How can I produce plots like this?

Question

I have come across this kind of a plot that performs hierarchical clustering over a given set of timeseries data. Can someone tell me how to draw such plots?

I am open to implementations in R or Javascript, especially using d3.js.

Answer 1

You can always create the plot by hand: with base graphics, you the fig parameter allows you to add plots inside another plot.

# Sample data
n <- 100
k <- 6
d <- matrix(rnorm(k*n),nc=k)
d[,2] <- d[,1]  # To help check the results
colnames(d) <- LETTERS[1:k]
x <- apply(d,2,cumsum)
r <- hclust(dist(t(d)))
# Plot
op <- par(mar=c(0,0,0,0),oma=c(0,2,0,0))
plot(NA,ylim=c(.5,k+.5), xlim=c(0,4),axes=FALSE)
# Dendrogram. See ?hclust for details.
xc <- yc <- rep(NA,k)
o <- 1:k
o[r$order] <- 1:k
for(i in 1:(k-1)) {
  a <- r$merge[i,1]
  x1 <- if( a<0 ) o[-a] else xc[a]
  y1 <- if( a<0 ) 0 else yc[a]
  b <- r$merge[i,2]
  x2 <- if( b<0 ) o[-b] else xc[b]
  y2 <- if( b<0 ) 0 else yc[b]
  lines( 
    3+c(y1,i,i,y2)/k,
    c(x1,x1,x2,x2),
    lwd=k-i
  )
  xc[i] <- (x1+x2)/2
  yc[i] <- i
}
# Time series
axis(2,1:k,colnames(d)[r$order],las=1)
u <- par()$usr
for(i in 1:k) {
  f <- c(0,3,i-.5,i+.5)
  f <- c( 
    (f[1]-u[1])/(u[2]-u[1]), 
    (f[2]-u[1])/(u[2]-u[1]), 
    (f[3]-u[3])/(u[4]-u[3]), 
    (f[4]-u[3])/(u[4]-u[3])
  )
  par(new=TRUE,fig=f)
  plot(x[,r$order[i]],axes=FALSE,xlab="",ylab="",main="",type="l",col="navy",lwd=2)
  box()
}
par(op)

(After writing this, I realize that it is probably easier to do with layout...)