Evenly spaced colours for discrete data

Maps each level to an evenly spaced hue on the colour wheel. It does not generate colour-blind safe palettes.

Usage

scale_colour_hue(
  name = waiver(),
  ...,
  h = c(0, 360) + 15,
  c = 100,
  l = 65,
  h.start = 0,
  direction = 1,
  na.value = "grey50",
  aesthetics = "colour"
)

scale_fill_hue(
  name = waiver(),
  ...,
  h = c(0, 360) + 15,
  c = 100,
  l = 65,
  h.start = 0,
  direction = 1,
  na.value = "grey50",
  aesthetics = "fill"
)

Arguments

name

The name of the scale. Used as the axis or legend title. If waiver(), the default, the name of the scale is taken from the first mapping used for that aesthetic. If NULL, the legend title will be omitted.

...

Arguments passed on to discrete_scale

breaks

One of:

• NULL for no breaks

• waiver() for the default breaks (the scale limits)

• A character vector of breaks

• A function that takes the limits as input and returns breaks as output. Also accepts rlang lambda function notation.

limits

One of:

• NULL to use the default scale values

• A character vector that defines possible values of the scale and their order

• A function that accepts the existing (automatic) values and returns new ones. Also accepts rlang lambda function notation.

drop

Should unused factor levels be omitted from the scale? The default, TRUE, uses the levels that appear in the data; FALSE includes the levels in the factor. Please note that to display every level in a legend, the layer should use show.legend = TRUE.

na.translate

Unlike continuous scales, discrete scales can easily show missing values, and do so by default. If you want to remove missing values from a discrete scale, specify na.translate = FALSE.

minor_breaks

One of:

• NULL for no minor breaks

• waiver() for the default breaks (none for discrete, one minor break between each major break for continuous)

• A numeric vector of positions

• A function that given the limits returns a vector of minor breaks. Also accepts rlang lambda function notation. When the function has two arguments, it will be given the limits and major break positions.

labels

One of the options below. Please note that when labels is a vector, it is highly recommended to also set the breaks argument as a vector to protect against unintended mismatches.

• NULL for no labels

• waiver() for the default labels computed by the transformation object

• A character vector giving labels (must be same length as breaks)

• An expression vector (must be the same length as breaks). See ?plotmath for details.

• A function that takes the breaks as input and returns labels as output. Also accepts rlang lambda function notation.

guide

A function used to create a guide or its name. See guides() for more information.

call

The call used to construct the scale for reporting messages.

super

The super class to use for the constructed scale

h

range of hues to use, in [0, 360]

c

chroma (intensity of colour), maximum value varies depending on combination of hue and luminance.

l

luminance (lightness), in [0, 100]

h.start

hue to start at

direction

direction to travel around the colour wheel, 1 = clockwise, -1 = counter-clockwise

na.value

Colour to use for missing values

aesthetics

Character string or vector of character strings listing the name(s) of the aesthetic(s) that this scale works with. This can be useful, for example, to apply colour settings to the colour and fill aesthetics at the same time, via aesthetics = c("colour", "fill").

See also

The documentation on colour aesthetics.

The hue and grey scales section of the online ggplot2 book.

Other colour scales: scale_alpha(), scale_colour_brewer(), scale_colour_continuous(), scale_colour_gradient(), scale_colour_grey(), scale_colour_identity(), scale_colour_manual(), scale_colour_steps(), scale_colour_viridis_d()

Examples

# \donttest{
set.seed(596)
dsamp <- diamonds[sample(nrow(diamonds), 1000), ]
(d <- ggplot(dsamp, aes(carat, price)) + geom_point(aes(colour = clarity)))


# Change scale label
d + scale_colour_hue()

d + scale_colour_hue("clarity")

d + scale_colour_hue(expression(clarity[beta]))


# Adjust luminosity and chroma
d + scale_colour_hue(l = 40, c = 30)

d + scale_colour_hue(l = 70, c = 30)

d + scale_colour_hue(l = 70, c = 150)

d + scale_colour_hue(l = 80, c = 150)


# Change range of hues used
d + scale_colour_hue(h = c(0, 90))

d + scale_colour_hue(h = c(90, 180))

d + scale_colour_hue(h = c(180, 270))

d + scale_colour_hue(h = c(270, 360))


# Vary opacity
# (only works with pdf, quartz and cairo devices)
d <- ggplot(dsamp, aes(carat, price, colour = clarity))
d + geom_point(alpha = 0.9)

d + geom_point(alpha = 0.5)

d + geom_point(alpha = 0.2)


# Colour of missing values is controlled with na.value:
miss <- factor(sample(c(NA, 1:5), nrow(mtcars), replace = TRUE))
ggplot(mtcars, aes(mpg, wt)) +
  geom_point(aes(colour = miss))

ggplot(mtcars, aes(mpg, wt)) +
  geom_point(aes(colour = miss)) +
  scale_colour_hue(na.value = "black")

# }