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.. | ||
gtsam | ||
CMakeLists.txt | ||
README.md | ||
gtsam.h | ||
gtsam_short.h | ||
requirements.txt | ||
setup.py.in |
README.md
This is the Cython/Python wrapper around the GTSAM C++ library.
INSTALL
- This wrapper needs Cython(>=0.25), numpy and eigency, which can be installed as follows:
cd <gtsam_folder>/cython
pip install -r requirements.txt
pip install eigency
Note: Currently there's some issue with including eigency in requirements.txt
- Build and install gtsam using cmake with GTSAM_INSTALL_CYTHON_TOOLBOX enabled Note: By default, the wrapped module will be installed in <your_installation_folder>/gtsam_cython. Change that in GTSAM_CYTHON_TOOLBOX_PATH
UNIT TESTS
The Cython toolbox also has a small set of unit tests located in the test directory. To run them:
cd /Users/yourname/gtsam_cython # Change to wherever you installed the toolbox
python -m unittest discover
WRITING YOUR OWN SCRIPTS
See the tests for examples.
Some important notes:
-
Vector/Matrix: Due to a design choice of eigency, numpy.array matrices with the default order='A' will always be transposed in C++ no matter how you transpose it in Python. Use order='F', or use two functions Vector and Matrix in gtsam_utils/np_utils.py for your conveniences. These two functions also help to avoid a common but very subtle bug of using integers when creating numpy arrays, e.g. np.array([1,2,3]). These can't be an input for gtsam functions as they only accept floating-point arrays. For more details, see: https://github.com/wouterboomsma/eigency#storage-layout---why-arrays-are-sometimes-transposed
-
Inner namespace: Classes in inner namespace will be prefixed by _ in Python. Examples: noiseModel_Gaussian, noiseModel_mEstimator_Tukey
-
Casting from a base class to a derive class must be done explicitly. Examples:
noiseBase = factor.get_noiseModel()
noiseGaussian = dynamic_cast_noiseModel_Gaussian_noiseModel_Base(noiseBase)
WRAPPING YOUR OWN PROJECT THAT USES GTSAM
-
Set PYTHONPATH to include ${GTSAM_CYTHON_TOOLBOX_PATH}
- so that it can find gtsam Cython header: gtsam/gtsam.pxd
-
Create your setup.py.in as follows:
from distutils.core import setup
from distutils.extension import Extension
from Cython.Build import cythonize
import eigency
include_dirs = ["${CMAKE_SOURCE_DIR}/cpp", "${CMAKE_BINARY_DIR}"]
include_dirs += "${GTSAM_INCLUDE_DIR}".split(";")
include_dirs += eigency.get_includes(include_eigen=False)
setup(
ext_modules=cythonize(Extension(
"your_module_name",
sources=["your_module_name.pyx"],
include_dirs= include_dirs,
libraries=['gtsam'],
library_dirs=["${GTSAM_DIR}/../../"],
language="c++",
extra_compile_args=["-std=c++11"])),
)
- In your CMakeList.txt
find_package(GTSAM REQUIRED) # Make sure gtsam's install folder is in your PATH
set(CMAKE_MODULE_PATH "${CMAKE_MODULE_PATH}" "${GTSAM_DIR}/../GTSAMCMakeTools")
# Wrap
include(GtsamCythonWrap)
wrap_and_install_library_cython("your_project_interface.h"
"from gtsam.gtsam cimport *" # extra import of gtsam/gtsam.pxd Cython header
"path_to_your_setup.py.in"
"your_install_path"
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
- 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
☐ Unify cython/gtsam.h and the original gtsam.h
- 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, to FastVector<size_t>.
Completed/Cancelled: ✔ 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? ✔ wrap VariableIndex: why is it in inference? If need to, shouldn't have constructors to specific FactorGraphs @done (23-11-16 13:00) ✔ Global functions @done (22-11-16 21:00) ✔ [REFACTOR] typesEqual --> isSameSignature @done (22-11-16 21:00) ✔ Proper overloads (constructors, static methods, methods) @done (20-11-16 21:00) ✔ Allow overloading methods. The current solution is annoying!!! @done (20-11-16 21:00) ✔ Casting from parent and grandparents @done (16-11-16 17:00) ✔ Allow overloading constructors. The current solution is annoying!!! @done (16-11-16 17:00) ✔ Support "print obj" @done (16-11-16 17:00) ✔ methods for FastVector: at, [], ... @done (16-11-16 17:00) ✔ Cython: Key and size_t: traits<size_t> doesn't exist @done (16-09-12 18:34) ✔ KeyVector, KeyList, KeySet... @done (16-09-13 17:19) ✔ [Nice to have] parse typedef @done (16-09-13 17:19) ✔ ctypedef at correct places @done (16-09-12 18:34) ✔ expand template variable type in constructor/static methods? @done (16-09-12 18:34) ✔ NonlinearOptimizer: copy constructor deleted!!! @done (16-09-13 17:20) ✔ Value: no default constructor @done (16-09-13 17:20) ✔ ctypedef PriorFactor[Vector] PriorFactorVector @done (16-09-19 12:25) ✔ Delete duplicate methods in derived class @done (16-09-12 13:38) ✔ Fix return properly @done (16-09-11 17:14) ✔ handle pair @done (16-09-11 17:14) ✔ Eigency: ambiguous call: A(const T&) A(const Vector& v) and Eigency A(Map[Vector]& v) @done (16-09-11 07:59) ✔ Eigency: Constructor: ambiguous construct from Vector/Matrix @done (16-09-11 07:59) ✔ Eigency: Fix method template of Vector/Matrix: template argument is [Vector] while arugment is Map[Vector] @done (16-09-11 08:22) ✔ 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" ??
Installation: ☐ Prerequisite: - Users create venv and pip install requirements before compiling - Wrap cython script in gtsam/cython folder ☐ Install built module into venv?