Metadata-Version: 2.4
Name: fracdiff-modern
Version: 1.0.0
Summary: Super-fast fractional differentiation.
Author-email: Shota Imaki <shota.imaki.0801@gmail.com>
Maintainer-email: Reis McMillan <reismcmillan19@gmail.com>
License-Expression: BSD-3-Clause
Project-URL: repository, https://github.com/Reis-McMillan/fracdiff
Project-URL: documentation, https://Reis-McMillan.github.io/fracdiff/
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
Classifier: Operating System :: OS Independent
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy>=1.21.2
Requires-Dist: scipy>=1.7.0
Requires-Dist: statsmodels>=0.13.0
Provides-Extra: sklearn
Requires-Dist: scikit-learn>=1.0.0; extra == "sklearn"
Provides-Extra: torch
Requires-Dist: torch>=1.10.0; extra == "torch"
Provides-Extra: dev
Requires-Dist: pytest; extra == "dev"
Requires-Dist: pytest-cov; extra == "dev"
Requires-Dist: tox; extra == "dev"
Requires-Dist: flake8; extra == "dev"
Requires-Dist: flake8-bugbear; extra == "dev"
Requires-Dist: flake8-comprehensions; extra == "dev"
Requires-Dist: furo; extra == "dev"
Requires-Dist: sphinx; extra == "dev"
Requires-Dist: sphinx_rtd_theme; extra == "dev"
Requires-Dist: sphinx-autobuild; extra == "dev"
Requires-Dist: build; extra == "dev"
Requires-Dist: twine; extra == "dev"
Dynamic: license-file

# fracdiff-modern

**Super-fast fractional differentiation for NumPy, PyTorch, and Scikit-Learn.**

`fracdiff-modern` is a maintained, modernized fork of the original `fracdiff` library. 
It features:
* **Python 3.10 - 3.13+ Support.**
* **Modern Build System**: Fully compatible with `pyproject.toml` and `setuptools >= 77`.

## Installation

Install the base package with NumPy and SciPy:
```sh
pip install fracdiff-modern
```

To use `fracdiff-modern` with Scikit-Learn or PyTorch functionality, install the extras:
```sh
pip install fracdiff-modern[sklearn,torch]
```

## Contributing

Any contributions are more than welcome.

See [Issue](https://github.com/Reis-McMillan/fracdiff/issues) for proposed features.
Please take a look at [CONTRIBUTING.md](.github/CONTRIBUTING.md) before creating a pull request.

## Acknowledgements

This package is a modernization of the original `fracdiff` library by **Shota Imaki**. The core algorithms and logic are based on his work in fractional calculus for financial time series.

## License

BSD-3-Clause License. See [LICENSE](LICENSE) for the full text.

## References

- [Marcos Lopez de Prado, "Advances in Financial Machine Learning", Wiley, (2018).][prado]

[prado]: https://www.wiley.com/en-us/Advances+in+Financial+Machine+Learning-p-9781119482086
