Comparing two-dimensional data sets in R; take II

David commented on yesterday's post and suggested to put the continuous fitted distribution in the background and the discrete, empirical distribution in the foreground. This looks quite nice, although there's a slight optical illusion that makes the circles look as if they'd be filled with a gradient, even though they're uniformly colored:

Not-so-good fit

Better fit

	pred <- ddply(data.frame(x=c(5:65)*0.01), .(x), function(t) data.frame(x = t$x, y = c(5:85)*0.01) )
	pred$enrichment <- predict(sigmoid, pred)
	max_pred <- max(pred$enrichment, d$enrichment)
	p <- ggplot(pred,aes(x,y))+geom_tile(aes(fill=enrichment))+scale_fill_gradient(low = "white", high = "steelblue",limits=c(0,max_pred))
	p <- p + xlab("x") + ylab("y")
	p <- p + geom_point(data=d,aes(x=x, y=y, colour=enrichment),size=20) +scale_colour_gradient(low = "white", high = "steelblue",limits=c(0,max_pred))
	print(p)

view raw gistfile1.r hosted with ❤ by GitHub