`check_model`: add title and save plot about performance HOT 5 CLOSED

library(performance)
data(iris)
m1 <- lm(Sepal.Width ~ Species + Petal.Length + Petal.Width, data = iris)
p <- plot(check_model(m1, panel = FALSE))

see::plots(p, title = "My title", subtitle = "My subtitle")

see::plots(p, title = "My title", subtitle = "My subtitle", n_colum = 2, tags = "A")

see::plots(p, title = "My title", caption = "Small caption at the bottom")

library(performance)
data(iris)
m1 <- lm(Sepal.Width ~ Species + Petal.Length + Petal.Width, data = iris)
p <- plot(check_model(m1, panel = FALSE))

p[[1]] <- p[[1]] + ggplot2::xlab("New Outcome Name")
see::plots(p)

# Create multiple models
# Function to iteratively add values to a string
# Source: https://purrr.tidyverse.org/reference/reduce.html
paste2 <- function(x, y, sep = " + ") paste(x, y, sep = sep)
# Iteratively add predictors to a formula
# Source: https://stackoverflow.com/questions/61419718/iteration-with-purrrreduce
model_formulas <- Reduce(f = paste2, x = mtcars[4:9] |> colnames(), init = "mpg ~ cyl + disp", accumulate = TRUE)
# Save models to a list
model_object_list <- lapply(X = model_formulas, 
                            FUN = \(x) caret::train(
                              formula(x),
                              data = mtcars,
                              method = "lm"
                              # Name models with their formula
                            )) |> setNames(model_formulas) 
#> Loading required package: ggplot2
#> Loading required package: lattice

# Plot making function
plot_func <- function(x, y) {
  p <- performance::check_model(x$finalModel, panel = FALSE) |> 
    plot() |> 
    # Add subtitle
    see::plots(subtitle = y)
  # Add response variable from model formula as x axis label of pp_check plot
  p[[1]] <- p[[1]] + ggplot2::xlab(sub(" ~.*", "", y))
  return(p)
}

plot_list <- purrr::map2(
  .f = plot_func, 
  .x = model_object_list, 
  # Add model formula to each plot as subtitle
  .y = names(model_object_list)) |> 
  setNames(model_formulas) 

# Save each plot with a modified version of model formula name, make output silent
invisible(
  plot_list |>
    purrr::map2(.y = model_formulas, .f = function(x = .x, y = .y) 
      ggplot2::ggsave(plot = x, filename = paste0(y |> janitor::make_clean_names(), ".png"), height=10, width=20))
)