Abstract
The R package colorspace provides a flexible toolbox for selecting individual colors or color palettes, manipulating these colors, and employing them in statistical graphics and data visualizations. In particular, the package provides a broad range of color palettes based on the HCL (hue-chroma-luminance) color space. The three HCL dimensions have been shown to match those of the human visual system very well, thus facilitating intuitive selection of color palettes through trajectories in this space. Using the HCL color model, general strategies for three types of palettes are implemented: (1) Qualitative for coding categorical information, i.e., where no particular ordering of categories is available. (2) Sequential for coding ordered/numeric information, i.e., going from high to low (or vice versa). (3) Diverging for coding ordered/numeric information around a central neutral value, i.e., where colors diverge from neutral to two extremes. To aid selection and application of these palettes, the package also contains scales for use with ggplot2, shiny and tcltk apps for interactive exploration, visualizations of palette properties, accompanying manipulation utilities (like desaturation and lighten/darken), and emulation of color vision deficiencies. The shiny apps are also hosted online at http://hclwizard.org/.
Highlights
Color is an integral element of many statistical graphics and data visualizations
As the properties of a palette in terms of the perceptual dimensions hue, chroma, and luminance are not always clear from looking just at color swatches or graphics based on these palettes, the specplot() function provides an explicit display for the coordinates of the HCL trajectory associated with a palette
This paper provides an overview of the broad capabilities of the colorspace package for selecting individual colors or color palettes, manipulating these colors, and employing them in various kinds of visualizations
Summary
Color is an integral element of many statistical graphics and data visualizations. colors should be carefully chosen to support all viewers in accessing the information displayed colorspace: Manipulating and Assessing Colors and Palettes. The colorspace package (Ihaka et al 2020) adopts a somewhat different approach that gives the user direct access to the construction principles underlying its palettes These are based on simple trajectories in the perceptually-based HCL (hue-chroma-luminance) color space (Wikipedia 2020e) whose axes match those of the human visual system very well: Hue (type of color, dominant wavelength), chroma (colorfulness), luminance (brightness), see Figure 1. Utilizing this color model the colorspace package can derive general and adaptable strategies for color palettes; manipulate individual colors and color palettes; and assess and visualize the properties of color palettes (beyond simple color swatches).
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