Optimize color palette for color vision deficiency

This function adapts color palettes to color vision deficiency (CVD) by optimizing the CVD severity to try reach a target color difference (DIN99d \(\delta E\)) of the user's choosing. Basically, it will choose a color palette that is as close as possible to the target \(\delta E\) by tweaking the CVD severity option in qualpal.

Usage

autopal(
  n,
  colorspace = "pretty",
  cvd = c("protan", "deutan", "tritan"),
  target = 20
)

Arguments

n

Number of colors to generate.

colorspace

Either 1) a list of three named numeric vectors: h (hue), s (saturation), and l (lightness), all of length 2 specifying a min and max value for the range. The values has to be in the range -360 to 360 for h, and 0 to 1 for s and l 2), or 2) a character vector specifying one of the predefined color spaces (see below).

cvd

Color vision deficiency adaptation to adapt the color palette to.

target

Target color difference.

Value

A list of class qualpal with the following components.

HSL

A matrix of the colors in the HSL color space.

DIN99d

A matrix of the colors in the DIN99d color space (after power transformations).

RGB

A matrix of the colors in the sRGB color space.

hex

A character vector of the colors in hex notation.

de_DIN99d

A distance matrix of color differences according to delta E DIN99d.

min_de_DIN99d

The smallest pairwise DIN99d color difference.

Details

The rationale for this function is that when there are few colors in a color palette, there is no cost involved in adapting colors to CVD -- the colors will still remain distinct. As more an more colors are added to the palette, however, adapting the color palette to CVD will eventually lead to colors that are too similar. This function gradually loosens the adaptation to CVDs by lowering the severity of CVD to simulate to before picking colors (the cvd_severity argument in qualpal)

Examples

pal <- autopal(3, cvd = "protan", target = 15)
plot(pal)