| scale_colour_gradient {ggplot2} | R Documentation |
Default colours are generated with munsell and
mnsl(c("2.5PB 2/4", "2.5PB 7/10"). Generally, for continuous
colour scales you want to keep hue constant, but vary chroma and
luminance. The munsell package makes this easy to do using the
Munsell colour system.
scale_colour_gradient(..., low = "#132B43", high = "#56B1F7", space = "Lab", na.value = "grey50", guide = "colourbar") scale_fill_gradient(..., low = "#132B43", high = "#56B1F7", space = "Lab", na.value = "grey50", guide = "colourbar") scale_colour_continuous(..., low = "#132B43", high = "#56B1F7", space = "Lab", na.value = "grey50", guide = "colourbar") scale_fill_continuous(..., low = "#132B43", high = "#56B1F7", space = "Lab", na.value = "grey50", guide = "colourbar") scale_color_continuous(..., low = "#132B43", high = "#56B1F7", space = "Lab", na.value = "grey50", guide = "colourbar") scale_color_gradient(..., low = "#132B43", high = "#56B1F7", space = "Lab", na.value = "grey50", guide = "colourbar")
... |
Other arguments passed on to |
low |
colour for low end of gradient. |
high |
colour for high end of gradient. |
space |
colour space in which to calculate gradient. "Lab" usually best unless gradient goes through white. |
na.value |
Colour to use for missing values |
guide |
Type of legend. Use |
seq_gradient_pal for details on underlying
palette
Other colour scales: scale_color_brewer,
scale_color_distiller,
scale_colour_brewer,
scale_colour_distiller,
scale_fill_brewer,
scale_fill_distiller;
scale_color_discrete,
scale_color_hue,
scale_colour_discrete,
scale_colour_hue,
scale_fill_discrete,
scale_fill_hue;
scale_color_gradient2,
scale_colour_gradient2,
scale_fill_gradient2;
scale_color_gradientn,
scale_colour_gradientn,
scale_fill_gradientn;
scale_color_grey,
scale_colour_grey,
scale_fill_grey
# It's hard to see, but look for the bright yellow dot
# in the bottom right hand corner
dsub <- subset(diamonds, x > 5 & x < 6 & y > 5 & y < 6)
(d <- qplot(x, y, data=dsub, colour=z))
# That one point throws our entire scale off. We could
# remove it, or manually tweak the limits of the scale
# Tweak scale limits. Any points outside these limits will not be
# plotted, and will not affect the calculation of statistics, etc
d + scale_colour_gradient(limits=c(3, 10))
d + scale_colour_gradient(limits=c(3, 4))
# Setting the limits manually is also useful when producing
# multiple plots that need to be comparable
# Alternatively we could try transforming the scale:
d + scale_colour_gradient(trans = "log")
d + scale_colour_gradient(trans = "sqrt")
# Other more trivial manipulations, including changing the name
# of the scale and the colours.
d + scale_colour_gradient("Depth")
d + scale_colour_gradient(expression(Depth[mm]))
d + scale_colour_gradient(limits=c(3, 4), low="red")
d + scale_colour_gradient(limits=c(3, 4), low="red", high="white")
# Much slower
d + scale_colour_gradient(limits=c(3, 4), low="red", high="white", space="Lab")
d + scale_colour_gradient(limits=c(3, 4), space="Lab")
# scale_fill_continuous works similarly, but for fill colours
(h <- qplot(x - y, data=dsub, geom="histogram", binwidth=0.01, fill=..count..))
h + scale_fill_continuous(low="black", high="pink", limits=c(0,3100))
# Colour of missing values is controlled with na.value:
miss <- sample(c(NA, 1:5), nrow(mtcars), rep = TRUE)
qplot(mpg, wt, data = mtcars, colour = miss)
qplot(mpg, wt, data = mtcars, colour = miss) +
scale_colour_gradient(na.value = "black")