Function to plot multiple lines in ggplot

Question

I am trying to create a function that takes a sequence of x values and vector to be used in an equation. For each value in the vector dM , I would like to calculate probabilities of each x value occurring (equation in function for loop). Put all probabilities in a data.frame with associated dM values (so two columns) and then use ggplot to map the line to show each relationship.

For example: pred_prob(0,870,50,c(-100,0)) this would mean from 0 to 870 by 50, calculate the probabilities for each value in the vector. Here is my working code. I suspect the nested for loop is not working as intended or how the data being stored is not correct.

pred_probs <- function(from,to,by,dM){
  pred_females = numeric(0)
  dM <- as.vector(dM)
  x_values <- seq(from = from, to = to, by = by)

  for( j in dM){
   for(i in x_values){
     prob=exp(-2.048e-02*i + 2.087e-02*j + -2.216e-05*i*j)/(1 + exp(-2.048e-02*i + 2.087e-02*j + -2.216e-05*i*j)) 
     pred_females = c(pred_females,prob,j)
   }
  pred_females <- as.data.frame(pred_females)
  ggplot(pred_females) + 
    geom_line(mapping = aes(x = x_values, y = pred_females, 
                            group = j, 
                            color = j))
  }
}
pred_prob(0,870,50,c(-100,0))

EDIT:

Output graph should look like this (only tw:

EDIT (again): This function satisfies my needs:

pred_probs <- function(to, from, by, dep){
tibble() %>% 
  expand(j=dep, i=seq(to, from, by)) %>% 
  mutate(prob=exp(-2.048e-02*i + 2.087e-02*j + -2.216e-05*i*j)/(1 + exp(-2.048e-02*i + 2.087e-02*j + -2.216e-05*i*j))) %>% 
  ggplot() +
  geom_line(aes(x = i, y = prob, color = as.factor(j)))
}
pred_probs(0,870,50,c(-300,-200,-100,0,100))

Answer 1

I'm not entirely clear what you're trying to do as there are several issues with your code, but I'm pretty confident that you can do what you want without any need for loops or functions.

Does this come close to what you want?

library(tidyverse)

tibble() %>% 
  expand(i=c(-200, -100, 0, 100), j=seq(0, 2000, 50)) %>% 
  mutate(prob=exp(-2.048e-02*i + 2.087e-02*j + -2.216e-05*i*j)/(1 + exp(-2.048e-02*i + 2.087e-02*j + -2.216e-05*i*j))) %>% 
  ggplot() +
    geom_line(aes(x = i, y = prob, color = as.factor(j)))