Metadata-Version: 2.4
Name: patato
Version: 0.6.1
Summary: A Python Toolkit for the analysis of photoacoustic tomography data.
Author-email: Thomas Else <telse@ic.ac.uk>
License: MIT License
        
        Copyright (c) 2023 Thomas Else
        
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Project-URL: Homepage, https://github.com/bohndieklab/patato
Project-URL: Bug Tracker, https://github.com/bohndieklab/patato/issues
Project-URL: Documentation, https://patato.readthedocs.io
Keywords: photoacoustics,jax,tomography,reconstruction,spectral unmixing,dynamic contrast enhanced,backprojection,model based
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: <3.14,>=3.8
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License-File: LICENSE.MD
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Requires-Dist: pylops
Requires-Dist: h5py
Requires-Dist: pandas
Requires-Dist: xarray
Requires-Dist: numpy>=1.22
Requires-Dist: scipy
Requires-Dist: matplotlib
Requires-Dist: matplotlib_scalebar
Requires-Dist: dask
Requires-Dist: pybind11
Requires-Dist: jax[cpu]
Requires-Dist: customtkinter
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Dynamic: license-file

[![Journal of open source software status](https://joss.theoj.org/papers/456eaf591244858915ad8730dcbc19d7/status.svg)](https://joss.theoj.org/papers/456eaf591244858915ad8730dcbc19d7)
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![Logo](https://github.com/BohndiekLab/patato/raw/main/docs/logos/PATATO%20Logo_1_Combination.png "Logo")

# PATATO: PhotoAcoustic Tomography Analysis TOolkit

[Documentation](https://patato.readthedocs.io/en/develop/)

PATATO is an Open-Source project to enable the analysis of photoacoustic (PA) imaging data in a transparent, reproducible and extendable way. We provide efficient, GPU-optimised implementations of common PA algorithms written around standard Python libraries, including filtered backprojection, model-based reconstruction and spectral unmixing.

The tool supports many file formats, such as the International Photoacoustic Standardisation Consortium (IPASC) data format, and it can be extended to support custom data formats. We hope that this toolkit can enable faster and wider dissemination of analysis techniques for PA imaging and provide a useful tool to the community.

* Please report any bugs or issues you find to our GitHub repository
* Please do get involved! Contact Thomas Else (telse@ic.ac.uk).

## Getting Started
In order to use PATATO, you must have a Python environment set up on your computer. We recommend using uv (https://docs.astral.sh/uv/) to run Python. This will help you to avoid dependency conflicts. You can alternatively use Anaconda or virtual environments.

**We currently recommend running PATATO on Python version 3.12.**

You can install patato with uv like so:

```shell
uv add patato
```

Or, using pip:

```shell
pip install patato
```

To setup support for GPU-based reconstruction, please follow the installation guide in the documentation.

## Citing PATATO

To cite PATATO, please reference our article in the Journal of Open Source software, [here](https://joss.theoj.org/papers/456eaf591244858915ad8730dcbc19d7).

## Documentation, examples and contributing
Documentation for PATATO can be found at https://patato.readthedocs.io/en/latest/?badge=latest.

Copyright (c) Thomas Else 2022-25.
Distributed under a MIT License.
