R legend for color density scatterplot produced using smoothScatter

Question

I am producing a color density scatterplot in R using the smoothScatter() function.

Example:

## A largish data set
n <- 10000
x1  <- matrix(rnorm(n), ncol = 2)
x2  <- matrix(rnorm(n, mean = 3, sd = 1.5), ncol = 2)
x   <- rbind(x1, x2)
oldpar <- par(mfrow = c(2, 2))
smoothScatter(x, nrpoints = 0)

Output:

The issue I am having is that I am unsure how to add a legend/color scale that describes the relative difference in numeric terms between different shades. For example, there is no way to tell whether the darkest blue in the figure above is 2 times, 10 times or 100 times as dense as the lightest blue without some sort of legend or color scale. Is there any way in R to retrieve the requisite information to make such a scale, or anything built in that can produce a color scale of this nature automatically?

Answer 1

Here is an answer that relies on fields::imageplot and some fiddling with par(mar) to get the margins correct

fudgeit <- function(){
  xm <- get('xm', envir = parent.frame(1))
  ym <- get('ym', envir = parent.frame(1))
  z  <- get('dens', envir = parent.frame(1))
  colramp <- get('colramp', parent.frame(1))
  fields::image.plot(xm,ym,z, col = colramp(256), legend.only = T, add =F)
}

par(mar = c(5,4,4,5) + .1)
smoothScatter(x, nrpoints = 0, postPlotHook = fudgeit)

You can fiddle around with image.plot to get what you want and look at ?bkde2D and the transformation argument to smoothScatter to get an idea of what the colours represent.