Continuous ggplot2 color scales using the color palettes generated by diverging_hcl.

scale_colour_continuous_diverging(
  palette = NULL,
  c1 = NULL,
  cmax = NULL,
  l1 = NULL,
  l2 = NULL,
  h1 = NULL,
  h2 = NULL,
  p1 = NULL,
  p2 = NULL,
  rev = FALSE,
  mid = 0,
  na.value = "grey50",
  guide = "colourbar",
  n_interp = 11,
  aesthetics = "colour",
  ...
)

scale_color_continuous_diverging(
  palette = NULL,
  c1 = NULL,
  cmax = NULL,
  l1 = NULL,
  l2 = NULL,
  h1 = NULL,
  h2 = NULL,
  p1 = NULL,
  p2 = NULL,
  rev = FALSE,
  mid = 0,
  na.value = "grey50",
  guide = "colourbar",
  n_interp = 11,
  aesthetics = "colour",
  ...
)

scale_fill_continuous_diverging(..., aesthetics = "fill")

Arguments

palette

The name of the palette to be used. Run hcl_palettes(type = "diverging") for available options.

c1

Chroma value at the scale endpoints.

cmax

Maximum chroma value.

l1

Luminance value at the scale endpoints.

l2

Luminance value at the scale midpoint.

h1

Hue value at the first endpoint.

h2

Hue value at the second endpoint.

p1

Control parameter determining how chroma should vary (1 = linear, 2 = quadratic, etc.).

p2

Control parameter determining how luminance should vary (1 = linear, 2 = quadratic, etc.).

rev

If TRUE, reverses the order of the colors in the color scale.

mid

Data value that should be mapped to the mid-point of the diverging color scale.

na.value

Color to be used for missing data points.

guide

Type of legend. Use "colourbar" for continuous color bar.

n_interp

Number of discrete colors that should be used to interpolate the continuous color scale. It is important to use an odd number to capture the color at the midpoint.

aesthetics

The ggplot2 aesthetics to which this scale should be applied.

...

common continuous scale parameters: `name`, `breaks`, `labels`, and `limits`. See continuous_scale for more details.

Details

If both a valid palette name and palette parameters are provided then the provided palette parameters overwrite the parameters in the named palette. This enables easy customization of named palettes.

Examples

# adapted from stackoverflow: https://stackoverflow.com/a/20127706/4975218 library("ggplot2") # generate dataset and base plot set.seed(100) df <- data.frame(country = LETTERS, V = runif(26, -40, 40)) df$country = factor(LETTERS, LETTERS[order(df$V)]) # reorder factors gg <- ggplot(df, aes(x = country, y = V, fill = V)) + geom_bar(stat = "identity") + labs(y = "Under/over valuation in %", x = "Country") + coord_flip() + theme_minimal() # plot with default diverging scale gg + scale_fill_continuous_diverging()
# plot with alternative scale gg + scale_fill_continuous_diverging(palette = "Purple-Green")
# plot with modified alternative scale gg + scale_fill_continuous_diverging(palette = "Blue-Red 3", l1 = 30, l2 = 100, p1 = .9, p2 = 1.2)