用户定义的R和ggpairs中的调色板 [英] User defined colour palette in R and ggpairs
问题描述
我试图在R中的 GGally
库中使用另一个调色板作为来自 ggpairs
的散点图。请参阅以获取更多信息。
I am trying to use another color palette for the scatter plots from ggpairs
from the GGally
library in R. See similar question here.
library(ggplot2)
library(GGally)
Works
ggplot(iris, aes(x=Sepal.Width, colour=Species)) + stat_ecdf() + scale_color_brewer(palette="Spectral")
Also works
ggplot <- function(...) ggplot2::ggplot(...) + scale_color_brewer(palette="Spectral")
ggplot(iris, aes(x=Sepal.Width, colour=Species)) + stat_ecdf()
Does not work
ggplot <- function(...) ggplot2::ggplot(...) + scale_color_brewer(palette="Spectral")
ggpairs(iris,
columns=, c("Sepal.Length", "Sepal.Width", "Petal.Length", "Petal.Width"),
colour='Species',
lower=list(continuous='points'),
axisLabels='none',
upper=list(continuous='blank')
)
but adding
putPlot(p, ggplot(iris, aes(x=Sepal.Length, colour=Species)) + stat_ecdf(), 1,1)
adds a plot in the right colors.
Workaround
I can change the plots afterwards with getPlot, but that's not pretty..
subplot <- getPlot(a, 2, 1) # retrieve the top left chart
subplotNew <- subplot + scale_color_brewer(palette="Spectral")
a <- putPlot(a, subplotNew, 2, 1)
How can I change the color scheme for the scatter plots in ggpairs? More specifically, I'd like to manually define the colors like so
scale_colour_manual(values=c("#FF0000","#000000", "#0000FF","#00FF00"))
Thanks!
Here is a hack that works:
ggplot <- function(...) ggplot2::ggplot(...) + scale_color_brewer(palette="Spectral")
unlockBinding("ggplot",parent.env(asNamespace("GGally")))
assign("ggplot",ggplot,parent.env(asNamespace("GGally")))
When you assign a new value to the ggplot
function, it is in the global environment. Now, GGally
imports everything including ggplot
when it loads (it didn't have to be that way). At that point, changing the ggplot
function in your global environment has no effect, because imports from GGally
have precedence. Instead, you need to update the ggplot
function on the GGally:imports
. There is only one problem: once a package is loaded, its bindings are locked. But we can unlock them (I am guessing this is frowned upon, hence labeling the solution a hack).
See Josh O'Brien's answer under Replace definition of built-in function in R? for more info.
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