Nothing
test_that("simulation study returns the expected schema and summarises cleanly", {
results <- run_simulation_study(
dimensions = list(c(25, 10)),
true_ncomp = 2,
missing_props = 10,
mechanisms = "MCAR",
reps = 3,
seed = 1,
max_ncomp = 4,
criteria = c("Q2-LOO", "AIC"),
incomplete_methods = "nipals_standard",
imputation_methods = "knn",
folds = 5
)
expect_named(results, c(
"study", "dataset", "n", "p", "true_ncomp", "target_ncomp", "mechanism",
"missing_prop", "method", "criterion", "selected_ncomp", "matched_target",
"runtime_sec", "seed", "status", "notes"
))
summary_df <- summarize_simulation_study(results)
expect_true(nrow(summary_df) > 0)
complete_rows <- results[results$method == "Complete" & results$status == "ok", , drop = FALSE]
q2_rate <- mean(complete_rows$matched_target[complete_rows$criterion == "Q2-LOO"])
aic_rate <- mean(complete_rows$matched_target[complete_rows$criterion == "AIC"])
expect_true(is.finite(q2_rate))
expect_true(is.finite(aic_rate))
expect_true(q2_rate >= aic_rate)
})
test_that("real-data study smoke test runs on bromhexine", {
results <- run_real_data_study(
dataset = "bromhexine",
seed = 1,
missing_props = 5,
mechanisms = "MCAR",
reps = 1,
baseline_reps = 3,
max_ncomp = 4,
criteria = c("Q2-10fold"),
incomplete_methods = "nipals_standard",
imputation_methods = "knn",
folds = 5
)
expect_true(nrow(results) > 0)
expect_true(any(results$dataset == "bromhexine"))
})
test_that("study runners do not impose a default seed", {
set.seed(303)
results <- run_simulation_study(
dimensions = list(c(20, 10)),
true_ncomp = 2,
missing_props = numeric(0),
mechanisms = character(0),
reps = 1,
seed = NULL,
max_ncomp = 3,
criteria = "AIC"
)
expect_true(nrow(results) > 0)
expect_true(all(is.na(results$seed)))
})
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