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 mc
plot(
x,
join = NULL,
which_setup = NULL,
parameter_comb = NULL,
plot = TRUE,
...
)
Arguments
- x
An object of class
mc
, for which holdssimple_output = TRUE
. See value offuture_mc()
.- join
A character vector containing the
nice_names
for the different parameter combinations (returned byfuture_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 byfuture_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 inparam_list
infuture_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
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.
Details
Only one of the arguments join
, which_setup
, and paramter_comb
can be specified at one time.
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
)
#> Running single test-iteration for each parameter combination...
#>
#> Test-run successfull: No errors occurred!
#> Running whole simulation: Overall 6 parameter combinations are simulated ...
#>
#> Simulation was successfull!
#> Running time: 00:00:00.95462
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