This is the Python wrapper around the GTSAM C++ library. We use our custom wrap library to generate the bindings to the underlying C++ code.
For instructions on updating the version of the wrap library included in GTSAM to the latest version, please refer to the wrap README
-
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 runningcmake
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)
, andnumpy(>=1.11.0)
. These can be installed as follows:pip install -r <gtsam_folder>/python/requirements.txt
-
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
. For example, if your local Python version is 3.6.10, then you should run:cmake .. -DGTSAM_BUILD_PYTHON=1 -DGTSAM_PYTHON_VERSION=3.6.10
-
Build GTSAM and the wrapper with
make
(orninja
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 runningmake
, and it will compile all the dependencies accordingly.
The Python toolbox also has a small set of unit tests located in the
test directory.
To run them, use make python-test
.
TODO
TODO
See the tests for examples.
-
Vector/Matrix:
- GTSAM expects double-precision floating point vectors and matrices.
Hence, you should pass numpy matrices with
dtype=float
, orfloat64
, 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.
- GTSAM expects double-precision floating point vectors and matrices.
Hence, you should pass numpy matrices with
Please refer to the template project and the corresponding tutorial available here.