https://github.com/metatensor/metatensor

Self-describing sparse tensor data format for atomistic machine learning and beyond
https://github.com/metatensor/metatensor

Last synced: 5 months ago
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Self-describing sparse tensor data format for atomistic machine learning and beyond

• Host: GitHub
• URL: https://github.com/metatensor/metatensor
• Owner: metatensor
• License: bsd-3-clause
• Created: 2022-03-01T15:58:28.000Z (over 3 years ago)
• Default Branch: main
• Last Pushed: 2025-05-12T13:49:08.000Z (5 months ago)
• Last Synced: 2025-05-12T14:59:46.545Z (5 months ago)
• Language: Python
• Homepage: https://docs.metatensor.org
• Size: 11.2 MB
• Stars: 73
• Watchers: 15
• Forks: 22
• Open Issues: 68
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.rst
  • License: LICENSE
  • Code of conduct: CODE_OF_CONDUCT.md
  • Authors: AUTHORS

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• best-of-atomistic-machine-learning - GitHub - 26% open · ⏱️ 02.10.2025): (Data Structures)

README

          




    





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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://docs.metatensor.org/).

## Contributors

Thanks goes to all people that make metatensor possible:

[![contributors list](https://contrib.rocks/image?repo=metatensor/metatensor)](https://github.com/metatensor/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/metatensor/metatensor/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22).