Metadata-Version: 2.3
Name: pybmc
Version: 0.1.0
Summary: A package for Bayesian model combination
License: GPL-3.0
Author: Kyle Godbey
Author-email: pybmc@ascsn.net
Requires-Python: >=3.10,<4.0
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Programming Language :: Python :: 3
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-Dist: matplotlib (>=3.7.0,<4.0.0)
Requires-Dist: numpy (>=2.0.0,<3.0.0)
Requires-Dist: pandas (>=2.0.0,<3.0.0)
Requires-Dist: scikit-learn (>=1.3.0,<2.0.0)
Requires-Dist: scipy (>=1.15.0,<2.0.0)
Project-URL: Documentation, https://ascsn.github.io/pybmc/
Project-URL: Homepage, https://github.com/ascsn/pybmc
Project-URL: Repository, https://github.com/ascsn/pybmc
Description-Content-Type: text/markdown

# pyBMC: A General Bayesian Model Combination Package

pyBMC is a Python package for performing Bayesian Model Combination (BMC) on various predictive models. It provides tools for data handling, orthogonalization, Gibbs sampling, and prediction with uncertainty quantification.

## Features

- **Data Management**: Load and preprocess nuclear mass data from HDF5 and CSV files
- **Orthogonalization**: Transform model predictions using Singular Value Decomposition (SVD)
- **Bayesian Inference**: Perform Gibbs sampling for model combination
- **Uncertainty Quantification**: Generate predictions with credible intervals
- **Model Evaluation**: Calculate coverage statistics for model validation

## Installation

```bash
pip install pybmc
```

## Quick Start

For a detailed walkthrough of how to use the package, please see the [Usage Guide](docs/usage.md).

## Documentation

Comprehensive documentation is available at [https://ascsn.github.io/pybmc/](https://ascsn.github.io/pybmc/), including:

- [Usage Guide](docs/usage.md)
- [API Reference](docs/api_reference.md)
- [Theory Background](docs/theory.md)
- [Contribution Guidelines](docs/CONTRIBUTING.md)

## Contributing

We welcome contributions! Please see our [Contribution Guidelines](docs/CONTRIBUTING.md) for details on how to contribute to the project.

## License

This project is licensed under the GPL-3.0 License - see the [LICENSE](LICENSE) file for details.

## Citation

If you use pyBMC in your research, please cite:

```bibtex
@software{pybmc,
  title = {pyBMC: Bayesian Model Combination},
  author = {Kyle Godbey and Troy Dasher and An Le},
  year = {2025},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/ascsn/pybmc}}
}
```

## Support

For questions or support, please open an issue on our [GitHub repository](https://github.com/ascsn/pybmc/issues).

