View source: R/scale_diverging.R
scale_colour_continuous_diverging | R Documentation |
Continuous ggplot2 color scales using the color palettes generated by diverging_hcl
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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
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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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