test_that("re-instantiating", { t1 = tsk("iris") t2 = tsk("california_housing") r = rsmp("cv", folds = 2) expect_resampling(r$instantiate(t1), task = t1) expect_resampling(r$instantiate(t2), task = t2) r = rsmp("custom") expect_error(r$instantiate(t1), "missing") expect_resampling(r$instantiate(t1, train_sets = list(1), test_sets = list(1)), task = t1) expect_resampling(r$instantiate(t2, train_sets = list(1), test_sets = list(2)), task = t2) }) test_that("param_vals", { task = tsk("iris") r = rsmp("bootstrap", repeats = 100L, ratio = 1) expect_identical(r$param_set$values$ratio, 1) expect_identical(r$param_set$values$repeats, 100L) r$instantiate(task) expect_true(r$is_instantiated) expect_identical(r$iters, 100L) expect_integerish(r$train_set(100), len = task$nrow) expect_resampling(r) expect_error({ r$param_set$values = list(repeats = 10L) r$param_set$get_values() }, "ratio") expect_error({ r$param_set$values = list(ratio = 0.5, repeats = 10L, foobar = 12) }, "foobar") }) test_that("hashing", { task = tsk("iris") keys = setdiff(mlr_resamplings$keys(), c("custom", "custom_cv", "ordered_holdout")) for (key in keys) { r = rsmp(key) with_seed(123L, r$instantiate(task)) hash = r$hash expect_string(hash, pattern = "^[a-z0-9]+$") with_seed(123L, r$instantiate(task)) expect_identical(r$hash, hash) if (key != "insample") { with_seed(124L, r$instantiate(task)) expect_false(identical(r$hash, hash)) } } }) test_that("cloning", { task = tsk("iris") keys = setdiff(mlr_resamplings$keys(), c("custom", "custom_cv", "ordered_holdout")) for (key in keys) { r = rsmp(key)$instantiate(task) clone = r$clone(deep = TRUE) expect_different_address(r$param_set, clone$param_set) if (is.data.table(r$instance)) { expect_different_address(r$instance, clone$instance) } } }) test_that("integer grouping col (#396)", { df = data.frame( id = rep(1L:10L, each = 2), x = rnorm(20) ) tsk = TaskRegr$new(id = "task", backend = df, target = "x") tsk$set_col_roles("id", "group") bs = rsmp("bootstrap", repeats = 10L, ratio = 1) bs$instantiate(tsk) set = bs$train_set(1) expect_integer(set) expect_true(every(split(seq_row(df), f = df$id), function(x) all(x %in% set) || all(x %nin% set))) set = bs$test_set(1) expect_integer(set) expect_true(every(split(seq_row(df), f = df$id), function(x) all(x %in% set) || all(x %nin% set))) }) test_that("as.data.table.Resampling", { r = rsmp("bootstrap") r$instantiate(tsk("mtcars")) tab = as.data.table(r) expect_data_table(tab, ncols = 3) expect_names(names(tab), permutation.of = c("set", "iteration", "row_id")) expect_integer(tab$iteration, any.missing = FALSE) expect_factor(tab$set, levels = c("train", "test"), any.missing = FALSE) expect_integer(tab$row_id, any.missing = FALSE) }) test_that("custom_cv", { task = tsk("penguins") ccv = rsmp("custom_cv") f = task$data(cols = "island")[[1L]] ccv$instantiate(task, f = f) expect_resampling(ccv, task = task) expect_equal(ccv$iters, 3L) expect_list(ccv$instance, "integer", len = 3) expect_names(names(ccv$instance), permutation.of = levels(f)) ccv$instantiate(task, col = "island") expect_resampling(ccv, task = task) expect_equal(ccv$iters, 3L) expect_list(ccv$instance, "integer", len = 3) names(ccv$instance) expect_names(names(ccv$instance), permutation.of = levels(f)) task = task$clone(TRUE)$filter(1:10) f = factor(rep(letters[1:3], each = 3)) expect_error(ccv$instantiate(task, f), "length") f[10] = NA ccv$instantiate(task, f) expect_data_table(as.data.table(ccv), nrows = 3L * 9L) f[] = NA expect_error(ccv$instantiate(task, f), "only missing") }) test_that("loo with groups", { task = tsk("penguins") task$set_col_roles("island", add_to = "group") loo = rsmp("loo") loo$instantiate(task) expect_equal(loo$iters, 3L) islands = cbind(row_id = task$row_ids, task$data(cols = "island")) tab = merge(as.data.table(loo), islands, by = "row_id") expect_true(all(tab[, .(n_islands = uniqueN(island)), by = row_id]$n_islands == 1L)) })