Metadata-Version: 2.4
Name: acellera-openff-nagl
Version: 0.5.4
Summary: A playground for applying graph convolutional networks to molecules.
Author-email: Lily Wang <lily.wang@openforcefield.org>
Maintainer-email: Lily Wang <lily.wang@openforcefield.org>
License: MIT License
        
        Copyright (c) 2022 Lily Wang
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
        copies or substantial portions of the Software.
        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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Project-URL: source, https://github.com/openforcefield/openff-nagl
Project-URL: documentation, https://docs.openforcefield.org/projects/nagl/
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
License-File: LICENSE-3RD-PARTY
License-File: AUTHORS.md
Provides-Extra: test
Requires-Dist: pytest>=6.0; extra == "test"
Requires-Dist: pytest-xdist>=2.5; extra == "test"
Requires-Dist: pytest-cov>=3.0; extra == "test"
Provides-Extra: doc
Requires-Dist: sphinx>=1.8; extra == "doc"
Dynamic: license-file

NAGL
==============================
[//]: # (Badges)

| **Latest release** | [![Last release tag](https://img.shields.io/github/release-pre/openforcefield/openff-nagl.svg)](https://github.com/openforcefield/openff-nagl/releases) ![GitHub commits since latest release (by date) for a branch](https://img.shields.io/github/commits-since/openforcefield/openff-nagl/latest)  [![Documentation Status](https://readthedocs.org/projects/openff-nagl/badge/?version=latest)](https://docs.openforcefield.org/projects/nagl/en/latest/?badge=latest)                                                                                                        |
| :----------------- | :--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| **Status**         | [![GH Actions Status](https://github.com/openforcefield/openff-nagl/actions/workflows/gh-ci.yaml/badge.svg)](https://github.com/openforcefield/openff-nagl/actions?query=branch%3Amain+workflow%3Agh-ci) [![codecov](https://codecov.io/gh/openforcefield/openff-nagl/branch/main/graph/badge.svg)](https://codecov.io/gh/openforcefield/openff-nagl/branch/main) |
| **Community**      | [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT) [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.12792526.svg)](https://doi.org/10.5281/zenodo.12792526)                                                                                                                                                                                                                                                                                                                                                                                                                                                           |

A playground for applying graph convolutional networks to molecules, with a focus on learning continuous "atom-type" embeddings and from these classical molecule force field parameters.

**Note:** This project is still in development and liable to substantial API and other changes.

This framework is mostly based upon the [*End-to-End Differentiable Molecular Mechanics Force Field Construction*](https://arxiv.org/abs/2010.01196) 
preprint by Wang, Fass and Chodera.

NAGL is bound by a [Code of Conduct](https://github.com/openforcefield/openff-nagl/blob/main/CODE_OF_CONDUCT.md).

### [Documentation](https://docs.openforcefield.org/projects/nagl/en/latest/?badge=latest)

See our documentation for notes on [installation](https://docs.openforcefield.org/projects/nagl/en/latest/installation.html), basic usage, theory, and examples!

### Copyright

The NAGL source code is hosted at https://github.com/openforcefield/openff-nagl
and is available under the MIT license (see the file [LICENSE](https://github.com/openforcefield/openff-nagl/blob/main/LICENSE)). Some parts inherit from code distributed under other licenses, as detailed in [LICENSE-3RD-PARTY](https://github.com/openforcefield/openff-nagl/blob/main/LICENSE-3RD-PARTY)).

NAGL inherits from Simon Boothroyd's NAGL library at https://github.com/SimonBoothroyd/nagl.
