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napari-brainbow-diagnose

License BSD-3 PyPI Python Version tests codecov napari hub

Explore image in channel coordinate spaces.

Original motivation: Brainbow dataset have unique features that need to be addressed by specialized tools. This plugin allows you to visualize the distribution of the channel ratio interactively in the image space and channel spaces.

You can also use this plugin along with the napari-cluster-plotter plugin to interact with individual objects.

demo_gif

Available Channel space transformation

The following channel spaces are available:

image|width=10

From Cartesian RGB:

Example Notebooks

You can use this plugin to visualize channel space of:

Example Datasets

If you want to use your dataset, you have to format it such as each channel is in one distinct napari.Layers You can open test dataset to try this plugin in File > Open Sample > napari-brainbow-diagnose.

  • The RGB Cube is an array with shape (3x256x256x256) cube : Great to check how the plugin work when all color are represented
  • ChroMS Cortex Sample is an array with shape (3x256x256x256) #Hugo : Real life brainbow image (Cortex E18 Emx1Cre) !

Once you have your layers you can use the dropdown and select the corresponding layer. It is advised to match the red, green, blue order so the ratio you see on the napari viewer corresponds to the Hue-Saturation Wheel of the plugin.

Installation

You can install napari-brainbow-diagnose via pip:

pip install napari-brainbow-diagnose

If you want to use napari-cluster-plotter plugin you also need to install it manually

To install latest development version :

pip install git+https://github.com/LaboratoryOpticsBiosciences/napari-brainbow-diagnose.git

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-brainbow-diagnose" is free and open source software

Issues

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


This napari plugin was generated with Cookiecutter using @napari's cookiecutter-napari-plugin template.