Metadata-Version: 2.1
Name: geomstats
Version: 1.21
Summary: Geometric statistics on manifolds
Home-page: http://github.com/geomstats/geomstats
Author: Nina Miolane
Author-email: ninamio78@gmail.com
License: MIT
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Description-Content-Type: text/markdown
Requires-Dist: autograd
Requires-Dist: joblib (==0.14.1)
Requires-Dist: matplotlib
Requires-Dist: numpy (>=1.18.1)
Requires-Dist: scikit-learn (>=0.22.1)
Requires-Dist: scipy (>=1.4.1)
Provides-Extra: all
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Requires-Dist: torch (==1.4.0) ; extra == 'all'
Requires-Dist: tensorflow (==2.0.1) ; (python_version < "3.8") and extra == 'all'
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Requires-Dist: torch (==1.4.0) ; extra == 'torch'

# Geomstats
[![Build Status](https://travis-ci.org/geomstats/geomstats.svg?branch=master)](https://travis-ci.org/geomstats/geomstats)[![Coverage Status](https://codecov.io/gh/geomstats/geomstats/branch/master/graph/badge.svg?flag=numpy)](https://codecov.io/gh/geomstats/geomstats)[![Coverage Status](https://codecov.io/gh/geomstats/geomstats/branch/master/graph/badge.svg?flag=tensorflow)](https://codecov.io/gh/geomstats/geomstats)[![Coverage Status](https://codecov.io/gh/geomstats/geomstats/branch/master/graph/badge.svg?flag=pytorch)](https://codecov.io/gh/geomstats/geomstats) (Coverages for: numpy, tensorflow, pytorch)


Computations and statistics on manifolds with geometric structures.

<img align="left" src="https://raw.githubusercontent.com/ninamiolane/geomstats/master/examples/imgs/h2_grid.png" width=110 height=110>

- To get started with ```geomstats```, see the [examples directory](https://github.com/geomstats/geomstats/tree/master/examples).
- For more in-depth applications of ``geomstats``, see the [applications repository](https://github.com/geomstats/applications/).
- The documentation of ```geomstats``` can be found on the [documentation website](https://geomstats.github.io/).
- If you find ``geomstats`` useful, please kindly cite our [paper](https://arxiv.org/abs/1805.08308).


## 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](https://github.com/geomstats/geomstats/blob/master/docs/contributing.rst) guidelines!

## Acknowledgements

This work is supported by:
- the Inria-Stanford associated team [GeomStats](http://www-sop.inria.fr/asclepios/projects/GeomStats/),
- the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (grant agreement [G-Statistics](https://team.inria.fr/epione/en/research/erc-g-statistics/) No. 786854),
- the French society for applied and industrial mathematics ([SMAI](http://smai.emath.fr/)),
- the National Science Foundation (grant NSF DMS RTG 1501767).


