6
votes

I have created a image plot for this data:

sample
         p         p.1         p.2         p.3         p.4
  p    1.0000000  0.24077171 -0.66666667 -0.49009803  0.61237244
  p.1  0.2407717  1.00000000  0.09028939 -0.83444087  0.14744196
  p.2 -0.6666667  0.09028939  1.00000000  0.21004201  0.10206207
  p.3 -0.4900980 -0.83444087  0.21004201  1.00000000 -0.08574929
  p.4  0.6123724  0.14744196  0.10206207 -0.08574929  1.00000000

Using this code:

  image.plot(sample,col=redblue(191), zlim=c(-1,1))

I get this image:

Instead of 0.0 0.2 0.4.. on x and y axes, I want p p.1 p.2... How do I get that that? Thank you for your time and consideration?

My heatmap looks like this:

enter image description here

its not symmetric. Can you please fix this? I am using this code:

shades=c(seq(-1,-0.5,length=64), seq(-0.5,0.5, length=64), seq(0.5,1,length=64))
heatmap.2(sample, dendrogram='none', symm=TRUE, Rowv=FALSE, Colv=FALSE, key=TRUE, cexCol=0.7, cexRow=1,scale="row", keysize=1, col=redblue(191), breaks=shades)

1
I sort of found a way to do it, but it's not very straightforward: image.plot(sample,col=rainbow(25), zlim=c(-1,1), axes=F); title(main="Graph"); axis(1, at=seq(0,0.8,0.2), labels=rownames(sample)); axis(2) For some reason, I wasn't able to directly make the x-axis labels. But after I used title(), I was allowed to create the x-axis labels. Someone might know how to do it more elegantly. - Alex

1 Answers

10
votes

Here is a better-ish solution:

 par(mar=c(5,4.5,4,7))
 image(sample, col=rainbow(25), axes=F)  #redblue() doesn't work on my computer.
 axis(2)
 axis(1, at=seq(0,0.8,0.2), labels=rownames(sample))
 image.plot(sample, legend.only=T)

enter image description here

EDIT: Does the plot below look like what you are looking for?

 sample = cor(matrix(rnorm(400), nrow=20))
 image(cor(matrix(rnorm(400), nrow=20)), axes=F)
 mtext(text=c(paste("country",1:21)), side=2, line=0.3, at=seq(0,1,0.05), las=1, cex=0.8)
 mtext(text=c(paste("country",1:21)), side=1, line=0.3, at=seq(0,1,0.05), las=2, cex=0.8)
 image.plot(sample, legend.only=T)

enter image description here