Metadata-Version: 2.1
Name: napari-ISM
Version: 0.1.0
Summary: It performs Adaptive Pixel Reassignment.
Home-page: https://github.com/VicidominiLab/napari-ISM
Author: Alessandro Zunino
Author-email: alessandro.zunino@iit.it
License: LGPL-3.0-only
Project-URL: Bug Tracker, https://github.com/VicidominiLab/napari-ISM/issues
Project-URL: Documentation, https://github.com/VicidominiLab/napari-ISM#README.md
Project-URL: Source Code, https://github.com/VicidominiLab/napari-ISM
Project-URL: User Support, https://github.com/VicidominiLab/napari-ISM/issues
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Developers
Classifier: Framework :: napari
Classifier: Topic :: Software Development :: Testing
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Operating System :: OS Independent
Classifier: License :: OSI Approved :: GNU Lesser General Public License v3 (LGPLv3)
Requires-Python: >=3.8
Description-Content-Type: text/markdown
Provides-Extra: testing
License-File: LICENSE

# napari-ISM

[![napari hub](https://img.shields.io/endpoint?url=https://api.napari-hub.org/shields/napari-ISM)](https://napari-hub.org/plugins/napari-ISM)
[![License](https://img.shields.io/pypi/l/napari-ISM.svg?color=green)](https://github.com/VicidominiLab/napari-ISM/raw/main/LICENSE)
[![PyPI](https://img.shields.io/pypi/v/napari-ISM.svg?color=green)](https://pypi.org/project/napari-ISM)
[![Python Version](https://img.shields.io/pypi/pyversions/napari-ISM.svg?color=green)](https://python.org)
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It performs Adaptive Pixel Reassignment via a phase-correlation algorithm. Once installed, you can upload any ISM-dataset in .h5 or .npy format. The plugin expects a numpy array of the format _rzxytc_ (r: repetition, z: axial dimension, xy: lateral dimensions, t: time dimension, c: detector element). If the _rzt_ dimensions are not present, add manually fake dimensions (e.g. using the _numpy.expand_dims_ function).
You can also generate a synthetic ISM-dataset from the File menu. Once a dataset is uploaded on an image layer, you can use the Napari plugin menu to perform either a sum on the _c_ dimension or perform Adaptive Pixel Reassignment on the _c_ dimension.

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and review the napari docs for plugin developers:
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## Installation

You can install `napari-ISM` via [pip]:

    pip install napari-ISM

It requires the following Python packages

    numpy
	scipy
	scikit-image
    h5py
	napari

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To install latest development version :

    pip install git+https://github.com/VicidominiLab/napari-ISM.git
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## Contributing

Contributions are very welcome. Tests can be run with [tox], please ensure
the coverage at least stays the same before you submit a pull request.

## License

Distributed under the terms of the [GNU LGPL v3.0] license,
"napari-ISM" is free and open source software

## Issues

If you encounter any problems, please [file an issue] along with a detailed description.

[napari]: https://github.com/napari/napari
[Cookiecutter]: https://github.com/audreyr/cookiecutter
[@napari]: https://github.com/napari
[MIT]: http://opensource.org/licenses/MIT
[BSD-3]: http://opensource.org/licenses/BSD-3-Clause
[GNU GPL v3.0]: http://www.gnu.org/licenses/gpl-3.0.txt
[GNU LGPL v3.0]: http://www.gnu.org/licenses/lgpl-3.0.txt
[Apache Software License 2.0]: http://www.apache.org/licenses/LICENSE-2.0
[Mozilla Public License 2.0]: https://www.mozilla.org/media/MPL/2.0/index.txt
[cookiecutter-napari-plugin]: https://github.com/napari/cookiecutter-napari-plugin

[file an issue]: https://github.com/VicidominiLab/napari-ISM/issues

[napari]: https://github.com/napari/napari
[tox]: https://tox.readthedocs.io/en/latest/
[pip]: https://pypi.org/project/pip/
[PyPI]: https://pypi.org/
