"A color space is perceptually uniform if a change of length in any direction X of the color space is perceived by a human as the same change. Non-uniform perceptual color spaces like RGB - Red Green Blue and RYB - Red Yellow Blue can have stark contrasts when transitioning from one hue to another hue. In data visualization, these contrasts can be mistaken as changes in the data rather than as transitions in the color palette."
"As a result, many data visualization practitioners prefer to work in the perceptual uniform CIE LAB or Hue Chroma Luminance (HCL) color spaces. Unfortunately, these color spaces have irregularly shaped geometries resulting in challenges to calculate color combinations that also pass color deficiency. Gen AI systems, like Grok, can help to quickly locate these perceptual uniform color schemes for data visualization."
Perceptual uniformity means equal-length changes in any direction of a color space appear equally different to humans. Non-uniform systems like RGB and RYB produce visual contrasts that can be misread as data changes. Practitioners favor perceptual uniform spaces such as CIE LAB or HCL for data visualization because they map perceived differences more consistently. Those spaces have irregular geometries that complicate computing color harmonies that remain distinct under color-vision deficiencies. Generative AI tools like xAI Grok can accelerate finding perceptually uniform triads and checking their performance under conditions such as protanopia, where loss of the red cone can cause problematic similarity.
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