using ggplots stat_function in a custom function - r

Question

I am trying to create some ggplots automaticly. Here is my working code example for adding stat_functions:
require(ggplot2)
p1 <- ggplot(data.frame(x = c(-2.5, 7.5)), aes(x = x)) + theme_minimal()+
stat_function(fun= function(x){1*x},lwd=1.25, colour = "navyblue") +
stat_function(fun= function(x){2*x},lwd=1.25, colour = "navyblue") +
stat_function(fun= function(x){3*-x},lwd=1.25, colour = "red")
p1
As you can see the stat_functions all use (nearly) the same function just with a different parameter.
Here is what i have tried to write:
f <- function(plot,list){
for (i in 1:length(list)){
plot <- plot + stat_function(fun= function(x){x*list[i]})
}
return(plot)
}
p1 <- ggplot(data.frame(x = c(-2.5, 7.5)), aes(x = x)) + theme_minimal()
p2 <- f(p1,c(1,2,3))
p2
This however doesnt return 3 lines, but only one. Why?

Answer 1

Your question is a bit confusing, because the first plot actually contains some other variable bits, but in your function you have a single stat_summary call for only one variable element.
Anyways. Keep the ggplot main object separate and create a list of additional objects, very easy for example with lapply. Add this list to your main plot as usual.
Check also https://ggplot2-book.org/programming.html
library(ggplot2)
p <- ggplot(data.frame(x = c(-2.5, 7.5)), aes(x = x)) + theme_minimal()
ls_sumfun <- lapply(1:3, function(y){
stat_function(fun= function(x){y*x}, lwd=1.25, colour = "navyblue")
}
)
p + ls_sumfun
Created on 2021-04-26 by the reprex package (v2.0.0)

Answer 2

In R, you can pass functions as arguments. You can also return functions from functions. This might make your code simpler and cleaner.
Here's an example:
p1 <- ggplot(data.frame(x = c(-2.5, 7.5)), aes(x = x))
add_stat_fun <- function (ggp, f) {
ggp + stat_function(fun = f)
}
make_multiply_fun <- function (multiplier) {
force(multiplier) # not sure if this is required...
f <- function (x) {multiplier * x}
return(f)
}
my_funs <- lapply(1:3, make_multiply_fun)
# my_funs is now a list of functions
add_stat_fun(p1, my_funs[[1]])
add_stat_fun(p1, my_funs[[2]])
add_stat_fun(p1, my_funs[[3]])