Suppose I have the data and plot as follows:
mydata = data.frame(x=rnorm(4), y=runif(4), tau=c(0,0,1,1))
ggplot(mydata) + geom_point(aes(x=x, y=y)) + facet_wrap(
There is an easier solution to this. The simulated data variable names have been changed for clarity in how they work within the labeller argument.
mydata = data.frame(x=rnorm(4), y=runif(4), tauvar=c(0,0,1,1),sigmavar=c(2,2,3,3))
ggplot(mydata) +
geom_point(aes(x=x, y=y)) +
facet_grid(sigmavar ~ tauvar,labeller = label_bquote(sigma==.(sigmavar),
tau==.(tauvar)))
here a solution with facet_grid
adn indexing the tau by its levels.
mydata = data.frame(x=rnorm(4), y=runif(4), tau=c(0,0,1,1))
ggplot(mydata) + geom_point(aes(x=x, y=y)) +
facet_grid(~ tau,labeller = label_bquote(tau ^ .(x)))
Edit To get the "tau=0" and "tau=1"
facet_grid(~ tau,labeller = label_bquote(tau == .(x)))
Edit2 second variable sigma
I find this solution, by defining a custom labeller. Hope someone ( ggplot2 guys ) give me a simpler solution.
my.label_bquote <- function (expr1 = (tau == .(x)),expr2 = (sigma == .(x)))
{
quoted1<- substitute(expr1)
quoted2 <- substitute(expr2)
function(variable, value) {
value <- as.character(value)
if(variable == 'tau')
lapply(value, function(x)
eval(substitute(bquote(expr1, list(x = x)),list(expr1 = quoted1))))
else
lapply(value, function(x)
eval(substitute(bquote(expr2, list(x = x)),list(expr2 = quoted2))))
}
}
mydata = data.frame(x=rnorm(4), y=runif(4), tau=c(0,0,1,1),sigma=c(2,2,3,3))
ggplot(mydata) + geom_point(aes(x=x, y=y)) +
facet_grid(sigma ~ tau,labeller = my.label_bquote())