View source: R/scale_diverging.R
scale_colour_continuous_diverging | R Documentation |
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,
alpha = 1,
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,
alpha = 1,
rev = FALSE,
mid = 0,
na.value = "grey50",
guide = "colourbar",
n_interp = 11,
aesthetics = "colour",
...
)
scale_fill_continuous_diverging(..., aesthetics = "fill")
palette |
The name of the palette to be used. Run |
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.). |
alpha |
Numeric vector of values in the range |
rev |
If |
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 |
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
|
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.
# 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)
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