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scikit-matter
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=============
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|tests | |codecov | |pypi | |conda | |docs | |doi |
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A collection of scikit-learn compatible utilities that implement methods born out of the
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Installation
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------------
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You can install *scikit-matter * either via pip using
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.. code-block :: bash
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pip install skmatter
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or conda
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.. code-block :: bash
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conda install -c conda-forge skmatter
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You can then ``import skmatter `` and use scikit-matter in your projects!
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.. marker-ci-tests
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Tests
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-----
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+ We are testing our code for Python 3.8 and 3.12 on `Windows Server 2019 `_, `macOS 11 `_
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+ and `Ubuntu LTS 22.04 `_.
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- We are testing our code for Python 3.8 and 3.11 on `Windows Server 2019
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- <https://github.com/actions/runner-images/blob/main/images/win/Windows2019-Readme.md> `_,
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- `macOS 11
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- <https://github.com/actions/runner-images/blob/main/images/macos/macos-11-Readme.md> `_
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- and `Ubuntu LTS 22.04
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- <https://github.com/actions/runner-images/
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- blob/main/images/linux/Ubuntu2204-Readme.md> `_.
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+ .. _`Windows Server 2019` : https://github.com/actions/runner-images/blob/main/images/win/Windows2019-Readme.md
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+ .. _`macOS 11` : https://github.com/actions/runner-images/blob/main/images/macos/macos-11-Readme.md
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+ .. _`Ubuntu LTS 22.04` : https://github.com/actions/runner-images/blob/main/images/linux/Ubuntu2204-Readme.md
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.. marker-issues
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Having problems or ideas?
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-------------------------
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Having a problem with scikit-matter? Please let us know by `submitting an issue
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<https://github.com/scikit-learn-contrib/scikit-matter/issues> `_.
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@@ -59,7 +52,6 @@ Submit new features or bug fixes through a `pull request
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Call for Contributions
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----------------------
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We always welcome new contributors. If you want to help us take a look at our
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`contribution guidelines `_ and afterwards you may start with an open issue marked as
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`good first issue `_.
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Citing scikit-matter
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--------------------
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- If you use scikit-matter for your work, please cite:
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+ If you use *scikit-matter * for your work, please cite:
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Goscinski A, Principe VP, Fraux G et al. scikit-matter :
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A Suite of Generalisable Machine Learning Methods Born out of Chemistry
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Contributors
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------------
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Thanks goes to all people that make scikit-matter possible:
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.. image :: https://contrib.rocks/image?repo=scikit-learn-contrib/scikit-matter
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