Extract Elements from SLiM's outputFull()
slim_extract_full(
output_full,
type = c("mutations", "individuals", "genomes", "coordinates", "sexes", "ages",
"full_individual"),
join = TRUE,
expand_mutations = FALSE
)A character vector where each element is the result of a
call to outputFull() in SLiM
Which type of data to return: "mutations", "individuals", "genomes", "coordinates", "sexes", or "ages"
If asking for multiple output type, should they be joined into one tibble (join = TRUE)
or left as separate tibbles returned in a list (join = FALSE)?
If asking for "genomes" output, should mutations be expanded into their own column (expand_mutations = TRUE)
or left as a vector of mutation ids in a list column (expand_mutations = FALSE)?
A tibble
if(slim_is_avail()) {
test_sim <- slim_script(
slim_block_init_minimal(mutation_rate = 1e-6),
slim_block_add_subpops(1, 100),
slim_block(1, 20, late(), {
r_output(sim.outputFull(), "out", do_every = 10)
})
) %>%
slim_run()
slim_extract_full(test_sim$output_data, type = "mutations")
}
#>
#>
#> Simulation finished with exit status: 0
#>
#> Success!
#> # A tibble: 178 × 11
#> generation mut_id unique_mut_id mut_type chrome_pos selection dominance
#> <int> <int> <int> <chr> <int> <dbl> <dbl>
#> 1 10 34 1 m1 49445 0 0.5
#> 2 10 13 7 m1 32572 0 0.5
#> 3 10 6 17 m1 95907 0 0.5
#> 4 10 3 38 m1 98747 0 0.5
#> 5 10 24 43 m1 4281 0 0.5
#> 6 10 25 48 m1 6378 0 0.5
#> 7 10 51 55 m1 10571 0 0.5
#> 8 10 12 56 m1 17226 0 0.5
#> 9 10 50 58 m1 57418 0 0.5
#> 10 10 32 66 m1 47339 0 0.5
#> # ℹ 168 more rows
#> # ℹ 4 more variables: subpop <chr>, first_gen <int>, prevalence <int>,
#> # nucleotide <chr>