@mattwigway/jupyterlab_colorblind

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).

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.

Prerequisites

• JupyterLab

Installation

To install using pip:

jupyter labextension install jupyterlab_colorblind

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