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Merge pull request #477 from borglab/temp/copy_python 

Mega change: New Wrapper (Python & MATLAB)
release/4.3a0
Fan Jiang 2020-08-19 11:34:39 -04:00 committed by GitHub
parent b09a6c98f9 905a13c940
commit ac35670728
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
505 changed files with 19800 additions and 16419 deletions
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6
.github/scripts/python.sh vendored
View File

@ -47,8 +47,6 @@ case $WRAPPER in
;;
esac
git submodule update --init --recursive
mkdir $GITHUB_WORKSPACE/build
cd $GITHUB_WORKSPACE/build
@ -82,9 +80,9 @@ case $WRAPPER in
$PYTHON -m unittest discover
;;
"pybind")
cd $GITHUB_WORKSPACE/python
cd $GITHUB_WORKSPACE/build/python
$PYTHON setup.py install --user --prefix=
cd $GITHUB_WORKSPACE/wrap/python/gtsam_py/tests
cd $GITHUB_WORKSPACE/python/gtsam/tests
$PYTHON -m unittest discover
;;
*)

1
.github/scripts/unix.sh vendored
View File

@ -47,7 +47,6 @@ function configure()
BUILD_DIR=$GITHUB_WORKSPACE/build
#env
git submodule update --init --recursive
rm -fr $BUILD_DIR || true
mkdir $BUILD_DIR && cd $BUILD_DIR

2
.github/workflows/build-python.yml vendored
View File

@ -27,7 +27,7 @@ jobs:
build_type: [Debug, Release]
python_version: [3]
wrapper: [cython]
wrapper: [pybind]
include:
- name: ubuntu-18.04-gcc-5
os: ubuntu-18.04

268
CMakeLists.txt
View File

@ -65,16 +65,19 @@ add_custom_target(uninstall
# Configurable Options
if(GTSAM_UNSTABLE_AVAILABLE)
option(GTSAM_BUILD_UNSTABLE "Enable/Disable libgtsam_unstable" ON)
option(GTSAM_UNSTABLE_BUILD_PYTHON "Enable/Disable Python wrapper for libgtsam_unstable" ON)
option(GTSAM_UNSTABLE_INSTALL_MATLAB_TOOLBOX "Enable/Disable MATLAB wrapper for libgtsam_unstable" OFF)
endif()
option(BUILD_SHARED_LIBS "Build shared gtsam library, instead of static" ON)
option(GTSAM_USE_QUATERNIONS "Enable/Disable using an internal Quaternion representation for rotations instead of rotation matrices. If enable, Rot3::EXPMAP is enforced by default." OFF)
option(GTSAM_POSE3_EXPMAP "Enable/Disable using Pose3::EXPMAP as the default mode. If disabled, Pose3::FIRST_ORDER will be used." ON)
option(GTSAM_ROT3_EXPMAP "Ignore if GTSAM_USE_QUATERNIONS is OFF (Rot3::EXPMAP by default). Otherwise, enable Rot3::EXPMAP, or if disabled, use Rot3::CAYLEY." ON)
option(GTSAM_POSE3_EXPMAP "Enable/Disable using Pose3::EXPMAP as the default mode. If disabled, Pose3::FIRST_ORDER will be used." ON)
option(GTSAM_ROT3_EXPMAP "Ignore if GTSAM_USE_QUATERNIONS is OFF (Rot3::EXPMAP by default). Otherwise, enable Rot3::EXPMAP, or if disabled, use Rot3::CAYLEY." ON)
option(GTSAM_ENABLE_CONSISTENCY_CHECKS "Enable/Disable expensive consistency checks" OFF)
option(GTSAM_WITH_TBB "Use Intel Threaded Building Blocks (TBB) if available" ON)
option(GTSAM_WITH_EIGEN_MKL "Eigen will use Intel MKL if available" OFF)
option(GTSAM_WITH_EIGEN_MKL_OPENMP "Eigen, when using Intel MKL, will also use OpenMP for multithreading if available" OFF)
option(GTSAM_THROW_CHEIRALITY_EXCEPTION "Throw exception when a triangulated point is behind a camera" ON)
option(GTSAM_BUILD_PYTHON "Enable/Disable building & installation of Python module with pybind11" OFF)
option(GTSAM_ALLOW_DEPRECATED_SINCE_V41 "Allow use of methods/functions deprecated in GTSAM 4.1" ON)
option(GTSAM_TYPEDEF_POINTS_TO_VECTORS "Typedef Point2 and Point3 to Eigen::Vector equivalents" OFF)
option(GTSAM_SUPPORT_NESTED_DISSECTION "Support Metis-based nested dissection" ON)
@ -99,37 +102,44 @@ 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_INSTALL_CYTHON_TOOLBOX "Enable/Disable installation of Cython toolbox" OFF)
option(GTSAM_BUILD_WRAP "Enable/Disable building of matlab/cython wrap utility (necessary for matlab/cython interface)" ON)
set(GTSAM_PYTHON_VERSION "Default" CACHE STRING "The version of python to build the cython wrapper for (or Default)")
set(GTSAM_PYTHON_VERSION "Default" CACHE STRING "The version of Python to build the wrappers against.")
# Check / set dependent variables for MATLAB wrapper
if((GTSAM_INSTALL_MATLAB_TOOLBOX OR GTSAM_INSTALL_CYTHON_TOOLBOX) AND NOT GTSAM_BUILD_WRAP)
message(FATAL_ERROR "GTSAM_INSTALL_MATLAB_TOOLBOX or GTSAM_INSTALL_CYTHON_TOOLBOX is enabled, please also enable GTSAM_BUILD_WRAP")
endif()
if((GTSAM_INSTALL_MATLAB_TOOLBOX OR GTSAM_INSTALL_CYTHON_TOOLBOX) AND GTSAM_BUILD_TYPE_POSTFIXES)
set(CURRENT_POSTFIX ${CMAKE_${CMAKE_BUILD_TYPE_UPPER}_POSTFIX})
endif()
if(GTSAM_INSTALL_WRAP AND NOT GTSAM_BUILD_WRAP)
message(FATAL_ERROR "GTSAM_INSTALL_WRAP is enabled, please also enable GTSAM_BUILD_WRAP")
if(GTSAM_INSTALL_MATLAB_TOOLBOX AND GTSAM_BUILD_TYPE_POSTFIXES)
set(CURRENT_POSTFIX ${CMAKE_${CMAKE_BUILD_TYPE_UPPER}_POSTFIX})
endif()
if(GTSAM_INSTALL_MATLAB_TOOLBOX AND NOT BUILD_SHARED_LIBS)
message(FATAL_ERROR "GTSAM_INSTALL_MATLAB_TOOLBOX and BUILD_SHARED_LIBS=OFF. The MATLAB wrapper cannot be compiled with a static GTSAM library because mex modules are themselves shared libraries. If you want a self-contained mex module, enable GTSAM_MEX_BUILD_STATIC_MODULE instead of BUILD_SHARED_LIBS=OFF.")
message(FATAL_ERROR "GTSAM_INSTALL_MATLAB_TOOLBOX and BUILD_SHARED_LIBS=OFF. The MATLAB wrapper cannot be compiled with a static GTSAM library because mex modules are themselves shared libraries. If you want a self-contained mex module, enable GTSAM_MEX_BUILD_STATIC_MODULE instead of BUILD_SHARED_LIBS=OFF.")
endif()
if(GTSAM_INSTALL_MATLAB_TOOLBOX AND GTSAM_TYPEDEF_POINTS_TO_VECTORS)
message(FATAL_ERROR "GTSAM_INSTALL_MATLAB_TOOLBOX and GTSAM_TYPEDEF_POINTS_TO_VECTORS are both enabled. For now, the MATLAB toolbox cannot deal with this yet. Please turn one of the two options off.")
endif()
if(GTSAM_BUILD_PYTHON)
if (NOT GTSAM_TYPEDEF_POINTS_TO_VECTORS)
message(FATAL_ERROR "GTSAM_BUILD_PYTHON requires GTSAM_TYPEDEF_POINTS_TO_VECTORS to be enabled but it is not.")
endif()
if(GTSAM_INSTALL_CYTHON_TOOLBOX AND GTSAM_TYPEDEF_POINTS_TO_VECTORS)
message(FATAL_ERROR "GTSAM_INSTALL_CYTHON_TOOLBOX and GTSAM_TYPEDEF_POINTS_TO_VECTORS are both enabled. For now, the CYTHON toolbox cannot deal with this yet. Please turn one of the two options off.")
if(GTSAM_UNSTABLE_BUILD_PYTHON)
if (NOT GTSAM_BUILD_UNSTABLE)
message(WARNING "GTSAM_UNSTABLE_BUILD_PYTHON requires the unstable module to be enabled.")
set(GTSAM_UNSTABLE_BUILD_PYTHON OFF)
endif()
endif()
set(GTSAM_PY_INSTALL_PATH "${CMAKE_INSTALL_PREFIX}/python")
endif()
# Flags for choosing default packaging tools
set(CPACK_SOURCE_GENERATOR "TGZ" CACHE STRING "CPack Default Source Generator")
set(CPACK_GENERATOR "TGZ" CACHE STRING "CPack Default Binary Generator")
if (CMAKE_GENERATOR STREQUAL "Ninja" AND
((CMAKE_CXX_COMPILER_ID STREQUAL "GNU" AND NOT CMAKE_CXX_COMPILER_VERSION VERSION_LESS 4.9) OR
(CMAKE_CXX_COMPILER_ID STREQUAL "Clang" AND NOT CMAKE_CXX_COMPILER_VERSION VERSION_LESS 3.5)))
# Force colored warnings in Ninja's output, if the compiler has -fdiagnostics-color support.
# Rationale in https://github.com/ninja-build/ninja/issues/814
add_compile_options(-fdiagnostics-color=always)
endif()
###############################################################################
# Find boost
@ -138,18 +148,18 @@ set(CPACK_GENERATOR "TGZ" CACHE STRING "CPack Default Binary Generator")
# Boost_NO_SYSTEM_PATHS: set to true to keep the find script from ignoring BOOST_ROOT
if(MSVC)
# By default, boost only builds static libraries on windows
set(Boost_USE_STATIC_LIBS ON) # only find static libs
# If we ever reset above on windows and, ...
# If we use Boost shared libs, disable auto linking.
# Some libraries, at least Boost Program Options, rely on this to export DLL symbols.
if(NOT Boost_USE_STATIC_LIBS)
list_append_cache(GTSAM_COMPILE_DEFINITIONS_PUBLIC BOOST_ALL_NO_LIB BOOST_ALL_DYN_LINK)
endif()
# Virtual memory range for PCH exceeded on VS2015
if(MSVC_VERSION LESS 1910) # older than VS2017
list_append_cache(GTSAM_COMPILE_OPTIONS_PRIVATE -Zm295)
endif()
# By default, boost only builds static libraries on windows
set(Boost_USE_STATIC_LIBS ON) # only find static libs
# If we ever reset above on windows and, ...
# If we use Boost shared libs, disable auto linking.
# Some libraries, at least Boost Program Options, rely on this to export DLL symbols.
if(NOT Boost_USE_STATIC_LIBS)
list_append_cache(GTSAM_COMPILE_DEFINITIONS_PUBLIC BOOST_ALL_NO_LIB BOOST_ALL_DYN_LINK)
endif()
# Virtual memory range for PCH exceeded on VS2015
if(MSVC_VERSION LESS 1910) # older than VS2017
list_append_cache(GTSAM_COMPILE_OPTIONS_PRIVATE -Zm295)
endif()
endif()
# If building DLLs in MSVC, we need to avoid EIGEN_STATIC_ASSERT()
@ -157,7 +167,7 @@ endif()
# See: https://bitbucket.org/gtborg/gtsam/issues/417/fail-to-build-on-msvc-2017
#
if(MSVC AND BUILD_SHARED_LIBS)
list_append_cache(GTSAM_COMPILE_DEFINITIONS_PUBLIC EIGEN_NO_STATIC_ASSERT)
list_append_cache(GTSAM_COMPILE_DEFINITIONS_PUBLIC EIGEN_NO_STATIC_ASSERT)
endif()
# Store these in variables so they are automatically replicated in GTSAMConfig.cmake and such.
@ -227,16 +237,16 @@ find_package(GooglePerfTools)
###############################################################################
# Support ccache, if installed
if(NOT MSVC AND NOT XCODE_VERSION)
find_program(CCACHE_FOUND ccache)
if(CCACHE_FOUND)
if(GTSAM_BUILD_WITH_CCACHE)
set_property(GLOBAL PROPERTY RULE_LAUNCH_COMPILE ccache)
set_property(GLOBAL PROPERTY RULE_LAUNCH_LINK ccache)
else()
set_property(GLOBAL PROPERTY RULE_LAUNCH_COMPILE "")
set_property(GLOBAL PROPERTY RULE_LAUNCH_LINK "")
endif()
endif(CCACHE_FOUND)
find_program(CCACHE_FOUND ccache)
if(CCACHE_FOUND)
if(GTSAM_BUILD_WITH_CCACHE)
set_property(GLOBAL PROPERTY RULE_LAUNCH_COMPILE ccache)
set_property(GLOBAL PROPERTY RULE_LAUNCH_LINK ccache)
else()
set_property(GLOBAL PROPERTY RULE_LAUNCH_COMPILE "")
set_property(GLOBAL PROPERTY RULE_LAUNCH_LINK "")
endif()
endif(CCACHE_FOUND)
endif()
###############################################################################
@ -280,74 +290,74 @@ option(GTSAM_WITH_EIGEN_UNSUPPORTED "Install Eigen's unsupported modules" OFF)
# Switch for using system Eigen or GTSAM-bundled Eigen
if(GTSAM_USE_SYSTEM_EIGEN)
find_package(Eigen3 REQUIRED)
find_package(Eigen3 REQUIRED)
# Use generic Eigen include paths e.g. <Eigen/Core>
set(GTSAM_EIGEN_INCLUDE_FOR_INSTALL "${EIGEN3_INCLUDE_DIR}")
# Use generic Eigen include paths e.g. <Eigen/Core>
set(GTSAM_EIGEN_INCLUDE_FOR_INSTALL "${EIGEN3_INCLUDE_DIR}")
# check if MKL is also enabled - can have one or the other, but not both!
# Note: Eigen >= v3.2.5 includes our patches
if(EIGEN_USE_MKL_ALL AND (EIGEN3_VERSION VERSION_LESS 3.2.5))
message(FATAL_ERROR "MKL requires at least Eigen 3.2.5, and your system appears to have an older version. Disable GTSAM_USE_SYSTEM_EIGEN to use GTSAM's copy of Eigen, or disable GTSAM_WITH_EIGEN_MKL")
endif()
# check if MKL is also enabled - can have one or the other, but not both!
# Note: Eigen >= v3.2.5 includes our patches
if(EIGEN_USE_MKL_ALL AND (EIGEN3_VERSION VERSION_LESS 3.2.5))
message(FATAL_ERROR "MKL requires at least Eigen 3.2.5, and your system appears to have an older version. Disable GTSAM_USE_SYSTEM_EIGEN to use GTSAM's copy of Eigen, or disable GTSAM_WITH_EIGEN_MKL")
endif()
# Check for Eigen version which doesn't work with MKL
# See http://eigen.tuxfamily.org/bz/show_bug.cgi?id=1527 for details.
if(EIGEN_USE_MKL_ALL AND (EIGEN3_VERSION VERSION_EQUAL 3.3.4))
message(FATAL_ERROR "MKL does not work with Eigen 3.3.4 because of a bug in Eigen. See http://eigen.tuxfamily.org/bz/show_bug.cgi?id=1527. Disable GTSAM_USE_SYSTEM_EIGEN to use GTSAM's copy of Eigen, disable GTSAM_WITH_EIGEN_MKL, or upgrade/patch your installation of Eigen.")
endif()
# Check for Eigen version which doesn't work with MKL
# See http://eigen.tuxfamily.org/bz/show_bug.cgi?id=1527 for details.
if(EIGEN_USE_MKL_ALL AND (EIGEN3_VERSION VERSION_EQUAL 3.3.4))
message(FATAL_ERROR "MKL does not work with Eigen 3.3.4 because of a bug in Eigen. See http://eigen.tuxfamily.org/bz/show_bug.cgi?id=1527. Disable GTSAM_USE_SYSTEM_EIGEN to use GTSAM's copy of Eigen, disable GTSAM_WITH_EIGEN_MKL, or upgrade/patch your installation of Eigen.")
endif()
# The actual include directory (for BUILD cmake target interface):
set(GTSAM_EIGEN_INCLUDE_FOR_BUILD "${EIGEN3_INCLUDE_DIR}")
# The actual include directory (for BUILD cmake target interface):
set(GTSAM_EIGEN_INCLUDE_FOR_BUILD "${EIGEN3_INCLUDE_DIR}")
else()
# Use bundled Eigen include path.
# Clear any variables set by FindEigen3
if(EIGEN3_INCLUDE_DIR)
set(EIGEN3_INCLUDE_DIR NOTFOUND CACHE STRING "" FORCE)
endif()
# Use bundled Eigen include path.
# Clear any variables set by FindEigen3
if(EIGEN3_INCLUDE_DIR)
set(EIGEN3_INCLUDE_DIR NOTFOUND CACHE STRING "" FORCE)
endif()
# set full path to be used by external projects
# this will be added to GTSAM_INCLUDE_DIR by gtsam_extra.cmake.in
set(GTSAM_EIGEN_INCLUDE_FOR_INSTALL "include/gtsam/3rdparty/Eigen/")
# set full path to be used by external projects
# this will be added to GTSAM_INCLUDE_DIR by gtsam_extra.cmake.in
set(GTSAM_EIGEN_INCLUDE_FOR_INSTALL "include/gtsam/3rdparty/Eigen/")
# The actual include directory (for BUILD cmake target interface):
set(GTSAM_EIGEN_INCLUDE_FOR_BUILD "${CMAKE_SOURCE_DIR}/gtsam/3rdparty/Eigen/")
# The actual include directory (for BUILD cmake target interface):
set(GTSAM_EIGEN_INCLUDE_FOR_BUILD "${CMAKE_SOURCE_DIR}/gtsam/3rdparty/Eigen/")
endif()
# Detect Eigen version:
set(EIGEN_VER_H "${GTSAM_EIGEN_INCLUDE_FOR_BUILD}/Eigen/src/Core/util/Macros.h")
if (EXISTS ${EIGEN_VER_H})
file(READ "${EIGEN_VER_H}" STR_EIGEN_VERSION)
file(READ "${EIGEN_VER_H}" STR_EIGEN_VERSION)
# Extract the Eigen version from the Macros.h file, lines "#define EIGEN_WORLD_VERSION XX", etc...
# Extract the Eigen version from the Macros.h file, lines "#define EIGEN_WORLD_VERSION XX", etc...
string(REGEX MATCH "EIGEN_WORLD_VERSION[ ]+[0-9]+" GTSAM_EIGEN_VERSION_WORLD "${STR_EIGEN_VERSION}")
string(REGEX MATCH "[0-9]+" GTSAM_EIGEN_VERSION_WORLD "${GTSAM_EIGEN_VERSION_WORLD}")
string(REGEX MATCH "EIGEN_WORLD_VERSION[ ]+[0-9]+" GTSAM_EIGEN_VERSION_WORLD "${STR_EIGEN_VERSION}")
string(REGEX MATCH "[0-9]+" GTSAM_EIGEN_VERSION_WORLD "${GTSAM_EIGEN_VERSION_WORLD}")
string(REGEX MATCH "EIGEN_MAJOR_VERSION[ ]+[0-9]+" GTSAM_EIGEN_VERSION_MAJOR "${STR_EIGEN_VERSION}")
string(REGEX MATCH "[0-9]+" GTSAM_EIGEN_VERSION_MAJOR "${GTSAM_EIGEN_VERSION_MAJOR}")
string(REGEX MATCH "EIGEN_MAJOR_VERSION[ ]+[0-9]+" GTSAM_EIGEN_VERSION_MAJOR "${STR_EIGEN_VERSION}")
string(REGEX MATCH "[0-9]+" GTSAM_EIGEN_VERSION_MAJOR "${GTSAM_EIGEN_VERSION_MAJOR}")
string(REGEX MATCH "EIGEN_MINOR_VERSION[ ]+[0-9]+" GTSAM_EIGEN_VERSION_MINOR "${STR_EIGEN_VERSION}")
string(REGEX MATCH "[0-9]+" GTSAM_EIGEN_VERSION_MINOR "${GTSAM_EIGEN_VERSION_MINOR}")
string(REGEX MATCH "EIGEN_MINOR_VERSION[ ]+[0-9]+" GTSAM_EIGEN_VERSION_MINOR "${STR_EIGEN_VERSION}")
string(REGEX MATCH "[0-9]+" GTSAM_EIGEN_VERSION_MINOR "${GTSAM_EIGEN_VERSION_MINOR}")
set(GTSAM_EIGEN_VERSION "${GTSAM_EIGEN_VERSION_WORLD}.${GTSAM_EIGEN_VERSION_MAJOR}.${GTSAM_EIGEN_VERSION_MINOR}")
set(GTSAM_EIGEN_VERSION "${GTSAM_EIGEN_VERSION_WORLD}.${GTSAM_EIGEN_VERSION_MAJOR}.${GTSAM_EIGEN_VERSION_MINOR}")
message(STATUS "Found Eigen version: ${GTSAM_EIGEN_VERSION}")
message(STATUS "Found Eigen version: ${GTSAM_EIGEN_VERSION}")
else()
message(WARNING "Cannot determine Eigen version, missing file: `${EIGEN_VER_H}`")
message(WARNING "Cannot determine Eigen version, missing file: `${EIGEN_VER_H}`")
endif ()
if (MSVC)
if (BUILD_SHARED_LIBS)
# mute eigen static assert to avoid errors in shared lib
list_append_cache(GTSAM_COMPILE_DEFINITIONS_PUBLIC EIGEN_NO_STATIC_ASSERT)
endif()
list_append_cache(GTSAM_COMPILE_OPTIONS_PRIVATE "/wd4244") # Disable loss of precision which is thrown all over our Eigen
if (BUILD_SHARED_LIBS)
# mute eigen static assert to avoid errors in shared lib
list_append_cache(GTSAM_COMPILE_DEFINITIONS_PUBLIC EIGEN_NO_STATIC_ASSERT)
endif()
list_append_cache(GTSAM_COMPILE_OPTIONS_PRIVATE "/wd4244") # Disable loss of precision which is thrown all over our Eigen
endif()
if (APPLE AND BUILD_SHARED_LIBS)
# Set the default install directory on macOS
set(CMAKE_INSTALL_NAME_DIR "${CMAKE_INSTALL_PREFIX}/lib")
# Set the default install directory on macOS
set(CMAKE_INSTALL_NAME_DIR "${CMAKE_INSTALL_PREFIX}/lib")
endif()
###############################################################################
@ -356,42 +366,42 @@ endif()
# Build list of possible allocators
set(possible_allocators "")
if(GTSAM_USE_TBB)
list(APPEND possible_allocators TBB)
set(preferred_allocator TBB)
list(APPEND possible_allocators TBB)
set(preferred_allocator TBB)
else()
list(APPEND possible_allocators BoostPool STL)
set(preferred_allocator STL)
list(APPEND possible_allocators BoostPool STL)
set(preferred_allocator STL)
endif()
if(GOOGLE_PERFTOOLS_FOUND)
list(APPEND possible_allocators tcmalloc)
list(APPEND possible_allocators tcmalloc)
endif()
# Check if current allocator choice is valid and set cache option
list(FIND possible_allocators "${GTSAM_DEFAULT_ALLOCATOR}" allocator_valid)
if(allocator_valid EQUAL -1)
set(GTSAM_DEFAULT_ALLOCATOR ${preferred_allocator} CACHE STRING "Default allocator" FORCE)
set(GTSAM_DEFAULT_ALLOCATOR ${preferred_allocator} CACHE STRING "Default allocator" FORCE)
else()
set(GTSAM_DEFAULT_ALLOCATOR ${preferred_allocator} CACHE STRING "Default allocator")
set(GTSAM_DEFAULT_ALLOCATOR ${preferred_allocator} CACHE STRING "Default allocator")
endif()
set_property(CACHE GTSAM_DEFAULT_ALLOCATOR PROPERTY STRINGS ${possible_allocators})
mark_as_advanced(GTSAM_DEFAULT_ALLOCATOR)
# Define compile flags depending on allocator
if("${GTSAM_DEFAULT_ALLOCATOR}" STREQUAL "BoostPool")
set(GTSAM_ALLOCATOR_BOOSTPOOL 1)
set(GTSAM_ALLOCATOR_BOOSTPOOL 1)
elseif("${GTSAM_DEFAULT_ALLOCATOR}" STREQUAL "STL")
set(GTSAM_ALLOCATOR_STL 1)
set(GTSAM_ALLOCATOR_STL 1)
elseif("${GTSAM_DEFAULT_ALLOCATOR}" STREQUAL "TBB")
set(GTSAM_ALLOCATOR_TBB 1)
set(GTSAM_ALLOCATOR_TBB 1)
elseif("${GTSAM_DEFAULT_ALLOCATOR}" STREQUAL "tcmalloc")
set(GTSAM_ALLOCATOR_STL 1) # tcmalloc replaces malloc, so to use it we use the STL allocator
list(APPEND GTSAM_ADDITIONAL_LIBRARIES "tcmalloc")
set(GTSAM_ALLOCATOR_STL 1) # tcmalloc replaces malloc, so to use it we use the STL allocator
list(APPEND GTSAM_ADDITIONAL_LIBRARIES "tcmalloc")
endif()
if(MSVC)
list_append_cache(GTSAM_COMPILE_DEFINITIONS_PRIVATE _CRT_SECURE_NO_WARNINGS _SCL_SECURE_NO_WARNINGS)
list_append_cache(GTSAM_COMPILE_OPTIONS_PRIVATE /wd4251 /wd4275 /wd4251 /wd4661 /wd4344 /wd4503) # Disable non-DLL-exported base class and other warnings
list_append_cache(GTSAM_COMPILE_OPTIONS_PRIVATE /bigobj) # Allow large object files for template-based code
list_append_cache(GTSAM_COMPILE_DEFINITIONS_PRIVATE _CRT_SECURE_NO_WARNINGS _SCL_SECURE_NO_WARNINGS)
list_append_cache(GTSAM_COMPILE_OPTIONS_PRIVATE /wd4251 /wd4275 /wd4251 /wd4661 /wd4344 /wd4503) # Disable non-DLL-exported base class and other warnings
list_append_cache(GTSAM_COMPILE_OPTIONS_PRIVATE /bigobj) # Allow large object files for template-based code
endif()
# GCC 4.8+ complains about local typedefs which we use for shared_ptr etc.
@ -419,14 +429,11 @@ endif()
# Build CppUnitLite
add_subdirectory(CppUnitLite)
# Build wrap
if (GTSAM_BUILD_WRAP)
add_subdirectory(wrap)
# suppress warning of cython line being too long
if(CMAKE_CXX_COMPILER_ID STREQUAL "GNU")
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -Wno-misleading-indentation")
endif()
endif(GTSAM_BUILD_WRAP)
# This is the new wrapper
if(GTSAM_BUILD_PYTHON)
list(APPEND CMAKE_MODULE_PATH "${CMAKE_CURRENT_LIST_DIR}/wrap/cmake")
add_subdirectory(python)
endif()
# Build GTSAM library
add_subdirectory(gtsam)
@ -447,23 +454,9 @@ endif()
# Matlab toolbox
if (GTSAM_INSTALL_MATLAB_TOOLBOX)
add_subdirectory(matlab)
add_subdirectory(matlab)
endif()
# Cython wrap
if (GTSAM_INSTALL_CYTHON_TOOLBOX)
set(GTSAM_INSTALL_CYTHON_TOOLBOX 1)
# Set up cache options
# Cython install path appended with Build type (e.g. cython, cythonDebug, etc).
# This does not override custom values set from the command line
set(GTSAM_CYTHON_INSTALL_PATH "${PROJECT_BINARY_DIR}/cython${GTSAM_BUILD_TAG}" CACHE PATH "Cython toolbox destination, blank defaults to PROJECT_BINARY_DIR/cython<GTSAM_BUILD_TAG>")
set(GTSAM_EIGENCY_INSTALL_PATH ${GTSAM_CYTHON_INSTALL_PATH}/gtsam_eigency)
add_subdirectory(cython ${GTSAM_CYTHON_INSTALL_PATH})
else()
set(GTSAM_INSTALL_CYTHON_TOOLBOX 0) # This will go into config.h
endif()
# Install config and export files
GtsamMakeConfigFile(GTSAM "${CMAKE_CURRENT_SOURCE_DIR}/gtsam_extra.cmake.in")
export(TARGETS ${GTSAM_EXPORTED_TARGETS} FILE GTSAM-exports.cmake)
@ -524,7 +517,9 @@ endif()
print_enabled_config(${BUILD_SHARED_LIBS} "Build shared GTSAM libraries")
print_enabled_config(${GTSAM_BUILD_TYPE_POSTFIXES} "Put build type in library name")
if(GTSAM_UNSTABLE_AVAILABLE)
print_enabled_config(${GTSAM_BUILD_UNSTABLE} "Build libgtsam_unstable")
print_enabled_config(${GTSAM_BUILD_UNSTABLE} "Build libgtsam_unstable ")
print_enabled_config(${GTSAM_UNSTABLE_BUILD_PYTHON} "Build GTSAM unstable Python ")
print_enabled_config(${GTSAM_UNSTABLE_INSTALL_MATLAB_TOOLBOX} "Build MATLAB Toolbox for unstable")
endif()
if(NOT MSVC AND NOT XCODE_VERSION)
@ -572,13 +567,13 @@ else()
endif()
if(NOT MSVC AND NOT XCODE_VERSION)
if(CCACHE_FOUND AND GTSAM_BUILD_WITH_CCACHE)
if(CCACHE_FOUND AND GTSAM_BUILD_WITH_CCACHE)
print_config("Build with ccache" "Yes")
elseif(CCACHE_FOUND)
elseif(CCACHE_FOUND)
print_config("Build with ccache" "ccache found but GTSAM_BUILD_WITH_CCACHE is disabled")
else()
else()
print_config("Build with ccache" "No")
endif()
endif()
endif()
message(STATUS "Packaging flags")
@ -594,7 +589,6 @@ print_enabled_config(${GTSAM_ALLOW_DEPRECATED_SINCE_V41} "Allow features deprec
print_enabled_config(${GTSAM_TYPEDEF_POINTS_TO_VECTORS} "Point3 is typedef to Vector3 ")
print_enabled_config(${GTSAM_SUPPORT_NESTED_DISSECTION} "Metis-based Nested Dissection ")
print_enabled_config(${GTSAM_TANGENT_PREINTEGRATION} "Use tangent-space preintegration")
print_enabled_config(${GTSAM_BUILD_WRAP} "Build Wrap ")
message(STATUS "MATLAB toolbox flags")
print_enabled_config(${GTSAM_INSTALL_MATLAB_TOOLBOX} "Install MATLAB toolbox ")
@ -602,23 +596,23 @@ if (${GTSAM_INSTALL_MATLAB_TOOLBOX})
print_config("MATLAB root" "${MATLAB_ROOT}")
print_config("MEX binary" "${MEX_COMMAND}")
endif()
message(STATUS "Cython toolbox flags ")
print_enabled_config(${GTSAM_INSTALL_CYTHON_TOOLBOX} "Install Cython toolbox ")
if(GTSAM_INSTALL_CYTHON_TOOLBOX)
print_config("Python version" "${GTSAM_PYTHON_VERSION}")
message(STATUS "Python toolbox flags ")
print_enabled_config(${GTSAM_BUILD_PYTHON} "Build Python module with pybind ")
if(GTSAM_BUILD_PYTHON)
print_config("Python version" ${GTSAM_PYTHON_VERSION})
endif()
message(STATUS "===============================================================")
# Print warnings at the end
if(GTSAM_WITH_TBB AND NOT TBB_FOUND)
message(WARNING "TBB 4.4 or newer was not found - this is ok, but note that GTSAM parallelization will be disabled. Set GTSAM_WITH_TBB to 'Off' to avoid this warning.")
message(WARNING "TBB 4.4 or newer was not found - this is ok, but note that GTSAM parallelization will be disabled. Set GTSAM_WITH_TBB to 'Off' to avoid this warning.")
endif()
if(GTSAM_WITH_EIGEN_MKL AND NOT MKL_FOUND)
message(WARNING "MKL was not found - this is ok, but note that MKL will be disabled. Set GTSAM_WITH_EIGEN_MKL to 'Off' to disable this warning. See INSTALL.md for notes on performance.")
message(WARNING "MKL was not found - this is ok, but note that MKL will be disabled. Set GTSAM_WITH_EIGEN_MKL to 'Off' to disable this warning. See INSTALL.md for notes on performance.")
endif()
if(GTSAM_WITH_EIGEN_MKL_OPENMP AND NOT OPENMP_FOUND AND MKL_FOUND)
message(WARNING "Your compiler does not support OpenMP. Set GTSAM_WITH_EIGEN_MKL_OPENMP to 'Off' to avoid this warning. See INSTALL.md for notes on performance.")
message(WARNING "Your compiler does not support OpenMP. Set GTSAM_WITH_EIGEN_MKL_OPENMP to 'Off' to avoid this warning. See INSTALL.md for notes on performance.")
endif()
# Include CPack *after* all flags

2
cmake/CMakeLists.txt
View File

@ -17,8 +17,6 @@ install(FILES
GtsamBuildTypes.cmake
GtsamMakeConfigFile.cmake
GtsamMatlabWrap.cmake
GtsamPythonWrap.cmake
GtsamCythonWrap.cmake
GtsamTesting.cmake
GtsamPrinting.cmake
FindCython.cmake

204
cmake/GtsamCythonWrap.cmake
View File

@ -1,204 +0,0 @@
# Check Cython version, need to be >=0.25.2
# Unset these cached variables to avoid surprises when the python/cython
# in the current environment are different from the cached!
unset(PYTHON_EXECUTABLE CACHE)
unset(CYTHON_EXECUTABLE CACHE)
unset(PYTHON_INCLUDE_DIR CACHE)
unset(PYTHON_MAJOR_VERSION CACHE)
unset(PYTHON_LIBRARY CACHE)
# Allow override from command line
if(NOT DEFINED GTSAM_USE_CUSTOM_PYTHON_LIBRARY)
if(GTSAM_PYTHON_VERSION STREQUAL "Default")
find_package(PythonInterp REQUIRED)
find_package(PythonLibs REQUIRED)
else()
find_package(PythonInterp ${GTSAM_PYTHON_VERSION} EXACT REQUIRED)
find_package(PythonLibs ${GTSAM_PYTHON_VERSION} EXACT REQUIRED)
endif()
endif()
find_package(Cython 0.25.2 REQUIRED)
execute_process(COMMAND "${PYTHON_EXECUTABLE}" "-c"
"from __future__ import print_function;import sys;print(sys.version[0], end='')"
OUTPUT_VARIABLE PYTHON_MAJOR_VERSION
)
# User-friendly Cython wrapping and installing function.
# Builds a Cython module from the provided interface_header.
# For example, for the interface header gtsam.h,
# this will build the wrap module 'gtsam'.
#
# Arguments:
#
# interface_header: The relative path to the wrapper interface definition file.
# extra_imports: extra header to import in the Cython pxd file.
# For example, to use Cython gtsam.pxd in your own module,
# use "from gtsam cimport *"
# install_path: destination to install the library
# libs: libraries to link with
# dependencies: Dependencies which need to be built before the wrapper
function(wrap_and_install_library_cython interface_header extra_imports install_path libs dependencies)
# Paths for generated files
get_filename_component(module_name "${interface_header}" NAME_WE)
set(generated_files_path "${install_path}")
wrap_library_cython("${interface_header}" "${generated_files_path}" "${extra_imports}" "${libs}" "${dependencies}")
endfunction()
function(set_up_required_cython_packages)
# Set up building of cython module
include_directories(${PYTHON_INCLUDE_DIRS})
find_package(NumPy REQUIRED)
include_directories(${NUMPY_INCLUDE_DIRS})
endfunction()
# Convert pyx to cpp by executing cython
# This is the first step to compile cython from the command line
# as described at: http://cython.readthedocs.io/en/latest/src/reference/compilation.html
#
# Arguments:
# - target: The specified target for this step
# - pyx_file: The input pyx_file in full *absolute* path
# - generated_cpp: The output cpp file in full absolute path
# - include_dirs: Directories to include when executing cython
function(pyx_to_cpp target pyx_file generated_cpp include_dirs)
foreach(dir ${include_dirs})
set(includes_for_cython ${includes_for_cython} -I ${dir})
endforeach()
add_custom_command(
OUTPUT ${generated_cpp}
COMMAND
${CYTHON_EXECUTABLE} -X boundscheck=False -v --fast-fail --cplus -${PYTHON_MAJOR_VERSION} ${includes_for_cython} ${pyx_file} -o ${generated_cpp}
VERBATIM)
add_custom_target(${target} ALL DEPENDS ${generated_cpp})
endfunction()
# Build the cpp file generated by converting pyx using cython
# This is the second step to compile cython from the command line
# as described at: http://cython.readthedocs.io/en/latest/src/reference/compilation.html
#
# Arguments:
# - target: The specified target for this step
# - cpp_file: The input cpp_file in full *absolute* path
# - output_lib_we: The output lib filename only (without extension)
# - output_dir: The output directory
function(build_cythonized_cpp target cpp_file output_lib_we output_dir)
add_library(${target} MODULE ${cpp_file})
if(WIN32)
# Use .pyd extension instead of .dll on Windows
set_target_properties(${target} PROPERTIES SUFFIX ".pyd")
# Add full path to the Python library
target_link_libraries(${target} ${PYTHON_LIBRARIES})
endif()
if(APPLE)
set(link_flags "-undefined dynamic_lookup")
endif()
set_target_properties(${target}
PROPERTIES COMPILE_FLAGS "-w"
LINK_FLAGS "${link_flags}"
OUTPUT_NAME ${output_lib_we}
PREFIX ""
${CMAKE_BUILD_TYPE_UPPER}_POSTFIX ""
LIBRARY_OUTPUT_DIRECTORY ${output_dir})
endfunction()
# Cythonize a pyx from the command line as described at
# http://cython.readthedocs.io/en/latest/src/reference/compilation.html
# Arguments:
# - target: The specified target
# - pyx_file: The input pyx_file in full *absolute* path
# - output_lib_we: The output lib filename only (without extension)
# - output_dir: The output directory
# - include_dirs: Directories to include when executing cython
# - libs: Libraries to link with
# - interface_header: For dependency. Any update in interface header will re-trigger cythonize
function(cythonize target pyx_file output_lib_we output_dir include_dirs libs interface_header dependencies)
get_filename_component(pyx_path "${pyx_file}" DIRECTORY)
get_filename_component(pyx_name "${pyx_file}" NAME_WE)
set(generated_cpp "${output_dir}/${pyx_name}.cpp")
set_up_required_cython_packages()
pyx_to_cpp(${target}_pyx2cpp ${pyx_file} ${generated_cpp} "${include_dirs}")
# Late dependency injection, to make sure this gets called whenever the interface header is updated
# See: https://stackoverflow.com/questions/40032593/cmake-does-not-rebuild-dependent-after-prerequisite-changes
add_custom_command(OUTPUT ${generated_cpp} DEPENDS ${interface_header} ${pyx_file} APPEND)
if (NOT "${dependencies}" STREQUAL "")
add_dependencies(${target}_pyx2cpp "${dependencies}")
endif()
build_cythonized_cpp(${target} ${generated_cpp} ${output_lib_we} ${output_dir})
if (NOT "${libs}" STREQUAL "")
target_link_libraries(${target} "${libs}")
endif()
add_dependencies(${target} ${target}_pyx2cpp)
if(TARGET ${python_install_target})
add_dependencies(${python_install_target} ${target})
endif()
endfunction()
# Internal function that wraps a library and compiles the wrapper
function(wrap_library_cython interface_header generated_files_path extra_imports libs dependencies)
# Wrap codegen interface
# Extract module path and name from interface header file name
# wrap requires interfacePath to be *absolute*
get_filename_component(interface_header "${interface_header}" ABSOLUTE)
get_filename_component(module_path "${interface_header}" PATH)
get_filename_component(module_name "${interface_header}" NAME_WE)
# Wrap module to Cython pyx
message(STATUS "Cython wrapper generating ${generated_files_path}/${module_name}.pyx")
set(generated_pyx "${generated_files_path}/${module_name}.pyx")
if(NOT EXISTS ${generated_files_path})
file(MAKE_DIRECTORY "${generated_files_path}")
endif()
add_custom_command(
OUTPUT ${generated_pyx}
DEPENDS ${interface_header} wrap
COMMAND
wrap --cython ${module_path} ${module_name} ${generated_files_path} "${extra_imports}"
VERBATIM
WORKING_DIRECTORY ${generated_files_path}/../)
add_custom_target(cython_wrap_${module_name}_pyx ALL DEPENDS ${generated_pyx})
if(NOT "${dependencies}" STREQUAL "")
add_dependencies(cython_wrap_${module_name}_pyx ${dependencies})
endif()
message(STATUS "Cythonize and build ${module_name}.pyx")
get_property(include_dirs DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR} PROPERTY INCLUDE_DIRECTORIES)
cythonize(cythonize_${module_name} ${generated_pyx} ${module_name}
${generated_files_path} "${include_dirs}" "${libs}" ${interface_header} cython_wrap_${module_name}_pyx)
# distclean
add_custom_target(wrap_${module_name}_cython_distclean
COMMAND cmake -E remove_directory ${generated_files_path})
endfunction()
# Helper function to install Cython scripts and handle multiple build types where the scripts
# should be installed to all build type toolboxes
#
# Arguments:
# source_directory: The source directory to be installed. "The last component of each directory
# name is appended to the destination directory but a trailing slash may be
# used to avoid this because it leaves the last component empty."
# (https://cmake.org/cmake/help/v3.3/command/install.html?highlight=install#installing-directories)
# dest_directory: The destination directory to install to.
# patterns: list of file patterns to install
function(install_cython_scripts source_directory dest_directory patterns)
set(patterns_args "")
set(exclude_patterns "")
foreach(pattern ${patterns})
list(APPEND patterns_args PATTERN "${pattern}")
endforeach()
file(COPY "${source_directory}" DESTINATION "${dest_directory}"
FILES_MATCHING ${patterns_args} PATTERN "${exclude_patterns}" EXCLUDE)
endfunction()

38
cmake/GtsamMatlabWrap.cmake
View File

@ -23,6 +23,11 @@ else()
file(GLOB matlab_bin_directories "/usr/local/MATLAB/*/bin")
set(mex_program_name "mex")
endif()
if(GTSAM_CUSTOM_MATLAB_PATH)
set(matlab_bin_directories ${GTSAM_CUSTOM_MATLAB_PATH})
endif()
# Run find_program explicitly putting $PATH after our predefined program
# directories using 'ENV PATH' and 'NO_SYSTEM_ENVIRONMENT_PATH' - this prevents
# finding the LaTeX mex program (totally unrelated to MATLAB Mex) when LaTeX is
@ -209,15 +214,34 @@ function(wrap_library_internal interfaceHeader linkLibraries extraIncludeDirs ex
# Set up generation of module source file
file(MAKE_DIRECTORY "${generated_files_path}")
if(GTSAM_PYTHON_VERSION STREQUAL "Default")
find_package(PythonInterp REQUIRED)
find_package(PythonLibs REQUIRED)
else()
find_package(PythonInterp
${GTSAM_PYTHON_VERSION}
EXACT
REQUIRED)
find_package(PythonLibs
${GTSAM_PYTHON_VERSION}
EXACT
REQUIRED)
endif()
set(_ignore gtsam::Point2
gtsam::Point3)
add_custom_command(
OUTPUT ${generated_cpp_file}
DEPENDS ${interfaceHeader} wrap ${module_library_target} ${otherLibraryTargets} ${otherSourcesAndObjects}
COMMAND
wrap --matlab
${modulePath}
${moduleName}
${generated_files_path}
${matlab_h_path}
DEPENDS ${interfaceHeader} ${module_library_target} ${otherLibraryTargets} ${otherSourcesAndObjects}
COMMAND
${PYTHON_EXECUTABLE}
${CMAKE_SOURCE_DIR}/wrap/matlab_wrapper.py
--src ${interfaceHeader}
--module_name ${moduleName}
--out ${generated_files_path}
--top_module_namespaces ${moduleName}
--ignore ${_ignore}
VERBATIM
WORKING_DIRECTORY ${generated_files_path})

102
cmake/GtsamPythonWrap.cmake
View File

@ -1,102 +0,0 @@
#Setup cache options
set(GTSAM_PYTHON_VERSION "Default" CACHE STRING "Target python version for GTSAM python module. Use 'Default' to chose the default version")
set(GTSAM_BUILD_PYTHON_FLAGS "" CACHE STRING "Extra flags for running Matlab PYTHON compilation")
set(GTSAM_PYTHON_INSTALL_PATH "" CACHE PATH "Python toolbox destination, blank defaults to CMAKE_INSTALL_PREFIX/borg/python")
if(NOT GTSAM_PYTHON_INSTALL_PATH)
set(GTSAM_PYTHON_INSTALL_PATH "${CMAKE_INSTALL_PREFIX}/borg/python")
endif()
#Author: Paul Furgale Modified by Andrew Melim
function(wrap_python TARGET_NAME PYTHON_MODULE_DIRECTORY)
# # Boost
# find_package(Boost COMPONENTS python filesystem system REQUIRED)
# include_directories(${Boost_INCLUDE_DIRS})
# # Find Python
# FIND_PACKAGE(PythonLibs 2.7 REQUIRED)
# INCLUDE_DIRECTORIES(${PYTHON_INCLUDE_DIRS})
IF(APPLE)
# The apple framework headers don't include the numpy headers for some reason.
GET_FILENAME_COMPONENT(REAL_PYTHON_INCLUDE ${PYTHON_INCLUDE_DIRS} REALPATH)
IF( ${REAL_PYTHON_INCLUDE} MATCHES Python.framework)
message("Trying to find extra headers for numpy from ${REAL_PYTHON_INCLUDE}.")
message("Looking in ${REAL_PYTHON_INCLUDE}/../../Extras/lib/python/numpy/core/include/numpy")
FIND_PATH(NUMPY_INCLUDE_DIR arrayobject.h
${REAL_PYTHON_INCLUDE}/../../Extras/lib/python/numpy/core/include/numpy
${REAL_PYTHON_INCLUDE}/numpy
)
IF(${NUMPY_INCLUDE_DIR} MATCHES NOTFOUND)
message("Unable to find numpy include directories: ${NUMPY_INCLUDE_DIR}")
ELSE()
message("Found headers at ${NUMPY_INCLUDE_DIR}")
INCLUDE_DIRECTORIES(${NUMPY_INCLUDE_DIR})
INCLUDE_DIRECTORIES(${NUMPY_INCLUDE_DIR}/..)
ENDIF()
ENDIF()
ENDIF(APPLE)
if(MSVC)
add_library(${moduleName}_python MODULE ${ARGN})
set_target_properties(${moduleName}_python PROPERTIES
OUTPUT_NAME ${moduleName}_python
CLEAN_DIRECT_OUTPUT 1
VERSION 1
SOVERSION 0
SUFFIX ".pyd")
target_link_libraries(${moduleName}_python ${Boost_PYTHON_LIBRARY} ${PYTHON_LIBRARY} ${gtsamLib}) #temp
set(PYLIB_OUTPUT_FILE $<TARGET_FILE:${moduleName}_python>)
message(${PYLIB_OUTPUT_FILE})
get_filename_component(PYLIB_OUTPUT_NAME ${PYLIB_OUTPUT_FILE} NAME_WE)
set(PYLIB_SO_NAME ${PYLIB_OUTPUT_NAME}.pyd)
ELSE()
# Create a shared library
add_library(${moduleName}_python SHARED ${generated_cpp_file})
set_target_properties(${moduleName}_python PROPERTIES
OUTPUT_NAME ${moduleName}_python
CLEAN_DIRECT_OUTPUT 1)
target_link_libraries(${moduleName}_python ${Boost_PYTHON_LIBRARY} ${PYTHON_LIBRARY} ${gtsamLib}) #temp
# On OSX and Linux, the python library must end in the extension .so. Build this
# filename here.
get_property(PYLIB_OUTPUT_FILE TARGET ${moduleName}_python PROPERTY LOCATION)
set(PYLIB_OUTPUT_FILE $<TARGET_FILE:${moduleName}_python>)
message(${PYLIB_OUTPUT_FILE})
get_filename_component(PYLIB_OUTPUT_NAME ${PYLIB_OUTPUT_FILE} NAME_WE)
set(PYLIB_SO_NAME lib${moduleName}_python.so)
ENDIF(MSVC)
# Installs the library in the gtsam folder, which is used by setup.py to create the gtsam package
set(PYTHON_MODULE_DIRECTORY ${CMAKE_SOURCE_DIR}/python/gtsam)
# Cause the library to be output in the correct directory.
add_custom_command(TARGET ${moduleName}_python
POST_BUILD
COMMAND cp -v ${PYLIB_OUTPUT_FILE} ${PYTHON_MODULE_DIRECTORY}/${PYLIB_SO_NAME}
WORKING_DIRECTORY ${PROJECT_SOURCE_DIR}
COMMENT "Copying library files to python directory" )
# Cause the library to be output in the correct directory.
add_custom_command(TARGET ${TARGET_NAME}
POST_BUILD
COMMAND cp -v ${PYLIB_OUTPUT_FILE} ${PYTHON_MODULE_DIRECTORY}/${PYLIB_SO_NAME}
WORKING_DIRECTORY ${PROJECT_SOURCE_DIR}
COMMENT "Copying library files to python directory" )
get_directory_property(AMCF ADDITIONAL_MAKE_CLEAN_FILES)
list(APPEND AMCF ${PYTHON_MODULE_DIRECTORY}/${PYLIB_SO_NAME})
set_directory_properties(PROPERTIES ADDITIONAL_MAKE_CLEAN_FILES "${AMCF}")
endfunction(wrap_python)
# Macro to get list of subdirectories
macro(SUBDIRLIST result curdir)
file(GLOB children RELATIVE ${curdir} ${curdir}/*)
set(dirlist "")
foreach(child ${children})
if(IS_DIRECTORY ${curdir}/${child})
list(APPEND dirlist ${child})
endif()
endforeach()
set(${result} ${dirlist})
endmacro()

5
cmake/dllexport.h.in
View File

@ -47,9 +47,14 @@
# endif
# endif
#else
#ifdef __APPLE__
# define @library_name@_EXPORT __attribute__((visibility("default")))
# define @library_name@_EXTERN_EXPORT extern
#else
# define @library_name@_EXPORT
# define @library_name@_EXTERN_EXPORT extern
#endif
#endif
#undef BUILD_SHARED_LIBS

57
cython/CMakeLists.txt
View File

@ -1,57 +0,0 @@
# Install cython components
include(GtsamCythonWrap)
# Create the cython toolbox for the gtsam library
if (GTSAM_INSTALL_CYTHON_TOOLBOX)
# Add the new make target command
set(python_install_target python-install)
add_custom_target(${python_install_target}
COMMAND ${PYTHON_EXECUTABLE} ${GTSAM_CYTHON_INSTALL_PATH}/setup.py install
WORKING_DIRECTORY ${GTSAM_CYTHON_INSTALL_PATH})
# build and include the eigency version of eigency
add_subdirectory(gtsam_eigency)
include_directories(${GTSAM_EIGENCY_INSTALL_PATH})
# Fix for error "C1128: number of sections exceeded object file format limit"
if(MSVC)
add_compile_options(/bigobj)
endif()
# First set up all the package related files.
# This also ensures the below wrap operations work correctly.
set(CYTHON_INSTALL_REQUIREMENTS_FILE "${PROJECT_SOURCE_DIR}/cython/requirements.txt")
# Install the custom-generated __init__.py
# This makes the cython (sub-)directories into python packages, so gtsam can be found while wrapping gtsam_unstable
configure_file(${PROJECT_SOURCE_DIR}/cython/gtsam/__init__.py ${GTSAM_CYTHON_INSTALL_PATH}/gtsam/__init__.py COPYONLY)
configure_file(${PROJECT_SOURCE_DIR}/cython/gtsam_unstable/__init__.py ${GTSAM_CYTHON_INSTALL_PATH}/gtsam_unstable/__init__.py COPYONLY)
configure_file(${PROJECT_SOURCE_DIR}/cython/setup.py.in ${GTSAM_CYTHON_INSTALL_PATH}/setup.py)
# Wrap gtsam
add_custom_target(gtsam_header DEPENDS "../gtsam.h")
wrap_and_install_library_cython("../gtsam.h" # interface_header
"" # extra imports
"${GTSAM_CYTHON_INSTALL_PATH}/gtsam" # install path
gtsam # library to link with
"wrap;cythonize_eigency;gtsam;gtsam_header" # dependencies which need to be built before wrapping
)
add_dependencies(${python_install_target} gtsam gtsam_header)
# Wrap gtsam_unstable
if(GTSAM_BUILD_UNSTABLE)
add_custom_target(gtsam_unstable_header DEPENDS "../gtsam_unstable/gtsam_unstable.h")
wrap_and_install_library_cython("../gtsam_unstable/gtsam_unstable.h" # interface_header
"from gtsam.gtsam cimport *" # extra imports
"${GTSAM_CYTHON_INSTALL_PATH}/gtsam_unstable" # install path
gtsam_unstable # library to link with
"gtsam_unstable;gtsam_unstable_header;cythonize_gtsam" # dependencies to be built before wrapping
)
add_dependencies(${python_install_target} gtsam_unstable gtsam_unstable_header)
endif()
# install scripts and tests
install_cython_scripts("${PROJECT_SOURCE_DIR}/cython/gtsam" "${GTSAM_CYTHON_INSTALL_PATH}" "*.py")
install_cython_scripts("${PROJECT_SOURCE_DIR}/cython/gtsam_unstable" "${GTSAM_CYTHON_INSTALL_PATH}" "*.py")
endif ()

147
cython/README.md
View File

@ -1,147 +0,0 @@
# Python Wrapper
This is the Python wrapper around the GTSAM C++ library. We use Cython to generate the bindings to the underlying C++ code.
## Requirements
- If you want to build the GTSAM python library for a specific python version (eg 3.6),
use the `-DGTSAM_PYTHON_VERSION=3.6` option when running `cmake` otherwise the default interpreter will be used.
- If the interpreter is inside an environment (such as an anaconda environment or virtualenv environment),
then the environment should be active while building GTSAM.
- This wrapper needs `Cython(>=0.25.2)`, `backports_abc(>=0.5)`, and `numpy(>=1.11.0)`. These can be installed as follows:
```bash
pip install -r <gtsam_folder>/cython/requirements.txt
```
- For compatibility with GTSAM's Eigen version, it contains its own cloned version of [Eigency](https://github.com/wouterboomsma/eigency.git),
named `gtsam_eigency`, to interface between C++'s Eigen and Python's numpy.
## Install
- Run cmake with the `GTSAM_INSTALL_CYTHON_TOOLBOX` cmake flag enabled to configure building the wrapper. The wrapped module will be built and copied to the directory defined by `GTSAM_CYTHON_INSTALL_PATH`, which is by default `<PROJECT_BINARY_DIR>/cython` in Release mode and `<PROJECT_BINARY_DIR>/cython<CMAKE_BUILD_TYPE>` for other modes.
- Build GTSAM and the wrapper with `make`.
- To install, simply run `make python-install`.
- The same command can be used to install into a virtual environment if it is active.
- **NOTE**: if you don't want GTSAM to install to a system directory such as `/usr/local`, pass `-DCMAKE_INSTALL_PREFIX="./install"` to cmake to install GTSAM to a subdirectory of the build directory.
- You can also directly run `make python-install` without running `make`, and it will compile all the dependencies accordingly.
## Unit Tests
The Cython toolbox also has a small set of unit tests located in the
test directory. To run them:
```bash
cd <GTSAM_CYTHON_INSTALL_PATH>
python -m unittest discover
```
## Utils
TODO
## Examples
TODO
## Writing Your Own Scripts
See the tests for examples.
### Some Important Notes:
- Vector/Matrix:
- GTSAM expects double-precision floating point vectors and matrices.
Hence, you should pass numpy matrices with `dtype=float`, or `float64`.
- Also, GTSAM expects _column-major_ matrices, unlike the default storage
scheme in numpy. Hence, you should pass column-major matrices to GTSAM using
the flag order='F'. And you always get column-major matrices back.
For more details, see [this link](https://github.com/wouterboomsma/eigency#storage-layout---why-arrays-are-sometimes-transposed).
- Passing row-major matrices of different dtype, e.g. `int`, will also work
as the wrapper converts them to column-major and dtype float for you,
using numpy.array.astype(float, order='F', copy=False).
However, this will result a copy if your matrix is not in the expected type
and storage order.
- Inner namespace: Classes in inner namespace will be prefixed by <innerNamespace>\_ in Python.
Examples: `noiseModel_Gaussian`, `noiseModel_mEstimator_Tukey`
- Casting from a base class to a derive class must be done explicitly.
Examples:
```python
noiseBase = factor.noiseModel()
noiseGaussian = dynamic_cast_noiseModel_Gaussian_noiseModel_Base(noiseBase)
```
## Wrapping Custom GTSAM-based Project
Please refer to the template project and the corresponding tutorial available [here](https://github.com/borglab/GTSAM-project-python).
## KNOWN ISSUES
- Doesn't work with python3 installed from homebrew
- size-related issue: can only wrap up to a certain number of classes: up to mEstimator!
- Guess: 64 vs 32b? disutils Compiler flags?
- Bug with Cython 0.24: instantiated factor classes return FastVector<size_t> for keys(), which can't be casted to FastVector<Key>
- Upgrading to 0.25 solves the problem
- Need default constructor and default copy constructor for almost every classes... :(
- support these constructors by default and declare "delete" for special classes?
### TODO
- [ ] allow duplication of parent' functions in child classes. Not allowed for now due to conflicts in Cython.
- [ ] a common header for boost shared_ptr? (Or wait until everything is switched to std::shared_ptr in GTSAM?)
- [ ] inner namespaces ==> inner packages?
- [ ] Wrap fixed-size Matrices/Vectors?
### Completed/Cancelled:
- [x] Fix Python tests: don't use " import <package> \* ": Bad style!!! (18-03-17 19:50)
- [x] Unit tests for cython wrappers @done (18-03-17 18:45) -- simply compare generated files
- [x] Wrap unstable @done (18-03-17 15:30)
- [x] Unify cython/GTSAM.h and the original GTSAM.h @done (18-03-17 15:30)
- [x] 18-03-17: manage to unify the two versions by removing std container stubs from the matlab version,and keeping KeyList/KeyVector/KeySet as in the matlab version. Probably Cython 0.25 fixes the casting problem.
- [x] 06-03-17: manage to remove the requirements for default and copy constructors
- [ ] 25-11-16: Try to unify but failed. Main reasons are: Key/size_t, std containers, KeyVector/KeyList/KeySet. Matlab doesn't need to know about Key, but I can't make Cython to ignore Key as it couldn't cast KeyVector, i.e. FastVector<Key>, to FastVector<size_t>.
- [ ] Marginal and JointMarginal: revert changes @failed (17-03-17 11:00) -- Cython does need a default constructor! It produces cpp code like this: `GTSAM::JointMarginal __pyx_t_1;` Users don't have to wrap this constructor, however.
- [x] Convert input numpy Matrix/Vector to float dtype and storage order 'F' automatically, cannot crash! @done (15-03-17 13:00)
- [x] Remove requirements.txt - Frank: don't bother with only 2 packages and a special case for eigency! @done (08-03-17 10:30)
- [x] CMake install script @done (25-11-16 02:30)
- [ ] [REFACTOR] better name for uninstantiateClass: very vague!! @cancelled (25-11-16 02:30) -- lazy
- [ ] forward declaration? @cancelled (23-11-16 13:00) - nothing to do, seem to work?
- [x] wrap VariableIndex: why is it in inference? If need to, shouldn't have constructors to specific FactorGraphs @done (23-11-16 13:00)
- [x] Global functions @done (22-11-16 21:00)
- [x] [REFACTOR] typesEqual --> isSameSignature @done (22-11-16 21:00)
- [x] Proper overloads (constructors, static methods, methods) @done (20-11-16 21:00)
- [x] Allow overloading methods. The current solution is annoying!!! @done (20-11-16 21:00)
- [x] Casting from parent and grandparents @done (16-11-16 17:00)
- [x] Allow overloading constructors. The current solution is annoying!!! @done (16-11-16 17:00)
- [x] Support "print obj" @done (16-11-16 17:00)
- [x] methods for FastVector: at, [], ... @done (16-11-16 17:00)
- [x] Cython: Key and size_t: traits<size_t> doesn't exist @done (16-09-12 18:34)
- [x] KeyVector, KeyList, KeySet... @done (16-09-13 17:19)
- [x] [Nice to have] parse typedef @done (16-09-13 17:19)
- [x] ctypedef at correct places @done (16-09-12 18:34)
- [x] expand template variable type in constructor/static methods? @done (16-09-12 18:34)
- [x] NonlinearOptimizer: copy constructor deleted!!! @done (16-09-13 17:20)
- [x] Value: no default constructor @done (16-09-13 17:20)
- [x] ctypedef PriorFactor[Vector] PriorFactorVector @done (16-09-19 12:25)
- [x] Delete duplicate methods in derived class @done (16-09-12 13:38)
- [x] Fix return properly @done (16-09-11 17:14)
- [x] handle pair @done (16-09-11 17:14)
- [x] Eigency: ambiguous call: A(const T&) A(const Vector& v) and Eigency A(Map[Vector]& v) @done (16-09-11 07:59)
- [x] Eigency: Constructor: ambiguous construct from Vector/Matrix @done (16-09-11 07:59)
- [x] Eigency: Fix method template of Vector/Matrix: template argument is [Vector] while arugment is Map[Vector] @done (16-09-11 08:22)
- [x] Robust noise: copy assignment operator is deleted because of shared_ptr of the abstract Base class @done (16-09-10 09:05)
- [ ] Cython: Constructor: generate default constructor? (hack: if it's serializable?) @cancelled (16-09-13 17:20)
- [ ] Eigency: Map[] to Block @created(16-09-10 07:59) @cancelled (16-09-11 08:28)
- inference before symbolic/linear
- what's the purpose of "virtual" ??

26
cython/gtsam/__init__.py
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@ -1,26 +0,0 @@
from .gtsam import *
try:
import gtsam_unstable
def _deprecated_wrapper(item, name):
def wrapper(*args, **kwargs):
from warnings import warn
message = ('importing the unstable item "{}" directly from gtsam is deprecated. '.format(name) +
'Please import it from gtsam_unstable.')
warn(message)
return item(*args, **kwargs)
return wrapper
for name in dir(gtsam_unstable):
if not name.startswith('__'):
item = getattr(gtsam_unstable, name)
if callable(item):
item = _deprecated_wrapper(item, name)
globals()[name] = item
except ImportError:
pass

153
cython/gtsam/examples/ImuFactorExample.py
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@ -1,153 +0,0 @@
"""
GTSAM Copyright 2010-2019, Georgia Tech Research Corporation,
Atlanta, Georgia 30332-0415
All Rights Reserved
See LICENSE for the license information
A script validating and demonstrating the ImuFactor inference.
Author: Frank Dellaert, Varun Agrawal
"""
from __future__ import print_function
import math
import gtsam
import matplotlib.pyplot as plt
import numpy as np
from gtsam import symbol_shorthand_B as B
from gtsam import symbol_shorthand_V as V
from gtsam import symbol_shorthand_X as X
from gtsam.utils.plot import plot_pose3
from mpl_toolkits.mplot3d import Axes3D
from PreintegrationExample import POSES_FIG, PreintegrationExample
BIAS_KEY = B(0)
np.set_printoptions(precision=3, suppress=True)
class ImuFactorExample(PreintegrationExample):
def __init__(self):
self.velocity = np.array([2, 0, 0])
self.priorNoise = gtsam.noiseModel_Isotropic.Sigma(6, 0.1)
self.velNoise = gtsam.noiseModel_Isotropic.Sigma(3, 0.1)
# Choose one of these twists to change scenario:
zero_twist = (np.zeros(3), np.zeros(3))
forward_twist = (np.zeros(3), self.velocity)
loop_twist = (np.array([0, -math.radians(30), 0]), self.velocity)
sick_twist = (
np.array([math.radians(30), -math.radians(30), 0]), self.velocity)
accBias = np.array([-0.3, 0.1, 0.2])
gyroBias = np.array([0.1, 0.3, -0.1])
bias = gtsam.imuBias_ConstantBias(accBias, gyroBias)
dt = 1e-2
super(ImuFactorExample, self).__init__(sick_twist, bias, dt)
def addPrior(self, i, graph):
state = self.scenario.navState(i)
graph.push_back(gtsam.PriorFactorPose3(
X(i), state.pose(), self.priorNoise))
graph.push_back(gtsam.PriorFactorVector(
V(i), state.velocity(), self.velNoise))
def run(self):
graph = gtsam.NonlinearFactorGraph()
# initialize data structure for pre-integrated IMU measurements
pim = gtsam.PreintegratedImuMeasurements(self.params, self.actualBias)
T = 12
num_poses = T + 1 # assumes 1 factor per second
initial = gtsam.Values()
initial.insert(BIAS_KEY, self.actualBias)
for i in range(num_poses):
state_i = self.scenario.navState(float(i))
poseNoise = gtsam.Pose3.Expmap(np.random.randn(3)*0.1)
pose = state_i.pose().compose(poseNoise)
velocity = state_i.velocity() + np.random.randn(3)*0.1
initial.insert(X(i), pose)
initial.insert(V(i), velocity)
# simulate the loop
i = 0 # state index
actual_state_i = self.scenario.navState(0)
for k, t in enumerate(np.arange(0, T, self.dt)):
# get measurements and add them to PIM
measuredOmega = self.runner.measuredAngularVelocity(t)
measuredAcc = self.runner.measuredSpecificForce(t)
pim.integrateMeasurement(measuredAcc, measuredOmega, self.dt)
poseNoise = gtsam.Pose3.Expmap(np.random.randn(3)*0.1)
actual_state_i = gtsam.NavState(
actual_state_i.pose().compose(poseNoise),
actual_state_i.velocity() + np.random.randn(3)*0.1)
# Plot IMU many times
if k % 10 == 0:
self.plotImu(t, measuredOmega, measuredAcc)
# Plot every second
if k % int(1 / self.dt) == 0:
self.plotGroundTruthPose(t)
# create IMU factor every second
if (k + 1) % int(1 / self.dt) == 0:
factor = gtsam.ImuFactor(X(i), V(i), X(
i + 1), V(i + 1), BIAS_KEY, pim)
graph.push_back(factor)
if True:
print(factor)
print(pim.predict(actual_state_i, self.actualBias))
pim.resetIntegration()
actual_state_i = self.scenario.navState(t + self.dt)
i += 1
# add priors on beginning and end
self.addPrior(0, graph)
self.addPrior(num_poses - 1, graph)
# optimize using Levenberg-Marquardt optimization
params = gtsam.LevenbergMarquardtParams()
params.setVerbosityLM("SUMMARY")
optimizer = gtsam.LevenbergMarquardtOptimizer(graph, initial, params)
result = optimizer.optimize()
# Calculate and print marginal covariances
marginals = gtsam.Marginals(graph, result)
print("Covariance on bias:\n", marginals.marginalCovariance(BIAS_KEY))
for i in range(num_poses):
print("Covariance on pose {}:\n{}\n".format(
i, marginals.marginalCovariance(X(i))))
print("Covariance on vel {}:\n{}\n".format(
i, marginals.marginalCovariance(V(i))))
# Plot resulting poses
i = 0
while result.exists(X(i)):
pose_i = result.atPose3(X(i))
plot_pose3(POSES_FIG, pose_i, 0.1)
i += 1
gtsam.utils.plot.set_axes_equal(POSES_FIG)
print(result.atimuBias_ConstantBias(BIAS_KEY))
plt.ioff()
plt.show()
if __name__ == '__main__':
ImuFactorExample().run()

42
cython/gtsam_eigency/CMakeLists.txt
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@ -1,42 +0,0 @@
include(GtsamCythonWrap)
# Copy eigency's sources to the build folder
# so that the cython-generated header "conversions_api.h" can be found when cythonizing eigency's core
# and eigency's cython pxd headers can be found when cythonizing gtsam
file(COPY "." DESTINATION ".")
set(OUTPUT_DIR "${GTSAM_CYTHON_INSTALL_PATH}/gtsam_eigency")
set(EIGENCY_INCLUDE_DIR ${OUTPUT_DIR})
# This is to make the build/cython/gtsam_eigency folder a python package
configure_file(__init__.py.in ${OUTPUT_DIR}/__init__.py)
# include eigency headers
include_directories(${EIGENCY_INCLUDE_DIR})
# Cythonize and build eigency
message(STATUS "Cythonize and build eigency")
# Important trick: use "../gtsam_eigency/conversions.pyx" to let cython know that the conversions module is
# a part of the gtsam_eigency package and generate the function call import_gtsam_eigency__conversions()
# in conversions_api.h correctly!
cythonize(cythonize_eigency_conversions "../gtsam_eigency/conversions.pyx" "conversions"
"${OUTPUT_DIR}" "${EIGENCY_INCLUDE_DIR}" "" "" "")
cythonize(cythonize_eigency_core "../gtsam_eigency/core.pyx" "core"
${OUTPUT_DIR} "${EIGENCY_INCLUDE_DIR}" "" "" "")
# Include Eigen headers:
target_include_directories(cythonize_eigency_conversions PUBLIC
$<BUILD_INTERFACE:${GTSAM_EIGEN_INCLUDE_FOR_BUILD}>
$<INSTALL_INTERFACE:${GTSAM_EIGEN_INCLUDE_FOR_INSTALL}>
)
target_include_directories(cythonize_eigency_core PUBLIC
$<BUILD_INTERFACE:${GTSAM_EIGEN_INCLUDE_FOR_BUILD}>
$<INSTALL_INTERFACE:${GTSAM_EIGEN_INCLUDE_FOR_INSTALL}>
)
add_dependencies(cythonize_eigency_core cythonize_eigency_conversions)
add_custom_target(cythonize_eigency)
add_dependencies(cythonize_eigency cythonize_eigency_conversions cythonize_eigency_core)
if(TARGET ${python_install_target})
add_dependencies(${python_install_target} cythonize_eigency)
endif()

20
cython/gtsam_eigency/LICENSE.txt
View File

@ -1,20 +0,0 @@
Copyright (c) 2016 Wouter Boomsma
Permission is hereby granted, free of charge, to any person obtaining
a copy of this software and associated documentation files (the
"Software"), to deal in the Software without restriction, including
without limitation the rights to use, copy, modify, merge, publish,
distribute, sublicense, and/or sell copies of the Software, and to
permit persons to whom the Software is furnished to do so, subject to
the following conditions:
The above copyright notice and this permission notice shall be
included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE
LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

13
cython/gtsam_eigency/__init__.py.in
View File

@ -1,13 +0,0 @@
import os
import numpy as np
__eigen_dir__ = "${GTSAM_EIGEN_INCLUDE_FOR_INSTALL}"
def get_includes(include_eigen=True):
root = os.path.dirname(__file__)
parent = os.path.join(root, "..")
path = [root, parent, np.get_include()]
if include_eigen:
path.append(os.path.join(root, __eigen_dir__))
return path

62
cython/gtsam_eigency/conversions.pxd
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@ -1,62 +0,0 @@
cimport numpy as np
cdef api np.ndarray[double, ndim=2] ndarray_double_C(double *data, long rows, long cols, long outer_stride, long inner_stride)
cdef api np.ndarray[double, ndim=2] ndarray_double_F(double *data, long rows, long cols, long outer_stride, long inner_stride)
cdef api np.ndarray[double, ndim=2] ndarray_copy_double_C(const double *data, long rows, long cols, long outer_stride, long inner_stride)
cdef api np.ndarray[double, ndim=2] ndarray_copy_double_F(const double *data, long rows, long cols, long outer_stride, long inner_stride)
cdef api np.ndarray[float, ndim=2] ndarray_float_C(float *data, long rows, long cols, long outer_stride, long inner_stride)
cdef api np.ndarray[float, ndim=2] ndarray_float_F(float *data, long rows, long cols, long outer_stride, long inner_stride)
cdef api np.ndarray[float, ndim=2] ndarray_copy_float_C(const float *data, long rows, long cols, long outer_stride, long inner_stride)
cdef api np.ndarray[float, ndim=2] ndarray_copy_float_F(const float *data, long rows, long cols, long outer_stride, long inner_stride)
cdef api np.ndarray[long, ndim=2] ndarray_long_C(long *data, long rows, long cols, long outer_stride, long inner_stride)
cdef api np.ndarray[long, ndim=2] ndarray_long_F(long *data, long rows, long cols, long outer_stride, long inner_stride)
cdef api np.ndarray[long, ndim=2] ndarray_copy_long_C(const long *data, long rows, long cols, long outer_stride, long inner_stride)
cdef api np.ndarray[long, ndim=2] ndarray_copy_long_F(const long *data, long rows, long cols, long outer_stride, long inner_stride)
cdef api np.ndarray[unsigned long, ndim=2] ndarray_ulong_C(unsigned long *data, long rows, long cols, long outer_stride, long inner_stride)
cdef api np.ndarray[unsigned long, ndim=2] ndarray_ulong_F(unsigned long *data, long rows, long cols, long outer_stride, long inner_stride)
cdef api np.ndarray[unsigned long, ndim=2] ndarray_copy_ulong_C(const unsigned long *data, long rows, long cols, long outer_stride, long inner_stride)
cdef api np.ndarray[unsigned long, ndim=2] ndarray_copy_ulong_F(const unsigned long *data, long rows, long cols, long outer_stride, long inner_stride)
cdef api np.ndarray[int, ndim=2] ndarray_int_C(int *data, long rows, long cols, long outer_stride, long inner_stride)
cdef api np.ndarray[int, ndim=2] ndarray_int_F(int *data, long rows, long cols, long outer_stride, long inner_stride)
cdef api np.ndarray[int, ndim=2] ndarray_copy_int_C(const int *data, long rows, long cols, long outer_stride, long inner_stride)
cdef api np.ndarray[int, ndim=2] ndarray_copy_int_F(const int *data, long rows, long cols, long outer_stride, long inner_stride)
cdef api np.ndarray[unsigned int, ndim=2] ndarray_uint_C(unsigned int *data, long rows, long cols, long outer_stride, long inner_stride)
cdef api np.ndarray[unsigned int, ndim=2] ndarray_uint_F(unsigned int *data, long rows, long cols, long outer_stride, long inner_stride)
cdef api np.ndarray[unsigned int, ndim=2] ndarray_copy_uint_C(const unsigned int *data, long rows, long cols, long outer_stride, long inner_stride)
cdef api np.ndarray[unsigned int, ndim=2] ndarray_copy_uint_F(const unsigned int *data, long rows, long cols, long outer_stride, long inner_stride)
cdef api np.ndarray[short, ndim=2] ndarray_short_C(short *data, long rows, long cols, long outer_stride, long inner_stride)
cdef api np.ndarray[short, ndim=2] ndarray_short_F(short *data, long rows, long cols, long outer_stride, long inner_stride)
cdef api np.ndarray[short, ndim=2] ndarray_copy_short_C(const short *data, long rows, long cols, long outer_stride, long inner_stride)
cdef api np.ndarray[short, ndim=2] ndarray_copy_short_F(const short *data, long rows, long cols, long outer_stride, long inner_stride)
cdef api np.ndarray[unsigned short, ndim=2] ndarray_ushort_C(unsigned short *data, long rows, long cols, long outer_stride, long inner_stride)
cdef api np.ndarray[unsigned short, ndim=2] ndarray_ushort_F(unsigned short *data, long rows, long cols, long outer_stride, long inner_stride)
cdef api np.ndarray[unsigned short, ndim=2] ndarray_copy_ushort_C(const unsigned short *data, long rows, long cols, long outer_stride, long inner_stride)
cdef api np.ndarray[unsigned short, ndim=2] ndarray_copy_ushort_F(const unsigned short *data, long rows, long cols, long outer_stride, long inner_stride)
cdef api np.ndarray[signed char, ndim=2] ndarray_schar_C(signed char *data, long rows, long cols, long outer_stride, long inner_stride)
cdef api np.ndarray[signed char, ndim=2] ndarray_schar_F(signed char *data, long rows, long cols, long outer_stride, long inner_stride)
cdef api np.ndarray[signed char, ndim=2] ndarray_copy_schar_C(const signed char *data, long rows, long cols, long outer_stride, long inner_stride)
cdef api np.ndarray[signed char, ndim=2] ndarray_copy_schar_F(const signed char *data, long rows, long cols, long outer_stride, long inner_stride)
cdef api np.ndarray[unsigned char, ndim=2] ndarray_uchar_C(unsigned char *data, long rows, long cols, long outer_stride, long inner_stride)
cdef api np.ndarray[unsigned char, ndim=2] ndarray_uchar_F(unsigned char *data, long rows, long cols, long outer_stride, long inner_stride)
cdef api np.ndarray[unsigned char, ndim=2] ndarray_copy_uchar_C(const unsigned char *data, long rows, long cols, long outer_stride, long inner_stride)
cdef api np.ndarray[unsigned char, ndim=2] ndarray_copy_uchar_F(const unsigned char *data, long rows, long cols, long outer_stride, long inner_stride)
cdef api np.ndarray[np.complex128_t, ndim=2] ndarray_complex_double_C(np.complex128_t *data, long rows, long cols, long outer_stride, long inner_stride)
cdef api np.ndarray[np.complex128_t, ndim=2] ndarray_complex_double_F(np.complex128_t *data, long rows, long cols, long outer_stride, long inner_stride)
cdef api np.ndarray[np.complex128_t, ndim=2] ndarray_copy_complex_double_C(const np.complex128_t *data, long rows, long cols, long outer_stride, long inner_stride)
cdef api np.ndarray[np.complex128_t, ndim=2] ndarray_copy_complex_double_F(const np.complex128_t *data, long rows, long cols, long outer_stride, long inner_stride)
cdef api np.ndarray[np.complex64_t, ndim=2] ndarray_complex_float_C(np.complex64_t *data, long rows, long cols, long outer_stride, long inner_stride)
cdef api np.ndarray[np.complex64_t, ndim=2] ndarray_complex_float_F(np.complex64_t *data, long rows, long cols, long outer_stride, long inner_stride)
cdef api np.ndarray[np.complex64_t, ndim=2] ndarray_copy_complex_float_C(const np.complex64_t *data, long rows, long cols, long outer_stride, long inner_stride)
cdef api np.ndarray[np.complex64_t, ndim=2] ndarray_copy_complex_float_F(const np.complex64_t *data, long rows, long cols, long outer_stride, long inner_stride)

327
cython/gtsam_eigency/conversions.pyx
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@ -1,327 +0,0 @@
cimport cython
import numpy as np
from numpy.lib.stride_tricks import as_strided
@cython.boundscheck(False)
cdef np.ndarray[double, ndim=2] ndarray_double_C(double *data, long rows, long cols, long row_stride, long col_stride):
cdef double[:,:] mem_view = <double[:rows,:cols]>data
dtype = 'double'
cdef int itemsize = np.dtype(dtype).itemsize
return as_strided(np.asarray(mem_view, dtype=dtype, order="C"), strides=[row_stride*itemsize, col_stride*itemsize])
@cython.boundscheck(False)
cdef np.ndarray[double, ndim=2] ndarray_double_F(double *data, long rows, long cols, long row_stride, long col_stride):
cdef double[::1,:] mem_view = <double[:rows:1,:cols]>data
dtype = 'double'
cdef int itemsize = np.dtype(dtype).itemsize
return as_strided(np.asarray(mem_view, dtype=dtype, order="F"), strides=[row_stride*itemsize, col_stride*itemsize])
@cython.boundscheck(False)
cdef np.ndarray[double, ndim=2] ndarray_copy_double_C(const double *data, long rows, long cols, long row_stride, long col_stride):
cdef double[:,:] mem_view = <double[:rows,:cols]>data
dtype = 'double'
cdef int itemsize = np.dtype(dtype).itemsize
return np.copy(as_strided(np.asarray(mem_view, dtype=dtype, order="C"), strides=[row_stride*itemsize, col_stride*itemsize]))
@cython.boundscheck(False)
cdef np.ndarray[double, ndim=2] ndarray_copy_double_F(const double *data, long rows, long cols, long row_stride, long col_stride):
cdef double[::1,:] mem_view = <double[:rows:1,:cols]>data
dtype = 'double'
cdef int itemsize = np.dtype(dtype).itemsize
return np.copy(as_strided(np.asarray(mem_view, dtype=dtype, order="F"), strides=[row_stride*itemsize, col_stride*itemsize]))
@cython.boundscheck(False)
cdef np.ndarray[float, ndim=2] ndarray_float_C(float *data, long rows, long cols, long row_stride, long col_stride):
cdef float[:,:] mem_view = <float[:rows,:cols]>data
dtype = 'float'
cdef int itemsize = np.dtype(dtype).itemsize
return as_strided(np.asarray(mem_view, dtype=dtype, order="C"), strides=[row_stride*itemsize, col_stride*itemsize])
@cython.boundscheck(False)
cdef np.ndarray[float, ndim=2] ndarray_float_F(float *data, long rows, long cols, long row_stride, long col_stride):
cdef float[::1,:] mem_view = <float[:rows:1,:cols]>data
dtype = 'float'
cdef int itemsize = np.dtype(dtype).itemsize
return as_strided(np.asarray(mem_view, dtype=dtype, order="F"), strides=[row_stride*itemsize, col_stride*itemsize])
@cython.boundscheck(False)
cdef np.ndarray[float, ndim=2] ndarray_copy_float_C(const float *data, long rows, long cols, long row_stride, long col_stride):
cdef float[:,:] mem_view = <float[:rows,:cols]>data
dtype = 'float'
cdef int itemsize = np.dtype(dtype).itemsize
return np.copy(as_strided(np.asarray(mem_view, dtype=dtype, order="C"), strides=[row_stride*itemsize, col_stride*itemsize]))
@cython.boundscheck(False)
cdef np.ndarray[float, ndim=2] ndarray_copy_float_F(const float *data, long rows, long cols, long row_stride, long col_stride):
cdef float[::1,:] mem_view = <float[:rows:1,:cols]>data
dtype = 'float'
cdef int itemsize = np.dtype(dtype).itemsize
return np.copy(as_strided(np.asarray(mem_view, dtype=dtype, order="F"), strides=[row_stride*itemsize, col_stride*itemsize]))
@cython.boundscheck(False)
cdef np.ndarray[long, ndim=2] ndarray_long_C(long *data, long rows, long cols, long row_stride, long col_stride):
cdef long[:,:] mem_view = <long[:rows,:cols]>data
dtype = 'int_'
cdef int itemsize = np.dtype(dtype).itemsize
return as_strided(np.asarray(mem_view, dtype=dtype, order="C"), strides=[row_stride*itemsize, col_stride*itemsize])
@cython.boundscheck(False)
cdef np.ndarray[long, ndim=2] ndarray_long_F(long *data, long rows, long cols, long row_stride, long col_stride):
cdef long[::1,:] mem_view = <long[:rows:1,:cols]>data
dtype = 'int_'
cdef int itemsize = np.dtype(dtype).itemsize
return as_strided(np.asarray(mem_view, dtype=dtype, order="F"), strides=[row_stride*itemsize, col_stride*itemsize])
@cython.boundscheck(False)
cdef np.ndarray[long, ndim=2] ndarray_copy_long_C(const long *data, long rows, long cols, long row_stride, long col_stride):
cdef long[:,:] mem_view = <long[:rows,:cols]>data
dtype = 'int_'
cdef int itemsize = np.dtype(dtype).itemsize
return np.copy(as_strided(np.asarray(mem_view, dtype=dtype, order="C"), strides=[row_stride*itemsize, col_stride*itemsize]))
@cython.boundscheck(False)
cdef np.ndarray[long, ndim=2] ndarray_copy_long_F(const long *data, long rows, long cols, long row_stride, long col_stride):
cdef long[::1,:] mem_view = <long[:rows:1,:cols]>data
dtype = 'int_'
cdef int itemsize = np.dtype(dtype).itemsize
return np.copy(as_strided(np.asarray(mem_view, dtype=dtype, order="F"), strides=[row_stride*itemsize, col_stride*itemsize]))
@cython.boundscheck(False)
cdef np.ndarray[unsigned long, ndim=2] ndarray_ulong_C(unsigned long *data, long rows, long cols, long row_stride, long col_stride):
cdef unsigned long[:,:] mem_view = <unsigned long[:rows,:cols]>data
dtype = 'uint'
cdef int itemsize = np.dtype(dtype).itemsize
return as_strided(np.asarray(mem_view, dtype=dtype, order="C"), strides=[row_stride*itemsize, col_stride*itemsize])
@cython.boundscheck(False)
cdef np.ndarray[unsigned long, ndim=2] ndarray_ulong_F(unsigned long *data, long rows, long cols, long row_stride, long col_stride):
cdef unsigned long[::1,:] mem_view = <unsigned long[:rows:1,:cols]>data
dtype = 'uint'
cdef int itemsize = np.dtype(dtype).itemsize
return as_strided(np.asarray(mem_view, dtype=dtype, order="F"), strides=[row_stride*itemsize, col_stride*itemsize])
@cython.boundscheck(False)
cdef np.ndarray[unsigned long, ndim=2] ndarray_copy_ulong_C(const unsigned long *data, long rows, long cols, long row_stride, long col_stride):
cdef unsigned long[:,:] mem_view = <unsigned long[:rows,:cols]>data
dtype = 'uint'
cdef int itemsize = np.dtype(dtype).itemsize
return np.copy(as_strided(np.asarray(mem_view, dtype=dtype, order="C"), strides=[row_stride*itemsize, col_stride*itemsize]))
@cython.boundscheck(False)
cdef np.ndarray[unsigned long, ndim=2] ndarray_copy_ulong_F(const unsigned long *data, long rows, long cols, long row_stride, long col_stride):
cdef unsigned long[::1,:] mem_view = <unsigned long[:rows:1,:cols]>data
dtype = 'uint'
cdef int itemsize = np.dtype(dtype).itemsize
return np.copy(as_strided(np.asarray(mem_view, dtype=dtype, order="F"), strides=[row_stride*itemsize, col_stride*itemsize]))
@cython.boundscheck(False)
cdef np.ndarray[int, ndim=2] ndarray_int_C(int *data, long rows, long cols, long row_stride, long col_stride):
cdef int[:,:] mem_view = <int[:rows,:cols]>data
dtype = 'int'
cdef int itemsize = np.dtype(dtype).itemsize
return as_strided(np.asarray(mem_view, dtype=dtype, order="C"), strides=[row_stride*itemsize, col_stride*itemsize])
@cython.boundscheck(False)
cdef np.ndarray[int, ndim=2] ndarray_int_F(int *data, long rows, long cols, long row_stride, long col_stride):
cdef int[::1,:] mem_view = <int[:rows:1,:cols]>data
dtype = 'int'
cdef int itemsize = np.dtype(dtype).itemsize
return as_strided(np.asarray(mem_view, dtype=dtype, order="F"), strides=[row_stride*itemsize, col_stride*itemsize])
@cython.boundscheck(False)
cdef np.ndarray[int, ndim=2] ndarray_copy_int_C(const int *data, long rows, long cols, long row_stride, long col_stride):
cdef int[:,:] mem_view = <int[:rows,:cols]>data
dtype = 'int'
cdef int itemsize = np.dtype(dtype).itemsize
return np.copy(as_strided(np.asarray(mem_view, dtype=dtype, order="C"), strides=[row_stride*itemsize, col_stride*itemsize]))
@cython.boundscheck(False)
cdef np.ndarray[int, ndim=2] ndarray_copy_int_F(const int *data, long rows, long cols, long row_stride, long col_stride):
cdef int[::1,:] mem_view = <int[:rows:1,:cols]>data
dtype = 'int'
cdef int itemsize = np.dtype(dtype).itemsize
return np.copy(as_strided(np.asarray(mem_view, dtype=dtype, order="F"), strides=[row_stride*itemsize, col_stride*itemsize]))
@cython.boundscheck(False)
cdef np.ndarray[unsigned int, ndim=2] ndarray_uint_C(unsigned int *data, long rows, long cols, long row_stride, long col_stride):
cdef unsigned int[:,:] mem_view = <unsigned int[:rows,:cols]>data
dtype = 'uint'
cdef int itemsize = np.dtype(dtype).itemsize
return as_strided(np.asarray(mem_view, dtype=dtype, order="C"), strides=[row_stride*itemsize, col_stride*itemsize])
@cython.boundscheck(False)
cdef np.ndarray[unsigned int, ndim=2] ndarray_uint_F(unsigned int *data, long rows, long cols, long row_stride, long col_stride):
cdef unsigned int[::1,:] mem_view = <unsigned int[:rows:1,:cols]>data
dtype = 'uint'
cdef int itemsize = np.dtype(dtype).itemsize
return as_strided(np.asarray(mem_view, dtype=dtype, order="F"), strides=[row_stride*itemsize, col_stride*itemsize])
@cython.boundscheck(False)
cdef np.ndarray[unsigned int, ndim=2] ndarray_copy_uint_C(const unsigned int *data, long rows, long cols, long row_stride, long col_stride):
cdef unsigned int[:,:] mem_view = <unsigned int[:rows,:cols]>data
dtype = 'uint'
cdef int itemsize = np.dtype(dtype).itemsize
return np.copy(as_strided(np.asarray(mem_view, dtype=dtype, order="C"), strides=[row_stride*itemsize, col_stride*itemsize]))
@cython.boundscheck(False)
cdef np.ndarray[unsigned int, ndim=2] ndarray_copy_uint_F(const unsigned int *data, long rows, long cols, long row_stride, long col_stride):
cdef unsigned int[::1,:] mem_view = <unsigned int[:rows:1,:cols]>data
dtype = 'uint'
cdef int itemsize = np.dtype(dtype).itemsize
return np.copy(as_strided(np.asarray(mem_view, dtype=dtype, order="F"), strides=[row_stride*itemsize, col_stride*itemsize]))
@cython.boundscheck(False)
cdef np.ndarray[short, ndim=2] ndarray_short_C(short *data, long rows, long cols, long row_stride, long col_stride):
cdef short[:,:] mem_view = <short[:rows,:cols]>data
dtype = 'short'
cdef int itemsize = np.dtype(dtype).itemsize
return as_strided(np.asarray(mem_view, dtype=dtype, order="C"), strides=[row_stride*itemsize, col_stride*itemsize])
@cython.boundscheck(False)
cdef np.ndarray[short, ndim=2] ndarray_short_F(short *data, long rows, long cols, long row_stride, long col_stride):
cdef short[::1,:] mem_view = <short[:rows:1,:cols]>data
dtype = 'short'
cdef int itemsize = np.dtype(dtype).itemsize
return as_strided(np.asarray(mem_view, dtype=dtype, order="F"), strides=[row_stride*itemsize, col_stride*itemsize])
@cython.boundscheck(False)
cdef np.ndarray[short, ndim=2] ndarray_copy_short_C(const short *data, long rows, long cols, long row_stride, long col_stride):
cdef short[:,:] mem_view = <short[:rows,:cols]>data
dtype = 'short'
cdef int itemsize = np.dtype(dtype).itemsize
return np.copy(as_strided(np.asarray(mem_view, dtype=dtype, order="C"), strides=[row_stride*itemsize, col_stride*itemsize]))
@cython.boundscheck(False)
cdef np.ndarray[short, ndim=2] ndarray_copy_short_F(const short *data, long rows, long cols, long row_stride, long col_stride):
cdef short[::1,:] mem_view = <short[:rows:1,:cols]>data
dtype = 'short'
cdef int itemsize = np.dtype(dtype).itemsize
return np.copy(as_strided(np.asarray(mem_view, dtype=dtype, order="F"), strides=[row_stride*itemsize, col_stride*itemsize]))
@cython.boundscheck(False)
cdef np.ndarray[unsigned short, ndim=2] ndarray_ushort_C(unsigned short *data, long rows, long cols, long row_stride, long col_stride):
cdef unsigned short[:,:] mem_view = <unsigned short[:rows,:cols]>data
dtype = 'ushort'
cdef int itemsize = np.dtype(dtype).itemsize
return as_strided(np.asarray(mem_view, dtype=dtype, order="C"), strides=[row_stride*itemsize, col_stride*itemsize])
@cython.boundscheck(False)
cdef np.ndarray[unsigned short, ndim=2] ndarray_ushort_F(unsigned short *data, long rows, long cols, long row_stride, long col_stride):
cdef unsigned short[::1,:] mem_view = <unsigned short[:rows:1,:cols]>data
dtype = 'ushort'
cdef int itemsize = np.dtype(dtype).itemsize
return as_strided(np.asarray(mem_view, dtype=dtype, order="F"), strides=[row_stride*itemsize, col_stride*itemsize])
@cython.boundscheck(False)
cdef np.ndarray[unsigned short, ndim=2] ndarray_copy_ushort_C(const unsigned short *data, long rows, long cols, long row_stride, long col_stride):
cdef unsigned short[:,:] mem_view = <unsigned short[:rows,:cols]>data
dtype = 'ushort'
cdef int itemsize = np.dtype(dtype).itemsize
return np.copy(as_strided(np.asarray(mem_view, dtype=dtype, order="C"), strides=[row_stride*itemsize, col_stride*itemsize]))
@cython.boundscheck(False)
cdef np.ndarray[unsigned short, ndim=2] ndarray_copy_ushort_F(const unsigned short *data, long rows, long cols, long row_stride, long col_stride):
cdef unsigned short[::1,:] mem_view = <unsigned short[:rows:1,:cols]>data
dtype = 'ushort'
cdef int itemsize = np.dtype(dtype).itemsize
return np.copy(as_strided(np.asarray(mem_view, dtype=dtype, order="F"), strides=[row_stride*itemsize, col_stride*itemsize]))
@cython.boundscheck(False)
cdef np.ndarray[signed char, ndim=2] ndarray_schar_C(signed char *data, long rows, long cols, long row_stride, long col_stride):
cdef signed char[:,:] mem_view = <signed char[:rows,:cols]>data
dtype = 'int8'
cdef int itemsize = np.dtype(dtype).itemsize
return as_strided(np.asarray(mem_view, dtype=dtype, order="C"), strides=[row_stride*itemsize, col_stride*itemsize])
@cython.boundscheck(False)
cdef np.ndarray[signed char, ndim=2] ndarray_schar_F(signed char *data, long rows, long cols, long row_stride, long col_stride):
cdef signed char[::1,:] mem_view = <signed char[:rows:1,:cols]>data
dtype = 'int8'
cdef int itemsize = np.dtype(dtype).itemsize
return as_strided(np.asarray(mem_view, dtype=dtype, order="F"), strides=[row_stride*itemsize, col_stride*itemsize])
@cython.boundscheck(False)
cdef np.ndarray[signed char, ndim=2] ndarray_copy_schar_C(const signed char *data, long rows, long cols, long row_stride, long col_stride):
cdef signed char[:,:] mem_view = <signed char[:rows,:cols]>data
dtype = 'int8'
cdef int itemsize = np.dtype(dtype).itemsize
return np.copy(as_strided(np.asarray(mem_view, dtype=dtype, order="C"), strides=[row_stride*itemsize, col_stride*itemsize]))
@cython.boundscheck(False)
cdef np.ndarray[signed char, ndim=2] ndarray_copy_schar_F(const signed char *data, long rows, long cols, long row_stride, long col_stride):
cdef signed char[::1,:] mem_view = <signed char[:rows:1,:cols]>data
dtype = 'int8'
cdef int itemsize = np.dtype(dtype).itemsize
return np.copy(as_strided(np.asarray(mem_view, dtype=dtype, order="F"), strides=[row_stride*itemsize, col_stride*itemsize]))
@cython.boundscheck(False)
cdef np.ndarray[unsigned char, ndim=2] ndarray_uchar_C(unsigned char *data, long rows, long cols, long row_stride, long col_stride):
cdef unsigned char[:,:] mem_view = <unsigned char[:rows,:cols]>data
dtype = 'uint8'
cdef int itemsize = np.dtype(dtype).itemsize
return as_strided(np.asarray(mem_view, dtype=dtype, order="C"), strides=[row_stride*itemsize, col_stride*itemsize])
@cython.boundscheck(False)
cdef np.ndarray[unsigned char, ndim=2] ndarray_uchar_F(unsigned char *data, long rows, long cols, long row_stride, long col_stride):
cdef unsigned char[::1,:] mem_view = <unsigned char[:rows:1,:cols]>data
dtype = 'uint8'
cdef int itemsize = np.dtype(dtype).itemsize
return as_strided(np.asarray(mem_view, dtype=dtype, order="F"), strides=[row_stride*itemsize, col_stride*itemsize])
@cython.boundscheck(False)
cdef np.ndarray[unsigned char, ndim=2] ndarray_copy_uchar_C(const unsigned char *data, long rows, long cols, long row_stride, long col_stride):
cdef unsigned char[:,:] mem_view = <unsigned char[:rows,:cols]>data
dtype = 'uint8'
cdef int itemsize = np.dtype(dtype).itemsize
return np.copy(as_strided(np.asarray(mem_view, dtype=dtype, order="C"), strides=[row_stride*itemsize, col_stride*itemsize]))
@cython.boundscheck(False)
cdef np.ndarray[unsigned char, ndim=2] ndarray_copy_uchar_F(const unsigned char *data, long rows, long cols, long row_stride, long col_stride):
cdef unsigned char[::1,:] mem_view = <unsigned char[:rows:1,:cols]>data
dtype = 'uint8'
cdef int itemsize = np.dtype(dtype).itemsize
return np.copy(as_strided(np.asarray(mem_view, dtype=dtype, order="F"), strides=[row_stride*itemsize, col_stride*itemsize]))
@cython.boundscheck(False)
cdef np.ndarray[np.complex128_t, ndim=2] ndarray_complex_double_C(np.complex128_t *data, long rows, long cols, long row_stride, long col_stride):
cdef np.complex128_t[:,:] mem_view = <np.complex128_t[:rows,:cols]>data
dtype = 'complex128'
cdef int itemsize = np.dtype(dtype).itemsize
return as_strided(np.asarray(mem_view, dtype=dtype, order="C"), strides=[row_stride*itemsize, col_stride*itemsize])
@cython.boundscheck(False)
cdef np.ndarray[np.complex128_t, ndim=2] ndarray_complex_double_F(np.complex128_t *data, long rows, long cols, long row_stride, long col_stride):
cdef np.complex128_t[::1,:] mem_view = <np.complex128_t[:rows:1,:cols]>data
dtype = 'complex128'
cdef int itemsize = np.dtype(dtype).itemsize
return as_strided(np.asarray(mem_view, dtype=dtype, order="F"), strides=[row_stride*itemsize, col_stride*itemsize])
@cython.boundscheck(False)
cdef np.ndarray[np.complex128_t, ndim=2] ndarray_copy_complex_double_C(const np.complex128_t *data, long rows, long cols, long row_stride, long col_stride):
cdef np.complex128_t[:,:] mem_view = <np.complex128_t[:rows,:cols]>data
dtype = 'complex128'
cdef int itemsize = np.dtype(dtype).itemsize
return np.copy(as_strided(np.asarray(mem_view, dtype=dtype, order="C"), strides=[row_stride*itemsize, col_stride*itemsize]))
@cython.boundscheck(False)
cdef np.ndarray[np.complex128_t, ndim=2] ndarray_copy_complex_double_F(const np.complex128_t *data, long rows, long cols, long row_stride, long col_stride):
cdef np.complex128_t[::1,:] mem_view = <np.complex128_t[:rows:1,:cols]>data
dtype = 'complex128'
cdef int itemsize = np.dtype(dtype).itemsize
return np.copy(as_strided(np.asarray(mem_view, dtype=dtype, order="F"), strides=[row_stride*itemsize, col_stride*itemsize]))
@cython.boundscheck(False)
cdef np.ndarray[np.complex64_t, ndim=2] ndarray_complex_float_C(np.complex64_t *data, long rows, long cols, long row_stride, long col_stride):
cdef np.complex64_t[:,:] mem_view = <np.complex64_t[:rows,:cols]>data
dtype = 'complex64'
cdef int itemsize = np.dtype(dtype).itemsize
return as_strided(np.asarray(mem_view, dtype=dtype, order="C"), strides=[row_stride*itemsize, col_stride*itemsize])
@cython.boundscheck(False)
cdef np.ndarray[np.complex64_t, ndim=2] ndarray_complex_float_F(np.complex64_t *data, long rows, long cols, long row_stride, long col_stride):
cdef np.complex64_t[::1,:] mem_view = <np.complex64_t[:rows:1,:cols]>data
dtype = 'complex64'
cdef int itemsize = np.dtype(dtype).itemsize
return as_strided(np.asarray(mem_view, dtype=dtype, order="F"), strides=[row_stride*itemsize, col_stride*itemsize])
@cython.boundscheck(False)
cdef np.ndarray[np.complex64_t, ndim=2] ndarray_copy_complex_float_C(const np.complex64_t *data, long rows, long cols, long row_stride, long col_stride):
cdef np.complex64_t[:,:] mem_view = <np.complex64_t[:rows,:cols]>data
dtype = 'complex64'
cdef int itemsize = np.dtype(dtype).itemsize
return np.copy(as_strided(np.asarray(mem_view, dtype=dtype, order="C"), strides=[row_stride*itemsize, col_stride*itemsize]))
@cython.boundscheck(False)
cdef np.ndarray[np.complex64_t, ndim=2] ndarray_copy_complex_float_F(const np.complex64_t *data, long rows, long cols, long row_stride, long col_stride):
cdef np.complex64_t[::1,:] mem_view = <np.complex64_t[:rows:1,:cols]>data
dtype = 'complex64'
cdef int itemsize = np.dtype(dtype).itemsize
return np.copy(as_strided(np.asarray(mem_view, dtype=dtype, order="F"), strides=[row_stride*itemsize, col_stride*itemsize]))

917
cython/gtsam_eigency/core.pxd
View File

@ -1,917 +0,0 @@
cimport cython
cimport numpy as np
ctypedef signed char schar;
ctypedef unsigned char uchar;
ctypedef fused dtype:
uchar
schar
short
int
long
float
double
ctypedef fused DenseType:
Matrix
Array
ctypedef fused Rows:
_1
_2
_3
_4
_5
_6
_7
_8
_9
_10
_11
_12
_13
_14
_15
_16
_17
_18
_19
_20
_21
_22
_23
_24
_25
_26
_27
_28
_29
_30
_31
_32
Dynamic
ctypedef Rows Cols
ctypedef Rows StrideOuter
ctypedef Rows StrideInner
ctypedef fused DenseTypeShort:
Vector1i
Vector2i
Vector3i
Vector4i
VectorXi
RowVector1i
RowVector2i
RowVector3i
RowVector4i
RowVectorXi
Matrix1i
Matrix2i
Matrix3i
Matrix4i
MatrixXi
Vector1f
Vector2f
Vector3f
Vector4f
VectorXf
RowVector1f
RowVector2f
RowVector3f
RowVector4f
RowVectorXf
Matrix1f
Matrix2f
Matrix3f
Matrix4f
MatrixXf
Vector1d
Vector2d
Vector3d
Vector4d
VectorXd
RowVector1d
RowVector2d
RowVector3d
RowVector4d
RowVectorXd
Matrix1d
Matrix2d
Matrix3d
Matrix4d
MatrixXd
Vector1cf
Vector2cf
Vector3cf
Vector4cf
VectorXcf
RowVector1cf
RowVector2cf
RowVector3cf
RowVector4cf
RowVectorXcf
Matrix1cf
Matrix2cf
Matrix3cf
Matrix4cf
MatrixXcf
Vector1cd
Vector2cd
Vector3cd
Vector4cd
VectorXcd
RowVector1cd
RowVector2cd
RowVector3cd
RowVector4cd
RowVectorXcd
Matrix1cd
Matrix2cd
Matrix3cd
Matrix4cd
MatrixXcd
Array22i
Array23i
Array24i
Array2Xi
Array32i
Array33i
Array34i
Array3Xi
Array42i
Array43i
Array44i
Array4Xi
ArrayX2i
ArrayX3i
ArrayX4i
ArrayXXi
Array2i
Array3i
Array4i
ArrayXi
Array22f
Array23f
Array24f
Array2Xf
Array32f
Array33f
Array34f
Array3Xf
Array42f
Array43f
Array44f
Array4Xf
ArrayX2f
ArrayX3f
ArrayX4f
ArrayXXf
Array2f
Array3f
Array4f
ArrayXf
Array22d
Array23d
Array24d
Array2Xd
Array32d
Array33d
Array34d
Array3Xd
Array42d
Array43d
Array44d
Array4Xd
ArrayX2d
ArrayX3d
ArrayX4d
ArrayXXd
Array2d
Array3d
Array4d
ArrayXd
Array22cf
Array23cf
Array24cf
Array2Xcf
Array32cf
Array33cf
Array34cf
Array3Xcf
Array42cf
Array43cf
Array44cf
Array4Xcf
ArrayX2cf
ArrayX3cf
ArrayX4cf
ArrayXXcf
Array2cf
Array3cf
Array4cf
ArrayXcf
Array22cd
Array23cd
Array24cd
Array2Xcd
Array32cd
Array33cd
Array34cd
Array3Xcd
Array42cd
Array43cd
Array44cd
Array4Xcd
ArrayX2cd
ArrayX3cd
ArrayX4cd
ArrayXXcd
Array2cd
Array3cd
Array4cd
ArrayXcd
ctypedef fused StorageOrder:
RowMajor
ColMajor
ctypedef fused MapOptions:
Aligned
Unaligned
cdef extern from "eigency_cpp.h" namespace "eigency":
cdef cppclass _1 "1":
pass
cdef cppclass _2 "2":
pass
cdef cppclass _3 "3":
pass
cdef cppclass _4 "4":
pass
cdef cppclass _5 "5":
pass
cdef cppclass _6 "6":
pass
cdef cppclass _7 "7":
pass
cdef cppclass _8 "8":
pass
cdef cppclass _9 "9":
pass
cdef cppclass _10 "10":
pass
cdef cppclass _11 "11":
pass
cdef cppclass _12 "12":
pass
cdef cppclass _13 "13":
pass
cdef cppclass _14 "14":
pass
cdef cppclass _15 "15":
pass
cdef cppclass _16 "16":
pass
cdef cppclass _17 "17":
pass
cdef cppclass _18 "18":
pass
cdef cppclass _19 "19":
pass
cdef cppclass _20 "20":
pass
cdef cppclass _21 "21":
pass
cdef cppclass _22 "22":
pass
cdef cppclass _23 "23":
pass
cdef cppclass _24 "24":
pass
cdef cppclass _25 "25":
pass
cdef cppclass _26 "26":
pass
cdef cppclass _27 "27":
pass
cdef cppclass _28 "28":
pass
cdef cppclass _29 "29":
pass
cdef cppclass _30 "30":
pass
cdef cppclass _31 "31":
pass
cdef cppclass _32 "32":
pass
cdef cppclass PlainObjectBase:
pass
cdef cppclass Map[DenseTypeShort](PlainObjectBase):
Map() except +
Map(np.ndarray array) except +
cdef cppclass FlattenedMap[DenseType, dtype, Rows, Cols]:
FlattenedMap() except +
FlattenedMap(np.ndarray array) except +
cdef cppclass FlattenedMapWithOrder "eigency::FlattenedMap" [DenseType, dtype, Rows, Cols, StorageOrder]:
FlattenedMapWithOrder() except +
FlattenedMapWithOrder(np.ndarray array) except +
cdef cppclass FlattenedMapWithStride "eigency::FlattenedMap" [DenseType, dtype, Rows, Cols, StorageOrder, MapOptions, StrideOuter, StrideInner]:
FlattenedMapWithStride() except +
FlattenedMapWithStride(np.ndarray array) except +
cdef np.ndarray ndarray_view(PlainObjectBase &)
cdef np.ndarray ndarray_copy(PlainObjectBase &)
cdef np.ndarray ndarray(PlainObjectBase &)
cdef extern from "eigency_cpp.h" namespace "Eigen":
cdef cppclass Dynamic:
pass
cdef cppclass RowMajor:
pass
cdef cppclass ColMajor:
pass
cdef cppclass Aligned:
pass
cdef cppclass Unaligned:
pass
cdef cppclass Matrix(PlainObjectBase):
pass
cdef cppclass Array(PlainObjectBase):
pass
cdef cppclass VectorXd(PlainObjectBase):
pass
cdef cppclass Vector1i(PlainObjectBase):
pass
cdef cppclass Vector2i(PlainObjectBase):
pass
cdef cppclass Vector3i(PlainObjectBase):
pass
cdef cppclass Vector4i(PlainObjectBase):
pass
cdef cppclass VectorXi(PlainObjectBase):
pass
cdef cppclass RowVector1i(PlainObjectBase):
pass
cdef cppclass RowVector2i(PlainObjectBase):
pass
cdef cppclass RowVector3i(PlainObjectBase):
pass
cdef cppclass RowVector4i(PlainObjectBase):
pass
cdef cppclass RowVectorXi(PlainObjectBase):
pass
cdef cppclass Matrix1i(PlainObjectBase):
pass
cdef cppclass Matrix2i(PlainObjectBase):
pass
cdef cppclass Matrix3i(PlainObjectBase):
pass
cdef cppclass Matrix4i(PlainObjectBase):
pass
cdef cppclass MatrixXi(PlainObjectBase):
pass
cdef cppclass Vector1f(PlainObjectBase):
pass
cdef cppclass Vector2f(PlainObjectBase):
pass
cdef cppclass Vector3f(PlainObjectBase):
pass
cdef cppclass Vector4f(PlainObjectBase):
pass
cdef cppclass VectorXf(PlainObjectBase):
pass
cdef cppclass RowVector1f(PlainObjectBase):
pass
cdef cppclass RowVector2f(PlainObjectBase):
pass
cdef cppclass RowVector3f(PlainObjectBase):
pass
cdef cppclass RowVector4f(PlainObjectBase):
pass
cdef cppclass RowVectorXf(PlainObjectBase):
pass
cdef cppclass Matrix1f(PlainObjectBase):
pass
cdef cppclass Matrix2f(PlainObjectBase):
pass
cdef cppclass Matrix3f(PlainObjectBase):
pass
cdef cppclass Matrix4f(PlainObjectBase):
pass
cdef cppclass MatrixXf(PlainObjectBase):
pass
cdef cppclass Vector1d(PlainObjectBase):
pass
cdef cppclass Vector2d(PlainObjectBase):
pass
cdef cppclass Vector3d(PlainObjectBase):
pass
cdef cppclass Vector4d(PlainObjectBase):
pass
cdef cppclass VectorXd(PlainObjectBase):
pass
cdef cppclass RowVector1d(PlainObjectBase):
pass
cdef cppclass RowVector2d(PlainObjectBase):
pass
cdef cppclass RowVector3d(PlainObjectBase):
pass
cdef cppclass RowVector4d(PlainObjectBase):
pass
cdef cppclass RowVectorXd(PlainObjectBase):
pass
cdef cppclass Matrix1d(PlainObjectBase):
pass
cdef cppclass Matrix2d(PlainObjectBase):
pass
cdef cppclass Matrix3d(PlainObjectBase):
pass
cdef cppclass Matrix4d(PlainObjectBase):
pass
cdef cppclass MatrixXd(PlainObjectBase):
pass
cdef cppclass Vector1cf(PlainObjectBase):
pass
cdef cppclass Vector2cf(PlainObjectBase):
pass
cdef cppclass Vector3cf(PlainObjectBase):
pass
cdef cppclass Vector4cf(PlainObjectBase):
pass
cdef cppclass VectorXcf(PlainObjectBase):
pass
cdef cppclass RowVector1cf(PlainObjectBase):
pass
cdef cppclass RowVector2cf(PlainObjectBase):
pass
cdef cppclass RowVector3cf(PlainObjectBase):
pass
cdef cppclass RowVector4cf(PlainObjectBase):
pass
cdef cppclass RowVectorXcf(PlainObjectBase):
pass
cdef cppclass Matrix1cf(PlainObjectBase):
pass
cdef cppclass Matrix2cf(PlainObjectBase):
pass
cdef cppclass Matrix3cf(PlainObjectBase):
pass
cdef cppclass Matrix4cf(PlainObjectBase):
pass
cdef cppclass MatrixXcf(PlainObjectBase):
pass
cdef cppclass Vector1cd(PlainObjectBase):
pass
cdef cppclass Vector2cd(PlainObjectBase):
pass
cdef cppclass Vector3cd(PlainObjectBase):
pass
cdef cppclass Vector4cd(PlainObjectBase):
pass
cdef cppclass VectorXcd(PlainObjectBase):
pass
cdef cppclass RowVector1cd(PlainObjectBase):
pass
cdef cppclass RowVector2cd(PlainObjectBase):
pass
cdef cppclass RowVector3cd(PlainObjectBase):
pass
cdef cppclass RowVector4cd(PlainObjectBase):
pass
cdef cppclass RowVectorXcd(PlainObjectBase):
pass
cdef cppclass Matrix1cd(PlainObjectBase):
pass
cdef cppclass Matrix2cd(PlainObjectBase):
pass
cdef cppclass Matrix3cd(PlainObjectBase):
pass
cdef cppclass Matrix4cd(PlainObjectBase):
pass
cdef cppclass MatrixXcd(PlainObjectBase):
pass
cdef cppclass Array22i(PlainObjectBase):
pass
cdef cppclass Array23i(PlainObjectBase):
pass
cdef cppclass Array24i(PlainObjectBase):
pass
cdef cppclass Array2Xi(PlainObjectBase):
pass
cdef cppclass Array32i(PlainObjectBase):
pass
cdef cppclass Array33i(PlainObjectBase):
pass
cdef cppclass Array34i(PlainObjectBase):
pass
cdef cppclass Array3Xi(PlainObjectBase):
pass
cdef cppclass Array42i(PlainObjectBase):
pass
cdef cppclass Array43i(PlainObjectBase):
pass
cdef cppclass Array44i(PlainObjectBase):
pass
cdef cppclass Array4Xi(PlainObjectBase):
pass
cdef cppclass ArrayX2i(PlainObjectBase):
pass
cdef cppclass ArrayX3i(PlainObjectBase):
pass
cdef cppclass ArrayX4i(PlainObjectBase):
pass
cdef cppclass ArrayXXi(PlainObjectBase):
pass
cdef cppclass Array2i(PlainObjectBase):
pass
cdef cppclass Array3i(PlainObjectBase):
pass
cdef cppclass Array4i(PlainObjectBase):
pass
cdef cppclass ArrayXi(PlainObjectBase):
pass
cdef cppclass Array22f(PlainObjectBase):
pass
cdef cppclass Array23f(PlainObjectBase):
pass
cdef cppclass Array24f(PlainObjectBase):
pass
cdef cppclass Array2Xf(PlainObjectBase):
pass
cdef cppclass Array32f(PlainObjectBase):
pass
cdef cppclass Array33f(PlainObjectBase):
pass
cdef cppclass Array34f(PlainObjectBase):
pass
cdef cppclass Array3Xf(PlainObjectBase):
pass
cdef cppclass Array42f(PlainObjectBase):
pass
cdef cppclass Array43f(PlainObjectBase):
pass
cdef cppclass Array44f(PlainObjectBase):
pass
cdef cppclass Array4Xf(PlainObjectBase):
pass
cdef cppclass ArrayX2f(PlainObjectBase):
pass
cdef cppclass ArrayX3f(PlainObjectBase):
pass
cdef cppclass ArrayX4f(PlainObjectBase):
pass
cdef cppclass ArrayXXf(PlainObjectBase):
pass
cdef cppclass Array2f(PlainObjectBase):
pass
cdef cppclass Array3f(PlainObjectBase):
pass
cdef cppclass Array4f(PlainObjectBase):
pass
cdef cppclass ArrayXf(PlainObjectBase):
pass
cdef cppclass Array22d(PlainObjectBase):
pass
cdef cppclass Array23d(PlainObjectBase):
pass
cdef cppclass Array24d(PlainObjectBase):
pass
cdef cppclass Array2Xd(PlainObjectBase):
pass
cdef cppclass Array32d(PlainObjectBase):
pass
cdef cppclass Array33d(PlainObjectBase):
pass
cdef cppclass Array34d(PlainObjectBase):
pass
cdef cppclass Array3Xd(PlainObjectBase):
pass
cdef cppclass Array42d(PlainObjectBase):
pass
cdef cppclass Array43d(PlainObjectBase):
pass
cdef cppclass Array44d(PlainObjectBase):
pass
cdef cppclass Array4Xd(PlainObjectBase):
pass
cdef cppclass ArrayX2d(PlainObjectBase):
pass
cdef cppclass ArrayX3d(PlainObjectBase):
pass
cdef cppclass ArrayX4d(PlainObjectBase):
pass
cdef cppclass ArrayXXd(PlainObjectBase):
pass
cdef cppclass Array2d(PlainObjectBase):
pass
cdef cppclass Array3d(PlainObjectBase):
pass
cdef cppclass Array4d(PlainObjectBase):
pass
cdef cppclass ArrayXd(PlainObjectBase):
pass
cdef cppclass Array22cf(PlainObjectBase):
pass
cdef cppclass Array23cf(PlainObjectBase):
pass
cdef cppclass Array24cf(PlainObjectBase):
pass
cdef cppclass Array2Xcf(PlainObjectBase):
pass
cdef cppclass Array32cf(PlainObjectBase):
pass
cdef cppclass Array33cf(PlainObjectBase):
pass
cdef cppclass Array34cf(PlainObjectBase):
pass
cdef cppclass Array3Xcf(PlainObjectBase):
pass
cdef cppclass Array42cf(PlainObjectBase):
pass
cdef cppclass Array43cf(PlainObjectBase):
pass
cdef cppclass Array44cf(PlainObjectBase):
pass
cdef cppclass Array4Xcf(PlainObjectBase):
pass
cdef cppclass ArrayX2cf(PlainObjectBase):
pass
cdef cppclass ArrayX3cf(PlainObjectBase):
pass
cdef cppclass ArrayX4cf(PlainObjectBase):
pass
cdef cppclass ArrayXXcf(PlainObjectBase):
pass
cdef cppclass Array2cf(PlainObjectBase):
pass
cdef cppclass Array3cf(PlainObjectBase):
pass
cdef cppclass Array4cf(PlainObjectBase):
pass
cdef cppclass ArrayXcf(PlainObjectBase):
pass
cdef cppclass Array22cd(PlainObjectBase):
pass
cdef cppclass Array23cd(PlainObjectBase):
pass
cdef cppclass Array24cd(PlainObjectBase):
pass
cdef cppclass Array2Xcd(PlainObjectBase):
pass
cdef cppclass Array32cd(PlainObjectBase):
pass
cdef cppclass Array33cd(PlainObjectBase):
pass
cdef cppclass Array34cd(PlainObjectBase):
pass
cdef cppclass Array3Xcd(PlainObjectBase):
pass
cdef cppclass Array42cd(PlainObjectBase):
pass
cdef cppclass Array43cd(PlainObjectBase):
pass
cdef cppclass Array44cd(PlainObjectBase):
pass
cdef cppclass Array4Xcd(PlainObjectBase):
pass
cdef cppclass ArrayX2cd(PlainObjectBase):
pass
cdef cppclass ArrayX3cd(PlainObjectBase):
pass
cdef cppclass ArrayX4cd(PlainObjectBase):
pass
cdef cppclass ArrayXXcd(PlainObjectBase):
pass
cdef cppclass Array2cd(PlainObjectBase):
pass
cdef cppclass Array3cd(PlainObjectBase):
pass
cdef cppclass Array4cd(PlainObjectBase):
pass
cdef cppclass ArrayXcd(PlainObjectBase):
pass

1
cython/gtsam_eigency/core.pyx
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@ -1 +0,0 @@

504
cython/gtsam_eigency/eigency_cpp.h
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@ -1,504 +0,0 @@
#include <Eigen/Dense>
#include <iostream>
#include <stdexcept>
#include <complex>
typedef ::std::complex< double > __pyx_t_double_complex;
typedef ::std::complex< float > __pyx_t_float_complex;
#include "conversions_api.h"
#ifndef EIGENCY_CPP
#define EIGENCY_CPP
namespace eigency {
template<typename Scalar>
inline PyArrayObject *_ndarray_view(Scalar *, long rows, long cols, bool is_row_major, long outer_stride=0, long inner_stride=0);
template<typename Scalar>
inline PyArrayObject *_ndarray_copy(const Scalar *, long rows, long cols, bool is_row_major, long outer_stride=0, long inner_stride=0);
// Strides:
// Eigen and numpy differ in their way of dealing with strides. Eigen has the concept of outer and
// inner strides, which are dependent on whether the array/matrix is row-major of column-major:
// Inner stride: denotes the offset between succeeding elements in each row (row-major) or column (column-major).
// Outer stride: denotes the offset between succeeding rows (row-major) or succeeding columns (column-major).
// In contrast, numpy's stride is simply a measure of how fast each dimension should be incremented.
// Consequently, a switch in numpy storage order from row-major to column-major involves a switch
// in strides, while it does not affect the stride in Eigen.
template<>
inline PyArrayObject *_ndarray_view<double>(double *data, long rows, long cols, bool is_row_major, long outer_stride, long inner_stride) {
if (is_row_major) {
// Eigen row-major mode: row_stride=outer_stride, and col_stride=inner_stride
// If no stride is given, the row_stride is set to the number of columns.
return ndarray_double_C(data, rows, cols, outer_stride>0?outer_stride:cols, inner_stride>0?inner_stride:1);
} else {
// Eigen column-major mode: row_stride=outer_stride, and col_stride=inner_stride
// If no stride is given, the cow_stride is set to the number of rows.
return ndarray_double_F(data, rows, cols, inner_stride>0?inner_stride:1, outer_stride>0?outer_stride:rows);
}
}
template<>
inline PyArrayObject *_ndarray_copy<double>(const double *data, long rows, long cols, bool is_row_major, long outer_stride, long inner_stride) {
if (is_row_major)
return ndarray_copy_double_C(data, rows, cols, outer_stride>0?outer_stride:cols, inner_stride>0?inner_stride:1);
else
return ndarray_copy_double_F(data, rows, cols, inner_stride>0?inner_stride:1, outer_stride>0?outer_stride:rows);
}
template<>
inline PyArrayObject *_ndarray_view<float>(float *data, long rows, long cols, bool is_row_major, long outer_stride, long inner_stride) {
if (is_row_major)
return ndarray_float_C(data, rows, cols, outer_stride>0?outer_stride:cols, inner_stride>0?inner_stride:1);
else
return ndarray_float_F(data, rows, cols, inner_stride>0?inner_stride:1, outer_stride>0?outer_stride:rows);
}
template<>
inline PyArrayObject *_ndarray_copy<float>(const float *data, long rows, long cols, bool is_row_major, long outer_stride, long inner_stride) {
if (is_row_major)
return ndarray_copy_float_C(data, rows, cols, outer_stride>0?outer_stride:cols, inner_stride>0?inner_stride:1);
else
return ndarray_copy_float_F(data, rows, cols, inner_stride>0?inner_stride:1, outer_stride>0?outer_stride:rows);
}
template<>
inline PyArrayObject *_ndarray_view<long>(long *data, long rows, long cols, bool is_row_major, long outer_stride, long inner_stride) {
if (is_row_major)
return ndarray_long_C(data, rows, cols, outer_stride>0?outer_stride:cols, inner_stride>0?inner_stride:1);
else
return ndarray_long_F(data, rows, cols, inner_stride>0?inner_stride:1, outer_stride>0?outer_stride:rows);
}
template<>
inline PyArrayObject *_ndarray_copy<long>(const long *data, long rows, long cols, bool is_row_major, long outer_stride, long inner_stride) {
if (is_row_major)
return ndarray_copy_long_C(data, rows, cols, outer_stride>0?outer_stride:cols, inner_stride>0?inner_stride:1);
else
return ndarray_copy_long_F(data, rows, cols, inner_stride>0?inner_stride:1, outer_stride>0?outer_stride:rows);
}
template<>
inline PyArrayObject *_ndarray_view<unsigned long>(unsigned long *data, long rows, long cols, bool is_row_major, long outer_stride, long inner_stride) {
if (is_row_major)
return ndarray_ulong_C(data, rows, cols, outer_stride>0?outer_stride:cols, inner_stride>0?inner_stride:1);
else
return ndarray_ulong_F(data, rows, cols, inner_stride>0?inner_stride:1, outer_stride>0?outer_stride:rows);
}
template<>
inline PyArrayObject *_ndarray_copy<unsigned long>(const unsigned long *data, long rows, long cols, bool is_row_major, long outer_stride, long inner_stride) {
if (is_row_major)
return ndarray_copy_ulong_C(data, rows, cols, outer_stride>0?outer_stride:cols, inner_stride>0?inner_stride:1);
else
return ndarray_copy_ulong_F(data, rows, cols, inner_stride>0?inner_stride:1, outer_stride>0?outer_stride:rows);
}
template<>
inline PyArrayObject *_ndarray_view<int>(int *data, long rows, long cols, bool is_row_major, long outer_stride, long inner_stride) {
if (is_row_major)
return ndarray_int_C(data, rows, cols, outer_stride>0?outer_stride:cols, inner_stride>0?inner_stride:1);
else
return ndarray_int_F(data, rows, cols, inner_stride>0?inner_stride:1, outer_stride>0?outer_stride:rows);
}
template<>
inline PyArrayObject *_ndarray_copy<int>(const int *data, long rows, long cols, bool is_row_major, long outer_stride, long inner_stride) {
if (is_row_major)
return ndarray_copy_int_C(data, rows, cols, outer_stride>0?outer_stride:cols, inner_stride>0?inner_stride:1);
else
return ndarray_copy_int_F(data, rows, cols, inner_stride>0?inner_stride:1, outer_stride>0?outer_stride:rows);
}
template<>
inline PyArrayObject *_ndarray_view<unsigned int>(unsigned int *data, long rows, long cols, bool is_row_major, long outer_stride, long inner_stride) {
if (is_row_major)
return ndarray_uint_C(data, rows, cols, outer_stride>0?outer_stride:cols, inner_stride>0?inner_stride:1);
else
return ndarray_uint_F(data, rows, cols, inner_stride>0?inner_stride:1, outer_stride>0?outer_stride:rows);
}
template<>
inline PyArrayObject *_ndarray_copy<unsigned int>(const unsigned int *data, long rows, long cols, bool is_row_major, long outer_stride, long inner_stride) {
if (is_row_major)
return ndarray_copy_uint_C(data, rows, cols, outer_stride>0?outer_stride:cols, inner_stride>0?inner_stride:1);
else
return ndarray_copy_uint_F(data, rows, cols, inner_stride>0?inner_stride:1, outer_stride>0?outer_stride:rows);
}
template<>
inline PyArrayObject *_ndarray_view<short>(short *data, long rows, long cols, bool is_row_major, long outer_stride, long inner_stride) {
if (is_row_major)
return ndarray_short_C(data, rows, cols, outer_stride>0?outer_stride:cols, inner_stride>0?inner_stride:1);
else
return ndarray_short_F(data, rows, cols, inner_stride>0?inner_stride:1, outer_stride>0?outer_stride:rows);
}
template<>
inline PyArrayObject *_ndarray_copy<short>(const short *data, long rows, long cols, bool is_row_major, long outer_stride, long inner_stride) {
if (is_row_major)
return ndarray_copy_short_C(data, rows, cols, outer_stride>0?outer_stride:cols, inner_stride>0?inner_stride:1);
else
return ndarray_copy_short_F(data, rows, cols, inner_stride>0?inner_stride:1, outer_stride>0?outer_stride:rows);
}
template<>
inline PyArrayObject *_ndarray_view<unsigned short>(unsigned short *data, long rows, long cols, bool is_row_major, long outer_stride, long inner_stride) {
if (is_row_major)
return ndarray_ushort_C(data, rows, cols, outer_stride>0?outer_stride:cols, inner_stride>0?inner_stride:1);
else
return ndarray_ushort_F(data, rows, cols, inner_stride>0?inner_stride:1, outer_stride>0?outer_stride:rows);
}
template<>
inline PyArrayObject *_ndarray_copy<unsigned short>(const unsigned short *data, long rows, long cols, bool is_row_major, long outer_stride, long inner_stride) {
if (is_row_major)
return ndarray_copy_ushort_C(data, rows, cols, outer_stride>0?outer_stride:cols, inner_stride>0?inner_stride:1);
else
return ndarray_copy_ushort_F(data, rows, cols, inner_stride>0?inner_stride:1, outer_stride>0?outer_stride:rows);
}
template<>
inline PyArrayObject *_ndarray_view<signed char>(signed char *data, long rows, long cols, bool is_row_major, long outer_stride, long inner_stride) {
if (is_row_major)
return ndarray_schar_C(data, rows, cols, outer_stride>0?outer_stride:cols, inner_stride>0?inner_stride:1);
else
return ndarray_schar_F(data, rows, cols, inner_stride>0?inner_stride:1, outer_stride>0?outer_stride:rows);
}
template<>
inline PyArrayObject *_ndarray_copy<signed char>(const signed char *data, long rows, long cols, bool is_row_major, long outer_stride, long inner_stride) {
if (is_row_major)
return ndarray_copy_schar_C(data, rows, cols, outer_stride>0?outer_stride:cols, inner_stride>0?inner_stride:1);
else
return ndarray_copy_schar_F(data, rows, cols, inner_stride>0?inner_stride:1, outer_stride>0?outer_stride:rows);
}
template<>
inline PyArrayObject *_ndarray_view<unsigned char>(unsigned char *data, long rows, long cols, bool is_row_major, long outer_stride, long inner_stride) {
if (is_row_major)
return ndarray_uchar_C(data, rows, cols, outer_stride>0?outer_stride:cols, inner_stride>0?inner_stride:1);
else
return ndarray_uchar_F(data, rows, cols, inner_stride>0?inner_stride:1, outer_stride>0?outer_stride:rows);
}
template<>
inline PyArrayObject *_ndarray_copy<unsigned char>(const unsigned char *data, long rows, long cols, bool is_row_major, long outer_stride, long inner_stride) {
if (is_row_major)
return ndarray_copy_uchar_C(data, rows, cols, outer_stride>0?outer_stride:cols, inner_stride>0?inner_stride:1);
else
return ndarray_copy_uchar_F(data, rows, cols, inner_stride>0?inner_stride:1, outer_stride>0?outer_stride:rows);
}
template<>
inline PyArrayObject *_ndarray_view<std::complex<double> >(std::complex<double> *data, long rows, long cols, bool is_row_major, long outer_stride, long inner_stride) {
if (is_row_major)
return ndarray_complex_double_C(data, rows, cols, outer_stride>0?outer_stride:cols, inner_stride>0?inner_stride:1);
else
return ndarray_complex_double_F(data, rows, cols, inner_stride>0?inner_stride:1, outer_stride>0?outer_stride:rows);
}
template<>
inline PyArrayObject *_ndarray_copy<std::complex<double> >(const std::complex<double> *data, long rows, long cols, bool is_row_major, long outer_stride, long inner_stride) {
if (is_row_major)
return ndarray_copy_complex_double_C(data, rows, cols, outer_stride>0?outer_stride:cols, inner_stride>0?inner_stride:1);
else
return ndarray_copy_complex_double_F(data, rows, cols, inner_stride>0?inner_stride:1, outer_stride>0?outer_stride:rows);
}
template<>
inline PyArrayObject *_ndarray_view<std::complex<float> >(std::complex<float> *data, long rows, long cols, bool is_row_major, long outer_stride, long inner_stride) {
if (is_row_major)
return ndarray_complex_float_C(data, rows, cols, outer_stride>0?outer_stride:cols, inner_stride>0?inner_stride:1);
else
return ndarray_complex_float_F(data, rows, cols, inner_stride>0?inner_stride:1, outer_stride>0?outer_stride:rows);
}
template<>
inline PyArrayObject *_ndarray_copy<std::complex<float> >(const std::complex<float> *data, long rows, long cols, bool is_row_major, long outer_stride, long inner_stride) {
if (is_row_major)
return ndarray_copy_complex_float_C(data, rows, cols, outer_stride>0?outer_stride:cols, inner_stride>0?inner_stride:1);
else
return ndarray_copy_complex_float_F(data, rows, cols, inner_stride>0?inner_stride:1, outer_stride>0?outer_stride:rows);
}
template <typename Derived>
inline PyArrayObject *ndarray(Eigen::PlainObjectBase<Derived> &m) {
import_gtsam_eigency__conversions();
return _ndarray_view(m.data(), m.rows(), m.cols(), m.IsRowMajor);
}
// If C++11 is available, check if m is an r-value reference, in
// which case a copy should always be made
#if __cplusplus >= 201103L
template <typename Derived>
inline PyArrayObject *ndarray(Eigen::PlainObjectBase<Derived> &&m) {
import_gtsam_eigency__conversions();
return _ndarray_copy(m.data(), m.rows(), m.cols(), m.IsRowMajor);
}
#endif
template <typename Derived>
inline PyArrayObject *ndarray(const Eigen::PlainObjectBase<Derived> &m) {
import_gtsam_eigency__conversions();
return _ndarray_copy(m.data(), m.rows(), m.cols(), m.IsRowMajor);
}
template <typename Derived>
inline PyArrayObject *ndarray_view(Eigen::PlainObjectBase<Derived> &m) {
import_gtsam_eigency__conversions();
return _ndarray_view(m.data(), m.rows(), m.cols(), m.IsRowMajor);
}
template <typename Derived>
inline PyArrayObject *ndarray_view(const Eigen::PlainObjectBase<Derived> &m) {
import_gtsam_eigency__conversions();
return _ndarray_view(const_cast<typename Derived::Scalar*>(m.data()), m.rows(), m.cols(), m.IsRowMajor);
}
template <typename Derived>
inline PyArrayObject *ndarray_copy(const Eigen::PlainObjectBase<Derived> &m) {
import_gtsam_eigency__conversions();
return _ndarray_copy(m.data(), m.rows(), m.cols(), m.IsRowMajor);
}
template <typename Derived, int MapOptions, typename Stride>
inline PyArrayObject *ndarray(Eigen::Map<Derived, MapOptions, Stride> &m) {
import_gtsam_eigency__conversions();
return _ndarray_view(m.data(), m.rows(), m.cols(), m.IsRowMajor, m.outerStride(), m.innerStride());
}
template <typename Derived, int MapOptions, typename Stride>
inline PyArrayObject *ndarray(const Eigen::Map<Derived, MapOptions, Stride> &m) {
import_gtsam_eigency__conversions();
// Since this is a map, we assume that ownership is correctly taken care
// of, and we avoid taking a copy
return _ndarray_view(const_cast<typename Derived::Scalar*>(m.data()), m.rows(), m.cols(), m.IsRowMajor, m.outerStride(), m.innerStride());
}
template <typename Derived, int MapOptions, typename Stride>
inline PyArrayObject *ndarray_view(Eigen::Map<Derived, MapOptions, Stride> &m) {
import_gtsam_eigency__conversions();
return _ndarray_view(m.data(), m.rows(), m.cols(), m.IsRowMajor, m.outerStride(), m.innerStride());
}
template <typename Derived, int MapOptions, typename Stride>
inline PyArrayObject *ndarray_view(const Eigen::Map<Derived, MapOptions, Stride> &m) {
import_gtsam_eigency__conversions();
return _ndarray_view(const_cast<typename Derived::Scalar*>(m.data()), m.rows(), m.cols(), m.IsRowMajor, m.outerStride(), m.innerStride());
}
template <typename Derived, int MapOptions, typename Stride>
inline PyArrayObject *ndarray_copy(const Eigen::Map<Derived, MapOptions, Stride> &m) {
import_gtsam_eigency__conversions();
return _ndarray_copy(m.data(), m.rows(), m.cols(), m.IsRowMajor, m.outerStride(), m.innerStride());
}
template <typename MatrixType,
int _MapOptions = Eigen::Unaligned,
typename _StrideType=Eigen::Stride<0,0> >
class MapBase: public Eigen::Map<MatrixType, _MapOptions, _StrideType> {
public:
typedef Eigen::Map<MatrixType, _MapOptions, _StrideType> Base;
typedef typename Base::Scalar Scalar;
MapBase(Scalar* data,
long rows,
long cols,
_StrideType stride=_StrideType())
: Base(data,
// If both dimensions are dynamic or dimensions match, accept dimensions as they are
((Base::RowsAtCompileTime==Eigen::Dynamic && Base::ColsAtCompileTime==Eigen::Dynamic) ||
(Base::RowsAtCompileTime==rows && Base::ColsAtCompileTime==cols))
? rows
// otherwise, test if swapping them makes them fit
: ((Base::RowsAtCompileTime==cols || Base::ColsAtCompileTime==rows)
? cols
: rows),
((Base::RowsAtCompileTime==Eigen::Dynamic && Base::ColsAtCompileTime==Eigen::Dynamic) ||
(Base::RowsAtCompileTime==rows && Base::ColsAtCompileTime==cols))
? cols
: ((Base::RowsAtCompileTime==cols || Base::ColsAtCompileTime==rows)
? rows
: cols),
stride
) {}
MapBase &operator=(const MatrixType &other) {
Base::operator=(other);
return *this;
}
virtual ~MapBase() { }
};
template <template<class,int,int,int,int,int> class EigencyDenseBase,
typename Scalar,
int _Rows, int _Cols,
int _Options = Eigen::AutoAlign |
#if defined(__GNUC__) && __GNUC__==3 && __GNUC_MINOR__==4
// workaround a bug in at least gcc 3.4.6
// the innermost ?: ternary operator is misparsed. We write it slightly
// differently and this makes gcc 3.4.6 happy, but it's ugly.
// The error would only show up with EIGEN_DEFAULT_TO_ROW_MAJOR is defined
// (when EIGEN_DEFAULT_MATRIX_STORAGE_ORDER_OPTION is RowMajor)
( (_Rows==1 && _Cols!=1) ? Eigen::RowMajor
// EIGEN_DEFAULT_MATRIX_STORAGE_ORDER_OPTION contains explicit namespace since Eigen 3.1.19
#if EIGEN_VERSION_AT_LEAST(3,2,90)
: !(_Cols==1 && _Rows!=1) ? EIGEN_DEFAULT_MATRIX_STORAGE_ORDER_OPTION
#else
: !(_Cols==1 && _Rows!=1) ? Eigen::EIGEN_DEFAULT_MATRIX_STORAGE_ORDER_OPTION
#endif
: ColMajor ),
#else
( (_Rows==1 && _Cols!=1) ? Eigen::RowMajor
: (_Cols==1 && _Rows!=1) ? Eigen::ColMajor
// EIGEN_DEFAULT_MATRIX_STORAGE_ORDER_OPTION contains explicit namespace since Eigen 3.1.19
#if EIGEN_VERSION_AT_LEAST(3,2,90)
: EIGEN_DEFAULT_MATRIX_STORAGE_ORDER_OPTION ),
#else
: Eigen::EIGEN_DEFAULT_MATRIX_STORAGE_ORDER_OPTION ),
#endif
#endif
int _MapOptions = Eigen::Unaligned,
int _StrideOuter=0, int _StrideInner=0,
int _MaxRows = _Rows,
int _MaxCols = _Cols>
class FlattenedMap: public MapBase<EigencyDenseBase<Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>, _MapOptions, Eigen::Stride<_StrideOuter, _StrideInner> > {
public:
typedef MapBase<EigencyDenseBase<Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>, _MapOptions, Eigen::Stride<_StrideOuter, _StrideInner> > Base;
FlattenedMap()
: Base(NULL, 0, 0),
object_(NULL) {}
FlattenedMap(Scalar *data, long rows, long cols, long outer_stride=0, long inner_stride=0)
: Base(data, rows, cols,
Eigen::Stride<_StrideOuter, _StrideInner>(outer_stride, inner_stride)),
object_(NULL) {
}
FlattenedMap(PyArrayObject *object)
: Base((Scalar *)((PyArrayObject*)object)->data,
// : Base(_from_numpy<Scalar>((PyArrayObject*)object),
(((PyArrayObject*)object)->nd == 2) ? ((PyArrayObject*)object)->dimensions[0] : 1,
(((PyArrayObject*)object)->nd == 2) ? ((PyArrayObject*)object)->dimensions[1] : ((PyArrayObject*)object)->dimensions[0],
Eigen::Stride<_StrideOuter, _StrideInner>(_StrideOuter != Eigen::Dynamic ? _StrideOuter : (((PyArrayObject*)object)->nd == 2) ? ((PyArrayObject*)object)->dimensions[0] : 1,
_StrideInner != Eigen::Dynamic ? _StrideInner : (((PyArrayObject*)object)->nd == 2) ? ((PyArrayObject*)object)->dimensions[1] : ((PyArrayObject*)object)->dimensions[0])),
object_(object) {
if (((PyObject*)object != Py_None) && !PyArray_ISONESEGMENT(object))
throw std::invalid_argument("Numpy array must be a in one contiguous segment to be able to be transferred to a Eigen Map.");
Py_XINCREF(object_);
}
FlattenedMap &operator=(const FlattenedMap &other) {
if (other.object_) {
new (this) FlattenedMap(other.object_);
} else {
// Replace the memory that we point to (not a memory allocation)
new (this) FlattenedMap(const_cast<Scalar*>(other.data()),
other.rows(),
other.cols(),
other.outerStride(),
other.innerStride());
}
return *this;
}
operator Base() const {
return static_cast<Base>(*this);
}
operator Base&() const {
return static_cast<Base&>(*this);
}
operator EigencyDenseBase<Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>() const {
return EigencyDenseBase<Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>(static_cast<Base>(*this));
}
virtual ~FlattenedMap() {
Py_XDECREF(object_);
}
private:
PyArrayObject * const object_;
};
template <typename MatrixType>
class Map: public MapBase<MatrixType> {
public:
typedef MapBase<MatrixType> Base;
typedef typename MatrixType::Scalar Scalar;
enum {
RowsAtCompileTime = Base::Base::RowsAtCompileTime,
ColsAtCompileTime = Base::Base::ColsAtCompileTime
};
Map()
: Base(NULL,
(RowsAtCompileTime == Eigen::Dynamic) ? 0 : RowsAtCompileTime,
(ColsAtCompileTime == Eigen::Dynamic) ? 0 : ColsAtCompileTime),
object_(NULL) {
}
Map(Scalar *data, long rows, long cols)
: Base(data, rows, cols),
object_(NULL) {}
Map(PyArrayObject *object)
: Base((PyObject*)object == Py_None? NULL: (Scalar *)object->data,
// ROW: If array is in row-major order, transpose (see README)
(PyObject*)object == Py_None? 0 :
(!PyArray_IS_F_CONTIGUOUS(object)
? ((object->nd == 1)
? 1 // ROW: If 1D row-major numpy array, set to 1 (row vector)
: object->dimensions[1])
: object->dimensions[0]),
// COLUMN: If array is in row-major order: transpose (see README)
(PyObject*)object == Py_None? 0 :
(!PyArray_IS_F_CONTIGUOUS(object)
? object->dimensions[0]
: ((object->nd == 1)
? 1 // COLUMN: If 1D col-major numpy array, set to length (column vector)
: object->dimensions[1]))),
object_(object) {
if (((PyObject*)object != Py_None) && !PyArray_ISONESEGMENT(object))
throw std::invalid_argument("Numpy array must be a in one contiguous segment to be able to be transferred to a Eigen Map.");
Py_XINCREF(object_);
}
Map &operator=(const Map &other) {
if (other.object_) {
new (this) Map(other.object_);
} else {
// Replace the memory that we point to (not a memory allocation)
new (this) Map(const_cast<Scalar*>(other.data()),
other.rows(),
other.cols());
}
return *this;
}
Map &operator=(const MatrixType &other) {
MapBase<MatrixType>::operator=(other);
return *this;
}
operator Base() const {
return static_cast<Base>(*this);
}
operator Base&() const {
return static_cast<Base&>(*this);
}
operator MatrixType() const {
return MatrixType(static_cast<Base>(*this));
}
virtual ~Map() {
Py_XDECREF(object_);
}
private:
PyArrayObject * const object_;
};
}
#endif

3
cython/requirements.txt
View File

@ -1,3 +0,0 @@
Cython>=0.25.2
backports_abc>=0.5
numpy>=1.11.0

2
examples/IMUKittiExampleGPS.cpp
View File

@ -287,7 +287,7 @@ int main(int argc, char* argv[]) {
new_values.insert(current_pose_key, gps_pose);
printf("################ POSE INCLUDED AT TIME %lf ################\n", t);
gps_pose.translation().print();
cout << gps_pose.translation();
printf("\n\n");
} else {
new_values.insert(current_pose_key, current_pose_global);

2
gtsam/CMakeLists.txt
View File

@ -217,5 +217,5 @@ if (GTSAM_INSTALL_MATLAB_TOOLBOX)
endif()
# Wrap
wrap_and_install_library(../gtsam.h "${GTSAM_ADDITIONAL_LIBRARIES}" "" "${mexFlags}")
wrap_and_install_library(gtsam.i "${GTSAM_ADDITIONAL_LIBRARIES}" "" "${mexFlags}")
endif ()

29
gtsam.h → gtsam/gtsam.i
View File

@ -618,6 +618,9 @@ class SOn {
// Other methods
Vector vec() const;
Matrix matrix() const;
// enabling serialization functionality
void serialize() const;
};
#include <gtsam/geometry/Rot3.h>
@ -2171,7 +2174,11 @@ class Values {
// void insert(size_t j, const gtsam::Value& value);
// void update(size_t j, const gtsam::Value& val);
// gtsam::Value at(size_t j) const;
// The order is important: Vector has to precede Point2/Point3 so `atVector`
// can work for those fixed-size vectors.
void insert(size_t j, Vector vector);
void insert(size_t j, Matrix matrix);
void insert(size_t j, const gtsam::Point2& point2);
void insert(size_t j, const gtsam::Point3& point3);
void insert(size_t j, const gtsam::Rot2& rot2);
@ -2188,8 +2195,6 @@ class Values {
void insert(size_t j, const gtsam::PinholeCameraCal3_S2& simple_camera);
void insert(size_t j, const gtsam::imuBias::ConstantBias& constant_bias);
void insert(size_t j, const gtsam::NavState& nav_state);
void insert(size_t j, Vector vector);
void insert(size_t j, Matrix matrix);
void update(size_t j, const gtsam::Point2& point2);
void update(size_t j, const gtsam::Point3& point3);
@ -2797,16 +2802,16 @@ class SfmData {
string findExampleDataFile(string name);
pair<gtsam::NonlinearFactorGraph*, gtsam::Values*> load2D(string filename,
gtsam::noiseModel::Diagonal* model, int maxID, bool addNoise, bool smart);
gtsam::noiseModel::Diagonal* model, int maxIndex, bool addNoise, bool smart);
pair<gtsam::NonlinearFactorGraph*, gtsam::Values*> load2D(string filename,
gtsam::noiseModel::Diagonal* model, int maxID, bool addNoise);
gtsam::noiseModel::Diagonal* model, int maxIndex, bool addNoise);
pair<gtsam::NonlinearFactorGraph*, gtsam::Values*> load2D(string filename,
gtsam::noiseModel::Diagonal* model, int maxID);
gtsam::noiseModel::Diagonal* model, int maxIndex);
pair<gtsam::NonlinearFactorGraph*, gtsam::Values*> load2D(string filename,
gtsam::noiseModel::Diagonal* model);
pair<gtsam::NonlinearFactorGraph*, gtsam::Values*> load2D(string filename);
pair<gtsam::NonlinearFactorGraph*, gtsam::Values*> load2D_robust(string filename,
gtsam::noiseModel::Base* model);
gtsam::noiseModel::Base* model, int maxIndex);
void save2D(const gtsam::NonlinearFactorGraph& graph,
const gtsam::Values& config, gtsam::noiseModel::Diagonal* model,
string filename);
@ -2816,8 +2821,8 @@ class BetweenFactorPose3s
{
BetweenFactorPose3s();
size_t size() const;
gtsam::BetweenFactorPose3* at(size_t i) const;
void push_back(const gtsam::BetweenFactorPose3* factor);
gtsam::BetweenFactor<gtsam::Pose3>* at(size_t i) const;
void push_back(const gtsam::BetweenFactor<gtsam::Pose3>* factor);
};
#include <gtsam/slam/InitializePose3.h>
@ -2877,9 +2882,9 @@ virtual class FrobeniusBetweenFactor : gtsam::NoiseModelFactor {
#include <gtsam/sfm/ShonanFactor.h>
virtual class ShonanFactor3 : gtsam::NoiseModelFactor {
ShonanFactor(size_t key1, size_t key2, const gtsam::Rot3 &R12,
ShonanFactor3(size_t key1, size_t key2, const gtsam::Rot3 &R12,
size_t p);
ShonanFactor(size_t key1, size_t key2, const gtsam::Rot3 &R12,
ShonanFactor3(size_t key1, size_t key2, const gtsam::Rot3 &R12,
size_t p, gtsam::noiseModel::Base *model);
Vector evaluateError(const gtsam::SOn &Q1, const gtsam::SOn &Q2);
};
@ -2955,6 +2960,7 @@ class ShonanAveraging2 {
// Advanced API
gtsam::NonlinearFactorGraph buildGraphAt(size_t p) const;
gtsam::Values initializeRandomlyAt(size_t p) const;
double costAt(size_t p, const gtsam::Values& values) const;
pair<double, Vector> computeMinEigenVector(const gtsam::Values& values) const;
bool checkOptimality(const gtsam::Values& values) const;
@ -2999,6 +3005,7 @@ class ShonanAveraging3 {
// Advanced API
gtsam::NonlinearFactorGraph buildGraphAt(size_t p) const;
gtsam::Values initializeRandomlyAt(size_t p) const;
double costAt(size_t p, const gtsam::Values& values) const;
pair<double, Vector> computeMinEigenVector(const gtsam::Values& values) const;
bool checkOptimality(const gtsam::Values& values) const;

17
gtsam/sfm/ShonanAveraging.cpp
View File

@ -749,10 +749,23 @@ Values ShonanAveraging<d>::initializeRandomly(std::mt19937 &rng) const {
return initial;
}
/* ************************************************************************* */
template <size_t d> Values ShonanAveraging<d>::initializeRandomly() const {
return initializeRandomly(kRandomNumberGenerator);
}
/* ************************************************************************* */
template <size_t d>
Values ShonanAveraging<d>::initializeRandomly() const {
return ShonanAveraging<d>::initializeRandomly(kRandomNumberGenerator);
Values ShonanAveraging<d>::initializeRandomlyAt(size_t p,
std::mt19937 &rng) const {
const Values randomRotations = initializeRandomly(rng);
return LiftTo<Rot3>(p, randomRotations); // lift to p!
}
/* ************************************************************************* */
template <size_t d>
Values ShonanAveraging<d>::initializeRandomlyAt(size_t p) const {
return initializeRandomlyAt(p, kRandomNumberGenerator);
}
/* ************************************************************************* */

9
gtsam/sfm/ShonanAveraging.h
View File

@ -235,6 +235,15 @@ public:
*/
NonlinearFactorGraph buildGraphAt(size_t p) const;
/**
* Create initial Values of type SO(p)
* @param p the dimensionality of the rotation manifold
*/
Values initializeRandomlyAt(size_t p, std::mt19937 &rng) const;
/// Version of initializeRandomlyAt with fixed random seed.
Values initializeRandomlyAt(size_t p) const;
/**
* Calculate cost for SO(p)
* Values should be of type SO(p)

2
gtsam/slam/dataset.cpp
View File

@ -570,7 +570,7 @@ GraphAndValues load2D(pair<string, SharedNoiseModel> dataset, size_t maxIndex,
/* ************************************************************************* */
GraphAndValues load2D_robust(const string &filename,
noiseModel::Base::shared_ptr &model,
const noiseModel::Base::shared_ptr &model,
size_t maxIndex) {
return load2D(filename, model, maxIndex);
}

2
gtsam/slam/dataset.h
View File

@ -172,7 +172,7 @@ GTSAM_EXPORT GraphAndValues load2D(const std::string& filename,
/// @deprecated load2D now allows for arbitrary models and wrapping a robust kernel
GTSAM_EXPORT GraphAndValues load2D_robust(const std::string& filename,
noiseModel::Base::shared_ptr& model, size_t maxIndex = 0);
const noiseModel::Base::shared_ptr& model, size_t maxIndex = 0);
/** save 2d graph */
GTSAM_EXPORT void save2D(const NonlinearFactorGraph& graph,

6
gtsam_unstable/CMakeLists.txt
View File

@ -108,7 +108,7 @@ list(APPEND GTSAM_EXPORTED_TARGETS gtsam_unstable)
set(GTSAM_EXPORTED_TARGETS "${GTSAM_EXPORTED_TARGETS}" PARENT_SCOPE)
# Wrap version for gtsam_unstable
if (GTSAM_INSTALL_MATLAB_TOOLBOX)
if (GTSAM_UNSTABLE_INSTALL_MATLAB_TOOLBOX)
# Set up codegen
include(GtsamMatlabWrap)
@ -119,8 +119,8 @@ if (GTSAM_INSTALL_MATLAB_TOOLBOX)
endif()
# Wrap
wrap_and_install_library(gtsam_unstable.h "gtsam" "" "${mexFlags}")
endif(GTSAM_INSTALL_MATLAB_TOOLBOX)
wrap_and_install_library(gtsam_unstable.i "gtsam" "" "${mexFlags}")
endif(GTSAM_UNSTABLE_INSTALL_MATLAB_TOOLBOX)
# Build examples

0
gtsam_unstable/gtsam_unstable.h → gtsam_unstable/gtsam_unstable.i
View File

5
gtsam_unstable/slam/BetweenFactorEM.h
View File

@ -114,7 +114,7 @@ public:
/** implement functions needed to derive from Factor */
/* ************************************************************************* */
virtual double error(const Values& x) const {
double error(const Values &x) const override {
return whitenedError(x).squaredNorm();
}
@ -125,8 +125,7 @@ public:
* Hence \f$ b = z - h(x) = - \mathtt{error\_vector}(x) \f$
*/
/* This version of linearize recalculates the noise model each time */
virtual boost::shared_ptr<GaussianFactor> linearize(
const Values& x) const {
boost::shared_ptr<GaussianFactor> linearize(const Values &x) const override {
// Only linearize if the factor is active
if (!this->active(x))
return boost::shared_ptr<JacobianFactor>();

12
matlab/+gtsam/Point2.m Normal file
View File

@ -0,0 +1,12 @@
function pt = Point2(varargin)
% Point2 shim
if nargin == 2 && isa(varargin{1}, 'double')
pt = [varargin{1} varargin{2}]';
elseif nargin == 1
pt = varargin{1};
elseif nargin == 0
pt = [0 0]';
else
error('Arguments do not match any overload of Point2 shim');
end
end

12
matlab/+gtsam/Point3.m Normal file
View File

@ -0,0 +1,12 @@
function pt = Point3(varargin)
% Point3 shim
if nargin == 3 && isa(varargin{1}, 'double')
pt = [varargin{1} varargin{2} varargin{3}]';
elseif nargin == 1
pt = varargin{1};
elseif nargin == 0
pt = [0 0 0]';
else
error('Arguments do not match any overload of Point3 shim');
end
end

6
matlab/+gtsam/cylinderSampleProjection.m
View File

@ -50,9 +50,9 @@ for i = 1:cylinderNum
visible = true;
for k = 1:cylinderNum
rayCameraToPoint = pose.translation().between(sampledPoint3).vector();
rayCameraToCylinder = pose.translation().between(cylinders{k}.centroid).vector();
rayCylinderToPoint = cylinders{k}.centroid.between(sampledPoint3).vector();
rayCameraToPoint = pose.translation().between(sampledPoint3);
rayCameraToCylinder = pose.translation().between(cylinders{k}.centroid);
rayCylinderToPoint = cylinders{k}.centroid.between(sampledPoint3);
% Condition 1: all points in front of the cylinders'
% surfaces are visible

20
matlab/+gtsam/cylinderSampleProjectionStereo.m
View File

@ -25,20 +25,20 @@ for i = 1:cylinderNum
% For Cheirality Exception
sampledPoint3 = cylinders{i}.Points{j};
sampledPoint3local = pose.transformTo(sampledPoint3);
if sampledPoint3local.z < 0
if sampledPoint3local(3) < 0
continue;
end
% measurements
Z.du = K.fx() * K.baseline() / sampledPoint3local.z;
Z.uL = K.fx() * sampledPoint3local.x / sampledPoint3local.z + K.px();
Z.du = K.fx() * K.baseline() / sampledPoint3local(3);
Z.uL = K.fx() * sampledPoint3local(1) / sampledPoint3local(3) + K.px();
Z.uR = Z.uL + Z.du;
Z.v = K.fy() / sampledPoint3local.z + K.py();
Z.v = K.fy() / sampledPoint3local(3) + K.py();
% ignore points not visible in the scene
if Z.uL < 0 || Z.uL >= imageSize.x || ...
Z.uR < 0 || Z.uR >= imageSize.x || ...
Z.v < 0 || Z.v >= imageSize.y
if Z.uL < 0 || Z.uL >= imageSize(1) || ...
Z.uR < 0 || Z.uR >= imageSize(1) || ...
Z.v < 0 || Z.v >= imageSize(2)
continue;
end
@ -54,9 +54,9 @@ for i = 1:cylinderNum
visible = true;
for k = 1:cylinderNum
rayCameraToPoint = pose.translation().between(sampledPoint3).vector();
rayCameraToCylinder = pose.translation().between(cylinders{k}.centroid).vector();
rayCylinderToPoint = cylinders{k}.centroid.between(sampledPoint3).vector();
rayCameraToPoint = sampledPoint3 - pose.translation();
rayCameraToCylinder = cylinders{k}.centroid - pose.translation();
rayCylinderToPoint = sampledPoint3 - cylinders{k}.centroid;
% Condition 1: all points in front of the cylinders'
% surfaces are visible

6
matlab/+gtsam/cylinderSampling.m
View File

@ -12,8 +12,8 @@ function [cylinder] = cylinderSampling(baseCentroid, radius, height, density)
% sample the points
for i = 1:pointsNum
theta = 2 * pi * rand;
x = radius * cos(theta) + baseCentroid.x;
y = radius * sin(theta) + baseCentroid.y;
x = radius * cos(theta) + baseCentroid(1);
y = radius * sin(theta) + baseCentroid(2);
z = height * rand;
points3{i,1} = Point3([x,y,z]');
end
@ -22,5 +22,5 @@ function [cylinder] = cylinderSampling(baseCentroid, radius, height, density)
cylinder.radius = radius;
cylinder.height = height;
cylinder.Points = points3;
cylinder.centroid = Point3(baseCentroid.x, baseCentroid.y, height/2);
cylinder.centroid = Point3(baseCentroid(1), baseCentroid(2), height/2);
end

2
matlab/+gtsam/plotCamera.m
View File

@ -1,7 +1,7 @@
function plotCamera(pose, axisLength)
hold on
C = pose.translation().vector();
C = pose.translation();
R = pose.rotation().matrix();
xAxis = C+R(:,1)*axisLength;

16
matlab/+gtsam/plotFlyingResults.m
View File

@ -13,7 +13,7 @@ set(gcf, 'Position', [80,1,1800,1000]);
%% plot all the cylinders and sampled points
axis equal
axis([0, options.fieldSize.x, 0, options.fieldSize.y, 0, options.height + 30]);
axis([0, options.fieldSize(1), 0, options.fieldSize(2), 0, options.height + 30]);
xlabel('X (m)');
ylabel('Y (m)');
zlabel('Height (m)');
@ -50,8 +50,8 @@ for i = 1:cylinderNum
[X,Y,Z] = cylinder(cylinders{i}.radius, sampleDensity * cylinders{i}.radius * cylinders{i}.height);
X = X + cylinders{i}.centroid.x;
Y = Y + cylinders{i}.centroid.y;
X = X + cylinders{i}.centroid(1);
Y = Y + cylinders{i}.centroid(2);
Z = Z * cylinders{i}.height;
h_cylinder{i} = surf(X,Y,Z);
@ -76,7 +76,7 @@ for i = 1:posesSize
%plotCamera(poses{i}, 3);
gRp = poses{i}.rotation().matrix(); % rotation from pose to global
C = poses{i}.translation().vector();
C = poses{i}.translation();
axisLength = 3;
xAxis = C+gRp(:,1)*axisLength;
@ -111,14 +111,14 @@ for i = 1:posesSize
for j = 1:pointSize
if ~isempty(pts3d{j}.cov{i})
hold on
h_point{j} = plot3(pts3d{j}.data.x, pts3d{j}.data.y, pts3d{j}.data.z);
h_point_cov{j} = gtsam.covarianceEllipse3D([pts3d{j}.data.x; pts3d{j}.data.y; pts3d{j}.data.z], ...
h_point{j} = plot3(pts3d{j}.data(1), pts3d{j}.data(2), pts3d{j}.data(3));
h_point_cov{j} = gtsam.covarianceEllipse3D([pts3d{j}.data(1); pts3d{j}.data(2); pts3d{j}.data(3)], ...
pts3d{j}.cov{i}, options.plot.covarianceScale);
end
end
axis equal
axis([0, options.fieldSize.x, 0, options.fieldSize.y, 0, options.height + 30]);
axis([0, options.fieldSize(1), 0, options.fieldSize(2), 0, options.height + 30]);
drawnow
@ -158,7 +158,7 @@ for i = 1 : posesSize
hold on
campos([poses{i}.x, poses{i}.y, poses{i}.z]);
camtarget([options.fieldSize.x/2, options.fieldSize.y/2, 0]);
camtarget([options.fieldSize(1)/2, options.fieldSize(2)/2, 0]);
camlight(hlight, 'headlight');
if options.writeVideo

6
matlab/+gtsam/plotPoint2.m
View File

@ -1,10 +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 '*']);
plot(p(1),p(2),[color '*']);
else
plot(p.x,p.y,color);
plot(p(1),p(2),color);
end
if exist('P', 'var') && (~isempty(P))
gtsam.covarianceEllipse([p.x;p.y],P,color(1));
gtsam.covarianceEllipse([p(1);p(2)],P,color(1));
end

6
matlab/+gtsam/plotPoint3.m
View File

@ -1,12 +1,12 @@
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 '*']);
plot3(p(1),p(2),p(3),[color '*']);
else
plot3(p.x,p.y,p.z,color);
plot3(p(1),p(2),p(3),color);
end
if exist('P', 'var')
gtsam.covarianceEllipse3D([p.x;p.y;p.z],P);
gtsam.covarianceEllipse3D([p(1);p(2);p(3)],P);
end
end

2
matlab/+gtsam/plotPose3.m
View File

@ -4,7 +4,7 @@ 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();
C = pose.translation();
if ~isempty(axisLength)
% draw the camera axes

2
matlab/+gtsam/points2DTrackStereo.m
View File

@ -38,7 +38,7 @@ graph.add(PriorFactorPose3(symbol('x', 1), cameraPoses{1}, posePriorNoise));
%% initialize graph and values
initialEstimate = Values;
for i = 1:pointsNum
point_j = points3d{i}.data.retract(0.05*randn(3,1));
point_j = points3d{i}.data + (0.05*randn(3,1));
initialEstimate.insert(symbol('p', i), point_j);
end

24
matlab/gtsam_examples/CameraFlyingExample.m
View File

@ -46,7 +46,7 @@ options.camera.horizon = 60;
% camera baseline
options.camera.baseline = 0.05;
% camera focal length
options.camera.f = round(options.camera.resolution.x * options.camera.horizon / ...
options.camera.f = round(options.camera.resolution(1) * options.camera.horizon / ...
options.camera.fov);
% camera focal baseline
options.camera.fB = options.camera.f * options.camera.baseline;
@ -54,15 +54,15 @@ options.camera.fB = options.camera.f * options.camera.baseline;
options.camera.disparity = options.camera.fB / options.camera.horizon;
% Monocular Camera Calibration
options.camera.monoK = Cal3_S2(options.camera.f, options.camera.f, 0, ...
options.camera.resolution.x/2, options.camera.resolution.y/2);
options.camera.resolution(1)/2, options.camera.resolution(2)/2);
% Stereo Camera Calibration
options.camera.stereoK = Cal3_S2Stereo(options.camera.f, options.camera.f, 0, ...
options.camera.resolution.x/2, options.camera.resolution.y/2, options.camera.disparity);
options.camera.resolution(1)/2, options.camera.resolution(2)/2, options.camera.disparity);
% write video output
options.writeVideo = true;
% the testing field size (unit: meter)
options.fieldSize = Point2([100, 100]');
options.fieldSize = Point2(100, 100);
% camera flying speed (unit: meter / second)
options.speed = 20;
% camera flying height
@ -113,14 +113,14 @@ theta = 0;
i = 1;
while i <= cylinderNum
theta = theta + 2*pi/10;
x = 40 * rand * cos(theta) + options.fieldSize.x/2;
y = 20 * rand * sin(theta) + options.fieldSize.y/2;
baseCentroid{i} = Point2([x, y]');
x = 40 * rand * cos(theta) + options.fieldSize(1)/2;
y = 20 * rand * sin(theta) + options.fieldSize(2)/2;
baseCentroid{i} = Point2(x, y);
% prevent two cylinders interact with each other
regenerate = false;
for j = 1:i-1
if i > 1 && baseCentroid{i}.dist(baseCentroid{j}) < options.cylinder.radius * 2
if i > 1 && norm(baseCentroid{i} - baseCentroid{j}) < options.cylinder.radius * 2
regenerate = true;
break;
end
@ -146,17 +146,17 @@ while 1
angle = 0.1*pi*(rand-0.5);
inc_t = Point3(distance * cos(angle), ...
distance * sin(angle), 0);
t = t.compose(inc_t);
t = t + inc_t;
if t.x > options.fieldSize.x - 10 || t.y > options.fieldSize.y - 10;
if t(1) > options.fieldSize(1) - 10 || t(2) > options.fieldSize(2) - 10;
break;
end
%t = Point3([(i-1)*(options.fieldSize.x - 10)/options.poseNum + 10, ...
% 15, 10]');
camera = PinholeCameraCal3_S2.Lookat(t, ...
Point3(options.fieldSize.x/2, options.fieldSize.y/2, 0), ...
Point3([0,0,1]'), options.camera.monoK);
Point3(options.fieldSize(1)/2, options.fieldSize(2)/2, 0), ...
Point3(0,0,1), options.camera.monoK);
cameraPoses{end+1} = camera.pose;
end

4
matlab/gtsam_examples/MonocularVOExample.m
View File

@ -15,14 +15,14 @@ import gtsam.*
%% Create two cameras and corresponding essential matrix E
aRb = Rot3.Yaw(pi/2);
aTb = Point3 (0.1, 0, 0);
aTb = [.1, 0, 0]';
identity=Pose3;
aPb = Pose3(aRb, aTb);
cameraA = CalibratedCamera(identity);
cameraB = CalibratedCamera(aPb);
%% Create 5 points
P = { Point3(0, 0, 1), Point3(-0.1, 0, 1), Point3(0.1, 0, 1), Point3(0, 0.5, 0.5), Point3(0, -0.5, 0.5) };
P = { [0, 0, 1]', [-0.1, 0, 1]', [0.1, 0, 1]', [0, 0.5, 0.5]', [0, -0.5, 0.5]' };
%% Project points in both cameras
for i=1:5

9
matlab/gtsam_examples/PlanarSLAMExample.m
View File

@ -71,9 +71,12 @@ marginals = Marginals(graph, result);
plot2DTrajectory(result, [], marginals);
plot2DPoints(result, 'b', marginals);
plot([result.atPose2(i1).x; result.atPoint2(j1).x],[result.atPose2(i1).y; result.atPoint2(j1).y], 'c-');
plot([result.atPose2(i2).x; result.atPoint2(j1).x],[result.atPose2(i2).y; result.atPoint2(j1).y], 'c-');
plot([result.atPose2(i3).x; result.atPoint2(j2).x],[result.atPose2(i3).y; result.atPoint2(j2).y], 'c-');
p_j1 = result.atPoint2(j1);
p_j2 = result.atPoint2(j2);
plot([result.atPose2(i1).x; p_j1(1)],[result.atPose2(i1).y; p_j1(2)], 'c-');
plot([result.atPose2(i2).x; p_j1(1)],[result.atPose2(i2).y; p_j1(2)], 'c-');
plot([result.atPose2(i3).x; p_j2(1)],[result.atPose2(i3).y; p_j2(2)], 'c-');
axis([-0.6 4.8 -1 1])
axis equal
view(2)

11
matlab/gtsam_examples/PlanarSLAMExample_sampling.m
View File

@ -60,15 +60,18 @@ for j=1:2
S{j}=chol(Q{j}); % for sampling
end
plot([sample.atPose2(i1).x; sample.atPoint2(j1).x],[sample.atPose2(i1).y; sample.atPoint2(j1).y], 'c-');
plot([sample.atPose2(i2).x; sample.atPoint2(j1).x],[sample.atPose2(i2).y; sample.atPoint2(j1).y], 'c-');
plot([sample.atPose2(i3).x; sample.atPoint2(j2).x],[sample.atPose2(i3).y; sample.atPoint2(j2).y], 'c-');
p_j1 = sample.atPoint2(j1);
p_j2 = sample.atPoint2(j2);
plot([sample.atPose2(i1).x; p_j1(1)],[sample.atPose2(i1).y; p_j1(2)], 'c-');
plot([sample.atPose2(i2).x; p_j1(1)],[sample.atPose2(i2).y; p_j1(2)], 'c-');
plot([sample.atPose2(i3).x; p_j2(1)],[sample.atPose2(i3).y; p_j2(2)], '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));
proposedPoint = Point2(point{2} + delta);
plotPoint2(proposedPoint,'k.')
end

2
matlab/gtsam_examples/Pose2SLAMwSPCG.m
View File

@ -54,7 +54,7 @@ initialEstimate.print(sprintf('\nInitial estimate:\n'));
%% Optimize using Levenberg-Marquardt optimization with SubgraphSolver
params = gtsam.LevenbergMarquardtParams;
subgraphParams = gtsam.SubgraphSolverParameters;
params.setLinearSolverType('CONJUGATE_GRADIENT');
params.setLinearSolverType('ITERATIVE');
params.setIterativeParams(subgraphParams);
optimizer = gtsam.LevenbergMarquardtOptimizer(graph, initialEstimate);
result = optimizer.optimize();

4
matlab/gtsam_examples/SBAExample.m
View File

@ -47,7 +47,7 @@ end
%% Add Gaussian priors for a pose and a landmark to constrain the system
cameraPriorNoise = noiseModel.Diagonal.Sigmas(cameraNoiseSigmas);
firstCamera = PinholeCameraCal3_S2(truth.cameras{1}.pose, truth.K);
graph.add(PriorFactorSimpleCamera(symbol('c',1), firstCamera, cameraPriorNoise));
graph.add(PriorFactorPinholeCameraCal3_S2(symbol('c',1), firstCamera, cameraPriorNoise));
pointPriorNoise = noiseModel.Isotropic.Sigma(3,pointNoiseSigma);
graph.add(PriorFactorPoint3(symbol('p',1), truth.points{1}, pointPriorNoise));
@ -64,7 +64,7 @@ for i=1:size(truth.cameras,2)
initialEstimate.insert(symbol('c',i), camera_i);
end
for j=1:size(truth.points,2)
point_j = Point3(truth.points{j}.vector() + 0.1*randn(3,1));
point_j = Point3(truth.points{j} + 0.1*randn(3,1));
initialEstimate.insert(symbol('p',j), point_j);
end
initialEstimate.print(sprintf('\nInitial estimate:\n '));

2
matlab/gtsam_examples/SFMExample.m
View File

@ -58,7 +58,7 @@ for i=1:size(truth.cameras,2)
initialEstimate.insert(symbol('x',i), pose_i);
end
for j=1:size(truth.points,2)
point_j = Point3(truth.points{j}.vector() + 0.1*randn(3,1));
point_j = Point3(truth.points{j} + 0.1*randn(3,1));
initialEstimate.insert(symbol('p',j), point_j);
end
initialEstimate.print(sprintf('\nInitial estimate:\n '));

8
matlab/gtsam_examples/StereoVOExample.m
View File

@ -51,10 +51,10 @@ graph.add(GenericStereoFactor3D(StereoPoint2(320, 270, 115), stereo_model, x2, l
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));
initialEstimate.insert(x2, Pose3(Rot3(), [0.1, -.1, 1.1]'));
initialEstimate.insert(l1, [ 1, 1, 5]');
initialEstimate.insert(l2, [-1, 1, 5]');
initialEstimate.insert(l3, [ 0,-.5, 5]');
%% optimize
fprintf(1,'Optimizing\n'); tic

2
matlab/gtsam_examples/VisualizeMEstimators.m
View File

@ -48,7 +48,7 @@ function plot_m_estimator(x, model, plot_title, fig_id, filename)
rho = zeros(size(x));
for i = 1:size(x, 2)
w(i) = model.weight(x(i));
rho(i) = model.residual(x(i));
rho(i) = model.loss(x(i));
end
psi = w .* x;

2
matlab/gtsam_tests/testPlanarSLAMExample.m
View File

@ -66,4 +66,4 @@ CHECK('pose_1.equals(Pose2,1e-4)',pose_1.equals(Pose2,1e-4));
point_1 = result.atPoint2(symbol('l',1));
marginals.marginalCovariance(symbol('l',1));
CHECK('point_1.equals(Point2(2,2),1e-4)',point_1.equals(Point2(2,2),1e-4));
CHECK('point_1.equals(Point2(2,2),1e-4)',norm(point_1 - Point2(2,2)) < 1e-4);

2
matlab/gtsam_tests/testSFMExample.m
View File

@ -69,5 +69,5 @@ end
for j=1:size(truth.points,2)
point_j = result.atPoint3(symbol('p',j));
CHECK('point_j.equals(truth.points{j},1e-5)',point_j.equals(truth.points{j},1e-5))
CHECK('point_j.equals(truth.points{j},1e-5)',norm(point_j - truth.points{j}) < 1e-5)
end

2
matlab/gtsam_tests/testStereoVOExample.m
View File

@ -65,4 +65,4 @@ pose_x1 = result.atPose3(x1);
CHECK('pose_x1.equals(first_pose,1e-4)',pose_x1.equals(first_pose,1e-4));
point_l1 = result.atPoint3(l1);
CHECK('point_1.equals(expected_l1,1e-4)',point_l1.equals(expected_l1,1e-4));
CHECK('point_1.equals(expected_l1,1e-4)',norm(point_l1 - expected_l1) < 1e-4);

8
matlab/gtsam_tests/testValues.m
View File

@ -5,8 +5,8 @@ values = Values;
E = EssentialMatrix(Rot3,Unit3);
tol = 1e-9;
values.insert(0, Point2);
values.insert(1, Point3);
values.insert(0, Point2(0, 0));
values.insert(1, Point3(0, 0, 0));
values.insert(2, Rot2);
values.insert(3, Pose2);
values.insert(4, Rot3);
@ -21,8 +21,8 @@ values.insert(10, imuBias.ConstantBias);
values.insert(11, [1;2;3]);
values.insert(12, [1 2;3 4]);
EXPECT('at',values.atPoint2(0).equals(Point2,tol));
EXPECT('at',values.atPoint3(1).equals(Point3,tol));
EXPECT('at',values.atPoint2(0) == Point2(0, 0));
EXPECT('at',values.atPoint3(1) == Point3(0, 0, 0));
EXPECT('at',values.atRot2(2).equals(Rot2,tol));
EXPECT('at',values.atPose2(3).equals(Pose2,tol));
EXPECT('at',values.atRot3(4).equals(Rot3,tol));

2
matlab/gtsam_tests/testVisualISAMExample.m
View File

@ -51,5 +51,5 @@ end
for j=1:size(truth.points,2)
point_j = result.atPoint3(symbol('l',j));
CHECK('point_j.equals(truth.points{j},1e-5)',point_j.equals(truth.points{j},1e-5))
CHECK('point_j.equals(truth.points{j},1e-5)',norm(point_j - truth.points{j}) < 1e-5)
end

12
matlab/unstable_examples/+imuSimulator/IMUComparison.m
View File

@ -28,19 +28,19 @@ currentVelocityGlobalIMUbody = currentVelocityGlobal;
%% Prepare data structures for actual trajectory and estimates
% Actual trajectory
positions = zeros(3, length(times)+1);
positions(:,1) = currentPoseGlobal.translation.vector;
positions(:,1) = currentPoseGlobal.translation;
poses(1).p = positions(:,1);
poses(1).R = currentPoseGlobal.rotation.matrix;
% Trajectory estimate (integrated in the navigation frame)
positionsIMUnav = zeros(3, length(times)+1);
positionsIMUnav(:,1) = currentPoseGlobalIMUbody.translation.vector;
positionsIMUnav(:,1) = currentPoseGlobalIMUbody.translation;
posesIMUnav(1).p = positionsIMUnav(:,1);
posesIMUnav(1).R = poses(1).R;
% Trajectory estimate (integrated in the body frame)
positionsIMUbody = zeros(3, length(times)+1);
positionsIMUbody(:,1) = currentPoseGlobalIMUbody.translation.vector;
positionsIMUbody(:,1) = currentPoseGlobalIMUbody.translation;
posesIMUbody(1).p = positionsIMUbody(:,1);
posesIMUbody(1).R = poses(1).R;
@ -120,9 +120,9 @@ for t = times
currentPoseGlobalIMUnav, currentVelocityGlobalIMUnav, acc_omega, deltaT);
%% Store data in some structure for statistics and plots
positions(:,i) = currentPoseGlobal.translation.vector;
positionsIMUbody(:,i) = currentPoseGlobalIMUbody.translation.vector;
positionsIMUnav(:,i) = currentPoseGlobalIMUnav.translation.vector;
positions(:,i) = currentPoseGlobal.translation;
positionsIMUbody(:,i) = currentPoseGlobalIMUbody.translation;
positionsIMUnav(:,i) = currentPoseGlobalIMUnav.translation;
% -
poses(i).p = positions(:,i);
posesIMUbody(i).p = positionsIMUbody(:,i);

4
matlab/unstable_examples/+imuSimulator/IMUComparison_with_cov.m
View File

@ -28,7 +28,7 @@ currentVelocityGlobal = velocity;
%% Prepare data structures for actual trajectory and estimates
% Actual trajectory
positions = zeros(3, length(times)+1);
positions(:,1) = currentPoseGlobal.translation.vector;
positions(:,1) = currentPoseGlobal.translation;
poses(1).p = positions(:,1);
poses(1).R = currentPoseGlobal.rotation.matrix;
@ -112,7 +112,7 @@ for t = times
end
%% Store data in some structure for statistics and plots
positions(:,i) = currentPoseGlobal.translation.vector;
positions(:,i) = currentPoseGlobal.translation;
i = i + 1;
end

2
matlab/unstable_examples/+imuSimulator/calculateIMUMeas_coriolis.m
View File

@ -7,7 +7,7 @@ measuredOmega = omega1Body;
% Acceleration measurement (in this simple toy example no other forces
% act on the body and the only acceleration is the centripetal Coriolis acceleration)
measuredAcc = Point3(cross(omega1Body, velocity1Body)).vector;
measuredAcc = Point3(cross(omega1Body, velocity1Body));
acc_omega = [ measuredAcc; measuredOmega ];
end

6
matlab/unstable_examples/+imuSimulator/calculateIMUMeasurement.m
View File

@ -6,16 +6,16 @@ import gtsam.*;
% Calculate gyro measured rotation rate by transforming body rotation rate
% into the IMU frame.
measuredOmega = imuFrame.rotation.unrotate(Point3(omega1Body)).vector;
measuredOmega = imuFrame.rotation.unrotate(Point3(omega1Body));
% Transform both velocities into IMU frame, accounting for the velocity
% induced by rigid body rotation on a lever arm (Coriolis effect).
velocity1inertial = imuFrame.rotation.unrotate( ...
Point3(velocity1Body + cross(omega1Body, imuFrame.translation.vector))).vector;
Point3(velocity1Body + cross(omega1Body, imuFrame.translation)));
imu2in1 = Rot3.Expmap(measuredOmega * deltaT);
velocity2inertial = imu2in1.rotate(imuFrame.rotation.unrotate( ...
Point3(velocity2Body + cross(omega2Body, imuFrame.translation.vector)))).vector;
Point3(velocity2Body + cross(omega2Body, imuFrame.translation))));
% Acceleration in IMU frame
measuredAcc = (velocity2inertial - velocity1inertial) / deltaT;

30
matlab/unstable_examples/+imuSimulator/coriolisExample.m
View File

@ -190,13 +190,13 @@ for i = 1:length(times)
newFactors.add(PriorFactorConstantBias(currentBiasKey, zeroBias, sigma_init_b));
% Store data
positionsInFixedGT(:,1) = currentPoseFixedGT.translation.vector;
positionsInFixedGT(:,1) = currentPoseFixedGT.translation;
velocityInFixedGT(:,1) = currentVelocityFixedGT;
positionsInRotatingGT(:,1) = currentPoseRotatingGT.translation.vector;
%velocityInRotatingGT(:,1) = currentPoseRotatingGT.velocity.vector;
positionsEstimates(:,i) = currentPoseEstimate.translation.vector;
velocitiesEstimates(:,i) = currentVelocityEstimate.vector;
currentRotatingFrameForPlot(1).p = currentRotatingFrame.translation.vector;
positionsInRotatingGT(:,1) = currentPoseRotatingGT.translation;
%velocityInRotatingGT(:,1) = currentPoseRotatingGT.velocity;
positionsEstimates(:,i) = currentPoseEstimate.translation;
velocitiesEstimates(:,i) = currentVelocityEstimate;
currentRotatingFrameForPlot(1).p = currentRotatingFrame.translation;
currentRotatingFrameForPlot(1).R = currentRotatingFrame.rotation.matrix;
else
@ -204,18 +204,18 @@ for i = 1:length(times)
% Update the position and velocity
% x_t = x_0 + v_0*dt + 1/2*a_0*dt^2
% v_t = v_0 + a_0*dt
currentPositionFixedGT = Point3(currentPoseFixedGT.translation.vector ...
currentPositionFixedGT = Point3(currentPoseFixedGT.translation ...
+ currentVelocityFixedGT * deltaT + 0.5 * accelFixed * deltaT * deltaT);
currentVelocityFixedGT = currentVelocityFixedGT + accelFixed * deltaT;
currentPoseFixedGT = Pose3(Rot3, currentPositionFixedGT); % constant orientation
% Rotate pose in fixed frame to get pose in rotating frame
previousPositionRotatingGT = currentPoseRotatingGT.translation.vector;
previousPositionRotatingGT = currentPoseRotatingGT.translation;
currentRotatingFrame = currentRotatingFrame.compose(changePoseRotatingFrame);
inverseCurrentRotatingFrame = (currentRotatingFrame.inverse);
currentPoseRotatingGT = inverseCurrentRotatingFrame.compose(currentPoseFixedGT);
currentPositionRotatingGT = currentPoseRotatingGT.translation.vector;
currentPositionRotatingGT = currentPoseRotatingGT.translation;
% Get velocity in rotating frame by treating it like a position and using compose
% Maybe Luca knows a better way to do this within GTSAM.
@ -230,11 +230,11 @@ for i = 1:length(times)
% - 0.5 * accelFixed * deltaT * deltaT) / deltaT + accelFixed * deltaT;
% Store GT (ground truth) poses
positionsInFixedGT(:,i) = currentPoseFixedGT.translation.vector;
positionsInFixedGT(:,i) = currentPoseFixedGT.translation;
velocityInFixedGT(:,i) = currentVelocityFixedGT;
positionsInRotatingGT(:,i) = currentPoseRotatingGT.translation.vector;
positionsInRotatingGT(:,i) = currentPoseRotatingGT.translation;
velocityInRotatingGT(:,i) = currentVelocityRotatingGT;
currentRotatingFrameForPlot(i).p = currentRotatingFrame.translation.vector;
currentRotatingFrameForPlot(i).p = currentRotatingFrame.translation;
currentRotatingFrameForPlot(i).R = currentRotatingFrame.rotation.matrix;
%% Estimate trajectory in rotating frame using GTSAM (ground truth measurements)
@ -303,9 +303,9 @@ for i = 1:length(times)
currentVelocityEstimate = isam.calculateEstimate(currentVelKey);
currentBias = isam.calculateEstimate(currentBiasKey);
positionsEstimates(:,i) = currentPoseEstimate.translation.vector;
velocitiesEstimates(:,i) = currentVelocityEstimate.vector;
biasEstimates(:,i) = currentBias.vector;
positionsEstimates(:,i) = currentPoseEstimate.translation;
velocitiesEstimates(:,i) = currentVelocityEstimate;
biasEstimates(:,i) = currentBias;
% In matrix form: R_error = R_gt'*R_estimate
% Perform Logmap on the rotation matrix to get a vector

10
matlab/unstable_examples/+imuSimulator/covarianceAnalysisBetween.m
View File

@ -151,14 +151,14 @@ hold on;
if options.includeCameraFactors
b = [-1000 2000 -2000 2000 -30 30];
for i = 1:size(metadata.camera.gtLandmarkPoints,2)
p = metadata.camera.gtLandmarkPoints(i).vector;
p = metadata.camera.gtLandmarkPoints(i);
if(p(1) > b(1) && p(1) < b(2) && p(2) > b(3) && p(2) < b(4) && p(3) > b(5) && p(3) < b(6))
plot3(p(1), p(2), p(3), 'k+');
end
end
pointsToPlot = metadata.camera.gtLandmarkPoints(find(projectionFactorSeenBy > 0));
for i = 1:length(pointsToPlot)
p = pointsToPlot(i).vector;
p = pointsToPlot(i);
plot3(p(1), p(2), p(3), 'gs', 'MarkerSize', 10);
end
end
@ -233,9 +233,9 @@ for k=1:numMonteCarloRuns
for i=0:options.trajectoryLength
% compute estimation errors
currentPoseKey = symbol('x', i);
gtPosition = gtValues.at(currentPoseKey).translation.vector;
estPosition = estimate.at(currentPoseKey).translation.vector;
estR = estimate.at(currentPoseKey).rotation.matrix;
gtPosition = gtValues.atPose3(currentPoseKey).translation;
estPosition = estimate.atPose3(currentPoseKey).translation;
estR = estimate.atPose3(currentPoseKey).rotation.matrix;
errPosition = estPosition - gtPosition;
% compute covariances:

8
matlab/unstable_examples/+imuSimulator/covarianceAnalysisCreateFactorGraph.m
View File

@ -14,7 +14,7 @@ graph = NonlinearFactorGraph;
for i=0:length(measurements)
% Get the current pose
currentPoseKey = symbol('x', i);
currentPose = values.at(currentPoseKey);
currentPose = values.atPose3(currentPoseKey);
if i==0
%% first time step, add priors
@ -26,11 +26,11 @@ for i=0:length(measurements)
% IMU velocity and bias priors
if options.includeIMUFactors == 1
currentVelKey = symbol('v', 0);
currentVel = values.at(currentVelKey).vector;
currentVel = values.atPoint3(currentVelKey);
graph.add(PriorFactorLieVector(currentVelKey, LieVector(currentVel), noiseModels.noiseVel));
currentBiasKey = symbol('b', 0);
currentBias = values.at(currentBiasKey);
currentBias = values.atPoint3(currentBiasKey);
graph.add(PriorFactorConstantBias(currentBiasKey, currentBias, noiseModels.noisePriorBias));
end
@ -155,7 +155,7 @@ for i=0:length(measurements)
if options.includeCameraFactors == 1
for j = 1:length(measurements(i).landmarks)
cameraMeasurmentNoise = measurementNoise.cameraNoiseVector .* randn(2,1);
cameraPixelMeasurement = measurements(i).landmarks(j).vector;
cameraPixelMeasurement = measurements(i).landmarks(j);
% Only add the measurement if it is in the image frame (based on calibration)
if(cameraPixelMeasurement(1) > 0 && cameraPixelMeasurement(2) > 0 ...
&& cameraPixelMeasurement(1) < 2*metadata.camera.calibration.px ...

6
matlab/unstable_examples/+imuSimulator/covarianceAnalysisCreateTrajectory.m
View File

@ -40,7 +40,7 @@ if options.useRealData == 1
%% gt Between measurements
if options.includeBetweenFactors == 1 && i > 0
prevPose = values.at(currentPoseKey - 1);
prevPose = values.atPose3(currentPoseKey - 1);
deltaPose = prevPose.between(currentPose);
measurements(i).deltaVector = Pose3.Logmap(deltaPose);
end
@ -65,7 +65,7 @@ if options.useRealData == 1
IMUdeltaPose = IMUPose1.between(IMUPose2);
IMUdeltaPoseVector = Pose3.Logmap(IMUdeltaPose);
IMUdeltaRotVector = IMUdeltaPoseVector(1:3);
IMUdeltaPositionVector = IMUPose2.translation.vector - IMUPose1.translation.vector; % translation in absolute frame
IMUdeltaPositionVector = IMUPose2.translation - IMUPose1.translation; % translation in absolute frame
measurements(i).imu(j).deltaT = deltaT;
@ -88,7 +88,7 @@ if options.useRealData == 1
%% gt GPS measurements
if options.includeGPSFactors == 1 && i > 0
gpsPositionVector = imuSimulator.getPoseFromGtScenario(gtScenario,scenarioInd).translation.vector;
gpsPositionVector = imuSimulator.getPoseFromGtScenario(gtScenario,scenarioInd).translation;
measurements(i).gpsPositionVector = gpsPositionVector;
end

4
matlab/unstable_examples/+imuSimulator/integrateIMUTrajectory.m
View File

@ -5,9 +5,9 @@ function [ finalPose, finalVelocityGlobal ] = integrateIMUTrajectory( ...
import gtsam.*;
imu2in1 = Rot3.Expmap(acc_omegaIMU(4:6) * deltaT);
accelGlobal = initialPoseGlobal.rotation().rotate(Point3(acc_omegaIMU(1:3))).vector;
accelGlobal = initialPoseGlobal.rotation().rotate(Point3(acc_omegaIMU(1:3)));
finalPosition = Point3(initialPoseGlobal.translation.vector ...
finalPosition = Point3(initialPoseGlobal.translation ...
+ initialVelocityGlobal * deltaT + 0.5 * accelGlobal * deltaT * deltaT);
finalVelocityGlobal = initialVelocityGlobal + accelGlobal * deltaT;
finalRotation = initialPoseGlobal.rotation.compose(imu2in1);

6
matlab/unstable_examples/+imuSimulator/integrateIMUTrajectory_bodyFrame.m
View File

@ -3,7 +3,7 @@ function [ finalPose, finalVelocityGlobal ] = integrateIMUTrajectory_bodyFrame(
% Before integrating in the body frame we need to compensate for the Coriolis
% effect
acc_body = acc_omegaIMU(1:3) - Point3(cross(acc_omegaIMU(4:6), velocity1Body)).vector;
acc_body = acc_omegaIMU(1:3) - Point3(cross(acc_omegaIMU(4:6), velocity1Body));
% after compensating for coriolis this will be essentially zero
% since we are moving at constant body velocity
@ -16,8 +16,8 @@ finalPositionBody = velocity1Body * deltaT + 0.5 * acc_body * deltaT * deltaT;
finalVelocityBody = velocity1Body + acc_body * deltaT;
%% Express the integrated quantities in the global frame
finalVelocityGlobal = initialVelocityGlobal + (initialPoseGlobal.rotation().rotate(Point3(finalVelocityBody)).vector() );
finalPosition = initialPoseGlobal.translation().vector() + initialPoseGlobal.rotation().rotate( Point3(finalPositionBody)).vector() ;
finalVelocityGlobal = initialVelocityGlobal + (initialPoseGlobal.rotation().rotate(Point3(finalVelocityBody)) );
finalPosition = initialPoseGlobal.translation() + initialPoseGlobal.rotation().rotate( Point3(finalPositionBody)) ;
finalRotation = initialPoseGlobal.rotation.compose(imu2in1);
% Include position and rotation in a pose
finalPose = Pose3(finalRotation, Point3(finalPosition) );

4
matlab/unstable_examples/+imuSimulator/integrateIMUTrajectory_navFrame.m
View File

@ -9,8 +9,8 @@ finalRotation = initialPoseGlobal.rotation.compose(imu2in1);
intermediateRotation = initialPoseGlobal.rotation.compose( Rot3.Expmap(acc_omegaIMU(4:6) * deltaT/2 ));
% Integrate positions (equation (1) in Lupton)
accelGlobal = intermediateRotation.rotate(Point3(acc_omegaIMU(1:3))).vector;
finalPosition = Point3(initialPoseGlobal.translation.vector ...
accelGlobal = intermediateRotation.rotate(Point3(acc_omegaIMU(1:3)));
finalPosition = Point3(initialPoseGlobal.translation ...
+ initialVelocityGlobal * deltaT + 0.5 * accelGlobal * deltaT * deltaT);
finalVelocityGlobal = initialVelocityGlobal + accelGlobal * deltaT;

8
matlab/unstable_examples/+imuSimulator/integrateTrajectory.m
View File

@ -6,16 +6,16 @@ import gtsam.*;
% Rotation: R^1_2
body2in1 = Rot3.Expmap(omega1Body * deltaT);
% Velocity 2 in frame 1: v^1_2 = R^1_2 v^2_2
velocity2inertial = body2in1.rotate(Point3(velocity2Body)).vector;
velocity2inertial = body2in1.rotate(Point3(velocity2Body));
% Acceleration: a^1 = (v^1_2 - v^1_1)/dt
accelBody1 = (velocity2inertial - velocity1Body) / deltaT;
% Velocity 1 in frame W: v^W_1 = R^W_1 v^1_1
initialVelocityGlobal = initialPose.rotation().rotate(Point3(velocity1Body)).vector;
initialVelocityGlobal = initialPose.rotation().rotate(Point3(velocity1Body));
% Acceleration in frame W: a^W = R^W_1 a^1
accelGlobal = initialPose.rotation().rotate(Point3(accelBody1)).vector;
accelGlobal = initialPose.rotation().rotate(Point3(accelBody1));
finalPosition = Point3(initialPose.translation.vector + initialVelocityGlobal * deltaT + 0.5 * accelGlobal * deltaT * deltaT);
finalPosition = Point3(initialPose.translation + initialVelocityGlobal * deltaT + 0.5 * accelGlobal * deltaT * deltaT);
finalVelocityGlobal = initialVelocityGlobal + accelGlobal * deltaT;
finalRotation = initialPose.rotation.compose(body2in1);
finalPose = Pose3(finalRotation, finalPosition);

4
matlab/unstable_examples/+imuSimulator/test1onestep.m
View File

@ -10,7 +10,7 @@ omega = [0;0;0.1];
velocity = [1;0;0];
R = Rot3.Expmap(omega * deltaT);
velocity2body = R.unrotate(Point3(velocity)).vector;
velocity2body = R.unrotate(Point3(velocity));
acc_omegaExpected = [-0.01; 0; 0; 0; 0; 0.1];
acc_omegaActual = imuSimulator.calculateIMUMeasurement(omega, omega, velocity, velocity2body, deltaT, Pose3(Rot3, Point3([1;0;0])));
disp('IMU measurement discrepancy:');
@ -40,7 +40,7 @@ disp(acc_omegaActual - acc_omegaExpected);
initialPose = Pose3;
initialVelocity = velocity;
finalPoseExpected = Pose3.Expmap([ omega; velocity ] * deltaT);
finalVelocityExpected = finalPoseExpected.rotation.rotate(Point3(velocity)).vector;
finalVelocityExpected = finalPoseExpected.rotation.rotate(Point3(velocity));
[ finalPoseActual, finalVelocityActual ] = imuSimulator.integrateTrajectory(initialPose, omega, velocity, velocity, deltaT);
disp('Final pose discrepancy:');
disp(finalPoseExpected.between(finalPoseActual).matrix);

6
matlab/unstable_examples/+imuSimulator/test2constglobal.m
View File

@ -21,12 +21,12 @@ positions = zeros(3, length(times)+1);
i = 2;
for t = times
velocity1body = currentPoseGlobal.rotation.unrotate(Point3(currentVelocityGlobal)).vector;
velocity1body = currentPoseGlobal.rotation.unrotate(Point3(currentVelocityGlobal));
R = Rot3.Expmap(omega * deltaT);
velocity2body = currentPoseGlobal.rotation.compose(R).unrotate(Point3(currentVelocityGlobal)).vector;
velocity2body = currentPoseGlobal.rotation.compose(R).unrotate(Point3(currentVelocityGlobal));
[ currentPoseGlobal, currentVelocityGlobal ] = imuSimulator.integrateTrajectory(currentPoseGlobal, omega, velocity1body, velocity2body, deltaT);
positions(:,i) = currentPoseGlobal.translation.vector;
positions(:,i) = currentPoseGlobal.translation;
i = i + 1;
end

16
matlab/unstable_examples/+imuSimulator/test3constbody.m
View File

@ -26,27 +26,27 @@ currentPoseGlobal = Pose3;
currentVelocityGlobal = velocity;
% Initial state (IMU)
currentPoseGlobalIMU = Pose3; %currentPoseGlobal.compose(IMUinBody);
%currentVelocityGlobalIMU = IMUinBody.rotation.unrotate(Point3(velocity)).vector; % no Coriolis here?
%currentVelocityGlobalIMU = IMUinBody.rotation.unrotate(Point3(velocity)); % no Coriolis here?
currentVelocityGlobalIMU = IMUinBody.rotation.unrotate( ...
Point3(velocity + cross(omega, IMUinBody.translation.vector))).vector;
Point3(velocity + cross(omega, IMUinBody.translation)));
% Positions
% body trajectory
positions = zeros(3, length(times)+1);
positions(:,1) = currentPoseGlobal.translation.vector;
positions(:,1) = currentPoseGlobal.translation;
poses(1).p = positions(:,1);
poses(1).R = currentPoseGlobal.rotation.matrix;
% Expected IMU trajectory (from body trajectory and lever arm)
positionsIMUe = zeros(3, length(times)+1);
positionsIMUe(:,1) = IMUinBody.compose(currentPoseGlobalIMU).translation.vector;
positionsIMUe(:,1) = IMUinBody.compose(currentPoseGlobalIMU).translation;
posesIMUe(1).p = positionsIMUe(:,1);
posesIMUe(1).R = poses(1).R * IMUinBody.rotation.matrix;
% Integrated IMU trajectory (from IMU measurements)
positionsIMU = zeros(3, length(times)+1);
positionsIMU(:,1) = IMUinBody.compose(currentPoseGlobalIMU).translation.vector;
positionsIMU(:,1) = IMUinBody.compose(currentPoseGlobalIMU).translation;
posesIMU(1).p = positionsIMU(:,1);
posesIMU(1).R = IMUinBody.compose(currentPoseGlobalIMU).rotation.matrix;
@ -62,9 +62,9 @@ for t = times
currentPoseGlobalIMU, currentVelocityGlobalIMU, acc_omega, deltaT);
% Store data in some structure for statistics and plots
positions(:,i) = currentPoseGlobal.translation.vector;
positionsIMUe(:,i) = currentPoseGlobal.translation.vector + currentPoseGlobal.rotation.matrix * IMUinBody.translation.vector;
positionsIMU(:,i) = IMUinBody.compose(currentPoseGlobalIMU).translation.vector;
positions(:,i) = currentPoseGlobal.translation;
positionsIMUe(:,i) = currentPoseGlobal.translation + currentPoseGlobal.rotation.matrix * IMUinBody.translation;
positionsIMU(:,i) = IMUinBody.compose(currentPoseGlobalIMU).translation;
poses(i).p = positions(:,i);
posesIMUe(i).p = positionsIMUe(:,i);

12
matlab/unstable_examples/+imuSimulator/test4circle.m
View File

@ -34,19 +34,19 @@ currentVelocityGlobalIMUbody = currentVelocityGlobal;
%% Prepare data structures for actual trajectory and estimates
% Actual trajectory
positions = zeros(3, length(times)+1);
positions(:,1) = currentPoseGlobal.translation.vector;
positions(:,1) = currentPoseGlobal.translation;
poses(1).p = positions(:,1);
poses(1).R = currentPoseGlobal.rotation.matrix;
% Trajectory estimate (integrated in the navigation frame)
positionsIMUnav = zeros(3, length(times)+1);
positionsIMUnav(:,1) = currentPoseGlobalIMUbody.translation.vector;
positionsIMUnav(:,1) = currentPoseGlobalIMUbody.translation;
posesIMUnav(1).p = positionsIMUnav(:,1);
posesIMUnav(1).R = poses(1).R;
% Trajectory estimate (integrated in the body frame)
positionsIMUbody = zeros(3, length(times)+1);
positionsIMUbody(:,1) = currentPoseGlobalIMUbody.translation.vector;
positionsIMUbody(:,1) = currentPoseGlobalIMUbody.translation;
posesIMUbody(1).p = positionsIMUbody(:,1);
posesIMUbody(1).R = poses(1).R;
@ -72,9 +72,9 @@ for t = times
currentPoseGlobalIMUnav, currentVelocityGlobalIMUnav, acc_omega, deltaT);
%% Store data in some structure for statistics and plots
positions(:,i) = currentPoseGlobal.translation.vector;
positionsIMUbody(:,i) = currentPoseGlobalIMUbody.translation.vector;
positionsIMUnav(:,i) = currentPoseGlobalIMUnav.translation.vector;
positions(:,i) = currentPoseGlobal.translation;
positionsIMUbody(:,i) = currentPoseGlobalIMUbody.translation;
positionsIMUnav(:,i) = currentPoseGlobalIMUnav.translation;
% -
poses(i).p = positions(:,i);
posesIMUbody(i).p = positionsIMUbody(:,i);

25
matlab/unstable_examples/FlightCameraTransformIMU.m
View File

@ -120,7 +120,7 @@ for i=1:size(trajectory)-1
end
% current ground-truth position indicator
h_cursor = plot3(a1, pose_t.x,pose_t.y,pose_t.z,'*');
h_cursor = plot3(a1, pose_t(1),pose_t(2),pose_t(3),'*');
camera_pose = pose.compose(camera_transform);
@ -198,7 +198,7 @@ for i=1:size(trajectory)-1
if ~result.exists(lKey)
p = landmarks.atPoint3(lKey);
n = normrnd(0,landmark_noise,3,1);
noisy_landmark = Point3(p.x()+n(1),p.y()+n(2),p.z()+n(3));
noisy_landmark = p + n;
initial.insert(lKey, noisy_landmark);
% and add a prior since its position is known
@ -245,32 +245,33 @@ for i=1:size(trajectory)-1
initial = Values;
fg = NonlinearFactorGraph;
currentVelocityGlobal = result.at(currentVelKey);
currentBias = result.at(currentBiasKey);
currentVelocityGlobal = result.atPoint3(currentVelKey);
currentBias = result.atConstantBias(currentBiasKey);
%% plot current pose result
isam_pose = result.at(xKey);
isam_pose = result.atPose3(xKey);
pose_t = isam_pose.translation();
if exist('h_result','var')
delete(h_result);
end
h_result = plot3(a1, pose_t.x,pose_t.y,pose_t.z,'^b', 'MarkerSize', 10);
h_result = plot3(a1, pose_t(1),pose_t(2),pose_t(3),'^b', 'MarkerSize', 10);
title(a1, sprintf('Step %d', i));
if exist('h_text1(1)', 'var')
delete(h_text1(1));
% delete(h_text2(1));
end
ty = result.at(transformKey).translation().y();
K_estimate = result.at(calibrationKey);
t = result.atPose3(transformKey).translation();
ty = t(2);
K_estimate = result.atCal3_S2(calibrationKey);
K_errors = K.localCoordinates(K_estimate);
camera_transform_estimate = result.at(transformKey);
camera_transform_estimate = result.atPose3(transformKey);
fx = result.at(calibrationKey).fx();
fy = result.at(calibrationKey).fy();
fx = result.atCal3_S2(calibrationKey).fx();
fy = result.atCal3_S2(calibrationKey).fy();
% h_text1 = text(-600,0,0,sprintf('Y-Transform(0.0): %0.2f',ty));
text(0,1300,0,sprintf('Calibration and IMU-cam transform errors:'));
@ -304,7 +305,7 @@ for i=1:size(trajectory)-1
end
%% print out final camera transform and write video
result.at(transformKey);
result.atPose3(transformKey);
if(write_video)
close(videoObj);
end

46
matlab/unstable_examples/TransformCalProjectionFactorIMUExampleISAM.m
View File

@ -53,7 +53,7 @@ y_shift = Point3(0,0.5,0);
% insert shifted points
for i=1:nrPoints
initial.insert(100+i,landmarks{i}.compose(y_shift));
initial.insert(100+i,landmarks{i} + y_shift);
end
figure(1);
@ -134,7 +134,7 @@ for i=1:steps
end
if i == 2
fg.add(PriorFactorPose3(2, Pose3(Rot3(),Point3(1,0,0)),pose_cov));
fg.add(PriorFactorLieVector(currentVelKey, currentVelocityGlobal, sigma_init_v));
fg.add(PriorFactorVector(currentVelKey, currentVelocityGlobal, sigma_init_v));
fg.add(PriorFactorConstantBias(currentBiasKey, currentBias, sigma_init_b));
end
if i > 1
@ -144,7 +144,7 @@ for i=1:steps
step = move_circle;
end
initial.insert(i,result.at(i-1).compose(step));
initial.insert(i,result.atPose3(i-1).compose(step));
fg.add(BetweenFactorPose3(i-1,i, step, covariance));
deltaT = 1;
@ -158,10 +158,13 @@ for i=1:steps
[ currentIMUPoseGlobal, currentVelocityGlobal ] = imuSimulator.integrateTrajectory( ...
currentIMUPoseGlobal, omega, velocity, velocity, deltaT);
currentSummarizedMeasurement = gtsam.ImuFactorPreintegratedMeasurements( ...
currentBias, IMU_metadata.AccelerometerSigma.^2 * eye(3), ...
IMU_metadata.GyroscopeSigma.^2 * eye(3), IMU_metadata.IntegrationSigma.^2 * eye(3));
params = gtsam.PreintegrationParams.MakeSharedD(9.81);
params.setAccelerometerCovariance(IMU_metadata.AccelerometerSigma.^2 * eye(3));
params.setGyroscopeCovariance(IMU_metadata.GyroscopeSigma.^2 * eye(3));
params.setIntegrationCovariance(IMU_metadata.IntegrationSigma.^2 * eye(3));
currentSummarizedMeasurement = gtsam.PreintegratedImuMeasurements( ...
params, currentBias);
accMeas = acc_omega(1:3)-g;
omegaMeas = acc_omega(4:6);
@ -171,7 +174,7 @@ for i=1:steps
fg.add(ImuFactor( ...
i-1, currentVelKey-1, ...
i, currentVelKey, ...
currentBiasKey, currentSummarizedMeasurement, g, w_coriolis));
currentBiasKey, currentSummarizedMeasurement));
% Bias evolution as given in the IMU metadata
fg.add(BetweenFactorConstantBias(currentBiasKey-1, currentBiasKey, imuBias.ConstantBias(zeros(3,1), zeros(3,1)), ...
@ -204,8 +207,8 @@ for i=1:steps
initial = Values;
fg = NonlinearFactorGraph;
currentVelocityGlobal = isam.calculateEstimate(currentVelKey);
currentBias = isam.calculateEstimate(currentBiasKey);
currentVelocityGlobal = isam.calculateEstimate().atVector(currentVelKey);
currentBias = isam.calculateEstimate().atConstantBias(currentBiasKey);
%% Compute some marginals
marginal = isam.marginalCovariance(calibrationKey);
@ -249,10 +252,10 @@ for i=1:steps
gtsam.plotPose3(currentIMUPoseGlobal, [], 2);
%% plot results
result_camera_transform = result.at(transformKey);
result_camera_transform = result.atPose3(transformKey);
for j=1:i
gtsam.plotPose3(result.at(j),[],0.5);
gtsam.plotPose3(result.at(j).compose(result_camera_transform),[],0.5);
gtsam.plotPose3(result.atPose3(j),[],0.5);
gtsam.plotPose3(result.atPose3(j).compose(result_camera_transform),[],0.5);
end
xlabel('x (m)');
@ -265,14 +268,15 @@ for i=1:steps
% axis equal
for l=101:100+nrPoints
plotPoint3(result.at(l),'g');
plotPoint3(result.atPoint3(l),'g');
end
ty = result.at(transformKey).translation().y();
fx = result.at(calibrationKey).fx();
fy = result.at(calibrationKey).fy();
px = result.at(calibrationKey).px();
py = result.at(calibrationKey).py();
t = result.atPose3(transformKey).translation();
ty = t(2);
fx = result.atCal3_S2(calibrationKey).fx();
fy = result.atCal3_S2(calibrationKey).fy();
px = result.atCal3_S2(calibrationKey).px();
py = result.atCal3_S2(calibrationKey).py();
text(1,5,5,sprintf('Y-Transform(0.0): %0.2f',ty));
text(1,5,3,sprintf('fx(900): %.0f',fx));
text(1,5,1,sprintf('fy(900): %.0f',fy));
@ -342,10 +346,10 @@ end
fprintf('Cheirality Exception count: %d\n', cheirality_exception_count);
disp('Transform after optimization');
result.at(transformKey)
result.atPose3(transformKey)
disp('Calibration after optimization');
result.at(calibrationKey)
result.atCal3_S2(calibrationKey)
disp('Bias after optimization');
currentBias

2
matlab/unstable_examples/TransformProjectionFactorExample.m
View File

@ -33,7 +33,7 @@ y_shift = Point3(0,1,0);
% insert shifted points
for i=1:nrPoints
initial.insert(100+i,landmarks{i}.compose(y_shift));
initial.insert(100+i,landmarks{i} + y_shift);
end
figure(1);

5
matlab/unstable_examples/TransformProjectionFactorExampleISAM.m
View File

@ -47,7 +47,7 @@ y_shift = Point3(0,1,0);
% insert shifted points
for i=1:nrPoints
initial.insert(100+i,landmarks{i}.compose(y_shift));
initial.insert(100+i,landmarks{i} + y_shift);
end
figure(1);
@ -146,7 +146,8 @@ for i=1:20
plotPoint3(result.atPoint3(l),'g');
end
ty = result.atPose3(1000).translation().y();
t = result.atPose3(1000).translation();
ty = t(2);
text(5,5,5,sprintf('Y-Transform: %0.2g',ty));
if(write_video)

6
matlab/unstable_examples/plot_projected_landmarks.m
View File

@ -25,9 +25,9 @@ for i = 0:measurement_keys.size-1
key_index = gtsam.symbolIndex(key);
p = landmarks.atPoint3(gtsam.symbol('l',key_index));
x(i+1) = p.x;
y(i+1) = p.y;
z(i+1) = p.z;
x(i+1) = p(1);
y(i+1) = p(2);
z(i+1) = p(3);
end

4
matlab/unstable_examples/project_landmarks.m
View File

@ -11,9 +11,9 @@ function [ measurements ] = project_landmarks( pose, landmarks, K )
z = camera.project(landmarks.atPoint3(symbol('l',i)));
% check bounding box
if z.x < 0 || z.x > 1280
if z(1) < 0 || z(1) > 1280
continue
elseif z.y < 0 || z.y > 960
elseif z(2) < 0 || z(2) > 960
continue
end

4
matlab/unstable_examples/testTSAMFactors.m
View File

@ -50,8 +50,8 @@ result = optimizer.optimize();
% Check result
CHECK('error',result.atPose2(100).equals(b1,1e-5))
CHECK('error',result.atPose2(10).equals(origin,1e-5))
CHECK('error',result.atPoint2(1).equals(Point2(0,1),1e-5))
CHECK('error',result.atPoint2(2).equals(Point2(0,1),1e-5))
CHECK('error',result.atPoint2(1) - Point2(0,1) < 1e-5)
CHECK('error',result.atPoint2(2) - Point2(0,1) < 1e-5)
CHECK('error',result.atPose2(20).equals(origin,1e-5))
CHECK('error',result.atPose2(200).equals(b2,1e-5))

107
python/CMakeLists.txt Normal file
View File

@ -0,0 +1,107 @@
set(GTSAM_PYTHON_BUILD_DIRECTORY ${PROJECT_BINARY_DIR}/python)
if (NOT GTSAM_BUILD_PYTHON)
return()
endif()
# Generate setup.py.
file(READ "${PROJECT_SOURCE_DIR}/README.md" README_CONTENTS)
configure_file(${PROJECT_SOURCE_DIR}/python/setup.py.in
${GTSAM_PYTHON_BUILD_DIRECTORY}/setup.py)
set(WRAP_USE_CUSTOM_PYTHON_LIBRARY ${GTSAM_USE_CUSTOM_PYTHON_LIBRARY})
set(WRAP_PYTHON_VERSION ${GTSAM_PYTHON_VERSION})
include(PybindWrap)
add_custom_target(gtsam_header DEPENDS "${PROJECT_SOURCE_DIR}/gtsam/gtsam.i")
add_custom_target(gtsam_unstable_header DEPENDS "${PROJECT_SOURCE_DIR}/gtsam_unstable/gtsam_unstable.i")
# ignoring the non-concrete types (type aliases)
set(ignore
gtsam::Point2
gtsam::Point3
gtsam::LieVector
gtsam::LieMatrix
gtsam::ISAM2ThresholdMapValue
gtsam::FactorIndices
gtsam::FactorIndexSet
gtsam::BetweenFactorPose3s
gtsam::Point2Vector
gtsam::Pose3Vector
gtsam::KeyVector)
pybind_wrap(gtsam_py # target
${PROJECT_SOURCE_DIR}/gtsam/gtsam.i # interface_header
"gtsam.cpp" # generated_cpp
"gtsam" # module_name
"gtsam" # top_namespace
"${ignore}" # ignore_classes
${PROJECT_SOURCE_DIR}/python/gtsam/gtsam.tpl
gtsam # libs
"gtsam;gtsam_header" # dependencies
ON # use_boost
)
set_target_properties(gtsam_py PROPERTIES
INSTALL_RPATH "${CMAKE_INSTALL_PREFIX}/lib"
INSTALL_RPATH_USE_LINK_PATH TRUE
OUTPUT_NAME "gtsam"
LIBRARY_OUTPUT_DIRECTORY "${GTSAM_PYTHON_BUILD_DIRECTORY}/gtsam"
DEBUG_POSTFIX "" # Otherwise you will have a wrong name
RELWITHDEBINFO_POSTFIX "" # Otherwise you will have a wrong name
)
set(GTSAM_MODULE_PATH ${GTSAM_PYTHON_BUILD_DIRECTORY}/gtsam)
# Symlink all tests .py files to build folder.
create_symlinks("${CMAKE_CURRENT_SOURCE_DIR}/gtsam"
"${GTSAM_MODULE_PATH}")
if(GTSAM_UNSTABLE_BUILD_PYTHON)
set(ignore
gtsam::Point2
gtsam::Point3
gtsam::LieVector
gtsam::LieMatrix
gtsam::ISAM2ThresholdMapValue
gtsam::FactorIndices
gtsam::FactorIndexSet
gtsam::BetweenFactorPose3s
gtsam::Point2Vector
gtsam::Pose3Vector
gtsam::KeyVector
gtsam::FixedLagSmootherKeyTimestampMapValue)
pybind_wrap(gtsam_unstable_py # target
${PROJECT_SOURCE_DIR}/gtsam_unstable/gtsam_unstable.i # interface_header
"gtsam_unstable.cpp" # generated_cpp
"gtsam_unstable" # module_name
"gtsam" # top_namespace
"${ignore}" # ignore_classes
${PROJECT_SOURCE_DIR}/python/gtsam_unstable/gtsam_unstable.tpl
gtsam_unstable # libs
"gtsam_unstable;gtsam_unstable_header" # dependencies
ON # use_boost
)
set_target_properties(gtsam_unstable_py PROPERTIES
INSTALL_RPATH "${CMAKE_INSTALL_PREFIX}/lib"
INSTALL_RPATH_USE_LINK_PATH TRUE
OUTPUT_NAME "gtsam_unstable"
LIBRARY_OUTPUT_DIRECTORY "${GTSAM_PYTHON_BUILD_DIRECTORY}/gtsam_unstable"
DEBUG_POSTFIX "" # Otherwise you will have a wrong name
RELWITHDEBINFO_POSTFIX "" # Otherwise you will have a wrong name
)
set(GTSAM_UNSTABLE_MODULE_PATH ${GTSAM_PYTHON_BUILD_DIRECTORY}/gtsam_unstable)
# Symlink all tests .py files to build folder.
create_symlinks("${CMAKE_CURRENT_SOURCE_DIR}/gtsam_unstable"
"${GTSAM_UNSTABLE_MODULE_PATH}")
endif()
set(GTSAM_PYTHON_INSTALL_TARGET python-install)
add_custom_target(${GTSAM_PYTHON_INSTALL_TARGET}
COMMAND ${PYTHON_EXECUTABLE} ${GTSAM_PYTHON_BUILD_DIRECTORY}/setup.py install
DEPENDS gtsam_py gtsam_unstable_py
WORKING_DIRECTORY ${GTSAM_PYTHON_BUILD_DIRECTORY})

65
python/README.md Normal file
View File

@ -0,0 +1,65 @@
# README
# Python Wrapper
This is the Python wrapper around the GTSAM C++ library. We use our custom [wrap library](https://github.com/borglab/wrap) to generate the bindings to the underlying C++ code.
## Requirements
- If you want to build the GTSAM python library for a specific python version (eg 3.6),
use the `-DGTSAM_PYTHON_VERSION=3.6` option when running `cmake` otherwise the default interpreter will be used.
- If the interpreter is inside an environment (such as an anaconda environment or virtualenv environment),
then the environment should be active while building GTSAM.
- This wrapper needs `pyparsing(>=2.4.2)`, and `numpy(>=1.11.0)`. These can be installed as follows:
```bash
pip install -r <gtsam_folder>/python/requirements.txt
```
## Install
- Run cmake with the `GTSAM_BUILD_PYTHON` cmake flag enabled to configure building the wrapper. The wrapped module will be built and copied to the directory `<PROJECT_BINARY_DIR>/python`.
- Build GTSAM and the wrapper with `make` (or `ninja` if you use `-GNinja`).
- To install, simply run `make python-install` (`ninja python-install`).
- The same command can be used to install into a virtual environment if it is active.
- **NOTE**: if you don't want GTSAM to install to a system directory such as `/usr/local`, pass `-DCMAKE_INSTALL_PREFIX="./install"` to cmake to install GTSAM to a subdirectory of the build directory.
- You can also directly run `make python-install` without running `make`, and it will compile all the dependencies accordingly.
## Unit Tests
The Python toolbox also has a small set of unit tests located in the
test directory. To run them:
```bash
cd <GTSAM_SOURCE_DIRECTORY>/python/gtsam/tests
python -m unittest discover
```
## Utils
TODO
## Examples
TODO
## Writing Your Own Scripts
See the tests for examples.
### Some Important Notes:
- Vector/Matrix:
- GTSAM expects double-precision floating point vectors and matrices.
Hence, you should pass numpy matrices with `dtype=float`, or `float64`, to avoid any conversion needed.
- Also, GTSAM expects _column-major_ matrices, unlike the default storage
scheme in numpy. But this is only performance-related as `pybind11` should translate them when needed. However, this will result a copy if your matrix is not in the expected type
and storage order.
## Wrapping Custom GTSAM-based Project
Please refer to the template project and the corresponding tutorial available [here](https://github.com/borglab/GTSAM-project-python).

27
python/gtsam/__init__.py Normal file
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@ -0,0 +1,27 @@
from .gtsam import *
def _init():
"""This function is to add shims for the long-gone Point2 and Point3 types"""
import numpy as np
global Point2 # export function
def Point2(x=0, y=0):
"""Shim for the deleted Point2 type."""
return np.array([x, y], dtype=float)
global Point3 # export function
def Point3(x=0, y=0, z=0):
"""Shim for the deleted Point3 type."""
return np.array([x, y, z], dtype=float)
# for interactive debugging
if __name__ == "__main__":
# we want all definitions accessible
globals().update(locals())
_init()

6
cython/gtsam/examples/DogLegOptimizerExample.py → python/gtsam/examples/DogLegOptimizerExample.py
View File

@ -35,17 +35,17 @@ def run(args):
graph = gtsam.NonlinearFactorGraph()
# Priors
prior = gtsam.noiseModel_Isotropic.Sigma(3, 1)
prior = gtsam.noiseModel.Isotropic.Sigma(3, 1)
graph.add(gtsam.PriorFactorPose2(11, T11, prior))
graph.add(gtsam.PriorFactorPose2(21, T21, prior))
# Odometry
model = gtsam.noiseModel_Diagonal.Sigmas(np.array([0.01, 0.01, 0.3]))
model = gtsam.noiseModel.Diagonal.Sigmas(np.array([0.01, 0.01, 0.3]))
graph.add(gtsam.BetweenFactorPose2(11, 12, T11.between(T12), model))
graph.add(gtsam.BetweenFactorPose2(21, 22, T21.between(T22), model))
# Range
model_rho = gtsam.noiseModel_Isotropic.Sigma(1, 0.01)
model_rho = gtsam.noiseModel.Isotropic.Sigma(1, 0.01)
graph.add(gtsam.RangeFactorPose2(12, 22, 1.0, model_rho))
params = gtsam.DoglegParams()

4
cython/gtsam/examples/GPSFactorExample.py → python/gtsam/examples/GPSFactorExample.py
View File

@ -26,8 +26,8 @@ lon0 = -84.30626
h0 = 274
# Create noise models
GPS_NOISE = gtsam.noiseModel_Isotropic.Sigma(3, 0.1)
PRIOR_NOISE = gtsam.noiseModel_Isotropic.Sigma(6, 0.25)
GPS_NOISE = gtsam.noiseModel.Isotropic.Sigma(3, 0.1)
PRIOR_NOISE = gtsam.noiseModel.Isotropic.Sigma(6, 0.25)
# Create an empty nonlinear factor graph
graph = gtsam.NonlinearFactorGraph()

180
python/gtsam/examples/ImuFactorExample.py Normal file
View File

@ -0,0 +1,180 @@
"""
GTSAM Copyright 2010-2019, Georgia Tech Research Corporation,
Atlanta, Georgia 30332-0415
All Rights Reserved
See LICENSE for the license information
A script validating and demonstrating the ImuFactor inference.
Author: Frank Dellaert, Varun Agrawal
"""
from __future__ import print_function
import argparse
import math
import gtsam
import matplotlib.pyplot as plt
import numpy as np
from gtsam.symbol_shorthand import B, V, X
from gtsam.utils.plot import plot_pose3
from mpl_toolkits.mplot3d import Axes3D
from PreintegrationExample import POSES_FIG, PreintegrationExample
BIAS_KEY = B(0)
np.set_printoptions(precision=3, suppress=True)
class ImuFactorExample(PreintegrationExample):
def __init__(self, twist_scenario="sick_twist"):
self.velocity = np.array([2, 0, 0])
self.priorNoise = gtsam.noiseModel.Isotropic.Sigma(6, 0.1)
self.velNoise = gtsam.noiseModel.Isotropic.Sigma(3, 0.1)
# Choose one of these twists to change scenario:
twist_scenarios = dict(
zero_twist=(np.zeros(3), np.zeros(3)),
forward_twist=(np.zeros(3), self.velocity),
loop_twist=(np.array([0, -math.radians(30), 0]), self.velocity),
sick_twist=(np.array([math.radians(30), -math.radians(30), 0]),
self.velocity)
)
accBias = np.array([-0.3, 0.1, 0.2])
gyroBias = np.array([0.1, 0.3, -0.1])
bias = gtsam.imuBias.ConstantBias(accBias, gyroBias)
dt = 1e-2
super(ImuFactorExample, self).__init__(twist_scenarios[twist_scenario],
bias, dt)
def addPrior(self, i, graph):
state = self.scenario.navState(i)
graph.push_back(gtsam.PriorFactorPose3(
X(i), state.pose(), self.priorNoise))
graph.push_back(gtsam.PriorFactorVector(
V(i), state.velocity(), self.velNoise))
def run(self, T=12, compute_covariances=False, verbose=True):
graph = gtsam.NonlinearFactorGraph()
# initialize data structure for pre-integrated IMU measurements
pim = gtsam.PreintegratedImuMeasurements(self.params, self.actualBias)
T = 12
num_poses = T # assumes 1 factor per second
initial = gtsam.Values()
initial.insert(BIAS_KEY, self.actualBias)
# simulate the loop
i = 0 # state index
initial_state_i = self.scenario.navState(0)
initial.insert(X(i), initial_state_i.pose())
initial.insert(V(i), initial_state_i.velocity())
# add prior on beginning
self.addPrior(0, graph)
for k, t in enumerate(np.arange(0, T, self.dt)):
# get measurements and add them to PIM
measuredOmega = self.runner.measuredAngularVelocity(t)
measuredAcc = self.runner.measuredSpecificForce(t)
pim.integrateMeasurement(measuredAcc, measuredOmega, self.dt)
# Plot IMU many times
if k % 10 == 0:
self.plotImu(t, measuredOmega, measuredAcc)
if (k+1) % int(1 / self.dt) == 0:
# Plot every second
self.plotGroundTruthPose(t, scale=1)
plt.title("Ground Truth Trajectory")
# create IMU factor every second
factor = gtsam.ImuFactor(X(i), V(i),
X(i + 1), V(i + 1),
BIAS_KEY, pim)
graph.push_back(factor)
if verbose:
print(factor)
print(pim.predict(actual_state_i, self.actualBias))
pim.resetIntegration()
rotationNoise = gtsam.Rot3.Expmap(np.random.randn(3)*0.1)
translationNoise = gtsam.Point3(*np.random.randn(3)*1)
poseNoise = gtsam.Pose3(rotationNoise, translationNoise)
actual_state_i = self.scenario.navState(t + self.dt)
print("Actual state at {0}:\n{1}".format(
t+self.dt, actual_state_i))
noisy_state_i = gtsam.NavState(
actual_state_i.pose().compose(poseNoise),
actual_state_i.velocity() + np.random.randn(3)*0.1)
initial.insert(X(i+1), noisy_state_i.pose())
initial.insert(V(i+1), noisy_state_i.velocity())
i += 1
# add priors on end
# self.addPrior(num_poses - 1, graph)
initial.print_("Initial values:")
# optimize using Levenberg-Marquardt optimization
params = gtsam.LevenbergMarquardtParams()
params.setVerbosityLM("SUMMARY")
optimizer = gtsam.LevenbergMarquardtOptimizer(graph, initial, params)
result = optimizer.optimize()
result.print_("Optimized values:")
if compute_covariances:
# Calculate and print marginal covariances
marginals = gtsam.Marginals(graph, result)
print("Covariance on bias:\n",
marginals.marginalCovariance(BIAS_KEY))
for i in range(num_poses):
print("Covariance on pose {}:\n{}\n".format(
i, marginals.marginalCovariance(X(i))))
print("Covariance on vel {}:\n{}\n".format(
i, marginals.marginalCovariance(V(i))))
# Plot resulting poses
i = 0
while result.exists(X(i)):
pose_i = result.atPose3(X(i))
plot_pose3(POSES_FIG+1, pose_i, 1)
i += 1
plt.title("Estimated Trajectory")
gtsam.utils.plot.set_axes_equal(POSES_FIG+1)
print("Bias Values", result.atConstantBias(BIAS_KEY))
plt.ioff()
plt.show()
if __name__ == '__main__':
parser = argparse.ArgumentParser("ImuFactorExample.py")
parser.add_argument("--twist_scenario",
default="sick_twist",
choices=("zero_twist", "forward_twist", "loop_twist", "sick_twist"))
parser.add_argument("--time", "-T", default=12,
type=int, help="Total time in seconds")
parser.add_argument("--compute_covariances",
default=False, action='store_true')
parser.add_argument("--verbose", default=False, action='store_true')
args = parser.parse_args()
ImuFactorExample(args.twist_scenario).run(
args.time, args.compute_covariances, args.verbose)

130
cython/gtsam/examples/ImuFactorExample2.py → python/gtsam/examples/ImuFactorISAM2Example.py
View File

@ -1,6 +1,6 @@
"""
iSAM2 example with ImuFactor.
Author: Robert Truax (C++), Frank Dellaert (Python)
Author: Robert Truax (C++), Frank Dellaert, Varun Agrawal
"""
# pylint: disable=invalid-name, E1101
@ -9,7 +9,6 @@ from __future__ import print_function
import math
import gtsam
import gtsam.utils.plot as gtsam_plot
import matplotlib.pyplot as plt
import numpy as np
from gtsam import (ISAM2, BetweenFactorConstantBias, Cal3_S2,
@ -17,9 +16,8 @@ from gtsam import (ISAM2, BetweenFactorConstantBias, Cal3_S2,
PinholeCameraCal3_S2, Point3, Pose3,
PriorFactorConstantBias, PriorFactorPose3,
PriorFactorVector, Rot3, Values)
from gtsam import symbol_shorthand_B as B
from gtsam import symbol_shorthand_V as V
from gtsam import symbol_shorthand_X as X
from gtsam.symbol_shorthand import B, V, X
from gtsam.utils import plot
from mpl_toolkits.mplot3d import Axes3D # pylint: disable=W0611
@ -28,46 +26,45 @@ def vector3(x, y, z):
return np.array([x, y, z], dtype=np.float)
def ISAM2_plot(values, fignum=0):
"""Plot poses."""
fig = plt.figure(fignum)
axes = fig.gca(projection='3d')
plt.cla()
i = 0
min_bounds = 0, 0, 0
max_bounds = 0, 0, 0
while values.exists(X(i)):
pose_i = values.atPose3(X(i))
gtsam_plot.plot_pose3(fignum, pose_i, 10)
position = pose_i.translation().vector()
min_bounds = [min(v1, v2) for (v1, v2) in zip(position, min_bounds)]
max_bounds = [max(v1, v2) for (v1, v2) in zip(position, max_bounds)]
# max_bounds = min(pose_i.x(), max_bounds[0]), 0, 0
i += 1
# draw
axes.set_xlim3d(min_bounds[0]-1, max_bounds[0]+1)
axes.set_ylim3d(min_bounds[1]-1, max_bounds[1]+1)
axes.set_zlim3d(min_bounds[2]-1, max_bounds[2]+1)
plt.pause(1)
# IMU preintegration parameters
# Default Params for a Z-up navigation frame, such as ENU: gravity points along negative Z-axis
g = 9.81
n_gravity = vector3(0, 0, -g)
PARAMS = gtsam.PreintegrationParams.MakeSharedU(g)
I = np.eye(3)
PARAMS.setAccelerometerCovariance(I * 0.1)
PARAMS.setGyroscopeCovariance(I * 0.1)
PARAMS.setIntegrationCovariance(I * 0.1)
PARAMS.setUse2ndOrderCoriolis(False)
PARAMS.setOmegaCoriolis(vector3(0, 0, 0))
BIAS_COVARIANCE = gtsam.noiseModel_Isotropic.Variance(6, 0.1)
DELTA = Pose3(Rot3.Rodrigues(0, 0, 0),
Point3(0.05, -0.10, 0.20))
def preintegration_parameters():
# IMU preintegration parameters
# Default Params for a Z-up navigation frame, such as ENU: gravity points along negative Z-axis
PARAMS = gtsam.PreintegrationParams.MakeSharedU(g)
I = np.eye(3)
PARAMS.setAccelerometerCovariance(I * 0.1)
PARAMS.setGyroscopeCovariance(I * 0.1)
PARAMS.setIntegrationCovariance(I * 0.1)
PARAMS.setUse2ndOrderCoriolis(False)
PARAMS.setOmegaCoriolis(vector3(0, 0, 0))
BIAS_COVARIANCE = gtsam.noiseModel.Isotropic.Variance(6, 0.1)
DELTA = Pose3(Rot3.Rodrigues(0, 0, 0),
Point3(0.05, -0.10, 0.20))
return PARAMS, BIAS_COVARIANCE, DELTA
def get_camera(radius):
up = Point3(0, 0, 1)
target = Point3(0, 0, 0)
position = Point3(radius, 0, 0)
camera = PinholeCameraCal3_S2.Lookat(position, target, up, Cal3_S2())
return camera
def get_scenario(radius, pose_0, angular_velocity, delta_t):
"""Create the set of ground-truth landmarks and poses"""
angular_velocity_vector = vector3(0, -angular_velocity, 0)
linear_velocity_vector = vector3(radius * angular_velocity, 0, 0)
scenario = ConstantTwistScenario(
angular_velocity_vector, linear_velocity_vector, pose_0)
return scenario
def IMU_example():
@ -75,23 +72,17 @@ def IMU_example():
# Start with a camera on x-axis looking at origin
radius = 30
up = Point3(0, 0, 1)
target = Point3(0, 0, 0)
position = Point3(radius, 0, 0)
camera = PinholeCameraCal3_S2.Lookat(position, target, up, Cal3_S2())
camera = get_camera(radius)
pose_0 = camera.pose()
# Create the set of ground-truth landmarks and poses
angular_velocity = math.radians(180) # rad/sec
delta_t = 1.0/18 # makes for 10 degrees per step
angular_velocity = math.radians(180) # rad/sec
scenario = get_scenario(radius, pose_0, angular_velocity, delta_t)
angular_velocity_vector = vector3(0, -angular_velocity, 0)
linear_velocity_vector = vector3(radius * angular_velocity, 0, 0)
scenario = ConstantTwistScenario(
angular_velocity_vector, linear_velocity_vector, pose_0)
PARAMS, BIAS_COVARIANCE, DELTA = preintegration_parameters()
# Create a factor graph
newgraph = NonlinearFactorGraph()
graph = NonlinearFactorGraph()
# Create (incremental) ISAM2 solver
isam = ISAM2()
@ -102,23 +93,23 @@ def IMU_example():
# Add a prior on pose x0. This indirectly specifies where the origin is.
# 30cm std on x,y,z 0.1 rad on roll,pitch,yaw
noise = gtsam.noiseModel_Diagonal.Sigmas(
noise = gtsam.noiseModel.Diagonal.Sigmas(
np.array([0.1, 0.1, 0.1, 0.3, 0.3, 0.3]))
newgraph.push_back(PriorFactorPose3(X(0), pose_0, noise))
graph.push_back(PriorFactorPose3(X(0), pose_0, noise))
# Add imu priors
biasKey = B(0)
biasnoise = gtsam.noiseModel_Isotropic.Sigma(6, 0.1)
biasprior = PriorFactorConstantBias(biasKey, gtsam.imuBias_ConstantBias(),
biasnoise = gtsam.noiseModel.Isotropic.Sigma(6, 0.1)
biasprior = PriorFactorConstantBias(biasKey, gtsam.imuBias.ConstantBias(),
biasnoise)
newgraph.push_back(biasprior)
initialEstimate.insert(biasKey, gtsam.imuBias_ConstantBias())
velnoise = gtsam.noiseModel_Isotropic.Sigma(3, 0.1)
graph.push_back(biasprior)
initialEstimate.insert(biasKey, gtsam.imuBias.ConstantBias())
velnoise = gtsam.noiseModel.Isotropic.Sigma(3, 0.1)
# Calculate with correct initial velocity
n_velocity = vector3(0, angular_velocity * radius, 0)
velprior = PriorFactorVector(V(0), n_velocity, velnoise)
newgraph.push_back(velprior)
graph.push_back(velprior)
initialEstimate.insert(V(0), n_velocity)
accum = gtsam.PreintegratedImuMeasurements(PARAMS)
@ -139,9 +130,9 @@ def IMU_example():
if i % 5 == 0:
biasKey += 1
factor = BetweenFactorConstantBias(
biasKey - 1, biasKey, gtsam.imuBias_ConstantBias(), BIAS_COVARIANCE)
newgraph.add(factor)
initialEstimate.insert(biasKey, gtsam.imuBias_ConstantBias())
biasKey - 1, biasKey, gtsam.imuBias.ConstantBias(), BIAS_COVARIANCE)
graph.add(factor)
initialEstimate.insert(biasKey, gtsam.imuBias.ConstantBias())
# Predict acceleration and gyro measurements in (actual) body frame
nRb = scenario.rotation(t).matrix()
@ -152,21 +143,24 @@ def IMU_example():
# Add Imu Factor
imufac = ImuFactor(X(i - 1), V(i - 1), X(i), V(i), biasKey, accum)
newgraph.add(imufac)
graph.add(imufac)
# insert new velocity, which is wrong
initialEstimate.insert(V(i), n_velocity)
accum.resetIntegration()
# Incremental solution
isam.update(newgraph, initialEstimate)
isam.update(graph, initialEstimate)
result = isam.calculateEstimate()
ISAM2_plot(result)
plot.plot_incremental_trajectory(0, result,
start=i, scale=3, time_interval=0.01)
# reset
newgraph = NonlinearFactorGraph()
graph = NonlinearFactorGraph()
initialEstimate.clear()
plt.show()
if __name__ == '__main__':
IMU_example()

4
cython/gtsam/examples/OdometryExample.py → python/gtsam/examples/OdometryExample.py
View File

@ -21,8 +21,8 @@ import matplotlib.pyplot as plt
import gtsam.utils.plot as gtsam_plot
# Create noise models
ODOMETRY_NOISE = gtsam.noiseModel_Diagonal.Sigmas(np.array([0.2, 0.2, 0.1]))
PRIOR_NOISE = gtsam.noiseModel_Diagonal.Sigmas(np.array([0.3, 0.3, 0.1]))
ODOMETRY_NOISE = gtsam.noiseModel.Diagonal.Sigmas(np.array([0.2, 0.2, 0.1]))
PRIOR_NOISE = gtsam.noiseModel.Diagonal.Sigmas(np.array([0.3, 0.3, 0.1]))
# Create an empty nonlinear factor graph
graph = gtsam.NonlinearFactorGraph()

6
cython/gtsam/examples/PlanarManipulatorExample.py → python/gtsam/examples/PlanarManipulatorExample.py
View File

@ -167,13 +167,11 @@ class ThreeLinkArm(object):
axes = fig.gca()
sXl1 = Pose2(0, 0, math.radians(90))
t = sXl1.translation()
p1 = np.array([t.x(), t.y()])
p1 = sXl1.translation()
gtsam_plot.plot_pose2_on_axes(axes, sXl1)
def plot_line(p, g, color):
t = g.translation()
q = np.array([t.x(), t.y()])
q = g.translation()
line = np.append(p[np.newaxis], q[np.newaxis], axis=0)
axes.plot(line[:, 0], line[:, 1], color)
return q

12
cython/gtsam/examples/PlanarSLAMExample.py → python/gtsam/examples/PlanarSLAMExample.py
View File

@ -13,15 +13,15 @@ Author: Alex Cunningham (C++), Kevin Deng & Frank Dellaert (Python)
from __future__ import print_function
import gtsam
import numpy as np
from gtsam import symbol_shorthand_L as L
from gtsam import symbol_shorthand_X as X
import gtsam
from gtsam.symbol_shorthand import X, L
# Create noise models
PRIOR_NOISE = gtsam.noiseModel_Diagonal.Sigmas(np.array([0.3, 0.3, 0.1]))
ODOMETRY_NOISE = gtsam.noiseModel_Diagonal.Sigmas(np.array([0.2, 0.2, 0.1]))
MEASUREMENT_NOISE = gtsam.noiseModel_Diagonal.Sigmas(np.array([0.1, 0.2]))
PRIOR_NOISE = gtsam.noiseModel.Diagonal.Sigmas(np.array([0.3, 0.3, 0.1]))
ODOMETRY_NOISE = gtsam.noiseModel.Diagonal.Sigmas(np.array([0.2, 0.2, 0.1]))
MEASUREMENT_NOISE = gtsam.noiseModel.Diagonal.Sigmas(np.array([0.1, 0.2]))
# Create an empty nonlinear factor graph
graph = gtsam.NonlinearFactorGraph()

5
cython/gtsam/examples/Pose2SLAMExample.py → python/gtsam/examples/Pose2SLAMExample.py
View File

@ -27,10 +27,9 @@ def vector3(x, y, z):
"""Create 3d double numpy array."""
return np.array([x, y, z], dtype=np.float)
# Create noise models
PRIOR_NOISE = gtsam.noiseModel_Diagonal.Sigmas(vector3(0.3, 0.3, 0.1))
ODOMETRY_NOISE = gtsam.noiseModel_Diagonal.Sigmas(vector3(0.2, 0.2, 0.1))
PRIOR_NOISE = gtsam.noiseModel.Diagonal.Sigmas(vector3(0.3, 0.3, 0.1))
ODOMETRY_NOISE = gtsam.noiseModel.Diagonal.Sigmas(vector3(0.2, 0.2, 0.1))
# 1. Create a factor graph container and add factors to it
graph = gtsam.NonlinearFactorGraph()

4
cython/gtsam/examples/Pose2SLAMExample_g2o.py → python/gtsam/examples/Pose2SLAMExample_g2o.py
View File

@ -53,7 +53,7 @@ graph, initial = gtsam.readG2o(g2oFile, is3D)
assert args.kernel == "none", "Supplied kernel type is not yet implemented"
# Add prior on the pose having index (key) = 0
priorModel = gtsam.noiseModel_Diagonal.Variances(vector3(1e-6, 1e-6, 1e-8))
priorModel = gtsam.noiseModel.Diagonal.Variances(vector3(1e-6, 1e-6, 1e-8))
graph.add(gtsam.PriorFactorPose2(0, gtsam.Pose2(), priorModel))
params = gtsam.GaussNewtonParams()
@ -82,7 +82,7 @@ else:
print ("Done!")
if args.plot:
resultPoses = gtsam.utilities_extractPose2(result)
resultPoses = gtsam.utilities.extractPose2(result)
for i in range(resultPoses.shape[0]):
plot.plot_pose2(1, gtsam.Pose2(resultPoses[i, :]))
plt.show()

6
cython/gtsam/examples/Pose3SLAMExample_g2o.py → python/gtsam/examples/Pose3SLAMExample_g2o.py
View File

@ -39,11 +39,11 @@ is3D = True
graph, initial = gtsam.readG2o(g2oFile, is3D)
# Add Prior on the first key
priorModel = gtsam.noiseModel_Diagonal.Variances(vector6(1e-6, 1e-6, 1e-6,
priorModel = gtsam.noiseModel.Diagonal.Variances(vector6(1e-6, 1e-6, 1e-6,
1e-4, 1e-4, 1e-4))
print("Adding prior to g2o file ")
firstKey = initial.keys().at(0)
firstKey = initial.keys()[0]
graph.add(gtsam.PriorFactorPose3(firstKey, gtsam.Pose3(), priorModel))
params = gtsam.GaussNewtonParams()
@ -65,7 +65,7 @@ else:
print ("Done!")
if args.plot:
resultPoses = gtsam.utilities_allPose3s(result)
resultPoses = gtsam.utilities.allPose3s(result)
for i in range(resultPoses.size()):
plot.plot_pose3(1, resultPoses.atPose3(i))
plt.show()

4
cython/gtsam/examples/Pose3SLAMExample_initializePose3Chordal.py → python/gtsam/examples/Pose3SLAMExample_initializePose3Chordal.py
View File

@ -24,9 +24,9 @@ is3D = True
graph, initial = gtsam.readG2o(g2oFile, is3D)
# Add prior on the first key. TODO: assumes first key ios z
priorModel = gtsam.noiseModel_Diagonal.Variances(
priorModel = gtsam.noiseModel.Diagonal.Variances(
np.array([1e-6, 1e-6, 1e-6, 1e-4, 1e-4, 1e-4]))
firstKey = initial.keys().at(0)
firstKey = initial.keys()[0]
graph.add(gtsam.PriorFactorPose3(0, gtsam.Pose3(), priorModel))
# Initializing Pose3 - chordal relaxation"

47
cython/gtsam/examples/PreintegrationExample.py → python/gtsam/examples/PreintegrationExample.py
View File

@ -10,12 +10,11 @@ A script validating the Preintegration of IMU measurements
import math
import gtsam
import matplotlib.pyplot as plt
import numpy as np
from mpl_toolkits.mplot3d import Axes3D
import gtsam
from gtsam.utils.plot import plot_pose3
from mpl_toolkits.mplot3d import Axes3D
IMU_FIG = 1
POSES_FIG = 2
@ -68,60 +67,62 @@ class PreintegrationExample(object):
else:
accBias = np.array([0, 0.1, 0])
gyroBias = np.array([0, 0, 0])
self.actualBias = gtsam.imuBias_ConstantBias(accBias, gyroBias)
self.actualBias = gtsam.imuBias.ConstantBias(accBias, gyroBias)
self.runner = gtsam.ScenarioRunner(
self.scenario, self.params, self.dt, self.actualBias)
fig, self.axes = plt.subplots(4, 3)
fig.set_tight_layout(True)
def plotImu(self, t, measuredOmega, measuredAcc):
plt.figure(IMU_FIG)
# plot angular velocity
omega_b = self.scenario.omega_b(t)
for i, (label, color) in enumerate(zip(self.labels, self.colors)):
plt.subplot(4, 3, i + 1)
plt.scatter(t, omega_b[i], color='k', marker='.')
plt.scatter(t, measuredOmega[i], color=color, marker='.')
plt.xlabel('angular velocity ' + label)
ax = self.axes[0][i]
ax.scatter(t, omega_b[i], color='k', marker='.')
ax.scatter(t, measuredOmega[i], color=color, marker='.')
ax.set_xlabel('angular velocity ' + label)
# plot acceleration in nav
acceleration_n = self.scenario.acceleration_n(t)
for i, (label, color) in enumerate(zip(self.labels, self.colors)):
plt.subplot(4, 3, i + 4)
plt.scatter(t, acceleration_n[i], color=color, marker='.')
plt.xlabel('acceleration in nav ' + label)
ax = self.axes[1][i]
ax.scatter(t, acceleration_n[i], color=color, marker='.')
ax.set_xlabel('acceleration in nav ' + label)
# plot acceleration in body
acceleration_b = self.scenario.acceleration_b(t)
for i, (label, color) in enumerate(zip(self.labels, self.colors)):
plt.subplot(4, 3, i + 7)
plt.scatter(t, acceleration_b[i], color=color, marker='.')
plt.xlabel('acceleration in body ' + label)
ax = self.axes[2][i]
ax.scatter(t, acceleration_b[i], color=color, marker='.')
ax.set_xlabel('acceleration in body ' + label)
# plot actual specific force, as well as corrupted
actual = self.runner.actualSpecificForce(t)
for i, (label, color) in enumerate(zip(self.labels, self.colors)):
plt.subplot(4, 3, i + 10)
plt.scatter(t, actual[i], color='k', marker='.')
plt.scatter(t, measuredAcc[i], color=color, marker='.')
plt.xlabel('specific force ' + label)
ax = self.axes[3][i]
ax.scatter(t, actual[i], color='k', marker='.')
ax.scatter(t, measuredAcc[i], color=color, marker='.')
ax.set_xlabel('specific force ' + label)
def plotGroundTruthPose(self, t):
def plotGroundTruthPose(self, t, scale=0.3, time_interval=0.01):
# plot ground truth pose, as well as prediction from integrated IMU measurements
actualPose = self.scenario.pose(t)
plot_pose3(POSES_FIG, actualPose, 0.3)
t = actualPose.translation()
self.maxDim = max([abs(t.x()), abs(t.y()), abs(t.z()), self.maxDim])
self.maxDim = max([max(np.abs(t)), self.maxDim])
ax = plt.gca()
ax.set_xlim3d(-self.maxDim, self.maxDim)
ax.set_ylim3d(-self.maxDim, self.maxDim)
ax.set_zlim3d(-self.maxDim, self.maxDim)
plt.pause(0.01)
plt.pause(time_interval)
def run(self):
def run(self, T=12):
# simulate the loop
T = 12
for i, t in enumerate(np.arange(0, T, self.dt)):
measuredOmega = self.runner.measuredAngularVelocity(t)
measuredAcc = self.runner.measuredSpecificForce(t)

19
cython/gtsam/examples/README.md → python/gtsam/examples/README.md
View File

@ -1,17 +1,12 @@
These examples are almost identical to the old handwritten python wrapper
examples. However, there are just some slight name changes, for example
`noiseModel.Diagonal` becomes `noiseModel_Diagonal` etc...
Also, instead of `gtsam.Symbol('b', 0)` we can simply say `gtsam.symbol_shorthand_B(0)` or `B(0)` if we use python aliasing.
# Porting Progress
| C++ Example Name | Ported |
|-------------------------------------------------------|--------|
| CameraResectioning | |
| CreateSFMExampleData | |
| DiscreteBayesNet_FG | none of the required discrete functionality is exposed through cython |
| easyPoint2KalmanFilter | ExtendedKalmanFilter not exposed through cython |
| elaboratePoint2KalmanFilter | GaussianSequentialSolver not exposed through cython |
| DiscreteBayesNet_FG | none of the required discrete functionality is exposed through Python |
| easyPoint2KalmanFilter | ExtendedKalmanFilter not yet exposed through Python |
| elaboratePoint2KalmanFilter | GaussianSequentialSolver not yet exposed through Python |
| ImuFactorExample2 | X |
| ImuFactorsExample | |
| ISAM2Example_SmartFactor | |
@ -25,7 +20,7 @@ Also, instead of `gtsam.Symbol('b', 0)` we can simply say `gtsam.symbol_shorthan
| Pose2SLAMExample_g2o | X |
| Pose2SLAMExample_graph | |
| Pose2SLAMExample_graphviz | |
| Pose2SLAMExample_lago | lago not exposed through cython |
| Pose2SLAMExample_lago | lago not yet exposed through Python |
| Pose2SLAMStressTest | |
| Pose2SLAMwSPCG | |
| Pose3SLAMExample_changeKeys | |
@ -47,11 +42,11 @@ Also, instead of `gtsam.Symbol('b', 0)` we can simply say `gtsam.symbol_shorthan
| StereoVOExample | |
| StereoVOExample_large | |
| TimeTBB | |
| UGM_chain | discrete functionality not exposed |
| UGM_small | discrete functionality not exposed |
| UGM_chain | discrete functionality not yet exposed |
| UGM_small | discrete functionality not yet exposed |
| VisualISAM2Example | X |
| VisualISAMExample | X |
Extra Examples (with no C++ equivalent)
- PlanarManipulatorExample
- SFMData
- SFMData

19
cython/gtsam/examples/SFMExample.py → python/gtsam/examples/SFMExample.py
View File

@ -13,14 +13,15 @@ from __future__ import print_function
import gtsam
import matplotlib.pyplot as plt
import numpy as np
from gtsam import symbol_shorthand_L as L
from gtsam import symbol_shorthand_X as X
from gtsam import symbol_shorthand
L = symbol_shorthand.L
X = symbol_shorthand.X
from gtsam.examples import SFMdata
from gtsam.gtsam import (Cal3_S2, DoglegOptimizer,
from gtsam import (Cal3_S2, DoglegOptimizer,
GenericProjectionFactorCal3_S2, Marginals,
NonlinearFactorGraph, PinholeCameraCal3_S2, Point3,
Pose3, PriorFactorPoint3, PriorFactorPose3, Rot3,
SimpleCamera, Values)
Pose3, PriorFactorPoint3, PriorFactorPose3, Rot3, Values)
from gtsam.utils import plot
@ -56,7 +57,7 @@ def main():
K = Cal3_S2(50.0, 50.0, 0.0, 50.0, 50.0)
# Define the camera observation noise model
measurement_noise = gtsam.noiseModel_Isotropic.Sigma(2, 1.0) # one pixel in u and v
measurement_noise = gtsam.noiseModel.Isotropic.Sigma(2, 1.0) # one pixel in u and v
# Create the set of ground-truth landmarks
points = SFMdata.createPoints()
@ -69,7 +70,7 @@ def main():
# Add a prior on pose x1. This indirectly specifies where the origin is.
# 0.3 rad std on roll,pitch,yaw and 0.1m on x,y,z
pose_noise = gtsam.noiseModel_Diagonal.Sigmas(np.array([0.3, 0.3, 0.3, 0.1, 0.1, 0.1]))
pose_noise = gtsam.noiseModel.Diagonal.Sigmas(np.array([0.3, 0.3, 0.3, 0.1, 0.1, 0.1]))
factor = PriorFactorPose3(X(0), poses[0], pose_noise)
graph.push_back(factor)
@ -85,7 +86,7 @@ def main():
# 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.
point_noise = gtsam.noiseModel_Isotropic.Sigma(3, 0.1)
point_noise = gtsam.noiseModel.Isotropic.Sigma(3, 0.1)
factor = PriorFactorPoint3(L(0), points[0], point_noise)
graph.push_back(factor)
graph.print_('Factor Graph:\n')
@ -97,7 +98,7 @@ def main():
transformed_pose = pose.retract(0.1*np.random.randn(6,1))
initial_estimate.insert(X(i), transformed_pose)
for j, point in enumerate(points):
transformed_point = Point3(point.vector() + 0.1*np.random.randn(3))
transformed_point = point + 0.1*np.random.randn(3)
initial_estimate.insert(L(j), transformed_point)
initial_estimate.print_('Initial Estimates:\n')

3
cython/gtsam/examples/SFMdata.py → python/gtsam/examples/SFMdata.py
View File

@ -33,7 +33,8 @@ def createPoses(K):
poses = []
for theta in angles:
position = gtsam.Point3(radius*np.cos(theta),
radius*np.sin(theta), height)
radius*np.sin(theta),
height)
camera = gtsam.PinholeCameraCal3_S2.Lookat(position, target, up, K)
poses.append(camera.pose())
return poses

7
cython/gtsam/examples/SimpleRotation.py → python/gtsam/examples/SimpleRotation.py
View File

@ -10,10 +10,9 @@ This example will perform a relatively trivial optimization on
a single variable with a single factor.
"""
import gtsam
import numpy as np
from gtsam import symbol_shorthand_X as X
import gtsam
from gtsam.symbol_shorthand import X
def main():
"""
@ -33,7 +32,7 @@ def main():
"""
prior = gtsam.Rot2.fromAngle(np.deg2rad(30))
prior.print_('goal angle')
model = gtsam.noiseModel_Isotropic.Sigma(dim=1, sigma=np.deg2rad(1))
model = gtsam.noiseModel.Isotropic.Sigma(dim=1, sigma=np.deg2rad(1))
key = X(1)
factor = gtsam.PriorFactorRot2(key, prior, model)

11
cython/gtsam/examples/VisualISAM2Example.py → python/gtsam/examples/VisualISAM2Example.py
View File

@ -17,8 +17,7 @@ import gtsam
import gtsam.utils.plot as gtsam_plot
import matplotlib.pyplot as plt
import numpy as np
from gtsam import symbol_shorthand_L as L
from gtsam import symbol_shorthand_X as X
from gtsam.symbol_shorthand import L, X
from gtsam.examples import SFMdata
from mpl_toolkits.mplot3d import Axes3D # pylint: disable=W0611
@ -64,7 +63,7 @@ def visual_ISAM2_example():
K = gtsam.Cal3_S2(50.0, 50.0, 0.0, 50.0, 50.0)
# Define the camera observation noise model
measurement_noise = gtsam.noiseModel_Isotropic.Sigma(
measurement_noise = gtsam.noiseModel.Isotropic.Sigma(
2, 1.0) # one pixel in u and v
# Create the set of ground-truth landmarks
@ -110,12 +109,12 @@ def visual_ISAM2_example():
# at least twice before adding it to iSAM.
if i == 0:
# Add a prior on pose x0
pose_noise = gtsam.noiseModel_Diagonal.Sigmas(np.array(
pose_noise = gtsam.noiseModel.Diagonal.Sigmas(np.array(
[0.1, 0.1, 0.1, 0.3, 0.3, 0.3])) # 30cm std on x,y,z 0.1 rad on roll,pitch,yaw
graph.push_back(gtsam.PriorFactorPose3(X(0), poses[0], pose_noise))
# Add a prior on landmark l0
point_noise = gtsam.noiseModel_Isotropic.Sigma(3, 0.1)
point_noise = gtsam.noiseModel.Isotropic.Sigma(3, 0.1)
graph.push_back(gtsam.PriorFactorPoint3(
L(0), points[0], point_noise)) # add directly to graph
@ -123,7 +122,7 @@ def visual_ISAM2_example():
# Intentionally initialize the variables off from the ground truth
for j, point in enumerate(points):
initial_estimate.insert(L(j), gtsam.Point3(
point.x()-0.25, point.y()+0.20, point.z()+0.15))
point[0]-0.25, point[1]+0.20, point[2]+0.15))
else:
# Update iSAM with the new factors
isam.update(graph, initial_estimate)

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