| brewer_scale | R Documentation |
ColorBrewer scales and palettes
brewer_scale(
name = "Blues",
model = "lab",
interp = "linear",
domain = c(0, 1),
reverse = FALSE
)
brewer_map(x, ...)
brewer_palette(name = "Blues", ...)
brewer_colors(n, name = "Blues", ...)
name |
name of a ColorBrewer palette. See |
model |
string defining the color model in which to perform the interpolation; valid models are |
interp |
string defining the type of interpolation to perform; either |
domain |
vector of two values between which the scale is computed. |
reverse |
whether to reverse the order of colors along the scale. |
x |
a vector whose values will be coerced to numbers and mapped to colors. |
... |
passed to |
n |
number of colors to extract from the color palette. |
*_scale returns a function. This function takes a single argument (x: a numeric vector), maps its values to colors, and returns thee colors as hex codes.
*_map is a shortcut for *_scale(domain=range(x))(x): it creates a scale that spans the range of values in argument x, maps the content of x on that scale, and returns the colors.
*_palette returns a function. This function takes an integer (n) as argument, picks n colors evenly spaced along the scale, and returns them as hex codes.
*_colors is a shortcut for *_palette()(n) and directly returns n evenly spaced colors. It is equivalent to built-in functions such as heat.colors, topo.colors, etc.
scale_* return a ggplot2 scale, either discrete (similar to scale_color_discrete) or continuous (similar to scale_color_continuous).
brewer for the colors in the palettes and brewer_info for a list of palettes and their characteristics.
Other color scales and palettes:
chroma_scale(),
cubehelix_scale(),
etopo_scale(),
hue_scale(),
inferno_scale(),
interp_scale(),
light_scale(),
magma_scale(),
plasma_scale(),
turbo_scale(),
viridis_scale(),
vsup_scale(),
wikitopo_scale()
# Define a scale function
ygb <- brewer_scale(name="YlGnBu")
ygb(c(0, 0.2, 0.6, 1))
# Define a palette function
bgy_pal <- brewer_palette(name="YlGnBu", reverse=TRUE)
bgy_pal(10)
show_col(bgy_pal(100))
# Show 7 colors from each palette
show_col(lapply(brewer_info$name, function(x) {brewer_colors(n=7, name=x)}))
# Warn about the potentially inappropriate use of many colors
brewer_colors(n=15, name="Blues")
brewer_colors(n=15, name="Pastel1")
brewer_palette(name="Pastel1")(15)
# Some warnings can be avoided by explicitly requiring a palette
# which, by definition, is taken from a *continuous* scale
brewer_palette(name="Blues")(15)
brewer_palette(name="Pastel1")(15)
# Sequential ColorBrewer palettes are good for continuous variables
# such as the elevation of the Maunga Whau volcano
image(maunga, col=brewer_colors(100, name="YlOrBr", reverse=TRUE))
contour(maunga, col=alpha("white", 0.5), add=TRUE)
persp(maunga, theta=50, phi=25, scale=FALSE, expand=2,
border=alpha("black", 0.4),
col=brewer_map(persp_facets(maunga$z), "YlOrBr", reverse=TRUE))
## Not run:
library("rgl")
persp3d(maunga, aspect=c(1,0.7,0.2), axes=FALSE, box=FALSE,
col=brewer_map(maunga$z, "YlOrBr", reverse=TRUE))
## End(Not run)
# Qualitative palettes are appropriate for discrete variables
attach(iris)
plot(Petal.Length, Sepal.Length, pch=19, col=brewer_map(Species, "Set2"))
legend(1, 8, legend=levels(Species), pch=19,
col=brewer_colors(n=nlevels(Species), name="Set2"))
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