knitr::opts_chunk$set( collapse = TRUE, comment = "#>" )
Deciding if a color palette is a colorblind friendly is a hard task. This cannot be done in an entirely automatic fashion, as the decision needs to be confirmed by visual judgments. The goal of colorblindcheck is to provide tools to decide if the selected color palette is colorblind friendly, including:
palette_dist()
- Calculation of the distances between the colors in the input palette and between the colors in simulations of the color vision deficiencies - deuteranopia, protanopia, and tritanopia.palette_plot()
- Plotting of the original input palette and simulations of color vision deficiencies - deuteranopia, protanopia, and tritanopia.palette_check()
- Creating summary statistics comparing the original input palette and simulations of color vision deficiencies - deuteranopia, protanopia, and tritanopia.The work in this package was inspired by a blog post I wrote some code that automatically checks visualizations for non-colorblind safe colors. Here's how it works by Gregor Aisch.
The colorblindcheck accepts a vector of hexadecimal color descriptions as the input.
It can be created using different existing R functions (e.g. rainbow()
) or packages (e.g. colorspace, RColorBrewer, rcartocolor, etc.).
library(colorblindcheck) rainbow_pal = rainbow(n = 7) rainbow_pal
The primary function in this package is palette_check()
, which creates a summary comparison between the original input palette and simulations of color vision deficiencies - deuteranopia, protanopia, and tritanopia.
palette_check(rainbow_pal, plot = TRUE)
The palette_check()
function returns a data.frame with 4 observations and 8 variables:
name
: original input color palette (normal), deuteranopia, protanopia, and tritanopian
: number of colorstolerance
: minimal value of the acceptable difference between the colors to distinguish between themncp
: number of color pairsndcp
: number of differentiable color pairs (color pairs with distances above the tolerance value)min_dist
: minimal distance between colorsmean_dist
: average distance between colorsmax_dist
: maximal distance between colorsAdditionally, a plot comparing the original input palette and simulations of color vision deficiencies - deuteranopia, protanopia, and tritanopia can be shown. This help to decide if the selected color palette is colorblind friendly.
For example, the above output shows that the minimal distance between colors in the input palette is about 12; however, the minimum distance between colors simulation of tritanopia is only about 2. It can suggest that some colors in this palette would not be distinguishable by people with color vision deficiencies.
The palette_dist()
function calculates distances between the colors in the input palette, as well as in a simulation of the selected color vision deficiency - deuteranopia, protanopia, and tritanopia.
It allows finding which colors are the most or the least similar and to compare the behavior of color palettes for different color vision deficiencies.
In the original rainbow_pal
object, the closest colors were the third and the fourth one (a distance of about 12); however, the deuteranopia version has a minimal distance of 3 between the second and third color.
# normal palette_dist(rainbow_pal) # deuteranopia palette_dist(rainbow_pal, cvd = "pro")
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