{"id":24111263,"url":"https://github.com/adosar/aidsorb","last_synced_at":"2025-05-13T04:42:25.915Z","repository":{"id":257807160,"uuid":"761775300","full_name":"adosar/aidsorb","owner":"adosar","description":"Python package for deep learning on molecular point 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align=\"center\"\u003e\n  \u003cpicture\u003e\n    \u003csource media=\"(prefers-color-scheme: dark)\" srcset=\"https://raw.githubusercontent.com/adosar/aidsorb/master/docs/source/images/aidsorb_logo_dark.svg\"\u003e\n    \u003csource media=\"(prefers-color-scheme: light)\" srcset=\"https://raw.githubusercontent.com/adosar/aidsorb/master/docs/source/images/aidsorb_logo_light.svg\"\u003e\n    \u003cimg alt=\"AIdsorb logo\" src=\"https://raw.githubusercontent.com/adosar/aidsorb/master/docs/source/images/aidsorb_logo_light.svg\" width=40%/\u003e\n  \u003c/picture\u003e\n\u003c/h1\u003e\n\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"https://readme-typing-svg.demolab.com?font=Roboto+Slab\u0026weight=700\u0026duration=3000\u0026pause=1000\u0026color=FFFFFF\u0026background=000000\u0026center=true\u0026vCenter=true\u0026height=40\u0026lines=%F0%9F%9A%80+Simple%2C+easy+to+use+and+reproduce;%F0%9F%94%A5+Supports+PyTorch;%E2%9A%A1+Supports+PyTorch+Lightning;%F0%9F%8E%89+A+.yaml+is+all+you+need!\" /\u003e\n\u003c/p\u003e\n\n\u003ch4 align=\"center\"\u003e\n  \u003cimg alt=\"Static Badge\" src=\"https://img.shields.io/badge/Python%203.11%2B-black?style=for-the-badge\u0026logo=python\u0026logoColor=cyan\"\u003e\n  \u003cimg alt=\"Static Badge\" src=\"https://img.shields.io/badge/GPL--3.0--only-black?style=for-the-badge\u0026logo=gnu\u0026logoColor=cyan\"\u003e\n  \u003cimg alt=\"GitHub Actions Workflow Status\" src=\"https://img.shields.io/github/actions/workflow/status/adosar/aidsorb/unittest.yaml?style=for-the-badge\u0026logo=github\u0026logoColor=cyan\u0026label=Tests\u0026labelColor=black\"\u003e\n  \u003cimg alt=\"GitHub Actions Workflow Status\" src=\"https://img.shields.io/github/actions/workflow/status/adosar/aidsorb/pylint.yaml?style=for-the-badge\u0026logo=github\u0026logoColor=cyan\u0026label=Lint\u0026labelColor=black\"\u003e\n  \u003cimg alt=\"GitHub Actions Workflow Status\" src=\"https://img.shields.io/github/actions/workflow/status/adosar/aidsorb/pypi.yaml?style=for-the-badge\u0026logo=github\u0026logoColor=cyan\u0026label=Build\u0026labelColor=black\"\u003e\n\t\n  [![Docs](https://img.shields.io/badge/foo-stable-black?style=for-the-badge\u0026logo=readthedocs\u0026logoColor=cyan\u0026label=ReadTheDocs\u0026labelColor=black\u0026color=purple)](https://aidsorb.readthedocs.io/en/stable/)\n  [![PyPI](https://img.shields.io/pypi/v/aidsorb?style=for-the-badge\u0026logo=pypi\u0026logoColor=cyan\u0026labelColor=black\u0026color=purple)](https://pypi.org/project/aidsorb/)\n  [![App](https://img.shields.io/badge/online%20app-purple?style=for-the-badge\u0026logo=streamlit\u0026logoSize=auto\u0026logoColor=cyan\u0026label=streamlit\u0026labelColor=black)](https://aidsorb-online.streamlit.app)\n\u003c/h4\u003e\n\n**AIdsorb** is a Python package for **deep learning on molecular point clouds**.\n\nThis package aims to provide a **simple, easy-to-use and reproduce** interface for:\n\n-   📥 **Creating molecular point clouds**\n  \n-   🤖 **Training DL algorithms on molecular point clouds**\n\n\u003cp align=\"center\"\u003e\n  \u003cimg alt=\"IRMOF-1\" src=\"https://raw.githubusercontent.com/adosar/aidsorb/master/docs/source/images/IRMOF-1.gif\" width=\"25%\"/\u003e\n  \u003cimg alt=\"Cu-BTC\" src=\"https://raw.githubusercontent.com/adosar/aidsorb/master/docs/source/images/Cu-BTC.gif\" width=\"25%\"/\u003e\n  \u003cimg alt=\"UiO-66\" src=\"https://raw.githubusercontent.com/adosar/aidsorb/master/docs/source/images/UiO-66.gif\" width=\"25%\"/\u003e\n\u003c/p\u003e\n\n## ⚙️  Installation\n\u003e [!IMPORTANT] \n\u003e It is strongly recommended to **perform the installation inside a virtual environment**.\n\nAssuming an activated virtual environment:\n```bash\npip install aidsorb\n```\n\n## 🚀 Usage\n\u003e [!NOTE] \n\u003e Refer to the 📚 [Documentation](https://aidsorb.readthedocs.io/en/stable/) for more information.\n\nHere is a summary of what you can do from the command line:\n\n1. Visualize a molecular point cloud:\n\t```bash\n\taidsorb visualize path/to/structure\n\t```\n\n2.  Create and prepare point clouds:\n\t```bash\n\taidsorb create path/to/structures path/to/pcd_data  # Create and store point clouds\n\taidsorb prepare path/to/pcd_data  # Split point clouds to train, valdation and test\n\t```\n\t\n3. Train and test a model:\n\t```bash\n\taidsorb-lit fit --config=path/to/config.yaml\n\taidsorb-lit test --config=path/to/config.yaml --ckpt_path=path/to/ckpt\n\t```\n\n## 💡 Contributing\n\n🙌 We welcome contributions from the community to help improve and expand this\nproject!\n\nYou can start by 🛠️ [opening an issue](https://github.com/adosar/aidsorb/issues) for:\n\n* 🐛 Reporting bugs\n* 🌟 Suggesting new features\n* 📚 Improving documentation\n* 🎨 Adding your example to the [Gallery](https://aidsorb.readthedocs.io/en/stable/auto_examples/index.html)\n\nWe appreciate your efforts to submit well-documented 🔃 [pull\nrequests](https://github.com/adosar/aidsorb/pulls) and participate in\ndiscussions.\n\n💪 Together, we can make this project even better!\n\n\n## 📑 Citing\n* **To cite the software**, please refer to the [citation file](./CITATION.cff) or click the citation button.\n* **To cite the paper**, please use the following BibTeX entry:\n\u003cdetails\u003e\n\u003csummary\u003eShow BibTex entry\u003c/summary\u003e\n\t\n```bibtex\n@article{Sarikas2024,\n  title = {Gas adsorption meets geometric deep learning: points, set and match},\n  volume = {14},\n  ISSN = {2045-2322},\n  url = {http://dx.doi.org/10.1038/s41598-024-76319-8},\n  DOI = {10.1038/s41598-024-76319-8},\n  number = {1},\n  journal = {Scientific Reports},\n  publisher = {Springer Science and Business Media LLC},\n  author = {Sarikas,  Antonios P. and Gkagkas,  Konstantinos and Froudakis,  George E.},\n  year = {2024},\n  month = nov\n}\n```\n\u003c/details\u003e\n\n## ⚖️ License\n**AIdosrb** is released under the [GNU General Public License v3.0 only](https://spdx.org/licenses/GPL-3.0-only.html).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fadosar%2Faidsorb","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fadosar%2Faidsorb","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fadosar%2Faidsorb/lists"}