| Name | patato JSON |
| Version |
0.6.1
JSON |
| download |
| home_page | None |
| Summary | A Python Toolkit for the analysis of photoacoustic tomography data. |
| upload_time | 2025-08-19 12:50:29 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | <3.14,>=3.8 |
| license | MIT License
Copyright (c) 2023 Thomas Else
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE. |
| keywords |
photoacoustics
jax
tomography
reconstruction
spectral unmixing
dynamic contrast enhanced
backprojection
model based
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
[](https://joss.theoj.org/papers/456eaf591244858915ad8730dcbc19d7)
[](https://patato.readthedocs.io/en/latest/?badge=latest)
[](https://github.com/bohndieklab/patato/blob/main/LICENSE.MD)
[](https://badge.fury.io/py/patato)
[](https://github.com/bohndieklab/patato/actions/workflows/build_wheels.yml)
# 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.
Raw data
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