ordering; ordering += kx1,kx2,kl1; - GaussianFactorGraph fg = createGaussianFactorGraph(ordering); + GaussianFactorGraph fg = example::createGaussianFactorGraph(ordering); // get the first factor from the factor graph GaussianFactor::shared_ptr lf = fg[0]; // check the error of the first factor with noisy config - VectorValues cfg = createZeroDelta(ordering); + VectorValues cfg = example::createZeroDelta(ordering); // calculate the error from the factor kf1 // note the error is the same as in testNonlinearFactor @@ -180,53 +104,13 @@ TEST( GaussianFactor, error ) DOUBLES_EQUAL( 1.0, actual, 0.00000001 ); } -///* ************************************************************************* */ -// SL-FIX TEST( GaussianFactor, eliminate ) -//{ -// // create a small linear factor graph -// Ordering ordering; ordering += kx1,kx2,kl1; -// GaussianFactorGraph fg = createGaussianFactorGraph(ordering); -// -// // get two factors from it and insert the factors into a vector -// vector lfg; -// lfg.push_back(fg[4 - 1]); -// lfg.push_back(fg[2 - 1]); -// -// // combine in a factor -// GaussianFactor combined(lfg); -// -// // eliminate the combined factor -// GaussianConditional::shared_ptr actualCG; -// GaussianFactor::shared_ptr actualLF; -// boost::tie(actualCG,actualLF) = combined.eliminate(kx2); -// -// // create expected Conditional Gaussian -// Matrix I = eye(2)*sqrt(125.0); -// Matrix R11 = I, S12 = -0.2*I, S13 = -0.8*I; -// Vector d = I*Vector_(2,0.2,-0.14); -// -// // Check the conditional Gaussian -// GaussianConditional -// expectedCG(kx2, d, R11, kl1, S12, kx1, S13, repeat(2, 1.0)); -// -// // the expected linear factor -// I = eye(2)/0.2236; -// Matrix Bl1 = I, Bx1 = -I; -// Vector b1 = I*Vector_(2,0.0,0.2); -// -// GaussianFactor expectedLF(kl1, Bl1, kx1, Bx1, b1, repeat(2,1.0)); -// -// // check if the result matches -// EXPECT(assert_equal(expectedCG,*actualCG,1e-3)); -// EXPECT(assert_equal(expectedLF,*actualLF,1e-3)); -//} - /* ************************************************************************* */ TEST( GaussianFactor, matrix ) { + const Key kx1 = X(1), kx2 = X(2), kl1 = L(1); // create a small linear factor graph Ordering ordering; ordering += kx1,kx2,kl1; - FactorGraph fg = createGaussianFactorGraph(ordering); + GaussianFactorGraph fg = example::createGaussianFactorGraph(ordering); // get the factor kf2 from the factor graph //GaussianFactor::shared_ptr lf = fg[1]; // NOTE: using the older version @@ -263,7 +147,7 @@ TEST( GaussianFactor, matrix ) EQUALITY(b_act2,b2); // Ensure that whitening is consistent - shared_ptr model = lf->get_model(); + boost::shared_ptr model = lf->get_model(); model->WhitenSystem(A_act2, b_act2); EQUALITY(A_act1, A_act2); EQUALITY(b_act1, b_act2); @@ -272,9 +156,10 @@ TEST( GaussianFactor, matrix ) /* ************************************************************************* */ TEST( GaussianFactor, matrix_aug ) { + const Key kx1 = X(1), kx2 = X(2), kl1 = L(1); // create a small linear factor graph Ordering ordering; ordering += kx1,kx2,kl1; - FactorGraph fg = createGaussianFactorGraph(ordering); + GaussianFactorGraph fg = example::createGaussianFactorGraph(ordering); // get the factor kf2 from the factor graph //GaussianFactor::shared_ptr lf = fg[1]; @@ -307,7 +192,7 @@ TEST( GaussianFactor, matrix_aug ) EQUALITY(Ab_act2,Ab2); // Ensure that whitening is consistent - shared_ptr model = lf->get_model(); + boost::shared_ptr model = lf->get_model(); model->WhitenInPlace(Ab_act1); EQUALITY(Ab_act1, Ab_act2); } @@ -320,72 +205,13 @@ void print(const list& i) { cout << endl; } -///* ************************************************************************* */ -// SL-FIX TEST( GaussianFactor, sparse ) -//{ -// // create a small linear factor graph -// Ordering ordering; ordering += kx1,kx2,kl1; -// GaussianFactorGraph fg = createGaussianFactorGraph(ordering); -// -// // get the factor kf2 from the factor graph -// GaussianFactor::shared_ptr lf = fg[1]; -// -// // render with a given ordering -// Ordering ord; -// ord += kx1,kx2; -// -// list i,j; -// list s; -// boost::tie(i,j,s) = lf->sparse(fg.columnIndices(ord)); -// -// list i1,j1; -// i1 += 1,2,1,2; -// j1 += 1,2,3,4; -// -// list s1; -// s1 += -10,-10,10,10; -// -// EXPECT(i==i1); -// EXPECT(j==j1); -// EXPECT(s==s1); -//} - -///* ************************************************************************* */ -// SL-FIX TEST( GaussianFactor, sparse2 ) -//{ -// // create a small linear factor graph -// Ordering ordering; ordering += kx1,kx2,kl1; -// GaussianFactorGraph fg = createGaussianFactorGraph(ordering); -// -// // get the factor kf2 from the factor graph -// GaussianFactor::shared_ptr lf = fg[1]; -// -// // render with a given ordering -// Ordering ord; -// ord += kx2,kl1,kx1; -// -// list i,j; -// list s; -// boost::tie(i,j,s) = lf->sparse(fg.columnIndices(ord)); -// -// list i1,j1; -// i1 += 1,2,1,2; -// j1 += 5,6,1,2; -// -// list s1; -// s1 += -10,-10,10,10; -// -// EXPECT(i==i1); -// EXPECT(j==j1); -// EXPECT(s==s1); -//} - /* ************************************************************************* */ TEST( GaussianFactor, size ) { // create a linear factor graph + const Key kx1 = X(1), kx2 = X(2), kl1 = L(1); Ordering ordering; ordering += kx1,kx2,kl1; - GaussianFactorGraph fg = createGaussianFactorGraph(ordering); + GaussianFactorGraph fg = example::createGaussianFactorGraph(ordering); // get some factors from the graph boost::shared_ptr factor1 = fg[0]; diff --git a/tests/testGaussianFactorGraphB.cpp b/tests/testGaussianFactorGraphB.cpp index 2e68200f5..306c64fb7 100644 --- a/tests/testGaussianFactorGraphB.cpp +++ b/tests/testGaussianFactorGraphB.cpp @@ -15,9 +15,17 @@ * @author Christian Potthast **/ -#include -#include -using namespace std; +#include +#include +#include +#include +#include +#include +#include +#include +#include + +#include #include #include @@ -26,192 +34,62 @@ using namespace std; #include // for operator += using namespace boost::assign; -#include - -#include -#include -#include -#include -#include -#include -#include +#include +#include +using namespace std; using namespace gtsam; using namespace example; double tol=1e-5; -Key kx(size_t i) { return Symbol('x',i); } -Key kl(size_t i) { return Symbol('l',i); } +using symbol_shorthand::X; +using symbol_shorthand::L; /* ************************************************************************* */ TEST( GaussianFactorGraph, equals ) { - Ordering ordering; ordering += kx(1),kx(2),kl(1); + Ordering ordering; ordering += X(1),X(2),L(1); GaussianFactorGraph fg = createGaussianFactorGraph(ordering); GaussianFactorGraph fg2 = createGaussianFactorGraph(ordering); EXPECT(fg.equals(fg2)); } /* ************************************************************************* */ -//TEST( GaussianFactorGraph, error ) { -// Ordering ordering; ordering += kx(1),kx(2),kl(1); -// FactorGraph fg = createGaussianFactorGraph(ordering); -// VectorValues cfg = createZeroDelta(ordering); -// -// // note the error is the same as in testNonlinearFactorGraph as a -// // zero delta config in the linear graph is equivalent to noisy in -// // non-linear, which is really linear under the hood -// double actual = fg.error(cfg); -// DOUBLES_EQUAL( 5.625, actual, 1e-9 ); -//} +TEST( GaussianFactorGraph, error ) { + Ordering ordering; ordering += X(1),X(2),L(1); + GaussianFactorGraph fg = createGaussianFactorGraph(ordering); + VectorValues cfg = createZeroDelta(ordering); -/* ************************************************************************* */ -/* unit test for find seperator */ -/* ************************************************************************* */ -// SL-NEEDED? TEST( GaussianFactorGraph, find_separator ) -//{ -// GaussianFactorGraph fg = createGaussianFactorGraph(); -// -// set separator = fg.find_separator(kx(2)); -// set expected; -// expected.insert(kx(1)); -// expected.insert(kl(1)); -// -// EXPECT(separator.size()==expected.size()); -// set::iterator it1 = separator.begin(), it2 = expected.begin(); -// for(; it1!=separator.end(); it1++, it2++) -// EXPECT(*it1 == *it2); -//} - -///* ************************************************************************* */ -// SL-FIX TEST( GaussianFactorGraph, combine_factors_x1 ) -//{ -// // create a small example for a linear factor graph -// GaussianFactorGraph fg = createGaussianFactorGraph(); -// -// // combine all factors -// GaussianFactor::shared_ptr actual = removeAndCombineFactors(fg,kx(1)); -// -// // the expected linear factor -// Matrix Al1 = Matrix_(6,2, -// 0., 0., -// 0., 0., -// 0., 0., -// 0., 0., -// 5., 0., -// 0., 5. -// ); -// -// Matrix Ax1 = Matrix_(6,2, -// 10., 0., -// 0., 10., -// -10., 0., -// 0.,-10., -// -5., 0., -// 0.,-5. -// ); -// -// Matrix Ax2 = Matrix_(6,2, -// 0., 0., -// 0., 0., -// 10., 0., -// 0., 10., -// 0., 0., -// 0., 0. -// ); -// -// // the expected RHS vector -// Vector b(6); -// b(0) = -1; -// b(1) = -1; -// b(2) = 2; -// b(3) = -1; -// b(4) = 0; -// b(5) = 1; -// -// vector > meas; -// meas.push_back(make_pair(kl(1), Al1)); -// meas.push_back(make_pair(kx(1), Ax1)); -// meas.push_back(make_pair(kx(2), Ax2)); -// GaussianFactor expected(meas, b, ones(6)); -// //GaussianFactor expected(kl(1), Al1, kx(1), Ax1, kx(2), Ax2, b); -// -// // check if the two factors are the same -// EXPECT(assert_equal(expected,*actual)); -//} -// -///* ************************************************************************* */ -// SL-FIX TEST( GaussianFactorGraph, combine_factors_x2 ) -//{ -// // create a small example for a linear factor graph -// GaussianFactorGraph fg = createGaussianFactorGraph(); -// -// // combine all factors -// GaussianFactor::shared_ptr actual = removeAndCombineFactors(fg,kx(2)); -// -// // the expected linear factor -// Matrix Al1 = Matrix_(4,2, -// // l1 -// 0., 0., -// 0., 0., -// 5., 0., -// 0., 5. -// ); -// -// Matrix Ax1 = Matrix_(4,2, -// // x1 -// -10., 0., // f2 -// 0.,-10., // f2 -// 0., 0., // f4 -// 0., 0. // f4 -// ); -// -// Matrix Ax2 = Matrix_(4,2, -// // x2 -// 10., 0., -// 0., 10., -// -5., 0., -// 0.,-5. -// ); -// -// // the expected RHS vector -// Vector b(4); -// b(0) = 2; -// b(1) = -1; -// b(2) = -1; -// b(3) = 1.5; -// -// vector > meas; -// meas.push_back(make_pair(kl(1), Al1)); -// meas.push_back(make_pair(kx(1), Ax1)); -// meas.push_back(make_pair(kx(2), Ax2)); -// GaussianFactor expected(meas, b, ones(4)); -// -// // check if the two factors are the same -// EXPECT(assert_equal(expected,*actual)); -//} + // note the error is the same as in testNonlinearFactorGraph as a + // zero delta config in the linear graph is equivalent to noisy in + // non-linear, which is really linear under the hood + double actual = fg.error(cfg); + DOUBLES_EQUAL( 5.625, actual, 1e-9 ); +} /* ************************************************************************* */ TEST( GaussianFactorGraph, eliminateOne_x1 ) { - Ordering ordering; ordering += kx(1),kl(1),kx(2); + Ordering ordering; ordering += X(1),L(1),X(2); GaussianFactorGraph fg = createGaussianFactorGraph(ordering); - GaussianFactorGraph::FactorizationResult result = inference::eliminateOne(fg, 0, EliminateQR); + GaussianConditional::shared_ptr conditional; + GaussianFactorGraph remaining; + boost::tie(conditional,remaining) = inference::eliminateOne(fg, 0, EliminateQR); // create expected Conditional Gaussian Matrix I = 15*eye(2), R11 = I, S12 = -0.111111*I, S13 = -0.444444*I; Vector d = Vector_(2, -0.133333, -0.0222222), sigma = ones(2); - GaussianConditional expected(ordering[kx(1)],15*d,R11,ordering[kl(1)],S12,ordering[kx(2)],S13,sigma); + GaussianConditional expected(ordering[X(1)],15*d,R11,ordering[L(1)],S12,ordering[X(2)],S13,sigma); - EXPECT(assert_equal(expected,*result.first,tol)); + EXPECT(assert_equal(expected,*conditional,tol)); } /* ************************************************************************* */ TEST( GaussianFactorGraph, eliminateOne_x2 ) { - Ordering ordering; ordering += kx(2),kl(1),kx(1); + Ordering ordering; ordering += X(2),L(1),X(1); GaussianFactorGraph fg = createGaussianFactorGraph(ordering); GaussianConditional::shared_ptr actual = inference::eliminateOne(fg, 0, EliminateQR).first; @@ -219,7 +97,7 @@ TEST( GaussianFactorGraph, eliminateOne_x2 ) double sig = 0.0894427; Matrix I = eye(2)/sig, R11 = I, S12 = -0.2*I, S13 = -0.8*I; Vector d = Vector_(2, 0.2, -0.14)/sig, sigma = ones(2); - GaussianConditional expected(ordering[kx(2)],d,R11,ordering[kl(1)],S12,ordering[kx(1)],S13,sigma); + GaussianConditional expected(ordering[X(2)],d,R11,ordering[L(1)],S12,ordering[X(1)],S13,sigma); EXPECT(assert_equal(expected,*actual,tol)); } @@ -227,15 +105,15 @@ TEST( GaussianFactorGraph, eliminateOne_x2 ) /* ************************************************************************* */ TEST( GaussianFactorGraph, eliminateOne_l1 ) { - Ordering ordering; ordering += kl(1),kx(1),kx(2); + Ordering ordering; ordering += L(1),X(1),X(2); GaussianFactorGraph fg = createGaussianFactorGraph(ordering); GaussianConditional::shared_ptr actual = inference::eliminateOne(fg, 0, EliminateQR).first; // create expected Conditional Gaussian - double sig = sqrt(2)/10.; + double sig = sqrt(2.0)/10.; Matrix I = eye(2)/sig, R11 = I, S12 = -0.5*I, S13 = -0.5*I; Vector d = Vector_(2, -0.1, 0.25)/sig, sigma = ones(2); - GaussianConditional expected(ordering[kl(1)],d,R11,ordering[kx(1)],S12,ordering[kx(2)],S13,sigma); + GaussianConditional expected(ordering[L(1)],d,R11,ordering[X(1)],S12,ordering[X(2)],S13,sigma); EXPECT(assert_equal(expected,*actual,tol)); } @@ -243,16 +121,16 @@ TEST( GaussianFactorGraph, eliminateOne_l1 ) /* ************************************************************************* */ TEST( GaussianFactorGraph, eliminateOne_x1_fast ) { - Ordering ordering; ordering += kx(1),kl(1),kx(2); + Ordering ordering; ordering += X(1),L(1),X(2); GaussianFactorGraph fg = createGaussianFactorGraph(ordering); - GaussianFactorGraph::FactorizationResult result = inference::eliminateOne(fg, ordering[kx(1)], EliminateQR); - GaussianConditional::shared_ptr conditional = result.first; - GaussianFactorGraph remaining = result.second; + GaussianConditional::shared_ptr conditional; + GaussianFactorGraph remaining; + boost::tie(conditional,remaining) = inference::eliminateOne(fg, ordering[X(1)], EliminateQR); // create expected Conditional Gaussian Matrix I = 15*eye(2), R11 = I, S12 = -0.111111*I, S13 = -0.444444*I; Vector d = Vector_(2, -0.133333, -0.0222222), sigma = ones(2); - GaussianConditional expected(ordering[kx(1)],15*d,R11,ordering[kl(1)],S12,ordering[kx(2)],S13,sigma); + GaussianConditional expected(ordering[X(1)],15*d,R11,ordering[L(1)],S12,ordering[X(2)],S13,sigma); // Create expected remaining new factor JacobianFactor expectedFactor(1, Matrix_(4,2, @@ -265,7 +143,7 @@ TEST( GaussianFactorGraph, eliminateOne_x1_fast ) 0., -2.357022603955159, 7.071067811865475, 0., 0., 7.071067811865475), - Vector_(4, -0.707106781186547, 0.942809041582063, 0.707106781186547, -1.414213562373094), sharedUnit(4)); + Vector_(4, -0.707106781186547, 0.942809041582063, 0.707106781186547, -1.414213562373094), noiseModel::Unit::Create(4)); EXPECT(assert_equal(expected,*conditional,tol)); EXPECT(assert_equal((const GaussianFactor&)expectedFactor,*remaining.back(),tol)); @@ -274,15 +152,15 @@ TEST( GaussianFactorGraph, eliminateOne_x1_fast ) /* ************************************************************************* */ TEST( GaussianFactorGraph, eliminateOne_x2_fast ) { - Ordering ordering; ordering += kx(1),kl(1),kx(2); + Ordering ordering; ordering += X(1),L(1),X(2); GaussianFactorGraph fg = createGaussianFactorGraph(ordering); - GaussianConditional::shared_ptr actual = inference::eliminateOne(fg, ordering[kx(2)], EliminateQR).first; + GaussianConditional::shared_ptr actual = inference::eliminateOne(fg, ordering[X(2)], EliminateQR).first; // create expected Conditional Gaussian double sig = 0.0894427; Matrix I = eye(2)/sig, R11 = I, S12 = -0.2*I, S13 = -0.8*I; Vector d = Vector_(2, 0.2, -0.14)/sig, sigma = ones(2); - GaussianConditional expected(ordering[kx(2)],d,R11,ordering[kx(1)],S13,ordering[kl(1)],S12,sigma); + GaussianConditional expected(ordering[X(2)],d,R11,ordering[X(1)],S13,ordering[L(1)],S12,sigma); EXPECT(assert_equal(expected,*actual,tol)); } @@ -290,15 +168,15 @@ TEST( GaussianFactorGraph, eliminateOne_x2_fast ) /* ************************************************************************* */ TEST( GaussianFactorGraph, eliminateOne_l1_fast ) { - Ordering ordering; ordering += kx(1),kl(1),kx(2); + Ordering ordering; ordering += X(1),L(1),X(2); GaussianFactorGraph fg = createGaussianFactorGraph(ordering); - GaussianConditional::shared_ptr actual = inference::eliminateOne(fg, ordering[kl(1)], EliminateQR).first; + GaussianConditional::shared_ptr actual = inference::eliminateOne(fg, ordering[L(1)], EliminateQR).first; // create expected Conditional Gaussian - double sig = sqrt(2)/10.; + double sig = sqrt(2.0)/10.; Matrix I = eye(2)/sig, R11 = I, S12 = -0.5*I, S13 = -0.5*I; Vector d = Vector_(2, -0.1, 0.25)/sig, sigma = ones(2); - GaussianConditional expected(ordering[kl(1)],d,R11,ordering[kx(1)],S12,ordering[kx(2)],S13,sigma); + GaussianConditional expected(ordering[L(1)],d,R11,ordering[X(1)],S12,ordering[X(2)],S13,sigma); EXPECT(assert_equal(expected,*actual,tol)); } @@ -310,18 +188,18 @@ TEST( GaussianFactorGraph, eliminateAll ) Matrix I = eye(2); Ordering ordering; - ordering += kx(2),kl(1),kx(1); + ordering += X(2),L(1),X(1); Vector d1 = Vector_(2, -0.1,-0.1); - GaussianBayesNet expected = simpleGaussian(ordering[kx(1)],d1,0.1); + GaussianBayesNet expected = simpleGaussian(ordering[X(1)],d1,0.1); double sig1 = 0.149071; Vector d2 = Vector_(2, 0.0, 0.2)/sig1, sigma2 = ones(2); - push_front(expected,ordering[kl(1)],d2, I/sig1,ordering[kx(1)], (-1)*I/sig1,sigma2); + push_front(expected,ordering[L(1)],d2, I/sig1,ordering[X(1)], (-1)*I/sig1,sigma2); double sig2 = 0.0894427; Vector d3 = Vector_(2, 0.2, -0.14)/sig2, sigma3 = ones(2); - push_front(expected,ordering[kx(2)],d3, I/sig2,ordering[kl(1)], (-0.2)*I/sig2, ordering[kx(1)], (-0.8)*I/sig2, sigma3); + push_front(expected,ordering[X(2)],d3, I/sig2,ordering[L(1)], (-0.2)*I/sig2, ordering[X(1)], (-0.8)*I/sig2, sigma3); // Check one ordering GaussianFactorGraph fg1 = createGaussianFactorGraph(ordering); @@ -332,52 +210,11 @@ TEST( GaussianFactorGraph, eliminateAll ) EXPECT(assert_equal(expected,actualQR,tol)); } -///* ************************************************************************* */ -//TEST( GaussianFactorGraph, eliminateAll_fast ) -//{ -// // create expected Chordal bayes Net -// Matrix I = eye(2); -// -// Vector d1 = Vector_(2, -0.1,-0.1); -// GaussianBayesNet expected = simpleGaussian(kx(1),d1,0.1); -// -// double sig1 = 0.149071; -// Vector d2 = Vector_(2, 0.0, 0.2)/sig1, sigma2 = ones(2); -// push_front(expected,kl(1),d2, I/sig1,kx(1), (-1)*I/sig1,sigma2); -// -// double sig2 = 0.0894427; -// Vector d3 = Vector_(2, 0.2, -0.14)/sig2, sigma3 = ones(2); -// push_front(expected,kx(2),d3, I/sig2,kl(1), (-0.2)*I/sig2, kx(1), (-0.8)*I/sig2, sigma3); -// -// // Check one ordering -// GaussianFactorGraph fg1 = createGaussianFactorGraph(); -// Ordering ordering; -// ordering += kx(2),kl(1),kx(1); -// GaussianBayesNet actual = fg1.eliminate(ordering, false); -// EXPECT(assert_equal(expected,actual,tol)); -//} - -///* ************************************************************************* */ -//TEST( GaussianFactorGraph, add_priors ) -//{ -// Ordering ordering; ordering += kl(1),kx(1),kx(2); -// GaussianFactorGraph fg = createGaussianFactorGraph(ordering); -// GaussianFactorGraph actual = fg.add_priors(3, vector(3,2)); -// GaussianFactorGraph expected = createGaussianFactorGraph(ordering); -// Matrix A = eye(2); -// Vector b = zero(2); -// SharedDiagonal sigma = sharedSigma(2,3.0); -// expected.push_back(GaussianFactor::shared_ptr(new JacobianFactor(ordering[kl(1)],A,b,sigma))); -// expected.push_back(GaussianFactor::shared_ptr(new JacobianFactor(ordering[kx(1)],A,b,sigma))); -// expected.push_back(GaussianFactor::shared_ptr(new JacobianFactor(ordering[kx(2)],A,b,sigma))); -// EXPECT(assert_equal(expected,actual)); -//} - /* ************************************************************************* */ TEST( GaussianFactorGraph, copying ) { // Create a graph - Ordering ordering; ordering += kx(2),kl(1),kx(1); + Ordering ordering; ordering += X(2),L(1),X(1); GaussianFactorGraph actual = createGaussianFactorGraph(ordering); // Copy the graph ! @@ -393,51 +230,11 @@ TEST( GaussianFactorGraph, copying ) EXPECT(assert_equal(expected,actual)); } -///* ************************************************************************* */ -// SL-FIX TEST( GaussianFactorGraph, matrix ) -//{ -// // render with a given ordering -// Ordering ord; -// ord += kx(2),kl(1),kx(1); -// -// // Create a graph -// GaussianFactorGraph fg = createGaussianFactorGraph(ordering); -// -// Matrix A; Vector b; -// boost::tie(A,b) = fg.matrix(); -// -// Matrix A1 = Matrix_(2*4,3*2, -// +0., 0., 0., 0., 10., 0., // unary factor on x1 (prior) -// +0., 0., 0., 0., 0., 10., -// 10., 0., 0., 0.,-10., 0., // binary factor on x2,x1 (odometry) -// +0., 10., 0., 0., 0.,-10., -// +0., 0., 5., 0., -5., 0., // binary factor on l1,x1 (z1) -// +0., 0., 0., 5., 0., -5., -// -5., 0., 5., 0., 0., 0., // binary factor on x2,l1 (z2) -// +0., -5., 0., 5., 0., 0. -// ); -// Vector b1 = Vector_(8,-1., -1., 2., -1., 0., 1., -1., 1.5); -// -// EQUALITY(A,A1); -// EXPECT(b==b1); -//} - -///* ************************************************************************* */ -// SL-FIX TEST( GaussianFactorGraph, sizeOfA ) -//{ -// // create a small linear factor graph -// GaussianFactorGraph fg = createGaussianFactorGraph(); -// -// pair mn = fg.sizeOfA(); -// EXPECT(8 == mn.first); -// EXPECT(6 == mn.second); -//} - /* ************************************************************************* */ TEST( GaussianFactorGraph, CONSTRUCTOR_GaussianBayesNet ) { Ordering ord; - ord += kx(2),kl(1),kx(1); + ord += X(2),L(1),X(1); GaussianFactorGraph fg = createGaussianFactorGraph(ord); // render with a given ordering @@ -447,39 +244,24 @@ TEST( GaussianFactorGraph, CONSTRUCTOR_GaussianBayesNet ) GaussianFactorGraph fg2(CBN); GaussianBayesNet CBN2 = *GaussianSequentialSolver(fg2).eliminate(); EXPECT(assert_equal(CBN,CBN2)); - - // Base FactorGraph only -// FactorGraph fg3(CBN); -// GaussianBayesNet CBN3 = gtsam::eliminate(fg3,ord); -// EXPECT(assert_equal(CBN,CBN3)); } /* ************************************************************************* */ TEST( GaussianFactorGraph, getOrdering) { - Ordering original; original += kl(1),kx(1),kx(2); + Ordering original; original += L(1),X(1),X(2); FactorGraph symbolic(createGaussianFactorGraph(original)); Permutation perm(*inference::PermutationCOLAMD(VariableIndex(symbolic))); Ordering actual = original; actual.permuteWithInverse((*perm.inverse())); - Ordering expected; expected += kl(1),kx(2),kx(1); + Ordering expected; expected += L(1),X(2),X(1); EXPECT(assert_equal(expected,actual)); } -// SL-FIX TEST( GaussianFactorGraph, getOrdering2) -//{ -// Ordering expected; -// expected += kl(1),kx(1); -// GaussianFactorGraph fg = createGaussianFactorGraph(); -// set interested; interested += kl(1),kx(1); -// Ordering actual = fg.getOrdering(interested); -// EXPECT(assert_equal(expected,actual)); -//} - /* ************************************************************************* */ TEST( GaussianFactorGraph, optimize_Cholesky ) { // create an ordering - Ordering ord; ord += kx(2),kl(1),kx(1); + Ordering ord; ord += X(2),L(1),X(1); // create a graph GaussianFactorGraph fg = createGaussianFactorGraph(ord); @@ -497,7 +279,7 @@ TEST( GaussianFactorGraph, optimize_Cholesky ) TEST( GaussianFactorGraph, optimize_QR ) { // create an ordering - Ordering ord; ord += kx(2),kl(1),kx(1); + Ordering ord; ord += X(2),L(1),X(1); // create a graph GaussianFactorGraph fg = createGaussianFactorGraph(ord); @@ -511,29 +293,11 @@ TEST( GaussianFactorGraph, optimize_QR ) EXPECT(assert_equal(expected,actual)); } -///* ************************************************************************* */ -// SL-FIX TEST( GaussianFactorGraph, optimizeMultiFrontlas ) -//{ -// // create an ordering -// Ordering ord; ord += kx(2),kl(1),kx(1); -// -// // create a graph -// GaussianFactorGraph fg = createGaussianFactorGraph(ord); -// -// // optimize the graph -// VectorValues actual = fg.optimizeMultiFrontals(ord); -// -// // verify -// VectorValues expected = createCorrectDelta(); -// -// EXPECT(assert_equal(expected,actual)); -//} - /* ************************************************************************* */ TEST( GaussianFactorGraph, combine) { // create an ordering - Ordering ord; ord += kx(2),kl(1),kx(1); + Ordering ord; ord += X(2),L(1),X(1); // create a test graph GaussianFactorGraph fg1 = createGaussianFactorGraph(ord); @@ -555,7 +319,7 @@ TEST( GaussianFactorGraph, combine) TEST( GaussianFactorGraph, combine2) { // create an ordering - Ordering ord; ord += kx(2),kl(1),kx(1); + Ordering ord; ord += X(2),L(1),X(1); // create a test graph GaussianFactorGraph fg1 = createGaussianFactorGraph(ord); @@ -581,48 +345,6 @@ void print(vector v) { cout << endl; } -///* ************************************************************************* */ -// SL-NEEDED? TEST( GaussianFactorGraph, factor_lookup) -//{ -// // create a test graph -// GaussianFactorGraph fg = createGaussianFactorGraph(); -// -// // ask for all factor indices connected to x1 -// list x1_factors = fg.factors(kx(1)); -// size_t x1_indices[] = { 0, 1, 2 }; -// list x1_expected(x1_indices, x1_indices + 3); -// EXPECT(x1_factors==x1_expected); -// -// // ask for all factor indices connected to x2 -// list x2_factors = fg.factors(kx(2)); -// size_t x2_indices[] = { 1, 3 }; -// list x2_expected(x2_indices, x2_indices + 2); -// EXPECT(x2_factors==x2_expected); -//} - -///* ************************************************************************* */ -// SL-NEEDED? TEST( GaussianFactorGraph, findAndRemoveFactors ) -//{ -// // create the graph -// GaussianFactorGraph fg = createGaussianFactorGraph(); -// -// // We expect to remove these three factors: 0, 1, 2 -// GaussianFactor::shared_ptr f0 = fg[0]; -// GaussianFactor::shared_ptr f1 = fg[1]; -// GaussianFactor::shared_ptr f2 = fg[2]; -// -// // call the function -// vector factors = fg.findAndRemoveFactors(kx(1)); -// -// // Check the factors -// EXPECT(f0==factors[0]); -// EXPECT(f1==factors[1]); -// EXPECT(f2==factors[2]); -// -// // EXPECT if the factors are deleted from the factor graph -// LONGS_EQUAL(1,fg.nrFactors()); -//} - /* ************************************************************************* */ TEST(GaussianFactorGraph, createSmoother) { @@ -632,83 +354,22 @@ TEST(GaussianFactorGraph, createSmoother) LONGS_EQUAL(5,fg2.size()); } -///* ************************************************************************* */ -// SL-NEEDED? TEST( GaussianFactorGraph, variables ) -//{ -// GaussianFactorGraph fg = createGaussianFactorGraph(); -// Dimensions expected; -// insert(expected)(kl(1), 2)(kx(1), 2)(kx(2), 2); -// Dimensions actual = fg.dimensions(); -// EXPECT(expected==actual); -//} - -///* ************************************************************************* */ -// SL-NEEDED? TEST( GaussianFactorGraph, keys ) -//{ -// GaussianFactorGraph fg = createGaussianFactorGraph(); -// Ordering expected; -// expected += kl(1),kx(1),kx(2); -// EXPECT(assert_equal(expected,fg.keys())); -//} - -///* ************************************************************************* */ -// SL-NEEDED? TEST( GaussianFactorGraph, involves ) -//{ -// GaussianFactorGraph fg = createGaussianFactorGraph(); -// EXPECT(fg.involves(kl(1))); -// EXPECT(fg.involves(kx(1))); -// EXPECT(fg.involves(kx(2))); -// EXPECT(!fg.involves(kx(3))); -//} - /* ************************************************************************* */ double error(const VectorValues& x) { // create an ordering - Ordering ord; ord += kx(2),kl(1),kx(1); + Ordering ord; ord += X(2),L(1),X(1); GaussianFactorGraph fg = createGaussianFactorGraph(ord); return fg.error(x); } -///* ************************************************************************* */ -// SL-NEEDED? TEST( GaussianFactorGraph, gradient ) -//{ -// GaussianFactorGraph fg = createGaussianFactorGraph(); -// -// // Construct expected gradient -// VectorValues expected; -// -// // 2*f(x) = 100*(x1+c[kx(1)])^2 + 100*(x2-x1-[0.2;-0.1])^2 + 25*(l1-x1-[0.0;0.2])^2 + 25*(l1-x2-[-0.2;0.3])^2 -// // worked out: df/dx1 = 100*[0.1;0.1] + 100*[0.2;-0.1]) + 25*[0.0;0.2] = [10+20;10-10+5] = [30;5] -// expected.insert(kl(1),Vector_(2, 5.0,-12.5)); -// expected.insert(kx(1),Vector_(2, 30.0, 5.0)); -// expected.insert(kx(2),Vector_(2,-25.0, 17.5)); -// -// // Check the gradient at delta=0 -// VectorValues zero = createZeroDelta(); -// VectorValues actual = fg.gradient(zero); -// EXPECT(assert_equal(expected,actual)); -// -// // Check it numerically for good measure -// Vector numerical_g = numericalGradient(error,zero,0.001); -// EXPECT(assert_equal(Vector_(6,5.0,-12.5,30.0,5.0,-25.0,17.5),numerical_g)); -// -// // Check the gradient at the solution (should be zero) -// Ordering ord; -// ord += kx(2),kl(1),kx(1); -// GaussianFactorGraph fg2 = createGaussianFactorGraph(); -// VectorValues solution = fg2.optimize(ord); // destructive -// VectorValues actual2 = fg.gradient(solution); -// EXPECT(assert_equal(zero,actual2)); -//} - /* ************************************************************************* */ TEST( GaussianFactorGraph, multiplication ) { // create an ordering - Ordering ord; ord += kx(2),kl(1),kx(1); + Ordering ord; ord += X(2),L(1),X(1); - FactorGraph A = createGaussianFactorGraph(ord); + GaussianFactorGraph A = createGaussianFactorGraph(ord); VectorValues x = createCorrectDelta(ord); Errors actual = A * x; Errors expected; @@ -719,61 +380,26 @@ TEST( GaussianFactorGraph, multiplication ) EXPECT(assert_equal(expected,actual)); } -///* ************************************************************************* */ -// SL-NEEDED? TEST( GaussianFactorGraph, transposeMultiplication ) -//{ -// // create an ordering -// Ordering ord; ord += kx(2),kl(1),kx(1); -// -// GaussianFactorGraph A = createGaussianFactorGraph(ord); -// Errors e; -// e += Vector_(2, 0.0, 0.0); -// e += Vector_(2,15.0, 0.0); -// e += Vector_(2, 0.0,-5.0); -// e += Vector_(2,-7.5,-5.0); -// -// VectorValues expected = createZeroDelta(ord), actual = A ^ e; -// expected[ord[kl(1)]] = Vector_(2, -37.5,-50.0); -// expected[ord[kx(1)]] = Vector_(2,-150.0, 25.0); -// expected[ord[kx(2)]] = Vector_(2, 187.5, 25.0); -// EXPECT(assert_equal(expected,actual)); -//} - -///* ************************************************************************* */ -// SL-NEEDED? TEST( GaussianFactorGraph, rhs ) -//{ -// // create an ordering -// Ordering ord; ord += kx(2),kl(1),kx(1); -// -// GaussianFactorGraph Ab = createGaussianFactorGraph(ord); -// Errors expected = createZeroDelta(ord), actual = Ab.rhs(); -// expected.push_back(Vector_(2,-1.0,-1.0)); -// expected.push_back(Vector_(2, 2.0,-1.0)); -// expected.push_back(Vector_(2, 0.0, 1.0)); -// expected.push_back(Vector_(2,-1.0, 1.5)); -// EXPECT(assert_equal(expected,actual)); -//} - /* ************************************************************************* */ // Extra test on elimination prompted by Michael's email to Frank 1/4/2010 TEST( GaussianFactorGraph, elimination ) { Ordering ord; - ord += kx(1), kx(2); + ord += X(1), X(2); // Create Gaussian Factor Graph GaussianFactorGraph fg; Matrix Ap = eye(1), An = eye(1) * -1; Vector b = Vector_(1, 0.0); - SharedDiagonal sigma = sharedSigma(1,2.0); - fg.add(ord[kx(1)], An, ord[kx(2)], Ap, b, sigma); - fg.add(ord[kx(1)], Ap, b, sigma); - fg.add(ord[kx(2)], Ap, b, sigma); + SharedDiagonal sigma = noiseModel::Isotropic::Sigma(1,2.0); + fg.add(ord[X(1)], An, ord[X(2)], Ap, b, sigma); + fg.add(ord[X(1)], Ap, b, sigma); + fg.add(ord[X(2)], Ap, b, sigma); // Eliminate GaussianBayesNet bayesNet = *GaussianSequentialSolver(fg).eliminate(); // Check sigma - EXPECT_DOUBLES_EQUAL(1.0,bayesNet[ord[kx(2)]]->get_sigmas()(0),1e-5); + EXPECT_DOUBLES_EQUAL(1.0,bayesNet[ord[X(2)]]->get_sigmas()(0),1e-5); // Check matrix Matrix R;Vector d; @@ -820,22 +446,6 @@ TEST( GaussianFactorGraph, constrained_single ) EXPECT(assert_equal(expected, actual)); } -///* ************************************************************************* */ -//SL-FIX TEST( GaussianFactorGraph, constrained_single2 ) -//{ -// // get a graph with a constraint in it -// GaussianFactorGraph fg = createSingleConstraintGraph(); -// -// // eliminate and solve -// Ordering ord; -// ord += "yk, x"; -// VectorValues actual = fg.optimize(ord); -// -// // verify -// VectorValues expected = createSingleConstraintValues(); -// EXPECT(assert_equal(expected, actual)); -//} - /* ************************************************************************* */ TEST( GaussianFactorGraph, constrained_multi1 ) { @@ -851,171 +461,39 @@ TEST( GaussianFactorGraph, constrained_multi1 ) EXPECT(assert_equal(expected, actual)); } -///* ************************************************************************* */ -//SL-FIX TEST( GaussianFactorGraph, constrained_multi2 ) -//{ -// // get a graph with a constraint in it -// GaussianFactorGraph fg = createMultiConstraintGraph(); -// -// // eliminate and solve -// Ordering ord; -// ord += "zk, xk, y"; -// VectorValues actual = fg.optimize(ord); -// -// // verify -// VectorValues expected = createMultiConstraintValues(); -// EXPECT(assert_equal(expected, actual)); -//} - /* ************************************************************************* */ -SharedDiagonal model = sharedSigma(2,1); - -// SL-FIX TEST( GaussianFactorGraph, findMinimumSpanningTree ) -//{ -// GaussianFactorGraph g; -// Matrix I = eye(2); -// Vector b = Vector_(0, 0, 0); -// g.add(kx(1), I, kx(2), I, b, model); -// g.add(kx(1), I, kx(3), I, b, model); -// g.add(kx(1), I, kx(4), I, b, model); -// g.add(kx(2), I, kx(3), I, b, model); -// g.add(kx(2), I, kx(4), I, b, model); -// g.add(kx(3), I, kx(4), I, b, model); -// -// map tree = g.findMinimumSpanningTree(); -// EXPECT(tree[kx(1)].compare(kx(1))==0); -// EXPECT(tree[kx(2)].compare(kx(1))==0); -// EXPECT(tree[kx(3)].compare(kx(1))==0); -// EXPECT(tree[kx(4)].compare(kx(1))==0); -//} - -///* ************************************************************************* */ -// SL-FIX TEST( GaussianFactorGraph, split ) -//{ -// GaussianFactorGraph g; -// Matrix I = eye(2); -// Vector b = Vector_(0, 0, 0); -// g.add(kx(1), I, kx(2), I, b, model); -// g.add(kx(1), I, kx(3), I, b, model); -// g.add(kx(1), I, kx(4), I, b, model); -// g.add(kx(2), I, kx(3), I, b, model); -// g.add(kx(2), I, kx(4), I, b, model); -// -// PredecessorMap tree; -// tree[kx(1)] = kx(1); -// tree[kx(2)] = kx(1); -// tree[kx(3)] = kx(1); -// tree[kx(4)] = kx(1); -// -// GaussianFactorGraph Ab1, Ab2; -// g.split(tree, Ab1, Ab2); -// LONGS_EQUAL(3, Ab1.size()); -// LONGS_EQUAL(2, Ab2.size()); -//} +static SharedDiagonal model = noiseModel::Isotropic::Sigma(2,1); /* ************************************************************************* */ TEST(GaussianFactorGraph, replace) { - Ordering ord; ord += kx(1),kx(2),kx(3),kx(4),kx(5),kx(6); - SharedDiagonal noise(sharedSigma(3, 1.0)); + Ordering ord; ord += X(1),X(2),X(3),X(4),X(5),X(6); + SharedDiagonal noise(noiseModel::Isotropic::Sigma(3, 1.0)); GaussianFactorGraph::sharedFactor f1(new JacobianFactor( - ord[kx(1)], eye(3,3), ord[kx(2)], eye(3,3), zero(3), noise)); + ord[X(1)], eye(3,3), ord[X(2)], eye(3,3), zero(3), noise)); GaussianFactorGraph::sharedFactor f2(new JacobianFactor( - ord[kx(2)], eye(3,3), ord[kx(3)], eye(3,3), zero(3), noise)); + ord[X(2)], eye(3,3), ord[X(3)], eye(3,3), zero(3), noise)); GaussianFactorGraph::sharedFactor f3(new JacobianFactor( - ord[kx(3)], eye(3,3), ord[kx(4)], eye(3,3), zero(3), noise)); + ord[X(3)], eye(3,3), ord[X(4)], eye(3,3), zero(3), noise)); GaussianFactorGraph::sharedFactor f4(new JacobianFactor( - ord[kx(5)], eye(3,3), ord[kx(6)], eye(3,3), zero(3), noise)); + ord[X(5)], eye(3,3), ord[X(6)], eye(3,3), zero(3), noise)); GaussianFactorGraph actual; actual.push_back(f1); -// actual.checkGraphConsistency(); actual.push_back(f2); -// actual.checkGraphConsistency(); actual.push_back(f3); -// actual.checkGraphConsistency(); actual.replace(0, f4); -// actual.checkGraphConsistency(); GaussianFactorGraph expected; expected.push_back(f4); -// actual.checkGraphConsistency(); expected.push_back(f2); -// actual.checkGraphConsistency(); expected.push_back(f3); -// actual.checkGraphConsistency(); EXPECT(assert_equal(expected, actual)); } -///* ************************************************************************* */ -//TEST ( GaussianFactorGraph, combine_matrix ) { -// // create a small linear factor graph -// GaussianFactorGraph fg = createGaussianFactorGraph(); -// Dimensions dimensions = fg.dimensions(); -// -// // get two factors from it and insert the factors into a vector -// vector lfg; -// lfg.push_back(fg[4 - 1]); -// lfg.push_back(fg[2 - 1]); -// -// // combine in a factor -// Matrix Ab; SharedDiagonal noise; -// Ordering order; order += kx(2), kl(1), kx(1); -// boost::tie(Ab, noise) = combineFactorsAndCreateMatrix(lfg, order, dimensions); -// -// // the expected augmented matrix -// Matrix expAb = Matrix_(4, 7, -// -5., 0., 5., 0., 0., 0.,-1.0, -// +0., -5., 0., 5., 0., 0., 1.5, -// 10., 0., 0., 0.,-10., 0., 2.0, -// +0., 10., 0., 0., 0.,-10.,-1.0); -// -// // expected noise model -// SharedDiagonal expModel = noiseModel::Unit::Create(4); -// -// EXPECT(assert_equal(expAb, Ab)); -// EXPECT(assert_equal(*expModel, *noise)); -//} - -/* ************************************************************************* */ -/* - * x2 x1 x3 b - * 1 1 1 1 1 0 1 - * 1 1 1 -> 1 1 1 - * 1 1 1 1 - */ -// SL-NEEDED? TEST ( GaussianFactorGraph, eliminateFrontals ) { -// typedef GaussianFactorGraph::sharedFactor Factor; -// SharedDiagonal model(Vector_(1, 0.5)); -// GaussianFactorGraph fg; -// Factor factor1(new JacobianFactor(kx(1), Matrix_(1,1,1.), kx(2), Matrix_(1,1,1.), Vector_(1,1.), model)); -// Factor factor2(new JacobianFactor(kx(2), Matrix_(1,1,1.), kx(3), Matrix_(1,1,1.), Vector_(1,1.), model)); -// Factor factor3(new JacobianFactor(kx(3), Matrix_(1,1,1.), kx(3), Matrix_(1,1,1.), Vector_(1,1.), model)); -// fg.push_back(factor1); -// fg.push_back(factor2); -// fg.push_back(factor3); -// -// Ordering frontals; frontals += kx(2), kx(1); -// GaussianBayesNet bn = fg.eliminateFrontals(frontals); -// -// GaussianBayesNet bn_expected; -// GaussianBayesNet::sharedConditional conditional1(new GaussianConditional(kx(2), Vector_(1, 2.), Matrix_(1, 1, 2.), -// kx(1), Matrix_(1, 1, 1.), kx(3), Matrix_(1, 1, 1.), Vector_(1, 1.))); -// GaussianBayesNet::sharedConditional conditional2(new GaussianConditional(kx(1), Vector_(1, 0.), Matrix_(1, 1, -1.), -// kx(3), Matrix_(1, 1, 1.), Vector_(1, 1.))); -// bn_expected.push_back(conditional1); -// bn_expected.push_back(conditional2); -// EXPECT(assert_equal(bn_expected, bn)); -// -// GaussianFactorGraph::sharedFactor factor_expected(new JacobianFactor(kx(3), Matrix_(1, 1, 2.), Vector_(1, 2.), SharedDiagonal(Vector_(1, 1.)))); -// GaussianFactorGraph fg_expected; -// fg_expected.push_back(factor_expected); -// EXPECT(assert_equal(fg_expected, fg)); -//} - /* ************************************************************************* */ TEST(GaussianFactorGraph, createSmoother2) { @@ -1026,8 +504,8 @@ TEST(GaussianFactorGraph, createSmoother2) LONGS_EQUAL(5,fg2.size()); // eliminate - vector x3var; x3var.push_back(ordering[kx(3)]); - vector x1var; x1var.push_back(ordering[kx(1)]); + vector x3var; x3var.push_back(ordering[X(3)]); + vector x1var; x1var.push_back(ordering[X(1)]); GaussianBayesNet p_x3 = *GaussianSequentialSolver( *GaussianSequentialSolver(fg2).jointFactorGraph(x3var)).eliminate(); GaussianBayesNet p_x1 = *GaussianSequentialSolver( @@ -1044,8 +522,8 @@ TEST(GaussianFactorGraph, hasConstraints) FactorGraph fgc2 = createSimpleConstraintGraph() ; EXPECT(hasConstraints(fgc2)); - Ordering ordering; ordering += kx(1), kx(2), kl(1); - FactorGraph fg = createGaussianFactorGraph(ordering); + Ordering ordering; ordering += X(1), X(2), L(1); + GaussianFactorGraph fg = createGaussianFactorGraph(ordering); EXPECT(!hasConstraints(fg)); } diff --git a/tests/testGaussianISAM.cpp b/tests/testGaussianISAM.cpp index 4c798aa8d..74417b57a 100644 --- a/tests/testGaussianISAM.cpp +++ b/tests/testGaussianISAM.cpp @@ -15,41 +15,42 @@ * @author Michael Kaess */ -#include -#include // for operator += -using namespace boost::assign; - -#include - -#include +#include #include +#include #include -#include #include #include #include -#include +#include +#include + +#include + +#include +#include // for operator += +using namespace boost::assign; using namespace std; using namespace gtsam; using namespace example; -Key kx(size_t i) { return Symbol('x',i); } -Key kl(size_t i) { return Symbol('l',i); } +using symbol_shorthand::X; +using symbol_shorthand::L; /* ************************************************************************* */ // Some numbers that should be consistent among all smoother tests -double sigmax1 = 0.786153, sigmax2 = 1.0/1.47292, sigmax3 = 0.671512, sigmax4 = - 0.669534, sigmax5 = sigmax3, sigmax6 = sigmax2, sigmax7 = sigmax1; +static double sigmax1 = 0.786153, sigmax2 = 1.0/1.47292, sigmax3 = 0.671512, sigmax4 = + 0.669534 /*, sigmax5 = sigmax3, sigmax6 = sigmax2*/, sigmax7 = sigmax1; -const double tol = 1e-4; +static const double tol = 1e-4; /* ************************************************************************* */ -TEST_UNSAFE( ISAM, iSAM_smoother ) +TEST( ISAM, iSAM_smoother ) { Ordering ordering; - for (int t = 1; t <= 7; t++) ordering += kx(t); + for (int t = 1; t <= 7; t++) ordering += X(t); // Create smoother with 7 nodes GaussianFactorGraph smoother = createSmoother(7, ordering).first; @@ -75,31 +76,6 @@ TEST_UNSAFE( ISAM, iSAM_smoother ) EXPECT(assert_equal(e, optimized)); } -/* ************************************************************************* */ -// SL-FIX TEST( ISAM, iSAM_smoother2 ) -//{ -// // Create smoother with 7 nodes -// GaussianFactorGraph smoother = createSmoother(7); -// -// // Create initial tree from first 4 timestamps in reverse order ! -// Ordering ord; ord += kx(4),kx(3),kx(2),kx(1); -// GaussianFactorGraph factors1; -// for (int i=0;i<7;i++) factors1.push_back(smoother[i]); -// GaussianISAM actual(*inference::Eliminate(factors1)); -// -// // run iSAM with remaining factors -// GaussianFactorGraph factors2; -// for (int i=7;i<13;i++) factors2.push_back(smoother[i]); -// actual.update(factors2); -// -// // Create expected Bayes Tree by solving smoother with "natural" ordering -// Ordering ordering; -// for (int t = 1; t <= 7; t++) ordering += symbol('x', t); -// GaussianISAM expected(smoother.eliminate(ordering)); -// -// EXPECT(assert_equal(expected, actual)); -//} - /* ************************************************************************* * Bayes tree for smoother with "natural" ordering: C1 x6 x7 @@ -129,7 +105,7 @@ TEST_UNSAFE( BayesTree, linear_smoother_shortcuts ) EXPECT(assert_equal(empty,actual1,tol)); // Check the conditional P(C2|Root) - GaussianISAM::sharedClique C2 = isamTree[ordering[kx(5)]]; + GaussianISAM::sharedClique C2 = isamTree[ordering[X(5)]]; GaussianBayesNet actual2 = GaussianISAM::shortcut(C2,R); EXPECT(assert_equal(empty,actual2,tol)); @@ -137,8 +113,8 @@ TEST_UNSAFE( BayesTree, linear_smoother_shortcuts ) double sigma3 = 0.61808; Matrix A56 = Matrix_(2,2,-0.382022,0.,0.,-0.382022); GaussianBayesNet expected3; - push_front(expected3,ordering[kx(5)], zero(2), eye(2)/sigma3, ordering[kx(6)], A56/sigma3, ones(2)); - GaussianISAM::sharedClique C3 = isamTree[ordering[kx(4)]]; + push_front(expected3,ordering[X(5)], zero(2), eye(2)/sigma3, ordering[X(6)], A56/sigma3, ones(2)); + GaussianISAM::sharedClique C3 = isamTree[ordering[X(4)]]; GaussianBayesNet actual3 = GaussianISAM::shortcut(C3,R); EXPECT(assert_equal(expected3,actual3,tol)); @@ -146,8 +122,8 @@ TEST_UNSAFE( BayesTree, linear_smoother_shortcuts ) double sigma4 = 0.661968; Matrix A46 = Matrix_(2,2,-0.146067,0.,0.,-0.146067); GaussianBayesNet expected4; - push_front(expected4, ordering[kx(4)], zero(2), eye(2)/sigma4, ordering[kx(6)], A46/sigma4, ones(2)); - GaussianISAM::sharedClique C4 = isamTree[ordering[kx(3)]]; + push_front(expected4, ordering[X(4)], zero(2), eye(2)/sigma4, ordering[X(6)], A46/sigma4, ones(2)); + GaussianISAM::sharedClique C4 = isamTree[ordering[X(3)]]; GaussianBayesNet actual4 = GaussianISAM::shortcut(C4,R); EXPECT(assert_equal(expected4,actual4,tol)); } @@ -175,7 +151,7 @@ TEST_UNSAFE( BayesTree, balanced_smoother_marginals ) { // Create smoother with 7 nodes Ordering ordering; - ordering += kx(1),kx(3),kx(5),kx(7),kx(2),kx(6),kx(4); + ordering += X(1),X(3),X(5),X(7),X(2),X(6),X(4); GaussianFactorGraph smoother = createSmoother(7, ordering).first; // Create the Bayes tree @@ -192,48 +168,48 @@ TEST_UNSAFE( BayesTree, balanced_smoother_marginals ) double tol=1e-5; // Check marginal on x1 - GaussianBayesNet expected1 = simpleGaussian(ordering[kx(1)], zero(2), sigmax1); - GaussianBayesNet actual1 = *bayesTree.marginalBayesNet(ordering[kx(1)]); + GaussianBayesNet expected1 = simpleGaussian(ordering[X(1)], zero(2), sigmax1); + GaussianBayesNet actual1 = *bayesTree.marginalBayesNet(ordering[X(1)]); Matrix expectedCovarianceX1 = eye(2,2) * (sigmax1 * sigmax1); Matrix actualCovarianceX1; - actualCovarianceX1 = bayesTree.marginalCovariance(ordering[kx(1)]); + actualCovarianceX1 = bayesTree.marginalCovariance(ordering[X(1)]); EXPECT(assert_equal(expectedCovarianceX1, actualCovarianceX1, tol)); EXPECT(assert_equal(expected1,actual1,tol)); // Check marginal on x2 double sigx2 = 0.68712938; // FIXME: this should be corrected analytically - GaussianBayesNet expected2 = simpleGaussian(ordering[kx(2)], zero(2), sigx2); - GaussianBayesNet actual2 = *bayesTree.marginalBayesNet(ordering[kx(2)]); + GaussianBayesNet expected2 = simpleGaussian(ordering[X(2)], zero(2), sigx2); + GaussianBayesNet actual2 = *bayesTree.marginalBayesNet(ordering[X(2)]); Matrix expectedCovarianceX2 = eye(2,2) * (sigx2 * sigx2); Matrix actualCovarianceX2; - actualCovarianceX2 = bayesTree.marginalCovariance(ordering[kx(2)]); + actualCovarianceX2 = bayesTree.marginalCovariance(ordering[X(2)]); EXPECT(assert_equal(expectedCovarianceX2, actualCovarianceX2, tol)); EXPECT(assert_equal(expected2,actual2,tol)); // Check marginal on x3 - GaussianBayesNet expected3 = simpleGaussian(ordering[kx(3)], zero(2), sigmax3); - GaussianBayesNet actual3 = *bayesTree.marginalBayesNet(ordering[kx(3)]); + GaussianBayesNet expected3 = simpleGaussian(ordering[X(3)], zero(2), sigmax3); + GaussianBayesNet actual3 = *bayesTree.marginalBayesNet(ordering[X(3)]); Matrix expectedCovarianceX3 = eye(2,2) * (sigmax3 * sigmax3); Matrix actualCovarianceX3; - actualCovarianceX3 = bayesTree.marginalCovariance(ordering[kx(3)]); + actualCovarianceX3 = bayesTree.marginalCovariance(ordering[X(3)]); EXPECT(assert_equal(expectedCovarianceX3, actualCovarianceX3, tol)); EXPECT(assert_equal(expected3,actual3,tol)); // Check marginal on x4 - GaussianBayesNet expected4 = simpleGaussian(ordering[kx(4)], zero(2), sigmax4); - GaussianBayesNet actual4 = *bayesTree.marginalBayesNet(ordering[kx(4)]); + GaussianBayesNet expected4 = simpleGaussian(ordering[X(4)], zero(2), sigmax4); + GaussianBayesNet actual4 = *bayesTree.marginalBayesNet(ordering[X(4)]); Matrix expectedCovarianceX4 = eye(2,2) * (sigmax4 * sigmax4); Matrix actualCovarianceX4; - actualCovarianceX4 = bayesTree.marginalCovariance(ordering[kx(4)]); + actualCovarianceX4 = bayesTree.marginalCovariance(ordering[X(4)]); EXPECT(assert_equal(expectedCovarianceX4, actualCovarianceX4, tol)); EXPECT(assert_equal(expected4,actual4,tol)); // Check marginal on x7 (should be equal to x1) - GaussianBayesNet expected7 = simpleGaussian(ordering[kx(7)], zero(2), sigmax7); - GaussianBayesNet actual7 = *bayesTree.marginalBayesNet(ordering[kx(7)]); + GaussianBayesNet expected7 = simpleGaussian(ordering[X(7)], zero(2), sigmax7); + GaussianBayesNet actual7 = *bayesTree.marginalBayesNet(ordering[X(7)]); Matrix expectedCovarianceX7 = eye(2,2) * (sigmax7 * sigmax7); Matrix actualCovarianceX7; - actualCovarianceX7 = bayesTree.marginalCovariance(ordering[kx(7)]); + actualCovarianceX7 = bayesTree.marginalCovariance(ordering[X(7)]); EXPECT(assert_equal(expectedCovarianceX7, actualCovarianceX7, tol)); EXPECT(assert_equal(expected7,actual7,tol)); } @@ -243,7 +219,7 @@ TEST_UNSAFE( BayesTree, balanced_smoother_shortcuts ) { // Create smoother with 7 nodes Ordering ordering; - ordering += kx(1),kx(3),kx(5),kx(7),kx(2),kx(6),kx(4); + ordering += X(1),X(3),X(5),X(7),X(2),X(6),X(4); GaussianFactorGraph smoother = createSmoother(7, ordering).first; // Create the Bayes tree @@ -257,19 +233,19 @@ TEST_UNSAFE( BayesTree, balanced_smoother_shortcuts ) EXPECT(assert_equal(empty,actual1,tol)); // Check the conditional P(C2|Root) - GaussianISAM::sharedClique C2 = isamTree[ordering[kx(3)]]; + GaussianISAM::sharedClique C2 = isamTree[ordering[X(3)]]; GaussianBayesNet actual2 = GaussianISAM::shortcut(C2,R); EXPECT(assert_equal(empty,actual2,tol)); // Check the conditional P(C3|Root), which should be equal to P(x2|x4) /** TODO: Note for multifrontal conditional: - * p_x2_x4 is now an element conditional of the multifrontal conditional bayesTree[ordering[kx(2)]]->conditional() + * p_x2_x4 is now an element conditional of the multifrontal conditional bayesTree[ordering[X(2)]]->conditional() * We don't know yet how to take it out. */ -// GaussianConditional::shared_ptr p_x2_x4 = bayesTree[ordering[kx(2)]]->conditional(); +// GaussianConditional::shared_ptr p_x2_x4 = bayesTree[ordering[X(2)]]->conditional(); // p_x2_x4->print("Conditional p_x2_x4: "); // GaussianBayesNet expected3(p_x2_x4); -// GaussianISAM::sharedClique C3 = isamTree[ordering[kx(1)]]; +// GaussianISAM::sharedClique C3 = isamTree[ordering[X(1)]]; // GaussianBayesNet actual3 = GaussianISAM::shortcut(C3,R); // EXPECT(assert_equal(expected3,actual3,tol)); } @@ -279,7 +255,7 @@ TEST_UNSAFE( BayesTree, balanced_smoother_shortcuts ) //{ // // Create smoother with 7 nodes // Ordering ordering; -// ordering += kx(1),kx(3),kx(5),kx(7),kx(2),kx(6),kx(4); +// ordering += X(1),X(3),X(5),X(7),X(2),X(6),X(4); // GaussianFactorGraph smoother = createSmoother(7, ordering).first; // // // Create the Bayes tree @@ -288,9 +264,9 @@ TEST_UNSAFE( BayesTree, balanced_smoother_shortcuts ) // // // Check the clique marginal P(C3) // double sigmax2_alt = 1/1.45533; // THIS NEEDS TO BE CHECKED! -// GaussianBayesNet expected = simpleGaussian(ordering[kx(2)],zero(2),sigmax2_alt); -// push_front(expected,ordering[kx(1)], zero(2), eye(2)*sqrt(2), ordering[kx(2)], -eye(2)*sqrt(2)/2, ones(2)); -// GaussianISAM::sharedClique R = bayesTree.root(), C3 = bayesTree[ordering[kx(1)]]; +// GaussianBayesNet expected = simpleGaussian(ordering[X(2)],zero(2),sigmax2_alt); +// push_front(expected,ordering[X(1)], zero(2), eye(2)*sqrt(2), ordering[X(2)], -eye(2)*sqrt(2)/2, ones(2)); +// GaussianISAM::sharedClique R = bayesTree.root(), C3 = bayesTree[ordering[X(1)]]; // GaussianFactorGraph marginal = C3->marginal(R); // GaussianVariableIndex varIndex(marginal); // Permutation toFront(Permutation::PullToFront(C3->keys(), varIndex.size())); @@ -308,7 +284,7 @@ TEST_UNSAFE( BayesTree, balanced_smoother_joint ) { // Create smoother with 7 nodes Ordering ordering; - ordering += kx(1),kx(3),kx(5),kx(7),kx(2),kx(6),kx(4); + ordering += X(1),X(3),X(5),X(7),X(2),X(6),X(4); GaussianFactorGraph smoother = createSmoother(7, ordering).first; // Create the Bayes tree, expected to look like: @@ -327,41 +303,41 @@ TEST_UNSAFE( BayesTree, balanced_smoother_joint ) GaussianBayesNet expected1; // Why does the sign get flipped on the prior? GaussianConditional::shared_ptr - parent1(new GaussianConditional(ordering[kx(7)], zero(2), -1*I/sigmax7, ones(2))); + parent1(new GaussianConditional(ordering[X(7)], zero(2), -1*I/sigmax7, ones(2))); expected1.push_front(parent1); - push_front(expected1,ordering[kx(1)], zero(2), I/sigmax7, ordering[kx(7)], A/sigmax7, sigma); - GaussianBayesNet actual1 = *bayesTree.jointBayesNet(ordering[kx(1)],ordering[kx(7)]); + push_front(expected1,ordering[X(1)], zero(2), I/sigmax7, ordering[X(7)], A/sigmax7, sigma); + GaussianBayesNet actual1 = *bayesTree.jointBayesNet(ordering[X(1)],ordering[X(7)]); EXPECT(assert_equal(expected1,actual1,tol)); // // Check the joint density P(x7,x1) factored as P(x7|x1)P(x1) // GaussianBayesNet expected2; // GaussianConditional::shared_ptr -// parent2(new GaussianConditional(ordering[kx(1)], zero(2), -1*I/sigmax1, ones(2))); +// parent2(new GaussianConditional(ordering[X(1)], zero(2), -1*I/sigmax1, ones(2))); // expected2.push_front(parent2); -// push_front(expected2,ordering[kx(7)], zero(2), I/sigmax1, ordering[kx(1)], A/sigmax1, sigma); -// GaussianBayesNet actual2 = *bayesTree.jointBayesNet(ordering[kx(7)],ordering[kx(1)]); +// push_front(expected2,ordering[X(7)], zero(2), I/sigmax1, ordering[X(1)], A/sigmax1, sigma); +// GaussianBayesNet actual2 = *bayesTree.jointBayesNet(ordering[X(7)],ordering[X(1)]); // EXPECT(assert_equal(expected2,actual2,tol)); // Check the joint density P(x1,x4), i.e. with a root variable GaussianBayesNet expected3; GaussianConditional::shared_ptr - parent3(new GaussianConditional(ordering[kx(4)], zero(2), I/sigmax4, ones(2))); + parent3(new GaussianConditional(ordering[X(4)], zero(2), I/sigmax4, ones(2))); expected3.push_front(parent3); double sig14 = 0.784465; Matrix A14 = -0.0769231*I; - push_front(expected3,ordering[kx(1)], zero(2), I/sig14, ordering[kx(4)], A14/sig14, sigma); - GaussianBayesNet actual3 = *bayesTree.jointBayesNet(ordering[kx(1)],ordering[kx(4)]); + push_front(expected3,ordering[X(1)], zero(2), I/sig14, ordering[X(4)], A14/sig14, sigma); + GaussianBayesNet actual3 = *bayesTree.jointBayesNet(ordering[X(1)],ordering[X(4)]); EXPECT(assert_equal(expected3,actual3,tol)); // // Check the joint density P(x4,x1), i.e. with a root variable, factored the other way // GaussianBayesNet expected4; // GaussianConditional::shared_ptr -// parent4(new GaussianConditional(ordering[kx(1)], zero(2), -1.0*I/sigmax1, ones(2))); +// parent4(new GaussianConditional(ordering[X(1)], zero(2), -1.0*I/sigmax1, ones(2))); // expected4.push_front(parent4); // double sig41 = 0.668096; // Matrix A41 = -0.055794*I; -// push_front(expected4,ordering[kx(4)], zero(2), I/sig41, ordering[kx(1)], A41/sig41, sigma); -// GaussianBayesNet actual4 = *bayesTree.jointBayesNet(ordering[kx(4)],ordering[kx(1)]); +// push_front(expected4,ordering[X(4)], zero(2), I/sig41, ordering[X(1)], A41/sig41, sigma); +// GaussianBayesNet actual4 = *bayesTree.jointBayesNet(ordering[X(4)],ordering[X(1)]); // EXPECT(assert_equal(expected4,actual4,tol)); } @@ -372,9 +348,9 @@ TEST_UNSAFE(BayesTree, simpleMarginal) Matrix A12 = Rot2::fromDegrees(45.0).matrix(); - gfg.add(0, eye(2), zero(2), sharedSigma(2, 1.0)); - gfg.add(0, -eye(2), 1, eye(2), ones(2), sharedSigma(2, 1.0)); - gfg.add(1, -eye(2), 2, A12, ones(2), sharedSigma(2, 1.0)); + gfg.add(0, eye(2), zero(2), noiseModel::Isotropic::Sigma(2, 1.0)); + gfg.add(0, -eye(2), 1, eye(2), ones(2), noiseModel::Isotropic::Sigma(2, 1.0)); + gfg.add(1, -eye(2), 2, A12, ones(2), noiseModel::Isotropic::Sigma(2, 1.0)); Matrix expected(GaussianSequentialSolver(gfg).marginalCovariance(2)); Matrix actual(GaussianMultifrontalSolver(gfg).marginalCovariance(2)); diff --git a/tests/testGaussianISAM2.cpp b/tests/testGaussianISAM2.cpp index 40e1ca4e1..c4b90d882 100644 --- a/tests/testGaussianISAM2.cpp +++ b/tests/testGaussianISAM2.cpp @@ -4,93 +4,99 @@ * @author Michael Kaess */ +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +#include + #include #include // for operator += #include using namespace boost::assign; -#include - -#include -#include -#include -#include -#include -#include -#include -#include -#include - using namespace std; using namespace gtsam; -using namespace example; using boost::shared_ptr; const double tol = 1e-4; +// SETDEBUG("ISAM2 update", true); +// SETDEBUG("ISAM2 update verbose", true); +// SETDEBUG("ISAM2 recalculate", true); + +// Set up parameters +SharedDiagonal odoNoise = noiseModel::Diagonal::Sigmas(Vector_(3, 0.1, 0.1, M_PI/100.0)); +SharedDiagonal brNoise = noiseModel::Diagonal::Sigmas(Vector_(2, M_PI/100.0, 0.1)); + ISAM2 createSlamlikeISAM2( boost::optional init_values = boost::none, - boost::optional full_graph = boost::none, + boost::optional full_graph = boost::none, const ISAM2Params& params = ISAM2Params(ISAM2GaussNewtonParams(0.001), 0.0, 0, false, true)) { - // Pose and landmark key types from planarSLAM - using planarSLAM::PoseKey; - using planarSLAM::PointKey; - - // Set up parameters - SharedDiagonal odoNoise = sharedSigmas(Vector_(3, 0.1, 0.1, M_PI/100.0)); - SharedDiagonal brNoise = sharedSigmas(Vector_(2, M_PI/100.0, 0.1)); - // These variables will be reused and accumulate factors and values ISAM2 isam(params); -// ISAM2 isam(ISAM2Params(ISAM2GaussNewtonParams(0.001), 0.0, 0, false, true)); Values fullinit; - planarSLAM::Graph fullgraph; + NonlinearFactorGraph fullgraph; // i keeps track of the time step size_t i = 0; // Add a prior at time 0 and update isam { - planarSLAM::Graph newfactors; - newfactors.addPrior(0, Pose2(0.0, 0.0, 0.0), odoNoise); + NonlinearFactorGraph newfactors; + newfactors.add(PriorFactor(0, Pose2(0.0, 0.0, 0.0), odoNoise)); fullgraph.push_back(newfactors); Values init; - init.insert(PoseKey(0), Pose2(0.01, 0.01, 0.01)); - fullinit.insert(PoseKey(0), Pose2(0.01, 0.01, 0.01)); + init.insert((0), Pose2(0.01, 0.01, 0.01)); + fullinit.insert((0), Pose2(0.01, 0.01, 0.01)); isam.update(newfactors, init); } // Add odometry from time 0 to time 5 for( ; i<5; ++i) { - planarSLAM::Graph newfactors; - newfactors.addOdometry(i, i+1, Pose2(1.0, 0.0, 0.0), odoNoise); + NonlinearFactorGraph newfactors; + newfactors.add(BetweenFactor(i, i+1, Pose2(1.0, 0.0, 0.0), odoNoise)); fullgraph.push_back(newfactors); Values init; - init.insert(PoseKey(i+1), Pose2(double(i+1)+0.1, -0.1, 0.01)); - fullinit.insert(PoseKey(i+1), Pose2(double(i+1)+0.1, -0.1, 0.01)); + init.insert((i+1), Pose2(double(i+1)+0.1, -0.1, 0.01)); + fullinit.insert((i+1), Pose2(double(i+1)+0.1, -0.1, 0.01)); isam.update(newfactors, init); } // Add odometry from time 5 to 6 and landmark measurement at time 5 { - planarSLAM::Graph newfactors; - newfactors.addOdometry(i, i+1, Pose2(1.0, 0.0, 0.0), odoNoise); - newfactors.addBearingRange(i, 0, Rot2::fromAngle(M_PI/4.0), 5.0, brNoise); - newfactors.addBearingRange(i, 1, Rot2::fromAngle(-M_PI/4.0), 5.0, brNoise); + NonlinearFactorGraph newfactors; + newfactors.add(BetweenFactor(i, i+1, Pose2(1.0, 0.0, 0.0), odoNoise)); + newfactors.add(BearingRangeFactor(i, 100, Rot2::fromAngle(M_PI/4.0), 5.0, brNoise)); + newfactors.add(BearingRangeFactor(i, 101, Rot2::fromAngle(-M_PI/4.0), 5.0, brNoise)); fullgraph.push_back(newfactors); Values init; - init.insert(PoseKey(i+1), Pose2(1.01, 0.01, 0.01)); - init.insert(PointKey(0), Point2(5.0/sqrt(2.0), 5.0/sqrt(2.0))); - init.insert(PointKey(1), Point2(5.0/sqrt(2.0), -5.0/sqrt(2.0))); - fullinit.insert(PoseKey(i+1), Pose2(1.01, 0.01, 0.01)); - fullinit.insert(PointKey(0), Point2(5.0/sqrt(2.0), 5.0/sqrt(2.0))); - fullinit.insert(PointKey(1), Point2(5.0/sqrt(2.0), -5.0/sqrt(2.0))); + init.insert((i+1), Pose2(1.01, 0.01, 0.01)); + init.insert(100, Point2(5.0/sqrt(2.0), 5.0/sqrt(2.0))); + init.insert(101, Point2(5.0/sqrt(2.0), -5.0/sqrt(2.0))); + fullinit.insert((i+1), Pose2(1.01, 0.01, 0.01)); + fullinit.insert(100, Point2(5.0/sqrt(2.0), 5.0/sqrt(2.0))); + fullinit.insert(101, Point2(5.0/sqrt(2.0), -5.0/sqrt(2.0))); isam.update(newfactors, init); ++ i; @@ -98,28 +104,28 @@ ISAM2 createSlamlikeISAM2( // Add odometry from time 6 to time 10 for( ; i<10; ++i) { - planarSLAM::Graph newfactors; - newfactors.addOdometry(i, i+1, Pose2(1.0, 0.0, 0.0), odoNoise); + NonlinearFactorGraph newfactors; + newfactors.add(BetweenFactor(i, i+1, Pose2(1.0, 0.0, 0.0), odoNoise)); fullgraph.push_back(newfactors); Values init; - init.insert(PoseKey(i+1), Pose2(double(i+1)+0.1, -0.1, 0.01)); - fullinit.insert(PoseKey(i+1), Pose2(double(i+1)+0.1, -0.1, 0.01)); + init.insert((i+1), Pose2(double(i+1)+0.1, -0.1, 0.01)); + fullinit.insert((i+1), Pose2(double(i+1)+0.1, -0.1, 0.01)); isam.update(newfactors, init); } // Add odometry from time 10 to 11 and landmark measurement at time 10 { - planarSLAM::Graph newfactors; - newfactors.addOdometry(i, i+1, Pose2(1.0, 0.0, 0.0), odoNoise); - newfactors.addBearingRange(i, 0, Rot2::fromAngle(M_PI/4.0 + M_PI/16.0), 4.5, brNoise); - newfactors.addBearingRange(i, 1, Rot2::fromAngle(-M_PI/4.0 + M_PI/16.0), 4.5, brNoise); + NonlinearFactorGraph newfactors; + newfactors.add(BetweenFactor(i, i+1, Pose2(1.0, 0.0, 0.0), odoNoise)); + newfactors.add(BearingRangeFactor(i, 100, Rot2::fromAngle(M_PI/4.0 + M_PI/16.0), 4.5, brNoise)); + newfactors.add(BearingRangeFactor(i, 101, Rot2::fromAngle(-M_PI/4.0 + M_PI/16.0), 4.5, brNoise)); fullgraph.push_back(newfactors); Values init; - init.insert(PoseKey(i+1), Pose2(6.9, 0.1, 0.01)); - fullinit.insert(PoseKey(i+1), Pose2(6.9, 0.1, 0.01)); + init.insert((i+1), Pose2(6.9, 0.1, 0.01)); + fullinit.insert((i+1), Pose2(6.9, 0.1, 0.01)); isam.update(newfactors, init); ++ i; @@ -135,119 +141,161 @@ ISAM2 createSlamlikeISAM2( } /* ************************************************************************* */ -TEST_UNSAFE(ISAM2, AddVariables) { +TEST_UNSAFE(ISAM2, ImplAddVariables) { // Create initial state Values theta; - theta.insert(planarSLAM::PoseKey(0), Pose2(.1, .2, .3)); - theta.insert(planarSLAM::PointKey(0), Point2(.4, .5)); + theta.insert(0, Pose2(.1, .2, .3)); + theta.insert(100, Point2(.4, .5)); Values newTheta; - newTheta.insert(planarSLAM::PoseKey(1), Pose2(.6, .7, .8)); + newTheta.insert(1, Pose2(.6, .7, .8)); - VectorValues deltaUnpermuted; - deltaUnpermuted.insert(0, Vector_(3, .1, .2, .3)); - deltaUnpermuted.insert(1, Vector_(2, .4, .5)); + VectorValues delta; + delta.insert(0, Vector_(3, .1, .2, .3)); + delta.insert(1, Vector_(2, .4, .5)); - Permutation permutation(2); - permutation[0] = 1; - permutation[1] = 0; + VectorValues deltaNewton; + deltaNewton.insert(0, Vector_(3, .1, .2, .3)); + deltaNewton.insert(1, Vector_(2, .4, .5)); - Permuted delta(permutation, deltaUnpermuted); - - VectorValues deltaNewtonUnpermuted; - deltaNewtonUnpermuted.insert(0, Vector_(3, .1, .2, .3)); - deltaNewtonUnpermuted.insert(1, Vector_(2, .4, .5)); - - Permutation permutationNewton(2); - permutationNewton[0] = 1; - permutationNewton[1] = 0; - - Permuted deltaNewton(permutationNewton, deltaNewtonUnpermuted); - - VectorValues deltaRgUnpermuted; - deltaRgUnpermuted.insert(0, Vector_(3, .1, .2, .3)); - deltaRgUnpermuted.insert(1, Vector_(2, .4, .5)); - - Permutation permutationRg(2); - permutationRg[0] = 1; - permutationRg[1] = 0; - - Permuted deltaRg(permutationRg, deltaRgUnpermuted); + VectorValues deltaRg; + deltaRg.insert(0, Vector_(3, .1, .2, .3)); + deltaRg.insert(1, Vector_(2, .4, .5)); vector replacedKeys(2, false); - Ordering ordering; ordering += planarSLAM::PointKey(0), planarSLAM::PoseKey(0); - - ISAM2::Nodes nodes(2); + Ordering ordering; ordering += 100, 0; // Verify initial state - LONGS_EQUAL(0, ordering[planarSLAM::PointKey(0)]); - LONGS_EQUAL(1, ordering[planarSLAM::PoseKey(0)]); - EXPECT(assert_equal(deltaUnpermuted[1], delta[ordering[planarSLAM::PointKey(0)]])); - EXPECT(assert_equal(deltaUnpermuted[0], delta[ordering[planarSLAM::PoseKey(0)]])); + LONGS_EQUAL(0, ordering[100]); + LONGS_EQUAL(1, ordering[0]); + EXPECT(assert_equal(delta[0], delta[ordering[100]])); + EXPECT(assert_equal(delta[1], delta[ordering[0]])); // Create expected state Values thetaExpected; - thetaExpected.insert(planarSLAM::PoseKey(0), Pose2(.1, .2, .3)); - thetaExpected.insert(planarSLAM::PointKey(0), Point2(.4, .5)); - thetaExpected.insert(planarSLAM::PoseKey(1), Pose2(.6, .7, .8)); + thetaExpected.insert(0, Pose2(.1, .2, .3)); + thetaExpected.insert(100, Point2(.4, .5)); + thetaExpected.insert(1, Pose2(.6, .7, .8)); - VectorValues deltaUnpermutedExpected; - deltaUnpermutedExpected.insert(0, Vector_(3, .1, .2, .3)); - deltaUnpermutedExpected.insert(1, Vector_(2, .4, .5)); - deltaUnpermutedExpected.insert(2, Vector_(3, 0.0, 0.0, 0.0)); + VectorValues deltaExpected; + deltaExpected.insert(0, Vector_(3, .1, .2, .3)); + deltaExpected.insert(1, Vector_(2, .4, .5)); + deltaExpected.insert(2, Vector_(3, 0.0, 0.0, 0.0)); - Permutation permutationExpected(3); - permutationExpected[0] = 1; - permutationExpected[1] = 0; - permutationExpected[2] = 2; + VectorValues deltaNewtonExpected; + deltaNewtonExpected.insert(0, Vector_(3, .1, .2, .3)); + deltaNewtonExpected.insert(1, Vector_(2, .4, .5)); + deltaNewtonExpected.insert(2, Vector_(3, 0.0, 0.0, 0.0)); - Permuted deltaExpected(permutationExpected, deltaUnpermutedExpected); - - VectorValues deltaNewtonUnpermutedExpected; - deltaNewtonUnpermutedExpected.insert(0, Vector_(3, .1, .2, .3)); - deltaNewtonUnpermutedExpected.insert(1, Vector_(2, .4, .5)); - deltaNewtonUnpermutedExpected.insert(2, Vector_(3, 0.0, 0.0, 0.0)); - - Permutation permutationNewtonExpected(3); - permutationNewtonExpected[0] = 1; - permutationNewtonExpected[1] = 0; - permutationNewtonExpected[2] = 2; - - Permuted deltaNewtonExpected(permutationNewtonExpected, deltaNewtonUnpermutedExpected); - - VectorValues deltaRgUnpermutedExpected; - deltaRgUnpermutedExpected.insert(0, Vector_(3, .1, .2, .3)); - deltaRgUnpermutedExpected.insert(1, Vector_(2, .4, .5)); - deltaRgUnpermutedExpected.insert(2, Vector_(3, 0.0, 0.0, 0.0)); - - Permutation permutationRgExpected(3); - permutationRgExpected[0] = 1; - permutationRgExpected[1] = 0; - permutationRgExpected[2] = 2; - - Permuted deltaRgExpected(permutationRgExpected, deltaRgUnpermutedExpected); + VectorValues deltaRgExpected; + deltaRgExpected.insert(0, Vector_(3, .1, .2, .3)); + deltaRgExpected.insert(1, Vector_(2, .4, .5)); + deltaRgExpected.insert(2, Vector_(3, 0.0, 0.0, 0.0)); vector replacedKeysExpected(3, false); - Ordering orderingExpected; orderingExpected += planarSLAM::PointKey(0), planarSLAM::PoseKey(0), planarSLAM::PoseKey(1); - - ISAM2::Nodes nodesExpected( - 3, ISAM2::sharedClique()); + Ordering orderingExpected; orderingExpected += 100, 0, 1; // Expand initial state - ISAM2::Impl::AddVariables(newTheta, theta, delta, deltaNewton, deltaRg, replacedKeys, ordering, nodes); + ISAM2::Impl::AddVariables(newTheta, theta, delta, deltaNewton, deltaRg, replacedKeys, ordering); EXPECT(assert_equal(thetaExpected, theta)); - EXPECT(assert_equal(deltaUnpermutedExpected, deltaUnpermuted)); - EXPECT(assert_equal(deltaExpected.permutation(), delta.permutation())); - EXPECT(assert_equal(deltaNewtonUnpermutedExpected, deltaNewtonUnpermuted)); - EXPECT(assert_equal(deltaNewtonExpected.permutation(), deltaNewton.permutation())); - EXPECT(assert_equal(deltaRgUnpermutedExpected, deltaRgUnpermuted)); - EXPECT(assert_equal(deltaRgExpected.permutation(), deltaRg.permutation())); + EXPECT(assert_equal(deltaExpected, delta)); + EXPECT(assert_equal(deltaNewtonExpected, deltaNewton)); + EXPECT(assert_equal(deltaRgExpected, deltaRg)); EXPECT(assert_container_equality(replacedKeysExpected, replacedKeys)); EXPECT(assert_equal(orderingExpected, ordering)); } +/* ************************************************************************* */ +TEST_UNSAFE(ISAM2, ImplRemoveVariables) { + + // Create initial state + Values theta; + theta.insert(0, Pose2(.1, .2, .3)); + theta.insert(1, Pose2(.6, .7, .8)); + theta.insert(100, Point2(.4, .5)); + + SymbolicFactorGraph sfg; + sfg.push_back(boost::make_shared(Index(0), Index(2))); + sfg.push_back(boost::make_shared(Index(0), Index(1))); + VariableIndex variableIndex(sfg); + + VectorValues delta; + delta.insert(0, Vector_(3, .1, .2, .3)); + delta.insert(1, Vector_(3, .4, .5, .6)); + delta.insert(2, Vector_(2, .7, .8)); + + VectorValues deltaNewton; + deltaNewton.insert(0, Vector_(3, .1, .2, .3)); + deltaNewton.insert(1, Vector_(3, .4, .5, .6)); + deltaNewton.insert(2, Vector_(2, .7, .8)); + + VectorValues deltaRg; + deltaRg.insert(0, Vector_(3, .1, .2, .3)); + deltaRg.insert(1, Vector_(3, .4, .5, .6)); + deltaRg.insert(2, Vector_(2, .7, .8)); + + vector replacedKeys(3, false); + replacedKeys[0] = true; + replacedKeys[1] = false; + replacedKeys[2] = true; + + Ordering ordering; ordering += 100, 1, 0; + + ISAM2::Nodes nodes(3); + + // Verify initial state + LONGS_EQUAL(0, ordering[100]); + LONGS_EQUAL(1, ordering[1]); + LONGS_EQUAL(2, ordering[0]); + + // Create expected state + Values thetaExpected; + thetaExpected.insert(0, Pose2(.1, .2, .3)); + thetaExpected.insert(100, Point2(.4, .5)); + + SymbolicFactorGraph sfgRemoved; + sfgRemoved.push_back(boost::make_shared(Index(0), Index(1))); + sfgRemoved.push_back(SymbolicFactorGraph::sharedFactor()); // Add empty factor to keep factor indices consistent + VariableIndex variableIndexExpected(sfgRemoved); + + VectorValues deltaExpected; + deltaExpected.insert(0, Vector_(3, .1, .2, .3)); + deltaExpected.insert(1, Vector_(2, .7, .8)); + + VectorValues deltaNewtonExpected; + deltaNewtonExpected.insert(0, Vector_(3, .1, .2, .3)); + deltaNewtonExpected.insert(1, Vector_(2, .7, .8)); + + VectorValues deltaRgExpected; + deltaRgExpected.insert(0, Vector_(3, .1, .2, .3)); + deltaRgExpected.insert(1, Vector_(2, .7, .8)); + + vector replacedKeysExpected(2, true); + + Ordering orderingExpected; orderingExpected += 100, 0; + + ISAM2::Nodes nodesExpected(2); + + // Reduce initial state + FastSet unusedKeys; + unusedKeys.insert(1); + vector removedFactorsI; removedFactorsI.push_back(1); + SymbolicFactorGraph removedFactors; removedFactors.push_back(sfg[1]); + variableIndex.remove(removedFactorsI, removedFactors); + GaussianFactorGraph linearFactors; + ISAM2::Impl::RemoveVariables(unusedKeys, ISAM2::sharedClique(), theta, variableIndex, delta, deltaNewton, deltaRg, + replacedKeys, ordering, nodes, linearFactors); + + EXPECT(assert_equal(thetaExpected, theta)); + EXPECT(assert_equal(variableIndexExpected, variableIndex)); + EXPECT(assert_equal(deltaExpected, delta)); + EXPECT(assert_equal(deltaNewtonExpected, deltaNewton)); + EXPECT(assert_equal(deltaRgExpected, deltaRg)); + EXPECT(assert_container_equality(replacedKeysExpected, replacedKeys)); + EXPECT(assert_equal(orderingExpected, ordering)); +} /* ************************************************************************* */ //TEST(ISAM2, IndicesFromFactors) { @@ -255,10 +303,10 @@ TEST_UNSAFE(ISAM2, AddVariables) { // using namespace gtsam::planarSLAM; // typedef GaussianISAM2::Impl Impl; // -// Ordering ordering; ordering += PointKey(0), PoseKey(0), PoseKey(1); -// planarSLAM::Graph graph; -// graph.addPrior(PoseKey(0), Pose2(), sharedUnit(Pose2::dimension)); -// graph.addRange(PoseKey(0), PointKey(0), 1.0, sharedUnit(1)); +// Ordering ordering; ordering += (0), (0), (1); +// NonlinearFactorGraph graph; +// graph.add(PriorFactor((0), Pose2(), noiseModel::Unit::Create(Pose2::dimension)); +// graph.addRange((0), (0), 1.0, noiseModel::Unit::Create(1)); // // FastSet expected; // expected.insert(0); @@ -307,7 +355,7 @@ TEST(ISAM2, optimize2) { // Create initialization Values theta; - theta.insert(planarSLAM::PoseKey(0), Pose2(0.01, 0.01, 0.01)); + theta.insert((0), Pose2(0.01, 0.01, 0.01)); // Create conditional Vector d(3); d << -0.1, -0.1, -0.31831; @@ -318,7 +366,7 @@ TEST(ISAM2, optimize2) { GaussianConditional::shared_ptr conditional(new GaussianConditional(0, d, R, Vector::Ones(3))); // Create ordering - Ordering ordering; ordering += planarSLAM::PoseKey(0); + Ordering ordering; ordering += (0); // Expected vector VectorValues expected(1, 3); @@ -336,7 +384,11 @@ TEST(ISAM2, optimize2) { } /* ************************************************************************* */ -bool isam_check(const planarSLAM::Graph& fullgraph, const Values& fullinit, const ISAM2& isam) { +bool isam_check(const NonlinearFactorGraph& fullgraph, const Values& fullinit, const ISAM2& isam, Test& test, TestResult& result) { + + TestResult& result_ = result; + const std::string name_ = test.getName(); + Values actual = isam.calculateEstimate(); Ordering ordering = isam.getOrdering(); // *fullgraph.orderingCOLAMD(fullinit).first; GaussianFactorGraph linearized = *fullgraph.linearize(fullinit, ordering); @@ -346,539 +398,94 @@ bool isam_check(const planarSLAM::Graph& fullgraph, const Values& fullinit, cons VectorValues delta = optimize(gbn); Values expected = fullinit.retract(delta, ordering); - return assert_equal(expected, actual); + bool isamEqual = assert_equal(expected, actual); + + // The following two checks make sure that the cached gradients are maintained and used correctly + + // Check gradient at each node + bool nodeGradientsOk = true; + typedef ISAM2::sharedClique sharedClique; + BOOST_FOREACH(const sharedClique& clique, isam.nodes()) { + // Compute expected gradient + FactorGraph jfg; + jfg.push_back(JacobianFactor::shared_ptr(new JacobianFactor(*clique->conditional()))); + VectorValues expectedGradient(*allocateVectorValues(isam)); + gradientAtZero(jfg, expectedGradient); + // Compare with actual gradients + int variablePosition = 0; + for(GaussianConditional::const_iterator jit = clique->conditional()->begin(); jit != clique->conditional()->end(); ++jit) { + const int dim = clique->conditional()->dim(jit); + Vector actual = clique->gradientContribution().segment(variablePosition, dim); + bool gradOk = assert_equal(expectedGradient[*jit], actual); + EXPECT(gradOk); + nodeGradientsOk = nodeGradientsOk && gradOk; + variablePosition += dim; + } + bool dimOk = clique->gradientContribution().rows() == variablePosition; + EXPECT(dimOk); + nodeGradientsOk = nodeGradientsOk && dimOk; + } + + // Check gradient + VectorValues expectedGradient(*allocateVectorValues(isam)); + gradientAtZero(FactorGraph(isam), expectedGradient); + VectorValues expectedGradient2(gradient(FactorGraph(isam), VectorValues::Zero(expectedGradient))); + VectorValues actualGradient(*allocateVectorValues(isam)); + gradientAtZero(isam, actualGradient); + bool expectedGradOk = assert_equal(expectedGradient2, expectedGradient); + EXPECT(expectedGradOk); + bool totalGradOk = assert_equal(expectedGradient, actualGradient); + EXPECT(totalGradOk); + + return nodeGradientsOk && expectedGradOk && totalGradOk && isamEqual; } /* ************************************************************************* */ TEST(ISAM2, slamlike_solution_gaussnewton) { - -// SETDEBUG("ISAM2 update", true); -// SETDEBUG("ISAM2 update verbose", true); -// SETDEBUG("ISAM2 recalculate", true); - - // Pose and landmark key types from planarSLAM - using planarSLAM::PoseKey; - using planarSLAM::PointKey; - - // Set up parameters - SharedDiagonal odoNoise = sharedSigmas(Vector_(3, 0.1, 0.1, M_PI/100.0)); - SharedDiagonal brNoise = sharedSigmas(Vector_(2, M_PI/100.0, 0.1)); - // These variables will be reused and accumulate factors and values - ISAM2 isam(ISAM2Params(ISAM2GaussNewtonParams(0.001), 0.0, 0, false)); Values fullinit; - planarSLAM::Graph fullgraph; - - // i keeps track of the time step - size_t i = 0; - - // Add a prior at time 0 and update isam - { - planarSLAM::Graph newfactors; - newfactors.addPrior(0, Pose2(0.0, 0.0, 0.0), odoNoise); - fullgraph.push_back(newfactors); - - Values init; - init.insert(PoseKey(0), Pose2(0.01, 0.01, 0.01)); - fullinit.insert(PoseKey(0), Pose2(0.01, 0.01, 0.01)); - - isam.update(newfactors, init); - } - - CHECK(isam_check(fullgraph, fullinit, isam)); - - // Add odometry from time 0 to time 5 - for( ; i<5; ++i) { - planarSLAM::Graph newfactors; - newfactors.addOdometry(i, i+1, Pose2(1.0, 0.0, 0.0), odoNoise); - fullgraph.push_back(newfactors); - - Values init; - init.insert(PoseKey(i+1), Pose2(double(i+1)+0.1, -0.1, 0.01)); - fullinit.insert(PoseKey(i+1), Pose2(double(i+1)+0.1, -0.1, 0.01)); - - isam.update(newfactors, init); - } - - // Add odometry from time 5 to 6 and landmark measurement at time 5 - { - planarSLAM::Graph newfactors; - newfactors.addOdometry(i, i+1, Pose2(1.0, 0.0, 0.0), odoNoise); - newfactors.addBearingRange(i, 0, Rot2::fromAngle(M_PI/4.0), 5.0, brNoise); - newfactors.addBearingRange(i, 1, Rot2::fromAngle(-M_PI/4.0), 5.0, brNoise); - fullgraph.push_back(newfactors); - - Values init; - init.insert(PoseKey(i+1), Pose2(1.01, 0.01, 0.01)); - init.insert(PointKey(0), Point2(5.0/sqrt(2.0), 5.0/sqrt(2.0))); - init.insert(PointKey(1), Point2(5.0/sqrt(2.0), -5.0/sqrt(2.0))); - fullinit.insert(PoseKey(i+1), Pose2(1.01, 0.01, 0.01)); - fullinit.insert(PointKey(0), Point2(5.0/sqrt(2.0), 5.0/sqrt(2.0))); - fullinit.insert(PointKey(1), Point2(5.0/sqrt(2.0), -5.0/sqrt(2.0))); - - isam.update(newfactors, init); - ++ i; - } - - // Add odometry from time 6 to time 10 - for( ; i<10; ++i) { - planarSLAM::Graph newfactors; - newfactors.addOdometry(i, i+1, Pose2(1.0, 0.0, 0.0), odoNoise); - fullgraph.push_back(newfactors); - - Values init; - init.insert(PoseKey(i+1), Pose2(double(i+1)+0.1, -0.1, 0.01)); - fullinit.insert(PoseKey(i+1), Pose2(double(i+1)+0.1, -0.1, 0.01)); - - isam.update(newfactors, init); - } - - // Add odometry from time 10 to 11 and landmark measurement at time 10 - { - planarSLAM::Graph newfactors; - newfactors.addOdometry(i, i+1, Pose2(1.0, 0.0, 0.0), odoNoise); - newfactors.addBearingRange(i, 0, Rot2::fromAngle(M_PI/4.0 + M_PI/16.0), 4.5, brNoise); - newfactors.addBearingRange(i, 1, Rot2::fromAngle(-M_PI/4.0 + M_PI/16.0), 4.5, brNoise); - fullgraph.push_back(newfactors); - - Values init; - init.insert(PoseKey(i+1), Pose2(6.9, 0.1, 0.01)); - fullinit.insert(PoseKey(i+1), Pose2(6.9, 0.1, 0.01)); - - isam.update(newfactors, init); - ++ i; - } + NonlinearFactorGraph fullgraph; + ISAM2 isam = createSlamlikeISAM2(fullinit, fullgraph, ISAM2Params(ISAM2GaussNewtonParams(0.001), 0.0, 0, false)); // Compare solutions - CHECK(isam_check(fullgraph, fullinit, isam)); - - // Check gradient at each node - typedef ISAM2::sharedClique sharedClique; - BOOST_FOREACH(const sharedClique& clique, isam.nodes()) { - // Compute expected gradient - FactorGraph jfg; - jfg.push_back(JacobianFactor::shared_ptr(new JacobianFactor(*clique->conditional()))); - VectorValues expectedGradient(*allocateVectorValues(isam)); - gradientAtZero(jfg, expectedGradient); - // Compare with actual gradients - int variablePosition = 0; - for(GaussianConditional::const_iterator jit = clique->conditional()->begin(); jit != clique->conditional()->end(); ++jit) { - const int dim = clique->conditional()->dim(jit); - Vector actual = clique->gradientContribution().segment(variablePosition, dim); - EXPECT(assert_equal(expectedGradient[*jit], actual)); - variablePosition += dim; - } - LONGS_EQUAL(clique->gradientContribution().rows(), variablePosition); - } - - // Check gradient - VectorValues expectedGradient(*allocateVectorValues(isam)); - gradientAtZero(FactorGraph(isam), expectedGradient); - VectorValues expectedGradient2(gradient(FactorGraph(isam), VectorValues::Zero(expectedGradient))); - VectorValues actualGradient(*allocateVectorValues(isam)); - gradientAtZero(isam, actualGradient); - EXPECT(assert_equal(expectedGradient2, expectedGradient)); - EXPECT(assert_equal(expectedGradient, actualGradient)); + CHECK(isam_check(fullgraph, fullinit, isam, *this, result_)); } /* ************************************************************************* */ TEST(ISAM2, slamlike_solution_dogleg) { - -// SETDEBUG("ISAM2 update", true); -// SETDEBUG("ISAM2 update verbose", true); -// SETDEBUG("ISAM2 recalculate", true); - - // Pose and landmark key types from planarSLAM - using planarSLAM::PoseKey; - using planarSLAM::PointKey; - - // Set up parameters - SharedDiagonal odoNoise = sharedSigmas(Vector_(3, 0.1, 0.1, M_PI/100.0)); - SharedDiagonal brNoise = sharedSigmas(Vector_(2, M_PI/100.0, 0.1)); - // These variables will be reused and accumulate factors and values - ISAM2 isam(ISAM2Params(ISAM2DoglegParams(1.0), 0.0, 0, false)); Values fullinit; - planarSLAM::Graph fullgraph; - - // i keeps track of the time step - size_t i = 0; - - // Add a prior at time 0 and update isam - { - planarSLAM::Graph newfactors; - newfactors.addPrior(0, Pose2(0.0, 0.0, 0.0), odoNoise); - fullgraph.push_back(newfactors); - - Values init; - init.insert(PoseKey(0), Pose2(0.01, 0.01, 0.01)); - fullinit.insert(PoseKey(0), Pose2(0.01, 0.01, 0.01)); - - isam.update(newfactors, init); - } - - CHECK(isam_check(fullgraph, fullinit, isam)); - - // Add odometry from time 0 to time 5 - for( ; i<5; ++i) { - planarSLAM::Graph newfactors; - newfactors.addOdometry(i, i+1, Pose2(1.0, 0.0, 0.0), odoNoise); - fullgraph.push_back(newfactors); - - Values init; - init.insert(PoseKey(i+1), Pose2(double(i+1)+0.1, -0.1, 0.01)); - fullinit.insert(PoseKey(i+1), Pose2(double(i+1)+0.1, -0.1, 0.01)); - - isam.update(newfactors, init); - } - - // Add odometry from time 5 to 6 and landmark measurement at time 5 - { - planarSLAM::Graph newfactors; - newfactors.addOdometry(i, i+1, Pose2(1.0, 0.0, 0.0), odoNoise); - newfactors.addBearingRange(i, 0, Rot2::fromAngle(M_PI/4.0), 5.0, brNoise); - newfactors.addBearingRange(i, 1, Rot2::fromAngle(-M_PI/4.0), 5.0, brNoise); - fullgraph.push_back(newfactors); - - Values init; - init.insert(PoseKey(i+1), Pose2(1.01, 0.01, 0.01)); - init.insert(PointKey(0), Point2(5.0/sqrt(2.0), 5.0/sqrt(2.0))); - init.insert(PointKey(1), Point2(5.0/sqrt(2.0), -5.0/sqrt(2.0))); - fullinit.insert(PoseKey(i+1), Pose2(1.01, 0.01, 0.01)); - fullinit.insert(PointKey(0), Point2(5.0/sqrt(2.0), 5.0/sqrt(2.0))); - fullinit.insert(PointKey(1), Point2(5.0/sqrt(2.0), -5.0/sqrt(2.0))); - - isam.update(newfactors, init); - ++ i; - } - - // Add odometry from time 6 to time 10 - for( ; i<10; ++i) { - planarSLAM::Graph newfactors; - newfactors.addOdometry(i, i+1, Pose2(1.0, 0.0, 0.0), odoNoise); - fullgraph.push_back(newfactors); - - Values init; - init.insert(PoseKey(i+1), Pose2(double(i+1)+0.1, -0.1, 0.01)); - fullinit.insert(PoseKey(i+1), Pose2(double(i+1)+0.1, -0.1, 0.01)); - - isam.update(newfactors, init); - } - - // Add odometry from time 10 to 11 and landmark measurement at time 10 - { - planarSLAM::Graph newfactors; - newfactors.addOdometry(i, i+1, Pose2(1.0, 0.0, 0.0), odoNoise); - newfactors.addBearingRange(i, 0, Rot2::fromAngle(M_PI/4.0 + M_PI/16.0), 4.5, brNoise); - newfactors.addBearingRange(i, 1, Rot2::fromAngle(-M_PI/4.0 + M_PI/16.0), 4.5, brNoise); - fullgraph.push_back(newfactors); - - Values init; - init.insert(PoseKey(i+1), Pose2(6.9, 0.1, 0.01)); - fullinit.insert(PoseKey(i+1), Pose2(6.9, 0.1, 0.01)); - - isam.update(newfactors, init); - ++ i; - } + NonlinearFactorGraph fullgraph; + ISAM2 isam = createSlamlikeISAM2(fullinit, fullgraph, ISAM2Params(ISAM2DoglegParams(1.0), 0.0, 0, false)); // Compare solutions - CHECK(isam_check(fullgraph, fullinit, isam)); - - // Check gradient at each node - typedef ISAM2::sharedClique sharedClique; - BOOST_FOREACH(const sharedClique& clique, isam.nodes()) { - // Compute expected gradient - FactorGraph jfg; - jfg.push_back(JacobianFactor::shared_ptr(new JacobianFactor(*clique->conditional()))); - VectorValues expectedGradient(*allocateVectorValues(isam)); - gradientAtZero(jfg, expectedGradient); - // Compare with actual gradients - int variablePosition = 0; - for(GaussianConditional::const_iterator jit = clique->conditional()->begin(); jit != clique->conditional()->end(); ++jit) { - const int dim = clique->conditional()->dim(jit); - Vector actual = clique->gradientContribution().segment(variablePosition, dim); - EXPECT(assert_equal(expectedGradient[*jit], actual)); - variablePosition += dim; - } - LONGS_EQUAL(clique->gradientContribution().rows(), variablePosition); - } - - // Check gradient - VectorValues expectedGradient(*allocateVectorValues(isam)); - gradientAtZero(FactorGraph(isam), expectedGradient); - VectorValues expectedGradient2(gradient(FactorGraph(isam), VectorValues::Zero(expectedGradient))); - VectorValues actualGradient(*allocateVectorValues(isam)); - gradientAtZero(isam, actualGradient); - EXPECT(assert_equal(expectedGradient2, expectedGradient)); - EXPECT(assert_equal(expectedGradient, actualGradient)); + CHECK(isam_check(fullgraph, fullinit, isam, *this, result_)); } /* ************************************************************************* */ TEST(ISAM2, slamlike_solution_gaussnewton_qr) { - -// SETDEBUG("ISAM2 update", true); -// SETDEBUG("ISAM2 update verbose", true); -// SETDEBUG("ISAM2 recalculate", true); - - // Pose and landmark key types from planarSLAM - using planarSLAM::PoseKey; - using planarSLAM::PointKey; - - // Set up parameters - SharedDiagonal odoNoise = sharedSigmas(Vector_(3, 0.1, 0.1, M_PI/100.0)); - SharedDiagonal brNoise = sharedSigmas(Vector_(2, M_PI/100.0, 0.1)); - // These variables will be reused and accumulate factors and values - ISAM2 isam(ISAM2Params(ISAM2GaussNewtonParams(0.001), 0.0, 0, false, false, ISAM2Params::QR)); Values fullinit; - planarSLAM::Graph fullgraph; + NonlinearFactorGraph fullgraph; + ISAM2 isam = createSlamlikeISAM2(fullinit, fullgraph, ISAM2Params(ISAM2GaussNewtonParams(0.001), 0.0, 0, false, false, ISAM2Params::QR)); - // i keeps track of the time step - size_t i = 0; - - // Add a prior at time 0 and update isam - { - planarSLAM::Graph newfactors; - newfactors.addPrior(0, Pose2(0.0, 0.0, 0.0), odoNoise); - fullgraph.push_back(newfactors); - - Values init; - init.insert(PoseKey(0), Pose2(0.01, 0.01, 0.01)); - fullinit.insert(PoseKey(0), Pose2(0.01, 0.01, 0.01)); - - isam.update(newfactors, init); - } - - CHECK(isam_check(fullgraph, fullinit, isam)); - - // Add odometry from time 0 to time 5 - for( ; i<5; ++i) { - planarSLAM::Graph newfactors; - newfactors.addOdometry(i, i+1, Pose2(1.0, 0.0, 0.0), odoNoise); - fullgraph.push_back(newfactors); - - Values init; - init.insert(PoseKey(i+1), Pose2(double(i+1)+0.1, -0.1, 0.01)); - fullinit.insert(PoseKey(i+1), Pose2(double(i+1)+0.1, -0.1, 0.01)); - - isam.update(newfactors, init); - } - - // Add odometry from time 5 to 6 and landmark measurement at time 5 - { - planarSLAM::Graph newfactors; - newfactors.addOdometry(i, i+1, Pose2(1.0, 0.0, 0.0), odoNoise); - newfactors.addBearingRange(i, 0, Rot2::fromAngle(M_PI/4.0), 5.0, brNoise); - newfactors.addBearingRange(i, 1, Rot2::fromAngle(-M_PI/4.0), 5.0, brNoise); - fullgraph.push_back(newfactors); - - Values init; - init.insert(PoseKey(i+1), Pose2(1.01, 0.01, 0.01)); - init.insert(PointKey(0), Point2(5.0/sqrt(2.0), 5.0/sqrt(2.0))); - init.insert(PointKey(1), Point2(5.0/sqrt(2.0), -5.0/sqrt(2.0))); - fullinit.insert(PoseKey(i+1), Pose2(1.01, 0.01, 0.01)); - fullinit.insert(PointKey(0), Point2(5.0/sqrt(2.0), 5.0/sqrt(2.0))); - fullinit.insert(PointKey(1), Point2(5.0/sqrt(2.0), -5.0/sqrt(2.0))); - - isam.update(newfactors, init); - ++ i; - } - - // Add odometry from time 6 to time 10 - for( ; i<10; ++i) { - planarSLAM::Graph newfactors; - newfactors.addOdometry(i, i+1, Pose2(1.0, 0.0, 0.0), odoNoise); - fullgraph.push_back(newfactors); - - Values init; - init.insert(PoseKey(i+1), Pose2(double(i+1)+0.1, -0.1, 0.01)); - fullinit.insert(PoseKey(i+1), Pose2(double(i+1)+0.1, -0.1, 0.01)); - - isam.update(newfactors, init); - } - - // Add odometry from time 10 to 11 and landmark measurement at time 10 - { - planarSLAM::Graph newfactors; - newfactors.addOdometry(i, i+1, Pose2(1.0, 0.0, 0.0), odoNoise); - newfactors.addBearingRange(i, 0, Rot2::fromAngle(M_PI/4.0 + M_PI/16.0), 4.5, brNoise); - newfactors.addBearingRange(i, 1, Rot2::fromAngle(-M_PI/4.0 + M_PI/16.0), 4.5, brNoise); - fullgraph.push_back(newfactors); - - Values init; - init.insert(PoseKey(i+1), Pose2(6.9, 0.1, 0.01)); - fullinit.insert(PoseKey(i+1), Pose2(6.9, 0.1, 0.01)); - - isam.update(newfactors, init); - ++ i; - } - - // Compare solutions - CHECK(isam_check(fullgraph, fullinit, isam)); - - // Check gradient at each node - typedef ISAM2::sharedClique sharedClique; - BOOST_FOREACH(const sharedClique& clique, isam.nodes()) { - // Compute expected gradient - FactorGraph jfg; - jfg.push_back(JacobianFactor::shared_ptr(new JacobianFactor(*clique->conditional()))); - VectorValues expectedGradient(*allocateVectorValues(isam)); - gradientAtZero(jfg, expectedGradient); - // Compare with actual gradients - int variablePosition = 0; - for(GaussianConditional::const_iterator jit = clique->conditional()->begin(); jit != clique->conditional()->end(); ++jit) { - const int dim = clique->conditional()->dim(jit); - Vector actual = clique->gradientContribution().segment(variablePosition, dim); - EXPECT(assert_equal(expectedGradient[*jit], actual)); - variablePosition += dim; - } - LONGS_EQUAL(clique->gradientContribution().rows(), variablePosition); - } - - // Check gradient - VectorValues expectedGradient(*allocateVectorValues(isam)); - gradientAtZero(FactorGraph(isam), expectedGradient); - VectorValues expectedGradient2(gradient(FactorGraph(isam), VectorValues::Zero(expectedGradient))); - VectorValues actualGradient(*allocateVectorValues(isam)); - gradientAtZero(isam, actualGradient); - EXPECT(assert_equal(expectedGradient2, expectedGradient)); - EXPECT(assert_equal(expectedGradient, actualGradient)); + // Compare solutions + CHECK(isam_check(fullgraph, fullinit, isam, *this, result_)); } /* ************************************************************************* */ TEST(ISAM2, slamlike_solution_dogleg_qr) { - -// SETDEBUG("ISAM2 update", true); -// SETDEBUG("ISAM2 update verbose", true); -// SETDEBUG("ISAM2 recalculate", true); - - // Pose and landmark key types from planarSLAM - using planarSLAM::PoseKey; - using planarSLAM::PointKey; - - // Set up parameters - SharedDiagonal odoNoise = sharedSigmas(Vector_(3, 0.1, 0.1, M_PI/100.0)); - SharedDiagonal brNoise = sharedSigmas(Vector_(2, M_PI/100.0, 0.1)); - // These variables will be reused and accumulate factors and values - ISAM2 isam(ISAM2Params(ISAM2DoglegParams(1.0), 0.0, 0, false, false, ISAM2Params::QR)); Values fullinit; - planarSLAM::Graph fullgraph; - - // i keeps track of the time step - size_t i = 0; - - // Add a prior at time 0 and update isam - { - planarSLAM::Graph newfactors; - newfactors.addPrior(0, Pose2(0.0, 0.0, 0.0), odoNoise); - fullgraph.push_back(newfactors); - - Values init; - init.insert(PoseKey(0), Pose2(0.01, 0.01, 0.01)); - fullinit.insert(PoseKey(0), Pose2(0.01, 0.01, 0.01)); - - isam.update(newfactors, init); - } - - CHECK(isam_check(fullgraph, fullinit, isam)); - - // Add odometry from time 0 to time 5 - for( ; i<5; ++i) { - planarSLAM::Graph newfactors; - newfactors.addOdometry(i, i+1, Pose2(1.0, 0.0, 0.0), odoNoise); - fullgraph.push_back(newfactors); - - Values init; - init.insert(PoseKey(i+1), Pose2(double(i+1)+0.1, -0.1, 0.01)); - fullinit.insert(PoseKey(i+1), Pose2(double(i+1)+0.1, -0.1, 0.01)); - - isam.update(newfactors, init); - } - - // Add odometry from time 5 to 6 and landmark measurement at time 5 - { - planarSLAM::Graph newfactors; - newfactors.addOdometry(i, i+1, Pose2(1.0, 0.0, 0.0), odoNoise); - newfactors.addBearingRange(i, 0, Rot2::fromAngle(M_PI/4.0), 5.0, brNoise); - newfactors.addBearingRange(i, 1, Rot2::fromAngle(-M_PI/4.0), 5.0, brNoise); - fullgraph.push_back(newfactors); - - Values init; - init.insert(PoseKey(i+1), Pose2(1.01, 0.01, 0.01)); - init.insert(PointKey(0), Point2(5.0/sqrt(2.0), 5.0/sqrt(2.0))); - init.insert(PointKey(1), Point2(5.0/sqrt(2.0), -5.0/sqrt(2.0))); - fullinit.insert(PoseKey(i+1), Pose2(1.01, 0.01, 0.01)); - fullinit.insert(PointKey(0), Point2(5.0/sqrt(2.0), 5.0/sqrt(2.0))); - fullinit.insert(PointKey(1), Point2(5.0/sqrt(2.0), -5.0/sqrt(2.0))); - - isam.update(newfactors, init); - ++ i; - } - - // Add odometry from time 6 to time 10 - for( ; i<10; ++i) { - planarSLAM::Graph newfactors; - newfactors.addOdometry(i, i+1, Pose2(1.0, 0.0, 0.0), odoNoise); - fullgraph.push_back(newfactors); - - Values init; - init.insert(PoseKey(i+1), Pose2(double(i+1)+0.1, -0.1, 0.01)); - fullinit.insert(PoseKey(i+1), Pose2(double(i+1)+0.1, -0.1, 0.01)); - - isam.update(newfactors, init); - } - - // Add odometry from time 10 to 11 and landmark measurement at time 10 - { - planarSLAM::Graph newfactors; - newfactors.addOdometry(i, i+1, Pose2(1.0, 0.0, 0.0), odoNoise); - newfactors.addBearingRange(i, 0, Rot2::fromAngle(M_PI/4.0 + M_PI/16.0), 4.5, brNoise); - newfactors.addBearingRange(i, 1, Rot2::fromAngle(-M_PI/4.0 + M_PI/16.0), 4.5, brNoise); - fullgraph.push_back(newfactors); - - Values init; - init.insert(PoseKey(i+1), Pose2(6.9, 0.1, 0.01)); - fullinit.insert(PoseKey(i+1), Pose2(6.9, 0.1, 0.01)); - - isam.update(newfactors, init); - ++ i; - } + NonlinearFactorGraph fullgraph; + ISAM2 isam = createSlamlikeISAM2(fullinit, fullgraph, ISAM2Params(ISAM2DoglegParams(1.0), 0.0, 0, false, false, ISAM2Params::QR)); // Compare solutions - CHECK(isam_check(fullgraph, fullinit, isam)); - - // Check gradient at each node - typedef ISAM2::sharedClique sharedClique; - BOOST_FOREACH(const sharedClique& clique, isam.nodes()) { - // Compute expected gradient - FactorGraph jfg; - jfg.push_back(JacobianFactor::shared_ptr(new JacobianFactor(*clique->conditional()))); - VectorValues expectedGradient(*allocateVectorValues(isam)); - gradientAtZero(jfg, expectedGradient); - // Compare with actual gradients - int variablePosition = 0; - for(GaussianConditional::const_iterator jit = clique->conditional()->begin(); jit != clique->conditional()->end(); ++jit) { - const int dim = clique->conditional()->dim(jit); - Vector actual = clique->gradientContribution().segment(variablePosition, dim); - EXPECT(assert_equal(expectedGradient[*jit], actual)); - variablePosition += dim; - } - LONGS_EQUAL(clique->gradientContribution().rows(), variablePosition); - } - - // Check gradient - VectorValues expectedGradient(*allocateVectorValues(isam)); - gradientAtZero(FactorGraph(isam), expectedGradient); - VectorValues expectedGradient2(gradient(FactorGraph(isam), VectorValues::Zero(expectedGradient))); - VectorValues actualGradient(*allocateVectorValues(isam)); - gradientAtZero(isam, actualGradient); - EXPECT(assert_equal(expectedGradient2, expectedGradient)); - EXPECT(assert_equal(expectedGradient, actualGradient)); + CHECK(isam_check(fullgraph, fullinit, isam, *this, result_)); } /* ************************************************************************* */ @@ -894,8 +501,8 @@ TEST(ISAM2, clone) { // Modify original isam NonlinearFactorGraph factors; - factors.add(BetweenFactor(Symbol('x',0), Symbol('x',10), - isam.calculateEstimate(Symbol('x',0)).between(isam.calculateEstimate(Symbol('x',10))), sharedUnit(3))); + factors.add(BetweenFactor(0, 10, + isam.calculateEstimate(0).between(isam.calculateEstimate(10)), noiseModel::Unit::Create(3))); isam.update(factors); CHECK(assert_equal(createSlamlikeISAM2(), clone2)); @@ -978,167 +585,57 @@ TEST(ISAM2, permute_cached) { /* ************************************************************************* */ TEST(ISAM2, removeFactors) { - -// SETDEBUG("ISAM2 update", true); -// SETDEBUG("ISAM2 update verbose", true); -// SETDEBUG("ISAM2 recalculate", true); - // This test builds a graph in the same way as the "slamlike" test above, but // then removes the 2nd-to-last landmark measurement - // Pose and landmark key types from planarSLAM - using planarSLAM::PoseKey; - using planarSLAM::PointKey; - - // Set up parameters - SharedDiagonal odoNoise = sharedSigmas(Vector_(3, 0.1, 0.1, M_PI/100.0)); - SharedDiagonal brNoise = sharedSigmas(Vector_(2, M_PI/100.0, 0.1)); - // These variables will be reused and accumulate factors and values - ISAM2 isam(ISAM2Params(ISAM2GaussNewtonParams(0.001), 0.0, 0, false)); Values fullinit; - planarSLAM::Graph fullgraph; + NonlinearFactorGraph fullgraph; + ISAM2 isam = createSlamlikeISAM2(fullinit, fullgraph, ISAM2Params(ISAM2GaussNewtonParams(0.001), 0.0, 0, false)); - // i keeps track of the time step - size_t i = 0; + // Remove the 2nd measurement on landmark 0 (Key 100) + FastVector toRemove; + toRemove.push_back(12); + isam.update(NonlinearFactorGraph(), Values(), toRemove); - // Add a prior at time 0 and update isam - { - planarSLAM::Graph newfactors; - newfactors.addPrior(0, Pose2(0.0, 0.0, 0.0), odoNoise); - fullgraph.push_back(newfactors); - - Values init; - init.insert(PoseKey(0), Pose2(0.01, 0.01, 0.01)); - fullinit.insert(PoseKey(0), Pose2(0.01, 0.01, 0.01)); - - isam.update(newfactors, init); - } - - CHECK(isam_check(fullgraph, fullinit, isam)); - - // Add odometry from time 0 to time 5 - for( ; i<5; ++i) { - planarSLAM::Graph newfactors; - newfactors.addOdometry(i, i+1, Pose2(1.0, 0.0, 0.0), odoNoise); - fullgraph.push_back(newfactors); - - Values init; - init.insert(PoseKey(i+1), Pose2(double(i+1)+0.1, -0.1, 0.01)); - fullinit.insert(PoseKey(i+1), Pose2(double(i+1)+0.1, -0.1, 0.01)); - - isam.update(newfactors, init); - } - - // Add odometry from time 5 to 6 and landmark measurement at time 5 - { - planarSLAM::Graph newfactors; - newfactors.addOdometry(i, i+1, Pose2(1.0, 0.0, 0.0), odoNoise); - newfactors.addBearingRange(i, 0, Rot2::fromAngle(M_PI/4.0), 5.0, brNoise); - newfactors.addBearingRange(i, 1, Rot2::fromAngle(-M_PI/4.0), 5.0, brNoise); - fullgraph.push_back(newfactors); - - Values init; - init.insert(PoseKey(i+1), Pose2(1.01, 0.01, 0.01)); - init.insert(PointKey(0), Point2(5.0/sqrt(2.0), 5.0/sqrt(2.0))); - init.insert(PointKey(1), Point2(5.0/sqrt(2.0), -5.0/sqrt(2.0))); - fullinit.insert(PoseKey(i+1), Pose2(1.01, 0.01, 0.01)); - fullinit.insert(PointKey(0), Point2(5.0/sqrt(2.0), 5.0/sqrt(2.0))); - fullinit.insert(PointKey(1), Point2(5.0/sqrt(2.0), -5.0/sqrt(2.0))); - - isam.update(newfactors, init); - ++ i; - } - - // Add odometry from time 6 to time 10 - for( ; i<10; ++i) { - planarSLAM::Graph newfactors; - newfactors.addOdometry(i, i+1, Pose2(1.0, 0.0, 0.0), odoNoise); - fullgraph.push_back(newfactors); - - Values init; - init.insert(PoseKey(i+1), Pose2(double(i+1)+0.1, -0.1, 0.01)); - fullinit.insert(PoseKey(i+1), Pose2(double(i+1)+0.1, -0.1, 0.01)); - - isam.update(newfactors, init); - } - - // Add odometry from time 10 to 11 and landmark measurement at time 10 - { - planarSLAM::Graph newfactors; - newfactors.addOdometry(i, i+1, Pose2(1.0, 0.0, 0.0), odoNoise); - newfactors.addBearingRange(i, 0, Rot2::fromAngle(M_PI/4.0 + M_PI/16.0), 4.5, brNoise); - newfactors.addBearingRange(i, 1, Rot2::fromAngle(-M_PI/4.0 + M_PI/16.0), 4.5, brNoise); - fullgraph.push_back(newfactors[0]); - fullgraph.push_back(newfactors[2]); // Don't add measurement on landmark 0 - - Values init; - init.insert(PoseKey(i+1), Pose2(6.9, 0.1, 0.01)); - fullinit.insert(PoseKey(i+1), Pose2(6.9, 0.1, 0.01)); - - ISAM2Result result = isam.update(newfactors, init); - ++ i; - - // Remove the measurement on landmark 0 - FastVector toRemove; - EXPECT_LONGS_EQUAL(isam.getFactorsUnsafe().size()-2, result.newFactorsIndices[1]); - toRemove.push_back(result.newFactorsIndices[1]); - isam.update(planarSLAM::Graph(), Values(), toRemove); - } + // Remove the factor from the full system + fullgraph.remove(12); // Compare solutions - CHECK(isam_check(fullgraph, fullinit, isam)); - - // Check gradient at each node - typedef ISAM2::sharedClique sharedClique; - BOOST_FOREACH(const sharedClique& clique, isam.nodes()) { - // Compute expected gradient - FactorGraph jfg; - jfg.push_back(JacobianFactor::shared_ptr(new JacobianFactor(*clique->conditional()))); - VectorValues expectedGradient(*allocateVectorValues(isam)); - gradientAtZero(jfg, expectedGradient); - // Compare with actual gradients - int variablePosition = 0; - for(GaussianConditional::const_iterator jit = clique->conditional()->begin(); jit != clique->conditional()->end(); ++jit) { - const int dim = clique->conditional()->dim(jit); - Vector actual = clique->gradientContribution().segment(variablePosition, dim); - EXPECT(assert_equal(expectedGradient[*jit], actual)); - variablePosition += dim; - } - LONGS_EQUAL(clique->gradientContribution().rows(), variablePosition); - } - - // Check gradient - VectorValues expectedGradient(*allocateVectorValues(isam)); - gradientAtZero(FactorGraph(isam), expectedGradient); - VectorValues expectedGradient2(gradient(FactorGraph(isam), VectorValues::Zero(expectedGradient))); - VectorValues actualGradient(*allocateVectorValues(isam)); - gradientAtZero(isam, actualGradient); - EXPECT(assert_equal(expectedGradient2, expectedGradient)); - EXPECT(assert_equal(expectedGradient, actualGradient)); + CHECK(isam_check(fullgraph, fullinit, isam, *this, result_)); } /* ************************************************************************* */ -TEST(ISAM2, swapFactors) +TEST_UNSAFE(ISAM2, removeVariables) { + // These variables will be reused and accumulate factors and values + Values fullinit; + NonlinearFactorGraph fullgraph; + ISAM2 isam = createSlamlikeISAM2(fullinit, fullgraph, ISAM2Params(ISAM2GaussNewtonParams(0.001), 0.0, 0, false)); -// SETDEBUG("ISAM2 update", true); -// SETDEBUG("ISAM2 update verbose", true); -// SETDEBUG("ISAM2 recalculate", true); + // Remove the measurement on landmark 0 (Key 100) + FastVector toRemove; + toRemove.push_back(7); + toRemove.push_back(14); + isam.update(NonlinearFactorGraph(), Values(), toRemove); + // Remove the factors and variable from the full system + fullgraph.remove(7); + fullgraph.remove(14); + fullinit.erase(100); + + // Compare solutions + CHECK(isam_check(fullgraph, fullinit, isam, *this, result_)); +} + +/* ************************************************************************* */ +TEST_UNSAFE(ISAM2, swapFactors) +{ // This test builds a graph in the same way as the "slamlike" test above, but // then swaps the 2nd-to-last landmark measurement with a different one - // Pose and landmark key types from planarSLAM - using planarSLAM::PoseKey; - using planarSLAM::PointKey; - - // Set up parameters - SharedDiagonal odoNoise = sharedSigmas(Vector_(3, 0.1, 0.1, M_PI/100.0)); - SharedDiagonal brNoise = sharedSigmas(Vector_(2, M_PI/100.0, 0.1)); - Values fullinit; - planarSLAM::Graph fullgraph; + NonlinearFactorGraph fullgraph; ISAM2 isam = createSlamlikeISAM2(fullinit, fullgraph); // Remove the measurement on landmark 0 and replace with a different one @@ -1148,16 +645,16 @@ TEST(ISAM2, swapFactors) toRemove.push_back(swap_idx); fullgraph.remove(swap_idx); - planarSLAM::Graph swapfactors; -// swapfactors.addBearingRange(10, 0, Rot2::fromAngle(M_PI/4.0 + M_PI/16.0), 4.5, brNoise); // original factor - swapfactors.addBearingRange(10, 0, Rot2::fromAngle(M_PI/4.0 + M_PI/16.0), 5.0, brNoise); + NonlinearFactorGraph swapfactors; +// swapfactors.add(BearingRange(10, 100, Rot2::fromAngle(M_PI/4.0 + M_PI/16.0), 4.5, brNoise); // original factor + swapfactors.add(BearingRangeFactor(10, 100, Rot2::fromAngle(M_PI/4.0 + M_PI/16.0), 5.0, brNoise)); fullgraph.push_back(swapfactors); isam.update(swapfactors, Values(), toRemove); } // Compare solutions - EXPECT(assert_equal(fullgraph, planarSLAM::Graph(isam.getFactorsUnsafe()))); - EXPECT(isam_check(fullgraph, fullinit, isam)); + EXPECT(assert_equal(fullgraph, NonlinearFactorGraph(isam.getFactorsUnsafe()))); + EXPECT(isam_check(fullgraph, fullinit, isam, *this, result_)); // Check gradient at each node typedef ISAM2::sharedClique sharedClique; @@ -1191,56 +688,43 @@ TEST(ISAM2, swapFactors) /* ************************************************************************* */ TEST(ISAM2, constrained_ordering) { - -// SETDEBUG("ISAM2 update", true); -// SETDEBUG("ISAM2 update verbose", true); -// SETDEBUG("ISAM2 recalculate", true); - - // Pose and landmark key types from planarSLAM - using planarSLAM::PoseKey; - using planarSLAM::PointKey; - - // Set up parameters - SharedDiagonal odoNoise = sharedSigmas(Vector_(3, 0.1, 0.1, M_PI/100.0)); - SharedDiagonal brNoise = sharedSigmas(Vector_(2, M_PI/100.0, 0.1)); - // These variables will be reused and accumulate factors and values ISAM2 isam(ISAM2Params(ISAM2GaussNewtonParams(0.001), 0.0, 0, false)); Values fullinit; - planarSLAM::Graph fullgraph; + NonlinearFactorGraph fullgraph; // We will constrain x3 and x4 to the end FastMap constrained; - constrained.insert(make_pair(planarSLAM::PoseKey(3), 1)); - constrained.insert(make_pair(planarSLAM::PoseKey(4), 2)); + constrained.insert(make_pair((3), 1)); + constrained.insert(make_pair((4), 2)); // i keeps track of the time step size_t i = 0; // Add a prior at time 0 and update isam { - planarSLAM::Graph newfactors; - newfactors.addPrior(0, Pose2(0.0, 0.0, 0.0), odoNoise); + NonlinearFactorGraph newfactors; + newfactors.add(PriorFactor(0, Pose2(0.0, 0.0, 0.0), odoNoise)); fullgraph.push_back(newfactors); Values init; - init.insert(PoseKey(0), Pose2(0.01, 0.01, 0.01)); - fullinit.insert(PoseKey(0), Pose2(0.01, 0.01, 0.01)); + init.insert((0), Pose2(0.01, 0.01, 0.01)); + fullinit.insert((0), Pose2(0.01, 0.01, 0.01)); isam.update(newfactors, init); } - CHECK(isam_check(fullgraph, fullinit, isam)); + CHECK(isam_check(fullgraph, fullinit, isam, *this, result_)); // Add odometry from time 0 to time 5 for( ; i<5; ++i) { - planarSLAM::Graph newfactors; - newfactors.addOdometry(i, i+1, Pose2(1.0, 0.0, 0.0), odoNoise); + NonlinearFactorGraph newfactors; + newfactors.add(BetweenFactor(i, i+1, Pose2(1.0, 0.0, 0.0), odoNoise)); fullgraph.push_back(newfactors); Values init; - init.insert(PoseKey(i+1), Pose2(double(i+1)+0.1, -0.1, 0.01)); - fullinit.insert(PoseKey(i+1), Pose2(double(i+1)+0.1, -0.1, 0.01)); + init.insert((i+1), Pose2(double(i+1)+0.1, -0.1, 0.01)); + fullinit.insert((i+1), Pose2(double(i+1)+0.1, -0.1, 0.01)); if(i >= 3) isam.update(newfactors, init, FastVector(), constrained); @@ -1250,19 +734,19 @@ TEST(ISAM2, constrained_ordering) // Add odometry from time 5 to 6 and landmark measurement at time 5 { - planarSLAM::Graph newfactors; - newfactors.addOdometry(i, i+1, Pose2(1.0, 0.0, 0.0), odoNoise); - newfactors.addBearingRange(i, 0, Rot2::fromAngle(M_PI/4.0), 5.0, brNoise); - newfactors.addBearingRange(i, 1, Rot2::fromAngle(-M_PI/4.0), 5.0, brNoise); + NonlinearFactorGraph newfactors; + newfactors.add(BetweenFactor(i, i+1, Pose2(1.0, 0.0, 0.0), odoNoise)); + newfactors.add(BearingRangeFactor(i, 100, Rot2::fromAngle(M_PI/4.0), 5.0, brNoise)); + newfactors.add(BearingRangeFactor(i, 101, Rot2::fromAngle(-M_PI/4.0), 5.0, brNoise)); fullgraph.push_back(newfactors); Values init; - init.insert(PoseKey(i+1), Pose2(1.01, 0.01, 0.01)); - init.insert(PointKey(0), Point2(5.0/sqrt(2.0), 5.0/sqrt(2.0))); - init.insert(PointKey(1), Point2(5.0/sqrt(2.0), -5.0/sqrt(2.0))); - fullinit.insert(PoseKey(i+1), Pose2(1.01, 0.01, 0.01)); - fullinit.insert(PointKey(0), Point2(5.0/sqrt(2.0), 5.0/sqrt(2.0))); - fullinit.insert(PointKey(1), Point2(5.0/sqrt(2.0), -5.0/sqrt(2.0))); + init.insert((i+1), Pose2(1.01, 0.01, 0.01)); + init.insert(100, Point2(5.0/sqrt(2.0), 5.0/sqrt(2.0))); + init.insert(101, Point2(5.0/sqrt(2.0), -5.0/sqrt(2.0))); + fullinit.insert((i+1), Pose2(1.01, 0.01, 0.01)); + fullinit.insert(100, Point2(5.0/sqrt(2.0), 5.0/sqrt(2.0))); + fullinit.insert(101, Point2(5.0/sqrt(2.0), -5.0/sqrt(2.0))); isam.update(newfactors, init, FastVector(), constrained); ++ i; @@ -1270,38 +754,38 @@ TEST(ISAM2, constrained_ordering) // Add odometry from time 6 to time 10 for( ; i<10; ++i) { - planarSLAM::Graph newfactors; - newfactors.addOdometry(i, i+1, Pose2(1.0, 0.0, 0.0), odoNoise); + NonlinearFactorGraph newfactors; + newfactors.add(BetweenFactor(i, i+1, Pose2(1.0, 0.0, 0.0), odoNoise)); fullgraph.push_back(newfactors); Values init; - init.insert(PoseKey(i+1), Pose2(double(i+1)+0.1, -0.1, 0.01)); - fullinit.insert(PoseKey(i+1), Pose2(double(i+1)+0.1, -0.1, 0.01)); + init.insert((i+1), Pose2(double(i+1)+0.1, -0.1, 0.01)); + fullinit.insert((i+1), Pose2(double(i+1)+0.1, -0.1, 0.01)); isam.update(newfactors, init, FastVector(), constrained); } // Add odometry from time 10 to 11 and landmark measurement at time 10 { - planarSLAM::Graph newfactors; - newfactors.addOdometry(i, i+1, Pose2(1.0, 0.0, 0.0), odoNoise); - newfactors.addBearingRange(i, 0, Rot2::fromAngle(M_PI/4.0 + M_PI/16.0), 4.5, brNoise); - newfactors.addBearingRange(i, 1, Rot2::fromAngle(-M_PI/4.0 + M_PI/16.0), 4.5, brNoise); + NonlinearFactorGraph newfactors; + newfactors.add(BetweenFactor(i, i+1, Pose2(1.0, 0.0, 0.0), odoNoise)); + newfactors.add(BearingRangeFactor(i, 100, Rot2::fromAngle(M_PI/4.0 + M_PI/16.0), 4.5, brNoise)); + newfactors.add(BearingRangeFactor(i, 101, Rot2::fromAngle(-M_PI/4.0 + M_PI/16.0), 4.5, brNoise)); fullgraph.push_back(newfactors); Values init; - init.insert(PoseKey(i+1), Pose2(6.9, 0.1, 0.01)); - fullinit.insert(PoseKey(i+1), Pose2(6.9, 0.1, 0.01)); + init.insert((i+1), Pose2(6.9, 0.1, 0.01)); + fullinit.insert((i+1), Pose2(6.9, 0.1, 0.01)); isam.update(newfactors, init, FastVector(), constrained); ++ i; } // Compare solutions - EXPECT(isam_check(fullgraph, fullinit, isam)); + EXPECT(isam_check(fullgraph, fullinit, isam, *this, result_)); // Check that x3 and x4 are last, but either can come before the other - EXPECT(isam.getOrdering()[planarSLAM::PoseKey(3)] == 12 && isam.getOrdering()[planarSLAM::PoseKey(4)] == 13); + EXPECT(isam.getOrdering()[(3)] == 12 && isam.getOrdering()[(4)] == 13); // Check gradient at each node typedef ISAM2::sharedClique sharedClique; @@ -1332,6 +816,21 @@ TEST(ISAM2, constrained_ordering) EXPECT(assert_equal(expectedGradient, actualGradient)); } +/* ************************************************************************* */ +TEST(ISAM2, slamlike_solution_partial_relinearization_check) +{ + + // These variables will be reused and accumulate factors and values + Values fullinit; + NonlinearFactorGraph fullgraph; + ISAM2Params params(ISAM2GaussNewtonParams(0.001), 0.0, 0, false); + params.enablePartialRelinearizationCheck = true; + ISAM2 isam = createSlamlikeISAM2(fullinit, fullgraph, params); + + // Compare solutions + CHECK(isam_check(fullgraph, fullinit, isam, *this, result_)); +} + /* ************************************************************************* */ int main() { TestResult tr; return TestRegistry::runAllTests(tr);} /* ************************************************************************* */ diff --git a/tests/testGaussianJunctionTreeB.cpp b/tests/testGaussianJunctionTreeB.cpp index 074693123..422e52377 100644 --- a/tests/testGaussianJunctionTreeB.cpp +++ b/tests/testGaussianJunctionTreeB.cpp @@ -15,9 +15,24 @@ * @author nikai */ -#include -#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include #include +#include +#include + +#include #include #include // for operator += @@ -25,23 +40,14 @@ #include using namespace boost::assign; -#include -#include -#include -#include -#include -#include -#include -#include -#include -#include +#include using namespace std; using namespace gtsam; using namespace example; -Key kx(size_t i) { return Symbol('x',i); } -Key kl(size_t i) { return Symbol('l',i); } +using symbol_shorthand::X; +using symbol_shorthand::L; /* ************************************************************************* * Bayes tree for smoother with "nested dissection" ordering: @@ -50,23 +56,23 @@ Key kl(size_t i) { return Symbol('l',i); } C3 x1 : x2 C4 x7 : x6 */ -TEST( GaussianJunctionTree, constructor2 ) +TEST( GaussianJunctionTreeB, constructor2 ) { // create a graph - Ordering ordering; ordering += kx(1),kx(3),kx(5),kx(7),kx(2),kx(6),kx(4); + Ordering ordering; ordering += X(1),X(3),X(5),X(7),X(2),X(6),X(4); GaussianFactorGraph fg = createSmoother(7, ordering).first; // create an ordering GaussianJunctionTree actual(fg); - vector frontal1; frontal1 += ordering[kx(5)], ordering[kx(6)], ordering[kx(4)]; - vector frontal2; frontal2 += ordering[kx(3)], ordering[kx(2)]; - vector frontal3; frontal3 += ordering[kx(1)]; - vector frontal4; frontal4 += ordering[kx(7)]; + vector frontal1; frontal1 += ordering[X(5)], ordering[X(6)], ordering[X(4)]; + vector frontal2; frontal2 += ordering[X(3)], ordering[X(2)]; + vector frontal3; frontal3 += ordering[X(1)]; + vector frontal4; frontal4 += ordering[X(7)]; vector sep1; - vector sep2; sep2 += ordering[kx(4)]; - vector sep3; sep3 += ordering[kx(2)]; - vector sep4; sep4 += ordering[kx(6)]; + vector sep2; sep2 += ordering[X(4)]; + vector sep3; sep3 += ordering[X(2)]; + vector sep4; sep4 += ordering[X(6)]; EXPECT(assert_equal(frontal1, actual.root()->frontal)); EXPECT(assert_equal(sep1, actual.root()->separator)); LONGS_EQUAL(5, actual.root()->size()); @@ -86,7 +92,7 @@ TEST( GaussianJunctionTree, constructor2 ) } /* ************************************************************************* */ -TEST( GaussianJunctionTree, optimizeMultiFrontal ) +TEST( GaussianJunctionTreeB, optimizeMultiFrontal ) { // create a graph GaussianFactorGraph fg; @@ -101,17 +107,17 @@ TEST( GaussianJunctionTree, optimizeMultiFrontal ) VectorValues expected(vector(7,2)); // expected solution Vector v = Vector_(2, 0., 0.); for (int i=1; i<=7; i++) - expected[ordering[Symbol('x',i)]] = v; + expected[ordering[X(i)]] = v; EXPECT(assert_equal(expected,actual)); } /* ************************************************************************* */ -TEST( GaussianJunctionTree, optimizeMultiFrontal2) +TEST( GaussianJunctionTreeB, optimizeMultiFrontal2) { // create a graph example::Graph nlfg = createNonlinearFactorGraph(); Values noisy = createNoisyValues(); - Ordering ordering; ordering += kx(1),kx(2),kl(1); + Ordering ordering; ordering += X(1),X(2),L(1); GaussianFactorGraph fg = *nlfg.linearize(noisy, ordering); // optimize the graph @@ -124,52 +130,49 @@ TEST( GaussianJunctionTree, optimizeMultiFrontal2) } /* ************************************************************************* */ -TEST(GaussianJunctionTree, slamlike) { - using planarSLAM::PoseKey; - using planarSLAM::PointKey; - +TEST(GaussianJunctionTreeB, slamlike) { Values init; - planarSLAM::Graph newfactors; - planarSLAM::Graph fullgraph; - SharedDiagonal odoNoise = sharedSigmas(Vector_(3, 0.1, 0.1, M_PI/100.0)); - SharedDiagonal brNoise = sharedSigmas(Vector_(2, M_PI/100.0, 0.1)); + NonlinearFactorGraph newfactors; + NonlinearFactorGraph fullgraph; + SharedDiagonal odoNoise = noiseModel::Diagonal::Sigmas(Vector_(3, 0.1, 0.1, M_PI/100.0)); + SharedDiagonal brNoise = noiseModel::Diagonal::Sigmas(Vector_(2, M_PI/100.0, 0.1)); size_t i = 0; - newfactors = planarSLAM::Graph(); - newfactors.addPrior(0, Pose2(0.0, 0.0, 0.0), odoNoise); - init.insert(PoseKey(0), Pose2(0.01, 0.01, 0.01)); + newfactors = NonlinearFactorGraph(); + newfactors.add(PriorFactor(X(0), Pose2(0.0, 0.0, 0.0), odoNoise)); + init.insert(X(0), Pose2(0.01, 0.01, 0.01)); fullgraph.push_back(newfactors); for( ; i<5; ++i) { - newfactors = planarSLAM::Graph(); - newfactors.addOdometry(i, i+1, Pose2(1.0, 0.0, 0.0), odoNoise); - init.insert(PoseKey(i+1), Pose2(double(i+1)+0.1, -0.1, 0.01)); + newfactors = NonlinearFactorGraph(); + newfactors.add(BetweenFactor(X(i), X(i+1), Pose2(1.0, 0.0, 0.0), odoNoise)); + init.insert(X(i+1), Pose2(double(i+1)+0.1, -0.1, 0.01)); fullgraph.push_back(newfactors); } - newfactors = planarSLAM::Graph(); - newfactors.addOdometry(i, i+1, Pose2(1.0, 0.0, 0.0), odoNoise); - newfactors.addBearingRange(i, 0, Rot2::fromAngle(M_PI/4.0), 5.0, brNoise); - newfactors.addBearingRange(i, 1, Rot2::fromAngle(-M_PI/4.0), 5.0, brNoise); - init.insert(PoseKey(i+1), Pose2(1.01, 0.01, 0.01)); - init.insert(PointKey(0), Point2(5.0/sqrt(2.0), 5.0/sqrt(2.0))); - init.insert(PointKey(1), Point2(5.0/sqrt(2.0), -5.0/sqrt(2.0))); + newfactors = NonlinearFactorGraph(); + newfactors.add(BetweenFactor(X(i), X(i+1), Pose2(1.0, 0.0, 0.0), odoNoise)); + newfactors.add(BearingRangeFactor(X(i), L(0), Rot2::fromAngle(M_PI/4.0), 5.0, brNoise)); + newfactors.add(BearingRangeFactor(X(i), L(1), Rot2::fromAngle(-M_PI/4.0), 5.0, brNoise)); + init.insert(X(i+1), Pose2(1.01, 0.01, 0.01)); + init.insert(L(0), Point2(5.0/sqrt(2.0), 5.0/sqrt(2.0))); + init.insert(L(1), Point2(5.0/sqrt(2.0), -5.0/sqrt(2.0))); fullgraph.push_back(newfactors); ++ i; for( ; i<5; ++i) { - newfactors = planarSLAM::Graph(); - newfactors.addOdometry(i, i+1, Pose2(1.0, 0.0, 0.0), odoNoise); - init.insert(PoseKey(i+1), Pose2(double(i+1)+0.1, -0.1, 0.01)); + newfactors = NonlinearFactorGraph(); + newfactors.add(BetweenFactor(X(i), X(i+1), Pose2(1.0, 0.0, 0.0), odoNoise)); + init.insert(X(i+1), Pose2(double(i+1)+0.1, -0.1, 0.01)); fullgraph.push_back(newfactors); } - newfactors = planarSLAM::Graph(); - newfactors.addOdometry(i, i+1, Pose2(1.0, 0.0, 0.0), odoNoise); - newfactors.addBearingRange(i, 0, Rot2::fromAngle(M_PI/4.0 + M_PI/16.0), 4.5, brNoise); - newfactors.addBearingRange(i, 1, Rot2::fromAngle(-M_PI/4.0 + M_PI/16.0), 4.5, brNoise); - init.insert(PoseKey(i+1), Pose2(6.9, 0.1, 0.01)); + newfactors = NonlinearFactorGraph(); + newfactors.add(BetweenFactor(X(i), X(i+1), Pose2(1.0, 0.0, 0.0), odoNoise)); + newfactors.add(BearingRangeFactor(X(i), L(0), Rot2::fromAngle(M_PI/4.0 + M_PI/16.0), 4.5, brNoise)); + newfactors.add(BearingRangeFactor(X(i), L(1), Rot2::fromAngle(-M_PI/4.0 + M_PI/16.0), 4.5, brNoise)); + init.insert(X(i+1), Pose2(6.9, 0.1, 0.01)); fullgraph.push_back(newfactors); ++ i; @@ -189,21 +192,21 @@ TEST(GaussianJunctionTree, slamlike) { } /* ************************************************************************* */ -TEST(GaussianJunctionTree, simpleMarginal) { +TEST(GaussianJunctionTreeB, simpleMarginal) { typedef BayesTree GaussianBayesTree; // Create a simple graph - pose2SLAM::Graph fg; - fg.addPrior(0, Pose2(), sharedSigma(3, 10.0)); - fg.addOdometry(0, 1, Pose2(1.0, 0.0, 0.0), sharedSigmas(Vector_(3, 10.0, 1.0, 1.0))); + NonlinearFactorGraph fg; + fg.add(PriorFactor(X(0), Pose2(), noiseModel::Isotropic::Sigma(3, 10.0))); + fg.add(BetweenFactor(X(0), X(1), Pose2(1.0, 0.0, 0.0), noiseModel::Diagonal::Sigmas(Vector_(3, 10.0, 1.0, 1.0)))); Values init; - init.insert(pose2SLAM::PoseKey(0), Pose2()); - init.insert(pose2SLAM::PoseKey(1), Pose2(1.0, 0.0, 0.0)); + init.insert(X(0), Pose2()); + init.insert(X(1), Pose2(1.0, 0.0, 0.0)); Ordering ordering; - ordering += kx(1), kx(0); + ordering += X(1), X(0); GaussianFactorGraph gfg = *fg.linearize(init, ordering); diff --git a/tests/testGradientDescentOptimizer.cpp b/tests/testGradientDescentOptimizer.cpp new file mode 100644 index 000000000..4f556eb0f --- /dev/null +++ b/tests/testGradientDescentOptimizer.cpp @@ -0,0 +1,106 @@ +/** + * @file testGradientDescentOptimizer.cpp + * @brief + * @author ydjian + * @date Jun 11, 2012 + */ + +#include +#include +#include +#include +#include +#include + +#include + +#include +#include +#include + + +using namespace std; +using namespace gtsam; + + +boost::tuple generateProblem() { + + // 1. Create graph container and add factors to it + NonlinearFactorGraph graph ; + + // 2a. Add Gaussian prior + Pose2 priorMean(0.0, 0.0, 0.0); // prior at origin + SharedDiagonal priorNoise = noiseModel::Diagonal::Sigmas(Vector_(3, 0.3, 0.3, 0.1)); + graph.add(PriorFactor(1, priorMean, priorNoise)); + + // 2b. Add odometry factors + SharedDiagonal odometryNoise = noiseModel::Diagonal::Sigmas(Vector_(3, 0.2, 0.2, 0.1)); + graph.add(BetweenFactor(1, 2, Pose2(2.0, 0.0, 0.0 ), odometryNoise)); + graph.add(BetweenFactor(2, 3, Pose2(2.0, 0.0, M_PI_2), odometryNoise)); + graph.add(BetweenFactor(3, 4, Pose2(2.0, 0.0, M_PI_2), odometryNoise)); + graph.add(BetweenFactor(4, 5, Pose2(2.0, 0.0, M_PI_2), odometryNoise)); + + // 2c. Add pose constraint + SharedDiagonal constraintUncertainty = noiseModel::Diagonal::Sigmas(Vector_(3, 0.2, 0.2, 0.1)); + graph.add(BetweenFactor(5, 2, Pose2(2.0, 0.0, M_PI_2), constraintUncertainty)); + + // 3. Create the data structure to hold the initialEstimate estinmate to the solution + Values initialEstimate; + Pose2 x1(0.5, 0.0, 0.2 ); initialEstimate.insert(1, x1); + Pose2 x2(2.3, 0.1,-0.2 ); initialEstimate.insert(2, x2); + Pose2 x3(4.1, 0.1, M_PI_2); initialEstimate.insert(3, x3); + Pose2 x4(4.0, 2.0, M_PI ); initialEstimate.insert(4, x4); + Pose2 x5(2.1, 2.1,-M_PI_2); initialEstimate.insert(5, x5); + + return boost::tie(graph, initialEstimate); +} + +/* ************************************************************************* */ +TEST(optimize, GradientDescentOptimizer) { + + NonlinearFactorGraph graph; + Values initialEstimate; + + boost::tie(graph, initialEstimate) = generateProblem(); + // cout << "initial error = " << graph.error(initialEstimate) << endl ; + + // Single Step Optimization using Levenberg-Marquardt + NonlinearOptimizerParams param; + param.maxIterations = 500; /* requires a larger number of iterations to converge */ + param.verbosity = NonlinearOptimizerParams::SILENT; + + NonlinearConjugateGradientOptimizer optimizer(graph, initialEstimate, param); + Values result = optimizer.optimize(); +// cout << "gd1 solver final error = " << graph.error(result) << endl; + + /* the optimality of the solution is not comparable to the */ + DOUBLES_EQUAL(0.0, graph.error(result), 1e-2); + + CHECK(1); +} + +/* ************************************************************************* */ +TEST(optimize, ConjugateGradientOptimizer) { + + NonlinearFactorGraph graph; + Values initialEstimate; + + boost::tie(graph, initialEstimate) = generateProblem(); +// cout << "initial error = " << graph.error(initialEstimate) << endl ; + + // Single Step Optimization using Levenberg-Marquardt + NonlinearOptimizerParams param; + param.maxIterations = 500; /* requires a larger number of iterations to converge */ + param.verbosity = NonlinearOptimizerParams::SILENT; + + NonlinearConjugateGradientOptimizer optimizer(graph, initialEstimate, param); + Values result = optimizer.optimize(); +// cout << "cg final error = " << graph.error(result) << endl; + + /* the optimality of the solution is not comparable to the */ + DOUBLES_EQUAL(0.0, graph.error(result), 1e-2); +} + +/* ************************************************************************* */ +int main() { TestResult tr; return TestRegistry::runAllTests(tr); } +/* ************************************************************************* */ diff --git a/tests/testGraph.cpp b/tests/testGraph.cpp index f56efae82..14655a249 100644 --- a/tests/testGraph.cpp +++ b/tests/testGraph.cpp @@ -16,38 +16,36 @@ * @brief unit test for graph-inl.h */ -#include +#include +#include +#include +#include + +#include + #include #include // for operator += using namespace boost::assign; -#include - -// TODO: DANGEROUS, create shared pointers -#define GTSAM_MAGIC_GAUSSIAN 3 - -#include -#include +#include using namespace std; using namespace gtsam; -Key kx(size_t i) { return Symbol('x',i); } - /* ************************************************************************* */ // x1 -> x2 // -> x3 -> x4 // -> x5 TEST ( Ordering, predecessorMap2Keys ) { PredecessorMap p_map; - p_map.insert(kx(1),kx(1)); - p_map.insert(kx(2),kx(1)); - p_map.insert(kx(3),kx(1)); - p_map.insert(kx(4),kx(3)); - p_map.insert(kx(5),kx(1)); + p_map.insert(1,1); + p_map.insert(2,1); + p_map.insert(3,1); + p_map.insert(4,3); + p_map.insert(5,1); list expected; - expected += kx(4),kx(5),kx(3),kx(2),kx(1);//PoseKey(4), PoseKey(5), PoseKey(3), PoseKey(2), PoseKey(1); + expected += 4,5,3,2,1; list actual = predecessorMap2Keys(p_map); LONGS_EQUAL(expected.size(), actual.size()); @@ -67,47 +65,148 @@ TEST( Graph, predecessorMap2Graph ) map key2vertex; PredecessorMap p_map; - p_map.insert(kx(1), kx(2)); - p_map.insert(kx(2), kx(2)); - p_map.insert(kx(3), kx(2)); - tie(graph, root, key2vertex) = predecessorMap2Graph, SVertex, Key>(p_map); + p_map.insert(1, 2); + p_map.insert(2, 2); + p_map.insert(3, 2); + boost::tie(graph, root, key2vertex) = predecessorMap2Graph, SVertex, Key>(p_map); LONGS_EQUAL(3, boost::num_vertices(graph)); - CHECK(root == key2vertex[kx(2)]); + CHECK(root == key2vertex[2]); } /* ************************************************************************* */ TEST( Graph, composePoses ) { - pose2SLAM::Graph graph; - Matrix cov = eye(3); + NonlinearFactorGraph graph; + SharedNoiseModel cov = noiseModel::Unit::Create(3); Pose2 p1(1.0, 2.0, 0.3), p2(4.0, 5.0, 0.6), p3(7.0, 8.0, 0.9), p4(2.0, 2.0, 2.9); Pose2 p12=p1.between(p2), p23=p2.between(p3), p43=p4.between(p3); - graph.addOdometry(1,2, p12, cov); - graph.addOdometry(2,3, p23, cov); - graph.addOdometry(4,3, p43, cov); + graph.add(BetweenFactor(1,2, p12, cov)); + graph.add(BetweenFactor(2,3, p23, cov)); + graph.add(BetweenFactor(4,3, p43, cov)); PredecessorMap tree; - tree.insert(pose2SLAM::PoseKey(1),pose2SLAM::PoseKey(2)); - tree.insert(pose2SLAM::PoseKey(2),pose2SLAM::PoseKey(2)); - tree.insert(pose2SLAM::PoseKey(3),pose2SLAM::PoseKey(2)); - tree.insert(pose2SLAM::PoseKey(4),pose2SLAM::PoseKey(3)); + tree.insert(1,2); + tree.insert(2,2); + tree.insert(3,2); + tree.insert(4,3); Pose2 rootPose = p2; - boost::shared_ptr actual = composePoses (graph, tree, rootPose); + boost::shared_ptr actual = composePoses, Pose2, Key> (graph, tree, rootPose); Values expected; - expected.insert(pose2SLAM::PoseKey(1), p1); - expected.insert(pose2SLAM::PoseKey(2), p2); - expected.insert(pose2SLAM::PoseKey(3), p3); - expected.insert(pose2SLAM::PoseKey(4), p4); + expected.insert(1, p1); + expected.insert(2, p2); + expected.insert(3, p3); + expected.insert(4, p4); LONGS_EQUAL(4, actual->size()); CHECK(assert_equal(expected, *actual)); } +// SL-FIX TEST( GaussianFactorGraph, findMinimumSpanningTree ) +//{ +// GaussianFactorGraph g; +// Matrix I = eye(2); +// Vector b = Vector_(0, 0, 0); +// g.add(X(1), I, X(2), I, b, model); +// g.add(X(1), I, X(3), I, b, model); +// g.add(X(1), I, X(4), I, b, model); +// g.add(X(2), I, X(3), I, b, model); +// g.add(X(2), I, X(4), I, b, model); +// g.add(X(3), I, X(4), I, b, model); +// +// map tree = g.findMinimumSpanningTree(); +// EXPECT(tree[X(1)].compare(X(1))==0); +// EXPECT(tree[X(2)].compare(X(1))==0); +// EXPECT(tree[X(3)].compare(X(1))==0); +// EXPECT(tree[X(4)].compare(X(1))==0); +//} + +///* ************************************************************************* */ +// SL-FIX TEST( GaussianFactorGraph, split ) +//{ +// GaussianFactorGraph g; +// Matrix I = eye(2); +// Vector b = Vector_(0, 0, 0); +// g.add(X(1), I, X(2), I, b, model); +// g.add(X(1), I, X(3), I, b, model); +// g.add(X(1), I, X(4), I, b, model); +// g.add(X(2), I, X(3), I, b, model); +// g.add(X(2), I, X(4), I, b, model); +// +// PredecessorMap tree; +// tree[X(1)] = X(1); +// tree[X(2)] = X(1); +// tree[X(3)] = X(1); +// tree[X(4)] = X(1); +// +// GaussianFactorGraph Ab1, Ab2; +// g.split(tree, Ab1, Ab2); +// LONGS_EQUAL(3, Ab1.size()); +// LONGS_EQUAL(2, Ab2.size()); +//} + +///* ************************************************************************* */ +// SL-FIX TEST( FactorGraph, splitMinimumSpanningTree ) +//{ +// SymbolicFactorGraph G; +// G.push_factor("x1", "x2"); +// G.push_factor("x1", "x3"); +// G.push_factor("x1", "x4"); +// G.push_factor("x2", "x3"); +// G.push_factor("x2", "x4"); +// G.push_factor("x3", "x4"); +// +// SymbolicFactorGraph T, C; +// boost::tie(T, C) = G.splitMinimumSpanningTree(); +// +// SymbolicFactorGraph expectedT, expectedC; +// expectedT.push_factor("x1", "x2"); +// expectedT.push_factor("x1", "x3"); +// expectedT.push_factor("x1", "x4"); +// expectedC.push_factor("x2", "x3"); +// expectedC.push_factor("x2", "x4"); +// expectedC.push_factor("x3", "x4"); +// CHECK(assert_equal(expectedT,T)); +// CHECK(assert_equal(expectedC,C)); +//} + +///* ************************************************************************* */ +///** +// * x1 - x2 - x3 - x4 - x5 +// * | | / | +// * l1 l2 l3 +// */ +// SL-FIX TEST( FactorGraph, removeSingletons ) +//{ +// SymbolicFactorGraph G; +// G.push_factor("x1", "x2"); +// G.push_factor("x2", "x3"); +// G.push_factor("x3", "x4"); +// G.push_factor("x4", "x5"); +// G.push_factor("x2", "l1"); +// G.push_factor("x3", "l2"); +// G.push_factor("x4", "l2"); +// G.push_factor("x4", "l3"); +// +// SymbolicFactorGraph singletonGraph; +// set singletons; +// boost::tie(singletonGraph, singletons) = G.removeSingletons(); +// +// set singletons_excepted; singletons_excepted += "x1", "x2", "x5", "l1", "l3"; +// CHECK(singletons_excepted == singletons); +// +// SymbolicFactorGraph singletonGraph_excepted; +// singletonGraph_excepted.push_factor("x2", "l1"); +// singletonGraph_excepted.push_factor("x4", "l3"); +// singletonGraph_excepted.push_factor("x1", "x2"); +// singletonGraph_excepted.push_factor("x4", "x5"); +// singletonGraph_excepted.push_factor("x2", "x3"); +// CHECK(singletonGraph_excepted.equals(singletonGraph)); +//} + /* ************************************************************************* */ int main() { TestResult tr; diff --git a/tests/testInferenceB.cpp b/tests/testInferenceB.cpp index 6ad070698..9b8127473 100644 --- a/tests/testInferenceB.cpp +++ b/tests/testInferenceB.cpp @@ -17,14 +17,27 @@ #include +#include +#include +#include +#include +#include +#include #include #include -#include -#include +#include +#include +#include + +#include using namespace std; using namespace gtsam; +// Convenience for named keys +using symbol_shorthand::X; +using symbol_shorthand::L; + /* ************************************************************************* */ // The tests below test the *generic* inference algorithms. Some of these have // specialized versions in the derived classes GaussianFactorGraph etc... @@ -41,34 +54,34 @@ TEST( inference, marginals ) *GaussianSequentialSolver(GaussianFactorGraph(cbn)).jointFactorGraph(xvar)).eliminate(); // expected is just scalar Gaussian on x - GaussianBayesNet expected = scalarGaussian(0, 4, sqrt(2)); + GaussianBayesNet expected = scalarGaussian(0, 4, sqrt(2.0)); CHECK(assert_equal(expected,actual)); } /* ************************************************************************* */ TEST( inference, marginals2) { - planarSLAM::Graph fg; - SharedDiagonal poseModel(sharedSigma(3, 0.1)); - SharedDiagonal pointModel(sharedSigma(3, 0.1)); + NonlinearFactorGraph fg; + SharedDiagonal poseModel(noiseModel::Isotropic::Sigma(3, 0.1)); + SharedDiagonal pointModel(noiseModel::Isotropic::Sigma(3, 0.1)); - fg.addPrior(0, Pose2(), poseModel); - fg.addOdometry(0, 1, Pose2(1.0,0.0,0.0), poseModel); - fg.addOdometry(1, 2, Pose2(1.0,0.0,0.0), poseModel); - fg.addBearingRange(0, 0, Rot2(), 1.0, pointModel); - fg.addBearingRange(1, 0, Rot2(), 1.0, pointModel); - fg.addBearingRange(2, 0, Rot2(), 1.0, pointModel); + fg.add(PriorFactor(X(0), Pose2(), poseModel)); + fg.add(BetweenFactor(X(0), X(1), Pose2(1.0,0.0,0.0), poseModel)); + fg.add(BetweenFactor(X(1), X(2), Pose2(1.0,0.0,0.0), poseModel)); + fg.add(BearingRangeFactor(X(0), L(0), Rot2(), 1.0, pointModel)); + fg.add(BearingRangeFactor(X(1), L(0), Rot2(), 1.0, pointModel)); + fg.add(BearingRangeFactor(X(2), L(0), Rot2(), 1.0, pointModel)); Values init; - init.insert(planarSLAM::PoseKey(0), Pose2(0.0,0.0,0.0)); - init.insert(planarSLAM::PoseKey(1), Pose2(1.0,0.0,0.0)); - init.insert(planarSLAM::PoseKey(2), Pose2(2.0,0.0,0.0)); - init.insert(planarSLAM::PointKey(0), Point2(1.0,1.0)); + init.insert(X(0), Pose2(0.0,0.0,0.0)); + init.insert(X(1), Pose2(1.0,0.0,0.0)); + init.insert(X(2), Pose2(2.0,0.0,0.0)); + init.insert(L(0), Point2(1.0,1.0)); Ordering ordering(*fg.orderingCOLAMD(init)); FactorGraph::shared_ptr gfg(fg.linearize(init, ordering)); GaussianMultifrontalSolver solver(*gfg); - solver.marginalFactor(ordering[planarSLAM::PointKey(0)]); + solver.marginalFactor(ordering[L(0)]); } /* ************************************************************************* */ diff --git a/tests/testIterative.cpp b/tests/testIterative.cpp new file mode 100644 index 000000000..bfa3a8e79 --- /dev/null +++ b/tests/testIterative.cpp @@ -0,0 +1,154 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file testIterative.cpp + * @brief Unit tests for iterative methods + * @author Frank Dellaert + **/ + +#include +#include +#include +#include +#include +#include +#include +#include +#include + +#include + +using namespace std; +using namespace gtsam; +using namespace example; +using symbol_shorthand::X; // to create pose keys +using symbol_shorthand::L; // to create landmark keys + +static ConjugateGradientParameters parameters; +// add following below to add printing: +// parameters.verbosity_ = ConjugateGradientParameters::COMPLEXITY; + +/* ************************************************************************* */ +TEST( Iterative, steepestDescent ) +{ + // Create factor graph + Ordering ordering; + ordering += L(1), X(1), X(2); + GaussianFactorGraph fg = createGaussianFactorGraph(ordering); + + // eliminate and solve + VectorValues expected = *GaussianSequentialSolver(fg).optimize(); + + // Do gradient descent + VectorValues zero = VectorValues::Zero(expected); // TODO, how do we do this normally? + VectorValues actual = steepestDescent(fg, zero, parameters); + CHECK(assert_equal(expected,actual,1e-2)); +} + +/* ************************************************************************* */ +TEST( Iterative, conjugateGradientDescent ) +{ + // Create factor graph + Ordering ordering; + ordering += L(1), X(1), X(2); + GaussianFactorGraph fg = createGaussianFactorGraph(ordering); + + // eliminate and solve + VectorValues expected = *GaussianSequentialSolver(fg).optimize(); + + // get matrices + Matrix A; + Vector b; + Vector x0 = gtsam::zero(6); + boost::tie(A, b) = fg.jacobian(); + Vector expectedX = Vector_(6, -0.1, 0.1, -0.1, -0.1, 0.1, -0.2); + + // Do conjugate gradient descent, System version + System Ab(A, b); + Vector actualX = conjugateGradientDescent(Ab, x0, parameters); + CHECK(assert_equal(expectedX,actualX,1e-9)); + + // Do conjugate gradient descent, Matrix version + Vector actualX2 = conjugateGradientDescent(A, b, x0, parameters); + CHECK(assert_equal(expectedX,actualX2,1e-9)); + + // Do conjugate gradient descent on factor graph + VectorValues zero = VectorValues::Zero(expected); + VectorValues actual = conjugateGradientDescent(fg, zero, parameters); + CHECK(assert_equal(expected,actual,1e-2)); +} + +/* ************************************************************************* */ +TEST( Iterative, conjugateGradientDescent_hard_constraint ) +{ + Values config; + Pose2 pose1 = Pose2(0.,0.,0.); + config.insert(X(1), pose1); + config.insert(X(2), Pose2(1.5,0.,0.)); + + NonlinearFactorGraph graph; + graph.add(NonlinearEquality(X(1), pose1)); + graph.add(BetweenFactor(X(1),X(2), Pose2(1.,0.,0.), noiseModel::Isotropic::Sigma(3, 1))); + + Ordering ordering; + ordering += X(1), X(2); + boost::shared_ptr fg = graph.linearize(config,ordering); + + VectorValues zeros = VectorValues::Zero(2, 3); + + ConjugateGradientParameters parameters; + parameters.setEpsilon_abs(1e-3); + parameters.setEpsilon_rel(1e-5); + parameters.setMaxIterations(100); + VectorValues actual = conjugateGradientDescent(*fg, zeros, parameters); + + VectorValues expected; + expected.insert(0, zero(3)); + expected.insert(1, Vector_(3,-0.5,0.,0.)); + CHECK(assert_equal(expected, actual)); +} + +/* ************************************************************************* */ +TEST( Iterative, conjugateGradientDescent_soft_constraint ) +{ + Values config; + config.insert(X(1), Pose2(0.,0.,0.)); + config.insert(X(2), Pose2(1.5,0.,0.)); + + NonlinearFactorGraph graph; + graph.add(PriorFactor(X(1), Pose2(0.,0.,0.), noiseModel::Isotropic::Sigma(3, 1e-10))); + graph.add(BetweenFactor(X(1),X(2), Pose2(1.,0.,0.), noiseModel::Isotropic::Sigma(3, 1))); + + Ordering ordering; + ordering += X(1), X(2); + boost::shared_ptr fg = graph.linearize(config,ordering); + + VectorValues zeros = VectorValues::Zero(2, 3); + + ConjugateGradientParameters parameters; + parameters.setEpsilon_abs(1e-3); + parameters.setEpsilon_rel(1e-5); + parameters.setMaxIterations(100); + VectorValues actual = conjugateGradientDescent(*fg, zeros, parameters); + + VectorValues expected; + expected.insert(0, zero(3)); + expected.insert(1, Vector_(3,-0.5,0.,0.)); + CHECK(assert_equal(expected, actual)); +} + +/* ************************************************************************* */ +int main() { + TestResult tr; + return TestRegistry::runAllTests(tr); +} +/* ************************************************************************* */ diff --git a/tests/testMarginals.cpp b/tests/testMarginals.cpp index a91e6b576..c9bd43b27 100644 --- a/tests/testMarginals.cpp +++ b/tests/testMarginals.cpp @@ -51,34 +51,34 @@ TEST(Marginals, planarSLAMmarginals) { /* add prior */ // gaussian for prior - SharedDiagonal prior_model = noiseModel::Diagonal::Sigmas(Vector_(3, 0.3, 0.3, 0.1)); - Pose2 prior_measurement(0.0, 0.0, 0.0); // prior at origin - graph.add(PriorFactor(x1, prior_measurement, prior_model)); // add the factor to the graph + SharedDiagonal priorNoise = noiseModel::Diagonal::Sigmas(Vector_(3, 0.3, 0.3, 0.1)); + Pose2 priorMean(0.0, 0.0, 0.0); // prior at origin + graph.add(PriorFactor(x1, priorMean, priorNoise)); // add the factor to the graph /* add odometry */ // general noisemodel for odometry - SharedDiagonal odom_model = noiseModel::Diagonal::Sigmas(Vector_(3, 0.2, 0.2, 0.1)); - Pose2 odom_measurement(2.0, 0.0, 0.0); // create a measurement for both factors (the same in this case) + SharedDiagonal odometryNoise = noiseModel::Diagonal::Sigmas(Vector_(3, 0.2, 0.2, 0.1)); + Pose2 odometry(2.0, 0.0, 0.0); // create a measurement for both factors (the same in this case) // create between factors to represent odometry - graph.add(BetweenFactor(x1, x2, odom_measurement, odom_model)); - graph.add(BetweenFactor(x2, x3, odom_measurement, odom_model)); + graph.add(BetweenFactor(x1, x2, odometry, odometryNoise)); + graph.add(BetweenFactor(x2, x3, odometry, odometryNoise)); /* add measurements */ // general noisemodel for measurements - SharedDiagonal meas_model = noiseModel::Diagonal::Sigmas(Vector_(2, 0.1, 0.2)); + SharedDiagonal measurementNoise = noiseModel::Diagonal::Sigmas(Vector_(2, 0.1, 0.2)); // create the measurement values - indices are (pose id, landmark id) Rot2 bearing11 = Rot2::fromDegrees(45), bearing21 = Rot2::fromDegrees(90), bearing32 = Rot2::fromDegrees(90); - double range11 = sqrt(4+4), + double range11 = sqrt(4.0+4.0), range21 = 2.0, range32 = 2.0; // create bearing/range factors - graph.add(BearingRangeFactor(x1, l1, bearing11, range11, meas_model)); - graph.add(BearingRangeFactor(x2, l1, bearing21, range21, meas_model)); - graph.add(BearingRangeFactor(x3, l2, bearing32, range32, meas_model)); + graph.add(BearingRangeFactor(x1, l1, bearing11, range11, measurementNoise)); + graph.add(BearingRangeFactor(x2, l1, bearing21, range21, measurementNoise)); + graph.add(BearingRangeFactor(x3, l2, bearing32, range32, measurementNoise)); // linearization point for marginals Values soln; @@ -180,7 +180,62 @@ TEST(Marginals, planarSLAMmarginals) { EXPECT(assert_equal(expectedx1, Matrix(joint_l2x1(x1,x1)), 1e-6)); } +/* ************************************************************************* */ +TEST(Marginals, order) { + NonlinearFactorGraph fg; + fg.add(PriorFactor(0, Pose2(), noiseModel::Unit::Create(3))); + fg.add(BetweenFactor(0, 1, Pose2(1,0,0), noiseModel::Unit::Create(3))); + fg.add(BetweenFactor(1, 2, Pose2(1,0,0), noiseModel::Unit::Create(3))); + fg.add(BetweenFactor(2, 3, Pose2(1,0,0), noiseModel::Unit::Create(3))); + Values vals; + vals.insert(0, Pose2()); + vals.insert(1, Pose2(1,0,0)); + vals.insert(2, Pose2(2,0,0)); + vals.insert(3, Pose2(3,0,0)); + + vals.insert(100, Point2(0,1)); + vals.insert(101, Point2(1,1)); + + fg.add(BearingRangeFactor(0, 100, + vals.at(0).bearing(vals.at(100)), + vals.at(0).range(vals.at(100)), noiseModel::Unit::Create(2))); + fg.add(BearingRangeFactor(0, 101, + vals.at(0).bearing(vals.at(101)), + vals.at(0).range(vals.at(101)), noiseModel::Unit::Create(2))); + + fg.add(BearingRangeFactor(1, 100, + vals.at(1).bearing(vals.at(100)), + vals.at(1).range(vals.at(100)), noiseModel::Unit::Create(2))); + fg.add(BearingRangeFactor(1, 101, + vals.at(1).bearing(vals.at(101)), + vals.at(1).range(vals.at(101)), noiseModel::Unit::Create(2))); + + fg.add(BearingRangeFactor(2, 100, + vals.at(2).bearing(vals.at(100)), + vals.at(2).range(vals.at(100)), noiseModel::Unit::Create(2))); + fg.add(BearingRangeFactor(2, 101, + vals.at(2).bearing(vals.at(101)), + vals.at(2).range(vals.at(101)), noiseModel::Unit::Create(2))); + + fg.add(BearingRangeFactor(3, 100, + vals.at(3).bearing(vals.at(100)), + vals.at(3).range(vals.at(100)), noiseModel::Unit::Create(2))); + fg.add(BearingRangeFactor(3, 101, + vals.at(3).bearing(vals.at(101)), + vals.at(3).range(vals.at(101)), noiseModel::Unit::Create(2))); + + Marginals marginals(fg, vals); + FastVector keys(fg.keys()); + JointMarginal joint = marginals.jointMarginalCovariance(keys); + + LONGS_EQUAL(3, joint(0,0).rows()); + LONGS_EQUAL(3, joint(1,1).rows()); + LONGS_EQUAL(3, joint(2,2).rows()); + LONGS_EQUAL(3, joint(3,3).rows()); + LONGS_EQUAL(2, joint(100,100).rows()); + LONGS_EQUAL(2, joint(101,101).rows()); +} /* ************************************************************************* */ int main() { TestResult tr; return TestRegistry::runAllTests(tr);} diff --git a/tests/testNonlinearEquality.cpp b/tests/testNonlinearEquality.cpp index 94ab58831..2b580560f 100644 --- a/tests/testNonlinearEquality.cpp +++ b/tests/testNonlinearEquality.cpp @@ -14,15 +14,22 @@ * @author Alex Cunningham */ -#include +#include -#include #include -#include -#include +#include +#include #include #include #include +#include +#include +#include +#include +#include +#include + +#include using namespace std; using namespace gtsam; @@ -35,7 +42,7 @@ typedef PriorFactor PosePrior; typedef NonlinearEquality PoseNLE; typedef boost::shared_ptr shared_poseNLE; -Symbol key('x',1); +static Symbol key('x',1); /* ************************************************************************* */ TEST ( NonlinearEquality, linearization ) { @@ -239,8 +246,8 @@ TEST ( NonlinearEquality, allow_error_optimize_with_factors ) { } /* ************************************************************************* */ -SharedDiagonal hard_model = noiseModel::Constrained::All(2); -SharedDiagonal soft_model = noiseModel::Isotropic::Sigma(2, 1.0); +static SharedDiagonal hard_model = noiseModel::Constrained::All(2); +static SharedDiagonal soft_model = noiseModel::Isotropic::Sigma(2, 1.0); /* ************************************************************************* */ TEST( testNonlinearEqualityConstraint, unary_basics ) { @@ -502,13 +509,13 @@ TEST (testNonlinearEqualityConstraint, map_warp ) { } // make a realistic calibration matrix -double fov = 60; // degrees -size_t w=640,h=480; -Cal3_S2 K(fov,w,h); -boost::shared_ptr shK(new Cal3_S2(K)); +static double fov = 60; // degrees +static size_t w=640,h=480; +static Cal3_S2 K(fov,w,h); +static boost::shared_ptr shK(new Cal3_S2(K)); // typedefs for visual SLAM example -typedef visualSLAM::Graph VGraph; +typedef NonlinearFactorGraph VGraph; // factors for visual slam typedef NonlinearEquality2 Point3Equality; @@ -522,9 +529,9 @@ TEST (testNonlinearEqualityConstraint, stereo_constrained ) { 0.0, 0.0, 1.0, 0.0, -1.0, 0.0)); Pose3 pose1(faceDownY, Point3()); // origin, left camera - SimpleCamera camera1(K, pose1); + SimpleCamera camera1(pose1, K); Pose3 pose2(faceDownY, Point3(2.0, 0.0, 0.0)); // 2 units to the left - SimpleCamera camera2(K, pose2); + SimpleCamera camera2(pose2, K); Point3 landmark(1.0, 5.0, 0.0); //centered between the cameras, 5 units away // keys @@ -535,13 +542,13 @@ TEST (testNonlinearEqualityConstraint, stereo_constrained ) { VGraph graph; // create equality constraints for poses - graph.addPoseConstraint(1, camera1.pose()); - graph.addPoseConstraint(2, camera2.pose()); + graph.add(NonlinearEquality(x1, camera1.pose())); + graph.add(NonlinearEquality(x2, camera2.pose())); // create factors SharedDiagonal vmodel = noiseModel::Unit::Create(3); - graph.addMeasurement(camera1.project(landmark), vmodel, 1, 1, shK); - graph.addMeasurement(camera2.project(landmark), vmodel, 2, 2, shK); + graph.add(GenericProjectionFactor(camera1.project(landmark), vmodel, x1, l1, shK)); + graph.add(GenericProjectionFactor(camera2.project(landmark), vmodel, x2, l2, shK)); // add equality constraint graph.add(Point3Equality(l1, l2)); diff --git a/tests/testNonlinearFactor.cpp b/tests/testNonlinearFactor.cpp index d32a50fe5..c8824749d 100644 --- a/tests/testNonlinearFactor.cpp +++ b/tests/testNonlinearFactor.cpp @@ -28,17 +28,19 @@ #include #include #include -#include -#include +#include +#include #include #include +#include using namespace std; using namespace gtsam; using namespace example; -using simulated2D::PoseKey; -using simulated2D::PointKey; +// Convenience for named keys +using symbol_shorthand::X; +using symbol_shorthand::L; typedef boost::shared_ptr shared_nlf; @@ -49,11 +51,11 @@ TEST( NonlinearFactor, equals ) // create two nonlinear2 factors Point2 z3(0.,-1.); - simulated2D::Measurement f0(z3, sigma, PoseKey(1),PointKey(1)); + simulated2D::Measurement f0(z3, sigma, X(1),L(1)); // measurement between x2 and l1 Point2 z4(-1.5, -1.); - simulated2D::Measurement f1(z4, sigma, PoseKey(2),PointKey(1)); + simulated2D::Measurement f1(z4, sigma, X(2),L(1)); CHECK(assert_equal(f0,f0)); CHECK(f0.equals(f0)); @@ -71,8 +73,8 @@ TEST( NonlinearFactor, equals2 ) Graph::sharedFactor f0 = fg[0], f1 = fg[1]; CHECK(f0->equals(*f0)); -// SL-FIX CHECK(!f0->equals(*f1)); -// SL-FIX CHECK(!f1->equals(*f0)); + CHECK(!f0->equals(*f1)); + CHECK(!f1->equals(*f0)); } /* ************************************************************************* */ @@ -199,16 +201,16 @@ TEST( NonlinearFactor, linearize_constraint1 ) SharedDiagonal constraint = noiseModel::Constrained::MixedSigmas(sigmas); Point2 mu(1., -1.); - Graph::sharedFactor f0(new simulated2D::Prior(mu, constraint, PoseKey(1))); + Graph::sharedFactor f0(new simulated2D::Prior(mu, constraint, X(1))); Values config; - config.insert(simulated2D::PoseKey(1), Point2(1.0, 2.0)); + config.insert(X(1), Point2(1.0, 2.0)); GaussianFactor::shared_ptr actual = f0->linearize(config, *config.orderingArbitrary()); // create expected Ordering ord(*config.orderingArbitrary()); Vector b = Vector_(2, 0., -3.); - JacobianFactor expected(ord[PoseKey(1)], Matrix_(2,2, 5.0, 0.0, 0.0, 1.0), b, constraint); + JacobianFactor expected(ord[X(1)], Matrix_(2,2, 5.0, 0.0, 0.0, 1.0), b, constraint); CHECK(assert_equal((const GaussianFactor&)expected, *actual)); } @@ -219,18 +221,18 @@ TEST( NonlinearFactor, linearize_constraint2 ) SharedDiagonal constraint = noiseModel::Constrained::MixedSigmas(sigmas); Point2 z3(1.,-1.); - simulated2D::Measurement f0(z3, constraint, PoseKey(1),PointKey(1)); + simulated2D::Measurement f0(z3, constraint, X(1),L(1)); Values config; - config.insert(simulated2D::PoseKey(1), Point2(1.0, 2.0)); - config.insert(simulated2D::PointKey(1), Point2(5.0, 4.0)); + config.insert(X(1), Point2(1.0, 2.0)); + config.insert(L(1), Point2(5.0, 4.0)); GaussianFactor::shared_ptr actual = f0.linearize(config, *config.orderingArbitrary()); // create expected Ordering ord(*config.orderingArbitrary()); Matrix A = Matrix_(2,2, 5.0, 0.0, 0.0, 1.0); Vector b = Vector_(2, -15., -3.); - JacobianFactor expected(ord[PoseKey(1)], -1*A, ord[PointKey(1)], A, b, constraint); + JacobianFactor expected(ord[X(1)], -1*A, ord[L(1)], A, b, constraint); CHECK(assert_equal((const GaussianFactor&)expected, *actual)); } @@ -238,7 +240,7 @@ TEST( NonlinearFactor, linearize_constraint2 ) class TestFactor4 : public NoiseModelFactor4 { public: typedef NoiseModelFactor4 Base; - TestFactor4() : Base(sharedSigmas(Vector_(1, 2.0)), PoseKey(1), PoseKey(2), PoseKey(3), PoseKey(4)) {} + TestFactor4() : Base(noiseModel::Diagonal::Sigmas(Vector_(1, 2.0)), X(1), X(2), X(3), X(4)) {} virtual Vector evaluateError(const LieVector& x1, const LieVector& x2, const LieVector& x3, const LieVector& x4, @@ -254,19 +256,23 @@ public: } return (Vector(1) << x1 + x2 + x3 + x4).finished(); } + + virtual gtsam::NonlinearFactor::shared_ptr clone() const { + return boost::static_pointer_cast( + gtsam::NonlinearFactor::shared_ptr(new TestFactor4(*this))); } }; /* ************************************ */ TEST(NonlinearFactor, NoiseModelFactor4) { TestFactor4 tf; Values tv; - tv.insert(PoseKey(1), LieVector(1, 1.0)); - tv.insert(PoseKey(2), LieVector(1, 2.0)); - tv.insert(PoseKey(3), LieVector(1, 3.0)); - tv.insert(PoseKey(4), LieVector(1, 4.0)); + tv.insert(X(1), LieVector(1, 1.0)); + tv.insert(X(2), LieVector(1, 2.0)); + tv.insert(X(3), LieVector(1, 3.0)); + tv.insert(X(4), LieVector(1, 4.0)); EXPECT(assert_equal(Vector_(1, 10.0), tf.unwhitenedError(tv))); DOUBLES_EQUAL(25.0/2.0, tf.error(tv), 1e-9); - Ordering ordering; ordering += PoseKey(1), PoseKey(2), PoseKey(3), PoseKey(4); + Ordering ordering; ordering += X(1), X(2), X(3), X(4); JacobianFactor jf(*boost::dynamic_pointer_cast(tf.linearize(tv, ordering))); LONGS_EQUAL(jf.keys()[0], 0); LONGS_EQUAL(jf.keys()[1], 1); @@ -283,7 +289,7 @@ TEST(NonlinearFactor, NoiseModelFactor4) { class TestFactor5 : public NoiseModelFactor5 { public: typedef NoiseModelFactor5 Base; - TestFactor5() : Base(sharedSigmas(Vector_(1, 2.0)), PoseKey(1), PoseKey(2), PoseKey(3), PoseKey(4), PoseKey(5)) {} + TestFactor5() : Base(noiseModel::Diagonal::Sigmas(Vector_(1, 2.0)), X(1), X(2), X(3), X(4), X(5)) {} virtual Vector evaluateError(const X1& x1, const X2& x2, const X3& x3, const X4& x4, const X5& x5, @@ -307,14 +313,14 @@ public: TEST(NonlinearFactor, NoiseModelFactor5) { TestFactor5 tf; Values tv; - tv.insert(PoseKey(1), LieVector(1, 1.0)); - tv.insert(PoseKey(2), LieVector(1, 2.0)); - tv.insert(PoseKey(3), LieVector(1, 3.0)); - tv.insert(PoseKey(4), LieVector(1, 4.0)); - tv.insert(PoseKey(5), LieVector(1, 5.0)); + tv.insert(X(1), LieVector(1, 1.0)); + tv.insert(X(2), LieVector(1, 2.0)); + tv.insert(X(3), LieVector(1, 3.0)); + tv.insert(X(4), LieVector(1, 4.0)); + tv.insert(X(5), LieVector(1, 5.0)); EXPECT(assert_equal(Vector_(1, 15.0), tf.unwhitenedError(tv))); DOUBLES_EQUAL(56.25/2.0, tf.error(tv), 1e-9); - Ordering ordering; ordering += PoseKey(1), PoseKey(2), PoseKey(3), PoseKey(4), PoseKey(5); + Ordering ordering; ordering += X(1), X(2), X(3), X(4), X(5); JacobianFactor jf(*boost::dynamic_pointer_cast(tf.linearize(tv, ordering))); LONGS_EQUAL(jf.keys()[0], 0); LONGS_EQUAL(jf.keys()[1], 1); @@ -333,7 +339,7 @@ TEST(NonlinearFactor, NoiseModelFactor5) { class TestFactor6 : public NoiseModelFactor6 { public: typedef NoiseModelFactor6 Base; - TestFactor6() : Base(sharedSigmas(Vector_(1, 2.0)), PoseKey(1), PoseKey(2), PoseKey(3), PoseKey(4), PoseKey(5), PoseKey(6)) {} + TestFactor6() : Base(noiseModel::Diagonal::Sigmas(Vector_(1, 2.0)), X(1), X(2), X(3), X(4), X(5), X(6)) {} virtual Vector evaluateError(const X1& x1, const X2& x2, const X3& x3, const X4& x4, const X5& x5, const X6& x6, @@ -353,21 +359,22 @@ public: } return (Vector(1) << x1 + x2 + x3 + x4 + x5 + x6).finished(); } + }; /* ************************************ */ TEST(NonlinearFactor, NoiseModelFactor6) { TestFactor6 tf; Values tv; - tv.insert(PoseKey(1), LieVector(1, 1.0)); - tv.insert(PoseKey(2), LieVector(1, 2.0)); - tv.insert(PoseKey(3), LieVector(1, 3.0)); - tv.insert(PoseKey(4), LieVector(1, 4.0)); - tv.insert(PoseKey(5), LieVector(1, 5.0)); - tv.insert(PoseKey(6), LieVector(1, 6.0)); + tv.insert(X(1), LieVector(1, 1.0)); + tv.insert(X(2), LieVector(1, 2.0)); + tv.insert(X(3), LieVector(1, 3.0)); + tv.insert(X(4), LieVector(1, 4.0)); + tv.insert(X(5), LieVector(1, 5.0)); + tv.insert(X(6), LieVector(1, 6.0)); EXPECT(assert_equal(Vector_(1, 21.0), tf.unwhitenedError(tv))); DOUBLES_EQUAL(110.25/2.0, tf.error(tv), 1e-9); - Ordering ordering; ordering += PoseKey(1), PoseKey(2), PoseKey(3), PoseKey(4), PoseKey(5), PoseKey(6); + Ordering ordering; ordering += X(1), X(2), X(3), X(4), X(5), X(6); JacobianFactor jf(*boost::dynamic_pointer_cast(tf.linearize(tv, ordering))); LONGS_EQUAL(jf.keys()[0], 0); LONGS_EQUAL(jf.keys()[1], 1); @@ -385,6 +392,42 @@ TEST(NonlinearFactor, NoiseModelFactor6) { } +/* ************************************************************************* */ +TEST( NonlinearFactor, clone_rekey ) +{ + shared_nlf init(new TestFactor4()); + EXPECT_LONGS_EQUAL(X(1), init->keys()[0]); + EXPECT_LONGS_EQUAL(X(2), init->keys()[1]); + EXPECT_LONGS_EQUAL(X(3), init->keys()[2]); + EXPECT_LONGS_EQUAL(X(4), init->keys()[3]); + + // Standard clone + shared_nlf actClone = init->clone(); + EXPECT(actClone.get() != init.get()); // Ensure different pointers + EXPECT(assert_equal(*init, *actClone)); + + // Re-key factor - clones with different keys + std::vector new_keys(4); + new_keys[0] = X(5); + new_keys[1] = X(6); + new_keys[2] = X(7); + new_keys[3] = X(8); + shared_nlf actRekey = init->rekey(new_keys); + EXPECT(actRekey.get() != init.get()); // Ensure different pointers + + // Ensure init is unchanged + EXPECT_LONGS_EQUAL(X(1), init->keys()[0]); + EXPECT_LONGS_EQUAL(X(2), init->keys()[1]); + EXPECT_LONGS_EQUAL(X(3), init->keys()[2]); + EXPECT_LONGS_EQUAL(X(4), init->keys()[3]); + + // Check new keys + EXPECT_LONGS_EQUAL(X(5), actRekey->keys()[0]); + EXPECT_LONGS_EQUAL(X(6), actRekey->keys()[1]); + EXPECT_LONGS_EQUAL(X(7), actRekey->keys()[2]); + EXPECT_LONGS_EQUAL(X(8), actRekey->keys()[3]); +} + /* ************************************************************************* */ int main() { TestResult tr; return TestRegistry::runAllTests(tr);} /* ************************************************************************* */ diff --git a/tests/testNonlinearFactorGraph.cpp b/tests/testNonlinearFactorGraph.cpp index 92e569038..f677eb0dc 100644 --- a/tests/testNonlinearFactorGraph.cpp +++ b/tests/testNonlinearFactorGraph.cpp @@ -29,15 +29,16 @@ using namespace boost::assign; #include #include -#include +#include #include #include +#include using namespace gtsam; using namespace example; -Key kx(size_t i) { return Symbol('x',i); } -Key kl(size_t i) { return Symbol('l',i); } +using symbol_shorthand::X; +using symbol_shorthand::L; /* ************************************************************************* */ TEST( Graph, equals ) @@ -64,25 +65,32 @@ TEST( Graph, error ) TEST( Graph, keys ) { Graph fg = createNonlinearFactorGraph(); - set actual = fg.keys(); + FastSet actual = fg.keys(); LONGS_EQUAL(3, actual.size()); - set::const_iterator it = actual.begin(); - LONGS_EQUAL(kl(1), *(it++)); - LONGS_EQUAL(kx(1), *(it++)); - LONGS_EQUAL(kx(2), *(it++)); + FastSet::const_iterator it = actual.begin(); + LONGS_EQUAL(L(1), *(it++)); + LONGS_EQUAL(X(1), *(it++)); + LONGS_EQUAL(X(2), *(it++)); } /* ************************************************************************* */ TEST( Graph, GET_ORDERING) { // Ordering expected; expected += "x1","l1","x2"; // For starting with x1,x2,l1 - Ordering expected; expected += kl(1), kx(2), kx(1); // For starting with l1,x1,x2 + Ordering expected; expected += L(1), X(2), X(1); // For starting with l1,x1,x2 Graph nlfg = createNonlinearFactorGraph(); SymbolicFactorGraph::shared_ptr symbolic; Ordering::shared_ptr ordering; boost::tie(symbolic, ordering) = nlfg.symbolic(createNoisyValues()); Ordering actual = *nlfg.orderingCOLAMD(createNoisyValues()); - CHECK(assert_equal(expected,actual)); + EXPECT(assert_equal(expected,actual)); + + // Constrained ordering - put x2 at the end + std::map constraints; + constraints[X(2)] = 1; + Ordering actualConstrained = *nlfg.orderingCOLAMDConstrained(createNoisyValues(), constraints); + Ordering expectedConstrained; expectedConstrained += L(1), X(1), X(2); + EXPECT(assert_equal(expectedConstrained, actualConstrained)); } /* ************************************************************************* */ @@ -108,8 +116,42 @@ TEST( Graph, linearize ) } /* ************************************************************************* */ -int main() { - TestResult tr; - return TestRegistry::runAllTests(tr); +TEST( Graph, clone ) +{ + Graph fg = createNonlinearFactorGraph(); + Graph actClone = fg.clone(); + EXPECT(assert_equal(fg, actClone)); + for (size_t i=0; i rekey_mapping; + rekey_mapping.insert(make_pair(L(1), L(4))); + Graph actRekey = init.rekey(rekey_mapping); + + // ensure deep clone + LONGS_EQUAL(init.size(), actRekey.size()); + for (size_t i=0; i -#include +#include +#include #include -#include +#include +#include +#include +#include +#include + using namespace gtsam; -using namespace planarSLAM; -typedef NonlinearISAM<> PlanarISAM; +typedef NonlinearISAM PlanarISAM; const double tol=1e-5; @@ -26,22 +31,22 @@ TEST(testNonlinearISAM, markov_chain ) { // create initial graph Pose2 cur_pose; // start at origin - Graph start_factors; - start_factors.addPoseConstraint(0, cur_pose); + NonlinearFactorGraph start_factors; + start_factors.add(NonlinearEquality(0, cur_pose)); - planarSLAM::Values init; - planarSLAM::Values expected; - init.insertPose(0, cur_pose); - expected.insertPose(0, cur_pose); + Values init; + Values expected; + init.insert(0, cur_pose); + expected.insert(0, cur_pose); isam.update(start_factors, init); // loop for a period of time to verify memory usage size_t nrPoses = 21; Pose2 z(1.0, 2.0, 0.1); for (size_t i=1; i<=nrPoses; ++i) { - Graph new_factors; - new_factors.addOdometry(i-1, i, z, model); - planarSLAM::Values new_init; + NonlinearFactorGraph new_factors; + new_factors.add(BetweenFactor(i-1, i, z, model)); + Values new_init; // perform a check on changing orderings if (i == 5) { @@ -54,20 +59,20 @@ TEST(testNonlinearISAM, markov_chain ) { ordering.push_back(secondLast); isam.setOrdering(ordering); - Ordering expected; expected += PoseKey(0), PoseKey(1), PoseKey(2), PoseKey(4), PoseKey(3); + Ordering expected; expected += (0), (1), (2), (4), (3); EXPECT(assert_equal(expected, isam.getOrdering())); } cur_pose = cur_pose.compose(z); - new_init.insertPose(i, cur_pose.retract(sampler.sample())); - expected.insertPose(i, cur_pose); + new_init.insert(i, cur_pose.retract(sampler.sample())); + expected.insert(i, cur_pose); isam.update(new_factors, new_init); } // verify values - all but the last one should be very close - planarSLAM::Values actual = isam.estimate(); + Values actual = isam.estimate(); for (size_t i=0; i(i), actual.at(i), tol)); } } diff --git a/tests/testNonlinearOptimizer.cpp b/tests/testNonlinearOptimizer.cpp index d1eb01f27..cb5e8f482 100644 --- a/tests/testNonlinearOptimizer.cpp +++ b/tests/testNonlinearOptimizer.cpp @@ -15,32 +15,36 @@ * @author Frank Dellaert */ -#include -using namespace std; - -#include // for operator += -using namespace boost::assign; +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include #include #include -using namespace boost; +#include // for operator += +using namespace boost::assign; -#include -#include -#include -#include -#include -#include -#include -#include +#include +using namespace std; using namespace gtsam; const double tol = 1e-5; -Key kx(size_t i) { return Symbol('x',i); } -Key kl(size_t i) { return Symbol('l',i); } +using symbol_shorthand::X; +using symbol_shorthand::L; /* ************************************************************************* */ TEST( NonlinearOptimizer, iterateLM ) @@ -51,7 +55,7 @@ TEST( NonlinearOptimizer, iterateLM ) // config far from minimum Point2 x0(3,0); Values config; - config.insert(simulated2D::PoseKey(1), x0); + config.insert(X(1), x0); // normal iterate GaussNewtonParams gnParams; @@ -75,18 +79,18 @@ TEST( NonlinearOptimizer, optimize ) // test error at minimum Point2 xstar(0,0); Values cstar; - cstar.insert(simulated2D::PoseKey(1), xstar); + cstar.insert(X(1), xstar); DOUBLES_EQUAL(0.0,fg.error(cstar),0.0); // test error at initial = [(1-cos(3))^2 + (sin(3))^2]*50 = Point2 x0(3,3); Values c0; - c0.insert(simulated2D::PoseKey(1), x0); + c0.insert(X(1), x0); DOUBLES_EQUAL(199.0,fg.error(c0),1e-3); // optimize parameters Ordering ord; - ord.push_back(kx(1)); + ord.push_back(X(1)); // Gauss-Newton GaussNewtonParams gnParams; @@ -114,7 +118,7 @@ TEST( NonlinearOptimizer, SimpleLMOptimizer ) Point2 x0(3,3); Values c0; - c0.insert(simulated2D::PoseKey(1), x0); + c0.insert(X(1), x0); Values actual = LevenbergMarquardtOptimizer(fg, c0).optimize(); DOUBLES_EQUAL(0,fg.error(actual),tol); @@ -127,7 +131,7 @@ TEST( NonlinearOptimizer, SimpleGNOptimizer ) Point2 x0(3,3); Values c0; - c0.insert(simulated2D::PoseKey(1), x0); + c0.insert(X(1), x0); Values actual = GaussNewtonOptimizer(fg, c0).optimize(); DOUBLES_EQUAL(0,fg.error(actual),tol); @@ -140,7 +144,7 @@ TEST( NonlinearOptimizer, SimpleDLOptimizer ) Point2 x0(3,3); Values c0; - c0.insert(simulated2D::PoseKey(1), x0); + c0.insert(X(1), x0); Values actual = DoglegOptimizer(fg, c0).optimize(); DOUBLES_EQUAL(0,fg.error(actual),tol); @@ -150,15 +154,15 @@ TEST( NonlinearOptimizer, SimpleDLOptimizer ) TEST( NonlinearOptimizer, optimization_method ) { LevenbergMarquardtParams paramsQR; - paramsQR.factorization = LevenbergMarquardtParams::QR; + paramsQR.linearSolverType = LevenbergMarquardtParams::MULTIFRONTAL_QR; LevenbergMarquardtParams paramsChol; - paramsChol.factorization = LevenbergMarquardtParams::CHOLESKY; + paramsChol.linearSolverType = LevenbergMarquardtParams::MULTIFRONTAL_CHOLESKY; example::Graph fg = example::createReallyNonlinearFactorGraph(); Point2 x0(3,3); Values c0; - c0.insert(simulated2D::PoseKey(1), x0); + c0.insert(X(1), x0); Values actualMFQR = LevenbergMarquardtOptimizer(fg, c0, paramsQR).optimize(); DOUBLES_EQUAL(0,fg.error(actualMFQR),tol); @@ -171,23 +175,23 @@ TEST( NonlinearOptimizer, optimization_method ) TEST( NonlinearOptimizer, Factorization ) { Values config; - config.insert(pose2SLAM::PoseKey(1), Pose2(0.,0.,0.)); - config.insert(pose2SLAM::PoseKey(2), Pose2(1.5,0.,0.)); + config.insert(X(1), Pose2(0.,0.,0.)); + config.insert(X(2), Pose2(1.5,0.,0.)); - pose2SLAM::Graph graph; - graph.addPrior(1, Pose2(0.,0.,0.), noiseModel::Isotropic::Sigma(3, 1e-10)); - graph.addOdometry(1,2, Pose2(1.,0.,0.), noiseModel::Isotropic::Sigma(3, 1)); + NonlinearFactorGraph graph; + graph.add(PriorFactor(X(1), Pose2(0.,0.,0.), noiseModel::Isotropic::Sigma(3, 1e-10))); + graph.add(BetweenFactor(X(1),X(2), Pose2(1.,0.,0.), noiseModel::Isotropic::Sigma(3, 1))); Ordering ordering; - ordering.push_back(pose2SLAM::PoseKey(1)); - ordering.push_back(pose2SLAM::PoseKey(2)); + ordering.push_back(X(1)); + ordering.push_back(X(2)); LevenbergMarquardtOptimizer optimizer(graph, config, ordering); optimizer.iterate(); Values expected; - expected.insert(pose2SLAM::PoseKey(1), Pose2(0.,0.,0.)); - expected.insert(pose2SLAM::PoseKey(2), Pose2(1.,0.,0.)); + expected.insert(X(1), Pose2(0.,0.,0.)); + expected.insert(X(2), Pose2(1.,0.,0.)); CHECK(assert_equal(expected, optimizer.values(), 1e-5)); } @@ -202,18 +206,18 @@ TEST(NonlinearOptimizer, NullFactor) { // test error at minimum Point2 xstar(0,0); Values cstar; - cstar.insert(simulated2D::PoseKey(1), xstar); + cstar.insert(X(1), xstar); DOUBLES_EQUAL(0.0,fg.error(cstar),0.0); // test error at initial = [(1-cos(3))^2 + (sin(3))^2]*50 = Point2 x0(3,3); Values c0; - c0.insert(simulated2D::PoseKey(1), x0); + c0.insert(X(1), x0); DOUBLES_EQUAL(199.0,fg.error(c0),1e-3); // optimize parameters Ordering ord; - ord.push_back(kx(1)); + ord.push_back(X(1)); // Gauss-Newton Values actual1 = GaussNewtonOptimizer(fg, c0, ord).optimize(); @@ -232,9 +236,9 @@ TEST(NonlinearOptimizer, NullFactor) { TEST(NonlinearOptimizer, MoreOptimization) { NonlinearFactorGraph fg; - fg.add(PriorFactor(0, Pose2(0,0,0), sharedSigma(3,1))); - fg.add(BetweenFactor(0, 1, Pose2(1,0,M_PI/2), sharedSigma(3,1))); - fg.add(BetweenFactor(1, 2, Pose2(1,0,M_PI/2), sharedSigma(3,1))); + fg.add(PriorFactor(0, Pose2(0,0,0), noiseModel::Isotropic::Sigma(3,1))); + fg.add(BetweenFactor(0, 1, Pose2(1,0,M_PI/2), noiseModel::Isotropic::Sigma(3,1))); + fg.add(BetweenFactor(1, 2, Pose2(1,0,M_PI/2), noiseModel::Isotropic::Sigma(3,1))); Values init; init.insert(0, Pose2(3,4,-M_PI)); diff --git a/tests/testOccupancyGrid.cpp b/tests/testOccupancyGrid.cpp new file mode 100644 index 000000000..86678cc12 --- /dev/null +++ b/tests/testOccupancyGrid.cpp @@ -0,0 +1,332 @@ +/** + * @file testOccupancyGrid.cpp + * @date May 14, 2012 + * @author Brian Peasley + * @author Frank Dellaert + */ + + +#include +#include +#include +#include +//#include // FIXME: does not exist in boost 1.46 +#include // Old header - should still exist + +#include +#include +#include + +using namespace std; +using namespace gtsam; + + +/** + * Laser Factor + * @brief factor that encodes a laser measurements likelihood. + */ + +class LaserFactor : public DiscreteFactor{ +private: + vector m_cells; ///cells in which laser passes through + +public: + + ///constructor + LaserFactor(const vector &cells) : m_cells(cells) {} + + /** + * Find value for given assignment of values to variables + * return 1000 if any of the non-last cell is occupied and 1 otherwise + * Values contains all occupancy values (0 or 1) + */ + virtual double operator()(const Values &vals) const{ + + // loops through all but the last cell and checks that they are all 0. Otherwise return 1000. + for(Index i = 0; i < m_cells.size() - 1; i++){ + if(vals.at(m_cells[i]) == 1) + return 1000; + } + + // check if the last cell hit by the laser is 1. return 900 otherwise. + if(vals.at(m_cells[m_cells.size() - 1]) == 0) + return 900; + + return 1; + + } + + /// Multiply in a DecisionTreeFactor and return the result as DecisionTreeFactor + virtual DecisionTreeFactor operator*(const DecisionTreeFactor&) const{ + throw runtime_error("operator * not implemented"); + } + + virtual DecisionTreeFactor toDecisionTreeFactor() const{ + throw runtime_error("DecisionTreeFactor toDecisionTreeFactor not implemented"); + } +}; + +/** + * OccupancyGrid Class + * An occupancy grid is just a factor graph. + * Every cell in the occupancy grid is a variable in the factor graph. + * Measurements will create factors, as well as the prior. + */ +class OccupancyGrid : public DiscreteFactorGraph { +private: + size_t width_; //number of cells wide the grid is + size_t height_; //number of cells tall the grid is + double res_; //the resolution at which the grid is created + + vector cells_; //list of keys of all cells in the grid + vector laser_indices_; //indices of the laser factor in factors_ + + +public: + + size_t width() const { + return width_; + } + size_t height() const { + return height_; + } + // should we just not typedef Values Occupancy; ? + class Occupancy : public Values { + private: + public: + }; + + + typedef std::vector Marginals; + ///constructor + ///Creates a 2d grid of cells with the origin in the center of the grid + OccupancyGrid(double width, double height, double resolution){ + width_ = width/resolution; + height_ = height/resolution; + res_ = resolution; + + for(Index i = 0; i < cellCount(); i++) + cells_.push_back(i); + } + + /// Returns an empty occupancy grid of size width_ x height_ + Occupancy emptyOccupancy(){ + Occupancy occupancy; //mapping from Index to value (0 or 1) + for(size_t i = 0; i < cellCount(); i++) + occupancy.insert(pair((Index)i,0)); + + return occupancy; + } + + ///add a prior + void addPosePrior(Index cell, double prior){ + size_t numStates = 2; + DiscreteKey key(cell, numStates); + + //add a factor + vector table(2); + table[0] = 1-prior; + table[1] = prior; + add(key, table); + } + + ///add a laser measurement + void addLaser(const Pose2 &pose, double range){ + //ray trace from pose to range t//a >= 1 accept new stateo find all cells the laser passes through + double x = pose.x(); //start position of the laser + double y = pose.y(); + double step = res_/8.0; //amount to step in each iteration of laser traversal + + Index key; + vector cells; //list of keys of cells hit by the laser + + //traverse laser + for(double i = 0; i < range; i += step){ + //get point on laser + x = pose.x() + i*cos(pose.theta()); + y = pose.y() + i*sin(pose.theta()); + + //printf("%lf %lf\n", x, y); + //get the key of the cell that holds point (x,y) + key = keyLookup(x,y); + + //add cell to list of cells if it is new + if(i == 0 || key != cells[cells.size()-1]) + cells.push_back(key); + } + +// for(size_t i = 0; i < cells.size(); i++) +// printf("%ld ", cells[i]); +// printf("\n"); + + //add a factor that connects all those cells + laser_indices_.push_back(factors_.size()); + push_back(boost::make_shared(cells)); + + } + + /// returns the number of cells in the grid + size_t cellCount() const { + return width_*height_; + } + + /// returns the key of the cell in which point (x,y) lies. + Index keyLookup(double x, double y) const { + //move (x,y) to the nearest resolution + x *= (1.0/res_); + y *= (1.0/res_); + + //round to nearest integer + x = (double)((int)x); + y = (double)((int)y); + + //determine index + x += width_/2; + y = height_/2 - y; + + //bounds checking + size_t index = y*width_ + x; + index = index >= width_*height_ ? -1 : index; + + return cells_[index]; + } + + /** + * @brief Computes the value of a laser factor + * @param index defines which laser is to be used + * @param occupancy defines the grid which the laser will be evaulated with + * @ret a double value that is the value of the specified laser factor for the grid + */ + double laserFactorValue(Index index, const Occupancy &occupancy) const{ + return (*factors_[ laser_indices_[index] ])(occupancy); + } + + /// returns the sum of the laser factors for the current state of the grid + double operator()(const Occupancy &occupancy) const { + double value = 0; + + // loop over all laser factors in the graph + //printf("%ld\n", (*this).size()); + + for(Index i = 0; i < laser_indices_.size(); i++){ + value += laserFactorValue(i, occupancy); + } + + return value; + } + + /** + * @brief Run a metropolis sampler. + * @param iterations defines the number of iterations to run. + * @return vector of marginal probabilities. + */ + Marginals runMetropolis(size_t iterations){ + Occupancy occupancy = emptyOccupancy(); + + size_t size = cellCount(); + Marginals marginals(size); + + // NOTE: using older interface for boost.random due to interface changes after boost 1.46 + boost::mt19937 rng; + boost::uniform_int random_cell(0,size-1); + + // run Metropolis for the requested number of operations + // compute initial probability of occupancy grid, P(x_t) + + double Px = (*this)(occupancy); + + for(size_t it = 0; it < marginals.size(); it++) + marginals[it] = 0; + + for(size_t it = 0; it < iterations; it++){ + //choose a random cell + Index x = random_cell(rng); + //printf("%ld:",x); + //flip the state of a random cell, x + occupancy[x] = 1 - occupancy[x]; + + //compute probability of new occupancy grid, P(x') + //by summing over all LaserFactor::operator() + double Px_prime = (*this)(occupancy); + + //occupancy.print(); + //calculate acceptance ratio, a + double a = Px_prime/Px; + + //if a <= 1 otherwise accept with probability a + //if we accept the new state P(x_t) = P(x') + // printf(" %.3lf %.3lf\t", Px, Px_prime); + if(a <= 1){ + Px = Px_prime; + //printf("\taccept\n"); + } + else{ + occupancy[x] = 1 - occupancy[x]; + // printf("\treject\n"); + } + + //increment the number of iterations each cell has been on + for(size_t i = 0; i < size; i++){ + if(occupancy[i] == 1) + marginals[i]++; + } + } + + //compute the marginals + for(size_t it = 0; it < size; it++) + marginals[it] /= iterations; + + return marginals; + } + +}; + +/* ************************************************************************* */ +TEST_UNSAFE( OccupancyGrid, Test1) { + //Build a small grid and test optimization + + //Build small grid + double width = 3; //meters + double height = 2; //meters + double resolution = 0.5; //meters + OccupancyGrid occupancyGrid(width, height, resolution); //default center to middle + + //Add measurements + Pose2 pose(0,0,0); + double range = 1; + + occupancyGrid.addPosePrior(0, 0.7); + EXPECT_LONGS_EQUAL(1, occupancyGrid.size()); + + occupancyGrid.addLaser(pose, range); + EXPECT_LONGS_EQUAL(2, occupancyGrid.size()); + + OccupancyGrid::Occupancy occupancy = occupancyGrid.emptyOccupancy(); + EXPECT_LONGS_EQUAL(900, occupancyGrid.laserFactorValue(0,occupancy)); + + + occupancy[16] = 1; + EXPECT_LONGS_EQUAL(1, occupancyGrid.laserFactorValue(0,occupancy)); + + occupancy[15] = 1; + EXPECT_LONGS_EQUAL(1000, occupancyGrid.laserFactorValue(0,occupancy)); + + occupancy[16] = 0; + EXPECT_LONGS_EQUAL(1000, occupancyGrid.laserFactorValue(0,occupancy)); + + + //run MCMC + OccupancyGrid::Marginals occupancyMarginals = occupancyGrid.runMetropolis(50000); + EXPECT_LONGS_EQUAL( (width*height)/pow(resolution,2), occupancyMarginals.size()); + + + +} + +/* ************************************************************************* */ +int main() { + TestResult tr; + return TestRegistry::runAllTests(tr); +} +/* ************************************************************************* */ + diff --git a/tests/testPose2SLAMwSPCG.cpp b/tests/testPose2SLAMwSPCG.cpp deleted file mode 100644 index 439228c79..000000000 --- a/tests/testPose2SLAMwSPCG.cpp +++ /dev/null @@ -1,72 +0,0 @@ -/** - * @file testPose2SLAMwSPCG - * @author Alex Cunningham - */ - -#include - -#include -#include - -using namespace std; -using namespace gtsam; -using namespace pose2SLAM; - -const double tol = 1e-5; - -/* ************************************************************************* */ -TEST(testPose2SLAMwSPCG, example1) { - - /* generate synthetic data */ - const SharedNoiseModel sigma(noiseModel::Unit::Create(0.1)); - Key x1(1), x2(2), x3(3), x4(4), x5(5), x6(6), x7(7), x8(8), x9(9); - - // create a 3 by 3 grid - // x3 x6 x9 - // x2 x5 x8 - // x1 x4 x7 - Graph graph; - graph.addConstraint(x1,x2,Pose2(0,2,0),sigma) ; - graph.addConstraint(x2,x3,Pose2(0,2,0),sigma) ; - graph.addConstraint(x4,x5,Pose2(0,2,0),sigma) ; - graph.addConstraint(x5,x6,Pose2(0,2,0),sigma) ; - graph.addConstraint(x7,x8,Pose2(0,2,0),sigma) ; - graph.addConstraint(x8,x9,Pose2(0,2,0),sigma) ; - graph.addConstraint(x1,x4,Pose2(2,0,0),sigma) ; - graph.addConstraint(x4,x7,Pose2(2,0,0),sigma) ; - graph.addConstraint(x2,x5,Pose2(2,0,0),sigma) ; - graph.addConstraint(x5,x8,Pose2(2,0,0),sigma) ; - graph.addConstraint(x3,x6,Pose2(2,0,0),sigma) ; - graph.addConstraint(x6,x9,Pose2(2,0,0),sigma) ; - graph.addPrior(x1, Pose2(0,0,0), sigma) ; - - Values initial; - initial.insert(x1, Pose2( 0, 0, 0)); - initial.insert(x2, Pose2( 0, 2.1, 0.01)); - initial.insert(x3, Pose2( 0, 3.9,-0.01)); - initial.insert(x4, Pose2(2.1,-0.1, 0)); - initial.insert(x5, Pose2(1.9, 2.1, 0.02)); - initial.insert(x6, Pose2(2.0, 3.9,-0.02)); - initial.insert(x7, Pose2(4.0, 0.1, 0.03 )); - initial.insert(x8, Pose2(3.9, 2.1, 0.01)); - initial.insert(x9, Pose2(4.1, 3.9,-0.01)); - - Values expected; - expected.insert(x1, Pose2(0.0, 0.0, 0.0)); - expected.insert(x2, Pose2(0.0, 2.0, 0.0)); - expected.insert(x3, Pose2(0.0, 4.0, 0.0)); - expected.insert(x4, Pose2(2.0, 0.0, 0.0)); - expected.insert(x5, Pose2(2.0, 2.0, 0.0)); - expected.insert(x6, Pose2(2.0, 4.0, 0.0)); - expected.insert(x7, Pose2(4.0, 0.0, 0.0 )); - expected.insert(x8, Pose2(4.0, 2.0, 0.0)); - expected.insert(x9, Pose2(4.0, 4.0, 0.0)); - - Values actual = optimizeSPCG(graph, initial); - - EXPECT(assert_equal(expected, actual, tol)); -} - -/* ************************************************************************* */ -int main() { TestResult tr; return TestRegistry::runAllTests(tr); } -/* ************************************************************************* */ diff --git a/tests/testRot3Optimization.cpp b/tests/testRot3Optimization.cpp index df2471933..89b621ed2 100644 --- a/tests/testRot3Optimization.cpp +++ b/tests/testRot3Optimization.cpp @@ -24,6 +24,7 @@ #include #include #include +#include #include #include @@ -40,11 +41,11 @@ TEST(Rot3, optimize) { Values truth; Values initial; Graph fg; - fg.add(Prior(Symbol('r',0), Rot3(), sharedSigma(3, 0.01))); + fg.add(Prior(Symbol('r',0), Rot3(), noiseModel::Isotropic::Sigma(3, 0.01))); for(int j=0; j<6; ++j) { truth.insert(Symbol('r',j), Rot3::Rz(M_PI/3.0 * double(j))); initial.insert(Symbol('r',j), Rot3::Rz(M_PI/3.0 * double(j) + 0.1 * double(j%2))); - fg.add(Between(Symbol('r',j), Symbol('r',(j+1)%6), Rot3::Rz(M_PI/3.0), sharedSigma(3, 0.01))); + fg.add(Between(Symbol('r',j), Symbol('r',(j+1)%6), Rot3::Rz(M_PI/3.0), noiseModel::Isotropic::Sigma(3, 0.01))); } Values final = GaussNewtonOptimizer(fg, initial).optimize(); diff --git a/tests/testSerializationSLAM.cpp b/tests/testSerializationSLAM.cpp new file mode 100644 index 000000000..4f9664e20 --- /dev/null +++ b/tests/testSerializationSLAM.cpp @@ -0,0 +1,594 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file testSerializationSLAM.cpp + * @brief test serialization + * @author Richard Roberts + * @date Feb 7, 2012 + */ + +#include +//#include +#include +#include +#include +//#include +#include +//#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +#include +#include + +using namespace std; +using namespace gtsam; +using namespace gtsam::serializationTestHelpers; + +// Creating as many permutations of factors as possible +typedef PriorFactor PriorFactorLieVector; +typedef PriorFactor PriorFactorLieMatrix; +typedef PriorFactor PriorFactorPoint2; +typedef PriorFactor PriorFactorStereoPoint2; +typedef PriorFactor PriorFactorPoint3; +typedef PriorFactor PriorFactorRot2; +typedef PriorFactor PriorFactorRot3; +typedef PriorFactor PriorFactorPose2; +typedef PriorFactor PriorFactorPose3; +typedef PriorFactor PriorFactorCal3_S2; +typedef PriorFactor PriorFactorCal3DS2; +typedef PriorFactor PriorFactorCalibratedCamera; +typedef PriorFactor PriorFactorSimpleCamera; +typedef PriorFactor PriorFactorStereoCamera; + +typedef BetweenFactor BetweenFactorLieVector; +typedef BetweenFactor BetweenFactorLieMatrix; +typedef BetweenFactor BetweenFactorPoint2; +typedef BetweenFactor BetweenFactorPoint3; +typedef BetweenFactor BetweenFactorRot2; +typedef BetweenFactor BetweenFactorRot3; +typedef BetweenFactor BetweenFactorPose2; +typedef BetweenFactor BetweenFactorPose3; + +typedef NonlinearEquality NonlinearEqualityLieVector; +typedef NonlinearEquality NonlinearEqualityLieMatrix; +typedef NonlinearEquality NonlinearEqualityPoint2; +typedef NonlinearEquality NonlinearEqualityStereoPoint2; +typedef NonlinearEquality NonlinearEqualityPoint3; +typedef NonlinearEquality NonlinearEqualityRot2; +typedef NonlinearEquality NonlinearEqualityRot3; +typedef NonlinearEquality NonlinearEqualityPose2; +typedef NonlinearEquality NonlinearEqualityPose3; +typedef NonlinearEquality NonlinearEqualityCal3_S2; +typedef NonlinearEquality NonlinearEqualityCal3DS2; +typedef NonlinearEquality NonlinearEqualityCalibratedCamera; +typedef NonlinearEquality NonlinearEqualitySimpleCamera; +typedef NonlinearEquality NonlinearEqualityStereoCamera; + +typedef RangeFactor RangeFactorPosePoint2; +typedef RangeFactor RangeFactorPosePoint3; +typedef RangeFactor RangeFactorPose2; +typedef RangeFactor RangeFactorPose3; +typedef RangeFactor RangeFactorCalibratedCameraPoint; +typedef RangeFactor RangeFactorSimpleCameraPoint; +typedef RangeFactor RangeFactorCalibratedCamera; +typedef RangeFactor RangeFactorSimpleCamera; + +typedef BearingFactor BearingFactor2D; +typedef BearingFactor BearingFactor3D; + +typedef BearingRangeFactor BearingRangeFactor2D; +typedef BearingRangeFactor BearingRangeFactor3D; + +typedef GenericProjectionFactor GenericProjectionFactorCal3_S2; +typedef GenericProjectionFactor GenericProjectionFactorCal3DS2; + +typedef gtsam::GeneralSFMFactor GeneralSFMFactorCal3_S2; +//typedef gtsam::GeneralSFMFactor GeneralSFMFactorCal3DS2; + +typedef gtsam::GeneralSFMFactor2 GeneralSFMFactor2Cal3_S2; + +typedef gtsam::GenericStereoFactor GenericStereoFactor3D; + + +// Convenience for named keys +using symbol_shorthand::X; +using symbol_shorthand::L; + + +/* Create GUIDs for Noisemodels */ +/* ************************************************************************* */ +BOOST_CLASS_EXPORT_GUID(gtsam::noiseModel::Constrained, "gtsam_noiseModel_Constrained"); +BOOST_CLASS_EXPORT_GUID(gtsam::noiseModel::Diagonal, "gtsam_noiseModel_Diagonal"); +BOOST_CLASS_EXPORT_GUID(gtsam::noiseModel::Gaussian, "gtsam_noiseModel_Gaussian"); +BOOST_CLASS_EXPORT_GUID(gtsam::noiseModel::Unit, "gtsam_noiseModel_Unit"); +BOOST_CLASS_EXPORT_GUID(gtsam::noiseModel::Isotropic, "gtsam_noiseModel_Isotropic"); + +BOOST_CLASS_EXPORT_GUID(gtsam::SharedNoiseModel, "gtsam_SharedNoiseModel"); +BOOST_CLASS_EXPORT_GUID(gtsam::SharedDiagonal, "gtsam_SharedDiagonal"); + +/* Create GUIDs for geometry */ +/* ************************************************************************* */ +BOOST_CLASS_EXPORT(gtsam::LieVector); +BOOST_CLASS_EXPORT(gtsam::LieMatrix); +BOOST_CLASS_EXPORT(gtsam::Point2); +BOOST_CLASS_EXPORT(gtsam::StereoPoint2); +BOOST_CLASS_EXPORT(gtsam::Point3); +BOOST_CLASS_EXPORT(gtsam::Rot2); +BOOST_CLASS_EXPORT(gtsam::Rot3); +BOOST_CLASS_EXPORT(gtsam::Pose2); +BOOST_CLASS_EXPORT(gtsam::Pose3); +BOOST_CLASS_EXPORT(gtsam::Cal3_S2); +BOOST_CLASS_EXPORT(gtsam::Cal3DS2); +BOOST_CLASS_EXPORT(gtsam::Cal3_S2Stereo); +BOOST_CLASS_EXPORT(gtsam::CalibratedCamera); +BOOST_CLASS_EXPORT(gtsam::SimpleCamera); +BOOST_CLASS_EXPORT(gtsam::StereoCamera); + + +/* Create GUIDs for factors */ +/* ************************************************************************* */ +BOOST_CLASS_EXPORT_GUID(gtsam::JacobianFactor, "gtsam::JacobianFactor"); +BOOST_CLASS_EXPORT_GUID(gtsam::HessianFactor , "gtsam::HessianFactor"); + +BOOST_CLASS_EXPORT_GUID(PriorFactorLieVector, "gtsam::PriorFactorLieVector"); +BOOST_CLASS_EXPORT_GUID(PriorFactorLieMatrix, "gtsam::PriorFactorLieMatrix"); +BOOST_CLASS_EXPORT_GUID(PriorFactorPoint2, "gtsam::PriorFactorPoint2"); +BOOST_CLASS_EXPORT_GUID(PriorFactorStereoPoint2, "gtsam::PriorFactorStereoPoint2"); +BOOST_CLASS_EXPORT_GUID(PriorFactorPoint3, "gtsam::PriorFactorPoint3"); +BOOST_CLASS_EXPORT_GUID(PriorFactorRot2, "gtsam::PriorFactorRot2"); +BOOST_CLASS_EXPORT_GUID(PriorFactorRot3, "gtsam::PriorFactorRot3"); +BOOST_CLASS_EXPORT_GUID(PriorFactorPose2, "gtsam::PriorFactorPose2"); +BOOST_CLASS_EXPORT_GUID(PriorFactorPose3, "gtsam::PriorFactorPose3"); +BOOST_CLASS_EXPORT_GUID(PriorFactorCal3_S2, "gtsam::PriorFactorCal3_S2"); +BOOST_CLASS_EXPORT_GUID(PriorFactorCal3DS2, "gtsam::PriorFactorCal3DS2"); +BOOST_CLASS_EXPORT_GUID(PriorFactorCalibratedCamera, "gtsam::PriorFactorCalibratedCamera"); +BOOST_CLASS_EXPORT_GUID(PriorFactorSimpleCamera, "gtsam::PriorFactorSimpleCamera"); +BOOST_CLASS_EXPORT_GUID(PriorFactorStereoCamera, "gtsam::PriorFactorStereoCamera"); + +BOOST_CLASS_EXPORT_GUID(BetweenFactorLieVector, "gtsam::BetweenFactorLieVector"); +BOOST_CLASS_EXPORT_GUID(BetweenFactorLieMatrix, "gtsam::BetweenFactorLieMatrix"); +BOOST_CLASS_EXPORT_GUID(BetweenFactorPoint2, "gtsam::BetweenFactorPoint2"); +BOOST_CLASS_EXPORT_GUID(BetweenFactorPoint3, "gtsam::BetweenFactorPoint3"); +BOOST_CLASS_EXPORT_GUID(BetweenFactorRot2, "gtsam::BetweenFactorRot2"); +BOOST_CLASS_EXPORT_GUID(BetweenFactorRot3, "gtsam::BetweenFactorRot3"); +BOOST_CLASS_EXPORT_GUID(BetweenFactorPose2, "gtsam::BetweenFactorPose2"); +BOOST_CLASS_EXPORT_GUID(BetweenFactorPose3, "gtsam::BetweenFactorPose3"); + +BOOST_CLASS_EXPORT_GUID(NonlinearEqualityLieVector, "gtsam::NonlinearEqualityLieVector"); +BOOST_CLASS_EXPORT_GUID(NonlinearEqualityLieMatrix, "gtsam::NonlinearEqualityLieMatrix"); +BOOST_CLASS_EXPORT_GUID(NonlinearEqualityPoint2, "gtsam::NonlinearEqualityPoint2"); +BOOST_CLASS_EXPORT_GUID(NonlinearEqualityStereoPoint2, "gtsam::NonlinearEqualityStereoPoint2"); +BOOST_CLASS_EXPORT_GUID(NonlinearEqualityPoint3, "gtsam::NonlinearEqualityPoint3"); +BOOST_CLASS_EXPORT_GUID(NonlinearEqualityRot2, "gtsam::NonlinearEqualityRot2"); +BOOST_CLASS_EXPORT_GUID(NonlinearEqualityRot3, "gtsam::NonlinearEqualityRot3"); +BOOST_CLASS_EXPORT_GUID(NonlinearEqualityPose2, "gtsam::NonlinearEqualityPose2"); +BOOST_CLASS_EXPORT_GUID(NonlinearEqualityPose3, "gtsam::NonlinearEqualityPose3"); +BOOST_CLASS_EXPORT_GUID(NonlinearEqualityCal3_S2, "gtsam::NonlinearEqualityCal3_S2"); +BOOST_CLASS_EXPORT_GUID(NonlinearEqualityCal3DS2, "gtsam::NonlinearEqualityCal3DS2"); +BOOST_CLASS_EXPORT_GUID(NonlinearEqualityCalibratedCamera, "gtsam::NonlinearEqualityCalibratedCamera"); +BOOST_CLASS_EXPORT_GUID(NonlinearEqualitySimpleCamera, "gtsam::NonlinearEqualitySimpleCamera"); +BOOST_CLASS_EXPORT_GUID(NonlinearEqualityStereoCamera, "gtsam::NonlinearEqualityStereoCamera"); + +BOOST_CLASS_EXPORT_GUID(RangeFactorPosePoint2, "gtsam::RangeFactorPosePoint2"); +BOOST_CLASS_EXPORT_GUID(RangeFactorPosePoint3, "gtsam::RangeFactorPosePoint3"); +BOOST_CLASS_EXPORT_GUID(RangeFactorPose2, "gtsam::RangeFactorPose2"); +BOOST_CLASS_EXPORT_GUID(RangeFactorPose3, "gtsam::RangeFactorPose3"); +BOOST_CLASS_EXPORT_GUID(RangeFactorCalibratedCameraPoint, "gtsam::RangeFactorCalibratedCameraPoint"); +BOOST_CLASS_EXPORT_GUID(RangeFactorSimpleCameraPoint, "gtsam::RangeFactorSimpleCameraPoint"); +BOOST_CLASS_EXPORT_GUID(RangeFactorCalibratedCamera, "gtsam::RangeFactorCalibratedCamera"); +BOOST_CLASS_EXPORT_GUID(RangeFactorSimpleCamera, "gtsam::RangeFactorSimpleCamera"); + +BOOST_CLASS_EXPORT_GUID(BearingFactor2D, "gtsam::BearingFactor2D"); + +BOOST_CLASS_EXPORT_GUID(BearingRangeFactor2D, "gtsam::BearingRangeFactor2D"); + +BOOST_CLASS_EXPORT_GUID(GenericProjectionFactorCal3_S2, "gtsam::GenericProjectionFactorCal3_S2"); +BOOST_CLASS_EXPORT_GUID(GenericProjectionFactorCal3DS2, "gtsam::GenericProjectionFactorCal3DS2"); + +BOOST_CLASS_EXPORT_GUID(GeneralSFMFactorCal3_S2, "gtsam::GeneralSFMFactorCal3_S2"); +//BOOST_CLASS_EXPORT_GUID(GeneralSFMFactorCal3DS2, "gtsam::GeneralSFMFactorCal3DS2"); + +BOOST_CLASS_EXPORT_GUID(GeneralSFMFactor2Cal3_S2, "gtsam::GeneralSFMFactor2Cal3_S2"); + +BOOST_CLASS_EXPORT_GUID(GenericStereoFactor3D, "gtsam::GenericStereoFactor3D"); + + +/* ************************************************************************* */ +TEST (Serialization, smallExample_linear) { + using namespace example; + + Ordering ordering; ordering += X(1),X(2),L(1); + GaussianFactorGraph fg = createGaussianFactorGraph(ordering); + EXPECT(equalsObj(ordering)); + EXPECT(equalsXML(ordering)); + + EXPECT(equalsObj(fg)); + EXPECT(equalsXML(fg)); + + GaussianBayesNet cbn = createSmallGaussianBayesNet(); + EXPECT(equalsObj(cbn)); + EXPECT(equalsXML(cbn)); +} + +/* ************************************************************************* */ +TEST (Serialization, gaussianISAM) { + using namespace example; + Ordering ordering; + GaussianFactorGraph smoother; + boost::tie(smoother, ordering) = createSmoother(7); + BayesTree bayesTree = *GaussianMultifrontalSolver(smoother).eliminate(); + GaussianISAM isam(bayesTree); + + EXPECT(equalsObj(isam)); + EXPECT(equalsXML(isam)); +} + +/* ************************************************************************* */ +/* Create GUIDs for factors in simulated2D */ +BOOST_CLASS_EXPORT_GUID(simulated2D::Prior, "gtsam::simulated2D::Prior" ) +BOOST_CLASS_EXPORT_GUID(simulated2D::Odometry, "gtsam::simulated2D::Odometry" ) +BOOST_CLASS_EXPORT_GUID(simulated2D::Measurement, "gtsam::simulated2D::Measurement") + +/* ************************************************************************* */ +TEST (Serialization, smallExample_nonlinear) { + using namespace example; + NonlinearFactorGraph nfg = createNonlinearFactorGraph(); + Values c1 = createValues(); + EXPECT(equalsObj(nfg)); + EXPECT(equalsXML(nfg)); + + EXPECT(equalsObj(c1)); + EXPECT(equalsXML(c1)); +} + +/* ************************************************************************* */ +TEST (Serialization, factors) { + + LieVector lieVector(4, 1.0, 2.0, 3.0, 4.0); + LieMatrix lieMatrix(2, 3, 1.0, 2.0, 3.0, 4.0, 5.0 ,6.0); + Point2 point2(1.0, 2.0); + StereoPoint2 stereoPoint2(1.0, 2.0, 3.0); + Point3 point3(1.0, 2.0, 3.0); + Rot2 rot2(1.0); + Rot3 rot3(Rot3::RzRyRx(1.0, 2.0, 3.0)); + Pose2 pose2(rot2, point2); + Pose3 pose3(rot3, point3); + Cal3_S2 cal3_s2(1.0, 2.0, 3.0, 4.0, 5.0); + Cal3DS2 cal3ds2(1.0, 2.0, 3.0, 4.0, 5.0,6.0, 7.0, 8.0, 9.0); + Cal3_S2Stereo cal3_s2stereo(1.0, 2.0, 3.0, 4.0, 5.0, 1.0); + CalibratedCamera calibratedCamera(pose3); + SimpleCamera simpleCamera(pose3, cal3_s2); + StereoCamera stereoCamera(pose3, boost::make_shared(cal3_s2stereo)); + + + Symbol a01('a',1), a02('a',2), a03('a',3), a04('a',4), a05('a',5), + a06('a',6), a07('a',7), a08('a',8), a09('a',9), a10('a',10), + a11('a',11), a12('a',12), a13('a',13), a14('a',14), a15('a',15); + Symbol b01('b',1), b02('b',2), b03('b',3), b04('b',4), b05('b',5), + b06('b',6), b07('b',7), b08('b',8), b09('b',9), b10('b',10), + b11('b',11), b12('b',12), b13('b',13), b14('b',14), b15('b',15); + + Values values; + values.insert(a01, lieVector); + values.insert(a02, lieMatrix); + values.insert(a03, point2); + values.insert(a04, stereoPoint2); + values.insert(a05, point3); + values.insert(a06, rot2); + values.insert(a07, rot3); + values.insert(a08, pose2); + values.insert(a09, pose3); + values.insert(a10, cal3_s2); + values.insert(a11, cal3ds2); + values.insert(a12, calibratedCamera); + values.insert(a13, simpleCamera); + values.insert(a14, stereoCamera); + + + SharedNoiseModel model1 = noiseModel::Isotropic::Sigma(1, 0.3); + SharedNoiseModel model2 = noiseModel::Isotropic::Sigma(2, 0.3); + SharedNoiseModel model3 = noiseModel::Isotropic::Sigma(3, 0.3); + SharedNoiseModel model4 = noiseModel::Isotropic::Sigma(4, 0.3); + SharedNoiseModel model5 = noiseModel::Isotropic::Sigma(5, 0.3); + SharedNoiseModel model6 = noiseModel::Isotropic::Sigma(6, 0.3); + SharedNoiseModel model9 = noiseModel::Isotropic::Sigma(9, 0.3); + SharedNoiseModel model11 = noiseModel::Isotropic::Sigma(11, 0.3); + + + + PriorFactorLieVector priorFactorLieVector(a01, lieVector, model4); + PriorFactorLieMatrix priorFactorLieMatrix(a02, lieMatrix, model6); + PriorFactorPoint2 priorFactorPoint2(a03, point2, model2); + PriorFactorStereoPoint2 priorFactorStereoPoint2(a04, stereoPoint2, model3); + PriorFactorPoint3 priorFactorPoint3(a05, point3, model3); + PriorFactorRot2 priorFactorRot2(a06, rot2, model1); + PriorFactorRot3 priorFactorRot3(a07, rot3, model3); + PriorFactorPose2 priorFactorPose2(a08, pose2, model3); + PriorFactorPose3 priorFactorPose3(a09, pose3, model6); + PriorFactorCal3_S2 priorFactorCal3_S2(a10, cal3_s2, model5); + PriorFactorCal3DS2 priorFactorCal3DS2(a11, cal3ds2, model9); + PriorFactorCalibratedCamera priorFactorCalibratedCamera(a12, calibratedCamera, model6); + PriorFactorSimpleCamera priorFactorSimpleCamera(a13, simpleCamera, model11); + PriorFactorStereoCamera priorFactorStereoCamera(a14, stereoCamera, model11); + + BetweenFactorLieVector betweenFactorLieVector(a01, b01, lieVector, model4); + BetweenFactorLieMatrix betweenFactorLieMatrix(a02, b02, lieMatrix, model6); + BetweenFactorPoint2 betweenFactorPoint2(a03, b03, point2, model2); + BetweenFactorPoint3 betweenFactorPoint3(a05, b05, point3, model3); + BetweenFactorRot2 betweenFactorRot2(a06, b06, rot2, model1); + BetweenFactorRot3 betweenFactorRot3(a07, b07, rot3, model3); + BetweenFactorPose2 betweenFactorPose2(a08, b08, pose2, model3); + BetweenFactorPose3 betweenFactorPose3(a09, b09, pose3, model6); + + NonlinearEqualityLieVector nonlinearEqualityLieVector(a01, lieVector); + NonlinearEqualityLieMatrix nonlinearEqualityLieMatrix(a02, lieMatrix); + NonlinearEqualityPoint2 nonlinearEqualityPoint2(a03, point2); + NonlinearEqualityStereoPoint2 nonlinearEqualityStereoPoint2(a04, stereoPoint2); + NonlinearEqualityPoint3 nonlinearEqualityPoint3(a05, point3); + NonlinearEqualityRot2 nonlinearEqualityRot2(a06, rot2); + NonlinearEqualityRot3 nonlinearEqualityRot3(a07, rot3); + NonlinearEqualityPose2 nonlinearEqualityPose2(a08, pose2); + NonlinearEqualityPose3 nonlinearEqualityPose3(a09, pose3); + NonlinearEqualityCal3_S2 nonlinearEqualityCal3_S2(a10, cal3_s2); + NonlinearEqualityCal3DS2 nonlinearEqualityCal3DS2(a11, cal3ds2); + NonlinearEqualityCalibratedCamera nonlinearEqualityCalibratedCamera(a12, calibratedCamera); + NonlinearEqualitySimpleCamera nonlinearEqualitySimpleCamera(a13, simpleCamera); + NonlinearEqualityStereoCamera nonlinearEqualityStereoCamera(a14, stereoCamera); + + RangeFactorPosePoint2 rangeFactorPosePoint2(a08, a03, 2.0, model1); + RangeFactorPosePoint3 rangeFactorPosePoint3(a09, a05, 2.0, model1); + RangeFactorPose2 rangeFactorPose2(a08, b08, 2.0, model1); + RangeFactorPose3 rangeFactorPose3(a09, b09, 2.0, model1); + RangeFactorCalibratedCameraPoint rangeFactorCalibratedCameraPoint(a12, a05, 2.0, model1); + RangeFactorSimpleCameraPoint rangeFactorSimpleCameraPoint(a13, a05, 2.0, model1); + RangeFactorCalibratedCamera rangeFactorCalibratedCamera(a12, b12, 2.0, model1); + RangeFactorSimpleCamera rangeFactorSimpleCamera(a13, b13, 2.0, model1); + + BearingFactor2D bearingFactor2D(a08, a03, rot2, model1); + + BearingRangeFactor2D bearingRangeFactor2D(a08, a03, rot2, 2.0, model2); + + GenericProjectionFactorCal3_S2 genericProjectionFactorCal3_S2(point2, model2, a09, a05, boost::make_shared(cal3_s2)); + GenericProjectionFactorCal3DS2 genericProjectionFactorCal3DS2(point2, model2, a09, a05, boost::make_shared(cal3ds2)); + + GeneralSFMFactorCal3_S2 generalSFMFactorCal3_S2(point2, model2, a13, a05); + + GeneralSFMFactor2Cal3_S2 generalSFMFactor2Cal3_S2(point2, model2, a09, a05, a10); + + GenericStereoFactor3D genericStereoFactor3D(stereoPoint2, model3, a09, a05, boost::make_shared(cal3_s2stereo)); + + + NonlinearFactorGraph graph; + graph.add(priorFactorLieVector); + graph.add(priorFactorLieMatrix); + graph.add(priorFactorPoint2); + graph.add(priorFactorStereoPoint2); + graph.add(priorFactorPoint3); + graph.add(priorFactorRot2); + graph.add(priorFactorRot3); + graph.add(priorFactorPose2); + graph.add(priorFactorPose3); + graph.add(priorFactorCal3_S2); + graph.add(priorFactorCal3DS2); + graph.add(priorFactorCalibratedCamera); + graph.add(priorFactorSimpleCamera); + graph.add(priorFactorStereoCamera); + + graph.add(betweenFactorLieVector); + graph.add(betweenFactorLieMatrix); + graph.add(betweenFactorPoint2); + graph.add(betweenFactorPoint3); + graph.add(betweenFactorRot2); + graph.add(betweenFactorRot3); + graph.add(betweenFactorPose2); + graph.add(betweenFactorPose3); + + graph.add(nonlinearEqualityLieVector); + graph.add(nonlinearEqualityLieMatrix); + graph.add(nonlinearEqualityPoint2); + graph.add(nonlinearEqualityStereoPoint2); + graph.add(nonlinearEqualityPoint3); + graph.add(nonlinearEqualityRot2); + graph.add(nonlinearEqualityRot3); + graph.add(nonlinearEqualityPose2); + graph.add(nonlinearEqualityPose3); + graph.add(nonlinearEqualityCal3_S2); + graph.add(nonlinearEqualityCal3DS2); + graph.add(nonlinearEqualityCalibratedCamera); + graph.add(nonlinearEqualitySimpleCamera); + graph.add(nonlinearEqualityStereoCamera); + + graph.add(rangeFactorPosePoint2); + graph.add(rangeFactorPosePoint3); + graph.add(rangeFactorPose2); + graph.add(rangeFactorPose3); + graph.add(rangeFactorCalibratedCameraPoint); + graph.add(rangeFactorSimpleCameraPoint); + graph.add(rangeFactorCalibratedCamera); + graph.add(rangeFactorSimpleCamera); + + graph.add(bearingFactor2D); + + graph.add(bearingRangeFactor2D); + + graph.add(genericProjectionFactorCal3_S2); + graph.add(genericProjectionFactorCal3DS2); + + graph.add(generalSFMFactorCal3_S2); + + graph.add(generalSFMFactor2Cal3_S2); + + graph.add(genericStereoFactor3D); + + + // text + EXPECT(equalsObj(a01)); + EXPECT(equalsObj(b02)); + EXPECT(equalsObj(values)); + EXPECT(equalsObj(graph)); + + EXPECT(equalsObj(priorFactorLieVector)); + EXPECT(equalsObj(priorFactorLieMatrix)); + EXPECT(equalsObj(priorFactorPoint2)); + EXPECT(equalsObj(priorFactorStereoPoint2)); + EXPECT(equalsObj(priorFactorPoint3)); + EXPECT(equalsObj(priorFactorRot2)); + EXPECT(equalsObj(priorFactorRot3)); + EXPECT(equalsObj(priorFactorPose2)); + EXPECT(equalsObj(priorFactorPose3)); + EXPECT(equalsObj(priorFactorCal3_S2)); + EXPECT(equalsObj(priorFactorCal3DS2)); + EXPECT(equalsObj(priorFactorCalibratedCamera)); + EXPECT(equalsObj(priorFactorSimpleCamera)); + EXPECT(equalsObj(priorFactorStereoCamera)); + + EXPECT(equalsObj(betweenFactorLieVector)); + EXPECT(equalsObj(betweenFactorLieMatrix)); + EXPECT(equalsObj(betweenFactorPoint2)); + EXPECT(equalsObj(betweenFactorPoint3)); + EXPECT(equalsObj(betweenFactorRot2)); + EXPECT(equalsObj(betweenFactorRot3)); + EXPECT(equalsObj(betweenFactorPose2)); + EXPECT(equalsObj(betweenFactorPose3)); + + EXPECT(equalsObj(nonlinearEqualityLieVector)); + EXPECT(equalsObj(nonlinearEqualityLieMatrix)); + EXPECT(equalsObj(nonlinearEqualityPoint2)); + EXPECT(equalsObj(nonlinearEqualityStereoPoint2)); + EXPECT(equalsObj(nonlinearEqualityPoint3)); + EXPECT(equalsObj(nonlinearEqualityRot2)); + EXPECT(equalsObj(nonlinearEqualityRot3)); + EXPECT(equalsObj(nonlinearEqualityPose2)); + EXPECT(equalsObj(nonlinearEqualityPose3)); + EXPECT(equalsObj(nonlinearEqualityCal3_S2)); + EXPECT(equalsObj(nonlinearEqualityCal3DS2)); + EXPECT(equalsObj(nonlinearEqualityCalibratedCamera)); + EXPECT(equalsObj(nonlinearEqualitySimpleCamera)); + EXPECT(equalsObj(nonlinearEqualityStereoCamera)); + + EXPECT(equalsObj(rangeFactorPosePoint2)); + EXPECT(equalsObj(rangeFactorPosePoint3)); + EXPECT(equalsObj(rangeFactorPose2)); + EXPECT(equalsObj(rangeFactorPose3)); + EXPECT(equalsObj(rangeFactorCalibratedCameraPoint)); + EXPECT(equalsObj(rangeFactorSimpleCameraPoint)); + EXPECT(equalsObj(rangeFactorCalibratedCamera)); + EXPECT(equalsObj(rangeFactorSimpleCamera)); + + EXPECT(equalsObj(bearingFactor2D)); + + EXPECT(equalsObj(bearingRangeFactor2D)); + + EXPECT(equalsObj(genericProjectionFactorCal3_S2)); + EXPECT(equalsObj(genericProjectionFactorCal3DS2)); + + EXPECT(equalsObj(generalSFMFactorCal3_S2)); + + EXPECT(equalsObj(generalSFMFactor2Cal3_S2)); + + EXPECT(equalsObj(genericStereoFactor3D)); + + + // xml + EXPECT(equalsXML(a01)); + EXPECT(equalsXML(b02)); + EXPECT(equalsXML(values)); + EXPECT(equalsXML(graph)); + + EXPECT(equalsXML(priorFactorLieVector)); + EXPECT(equalsXML(priorFactorLieMatrix)); + EXPECT(equalsXML(priorFactorPoint2)); + EXPECT(equalsXML(priorFactorStereoPoint2)); + EXPECT(equalsXML(priorFactorPoint3)); + EXPECT(equalsXML(priorFactorRot2)); + EXPECT(equalsXML(priorFactorRot3)); + EXPECT(equalsXML(priorFactorPose2)); + EXPECT(equalsXML(priorFactorPose3)); + EXPECT(equalsXML(priorFactorCal3_S2)); + EXPECT(equalsXML(priorFactorCal3DS2)); + EXPECT(equalsXML(priorFactorCalibratedCamera)); + EXPECT(equalsXML(priorFactorSimpleCamera)); + EXPECT(equalsXML(priorFactorStereoCamera)); + + EXPECT(equalsXML(betweenFactorLieVector)); + EXPECT(equalsXML(betweenFactorLieMatrix)); + EXPECT(equalsXML(betweenFactorPoint2)); + EXPECT(equalsXML(betweenFactorPoint3)); + EXPECT(equalsXML(betweenFactorRot2)); + EXPECT(equalsXML(betweenFactorRot3)); + EXPECT(equalsXML(betweenFactorPose2)); + EXPECT(equalsXML(betweenFactorPose3)); + + EXPECT(equalsXML(nonlinearEqualityLieVector)); + EXPECT(equalsXML(nonlinearEqualityLieMatrix)); + EXPECT(equalsXML(nonlinearEqualityPoint2)); + EXPECT(equalsXML(nonlinearEqualityStereoPoint2)); + EXPECT(equalsXML(nonlinearEqualityPoint3)); + EXPECT(equalsXML(nonlinearEqualityRot2)); + EXPECT(equalsXML(nonlinearEqualityRot3)); + EXPECT(equalsXML(nonlinearEqualityPose2)); + EXPECT(equalsXML(nonlinearEqualityPose3)); + EXPECT(equalsXML(nonlinearEqualityCal3_S2)); + EXPECT(equalsXML(nonlinearEqualityCal3DS2)); + EXPECT(equalsXML(nonlinearEqualityCalibratedCamera)); + EXPECT(equalsXML(nonlinearEqualitySimpleCamera)); + EXPECT(equalsXML(nonlinearEqualityStereoCamera)); + + EXPECT(equalsXML(rangeFactorPosePoint2)); + EXPECT(equalsXML(rangeFactorPosePoint3)); + EXPECT(equalsXML(rangeFactorPose2)); + EXPECT(equalsXML(rangeFactorPose3)); + EXPECT(equalsXML(rangeFactorCalibratedCameraPoint)); + EXPECT(equalsXML(rangeFactorSimpleCameraPoint)); + EXPECT(equalsXML(rangeFactorCalibratedCamera)); + EXPECT(equalsXML(rangeFactorSimpleCamera)); + + EXPECT(equalsXML(bearingFactor2D)); + + EXPECT(equalsXML(bearingRangeFactor2D)); + + EXPECT(equalsXML(genericProjectionFactorCal3_S2)); + EXPECT(equalsXML(genericProjectionFactorCal3DS2)); + + EXPECT(equalsXML(generalSFMFactorCal3_S2)); + + EXPECT(equalsXML(generalSFMFactor2Cal3_S2)); + + EXPECT(equalsXML(genericStereoFactor3D)); +} + + +/* ************************************************************************* */ +int main() { TestResult tr; return TestRegistry::runAllTests(tr); } +/* ************************************************************************* */ diff --git a/gtsam/slam/tests/testSimulated2D.cpp b/tests/testSimulated2D.cpp similarity index 92% rename from gtsam/slam/tests/testSimulated2D.cpp rename to tests/testSimulated2D.cpp index 3513927a7..165177a56 100644 --- a/gtsam/slam/tests/testSimulated2D.cpp +++ b/tests/testSimulated2D.cpp @@ -21,7 +21,7 @@ #include #include -#include +#include using namespace std; using namespace gtsam; @@ -31,8 +31,8 @@ using namespace simulated2D; TEST( simulated2D, Simulated2DValues ) { simulated2D::Values actual; - actual.insert(simulated2D::PoseKey(1),Point2(1,1)); - actual.insert(simulated2D::PointKey(2),Point2(2,2)); + actual.insert(1,Point2(1,1)); + actual.insert(2,Point2(2,2)); EXPECT(assert_equal(actual,actual,1e-9)); } diff --git a/gtsam/slam/tests/testSimulated2DOriented.cpp b/tests/testSimulated2DOriented.cpp similarity index 82% rename from gtsam/slam/tests/testSimulated2DOriented.cpp rename to tests/testSimulated2DOriented.cpp index 64844cb2a..bce932235 100644 --- a/gtsam/slam/tests/testSimulated2DOriented.cpp +++ b/tests/testSimulated2DOriented.cpp @@ -16,17 +16,21 @@ * @brief unit tests for simulated2DOriented */ -#include -#include - +#include +#include +#include #include #include -#include -#include using namespace std; using namespace gtsam; -using namespace simulated2DOriented; + +#include +#include + +// Convenience for named keys +using symbol_shorthand::X; +using symbol_shorthand::L; /* ************************************************************************* */ TEST( simulated2DOriented, Dprior ) @@ -54,12 +58,12 @@ TEST( simulated2DOriented, Dprior ) TEST( simulated2DOriented, constructor ) { Pose2 measurement(0.2, 0.3, 0.1); - SharedDiagonal model(Vector_(3, 1., 1., 1.)); - simulated2DOriented::Odometry factor(measurement, model, simulated2DOriented::PoseKey(1), simulated2DOriented::PoseKey(2)); + SharedDiagonal model = noiseModel::Diagonal::Sigmas(Vector_(3, 1., 1., 1.)); + simulated2DOriented::Odometry factor(measurement, model, X(1), X(2)); simulated2DOriented::Values config; - config.insert(simulated2DOriented::PoseKey(1), Pose2(1., 0., 0.2)); - config.insert(simulated2DOriented::PoseKey(2), Pose2(2., 0., 0.1)); + config.insert(X(1), Pose2(1., 0., 0.2)); + config.insert(X(2), Pose2(2., 0., 0.1)); boost::shared_ptr lf = factor.linearize(config, *config.orderingArbitrary()); } diff --git a/gtsam_unstable/slam/tests/testSimulated3D.cpp b/tests/testSimulated3D.cpp similarity index 89% rename from gtsam_unstable/slam/tests/testSimulated3D.cpp rename to tests/testSimulated3D.cpp index 50171bc76..be9548a8e 100644 --- a/gtsam_unstable/slam/tests/testSimulated3D.cpp +++ b/tests/testSimulated3D.cpp @@ -15,23 +15,28 @@ * @author Alex Cunningham **/ -#include -#include - +#include +#include +#include #include #include -#include -#include + +#include + +#include using namespace gtsam; -using namespace simulated3D; + +// Convenience for named keys +using symbol_shorthand::X; +using symbol_shorthand::L; /* ************************************************************************* */ TEST( simulated3D, Values ) { Values actual; - actual.insert(simulated3D::PointKey(1),Point3(1,1,1)); - actual.insert(simulated3D::PoseKey(2),Point3(2,2,2)); + actual.insert(L(1),Point3(1,1,1)); + actual.insert(X(2),Point3(2,2,2)); EXPECT(assert_equal(actual,actual,1e-9)); } diff --git a/tests/testSubgraphPreconditioner.cpp b/tests/testSubgraphPreconditioner.cpp new file mode 100644 index 000000000..39c5e2b70 --- /dev/null +++ b/tests/testSubgraphPreconditioner.cpp @@ -0,0 +1,222 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file testSubgraphConditioner.cpp + * @brief Unit tests for SubgraphPreconditioner + * @author Frank Dellaert + **/ + +#include +#include +#include +#include +#include +#include +#include +#include + +#include + +#include +#include +#include +using namespace boost::assign; + +using namespace std; +using namespace gtsam; +using namespace example; + +// define keys +// Create key for simulated planar graph +Symbol key(int x, int y) { + return symbol_shorthand::X(1000*x+y); +} + +/* ************************************************************************* */ +TEST( SubgraphPreconditioner, planarOrdering ) { + // Check canonical ordering + Ordering expected, ordering = planarOrdering(3); + expected += + key(3, 3), key(2, 3), key(1, 3), + key(3, 2), key(2, 2), key(1, 2), + key(3, 1), key(2, 1), key(1, 1); + CHECK(assert_equal(expected,ordering)); +} + +/* ************************************************************************* */ +/** unnormalized error */ +static double error(const GaussianFactorGraph& fg, const VectorValues& x) { + double total_error = 0.; + BOOST_FOREACH(const GaussianFactor::shared_ptr& factor, fg) + total_error += factor->error(x); + return total_error; +} + +/* ************************************************************************* */ +TEST( SubgraphPreconditioner, planarGraph ) + { + // Check planar graph construction + GaussianFactorGraph A; + VectorValues xtrue; + boost::tie(A, xtrue) = planarGraph(3); + LONGS_EQUAL(13,A.size()); + LONGS_EQUAL(9,xtrue.size()); + DOUBLES_EQUAL(0,error(A,xtrue),1e-9); // check zero error for xtrue + + // Check that xtrue is optimal + GaussianBayesNet::shared_ptr R1 = GaussianSequentialSolver(A).eliminate(); + VectorValues actual = optimize(*R1); + CHECK(assert_equal(xtrue,actual)); +} + +/* ************************************************************************* */ +TEST( SubgraphPreconditioner, splitOffPlanarTree ) +{ + // Build a planar graph + GaussianFactorGraph A; + VectorValues xtrue; + boost::tie(A, xtrue) = planarGraph(3); + + // Get the spanning tree and constraints, and check their sizes + GaussianFactorGraph T, C; + boost::tie(T, C) = splitOffPlanarTree(3, A); + LONGS_EQUAL(9,T.size()); + LONGS_EQUAL(4,C.size()); + + // Check that the tree can be solved to give the ground xtrue + GaussianBayesNet::shared_ptr R1 = GaussianSequentialSolver(T).eliminate(); + VectorValues xbar = optimize(*R1); + CHECK(assert_equal(xtrue,xbar)); +} + +/* ************************************************************************* */ + +TEST( SubgraphPreconditioner, system ) +{ + // Build a planar graph + GaussianFactorGraph Ab; + VectorValues xtrue; + size_t N = 3; + boost::tie(Ab, xtrue) = planarGraph(N); // A*x-b + + // Get the spanning tree and corresponding ordering + GaussianFactorGraph Ab1_, Ab2_; // A1*x-b1 and A2*x-b2 + boost::tie(Ab1_, Ab2_) = splitOffPlanarTree(N, Ab); + SubgraphPreconditioner::sharedFG Ab1(new GaussianFactorGraph(Ab1_)); + SubgraphPreconditioner::sharedFG Ab2(new GaussianFactorGraph(Ab2_)); + + // Eliminate the spanning tree to build a prior + SubgraphPreconditioner::sharedBayesNet Rc1 = GaussianSequentialSolver(Ab1_).eliminate(); // R1*x-c1 + VectorValues xbar = optimize(*Rc1); // xbar = inv(R1)*c1 + + // Create Subgraph-preconditioned system + VectorValues::shared_ptr xbarShared(new VectorValues(xbar)); // TODO: horrible + SubgraphPreconditioner system(Ab2, Rc1, xbarShared); + + // Create zero config + VectorValues zeros = VectorValues::Zero(xbar); + + // Set up y0 as all zeros + VectorValues y0 = zeros; + + // y1 = perturbed y0 + VectorValues y1 = zeros; + y1[1] = Vector_(2, 1.0, -1.0); + + // Check corresponding x values + VectorValues expected_x1 = xtrue, x1 = system.x(y1); + expected_x1[1] = Vector_(2, 2.01, 2.99); + expected_x1[0] = Vector_(2, 3.01, 2.99); + CHECK(assert_equal(xtrue, system.x(y0))); + CHECK(assert_equal(expected_x1,system.x(y1))); + + // Check errors + DOUBLES_EQUAL(0,error(Ab,xtrue),1e-9); + DOUBLES_EQUAL(3,error(Ab,x1),1e-9); + DOUBLES_EQUAL(0,error(system,y0),1e-9); + DOUBLES_EQUAL(3,error(system,y1),1e-9); + + // Test gradient in x + VectorValues expected_gx0 = zeros; + VectorValues expected_gx1 = zeros; + CHECK(assert_equal(expected_gx0,gradient(Ab,xtrue))); + expected_gx1[2] = Vector_(2, -100., 100.); + expected_gx1[4] = Vector_(2, -100., 100.); + expected_gx1[1] = Vector_(2, 200., -200.); + expected_gx1[3] = Vector_(2, -100., 100.); + expected_gx1[0] = Vector_(2, 100., -100.); + CHECK(assert_equal(expected_gx1,gradient(Ab,x1))); + + // Test gradient in y + VectorValues expected_gy0 = zeros; + VectorValues expected_gy1 = zeros; + expected_gy1[2] = Vector_(2, 2., -2.); + expected_gy1[4] = Vector_(2, -2., 2.); + expected_gy1[1] = Vector_(2, 3., -3.); + expected_gy1[3] = Vector_(2, -1., 1.); + expected_gy1[0] = Vector_(2, 1., -1.); + CHECK(assert_equal(expected_gy0,gradient(system,y0))); + CHECK(assert_equal(expected_gy1,gradient(system,y1))); + + // Check it numerically for good measure + // TODO use boost::bind(&SubgraphPreconditioner::error,&system,_1) + // Vector numerical_g1 = numericalGradient (error, y1, 0.001); + // Vector expected_g1 = Vector_(18, 0., 0., 0., 0., 2., -2., 0., 0., -2., 2., + // 3., -3., 0., 0., -1., 1., 1., -1.); + // CHECK(assert_equal(expected_g1,numerical_g1)); +} + +/* ************************************************************************* */ +TEST( SubgraphPreconditioner, conjugateGradients ) +{ + // Build a planar graph + GaussianFactorGraph Ab; + VectorValues xtrue; + size_t N = 3; + boost::tie(Ab, xtrue) = planarGraph(N); // A*x-b + + // Get the spanning tree and corresponding ordering + GaussianFactorGraph Ab1_, Ab2_; // A1*x-b1 and A2*x-b2 + boost::tie(Ab1_, Ab2_) = splitOffPlanarTree(N, Ab); + SubgraphPreconditioner::sharedFG Ab1(new GaussianFactorGraph(Ab1_)); + SubgraphPreconditioner::sharedFG Ab2(new GaussianFactorGraph(Ab2_)); + + // Eliminate the spanning tree to build a prior + Ordering ordering = planarOrdering(N); + SubgraphPreconditioner::sharedBayesNet Rc1 = GaussianSequentialSolver(Ab1_).eliminate(); // R1*x-c1 + VectorValues xbar = optimize(*Rc1); // xbar = inv(R1)*c1 + + // Create Subgraph-preconditioned system + VectorValues::shared_ptr xbarShared(new VectorValues(xbar)); // TODO: horrible + SubgraphPreconditioner system(Ab2, Rc1, xbarShared); + + // Create zero config y0 and perturbed config y1 + VectorValues y0 = VectorValues::Zero(xbar); + + VectorValues y1 = y0; + y1[1] = Vector_(2, 1.0, -1.0); + VectorValues x1 = system.x(y1); + + // Solve for the remaining constraints using PCG + ConjugateGradientParameters parameters; + VectorValues actual = conjugateGradients(system, y1, parameters); + CHECK(assert_equal(y0,actual)); + + // Compare with non preconditioned version: + VectorValues actual2 = conjugateGradientDescent(Ab, x1, parameters); + CHECK(assert_equal(xtrue,actual2,1e-4)); +} + +/* ************************************************************************* */ +int main() { TestResult tr; return TestRegistry::runAllTests(tr); } +/* ************************************************************************* */ diff --git a/tests/testSubgraphSolver.cpp b/tests/testSubgraphSolver.cpp new file mode 100644 index 000000000..700f35261 --- /dev/null +++ b/tests/testSubgraphSolver.cpp @@ -0,0 +1,114 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file testSubgraphSolver.cpp + * @brief Unit tests for SubgraphSolver + * @author Yong-Dian Jian + **/ + +#include +#include +#include +#include +#include +#include +#include +#include +#include + +#include + +#include +#include +#include +using namespace boost::assign; + +using namespace std; +using namespace gtsam; +using namespace example; + +/* ************************************************************************* */ +/** unnormalized error */ +static double error(const GaussianFactorGraph& fg, const VectorValues& x) { + double total_error = 0.; + BOOST_FOREACH(const GaussianFactor::shared_ptr& factor, fg) + total_error += factor->error(x); + return total_error; +} + + +/* ************************************************************************* */ +TEST( SubgraphSolver, constructor1 ) +{ + // Build a planar graph + GaussianFactorGraph Ab; + VectorValues xtrue; + size_t N = 3; + boost::tie(Ab, xtrue) = planarGraph(N); // A*x-b + + // The first constructor just takes a factor graph (and parameters) + // and it will split the graph into A1 and A2, where A1 is a spanning tree + SubgraphSolverParameters parameters; + SubgraphSolver solver(Ab, parameters); + VectorValues optimized = solver.optimize(); // does PCG optimization + DOUBLES_EQUAL(0.0, error(Ab, optimized), 1e-5); +} + +/* ************************************************************************* */ +TEST( SubgraphSolver, constructor2 ) +{ + // Build a planar graph + GaussianFactorGraph Ab; + VectorValues xtrue; + size_t N = 3; + boost::tie(Ab, xtrue) = planarGraph(N); // A*x-b + + // Get the spanning tree and corresponding ordering + GaussianFactorGraph Ab1_, Ab2_; // A1*x-b1 and A2*x-b2 + boost::tie(Ab1_, Ab2_) = splitOffPlanarTree(N, Ab); + + // The second constructor takes two factor graphs, + // so the caller can specify the preconditioner (Ab1) and the constraints that are left out (Ab2) + SubgraphSolverParameters parameters; + SubgraphSolver solver(Ab1_, Ab2_, parameters); + VectorValues optimized = solver.optimize(); + DOUBLES_EQUAL(0.0, error(Ab, optimized), 1e-5); +} + +/* ************************************************************************* */ +TEST( SubgraphSolver, constructor3 ) +{ + // Build a planar graph + GaussianFactorGraph Ab; + VectorValues xtrue; + size_t N = 3; + boost::tie(Ab, xtrue) = planarGraph(N); // A*x-b + + // Get the spanning tree and corresponding ordering + GaussianFactorGraph Ab1_, Ab2_; // A1*x-b1 and A2*x-b2 + boost::tie(Ab1_, Ab2_) = splitOffPlanarTree(N, Ab); + + // The caller solves |A1*x-b1|^2 == |R1*x-c1|^2 via QR factorization, where R1 is square UT + GaussianBayesNet::shared_ptr Rc1 = // + EliminationTree::Create(Ab1_)->eliminate(&EliminateQR); + + // The third constructor allows the caller to pass an already solved preconditioner Rc1_ + // as a Bayes net, in addition to the "loop closing constraints" Ab2, as before + SubgraphSolverParameters parameters; + SubgraphSolver solver(Rc1, Ab2_, parameters); + VectorValues optimized = solver.optimize(); + DOUBLES_EQUAL(0.0, error(Ab, optimized), 1e-5); +} + +/* ************************************************************************* */ +int main() { TestResult tr; return TestRegistry::runAllTests(tr); } +/* ************************************************************************* */ diff --git a/tests/testSymbolicBayesNetB.cpp b/tests/testSymbolicBayesNetB.cpp index e25cf33ca..58ba3060b 100644 --- a/tests/testSymbolicBayesNetB.cpp +++ b/tests/testSymbolicBayesNetB.cpp @@ -22,27 +22,28 @@ using namespace boost::assign; #include #include -#include +#include #include #include #include +#include using namespace std; using namespace gtsam; using namespace example; -Key kx(size_t i) { return Symbol('x',i); } -Key kl(size_t i) { return Symbol('l',i); } +using symbol_shorthand::X; +using symbol_shorthand::L; /* ************************************************************************* */ TEST( SymbolicBayesNet, constructor ) { - Ordering o; o += kx(2),kl(1),kx(1); + Ordering o; o += X(2),L(1),X(1); // Create manually IndexConditional::shared_ptr - x2(new IndexConditional(o[kx(2)],o[kl(1)], o[kx(1)])), - l1(new IndexConditional(o[kl(1)],o[kx(1)])), - x1(new IndexConditional(o[kx(1)])); + x2(new IndexConditional(o[X(2)],o[L(1)], o[X(1)])), + l1(new IndexConditional(o[L(1)],o[X(1)])), + x1(new IndexConditional(o[X(1)])); BayesNet expected; expected.push_back(x2); expected.push_back(l1); @@ -53,8 +54,7 @@ TEST( SymbolicBayesNet, constructor ) SymbolicFactorGraph fg(factorGraph); // eliminate it - SymbolicBayesNet actual = *SymbolicSequentialSolver(fg).eliminate( - &EliminateSymbolic); + SymbolicBayesNet actual = *SymbolicSequentialSolver(fg).eliminate(); CHECK(assert_equal(expected, actual)); } diff --git a/tests/testSymbolicFactorGraphB.cpp b/tests/testSymbolicFactorGraphB.cpp index 9b195e0c1..ddb53b13c 100644 --- a/tests/testSymbolicFactorGraphB.cpp +++ b/tests/testSymbolicFactorGraphB.cpp @@ -15,37 +15,37 @@ * @author Frank Dellaert */ -#include // for operator += -using namespace boost::assign; - -#include - -#include +#include +#include +#include #include #include #include -#include + +#include + +#include // for operator += +using namespace boost::assign; using namespace std; using namespace gtsam; -using namespace example; -Key kx(size_t i) { return Symbol('x',i); } -Key kl(size_t i) { return Symbol('l',i); } +using symbol_shorthand::X; +using symbol_shorthand::L; /* ************************************************************************* */ TEST( SymbolicFactorGraph, symbolicFactorGraph ) { - Ordering o; o += kx(1),kl(1),kx(2); + Ordering o; o += X(1),L(1),X(2); // construct expected symbolic graph SymbolicFactorGraph expected; - expected.push_factor(o[kx(1)]); - expected.push_factor(o[kx(1)],o[kx(2)]); - expected.push_factor(o[kx(1)],o[kl(1)]); - expected.push_factor(o[kx(2)],o[kl(1)]); + expected.push_factor(o[X(1)]); + expected.push_factor(o[X(1)],o[X(2)]); + expected.push_factor(o[X(1)],o[L(1)]); + expected.push_factor(o[X(2)],o[L(1)]); // construct it from the factor graph - GaussianFactorGraph factorGraph = createGaussianFactorGraph(o); + GaussianFactorGraph factorGraph = example::createGaussianFactorGraph(o); SymbolicFactorGraph actual(factorGraph); CHECK(assert_equal(expected, actual)); @@ -55,11 +55,11 @@ TEST( SymbolicFactorGraph, symbolicFactorGraph ) //TEST( SymbolicFactorGraph, findAndRemoveFactors ) //{ // // construct it from the factor graph graph -// GaussianFactorGraph factorGraph = createGaussianFactorGraph(); +// GaussianFactorGraph factorGraph = example::createGaussianFactorGraph(); // SymbolicFactorGraph actual(factorGraph); // SymbolicFactor::shared_ptr f1 = actual[0]; // SymbolicFactor::shared_ptr f3 = actual[2]; -// actual.findAndRemoveFactors(kx(2)); +// actual.findAndRemoveFactors(X(2)); // // // construct expected graph after find_factors_and_remove // SymbolicFactorGraph expected; @@ -75,17 +75,17 @@ TEST( SymbolicFactorGraph, symbolicFactorGraph ) //TEST( SymbolicFactorGraph, factors) //{ // // create a test graph -// GaussianFactorGraph factorGraph = createGaussianFactorGraph(); +// GaussianFactorGraph factorGraph = example::createGaussianFactorGraph(); // SymbolicFactorGraph fg(factorGraph); // // // ask for all factor indices connected to x1 -// list x1_factors = fg.factors(kx(1)); +// list x1_factors = fg.factors(X(1)); // int x1_indices[] = { 0, 1, 2 }; // list x1_expected(x1_indices, x1_indices + 3); // CHECK(x1_factors==x1_expected); // // // ask for all factor indices connected to x2 -// list x2_factors = fg.factors(kx(2)); +// list x2_factors = fg.factors(X(2)); // int x2_indices[] = { 1, 3 }; // list x2_expected(x2_indices, x2_indices + 2); // CHECK(x2_factors==x2_expected); @@ -95,30 +95,30 @@ TEST( SymbolicFactorGraph, symbolicFactorGraph ) //TEST( SymbolicFactorGraph, removeAndCombineFactors ) //{ // // create a test graph -// GaussianFactorGraph factorGraph = createGaussianFactorGraph(); +// GaussianFactorGraph factorGraph = example::createGaussianFactorGraph(); // SymbolicFactorGraph fg(factorGraph); // // // combine all factors connected to x1 -// SymbolicFactor::shared_ptr actual = removeAndCombineFactors(fg,kx(1)); +// SymbolicFactor::shared_ptr actual = removeAndCombineFactors(fg,X(1)); // // // check result -// SymbolicFactor expected(kl(1),kx(1),kx(2)); +// SymbolicFactor expected(L(1),X(1),X(2)); // CHECK(assert_equal(expected,*actual)); //} ///* ************************************************************************* */ //TEST( SymbolicFactorGraph, eliminateOne ) //{ -// Ordering o; o += kx(1),kl(1),kx(2); +// Ordering o; o += X(1),L(1),X(2); // // create a test graph -// GaussianFactorGraph factorGraph = createGaussianFactorGraph(o); +// GaussianFactorGraph factorGraph = example::createGaussianFactorGraph(o); // SymbolicFactorGraph fg(factorGraph); // // // eliminate -// IndexConditional::shared_ptr actual = GaussianSequentialSolver::EliminateUntil(fg, o[kx(1)]+1); +// IndexConditional::shared_ptr actual = GaussianSequentialSolver::EliminateUntil(fg, o[X(1)]+1); // // // create expected symbolic IndexConditional -// IndexConditional expected(o[kx(1)],o[kl(1)],o[kx(2)]); +// IndexConditional expected(o[X(1)],o[L(1)],o[X(2)]); // // CHECK(assert_equal(expected,*actual)); //} @@ -126,12 +126,12 @@ TEST( SymbolicFactorGraph, symbolicFactorGraph ) /* ************************************************************************* */ TEST( SymbolicFactorGraph, eliminate ) { - Ordering o; o += kx(2),kl(1),kx(1); + Ordering o; o += X(2),L(1),X(1); // create expected Chordal bayes Net - IndexConditional::shared_ptr x2(new IndexConditional(o[kx(2)], o[kl(1)], o[kx(1)])); - IndexConditional::shared_ptr l1(new IndexConditional(o[kl(1)], o[kx(1)])); - IndexConditional::shared_ptr x1(new IndexConditional(o[kx(1)])); + IndexConditional::shared_ptr x2(new IndexConditional(o[X(2)], o[L(1)], o[X(1)])); + IndexConditional::shared_ptr l1(new IndexConditional(o[L(1)], o[X(1)])); + IndexConditional::shared_ptr x1(new IndexConditional(o[X(1)])); SymbolicBayesNet expected; expected.push_back(x2); @@ -139,11 +139,11 @@ TEST( SymbolicFactorGraph, eliminate ) expected.push_back(x1); // create a test graph - GaussianFactorGraph factorGraph = createGaussianFactorGraph(o); + GaussianFactorGraph factorGraph = example::createGaussianFactorGraph(o); SymbolicFactorGraph fg(factorGraph); // eliminate it - SymbolicBayesNet actual = *SymbolicSequentialSolver(fg).eliminate(&EliminateSymbolic); + SymbolicBayesNet actual = *SymbolicSequentialSolver(fg).eliminate(); CHECK(assert_equal(expected,actual)); } diff --git a/tests/timeGaussianFactorGraph.cpp b/tests/timeGaussianFactorGraph.cpp index 3c9d83b3d..f8d76c1dd 100644 --- a/tests/timeGaussianFactorGraph.cpp +++ b/tests/timeGaussianFactorGraph.cpp @@ -19,7 +19,7 @@ #include #include // for operator += in Ordering #include -#include +#include #include using namespace std; @@ -43,10 +43,8 @@ double timeKalmanSmoother(int T) { // Create a planar factor graph and optimize // todo: use COLAMD ordering again (removed when linear baked-in ordering added) double timePlanarSmoother(int N, bool old = true) { - boost::tuple pg = planarGraph(N); + boost::tuple pg = planarGraph(N); GaussianFactorGraph& fg(pg.get<0>()); -// Ordering& ordering(pg.get<1>()); -// VectorValues& config(pg.get<2>()); clock_t start = clock(); GaussianSequentialSolver(fg).optimize(); clock_t end = clock (); @@ -58,10 +56,8 @@ double timePlanarSmoother(int N, bool old = true) { // Create a planar factor graph and eliminate // todo: use COLAMD ordering again (removed when linear baked-in ordering added) double timePlanarSmootherEliminate(int N, bool old = true) { - boost::tuple pg = planarGraph(N); + boost::tuple pg = planarGraph(N); GaussianFactorGraph& fg(pg.get<0>()); -// Ordering& ordering(pg.get<1>()); -// VectorValues& config(pg.get<2>()); clock_t start = clock(); GaussianSequentialSolver(fg).eliminate(); clock_t end = clock (); diff --git a/tests/timeMultifrontalOnDataset.cpp b/tests/timeMultifrontalOnDataset.cpp index 874ccf8bb..5bc34b386 100644 --- a/tests/timeMultifrontalOnDataset.cpp +++ b/tests/timeMultifrontalOnDataset.cpp @@ -44,11 +44,11 @@ int main(int argc, char *argv[]) { else if (argc == 4) nrTrials = strtoul(argv[3], NULL, 10); - pair, shared_ptr > data = load2D(dataset(datasetname)); + pair, boost::shared_ptr > data = load2D(dataset(datasetname)); // Add a prior on the first pose if (soft_prior) - data.first->addPrior(0, Pose2(), sharedSigma(Pose2::Dim(), 0.0005)); + data.first->addPosePrior(0, Pose2(), noiseModel::Isotropic::Sigma(Pose2::Dim(), 0.0005)); else data.first->addPoseConstraint(0, Pose2()); diff --git a/tests/timeSequentialOnDataset.cpp b/tests/timeSequentialOnDataset.cpp index 9e1b986f9..03f33d334 100644 --- a/tests/timeSequentialOnDataset.cpp +++ b/tests/timeSequentialOnDataset.cpp @@ -44,11 +44,11 @@ int main(int argc, char *argv[]) { else if (argc == 4) nrTrials = strtoul(argv[3], NULL, 10); - pair, shared_ptr > data = load2D(dataset(datasetname)); + pair, boost::shared_ptr > data = load2D(dataset(datasetname)); // Add a prior on the first pose if (soft_prior) - data.first->addPrior(0, Pose2(), sharedSigma(Pose2::Dim(), 0.0005)); + data.first->addPosePrior(0, Pose2(), noiseModel::Isotropic::Sigma(Pose2::Dim(), 0.0005)); else data.first->addPoseConstraint(0, Pose2()); diff --git a/wrap/Argument.cpp b/wrap/Argument.cpp index ff42b33b1..6956b310b 100644 --- a/wrap/Argument.cpp +++ b/wrap/Argument.cpp @@ -12,6 +12,8 @@ /** * @file Argument.ccp * @author Frank Dellaert + * @author Andrew Melim + * @author Richard Roberts **/ #include @@ -30,10 +32,14 @@ string Argument::matlabClass(const string& delim) const { string result; BOOST_FOREACH(const string& ns, namespaces) result += ns + delim; - if (type=="string") + if (type=="string" || type=="unsigned char" || type=="char") return result + "char"; - if (type=="bool" || type=="int" || type=="size_t" || type=="Vector" || type=="Matrix") - return result + "double"; + if (type=="Vector" || type=="Matrix") + return result + "double"; + if (type=="int" || type=="size_t") + return result + "numeric"; + if (type=="bool") + return result + "logical"; return result + type; } @@ -42,11 +48,11 @@ void Argument::matlab_unwrap(FileWriter& file, const string& matlabName) const { file.oss << " "; string cppType = qualifiedType("::"); - string matlabType = qualifiedType(); + string matlabUniqueType = qualifiedType(); if (is_ptr) // A pointer: emit an "unwrap_shared_ptr" call which returns a pointer - file.oss << "shared_ptr<" << cppType << "> " << name << " = unwrap_shared_ptr< "; + file.oss << "boost::shared_ptr<" << cppType << "> " << name << " = unwrap_shared_ptr< "; else if (is_ref) // A reference: emit an "unwrap_shared_ptr" call and de-reference the pointer file.oss << cppType << "& " << name << " = *unwrap_shared_ptr< "; @@ -59,7 +65,7 @@ void Argument::matlab_unwrap(FileWriter& file, const string& matlabName) const { file.oss << cppType << " " << name << " = unwrap< "; file.oss << cppType << " >(" << matlabName; - if (is_ptr || is_ref) file.oss << ", \"" << matlabType << "\""; + if (is_ptr || is_ref) file.oss << ", \"ptr_" << matlabUniqueType << "\""; file.oss << ");" << endl; } @@ -122,3 +128,4 @@ void ArgumentList::matlab_unwrap(FileWriter& file, int start) const { } /* ************************************************************************* */ + diff --git a/wrap/Argument.h b/wrap/Argument.h index 000e3079a..4dcf6b563 100644 --- a/wrap/Argument.h +++ b/wrap/Argument.h @@ -13,6 +13,8 @@ * @file Argument.h * @brief arguments to constructors and methods * @author Frank Dellaert + * @author Andrew Melim + * @author Richard Roberts **/ #pragma once @@ -65,6 +67,7 @@ struct ArgumentList: public std::vector { * @param start initial index for input array, set to 1 for method */ void matlab_unwrap(FileWriter& file, int start = 0) const; // MATLAB to C++ + }; } // \namespace wrap diff --git a/wrap/CMakeLists.txt b/wrap/CMakeLists.txt index 8feb5779b..14d9a1f84 100644 --- a/wrap/CMakeLists.txt +++ b/wrap/CMakeLists.txt @@ -1,15 +1,21 @@ # Build/install Wrap +set(WRAP_BOOST_LIBRARIES ${Boost_SYSTEM_LIBRARY} ${Boost_FILESYSTEM_LIBRARY} ${Boost_THREAD_LIBRARY}) + # Build the executable itself file(GLOB wrap_srcs "*.cpp") -list(REMOVE_ITEM wrap_srcs wrap.cpp) -add_library(wrap_lib STATIC ${wrap_srcs}) +file(GLOB wrap_headers "*.h") +list(REMOVE_ITEM wrap_srcs ${CMAKE_CURRENT_SOURCE_DIR}/wrap.cpp) +add_library(wrap_lib STATIC ${wrap_srcs} ${wrap_headers}) +gtsam_assign_source_folders(${wrap_srcs} ${wrap_headers}) add_executable(wrap wrap.cpp) -target_link_libraries(wrap wrap_lib) +target_link_libraries(wrap wrap_lib ${WRAP_BOOST_LIBRARIES}) -# Install wrap binary +# Install wrap binary and export target if (GTSAM_INSTALL_WRAP) - install(TARGETS wrap DESTINATION bin) + install(TARGETS wrap EXPORT GTSAM-exports DESTINATION bin) + list(APPEND GTSAM_EXPORTED_TARGETS wrap) + set(GTSAM_EXPORTED_TARGETS "${GTSAM_EXPORTED_TARGETS}" PARENT_SCOPE) endif(GTSAM_INSTALL_WRAP) # Install matlab header @@ -17,56 +23,8 @@ install(FILES matlab.h DESTINATION include/wrap) # Build tests if (GTSAM_BUILD_TESTS) - add_definitions(-DTOPSRCDIR="${CMAKE_SOURCE_DIR}") - set(wrap_local_libs wrap_lib) + set(wrap_local_libs wrap_lib ${WRAP_BOOST_LIBRARIES}) gtsam_add_subdir_tests("wrap" "${wrap_local_libs}" "${wrap_local_libs}" "") endif(GTSAM_BUILD_TESTS) -# Wrap codegen -#usage: wrap mexExtension interfacePath moduleName toolboxPath -# mexExtension : OS/CPU-dependent extension for MEX binaries -# interfacePath : *absolute* path to directory of module interface file -# moduleName : the name of the module, interface file must be called moduleName.h -# toolboxPath : the directory in which to generate the wrappers -# [mexFlags] : extra flags for the mex command -set(mexFlags "-I${Boost_INCLUDE_DIR} -I${CMAKE_INSTALL_PREFIX}/include -I${CMAKE_INSTALL_PREFIX}/include/gtsam -I${CMAKE_INSTALL_PREFIX}/include/gtsam/base -I${CMAKE_INSTALL_PREFIX}/include/gtsam/geometry -I${CMAKE_INSTALL_PREFIX}/include/gtsam/linear -I${CMAKE_INSTALL_PREFIX}/include/gtsam/nonlinear -I${CMAKE_INSTALL_PREFIX}/include/gtsam/slam -L${CMAKE_INSTALL_PREFIX}/lib -lgtsam") -set(toolbox_path ${CMAKE_BINARY_DIR}/wrap/gtsam) -set(moduleName gtsam) - -include(GtsamMatlabWrap) -find_mexextension() - -# get binary path for wrap executable to allow for different build configurations (e.g., ROS) -if (NOT EXECUTABLE_OUTPUT_PATH) - set(EXECUTABLE_OUTPUT_PATH ${CMAKE_CURRENT_BINARY_DIR}) -endif() - -# Code generation command -add_custom_target(wrap_gtsam ALL COMMAND - ${EXECUTABLE_OUTPUT_PATH}/wrap ${GTSAM_MEX_BIN_EXTENSION} ${CMAKE_CURRENT_SOURCE_DIR}/../ ${moduleName} ${toolbox_path} "${mexFlags}" - DEPENDS wrap) - -set(GTSAM_TOOLBOX_INSTALL_PATH ${CMAKE_INSTALL_PREFIX}/borg/toolbox CACHE DOCSTRING "Path to install matlab toolbox") - -if (GTSAM_INSTALL_MATLAB_TOOLBOX) - # Primary toolbox files - message(STATUS "Installing Matlab Toolbox to ${GTSAM_TOOLBOX_INSTALL_PATH}") - install(DIRECTORY DESTINATION ${GTSAM_TOOLBOX_INSTALL_PATH}) # make an empty folder - # exploit need for trailing slash to specify a full folder, rather than just its contents to copy - install(DIRECTORY ${toolbox_path} DESTINATION ${GTSAM_TOOLBOX_INSTALL_PATH}) - - # Examples - if (GTSAM_INSTALL_MATLAB_EXAMPLES) - message(STATUS "Installing Matlab Toolbox Examples") - file(GLOB matlab_examples "${CMAKE_SOURCE_DIR}/examples/matlab/*.m") - install(FILES ${matlab_examples} DESTINATION ${GTSAM_TOOLBOX_INSTALL_PATH}/gtsam/examples) - endif (GTSAM_INSTALL_MATLAB_EXAMPLES) - - # Tests - if (GTSAM_INSTALL_MATLAB_TESTS) - message(STATUS "Installing Matlab Toolbox Tests") - file(GLOB matlab_tests "${CMAKE_SOURCE_DIR}/tests/matlab/*.m") - install(FILES ${matlab_tests} DESTINATION ${GTSAM_TOOLBOX_INSTALL_PATH}/gtsam/tests) - endif (GTSAM_INSTALL_MATLAB_TESTS) -endif (GTSAM_INSTALL_MATLAB_TOOLBOX) diff --git a/wrap/Class.cpp b/wrap/Class.cpp index 6f6f91b0a..48fbeb6bf 100644 --- a/wrap/Class.cpp +++ b/wrap/Class.cpp @@ -1,165 +1,393 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file Class.cpp + * @author Frank Dellaert + * @author Andrew Melim + * @author Richard Roberts + **/ + +#include +#include +#include +//#include // on Linux GCC: fails with error regarding needing C++0x std flags +//#include // same failure as above +#include // works on Linux GCC + +#include +#include + +#include "Class.h" +#include "utilities.h" +#include "Argument.h" + +using namespace std; +using namespace wrap; + +/* ************************************************************************* */ +void Class::matlab_proxy(const string& toolboxPath, const string& wrapperName, + const TypeAttributesTable& typeAttributes, + FileWriter& wrapperFile, vector& functionNames) const { + + // Create namespace folders + createNamespaceStructure(namespaces, toolboxPath); + + // open destination classFile + string classFile = toolboxPath; + if(!namespaces.empty()) + classFile += "/+" + wrap::qualifiedName("/+", namespaces); + classFile += "/" + name + ".m"; + FileWriter proxyFile(classFile, verbose_, "%"); + + // get the name of actual matlab object + const string matlabQualName = qualifiedName("."), matlabUniqueName = qualifiedName(), cppName = qualifiedName("::"); + const string matlabBaseName = wrap::qualifiedName(".", qualifiedParent); + const string cppBaseName = wrap::qualifiedName("::", qualifiedParent); + + // emit class proxy code + // we want our class to inherit the handle class for memory purposes + const string parent = qualifiedParent.empty() ? "handle" : matlabBaseName; + comment_fragment(proxyFile); + proxyFile.oss << "classdef " << name << " < " << parent << endl; + proxyFile.oss << " properties\n"; + proxyFile.oss << " ptr_" << matlabUniqueName << " = 0\n"; + proxyFile.oss << " end\n"; + proxyFile.oss << " methods\n"; + + // Constructor + proxyFile.oss << " function obj = " << name << "(varargin)\n"; + // Special pointer constructors - one in MATLAB to create an object and + // assign a pointer returned from a C++ function. In turn this MATLAB + // constructor calls a special C++ function that just adds the object to + // its collector. This allows wrapped functions to return objects in + // other wrap modules - to add these to their collectors the pointer is + // passed from one C++ module into matlab then back into the other C++ + // module. + pointer_constructor_fragments(proxyFile, wrapperFile, wrapperName, functionNames); + wrapperFile.oss << "\n"; + // Regular constructors + BOOST_FOREACH(ArgumentList a, constructor.args_list) + { + const int id = (int)functionNames.size(); + constructor.proxy_fragment(proxyFile, wrapperName, !qualifiedParent.empty(), id, a); + const string wrapFunctionName = constructor.wrapper_fragment(wrapperFile, + cppName, matlabUniqueName, cppBaseName, id, a); + wrapperFile.oss << "\n"; + functionNames.push_back(wrapFunctionName); + } + proxyFile.oss << " else\n"; + proxyFile.oss << " error('Arguments do not match any overload of " << matlabQualName << " constructor');\n"; + proxyFile.oss << " end\n"; + if(!qualifiedParent.empty()) + proxyFile.oss << " obj = obj@" << matlabBaseName << "(uint64(" << ptr_constructor_key << "), base_ptr);\n"; + proxyFile.oss << " obj.ptr_" << matlabUniqueName << " = my_ptr;\n"; + proxyFile.oss << " end\n\n"; + + // Deconstructor + { + const int id = (int)functionNames.size(); + deconstructor.proxy_fragment(proxyFile, wrapperName, matlabUniqueName, id); + proxyFile.oss << "\n"; + const string functionName = deconstructor.wrapper_fragment(wrapperFile, cppName, matlabUniqueName, id); + wrapperFile.oss << "\n"; + functionNames.push_back(functionName); + } + proxyFile.oss << " function display(obj), obj.print(''); end\n %DISPLAY Calls print on the object\n"; + proxyFile.oss << " function disp(obj), obj.display; end\n %DISP Calls print on the object\n"; + + // Methods + BOOST_FOREACH(const Methods::value_type& name_m, methods) { + const Method& m = name_m.second; + m.proxy_wrapper_fragments(proxyFile, wrapperFile, cppName, matlabQualName, matlabUniqueName, wrapperName, typeAttributes, functionNames); + proxyFile.oss << "\n"; + wrapperFile.oss << "\n"; + } + + proxyFile.oss << " end\n"; + proxyFile.oss << "\n"; + proxyFile.oss << " methods(Static = true)\n"; + + // Static methods + BOOST_FOREACH(const StaticMethods::value_type& name_m, static_methods) { + const StaticMethod& m = name_m.second; + m.proxy_wrapper_fragments(proxyFile, wrapperFile, cppName, matlabQualName, matlabUniqueName, wrapperName, typeAttributes, functionNames); + proxyFile.oss << "\n"; + wrapperFile.oss << "\n"; + } + + proxyFile.oss << " end\n"; + proxyFile.oss << "end\n"; + + // Close file + proxyFile.emit(true); +} + +/* ************************************************************************* */ +string Class::qualifiedName(const string& delim) const { + return ::wrap::qualifiedName(delim, namespaces, name); +} + +/* ************************************************************************* */ +void Class::pointer_constructor_fragments(FileWriter& proxyFile, FileWriter& wrapperFile, const string& wrapperName, vector& functionNames) const { + + const string matlabUniqueName = qualifiedName(), cppName = qualifiedName("::"); + const string baseCppName = wrap::qualifiedName("::", qualifiedParent); + + const int collectorInsertId = (int)functionNames.size(); + const string collectorInsertFunctionName = matlabUniqueName + "_collectorInsertAndMakeBase_" + boost::lexical_cast(collectorInsertId); + functionNames.push_back(collectorInsertFunctionName); + + int upcastFromVoidId; + string upcastFromVoidFunctionName; + if(isVirtual) { + upcastFromVoidId = (int)functionNames.size(); + upcastFromVoidFunctionName = matlabUniqueName + "_upcastFromVoid_" + boost::lexical_cast(upcastFromVoidId); + functionNames.push_back(upcastFromVoidFunctionName); + } + + // MATLAB constructor that assigns pointer to matlab object then calls c++ + // function to add the object to the collector. + if(isVirtual) { + proxyFile.oss << " if (nargin == 2 || (nargin == 3 && strcmp(varargin{3}, 'void')))"; + } else { + proxyFile.oss << " if nargin == 2"; + } + proxyFile.oss << " && isa(varargin{1}, 'uint64') && varargin{1} == uint64(" << ptr_constructor_key << ")\n"; + if(isVirtual) { + proxyFile.oss << " if nargin == 2\n"; + proxyFile.oss << " my_ptr = varargin{2};\n"; + proxyFile.oss << " else\n"; + proxyFile.oss << " my_ptr = " << wrapperName << "(" << upcastFromVoidId << ", varargin{2});\n"; + proxyFile.oss << " end\n"; + } else { + proxyFile.oss << " my_ptr = varargin{2};\n"; + } + if(qualifiedParent.empty()) // If this class has a base class, we'll get a base class pointer back + proxyFile.oss << " "; + else + proxyFile.oss << " base_ptr = "; + proxyFile.oss << wrapperName << "(" << collectorInsertId << ", my_ptr);\n"; // Call collector insert and get base class ptr + + // C++ function to add pointer from MATLAB to collector. The pointer always + // comes from a C++ return value; this mechanism allows the object to be added + // to a collector in a different wrap module. If this class has a base class, + // a new pointer to the base class is allocated and returned. + wrapperFile.oss << "void " << collectorInsertFunctionName << "(int nargout, mxArray *out[], int nargin, const mxArray *in[])\n"; + wrapperFile.oss << "{\n"; + wrapperFile.oss << " mexAtExit(&_deleteAllObjects);\n"; + // Typedef boost::shared_ptr + wrapperFile.oss << " typedef boost::shared_ptr<" << cppName << "> Shared;\n"; + wrapperFile.oss << "\n"; + // Get self pointer passed in + wrapperFile.oss << " Shared *self = *reinterpret_cast (mxGetData(in[0]));\n"; + // Add to collector + wrapperFile.oss << " collector_" << matlabUniqueName << ".insert(self);\n"; + // If we have a base class, return the base class pointer (MATLAB will call the base class collectorInsertAndMakeBase to add this to the collector and recurse the heirarchy) + if(!qualifiedParent.empty()) { + wrapperFile.oss << "\n"; + wrapperFile.oss << " typedef boost::shared_ptr<" << baseCppName << "> SharedBase;\n"; + wrapperFile.oss << " out[0] = mxCreateNumericMatrix(1, 1, mxUINT32OR64_CLASS, mxREAL);\n"; + wrapperFile.oss << " *reinterpret_cast(mxGetData(out[0])) = new SharedBase(*self);\n"; + } + wrapperFile.oss << "}\n"; + + // If this is a virtual function, C++ function to dynamic upcast it from a + // shared_ptr. This mechanism allows automatic dynamic creation of the + // real underlying derived-most class when a C++ method returns a virtual + // base class. + if(isVirtual) + wrapperFile.oss << + "\n" + "void " << upcastFromVoidFunctionName << "(int nargout, mxArray *out[], int nargin, const mxArray *in[]) {\n" + " mexAtExit(&_deleteAllObjects);\n" + " typedef boost::shared_ptr<" << cppName << "> Shared;\n" + " boost::shared_ptr *asVoid = *reinterpret_cast**> (mxGetData(in[0]));\n" + " out[0] = mxCreateNumericMatrix(1, 1, mxUINT32OR64_CLASS, mxREAL);\n" + " Shared *self = new Shared(boost::static_pointer_cast<" << cppName << ">(*asVoid));\n" + " *reinterpret_cast(mxGetData(out[0])) = self;\n" + "}\n"; +} + +/* ************************************************************************* */ +vector expandArgumentListsTemplate(const vector& argLists, const string& templateArg, const vector& instName, const std::vector& expandedClassNamespace, const string& expandedClassName) { + vector result; + BOOST_FOREACH(const ArgumentList& argList, argLists) { + ArgumentList instArgList; + BOOST_FOREACH(const Argument& arg, argList) { + Argument instArg = arg; + if(arg.type == templateArg) { + instArg.namespaces.assign(instName.begin(), instName.end()-1); + instArg.type = instName.back(); + } else if(arg.type == "This") { + instArg.namespaces.assign(expandedClassNamespace.begin(), expandedClassNamespace.end()); + instArg.type = expandedClassName; + } + instArgList.push_back(instArg); + } + result.push_back(instArgList); + } + return result; +} + +/* ************************************************************************* */ +template +map expandMethodTemplate(const map& methods, const string& templateArg, const vector& instName, const std::vector& expandedClassNamespace, const string& expandedClassName) { + map result; + typedef pair Name_Method; + BOOST_FOREACH(const Name_Method& name_method, methods) { + const METHOD& method = name_method.second; + METHOD instMethod = method; + instMethod.argLists = expandArgumentListsTemplate(method.argLists, templateArg, instName, expandedClassNamespace, expandedClassName); + instMethod.returnVals.clear(); + BOOST_FOREACH(const ReturnValue& retVal, method.returnVals) { + ReturnValue instRetVal = retVal; + if(retVal.type1 == templateArg) { + instRetVal.namespaces1.assign(instName.begin(), instName.end()-1); + instRetVal.type1 = instName.back(); + } else if(retVal.type1 == "This") { + instRetVal.namespaces1.assign(expandedClassNamespace.begin(), expandedClassNamespace.end()); + instRetVal.type1 = expandedClassName; + } + if(retVal.type2 == templateArg) { + instRetVal.namespaces2.assign(instName.begin(), instName.end()-1); + instRetVal.type2 = instName.back(); + } else if(retVal.type1 == "This") { + instRetVal.namespaces2.assign(expandedClassNamespace.begin(), expandedClassNamespace.end()); + instRetVal.type2 = expandedClassName; + } + instMethod.returnVals.push_back(instRetVal); + } + result.insert(make_pair(name_method.first, instMethod)); + } + return result; +} + +/* ************************************************************************* */ +Class expandClassTemplate(const Class& cls, const string& templateArg, const vector& instName, const std::vector& expandedClassNamespace, const string& expandedClassName) { + Class inst; + inst.name = cls.name; + inst.templateArgs = cls.templateArgs; + inst.typedefName = cls.typedefName; + inst.isVirtual = cls.isVirtual; + inst.qualifiedParent = cls.qualifiedParent; + inst.methods = expandMethodTemplate(cls.methods, templateArg, instName, expandedClassNamespace, expandedClassName); + inst.static_methods = expandMethodTemplate(cls.static_methods, templateArg, instName, expandedClassNamespace, expandedClassName); + inst.namespaces = cls.namespaces; + inst.constructor = cls.constructor; + inst.constructor.args_list = expandArgumentListsTemplate(cls.constructor.args_list, templateArg, instName, expandedClassNamespace, expandedClassName); + inst.constructor.name = inst.name; + inst.deconstructor = cls.deconstructor; + inst.deconstructor.name = inst.name; + inst.verbose_ = cls.verbose_; + return inst; +} + +/* ************************************************************************* */ +vector Class::expandTemplate(const string& templateArg, const vector >& instantiations) const { + vector result; + BOOST_FOREACH(const vector& instName, instantiations) { + const string expandedName = name + instName.back(); + Class inst = expandClassTemplate(*this, templateArg, instName, this->namespaces, expandedName); + inst.name = expandedName; + inst.templateArgs.clear(); + inst.typedefName = qualifiedName("::") + "<" + wrap::qualifiedName("::", instName) + ">"; + result.push_back(inst); + } + return result; +} + +/* ************************************************************************* */ +Class Class::expandTemplate(const string& templateArg, const vector& instantiation, const std::vector& expandedClassNamespace, const string& expandedClassName) const { + return expandClassTemplate(*this, templateArg, instantiation, expandedClassNamespace, expandedClassName); +} + +/* ************************************************************************* */ +std::string Class::getTypedef() const { + string result; + BOOST_FOREACH(const string& namesp, namespaces) { + result += ("namespace " + namesp + " { "); + } + result += ("typedef " + typedefName + " " + name + ";"); + for (size_t i = 0; i -#include -#include - -#include - -#include "Class.h" -#include "utilities.h" - -using namespace std; -using namespace wrap; - -/* ************************************************************************* */ -void Class::matlab_proxy(const string& classFile) const { - // open destination classFile - FileWriter file(classFile, verbose_, "%"); - - // get the name of actual matlab object - string matlabName = qualifiedName(); - - // emit class proxy code - // we want our class to inherit the handle class for memory purposes - file.oss << "classdef " << matlabName << " < handle" << endl; - file.oss << " properties" << endl; - file.oss << " self = 0" << endl; - file.oss << " end" << endl; - file.oss << " methods" << endl; - // constructor - file.oss << " function obj = " << matlabName << "(varargin)" << endl; - BOOST_FOREACH(Constructor c, constructors) - c.matlab_proxy_fragment(file,matlabName); - file.oss << " if nargin ~= 13 && obj.self == 0, error('" << matlabName << " constructor failed'); end" << endl; - file.oss << " end" << endl; - // deconstructor - file.oss << " function delete(obj)" << endl; - file.oss << " delete_" << matlabName << "(obj);" << endl; - file.oss << " end" << endl; - file.oss << " function display(obj), obj.print(''); end" << endl; - file.oss << " function disp(obj), obj.display; end" << endl; - file.oss << " end" << endl; - file.oss << "end" << endl; - - // close file - file.emit(true); -} - -/* ************************************************************************* */ -void Class::matlab_constructors(const string& toolboxPath) const { - BOOST_FOREACH(Constructor c, constructors) { - c.matlab_mfile (toolboxPath, qualifiedName()); - c.matlab_wrapper(toolboxPath, qualifiedName("::"), qualifiedName(), using_namespaces, includes); - } -} - -/* ************************************************************************* */ -void Class::matlab_deconstructor(const string& toolboxPath) const { - d.matlab_mfile (toolboxPath, qualifiedName()); - d.matlab_wrapper(toolboxPath, qualifiedName("::"), qualifiedName(), using_namespaces, includes); -} -/* ************************************************************************* */ -void Class::matlab_methods(const string& classPath) const { - string matlabName = qualifiedName(), cppName = qualifiedName("::"); - BOOST_FOREACH(Method m, methods) { - m.matlab_mfile (classPath); - m.matlab_wrapper(classPath, name, cppName, matlabName, using_namespaces, includes); - } -} - -/* ************************************************************************* */ -void Class::matlab_static_methods(const string& toolboxPath) const { - string matlabName = qualifiedName(), cppName = qualifiedName("::"); - BOOST_FOREACH(const StaticMethod& m, static_methods) { - m.matlab_mfile (toolboxPath, qualifiedName()); - m.matlab_wrapper(toolboxPath, name, matlabName, cppName, using_namespaces, includes); - } -} - -/* ************************************************************************* */ -void Class::matlab_make_fragment(FileWriter& file, - const string& toolboxPath, - const string& mexFlags) const { - string mex = "mex " + mexFlags + " "; - string matlabClassName = qualifiedName(); - BOOST_FOREACH(Constructor c, constructors) - file.oss << mex << c.matlab_wrapper_name(matlabClassName) << ".cpp" << endl; - file.oss << mex << d.matlab_wrapper_name(matlabClassName) << ".cpp" << endl; - BOOST_FOREACH(StaticMethod sm, static_methods) - file.oss << mex << matlabClassName + "_" + sm.name << ".cpp" << endl; - file.oss << endl << "cd @" << matlabClassName << endl; - BOOST_FOREACH(Method m, methods) - file.oss << mex << m.name << ".cpp" << endl; - file.oss << endl; -} - -/* ************************************************************************* */ -void Class::makefile_fragment(FileWriter& file) const { -// new_Point2_.$(MEXENDING): new_Point2_.cpp -// $(MEX) $(mex_flags) new_Point2_.cpp -// new_Point2_dd.$(MEXENDING): new_Point2_dd.cpp -// $(MEX) $(mex_flags) new_Point2_dd.cpp -// @Point2/x.$(MEXENDING): @Point2/x.cpp -// $(MEX) $(mex_flags) @Point2/x.cpp -output @Point2/x -// @Point2/y.$(MEXENDING): @Point2/y.cpp -// $(MEX) $(mex_flags) @Point2/y.cpp -output @Point2/y -// @Point2/dim.$(MEXENDING): @Point2/dim.cpp -// $(MEX) $(mex_flags) @Point2/dim.cpp -output @Point2/dim -// -// Point2: new_Point2_.$(MEXENDING) new_Point2_dd.$(MEXENDING) @Point2/x.$(MEXENDING) @Point2/y.$(MEXENDING) @Point2/dim.$(MEXENDING) - - string matlabName = qualifiedName(); - - // collect names - vector file_names; - BOOST_FOREACH(Constructor c, constructors) { - string file_base = c.matlab_wrapper_name(matlabName); - file_names.push_back(file_base); - } - file_names.push_back(d.matlab_wrapper_name(matlabName)); - BOOST_FOREACH(StaticMethod c, static_methods) { - string file_base = matlabName + "_" + c.name; - file_names.push_back(file_base); - } - BOOST_FOREACH(Method c, methods) { - string file_base = "@" + matlabName + "/" + c.name; - file_names.push_back(file_base); + if (!constructor.args_list.empty()) + proxyFile.oss << "%\n%-------Constructors-------\n"; + BOOST_FOREACH(ArgumentList argList, constructor.args_list) { + string up_name = boost::to_upper_copy(name); + proxyFile.oss << "%" << name << "("; + unsigned int i = 0; + BOOST_FOREACH(const Argument& arg, argList) { + if (i != argList.size() - 1) + proxyFile.oss << arg.type << " " << arg.name << ", "; + else + proxyFile.oss << arg.type << " " << arg.name; + i++; + } + proxyFile.oss << ")\n"; } - BOOST_FOREACH(const string& file_base, file_names) { - file.oss << file_base << ".$(MEXENDING): " << file_base << ".cpp" << endl; - file.oss << "\t$(MEX) $(mex_flags) " << file_base << ".cpp -output " << file_base << endl; + if (!methods.empty()) + proxyFile.oss << "%\n%-------Methods-------\n"; + BOOST_FOREACH(const Methods::value_type& name_m, methods) { + const Method& m = name_m.second; + BOOST_FOREACH(ArgumentList argList, m.argLists) { + string up_name = boost::to_upper_copy(m.name); + proxyFile.oss << "%" << m.name << "("; + unsigned int i = 0; + BOOST_FOREACH(const Argument& arg, argList) { + if (i != argList.size() - 1) + proxyFile.oss << arg.type << " " << arg.name << ", "; + else + proxyFile.oss << arg.type << " " << arg.name; + i++; + } + proxyFile.oss << ") : returns " + << m.returnVals[0].return_type(false, m.returnVals[0].pair) << endl; + } } - // class target - file.oss << "\n" << matlabName << ": "; - BOOST_FOREACH(const string& file_base, file_names) { - file.oss << file_base << ".$(MEXENDING) "; + if (!static_methods.empty()) + proxyFile.oss << "%\n%-------Static Methods-------\n"; + BOOST_FOREACH(const StaticMethods::value_type& name_m, static_methods) { + const StaticMethod& m = name_m.second; + BOOST_FOREACH(ArgumentList argList, m.argLists) { + string up_name = boost::to_upper_copy(m.name); + proxyFile.oss << "%" << m.name << "("; + unsigned int i = 0; + BOOST_FOREACH(const Argument& arg, argList) { + if (i != argList.size() - 1) + proxyFile.oss << arg.type << " " << arg.name << ", "; + else + proxyFile.oss << arg.type << " " << arg.name; + i++; + } + + proxyFile.oss << ") : returns " + << m.returnVals[0].return_type(false, m.returnVals[0].pair) << endl; + } } - file.oss << "\n" << endl; -} -/* ************************************************************************* */ -string Class::qualifiedName(const string& delim) const { - string result; - BOOST_FOREACH(const string& ns, namespaces) - result += ns + delim; - return result + name; + proxyFile.oss << "%\n"; } - -/* ************************************************************************* */ +/* ************************************************************************* */ diff --git a/wrap/Class.h b/wrap/Class.h index 875b3203e..0d2736382 100644 --- a/wrap/Class.h +++ b/wrap/Class.h @@ -13,46 +13,60 @@ * @file Class.h * @brief describe the C++ class that is being wrapped * @author Frank Dellaert + * @author Andrew Melim + * @author Richard Roberts **/ #pragma once #include +#include #include "Constructor.h" #include "Deconstructor.h" #include "Method.h" #include "StaticMethod.h" +#include "TypeAttributesTable.h" +#include namespace wrap { /// Class has name, constructors, methods struct Class { + typedef std::map Methods; + typedef std::map StaticMethods; + /// Constructor creates an empty class - Class(bool verbose=true) : verbose_(verbose) {} + Class(bool verbose=true) : isVirtual(false), verbose_(verbose) {} // Then the instance variables are set directly by the Module constructor std::string name; ///< Class name - std::vector constructors; ///< Class constructors - std::vector methods; ///< Class methods - std::vector static_methods; ///< Static methods + std::vector templateArgs; ///< Template arguments + std::string typedefName; ///< The name to typedef *from*, if this class is actually a typedef, i.e. typedef [typedefName] [name] + bool isVirtual; ///< Whether the class is part of a virtual inheritance chain + std::vector qualifiedParent; ///< The *single* parent - the last string is the parent class name, preceededing elements are a namespace stack + Methods methods; ///< Class methods + StaticMethods static_methods; ///< Static methods std::vector namespaces; ///< Stack of namespaces - std::vector using_namespaces; ///< default namespaces - std::vector includes; ///< header include overrides - Deconstructor d; + Constructor constructor; ///< Class constructors + Deconstructor deconstructor; ///< Deconstructor to deallocate C++ object bool verbose_; ///< verbose flag // And finally MATLAB code is emitted, methods below called by Module::matlab_code - void matlab_proxy(const std::string& classFile) const; ///< emit proxy class - void matlab_constructors(const std::string& toolboxPath) const; ///< emit constructor wrappers - void matlab_deconstructor(const std::string& toolboxPath) const; - void matlab_methods(const std::string& classPath) const; ///< emit method wrappers - void matlab_static_methods(const std::string& classPath) const; ///< emit static method wrappers - void matlab_make_fragment(FileWriter& file, - const std::string& toolboxPath, - const std::string& mexFlags) const; ///< emit make fragment for global make script - void makefile_fragment(FileWriter& file) const; ///< emit makefile fragment + void matlab_proxy(const std::string& toolboxPath, const std::string& wrapperName, const TypeAttributesTable& typeAttributes, + FileWriter& wrapperFile, std::vector& functionNames) const; ///< emit proxy class std::string qualifiedName(const std::string& delim = "") const; ///< creates a namespace-qualified name, optional delimiter + + std::vector expandTemplate(const std::string& templateArg, const std::vector >& instantiations) const; + Class expandTemplate(const std::string& templateArg, const std::vector& instantiation, const std::vector& expandedClassNamespace, const std::string& expandedClassName) const; + + // The typedef line for this class, if this class is a typedef, otherwise returns an empty string. + std::string getTypedef() const; + + +private: + void pointer_constructor_fragments(FileWriter& proxyFile, FileWriter& wrapperFile, const std::string& wrapperName, std::vector& functionNames) const; + void comment_fragment(FileWriter& proxyFile) const; }; } // \namespace wrap diff --git a/wrap/Constructor.cpp b/wrap/Constructor.cpp index fda7db1b4..7d18cb8db 100644 --- a/wrap/Constructor.cpp +++ b/wrap/Constructor.cpp @@ -12,12 +12,16 @@ /** * @file Constructor.ccp * @author Frank Dellaert + * @author Andrew Melim + * @author Richard Roberts **/ #include #include +#include #include +#include #include "utilities.h" #include "Constructor.h" @@ -25,82 +29,80 @@ using namespace std; using namespace wrap; + /* ************************************************************************* */ string Constructor::matlab_wrapper_name(const string& className) const { - string str = "new_" + className + "_" + args.signature(); + string str = "new_" + className; return str; } /* ************************************************************************* */ -void Constructor::matlab_proxy_fragment(FileWriter& file, const string& className) const { +void Constructor::proxy_fragment(FileWriter& file, const std::string& wrapperName, + bool hasParent, const int id, const ArgumentList args) const { size_t nrArgs = args.size(); // check for number of arguments... - file.oss << " if (nargin == " << nrArgs; + file.oss << " elseif nargin == " << nrArgs; if (nrArgs>0) file.oss << " && "; // ...and their types bool first = true; for(size_t i=0;i& using_namespaces, const vector& includes) const { - string matlabName = matlab_wrapper_name(matlabClassName); + const string& matlabUniqueName, + const string& cppBaseClassName, + int id, + const ArgumentList& al) const { - // open destination wrapperFile - string wrapperFile = toolboxPath + "/" + matlabName + ".cpp"; - FileWriter file(wrapperFile, verbose_, "//"); + const string wrapFunctionName = matlabUniqueName + "_constructor_" + boost::lexical_cast(id); - // generate code - generateIncludes(file, name, includes); - generateUsingNamespace(file, using_namespaces); + file.oss << "void " << wrapFunctionName << "(int nargout, mxArray *out[], int nargin, const mxArray *in[])" << endl; + file.oss << "{\n"; + file.oss << " mexAtExit(&_deleteAllObjects);\n"; + //Typedef boost::shared_ptr + file.oss << " typedef boost::shared_ptr<" << cppClassName << "> Shared;\n"; + file.oss << "\n"; + + //Check to see if there will be any arguments and remove {} for consiseness + if(al.size() > 0) + al.matlab_unwrap(file); // unwrap arguments + file.oss << " Shared *self = new Shared(new " << cppClassName << "(" << al.names() << "));" << endl; + file.oss << " collector_" << matlabUniqueName << ".insert(self);\n"; + + if(verbose_) + file.oss << " std::cout << \"constructed \" << self << \" << std::endl;" << endl; + file.oss << " out[0] = mxCreateNumericMatrix(1, 1, mxUINT32OR64_CLASS, mxREAL);" << endl; + file.oss << " *reinterpret_cast (mxGetData(out[0])) = self;" << endl; + + // If we have a base class, return the base class pointer (MATLAB will call the base class collectorInsertAndMakeBase to add this to the collector and recurse the heirarchy) + if(!cppBaseClassName.empty()) { + file.oss << "\n"; + file.oss << " typedef boost::shared_ptr<" << cppBaseClassName << "> SharedBase;\n"; + file.oss << " out[1] = mxCreateNumericMatrix(1, 1, mxUINT32OR64_CLASS, mxREAL);\n"; + file.oss << " *reinterpret_cast(mxGetData(out[1])) = new SharedBase(*self);\n"; + } - file.oss << "void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[])" << endl; - file.oss << "{" << endl; - file.oss << " checkArguments(\"" << matlabName << "\",nargout,nargin," << args.size() << ");" << endl; - args.matlab_unwrap(file); // unwrap arguments - file.oss << " " << cppClassName << "* self = new " << cppClassName << "(" << args.names() << ");" << endl; // need qualified name, delim: "::" - file.oss << " out[0] = wrap_constructed(self,\"" << matlabClassName << "\");" << endl; // need matlab qualified name file.oss << "}" << endl; - // close file - file.emit(true); + return wrapFunctionName; } /* ************************************************************************* */ diff --git a/wrap/Constructor.h b/wrap/Constructor.h index 4aba5b984..fe8a96ccd 100644 --- a/wrap/Constructor.h +++ b/wrap/Constructor.h @@ -13,6 +13,7 @@ * @file Constructor.h * @brief class describing a constructor + code generation * @author Frank Dellaert + * @author Richard Roberts **/ #pragma once @@ -28,12 +29,12 @@ namespace wrap { struct Constructor { /// Constructor creates an empty class - Constructor(bool verbose = true) : + Constructor(bool verbose = false) : verbose_(verbose) { } // Then the instance variables are set directly by the Module constructor - ArgumentList args; + std::vector args_list; std::string name; bool verbose_; @@ -48,19 +49,22 @@ struct Constructor { * Create fragment to select constructor in proxy class, e.g., * if nargin == 2, obj.self = new_Pose3_RP(varargin{1},varargin{2}); end */ - void matlab_proxy_fragment(FileWriter& file, const std::string& className) const; - - /// m-file - void matlab_mfile(const std::string& toolboxPath, - const std::string& qualifiedMatlabName) const; + void proxy_fragment(FileWriter& file, const std::string& wrapperName, + bool hasParent, const int id, const ArgumentList args) const; /// cpp wrapper - void matlab_wrapper(const std::string& toolboxPath, + std::string wrapper_fragment(FileWriter& file, const std::string& cppClassName, - const std::string& matlabClassName, - const std::vector& using_namespaces, - const std::vector& includes) const; + const std::string& matlabUniqueName, + const std::string& cppBaseClassName, + int id, + const ArgumentList& al) const; + + /// constructor function + void generate_construct(FileWriter& file, const std::string& cppClassName, + std::vector& args_list) const; + }; -} // \namespace wrap +} // \namespace wrap diff --git a/wrap/Deconstructor.cpp b/wrap/Deconstructor.cpp index 93ed724f5..b2355f20e 100644 --- a/wrap/Deconstructor.cpp +++ b/wrap/Deconstructor.cpp @@ -13,12 +13,14 @@ * @file Deconstructor.ccp * @author Frank Dellaert * @author Andrew Melim + * @author Richard Roberts **/ #include #include #include +#include #include "utilities.h" #include "Deconstructor.h" @@ -33,51 +35,40 @@ string Deconstructor::matlab_wrapper_name(const string& className) const { } /* ************************************************************************* */ -void Deconstructor::matlab_mfile(const string& toolboxPath, const string& qualifiedMatlabName) const { +void Deconstructor::proxy_fragment(FileWriter& file, + const std::string& wrapperName, + const std::string& matlabUniqueName, int id) const { - string matlabName = matlab_wrapper_name(qualifiedMatlabName); - - // open destination m-file - string wrapperFile = toolboxPath + "/" + matlabName + ".m"; - FileWriter file(wrapperFile, verbose_, "%"); - - // generate code - file.oss << "function result = " << matlabName << "(obj"; - if (args.size()) file.oss << "," << args.names(); - file.oss << ")" << endl; - file.oss << " error('need to compile " << matlabName << ".cpp');" << endl; - file.oss << "end" << endl; - - // close file - file.emit(true); + file.oss << " function delete(obj)\n"; + file.oss << " " << wrapperName << "(" << id << ", obj.ptr_" << matlabUniqueName << ");\n"; + file.oss << " end\n"; } /* ************************************************************************* */ -void Deconstructor::matlab_wrapper(const string& toolboxPath, +string Deconstructor::wrapper_fragment(FileWriter& file, const string& cppClassName, - const string& matlabClassName, - const vector& using_namespaces, const vector& includes) const { - string matlabName = matlab_wrapper_name(matlabClassName); + const string& matlabUniqueName, + int id) const { + + const string matlabName = matlab_wrapper_name(matlabUniqueName); - // open destination wrapperFile - string wrapperFile = toolboxPath + "/" + matlabName + ".cpp"; - FileWriter file(wrapperFile, verbose_, "//"); - - // generate code - // - generateIncludes(file, name, includes); - cout << "Generate includes " << name << endl; - generateUsingNamespace(file, using_namespaces); + const string wrapFunctionName = matlabUniqueName + "_deconstructor_" + boost::lexical_cast(id); - file.oss << "void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[])" << endl; + file.oss << "void " << wrapFunctionName << "(int nargout, mxArray *out[], int nargin, const mxArray *in[])" << endl; file.oss << "{" << endl; + file.oss << " typedef boost::shared_ptr<" << cppClassName << "> Shared;" << endl; //Deconstructor takes 1 arg, the mxArray obj file.oss << " checkArguments(\"" << matlabName << "\",nargout,nargin," << "1" << ");" << endl; - file.oss << " delete_shared_ptr< " << cppClassName << " >(in[0],\"" << matlabClassName << "\");" << endl; + file.oss << " Shared *self = *reinterpret_cast(mxGetData(in[0]));\n"; + file.oss << " Collector_" << matlabUniqueName << "::iterator item;\n"; + file.oss << " item = collector_" << matlabUniqueName << ".find(self);\n"; + file.oss << " if(item != collector_" << matlabUniqueName << ".end()) {\n"; + file.oss << " delete self;\n"; + file.oss << " collector_" << matlabUniqueName << ".erase(item);\n"; + file.oss << " }\n"; file.oss << "}" << endl; - // close file - file.emit(true); + return wrapFunctionName; } /* ************************************************************************* */ diff --git a/wrap/Deconstructor.h b/wrap/Deconstructor.h index a5af4e327..a3b71b04e 100644 --- a/wrap/Deconstructor.h +++ b/wrap/Deconstructor.h @@ -14,6 +14,7 @@ * @brief class describing a constructor + code generation * @author Frank Dellaert * @author Andrew Melim + * @author Richard Roberts **/ #pragma once @@ -34,7 +35,6 @@ struct Deconstructor { } // Then the instance variables are set directly by the Module deconstructor - ArgumentList args; std::string name; bool verbose_; @@ -46,15 +46,15 @@ struct Deconstructor { std::string matlab_wrapper_name(const std::string& className) const; /// m-file - void matlab_mfile(const std::string& toolboxPath, - const std::string& qualifiedMatlabName) const; + void proxy_fragment(FileWriter& file, + const std::string& wrapperName, + const std::string& matlabUniqueName, int id) const; /// cpp wrapper - void matlab_wrapper(const std::string& toolboxPath, + std::string wrapper_fragment(FileWriter& file, const std::string& cppClassName, - const std::string& matlabClassName, - const std::vector& using_namespaces, - const std::vector& includes) const; + const std::string& matlabUniqueName, + int id) const; }; } // \namespace wrap diff --git a/wrap/FileWriter.cpp b/wrap/FileWriter.cpp index ae474be0a..515a5dbf3 100644 --- a/wrap/FileWriter.cpp +++ b/wrap/FileWriter.cpp @@ -35,17 +35,17 @@ void FileWriter::emit(bool add_header, bool force_overwrite) const { // Only write a file if it is new, an update, or overwrite is forced string new_contents = oss.str(); if (force_overwrite || !file_exists || existing_contents != new_contents) { - ofstream ofs(filename_.c_str()); + ofstream ofs(filename_.c_str(), ios::binary); // Binary to use LF line endings instead of CRLF if (!ofs) throw CantOpenFile(filename_); - // header - if (add_header) - ofs << comment_str_ << " automatically generated by wrap" << endl; - // dump in stringstream ofs << new_contents; ofs.close(); if (verbose_) cerr << " ...complete" << endl; + + // Add small message whenever writing a new file and not running in full verbose mode + if (!verbose_) + cout << "wrap: generating " << filename_ << endl; } else { if (verbose_) cerr << " ...no update" << endl; } diff --git a/wrap/FileWriter.h b/wrap/FileWriter.h index f081b86ed..ecafc0c35 100644 --- a/wrap/FileWriter.h +++ b/wrap/FileWriter.h @@ -25,7 +25,7 @@ public: std::ostringstream oss; ///< Primary stream for operating on the file /** Create a writer with a filename and delimiter for the header comment */ - FileWriter(const std::string& filename, bool verbose, const std::string& comment_str=""); + FileWriter(const std::string& filename, bool verbose, const std::string& comment_str); /** Writes the contents of the stringstream to the file, checking if actually new */ void emit(bool add_header, bool force=false) const; diff --git a/wrap/ForwardDeclaration.h b/wrap/ForwardDeclaration.h new file mode 100644 index 000000000..2c9b6fa0c --- /dev/null +++ b/wrap/ForwardDeclaration.h @@ -0,0 +1,32 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file Class.h + * @brief describe the C++ class that is being wrapped + * @author Frank Dellaert + * @author Andrew Melim + * @author Richard Roberts + **/ + +#pragma once + +#include + +namespace wrap { + + struct ForwardDeclaration { + std::string name; + bool isVirtual; + ForwardDeclaration() : isVirtual(false) {} + }; + +} \ No newline at end of file diff --git a/wrap/GlobalFunction.cpp b/wrap/GlobalFunction.cpp new file mode 100644 index 000000000..084f83be0 --- /dev/null +++ b/wrap/GlobalFunction.cpp @@ -0,0 +1,161 @@ +/** + * @file GlobalFunction.cpp + * + * @date Jul 22, 2012 + * @author Alex Cunningham + */ + +#include "GlobalFunction.h" +#include "utilities.h" + +#include +#include + +namespace wrap { + +using namespace std; + +/* ************************************************************************* */ +void GlobalFunction::addOverload(bool verbose, const std::string& name, + const ArgumentList& args, const ReturnValue& retVal, const StrVec& ns_stack) { + this->verbose_ = verbose; + this->name = name; + this->argLists.push_back(args); + this->returnVals.push_back(retVal); + this->namespaces.push_back(ns_stack); +} + +/* ************************************************************************* */ +void GlobalFunction::matlab_proxy(const std::string& toolboxPath, const std::string& wrapperName, + const TypeAttributesTable& typeAttributes, FileWriter& wrapperFile, + std::vector& functionNames) const { + + // cluster overloads with same namespace + // create new GlobalFunction structures around namespaces - same namespaces and names are overloads + // map of namespace to global function + typedef map GlobalFunctionMap; + GlobalFunctionMap grouped_functions; + for (size_t i=0; i& functionNames) const { + + // create the folder for the namespace + const StrVec& ns = namespaces.front(); + createNamespaceStructure(ns, toolboxPath); + + // open destination mfunctionFileName + string mfunctionFileName = toolboxPath; + if(!ns.empty()) + mfunctionFileName += "/+" + wrap::qualifiedName("/+", ns); + mfunctionFileName += "/" + name + ".m"; + FileWriter mfunctionFile(mfunctionFileName, verbose_, "%"); + + // get the name of actual matlab object + const string + matlabQualName = qualifiedName(".", ns, name), + matlabUniqueName = qualifiedName("", ns, name), + cppName = qualifiedName("::", ns, name); + + mfunctionFile.oss << "function varargout = " << name << "(varargin)\n"; + + for(size_t overload = 0; overload < argLists.size(); ++overload) { + const ArgumentList& args = argLists[overload]; + const ReturnValue& returnVal = returnVals[overload]; + size_t nrArgs = args.size(); + + const int id = functionNames.size(); + + // Output proxy matlab code + + // check for number of arguments... + mfunctionFile.oss << (overload==0?"":"else") << "if length(varargin) == " << nrArgs; + if (nrArgs>0) mfunctionFile.oss << " && "; + // ...and their types + bool first = true; + for(size_t i=0;i(id); + + // call + wrapperFile.oss << "void " << wrapFunctionName << "(int nargout, mxArray *out[], int nargin, const mxArray *in[])\n"; + // start + wrapperFile.oss << "{\n"; + + returnVal.wrapTypeUnwrap(wrapperFile); + + // check arguments + // NOTE: for static functions, there is no object passed + wrapperFile.oss << " checkArguments(\"" << matlabUniqueName << "\",nargout,nargin," << args.size() << ");\n"; + + // unwrap arguments, see Argument.cpp + args.matlab_unwrap(wrapperFile,0); // We start at 0 because there is no self object + + // call method with default type and wrap result + if (returnVal.type1!="void") + returnVal.wrap_result(cppName+"("+args.names()+")", wrapperFile, typeAttributes); + else + wrapperFile.oss << cppName+"("+args.names()+");\n"; + + // finish + wrapperFile.oss << "}\n"; + + // Add to function list + functionNames.push_back(wrapFunctionName); + } + + mfunctionFile.oss << "else\n"; + mfunctionFile.oss << " error('Arguments do not match any overload of function " << matlabQualName << "');" << endl; + mfunctionFile.oss << "end" << endl; + + // Close file + mfunctionFile.emit(true); +} + +/* ************************************************************************* */ + + +} // \namespace wrap + + + + diff --git a/wrap/GlobalFunction.h b/wrap/GlobalFunction.h new file mode 100644 index 000000000..37a70df2a --- /dev/null +++ b/wrap/GlobalFunction.h @@ -0,0 +1,58 @@ +/** + * @file GlobalFunction.h + * + * @brief Implements codegen for a global function wrapped in matlab + * + * @date Jul 22, 2012 + * @author Alex Cunningham + */ + +#pragma once + +#include "Argument.h" +#include "ReturnValue.h" + +namespace wrap { + +struct GlobalFunction { + + typedef std::vector StrVec; + + bool verbose_; + std::string name; + + // each overload, regardless of namespace + std::vector argLists; ///< arugments for each overload + std::vector returnVals; ///< returnVals for each overload + std::vector namespaces; ///< Stack of namespaces + + // Constructor only used in Module + GlobalFunction(bool verbose = true) : verbose_(verbose) {} + + // Used to reconstruct + GlobalFunction(const std::string& name_, bool verbose = true) + : verbose_(verbose), name(name_) {} + + // adds an overloaded version of this function + void addOverload(bool verbose, const std::string& name, + const ArgumentList& args, const ReturnValue& retVal, const StrVec& ns_stack); + + // codegen function called from Module to build the cpp and matlab versions of the function + void matlab_proxy(const std::string& toolboxPath, const std::string& wrapperName, + const TypeAttributesTable& typeAttributes, FileWriter& wrapperFile, + std::vector& functionNames) const; + +private: + + // Creates a single global function - all in same namespace + void generateSingleFunction(const std::string& toolboxPath, const std::string& wrapperName, + const TypeAttributesTable& typeAttributes, FileWriter& wrapperFile, + std::vector& functionNames) const; + +}; + +} // \namespace wrap + + + + diff --git a/wrap/Method.cpp b/wrap/Method.cpp index 3d53956f1..e4def9bc0 100644 --- a/wrap/Method.cpp +++ b/wrap/Method.cpp @@ -12,12 +12,14 @@ /** * @file Method.ccp * @author Frank Dellaert + * @author Richard Roberts **/ #include #include #include +#include #include "Method.h" #include "utilities.h" @@ -26,45 +28,146 @@ using namespace std; using namespace wrap; /* ************************************************************************* */ -void Method::matlab_mfile(const string& classPath) const { +void Method::addOverload(bool verbose, bool is_const, const std::string& name, + const ArgumentList& args, const ReturnValue& retVal) { + this->verbose_ = verbose; + this->is_const_ = is_const; + this->name = name; + this->argLists.push_back(args); + this->returnVals.push_back(retVal); +} - // open destination m-file - string wrapperFile = classPath + "/" + name + ".m"; - FileWriter file(wrapperFile, verbose_); +void Method::proxy_wrapper_fragments(FileWriter& proxyFile, FileWriter& wrapperFile, + const string& cppClassName, + const std::string& matlabQualName, + const std::string& matlabUniqueName, + const string& wrapperName, + const TypeAttributesTable& typeAttributes, + vector& functionNames) const { - // generate code - string returnType = returnVal.matlab_returnType(); - file.oss << "function " << returnType << " = " << name << "(obj"; - if (args.size()) file.oss << "," << args.names(); - file.oss << ")" << endl; - file.oss << "% usage: obj." << name << "(" << args.names() << ")" << endl; - file.oss << " error('need to compile " << name << ".cpp');" << endl; - file.oss << "end" << endl; + proxyFile.oss << " function varargout = " << name << "(this, varargin)\n"; + //Comments for documentation + string up_name = boost::to_upper_copy(name); + proxyFile.oss << " % " << up_name << " usage:"; + unsigned int argLCount = 0; + BOOST_FOREACH(ArgumentList argList, argLists) + { + proxyFile.oss << " " << name << "("; + unsigned int i = 0; + BOOST_FOREACH(const Argument& arg, argList) + { + if(i != argList.size()-1) + proxyFile.oss << arg.type << " " << arg.name << ", "; + else + proxyFile.oss << arg.type << " " << arg.name; + i++; + } + if(argLCount != argLists.size()-1) + proxyFile.oss << "), "; + else + proxyFile.oss << ") : returns " << returnVals[0].return_type(false, returnVals[0].pair) << endl; + argLCount++; + } - // close file - file.emit(true); + proxyFile.oss << " % " << "Doxygen can be found at http://research.cc.gatech.edu/borg/sites/edu.borg/html/index.html" << endl; + proxyFile.oss << " % " << "" << endl; + proxyFile.oss << " % " << "Method Overloads" << endl; + BOOST_FOREACH(ArgumentList argList, argLists) + { + proxyFile.oss << " % " << name << "("; + unsigned int i = 0; + BOOST_FOREACH(const Argument& arg, argList) + { + if(i != argList.size()-1) + proxyFile.oss << arg.type << " " << arg.name << ", "; + else + proxyFile.oss << arg.type << " " << arg.name; + i++; + } + proxyFile.oss << ")" << endl; + } + + for(size_t overload = 0; overload < argLists.size(); ++overload) { + const ArgumentList& args = argLists[overload]; + const ReturnValue& returnVal = returnVals[overload]; + size_t nrArgs = args.size(); + + const int id = functionNames.size(); + + // Output proxy matlab code + + // check for number of arguments... + proxyFile.oss << " " << (overload==0?"":"else") << "if length(varargin) == " << nrArgs; + if (nrArgs>0) proxyFile.oss << " && "; + // ...and their types + bool first = true; + for(size_t i=0;i& using_namespaces, const std::vector& includes) const { - // open destination wrapperFile - string wrapperFile = classPath + "/" + name + ".cpp"; - FileWriter file(wrapperFile, verbose_, "//"); + const string& matlabUniqueName, + int overload, + int id, + const TypeAttributesTable& typeAttributes) const { // generate code - // header - generateIncludes(file, className, includes); - generateUsingNamespace(file, using_namespaces); + const string wrapFunctionName = matlabUniqueName + "_" + name + "_" + boost::lexical_cast(id); - // call - file.oss << "void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[])\n"; - // start - file.oss << "{\n"; + const ArgumentList& args = argLists[overload]; + const ReturnValue& returnVal = returnVals[overload]; + + // call + file.oss << "void " << wrapFunctionName << "(int nargout, mxArray *out[], int nargin, const mxArray *in[])\n"; + // start + file.oss << "{\n"; + + if(returnVal.isPair) + { + if(returnVal.category1 == ReturnValue::CLASS) + file.oss << " typedef boost::shared_ptr<" << returnVal.qualifiedType1("::") << "> Shared" << returnVal.type1 << ";"<< endl; + if(returnVal.category2 == ReturnValue::CLASS) + file.oss << " typedef boost::shared_ptr<" << returnVal.qualifiedType2("::") << "> Shared" << returnVal.type2 << ";"<< endl; + } + else + if(returnVal.category1 == ReturnValue::CLASS) + file.oss << " typedef boost::shared_ptr<" << returnVal.qualifiedType1("::") << "> Shared" << returnVal.type1 << ";"<< endl; + + file.oss << " typedef boost::shared_ptr<" << cppClassName << "> Shared;" << endl; // check arguments // extra argument obj -> nargin-1 is passed ! @@ -73,28 +176,21 @@ void Method::matlab_wrapper(const string& classPath, // get class pointer // example: shared_ptr = unwrap_shared_ptr< Test >(in[0], "Test"); - file.oss << " shared_ptr<" << cppClassName << "> self = unwrap_shared_ptr< " << cppClassName - << " >(in[0],\"" << matlabClassName << "\");" << endl; - + file.oss << " Shared obj = unwrap_shared_ptr<" << cppClassName << ">(in[0], \"ptr_" << matlabUniqueName << "\");" << endl; // unwrap arguments, see Argument.cpp args.matlab_unwrap(file,1); - // call method - // example: bool result = self->return_field(t); - file.oss << " "; + // call method and wrap result + // example: out[0]=wrap(self->return_field(t)); if (returnVal.type1!="void") - file.oss << returnVal.return_type(true,ReturnValue::pair) << " result = "; - file.oss << "self->" << name << "(" << args.names() << ");\n"; - - // wrap result - // example: out[0]=wrap(result); - returnVal.wrap_result(file); + returnVal.wrap_result("obj->"+name+"("+args.names()+")", file, typeAttributes); + else + file.oss << " obj->"+name+"("+args.names()+");\n"; // finish file.oss << "}\n"; - // close file - file.emit(true); + return wrapFunctionName; } /* ************************************************************************* */ diff --git a/wrap/Method.h b/wrap/Method.h index bcfac82e3..0b17e690e 100644 --- a/wrap/Method.h +++ b/wrap/Method.h @@ -13,6 +13,7 @@ * @file Method.h * @brief describes and generates code for methods * @author Frank Dellaert + * @author Richard Roberts **/ #pragma once @@ -22,6 +23,8 @@ #include "Argument.h" #include "ReturnValue.h" +#include "TypeAttributesTable.h" +#include namespace wrap { @@ -30,25 +33,35 @@ struct Method { /// Constructor creates empty object Method(bool verbose = true) : - verbose_(verbose) {} + verbose_(verbose), is_const_(false) {} // Then the instance variables are set directly by the Module constructor bool verbose_; bool is_const_; std::string name; - ArgumentList args; - ReturnValue returnVal; + std::vector argLists; + std::vector returnVals; + + // The first time this function is called, it initializes the class members + // with those in rhs, but in subsequent calls it adds additional argument + // lists as function overloads. + void addOverload(bool verbose, bool is_const, const std::string& name, + const ArgumentList& args, const ReturnValue& retVal); // MATLAB code generation // classPath is class directory, e.g., ../matlab/@Point2 + void proxy_wrapper_fragments(FileWriter& proxyFile, FileWriter& wrapperFile, + const std::string& cppClassName, const std::string& matlabQualName, const std::string& matlabUniqueName, + const std::string& wrapperName, const TypeAttributesTable& typeAttributes, + std::vector& functionNames) const; - void matlab_mfile(const std::string& classPath) const; ///< m-file - void matlab_wrapper(const std::string& classPath, - const std::string& className, +private: + std::string wrapper_fragment(FileWriter& file, const std::string& cppClassName, - const std::string& matlabClassname, - const std::vector& using_namespaces, - const std::vector& includes) const; ///< cpp wrapper + const std::string& matlabUniqueName, + int overload, + int id, + const TypeAttributesTable& typeAttributes) const; ///< cpp wrapper }; } // \namespace wrap diff --git a/wrap/Module.cpp b/wrap/Module.cpp index dfd781016..aad533a9a 100644 --- a/wrap/Module.cpp +++ b/wrap/Module.cpp @@ -1,380 +1,664 @@ -/* ---------------------------------------------------------------------------- +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file Module.ccp + * @author Frank Dellaert + * @author Alex Cunningham + * @author Andrew Melim + * @author Richard Roberts + **/ + +#include "Module.h" +#include "FileWriter.h" +#include "TypeAttributesTable.h" +#include "utilities.h" +#include "spirit_actors.h" + +//#define BOOST_SPIRIT_DEBUG +#include +#include +#include +#include +#include +#include +#include +#include +#include + +#include +#include + +using namespace std; +using namespace wrap; +using namespace BOOST_SPIRIT_CLASSIC_NS; +namespace bl = boost::lambda; +namespace fs = boost::filesystem; + +typedef rule Rule; + +/* ************************************************************************* */ +// We parse an interface file into a Module object. +// The grammar is defined using the boost/spirit combinatorial parser. +// For example, str_p("const") parses the string "const", and the >> +// operator creates a sequence parser. The grammar below, composed of rules +// and with start rule [class_p], doubles as the specs for our interface files. +/* ************************************************************************* */ + +/* ************************************************************************* */ +void handle_possible_template(vector& classes, const Class& cls, const string& templateArgument, const vector >& instantiations) { + if(instantiations.empty()) { + classes.push_back(cls); + } else { + vector classInstantiations = cls.expandTemplate(templateArgument, instantiations); + BOOST_FOREACH(const Class& c, classInstantiations) { + classes.push_back(c); + } + } +} + +/* ************************************************************************* */ +Module::Module(const string& interfacePath, + const string& moduleName, bool enable_verbose) : name(moduleName), verbose(enable_verbose) +{ + // these variables will be imperatively updated to gradually build [cls] + // The one with postfix 0 are used to reset the variables after parse. + string methodName, methodName0; + bool isConst, isConst0 = false; + ReturnValue retVal0, retVal; + Argument arg0, arg; + ArgumentList args0, args; + vector arg_dup; ///keep track of duplicates + Constructor constructor0(enable_verbose), constructor(enable_verbose); + Deconstructor deconstructor0(enable_verbose), deconstructor(enable_verbose); + StaticMethod static_method0(enable_verbose), static_method(enable_verbose); + Class cls0(enable_verbose),cls(enable_verbose); + GlobalFunction globalFunc0(enable_verbose), globalFunc(enable_verbose); + ForwardDeclaration fwDec0, fwDec; + vector namespaces, /// current namespace tag + namespaces_return; /// namespace for current return type + string templateArgument; + vector templateInstantiationNamespace; + vector > templateInstantiations; + TemplateInstantiationTypedef singleInstantiation, singleInstantiation0; + string include_path = ""; + const string null_str = ""; + + //---------------------------------------------------------------------------- + // Grammar with actions that build the Class object. Actions are + // defined within the square brackets [] and are executed whenever a + // rule is successfully parsed. Define BOOST_SPIRIT_DEBUG to debug. + // The grammar is allows a very restricted C++ header + // lexeme_d turns off white space skipping + // http://www.boost.org/doc/libs/1_37_0/libs/spirit/classic/doc/directives.html + // ---------------------------------------------------------------------------- + + Rule comments_p = comment_p("/*", "*/") | comment_p("//", eol_p); + + Rule basisType_p = + (str_p("string") | "bool" | "size_t" | "int" | "double" | "char" | "unsigned char"); + + Rule keywords_p = + (str_p("const") | "static" | "namespace" | basisType_p); + + Rule eigenType_p = + (str_p("Vector") | "Matrix"); + + Rule className_p = (lexeme_d[upper_p >> *(alnum_p | '_')] - eigenType_p - keywords_p); + + Rule namespace_name_p = lexeme_d[lower_p >> *(alnum_p | '_')] - keywords_p; + + Rule namespace_arg_p = namespace_name_p[push_back_a(arg.namespaces)] >> str_p("::"); + + Rule argEigenType_p = + eigenType_p[assign_a(arg.type)] >> + !ch_p('*')[assign_a(arg.is_ptr,true)]; + + Rule eigenRef_p = + !str_p("const") [assign_a(arg.is_const,true)] >> + eigenType_p [assign_a(arg.type)] >> + ch_p('&') [assign_a(arg.is_ref,true)]; + + Rule classArg_p = + !str_p("const") [assign_a(arg.is_const,true)] >> + *namespace_arg_p >> + className_p[assign_a(arg.type)] >> + (ch_p('*')[assign_a(arg.is_ptr,true)] | ch_p('&')[assign_a(arg.is_ref,true)]); + + Rule name_p = lexeme_d[alpha_p >> *(alnum_p | '_')]; + + Rule classParent_p = + *(namespace_name_p[push_back_a(cls.qualifiedParent)] >> str_p("::")) >> + className_p[push_back_a(cls.qualifiedParent)]; + + Rule templateInstantiation_p = + (*(namespace_name_p[push_back_a(templateInstantiationNamespace)] >> str_p("::")) >> + className_p[push_back_a(templateInstantiationNamespace)]) + [push_back_a(templateInstantiations, templateInstantiationNamespace)] + [clear_a(templateInstantiationNamespace)]; + + Rule templateInstantiations_p = + (str_p("template") >> + '<' >> name_p[assign_a(templateArgument)] >> '=' >> '{' >> + !(templateInstantiation_p >> *(',' >> templateInstantiation_p)) >> + '}' >> '>') + [push_back_a(cls.templateArgs, templateArgument)]; + + Rule templateSingleInstantiationArg_p = + (*(namespace_name_p[push_back_a(templateInstantiationNamespace)] >> str_p("::")) >> + className_p[push_back_a(templateInstantiationNamespace)]) + [push_back_a(singleInstantiation.typeList, templateInstantiationNamespace)] + [clear_a(templateInstantiationNamespace)]; + + Rule templateSingleInstantiation_p = + (str_p("typedef") >> + *(namespace_name_p[push_back_a(singleInstantiation.classNamespaces)] >> str_p("::")) >> + className_p[assign_a(singleInstantiation.className)] >> + '<' >> templateSingleInstantiationArg_p >> *(',' >> templateSingleInstantiationArg_p) >> + '>' >> + className_p[assign_a(singleInstantiation.name)] >> + ';') + [assign_a(singleInstantiation.namespaces, namespaces)] + [push_back_a(templateInstantiationTypedefs, singleInstantiation)] + [assign_a(singleInstantiation, singleInstantiation0)]; + + Rule templateList_p = + (str_p("template") >> + '<' >> name_p[push_back_a(cls.templateArgs)] >> *(',' >> name_p[push_back_a(cls.templateArgs)]) >> + '>'); + + Rule argument_p = + ((basisType_p[assign_a(arg.type)] | argEigenType_p | eigenRef_p | classArg_p) + >> name_p[assign_a(arg.name)]) + [push_back_a(args, arg)] + [assign_a(arg,arg0)]; + + Rule argumentList_p = !argument_p >> * (',' >> argument_p); + + Rule constructor_p = + (className_p >> '(' >> argumentList_p >> ')' >> ';' >> !comments_p) + [push_back_a(constructor.args_list, args)] + [assign_a(args,args0)]; + //[assign_a(constructor.args,args)] + //[assign_a(constructor.name,cls.name)] + //[push_back_a(cls.constructors, constructor)] + //[assign_a(constructor,constructor0)]; + + Rule namespace_ret_p = namespace_name_p[push_back_a(namespaces_return)] >> str_p("::"); + + Rule returnType1_p = + (basisType_p[assign_a(retVal.type1)][assign_a(retVal.category1, ReturnValue::BASIS)]) | + ((*namespace_ret_p)[assign_a(retVal.namespaces1, namespaces_return)][clear_a(namespaces_return)] + >> (className_p[assign_a(retVal.type1)][assign_a(retVal.category1, ReturnValue::CLASS)]) >> + !ch_p('*')[assign_a(retVal.isPtr1,true)]) | + (eigenType_p[assign_a(retVal.type1)][assign_a(retVal.category1, ReturnValue::EIGEN)]); + + Rule returnType2_p = + (basisType_p[assign_a(retVal.type2)][assign_a(retVal.category2, ReturnValue::BASIS)]) | + ((*namespace_ret_p)[assign_a(retVal.namespaces2, namespaces_return)][clear_a(namespaces_return)] + >> (className_p[assign_a(retVal.type2)][assign_a(retVal.category2, ReturnValue::CLASS)]) >> + !ch_p('*') [assign_a(retVal.isPtr2,true)]) | + (eigenType_p[assign_a(retVal.type2)][assign_a(retVal.category2, ReturnValue::EIGEN)]); + + Rule pair_p = + (str_p("pair") >> '<' >> returnType1_p >> ',' >> returnType2_p >> '>') + [assign_a(retVal.isPair,true)]; + + Rule void_p = str_p("void")[assign_a(retVal.type1)]; + + Rule returnType_p = void_p | returnType1_p | pair_p; + + Rule methodName_p = lexeme_d[lower_p >> *(alnum_p | '_')]; + + Rule method_p = + (returnType_p >> methodName_p[assign_a(methodName)] >> + '(' >> argumentList_p >> ')' >> + !str_p("const")[assign_a(isConst,true)] >> ';' >> *comments_p) + [bl::bind(&Method::addOverload, + bl::var(cls.methods)[bl::var(methodName)], + verbose, + bl::var(isConst), + bl::var(methodName), + bl::var(args), + bl::var(retVal))] + [assign_a(isConst,isConst0)] + [assign_a(methodName,methodName0)] + [assign_a(args,args0)] + [assign_a(retVal,retVal0)]; + + Rule staticMethodName_p = lexeme_d[(upper_p | lower_p) >> *(alnum_p | '_')]; + + Rule static_method_p = + (str_p("static") >> returnType_p >> staticMethodName_p[assign_a(methodName)] >> + '(' >> argumentList_p >> ')' >> ';' >> *comments_p) + [bl::bind(&StaticMethod::addOverload, + bl::var(cls.static_methods)[bl::var(methodName)], + verbose, + bl::var(methodName), + bl::var(args), + bl::var(retVal))] + [assign_a(methodName,methodName0)] + [assign_a(args,args0)] + [assign_a(retVal,retVal0)]; + + Rule functions_p = constructor_p | method_p | static_method_p; + + Rule class_p = + (str_p("")[assign_a(cls,cls0)]) + >> (!(templateInstantiations_p | templateList_p) + >> !(str_p("virtual")[assign_a(cls.isVirtual, true)]) + >> str_p("class") + >> className_p[assign_a(cls.name)] + >> ((':' >> classParent_p >> '{') | '{') + >> *(functions_p | comments_p) + >> str_p("};")) + [assign_a(constructor.name, cls.name)] + [assign_a(cls.constructor, constructor)] + [assign_a(cls.namespaces, namespaces)] + [assign_a(deconstructor.name,cls.name)] + [assign_a(cls.deconstructor, deconstructor)] + [bl::bind(&handle_possible_template, bl::var(classes), bl::var(cls), bl::var(templateArgument), bl::var(templateInstantiations))] + [assign_a(deconstructor,deconstructor0)] + [assign_a(constructor, constructor0)] + [assign_a(cls,cls0)] + [clear_a(templateArgument)] + [clear_a(templateInstantiations)]; + + Rule global_function_p = + (returnType_p >> staticMethodName_p[assign_a(methodName)] >> + '(' >> argumentList_p >> ')' >> ';' >> *comments_p) + [bl::bind(&GlobalFunction::addOverload, + bl::var(global_functions)[bl::var(methodName)], + verbose, + bl::var(methodName), + bl::var(args), + bl::var(retVal), + bl::var(namespaces))] + [assign_a(methodName,methodName0)] + [assign_a(args,args0)] + [assign_a(retVal,retVal0)]; + + Rule include_p = str_p("#include") >> ch_p('<') >> (*(anychar_p - '>'))[push_back_a(includes)] >> ch_p('>'); + + Rule namespace_def_p = + (str_p("namespace") + >> namespace_name_p[push_back_a(namespaces)] + >> ch_p('{') + >> *(include_p | class_p | templateSingleInstantiation_p | global_function_p | namespace_def_p | comments_p) + >> ch_p('}')) + [pop_a(namespaces)]; + + Rule forward_declaration_p = + !(str_p("virtual")[assign_a(fwDec.isVirtual, true)]) + >> str_p("class") + >> (*(namespace_name_p >> str_p("::")) >> className_p)[assign_a(fwDec.name)] + >> ch_p(';') + [push_back_a(forward_declarations, fwDec)] + [assign_a(fwDec, fwDec0)]; + + Rule module_content_p = comments_p | include_p | class_p | templateSingleInstantiation_p | forward_declaration_p | global_function_p | namespace_def_p; + + Rule module_p = *module_content_p >> !end_p; + + //---------------------------------------------------------------------------- + // for debugging, define BOOST_SPIRIT_DEBUG +# ifdef BOOST_SPIRIT_DEBUG + BOOST_SPIRIT_DEBUG_NODE(className_p); + BOOST_SPIRIT_DEBUG_NODE(classPtr_p); + BOOST_SPIRIT_DEBUG_NODE(classRef_p); + BOOST_SPIRIT_DEBUG_NODE(basisType_p); + BOOST_SPIRIT_DEBUG_NODE(name_p); + BOOST_SPIRIT_DEBUG_NODE(argument_p); + BOOST_SPIRIT_DEBUG_NODE(argumentList_p); + BOOST_SPIRIT_DEBUG_NODE(constructor_p); + BOOST_SPIRIT_DEBUG_NODE(returnType1_p); + BOOST_SPIRIT_DEBUG_NODE(returnType2_p); + BOOST_SPIRIT_DEBUG_NODE(pair_p); + BOOST_SPIRIT_DEBUG_NODE(void_p); + BOOST_SPIRIT_DEBUG_NODE(returnType_p); + BOOST_SPIRIT_DEBUG_NODE(methodName_p); + BOOST_SPIRIT_DEBUG_NODE(method_p); + BOOST_SPIRIT_DEBUG_NODE(class_p); + BOOST_SPIRIT_DEBUG_NODE(namespace_def_p); + BOOST_SPIRIT_DEBUG_NODE(module_p); +# endif + //---------------------------------------------------------------------------- + + // read interface file + string interfaceFile = interfacePath + "/" + moduleName + ".h"; + string contents = file_contents(interfaceFile); + + // and parse contents + parse_info info = parse(contents.c_str(), module_p, space_p); + if(!info.full) { + printf("parsing stopped at \n%.20s\n",info.stop); + throw ParseFailed((int)info.length); + } - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + //Explicitly add methods to the classes from parents so it shows in documentation + BOOST_FOREACH(Class& cls, classes) + { + map inhereted = appendInheretedMethods(cls, classes); + cls.methods.insert(inhereted.begin(), inhereted.end()); + } - * See LICENSE for the license information - * -------------------------------------------------------------------------- */ +} + +/* ************************************************************************* */ +template +void verifyArguments(const vector& validArgs, const map& vt) { + typedef typename map::value_type Name_Method; + BOOST_FOREACH(const Name_Method& name_method, vt) { + const T& t = name_method.second; + BOOST_FOREACH(const ArgumentList& argList, t.argLists) { + BOOST_FOREACH(Argument arg, argList) { + string fullType = arg.qualifiedType("::"); + if(find(validArgs.begin(), validArgs.end(), fullType) + == validArgs.end()) + throw DependencyMissing(fullType, t.name); + } + } + } +} + +/* ************************************************************************* */ +template +void verifyReturnTypes(const vector& validtypes, const map& vt) { + typedef typename map::value_type Name_Method; + BOOST_FOREACH(const Name_Method& name_method, vt) { + const T& t = name_method.second; + BOOST_FOREACH(const ReturnValue& retval, t.returnVals) { + if (find(validtypes.begin(), validtypes.end(), retval.qualifiedType1("::")) == validtypes.end()) + throw DependencyMissing(retval.qualifiedType1("::"), t.name); + if (retval.isPair && find(validtypes.begin(), validtypes.end(), retval.qualifiedType2("::")) == validtypes.end()) + throw DependencyMissing(retval.qualifiedType2("::"), t.name); + } + } +} + +/* ************************************************************************* */ +void Module::generateIncludes(FileWriter& file) const { + + // collect includes + vector all_includes(includes); + + // sort and remove duplicates + sort(all_includes.begin(), all_includes.end()); + vector::const_iterator last_include = unique(all_includes.begin(), all_includes.end()); + vector::const_iterator it = all_includes.begin(); + // add includes to file + for (; it != last_include; ++it) + file.oss << "#include <" << *it << ">" << endl; + file.oss << "\n"; +} + +/* ************************************************************************* */ +void Module::matlab_code(const string& toolboxPath, const string& headerPath) const { + + fs::create_directories(toolboxPath); + + // create the unified .cpp switch file + const string wrapperName = name + "_wrapper"; + string wrapperFileName = toolboxPath + "/" + wrapperName + ".cpp"; + FileWriter wrapperFile(wrapperFileName, verbose, "//"); + vector functionNames; // Function names stored by index for switch + wrapperFile.oss << "#include \n"; + wrapperFile.oss << "#include \n"; + wrapperFile.oss << "#include \n"; + wrapperFile.oss << "\n"; + + // Expand templates - This is done first so that template instantiations are + // counted in the list of valid types, have their attributes and dependencies + // checked, etc. + vector expandedClasses = ExpandTypedefInstantiations(classes, templateInstantiationTypedefs); + + // Dependency check list + vector validTypes = GenerateValidTypes(expandedClasses, forward_declarations); + + // Check that all classes have been defined somewhere + verifyArguments(validTypes, global_functions); + verifyReturnTypes(validTypes, global_functions); + + BOOST_FOREACH(const Class& cls, expandedClasses) { + // verify all of the function arguments + //TODO:verifyArguments(validTypes, cls.constructor.args_list); + verifyArguments(validTypes, cls.static_methods); + verifyArguments(validTypes, cls.methods); + + // verify function return types + verifyReturnTypes(validTypes, cls.static_methods); + verifyReturnTypes(validTypes, cls.methods); + + // verify parents + if(!cls.qualifiedParent.empty() && std::find(validTypes.begin(), validTypes.end(), wrap::qualifiedName("::", cls.qualifiedParent)) == validTypes.end()) + throw DependencyMissing(wrap::qualifiedName("::", cls.qualifiedParent), cls.qualifiedName("::")); -/** - * @file Module.ccp - * @author Frank Dellaert - * @author Alex Cunningham - * @author Andrew Melim - **/ - -#include "Module.h" -#include "FileWriter.h" -#include "utilities.h" -#include "spirit_actors.h" - -//#define BOOST_SPIRIT_DEBUG -#include -#include -#include - -#include - -using namespace std; -using namespace wrap; -using namespace BOOST_SPIRIT_CLASSIC_NS; - -typedef rule Rule; - -/* ************************************************************************* */ -// We parse an interface file into a Module object. -// The grammar is defined using the boost/spirit combinatorial parser. -// For example, str_p("const") parses the string "const", and the >> -// operator creates a sequence parser. The grammar below, composed of rules -// and with start rule [class_p], doubles as the specs for our interface files. -/* ************************************************************************* */ - -Module::Module(const string& interfacePath, - const string& moduleName, bool enable_verbose) : name(moduleName), verbose(enable_verbose) + } + + // Create type attributes table and check validity + TypeAttributesTable typeAttributes; + typeAttributes.addClasses(expandedClasses); + typeAttributes.addForwardDeclarations(forward_declarations); + typeAttributes.checkValidity(expandedClasses); + + // Generate includes while avoiding redundant includes + generateIncludes(wrapperFile); + + // create typedef classes - we put this at the top of the wrap file so that collectors and method arguments can use these typedefs + BOOST_FOREACH(const Class& cls, expandedClasses) { + if(!cls.typedefName.empty()) + wrapperFile.oss << cls.getTypedef() << "\n"; + } + wrapperFile.oss << "\n"; + + // Generate collectors and cleanup function to be called from mexAtExit + WriteCollectorsAndCleanupFcn(wrapperFile, name, expandedClasses); + + // generate RTTI registry (for returning derived-most types) + WriteRTTIRegistry(wrapperFile, name, expandedClasses); + + // create proxy class and wrapper code + BOOST_FOREACH(const Class& cls, expandedClasses) { + cls.matlab_proxy(toolboxPath, wrapperName, typeAttributes, wrapperFile, functionNames); + } + + // create matlab files and wrapper code for global functions + BOOST_FOREACH(const GlobalFunctions::value_type& p, global_functions) { + p.second.matlab_proxy(toolboxPath, wrapperName, typeAttributes, wrapperFile, functionNames); + } + + // finish wrapper file + wrapperFile.oss << "\n"; + finish_wrapper(wrapperFile, functionNames); + + wrapperFile.emit(true); + } +/* ************************************************************************* */ +map Module::appendInheretedMethods(const Class& cls, const vector& classes) { - // these variables will be imperatively updated to gradually build [cls] - // The one with postfix 0 are used to reset the variables after parse. - ReturnValue retVal0, retVal; - Argument arg0, arg; - ArgumentList args0, args; - Constructor constructor0(enable_verbose), constructor(enable_verbose); - Deconstructor deconstructor0(enable_verbose), deconstructor(enable_verbose); - Method method0(enable_verbose), method(enable_verbose); - StaticMethod static_method0(enable_verbose), static_method(enable_verbose); - Class cls0(enable_verbose),cls(enable_verbose); - vector namespaces, /// current namespace tag - namespace_includes, /// current set of includes - namespaces_return, /// namespace for current return type - using_namespace_current; /// All namespaces from "using" declarations - string include_path = ""; - string class_name = ""; - const string null_str = ""; - - //---------------------------------------------------------------------------- - // Grammar with actions that build the Class object. Actions are - // defined within the square brackets [] and are executed whenever a - // rule is successfully parsed. Define BOOST_SPIRIT_DEBUG to debug. - // The grammar is allows a very restricted C++ header - // lexeme_d turns off white space skipping - // http://www.boost.org/doc/libs/1_37_0/libs/spirit/classic/doc/directives.html - // ---------------------------------------------------------------------------- - - Rule comments_p = comment_p("/*", "*/") | comment_p("//", eol_p); - - Rule basisType_p = - (str_p("string") | "bool" | "size_t" | "int" | "double" | "char" | "unsigned char"); - - Rule keywords_p = - (str_p("const") | "static" | "namespace" | basisType_p); - - Rule eigenType_p = - (str_p("Vector") | "Matrix"); - - Rule className_p = (lexeme_d[upper_p >> *(alnum_p | '_')] - eigenType_p - keywords_p)[assign_a(class_name)]; - - Rule namespace_name_p = lexeme_d[lower_p >> *(alnum_p | '_')] - keywords_p; - - Rule namespace_arg_p = namespace_name_p[push_back_a(arg.namespaces)] >> str_p("::"); - - Rule argEigenType_p = - eigenType_p[assign_a(arg.type)] >> - !ch_p('*')[assign_a(arg.is_ptr,true)]; - - Rule eigenRef_p = - !str_p("const") [assign_a(arg.is_const,true)] >> - eigenType_p [assign_a(arg.type)] >> - ch_p('&') [assign_a(arg.is_ref,true)]; - - Rule classArg_p = - !str_p("const") [assign_a(arg.is_const,true)] >> - *namespace_arg_p >> - className_p[assign_a(arg.type)] >> - (ch_p('*')[assign_a(arg.is_ptr,true)] | ch_p('&')[assign_a(arg.is_ref,true)]); - - Rule name_p = lexeme_d[alpha_p >> *(alnum_p | '_')]; - - Rule argument_p = - ((basisType_p[assign_a(arg.type)] | argEigenType_p | eigenRef_p | classArg_p) - >> name_p[assign_a(arg.name)]) - [push_back_a(args, arg)] - [assign_a(arg,arg0)]; - - Rule argumentList_p = !argument_p >> * (',' >> argument_p); - - Rule constructor_p = - (className_p >> '(' >> argumentList_p >> ')' >> ';' >> !comments_p) - [assign_a(constructor.args,args)] - [assign_a(constructor.name,cls.name)] - [assign_a(args,args0)] - [push_back_a(cls.constructors, constructor)] - [assign_a(constructor,constructor0)]; - - Rule namespace_ret_p = namespace_name_p[push_back_a(namespaces_return)] >> str_p("::"); - - Rule returnType1_p = - (basisType_p[assign_a(retVal.type1)][assign_a(retVal.category1, ReturnValue::BASIS)]) | - ((*namespace_ret_p)[assign_a(retVal.namespaces1, namespaces_return)][clear_a(namespaces_return)] - >> (className_p[assign_a(retVal.type1)][assign_a(retVal.category1, ReturnValue::CLASS)]) >> - !ch_p('*')[assign_a(retVal.isPtr1,true)]) | - (eigenType_p[assign_a(retVal.type1)][assign_a(retVal.category1, ReturnValue::EIGEN)]); - - Rule returnType2_p = - (basisType_p[assign_a(retVal.type2)][assign_a(retVal.category2, ReturnValue::BASIS)]) | - ((*namespace_ret_p)[assign_a(retVal.namespaces2, namespaces_return)][clear_a(namespaces_return)] - >> (className_p[assign_a(retVal.type2)][assign_a(retVal.category2, ReturnValue::CLASS)]) >> - !ch_p('*') [assign_a(retVal.isPtr2,true)]) | - (eigenType_p[assign_a(retVal.type2)][assign_a(retVal.category2, ReturnValue::EIGEN)]); - - Rule pair_p = - (str_p("pair") >> '<' >> returnType1_p >> ',' >> returnType2_p >> '>') - [assign_a(retVal.isPair,true)]; - - Rule void_p = str_p("void")[assign_a(retVal.type1)]; - - Rule returnType_p = void_p | returnType1_p | pair_p; - - Rule methodName_p = lexeme_d[lower_p >> *(alnum_p | '_')]; - - Rule method_p = - (returnType_p >> methodName_p[assign_a(method.name)] >> - '(' >> argumentList_p >> ')' >> - !str_p("const")[assign_a(method.is_const_,true)] >> ';' >> *comments_p) - [assign_a(method.args,args)] - [assign_a(args,args0)] - [assign_a(method.returnVal,retVal)] - [assign_a(retVal,retVal0)] - [push_back_a(cls.methods, method)] - [assign_a(method,method0)]; - - Rule staticMethodName_p = lexeme_d[(upper_p | lower_p) >> *(alnum_p | '_')]; - - Rule static_method_p = - (str_p("static") >> returnType_p >> staticMethodName_p[assign_a(static_method.name)] >> - '(' >> argumentList_p >> ')' >> ';' >> *comments_p) - [assign_a(static_method.args,args)] - [assign_a(args,args0)] - [assign_a(static_method.returnVal,retVal)] - [assign_a(retVal,retVal0)] - [push_back_a(cls.static_methods, static_method)] - [assign_a(static_method,static_method0)]; - - Rule functions_p = constructor_p | method_p | static_method_p; - - Rule include_p = str_p("#include") >> ch_p('<') >> (*(anychar_p - '>'))[assign_a(include_path)] >> ch_p('>'); - - Rule class_p = - (!include_p - >> str_p("class")[push_back_a(cls.includes, include_path)][assign_a(include_path, null_str)] - >> className_p[assign_a(cls.name)] - >> '{' - >> *(functions_p | comments_p) - >> str_p("};")) - [assign_a(cls.namespaces, namespaces)] - [assign_a(cls.using_namespaces, using_namespace_current)] - [append_a(cls.includes, namespace_includes)] - [assign_a(deconstructor.name,cls.name)] - [assign_a(cls.d, deconstructor)] - [push_back_a(classes,cls)] - [assign_a(deconstructor,deconstructor0)] - [assign_a(cls,cls0)]; - - Rule namespace_def_p = - (!include_p - >> str_p("namespace")[push_back_a(namespace_includes, include_path)][assign_a(include_path, null_str)] - >> namespace_name_p[push_back_a(namespaces)] - >> ch_p('{') - >> *(class_p | namespace_def_p | comments_p) - >> str_p("}///\\namespace") // end namespace, avoid confusion with classes - >> !namespace_name_p) - [pop_a(namespaces)] - [pop_a(namespace_includes)]; - - Rule using_namespace_p = - str_p("using") >> str_p("namespace") - >> namespace_name_p[push_back_a(using_namespace_current)] >> ch_p(';'); - - Rule forward_declaration_p = - str_p("class") >> - (*(namespace_name_p >> str_p("::")) >> className_p)[push_back_a(forward_declarations)] - >> ch_p(';'); - - Rule module_content_p = comments_p | using_namespace_p | class_p | forward_declaration_p | namespace_def_p ; - - Rule module_p = *module_content_p >> !end_p; - - //---------------------------------------------------------------------------- - // for debugging, define BOOST_SPIRIT_DEBUG -# ifdef BOOST_SPIRIT_DEBUG - BOOST_SPIRIT_DEBUG_NODE(className_p); - BOOST_SPIRIT_DEBUG_NODE(classPtr_p); - BOOST_SPIRIT_DEBUG_NODE(classRef_p); - BOOST_SPIRIT_DEBUG_NODE(basisType_p); - BOOST_SPIRIT_DEBUG_NODE(name_p); - BOOST_SPIRIT_DEBUG_NODE(argument_p); - BOOST_SPIRIT_DEBUG_NODE(argumentList_p); - BOOST_SPIRIT_DEBUG_NODE(constructor_p); - BOOST_SPIRIT_DEBUG_NODE(returnType1_p); - BOOST_SPIRIT_DEBUG_NODE(returnType2_p); - BOOST_SPIRIT_DEBUG_NODE(pair_p); - BOOST_SPIRIT_DEBUG_NODE(void_p); - BOOST_SPIRIT_DEBUG_NODE(returnType_p); - BOOST_SPIRIT_DEBUG_NODE(methodName_p); - BOOST_SPIRIT_DEBUG_NODE(method_p); - BOOST_SPIRIT_DEBUG_NODE(class_p); - BOOST_SPIRIT_DEBUG_NODE(namespace_def_p); - BOOST_SPIRIT_DEBUG_NODE(module_p); -# endif - //---------------------------------------------------------------------------- - - // read interface file - string interfaceFile = interfacePath + "/" + moduleName + ".h"; - string contents = file_contents(interfaceFile); - - // and parse contents - parse_info info = parse(contents.c_str(), module_p, space_p); - if(!info.full) { - printf("parsing stopped at \n%.20s\n",info.stop); - throw ParseFailed(info.length); - } -} - -/* ************************************************************************* */ -template -void verifyArguments(const vector& validArgs, const vector& vt) { - BOOST_FOREACH(const T& t, vt) { - BOOST_FOREACH(Argument arg, t.args) { - string fullType = arg.qualifiedType("::"); - if(find(validArgs.begin(), validArgs.end(), fullType) - == validArgs.end()) - throw DependencyMissing(fullType, t.name); - } - } -} - -/* ************************************************************************* */ -template -void verifyReturnTypes(const vector& validtypes, const vector& vt) { - BOOST_FOREACH(const T& t, vt) { - const ReturnValue& retval = t.returnVal; - if (find(validtypes.begin(), validtypes.end(), retval.qualifiedType1("::")) == validtypes.end()) - throw DependencyMissing(retval.qualifiedType1("::"), t.name); - if (retval.isPair && find(validtypes.begin(), validtypes.end(), retval.qualifiedType2("::")) == validtypes.end()) - throw DependencyMissing(retval.qualifiedType2("::"), t.name); - } -} - -/* ************************************************************************* */ -void Module::matlab_code(const string& toolboxPath, - const string& mexExt, const string& mexFlags) const { - string installCmd = "install -d " + toolboxPath; - system(installCmd.c_str()); - - // create make m-file - string matlabMakeFileName = toolboxPath + "/make_" + name + ".m"; - FileWriter makeModuleMfile(matlabMakeFileName, verbose, "%"); - - // create the (actual) make file - string makeFileName = toolboxPath + "/Makefile"; - FileWriter makeModuleMakefile(makeFileName, verbose, "#"); - - makeModuleMfile.oss << "echo on" << endl << endl; - makeModuleMfile.oss << "toolboxpath = mfilename('fullpath');" << endl; - makeModuleMfile.oss << "delims = find(toolboxpath == '/');" << endl; - makeModuleMfile.oss << "toolboxpath = toolboxpath(1:(delims(end)-1));" << endl; - makeModuleMfile.oss << "clear delims" << endl; - makeModuleMfile.oss << "addpath(toolboxpath);" << endl << endl; - - makeModuleMakefile.oss << "\nMEX = mex\n"; - makeModuleMakefile.oss << "MEXENDING = " << mexExt << "\n"; - makeModuleMakefile.oss << "mex_flags = " << mexFlags << "\n\n"; - - // Dependency check list - vector validTypes = forward_declarations; - validTypes.push_back("void"); - validTypes.push_back("string"); - validTypes.push_back("int"); - validTypes.push_back("bool"); - validTypes.push_back("char"); - validTypes.push_back("unsigned char"); - validTypes.push_back("size_t"); - validTypes.push_back("double"); - validTypes.push_back("Vector"); - validTypes.push_back("Matrix"); - - // add 'all' to Makefile - makeModuleMakefile.oss << "all: "; - BOOST_FOREACH(Class cls, classes) { - makeModuleMakefile.oss << cls.qualifiedName() << " "; - //Create a list of parsed classes for dependency checking - validTypes.push_back(cls.qualifiedName("::")); + map methods; + if(!cls.qualifiedParent.empty()) + { + cout << "Class: " << cls.name << " Parent Name: " << cls.qualifiedParent.back() << endl; + //Find Class + BOOST_FOREACH(const Class& parent, classes) + { + //We found the class for our parent + if(parent.name == cls.qualifiedParent.back()) + { + cout << "Inner class: " << cls.qualifiedParent.back() << endl; + Methods inhereted = appendInheretedMethods(parent, classes); + methods.insert(inhereted.begin(), inhereted.end()); + } + } + } + else + { + cout << "Dead end: " << cls.name << endl; + methods.insert(cls.methods.begin(), cls.methods.end()); } - makeModuleMakefile.oss << "\n\n"; - // generate proxy classes and wrappers - BOOST_FOREACH(Class cls, classes) { - // create directory if needed - string classPath = toolboxPath + "/@" + cls.qualifiedName(); - string installCmd = "install -d " + classPath; - system(installCmd.c_str()); - - // create proxy class - string classFile = classPath + "/" + cls.qualifiedName() + ".m"; - cls.matlab_proxy(classFile); - - // verify all of the function arguments - verifyArguments(validTypes, cls.constructors); - verifyArguments(validTypes, cls.static_methods); - verifyArguments(validTypes, cls.methods); - - // verify function return types - verifyReturnTypes(validTypes, cls.static_methods); - verifyReturnTypes(validTypes, cls.methods); - - // create constructor and method wrappers - cls.matlab_constructors(toolboxPath); - cls.matlab_static_methods(toolboxPath); - cls.matlab_methods(classPath); - - // create deconstructor - cls.matlab_deconstructor(toolboxPath); - - // add lines to make m-file - makeModuleMfile.oss << "%% " << cls.qualifiedName() << endl; - makeModuleMfile.oss << "cd(toolboxpath)" << endl; - cls.matlab_make_fragment(makeModuleMfile, toolboxPath, mexFlags); - - // add section to the (actual) make file - makeModuleMakefile.oss << "# " << cls.qualifiedName() << endl; - cls.makefile_fragment(makeModuleMakefile); - } - - // finish make m-file - makeModuleMfile.oss << "cd(toolboxpath)" << endl << endl; - makeModuleMfile.oss << "echo off" << endl; - makeModuleMfile.emit(true); // By default, compare existing file first - - // make clean at end of Makefile - makeModuleMakefile.oss << "\n\nclean: \n"; - makeModuleMakefile.oss << "\trm -rf *.$(MEXENDING)\n"; - BOOST_FOREACH(Class cls, classes) - makeModuleMakefile.oss << "\trm -rf @" << cls.qualifiedName() << "/*.$(MEXENDING)\n"; - - // finish Makefile - makeModuleMakefile.oss << "\n" << endl; - makeModuleMakefile.emit(true); - } - -/* ************************************************************************* */ + return methods; +} + +/* ************************************************************************* */ + void Module::finish_wrapper(FileWriter& file, const std::vector& functionNames) const { + file.oss << "void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[])\n"; + file.oss << "{\n"; + file.oss << " mstream mout;\n"; // Send stdout to MATLAB console + file.oss << " std::streambuf *outbuf = std::cout.rdbuf(&mout);\n\n"; + file.oss << " _" << name << "_RTTIRegister();\n\n"; + file.oss << " int id = unwrap(in[0]);\n\n"; + file.oss << " try {\n"; + file.oss << " switch(id) {\n"; + for(size_t id = 0; id < functionNames.size(); ++id) { + file.oss << " case " << id << ":\n"; + file.oss << " " << functionNames[id] << "(nargout, out, nargin-1, in+1);\n"; + file.oss << " break;\n"; + } + file.oss << " }\n"; + file.oss << " } catch(const std::exception& e) {\n"; + file.oss << " mexErrMsgTxt((\"Exception from gtsam:\\n\" + std::string(e.what()) + \"\\n\").c_str());\n"; + file.oss << " }\n"; + file.oss << "\n"; + file.oss << " std::cout.rdbuf(outbuf);\n"; // Restore cout + file.oss << "}\n"; + } + +/* ************************************************************************* */ +vector Module::ExpandTypedefInstantiations(const vector& classes, const vector instantiations) { + + vector expandedClasses = classes; + + BOOST_FOREACH(const TemplateInstantiationTypedef& inst, instantiations) { + // Add the new class to the list + expandedClasses.push_back(inst.findAndExpand(classes)); + } + + // Remove all template classes + for(size_t i = 0; i < expandedClasses.size(); ++i) + if(!expandedClasses[size_t(i)].templateArgs.empty()) { + expandedClasses.erase(expandedClasses.begin() + size_t(i)); + -- i; + } + + return expandedClasses; +} + +/* ************************************************************************* */ +vector Module::GenerateValidTypes(const vector& classes, const vector forwardDeclarations) { + vector validTypes; + BOOST_FOREACH(const ForwardDeclaration& fwDec, forwardDeclarations) { + validTypes.push_back(fwDec.name); + } + validTypes.push_back("void"); + validTypes.push_back("string"); + validTypes.push_back("int"); + validTypes.push_back("bool"); + validTypes.push_back("char"); + validTypes.push_back("unsigned char"); + validTypes.push_back("size_t"); + validTypes.push_back("double"); + validTypes.push_back("Vector"); + validTypes.push_back("Matrix"); + //Create a list of parsed classes for dependency checking + BOOST_FOREACH(const Class& cls, classes) { + validTypes.push_back(cls.qualifiedName("::")); + } + + return validTypes; +} + +/* ************************************************************************* */ +void Module::WriteCollectorsAndCleanupFcn(FileWriter& wrapperFile, const std::string& moduleName, const std::vector& classes) { + // Generate all collectors + BOOST_FOREACH(const Class& cls, classes) { + const string matlabUniqueName = cls.qualifiedName(), + cppName = cls.qualifiedName("::"); + wrapperFile.oss << "typedef std::set*> " + << "Collector_" << matlabUniqueName << ";\n"; + wrapperFile.oss << "static Collector_" << matlabUniqueName << + " collector_" << matlabUniqueName << ";\n"; + } + + // generate mexAtExit cleanup function + wrapperFile.oss << + "\nvoid _deleteAllObjects()\n" + "{\n" + " mstream mout;\n" // Send stdout to MATLAB console + " std::streambuf *outbuf = std::cout.rdbuf(&mout);\n\n" + " bool anyDeleted = false;\n"; + BOOST_FOREACH(const Class& cls, classes) { + const string matlabUniqueName = cls.qualifiedName(); + const string cppName = cls.qualifiedName("::"); + const string collectorType = "Collector_" + matlabUniqueName; + const string collectorName = "collector_" + matlabUniqueName; + // The extra curly-braces around the for loops work around a limitation in MSVC (existing + // since 2005!) preventing more than 248 blocks. + wrapperFile.oss << + " { for(" << collectorType << "::iterator iter = " << collectorName << ".begin();\n" + " iter != " << collectorName << ".end(); ) {\n" + " delete *iter;\n" + " " << collectorName << ".erase(iter++);\n" + " anyDeleted = true;\n" + " } }\n"; + } + wrapperFile.oss << + " if(anyDeleted)\n" + " cout <<\n" + " \"WARNING: Wrap modules with variables in the workspace have been reloaded due to\\n\"\n" + " \"calling destructors, call 'clear all' again if you plan to now recompile a wrap\\n\"\n" + " \"module, so that your recompiled module is used instead of the old one.\" << endl;\n" + " std::cout.rdbuf(outbuf);\n" // Restore cout + "}\n\n"; +} + +/* ************************************************************************* */ +void Module::WriteRTTIRegistry(FileWriter& wrapperFile, const std::string& moduleName, const std::vector& classes) { + wrapperFile.oss << + "void _" << moduleName << "_RTTIRegister() {\n" + " const mxArray *alreadyCreated = mexGetVariablePtr(\"global\", \"gtsam_" + moduleName + "_rttiRegistry_created\");\n" + " if(!alreadyCreated) {\n" + " std::map types;\n"; + BOOST_FOREACH(const Class& cls, classes) { + if(cls.isVirtual) + wrapperFile.oss << + " types.insert(std::make_pair(typeid(" << cls.qualifiedName("::") << ").name(), \"" << cls.qualifiedName(".") << "\"));\n"; + } + wrapperFile.oss << "\n"; + + wrapperFile.oss << + " mxArray *registry = mexGetVariable(\"global\", \"gtsamwrap_rttiRegistry\");\n" + " if(!registry)\n" + " registry = mxCreateStructMatrix(1, 1, 0, NULL);\n" + " typedef std::pair StringPair;\n" + " BOOST_FOREACH(const StringPair& rtti_matlab, types) {\n" + " int fieldId = mxAddField(registry, rtti_matlab.first.c_str());\n" + " if(fieldId < 0)\n" + " mexErrMsgTxt(\"gtsam wrap: Error indexing RTTI types, inheritance will not work correctly\");\n" + " mxArray *matlabName = mxCreateString(rtti_matlab.second.c_str());\n" + " mxSetFieldByNumber(registry, 0, fieldId, matlabName);\n" + " }\n" + " if(mexPutVariable(\"global\", \"gtsamwrap_rttiRegistry\", registry) != 0)\n" + " mexErrMsgTxt(\"gtsam wrap: Error indexing RTTI types, inheritance will not work correctly\");\n" + " mxDestroyArray(registry);\n" + " \n" + " mxArray *newAlreadyCreated = mxCreateNumericMatrix(0, 0, mxINT8_CLASS, mxREAL);\n" + " if(mexPutVariable(\"global\", \"gtsam_" + moduleName + "_rttiRegistry_created\", newAlreadyCreated) != 0)\n" + " mexErrMsgTxt(\"gtsam wrap: Error indexing RTTI types, inheritance will not work correctly\");\n" + " mxDestroyArray(newAlreadyCreated);\n" + " }\n" + "}\n" + "\n"; +} + +/* ************************************************************************* */ diff --git a/wrap/Module.h b/wrap/Module.h index 3e97d9ba2..a1dfe88d8 100644 --- a/wrap/Module.h +++ b/wrap/Module.h @@ -13,14 +13,19 @@ * @file Module.h * @brief describes module to be wrapped * @author Frank Dellaert + * @author Richard Roberts **/ #pragma once #include #include +#include #include "Class.h" +#include "GlobalFunction.h" +#include "TemplateInstantiationTypedef.h" +#include "ForwardDeclaration.h" namespace wrap { @@ -28,21 +33,40 @@ namespace wrap { * A module just has a name and a list of classes */ struct Module { + + typedef std::map GlobalFunctions; + typedef std::map Methods; + std::string name; ///< module name std::vector classes; ///< list of classes + std::vector templateInstantiationTypedefs; ///< list of template instantiations bool verbose; ///< verbose flag -// std::vector using_namespaces; ///< all default namespaces - std::vector forward_declarations; + std::vector forward_declarations; + std::vector includes; ///< Include statements + GlobalFunctions global_functions; /// constructor that parses interface file Module(const std::string& interfacePath, const std::string& moduleName, bool enable_verbose=true); + //Recursive method to append all methods inhereted from parent classes + std::map appendInheretedMethods(const Class& cls, const std::vector& classes); + /// MATLAB code generation: - void matlab_code(const std::string& path, - const std::string& mexExt, - const std::string& mexFlags) const; + void matlab_code( + const std::string& path, + const std::string& headerPath) const; + + void finish_wrapper(FileWriter& file, const std::vector& functionNames) const; + + void generateIncludes(FileWriter& file) const; + +private: + static std::vector ExpandTypedefInstantiations(const std::vector& classes, const std::vector instantiations); + static std::vector GenerateValidTypes(const std::vector& classes, const std::vector forwardDeclarations); + static void WriteCollectorsAndCleanupFcn(FileWriter& wrapperFile, const std::string& moduleName, const std::vector& classes); + static void WriteRTTIRegistry(FileWriter& wrapperFile, const std::string& moduleName, const std::vector& classes); }; } // \namespace wrap diff --git a/wrap/README b/wrap/README index 6e7acc863..92fd1967c 100644 --- a/wrap/README +++ b/wrap/README @@ -1,14 +1,17 @@ Frank Dellaert October 2011 -The wrap library wraps the GTSAM library into a MATLAB toolbox. +The wrap library wraps the GTSAM library into a MATLAB toolbox. It was designed to be more general than just wrapping GTSAM, but a small amount of GTSAM specific code exists in matlab.h, the include file that is included by the -mex files. In addition, the current makefile (Oct 11) is GTSAM specific. +mex files. The GTSAM-specific functionality consists primarily of handling of +Eigen Matrix and Vector classes. + +For notes on creating a wrap interface, see gtsam.h for what features can be +wrapped into a toolbox, as well as the current state of the toolbox for gtsam. +For more technical details on the interface, please read comments in matlab.h -The classes and methods to be wrapped are specified in gtsam.h -This tool will not wrap arbitrary methods. Please read comments in matlab.h Some good things to know: OBJECT CREATION @@ -24,7 +27,5 @@ METHOD (AND CONSTRUCTOR) ARGUMENTS generation of the correct conversion routines unwrap and unwrap - passing classes as arguments works, provided they are passed by reference. This triggers a call to unwrap_shared_ptr -- GTSAM specific: keys will be cast automatically from strings via GTSAM_magic. This - allows us to not have to declare all key types in MATLAB. Just replace key arguments with - the (non-const, non-reference) string type + \ No newline at end of file diff --git a/wrap/ReturnValue.cpp b/wrap/ReturnValue.cpp index 2095abc5e..4f5a030cc 100644 --- a/wrap/ReturnValue.cpp +++ b/wrap/ReturnValue.cpp @@ -3,6 +3,8 @@ * * @date Dec 1, 2011 * @author Alex Cunningham + * @author Andrew Melim + * @author Richard Roberts */ #include @@ -17,11 +19,11 @@ using namespace wrap; string ReturnValue::return_type(bool add_ptr, pairing p) const { if (p==pair && isPair) { string str = "pair< " + - maybe_shared_ptr(add_ptr && isPtr1, qualifiedType1("::")) + ", " + - maybe_shared_ptr(add_ptr && isPtr2, qualifiedType2("::")) + " >"; + maybe_shared_ptr(add_ptr || isPtr1, qualifiedType1("::"), type1) + ", " + + maybe_shared_ptr(add_ptr || isPtr2, qualifiedType2("::"), type2) + " >"; return str; } else - return maybe_shared_ptr(add_ptr && isPtr1, (p==arg2)? qualifiedType2("::") : qualifiedType1("::")); + return maybe_shared_ptr(add_ptr && isPtr1, (p==arg2)? qualifiedType2("::") : qualifiedType1("::"), (p==arg2)? type2 : type1); } /* ************************************************************************* */ @@ -44,35 +46,98 @@ string ReturnValue::qualifiedType2(const string& delim) const { } /* ************************************************************************* */ -void ReturnValue::wrap_result(FileWriter& file) const { - string cppType1 = qualifiedType1("::"), matlabType1 = qualifiedType1(); - string cppType2 = qualifiedType2("::"), matlabType2 = qualifiedType2(); +//TODO:Fix this +void ReturnValue::wrap_result(const string& result, FileWriter& file, const TypeAttributesTable& typeAttributes) const { + string cppType1 = qualifiedType1("::"), matlabType1 = qualifiedType1("."); + string cppType2 = qualifiedType2("::"), matlabType2 = qualifiedType2("."); if (isPair) { + // For a pair, store the returned pair so we do not evaluate the function twice + file.oss << " " << return_type(false, pair) << " pairResult = " << result << ";\n"; + // first return value in pair - if (isPtr1) // if we already have a pointer - file.oss << " out[0] = wrap_shared_ptr(result.first,\"" << matlabType1 << "\");\n"; - else if (category1 == ReturnValue::CLASS) // if we are going to make one - file.oss << " out[0] = wrap_shared_ptr(make_shared< " << cppType1 << " >(result.first),\"" << matlabType1 << "\");\n"; - else // if basis type - file.oss << " out[0] = wrap< " << return_type(true,arg1) << " >(result.first);\n"; + if (category1 == ReturnValue::CLASS) { // if we are going to make one + string objCopy, ptrType; + ptrType = "Shared" + type1; + const bool isVirtual = typeAttributes.at(cppType1).isVirtual; + if(isVirtual) { + if(isPtr1) + objCopy = "pairResult.first"; + else + objCopy = "pairResult.first.clone()"; + } else { + if(isPtr1) + objCopy = "pairResult.first"; + else + objCopy = ptrType + "(new " + cppType1 + "(pairResult.first))"; + } + file.oss << " out[0] = wrap_shared_ptr(" << objCopy << ",\"" << matlabType1 << "\", " << (isVirtual ? "true" : "false") << ");\n"; + } else if(isPtr1) { + file.oss << " Shared" << type1 <<"* ret = new Shared" << type1 << "(pairResult.first);" << endl; + file.oss << " out[0] = wrap_shared_ptr(ret,\"" << matlabType1 << "\", false);\n"; + } else // if basis type + file.oss << " out[0] = wrap< " << return_type(true,arg1) << " >(pairResult.first);\n"; // second return value in pair - if (isPtr2) // if we already have a pointer - file.oss << " out[1] = wrap_shared_ptr(result.second,\"" << matlabType2 << "\");\n"; - else if (category2 == ReturnValue::CLASS) // if we are going to make one - file.oss << " out[1] = wrap_shared_ptr(make_shared< " << cppType2 << " >(result.second),\"" << matlabType2 << "\");\n"; - else - file.oss << " out[1] = wrap< " << return_type(true,arg2) << " >(result.second);\n"; + if (category2 == ReturnValue::CLASS) { // if we are going to make one + string objCopy, ptrType; + ptrType = "Shared" + type2; + const bool isVirtual = typeAttributes.at(cppType2).isVirtual; + if(isVirtual) { + if(isPtr2) + objCopy = "pairResult.second"; + else + objCopy = "pairResult.second.clone()"; + } else { + if(isPtr2) + objCopy = "pairResult.second"; + else + objCopy = ptrType + "(new " + cppType2 + "(pairResult.second))"; + } + file.oss << " out[1] = wrap_shared_ptr(" << objCopy << ",\"" << matlabType2 << "\", " << (isVirtual ? "true" : "false") << ");\n"; + } else if(isPtr2) { + file.oss << " Shared" << type2 <<"* ret = new Shared" << type2 << "(pairResult.second);" << endl; + file.oss << " out[1] = wrap_shared_ptr(ret,\"" << matlabType2 << "\");\n"; + } else + file.oss << " out[1] = wrap< " << return_type(true,arg2) << " >(pairResult.second);\n"; } - else if (isPtr1) - file.oss << " out[0] = wrap_shared_ptr(result,\"" << matlabType1 << "\");\n"; - else if (category1 == ReturnValue::CLASS) - file.oss << " out[0] = wrap_shared_ptr(make_shared< " << cppType1 << " >(result),\"" << matlabType1 << "\");\n"; - else if (matlabType1!="void") - file.oss << " out[0] = wrap< " << return_type(true,arg1) << " >(result);\n"; + else if (category1 == ReturnValue::CLASS){ + string objCopy, ptrType; + ptrType = "Shared" + type1; + const bool isVirtual = typeAttributes.at(cppType1).isVirtual; + if(isVirtual) { + if(isPtr1) + objCopy = result; + else + objCopy = result + ".clone()"; + } else { + if(isPtr1) + objCopy = result; + else + objCopy = ptrType + "(new " + cppType1 + "(" + result + "))"; + } + file.oss << " out[0] = wrap_shared_ptr(" << objCopy << ",\"" << matlabType1 << "\", " << (isVirtual ? "true" : "false") << ");\n"; + } else if(isPtr1) { + file.oss << " Shared" << type1 <<"* ret = new Shared" << type1 << "(" << result << ");" << endl; + file.oss << " out[0] = wrap_shared_ptr(ret,\"" << matlabType1 << "\");\n"; + } else if (matlabType1!="void") + file.oss << " out[0] = wrap< " << return_type(true,arg1) << " >(" << result << ");\n"; } /* ************************************************************************* */ +void ReturnValue::wrapTypeUnwrap(FileWriter& wrapperFile) const { + if(isPair) + { + if(category1 == ReturnValue::CLASS) + wrapperFile.oss << " typedef boost::shared_ptr<" << qualifiedType1("::") << "> Shared" << type1 << ";"<< endl; + if(category2 == ReturnValue::CLASS) + wrapperFile.oss << " typedef boost::shared_ptr<" << qualifiedType2("::") << "> Shared" << type2 << ";"<< endl; + } + else { + if (category1 == ReturnValue::CLASS) + wrapperFile.oss << " typedef boost::shared_ptr<" << qualifiedType1("::") << "> Shared" << type1 << ";"<< endl; + } +} +/* ************************************************************************* */ diff --git a/wrap/ReturnValue.h b/wrap/ReturnValue.h index 859e00433..2bffef680 100644 --- a/wrap/ReturnValue.h +++ b/wrap/ReturnValue.h @@ -5,11 +5,14 @@ * * @date Dec 1, 2011 * @author Alex Cunningham + * @author Richard Roberts */ #include +#include #include "FileWriter.h" +#include "TypeAttributesTable.h" #pragma once @@ -47,7 +50,9 @@ struct ReturnValue { std::string matlab_returnType() const; - void wrap_result(FileWriter& file) const; + void wrap_result(const std::string& result, FileWriter& file, const TypeAttributesTable& typeAttributes) const; + + void wrapTypeUnwrap(FileWriter& wrapperFile) const; }; diff --git a/wrap/StaticMethod.cpp b/wrap/StaticMethod.cpp index 3dd9e7c8b..d46fde81a 100644 --- a/wrap/StaticMethod.cpp +++ b/wrap/StaticMethod.cpp @@ -10,14 +10,17 @@ * -------------------------------------------------------------------------- */ /** - * @file Method.ccp + * @file StaticMethod.ccp * @author Frank Dellaert + * @author Andrew Melim + * @author Richard Roberts **/ #include #include #include +#include #include "StaticMethod.h" #include "utilities.h" @@ -25,71 +28,160 @@ using namespace std; using namespace wrap; + /* ************************************************************************* */ -void StaticMethod::matlab_mfile(const string& toolboxPath, const string& className) const { - - // open destination m-file - string full_name = className + "_" + name; - string wrapperFile = toolboxPath + "/" + full_name + ".m"; - FileWriter file(wrapperFile, verbose); - - // generate code - string returnType = returnVal.matlab_returnType(); - file.oss << "function " << returnType << " = " << full_name << "("; - if (args.size()) file.oss << args.names(); - file.oss << ")" << endl; - file.oss << "% usage: x = " << full_name << "(" << args.names() << ")" << endl; - file.oss << " error('need to compile " << full_name << ".cpp');" << endl; - file.oss << "end" << endl; - - // close file - file.emit(true); +void StaticMethod::addOverload(bool verbose, const std::string& name, + const ArgumentList& args, const ReturnValue& retVal) { + this->verbose = verbose; + this->name = name; + this->argLists.push_back(args); + this->returnVals.push_back(retVal); } /* ************************************************************************* */ -void StaticMethod::matlab_wrapper(const string& toolboxPath, const string& className, - const string& matlabClassName, const string& cppClassName, - const vector& using_namespaces, - const vector& includes) const { - // open destination wrapperFile - string full_name = matlabClassName + "_" + name; - string wrapperFile = toolboxPath + "/" + full_name + ".cpp"; - FileWriter file(wrapperFile, verbose, "//"); +void StaticMethod::proxy_wrapper_fragments(FileWriter& proxyFile, FileWriter& wrapperFile, + const string& cppClassName, + const std::string& matlabQualName, + const std::string& matlabUniqueName, + const string& wrapperName, + const TypeAttributesTable& typeAttributes, + vector& functionNames) const { + + string upperName = name; upperName[0] = std::toupper(upperName[0], std::locale()); + + proxyFile.oss << " function varargout = " << upperName << "(varargin)\n"; + //Comments for documentation + string up_name = boost::to_upper_copy(name); + proxyFile.oss << " % " << up_name << " usage:"; + unsigned int argLCount = 0; + BOOST_FOREACH(ArgumentList argList, argLists) + { + proxyFile.oss << " " << name << "("; + unsigned int i = 0; + BOOST_FOREACH(const Argument& arg, argList) + { + if(i != argList.size()-1) + proxyFile.oss << arg.type << " " << arg.name << ", "; + else + proxyFile.oss << arg.type << " " << arg.name; + i++; + } + if(argLCount != argLists.size()-1) + proxyFile.oss << "), "; + else + proxyFile.oss << ") : returns " << returnVals[0].return_type(false, returnVals[0].pair) << endl; + argLCount++; + } + + proxyFile.oss << " % " << "Doxygen can be found at http://research.cc.gatech.edu/borg/sites/edu.borg/html/index.html" << endl; + proxyFile.oss << " % " << "" << endl; + proxyFile.oss << " % " << "Usage" << endl; + BOOST_FOREACH(ArgumentList argList, argLists) + { + proxyFile.oss << " % " << up_name << "("; + unsigned int i = 0; + BOOST_FOREACH(const Argument& arg, argList) + { + if(i != argList.size()-1) + proxyFile.oss << arg.type << " " << arg.name << ", "; + else + proxyFile.oss << arg.type << " " << arg.name; + i++; + } + proxyFile.oss << ")" << endl; + } + + + for(size_t overload = 0; overload < argLists.size(); ++overload) { + const ArgumentList& args = argLists[overload]; + const ReturnValue& returnVal = returnVals[overload]; + size_t nrArgs = args.size(); + + const int id = functionNames.size(); + + // Output proxy matlab code + + // check for number of arguments... + proxyFile.oss << " " << (overload==0?"":"else") << "if length(varargin) == " << nrArgs; + if (nrArgs>0) proxyFile.oss << " && "; + // ...and their types + bool first = true; + for(size_t i=0;i(id); - // call - file.oss << "void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[])\n"; - // start - file.oss << "{\n"; + const ArgumentList& args = argLists[overload]; + const ReturnValue& returnVal = returnVals[overload]; + + // call + file.oss << "void " << wrapFunctionName << "(int nargout, mxArray *out[], int nargin, const mxArray *in[])\n"; + // start + file.oss << "{\n"; + + returnVal.wrapTypeUnwrap(file); + + file.oss << " typedef boost::shared_ptr<" << cppClassName << "> Shared;" << endl; // check arguments // NOTE: for static functions, there is no object passed - file.oss << " checkArguments(\"" << full_name << "\",nargout,nargin," << args.size() << ");\n"; + file.oss << " checkArguments(\"" << matlabUniqueName << "." << name << "\",nargout,nargin," << args.size() << ");\n"; // unwrap arguments, see Argument.cpp args.matlab_unwrap(file,0); // We start at 0 because there is no self object - file.oss << " "; - - // call method with default type + // call method with default type and wrap result if (returnVal.type1!="void") - file.oss << returnVal.return_type(true,ReturnValue::pair) << " result = "; - file.oss << cppClassName << "::" << name << "(" << args.names() << ");\n"; - - // wrap result - // example: out[0]=wrap(result); - returnVal.wrap_result(file); + returnVal.wrap_result(cppClassName+"::"+name+"("+args.names()+")", file, typeAttributes); + else + file.oss << cppClassName+"::"+name+"("+args.names()+");\n"; // finish file.oss << "}\n"; - // close file - file.emit(true); + return wrapFunctionName; } /* ************************************************************************* */ diff --git a/wrap/StaticMethod.h b/wrap/StaticMethod.h index f9cc14af7..9c1581400 100644 --- a/wrap/StaticMethod.h +++ b/wrap/StaticMethod.h @@ -14,6 +14,7 @@ * @brief describes and generates code for static methods * @author Frank Dellaert * @author Alex Cunningham + * @author Richard Roberts **/ #pragma once @@ -23,6 +24,8 @@ #include "Argument.h" #include "ReturnValue.h" +#include "TypeAttributesTable.h" +#include namespace wrap { @@ -36,20 +39,29 @@ struct StaticMethod { // Then the instance variables are set directly by the Module constructor bool verbose; std::string name; - ArgumentList args; - ReturnValue returnVal; + std::vector argLists; + std::vector returnVals; + + // The first time this function is called, it initializes the class members + // with those in rhs, but in subsequent calls it adds additional argument + // lists as function overloads. + void addOverload(bool verbose, const std::string& name, + const ArgumentList& args, const ReturnValue& retVal); // MATLAB code generation - // toolboxPath is the core toolbox directory, e.g., ../matlab - // NOTE: static functions are not inside the class, and - // are created with [ClassName]_[FunctionName]() format + // classPath is class directory, e.g., ../matlab/@Point2 + void proxy_wrapper_fragments(FileWriter& proxyFile, FileWriter& wrapperFile, + const std::string& cppClassName, const std::string& matlabQualName, const std::string& matlabUniqueName, + const std::string& wrapperName, const TypeAttributesTable& typeAttributes, + std::vector& functionNames) const; - void matlab_mfile(const std::string& toolboxPath, const std::string& className) const; ///< m-file - void matlab_wrapper(const std::string& toolboxPath, - const std::string& className, const std::string& matlabClassName, - const std::string& cppClassName, - const std::vector& using_namespaces, - const std::vector& includes) const; ///< cpp wrapper +private: + std::string wrapper_fragment(FileWriter& file, + const std::string& cppClassName, + const std::string& matlabUniqueName, + int overload, + int id, + const TypeAttributesTable& typeAttributes) const; ///< cpp wrapper }; } // \namespace wrap diff --git a/wrap/TemplateInstantiationTypedef.cpp b/wrap/TemplateInstantiationTypedef.cpp new file mode 100644 index 000000000..b822f732b --- /dev/null +++ b/wrap/TemplateInstantiationTypedef.cpp @@ -0,0 +1,61 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file Class.cpp + * @author Frank Dellaert + * @author Andrew Melim + * @author Richard Roberts + **/ + +#include "TemplateInstantiationTypedef.h" + +#include "utilities.h" + +using namespace std; + +namespace wrap { + + Class TemplateInstantiationTypedef::findAndExpand(const vector& classes) const { + // Find matching class + std::vector::const_iterator clsIt = classes.end(); + for(std::vector::const_iterator it = classes.begin(); it != classes.end(); ++it) { + if(it->name == className && it->namespaces == classNamespaces && it->templateArgs.size() == typeList.size()) { + clsIt = it; + break; + } + } + + if(clsIt == classes.end()) + throw DependencyMissing(wrap::qualifiedName("::", classNamespaces, className), + "instantiation into typedef name " + wrap::qualifiedName("::", namespaces, name) + + ". Ensure that the typedef provides the correct number of template arguments."); + + // Instantiate it + Class classInst = *clsIt; + for(size_t i = 0; i < typeList.size(); ++i) + classInst = classInst.expandTemplate(classInst.templateArgs[i], typeList[i], namespaces, name); + + // Fix class properties + classInst.name = name; + classInst.templateArgs.clear(); + classInst.typedefName = clsIt->qualifiedName("::") + "<"; + if(typeList.size() > 0) + classInst.typedefName += wrap::qualifiedName("::", typeList[0]); + for(size_t i = 1; i < typeList.size(); ++i) + classInst.typedefName += (", " + wrap::qualifiedName("::", typeList[i])); + classInst.typedefName += ">"; + classInst.namespaces = namespaces; + + return classInst; + } + +} \ No newline at end of file diff --git a/wrap/TemplateInstantiationTypedef.h b/wrap/TemplateInstantiationTypedef.h new file mode 100644 index 000000000..192d35324 --- /dev/null +++ b/wrap/TemplateInstantiationTypedef.h @@ -0,0 +1,39 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file Class.h + * @brief describe the C++ class that is being wrapped + * @author Frank Dellaert + * @author Andrew Melim + * @author Richard Roberts + **/ + +#pragma once + +#include +#include + +#include "Class.h" + +namespace wrap { + +struct TemplateInstantiationTypedef { + std::vector classNamespaces; + std::string className; + std::vector namespaces; + std::string name; + std::vector > typeList; + + Class findAndExpand(const std::vector& classes) const; +}; + +} \ No newline at end of file diff --git a/wrap/TypeAttributesTable.cpp b/wrap/TypeAttributesTable.cpp new file mode 100644 index 000000000..865015a6e --- /dev/null +++ b/wrap/TypeAttributesTable.cpp @@ -0,0 +1,58 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file Class.cpp + * @author Frank Dellaert + * @author Andrew Melim + * @author Richard Roberts + **/ + +#include "TypeAttributesTable.h" +#include "Class.h" +#include "utilities.h" + +#include + +using namespace std; + +namespace wrap { + + /* ************************************************************************* */ + void TypeAttributesTable::addClasses(const vector& classes) { + BOOST_FOREACH(const Class& cls, classes) { + if(!insert(make_pair(cls.qualifiedName("::"), TypeAttributes(cls.isVirtual))).second) + throw DuplicateDefinition("class " + cls.qualifiedName("::")); + } + } + + /* ************************************************************************* */ + void TypeAttributesTable::addForwardDeclarations(const vector& forwardDecls) { + BOOST_FOREACH(const ForwardDeclaration& fwDec, forwardDecls) { + if(!insert(make_pair(fwDec.name, TypeAttributes(fwDec.isVirtual))).second) + throw DuplicateDefinition("class " + fwDec.name); + } + } + + /* ************************************************************************* */ + void TypeAttributesTable::checkValidity(const vector& classes) const { + BOOST_FOREACH(const Class& cls, classes) { + // Check that class is virtual if it has a parent + if(!cls.qualifiedParent.empty() && !cls.isVirtual) + throw AttributeError(cls.qualifiedName("::"), "Has a base class so needs to be declared virtual, change to 'virtual class "+cls.name+" ...'"); + // Check that parent is virtual as well + if(!cls.qualifiedParent.empty() && !at(wrap::qualifiedName("::", cls.qualifiedParent)).isVirtual) + throw AttributeError(wrap::qualifiedName("::", cls.qualifiedParent), + "Is the base class of " + cls.qualifiedName("::") + ", so needs to be declared virtual"); + } + } + +} \ No newline at end of file diff --git a/wrap/TypeAttributesTable.h b/wrap/TypeAttributesTable.h new file mode 100644 index 000000000..dea6d0bf5 --- /dev/null +++ b/wrap/TypeAttributesTable.h @@ -0,0 +1,55 @@ +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file Class.h + * @brief describe the C++ class that is being wrapped + * @author Frank Dellaert + * @author Andrew Melim + * @author Richard Roberts + **/ + +#include +#include +#include + +#include "ForwardDeclaration.h" + +#pragma once + +namespace wrap { + + // Forward declarations + struct Class; + +/** Attributes about valid classes, both for classes defined in this module and + * also those forward-declared from others. At the moment this only contains + * whether the class is virtual, which is used to know how to copy the class, + * and whether to try to convert it to a more derived type upon returning it. + */ +struct TypeAttributes { + bool isVirtual; + TypeAttributes() : isVirtual(false) {} + TypeAttributes(bool isVirtual) : isVirtual(isVirtual) {} +}; + +/** Map of type names to attributes. */ +class TypeAttributesTable : public std::map { +public: + TypeAttributesTable() {} + + void addClasses(const std::vector& classes); + void addForwardDeclarations(const std::vector& forwardDecls); + + void checkValidity(const std::vector& classes) const; +}; + +} \ No newline at end of file diff --git a/wrap/matlab.h b/wrap/matlab.h index 2ef81f37f..5b438f1a6 100644 --- a/wrap/matlab.h +++ b/wrap/matlab.h @@ -1,456 +1,426 @@ -/* ---------------------------------------------------------------------------- - - * GTSAM Copyright 2010, Georgia Tech Research Corporation, - * Atlanta, Georgia 30332-0415 - * All Rights Reserved - * Authors: Frank Dellaert, et al. (see THANKS for the full author list) - - * See LICENSE for the license information - - * -------------------------------------------------------------------------- */ - -/** - * @file matlab.h - * @brief header file to be included in MATLAB wrappers - * @date 2008 - * @author Frank Dellaert - * - * wrapping and unwrapping is done using specialized templates, see - * http://www.cplusplus.com/doc/tutorial/templates.html - */ - -#include -#include - -using gtsam::Vector; -using gtsam::Matrix; - -extern "C" { -#include -} - -#include -#include - -#include -#include -#include - -using namespace std; -using namespace boost; // not usual, but for conciseness of generated code - -// start GTSAM Specifics ///////////////////////////////////////////////// -// to enable Matrix and Vector constructor for SharedGaussian: -#define GTSAM_MAGIC_GAUSSIAN -// end GTSAM Specifics ///////////////////////////////////////////////// - -#ifdef __LP64__ -// 64-bit Mac -#define mxUINT32OR64_CLASS mxUINT64_CLASS -#else -#define mxUINT32OR64_CLASS mxUINT32_CLASS -#endif - -//***************************************************************************** -// Utilities -//***************************************************************************** - -void error(const char* str) { - mexErrMsgIdAndTxt("wrap:error", str); -} - -mxArray *scalar(mxClassID classid) { - mwSize dims[1]; dims[0]=1; - return mxCreateNumericArray(1, dims, classid, mxREAL); -} - -void checkScalar(const mxArray* array, const char* str) { - int m = mxGetM(array), n = mxGetN(array); - if (m!=1 || n!=1) - mexErrMsgIdAndTxt("wrap: not a scalar in ", str); -} - -//***************************************************************************** -// Check arguments -//***************************************************************************** - -void checkArguments(const string& name, int nargout, int nargin, int expected) { - stringstream err; - err << name << " expects " << expected << " arguments, not " << nargin; - if (nargin!=expected) - error(err.str().c_str()); -} - -//***************************************************************************** -// wrapping C++ basis types in MATLAB arrays -//***************************************************************************** - -// default wrapping throws an error: only basis types are allowed in wrap -template -mxArray* wrap(Class& value) { - error("wrap internal error: attempted wrap of invalid type"); -} - -// specialization to string -// wraps into a character array -template<> -mxArray* wrap(string& value) { - return mxCreateString(value.c_str()); -} - -// specialization to char -template<> -mxArray* wrap(char& value) { - mxArray *result = scalar(mxUINT32OR64_CLASS); - *(char*)mxGetData(result) = value; - return result; -} - -// specialization to bool -template<> -mxArray* wrap(bool& value) { - mxArray *result = scalar(mxUINT32OR64_CLASS); - *(bool*)mxGetData(result) = value; - return result; -} - -// specialization to size_t -template<> -mxArray* wrap(size_t& value) { - mxArray *result = scalar(mxUINT32OR64_CLASS); - *(size_t*)mxGetData(result) = value; - return result; -} - -// specialization to int -template<> -mxArray* wrap(int& value) { - mxArray *result = scalar(mxUINT32OR64_CLASS); - *(int*)mxGetData(result) = value; - return result; -} - -// specialization to double -> just double -template<> -mxArray* wrap(double& value) { - return mxCreateDoubleScalar(value); -} - -// wrap a const Eigen vector into a double vector -mxArray* wrap_Vector(const gtsam::Vector& v) { - int m = v.size(); - mxArray *result = mxCreateDoubleMatrix(m, 1, mxREAL); - double *data = mxGetPr(result); - for (int i=0;i double vector -template<> -mxArray* wrap(gtsam::Vector& v) { - return wrap_Vector(v); -} - -// const version -template<> -mxArray* wrap(const gtsam::Vector& v) { - return wrap_Vector(v); -} - -// wrap a const Eigen MATRIX into a double matrix -mxArray* wrap_Matrix(const gtsam::Matrix& A) { - int m = A.rows(), n = A.cols(); -#ifdef DEBUG_WRAP - mexPrintf("wrap_Matrix called with A = \n", m,n); - gtsam::print(A); -#endif - mxArray *result = mxCreateDoubleMatrix(m, n, mxREAL); - double *data = mxGetPr(result); - // converts from column-major to row-major - for (int j=0;j double matrix -template<> -mxArray* wrap(gtsam::Matrix& A) { - return wrap_Matrix(A); -} - -// const version -template<> -mxArray* wrap(const gtsam::Matrix& A) { - return wrap_Matrix(A); -} - -//***************************************************************************** -// unwrapping MATLAB arrays into C++ basis types -//***************************************************************************** - -// default unwrapping throws an error -// as wrap only supports passing a reference or one of the basic types -template -T unwrap(const mxArray* array) { - error("wrap internal error: attempted unwrap of invalid type"); -} - -// specialization to string -// expects a character array -// Warning: relies on mxChar==char -template<> -string unwrap(const mxArray* array) { - char *data = mxArrayToString(array); - if (data==NULL) error("unwrap: not a character array"); - string str(data); - mxFree(data); - return str; -} - -// specialization to bool -template<> -bool unwrap(const mxArray* array) { - checkScalar(array,"unwrap"); - return mxGetScalar(array) != 0.0; -} - -// specialization to bool -template<> -char unwrap(const mxArray* array) { - checkScalar(array,"unwrap"); - return (char)mxGetScalar(array); -} - -// specialization to size_t -template<> -size_t unwrap(const mxArray* array) { - checkScalar(array,"unwrap"); - return (size_t)mxGetScalar(array); -} - -// specialization to int -template<> -int unwrap(const mxArray* array) { - checkScalar(array,"unwrap"); - return (int)mxGetScalar(array); -} - -// specialization to double -template<> -double unwrap(const mxArray* array) { - checkScalar(array,"unwrap"); - return (double)mxGetScalar(array); -} - -// specialization to Eigen vector -template<> -gtsam::Vector unwrap< gtsam::Vector >(const mxArray* array) { - int m = mxGetM(array), n = mxGetN(array); - if (mxIsDouble(array)==false || n!=1) error("unwrap: not a vector"); -#ifdef DEBUG_WRAP - mexPrintf("unwrap< gtsam::Vector > called with %dx%d argument\n", m,n); -#endif - double* data = (double*)mxGetData(array); - gtsam::Vector v(m); - for (int i=0;i -gtsam::Matrix unwrap< gtsam::Matrix >(const mxArray* array) { - if (mxIsDouble(array)==false) error("unwrap: not a matrix"); - int m = mxGetM(array), n = mxGetN(array); -#ifdef DEBUG_WRAP - mexPrintf("unwrap< gtsam::Matrix > called with %dx%d argument\n", m,n); -#endif - double* data = (double*)mxGetData(array); - gtsam::Matrix A(m,n); - // converts from row-major to column-major - for (int j=0;j -class ObjectHandle { -private: - ObjectHandle* signature; // use 'this' as a unique object signature - const std::type_info* type; // type checking information - shared_ptr t; // object pointer - -public: - // Constructor for free-store allocated objects. - // Creates shared pointer, will delete if is last one to hold pointer - ObjectHandle(T* ptr) : - type(&typeid(T)), t(shared_ptr (ptr)) { - signature = this; - } - - // Constructor for shared pointers - // Creates shared pointer, will delete if is last one to hold pointer - ObjectHandle(shared_ptr ptr) : - /*type(&typeid(T)),*/ t(ptr) { - signature = this; - } - - ~ObjectHandle() { - // object is in shared_ptr, will be automatically deleted - signature = 0; // destroy signature - } - - // Get the actual object contained by handle - shared_ptr get_object() const { - return t; - } - - // Print the mexhandle for debugging - void print(const char* str) { - mexPrintf("mexhandle %s:\n", str); - mexPrintf(" signature = %d:\n", signature); - mexPrintf(" pointer = %d:\n", t.get()); - } - - // Convert ObjectHandle to a mxArray handle (to pass back from mex-function). - // Create a numeric array as handle for an ObjectHandle. - // We ASSUME we can store object pointer in the mxUINT32 element of mxArray. - mxArray* to_mex_handle() { - mxArray* handle = mxCreateNumericMatrix(1, 1, mxUINT32OR64_CLASS, mxREAL); - *reinterpret_cast**> (mxGetPr(handle)) = this; - return handle; - } - - string type_name() const { - return type->name(); - } - - // Convert mxArray (passed to mex-function) to an ObjectHandle. - // Import a handle from MatLab as a mxArray of UINT32. Check that - // it is actually a pointer to an ObjectHandle. - static ObjectHandle* from_mex_handle(const mxArray* handle) { - if (mxGetClassID(handle) != mxUINT32OR64_CLASS || mxIsComplex(handle) - || mxGetM(handle) != 1 || mxGetN(handle) != 1) error( - "Parameter is not an ObjectHandle type."); - - // We *assume* we can store ObjectHandle pointer in the mxUINT32 of handle - ObjectHandle* obj = *reinterpret_cast (mxGetPr(handle)); - - if (!obj) // gross check to see we don't have an invalid pointer - error("Parameter is NULL. It does not represent an ObjectHandle object."); - // TODO: change this for max-min check for pointer values - - if (obj->signature != obj) // check memory has correct signature - error("Parameter does not represent an ObjectHandle object."); - - /* - if (*(obj->type) != typeid(T)) { // check type - mexPrintf("Given: <%s>, Required: <%s>.\n", obj->type_name(), typeid(T).name()); - error("Given ObjectHandle does not represent the correct type."); - } - */ - - return obj; - } - -}; - -//***************************************************************************** -// wrapping C++ objects in a MATLAB proxy class -//***************************************************************************** - -/* - For every C++ class Class, a matlab proxy class @Class/Class.m object - is created. Its constructor will check which of the C++ constructors - needs to be called, based on nr of arguments. It then calls the - corresponding mex function new_Class_signature, which will create a - C++ object using new, and pass the pointer to wrap_constructed - (below). This creates a mexhandle and returns it to the proxy class - constructor, which assigns it to self. Matlab owns this handle now. -*/ -template -mxArray* wrap_constructed(Class* pointer, const char *classname) { - ObjectHandle* handle = new ObjectHandle(pointer); - return handle->to_mex_handle(); -} - -/* - [create_object] creates a MATLAB proxy class object with a mexhandle - in the self property. Matlab does not allow the creation of matlab - objects from within mex files, hence we resort to an ugly trick: we - invoke the proxy class constructor by calling MATLAB, and pass 13 - dummy arguments to let the constructor know we want an object without - the self property initialized. We then assign the mexhandle to self. -*/ -// TODO: think about memory -mxArray* create_object(const char *classname, mxArray* h) { - mxArray *result; - mxArray* dummy[13] = {h,h,h,h,h, h,h,h,h,h, h,h,h}; - mexCallMATLAB(1,&result,13,dummy,classname); - mxSetProperty(result, 0, "self", h); - return result; -} - -/* - When the user calls a method that returns a shared pointer, we create - an ObjectHandle from the shared_pointer and return it as a proxy - class to matlab. -*/ -template -mxArray* wrap_shared_ptr(shared_ptr< Class > shared_ptr, const char *classname) { - ObjectHandle* handle = new ObjectHandle(shared_ptr); - return create_object(classname,handle->to_mex_handle()); -} - -//***************************************************************************** -// unwrapping a MATLAB proxy class to a C++ object reference -//***************************************************************************** - -/* - Besides the basis types, the only other argument type allowed is a - shared pointer to a C++ object. In this case, matlab needs to pass a - proxy class object to the mex function. [unwrap_shared_ptr] extracts - the ObjectHandle from the self property, and returns a shared pointer - to the object. -*/ -template -shared_ptr unwrap_shared_ptr(const mxArray* obj, const string& className) { - //Why is this here? -#ifndef UNSAFE_WRAP - bool isClass = mxIsClass(obj, className.c_str()); - if (!isClass) { - mexPrintf("Expected %s, got %s\n", className.c_str(), mxGetClassName(obj)); - error("Argument has wrong type."); - } -#endif - mxArray* mxh = mxGetProperty(obj,0,"self"); - if (mxh==NULL) error("unwrap_reference: invalid wrap object"); - ObjectHandle* handle = ObjectHandle::from_mex_handle(mxh); - return handle->get_object(); -} - -template -void delete_shared_ptr(const mxArray* obj, const string& className) { - //Why is this here? -#ifndef UNSAFE_WRAP - bool isClass = true;//mxIsClass(obj, className.c_str()); - if (!isClass) { - mexPrintf("Expected %s, got %s\n", className.c_str(), mxGetClassName(obj)); - error("Argument has wrong type."); - } -#endif - mxArray* mxh = mxGetProperty(obj,0,"self"); - if (mxh==NULL) error("unwrap_reference: invalid wrap object"); - ObjectHandle* handle = ObjectHandle::from_mex_handle(mxh); - delete handle; -} - -//***************************************************************************** +/* ---------------------------------------------------------------------------- + + * GTSAM Copyright 2010, Georgia Tech Research Corporation, + * Atlanta, Georgia 30332-0415 + * All Rights Reserved + * Authors: Frank Dellaert, et al. (see THANKS for the full author list) + + * See LICENSE for the license information + + * -------------------------------------------------------------------------- */ + +/** + * @file matlab.h + * @brief header file to be included in MATLAB wrappers + * @date 2008 + * @author Frank Dellaert + * @author Alex Cunningham + * @author Andrew Melim + * @author Richard Roberts + * + * wrapping and unwrapping is done using specialized templates, see + * http://www.cplusplus.com/doc/tutorial/templates.html + */ + +#include +#include + +using gtsam::Vector; +using gtsam::Matrix; + +extern "C" { +#include +} + +#include +#include +#include + +#include +#include +#include +#include +#include +#include + +using namespace std; +using namespace boost; // not usual, but for conciseness of generated code + +// start GTSAM Specifics ///////////////////////////////////////////////// +// to enable Matrix and Vector constructor for SharedGaussian: +#define GTSAM_MAGIC_GAUSSIAN +// end GTSAM Specifics ///////////////////////////////////////////////// + +#if defined(__LP64__) || defined(_WIN64) +// 64-bit +#define mxUINT32OR64_CLASS mxUINT64_CLASS +#else +#define mxUINT32OR64_CLASS mxUINT32_CLASS +#endif + +// "Unique" key to signal calling the matlab object constructor with a raw pointer +// to a shared pointer of the same C++ object type as the MATLAB type. +// Also present in utilities.h +static const uint64_t ptr_constructor_key = + (uint64_t('G') << 56) | + (uint64_t('T') << 48) | + (uint64_t('S') << 40) | + (uint64_t('A') << 32) | + (uint64_t('M') << 24) | + (uint64_t('p') << 16) | + (uint64_t('t') << 8) | + (uint64_t('r')); + +//***************************************************************************** +// Utilities +//***************************************************************************** + +void error(const char* str) { + mexErrMsgIdAndTxt("wrap:error", str); +} + +mxArray *scalar(mxClassID classid) { + mwSize dims[1]; dims[0]=1; + return mxCreateNumericArray(1, dims, classid, mxREAL); +} + +void checkScalar(const mxArray* array, const char* str) { + int m = mxGetM(array), n = mxGetN(array); + if (m!=1 || n!=1) + mexErrMsgIdAndTxt("wrap: not a scalar in ", str); +} + +// Replacement streambuf for cout that writes to the MATLAB console +// Thanks to http://stackoverflow.com/a/249008 +class mstream : public std::streambuf { +protected: + virtual std::streamsize xsputn(const char *s, std::streamsize n) { + mexPrintf("%.*s",n,s); + return n; + } + virtual int overflow(int c = EOF) { + if (c != EOF) { + mexPrintf("%.1s",&c); + } + return 1; + } +}; + +//***************************************************************************** +// Check arguments +//***************************************************************************** + +void checkArguments(const string& name, int nargout, int nargin, int expected) { + stringstream err; + err << name << " expects " << expected << " arguments, not " << nargin; + if (nargin!=expected) + error(err.str().c_str()); +} + +//***************************************************************************** +// wrapping C++ basis types in MATLAB arrays +//***************************************************************************** + +// default wrapping throws an error: only basis types are allowed in wrap +template +mxArray* wrap(const Class& value) { + error("wrap internal error: attempted wrap of invalid type"); + return 0; +} + +// specialization to string +// wraps into a character array +template<> +mxArray* wrap(const string& value) { + return mxCreateString(value.c_str()); +} + +// specialization to char +template<> +mxArray* wrap(const char& value) { + mxArray *result = scalar(mxUINT32OR64_CLASS); + *(char*)mxGetData(result) = value; + return result; +} + +// specialization to unsigned char +template<> +mxArray* wrap(const unsigned char& value) { + mxArray *result = scalar(mxUINT32OR64_CLASS); + *(unsigned char*)mxGetData(result) = value; + return result; +} + +// specialization to bool +template<> +mxArray* wrap(const bool& value) { + mxArray *result = scalar(mxUINT32OR64_CLASS); + *(bool*)mxGetData(result) = value; + return result; +} + +// specialization to size_t +template<> +mxArray* wrap(const size_t& value) { + mxArray *result = scalar(mxUINT32OR64_CLASS); + *(size_t*)mxGetData(result) = value; + return result; +} + +// specialization to int +template<> +mxArray* wrap(const int& value) { + mxArray *result = scalar(mxUINT32OR64_CLASS); + *(int*)mxGetData(result) = value; + return result; +} + +// specialization to double -> just double +template<> +mxArray* wrap(const double& value) { + return mxCreateDoubleScalar(value); +} + +// wrap a const Eigen vector into a double vector +mxArray* wrap_Vector(const gtsam::Vector& v) { + int m = v.size(); + mxArray *result = mxCreateDoubleMatrix(m, 1, mxREAL); + double *data = mxGetPr(result); + for (int i=0;i double vector +template<> +mxArray* wrap(const gtsam::Vector& v) { + return wrap_Vector(v); +} + +// wrap a const Eigen MATRIX into a double matrix +mxArray* wrap_Matrix(const gtsam::Matrix& A) { + int m = A.rows(), n = A.cols(); +#ifdef DEBUG_WRAP + mexPrintf("wrap_Matrix called with A = \n", m,n); + gtsam::print(A); +#endif + mxArray *result = mxCreateDoubleMatrix(m, n, mxREAL); + double *data = mxGetPr(result); + // converts from column-major to row-major + for (int j=0;j double matrix +template<> +mxArray* wrap(const gtsam::Matrix& A) { + return wrap_Matrix(A); +} + +//***************************************************************************** +// unwrapping MATLAB arrays into C++ basis types +//***************************************************************************** + +// default unwrapping throws an error +// as wrap only supports passing a reference or one of the basic types +template +T unwrap(const mxArray* array) { + error("wrap internal error: attempted unwrap of invalid type"); +} + +// specialization to string +// expects a character array +// Warning: relies on mxChar==char +template<> +string unwrap(const mxArray* array) { + char *data = mxArrayToString(array); + if (data==NULL) error("unwrap: not a character array"); + string str(data); + mxFree(data); + return str; +} + +// Check for 64-bit, as Mathworks says mxGetScalar only good for 32 bit +template +T myGetScalar(const mxArray* array) { + switch (mxGetClassID(array)) { + case mxINT64_CLASS: + return (T) *(int64_t*) mxGetData(array); + case mxUINT64_CLASS: + return (T) *(uint64_t*) mxGetData(array); + default: + // hope for the best! + return (T) mxGetScalar(array); + } +} + +// specialization to bool +template<> +bool unwrap(const mxArray* array) { + checkScalar(array,"unwrap"); + return myGetScalar(array); +} + +// specialization to char +template<> +char unwrap(const mxArray* array) { + checkScalar(array,"unwrap"); + return myGetScalar(array); +} + +// specialization to unsigned char +template<> +unsigned char unwrap(const mxArray* array) { + checkScalar(array,"unwrap"); + return myGetScalar(array); +} + +// specialization to int +template<> +int unwrap(const mxArray* array) { + checkScalar(array,"unwrap"); + return myGetScalar(array); +} + +// specialization to size_t +template<> +size_t unwrap(const mxArray* array) { + checkScalar(array, "unwrap"); + return myGetScalar(array); +} + +// specialization to double +template<> +double unwrap(const mxArray* array) { + checkScalar(array,"unwrap"); + return myGetScalar(array); +} + +// specialization to Eigen vector +template<> +gtsam::Vector unwrap< gtsam::Vector >(const mxArray* array) { + int m = mxGetM(array), n = mxGetN(array); + if (mxIsDouble(array)==false || n!=1) error("unwrap: not a vector"); +#ifdef DEBUG_WRAP + mexPrintf("unwrap< gtsam::Vector > called with %dx%d argument\n", m,n); +#endif + double* data = (double*)mxGetData(array); + gtsam::Vector v(m); + for (int i=0;i +gtsam::Matrix unwrap< gtsam::Matrix >(const mxArray* array) { + if (mxIsDouble(array)==false) error("unwrap: not a matrix"); + int m = mxGetM(array), n = mxGetN(array); +#ifdef DEBUG_WRAP + mexPrintf("unwrap< gtsam::Matrix > called with %dx%d argument\n", m,n); +#endif + double* data = (double*)mxGetData(array); + gtsam::Matrix A(m,n); + // converts from row-major to column-major + for (int j=0;j(mxGetData(input[0])) = ptr_constructor_key; + // Second input argument is the pointer + input[1] = mxCreateNumericMatrix(1, 1, mxUINT32OR64_CLASS, mxREAL); + *reinterpret_cast(mxGetData(input[1])) = pointer; + // If the class is virtual, use the RTTI name to look up the derived matlab type + const char *derivedClassName; + if(isVirtual) { + const mxArray *rttiRegistry = mexGetVariablePtr("global", "gtsamwrap_rttiRegistry"); + if(!rttiRegistry) + mexErrMsgTxt( + "gtsam wrap: RTTI registry is missing - it could have been cleared from the workspace." + " You can issue 'clear all' to completely clear the workspace, and next time a wrapped object is" + " created the RTTI registry will be recreated."); + const mxArray *derivedNameMx = mxGetField(rttiRegistry, 0, rttiName); + if(!derivedNameMx) + mexErrMsgTxt(( + "gtsam wrap: The derived class type " + string(rttiName) + " was not found in the RTTI registry. " + "Try calling 'clear all' twice consecutively - we have seen things not get unloaded properly the " + "first time. If this does not work, this may indicate an inconsistency in your wrap interface file. " + "The most likely cause for this is that a base class was marked virtual in the wrap interface " + "definition header file for gtsam or for your module, but a derived type was returned by a C++ " + "function and that derived type was not marked virtual (or was not specified in the wrap interface " + "definition header at all).").c_str()); + size_t strLen = mxGetN(derivedNameMx); + char *buf = new char[strLen+1]; + if(mxGetString(derivedNameMx, buf, strLen+1)) + mexErrMsgTxt("gtsam wrap: Internal error reading RTTI table, try 'clear all' to clear your workspace and reinitialize the toolbox."); + derivedClassName = buf; + input[2] = mxCreateString("void"); + nargin = 3; + } else { + derivedClassName = classname.c_str(); + } + // Call special pointer constructor, which sets 'self' + mexCallMATLAB(1,&result, nargin, input, derivedClassName); + // Deallocate our memory + mxDestroyArray(input[0]); + mxDestroyArray(input[1]); + if(isVirtual) { + mxDestroyArray(input[2]); + delete[] derivedClassName; + } + return result; +} + +/* + When the user calls a method that returns a shared pointer, we create + an ObjectHandle from the shared_pointer and return it as a proxy + class to matlab. +*/ +template +mxArray* wrap_shared_ptr(boost::shared_ptr< Class > shared_ptr, const std::string& matlabName, bool isVirtual) { + // Create actual class object from out pointer + mxArray* result; + if(isVirtual) { + boost::shared_ptr void_ptr(shared_ptr); + result = create_object(matlabName, &void_ptr, isVirtual, typeid(*shared_ptr).name()); + } else { + boost::shared_ptr *heapPtr = new boost::shared_ptr(shared_ptr); + result = create_object(matlabName, heapPtr, isVirtual, ""); + } + return result; +} + +template +boost::shared_ptr unwrap_shared_ptr(const mxArray* obj, const string& propertyName) { + + mxArray* mxh = mxGetProperty(obj,0, propertyName.c_str()); + if (mxGetClassID(mxh) != mxUINT32OR64_CLASS || mxIsComplex(mxh) + || mxGetM(mxh) != 1 || mxGetN(mxh) != 1) error( + "Parameter is not an Shared type."); + + boost::shared_ptr* spp = *reinterpret_cast**> (mxGetData(mxh)); + return *spp; +} diff --git a/wrap/tests/expected/@Point2/Point2.m b/wrap/tests/expected/@Point2/Point2.m deleted file mode 100644 index 454d81399..000000000 --- a/wrap/tests/expected/@Point2/Point2.m +++ /dev/null @@ -1,18 +0,0 @@ -% automatically generated by wrap -classdef Point2 < handle - properties - self = 0 - end - methods - function obj = Point2(varargin) - if (nargin == 0), obj.self = new_Point2_(); end - if (nargin == 2 && isa(varargin{1},'double') && isa(varargin{2},'double')), obj.self = new_Point2_dd(varargin{1},varargin{2}); end - if nargin ~= 13 && obj.self == 0, error('Point2 constructor failed'); end - end - function delete(obj) - delete_Point2(obj); - end - function display(obj), obj.print(''); end - function disp(obj), obj.display; end - end -end diff --git a/wrap/tests/expected/@Point2/argChar.cpp b/wrap/tests/expected/@Point2/argChar.cpp deleted file mode 100644 index 017fe1761..000000000 --- a/wrap/tests/expected/@Point2/argChar.cpp +++ /dev/null @@ -1,10 +0,0 @@ -// automatically generated by wrap -#include -#include -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("argChar",nargout,nargin-1,1); - shared_ptr self = unwrap_shared_ptr< Point2 >(in[0],"Point2"); - char a = unwrap< char >(in[1]); - self->argChar(a); -} diff --git a/wrap/tests/expected/@Point2/argChar.m b/wrap/tests/expected/@Point2/argChar.m deleted file mode 100644 index 3eccf4b76..000000000 --- a/wrap/tests/expected/@Point2/argChar.m +++ /dev/null @@ -1,5 +0,0 @@ - automatically generated by wrap -function result = argChar(obj,a) -% usage: obj.argChar(a) - error('need to compile argChar.cpp'); -end diff --git a/wrap/tests/expected/@Point2/argUChar.cpp b/wrap/tests/expected/@Point2/argUChar.cpp deleted file mode 100644 index 341e4f8a7..000000000 --- a/wrap/tests/expected/@Point2/argUChar.cpp +++ /dev/null @@ -1,10 +0,0 @@ -// automatically generated by wrap -#include -#include -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("argUChar",nargout,nargin-1,1); - shared_ptr self = unwrap_shared_ptr< Point2 >(in[0],"Point2"); - unsigned char a = unwrap< unsigned char >(in[1]); - self->argUChar(a); -} diff --git a/wrap/tests/expected/@Point2/argUChar.m b/wrap/tests/expected/@Point2/argUChar.m deleted file mode 100644 index eedb50df0..000000000 --- a/wrap/tests/expected/@Point2/argUChar.m +++ /dev/null @@ -1,5 +0,0 @@ - automatically generated by wrap -function result = argUChar(obj,a) -% usage: obj.argUChar(a) - error('need to compile argUChar.cpp'); -end diff --git a/wrap/tests/expected/@Point2/dim.cpp b/wrap/tests/expected/@Point2/dim.cpp deleted file mode 100644 index 454153690..000000000 --- a/wrap/tests/expected/@Point2/dim.cpp +++ /dev/null @@ -1,10 +0,0 @@ -// automatically generated by wrap -#include -#include -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("dim",nargout,nargin-1,0); - shared_ptr self = unwrap_shared_ptr< Point2 >(in[0],"Point2"); - int result = self->dim(); - out[0] = wrap< int >(result); -} diff --git a/wrap/tests/expected/@Point2/dim.m b/wrap/tests/expected/@Point2/dim.m deleted file mode 100644 index 011eb28a7..000000000 --- a/wrap/tests/expected/@Point2/dim.m +++ /dev/null @@ -1,5 +0,0 @@ - automatically generated by wrap -function result = dim(obj) -% usage: obj.dim() - error('need to compile dim.cpp'); -end diff --git a/wrap/tests/expected/@Point2/returnChar.cpp b/wrap/tests/expected/@Point2/returnChar.cpp deleted file mode 100644 index 3b7733862..000000000 --- a/wrap/tests/expected/@Point2/returnChar.cpp +++ /dev/null @@ -1,10 +0,0 @@ -// automatically generated by wrap -#include -#include -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("returnChar",nargout,nargin-1,0); - shared_ptr self = unwrap_shared_ptr< Point2 >(in[0],"Point2"); - char result = self->returnChar(); - out[0] = wrap< char >(result); -} diff --git a/wrap/tests/expected/@Point2/returnChar.m b/wrap/tests/expected/@Point2/returnChar.m deleted file mode 100644 index c9334a503..000000000 --- a/wrap/tests/expected/@Point2/returnChar.m +++ /dev/null @@ -1,5 +0,0 @@ - automatically generated by wrap -function result = returnChar(obj) -% usage: obj.returnChar() - error('need to compile returnChar.cpp'); -end diff --git a/wrap/tests/expected/@Point2/vectorConfusion.cpp b/wrap/tests/expected/@Point2/vectorConfusion.cpp deleted file mode 100644 index 90be4194b..000000000 --- a/wrap/tests/expected/@Point2/vectorConfusion.cpp +++ /dev/null @@ -1,10 +0,0 @@ -// automatically generated by wrap -#include -#include -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("vectorConfusion",nargout,nargin-1,0); - shared_ptr self = unwrap_shared_ptr< Point2 >(in[0],"Point2"); - VectorNotEigen result = self->vectorConfusion(); - out[0] = wrap_shared_ptr(make_shared< VectorNotEigen >(result),"VectorNotEigen"); -} diff --git a/wrap/tests/expected/@Point2/vectorConfusion.m b/wrap/tests/expected/@Point2/vectorConfusion.m deleted file mode 100644 index 0db1db291..000000000 --- a/wrap/tests/expected/@Point2/vectorConfusion.m +++ /dev/null @@ -1,5 +0,0 @@ - automatically generated by wrap -function result = vectorConfusion(obj) -% usage: obj.vectorConfusion() - error('need to compile vectorConfusion.cpp'); -end diff --git a/wrap/tests/expected/@Point2/x.cpp b/wrap/tests/expected/@Point2/x.cpp deleted file mode 100644 index 8df8c6bbc..000000000 --- a/wrap/tests/expected/@Point2/x.cpp +++ /dev/null @@ -1,10 +0,0 @@ -// automatically generated by wrap -#include -#include -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("x",nargout,nargin-1,0); - shared_ptr self = unwrap_shared_ptr< Point2 >(in[0],"Point2"); - double result = self->x(); - out[0] = wrap< double >(result); -} diff --git a/wrap/tests/expected/@Point2/x.m b/wrap/tests/expected/@Point2/x.m deleted file mode 100644 index 0a6e99d16..000000000 --- a/wrap/tests/expected/@Point2/x.m +++ /dev/null @@ -1,5 +0,0 @@ - automatically generated by wrap -function result = x(obj) -% usage: obj.x() - error('need to compile x.cpp'); -end diff --git a/wrap/tests/expected/@Point2/y.cpp b/wrap/tests/expected/@Point2/y.cpp deleted file mode 100644 index 14e3663ed..000000000 --- a/wrap/tests/expected/@Point2/y.cpp +++ /dev/null @@ -1,10 +0,0 @@ -// automatically generated by wrap -#include -#include -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("y",nargout,nargin-1,0); - shared_ptr self = unwrap_shared_ptr< Point2 >(in[0],"Point2"); - double result = self->y(); - out[0] = wrap< double >(result); -} diff --git a/wrap/tests/expected/@Point2/y.m b/wrap/tests/expected/@Point2/y.m deleted file mode 100644 index ee5a55e1d..000000000 --- a/wrap/tests/expected/@Point2/y.m +++ /dev/null @@ -1,5 +0,0 @@ - automatically generated by wrap -function result = y(obj) -% usage: obj.y() - error('need to compile y.cpp'); -end diff --git a/wrap/tests/expected/@Point3/Point3.m b/wrap/tests/expected/@Point3/Point3.m deleted file mode 100644 index 3e7a6fd65..000000000 --- a/wrap/tests/expected/@Point3/Point3.m +++ /dev/null @@ -1,17 +0,0 @@ -% automatically generated by wrap -classdef Point3 < handle - properties - self = 0 - end - methods - function obj = Point3(varargin) - if (nargin == 3 && isa(varargin{1},'double') && isa(varargin{2},'double') && isa(varargin{3},'double')), obj.self = new_Point3_ddd(varargin{1},varargin{2},varargin{3}); end - if nargin ~= 13 && obj.self == 0, error('Point3 constructor failed'); end - end - function delete(obj) - delete_Point3(obj); - end - function display(obj), obj.print(''); end - function disp(obj), obj.display; end - end -end diff --git a/wrap/tests/expected/@Point3/norm.cpp b/wrap/tests/expected/@Point3/norm.cpp deleted file mode 100644 index 9936958d7..000000000 --- a/wrap/tests/expected/@Point3/norm.cpp +++ /dev/null @@ -1,11 +0,0 @@ -// automatically generated by wrap -#include -#include -using namespace geometry; -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("norm",nargout,nargin-1,0); - shared_ptr self = unwrap_shared_ptr< Point3 >(in[0],"Point3"); - double result = self->norm(); - out[0] = wrap< double >(result); -} diff --git a/wrap/tests/expected/@Point3/norm.m b/wrap/tests/expected/@Point3/norm.m deleted file mode 100644 index bb6482df4..000000000 --- a/wrap/tests/expected/@Point3/norm.m +++ /dev/null @@ -1,5 +0,0 @@ - automatically generated by wrap -function result = norm(obj) -% usage: obj.norm() - error('need to compile norm.cpp'); -end diff --git a/wrap/tests/expected/@Test/Test.m b/wrap/tests/expected/@Test/Test.m deleted file mode 100644 index b8e55381c..000000000 --- a/wrap/tests/expected/@Test/Test.m +++ /dev/null @@ -1,18 +0,0 @@ -% automatically generated by wrap -classdef Test < handle - properties - self = 0 - end - methods - function obj = Test(varargin) - if (nargin == 0), obj.self = new_Test_(); end - if (nargin == 2 && isa(varargin{1},'double') && isa(varargin{2},'double')), obj.self = new_Test_dM(varargin{1},varargin{2}); end - if nargin ~= 13 && obj.self == 0, error('Test constructor failed'); end - end - function delete(obj) - delete_Test(obj); - end - function display(obj), obj.print(''); end - function disp(obj), obj.display; end - end -end diff --git a/wrap/tests/expected/@Test/arg_EigenConstRef.cpp b/wrap/tests/expected/@Test/arg_EigenConstRef.cpp deleted file mode 100644 index 487741c07..000000000 --- a/wrap/tests/expected/@Test/arg_EigenConstRef.cpp +++ /dev/null @@ -1,11 +0,0 @@ -// automatically generated by wrap -#include -#include -using namespace geometry; -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("arg_EigenConstRef",nargout,nargin-1,1); - shared_ptr self = unwrap_shared_ptr< Test >(in[0],"Test"); - Matrix& value = *unwrap_shared_ptr< Matrix >(in[1], "Matrix"); - self->arg_EigenConstRef(value); -} diff --git a/wrap/tests/expected/@Test/arg_EigenConstRef.m b/wrap/tests/expected/@Test/arg_EigenConstRef.m deleted file mode 100644 index 76f190d99..000000000 --- a/wrap/tests/expected/@Test/arg_EigenConstRef.m +++ /dev/null @@ -1,5 +0,0 @@ - automatically generated by wrap -function result = arg_EigenConstRef(obj,value) -% usage: obj.arg_EigenConstRef(value) - error('need to compile arg_EigenConstRef.cpp'); -end diff --git a/wrap/tests/expected/@Test/create_MixedPtrs.cpp b/wrap/tests/expected/@Test/create_MixedPtrs.cpp deleted file mode 100644 index 269bb990c..000000000 --- a/wrap/tests/expected/@Test/create_MixedPtrs.cpp +++ /dev/null @@ -1,12 +0,0 @@ -// automatically generated by wrap -#include -#include -using namespace geometry; -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("create_MixedPtrs",nargout,nargin-1,0); - shared_ptr self = unwrap_shared_ptr< Test >(in[0],"Test"); - pair< Test, shared_ptr > result = self->create_MixedPtrs(); - out[0] = wrap_shared_ptr(make_shared< Test >(result.first),"Test"); - out[1] = wrap_shared_ptr(result.second,"Test"); -} diff --git a/wrap/tests/expected/@Test/create_MixedPtrs.m b/wrap/tests/expected/@Test/create_MixedPtrs.m deleted file mode 100644 index 764ce822c..000000000 --- a/wrap/tests/expected/@Test/create_MixedPtrs.m +++ /dev/null @@ -1,5 +0,0 @@ - automatically generated by wrap -function [first,second] = create_MixedPtrs(obj) -% usage: obj.create_MixedPtrs() - error('need to compile create_MixedPtrs.cpp'); -end diff --git a/wrap/tests/expected/@Test/create_ptrs.cpp b/wrap/tests/expected/@Test/create_ptrs.cpp deleted file mode 100644 index bfd9f39bf..000000000 --- a/wrap/tests/expected/@Test/create_ptrs.cpp +++ /dev/null @@ -1,12 +0,0 @@ -// automatically generated by wrap -#include -#include -using namespace geometry; -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("create_ptrs",nargout,nargin-1,0); - shared_ptr self = unwrap_shared_ptr< Test >(in[0],"Test"); - pair< shared_ptr, shared_ptr > result = self->create_ptrs(); - out[0] = wrap_shared_ptr(result.first,"Test"); - out[1] = wrap_shared_ptr(result.second,"Test"); -} diff --git a/wrap/tests/expected/@Test/create_ptrs.m b/wrap/tests/expected/@Test/create_ptrs.m deleted file mode 100644 index b1623b5bc..000000000 --- a/wrap/tests/expected/@Test/create_ptrs.m +++ /dev/null @@ -1,5 +0,0 @@ - automatically generated by wrap -function [first,second] = create_ptrs(obj) -% usage: obj.create_ptrs() - error('need to compile create_ptrs.cpp'); -end diff --git a/wrap/tests/expected/@Test/print.cpp b/wrap/tests/expected/@Test/print.cpp deleted file mode 100644 index e93f5f09a..000000000 --- a/wrap/tests/expected/@Test/print.cpp +++ /dev/null @@ -1,10 +0,0 @@ -// automatically generated by wrap -#include -#include -using namespace geometry; -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("print",nargout,nargin-1,0); - shared_ptr self = unwrap_shared_ptr< Test >(in[0],"Test"); - self->print(); -} diff --git a/wrap/tests/expected/@Test/print.m b/wrap/tests/expected/@Test/print.m deleted file mode 100644 index 2adca017d..000000000 --- a/wrap/tests/expected/@Test/print.m +++ /dev/null @@ -1,5 +0,0 @@ - automatically generated by wrap -function result = print(obj) -% usage: obj.print() - error('need to compile print.cpp'); -end diff --git a/wrap/tests/expected/@Test/return_Point2Ptr.cpp b/wrap/tests/expected/@Test/return_Point2Ptr.cpp deleted file mode 100644 index 9ad2a4360..000000000 --- a/wrap/tests/expected/@Test/return_Point2Ptr.cpp +++ /dev/null @@ -1,12 +0,0 @@ -// automatically generated by wrap -#include -#include -using namespace geometry; -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("return_Point2Ptr",nargout,nargin-1,1); - shared_ptr self = unwrap_shared_ptr< Test >(in[0],"Test"); - bool value = unwrap< bool >(in[1]); - shared_ptr result = self->return_Point2Ptr(value); - out[0] = wrap_shared_ptr(result,"Point2"); -} diff --git a/wrap/tests/expected/@Test/return_Point2Ptr.m b/wrap/tests/expected/@Test/return_Point2Ptr.m deleted file mode 100644 index 410081dcb..000000000 --- a/wrap/tests/expected/@Test/return_Point2Ptr.m +++ /dev/null @@ -1,5 +0,0 @@ - automatically generated by wrap -function result = return_Point2Ptr(obj,value) -% usage: obj.return_Point2Ptr(value) - error('need to compile return_Point2Ptr.cpp'); -end diff --git a/wrap/tests/expected/@Test/return_Test.cpp b/wrap/tests/expected/@Test/return_Test.cpp deleted file mode 100644 index 73c63a899..000000000 --- a/wrap/tests/expected/@Test/return_Test.cpp +++ /dev/null @@ -1,12 +0,0 @@ -// automatically generated by wrap -#include -#include -using namespace geometry; -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("return_Test",nargout,nargin-1,1); - shared_ptr self = unwrap_shared_ptr< Test >(in[0],"Test"); - shared_ptr value = unwrap_shared_ptr< Test >(in[1], "Test"); - Test result = self->return_Test(value); - out[0] = wrap_shared_ptr(make_shared< Test >(result),"Test"); -} diff --git a/wrap/tests/expected/@Test/return_Test.m b/wrap/tests/expected/@Test/return_Test.m deleted file mode 100644 index 2faa73be3..000000000 --- a/wrap/tests/expected/@Test/return_Test.m +++ /dev/null @@ -1,5 +0,0 @@ - automatically generated by wrap -function result = return_Test(obj,value) -% usage: obj.return_Test(value) - error('need to compile return_Test.cpp'); -end diff --git a/wrap/tests/expected/@Test/return_TestPtr.cpp b/wrap/tests/expected/@Test/return_TestPtr.cpp deleted file mode 100644 index 607e48cfd..000000000 --- a/wrap/tests/expected/@Test/return_TestPtr.cpp +++ /dev/null @@ -1,12 +0,0 @@ -// automatically generated by wrap -#include -#include -using namespace geometry; -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("return_TestPtr",nargout,nargin-1,1); - shared_ptr self = unwrap_shared_ptr< Test >(in[0],"Test"); - shared_ptr value = unwrap_shared_ptr< Test >(in[1], "Test"); - shared_ptr result = self->return_TestPtr(value); - out[0] = wrap_shared_ptr(result,"Test"); -} diff --git a/wrap/tests/expected/@Test/return_TestPtr.m b/wrap/tests/expected/@Test/return_TestPtr.m deleted file mode 100644 index 7c40e76c6..000000000 --- a/wrap/tests/expected/@Test/return_TestPtr.m +++ /dev/null @@ -1,5 +0,0 @@ - automatically generated by wrap -function result = return_TestPtr(obj,value) -% usage: obj.return_TestPtr(value) - error('need to compile return_TestPtr.cpp'); -end diff --git a/wrap/tests/expected/@Test/return_bool.cpp b/wrap/tests/expected/@Test/return_bool.cpp deleted file mode 100644 index d700ead2b..000000000 --- a/wrap/tests/expected/@Test/return_bool.cpp +++ /dev/null @@ -1,12 +0,0 @@ -// automatically generated by wrap -#include -#include -using namespace geometry; -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("return_bool",nargout,nargin-1,1); - shared_ptr self = unwrap_shared_ptr< Test >(in[0],"Test"); - bool value = unwrap< bool >(in[1]); - bool result = self->return_bool(value); - out[0] = wrap< bool >(result); -} diff --git a/wrap/tests/expected/@Test/return_bool.m b/wrap/tests/expected/@Test/return_bool.m deleted file mode 100644 index 76fc4363b..000000000 --- a/wrap/tests/expected/@Test/return_bool.m +++ /dev/null @@ -1,5 +0,0 @@ - automatically generated by wrap -function result = return_bool(obj,value) -% usage: obj.return_bool(value) - error('need to compile return_bool.cpp'); -end diff --git a/wrap/tests/expected/@Test/return_double.cpp b/wrap/tests/expected/@Test/return_double.cpp deleted file mode 100644 index 38770e1cd..000000000 --- a/wrap/tests/expected/@Test/return_double.cpp +++ /dev/null @@ -1,12 +0,0 @@ -// automatically generated by wrap -#include -#include -using namespace geometry; -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("return_double",nargout,nargin-1,1); - shared_ptr self = unwrap_shared_ptr< Test >(in[0],"Test"); - double value = unwrap< double >(in[1]); - double result = self->return_double(value); - out[0] = wrap< double >(result); -} diff --git a/wrap/tests/expected/@Test/return_double.m b/wrap/tests/expected/@Test/return_double.m deleted file mode 100644 index daed1d34b..000000000 --- a/wrap/tests/expected/@Test/return_double.m +++ /dev/null @@ -1,5 +0,0 @@ - automatically generated by wrap -function result = return_double(obj,value) -% usage: obj.return_double(value) - error('need to compile return_double.cpp'); -end diff --git a/wrap/tests/expected/@Test/return_field.cpp b/wrap/tests/expected/@Test/return_field.cpp deleted file mode 100644 index b5e067801..000000000 --- a/wrap/tests/expected/@Test/return_field.cpp +++ /dev/null @@ -1,12 +0,0 @@ -// automatically generated by wrap -#include -#include -using namespace geometry; -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("return_field",nargout,nargin-1,1); - shared_ptr self = unwrap_shared_ptr< Test >(in[0],"Test"); - Test& t = *unwrap_shared_ptr< Test >(in[1], "Test"); - bool result = self->return_field(t); - out[0] = wrap< bool >(result); -} diff --git a/wrap/tests/expected/@Test/return_field.m b/wrap/tests/expected/@Test/return_field.m deleted file mode 100644 index 11b5ebe07..000000000 --- a/wrap/tests/expected/@Test/return_field.m +++ /dev/null @@ -1,5 +0,0 @@ - automatically generated by wrap -function result = return_field(obj,t) -% usage: obj.return_field(t) - error('need to compile return_field.cpp'); -end diff --git a/wrap/tests/expected/@Test/return_int.cpp b/wrap/tests/expected/@Test/return_int.cpp deleted file mode 100644 index e2dfd25e8..000000000 --- a/wrap/tests/expected/@Test/return_int.cpp +++ /dev/null @@ -1,12 +0,0 @@ -// automatically generated by wrap -#include -#include -using namespace geometry; -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("return_int",nargout,nargin-1,1); - shared_ptr self = unwrap_shared_ptr< Test >(in[0],"Test"); - int value = unwrap< int >(in[1]); - int result = self->return_int(value); - out[0] = wrap< int >(result); -} diff --git a/wrap/tests/expected/@Test/return_int.m b/wrap/tests/expected/@Test/return_int.m deleted file mode 100644 index a6783acdf..000000000 --- a/wrap/tests/expected/@Test/return_int.m +++ /dev/null @@ -1,5 +0,0 @@ - automatically generated by wrap -function result = return_int(obj,value) -% usage: obj.return_int(value) - error('need to compile return_int.cpp'); -end diff --git a/wrap/tests/expected/@Test/return_matrix1.cpp b/wrap/tests/expected/@Test/return_matrix1.cpp deleted file mode 100644 index 8bb9acff8..000000000 --- a/wrap/tests/expected/@Test/return_matrix1.cpp +++ /dev/null @@ -1,12 +0,0 @@ -// automatically generated by wrap -#include -#include -using namespace geometry; -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("return_matrix1",nargout,nargin-1,1); - shared_ptr self = unwrap_shared_ptr< Test >(in[0],"Test"); - Matrix value = unwrap< Matrix >(in[1]); - Matrix result = self->return_matrix1(value); - out[0] = wrap< Matrix >(result); -} diff --git a/wrap/tests/expected/@Test/return_matrix1.m b/wrap/tests/expected/@Test/return_matrix1.m deleted file mode 100644 index 302f15372..000000000 --- a/wrap/tests/expected/@Test/return_matrix1.m +++ /dev/null @@ -1,5 +0,0 @@ - automatically generated by wrap -function result = return_matrix1(obj,value) -% usage: obj.return_matrix1(value) - error('need to compile return_matrix1.cpp'); -end diff --git a/wrap/tests/expected/@Test/return_matrix2.cpp b/wrap/tests/expected/@Test/return_matrix2.cpp deleted file mode 100644 index f1a22da47..000000000 --- a/wrap/tests/expected/@Test/return_matrix2.cpp +++ /dev/null @@ -1,12 +0,0 @@ -// automatically generated by wrap -#include -#include -using namespace geometry; -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("return_matrix2",nargout,nargin-1,1); - shared_ptr self = unwrap_shared_ptr< Test >(in[0],"Test"); - Matrix value = unwrap< Matrix >(in[1]); - Matrix result = self->return_matrix2(value); - out[0] = wrap< Matrix >(result); -} diff --git a/wrap/tests/expected/@Test/return_matrix2.m b/wrap/tests/expected/@Test/return_matrix2.m deleted file mode 100644 index 3ed4d0ec7..000000000 --- a/wrap/tests/expected/@Test/return_matrix2.m +++ /dev/null @@ -1,5 +0,0 @@ - automatically generated by wrap -function result = return_matrix2(obj,value) -% usage: obj.return_matrix2(value) - error('need to compile return_matrix2.cpp'); -end diff --git a/wrap/tests/expected/@Test/return_pair.cpp b/wrap/tests/expected/@Test/return_pair.cpp deleted file mode 100644 index 8f6949d7c..000000000 --- a/wrap/tests/expected/@Test/return_pair.cpp +++ /dev/null @@ -1,14 +0,0 @@ -// automatically generated by wrap -#include -#include -using namespace geometry; -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("return_pair",nargout,nargin-1,2); - shared_ptr self = unwrap_shared_ptr< Test >(in[0],"Test"); - Vector v = unwrap< Vector >(in[1]); - Matrix A = unwrap< Matrix >(in[2]); - pair< Vector, Matrix > result = self->return_pair(v,A); - out[0] = wrap< Vector >(result.first); - out[1] = wrap< Matrix >(result.second); -} diff --git a/wrap/tests/expected/@Test/return_pair.m b/wrap/tests/expected/@Test/return_pair.m deleted file mode 100644 index abb97336c..000000000 --- a/wrap/tests/expected/@Test/return_pair.m +++ /dev/null @@ -1,5 +0,0 @@ - automatically generated by wrap -function [first,second] = return_pair(obj,v,A) -% usage: obj.return_pair(v,A) - error('need to compile return_pair.cpp'); -end diff --git a/wrap/tests/expected/@Test/return_ptrs.cpp b/wrap/tests/expected/@Test/return_ptrs.cpp deleted file mode 100644 index 20d6c57fe..000000000 --- a/wrap/tests/expected/@Test/return_ptrs.cpp +++ /dev/null @@ -1,14 +0,0 @@ -// automatically generated by wrap -#include -#include -using namespace geometry; -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("return_ptrs",nargout,nargin-1,2); - shared_ptr self = unwrap_shared_ptr< Test >(in[0],"Test"); - shared_ptr p1 = unwrap_shared_ptr< Test >(in[1], "Test"); - shared_ptr p2 = unwrap_shared_ptr< Test >(in[2], "Test"); - pair< shared_ptr, shared_ptr > result = self->return_ptrs(p1,p2); - out[0] = wrap_shared_ptr(result.first,"Test"); - out[1] = wrap_shared_ptr(result.second,"Test"); -} diff --git a/wrap/tests/expected/@Test/return_ptrs.m b/wrap/tests/expected/@Test/return_ptrs.m deleted file mode 100644 index bed198563..000000000 --- a/wrap/tests/expected/@Test/return_ptrs.m +++ /dev/null @@ -1,5 +0,0 @@ - automatically generated by wrap -function [first,second] = return_ptrs(obj,p1,p2) -% usage: obj.return_ptrs(p1,p2) - error('need to compile return_ptrs.cpp'); -end diff --git a/wrap/tests/expected/@Test/return_size_t.cpp b/wrap/tests/expected/@Test/return_size_t.cpp deleted file mode 100644 index 6b12a167b..000000000 --- a/wrap/tests/expected/@Test/return_size_t.cpp +++ /dev/null @@ -1,12 +0,0 @@ -// automatically generated by wrap -#include -#include -using namespace geometry; -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("return_size_t",nargout,nargin-1,1); - shared_ptr self = unwrap_shared_ptr< Test >(in[0],"Test"); - size_t value = unwrap< size_t >(in[1]); - size_t result = self->return_size_t(value); - out[0] = wrap< size_t >(result); -} diff --git a/wrap/tests/expected/@Test/return_size_t.m b/wrap/tests/expected/@Test/return_size_t.m deleted file mode 100644 index 7cb2c6f0f..000000000 --- a/wrap/tests/expected/@Test/return_size_t.m +++ /dev/null @@ -1,5 +0,0 @@ - automatically generated by wrap -function result = return_size_t(obj,value) -% usage: obj.return_size_t(value) - error('need to compile return_size_t.cpp'); -end diff --git a/wrap/tests/expected/@Test/return_string.cpp b/wrap/tests/expected/@Test/return_string.cpp deleted file mode 100644 index c05a57fba..000000000 --- a/wrap/tests/expected/@Test/return_string.cpp +++ /dev/null @@ -1,12 +0,0 @@ -// automatically generated by wrap -#include -#include -using namespace geometry; -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("return_string",nargout,nargin-1,1); - shared_ptr self = unwrap_shared_ptr< Test >(in[0],"Test"); - string value = unwrap< string >(in[1]); - string result = self->return_string(value); - out[0] = wrap< string >(result); -} diff --git a/wrap/tests/expected/@Test/return_string.m b/wrap/tests/expected/@Test/return_string.m deleted file mode 100644 index 5661df443..000000000 --- a/wrap/tests/expected/@Test/return_string.m +++ /dev/null @@ -1,5 +0,0 @@ - automatically generated by wrap -function result = return_string(obj,value) -% usage: obj.return_string(value) - error('need to compile return_string.cpp'); -end diff --git a/wrap/tests/expected/@Test/return_vector1.cpp b/wrap/tests/expected/@Test/return_vector1.cpp deleted file mode 100644 index 3710e5d48..000000000 --- a/wrap/tests/expected/@Test/return_vector1.cpp +++ /dev/null @@ -1,12 +0,0 @@ -// automatically generated by wrap -#include -#include -using namespace geometry; -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("return_vector1",nargout,nargin-1,1); - shared_ptr self = unwrap_shared_ptr< Test >(in[0],"Test"); - Vector value = unwrap< Vector >(in[1]); - Vector result = self->return_vector1(value); - out[0] = wrap< Vector >(result); -} diff --git a/wrap/tests/expected/@Test/return_vector1.m b/wrap/tests/expected/@Test/return_vector1.m deleted file mode 100644 index 3746c4c20..000000000 --- a/wrap/tests/expected/@Test/return_vector1.m +++ /dev/null @@ -1,5 +0,0 @@ - automatically generated by wrap -function result = return_vector1(obj,value) -% usage: obj.return_vector1(value) - error('need to compile return_vector1.cpp'); -end diff --git a/wrap/tests/expected/@Test/return_vector2.cpp b/wrap/tests/expected/@Test/return_vector2.cpp deleted file mode 100644 index 72564f05c..000000000 --- a/wrap/tests/expected/@Test/return_vector2.cpp +++ /dev/null @@ -1,12 +0,0 @@ -// automatically generated by wrap -#include -#include -using namespace geometry; -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("return_vector2",nargout,nargin-1,1); - shared_ptr self = unwrap_shared_ptr< Test >(in[0],"Test"); - Vector value = unwrap< Vector >(in[1]); - Vector result = self->return_vector2(value); - out[0] = wrap< Vector >(result); -} diff --git a/wrap/tests/expected/@Test/return_vector2.m b/wrap/tests/expected/@Test/return_vector2.m deleted file mode 100644 index 426c63457..000000000 --- a/wrap/tests/expected/@Test/return_vector2.m +++ /dev/null @@ -1,5 +0,0 @@ - automatically generated by wrap -function result = return_vector2(obj,value) -% usage: obj.return_vector2(value) - error('need to compile return_vector2.cpp'); -end diff --git a/wrap/tests/expected/Makefile b/wrap/tests/expected/Makefile deleted file mode 100644 index a8959757b..000000000 --- a/wrap/tests/expected/Makefile +++ /dev/null @@ -1,103 +0,0 @@ -# automatically generated by wrap - -MEX = mex -MEXENDING = mexa64 -mex_flags = -O5 - -all: Point2 Point3 Test - -# Point2 -new_Point2_.$(MEXENDING): new_Point2_.cpp - $(MEX) $(mex_flags) new_Point2_.cpp -output new_Point2_ -new_Point2_dd.$(MEXENDING): new_Point2_dd.cpp - $(MEX) $(mex_flags) new_Point2_dd.cpp -output new_Point2_dd -delete_Point2.$(MEXENDING): delete_Point2.cpp - $(MEX) $(mex_flags) delete_Point2.cpp -output delete_Point2 -@Point2/x.$(MEXENDING): @Point2/x.cpp - $(MEX) $(mex_flags) @Point2/x.cpp -output @Point2/x -@Point2/y.$(MEXENDING): @Point2/y.cpp - $(MEX) $(mex_flags) @Point2/y.cpp -output @Point2/y -@Point2/dim.$(MEXENDING): @Point2/dim.cpp - $(MEX) $(mex_flags) @Point2/dim.cpp -output @Point2/dim -@Point2/returnChar.$(MEXENDING): @Point2/returnChar.cpp - $(MEX) $(mex_flags) @Point2/returnChar.cpp -output @Point2/returnChar -@Point2/argChar.$(MEXENDING): @Point2/argChar.cpp - $(MEX) $(mex_flags) @Point2/argChar.cpp -output @Point2/argChar -@Point2/argUChar.$(MEXENDING): @Point2/argUChar.cpp - $(MEX) $(mex_flags) @Point2/argUChar.cpp -output @Point2/argUChar -@Point2/vectorConfusion.$(MEXENDING): @Point2/vectorConfusion.cpp - $(MEX) $(mex_flags) @Point2/vectorConfusion.cpp -output @Point2/vectorConfusion - -Point2: new_Point2_.$(MEXENDING) new_Point2_dd.$(MEXENDING) delete_Point2.$(MEXENDING) @Point2/x.$(MEXENDING) @Point2/y.$(MEXENDING) @Point2/dim.$(MEXENDING) @Point2/returnChar.$(MEXENDING) @Point2/argChar.$(MEXENDING) @Point2/argUChar.$(MEXENDING) @Point2/vectorConfusion.$(MEXENDING) - -# Point3 -new_Point3_ddd.$(MEXENDING): new_Point3_ddd.cpp - $(MEX) $(mex_flags) new_Point3_ddd.cpp -output new_Point3_ddd -delete_Point3.$(MEXENDING): delete_Point3.cpp - $(MEX) $(mex_flags) delete_Point3.cpp -output delete_Point3 -Point3_staticFunction.$(MEXENDING): Point3_staticFunction.cpp - $(MEX) $(mex_flags) Point3_staticFunction.cpp -output Point3_staticFunction -Point3_StaticFunctionRet.$(MEXENDING): Point3_StaticFunctionRet.cpp - $(MEX) $(mex_flags) Point3_StaticFunctionRet.cpp -output Point3_StaticFunctionRet -@Point3/norm.$(MEXENDING): @Point3/norm.cpp - $(MEX) $(mex_flags) @Point3/norm.cpp -output @Point3/norm - -Point3: new_Point3_ddd.$(MEXENDING) delete_Point3.$(MEXENDING) Point3_staticFunction.$(MEXENDING) Point3_StaticFunctionRet.$(MEXENDING) @Point3/norm.$(MEXENDING) - -# Test -new_Test_.$(MEXENDING): new_Test_.cpp - $(MEX) $(mex_flags) new_Test_.cpp -output new_Test_ -new_Test_dM.$(MEXENDING): new_Test_dM.cpp - $(MEX) $(mex_flags) new_Test_dM.cpp -output new_Test_dM -delete_Test.$(MEXENDING): delete_Test.cpp - $(MEX) $(mex_flags) delete_Test.cpp -output delete_Test -@Test/return_pair.$(MEXENDING): @Test/return_pair.cpp - $(MEX) $(mex_flags) @Test/return_pair.cpp -output @Test/return_pair -@Test/return_bool.$(MEXENDING): @Test/return_bool.cpp - $(MEX) $(mex_flags) @Test/return_bool.cpp -output @Test/return_bool -@Test/return_size_t.$(MEXENDING): @Test/return_size_t.cpp - $(MEX) $(mex_flags) @Test/return_size_t.cpp -output @Test/return_size_t -@Test/return_int.$(MEXENDING): @Test/return_int.cpp - $(MEX) $(mex_flags) @Test/return_int.cpp -output @Test/return_int -@Test/return_double.$(MEXENDING): @Test/return_double.cpp - $(MEX) $(mex_flags) @Test/return_double.cpp -output @Test/return_double -@Test/return_string.$(MEXENDING): @Test/return_string.cpp - $(MEX) $(mex_flags) @Test/return_string.cpp -output @Test/return_string -@Test/return_vector1.$(MEXENDING): @Test/return_vector1.cpp - $(MEX) $(mex_flags) @Test/return_vector1.cpp -output @Test/return_vector1 -@Test/return_matrix1.$(MEXENDING): @Test/return_matrix1.cpp - $(MEX) $(mex_flags) @Test/return_matrix1.cpp -output @Test/return_matrix1 -@Test/return_vector2.$(MEXENDING): @Test/return_vector2.cpp - $(MEX) $(mex_flags) @Test/return_vector2.cpp -output @Test/return_vector2 -@Test/return_matrix2.$(MEXENDING): @Test/return_matrix2.cpp - $(MEX) $(mex_flags) @Test/return_matrix2.cpp -output @Test/return_matrix2 -@Test/arg_EigenConstRef.$(MEXENDING): @Test/arg_EigenConstRef.cpp - $(MEX) $(mex_flags) @Test/arg_EigenConstRef.cpp -output @Test/arg_EigenConstRef -@Test/return_field.$(MEXENDING): @Test/return_field.cpp - $(MEX) $(mex_flags) @Test/return_field.cpp -output @Test/return_field -@Test/return_TestPtr.$(MEXENDING): @Test/return_TestPtr.cpp - $(MEX) $(mex_flags) @Test/return_TestPtr.cpp -output @Test/return_TestPtr -@Test/return_Test.$(MEXENDING): @Test/return_Test.cpp - $(MEX) $(mex_flags) @Test/return_Test.cpp -output @Test/return_Test -@Test/return_Point2Ptr.$(MEXENDING): @Test/return_Point2Ptr.cpp - $(MEX) $(mex_flags) @Test/return_Point2Ptr.cpp -output @Test/return_Point2Ptr -@Test/create_ptrs.$(MEXENDING): @Test/create_ptrs.cpp - $(MEX) $(mex_flags) @Test/create_ptrs.cpp -output @Test/create_ptrs -@Test/create_MixedPtrs.$(MEXENDING): @Test/create_MixedPtrs.cpp - $(MEX) $(mex_flags) @Test/create_MixedPtrs.cpp -output @Test/create_MixedPtrs -@Test/return_ptrs.$(MEXENDING): @Test/return_ptrs.cpp - $(MEX) $(mex_flags) @Test/return_ptrs.cpp -output @Test/return_ptrs -@Test/print.$(MEXENDING): @Test/print.cpp - $(MEX) $(mex_flags) @Test/print.cpp -output @Test/print - -Test: new_Test_.$(MEXENDING) new_Test_dM.$(MEXENDING) delete_Test.$(MEXENDING) @Test/return_pair.$(MEXENDING) @Test/return_bool.$(MEXENDING) @Test/return_size_t.$(MEXENDING) @Test/return_int.$(MEXENDING) @Test/return_double.$(MEXENDING) @Test/return_string.$(MEXENDING) @Test/return_vector1.$(MEXENDING) @Test/return_matrix1.$(MEXENDING) @Test/return_vector2.$(MEXENDING) @Test/return_matrix2.$(MEXENDING) @Test/arg_EigenConstRef.$(MEXENDING) @Test/return_field.$(MEXENDING) @Test/return_TestPtr.$(MEXENDING) @Test/return_Test.$(MEXENDING) @Test/return_Point2Ptr.$(MEXENDING) @Test/create_ptrs.$(MEXENDING) @Test/create_MixedPtrs.$(MEXENDING) @Test/return_ptrs.$(MEXENDING) @Test/print.$(MEXENDING) - - - -clean: - rm -rf *.$(MEXENDING) - rm -rf @Point2/*.$(MEXENDING) - rm -rf @Point3/*.$(MEXENDING) - rm -rf @Test/*.$(MEXENDING) - - diff --git a/wrap/tests/expected/Point2.m b/wrap/tests/expected/Point2.m new file mode 100644 index 000000000..22dec9641 --- /dev/null +++ b/wrap/tests/expected/Point2.m @@ -0,0 +1,139 @@ +%class Point2, see Doxygen page for details +%at http://research.cc.gatech.edu/borg/sites/edu.borg/html/index.html +% +%-------Constructors------- +%Point2() +%Point2(double x, double y) +% +%-------Methods------- +%argChar(char a) : returns void +%argUChar(unsigned char a) : returns void +%dim() : returns int +%returnChar() : returns char +%vectorConfusion() : returns VectorNotEigen +%x() : returns double +%y() : returns double +% +classdef Point2 < handle + properties + ptr_Point2 = 0 + end + methods + function obj = Point2(varargin) + if nargin == 2 && isa(varargin{1}, 'uint64') && varargin{1} == uint64(5139824614673773682) + my_ptr = varargin{2}; + geometry_wrapper(0, my_ptr); + elseif nargin == 0 + my_ptr = geometry_wrapper(1); + elseif nargin == 2 && isa(varargin{1},'double') && isa(varargin{2},'double') + my_ptr = geometry_wrapper(2, varargin{1}, varargin{2}); + else + error('Arguments do not match any overload of Point2 constructor'); + end + obj.ptr_Point2 = my_ptr; + end + + function delete(obj) + geometry_wrapper(3, obj.ptr_Point2); + end + + function display(obj), obj.print(''); end + %DISPLAY Calls print on the object + function disp(obj), obj.display; end + %DISP Calls print on the object + function varargout = argChar(this, varargin) + % ARGCHAR usage: argChar(char a) : returns void + % Doxygen can be found at http://research.cc.gatech.edu/borg/sites/edu.borg/html/index.html + % + % Method Overloads + % argChar(char a) + if length(varargin) == 1 && isa(varargin{1},'char') + geometry_wrapper(4, this, varargin{:}); + else + error('Arguments do not match any overload of function Point2.argChar'); + end + end + + function varargout = argUChar(this, varargin) + % ARGUCHAR usage: argUChar(unsigned char a) : returns void + % Doxygen can be found at http://research.cc.gatech.edu/borg/sites/edu.borg/html/index.html + % + % Method Overloads + % argUChar(unsigned char a) + if length(varargin) == 1 && isa(varargin{1},'char') + geometry_wrapper(5, this, varargin{:}); + else + error('Arguments do not match any overload of function Point2.argUChar'); + end + end + + function varargout = dim(this, varargin) + % DIM usage: dim() : returns int + % Doxygen can be found at http://research.cc.gatech.edu/borg/sites/edu.borg/html/index.html + % + % Method Overloads + % dim() + if length(varargin) == 0 + varargout{1} = geometry_wrapper(6, this, varargin{:}); + else + error('Arguments do not match any overload of function Point2.dim'); + end + end + + function varargout = returnChar(this, varargin) + % RETURNCHAR usage: returnChar() : returns char + % Doxygen can be found at http://research.cc.gatech.edu/borg/sites/edu.borg/html/index.html + % + % Method Overloads + % returnChar() + if length(varargin) == 0 + varargout{1} = geometry_wrapper(7, this, varargin{:}); + else + error('Arguments do not match any overload of function Point2.returnChar'); + end + end + + function varargout = vectorConfusion(this, varargin) + % VECTORCONFUSION usage: vectorConfusion() : returns VectorNotEigen + % Doxygen can be found at http://research.cc.gatech.edu/borg/sites/edu.borg/html/index.html + % + % Method Overloads + % vectorConfusion() + if length(varargin) == 0 + varargout{1} = geometry_wrapper(8, this, varargin{:}); + else + error('Arguments do not match any overload of function Point2.vectorConfusion'); + end + end + + function varargout = x(this, varargin) + % X usage: x() : returns double + % Doxygen can be found at http://research.cc.gatech.edu/borg/sites/edu.borg/html/index.html + % + % Method Overloads + % x() + if length(varargin) == 0 + varargout{1} = geometry_wrapper(9, this, varargin{:}); + else + error('Arguments do not match any overload of function Point2.x'); + end + end + + function varargout = y(this, varargin) + % Y usage: y() : returns double + % Doxygen can be found at http://research.cc.gatech.edu/borg/sites/edu.borg/html/index.html + % + % Method Overloads + % y() + if length(varargin) == 0 + varargout{1} = geometry_wrapper(10, this, varargin{:}); + else + error('Arguments do not match any overload of function Point2.y'); + end + end + + end + + methods(Static = true) + end +end diff --git a/wrap/tests/expected/Point3.m b/wrap/tests/expected/Point3.m new file mode 100644 index 000000000..3a90f1982 --- /dev/null +++ b/wrap/tests/expected/Point3.m @@ -0,0 +1,82 @@ +%class Point3, see Doxygen page for details +%at http://research.cc.gatech.edu/borg/sites/edu.borg/html/index.html +% +%-------Constructors------- +%Point3(double x, double y, double z) +% +%-------Methods------- +%norm() : returns double +% +%-------Static Methods------- +%StaticFunctionRet(double z) : returns Point3 +%staticFunction() : returns double +% +classdef Point3 < handle + properties + ptr_Point3 = 0 + end + methods + function obj = Point3(varargin) + if nargin == 2 && isa(varargin{1}, 'uint64') && varargin{1} == uint64(5139824614673773682) + my_ptr = varargin{2}; + geometry_wrapper(11, my_ptr); + elseif nargin == 3 && isa(varargin{1},'double') && isa(varargin{2},'double') && isa(varargin{3},'double') + my_ptr = geometry_wrapper(12, varargin{1}, varargin{2}, varargin{3}); + else + error('Arguments do not match any overload of Point3 constructor'); + end + obj.ptr_Point3 = my_ptr; + end + + function delete(obj) + geometry_wrapper(13, obj.ptr_Point3); + end + + function display(obj), obj.print(''); end + %DISPLAY Calls print on the object + function disp(obj), obj.display; end + %DISP Calls print on the object + function varargout = norm(this, varargin) + % NORM usage: norm() : returns double + % Doxygen can be found at http://research.cc.gatech.edu/borg/sites/edu.borg/html/index.html + % + % Method Overloads + % norm() + if length(varargin) == 0 + varargout{1} = geometry_wrapper(14, this, varargin{:}); + else + error('Arguments do not match any overload of function Point3.norm'); + end + end + + end + + methods(Static = true) + function varargout = StaticFunctionRet(varargin) + % STATICFUNCTIONRET usage: StaticFunctionRet(double z) : returns Point3 + % Doxygen can be found at http://research.cc.gatech.edu/borg/sites/edu.borg/html/index.html + % + % Usage + % STATICFUNCTIONRET(double z) + if length(varargin) == 1 && isa(varargin{1},'double') + varargout{1} = geometry_wrapper(15, varargin{:}); + else + error('Arguments do not match any overload of function Point3.StaticFunctionRet'); + end + end + + function varargout = StaticFunction(varargin) + % STATICFUNCTION usage: staticFunction() : returns double + % Doxygen can be found at http://research.cc.gatech.edu/borg/sites/edu.borg/html/index.html + % + % Usage + % STATICFUNCTION() + if length(varargin) == 0 + varargout{1} = geometry_wrapper(16, varargin{:}); + else + error('Arguments do not match any overload of function Point3.StaticFunction'); + end + end + + end +end diff --git a/wrap/tests/expected/Point3_StaticFunctionRet.cpp b/wrap/tests/expected/Point3_StaticFunctionRet.cpp deleted file mode 100644 index 062194bd5..000000000 --- a/wrap/tests/expected/Point3_StaticFunctionRet.cpp +++ /dev/null @@ -1,11 +0,0 @@ -// automatically generated by wrap -#include -#include -using namespace geometry; -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("Point3_StaticFunctionRet",nargout,nargin,1); - double z = unwrap< double >(in[0]); - Point3 result = Point3::StaticFunctionRet(z); - out[0] = wrap_shared_ptr(make_shared< Point3 >(result),"Point3"); -} diff --git a/wrap/tests/expected/Point3_StaticFunctionRet.m b/wrap/tests/expected/Point3_StaticFunctionRet.m deleted file mode 100644 index 433d3c00d..000000000 --- a/wrap/tests/expected/Point3_StaticFunctionRet.m +++ /dev/null @@ -1,5 +0,0 @@ - automatically generated by wrap -function result = Point3_StaticFunctionRet(z) -% usage: x = Point3_StaticFunctionRet(z) - error('need to compile Point3_StaticFunctionRet.cpp'); -end diff --git a/wrap/tests/expected/Point3_staticFunction.cpp b/wrap/tests/expected/Point3_staticFunction.cpp deleted file mode 100644 index 6adfdbe5a..000000000 --- a/wrap/tests/expected/Point3_staticFunction.cpp +++ /dev/null @@ -1,10 +0,0 @@ -// automatically generated by wrap -#include -#include -using namespace geometry; -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("Point3_staticFunction",nargout,nargin,0); - double result = Point3::staticFunction(); - out[0] = wrap< double >(result); -} diff --git a/wrap/tests/expected/Point3_staticFunction.m b/wrap/tests/expected/Point3_staticFunction.m deleted file mode 100644 index ccf9b85bd..000000000 --- a/wrap/tests/expected/Point3_staticFunction.m +++ /dev/null @@ -1,5 +0,0 @@ - automatically generated by wrap -function result = Point3_staticFunction() -% usage: x = Point3_staticFunction() - error('need to compile Point3_staticFunction.cpp'); -end diff --git a/wrap/tests/expected/Test.m b/wrap/tests/expected/Test.m new file mode 100644 index 000000000..e493b9a04 --- /dev/null +++ b/wrap/tests/expected/Test.m @@ -0,0 +1,307 @@ +%class Test, see Doxygen page for details +%at http://research.cc.gatech.edu/borg/sites/edu.borg/html/index.html +% +%-------Constructors------- +%Test() +%Test(double a, Matrix b) +% +%-------Methods------- +%arg_EigenConstRef(Matrix value) : returns void +%create_MixedPtrs() : returns pair< Test, SharedTest > +%create_ptrs() : returns pair< SharedTest, SharedTest > +%print() : returns void +%return_Point2Ptr(bool value) : returns Point2 +%return_Test(Test value) : returns Test +%return_TestPtr(Test value) : returns Test +%return_bool(bool value) : returns bool +%return_double(double value) : returns double +%return_field(Test t) : returns bool +%return_int(int value) : returns int +%return_matrix1(Matrix value) : returns Matrix +%return_matrix2(Matrix value) : returns Matrix +%return_pair(Vector v, Matrix A) : returns pair< Vector, Matrix > +%return_ptrs(Test p1, Test p2) : returns pair< SharedTest, SharedTest > +%return_size_t(size_t value) : returns size_t +%return_string(string value) : returns string +%return_vector1(Vector value) : returns Vector +%return_vector2(Vector value) : returns Vector +% +classdef Test < handle + properties + ptr_Test = 0 + end + methods + function obj = Test(varargin) + if nargin == 2 && isa(varargin{1}, 'uint64') && varargin{1} == uint64(5139824614673773682) + my_ptr = varargin{2}; + geometry_wrapper(17, my_ptr); + elseif nargin == 0 + my_ptr = geometry_wrapper(18); + elseif nargin == 2 && isa(varargin{1},'double') && isa(varargin{2},'double') + my_ptr = geometry_wrapper(19, varargin{1}, varargin{2}); + else + error('Arguments do not match any overload of Test constructor'); + end + obj.ptr_Test = my_ptr; + end + + function delete(obj) + geometry_wrapper(20, obj.ptr_Test); + end + + function display(obj), obj.print(''); end + %DISPLAY Calls print on the object + function disp(obj), obj.display; end + %DISP Calls print on the object + function varargout = arg_EigenConstRef(this, varargin) + % ARG_EIGENCONSTREF usage: arg_EigenConstRef(Matrix value) : returns void + % Doxygen can be found at http://research.cc.gatech.edu/borg/sites/edu.borg/html/index.html + % + % Method Overloads + % arg_EigenConstRef(Matrix value) + if length(varargin) == 1 && isa(varargin{1},'double') + geometry_wrapper(21, this, varargin{:}); + else + error('Arguments do not match any overload of function Test.arg_EigenConstRef'); + end + end + + function varargout = create_MixedPtrs(this, varargin) + % CREATE_MIXEDPTRS usage: create_MixedPtrs() : returns pair< Test, SharedTest > + % Doxygen can be found at http://research.cc.gatech.edu/borg/sites/edu.borg/html/index.html + % + % Method Overloads + % create_MixedPtrs() + if length(varargin) == 0 + [ varargout{1} varargout{2} ] = geometry_wrapper(22, this, varargin{:}); + else + error('Arguments do not match any overload of function Test.create_MixedPtrs'); + end + end + + function varargout = create_ptrs(this, varargin) + % CREATE_PTRS usage: create_ptrs() : returns pair< SharedTest, SharedTest > + % Doxygen can be found at http://research.cc.gatech.edu/borg/sites/edu.borg/html/index.html + % + % Method Overloads + % create_ptrs() + if length(varargin) == 0 + [ varargout{1} varargout{2} ] = geometry_wrapper(23, this, varargin{:}); + else + error('Arguments do not match any overload of function Test.create_ptrs'); + end + end + + function varargout = print(this, varargin) + % PRINT usage: print() : returns void + % Doxygen can be found at http://research.cc.gatech.edu/borg/sites/edu.borg/html/index.html + % + % Method Overloads + % print() + if length(varargin) == 0 + geometry_wrapper(24, this, varargin{:}); + else + error('Arguments do not match any overload of function Test.print'); + end + end + + function varargout = return_Point2Ptr(this, varargin) + % RETURN_POINT2PTR usage: return_Point2Ptr(bool value) : returns Point2 + % Doxygen can be found at http://research.cc.gatech.edu/borg/sites/edu.borg/html/index.html + % + % Method Overloads + % return_Point2Ptr(bool value) + if length(varargin) == 1 && isa(varargin{1},'logical') + varargout{1} = geometry_wrapper(25, this, varargin{:}); + else + error('Arguments do not match any overload of function Test.return_Point2Ptr'); + end + end + + function varargout = return_Test(this, varargin) + % RETURN_TEST usage: return_Test(Test value) : returns Test + % Doxygen can be found at http://research.cc.gatech.edu/borg/sites/edu.borg/html/index.html + % + % Method Overloads + % return_Test(Test value) + if length(varargin) == 1 && isa(varargin{1},'Test') + varargout{1} = geometry_wrapper(26, this, varargin{:}); + else + error('Arguments do not match any overload of function Test.return_Test'); + end + end + + function varargout = return_TestPtr(this, varargin) + % RETURN_TESTPTR usage: return_TestPtr(Test value) : returns Test + % Doxygen can be found at http://research.cc.gatech.edu/borg/sites/edu.borg/html/index.html + % + % Method Overloads + % return_TestPtr(Test value) + if length(varargin) == 1 && isa(varargin{1},'Test') + varargout{1} = geometry_wrapper(27, this, varargin{:}); + else + error('Arguments do not match any overload of function Test.return_TestPtr'); + end + end + + function varargout = return_bool(this, varargin) + % RETURN_BOOL usage: return_bool(bool value) : returns bool + % Doxygen can be found at http://research.cc.gatech.edu/borg/sites/edu.borg/html/index.html + % + % Method Overloads + % return_bool(bool value) + if length(varargin) == 1 && isa(varargin{1},'logical') + varargout{1} = geometry_wrapper(28, this, varargin{:}); + else + error('Arguments do not match any overload of function Test.return_bool'); + end + end + + function varargout = return_double(this, varargin) + % RETURN_DOUBLE usage: return_double(double value) : returns double + % Doxygen can be found at http://research.cc.gatech.edu/borg/sites/edu.borg/html/index.html + % + % Method Overloads + % return_double(double value) + if length(varargin) == 1 && isa(varargin{1},'double') + varargout{1} = geometry_wrapper(29, this, varargin{:}); + else + error('Arguments do not match any overload of function Test.return_double'); + end + end + + function varargout = return_field(this, varargin) + % RETURN_FIELD usage: return_field(Test t) : returns bool + % Doxygen can be found at http://research.cc.gatech.edu/borg/sites/edu.borg/html/index.html + % + % Method Overloads + % return_field(Test t) + if length(varargin) == 1 && isa(varargin{1},'Test') + varargout{1} = geometry_wrapper(30, this, varargin{:}); + else + error('Arguments do not match any overload of function Test.return_field'); + end + end + + function varargout = return_int(this, varargin) + % RETURN_INT usage: return_int(int value) : returns int + % Doxygen can be found at http://research.cc.gatech.edu/borg/sites/edu.borg/html/index.html + % + % Method Overloads + % return_int(int value) + if length(varargin) == 1 && isa(varargin{1},'numeric') + varargout{1} = geometry_wrapper(31, this, varargin{:}); + else + error('Arguments do not match any overload of function Test.return_int'); + end + end + + function varargout = return_matrix1(this, varargin) + % RETURN_MATRIX1 usage: return_matrix1(Matrix value) : returns Matrix + % Doxygen can be found at http://research.cc.gatech.edu/borg/sites/edu.borg/html/index.html + % + % Method Overloads + % return_matrix1(Matrix value) + if length(varargin) == 1 && isa(varargin{1},'double') + varargout{1} = geometry_wrapper(32, this, varargin{:}); + else + error('Arguments do not match any overload of function Test.return_matrix1'); + end + end + + function varargout = return_matrix2(this, varargin) + % RETURN_MATRIX2 usage: return_matrix2(Matrix value) : returns Matrix + % Doxygen can be found at http://research.cc.gatech.edu/borg/sites/edu.borg/html/index.html + % + % Method Overloads + % return_matrix2(Matrix value) + if length(varargin) == 1 && isa(varargin{1},'double') + varargout{1} = geometry_wrapper(33, this, varargin{:}); + else + error('Arguments do not match any overload of function Test.return_matrix2'); + end + end + + function varargout = return_pair(this, varargin) + % RETURN_PAIR usage: return_pair(Vector v, Matrix A) : returns pair< Vector, Matrix > + % Doxygen can be found at http://research.cc.gatech.edu/borg/sites/edu.borg/html/index.html + % + % Method Overloads + % return_pair(Vector v, Matrix A) + if length(varargin) == 2 && isa(varargin{1},'double') && isa(varargin{2},'double') + [ varargout{1} varargout{2} ] = geometry_wrapper(34, this, varargin{:}); + else + error('Arguments do not match any overload of function Test.return_pair'); + end + end + + function varargout = return_ptrs(this, varargin) + % RETURN_PTRS usage: return_ptrs(Test p1, Test p2) : returns pair< SharedTest, SharedTest > + % Doxygen can be found at http://research.cc.gatech.edu/borg/sites/edu.borg/html/index.html + % + % Method Overloads + % return_ptrs(Test p1, Test p2) + if length(varargin) == 2 && isa(varargin{1},'Test') && isa(varargin{2},'Test') + [ varargout{1} varargout{2} ] = geometry_wrapper(35, this, varargin{:}); + else + error('Arguments do not match any overload of function Test.return_ptrs'); + end + end + + function varargout = return_size_t(this, varargin) + % RETURN_SIZE_T usage: return_size_t(size_t value) : returns size_t + % Doxygen can be found at http://research.cc.gatech.edu/borg/sites/edu.borg/html/index.html + % + % Method Overloads + % return_size_t(size_t value) + if length(varargin) == 1 && isa(varargin{1},'numeric') + varargout{1} = geometry_wrapper(36, this, varargin{:}); + else + error('Arguments do not match any overload of function Test.return_size_t'); + end + end + + function varargout = return_string(this, varargin) + % RETURN_STRING usage: return_string(string value) : returns string + % Doxygen can be found at http://research.cc.gatech.edu/borg/sites/edu.borg/html/index.html + % + % Method Overloads + % return_string(string value) + if length(varargin) == 1 && isa(varargin{1},'char') + varargout{1} = geometry_wrapper(37, this, varargin{:}); + else + error('Arguments do not match any overload of function Test.return_string'); + end + end + + function varargout = return_vector1(this, varargin) + % RETURN_VECTOR1 usage: return_vector1(Vector value) : returns Vector + % Doxygen can be found at http://research.cc.gatech.edu/borg/sites/edu.borg/html/index.html + % + % Method Overloads + % return_vector1(Vector value) + if length(varargin) == 1 && isa(varargin{1},'double') + varargout{1} = geometry_wrapper(38, this, varargin{:}); + else + error('Arguments do not match any overload of function Test.return_vector1'); + end + end + + function varargout = return_vector2(this, varargin) + % RETURN_VECTOR2 usage: return_vector2(Vector value) : returns Vector + % Doxygen can be found at http://research.cc.gatech.edu/borg/sites/edu.borg/html/index.html + % + % Method Overloads + % return_vector2(Vector value) + if length(varargin) == 1 && isa(varargin{1},'double') + varargout{1} = geometry_wrapper(39, this, varargin{:}); + else + error('Arguments do not match any overload of function Test.return_vector2'); + end + end + + end + + methods(Static = true) + end +end diff --git a/wrap/tests/expected/aGlobalFunction.m b/wrap/tests/expected/aGlobalFunction.m new file mode 100644 index 000000000..cee69491c --- /dev/null +++ b/wrap/tests/expected/aGlobalFunction.m @@ -0,0 +1,6 @@ +function varargout = aGlobalFunction(varargin) +if length(varargin) == 0 + varargout{1} = geometry_wrapper(40, varargin{:}); +else + error('Arguments do not match any overload of function aGlobalFunction'); +end diff --git a/wrap/tests/expected/delete_Point2.cpp b/wrap/tests/expected/delete_Point2.cpp deleted file mode 100644 index bd8bd12eb..000000000 --- a/wrap/tests/expected/delete_Point2.cpp +++ /dev/null @@ -1,8 +0,0 @@ -// automatically generated by wrap -#include -#include -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("delete_Point2",nargout,nargin,1); - delete_shared_ptr< Point2 >(in[0],"Point2"); -} diff --git a/wrap/tests/expected/delete_Point2.m b/wrap/tests/expected/delete_Point2.m deleted file mode 100644 index c6c623bec..000000000 --- a/wrap/tests/expected/delete_Point2.m +++ /dev/null @@ -1,4 +0,0 @@ -% automatically generated by wrap -function result = delete_Point2(obj) - error('need to compile delete_Point2.cpp'); -end diff --git a/wrap/tests/expected/delete_Point3.cpp b/wrap/tests/expected/delete_Point3.cpp deleted file mode 100644 index 9836bb25e..000000000 --- a/wrap/tests/expected/delete_Point3.cpp +++ /dev/null @@ -1,9 +0,0 @@ -// automatically generated by wrap -#include -#include -using namespace geometry; -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("delete_Point3",nargout,nargin,1); - delete_shared_ptr< Point3 >(in[0],"Point3"); -} diff --git a/wrap/tests/expected/delete_Point3.m b/wrap/tests/expected/delete_Point3.m deleted file mode 100644 index b52b898cf..000000000 --- a/wrap/tests/expected/delete_Point3.m +++ /dev/null @@ -1,4 +0,0 @@ -% automatically generated by wrap -function result = delete_Point3(obj) - error('need to compile delete_Point3.cpp'); -end diff --git a/wrap/tests/expected/delete_Test.cpp b/wrap/tests/expected/delete_Test.cpp deleted file mode 100644 index 6a22cc327..000000000 --- a/wrap/tests/expected/delete_Test.cpp +++ /dev/null @@ -1,9 +0,0 @@ -// automatically generated by wrap -#include -#include -using namespace geometry; -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("delete_Test",nargout,nargin,1); - delete_shared_ptr< Test >(in[0],"Test"); -} diff --git a/wrap/tests/expected/delete_Test.m b/wrap/tests/expected/delete_Test.m deleted file mode 100644 index 21ec790a3..000000000 --- a/wrap/tests/expected/delete_Test.m +++ /dev/null @@ -1,4 +0,0 @@ -% automatically generated by wrap -function result = delete_Test(obj) - error('need to compile delete_Test.cpp'); -end diff --git a/wrap/tests/expected/geometry_wrapper.cpp b/wrap/tests/expected/geometry_wrapper.cpp new file mode 100644 index 000000000..ad1df801c --- /dev/null +++ b/wrap/tests/expected/geometry_wrapper.cpp @@ -0,0 +1,618 @@ +#include +#include +#include + +#include + + +typedef std::set*> Collector_Point2; +static Collector_Point2 collector_Point2; +typedef std::set*> Collector_Point3; +static Collector_Point3 collector_Point3; +typedef std::set*> Collector_Test; +static Collector_Test collector_Test; + +void _deleteAllObjects() +{ + mstream mout; + std::streambuf *outbuf = std::cout.rdbuf(&mout); + + bool anyDeleted = false; + { for(Collector_Point2::iterator iter = collector_Point2.begin(); + iter != collector_Point2.end(); ) { + delete *iter; + collector_Point2.erase(iter++); + anyDeleted = true; + } } + { for(Collector_Point3::iterator iter = collector_Point3.begin(); + iter != collector_Point3.end(); ) { + delete *iter; + collector_Point3.erase(iter++); + anyDeleted = true; + } } + { for(Collector_Test::iterator iter = collector_Test.begin(); + iter != collector_Test.end(); ) { + delete *iter; + collector_Test.erase(iter++); + anyDeleted = true; + } } + if(anyDeleted) + cout << + "WARNING: Wrap modules with variables in the workspace have been reloaded due to\n" + "calling destructors, call 'clear all' again if you plan to now recompile a wrap\n" + "module, so that your recompiled module is used instead of the old one." << endl; + std::cout.rdbuf(outbuf); +} + +void _geometry_RTTIRegister() { + const mxArray *alreadyCreated = mexGetVariablePtr("global", "gtsam_geometry_rttiRegistry_created"); + if(!alreadyCreated) { + std::map types; + + mxArray *registry = mexGetVariable("global", "gtsamwrap_rttiRegistry"); + if(!registry) + registry = mxCreateStructMatrix(1, 1, 0, NULL); + typedef std::pair StringPair; + BOOST_FOREACH(const StringPair& rtti_matlab, types) { + int fieldId = mxAddField(registry, rtti_matlab.first.c_str()); + if(fieldId < 0) + mexErrMsgTxt("gtsam wrap: Error indexing RTTI types, inheritance will not work correctly"); + mxArray *matlabName = mxCreateString(rtti_matlab.second.c_str()); + mxSetFieldByNumber(registry, 0, fieldId, matlabName); + } + if(mexPutVariable("global", "gtsamwrap_rttiRegistry", registry) != 0) + mexErrMsgTxt("gtsam wrap: Error indexing RTTI types, inheritance will not work correctly"); + mxDestroyArray(registry); + + mxArray *newAlreadyCreated = mxCreateNumericMatrix(0, 0, mxINT8_CLASS, mxREAL); + if(mexPutVariable("global", "gtsam_geometry_rttiRegistry_created", newAlreadyCreated) != 0) + mexErrMsgTxt("gtsam wrap: Error indexing RTTI types, inheritance will not work correctly"); + mxDestroyArray(newAlreadyCreated); + } +} + +void Point2_collectorInsertAndMakeBase_0(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + mexAtExit(&_deleteAllObjects); + typedef boost::shared_ptr Shared; + + Shared *self = *reinterpret_cast (mxGetData(in[0])); + collector_Point2.insert(self); +} + +void Point2_constructor_1(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + mexAtExit(&_deleteAllObjects); + typedef boost::shared_ptr Shared; + + Shared *self = new Shared(new Point2()); + collector_Point2.insert(self); + out[0] = mxCreateNumericMatrix(1, 1, mxUINT32OR64_CLASS, mxREAL); + *reinterpret_cast (mxGetData(out[0])) = self; +} + +void Point2_constructor_2(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + mexAtExit(&_deleteAllObjects); + typedef boost::shared_ptr Shared; + + double x = unwrap< double >(in[0]); + double y = unwrap< double >(in[1]); + Shared *self = new Shared(new Point2(x,y)); + collector_Point2.insert(self); + out[0] = mxCreateNumericMatrix(1, 1, mxUINT32OR64_CLASS, mxREAL); + *reinterpret_cast (mxGetData(out[0])) = self; +} + +void Point2_deconstructor_3(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + typedef boost::shared_ptr Shared; + checkArguments("delete_Point2",nargout,nargin,1); + Shared *self = *reinterpret_cast(mxGetData(in[0])); + Collector_Point2::iterator item; + item = collector_Point2.find(self); + if(item != collector_Point2.end()) { + delete self; + collector_Point2.erase(item); + } +} + +void Point2_argChar_4(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + typedef boost::shared_ptr Shared; + checkArguments("argChar",nargout,nargin-1,1); + Shared obj = unwrap_shared_ptr(in[0], "ptr_Point2"); + char a = unwrap< char >(in[1]); + obj->argChar(a); +} + +void Point2_argUChar_5(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + typedef boost::shared_ptr Shared; + checkArguments("argUChar",nargout,nargin-1,1); + Shared obj = unwrap_shared_ptr(in[0], "ptr_Point2"); + unsigned char a = unwrap< unsigned char >(in[1]); + obj->argUChar(a); +} + +void Point2_dim_6(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + typedef boost::shared_ptr Shared; + checkArguments("dim",nargout,nargin-1,0); + Shared obj = unwrap_shared_ptr(in[0], "ptr_Point2"); + out[0] = wrap< int >(obj->dim()); +} + +void Point2_returnChar_7(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + typedef boost::shared_ptr Shared; + checkArguments("returnChar",nargout,nargin-1,0); + Shared obj = unwrap_shared_ptr(in[0], "ptr_Point2"); + out[0] = wrap< char >(obj->returnChar()); +} + +void Point2_vectorConfusion_8(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + typedef boost::shared_ptr SharedVectorNotEigen; + typedef boost::shared_ptr Shared; + checkArguments("vectorConfusion",nargout,nargin-1,0); + Shared obj = unwrap_shared_ptr(in[0], "ptr_Point2"); + out[0] = wrap_shared_ptr(SharedVectorNotEigen(new VectorNotEigen(obj->vectorConfusion())),"VectorNotEigen", false); +} + +void Point2_x_9(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + typedef boost::shared_ptr Shared; + checkArguments("x",nargout,nargin-1,0); + Shared obj = unwrap_shared_ptr(in[0], "ptr_Point2"); + out[0] = wrap< double >(obj->x()); +} + +void Point2_y_10(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + typedef boost::shared_ptr Shared; + checkArguments("y",nargout,nargin-1,0); + Shared obj = unwrap_shared_ptr(in[0], "ptr_Point2"); + out[0] = wrap< double >(obj->y()); +} + +void Point3_collectorInsertAndMakeBase_11(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + mexAtExit(&_deleteAllObjects); + typedef boost::shared_ptr Shared; + + Shared *self = *reinterpret_cast (mxGetData(in[0])); + collector_Point3.insert(self); +} + +void Point3_constructor_12(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + mexAtExit(&_deleteAllObjects); + typedef boost::shared_ptr Shared; + + double x = unwrap< double >(in[0]); + double y = unwrap< double >(in[1]); + double z = unwrap< double >(in[2]); + Shared *self = new Shared(new Point3(x,y,z)); + collector_Point3.insert(self); + out[0] = mxCreateNumericMatrix(1, 1, mxUINT32OR64_CLASS, mxREAL); + *reinterpret_cast (mxGetData(out[0])) = self; +} + +void Point3_deconstructor_13(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + typedef boost::shared_ptr Shared; + checkArguments("delete_Point3",nargout,nargin,1); + Shared *self = *reinterpret_cast(mxGetData(in[0])); + Collector_Point3::iterator item; + item = collector_Point3.find(self); + if(item != collector_Point3.end()) { + delete self; + collector_Point3.erase(item); + } +} + +void Point3_norm_14(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + typedef boost::shared_ptr Shared; + checkArguments("norm",nargout,nargin-1,0); + Shared obj = unwrap_shared_ptr(in[0], "ptr_Point3"); + out[0] = wrap< double >(obj->norm()); +} + +void Point3_StaticFunctionRet_15(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + typedef boost::shared_ptr SharedPoint3; + typedef boost::shared_ptr Shared; + checkArguments("Point3.StaticFunctionRet",nargout,nargin,1); + double z = unwrap< double >(in[0]); + out[0] = wrap_shared_ptr(SharedPoint3(new Point3(Point3::StaticFunctionRet(z))),"Point3", false); +} + +void Point3_staticFunction_16(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + typedef boost::shared_ptr Shared; + checkArguments("Point3.staticFunction",nargout,nargin,0); + out[0] = wrap< double >(Point3::staticFunction()); +} + +void Test_collectorInsertAndMakeBase_17(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + mexAtExit(&_deleteAllObjects); + typedef boost::shared_ptr Shared; + + Shared *self = *reinterpret_cast (mxGetData(in[0])); + collector_Test.insert(self); +} + +void Test_constructor_18(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + mexAtExit(&_deleteAllObjects); + typedef boost::shared_ptr Shared; + + Shared *self = new Shared(new Test()); + collector_Test.insert(self); + out[0] = mxCreateNumericMatrix(1, 1, mxUINT32OR64_CLASS, mxREAL); + *reinterpret_cast (mxGetData(out[0])) = self; +} + +void Test_constructor_19(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + mexAtExit(&_deleteAllObjects); + typedef boost::shared_ptr Shared; + + double a = unwrap< double >(in[0]); + Matrix b = unwrap< Matrix >(in[1]); + Shared *self = new Shared(new Test(a,b)); + collector_Test.insert(self); + out[0] = mxCreateNumericMatrix(1, 1, mxUINT32OR64_CLASS, mxREAL); + *reinterpret_cast (mxGetData(out[0])) = self; +} + +void Test_deconstructor_20(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + typedef boost::shared_ptr Shared; + checkArguments("delete_Test",nargout,nargin,1); + Shared *self = *reinterpret_cast(mxGetData(in[0])); + Collector_Test::iterator item; + item = collector_Test.find(self); + if(item != collector_Test.end()) { + delete self; + collector_Test.erase(item); + } +} + +void Test_arg_EigenConstRef_21(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + typedef boost::shared_ptr Shared; + checkArguments("arg_EigenConstRef",nargout,nargin-1,1); + Shared obj = unwrap_shared_ptr(in[0], "ptr_Test"); + Matrix& value = *unwrap_shared_ptr< Matrix >(in[1], "ptr_Matrix"); + obj->arg_EigenConstRef(value); +} + +void Test_create_MixedPtrs_22(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + typedef boost::shared_ptr SharedTest; + typedef boost::shared_ptr SharedTest; + typedef boost::shared_ptr Shared; + checkArguments("create_MixedPtrs",nargout,nargin-1,0); + Shared obj = unwrap_shared_ptr(in[0], "ptr_Test"); + pair< Test, SharedTest > pairResult = obj->create_MixedPtrs(); + out[0] = wrap_shared_ptr(SharedTest(new Test(pairResult.first)),"Test", false); + out[1] = wrap_shared_ptr(pairResult.second,"Test", false); +} + +void Test_create_ptrs_23(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + typedef boost::shared_ptr SharedTest; + typedef boost::shared_ptr SharedTest; + typedef boost::shared_ptr Shared; + checkArguments("create_ptrs",nargout,nargin-1,0); + Shared obj = unwrap_shared_ptr(in[0], "ptr_Test"); + pair< SharedTest, SharedTest > pairResult = obj->create_ptrs(); + out[0] = wrap_shared_ptr(pairResult.first,"Test", false); + out[1] = wrap_shared_ptr(pairResult.second,"Test", false); +} + +void Test_print_24(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + typedef boost::shared_ptr Shared; + checkArguments("print",nargout,nargin-1,0); + Shared obj = unwrap_shared_ptr(in[0], "ptr_Test"); + obj->print(); +} + +void Test_return_Point2Ptr_25(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + typedef boost::shared_ptr SharedPoint2; + typedef boost::shared_ptr Shared; + checkArguments("return_Point2Ptr",nargout,nargin-1,1); + Shared obj = unwrap_shared_ptr(in[0], "ptr_Test"); + bool value = unwrap< bool >(in[1]); + out[0] = wrap_shared_ptr(obj->return_Point2Ptr(value),"Point2", false); +} + +void Test_return_Test_26(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + typedef boost::shared_ptr SharedTest; + typedef boost::shared_ptr Shared; + checkArguments("return_Test",nargout,nargin-1,1); + Shared obj = unwrap_shared_ptr(in[0], "ptr_Test"); + boost::shared_ptr value = unwrap_shared_ptr< Test >(in[1], "ptr_Test"); + out[0] = wrap_shared_ptr(SharedTest(new Test(obj->return_Test(value))),"Test", false); +} + +void Test_return_TestPtr_27(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + typedef boost::shared_ptr SharedTest; + typedef boost::shared_ptr Shared; + checkArguments("return_TestPtr",nargout,nargin-1,1); + Shared obj = unwrap_shared_ptr(in[0], "ptr_Test"); + boost::shared_ptr value = unwrap_shared_ptr< Test >(in[1], "ptr_Test"); + out[0] = wrap_shared_ptr(obj->return_TestPtr(value),"Test", false); +} + +void Test_return_bool_28(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + typedef boost::shared_ptr Shared; + checkArguments("return_bool",nargout,nargin-1,1); + Shared obj = unwrap_shared_ptr(in[0], "ptr_Test"); + bool value = unwrap< bool >(in[1]); + out[0] = wrap< bool >(obj->return_bool(value)); +} + +void Test_return_double_29(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + typedef boost::shared_ptr Shared; + checkArguments("return_double",nargout,nargin-1,1); + Shared obj = unwrap_shared_ptr(in[0], "ptr_Test"); + double value = unwrap< double >(in[1]); + out[0] = wrap< double >(obj->return_double(value)); +} + +void Test_return_field_30(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + typedef boost::shared_ptr Shared; + checkArguments("return_field",nargout,nargin-1,1); + Shared obj = unwrap_shared_ptr(in[0], "ptr_Test"); + Test& t = *unwrap_shared_ptr< Test >(in[1], "ptr_Test"); + out[0] = wrap< bool >(obj->return_field(t)); +} + +void Test_return_int_31(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + typedef boost::shared_ptr Shared; + checkArguments("return_int",nargout,nargin-1,1); + Shared obj = unwrap_shared_ptr(in[0], "ptr_Test"); + int value = unwrap< int >(in[1]); + out[0] = wrap< int >(obj->return_int(value)); +} + +void Test_return_matrix1_32(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + typedef boost::shared_ptr Shared; + checkArguments("return_matrix1",nargout,nargin-1,1); + Shared obj = unwrap_shared_ptr(in[0], "ptr_Test"); + Matrix value = unwrap< Matrix >(in[1]); + out[0] = wrap< Matrix >(obj->return_matrix1(value)); +} + +void Test_return_matrix2_33(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + typedef boost::shared_ptr Shared; + checkArguments("return_matrix2",nargout,nargin-1,1); + Shared obj = unwrap_shared_ptr(in[0], "ptr_Test"); + Matrix value = unwrap< Matrix >(in[1]); + out[0] = wrap< Matrix >(obj->return_matrix2(value)); +} + +void Test_return_pair_34(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + typedef boost::shared_ptr Shared; + checkArguments("return_pair",nargout,nargin-1,2); + Shared obj = unwrap_shared_ptr(in[0], "ptr_Test"); + Vector v = unwrap< Vector >(in[1]); + Matrix A = unwrap< Matrix >(in[2]); + pair< Vector, Matrix > pairResult = obj->return_pair(v,A); + out[0] = wrap< Vector >(pairResult.first); + out[1] = wrap< Matrix >(pairResult.second); +} + +void Test_return_ptrs_35(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + typedef boost::shared_ptr SharedTest; + typedef boost::shared_ptr SharedTest; + typedef boost::shared_ptr Shared; + checkArguments("return_ptrs",nargout,nargin-1,2); + Shared obj = unwrap_shared_ptr(in[0], "ptr_Test"); + boost::shared_ptr p1 = unwrap_shared_ptr< Test >(in[1], "ptr_Test"); + boost::shared_ptr p2 = unwrap_shared_ptr< Test >(in[2], "ptr_Test"); + pair< SharedTest, SharedTest > pairResult = obj->return_ptrs(p1,p2); + out[0] = wrap_shared_ptr(pairResult.first,"Test", false); + out[1] = wrap_shared_ptr(pairResult.second,"Test", false); +} + +void Test_return_size_t_36(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + typedef boost::shared_ptr Shared; + checkArguments("return_size_t",nargout,nargin-1,1); + Shared obj = unwrap_shared_ptr(in[0], "ptr_Test"); + size_t value = unwrap< size_t >(in[1]); + out[0] = wrap< size_t >(obj->return_size_t(value)); +} + +void Test_return_string_37(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + typedef boost::shared_ptr Shared; + checkArguments("return_string",nargout,nargin-1,1); + Shared obj = unwrap_shared_ptr(in[0], "ptr_Test"); + string value = unwrap< string >(in[1]); + out[0] = wrap< string >(obj->return_string(value)); +} + +void Test_return_vector1_38(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + typedef boost::shared_ptr Shared; + checkArguments("return_vector1",nargout,nargin-1,1); + Shared obj = unwrap_shared_ptr(in[0], "ptr_Test"); + Vector value = unwrap< Vector >(in[1]); + out[0] = wrap< Vector >(obj->return_vector1(value)); +} + +void Test_return_vector2_39(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + typedef boost::shared_ptr Shared; + checkArguments("return_vector2",nargout,nargin-1,1); + Shared obj = unwrap_shared_ptr(in[0], "ptr_Test"); + Vector value = unwrap< Vector >(in[1]); + out[0] = wrap< Vector >(obj->return_vector2(value)); +} + +void aGlobalFunction_40(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + checkArguments("aGlobalFunction",nargout,nargin,0); + out[0] = wrap< Vector >(aGlobalFunction()); +} + +void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + mstream mout; + std::streambuf *outbuf = std::cout.rdbuf(&mout); + + _geometry_RTTIRegister(); + + int id = unwrap(in[0]); + + try { + switch(id) { + case 0: + Point2_collectorInsertAndMakeBase_0(nargout, out, nargin-1, in+1); + break; + case 1: + Point2_constructor_1(nargout, out, nargin-1, in+1); + break; + case 2: + Point2_constructor_2(nargout, out, nargin-1, in+1); + break; + case 3: + Point2_deconstructor_3(nargout, out, nargin-1, in+1); + break; + case 4: + Point2_argChar_4(nargout, out, nargin-1, in+1); + break; + case 5: + Point2_argUChar_5(nargout, out, nargin-1, in+1); + break; + case 6: + Point2_dim_6(nargout, out, nargin-1, in+1); + break; + case 7: + Point2_returnChar_7(nargout, out, nargin-1, in+1); + break; + case 8: + Point2_vectorConfusion_8(nargout, out, nargin-1, in+1); + break; + case 9: + Point2_x_9(nargout, out, nargin-1, in+1); + break; + case 10: + Point2_y_10(nargout, out, nargin-1, in+1); + break; + case 11: + Point3_collectorInsertAndMakeBase_11(nargout, out, nargin-1, in+1); + break; + case 12: + Point3_constructor_12(nargout, out, nargin-1, in+1); + break; + case 13: + Point3_deconstructor_13(nargout, out, nargin-1, in+1); + break; + case 14: + Point3_norm_14(nargout, out, nargin-1, in+1); + break; + case 15: + Point3_StaticFunctionRet_15(nargout, out, nargin-1, in+1); + break; + case 16: + Point3_staticFunction_16(nargout, out, nargin-1, in+1); + break; + case 17: + Test_collectorInsertAndMakeBase_17(nargout, out, nargin-1, in+1); + break; + case 18: + Test_constructor_18(nargout, out, nargin-1, in+1); + break; + case 19: + Test_constructor_19(nargout, out, nargin-1, in+1); + break; + case 20: + Test_deconstructor_20(nargout, out, nargin-1, in+1); + break; + case 21: + Test_arg_EigenConstRef_21(nargout, out, nargin-1, in+1); + break; + case 22: + Test_create_MixedPtrs_22(nargout, out, nargin-1, in+1); + break; + case 23: + Test_create_ptrs_23(nargout, out, nargin-1, in+1); + break; + case 24: + Test_print_24(nargout, out, nargin-1, in+1); + break; + case 25: + Test_return_Point2Ptr_25(nargout, out, nargin-1, in+1); + break; + case 26: + Test_return_Test_26(nargout, out, nargin-1, in+1); + break; + case 27: + Test_return_TestPtr_27(nargout, out, nargin-1, in+1); + break; + case 28: + Test_return_bool_28(nargout, out, nargin-1, in+1); + break; + case 29: + Test_return_double_29(nargout, out, nargin-1, in+1); + break; + case 30: + Test_return_field_30(nargout, out, nargin-1, in+1); + break; + case 31: + Test_return_int_31(nargout, out, nargin-1, in+1); + break; + case 32: + Test_return_matrix1_32(nargout, out, nargin-1, in+1); + break; + case 33: + Test_return_matrix2_33(nargout, out, nargin-1, in+1); + break; + case 34: + Test_return_pair_34(nargout, out, nargin-1, in+1); + break; + case 35: + Test_return_ptrs_35(nargout, out, nargin-1, in+1); + break; + case 36: + Test_return_size_t_36(nargout, out, nargin-1, in+1); + break; + case 37: + Test_return_string_37(nargout, out, nargin-1, in+1); + break; + case 38: + Test_return_vector1_38(nargout, out, nargin-1, in+1); + break; + case 39: + Test_return_vector2_39(nargout, out, nargin-1, in+1); + break; + case 40: + aGlobalFunction_40(nargout, out, nargin-1, in+1); + break; + } + } catch(const std::exception& e) { + mexErrMsgTxt(("Exception from gtsam:\n" + std::string(e.what()) + "\n").c_str()); + } + + std::cout.rdbuf(outbuf); +} diff --git a/wrap/tests/expected/make_geometry.m b/wrap/tests/expected/make_geometry.m deleted file mode 100644 index 7baac182f..000000000 --- a/wrap/tests/expected/make_geometry.m +++ /dev/null @@ -1,64 +0,0 @@ -% automatically generated by wrap -echo on - -toolboxpath = mfilename('fullpath'); -delims = find(toolboxpath == '/'); -toolboxpath = toolboxpath(1:(delims(end)-1)); -clear delims -addpath(toolboxpath); - -%% Point2 -cd(toolboxpath) -mex -O5 new_Point2_.cpp -mex -O5 new_Point2_dd.cpp -mex -O5 delete_Point2.cpp - -cd @Point2 -mex -O5 x.cpp -mex -O5 y.cpp -mex -O5 dim.cpp -mex -O5 returnChar.cpp -mex -O5 argChar.cpp -mex -O5 argUChar.cpp -mex -O5 vectorConfusion.cpp - -%% Point3 -cd(toolboxpath) -mex -O5 new_Point3_ddd.cpp -mex -O5 delete_Point3.cpp -mex -O5 Point3_staticFunction.cpp -mex -O5 Point3_StaticFunctionRet.cpp - -cd @Point3 -mex -O5 norm.cpp - -%% Test -cd(toolboxpath) -mex -O5 new_Test_.cpp -mex -O5 new_Test_dM.cpp -mex -O5 delete_Test.cpp - -cd @Test -mex -O5 return_pair.cpp -mex -O5 return_bool.cpp -mex -O5 return_size_t.cpp -mex -O5 return_int.cpp -mex -O5 return_double.cpp -mex -O5 return_string.cpp -mex -O5 return_vector1.cpp -mex -O5 return_matrix1.cpp -mex -O5 return_vector2.cpp -mex -O5 return_matrix2.cpp -mex -O5 arg_EigenConstRef.cpp -mex -O5 return_field.cpp -mex -O5 return_TestPtr.cpp -mex -O5 return_Test.cpp -mex -O5 return_Point2Ptr.cpp -mex -O5 create_ptrs.cpp -mex -O5 create_MixedPtrs.cpp -mex -O5 return_ptrs.cpp -mex -O5 print.cpp - -cd(toolboxpath) - -echo off diff --git a/wrap/tests/expected/new_Point2_.cpp b/wrap/tests/expected/new_Point2_.cpp deleted file mode 100644 index a88076efb..000000000 --- a/wrap/tests/expected/new_Point2_.cpp +++ /dev/null @@ -1,9 +0,0 @@ -// automatically generated by wrap -#include -#include -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("new_Point2_",nargout,nargin,0); - Point2* self = new Point2(); - out[0] = wrap_constructed(self,"Point2"); -} diff --git a/wrap/tests/expected/new_Point2_.m b/wrap/tests/expected/new_Point2_.m deleted file mode 100644 index b0b655b5e..000000000 --- a/wrap/tests/expected/new_Point2_.m +++ /dev/null @@ -1,4 +0,0 @@ -% automatically generated by wrap -function result = new_Point2_(obj) - error('need to compile new_Point2_.cpp'); -end diff --git a/wrap/tests/expected/new_Point2_dd.cpp b/wrap/tests/expected/new_Point2_dd.cpp deleted file mode 100644 index 7c7f062b7..000000000 --- a/wrap/tests/expected/new_Point2_dd.cpp +++ /dev/null @@ -1,11 +0,0 @@ -// automatically generated by wrap -#include -#include -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("new_Point2_dd",nargout,nargin,2); - double x = unwrap< double >(in[0]); - double y = unwrap< double >(in[1]); - Point2* self = new Point2(x,y); - out[0] = wrap_constructed(self,"Point2"); -} diff --git a/wrap/tests/expected/new_Point2_dd.m b/wrap/tests/expected/new_Point2_dd.m deleted file mode 100644 index 4a769ce30..000000000 --- a/wrap/tests/expected/new_Point2_dd.m +++ /dev/null @@ -1,4 +0,0 @@ -% automatically generated by wrap -function result = new_Point2_dd(obj,x,y) - error('need to compile new_Point2_dd.cpp'); -end diff --git a/wrap/tests/expected/new_Point3_ddd.cpp b/wrap/tests/expected/new_Point3_ddd.cpp deleted file mode 100644 index aa45dc71c..000000000 --- a/wrap/tests/expected/new_Point3_ddd.cpp +++ /dev/null @@ -1,13 +0,0 @@ -// automatically generated by wrap -#include -#include -using namespace geometry; -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("new_Point3_ddd",nargout,nargin,3); - double x = unwrap< double >(in[0]); - double y = unwrap< double >(in[1]); - double z = unwrap< double >(in[2]); - Point3* self = new Point3(x,y,z); - out[0] = wrap_constructed(self,"Point3"); -} diff --git a/wrap/tests/expected/new_Point3_ddd.m b/wrap/tests/expected/new_Point3_ddd.m deleted file mode 100644 index 154dda1d0..000000000 --- a/wrap/tests/expected/new_Point3_ddd.m +++ /dev/null @@ -1,4 +0,0 @@ -% automatically generated by wrap -function result = new_Point3_ddd(obj,x,y,z) - error('need to compile new_Point3_ddd.cpp'); -end diff --git a/wrap/tests/expected/new_Test_.cpp b/wrap/tests/expected/new_Test_.cpp deleted file mode 100644 index 9c66706ae..000000000 --- a/wrap/tests/expected/new_Test_.cpp +++ /dev/null @@ -1,10 +0,0 @@ -// automatically generated by wrap -#include -#include -using namespace geometry; -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("new_Test_",nargout,nargin,0); - Test* self = new Test(); - out[0] = wrap_constructed(self,"Test"); -} diff --git a/wrap/tests/expected/new_Test_.m b/wrap/tests/expected/new_Test_.m deleted file mode 100644 index 33c465f8b..000000000 --- a/wrap/tests/expected/new_Test_.m +++ /dev/null @@ -1,4 +0,0 @@ -% automatically generated by wrap -function result = new_Test_(obj) - error('need to compile new_Test_.cpp'); -end diff --git a/wrap/tests/expected/new_Test_dM.cpp b/wrap/tests/expected/new_Test_dM.cpp deleted file mode 100644 index e8a7c8de1..000000000 --- a/wrap/tests/expected/new_Test_dM.cpp +++ /dev/null @@ -1,12 +0,0 @@ -// automatically generated by wrap -#include -#include -using namespace geometry; -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("new_Test_dM",nargout,nargin,2); - double a = unwrap< double >(in[0]); - Matrix b = unwrap< Matrix >(in[1]); - Test* self = new Test(a,b); - out[0] = wrap_constructed(self,"Test"); -} diff --git a/wrap/tests/expected/new_Test_dM.m b/wrap/tests/expected/new_Test_dM.m deleted file mode 100644 index c7009d6a9..000000000 --- a/wrap/tests/expected/new_Test_dM.m +++ /dev/null @@ -1,4 +0,0 @@ -% automatically generated by wrap -function result = new_Test_dM(obj,a,b) - error('need to compile new_Test_dM.cpp'); -end diff --git a/wrap/tests/expected_namespaces/+ns1/ClassA.m b/wrap/tests/expected_namespaces/+ns1/ClassA.m new file mode 100644 index 000000000..f7dce6031 --- /dev/null +++ b/wrap/tests/expected_namespaces/+ns1/ClassA.m @@ -0,0 +1,36 @@ +%class ClassA, see Doxygen page for details +%at http://research.cc.gatech.edu/borg/sites/edu.borg/html/index.html +% +%-------Constructors------- +%ClassA() +% +classdef ClassA < handle + properties + ptr_ns1ClassA = 0 + end + methods + function obj = ClassA(varargin) + if nargin == 2 && isa(varargin{1}, 'uint64') && varargin{1} == uint64(5139824614673773682) + my_ptr = varargin{2}; + testNamespaces_wrapper(0, my_ptr); + elseif nargin == 0 + my_ptr = testNamespaces_wrapper(1); + else + error('Arguments do not match any overload of ns1.ClassA constructor'); + end + obj.ptr_ns1ClassA = my_ptr; + end + + function delete(obj) + testNamespaces_wrapper(2, obj.ptr_ns1ClassA); + end + + function display(obj), obj.print(''); end + %DISPLAY Calls print on the object + function disp(obj), obj.display; end + %DISP Calls print on the object + end + + methods(Static = true) + end +end diff --git a/wrap/tests/expected_namespaces/+ns1/ClassB.m b/wrap/tests/expected_namespaces/+ns1/ClassB.m new file mode 100644 index 000000000..df956a179 --- /dev/null +++ b/wrap/tests/expected_namespaces/+ns1/ClassB.m @@ -0,0 +1,36 @@ +%class ClassB, see Doxygen page for details +%at http://research.cc.gatech.edu/borg/sites/edu.borg/html/index.html +% +%-------Constructors------- +%ClassB() +% +classdef ClassB < handle + properties + ptr_ns1ClassB = 0 + end + methods + function obj = ClassB(varargin) + if nargin == 2 && isa(varargin{1}, 'uint64') && varargin{1} == uint64(5139824614673773682) + my_ptr = varargin{2}; + testNamespaces_wrapper(3, my_ptr); + elseif nargin == 0 + my_ptr = testNamespaces_wrapper(4); + else + error('Arguments do not match any overload of ns1.ClassB constructor'); + end + obj.ptr_ns1ClassB = my_ptr; + end + + function delete(obj) + testNamespaces_wrapper(5, obj.ptr_ns1ClassB); + end + + function display(obj), obj.print(''); end + %DISPLAY Calls print on the object + function disp(obj), obj.display; end + %DISP Calls print on the object + end + + methods(Static = true) + end +end diff --git a/wrap/tests/expected_namespaces/+ns1/aGlobalFunction.m b/wrap/tests/expected_namespaces/+ns1/aGlobalFunction.m new file mode 100644 index 000000000..a82518ad6 --- /dev/null +++ b/wrap/tests/expected_namespaces/+ns1/aGlobalFunction.m @@ -0,0 +1,6 @@ +function varargout = aGlobalFunction(varargin) +if length(varargin) == 0 + varargout{1} = testNamespaces_wrapper(22, varargin{:}); +else + error('Arguments do not match any overload of function ns1.aGlobalFunction'); +end diff --git a/wrap/tests/expected_namespaces/+ns2/+ns3/ClassB.m b/wrap/tests/expected_namespaces/+ns2/+ns3/ClassB.m new file mode 100644 index 000000000..23c3dbacb --- /dev/null +++ b/wrap/tests/expected_namespaces/+ns2/+ns3/ClassB.m @@ -0,0 +1,36 @@ +%class ClassB, see Doxygen page for details +%at http://research.cc.gatech.edu/borg/sites/edu.borg/html/index.html +% +%-------Constructors------- +%ClassB() +% +classdef ClassB < handle + properties + ptr_ns2ns3ClassB = 0 + end + methods + function obj = ClassB(varargin) + if nargin == 2 && isa(varargin{1}, 'uint64') && varargin{1} == uint64(5139824614673773682) + my_ptr = varargin{2}; + testNamespaces_wrapper(13, my_ptr); + elseif nargin == 0 + my_ptr = testNamespaces_wrapper(14); + else + error('Arguments do not match any overload of ns2.ns3.ClassB constructor'); + end + obj.ptr_ns2ns3ClassB = my_ptr; + end + + function delete(obj) + testNamespaces_wrapper(15, obj.ptr_ns2ns3ClassB); + end + + function display(obj), obj.print(''); end + %DISPLAY Calls print on the object + function disp(obj), obj.display; end + %DISP Calls print on the object + end + + methods(Static = true) + end +end diff --git a/wrap/tests/expected_namespaces/+ns2/ClassA.m b/wrap/tests/expected_namespaces/+ns2/ClassA.m new file mode 100644 index 000000000..c7ab901ae --- /dev/null +++ b/wrap/tests/expected_namespaces/+ns2/ClassA.m @@ -0,0 +1,96 @@ +%class ClassA, see Doxygen page for details +%at http://research.cc.gatech.edu/borg/sites/edu.borg/html/index.html +% +%-------Constructors------- +%ClassA() +% +%-------Methods------- +%memberFunction() : returns double +%nsArg(ClassB arg) : returns int +%nsReturn(double q) : returns ns2::ns3::ClassB +% +%-------Static Methods------- +%afunction() : returns double +% +classdef ClassA < handle + properties + ptr_ns2ClassA = 0 + end + methods + function obj = ClassA(varargin) + if nargin == 2 && isa(varargin{1}, 'uint64') && varargin{1} == uint64(5139824614673773682) + my_ptr = varargin{2}; + testNamespaces_wrapper(6, my_ptr); + elseif nargin == 0 + my_ptr = testNamespaces_wrapper(7); + else + error('Arguments do not match any overload of ns2.ClassA constructor'); + end + obj.ptr_ns2ClassA = my_ptr; + end + + function delete(obj) + testNamespaces_wrapper(8, obj.ptr_ns2ClassA); + end + + function display(obj), obj.print(''); end + %DISPLAY Calls print on the object + function disp(obj), obj.display; end + %DISP Calls print on the object + function varargout = memberFunction(this, varargin) + % MEMBERFUNCTION usage: memberFunction() : returns double + % Doxygen can be found at http://research.cc.gatech.edu/borg/sites/edu.borg/html/index.html + % + % Method Overloads + % memberFunction() + if length(varargin) == 0 + varargout{1} = testNamespaces_wrapper(9, this, varargin{:}); + else + error('Arguments do not match any overload of function ns2.ClassA.memberFunction'); + end + end + + function varargout = nsArg(this, varargin) + % NSARG usage: nsArg(ClassB arg) : returns int + % Doxygen can be found at http://research.cc.gatech.edu/borg/sites/edu.borg/html/index.html + % + % Method Overloads + % nsArg(ClassB arg) + if length(varargin) == 1 && isa(varargin{1},'ns1.ClassB') + varargout{1} = testNamespaces_wrapper(10, this, varargin{:}); + else + error('Arguments do not match any overload of function ns2.ClassA.nsArg'); + end + end + + function varargout = nsReturn(this, varargin) + % NSRETURN usage: nsReturn(double q) : returns ns2::ns3::ClassB + % Doxygen can be found at http://research.cc.gatech.edu/borg/sites/edu.borg/html/index.html + % + % Method Overloads + % nsReturn(double q) + if length(varargin) == 1 && isa(varargin{1},'double') + varargout{1} = testNamespaces_wrapper(11, this, varargin{:}); + else + error('Arguments do not match any overload of function ns2.ClassA.nsReturn'); + end + end + + end + + methods(Static = true) + function varargout = Afunction(varargin) + % AFUNCTION usage: afunction() : returns double + % Doxygen can be found at http://research.cc.gatech.edu/borg/sites/edu.borg/html/index.html + % + % Usage + % AFUNCTION() + if length(varargin) == 0 + varargout{1} = testNamespaces_wrapper(12, varargin{:}); + else + error('Arguments do not match any overload of function ns2.ClassA.Afunction'); + end + end + + end +end diff --git a/wrap/tests/expected_namespaces/+ns2/ClassC.m b/wrap/tests/expected_namespaces/+ns2/ClassC.m new file mode 100644 index 000000000..19b709f5c --- /dev/null +++ b/wrap/tests/expected_namespaces/+ns2/ClassC.m @@ -0,0 +1,36 @@ +%class ClassC, see Doxygen page for details +%at http://research.cc.gatech.edu/borg/sites/edu.borg/html/index.html +% +%-------Constructors------- +%ClassC() +% +classdef ClassC < handle + properties + ptr_ns2ClassC = 0 + end + methods + function obj = ClassC(varargin) + if nargin == 2 && isa(varargin{1}, 'uint64') && varargin{1} == uint64(5139824614673773682) + my_ptr = varargin{2}; + testNamespaces_wrapper(16, my_ptr); + elseif nargin == 0 + my_ptr = testNamespaces_wrapper(17); + else + error('Arguments do not match any overload of ns2.ClassC constructor'); + end + obj.ptr_ns2ClassC = my_ptr; + end + + function delete(obj) + testNamespaces_wrapper(18, obj.ptr_ns2ClassC); + end + + function display(obj), obj.print(''); end + %DISPLAY Calls print on the object + function disp(obj), obj.display; end + %DISP Calls print on the object + end + + methods(Static = true) + end +end diff --git a/wrap/tests/expected_namespaces/+ns2/aGlobalFunction.m b/wrap/tests/expected_namespaces/+ns2/aGlobalFunction.m new file mode 100644 index 000000000..8b6a5993f --- /dev/null +++ b/wrap/tests/expected_namespaces/+ns2/aGlobalFunction.m @@ -0,0 +1,6 @@ +function varargout = aGlobalFunction(varargin) +if length(varargin) == 0 + varargout{1} = testNamespaces_wrapper(23, varargin{:}); +else + error('Arguments do not match any overload of function ns2.aGlobalFunction'); +end diff --git a/wrap/tests/expected_namespaces/@ClassD/ClassD.m b/wrap/tests/expected_namespaces/@ClassD/ClassD.m deleted file mode 100644 index 8b78750d9..000000000 --- a/wrap/tests/expected_namespaces/@ClassD/ClassD.m +++ /dev/null @@ -1,17 +0,0 @@ -% automatically generated by wrap -classdef ClassD < handle - properties - self = 0 - end - methods - function obj = ClassD(varargin) - if (nargin == 0), obj.self = new_ClassD_(); end - if nargin ~= 13 && obj.self == 0, error('ClassD constructor failed'); end - end - function delete(obj) - delete_ClassD(obj) - end - function display(obj), obj.print(''); end - function disp(obj), obj.display; end - end -end diff --git a/wrap/tests/expected_namespaces/@ns1ClassA/ns1ClassA.m b/wrap/tests/expected_namespaces/@ns1ClassA/ns1ClassA.m deleted file mode 100644 index 806070a36..000000000 --- a/wrap/tests/expected_namespaces/@ns1ClassA/ns1ClassA.m +++ /dev/null @@ -1,17 +0,0 @@ -% automatically generated by wrap -classdef ns1ClassA < handle - properties - self = 0 - end - methods - function obj = ns1ClassA(varargin) - if (nargin == 0), obj.self = new_ns1ClassA_(); end - if nargin ~= 13 && obj.self == 0, error('ns1ClassA constructor failed'); end - end - function delete(obj) - delete_ns1ClassA(obj); - end - function display(obj), obj.print(''); end - function disp(obj), obj.display; end - end -end diff --git a/wrap/tests/expected_namespaces/@ns1ClassB/ns1ClassB.m b/wrap/tests/expected_namespaces/@ns1ClassB/ns1ClassB.m deleted file mode 100644 index 13d5846ae..000000000 --- a/wrap/tests/expected_namespaces/@ns1ClassB/ns1ClassB.m +++ /dev/null @@ -1,17 +0,0 @@ -% automatically generated by wrap -classdef ns1ClassB < handle - properties - self = 0 - end - methods - function obj = ns1ClassB(varargin) - if (nargin == 0), obj.self = new_ns1ClassB_(); end - if nargin ~= 13 && obj.self == 0, error('ns1ClassB constructor failed'); end - end - function delete(obj) - delete_ns1ClassB(obj); - end - function display(obj), obj.print(''); end - function disp(obj), obj.display; end - end -end diff --git a/wrap/tests/expected_namespaces/@ns2ClassA/memberFunction.cpp b/wrap/tests/expected_namespaces/@ns2ClassA/memberFunction.cpp deleted file mode 100644 index 8e5bc3960..000000000 --- a/wrap/tests/expected_namespaces/@ns2ClassA/memberFunction.cpp +++ /dev/null @@ -1,11 +0,0 @@ -// automatically generated by wrap -#include -#include -#include -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("memberFunction",nargout,nargin-1,0); - shared_ptr self = unwrap_shared_ptr< ns2::ClassA >(in[0],"ns2ClassA"); - double result = self->memberFunction(); - out[0] = wrap< double >(result); -} diff --git a/wrap/tests/expected_namespaces/@ns2ClassA/memberFunction.m b/wrap/tests/expected_namespaces/@ns2ClassA/memberFunction.m deleted file mode 100644 index 4523cba56..000000000 --- a/wrap/tests/expected_namespaces/@ns2ClassA/memberFunction.m +++ /dev/null @@ -1,5 +0,0 @@ - automatically generated by wrap -function result = memberFunction(obj) -% usage: obj.memberFunction() - error('need to compile memberFunction.cpp'); -end diff --git a/wrap/tests/expected_namespaces/@ns2ClassA/ns2ClassA.m b/wrap/tests/expected_namespaces/@ns2ClassA/ns2ClassA.m deleted file mode 100644 index 188ac087d..000000000 --- a/wrap/tests/expected_namespaces/@ns2ClassA/ns2ClassA.m +++ /dev/null @@ -1,17 +0,0 @@ -% automatically generated by wrap -classdef ns2ClassA < handle - properties - self = 0 - end - methods - function obj = ns2ClassA(varargin) - if (nargin == 0), obj.self = new_ns2ClassA_(); end - if nargin ~= 13 && obj.self == 0, error('ns2ClassA constructor failed'); end - end - function delete(obj) - delete_ns2ClassA(obj); - end - function display(obj), obj.print(''); end - function disp(obj), obj.display; end - end -end diff --git a/wrap/tests/expected_namespaces/@ns2ClassA/nsArg.cpp b/wrap/tests/expected_namespaces/@ns2ClassA/nsArg.cpp deleted file mode 100644 index 7c06bcfdc..000000000 --- a/wrap/tests/expected_namespaces/@ns2ClassA/nsArg.cpp +++ /dev/null @@ -1,12 +0,0 @@ -// automatically generated by wrap -#include -#include -#include -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("nsArg",nargout,nargin-1,1); - shared_ptr self = unwrap_shared_ptr< ns2::ClassA >(in[0],"ns2ClassA"); - ns1::ClassB& arg = *unwrap_shared_ptr< ns1::ClassB >(in[1], "ns1ClassB"); - int result = self->nsArg(arg); - out[0] = wrap< int >(result); -} diff --git a/wrap/tests/expected_namespaces/@ns2ClassA/nsArg.m b/wrap/tests/expected_namespaces/@ns2ClassA/nsArg.m deleted file mode 100644 index 4893ece7f..000000000 --- a/wrap/tests/expected_namespaces/@ns2ClassA/nsArg.m +++ /dev/null @@ -1,5 +0,0 @@ - automatically generated by wrap -function result = nsArg(obj,arg) -% usage: obj.nsArg(arg) - error('need to compile nsArg.cpp'); -end diff --git a/wrap/tests/expected_namespaces/@ns2ClassA/nsReturn.cpp b/wrap/tests/expected_namespaces/@ns2ClassA/nsReturn.cpp deleted file mode 100644 index c6714ee9f..000000000 --- a/wrap/tests/expected_namespaces/@ns2ClassA/nsReturn.cpp +++ /dev/null @@ -1,12 +0,0 @@ -// automatically generated by wrap -#include -#include -#include -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("nsReturn",nargout,nargin-1,1); - shared_ptr self = unwrap_shared_ptr< ns2::ClassA >(in[0],"ns2ClassA"); - double q = unwrap< double >(in[1]); - ns2::ns3::ClassB result = self->nsReturn(q); - out[0] = wrap_shared_ptr(make_shared< ns2::ns3::ClassB >(result),"ns2ns3ClassB"); -} diff --git a/wrap/tests/expected_namespaces/@ns2ClassA/nsReturn.m b/wrap/tests/expected_namespaces/@ns2ClassA/nsReturn.m deleted file mode 100644 index 2c900bc30..000000000 --- a/wrap/tests/expected_namespaces/@ns2ClassA/nsReturn.m +++ /dev/null @@ -1,5 +0,0 @@ - automatically generated by wrap -function result = nsReturn(obj,q) -% usage: obj.nsReturn(q) - error('need to compile nsReturn.cpp'); -end diff --git a/wrap/tests/expected_namespaces/@ns2ClassC/ns2ClassC.m b/wrap/tests/expected_namespaces/@ns2ClassC/ns2ClassC.m deleted file mode 100644 index 793e73e64..000000000 --- a/wrap/tests/expected_namespaces/@ns2ClassC/ns2ClassC.m +++ /dev/null @@ -1,17 +0,0 @@ -% automatically generated by wrap -classdef ns2ClassC < handle - properties - self = 0 - end - methods - function obj = ns2ClassC(varargin) - if (nargin == 0), obj.self = new_ns2ClassC_(); end - if nargin ~= 13 && obj.self == 0, error('ns2ClassC constructor failed'); end - end - function delete(obj) - delete_ns2ClassC(obj); - end - function display(obj), obj.print(''); end - function disp(obj), obj.display; end - end -end diff --git a/wrap/tests/expected_namespaces/@ns2ns3ClassB/ns2ns3ClassB.m b/wrap/tests/expected_namespaces/@ns2ns3ClassB/ns2ns3ClassB.m deleted file mode 100644 index 3997cd005..000000000 --- a/wrap/tests/expected_namespaces/@ns2ns3ClassB/ns2ns3ClassB.m +++ /dev/null @@ -1,17 +0,0 @@ -% automatically generated by wrap -classdef ns2ns3ClassB < handle - properties - self = 0 - end - methods - function obj = ns2ns3ClassB(varargin) - if (nargin == 0), obj.self = new_ns2ns3ClassB_(); end - if nargin ~= 13 && obj.self == 0, error('ns2ns3ClassB constructor failed'); end - end - function delete(obj) - delete_ns2ns3ClassB(obj); - end - function display(obj), obj.print(''); end - function disp(obj), obj.display; end - end -end diff --git a/wrap/tests/expected_namespaces/ClassD.m b/wrap/tests/expected_namespaces/ClassD.m new file mode 100644 index 000000000..453025961 --- /dev/null +++ b/wrap/tests/expected_namespaces/ClassD.m @@ -0,0 +1,36 @@ +%class ClassD, see Doxygen page for details +%at http://research.cc.gatech.edu/borg/sites/edu.borg/html/index.html +% +%-------Constructors------- +%ClassD() +% +classdef ClassD < handle + properties + ptr_ClassD = 0 + end + methods + function obj = ClassD(varargin) + if nargin == 2 && isa(varargin{1}, 'uint64') && varargin{1} == uint64(5139824614673773682) + my_ptr = varargin{2}; + testNamespaces_wrapper(19, my_ptr); + elseif nargin == 0 + my_ptr = testNamespaces_wrapper(20); + else + error('Arguments do not match any overload of ClassD constructor'); + end + obj.ptr_ClassD = my_ptr; + end + + function delete(obj) + testNamespaces_wrapper(21, obj.ptr_ClassD); + end + + function display(obj), obj.print(''); end + %DISPLAY Calls print on the object + function disp(obj), obj.display; end + %DISP Calls print on the object + end + + methods(Static = true) + end +end diff --git a/wrap/tests/expected_namespaces/Makefile b/wrap/tests/expected_namespaces/Makefile deleted file mode 100644 index c48a1b154..000000000 --- a/wrap/tests/expected_namespaces/Makefile +++ /dev/null @@ -1,76 +0,0 @@ -# automatically generated by wrap - -MEX = mex -MEXENDING = mexa64 -mex_flags = -O5 - -all: ns1ClassA ns1ClassB ns2ClassA ns2ns3ClassB ns2ClassC ClassD - -# ns1ClassA -new_ns1ClassA_.$(MEXENDING): new_ns1ClassA_.cpp - $(MEX) $(mex_flags) new_ns1ClassA_.cpp -output new_ns1ClassA_ -delete_ns1ClassA.$(MEXENDING): delete_ns1ClassA.cpp - $(MEX) $(mex_flags) delete_ns1ClassA.cpp -output delete_ns1ClassA - -ns1ClassA: new_ns1ClassA_.$(MEXENDING) delete_ns1ClassA.$(MEXENDING) - -# ns1ClassB -new_ns1ClassB_.$(MEXENDING): new_ns1ClassB_.cpp - $(MEX) $(mex_flags) new_ns1ClassB_.cpp -output new_ns1ClassB_ -delete_ns1ClassB.$(MEXENDING): delete_ns1ClassB.cpp - $(MEX) $(mex_flags) delete_ns1ClassB.cpp -output delete_ns1ClassB - -ns1ClassB: new_ns1ClassB_.$(MEXENDING) delete_ns1ClassB.$(MEXENDING) - -# ns2ClassA -new_ns2ClassA_.$(MEXENDING): new_ns2ClassA_.cpp - $(MEX) $(mex_flags) new_ns2ClassA_.cpp -output new_ns2ClassA_ -delete_ns2ClassA.$(MEXENDING): delete_ns2ClassA.cpp - $(MEX) $(mex_flags) delete_ns2ClassA.cpp -output delete_ns2ClassA -ns2ClassA_afunction.$(MEXENDING): ns2ClassA_afunction.cpp - $(MEX) $(mex_flags) ns2ClassA_afunction.cpp -output ns2ClassA_afunction -@ns2ClassA/memberFunction.$(MEXENDING): @ns2ClassA/memberFunction.cpp - $(MEX) $(mex_flags) @ns2ClassA/memberFunction.cpp -output @ns2ClassA/memberFunction -@ns2ClassA/nsArg.$(MEXENDING): @ns2ClassA/nsArg.cpp - $(MEX) $(mex_flags) @ns2ClassA/nsArg.cpp -output @ns2ClassA/nsArg -@ns2ClassA/nsReturn.$(MEXENDING): @ns2ClassA/nsReturn.cpp - $(MEX) $(mex_flags) @ns2ClassA/nsReturn.cpp -output @ns2ClassA/nsReturn - -ns2ClassA: new_ns2ClassA_.$(MEXENDING) delete_ns2ClassA.$(MEXENDING) ns2ClassA_afunction.$(MEXENDING) @ns2ClassA/memberFunction.$(MEXENDING) @ns2ClassA/nsArg.$(MEXENDING) @ns2ClassA/nsReturn.$(MEXENDING) - -# ns2ns3ClassB -new_ns2ns3ClassB_.$(MEXENDING): new_ns2ns3ClassB_.cpp - $(MEX) $(mex_flags) new_ns2ns3ClassB_.cpp -output new_ns2ns3ClassB_ -delete_ns2ns3ClassB.$(MEXENDING): delete_ns2ns3ClassB.cpp - $(MEX) $(mex_flags) delete_ns2ns3ClassB.cpp -output delete_ns2ns3ClassB - -ns2ns3ClassB: new_ns2ns3ClassB_.$(MEXENDING) delete_ns2ns3ClassB.$(MEXENDING) - -# ns2ClassC -new_ns2ClassC_.$(MEXENDING): new_ns2ClassC_.cpp - $(MEX) $(mex_flags) new_ns2ClassC_.cpp -output new_ns2ClassC_ -delete_ns2ClassC.$(MEXENDING): delete_ns2ClassC.cpp - $(MEX) $(mex_flags) delete_ns2ClassC.cpp -output delete_ns2ClassC - -ns2ClassC: new_ns2ClassC_.$(MEXENDING) delete_ns2ClassC.$(MEXENDING) - -# ClassD -new_ClassD_.$(MEXENDING): new_ClassD_.cpp - $(MEX) $(mex_flags) new_ClassD_.cpp -output new_ClassD_ -delete_ClassD.$(MEXENDING): delete_ClassD.cpp - $(MEX) $(mex_flags) delete_ClassD.cpp -output delete_ClassD - -ClassD: new_ClassD_.$(MEXENDING) delete_ClassD.$(MEXENDING) - - - -clean: - rm -rf *.$(MEXENDING) - rm -rf @ns1ClassA/*.$(MEXENDING) - rm -rf @ns1ClassB/*.$(MEXENDING) - rm -rf @ns2ClassA/*.$(MEXENDING) - rm -rf @ns2ns3ClassB/*.$(MEXENDING) - rm -rf @ns2ClassC/*.$(MEXENDING) - rm -rf @ClassD/*.$(MEXENDING) - - diff --git a/wrap/tests/expected_namespaces/delete_ClassD.cpp b/wrap/tests/expected_namespaces/delete_ClassD.cpp deleted file mode 100644 index 5284e33ba..000000000 --- a/wrap/tests/expected_namespaces/delete_ClassD.cpp +++ /dev/null @@ -1,8 +0,0 @@ -// automatically generated by wrap -#include -#include -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("delete_ClassD",nargout,nargin,1); - delete_shared_ptr< ClassD >(in[0],"ClassD"); -} diff --git a/wrap/tests/expected_namespaces/delete_ClassD.m b/wrap/tests/expected_namespaces/delete_ClassD.m deleted file mode 100644 index aef8cb642..000000000 --- a/wrap/tests/expected_namespaces/delete_ClassD.m +++ /dev/null @@ -1,4 +0,0 @@ -% automatically generated by wrap -function result = delete_ClassD(obj) - error('need to compile delete_ClassD.cpp'); -end diff --git a/wrap/tests/expected_namespaces/delete_ns1ClassA.cpp b/wrap/tests/expected_namespaces/delete_ns1ClassA.cpp deleted file mode 100644 index 17a25b523..000000000 --- a/wrap/tests/expected_namespaces/delete_ns1ClassA.cpp +++ /dev/null @@ -1,8 +0,0 @@ -// automatically generated by wrap -#include -#include -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("delete_ns1ClassA",nargout,nargin,1); - delete_shared_ptr< ns1::ClassA >(in[0],"ns1ClassA"); -} diff --git a/wrap/tests/expected_namespaces/delete_ns1ClassA.m b/wrap/tests/expected_namespaces/delete_ns1ClassA.m deleted file mode 100644 index 343d5636a..000000000 --- a/wrap/tests/expected_namespaces/delete_ns1ClassA.m +++ /dev/null @@ -1,4 +0,0 @@ -% automatically generated by wrap -function result = delete_ns1ClassA(obj) - error('need to compile delete_ns1ClassA.cpp'); -end diff --git a/wrap/tests/expected_namespaces/delete_ns1ClassB.cpp b/wrap/tests/expected_namespaces/delete_ns1ClassB.cpp deleted file mode 100644 index 7302cc3d3..000000000 --- a/wrap/tests/expected_namespaces/delete_ns1ClassB.cpp +++ /dev/null @@ -1,9 +0,0 @@ -// automatically generated by wrap -#include -#include -#include -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("delete_ns1ClassB",nargout,nargin,1); - delete_shared_ptr< ns1::ClassB >(in[0],"ns1ClassB"); -} diff --git a/wrap/tests/expected_namespaces/delete_ns1ClassB.m b/wrap/tests/expected_namespaces/delete_ns1ClassB.m deleted file mode 100644 index ec50f3f06..000000000 --- a/wrap/tests/expected_namespaces/delete_ns1ClassB.m +++ /dev/null @@ -1,4 +0,0 @@ -% automatically generated by wrap -function result = delete_ns1ClassB(obj) - error('need to compile delete_ns1ClassB.cpp'); -end diff --git a/wrap/tests/expected_namespaces/delete_ns2ClassA.cpp b/wrap/tests/expected_namespaces/delete_ns2ClassA.cpp deleted file mode 100644 index 0562ee073..000000000 --- a/wrap/tests/expected_namespaces/delete_ns2ClassA.cpp +++ /dev/null @@ -1,9 +0,0 @@ -// automatically generated by wrap -#include -#include -#include -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("delete_ns2ClassA",nargout,nargin,1); - delete_shared_ptr< ns2::ClassA >(in[0],"ns2ClassA"); -} diff --git a/wrap/tests/expected_namespaces/delete_ns2ClassA.m b/wrap/tests/expected_namespaces/delete_ns2ClassA.m deleted file mode 100644 index 4f1b92aa5..000000000 --- a/wrap/tests/expected_namespaces/delete_ns2ClassA.m +++ /dev/null @@ -1,4 +0,0 @@ -% automatically generated by wrap -function result = delete_ns2ClassA(obj) - error('need to compile delete_ns2ClassA.cpp'); -end diff --git a/wrap/tests/expected_namespaces/delete_ns2ClassC.cpp b/wrap/tests/expected_namespaces/delete_ns2ClassC.cpp deleted file mode 100644 index ef57796b7..000000000 --- a/wrap/tests/expected_namespaces/delete_ns2ClassC.cpp +++ /dev/null @@ -1,8 +0,0 @@ -// automatically generated by wrap -#include -#include -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("delete_ns2ClassC",nargout,nargin,1); - delete_shared_ptr< ns2::ClassC >(in[0],"ns2ClassC"); -} diff --git a/wrap/tests/expected_namespaces/delete_ns2ClassC.m b/wrap/tests/expected_namespaces/delete_ns2ClassC.m deleted file mode 100644 index 1db1ddc93..000000000 --- a/wrap/tests/expected_namespaces/delete_ns2ClassC.m +++ /dev/null @@ -1,4 +0,0 @@ -% automatically generated by wrap -function result = delete_ns2ClassC(obj) - error('need to compile delete_ns2ClassC.cpp'); -end diff --git a/wrap/tests/expected_namespaces/delete_ns2ns3ClassB.cpp b/wrap/tests/expected_namespaces/delete_ns2ns3ClassB.cpp deleted file mode 100644 index 0a6c4ce73..000000000 --- a/wrap/tests/expected_namespaces/delete_ns2ns3ClassB.cpp +++ /dev/null @@ -1,9 +0,0 @@ -// automatically generated by wrap -#include -#include -#include -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("delete_ns2ns3ClassB",nargout,nargin,1); - delete_shared_ptr< ns2::ns3::ClassB >(in[0],"ns2ns3ClassB"); -} diff --git a/wrap/tests/expected_namespaces/delete_ns2ns3ClassB.m b/wrap/tests/expected_namespaces/delete_ns2ns3ClassB.m deleted file mode 100644 index 427359eca..000000000 --- a/wrap/tests/expected_namespaces/delete_ns2ns3ClassB.m +++ /dev/null @@ -1,4 +0,0 @@ -% automatically generated by wrap -function result = delete_ns2ns3ClassB(obj) - error('need to compile delete_ns2ns3ClassB.cpp'); -end diff --git a/wrap/tests/expected_namespaces/make_testNamespaces.m b/wrap/tests/expected_namespaces/make_testNamespaces.m deleted file mode 100644 index eac4146c8..000000000 --- a/wrap/tests/expected_namespaces/make_testNamespaces.m +++ /dev/null @@ -1,58 +0,0 @@ -% automatically generated by wrap -echo on - -toolboxpath = mfilename('fullpath'); -delims = find(toolboxpath == '/'); -toolboxpath = toolboxpath(1:(delims(end)-1)); -clear delims -addpath(toolboxpath); - -%% ns1ClassA -cd(toolboxpath) -mex -O5 new_ns1ClassA_.cpp -mex -O5 delete_ns1ClassA.cpp - -cd @ns1ClassA - -%% ns1ClassB -cd(toolboxpath) -mex -O5 new_ns1ClassB_.cpp -mex -O5 delete_ns1ClassB.cpp - -cd @ns1ClassB - -%% ns2ClassA -cd(toolboxpath) -mex -O5 new_ns2ClassA_.cpp -mex -O5 delete_ns2ClassA.cpp -mex -O5 ns2ClassA_afunction.cpp - -cd @ns2ClassA -mex -O5 memberFunction.cpp -mex -O5 nsArg.cpp -mex -O5 nsReturn.cpp - -%% ns2ns3ClassB -cd(toolboxpath) -mex -O5 new_ns2ns3ClassB_.cpp -mex -O5 delete_ns2ns3ClassB.cpp - -cd @ns2ns3ClassB - -%% ns2ClassC -cd(toolboxpath) -mex -O5 new_ns2ClassC_.cpp -mex -O5 delete_ns2ClassC.cpp - -cd @ns2ClassC - -%% ClassD -cd(toolboxpath) -mex -O5 new_ClassD_.cpp -mex -O5 delete_ClassD.cpp - -cd @ClassD - -cd(toolboxpath) - -echo off diff --git a/wrap/tests/expected_namespaces/new_ClassD_.cpp b/wrap/tests/expected_namespaces/new_ClassD_.cpp deleted file mode 100644 index 59ea4398b..000000000 --- a/wrap/tests/expected_namespaces/new_ClassD_.cpp +++ /dev/null @@ -1,9 +0,0 @@ -// automatically generated by wrap -#include -#include -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("new_ClassD_",nargout,nargin,0); - ClassD* self = new ClassD(); - out[0] = wrap_constructed(self,"ClassD"); -} diff --git a/wrap/tests/expected_namespaces/new_ClassD_.m b/wrap/tests/expected_namespaces/new_ClassD_.m deleted file mode 100644 index abfd419f6..000000000 --- a/wrap/tests/expected_namespaces/new_ClassD_.m +++ /dev/null @@ -1,4 +0,0 @@ -% automatically generated by wrap -function result = new_ClassD_(obj) - error('need to compile new_ClassD_.cpp'); -end diff --git a/wrap/tests/expected_namespaces/new_ns1ClassA_.cpp b/wrap/tests/expected_namespaces/new_ns1ClassA_.cpp deleted file mode 100644 index cbb82eb70..000000000 --- a/wrap/tests/expected_namespaces/new_ns1ClassA_.cpp +++ /dev/null @@ -1,9 +0,0 @@ -// automatically generated by wrap -#include -#include -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("new_ns1ClassA_",nargout,nargin,0); - ns1::ClassA* self = new ns1::ClassA(); - out[0] = wrap_constructed(self,"ns1ClassA"); -} diff --git a/wrap/tests/expected_namespaces/new_ns1ClassA_.m b/wrap/tests/expected_namespaces/new_ns1ClassA_.m deleted file mode 100644 index 054aba2f0..000000000 --- a/wrap/tests/expected_namespaces/new_ns1ClassA_.m +++ /dev/null @@ -1,4 +0,0 @@ -% automatically generated by wrap -function result = new_ns1ClassA_(obj) - error('need to compile new_ns1ClassA_.cpp'); -end diff --git a/wrap/tests/expected_namespaces/new_ns1ClassB_.cpp b/wrap/tests/expected_namespaces/new_ns1ClassB_.cpp deleted file mode 100644 index d50cede19..000000000 --- a/wrap/tests/expected_namespaces/new_ns1ClassB_.cpp +++ /dev/null @@ -1,10 +0,0 @@ -// automatically generated by wrap -#include -#include -#include -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("new_ns1ClassB_",nargout,nargin,0); - ns1::ClassB* self = new ns1::ClassB(); - out[0] = wrap_constructed(self,"ns1ClassB"); -} diff --git a/wrap/tests/expected_namespaces/new_ns1ClassB_.m b/wrap/tests/expected_namespaces/new_ns1ClassB_.m deleted file mode 100644 index b92398a17..000000000 --- a/wrap/tests/expected_namespaces/new_ns1ClassB_.m +++ /dev/null @@ -1,4 +0,0 @@ -% automatically generated by wrap -function result = new_ns1ClassB_(obj) - error('need to compile new_ns1ClassB_.cpp'); -end diff --git a/wrap/tests/expected_namespaces/new_ns2ClassA_.cpp b/wrap/tests/expected_namespaces/new_ns2ClassA_.cpp deleted file mode 100644 index 81bae3198..000000000 --- a/wrap/tests/expected_namespaces/new_ns2ClassA_.cpp +++ /dev/null @@ -1,10 +0,0 @@ -// automatically generated by wrap -#include -#include -#include -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("new_ns2ClassA_",nargout,nargin,0); - ns2::ClassA* self = new ns2::ClassA(); - out[0] = wrap_constructed(self,"ns2ClassA"); -} diff --git a/wrap/tests/expected_namespaces/new_ns2ClassA_.m b/wrap/tests/expected_namespaces/new_ns2ClassA_.m deleted file mode 100644 index 88dedf719..000000000 --- a/wrap/tests/expected_namespaces/new_ns2ClassA_.m +++ /dev/null @@ -1,4 +0,0 @@ -% automatically generated by wrap -function result = new_ns2ClassA_(obj) - error('need to compile new_ns2ClassA_.cpp'); -end diff --git a/wrap/tests/expected_namespaces/new_ns2ClassC_.cpp b/wrap/tests/expected_namespaces/new_ns2ClassC_.cpp deleted file mode 100644 index fbee07926..000000000 --- a/wrap/tests/expected_namespaces/new_ns2ClassC_.cpp +++ /dev/null @@ -1,9 +0,0 @@ -// automatically generated by wrap -#include -#include -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("new_ns2ClassC_",nargout,nargin,0); - ns2::ClassC* self = new ns2::ClassC(); - out[0] = wrap_constructed(self,"ns2ClassC"); -} diff --git a/wrap/tests/expected_namespaces/new_ns2ClassC_.m b/wrap/tests/expected_namespaces/new_ns2ClassC_.m deleted file mode 100644 index b3f711e16..000000000 --- a/wrap/tests/expected_namespaces/new_ns2ClassC_.m +++ /dev/null @@ -1,4 +0,0 @@ -% automatically generated by wrap -function result = new_ns2ClassC_(obj) - error('need to compile new_ns2ClassC_.cpp'); -end diff --git a/wrap/tests/expected_namespaces/new_ns2ns3ClassB_.cpp b/wrap/tests/expected_namespaces/new_ns2ns3ClassB_.cpp deleted file mode 100644 index ca9d02df3..000000000 --- a/wrap/tests/expected_namespaces/new_ns2ns3ClassB_.cpp +++ /dev/null @@ -1,10 +0,0 @@ -// automatically generated by wrap -#include -#include -#include -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("new_ns2ns3ClassB_",nargout,nargin,0); - ns2::ns3::ClassB* self = new ns2::ns3::ClassB(); - out[0] = wrap_constructed(self,"ns2ns3ClassB"); -} diff --git a/wrap/tests/expected_namespaces/new_ns2ns3ClassB_.m b/wrap/tests/expected_namespaces/new_ns2ns3ClassB_.m deleted file mode 100644 index 2696c2498..000000000 --- a/wrap/tests/expected_namespaces/new_ns2ns3ClassB_.m +++ /dev/null @@ -1,4 +0,0 @@ -% automatically generated by wrap -function result = new_ns2ns3ClassB_(obj) - error('need to compile new_ns2ns3ClassB_.cpp'); -end diff --git a/wrap/tests/expected_namespaces/ns2ClassA_afunction.cpp b/wrap/tests/expected_namespaces/ns2ClassA_afunction.cpp deleted file mode 100644 index 72559acf8..000000000 --- a/wrap/tests/expected_namespaces/ns2ClassA_afunction.cpp +++ /dev/null @@ -1,10 +0,0 @@ -// automatically generated by wrap -#include -#include -#include -void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) -{ - checkArguments("ns2ClassA_afunction",nargout,nargin,0); - double result = ns2::ClassA::afunction(); - out[0] = wrap< double >(result); -} diff --git a/wrap/tests/expected_namespaces/ns2ClassA_afunction.m b/wrap/tests/expected_namespaces/ns2ClassA_afunction.m deleted file mode 100644 index 3a1101918..000000000 --- a/wrap/tests/expected_namespaces/ns2ClassA_afunction.m +++ /dev/null @@ -1,5 +0,0 @@ - automatically generated by wrap -function result = ns2ClassA_afunction() -% usage: x = ns2ClassA_afunction() - error('need to compile ns2ClassA_afunction.cpp'); -end diff --git a/wrap/tests/expected_namespaces/testNamespaces_wrapper.cpp b/wrap/tests/expected_namespaces/testNamespaces_wrapper.cpp new file mode 100644 index 000000000..29739a2f6 --- /dev/null +++ b/wrap/tests/expected_namespaces/testNamespaces_wrapper.cpp @@ -0,0 +1,435 @@ +#include +#include +#include + +#include +#include +#include +#include +#include + + +typedef std::set*> Collector_ns1ClassA; +static Collector_ns1ClassA collector_ns1ClassA; +typedef std::set*> Collector_ns1ClassB; +static Collector_ns1ClassB collector_ns1ClassB; +typedef std::set*> Collector_ns2ClassA; +static Collector_ns2ClassA collector_ns2ClassA; +typedef std::set*> Collector_ns2ns3ClassB; +static Collector_ns2ns3ClassB collector_ns2ns3ClassB; +typedef std::set*> Collector_ns2ClassC; +static Collector_ns2ClassC collector_ns2ClassC; +typedef std::set*> Collector_ClassD; +static Collector_ClassD collector_ClassD; + +void _deleteAllObjects() +{ + mstream mout; + std::streambuf *outbuf = std::cout.rdbuf(&mout); + + bool anyDeleted = false; + { for(Collector_ns1ClassA::iterator iter = collector_ns1ClassA.begin(); + iter != collector_ns1ClassA.end(); ) { + delete *iter; + collector_ns1ClassA.erase(iter++); + anyDeleted = true; + } } + { for(Collector_ns1ClassB::iterator iter = collector_ns1ClassB.begin(); + iter != collector_ns1ClassB.end(); ) { + delete *iter; + collector_ns1ClassB.erase(iter++); + anyDeleted = true; + } } + { for(Collector_ns2ClassA::iterator iter = collector_ns2ClassA.begin(); + iter != collector_ns2ClassA.end(); ) { + delete *iter; + collector_ns2ClassA.erase(iter++); + anyDeleted = true; + } } + { for(Collector_ns2ns3ClassB::iterator iter = collector_ns2ns3ClassB.begin(); + iter != collector_ns2ns3ClassB.end(); ) { + delete *iter; + collector_ns2ns3ClassB.erase(iter++); + anyDeleted = true; + } } + { for(Collector_ns2ClassC::iterator iter = collector_ns2ClassC.begin(); + iter != collector_ns2ClassC.end(); ) { + delete *iter; + collector_ns2ClassC.erase(iter++); + anyDeleted = true; + } } + { for(Collector_ClassD::iterator iter = collector_ClassD.begin(); + iter != collector_ClassD.end(); ) { + delete *iter; + collector_ClassD.erase(iter++); + anyDeleted = true; + } } + if(anyDeleted) + cout << + "WARNING: Wrap modules with variables in the workspace have been reloaded due to\n" + "calling destructors, call 'clear all' again if you plan to now recompile a wrap\n" + "module, so that your recompiled module is used instead of the old one." << endl; + std::cout.rdbuf(outbuf); +} + +void _testNamespaces_RTTIRegister() { + const mxArray *alreadyCreated = mexGetVariablePtr("global", "gtsam_testNamespaces_rttiRegistry_created"); + if(!alreadyCreated) { + std::map types; + + mxArray *registry = mexGetVariable("global", "gtsamwrap_rttiRegistry"); + if(!registry) + registry = mxCreateStructMatrix(1, 1, 0, NULL); + typedef std::pair StringPair; + BOOST_FOREACH(const StringPair& rtti_matlab, types) { + int fieldId = mxAddField(registry, rtti_matlab.first.c_str()); + if(fieldId < 0) + mexErrMsgTxt("gtsam wrap: Error indexing RTTI types, inheritance will not work correctly"); + mxArray *matlabName = mxCreateString(rtti_matlab.second.c_str()); + mxSetFieldByNumber(registry, 0, fieldId, matlabName); + } + if(mexPutVariable("global", "gtsamwrap_rttiRegistry", registry) != 0) + mexErrMsgTxt("gtsam wrap: Error indexing RTTI types, inheritance will not work correctly"); + mxDestroyArray(registry); + + mxArray *newAlreadyCreated = mxCreateNumericMatrix(0, 0, mxINT8_CLASS, mxREAL); + if(mexPutVariable("global", "gtsam_testNamespaces_rttiRegistry_created", newAlreadyCreated) != 0) + mexErrMsgTxt("gtsam wrap: Error indexing RTTI types, inheritance will not work correctly"); + mxDestroyArray(newAlreadyCreated); + } +} + +void ns1ClassA_collectorInsertAndMakeBase_0(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + mexAtExit(&_deleteAllObjects); + typedef boost::shared_ptr Shared; + + Shared *self = *reinterpret_cast (mxGetData(in[0])); + collector_ns1ClassA.insert(self); +} + +void ns1ClassA_constructor_1(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + mexAtExit(&_deleteAllObjects); + typedef boost::shared_ptr Shared; + + Shared *self = new Shared(new ns1::ClassA()); + collector_ns1ClassA.insert(self); + out[0] = mxCreateNumericMatrix(1, 1, mxUINT32OR64_CLASS, mxREAL); + *reinterpret_cast (mxGetData(out[0])) = self; +} + +void ns1ClassA_deconstructor_2(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + typedef boost::shared_ptr Shared; + checkArguments("delete_ns1ClassA",nargout,nargin,1); + Shared *self = *reinterpret_cast(mxGetData(in[0])); + Collector_ns1ClassA::iterator item; + item = collector_ns1ClassA.find(self); + if(item != collector_ns1ClassA.end()) { + delete self; + collector_ns1ClassA.erase(item); + } +} + +void ns1ClassB_collectorInsertAndMakeBase_3(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + mexAtExit(&_deleteAllObjects); + typedef boost::shared_ptr Shared; + + Shared *self = *reinterpret_cast (mxGetData(in[0])); + collector_ns1ClassB.insert(self); +} + +void ns1ClassB_constructor_4(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + mexAtExit(&_deleteAllObjects); + typedef boost::shared_ptr Shared; + + Shared *self = new Shared(new ns1::ClassB()); + collector_ns1ClassB.insert(self); + out[0] = mxCreateNumericMatrix(1, 1, mxUINT32OR64_CLASS, mxREAL); + *reinterpret_cast (mxGetData(out[0])) = self; +} + +void ns1ClassB_deconstructor_5(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + typedef boost::shared_ptr Shared; + checkArguments("delete_ns1ClassB",nargout,nargin,1); + Shared *self = *reinterpret_cast(mxGetData(in[0])); + Collector_ns1ClassB::iterator item; + item = collector_ns1ClassB.find(self); + if(item != collector_ns1ClassB.end()) { + delete self; + collector_ns1ClassB.erase(item); + } +} + +void ns2ClassA_collectorInsertAndMakeBase_6(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + mexAtExit(&_deleteAllObjects); + typedef boost::shared_ptr Shared; + + Shared *self = *reinterpret_cast (mxGetData(in[0])); + collector_ns2ClassA.insert(self); +} + +void ns2ClassA_constructor_7(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + mexAtExit(&_deleteAllObjects); + typedef boost::shared_ptr Shared; + + Shared *self = new Shared(new ns2::ClassA()); + collector_ns2ClassA.insert(self); + out[0] = mxCreateNumericMatrix(1, 1, mxUINT32OR64_CLASS, mxREAL); + *reinterpret_cast (mxGetData(out[0])) = self; +} + +void ns2ClassA_deconstructor_8(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + typedef boost::shared_ptr Shared; + checkArguments("delete_ns2ClassA",nargout,nargin,1); + Shared *self = *reinterpret_cast(mxGetData(in[0])); + Collector_ns2ClassA::iterator item; + item = collector_ns2ClassA.find(self); + if(item != collector_ns2ClassA.end()) { + delete self; + collector_ns2ClassA.erase(item); + } +} + +void ns2ClassA_memberFunction_9(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + typedef boost::shared_ptr Shared; + checkArguments("memberFunction",nargout,nargin-1,0); + Shared obj = unwrap_shared_ptr(in[0], "ptr_ns2ClassA"); + out[0] = wrap< double >(obj->memberFunction()); +} + +void ns2ClassA_nsArg_10(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + typedef boost::shared_ptr Shared; + checkArguments("nsArg",nargout,nargin-1,1); + Shared obj = unwrap_shared_ptr(in[0], "ptr_ns2ClassA"); + ns1::ClassB& arg = *unwrap_shared_ptr< ns1::ClassB >(in[1], "ptr_ns1ClassB"); + out[0] = wrap< int >(obj->nsArg(arg)); +} + +void ns2ClassA_nsReturn_11(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + typedef boost::shared_ptr SharedClassB; + typedef boost::shared_ptr Shared; + checkArguments("nsReturn",nargout,nargin-1,1); + Shared obj = unwrap_shared_ptr(in[0], "ptr_ns2ClassA"); + double q = unwrap< double >(in[1]); + out[0] = wrap_shared_ptr(SharedClassB(new ns2::ns3::ClassB(obj->nsReturn(q))),"ns2.ns3.ClassB", false); +} + +void ns2ClassA_afunction_12(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + typedef boost::shared_ptr Shared; + checkArguments("ns2ClassA.afunction",nargout,nargin,0); + out[0] = wrap< double >(ns2::ClassA::afunction()); +} + +void ns2ns3ClassB_collectorInsertAndMakeBase_13(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + mexAtExit(&_deleteAllObjects); + typedef boost::shared_ptr Shared; + + Shared *self = *reinterpret_cast (mxGetData(in[0])); + collector_ns2ns3ClassB.insert(self); +} + +void ns2ns3ClassB_constructor_14(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + mexAtExit(&_deleteAllObjects); + typedef boost::shared_ptr Shared; + + Shared *self = new Shared(new ns2::ns3::ClassB()); + collector_ns2ns3ClassB.insert(self); + out[0] = mxCreateNumericMatrix(1, 1, mxUINT32OR64_CLASS, mxREAL); + *reinterpret_cast (mxGetData(out[0])) = self; +} + +void ns2ns3ClassB_deconstructor_15(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + typedef boost::shared_ptr Shared; + checkArguments("delete_ns2ns3ClassB",nargout,nargin,1); + Shared *self = *reinterpret_cast(mxGetData(in[0])); + Collector_ns2ns3ClassB::iterator item; + item = collector_ns2ns3ClassB.find(self); + if(item != collector_ns2ns3ClassB.end()) { + delete self; + collector_ns2ns3ClassB.erase(item); + } +} + +void ns2ClassC_collectorInsertAndMakeBase_16(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + mexAtExit(&_deleteAllObjects); + typedef boost::shared_ptr Shared; + + Shared *self = *reinterpret_cast (mxGetData(in[0])); + collector_ns2ClassC.insert(self); +} + +void ns2ClassC_constructor_17(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + mexAtExit(&_deleteAllObjects); + typedef boost::shared_ptr Shared; + + Shared *self = new Shared(new ns2::ClassC()); + collector_ns2ClassC.insert(self); + out[0] = mxCreateNumericMatrix(1, 1, mxUINT32OR64_CLASS, mxREAL); + *reinterpret_cast (mxGetData(out[0])) = self; +} + +void ns2ClassC_deconstructor_18(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + typedef boost::shared_ptr Shared; + checkArguments("delete_ns2ClassC",nargout,nargin,1); + Shared *self = *reinterpret_cast(mxGetData(in[0])); + Collector_ns2ClassC::iterator item; + item = collector_ns2ClassC.find(self); + if(item != collector_ns2ClassC.end()) { + delete self; + collector_ns2ClassC.erase(item); + } +} + +void ClassD_collectorInsertAndMakeBase_19(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + mexAtExit(&_deleteAllObjects); + typedef boost::shared_ptr Shared; + + Shared *self = *reinterpret_cast (mxGetData(in[0])); + collector_ClassD.insert(self); +} + +void ClassD_constructor_20(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + mexAtExit(&_deleteAllObjects); + typedef boost::shared_ptr Shared; + + Shared *self = new Shared(new ClassD()); + collector_ClassD.insert(self); + out[0] = mxCreateNumericMatrix(1, 1, mxUINT32OR64_CLASS, mxREAL); + *reinterpret_cast (mxGetData(out[0])) = self; +} + +void ClassD_deconstructor_21(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + typedef boost::shared_ptr Shared; + checkArguments("delete_ClassD",nargout,nargin,1); + Shared *self = *reinterpret_cast(mxGetData(in[0])); + Collector_ClassD::iterator item; + item = collector_ClassD.find(self); + if(item != collector_ClassD.end()) { + delete self; + collector_ClassD.erase(item); + } +} + +void ns1aGlobalFunction_22(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + checkArguments("ns1aGlobalFunction",nargout,nargin,0); + out[0] = wrap< Vector >(ns1::aGlobalFunction()); +} + +void ns2aGlobalFunction_23(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + checkArguments("ns2aGlobalFunction",nargout,nargin,0); + out[0] = wrap< Vector >(ns2::aGlobalFunction()); +} + +void mexFunction(int nargout, mxArray *out[], int nargin, const mxArray *in[]) +{ + mstream mout; + std::streambuf *outbuf = std::cout.rdbuf(&mout); + + _testNamespaces_RTTIRegister(); + + int id = unwrap(in[0]); + + try { + switch(id) { + case 0: + ns1ClassA_collectorInsertAndMakeBase_0(nargout, out, nargin-1, in+1); + break; + case 1: + ns1ClassA_constructor_1(nargout, out, nargin-1, in+1); + break; + case 2: + ns1ClassA_deconstructor_2(nargout, out, nargin-1, in+1); + break; + case 3: + ns1ClassB_collectorInsertAndMakeBase_3(nargout, out, nargin-1, in+1); + break; + case 4: + ns1ClassB_constructor_4(nargout, out, nargin-1, in+1); + break; + case 5: + ns1ClassB_deconstructor_5(nargout, out, nargin-1, in+1); + break; + case 6: + ns2ClassA_collectorInsertAndMakeBase_6(nargout, out, nargin-1, in+1); + break; + case 7: + ns2ClassA_constructor_7(nargout, out, nargin-1, in+1); + break; + case 8: + ns2ClassA_deconstructor_8(nargout, out, nargin-1, in+1); + break; + case 9: + ns2ClassA_memberFunction_9(nargout, out, nargin-1, in+1); + break; + case 10: + ns2ClassA_nsArg_10(nargout, out, nargin-1, in+1); + break; + case 11: + ns2ClassA_nsReturn_11(nargout, out, nargin-1, in+1); + break; + case 12: + ns2ClassA_afunction_12(nargout, out, nargin-1, in+1); + break; + case 13: + ns2ns3ClassB_collectorInsertAndMakeBase_13(nargout, out, nargin-1, in+1); + break; + case 14: + ns2ns3ClassB_constructor_14(nargout, out, nargin-1, in+1); + break; + case 15: + ns2ns3ClassB_deconstructor_15(nargout, out, nargin-1, in+1); + break; + case 16: + ns2ClassC_collectorInsertAndMakeBase_16(nargout, out, nargin-1, in+1); + break; + case 17: + ns2ClassC_constructor_17(nargout, out, nargin-1, in+1); + break; + case 18: + ns2ClassC_deconstructor_18(nargout, out, nargin-1, in+1); + break; + case 19: + ClassD_collectorInsertAndMakeBase_19(nargout, out, nargin-1, in+1); + break; + case 20: + ClassD_constructor_20(nargout, out, nargin-1, in+1); + break; + case 21: + ClassD_deconstructor_21(nargout, out, nargin-1, in+1); + break; + case 22: + ns1aGlobalFunction_22(nargout, out, nargin-1, in+1); + break; + case 23: + ns2aGlobalFunction_23(nargout, out, nargin-1, in+1); + break; + } + } catch(const std::exception& e) { + mexErrMsgTxt(("Exception from gtsam:\n" + std::string(e.what()) + "\n").c_str()); + } + + std::cout.rdbuf(outbuf); +} diff --git a/wrap/tests/geometry.h b/wrap/tests/geometry.h index a287c44e6..54694a1cf 100644 --- a/wrap/tests/geometry.h +++ b/wrap/tests/geometry.h @@ -15,9 +15,6 @@ class Point2 { VectorNotEigen vectorConfusion(); }; -// flag a namespace as in use - only applies *after* the declaration -using namespace geometry; - class Point3 { Point3(double x, double y, double z); double norm() const; @@ -35,7 +32,9 @@ class Point3 { * A multi-line comment! */ +// An include! Can go anywhere outside of a class, in any order #include + class Test { /* a comment! */ @@ -80,6 +79,9 @@ class Test { // even more comments at the end! }; + +Vector aGlobalFunction(); + // comments at the end! // even more comments at the end! diff --git a/wrap/tests/testDependencies.h b/wrap/tests/testDependencies.h index 429bb5a2a..34a8056b8 100644 --- a/wrap/tests/testDependencies.h +++ b/wrap/tests/testDependencies.h @@ -1,24 +1,8 @@ //Header file to test dependency checking // class Pose3 { - Pose3(); - Pose3(const Rot3& r, const Point3& t);//What is Rot3? Throw here - Pose3(Vector v); - Pose3(Matrix t); - static Pose3 Expmap(Vector v); - static Vector Logmap(const Pose3& p); - static Rot3 testStaticDep(Rot3& r);//What is Rot3? Throw here - void print(string s) const; - bool equals(const Pose3& pose, double tol) const; - double x() const; - double y() const; - double z() const; - Rot3 testReturnType() const; // Throw here - Matrix matrix() const; - Matrix adjointMap() const; - Pose3 compose(const Pose3& p2); - Pose3 between(const Pose3& p2); - Pose3 retract(Vector v); - Point3 translation() const; - Rot3 rotation() const; //What is Rot3? Throw here + Pose3(const Rot3& r, const Point3& t); //What is Rot3? Throw here + static Rot3 testStaticDep(Rot3& r); //What is Rot3? Throw here + Rot3 testReturnType() const; // Throw here + void testMethodArg(const Rot3& r) const; }; diff --git a/wrap/tests/testNamespaces.h b/wrap/tests/testNamespaces.h index 644fdb3ea..2c12686c0 100644 --- a/wrap/tests/testNamespaces.h +++ b/wrap/tests/testNamespaces.h @@ -14,7 +14,10 @@ class ClassB { ClassB(); }; -}///\namespace ns1 +// check namespace handling +Vector aGlobalFunction(); + +} #include namespace ns2 { @@ -35,13 +38,16 @@ class ClassB { ClassB(); }; -}///\namespace ns3 +} class ClassC { ClassC(); }; -}///\namespace ns2 +// separate namespace global function, same name +Vector aGlobalFunction(); + +} //\namespace ns2 class ClassD { ClassD(); diff --git a/wrap/tests/testWrap.cpp b/wrap/tests/testWrap.cpp index cdee692a5..844281775 100644 --- a/wrap/tests/testWrap.cpp +++ b/wrap/tests/testWrap.cpp @@ -20,6 +20,7 @@ #include #include #include +#include #include #include @@ -28,6 +29,7 @@ using namespace std; using namespace boost::assign; using namespace wrap; +namespace fs = boost::filesystem; static bool enable_verbose = false; #ifdef TOPSRCDIR static string topdir = TOPSRCDIR; @@ -37,6 +39,10 @@ static string topdir = "TOPSRCDIR_NOT_CONFIGURED"; // If TOPSRCDIR is not define typedef vector strvec; +// NOTE: as this path is only used to generate makefiles, it is hardcoded here for testing +// In practice, this path will be an absolute system path, which makes testing it more annoying +static const std::string headerPath = "/not_really_a_real_path/borg/gtsam/wrap"; + /* ************************************************************************* */ TEST( wrap, ArgumentList ) { ArgumentList args; @@ -52,89 +58,105 @@ TEST( wrap, ArgumentList ) { } /* ************************************************************************* */ -TEST( wrap, check_exception ) { +TEST_UNSAFE( wrap, check_exception ) { THROWS_EXCEPTION(Module("/notarealpath", "geometry",enable_verbose)); CHECK_EXCEPTION(Module("/alsonotarealpath", "geometry",enable_verbose), CantOpenFile); // clean out previous generated code - string cleanCmd = "rm -rf actual_deps"; - system(cleanCmd.c_str()); + fs::remove_all("actual_deps"); string path = topdir + "/wrap/tests"; Module module(path.c_str(), "testDependencies",enable_verbose); - CHECK_EXCEPTION(module.matlab_code("actual_deps", "mexa64", "-O5"), DependencyMissing); + CHECK_EXCEPTION(module.matlab_code("actual_deps", headerPath), DependencyMissing); } /* ************************************************************************* */ -TEST( wrap, parse ) { - string header_path = topdir + "/wrap/tests"; - Module module(header_path.c_str(), "geometry",enable_verbose); +TEST( wrap, parse_geometry ) { + string markup_header_path = topdir + "/wrap/tests"; + Module module(markup_header_path.c_str(), "geometry",enable_verbose); EXPECT_LONGS_EQUAL(3, module.classes.size()); - // check using declarations - strvec exp_using1, exp_using2; exp_using2 += "geometry"; - // forward declarations - strvec exp_forward; exp_forward += "VectorNotEigen", "ns::OtherClass"; - EXPECT(assert_equal(exp_forward, module.forward_declarations)); + LONGS_EQUAL(2, module.forward_declarations.size()); + EXPECT(assert_equal("VectorNotEigen", module.forward_declarations[0].name)); + EXPECT(assert_equal("ns::OtherClass", module.forward_declarations[1].name)); + + // includes + strvec exp_includes; exp_includes += "folder/path/to/Test.h"; + EXPECT(assert_equal(exp_includes, module.includes)); + + LONGS_EQUAL(3, module.classes.size()); // check first class, Point2 { Class cls = module.classes.at(0); EXPECT(assert_equal("Point2", cls.name)); - EXPECT_LONGS_EQUAL(2, cls.constructors.size()); + EXPECT_LONGS_EQUAL(2, cls.constructor.args_list.size()); EXPECT_LONGS_EQUAL(7, cls.methods.size()); EXPECT_LONGS_EQUAL(0, cls.static_methods.size()); EXPECT_LONGS_EQUAL(0, cls.namespaces.size()); - EXPECT(assert_equal(exp_using1, cls.using_namespaces)); } // check second class, Point3 { Class cls = module.classes.at(1); EXPECT(assert_equal("Point3", cls.name)); - EXPECT_LONGS_EQUAL(1, cls.constructors.size()); + EXPECT_LONGS_EQUAL(1, cls.constructor.args_list.size()); EXPECT_LONGS_EQUAL(1, cls.methods.size()); EXPECT_LONGS_EQUAL(2, cls.static_methods.size()); EXPECT_LONGS_EQUAL(0, cls.namespaces.size()); - EXPECT(assert_equal(exp_using2, cls.using_namespaces)); // first constructor takes 3 doubles - Constructor c1 = cls.constructors.front(); - EXPECT_LONGS_EQUAL(3, c1.args.size()); + ArgumentList c1 = cls.constructor.args_list.front(); + EXPECT_LONGS_EQUAL(3, c1.size()); // check first double argument - Argument a1 = c1.args.front(); + Argument a1 = c1.front(); EXPECT(!a1.is_const); EXPECT(assert_equal("double", a1.type)); EXPECT(!a1.is_ref); EXPECT(assert_equal("x", a1.name)); // check method - Method m1 = cls.methods.front(); - EXPECT(assert_equal("double", m1.returnVal.type1)); + CHECK(cls.methods.find("norm") != cls.methods.end()); + Method m1 = cls.methods.find("norm")->second; + LONGS_EQUAL(1, m1.returnVals.size()); + EXPECT(assert_equal("double", m1.returnVals.front().type1)); EXPECT(assert_equal("norm", m1.name)); - EXPECT_LONGS_EQUAL(0, m1.args.size()); + LONGS_EQUAL(1, m1.argLists.size()); + EXPECT_LONGS_EQUAL(0, m1.argLists.front().size()); EXPECT(m1.is_const_); } // Test class is the third one { - LONGS_EQUAL(3, module.classes.size()); Class testCls = module.classes.at(2); - EXPECT_LONGS_EQUAL( 2, testCls.constructors.size()); + EXPECT_LONGS_EQUAL( 2, testCls.constructor.args_list.size()); EXPECT_LONGS_EQUAL(19, testCls.methods.size()); EXPECT_LONGS_EQUAL( 0, testCls.static_methods.size()); EXPECT_LONGS_EQUAL( 0, testCls.namespaces.size()); - EXPECT(assert_equal(exp_using2, testCls.using_namespaces)); - strvec exp_includes; exp_includes += "folder/path/to/Test.h"; - EXPECT(assert_equal(exp_includes, testCls.includes)); // function to parse: pair return_pair (Vector v, Matrix A) const; - Method m2 = testCls.methods.front(); - EXPECT(m2.returnVal.isPair); - EXPECT(m2.returnVal.category1 == ReturnValue::EIGEN); - EXPECT(m2.returnVal.category2 == ReturnValue::EIGEN); + CHECK(testCls.methods.find("return_pair") != testCls.methods.end()); + Method m2 = testCls.methods.find("return_pair")->second; + LONGS_EQUAL(1, m2.returnVals.size()); + EXPECT(m2.returnVals.front().isPair); + EXPECT(m2.returnVals.front().category1 == ReturnValue::EIGEN); + EXPECT(m2.returnVals.front().category2 == ReturnValue::EIGEN); + } + + // evaluate global functions +// Vector aGlobalFunction(); + LONGS_EQUAL(1, module.global_functions.size()); + CHECK(module.global_functions.find("aGlobalFunction") != module.global_functions.end()); + { + GlobalFunction gfunc = module.global_functions.at("aGlobalFunction"); + EXPECT(assert_equal("aGlobalFunction", gfunc.name)); + LONGS_EQUAL(1, gfunc.returnVals.size()); + EXPECT(assert_equal("Vector", gfunc.returnVals.front().type1)); + EXPECT_LONGS_EQUAL(1, gfunc.argLists.size()); + LONGS_EQUAL(1, gfunc.namespaces.size()); + EXPECT(gfunc.namespaces.front().empty()); } } @@ -144,13 +166,21 @@ TEST( wrap, parse_namespaces ) { Module module(header_path.c_str(), "testNamespaces",enable_verbose); EXPECT_LONGS_EQUAL(6, module.classes.size()); + { + strvec module_exp_includes; + module_exp_includes += "path/to/ns1.h"; + module_exp_includes += "path/to/ns1/ClassB.h"; + module_exp_includes += "path/to/ns2.h"; + module_exp_includes += "path/to/ns2/ClassA.h"; + module_exp_includes += "path/to/ns3.h"; + EXPECT(assert_equal(module_exp_includes, module.includes)); + } + { Class cls = module.classes.at(0); EXPECT(assert_equal("ClassA", cls.name)); strvec exp_namespaces; exp_namespaces += "ns1"; EXPECT(assert_equal(exp_namespaces, cls.namespaces)); - strvec exp_includes; exp_includes += "path/to/ns1.h", ""; - EXPECT(assert_equal(exp_includes, cls.includes)); } { @@ -158,8 +188,6 @@ TEST( wrap, parse_namespaces ) { EXPECT(assert_equal("ClassB", cls.name)); strvec exp_namespaces; exp_namespaces += "ns1"; EXPECT(assert_equal(exp_namespaces, cls.namespaces)); - strvec exp_includes; exp_includes += "path/to/ns1.h", "path/to/ns1/ClassB.h"; - EXPECT(assert_equal(exp_includes, cls.includes)); } { @@ -167,8 +195,6 @@ TEST( wrap, parse_namespaces ) { EXPECT(assert_equal("ClassA", cls.name)); strvec exp_namespaces; exp_namespaces += "ns2"; EXPECT(assert_equal(exp_namespaces, cls.namespaces)); - strvec exp_includes; exp_includes += "path/to/ns2.h", "path/to/ns2/ClassA.h"; - EXPECT(assert_equal(exp_includes, cls.includes)); } { @@ -176,8 +202,6 @@ TEST( wrap, parse_namespaces ) { EXPECT(assert_equal("ClassB", cls.name)); strvec exp_namespaces; exp_namespaces += "ns2", "ns3"; EXPECT(assert_equal(exp_namespaces, cls.namespaces)); - strvec exp_includes; exp_includes += "path/to/ns2.h", "path/to/ns3.h", ""; - EXPECT(assert_equal(exp_includes, cls.includes)); } { @@ -185,8 +209,6 @@ TEST( wrap, parse_namespaces ) { EXPECT(assert_equal("ClassC", cls.name)); strvec exp_namespaces; exp_namespaces += "ns2"; EXPECT(assert_equal(exp_namespaces, cls.namespaces)); - strvec exp_includes; exp_includes += "path/to/ns2.h", ""; - EXPECT(assert_equal(exp_includes, cls.includes)); } { @@ -194,10 +216,28 @@ TEST( wrap, parse_namespaces ) { EXPECT(assert_equal("ClassD", cls.name)); strvec exp_namespaces; EXPECT(assert_equal(exp_namespaces, cls.namespaces)); - strvec exp_includes; exp_includes += ""; - EXPECT(assert_equal(exp_includes, cls.includes)); } + // evaluate global functions +// Vector ns1::aGlobalFunction(); +// Vector ns2::aGlobalFunction(); + LONGS_EQUAL(1, module.global_functions.size()); + CHECK(module.global_functions.find("aGlobalFunction") != module.global_functions.end()); + { + GlobalFunction gfunc = module.global_functions.at("aGlobalFunction"); + EXPECT(assert_equal("aGlobalFunction", gfunc.name)); + LONGS_EQUAL(2, gfunc.returnVals.size()); + EXPECT(assert_equal("Vector", gfunc.returnVals.front().type1)); + EXPECT_LONGS_EQUAL(2, gfunc.argLists.size()); + + // check namespaces + LONGS_EQUAL(2, gfunc.namespaces.size()); + strvec exp_namespaces1; exp_namespaces1 += "ns1"; + EXPECT(assert_equal(exp_namespaces1, gfunc.namespaces.at(0))); + + strvec exp_namespaces2; exp_namespaces2 += "ns2"; + EXPECT(assert_equal(exp_namespaces2, gfunc.namespaces.at(1))); + } } /* ************************************************************************* */ @@ -208,95 +248,44 @@ TEST( wrap, matlab_code_namespaces ) { string path = topdir + "/wrap"; // clean out previous generated code - string cleanCmd = "rm -rf actual_namespaces"; - system(cleanCmd.c_str()); + fs::remove_all("actual_namespaces"); // emit MATLAB code - string exp_path = path + "/tests/expected_namespaces/"; - string act_path = "actual_namespaces/"; - module.matlab_code("actual_namespaces", "mexa64", "-O5"); + string exp_path = path + "/tests/expected_namespaces/"; + string act_path = "actual_namespaces/"; + module.matlab_code("actual_namespaces", headerPath); - EXPECT(files_equal(exp_path + "new_ClassD_.cpp" , act_path + "new_ClassD_.cpp" )); - EXPECT(files_equal(exp_path + "new_ClassD_.m" , act_path + "new_ClassD_.m" )); - EXPECT(files_equal(exp_path + "new_ns1ClassA_.cpp" , act_path + "new_ns1ClassA_.cpp" )); - EXPECT(files_equal(exp_path + "new_ns1ClassA_.m" , act_path + "new_ns1ClassA_.m" )); - EXPECT(files_equal(exp_path + "new_ns1ClassB_.cpp" , act_path + "new_ns1ClassB_.cpp" )); - EXPECT(files_equal(exp_path + "new_ns1ClassB_.m" , act_path + "new_ns1ClassB_.m" )); - EXPECT(files_equal(exp_path + "new_ns2ClassA_.cpp" , act_path + "new_ns2ClassA_.cpp" )); - EXPECT(files_equal(exp_path + "new_ns2ClassA_.m" , act_path + "new_ns2ClassA_.m" )); - EXPECT(files_equal(exp_path + "new_ns2ClassC_.cpp" , act_path + "new_ns2ClassC_.cpp" )); - EXPECT(files_equal(exp_path + "new_ns2ClassC_.m" , act_path + "new_ns2ClassC_.m" )); - EXPECT(files_equal(exp_path + "new_ns2ns3ClassB_.cpp" , act_path + "new_ns2ns3ClassB_.cpp" )); - EXPECT(files_equal(exp_path + "new_ns2ns3ClassB_.m" , act_path + "new_ns2ns3ClassB_.m" )); - EXPECT(files_equal(exp_path + "delete_ClassD.cpp" , act_path + "delete_ClassD.cpp" )); - EXPECT(files_equal(exp_path + "delete_ClassD.m" , act_path + "delete_ClassD.m" )); - EXPECT(files_equal(exp_path + "delete_ns1ClassA.cpp" , act_path + "delete_ns1ClassA.cpp" )); - EXPECT(files_equal(exp_path + "delete_ns1ClassA.m" , act_path + "delete_ns1ClassA.m" )); - EXPECT(files_equal(exp_path + "delete_ns1ClassB.cpp" , act_path + "delete_ns1ClassB.cpp" )); - EXPECT(files_equal(exp_path + "delete_ns1ClassB.m" , act_path + "delete_ns1ClassB.m" )); - EXPECT(files_equal(exp_path + "delete_ns2ClassA.cpp" , act_path + "delete_ns2ClassA.cpp" )); - EXPECT(files_equal(exp_path + "delete_ns2ClassA.m" , act_path + "delete_ns2ClassA.m" )); - EXPECT(files_equal(exp_path + "delete_ns2ClassC.cpp" , act_path + "delete_ns2ClassC.cpp" )); - EXPECT(files_equal(exp_path + "delete_ns2ClassC.m" , act_path + "delete_ns2ClassC.m" )); - EXPECT(files_equal(exp_path + "delete_ns2ns3ClassB.cpp" , act_path + "delete_ns2ns3ClassB.cpp" )); - EXPECT(files_equal(exp_path + "delete_ns2ns3ClassB.m" , act_path + "delete_ns2ns3ClassB.m" )); - EXPECT(files_equal(exp_path + "ns2ClassA_afunction.cpp" , act_path + "ns2ClassA_afunction.cpp" )); - EXPECT(files_equal(exp_path + "ns2ClassA_afunction.m" , act_path + "ns2ClassA_afunction.m" )); - EXPECT(files_equal(exp_path + "@ns2ClassA/memberFunction.cpp", act_path + "@ns2ClassA/memberFunction.cpp")); - EXPECT(files_equal(exp_path + "@ns2ClassA/memberFunction.m" , act_path + "@ns2ClassA/memberFunction.m" )); - EXPECT(files_equal(exp_path + "@ns2ClassA/ns2ClassA.m" , act_path + "@ns2ClassA/ns2ClassA.m" )); - EXPECT(files_equal(exp_path + "@ns2ClassA/nsArg.cpp" , act_path + "@ns2ClassA/nsArg.cpp" )); - EXPECT(files_equal(exp_path + "@ns2ClassA/nsArg.m" , act_path + "@ns2ClassA/nsArg.m" )); - EXPECT(files_equal(exp_path + "@ns2ClassA/nsReturn.cpp" , act_path + "@ns2ClassA/nsReturn.cpp" )); - EXPECT(files_equal(exp_path + "@ns2ClassA/nsReturn.m" , act_path + "@ns2ClassA/nsReturn.m" )); - - EXPECT(files_equal(exp_path + "make_testNamespaces.m", act_path + "make_testNamespaces.m")); - EXPECT(files_equal(exp_path + "Makefile" , act_path + "Makefile" )); + EXPECT(files_equal(exp_path + "ClassD.m" , act_path + "ClassD.m" )); + EXPECT(files_equal(exp_path + "+ns1/ClassA.m" , act_path + "+ns1/ClassA.m" )); + EXPECT(files_equal(exp_path + "+ns1/ClassB.m" , act_path + "+ns1/ClassB.m" )); + EXPECT(files_equal(exp_path + "+ns2/ClassA.m" , act_path + "+ns2/ClassA.m" )); + EXPECT(files_equal(exp_path + "+ns2/ClassC.m" , act_path + "+ns2/ClassC.m" )); + EXPECT(files_equal(exp_path + "+ns2/+ns3/ClassB.m" , act_path + "+ns2/+ns3/ClassB.m" )); + EXPECT(files_equal(exp_path + "testNamespaces_wrapper.cpp" , act_path + "testNamespaces_wrapper.cpp" )); } /* ************************************************************************* */ -TEST( wrap, matlab_code ) { +TEST( wrap, matlab_code_geometry ) { // Parse into class object string header_path = topdir + "/wrap/tests"; Module module(header_path,"geometry",enable_verbose); string path = topdir + "/wrap"; // clean out previous generated code - string cleanCmd = "rm -rf actual"; - system(cleanCmd.c_str()); + fs::remove_all("actual"); // emit MATLAB code // make_geometry will not compile, use make testwrap to generate real make - module.matlab_code("actual", "mexa64", "-O5"); + module.matlab_code("actual", headerPath); + string epath = path + "/tests/expected/"; + string apath = "actual/"; - EXPECT(files_equal(path + "/tests/expected/@Point2/Point2.m" , "actual/@Point2/Point2.m" )); - EXPECT(files_equal(path + "/tests/expected/@Point2/x.cpp" , "actual/@Point2/x.cpp" )); - EXPECT(files_equal(path + "/tests/expected/@Point3/Point3.m" , "actual/@Point3/Point3.m" )); - EXPECT(files_equal(path + "/tests/expected/new_Point3_ddd.m" , "actual/new_Point3_ddd.m" )); - EXPECT(files_equal(path + "/tests/expected/new_Point3_ddd.cpp", "actual/new_Point3_ddd.cpp")); - EXPECT(files_equal(path + "/tests/expected/Point3_staticFunction.m" , "actual/Point3_staticFunction.m" )); - EXPECT(files_equal(path + "/tests/expected/Point3_staticFunction.cpp", "actual/Point3_staticFunction.cpp")); - EXPECT(files_equal(path + "/tests/expected/@Point3/norm.m" , "actual/@Point3/norm.m" )); - EXPECT(files_equal(path + "/tests/expected/@Point3/norm.cpp" , "actual/@Point3/norm.cpp" )); - - EXPECT(files_equal(path + "/tests/expected/new_Test_.cpp" , "actual/new_Test_.cpp" )); - EXPECT(files_equal(path + "/tests/expected/delete_Test.cpp" , "actual/delete_Test.cpp" )); - EXPECT(files_equal(path + "/tests/expected/delete_Test.m" , "actual/delete_Test.m" )); - EXPECT(files_equal(path + "/tests/expected/@Test/Test.m" , "actual/@Test/Test.m" )); - EXPECT(files_equal(path + "/tests/expected/@Test/return_string.cpp" , "actual/@Test/return_string.cpp" )); - EXPECT(files_equal(path + "/tests/expected/@Test/return_pair.cpp" , "actual/@Test/return_pair.cpp" )); - EXPECT(files_equal(path + "/tests/expected/@Test/create_MixedPtrs.cpp", "actual/@Test/create_MixedPtrs.cpp")); - EXPECT(files_equal(path + "/tests/expected/@Test/return_field.cpp" , "actual/@Test/return_field.cpp" )); - EXPECT(files_equal(path + "/tests/expected/@Test/return_TestPtr.cpp", "actual/@Test/return_TestPtr.cpp")); - EXPECT(files_equal(path + "/tests/expected/@Test/return_Test.cpp" , "actual/@Test/return_Test.cpp" )); - EXPECT(files_equal(path + "/tests/expected/@Test/return_Point2Ptr.cpp", "actual/@Test/return_Point2Ptr.cpp")); - EXPECT(files_equal(path + "/tests/expected/@Test/return_ptrs.cpp" , "actual/@Test/return_ptrs.cpp" )); - EXPECT(files_equal(path + "/tests/expected/@Test/print.m" , "actual/@Test/print.m" )); - EXPECT(files_equal(path + "/tests/expected/@Test/print.cpp" , "actual/@Test/print.cpp" )); - - EXPECT(files_equal(path + "/tests/expected/make_geometry.m", "actual/make_geometry.m")); - EXPECT(files_equal(path + "/tests/expected/Makefile" , "actual/Makefile" )); + EXPECT(files_equal(epath + "geometry_wrapper.cpp" , apath + "geometry_wrapper.cpp" )); + EXPECT(files_equal(epath + "Point2.m" , apath + "Point2.m" )); + EXPECT(files_equal(epath + "Point3.m" , apath + "Point3.m" )); + EXPECT(files_equal(epath + "Test.m" , apath + "Test.m" )); + EXPECT(files_equal(epath + "aGlobalFunction.m" , apath + "aGlobalFunction.m" )); } /* ************************************************************************* */ diff --git a/wrap/utilities.cpp b/wrap/utilities.cpp index 7b82d9b9d..973778d71 100644 --- a/wrap/utilities.cpp +++ b/wrap/utilities.cpp @@ -12,12 +12,15 @@ /** * @file utilities.ccp * @author Frank Dellaert + * @author Andrew Melim + * @author Richard Roberts **/ #include #include #include +#include #include "utilities.h" @@ -103,33 +106,44 @@ bool files_equal(const string& expected, const string& actual, bool skipheader) } /* ************************************************************************* */ -string maybe_shared_ptr(bool add, const string& type) { - string str = add? "shared_ptr<" : ""; - str += type; - if (add) str += ">"; +string maybe_shared_ptr(bool add, const string& qtype, const string& type) { + string str = add? "Shared" : ""; + if (add) str += type; + else str += qtype; + + //if (add) str += ">"; return str; } /* ************************************************************************* */ -void generateUsingNamespace(FileWriter& file, const vector& using_namespaces) { - if (using_namespaces.empty()) return; - BOOST_FOREACH(const string& s, using_namespaces) - file.oss << "using namespace " << s << ";" << endl; +string qualifiedName(const string& separator, const vector& names, const string& finalName) { + string result; + if(!names.empty()) { + for(size_t i = 0; i < names.size() - 1; ++i) + result += (names[i] + separator); + if(finalName.empty()) + result += names.back(); + else + result += (names.back() + separator + finalName); + } else if(!finalName.empty()) { + result = finalName; + } + return result; } /* ************************************************************************* */ -void generateIncludes(FileWriter& file, const string& class_name, - const vector& includes) { - file.oss << "#include " << endl; - bool added_include = false; - BOOST_FOREACH(const string& s, includes) { - if (!s.empty()) { - file.oss << "#include <" << s << ">" << endl; - added_include = true; +void createNamespaceStructure(const std::vector& namespaces, const std::string& toolboxPath) { + using namespace boost::filesystem; + path curPath = toolboxPath; + BOOST_FOREACH(const string& subdir, namespaces) { + curPath /= "+" + subdir; + if(!is_directory(curPath)) { + if(exists("+" + subdir)) + throw OutputError("Need to write files to directory " + curPath.string() + ", which already exists as a file but is not a directory"); + else + boost::filesystem::create_directory(curPath); } } - if (!added_include) // add default include - file.oss << "#include <" << class_name << ".h>" << endl; } /* ************************************************************************* */ diff --git a/wrap/utilities.h b/wrap/utilities.h index 384ff3749..85a2246a2 100644 --- a/wrap/utilities.h +++ b/wrap/utilities.h @@ -10,8 +10,10 @@ * -------------------------------------------------------------------------- */ /** - * @file utilities.ccp + * @file utilities.h * @author Frank Dellaert + * @author Andrew Melim + * @author Richard Roberts **/ #pragma once @@ -20,6 +22,11 @@ #include #include #include +//#include // on Linux GCC: fails with error regarding needing C++0x std flags +//#include // same failure as above +#include // works on Linux GCC +#include +#include #include "FileWriter.h" @@ -27,44 +34,73 @@ namespace wrap { class CantOpenFile : public std::exception { private: - std::string filename_; + const std::string what_; public: - CantOpenFile(const std::string& filename) : filename_(filename) {} + CantOpenFile(const std::string& filename) : what_("Can't open file " + filename) {} ~CantOpenFile() throw() {} - virtual const char* what() const throw() { - return ("Can't open file " + filename_).c_str(); - } + virtual const char* what() const throw() { return what_.c_str(); } +}; + +class OutputError : public std::exception { +private: + const std::string what_; +public: + OutputError(const std::string& what) : what_(what) {} + ~OutputError() throw() {} + virtual const char* what() const throw() { return what_.c_str(); } }; class ParseFailed : public std::exception { private: - int length_; + const std::string what_; public: - ParseFailed(int length) : length_(length) {} - ~ParseFailed() throw() {} - virtual const char* what() const throw() { - std::stringstream buf; - int len = length_+1; - buf << "Parse failed at character [" << len << "]"; - return buf.str().c_str(); - } + ParseFailed(int length) : what_((boost::format("Parse failed at character [%d]")%(length-1)).str()) {} + ~ParseFailed() throw() {} + virtual const char* what() const throw() { return what_.c_str(); } }; class DependencyMissing : public std::exception { private: - std::string dependency_; - std::string location_; + const std::string what_; public: - DependencyMissing(const std::string& dep, const std::string& loc) { - dependency_ = dep; - location_ = loc; - } + DependencyMissing(const std::string& dep, const std::string& loc) : + what_("Missing dependency " + dep + " in " + loc) {} ~DependencyMissing() throw() {} - virtual const char* what() const throw() { - return ("Missing dependency " + dependency_ + " in " + location_).c_str(); - } + virtual const char* what() const throw() { return what_.c_str(); } }; +class DuplicateDefinition : public std::exception { +private: + const std::string what_; +public: + DuplicateDefinition(const std::string& name) : + what_("Duplicate definition of " + name) {} + ~DuplicateDefinition() throw() {} + virtual const char* what() const throw() { return what_.c_str(); } +}; + +class AttributeError : public std::exception { +private: + const std::string what_; +public: + AttributeError(const std::string& name, const std::string& problem) : + what_("Class " + name + ": " + problem) {} + ~AttributeError() throw() {} + virtual const char* what() const throw() { return what_.c_str(); } +}; + +// "Unique" key to signal calling the matlab object constructor with a raw pointer +// to a shared pointer of the same C++ object type as the MATLAB type. +// Also present in matlab.h +static const uint64_t ptr_constructor_key = + (uint64_t('G') << 56) | + (uint64_t('T') << 48) | + (uint64_t('S') << 40) | + (uint64_t('A') << 32) | + (uint64_t('M') << 24) | + (uint64_t('p') << 16) | + (uint64_t('t') << 8) | + (uint64_t('r')); /** * read contents of a file into a std::string @@ -84,17 +120,15 @@ bool assert_equal(const std::string& expected, const std::string& actual); bool assert_equal(const std::vector& expected, const std::vector& actual); // auxiliary function to wrap an argument into a shared_ptr template -std::string maybe_shared_ptr(bool add, const std::string& type); +std::string maybe_shared_ptr(bool add, const std::string& qtype, const std::string& type); /** - * Creates the "using namespace [name];" declarations + * Return a qualified name, if finalName is empty, only the names vector will + * be used (i.e. there won't be a trailing separator on the qualified name). */ -void generateUsingNamespace(FileWriter& file, const std::vector& using_namespaces); +std::string qualifiedName(const std::string& separator, const std::vector& names, const std::string& finalName = ""); -/** - * Creates the #include statements - */ -void generateIncludes(FileWriter& file, const std::string& class_name, - const std::vector& includes); +/** creates the necessary folders for namespaces, as specified by a namespace stack */ +void createNamespaceStructure(const std::vector& namespaces, const std::string& toolboxPath); } // \namespace wrap diff --git a/wrap/wrap.cpp b/wrap/wrap.cpp index f55927a5e..05763d892 100644 --- a/wrap/wrap.cpp +++ b/wrap/wrap.cpp @@ -24,36 +24,33 @@ using namespace std; /** * Top-level function to wrap a module - * @param mexExt is the extension for mex binaries for this os/cpu * @param interfacePath path to where interface file lives, e.g., borg/gtsam * @param moduleName name of the module to be generated e.g. gtsam * @param toolboxPath path where the toolbox should be generated, e.g. borg/gtsam/build - * @param nameSpace e.g. gtsam - * @param mexFlags extra arguments for mex script, i.e., include flags etc... + * @param headerPath is the path to matlab.h */ -void generate_matlab_toolbox(const string& mexExt, +void generate_matlab_toolbox( const string& interfacePath, const string& moduleName, const string& toolboxPath, - const string& mexFlags) + const string& headerPath) { // Parse interface file into class object // This recursively creates Class objects, Method objects, etc... - wrap::Module module(interfacePath, moduleName, true); + wrap::Module module(interfacePath, moduleName, false); // Then emit MATLAB code - module.matlab_code(toolboxPath,mexExt,mexFlags); + module.matlab_code(toolboxPath,headerPath); } /** Displays usage information */ void usage() { cerr << "wrap parses an interface file and produces a MATLAB toolbox" << endl; - cerr << "usage: wrap mexExtension interfacePath moduleName toolboxPath [mexFlags]" << endl; - cerr << " mexExtension : OS/CPU-dependent extension for MEX binaries" << endl; + cerr << "usage: wrap interfacePath moduleName toolboxPath headerPath" << endl; cerr << " interfacePath : *absolute* path to directory of module interface file" << endl; cerr << " moduleName : the name of the module, interface file must be called moduleName.h" << endl; cerr << " toolboxPath : the directory in which to generate the wrappers" << endl; - cerr << " [mexFlags] : extra flags for the mex command" << endl; + cerr << " headerPath : path to matlab.h" << endl; } /** @@ -61,7 +58,7 @@ void usage() { * Typically called from "make all" using appropriate arguments */ int main(int argc, const char* argv[]) { - if (argc<6 || argc>7) { + if (argc != 5) { cerr << "Invalid arguments:\n"; for (int i=0; i