Hyperspectral Imaging Analysis Plugin
Napari plugin to perform analysis on Hyperspectral Imaging datasets.
A Napari plugin to perform analysis on Hyperspectral Imaging datasets.
The 'Data Manager' widget loads, opens and visualize the datasets. The 'Fusion' widget fused two or three opened datasets. The 'UMAP' widget perform and visualize the Uniform Manifold Approximation and Projection analysis.
This napari plugin was generated with copier using the napari-plugin-template.
Installation
You can install napari-hsi-analysis via pip:
pip install napari-hsi-analysis
To install latest development version :
pip install git+https://github.com/alessiadb/napari-hsi-analysis.git
Usage
A detailed guide which shows how to use the plugin and how to properly choose the parameters can be found here.
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 BSD-3 license, "napari-hsi-analysis" is free and open source software
Issues
If you encounter any problems, please file an issue along with a detailed description.
Version:
- 0.3.1
Last updated:
- 2025-06-23
First released:
- 2025-03-12
License:
- Copyright (c) 2025, Alessia Di...
Operating system:
- Information not submitted
Requirements:
- numpy
- magicgui
- qtpy
- scikit-image
- scikit-learn
- h5py
- bokeh
- plotly
- PyWavelets
- scipy
- pyqtgraph
- qtawesome
- matplotlib
- umap-learn
- spectral
- tox; extra == "testing"
- pytest; extra == "testing"
- pytest-cov; extra == "testing"
- pytest-qt; extra == "testing"
- napari; extra == "testing"
- pyqt5; extra == "testing"
- numpy; extra == "testing"
- magicgui; extra == "testing"
- qtpy; extra == "testing"
- scikit-image; extra == "testing"
- scikit-learn; extra == "testing"
- h5py; extra == "testing"
- bokeh; extra == "testing"
- plotly; extra == "testing"
- PyWavelets; extra == "testing"
- scipy; extra == "testing"
- pyqtgraph; extra == "testing"
- qtawesome; extra == "testing"
- matplotlib; extra == "testing"
- umap-learn; extra == "testing"
- spectral; extra == "testing"