Metadata-Version: 2.1
Name: eko
Version: 0.8.5
Summary: Evolution Kernel Operator
Home-page: https://github.com/N3PDF/eko
Author: A. Candido
Author-email: alessandro.candido@mi.infn.it
Requires-Python: >=3.8,<3.11
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Physics
Provides-Extra: docs
Provides-Extra: mark
Requires-Dist: PyYAML (>=6.0,<7.0)
Requires-Dist: Sphinx (>=4.3.2,<5.0.0); extra == "docs"
Requires-Dist: banana-hep (>=0.6.0,<0.7.0); extra == "mark"
Requires-Dist: lz4 (>=3.1.10,<4.0.0)
Requires-Dist: matplotlib (>=3.5.1,<4.0.0); extra == "mark"
Requires-Dist: numba (>=0.55.0,<0.56.0)
Requires-Dist: numpy (>=1.21.0,<2.0.0)
Requires-Dist: pandas (>=1.3.0,<2.0.0); extra == "mark"
Requires-Dist: scipy (>=1.7.3,<2.0.0)
Requires-Dist: sphinx-rtd-theme (>=1.0.0,<2.0.0); extra == "docs"
Requires-Dist: sphinxcontrib-bibtex (>=2.4.1,<3.0.0); extra == "docs"
Requires-Dist: sqlalchemy (>=1.4.21,<2.0.0); extra == "mark"
Project-URL: Repository, https://github.com/N3PDF/eko
Description-Content-Type: text/markdown

<p align="center">
  <a href="https://n3pdf.github.io/eko/"><img alt="EKO" src="https://raw.githubusercontent.com/N3PDF/eko/master/doc/source/img/Logo.png" width=300></a>
</p>
<p align="center">
  <a href="https://github.com/N3PDF/eko/actions/workflows/unittests.yml"><img alt="Tests" src="https://github.com/N3PDF/eko/actions/workflows/unittests.yml/badge.svg" /></a>
  <a href="https://eko.readthedocs.io/en/latest/?badge=latest"><img alt="Docs" src="https://readthedocs.org/projects/eko/badge/?version=latest"></a>
  <a href="https://codecov.io/gh/N3PDF/eko"><img src="https://codecov.io/gh/N3PDF/eko/branch/master/graph/badge.svg" /></a>
  <a href="https://www.codefactor.io/repository/github/n3pdf/eko"><img src="https://www.codefactor.io/repository/github/n3pdf/eko/badge" alt="CodeFactor" /></a>
</p>

EKO is a Python module to solve the DGLAP equations in N-space in terms of Evolution Kernel Operators in x-space.

## Installation
EKO is available via PyPI: <a href="https://pypi.org/project/eko/"><img alt="PyPI" src="https://img.shields.io/pypi/v/eko"/></a> - so you can simply run
```bash
pip install eko
```

### Development

If you want to install from source you can run
```bash
git clone git@github.com:N3PDF/eko.git
cd eko
poetry install
```

To setup `poetry`, and other tools, see [Contribution
Guidelines](https://github.com/N3PDF/eko/blob/master/.github/CONTRIBUTING.md).

## Documentation
- The documentation is available here: <a href="https://eko.readthedocs.io/en/latest/?badge=latest"><img alt="Docs" src="https://readthedocs.org/projects/eko/badge/?version=latest"></a>
- To build the documentation from source install [graphviz](https://www.graphviz.org/) and run in addition to the installation commands
```bash
poe docs
```

## Citation policy
When using our code please cite
- our DOI: <a href="https://doi.org/10.5281/zenodo.3874237"><img src="https://zenodo.org/badge/DOI/10.5281/zenodo.3874237.svg" alt="DOI"/></a>
- our paper: [![arXiv](https://img.shields.io/badge/arXiv-2202.02338-b31b1b?labelColor=222222)](https://arxiv.org/abs/2202.02338)

## Contributing
- Your feedback is welcome! If you want to report a (possible) bug or want to ask for a new feature, please raise an issue: <a href="https://img.shields.io/github/issues/N3PDF/eko"><img alt="GitHub issues" src="https://img.shields.io/github/issues/N3PDF/eko"/></a>
- Please follow our [Code of Conduct](https://github.com/N3PDF/eko/blob/master/.github/CODE_OF_CONDUCT.md) and read the
  [Contribution Guidelines](https://github.com/N3PDF/eko/blob/master/.github/CONTRIBUTING.md)

