Reputation: 823
Say I have a data frame coefs
where each row contains model coefficients for a curve.
coefs <- structure(list(a1 = c(1.22228259789383, 1.2064168157394, 1.09555089661994, 0.943947433470916, 0.883490658557721, 0.46125552320107), d = c(0.385227755933488, 0.457271644919152, 0.340063262461958, 0.305629949064525, 0.42459163183877, 0.425710112988664), g = c(0, 0, 0, 0, 0, 0), u = c(1, 1, 1, 1, 1, 1)), .Names = c("a1", "d", "g", "u"), class = c("tbl_df", "tbl", "data.frame"), row.names = c(NA, -6L))
I'd like to use each row of the data frame to add a new curve to the plot based a defined function: (you may recognize it as a 2PL item response model)
TWOPL <- function(x,a1,b) {
1 / (1 + exp(-a1*(x-(b))))
}
Based on this and this question I tried the following ggplot command but get the error that computation failed:
library(ggplot2)
p <- ggplot(coefs, aes(x = 0))
p + stat_function(fun = TWOPL) + xlim(-5,5)
I know that I need a way to give the various coefficients to the function. As a test, I tried the function with a fixed parameters to create 1 curve and it works, for example:
#1 curve based on fixed parameters
TWOPL_copy <- function(x) {
1 / (1 + exp(-1.22*(x-(.385))))
}
p <- ggplot(data.frame(x = 0), aes(x = 0))
p + stat_function(fun = TWOPL_copy) + xlim(-5,5)
I'm wondering how I might send each row of the data frame to ggplot. An ideal next step would be to differentiate the colors of each line somehow.
Upvotes: 3
Views: 5035
Reputation: 43334
While you could call stat_function
for each set of parameters or with some pain call it programmatically, it's simpler to do the calculations yourself:
library(tidyverse)
coefs %>%
mutate(curve = letters[row_number()]) %>% # add curve name
crossing(x = seq(-5, 5, .1)) %>% # repeat each row for every occurence of x
mutate(y = TWOPL(x, a1, d)) %>% # compute y values
ggplot(aes(x, y, color = curve)) +
geom_line()
The simplest way to create the curves programmatically is to add a list of stat_function
calls to the plot. All aesthetics have to be iterated across, including color. An x
aesthetic must be supplied, but if you set xlim
, it doesn't matter what it is.
curves <- coefs %>%
mutate(curve = letters[row_number()]) %>%
pmap(function(...){
dots <- data_frame(...)
stat_function(data = dots, aes(0, color = curve),
fun = function(x) TWOPL(x, dots$a1, dots$d),
xlim = c(-5, 5))
})
ggplot() + curves
Upvotes: 9