dekoder 0.15.2

Evolution Kernel Operators
Documentation 
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<p align="center">
  <a href="https://eko.readthedocs.io/"><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://github.com/N3PDF/eko/actions/workflows/unittests-rust.yml"><img alt="Rust tests" src="https://github.com/N3PDF/eko/actions/workflows/unittests-rust.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/NNPDF/eko"><img src="https://codecov.io/gh/NNPDF/eko/branch/master/graph/badge.svg" /></a>
  <a href="https://www.codefactor.io/repository/github/nnpdf/eko"><img src="https://www.codefactor.io/repository/github/nnpdf/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>
```bash
pip install eko
```
- conda-forge: [![Conda Version](https://img.shields.io/conda/vn/conda-forge/eko.svg)](https://anaconda.org/conda-forge/eko)
```bash
conda 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
```

## Tests and benchmarks
- To run unit test you can do
```bash
poe tests
```

- Benchmarks of specific part of the code, such as the strong coupling or msbar masses running, are available doing
```bash
poe bench
```

- The complete list of benchmarks with external codes is available through `ekomark`: [documentation](https://eko.readthedocs.io/en/latest/development/Benchmarks.html)

## 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://github.com/N3PDF/eko/issues"><img alt="GitHub issues" src="https://img.shields.io/github/issues/N3PDF/eko"/></a>
- If you need help, for installation, usage, or anything related, feel free to open a new discussion in the ["Support" section](https://github.com/NNPDF/eko/discussions/categories/support)
- 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)