| hcl {grDevices} | R Documentation |
Create a vector of colors from vectors specifying hue, chroma and luminance.
hcl(h = 0, c = 35, l = 85, alpha, fixup = TRUE)
h |
The hue of the color specified as an angle in the range [0,360]. 0 yields red, 120 yields green 240 yields blue, etc. |
c |
The chroma of the color. The upper bound for chroma depends on hue and luminance. |
l |
A value in the range [0,100] giving the luminance of the colour. For a given combination of hue and chroma, only a subset of this range is possible. |
alpha |
numeric vector of values in the range |
fixup |
a logical value which indicates whether the resulting
RGB values should be corrected to ensure that a real color results.
if |
This function corresponds to polar coordinates in the CIE-LUV
color space. Steps of equal size in this space correspond to
approximately equal perceptual changes in color. Thus, hcl
can be thought of as a perceptually based version of hsv.
The function is primarily intended as a way of computing colors for filling areas in plots where area corresponds to a numerical value (pie charts, bar charts, mosaic plots, histograms, etc). Choosing colors which have equal chroma and luminance provides a way of minimising the irradiation illusion which would otherwise produce a misleading impression of how large the areas are.
The default values of chroma and luminance make it possible to generate a full range of hues and have a relatively pleasant pastel appearance.
The RGB values produced by this function correspond to the sRGB color space used on most PC computer displays. There are other packages which provide more general color space facilities.
Semi-transparent colors (0 < alpha < 1) are supported only on
some devices: see rgb.
A vector of character strings which can be used as color specifications by R graphics functions.
At present there is no guarantee that the colours rendered by R graphics devices will correspond to their sRGB description. It is planned to adopt sRGB as the standard R color description in future.
Ross Ihaka
Ihaka, R. (2003). Colour for Presentation Graphics, Proceedings of the 3rd International Workshop on Distributed Statistical Computing (DSC 2003), March 20-22, 2003, Technische Universität Wien, Vienna, Austria. http://www.ci.tuwien.ac.at/Conferences/DSC-2003.
require(graphics)
# The Foley and Van Dam PhD Data.
csd <- matrix(c( 4,2,4,6, 4,3,1,4, 4,7,7,1,
0,7,3,2, 4,5,3,2, 5,4,2,2,
3,1,3,0, 4,4,6,7, 1,10,8,7,
1,5,3,2, 1,5,2,1, 4,1,4,3,
0,3,0,6, 2,1,5,5), nrow=4)
csphd <- function(colors)
barplot(csd, col = colors, ylim = c(0,30),
names = 72:85, xlab = "Year", ylab = "Students",
legend = c("Winter", "Spring", "Summer", "Fall"),
main = "Computer Science PhD Graduates", las = 1)
# The Original (Metaphorical) Colors (Ouch!)
csphd(c("blue", "green", "yellow", "orange"))
# A Color Tetrad (Maximal Color Differences)
csphd(hcl(h = c(30, 120, 210, 300)))
# Same, but lighter and less colorful
# Turn off automatic correction to make sure
# that we have defined real colors.
csphd(hcl(h = c(30, 120, 210, 300),
c = 20, l = 90, fixup = FALSE))
# Analogous Colors
# Good for those with red/green color confusion
csphd(hcl(h = seq(60, 240, by = 60)))
# Metaphorical Colors
csphd(hcl(h = seq(210, 60, length = 4)))
# Cool Colors
csphd(hcl(h = seq(120, 0, length = 4) + 150))
# Warm Colors
csphd(hcl(h = seq(120, 0, length = 4) - 30))
# Single Color
hist(stats::rnorm(1000), col = hcl(240))