https://github.com/adosar/moxel
Python package for parallel calculation of energy voxels.
https://github.com/adosar/moxel
deep-learning feature-engineering material-science metal-organic-frameworks porous-materials reticular-chemistry voxels
Last synced: 4 months ago
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Python package for parallel calculation of energy voxels.
- Host: GitHub
- URL: https://github.com/adosar/moxel
- Owner: adosar
- License: gpl-3.0
- Created: 2023-08-05T18:13:45.000Z (about 2 years ago)
- Default Branch: master
- Last Pushed: 2025-05-14T21:14:40.000Z (5 months ago)
- Last Synced: 2025-05-24T23:12:36.892Z (5 months ago)
- Topics: deep-learning, feature-engineering, material-science, metal-organic-frameworks, porous-materials, reticular-chemistry, voxels
- Language: Python
- Homepage: https://moxel.readthedocs.io/en/stable/
- Size: 6.82 MB
- Stars: 2
- Watchers: 1
- Forks: 2
- Open Issues: 3
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
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[](https://www.python.org/downloads/)
[](https://spdx.org/licenses/GPL-3.0-only.html)
[](https://moxel.readthedocs.io)
[](https://pypi.org/project/pymoxel/)
[](https://moxel.readthedocs.io/en/stable/?badge=stable)
[](https://badge.fury.io/py/pymoxel)MOXελ is a Python package for **parallel calculation of energy voxels**, with
emphasis on reticular chemistry.The majority of time in a ML workflow goes into constructing the inputs and
making sure they are clean, rather than focusing on the ML part itself.MOXελ aims to provide a **simple and fast interface to generate energy voxels in
a ML-ready format**, minimizing as much as possible the time spent on these
preprocessing steps.
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## ⚙️ Installation
It is strongly recommended to **perform the installation inside a virtual environment**.Check the [installation steps](https://moxel.readthedocs.io/en/stable/installation.html).
Assuming an activated virtual environment:
```sh
pip install pymoxel
```## 🚀 Usage
```
moxel path/to/CIFs path/to/voxels_data/ --grid_size=5
```You can also use a configuration file:
```
moxel --config=path/to/config.yaml
```> [!NOTE]
> For more information, please refer to the [📚 Documentation](https://moxel.readthedocs.io/en/stable/index.html).## 📰 Citing MOXελ
If you use ΜΟΧελ in your research, please consider citing the following work:@article{Sarikas2024,
title = {Gas adsorption meets deep learning: voxelizing the potential energy surface of metal-organic frameworks},
volume = {14},
ISSN = {2045-2322},
url = {http://dx.doi.org/10.1038/s41598-023-50309-8},
DOI = {10.1038/s41598-023-50309-8},
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 = jan
}## 📇 TODO
1. Improve performance
2. Improve voxelization scheme
3. Improve modeling of interactions## 📑 License
MOXελ is released under the [GNU General Public License v3.0 only](https://spdx.org/licenses/GPL-3.0-only.html).