Metadata-Version: 2.1
Name: pidgan
Version: 0.0.2
Summary: GAN-based models to fast-simulate the LHCb PID detectors
Author-email: Matteo Barbetti <matteo.barbetti@fi.infn.it>, Lucio Anderlini <lucio.anderlini@fi.infn.it>
License: GPLv3 License
Project-URL: repository, https://github.com/mbarbetti/pidgan
Keywords: tensorflow,machine learning,deep learning,generative adversarial nets,lhcb experiment,lamarr,ultra-fast simulation,particle identification
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.11
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: <=3.11,>=3.7
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: tensorflow (>=2.7)
Requires-Dist: scikit-learn (>=1.0)
Requires-Dist: pyyaml
Provides-Extra: lamarr
Requires-Dist: numpy ; extra == 'lamarr'
Requires-Dist: pandas ; extra == 'lamarr'
Requires-Dist: uproot ; extra == 'lamarr'
Requires-Dist: matplotlib ; extra == 'lamarr'
Requires-Dist: html-reports (>=0.2) ; extra == 'lamarr'
Provides-Extra: style
Requires-Dist: black ; extra == 'style'
Requires-Dist: flake8 ; extra == 'style'
Requires-Dist: isort[colors] ; extra == 'style'
Provides-Extra: tests
Requires-Dist: pytest (>=6.0) ; extra == 'tests'
Requires-Dist: pytest-cov ; extra == 'tests'

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<h1 align="center">PIDGAN</h1>

<h2 align="center">
  <em>GAN-based models to fast-simulate the LHCb PID detectors</em>
</h2>

<p align="center">
  <a href="https://www.tensorflow.org/versions"><img alt="TensorFlow versions" src="https://img.shields.io/badge/tensorflow-2.7–2.12-f57000?style=flat"></a>
  <a href="https://scikit-learn.org/stable/whats_new.html"><img alt="scikit-learn versions" src="https://img.shields.io/badge/sklearn-1.0–1.2-f89939?style=flat"></a>
  <a href="https://www.python.org/downloads"><img alt="Python versions" src="https://img.shields.io/badge/python-3.7–3.11-blue?style=flat"></a>
  <a href="https://pypi.python.org/pypi/pidgan"><img alt="PyPI - Version" src="https://img.shields.io/pypi/v/pidgan"></a>
  <a href="LICENSE"><img alt="GitHub - License" src="https://img.shields.io/github/license/mbarbetti/pidgan"></a>
</p>

<p align="center">
  <a href="https://github.com/mbarbetti/pidgan/actions/workflows/tests.yml"><img alt="GitHub - Tests" src="https://github.com/mbarbetti/pidgan/actions/workflows/tests.yml/badge.svg?branch=main"></a>
  <a href="https://codecov.io/gh/mbarbetti/pidgan"><img alt="Codecov" src="https://codecov.io/gh/mbarbetti/pidgan/branch/main/graph/badge.svg?token=ZLWDgWhnkq"></a>
</p>

<p align="center">
  <a href="https://github.com/mbarbetti/pidgan/actions/workflows/style.yml"><img alt="GitHub - Style" src="https://github.com/mbarbetti/pidgan/actions/workflows/style.yml/badge.svg?branch=main"></a>
  <a href="https://github.com/psf/black"><img alt="Code style: black" src="https://img.shields.io/badge/code%20style-black-000000.svg"></a>
</p>

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### Generative Adversarial Networks

| Algorithms* | Implementation |  Test  |                         Paper                        |
|:-----------:|:--------------:|:------:|:----------------------------------------------------:|
|    `GAN`    |       ✅       |   ✅   |  [arXiv:1406.2661](https://arxiv.org/abs/1406.2661)  |
|  `BceGAN`   |       ✅       |   ✅   |                                                      |
|   `LSGAN`   |       ✅       |   ✅   | [arXiv:1611.04076](https://arxiv.org/abs/1611.04076) |
|   `WGAN`    |       ✅       |   ✅   | [arXiv:1701.07875](https://arxiv.org/abs/1701.07875) |
|  `WGAN_GP`  |       ✅       |   ✅   | [arXiv:1704.00028](https://arxiv.org/abs/1704.00028) |
| `CramerGAN` |       ✅       |   ✅   | [arXiv:1705.10743](https://arxiv.org/abs/1705.10743) |
| `WGAN_ALP`  |       ✅       |   ✅   | [arXiv:1907.05681](https://arxiv.org/abs/1907.05681) |

*Designed to operate according to the **conditional version** proposed in [arXiv:1411.1784](https://arxiv.org/abs/1411.1784)

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#### Some tricks:
* [arXiv:1606.03498](https://arxiv.org/abs/1606.03498)
* [arXiv:1701.04862](https://arxiv.org/abs/1701.04862)
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