vsup_scale: Value suppressing color scale and palette

In jiho/chroma: Parse and Manipulate Colors, Create Perceptually Correct Color Palettes

Value suppressing color scale and palette

Description

Value suppressing color scale, whereby uncertain values are plotted with the same colour, to prevent the reader from trying to distinguish them.

Usage

vsup_scale(
  colors = viridis_colors(6),
  branching = 2,
  layers = 4,
  mode = "hcl",
  domain = c(0, 1),
  uncertainty_domain = c(0, 1),
  reverse = FALSE,
  na.value = "red",
  extrapolate = FALSE
)

vsup_map(x, u, ...)

vsup_palette(u, ...)

vsup_colors(n, u, ...)

Arguments

colors	vector of colors specified as hex strings or named R colors. By default, those colors will be evenly distributed along the scale and new colors will be interpolated between them.
domain	vector of two values between which the scale is computed.
reverse	whether to reverse the order of colors along the scale.
na.value	value to return for missing values in the input. Can be either a color, NULL in which case a tentitatively appropriate color will be chosen automatically, or NA.
extrapolate	when FALSE, the default, return NA for input values that are out of the domain; when TRUE return the color corresponding to the extreme of the domain instead.
x	a vector whose values will be coerced to numbers and mapped to colors.
...	passed to vsup_scale from other vsup_* functions; passed to ggplot2::continuous_scale or ggplot2::discrete_scale from the scale_* functions, as appropriate. NB: in all situations, passing domain is meaningless and yields an error.
n	number of colors to extract from the color palette.

Value

*_scale returns a function. This function takes a single argument (x: a numeric vector), maps its values to colors, and returns thee colors as hex codes.

*_map is a shortcut for *_scale(domain=range(x))(x): it creates a scale that spans the range of values in argument x, maps the content of x on that scale, and returns the colors.

*_palette returns a function. This function takes an integer (n) as argument, picks n colors evenly spaced along the scale, and returns them as hex codes.

*_colors is a shortcut for *_palette()(n) and directly returns n evenly spaced colors. It is equivalent to built-in functions such as heat.colors, topo.colors, etc.

scale_* return a ggplot2 scale, either discrete (similar to scale_color_discrete) or continuous (similar to scale_color_continuous).

See Also

The hcl function, on which this one is based.

Other HCL-based scales: chroma_scale(), hue_scale(), light_scale()

Other color scales and palettes: brewer_scale(), chroma_scale(), cubehelix_scale(), etopo_scale(), hue_scale(), inferno_scale(), interp_scale(), light_scale(), magma_scale(), plasma_scale(), turbo_scale(), viridis_scale(), wikitopo_scale()

Examples

# display a range of values with increasing uncertainty
show_col(
  vsup_scale()(1:6/6, 0),
  vsup_scale()(1:6/6, 0.5),
  vsup_scale()(1:6/6, 1)
)

# starting from colours with different hues but similar chroma and luminance
# gives more continuous looking results; for example:
cols <- hue_colors(2, c=0.8, l=0.5)
show_col(cols)
# display a grid of colours corresponding to various values and uncertainties
g <- expand.grid(x=1:10, u=1:10)
plot(x ~ u, data=g, col=vsup_map(g$x, g$u, cols), pch=19, asp=1, cex=6)
# increase the number of steps (i.e. layers) in the uncertainty mapping,
# to get a smoother visual aspect
plot(x ~ u, data=g, col=vsup_map(g$x, g$u, colors=cols, layers=10, mode="hcl"), pch=19, asp=1, cex=6)
# and vary to modes to check their effect
plot(x ~ u, data=g, col=vsup_map(g$x, g$u, colors=cols, layers=10, mode="hc" ), pch=19, asp=1, cex=6)
plot(x ~ u, data=g, col=vsup_map(g$x, g$u, colors=cols, layers=10, mode="hl" ), pch=19, asp=1, cex=6)

vsup_palette(colors=cols)(10, u=0)
show_col(
  vsup_colors(10, 0   , layers=10, mode="hc"),
  vsup_colors(10, 0.25, layers=10, mode="hc"),
  vsup_colors(10, 0.5 , layers=10, mode="hc"),
  vsup_colors(10, 0.75, layers=10, mode="hc"),
  vsup_colors(10, 1   , layers=10, mode="hc")
)

jiho/chroma documentation built on Feb. 5, 2025, 10:32 p.m.