jupyterlab_colorblind's Introduction

jupyterlab_colorblind

Display plots with colorblindness simulation.

Once installed in JupyterLab, selecting a color-blindness mode under View -> Color-Blindness Simulation will transform all images to versions that simulate the type of color-blindness selected. Color-blindness affects a significant proportion of the population, making many data displays inaccessible to them. Almost 8% of Caucasian males are affected by red-green color blindness, with females and other racial groups less affected (Machado, Oliveira, and Fernandes, 2009).

Installation

In JupyerLab, click on extensions in the left panel, then search for @mattwigway/jupyterlab_colorblind.

Credits

The matrix color transformations come from Machado, Oliveira, and Fernandes, 2009, using the computed matrices they posted on the companion website for the article. All color-blindness simulations assume maximum severity of colorblindness. The idea to apply color-blindness filters using SVG filters in CSS comes from RGBlind. The relative frequency of different types of color blindness is based on Color Oracle.

Development

For a development install (requires npm version 4 or later), do the following in the repository directory:

# Clone the repo to your local environment
# Move to jupyterlab_colorblind directory
# Install dependencies
npm install
# Install your development version of the extension
jupyter labextension install .

You run JupyterLab in watch mode to watch for changes in the extension's source and automatically rebuild.

# Run jupyterlab in watch mode
jupyter lab --watch

Now every change will be built locally and bundled into JupyterLab. Be sure to refresh your browser page after saving file changes to reload the extension (note: you'll need to wait for webpack to finish, which can take 10s+ at times).

Uninstall

jupyter labextension uninstall jupyterlab_colorblind

References

Machado, G. M., Oliveira, M. M., & Fernandes, L. A. F. (2009). A Physiologically-based Model for Simulation of Color Vision Deficiency. IEEE Transactions on Visualization and Computer Graphics, 15(6), 1291–1298. https://doi.org/10.1109/TVCG.2009.113

jupyterlab_colorblind's People

mattwigway / jupyterlab_colorblind Goto Github PK