Optimizing colormaps with consideration for color vision deficiency to enable accurate interpretation of scientific data
Around 4% of the population suffer from colour blindness in one for or another with red/green colour blindness being the most common and sadly in many plots, graphs, presentations little effort is made to make things easier for those people with colour blindness.
Color blindness, also known as color vision deficiency (CVD), is the decreased ability to see color or differences in color. Simple tasks such as selecting ripe fruit, choosing clothing, and reading traffic lights can be more challenging. Color blindness may also make some educational activities more difficult.
A recent publication seeks to address this need, Optimizing colormaps with consideration for color vision deficiency to enable accurate interpretation of scientific data DOI
While there have been some attempts to make aesthetically pleasing or subjectively tolerable colormaps for those with CVD, our goal was to make optimized colormaps for the most accurate perception of scientific data by as many viewers as possible. We developed a Python module, cmaputil, to create CVD-optimized colormaps, which imports colormaps and modifies them to be perceptually uniform in CVD-safe colorspace while linearizing and maximizing the brightness range. The module is made available to the science community to enable others to easily create their own CVD-optimized colormaps.