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I have a few rasters I would like to plot using gplot in the rasterVis package. I just discovered gplot (which is fantastic and so much faster than doing data.frame(rasterToPoints(r))). However, I can't get a discrete image to show. Normally if r is a raster, I'd do:

rdf=data.frame(rasterToPoints(r))
rdf$cuts=cut(rdf$value,breaks=seq(0,max(rdf$value),length.out=5))
ggplot(rdf)+geom_raster(aes(x,y,fill=cuts))

But is there a way to avoid the call to rasterToPoints? It is very slow with large rasters. I did find I could do:

cuts=cut_interval(r@data@values,n=5)

but if you set the fill to cuts it plots the integer representation of the factors.

Here is some reproducible data:

x=seq(-107,-106,.1)
y=seq(33,34,.1)
coords=expand.grid(x,y)
rdf=data.frame(coords,depth=runif(nrow(coords),0,2)))
names(rdf)=c('x','y','value')
r=rasterFromXYZ(rdf)

Thanks

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Dominik
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1 Answers1

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gplot is a very simple wrapper around ggplot so don't expect too much from it. Instead, you can use part of its code to build your own solution. The main point here is to use sampleRegular to reduce the number of points to be displayed.

library(raster)
library(ggplot2)

x <- sampleRegular(r, size=5000, asRaster = TRUE)
dat <- as.data.frame(r, xy=TRUE)
dat$cuts <- cut(dat$value,
    breaks=seq(0, max(dat$value), length.out=5))
ggplot(aes(x = x, y = y), data = dat) +
    geom_raster(aes(x, y, fill=cuts))

However, if you are open to plot without ggplot2 you may find useful this other answer.

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Oscar Perpiñán
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  • Thanks for the tips. sampleRegular looks promising, didn't know about that.I'm also not bound to ggplot2 although my familiarity with it makes it attractive. – Dominik Nov 29 '13 at 21:13