Playing with CIE Lab Colors in R

Currently I’m taking the wonderful course Computing for Data Analysis on Coursera, and in this weeks lecture I learned about how to define custom color palettes in R.

You can do this using the colorRampPalette() function that comes with the grDevices package. Calling this function will return another function that you can call to generate the color palette.

> library(grDevices)
> palette = colorRampPalette(c("red", "yellow"))
> palette(5)
[1] "#FF0000" "#FF3F00" "#FF7F00" "#FFBF00" "#FFFF00"

By default, R uses the RGB color space to interpolate between colors. As I mentioned in earlier posts, this is not as ideal choice for data visualization. Fortunately, R allows you to interpolate in CIE Lab color space. Let’s write a quick function plotColors() to plot the colors. The function takes two arguments: palette is the palette function returned by colorRampPalette and n defines the number of color steps we want to display. Internally the function simply draws a bar chart without axes and with no spacing between the bars.

plotColors = function(palette, n=10) {
   colors = palette(n)
   barplot(rep(1,n), col=colors, border=colors, space=0, yaxt='n')
}

Now let’s look at the default interpolation between red and yellow in five steps. On my screen the first two colors look almost the same, although they are equally-spaced in RGB.

rgb interpolation between red and yellow

> pal = colorRampPalette(c("red", "yellow"))
> plotColors(pal, 5)

You can set the color space to CIE Lab by setting the parameter space to “Lab”. As you can see, the difference is huge. That’s not a question of taste.

CIE Lab interpolation

> pal = colorRampPalette(c("red", "yellow"), space="Lab")
> plotColors(pal, 5)

Feel free to play around with that code snippets yourself. Instead of the named colors you can also create palettes between arbitrary colors by providing hexadecimal codes:

> pal = colorRampPalette(c("#FF0000", "#0000FF"), space="Lab")
> plotColors(pal, 5)

You can find the full code for this example on Github.