Nothing
test_that(
"Same results using 1 core or 2.", {
library(parallel)
result_1core <- run_model_tabular(
location = system.file("tabular/thr", package = "heemod"),
save = FALSE, overwrite = FALSE, run_psa = FALSE
)
result_2core <- run_model_tabular(
location = system.file("tabular/thr", package = "heemod"),
reference = "REFERENCE_2core.csv",
save = FALSE, overwrite = FALSE, run_psa = FALSE
)
## the objects contain environments, so we can't use identical;
## instead, we'll check parts that use multi-core processing
##
## parameters from the discrete sensitivity analysis
expect_identical(
sapply(result_1core$dsa$dsa$.par_value, eval_tidy),
sapply(result_2core$dsa$dsa$.par_value, eval_tidy)
)
## counts from all models from the discrete sensitivity analysis
expect_identical(
get_counts(get_model(result_1core$dsa)),
get_counts(get_model(result_2core$dsa)))
## demographic analysis
expect_equal(
result_1core$demographics$updated_model[-3],
result_2core$demographics$updated_model[-3],
ignore_attr = TRUE)
}
)
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