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aidsorb

Python package for deep learning on molecular point clouds.

https://github.com/adosar/aidsorb

Science Score: 57.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ✓
    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ✓
    DOI references
    Found 4 DOI reference(s) in README
  • ○
    Academic publication links
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    Institutional organization owner
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    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (11.1%) to scientific vocabulary

Keywords

3d-deep-learning 3d-point-clouds deep-learning geometric-deep-learning machine-learning material-informatics metal-organic-frameworks point-clouds pytorch pytorch-lightning
Last synced: 6 months ago · JSON representation ·

Repository

Python package for deep learning on molecular point clouds.

Basic Info
Statistics
  • Stars: 4
  • Watchers: 1
  • Forks: 1
  • Open Issues: 2
  • Releases: 2
Topics
3d-deep-learning 3d-point-clouds deep-learning geometric-deep-learning machine-learning material-informatics metal-organic-frameworks point-clouds pytorch pytorch-lightning
Created almost 2 years ago · Last pushed 7 months ago
Metadata Files
Readme License Citation

README.md

AIdsorb logo

Static Badge Static Badge GitHub Actions Workflow Status GitHub Actions Workflow Status [![coverage](https://img.shields.io/codecov/c/gh/adosar/aidsorb?style=for-the-badge&logo=codecov&logoColor=cyan&label=CODECOV&labelColor=black&color=purple)](https://app.codecov.io/gh/adosar/aidsorb) [![Docs](https://img.shields.io/badge/foo-stable-black?style=for-the-badge&logo=readthedocs&logoColor=cyan&label=ReadTheDocs&labelColor=black&color=purple)](https://aidsorb.readthedocs.io/en/stable/) [![PyPI](https://img.shields.io/pypi/v/aidsorb?style=for-the-badge&logo=pypi&logoColor=cyan&labelColor=black&color=purple)](https://pypi.org/project/aidsorb/) [![App](https://img.shields.io/badge/online%20app-purple?style=for-the-badge&logo=streamlit&logoSize=auto&logoColor=cyan&label=streamlit&labelColor=black)](https://aidsorb-online.streamlit.app)

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:

  • 📥 Creating molecular point clouds

  • 🤖 Training DL algorithms on molecular point clouds

IRMOF-1 Cu-BTC UiO-66

⚙️ Installation

[!IMPORTANT] It is strongly recommended to perform the installation inside a virtual environment.

Assuming an activated virtual environment: bash pip install aidsorb

🚀 Usage

[!NOTE] Refer to the 📚 Documentation for more information.

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

  1. Visualize a molecular point cloud: bash aidsorb visualize path/to/structure

  2. Create and prepare point clouds: bash 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: bash aidsorb-lit fit --config=path/to/config.yaml aidsorb-lit test --config=path/to/config.yaml --ckpt_path=path/to/ckpt

💡 Contributing

🙌 We welcome contributions from the community to help improve and expand this project!

You can start by 🛠️ opening an issue for:

  • 🐛 Reporting bugs
  • 🌟 Suggesting new features
  • 📚 Improving documentation
  • 🎨 Adding your example to the Gallery

We appreciate your efforts to submit well-documented 🔃 pull requests and participate in discussions.

💪 Together, we can make this project even better!

📑 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

bibtex @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 }

⚖️ License

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

Owner

  • Name: Antonios P. Sarikas
  • Login: adosar
  • Kind: user
  • Company: Department of Chemistry, University of Crete

Citation (CITATION.cff) 

# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!

cff-version: 1.2.0
title: AIdsorb
message: >-
  If you use this software, please cite it using the
  metadata from this file.
type: software
authors:
  - given-names: Antonios P.
    family-names: Sarikas
    orcid: 'https://orcid.org/0009-0008-8420-927X'
identifiers:
  - type: doi
    value: 10.1038/s41598-024-76319-8
    description: The DOI of the paper.
repository-code: 'https://github.com/adosar/aidsorb'
url: 'https://aidsorb.readthedocs.io/en/stable/'
abstract: >-
  Python package for deep learning on molecular point
  clouds.
keywords:
  - deep learning
  - geometric deep learning
  - point clouds
  - machine learning
  - pytorch
  - pytorch lightning
  - porous materials
  - material informatics
  - metal-organic frameworks
  - molecular point clouds
license: GPL-3.0-only

GitHub Events

Total
  • Issues event: 112
  • Watch event: 4
  • Delete event: 2
  • Issue comment event: 18
  • Push event: 44
  • Create event: 2
Last Year
  • Issues event: 112
  • Watch event: 4
  • Delete event: 2
  • Issue comment event: 18
  • Push event: 44
  • Create event: 2

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 64
  • Total pull requests: 1
  • Average time to close issues: 2 days
  • Average time to close pull requests: about 1 hour
  • Total issue authors: 1
  • Total pull request authors: 1
  • Average comments per issue: 0.22
  • Average comments per pull request: 0.0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 63
  • Pull requests: 0
  • Average time to close issues: 2 days
  • Average time to close pull requests: N/A
  • Issue authors: 1
  • Pull request authors: 0
  • Average comments per issue: 0.22
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • adosar (64)
Pull Request Authors
  • adosar (1)
Top Labels
Issue Labels
enhancement (14) documentation (5) bug (1)
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 166 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 2
  • Total maintainers: 1
pypi.org: aidsorb

Python package for deep learning on molecular point clouds.

  • Versions: 2
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 166 Last month
Rankings
Dependent packages count: 10.3%
Average: 34.0%
Dependent repos count: 57.7%
Maintainers (1)
adosar
Last synced: 6 months ago

Dependencies

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.github/workflows/unittest.yaml actions
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docs/requirements.txt pypi
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pyproject.toml pypi
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  • lightning >=2.2.1
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