Metadata-Version: 2.4
Name: gpsr
Version: 0.1.0
Summary: Phase space reconstruction using differentiable beam dynamics and generative beam representations
Author: Ryan Roussel, Juan Pablo Gonzalez Aguilera
Project-URL: Homepage, https://github.com/roussel-ryan/gpsr
Classifier: Development Status :: 4 - Beta
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering
Requires-Python: >=3.10
Description-Content-Type: text/markdown
Requires-Dist: lightning
Requires-Dist: matplotlib
Requires-Dist: cheetah-accelerator>=0.7.1
Requires-Dist: tensorboard
Requires-Dist: scipy
Requires-Dist: scikit-image
Provides-Extra: dev
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Requires-Dist: pre-commit; extra == "dev"
Provides-Extra: doc
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Generative Phase Space Reconstruction (GPSR)
====

Flexible reconstruction of beam distributions from experimental measurements.

The goal of this package is to provide software necessary to reconstruct
phase space distributions from experimental data. This work is based on
the following publications:

[Phase Space Reconstruction from Accelerator Beam Measurements Using Neural Networks and Differentiable Simulations](https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.130.145001)

[Efficient six-dimensional phase space reconstructions from experimental measurements using generative machine learning](https://journals.aps.org/prab/abstract/10.1103/PhysRevAccelBeams.27.094601)

<div align="center">
  <img src="docs/assets/6d_cartoon.png", width="1000">
</div>

## Installation
Using `pip`

```shell
git clone https://github.com/roussel-ryan/gpsr.git
cd gpsr
pip install -e .
```
or for development,

```shell
pip install -e ".[dev]"
```
