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updated cython wrapper README

release/4.3a0
Varun Agrawal 2020-06-30 20:57:31 -05:00
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cython/README.md
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# Python Wrapper # Python Wrapper
This is the Cython/Python wrapper around the GTSAM C++ library. 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 2.7), use the `-DGTSAM_PYTHON_VERSION=2.7` 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 ## Install
- if you want to build the gtsam python library for a specific python version (eg 2.7), use the `-DGTSAM_PYTHON_VERSION=2.7` option when running `cmake` otherwise the default interpreter will be used. - 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: `<CMAKE_INSTALL_PREFIX>/cython.build`.
- 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. 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.
- Build and install gtsam using cmake with `GTSAM_INSTALL_CYTHON_TOOLBOX` enabled.
The wrapped module will be installed to `GTSAM_CYTHON_INSTALL_PATH`, which is
by default: `<your CMAKE_INSTALL_PREFIX>/cython`
- To use the library without installing system-wide: modify your `PYTHONPATH` to include the `GTSAM_CYTHON_INSTALL_PATH`: - To use the library without installing system-wide: modify your `PYTHONPATH` to include the `GTSAM_CYTHON_INSTALL_PATH`:
```bash
export PYTHONPATH=$PYTHONPATH:<GTSAM_CYTHON_INSTALL_PATH> ```bash
``` export PYTHONPATH=$PYTHONPATH:<GTSAM_CYTHON_INSTALL_PATH>
- To install system-wide: run `make install` then navigate to `GTSAM_CYTHON_INSTALL_PATH` and run `python setup.py 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. - Build GTSAM and the wrapper with `make`.
- if you run `setup.py` from the build directory rather than the installation directory, the script will warn you with the message: `setup.py is being run from an unexpected location`.
Before `make install` is run, not all the components of the package have been copied across, so running `setup.py` from the build directory would result in an incomplete package. - To install system-wide, simply run `make 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.
- If you run `setup.py` from the build directory rather than the installation directory, the script will warn you with the message: `setup.py is being run from an unexpected location`.
## Unit Tests ## Unit Tests
@ -47,48 +50,32 @@ See the tests for examples.
- Vector/Matrix: - Vector/Matrix:
+ GTSAM expects double-precision floating point vectors and matrices. + GTSAM expects double-precision floating point vectors and matrices.
Hence, you should pass numpy matrices with dtype=float, or 'float64'. Hence, you should pass numpy matrices with `dtype=float`, or `float64`.
+ Also, GTSAM expects *column-major* matrices, unlike the default storage + Also, GTSAM expects *column-major* matrices, unlike the default storage
scheme in numpy. Hence, you should pass column-major matrices to gtsam using 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. the flag order='F'. And you always get column-major matrices back.
For more details, see: https://github.com/wouterboomsma/eigency#storage-layout---why-arrays-are-sometimes-transposed 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 + 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, as the wrapper converts them to column-major and dtype float for you,
using numpy.array.astype(float, order='F', copy=False). using numpy.array.astype(float, order='F', copy=False).
However, this will result a copy if your matrix is not in the expected type However, this will result a copy if your matrix is not in the expected type
and storage order. and storage order.
- Inner namespace: Classes in inner namespace will be prefixed by <innerNamespace>_ in Python. - Inner namespace: Classes in inner namespace will be prefixed by <innerNamespace>_ in Python.
Examples: noiseModel_Gaussian, noiseModel_mEstimator_Tukey
Examples: `noiseModel_Gaussian`, `noiseModel_mEstimator_Tukey`
- Casting from a base class to a derive class must be done explicitly. - 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 Your Own Project That Uses GTSAM Examples:
```python
noiseBase = factor.noiseModel()
noiseGaussian = dynamic_cast_noiseModel_Gaussian_noiseModel_Base(noiseBase)
```
- Set PYTHONPATH to include ${GTSAM_CYTHON_INSTALL_PATH} ## Wrapping Custom GTSAM-based Project
+ so that it can find gtsam Cython header: gtsam/gtsam.pxd
- In your CMakeList.txt Please refer to the template project and the corresponding tutorial available [here](https://github.com/borglab/gtsam-project-python).
```cmake
find_package(GTSAM REQUIRED) # Make sure gtsam's install folder is in your PATH
set(CMAKE_MODULE_PATH "${CMAKE_MODULE_PATH}" "${GTSAM_DIR}/../GTSAMCMakeTools")
# Wrap
include(GtsamCythonWrap)
include_directories(${GTSAM_EIGENCY_INSTALL_PATH})
wrap_and_install_library_cython("your_project_interface.h"
"from gtsam.gtsam cimport *" # extra import of gtsam/gtsam.pxd Cython header
"your_install_path"
"libraries_to_link_with_the_cython_module"
"dependencies_which_need_to_be_built_before_the_wrapper"
)
#Optional: install_cython_scripts and install_cython_files. See GtsamCythonWrap.cmake.
```
## KNOWN ISSUES ## KNOWN ISSUES