Metadata-Version: 2.1
Name: metatensor
Version: 0.1.0
Summary: Self-describing sparse tensor data format for atomistic machine learning and beyond
Author: Guillaume Fraux, Davide Tisi, Philip Loche, Joseph W. Abbott, Jigyasa Nigam, Chiheb Ben Mahmoud
License: BSD-3-Clause
Project-URL: homepage, https://lab-cosmo.github.io/metatensor/latest/
Project-URL: documentation, https://lab-cosmo.github.io/metatensor/latest/
Project-URL: repository, https://github.com/lab-cosmo/metatensor
Keywords: machine learning,molecular modeling
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: POSIX
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: Microsoft :: Windows
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Topic :: Scientific/Engineering :: Chemistry
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires-Python: >=3.7
Description-Content-Type: text/markdown
License-File: LICENSE
License-File: AUTHORS
Requires-Dist: metatensor-core <0.2.0,>=0.1.0
Requires-Dist: metatensor-operations <0.2.0,>=0.1.0
Provides-Extra: torch
Requires-Dist: metatensor-torch <0.2.0,>=0.1.0 ; extra == 'torch'

# Metatensor

[![tests status](https://img.shields.io/github/checks-status/lab-cosmo/metatensor/master)](https://github.com/lab-cosmo/metatensor/actions?query=branch%3Amaster)
[![documentation](https://img.shields.io/badge/documentation-latest-sucess)](https://lab-cosmo.github.io/metatensor/latest/)
[![coverage](https://codecov.io/gh/lab-cosmo/metatensor/branch/master/graph/badge.svg)]( https://codecov.io/gh/lab-cosmo/metatensor)

Metatensor is a self-describing sparse tensor data format for atomistic machine
learning and beyond; storing values and gradients of these values together.
Think numpy `ndarray` or pytorch `Tensor` equipped with extra metadata for
atomic systems and other point clouds data. The core of this library is written
in Rust and we provide API for C, C++, and Python.

The main class of metatensor is the `TensorMap` data structure, defining a
custom block-sparse data format. If you are using metatensor from Python, we
additionally provide a collection of mathematical, logical and other utility
operations to make working with TensorMaps more convenient.

## Documentation

For details, tutorials, and examples, please have a look at our [documentation](https://lab-cosmo.github.io/metatensor/latest/).

## Contributors

Thanks goes to all people that make metatensor possible:

[![contributors list](https://contrib.rocks/image?repo=lab-cosmo/metatensor)](https://github.com/lab-cosmo/metatensor/graphs/contributors)

We always welcome new contributors. If you want to help us take a look at our
[contribution guidelines](CONTRIBUTING.rst) and afterwards you may start with an
open issue marked as [good first
issue](https://github.com/lab-cosmo/metatensor/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22).
