scikit-matter

|tests| |codecov| |pypi| |conda| |docs| |doi|

A collection of scikit-learn compatible utilities that implement methods born out of the materials science and chemistry communities.

For details, tutorials, and examples, please have a look at our documentation_.

.. _documentation: https://scikit-matter.readthedocs.io

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Installation

You can install scikit-matter either via pip using

.. code-block:: bash

pip install skmatter

or conda

.. code-block:: bash

conda install -c conda-forge skmatter

You can then import skmatter and use scikit-matter in your projects!

.. marker-ci-tests

Tests

We are testing our code for Python 3.8 and 3.12 on Windows Server 2019, macOS 11 and Ubuntu LTS 22.04_.

.. _Windows Server 2019: https://github.com/actions/runner-images/blob/main/images/win/Windows2019-Readme.md .. _macOS 11: https://github.com/actions/runner-images/blob/main/images/macos/macos-11-Readme.md .. _Ubuntu LTS 22.04: https://github.com/actions/runner-images/blob/main/images/linux/Ubuntu2204-Readme.md

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Having problems or ideas?

Having a problem with scikit-matter? Please let us know by submitting an issue <https://github.com/scikit-learn-contrib/scikit-matter/issues>_.

Submit new features or bug fixes through a pull request <https://github.com/scikit-learn-contrib/scikit-matter/pulls>_.

.. marker-contributing

Call for Contributions

We always welcome new contributors. If you want to help us take a look at our contribution guidelines_ and afterwards you may start with an open issue marked as good first issue_.

Writing code is not the only way to contribute to the project. You can also:

• review pull requests_
• help us stay on top of new and old issues_
• develop examples and tutorials_
• maintain and improve our documentation_
• contribute new datasets_

.. _contribution guidelines: https://scikit-matter.readthedocs.io/en/latest/contributing.html .. _good first issue: https://github.com/scikit-learn-contrib/scikit-matter/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22 .. _pull requests: https://github.com/scikit-learn-contrib/scikit-matter/pulls .. _issues: https://github.com/scikit-learn-contrib/scikit-matter/issues .. _improve our documentation: https://scikit-matter.readthedocs.io/en/latest/contributing.html#contributing-to-the-documentation .. _examples and tutorials: https://scikit-matter.readthedocs.io/en/latest/contributing.html#contributing-new-examples .. _new datasets: https://scikit-matter.readthedocs.io/en/latest/contributing.html#contributing-datasets

.. marker-contributors

Citing scikit-matter

If you use scikit-matter for your work, please cite:

Goscinski A, Principe VP, Fraux G et al. scikit-matter : A Suite of Generalisable Machine Learning Methods Born out of Chemistry and Materials Science. Open Res Europe 2023, 3:81. 10.12688/openreseurope.15789.2 <https://doi.org/10.12688/openreseurope.15789.2>_

Contributors

Thanks goes to all people that make scikit-matter possible:

.. image:: https://contrib.rocks/image?repo=scikit-learn-contrib/scikit-matter :target: https://github.com/scikit-learn-contrib/scikit-matter/graphs/contributors

.. |tests| image:: https://github.com/scikit-learn-contrib/scikit-matter/workflows/Test/badge.svg :alt: Github Actions Tests Job Status :target: (https://github.com/scikit-learn-contrib/scikit-matter/
actions?query=workflow%3ATests)

.. |codecov| image:: https://codecov.io/gh/scikit-learn-contrib/scikit-matter/branch/main/graph/badge.svg?token=UZJPJG34SM :alt: Code coverage :target: https://codecov.io/gh/scikit-learn-contrib/scikit-matter/

.. |docs| image:: https://img.shields.io/badge/documentation-latest-sucess :alt: Python :target: https://scikit-matter.readthedocs.io

.. |pypi| image:: https://img.shields.io/pypi/v/skmatter.svg :alt: Latest PYPI version :target: https://pypi.org/project/skmatter

.. |conda| image:: https://anaconda.org/conda-forge/skmatter/badges/version.svg :alt: Latest conda version :target: https://anaconda.org/conda-forge/skmatter

.. |doi| image:: https://img.shields.io/badge/DOI-10.12688-blue :alt: ORE Paper :target: https://doi.org/10.12688/openreseurope.15789.2