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Generate palettes of distinct colours through k means clustering of LAB colour space.

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hues

Travis-CI Build Status CRAN

This package generates and plot palettes of optimally distinct colours in perceptually uniform colour space, based on iwanthue. This is done through k-means clustering of CIE Lab colour space, according to user-selected constraints on hue, chroma, and lightness.

iwanthue palettes can be added directly onto ggplot2 objects via the functions scale_colour_iwanthue() and scale_fill_iwanthue().

Installation

The current CRAN version of hues can be installed with:

install.packages('hues')

The development version of hues can be installed using install_github from the devtools package:

# install.packages('devtools') # uncomment if devtools isn't already installed
devtools::install_github('johnbaums/hues')

Examples

The examples below show palettes corresponding to some presets given at the iwanthue website.

library(hues)
iwanthue(5, plot=TRUE)

iwanthue(5, 0, 240, 0, 24, 0, 100, plot=TRUE)    # shades

iwanthue(5, 0, 360, 0, 54, 67, 100, plot=TRUE)   # pastel

iwanthue(5, 0, 360, 54, 180, 27, 67, plot=TRUE)  # pimp

iwanthue(5, 0, 360, 36, 180, 13, 73, plot=TRUE)  # intense

iwanthue(3, 0, 300, 60, 180, 73, 100, plot=TRUE) # fluoro

iwanthue(3, 220, 260, 12, 150, 0, 53, plot=TRUE) # blue ocean

ggplot2 integration

library(ggplot2)
ggplot(iris, aes(x=Petal.Width, y=Petal.Length)) +
  geom_point(aes(color=Species), size=3) + 
  scale_colour_iwanthue()

ggplot(iris, aes(x=Petal.Width, y=Petal.Length)) +
  geom_point(aes(color=Species), size=3) + 
  scale_colour_iwanthue(hmax = 90)

ggplot(iris, aes(x=Petal.Width, y=Petal.Length)) +
  geom_point(aes(color=Species), size=3) + 
  scale_colour_iwanthue(hmin=0, hmax=300, cmin=60, cmax=180, lmin=73, lmax=100)

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Generate palettes of distinct colours through k means clustering of LAB colour space.

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