How can I color the area below several normal distributions?

Question

After several tries, I finally could obtained a unique figure with several normal distributions. In those distributions, the 1sd was also drawn as vertical rectangles. The code I used is this one:

x1<-50:200
a1<-dnorm(x1,134,20)
b1<-dnorm(x1,130,14)
c1<-dnorm(x1,132,12)
d1<-dnorm(x1,105,10)

scale<-range(pretty(range(a1,b1,c1,d1)))

remap<-function(x, to, from=range(x)) {
    (x-from[1]) / (from[2]-from[1]) * (to[2]-to[1]) + to[1] 
}

plot(NA, NA, xaxt="n", yaxt="n", type="n", xlim=scale, ylim=scale, xlab="Variable X", ylab="")
rect(remap(134-20, scale, range(x1)), scale[1],
     remap(134+20, scale, range(x1)), scale[2], col="#ff606025")
rect(remap(130-14, scale, range(x1)), scale[1],
     remap(130+14, scale, range(x1)), scale[2], col="#005ccd40")
rect(remap(132-12, scale, range(x1)), scale[1],
     remap(132+12, scale, range(x1)), scale[2], col="#005ccd40")
rect(remap(105-10, scale, range(x1)), scale[1],
     remap(105+10, scale, range(x1)), scale[2], col="#005ccd40")
#R1429
rect(remap(183, scale, range(x1)), scale[1],
     remap(183, scale, range(x1)), scale[2], col="darkblue", lwd=3,lty=3)

lines(remap(x1,scale), a1, col="#ff6060", lwd=3)
lines(remap(x1,scale), b1, col="#005ccd", lwd=3, lty=3)
lines(remap(x1,scale), c1, col="#005ccd", lwd=3)
lines(remap(x1,scale), d1, col="#005ccd", lwd=3,lty=3)

axis(2);
axis(1, at=remap(pretty(x1), scale), pretty(x1))

I got the next figure after running the code:

But my question is: how can I color only the area below each normal distribution, instead of doing vertical rectangles?

It would be much easier to interpret.

Thanks in advance!

Answer 1

Here's another version using ggvis:

library(dplyr)
library(ggvis)

## -- data generation copied from @NickK -- ##
data.frame(group = letters[1:4],
           m = c(130, 134, 132, 105),
           s = c(20, 14, 12, 10)) %>%
  group_by(group) %>%
  do(data_frame(group = .$group,
                x = 50:200,
                y = dnorm(x, .$m, .$s),
                withinSd = abs(x - .$m) <= .$s)) %>%
## ---------------------------------------- ##
  mutate(dash = ifelse(grepl("a|d", group), 5, 0),
         color = ifelse(grepl("a|c|d", group), "blue", "red"))  %>%
  ggvis() %>%
  layer_paths(~x, ~y, stroke := ~color, strokeDash := ~dash) %>%
  filter(withinSd) %>%
  layer_ribbons(~x, ~y, y2 = ~y-y, fill := ~color, fillOpacity := 0.2) %>%
  hide_legend("fill") %>%
  add_axis("y", title_offset = 50)

Answer 2

You can fill in under curves by using polygon.

## Some distributions
x1 <- 50:200
means <- c(134, 130, 132, 105)
sds <- c(20, 14, 12, 10)
dists <- lapply(seq_along(means), function(i) dnorm(x1, means[i], sds[i]))

## Some colors
cols <- colorRampPalette(c("red", "blue"))(length(dists))

## Blank plot
plot(c(x1[1], x1[length(x1)]), c(min(unlist(dists)), max(unlist(dists))), 
     type="n", xlab="X", ylab="Density")

## Add polygons
for (i in seq_along(dists))
    polygon(c(x1, rev(x1)), 
            c(numeric(length(x1)), rev(dists[[i]])), 
            col=cols[i],
            density=40)

Edit: for polygons within 1sd

xs <- sapply(seq_along(dists), function(i)  # get supports on x1
    do.call(`:`, as.list(which(x1 %in% (means[i] + c(-1,1)*sds[i])))))

plot(range(x1), range(unlist(dists)), type="n", xlab="X", ylab="Density")
for (i in seq_along(dists)) {
    x <- x1[xs[[i]]]
    polygon(c(x, rev(x)), 
            c(numeric(length(x)), rev(dists[[i]][xs[[i]]])), 
            col=cols[i],
            density=40)
    points(x1, dists[[i]], type="l", lty=2, col=cols[i])
}

Answer 3

Here's a way of doing it using some of Hadley Wickham's packages:

library("dplyr")
library("ggplot2")
library("tidyr")
data.frame(x = 50:200) %>%
  mutate(a = dnorm(x,134,20),
         b = dnorm(x,130,14),
         c = dnorm(x,132,12),
         d = dnorm(x,105,10)) %>%
  gather(group, y, -x) %>%
  ggplot(aes(x, y, fill = group)) %>%
  + geom_area(alpha = 0.3, position = "identity") %>%
  + geom_line() %>%
  print

Here's a version filling only within 1 SD:

data.frame(group = letters[1:4],
  m = c(130, 134, 132, 105),
  s = c(20, 14, 12, 10)
) %>%
  group_by(group) %>%
  do(data_frame(group = .$group,
    x = 50:200,
    y = dnorm(x, .$m, .$s),
    withinSd = abs(x - .$m) <= .$s)
  ) %>% {
    ggplot(., aes(x = x, y = y, colour = group)) +
      geom_line() +
      geom_area(aes(fill = group), filter(., withinSd),
        position = "identity", alpha = 0.3) +
      guides(colour = "none")
    }

If you wanted the graphs to all be the same height, you could just add a bit of extra dplyr magic:

data.frame(group = letters[1:4],
           m = c(130, 134, 132, 105),
           s = c(20, 14, 12, 10)
) %>%
  group_by(group) %>%
  do(data_frame(group = .$group,
                x = 50:200,
                y = dnorm(x, .$m, .$s),
                withinSd = abs(x - .$m) <= .$s)
  ) %>% 
  group_by(group) %>%
  mutate(y = y / max(y)) %>%
  {
    ggplot(., aes(x = x, y = y, colour = group)) +
      geom_line() +
      geom_area(aes(fill = group), filter(., withinSd),
                position = "identity", alpha = 0.3) +
      guides(colour = "none")
  }

Answer 4

Here's another version using base R. This one uses the type='h' option in lines() to draw a lot of vertical lines, so many that it ends up shading the region. Note that this required increasing the number of sample points in x1 (try changing x1 back to 50:200 to see what happens).

x1 <- seq(50,200,length=1000)
a1 <- dnorm(x1,134,20)
b1 <- dnorm(x1,130,14)
c1 <- dnorm(x1,132,12)
d1 <- dnorm(x1,105,10)

dists <- list(a1,b1,c1,d1)

# specify color names then convert them to RGB+alpha values
col <- c("red","green","blue","yellow")
col.rgba <- rgb(t(col2rgb(col))/255, alpha=0.2)

plot(NA, NA, xlim=range(x1), ylim=range(unlist(dists)), xlab="Variable X", ylab="")

# loop through each distribution
for (i in 1:length(dists)) {
  lines(x1, dists[[i]], type='h', lwd=2, col=col.rgba[i]) # add shaded region
  lines(x1, dists[[i]], type='l') # add solid line at top
}

Here's the output: