Matplotlib 'viridis' color map
This function creates a vector of
n equally spaced colors along the
Matplolib 'viridis' color map created by Stéfan van der Walt
and Nathaniel Smith. This color map is
designed in such a way that it will analytically be perfectly perceptually-uniform,
both in regular form and also when converted to black-and-white. It is also
designed to be perceived by readers with the most common form of color blindness.
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The number of colors (≥ 1) to be in the palette.
The alpha transparency, a number in [0,1], see argument alpha in
The (corrected) hue in [0,1] at which the viridis colormap begins.
The (corrected) hue in [0,1] at which the viridis colormap ends.
A character string indicating the colormap option to use. Four options are available: "magma" (or "A"), "inferno" (or "B"), "plasma" (or "C"), and "viridis" (or "D", the default option).
Here are the color scales:
inferno() are convenience
functions for the other colormap options, which are useful the scale must
be passed as a function name.
Semi-transparent colors (0 < alpha < 1) are supported only on some
viridis returns a character vector,
cv, of color hex
codes. This can be used either to create a user-defined color palette for
subsequent graphics by
col = specification in
graphics functions or in
viridisMap returns a
n lines data frame containing the
R), green (
G), blue (
B) and alpha (
n equally spaced colors along the 'viridis' color map.
n = 256 by default, which corresponds to the data from the original
'viridis' color map in Matplotlib.
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library(ggplot2) library(hexbin) dat <- data.frame(x = rnorm(10000), y = rnorm(10000)) ggplot(dat, aes(x = x, y = y)) + geom_hex() + coord_fixed() + scale_fill_gradientn(colours = viridis(256, option = "D")) # using code from RColorBrewer to demo the palette n = 200 image( 1:n, 1, as.matrix(1:n), col = viridis(n, option = "D"), xlab = "viridis n", ylab = "", xaxt = "n", yaxt = "n", bty = "n" )
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