Earlier this year, I released a color cycle picker that enforces a minimum perceptual distance between colors, including color vision deficiency simulations, with the goal of creating a better color cycle to replace the “category 10” color palette used by default in Matplotlib, along with other data visualization packages. While the picker works well for what it was designed for—allowing a user to create a color cycle—it requires user intervention to create color sets or cycles.1 The basic technique used—performing color vision deficiency simulations2 for various types of deficiencies and enforcing a minimum perceptual difference for the simulated colors using the CAM02-UCS3 perceptually uniform color space (where each type of deficiency is treated separately) and a minimum lightness distance (for grayscale)—is still valid for the random generation of color sets; it just needs to be extended to randomly sample the color space.
A color set doesn’t have a defined order, while a color cycle does. ↩
G. M. Machado, M. M. Oliveira, and L. A. F. Fernandes, “A Physiologically-based Model for Simulation of Color Vision Deficiency,” in IEEE Transactions on Visualization and Computer Graphics, vol. 15, no. 6, pp. 1291-1298, Nov.-Dec. 2009. doi:10.1109/TVCG.2009.113 ↩
Luo M.R., Li C. (2013) CIECAM02 and Its Recent Developments. In: Fernandez-Maloigne C. (eds) Advanced Color Image Processing and Analysis. Springer, New York, NY. doi:10.1007/978-1-4419-6190-7_2 ↩