68 lines
		
	
	
		
			2.6 KiB
		
	
	
	
		
			Markdown
		
	
	
			
		
		
	
	
			68 lines
		
	
	
		
			2.6 KiB
		
	
	
	
		
			Markdown
		
	
	
# README
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# Python Wrapper
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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.
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## Requirements
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- If you want to build the GTSAM python library for a specific python version (eg 3.6),
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  use the `-DGTSAM_PYTHON_VERSION=3.6` option when running `cmake` otherwise the default interpreter will be used.
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- If the interpreter is inside an environment (such as an anaconda environment or virtualenv environment),
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  then the environment should be active while building GTSAM.
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- This wrapper needs `pyparsing(>=2.4.2)`, and `numpy(>=1.11.0)`. These can be installed as follows:
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  ```bash
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  pip install -r <gtsam_folder>/python/requirements.txt
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  ```
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## Install
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- 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:
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  ```bash
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  cmake .. -DGTSAM_BUILD_PYTHON=1 -DGTSAM_PYTHON_VERSION=3.6.10
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  ```
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- Build GTSAM and the wrapper with `make` (or `ninja` if you use `-GNinja`).
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- To install, simply run `make python-install` (`ninja python-install`).
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  - The same command can be used to install into a virtual environment if it is active.
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  - **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.
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- You can also directly run `make python-install` without running `make`, and it will compile all the dependencies accordingly.
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## Unit Tests
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The Python toolbox also has a small set of unit tests located in the
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test directory. To run them:
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  ```bash
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  cd <GTSAM_SOURCE_DIRECTORY>/python/gtsam/tests
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  python -m unittest discover
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  ```
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## Utils
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TODO
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## Examples
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TODO
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## Writing Your Own Scripts
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See the tests for examples.
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### Some Important Notes:
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- Vector/Matrix:
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  - GTSAM expects double-precision floating point vectors and matrices.
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    Hence, you should pass numpy matrices with `dtype=float`, or `float64`, to avoid any conversion needed.
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  - Also, GTSAM expects _column-major_ matrices, unlike the default storage
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    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
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    and storage order.
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## Wrapping Custom GTSAM-based Project
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Please refer to the template project and the corresponding tutorial available [here](https://github.com/borglab/GTSAM-project-python).
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