| scale_color_viridis {viridis} | R Documentation |
Uses the viridis color scale.
scale_color_viridis(..., alpha = 1, begin = 0, end = 1, direction = 1, discrete = FALSE, option = "D") scale_colour_viridis(..., alpha = 1, begin = 0, end = 1, direction = 1, discrete = FALSE, option = "D") scale_fill_viridis(..., alpha = 1, begin = 0, end = 1, direction = 1, discrete = FALSE, option = "D")
... |
parameters to |
alpha |
pass through parameter to |
begin |
The (corrected) hue in [0,1] at which the viridis colormap begins. |
end |
The (corrected) hue in [0,1] at which the viridis colormap ends. |
direction |
Sets the order of colors in the scale. If 1, the default, colors are as output by viridis_pal. If -1, the order of colors is reversed. |
discrete |
generate a discrete palette? (default: |
option |
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). |
For discrete == FALSE (the default) all other arguments are as to
scale_fill_gradientn or scale_color_gradientn.
Otherwise the function will return a discrete_scale with the plot-computed
number of colors.
See viridis for more information on the color scale.
Noam Ross noam.ross@gmail.com / @noamross (continuous version), Bob Rudis bob@rud.is / @hrbrmstr (combined version)
library(ggplot2)
# ripped from the pages of ggplot2
p <- ggplot(mtcars, aes(wt, mpg))
p + geom_point(size=4, aes(colour = factor(cyl))) +
scale_color_viridis(discrete=TRUE) +
theme_bw()
# ripped from the pages of ggplot2
dsub <- subset(diamonds, x > 5 & x < 6 & y > 5 & y < 6)
dsub$diff <- with(dsub, sqrt(abs(x-y))* sign(x-y))
d <- ggplot(dsub, aes(x, y, colour=diff)) + geom_point()
d + scale_color_viridis() + theme_bw()
# from the main viridis example
dat <- data.frame(x = rnorm(10000), y = rnorm(10000))
ggplot(dat, aes(x = x, y = y)) +
geom_hex() + coord_fixed() +
scale_fill_viridis() + theme_bw()
library(ggplot2)
library(MASS)
library(gridExtra)
data("geyser", package="MASS")
ggplot(geyser, aes(x = duration, y = waiting)) +
xlim(0.5, 6) + ylim(40, 110) +
stat_density2d(aes(fill = ..level..), geom="polygon") +
theme_bw() +
theme(panel.grid=element_blank()) -> gg
grid.arrange(
gg + scale_fill_viridis(option="A") + labs(x="Virdis A", y=NULL),
gg + scale_fill_viridis(option="B") + labs(x="Virdis B", y=NULL),
gg + scale_fill_viridis(option="C") + labs(x="Virdis C", y=NULL),
gg + scale_fill_viridis(option="D") + labs(x="Virdis D", y=NULL),
ncol=2, nrow=2
)