I have a ggplot where I drew a normal probability curve and wanted to highlight multiple areas as below
library(dplyr)
library(ggplot2)
library(gghighlight)
df <- data.frame(x = seq(-5, 5, length.out = 100)) %>% mutate(y = dnorm(x))
ggplot(df, aes(x, y)) + geom_area(fill = "sky blue") + gghighlight(abs(x) < 1) + geom_area(fill = "red") + gghighlight(abs(x) < -1.6)
This plot does not work. However when I try to fill single area i.e.
`ggplot(df, aes(x, y)) +
geom_area(fill = "sky blue") + gghighlight(abs(x)` < 1)`
This works perfectly.
Is there any consistent way to highlight multiple areas with different colours?
I also want to put regular legend in my plot to articulate definition of different colours i.e. sky blue = Area 01 and red = Area 02.
Any pointer will be very helpful.
>Solution :
You can try stat_function in ggplot2, I didn’t made it with gghighlight, sorry. It allows you to choose a function and a geom, so for your case with help of geom_area it seems to do the trick:
ggplot() +
xlim(-5, 5) +
stat_function(fun = dnorm, geom = "area", fill = "grey") +
stat_function(mapping = aes(fill = "Area 01"), fun = dnorm, xlim = c(-1, 1), geom = "area") +
stat_function(mapping = aes(fill = "Area 02"), geom = "area", fun = function(x) ifelse(abs(x) > 1.6, dnorm(x), NA)) +
scale_fill_manual(name = "Custom legend", values = c("skyblue", "red"))
For the first function, it’s just the standard normal distribution, the second is your highlighted with absolute value less than 1 so just use xlim, and the third can be done with 2 stat_function(…, xlim = ) but you can also pass a vectorized function.
You can specify a fill in mapping so that a legend is created, and then customize colors in scale_fill_manual.
Here is the result, I hope this is what you wanted:
