Metadata-Version: 2.4
Name: acellera-openff-nagl
Version: 0.5.5
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-Expression: MIT
Project-URL: documentation, https://docs.openforcefield.org/projects/nagl/
Project-URL: source, https://github.com/openforcefield/openff-nagl
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
License-File: LICENSE-3RD-PARTY
License-File: AUTHORS.md
Provides-Extra: doc
Requires-Dist: sphinx>=1.8; extra == "doc"
Provides-Extra: test
Requires-Dist: pytest>=6; extra == "test"
Requires-Dist: pytest-cov>=3; extra == "test"
Requires-Dist: pytest-xdist>=2.5; extra == "test"
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.
