plot.mc: Plot the results of a Monte Carlo Simulation

In tidyMC: Monte Carlo Simulations Made Easy and Tidy

Plot the results of a Monte Carlo Simulation

Description

Plot density plots for numeric results and bar plots for non-numeric results of a Monte Carlo Simulation run by future_mc().

Usage

## S3 method for class 'mc'
plot(
  x,
  join = NULL,
  which_setup = NULL,
  parameter_comb = NULL,
  plot = TRUE,
  ...
)

Arguments

x	An object of class mc, for which holds simple_output = TRUE. See value of future_mc().
join	A character vector containing the nice_names for the different parameter combinations (returned by future_mc()), which should be plotted together. Default: Each parameter combination is plotted distinctly.
which_setup	A character vector containing the nice_names for the different parameter combinations (returned by future_mc()), which should be plotted. Default: All parameter combinations are plotted.
parameter_comb	Alternative to which_setup. A named list whose components are named after (some of) the parameters in param_list in future_mc() and each component is a vector containing the values for the parameters to filter by. Default: All parameter combinations are plotted.
plot	Boolean that specifies whether the plots should be printed while calling the function or not. Default: TRUE
...	ignored

Details

Only one of the arguments join, which_setup, and paramter_comb can be specified at one time.

Value

A list whose components are named after the outputs of fun and each component contains an object of class ggplot and gg which can be plotted and modified with the ggplot2 functions.

Examples

test_func <- function(param = 0.1, n = 100, x1 = 1, x2 = 2){

  data <- rnorm(n, mean = param) + x1 + x2
  stat <- mean(data)
  stat_2 <- var(data)

  if (x2 == 5){
    stop("x2 can't be 5!")
  }

  return(list(mean = stat, var = stat_2))
}

param_list <- list(param = seq(from = 0, to = 1, by = 0.5),
                   x1 = 1:2)

set.seed(101)
test_mc <- future_mc(
  fun = test_func,
  repetitions = 1000,
  param_list = param_list,
  n = 10,
  x2 = 2
)

returned_plot1 <- plot(test_mc)

returned_plot1$mean +
 ggplot2::theme_minimal() +
 ggplot2::geom_vline(xintercept = 3)

returned_plot2 <- plot(test_mc,
which_setup = test_mc$nice_names[1:2], plot = FALSE)
returned_plot2$mean

returned_plot3 <- plot(test_mc,
join = test_mc$nice_names[1:2], plot = FALSE)
returned_plot3$mean

tidyMC documentation built on May 29, 2024, 6:15 a.m.