Much work has been done in the last decade related to 1-dimensional colormaps (see for eaxmple Peter Kovesis paper and Nathaniel Smith and Stéfan van der Walts talk (2015)).
This post follows my previous post on 2D colormaps, and many of the design principles will be the same. However, with n ≥ 3, it quickly becomes unfeasible to create a full lookup table. With n = 3 channels and 256 values in each channel, the lookup table would be a matrix of 256^3 elements, likely much larger than the image the colormap is applied to. Instead, n independent 1D lookup tables are created, and the resulting colors are then combined.
Continue reading “Multivariate colormaps for n dimensions”