The ggplot
is elegant and fast and pretty, as usual. But if you want to use base graphics (image
, contour
, persp
) and display your actual frequencies (instead of the smoothing 2D kernel), you have to first obtain the binnings yourself and create a matrix of frequencies. Here's some code (not necessarily elegant, but pretty robust) that does 2D binning and generates plots somewhat similar to the ones above:
require(mvtnorm)
xy <- rmvnorm(1000,c(5,10),sigma=rbind(c(3,-2),c(-2,3)))
nbins <- 20
x.bin <- seq(floor(min(xy[,1])), ceiling(max(xy[,1])), length=nbins)
y.bin <- seq(floor(min(xy[,2])), ceiling(max(xy[,2])), length=nbins)
freq <- as.data.frame(table(findInterval(xy[,1], x.bin),findInterval(xy[,2], y.bin)))
freq[,1] <- as.numeric(freq[,1])
freq[,2] <- as.numeric(freq[,2])
freq2D <- diag(nbins)*0
freq2D[cbind(freq[,1], freq[,2])] <- freq[,3]
par(mfrow=c(1,2))
image(x.bin, y.bin, freq2D, col=topo.colors(max(freq2D)))
contour(x.bin, y.bin, freq2D, add=TRUE, col=rgb(1,1,1,.7))
palette(rainbow(max(freq2D)))
cols <- (freq2D[-1,-1] + freq2D[-1,-(nbins-1)] + freq2D[-(nbins-1),-(nbins-1)] + freq2D[-(nbins-1),-1])/4
persp(freq2D, col=cols)
For a really fun time, try making an interactive, zoomable, 3D surface:
require(rgl)
surface3d(x.bin,y.bin,freq2D/10, col="red")