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.
• Next hackathon in January 2020, Europe. Contact Nicolas Guigui or Nina Miolane if interested!

Installation

OS X & Linux:

pip3 install geomstats

Running tests

pip3 install nose2
nose2

Getting started

Define your backend by setting the environment variable GEOMSTATS_BACKEND to numpy, tensorflow, or pytorch:

export GEOMSTATS_BACKEND=numpy

Then, run example scripts:

python3 examples/plot_grid_h2.py

Contributing

See our CONTRIBUTING.md file!

Authors & Contributors

• Alice Le Brigant
• Claire Donnat
• Oleg Kachan
• Benjamin Hou
• Johan Mathe
• Nina Miolane
• Xavier Pennec

Acknowledgements

This work is partially supported by the National Science Foundation, grant NSF DMS RTG 1501767.