Render a SLiM script with special slimrlang formatting

If your slimr_script object has made use of special slimrlang syntax slimr_template, this function will 'render' the slimr_script into valid SLiM syntax, ready to be run with SLiM or slim_run

slim_script_render(
  slimr_script,
  template = NULL,
  replace_NAs = TRUE,
  reps = 1,
  parallel = FALSE,
  portable = FALSE
)

Arguments

slimr_script: The slimr_script object to be rendered
template: A list or data.frame containing values for any templated variables. If a list, it must be named, where the names correspond to the variables. If a list of lists, the inner lists must be named with the variable names, and slim_script_render will render a separate slimr_script for each top-level list element and return it as a slimr_script_coll object. If a data.frame (or tibble), then the column names should match the templated variables, and slim_script_render will render a separate slimr_script for each row and return it as a slimr_script_coll object.
replace_NAs: Should NA values in the template be replaced by their default values?
reps: Should the rendered script be replicated? If greater than 1, a slimr_script_coll will be returned. This can also be used with a slimr_script object that has already been rendered, in which case it will just repeat the rendered script in the result.
parallel: Should the rendering be done in parallel when rendering multiple scripts? Requires the furrr package and will use the plan set by future::plan
portable: If `TRUE`, the the script will be rendered in a 'portable' format, which allows the script to be modified in another program such as SLiMGUI, and then reimported into R, while maintaining `slimr` features. See details for more information on how this works.

Value

A rendered `slimr_script_coll` object

Examples

test_sim <- slim_script(
  slim_block_init_minimal(mutation_rate = r_template("mu", 1e-7)),
  slim_block_add_subpops(1, 100),
  slim_block(1, 20, late(), {
    r_output(sim.outputFull(), "out", do_every = 10)
  })
) %>%
  slim_script_render(data.frame(mu = c(1e-7, 1e-6, 1e-5)))
test_sim
#> <slimr_script_coll[3]>
#> <1>
#> 
#> block_init:initialize() {
#>     initializeMutationRate(1e-07);
#>     initializeMutationType("m1", 0.5, "f", 0);
#>     initializeGenomicElementType("g1", m1, 1);
#>     initializeGenomicElement(g1, 0, 1e+05 - 1);
#>     initializeRecombinationRate(1e-08);
#> }
#> 
#> block_2:1 early() {
#>     sim.addSubpop("p1", 100);
#> }
#> 
#> block_3:1:20 late() {
#>     {sim.outputFull() -> out}
#> }
#> 
#> <2>
#> 
#> block_init:initialize() {
#>     initializeMutationRate(1e-06);
#>     initializeMutationType("m1", 0.5, "f", 0);
#>     initializeGenomicElementType("g1", m1, 1);
#>     initializeGenomicElement(g1, 0, 1e+05 - 1);
#>     initializeRecombinationRate(1e-08);
#> }
#> 
#> block_2:1 early() {
#>     sim.addSubpop("p1", 100);
#> }
#> 
#> block_3:1:20 late() {
#>     {sim.outputFull() -> out}
#> }
#> 
#> <3>
#> 
#> block_init:initialize() {
#>     initializeMutationRate(1e-05);
#>     initializeMutationType("m1", 0.5, "f", 0);
#>     initializeGenomicElementType("g1", m1, 1);
#>     initializeGenomicElement(g1, 0, 1e+05 - 1);
#>     initializeRecombinationRate(1e-08);
#> }
#> 
#> block_2:1 early() {
#>     sim.addSubpop("p1", 100);
#> }
#> 
#> block_3:1:20 late() {
#>     {sim.outputFull() -> out}
#> }