ggplot2: set (nonlinear) values for alpha

Question

I'd like to plot a mirrored 95% density curve and map alpha to the density:

foo <- function(mw, sd, lower, upper) {
x <- seq(lower, upper, length=500)
dens <- dnorm(x, mean=mw, sd=sd, log=TRUE)
dens0 <- dens -min(dens)
return(data.frame(dens0, x))
}

df.rain <- foo(0,1,-1,1)

library(ggplot2)


drf <- ggplot(df.rain, aes(x=x, y=dens0))+
geom_line(aes(alpha=..y..))+
geom_line(aes(x=x, y=-dens0, alpha=-..y..))+
stat_identity(geom="segment", aes(xend=x, yend=0, alpha=..y..))+
stat_identity(geom="segment", aes(x=x, y=-dens0, xend=x, yend=0, alpha=-..y..))
drf

This works fine, but I'd like to make the contrast between the edges and the middle more prominent, i.e., I want the edges to be nearly white and only the middle part to be black. I've been tampering with scale_alpha() but without luck. Any ideas?

Edit: Ultimately, I'd like to plot several raindrops, i.e., the individual drops will be small but the shading should still be clearly visible.

Answer 1

Instead of mapping dens0 to the alpha, I'd map it to color:

drf <- ggplot(df.rain, aes(x=x, y=dens0))+
   geom_line(aes(color=..y..))+
   geom_line(aes(x=x, y=-dens0, color=-..y..))+
   stat_identity(geom="segment", aes(xend=x, yend=0, color=..y..))+
   stat_identity(geom="segment", aes(x=x, y=-dens0, xend=x, yend=0, color=-..y..))

Now we still have the contrast in color is mainly present in the tails. Using two colors helps a bit (note that the switch in color is at 0.25):

drf + scale_color_gradient2(midpoint = 0.25)

Finally, to include the distribution of the dens0 values, I base the midpoint of the color scale on the median value in the data:

drf + scale_color_gradient2(midpoint = median(df.rain$dens0))

Note!: But however the way you tweak your data, most contrast in your data is in the more extreme values in your dataset. Trying to mask this by messing with a non-linear scale, or by tweaking a color scale like I did, could present a false picture of the real data.

Answer 2

Here is a solution using geom_ribbon() instead of geom_line()

df.rain$group <- seq_along(df.rain$x)
tmp <- tail(df.rain, -1)
tmp$group <- tmp$group - 1
tmp$dens0 <- head(df.rain$dens0, -1)
dataset <- rbind(head(df.rain, -1), tmp)
ggplot(dataset, aes(x = x, ymin = -dens0, ymax = dens0, group = group, 
  alpha = dens0)) + geom_ribbon() + scale_alpha(range = c(0, 1))

ggplot(dataset, aes(x = x, ymin = -dens0, ymax = dens0, group = group, 
  fill = dens0)) + geom_ribbon() + 
  scale_fill_gradient(low = "white", high = "black")

See Paul's answer for changing the colours.

dataset9 <- merge(dataset, data.frame(study = 1:9))
ggplot(dataset9, aes(x = x, ymin = -dens0, ymax = dens0, group = group, 
    alpha = dens0)) + geom_ribbon() + scale_alpha(range = c(0, 0.5)) + 
    facet_wrap(~study)