Overview

The colorspace package provides several color manipulation utilities that are useful for creating, assessing, or transforming color palettes, namely:

Desaturation in HCL space

Desaturation should map a given color to the gray with the same “brightness”. In principle, any perceptually-based color model (HCL, HLS, HSV, …) could be employed for this but HCL works particularly well because its coordinates capture the perceptual properties better than most other color models.

The desaturate() function converts any given hex color code or named R color to the corresponding HCL coordinates and sets the chroma to zero. Thus, only the luminance matters which captures the “brightness” mentioned above. Finally, the resulting HCL coordinates are transformed back to hex color codes for use in R.

For illustration, a few simple examples are presented below. More examples in the context of palettes for statistical graphics are discussed along with the color vision deficiency article.

First, desaturate() is used to desaturate a vector of R color names:

desaturate(c("white", "orange", "blue", "black"))
## [1] "#FFFFFF" "#B8B8B8" "#4C4C4C" "#000000"

Notice that the hex codes corresponding to three coordinates in sRGB space are always the same, indicating gray colors.

Analogously, hex color codes can also be transformed - in this case RGB rainbow colors from the base R function rainbow():

## [1] "#FF0000" "#00FF00" "#0000FF"
## [1] "#7F7F7F" "#DCDCDC" "#4C4C4C"

Even this simple example suffices to show that the three RGB rainbow colors have very different grayscale levels. This deficiency is even clearer when using a full color wheel (of colors with hues in [0, 360] degrees). While the RGB rainbow() is very unbalanced the HCL rainbow_hcl() (or also qualitative_hcl()) is (by design) balanced with respect to luminance.

wheel <- function(col, radius = 1, ...)
  pie(rep(1, length(col)), col = col, radius = radius, ...) 
par(mar = rep(0.5, 4), mfrow = c(2, 2))
wheel(rainbow(8))
wheel(desaturate(rainbow(8)))
wheel(rainbow_hcl(8))
wheel(desaturate(rainbow_hcl(8)))

Lighten or darken colors

In principle, a similar approach for lightening and darkening colors can be employed as for desaturation above. The colors can simply be transformed to HCL space and then the luminance can either be decreased (turning the color darker) or increased (turning it lighter) while preserving the hue and chroma coordinates.

This strategy typically works well for lightening colors, although in some situations the result can be rather colorful. Conversely, when darkening rather light colors with little chroma, this can result in rather gray colors.

In these situations, an alternative might be to apply the analogous strategy in HLS space which is frequently used in HTML style sheets. However, this strategy may also yield colors that are either too gray or too colorful. A compromise that sometimes works well is to adjust the luminance coordinate in HCL space but to take the chroma coordinate corresponding to the HLS transformation.

We have found that typically the HCL-based transformation performs best for lightening colors and this is hence the default in lighten(). For darkening colors, the combined strategy often works best and is hence the default in darken(). In either case it is recommended to try the other available strategies in case the default yields unexpected results.

Regardless of the chosen color space, the adjustment of the L component can occur by two methods, relative (the default) and absolute. For example L - 100 * amount is used for absolute darkening, or L * (1 - amount) for relative darkening. See lighten() and darken() for more details.

For illustration a qualitative palette (Okabe-Ito) is transformed by two levels of both lightening and darkening, respectively.

oi <- c("#61A9D9", "#ADD668", "#E6D152", "#CE6BAF", "#797CBA")
swatchplot(
  "-40%" = lighten(oi, 0.4),
  "-20%" = lighten(oi, 0.2),
  "  0%" = oi,
  " 20%" =  darken(oi, 0.2),
  " 40%" =  darken(oi, 0.4),
  off = c(0, 0)
)

Adjust or extract the transparency of colors

Alpha transparency is useful for making colors semi-transparent, e.g., for overlaying different elements in graphics. An alpha value (or alpha channel) of 0 (or 00 in hex strings) corresponds to fully transparent and an alpha value of 1 (or FF in hex strings) corresponds to fully opaque. If a color hex string in R does not provide an explicit alpha transparency, the color is assumed to be fully opaque.

The adjust_transparency() function can be used to adjust the alpha transparency of a set of colors. It always returns a hex color specification. This hex color can have the alpha transparency added/removed/modified depending on the specification of the argument alpha:

  • alpha = NULL: Returns a hex vector with alpha transparency only if needed. Thus, it keeps the alpha transparency for the colors (if any) but only if different from opaque.
  • alpha = TRUE: Returns a hex vector with alpha transparency for all colors, using opaque (FF) as the default if missing.
  • alpha = FALSE: Returns a hex vector without alpha transparency for all colors (even if the original colors had non-opaque alpha).
  • alpha numeric: Returns a hex vector with alpha transparency for all colors set to the alpha argument (recycled if necessary).

For illustration, the transparency of a single black color is modified to three alpha levels: fully transparent, semi-transparent, and fully opaque, respectively. Black can be equivalently specified by name ("black"), hex string ("#000000"), or integer position in the palette (1).

adjust_transparency("black",   alpha = c(0, 0.5, 1))
## [1] "#00000000" "#00000080" "#000000FF"
adjust_transparency("#000000", alpha = c(0, 0.5, 1))
## [1] "#00000000" "#00000080" "#000000FF"
adjust_transparency(1,         alpha = c(0, 0.5, 1))
## [1] "#00000000" "#00000080" "#000000FF"

Subsequently, different settings of alpha are illustrated for adjusting a vector with three shades of gray, specified by name (gray, opaque), opaque hex string ("#BEBEBE"), and semi-transparent hex string ("#BEBEBE80"). Four types of adjustment are shown: only if necessary (alpha = NULL), add (alpha = TRUE), remove (alpha = FALSE), or modify (alpha = 0.8).

x <- c("gray", "#BEBEBE", "#BEBEBE80")
adjust_transparency(x, alpha = NULL)
## [1] "#BEBEBE"   "#BEBEBE"   "#BEBEBE80"
adjust_transparency(x, alpha = TRUE)
## [1] "#BEBEBEFF" "#BEBEBEFF" "#BEBEBE80"
adjust_transparency(x, alpha = FALSE)
## [1] "#BEBEBE" "#BEBEBE" "#BEBEBE"
adjust_transparency(x, alpha = 0.8)
## [1] "#BEBEBECC" "#BEBEBECC" "#BEBEBECC"

The extract_transparency() function can be used to extract the alpha transparency from a set of colors. It allows to specify the default value - that should be used for colors without an explicit alpha transparency (defaulting to fully opaque) - and mode of the return value. This can either be numeric (in [0, 1]), integer (0L, 1L, …, 255L), character (“00”, “01”, …, “FF”), or an object of class hexmode (internally represented as integer with printing as character). The default can use any of these modes as well (independent of the output mode) or be NA.

For illustration we extract the transparency from the gray colors in x in different formats and with different default values

extract_transparency(x, mode = "numeric")
## [1] 1.0000000 1.0000000 0.5019608
extract_transparency(x, mode = "hexmode")
## [1] "ff" "ff" "80"
extract_transparency(x, default = NA)
## [1]        NA        NA 0.5019608
extract_transparency(x, default = "80", mode = "integer")
## [1] 128 128 128

Compute and visualize W3C contrast ratios

The Web Content Accessibility Guidelines (WCAG) by the World Wide Web Consortium (W3C) recommend a contrast ratio of at least 4.5 for the color of regular text on the background color, and a ratio of at least 3 for large text. See . This relies on a specific definition of relative luminances (essentially based on power-transformed sRGB coordinates) that is different from the perceptual luminance as defined, for example, in the HCL color model. Note also that the WCAG pertain to text and background color and not to colors used in data visualization.

For illustration we compute and visualize the contrast ratios of the default palette in R compared to a white background.

## [1] 21.000000  3.758588  1.973030  3.163940  1.603030  4.805641  1.608044
## [8]  2.679156
contrast_ratio(palette(), "white", plot = TRUE)

Maximum chroma for given hue and luminance

As the possible combinations of chroma and luminance in HCL space depend on hue, it is not obvious which trajectories through HCL space are possible prior to trying a specific HCL coordinate by calling polarLUV(). To avoid having to fix up the color upon conversion to RGB hex() color codes, the max_chroma() function computes (approximately) the maximum chroma possible.

For illustration we show that for given luminance (here: L = 50) the maximum chroma varies substantially with hue:

max_chroma(h = seq(0, 360, by = 60), l = 50)
## [1] 137.96  59.99  69.06  39.81  65.45 119.54 137.96

Similarly, maximum chroma also varies substantially across luminance values for a given hue (here: H = 120, green):

max_chroma(h = 120, l = seq(0, 100, by = 20))
## [1]   0.00  28.04  55.35  82.79 110.28   0.00

In the plots below more combinations are visualized: In the left panel for maximum chroma across hues given luminance and in the right panel with increasing luminance given hue.

Additive mixing of two colors

In additive color models like RGB() or XYZ() it can be useful to combine colors by additive mixing. Below a fully saturated red and green are mixed, yielding a medium brownish yellow.

R <- RGB(1, 0, 0)
G <- RGB(0, 1, 0)
Y <- mixcolor(0.5, R, G)
Y
##        R   G B
## [1,] 0.5 0.5 0
par(mar = rep(0, 4))
swatchplot(c(hex(R), hex(Y), hex(G)))