Geometric statistics on manifolds
Project description
Geomstats
(Coverages for: numpy, tensorflow, pytorch)
Computations and statistics on manifolds with geometric structures.
- To get started with
geomstats
, see the examples directory. - For more in-depth applications of
geomstats
, see the applications repository. - The documentation of
geomstats
can be found on the documentation website. - If you find
geomstats
useful, please kindly cite our paper.
Installation
OS X & Linux:
pip3 install -r requirements.txt
pip3 install geomstats
Pytorch and tensorflow requirements are optional, as geomstats can be used with numpy only.
To change backend:
export GEOMSTATS_BACKEND=pytorch
Getting started
Run example scripts, for example:
python3 examples/plot_grid_h2.py
Contributing
Developers can install the dev-requirements:
pip3 install -r dev-requirements.txt
And run unit tests from this folder:
nose2 tests
See our contributing guidelines!
Acknowledgements
This work is supported by:
- the Inria-Stanford associated team GeomStats,
- the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (grant agreement G-Statistics No. 786854),
- the French society for applied and industrial mathematics (SMAI),
- the National Science Foundation (grant NSF DMS RTG 1501767).
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