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...)