I am not sure apeescape’s ggplot2 area plot with intensity colouring is really the best way of presenting the information, but it had me intrigued enough to replicate it using base R graphics.

The key technique is to draw a gradient line which R does not support natively so we have to roll our own code for that. Unfortunately, `lines(..., type="l")`

does not recycle the colour `col=`

argument, so we end up with rather more loops than I thought would be necessary.

(The answer is not to use `lines(..., type="h")`

which, confusingly, *does* recycle the colour `col=`

argument. This one had me for a while, but the `type=h`

lines always start from zero so you do not get the gradient feature.)

We also get a nice opportunity to use the under-appreciated `read.fwf`

function.

##!/usr/bin/Rscript ## nino.R - another version of http://bit.ly/9P9Gh1 ## Copyright © 2010 Allan Engelhardt (http://www.cybaea.net/) ## Get the data from the NOAA server nino <- read.fwf("http://www.cpc.noaa.gov/data/indices/wksst.for", widths=c(-1, 9, rep(c(-5, 4, 4), 4)), skip=4, col.names=c("Week", paste(rep(c("Nino12","Nino3","Nino34","Nino4"), rep(2, 4)), c("SST", "SSTA"), sep="."))) ## Make the date column something useful nino$Week <- as.Date(nino$Week, format="%d%b%Y") ## Make colour gradients ncol <- 50 grad.neg <- hsv(4/6, seq(0, 1, length.out=ncol), 1) # Blue gradient grad.pos <- hsv( 0, seq(0, 1, length.out=ncol), 1) # Red gradient ## Make plot plot(Nino34.SSTA ~ Week, data=nino, type="n", main="Nino34", xlab="Date", ylab="SSTA", axes=FALSE) do.call(function (...) rect(..., col="gray85", border=NA), as.list(par("usr")[c(1, 3, 2, 4)])) y <- nino$Nino34.SSTA # The values we will plot x <- nino$Week axis.Date(1, x=x, tck=1, col="white") axis(2, tck=1, col="white") box() idx <- integer(NROW(nino)) idx[y >= 0] <- 1 + round( y[y >= 0] * (ncol - 1) / max( y[y >= 0]), 0) idx[y < 0] <- 1 + round(-y[y < 0] * (ncol - 1) / max(-y[y < 0]), 0) draw.gradient <- function(x, ys, cols) { xs <- rep(x, 2) for (i in seq(1, length(ys)-1)) plot.xy(list(x=xs, y=c(ys[i], ys[i+1])), type="l", col=cols[i]) } for (i in 1:length(x)) { ys <- seq(0, y[i], length.out=idx[i]+1) cols <- (if (y[i] >=0) grad.pos else grad.neg) draw.gradient(x[i], ys, cols) }

The result is a decent gradient:

I deliberately omitted the scale legend on the right hand side following Allan’s First Law of Happy Graphics: Thou shall not present the same information twice.

For less dense information, you should increase the line width. That is left to the reader. (Hint: it is hard to get just right in base graphics, but `lwd <- ceiling(par("pin")[1] / dev.size("in")[1] * dev.size("px")[1] / length(x))`

could be a starting point for an approximation. We really need gradient-filled polygons in base R.)