Abstract
CMasher is a Python package that provides a curated collection of scientific colormaps, showcased in the online documentation (https://cmasher.readthedocs.io). The colormaps in CMasher are all designed to be perceptually uniform sequential using the 'viscm' package; most of them are color-vision deficiency friendly; and they cover a wide range of different color combinations to accommodate for most applications. It aims to provide several alternatives to commonly used colormaps, like 'chroma' and 'rainforest' for 'jet'; 'sunburst' for 'hot'; 'neutral' for 'binary'; and 'fusion' and 'redshift' for 'coolwarm'. With CMasher, I hope to help others with picking the correct colormap for the job.
Highlights
The use of colors in the visualization of scientific results is a common sight nowadays
In order to help with picking a scientific colormap, I introduce the CMasher package
A good scientific colormap is often described/characterized as perceptually uniform sequential, which means that the colormap is perceived as uniformly changing in lightness and saturation, mostly at the same hue (Rogowitz, Treinish, & Bryson, 1996; Sharpe, Stockman, Jaegle, & Nathans, 1999)
Summary
The use of colors in the visualization of scientific results is a common sight nowadays. In order to help with picking a scientific colormap, I introduce the CMasher package. A good scientific colormap is often described/characterized as perceptually uniform sequential, which means that the colormap is perceived as uniformly changing in lightness and saturation, mostly at the same hue (Rogowitz, Treinish, & Bryson, 1996; Sharpe, Stockman, Jaegle, & Nathans, 1999).
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