pairs() and more

Getting genetics done has a piece of code to make a more informative pairwise scatter plot than pairs()

# panel.smooth function is built in.
# panel.cor puts correlation in upper panels, size proportional to correlation
panel.cor <- function(x, y, digits=2, prefix="", cex.cor, ...)
{
    usr <- par("usr"); on.exit(par(usr))
    par(usr = c(0, 1, 0, 1))
    r <- abs(cor(x, y))
    txt <- format(c(r, 0.123456789), digits=digits)[1]
    txt <- paste(prefix, txt, sep="")
    if(missing(cex.cor)) cex.cor <- 0.8/strwidth(txt)
    text(0.5, 0.5, txt, cex = cex.cor * r)
}
 
# Plot #2: same as above, but add loess smoother in lower and correlation in upper
pairs(~Sepal.Length+Sepal.Width+Petal.Length+Petal.Width, 

data=iris,lower.panel=panel.smooth, upper.panel=panel.cor, 
      pch=20, main="Iris Scatterplot Matrix")

From the comments, we see alternatives are pairs.panels() from package psych and chart.Correlation() from package PerformanceAnalytics.