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AIdsorb logo

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AIdsorb is a Python package for deep learning on molecular point clouds.

This package aims to provide a simple, easy-to-use and reproduce interface for:

  • πŸ“₯ Creating molecular point clouds

  • πŸ€– Training DL algorithms on molecular point clouds

IRMOF-1 Cu-BTC UiO-66

βš™οΈ Installation

Important

It is strongly recommended to perform the installation inside a virtual environment.

Assuming an activated virtual environment:

pip install aidsorb

πŸš€ Usage

Note

Refer to the πŸ“š Documentation for more information.

Here is a summary of what you can do from the command line:

  1. Visualize a point cloud:

    aidsorb visualize path/to/structure_or_pcd  # Structure (.xyz, .cif, etc) or .npy
  2. Create and prepare point clouds:

    aidsorb create path/to/structures path/to/pcd_data  # Create and store point clouds
    aidsorb prepare path/to/pcd_data  # Split point clouds to train, valdation and test
  3. Train and test a model:

    aidsorb-lit fit --config=path/to/config.yaml
    aidsorb-lit test --config=path/to/config.yaml --ckpt_path=path/to/ckpt

πŸ’‘ Questions and Contributing

Questions

If you have any questions about how to use AIdsorb, we encourage you to post them in the πŸ’¬ Discussions section of the repository.

Note

Please make sure to read the documentation carefully first before asking your question.

Contributing

We welcome contributions from the community! Please read our πŸ™Œ Contributing Guidelines before submitting PRs or opening issues.

πŸ“‘ Citing

  • To cite the software, please refer to the citation file or click the citation button.
  • To cite the paper, please use the following BibTeX entry:
Show BibTex entry
@article{Sarikas2024,
  title = {Gas adsorption meets geometric deep learning: points, set and match},
  volume = {14},
  ISSN = {2045-2322},
  url = {http://dx.doi.org/10.1038/s41598-024-76319-8},
  DOI = {10.1038/s41598-024-76319-8},
  number = {1},
  journal = {Scientific Reports},
  publisher = {Springer Science and Business Media LLC},
  author = {Sarikas,  Antonios P. and Gkagkas,  Konstantinos and Froudakis,  George E.},
  year = {2024},
  month = nov
}

βš–οΈ License

AIdosrb is released under the GNU General Public License v3.0 only.