Today I wanted to compare the histograms from two data sets, but it’s hard to see the differences when the plots overlap. Here’s an example of the problem:

[sourcecode]

a = rnorm(10000,5)

b = rnorm(10000,3)

hist(a,xlim=c(0,10))

hist(b,col="gray20",add=T)

[/sourcecode]

Output:

I want to know what’s going on behind all that solid grey!

So I coded up a little function to add pseudo-transparency to pairs of histograms:

[sourcecode]

plotOverlappingHist <- function(a, b, colors=c("white","gray20","gray50"),

breaks=NULL, xlim=NULL, ylim=NULL){

ahist=NULL

bhist=NULL

if(!(is.null(breaks))){

ahist=hist(a,breaks=breaks,plot=F)

bhist=hist(b,breaks=breaks,plot=F)

} else {

ahist=hist(a,plot=F)

bhist=hist(b,plot=F)

dist = ahist$breaks[2]-ahist$breaks[1]

breaks = seq(min(ahist$breaks,bhist$breaks),max(ahist$breaks,bhist$breaks),dist)

ahist=hist(a,breaks=breaks,plot=F)

bhist=hist(b,breaks=breaks,plot=F)

}

if(is.null(xlim)){

xlim = c(min(ahist$breaks,bhist$breaks),max(ahist$breaks,bhist$breaks))

}

if(is.null(ylim)){

ylim = c(0,max(ahist$counts,bhist$counts))

}

overlap = ahist

for(i in 1:length(overlap$counts)){

if(ahist$counts[i] > 0 & bhist$counts[i] > 0){

overlap$counts[i] = min(ahist$counts[i],bhist$counts[i])

} else {

overlap$counts[i] = 0

}

}

plot(ahist, xlim=xlim, ylim=ylim, col=colors[1])

plot(bhist, xlim=xlim, ylim=ylim, col=colors[2], add=T)

plot(overlap, xlim=xlim, ylim=ylim, col=colors[3], add=T)

}

[/sourcecode]

The results are much easier to interpret:

[sourcecode]

a = rnorm(10000,5)

b = rnorm(10000,3)

plotOverlappingHist(a,b)

[/sourcecode]

I’m sure this could be improved upon and generalized to multiple histograms, but this solves my problem, so I’m calling it quits for now. Let me know if you make improvements or find it useful.