test_that("Feature columns can be reordered", { bh = load_dataset("BostonHousing", "mlbench") bh$medv = NULL task = tsk("boston_housing") task$col_roles$feature = setdiff(names(bh), "cmedv") expect_equal(task$feature_names, setdiff(names(bh), "cmedv")) expect_equal(names(task$data(rows = 1)), c("cmedv", setdiff(names(bh), "cmedv"))) task$col_roles$feature = shuffle(task$col_roles$feature) expect_equal(names(task$data(rows = 1)), c("cmedv", task$col_roles$feature)) }) test_that("Task duplicates rows", { task = tsk("iris") data = task$data(c(1L, 1L)) expect_data_table(data, nrows = 2L, any.missing = FALSE) }) test_that("Rows return ordered", { x = load_dataset("nhtemp", "datasets", TRUE) data = as.data.frame(x) data$x = as.numeric(data$x) data$t = as.integer(time(x)) data = data[rev(seq_row(data)), ] rownames(data) = NULL b = as_data_backend(data) task = TaskRegr$new(id = "nhtemp", b, target = "x") x = task$data() expect_true(is.unsorted(x$t)) task$col_roles$order = "t" x = task$data(ordered = TRUE) expect_integer(x$t, sorted = TRUE, any.missing = FALSE) x = task$data(ordered = FALSE) expect_true(is.unsorted(x$t)) x = task$data(rows = sample(nrow(data), 50), ordered = TRUE) expect_integer(x$t, sorted = TRUE, any.missing = FALSE) }) test_that("Rows return ordered with multiple order cols", { task = tsk("iris") x = task$data() expect_true(is.unsorted(x$Petal.Length)) task$col_roles$order = c("Petal.Length", "Petal.Width") expect_equal(task$col_roles$order, c("Petal.Length", "Petal.Width")) x = task$data(ordered = TRUE) expect_numeric(x$Petal.Length, sorted = TRUE, any.missing = FALSE) expect_true(x[, is.unsorted(Petal.Width)]) expect_true(all(x[, is.unsorted(Petal.Width), by = Petal.Width]$V1 == FALSE)) }) test_that("Task rbind", { task = tsk("iris") # expect_error(task$rbind(task), "data.frame") data = iris[1:10, ] task$rbind(iris[1:10, ]) expect_task(task) expect_equal(task$nrow, 160) task$rbind(iris[integer(), ]) expect_equal(task$nrow, 160) # #185 task = tsk("iris") task$select("Petal.Length") task$rbind(task$data()) expect_set_equal(task$row_ids, 1:300) task$rbind(data.table()) expect_equal(task$nrow, 300L) # #437 task = tsk("zoo") data = task$data() data$foo = 101:1 nt = task$clone()$rbind(data) expect_task(nt) expect_set_equal(nt$row_ids, 1:202) expect_equal(nt$row_names$row_name, c(task$row_names$row_name, rep(NA, 101))) expect_equal(nt$col_info[list("foo"), .N, nomatch = NULL], 0L) # #423 task = tsk("iris") task$row_roles$use = 1:10 task$row_roles$holdout = 11:150 task$rbind(iris[sample(nrow(iris), 5), ]) expect_set_equal(task$row_ids, c(1:10, 151:155)) # 496 data = iris data$blocks = sample(letters[1:2], nrow(iris), replace = TRUE) task = TaskClassif$new("iris", data, target = "Species") task$col_roles$feature = setdiff(task$col_roles$feature, "blocks") task$col_roles$group = "blocks" learner = lrn("classif.rpart") learner$train(task) expect_prediction(predict(learner, iris, predict_type = "")) # merge factor levels task = tsk("penguins") data = task$data(1) data$sex = factor("unsure", levels = c("male", "female", "unsure")) task$rbind(data) expect_equal(task$levels("sex")[[1]], c("female", "male", "unsure")) expect_equal(task$col_info[list("sex"), fix_factor_levels], TRUE) }) test_that("Task cbind", { task = tsk("iris") iris_col_hashes = task$col_hashes # expect_error(task$cbind(task), "data.frame") data = cbind(data.frame(foo = 150:1), data.frame(..row_id = task$row_ids)) task$cbind(data) expect_task(task) expect_equal(task$ncol, 6L) expect_names(task$feature_names, must.include = "foo") expect_equal(iris_col_hashes, task$col_hashes[names(iris_col_hashes)]) data = data.frame(bar = runif(150)) task$cbind(data) expect_task(task) expect_equal(task$ncol, 7L) expect_names(task$feature_names, must.include = "bar") data = data.frame(..row_id = task$row_ids) task$cbind(data) expect_equal(task$ncol, 7L) task$cbind(iris[, character()]) expect_equal(task$ncol, 7L) task$cbind(data.table()) expect_equal(task$ncol, 7L) y = task$data(cols = task$target_names, rows = shuffle(task$row_ids)) task$cbind(y) expect_equal(task$ncol, 7L) expect_disjunct(task$feature_names, task$target_names) # cbind to subsetted task task = tsk("iris")$filter(1:120) backend = data.table(x = runif(120)) task$cbind(backend) expect_equal(iris_col_hashes, task$col_hashes[names(iris_col_hashes)]) # cbind 0-row data (#461) task = tsk("iris")$filter(integer()) task$cbind(data.frame(x = integer())) expect_set_equal(c(task$target_names, task$feature_names), c(names(iris), "x")) }) test_that("cbind/rbind works", { task = tsk("iris") data = data.table(..row_id = 1:150, foo = 150:1) task$cbind(data) expect_task(task) expect_set_equal(c(task$feature_names, task$target_names), c(names(iris), "foo")) expect_data_table(task$data(), ncols = 6, any.missing = FALSE) task$rbind(cbind(data.table(..row_id = 201:210, foo = 99L), iris[1:10, ])) expect_task(task) expect_set_equal(task$row_ids, c(1:150, 201:210)) expect_data_table(task$data(), ncols = 6, nrows = 160, any.missing = FALSE) # auto generated ids task = tsk("zoo") newdata = task$data(1) newdata$animal = "boy" task$rbind(newdata) expect_set_equal(task$row_ids, 1:102) }) test_that("filter works", { task = tsk("iris") task$filter(1:100) expect_equal(task$nrow, 100L) task$filter(91:150) expect_equal(task$nrow, 10L) expect_equal(task$row_ids, 91:100) task$filter(91) expect_equal(task$nrow, 1L) expect_data_table(task$data(), nrows = 1L, any.missing = FALSE) }) test_that("select works", { task = tsk("iris") task$select(setdiff(task$feature_names, "Sepal.Length")) expect_equal(task$ncol, 4L) expect_error(task$select(c("Sepal.Width", "foobar"))) task$select("Sepal.Width") expect_equal(task$feature_names, "Sepal.Width") expect_error(task$select(1:4), "character") expect_error(task$select("xxx", "subset")) }) test_that("rename works", { task = tsk("iris") old = names(iris) new = paste0("xx_", old) task$rename(old, new) expect_set_equal(task$feature_names, setdiff(new, "xx_Species")) expect_equal(task$target_names, "xx_Species") expect_task_classif(task) }) test_that("stratify works", { task = tsk("iris") expect_false("strata" %in% task$properties) expect_null(task$strata) task$col_roles$stratum = task$target_names expect_true("strata" %in% task$properties) tab = task$strata expect_data_table(tab, ncols = 2, nrows = 3) expect_list(tab$row_id, "integer") }) test_that("groups/weights work", { b = as_data_backend(data.table(x = runif(20), y = runif(20), w = runif(20), g = sample(letters[1:2], 20, replace = TRUE))) task = TaskRegr$new("test", b, target = "y") task$set_row_roles(16:20, character()) expect_false("groups" %in% task$properties) expect_false("weights" %in% task$properties) expect_null(task$groups) expect_null(task$weights) task$col_roles$weight = "w" expect_subset("weights", task$properties) expect_data_table(task$weights, ncols = 2, nrows = 15) expect_numeric(task$weights$weight, any.missing = FALSE) task$col_roles$weight = character() expect_true("weights" %nin% task$properties) task$col_roles$group = "g" expect_subset("groups", task$properties) expect_data_table(task$groups, ncols = 2, nrows = 15) expect_subset(task$groups$group, c("a", "b")) task$col_roles$group = character() expect_true("groups" %nin% task$properties) expect_error({ task$col_roles$weight = c("w", "g") }, "up to one") }) test_that("ordered factors (#95)", { df = data.frame( x = c(1, 2, 3), y = factor(letters[1:3], levels = letters[1:3], ordered = TRUE), z = factor(c("M", "R", "R"), levels = c("M", "R")) ) b = as_data_backend(df) task = TaskClassif$new(id = "id", backend = b, target = "z") expect_subset(c("numeric", "ordered", "factor"), task$col_info$type) expect_set_equal(task$col_info[id == "z", levels][[1L]], c("M", "R")) expect_set_equal(task$col_info[id == "y", levels][[1L]], letters[1:3]) }) test_that("as.data.table", { task = tsk("iris") expect_data_table(as.data.table(task), nrows = 150, ncols = 5) }) test_that("extra factor levels are stored (#179)", { dt = data.table( x1 = factor(letters[1:5], levels = letters[5:1]), x2 = factor(letters[1:5], levels = letters), x3 = letters[1:5], target = 1:5) task = TaskRegr$new("extra_factor_levels", as_data_backend(dt), "target") expect_equal(task$levels("x2")$x2, letters) }) test_that("task$droplevels works", { dt = data.table( x1 = factor(letters[1:3]), target = 1:3 ) task = TaskRegr$new("droplevels", as_data_backend(dt), "target") task$filter(1:2) expect_equal(task$nrow, 2L) expect_equal(task$levels("x1")$x1, letters[1:3]) task$droplevels() expect_equal(task$levels("x1")$x1, letters[1:2]) }) test_that("task$missings() works", { task = tsk("pima") x = task$missings() y = map_int(task$data(), count_missing) expect_equal(x, y[match(names(x), names(y))]) # issue #862 task = tsk("iris")$cbind(data.frame(x = 1:150))$rename("x", "y") missings = task$missings(cols = character()) expect_integer(missings, len = 0L) testthat::expect_named(missings) }) test_that("task$feature_types preserves key (#193)", { task = tsk("iris")$select(character())$cbind(iris[1:4]) expect_data_table(task$feature_types, ncols = 2L, nrows = 4L, key = "id") }) test_that("switch columns on and off (#301)", { task = tsk("iris") task$col_roles$feature = setdiff(task$col_roles$feature, "Sepal.Length") task$cbind(data.table(x = 1:150)) task$col_roles$feature = union(task$col_roles$feature, "Sepal.Length") expect_data_table(task$data(), ncols = 6, nrows = 150, any.missing = FALSE) }) test_that("row roles setters", { task = tsk("iris") expect_error({ task$row_roles$use = "foo" }) expect_error({ task$row_roles$foo = 1L }) task$row_roles$use = 1:20 expect_equal(task$nrow, 20L) }) test_that("col roles getters/setters", { task = tsk("iris") expect_error({ task$col_roles$feature = "foo" }) # additional roles allowed (#558) task$col_roles$foo = "Species" task$col_roles$feature = setdiff(task$col_roles$feature, "Sepal.Length") expect_false("Sepal.Length" %in% task$feature_names) }) test_that("Task$row_names", { task = tsk("mtcars") tab = task$row_names expect_data_table(tab, any.missing = FALSE, ncols = 2, nrows = task$nrow) expect_integer(tab$row_id, unique = TRUE) expect_character(tab$row_name) tab = task$filter(1:10)$row_names expect_data_table(tab, any.missing = FALSE, ncols = 2, nrows = task$nrow) expect_integer(tab$row_id, unique = TRUE) expect_character(tab$row_name) }) test_that("Task$set_row_roles", { task = tsk("pima") task$set_row_roles(1:10, remove_from = "use") expect_true(all(1:10 %nin% task$row_ids)) task$set_row_roles(1:10, add_to = "use") expect_true(all(1:10 %in% task$row_ids)) task$set_row_roles(1:10, roles = "holdout") expect_true(all(1:10 %nin% task$row_ids)) }) test_that("Task$set_col_roles", { task = tsk("pima") task$set_col_roles("mass", remove_from = "feature") expect_true("mass" %nin% task$feature_names) task$set_col_roles("mass", add_to = "feature") expect_true("mass" %in% task$feature_names) task$set_col_roles("age", roles = "weight") expect_true("age" %nin% task$feature_names) expect_data_table(task$weights) task$set_col_roles("age", add_to = "feature", remove_from = "weight") expect_true("age" %in% task$feature_names) expect_null(task$weights) }) test_that("$add_strata", { task = tsk("mtcars") expect_equal(task$col_roles$stratum, character()) task$add_strata("mpg", bins = 5) expect_set_equal(task$col_roles$stratum, "..stratum_mpg") expect_data_table(task$strata, nrows = 5) task$add_strata("am", bins = 3) expect_set_equal(task$col_roles$stratum, c("..stratum_mpg", "..stratum_am")) task = tsk("mtcars") task$add_strata(c("mpg", "am"), bins = c(2, 5)) expect_set_equal(task$col_roles$stratum, c("..stratum_mpg", "..stratum_am")) }) test_that("column labels", { task = tsk("iris") expect_character(task$col_info$label) expect_true(allMissing(task$col_info$label)) expect_true(allMissing(task$labels)) task$labels = c(Species = "sp") expect_equal(task$labels[["Species"]], "sp") expect_equal(count_missing(task$labels), 4L) fn = task$feature_names task$labels = set_names(toupper(fn), fn) expect_equal(unname(task$labels), c("sp", toupper(fn))) expect_error({ task$labels = c(foo = "as") }, "names") dt = data.table(id = c(task$target_names, task$feature_names)) dt$label = tolower(dt$id) task$labels = dt expect_equal( unname(task$labels), tolower(c(task$target_names, task$feature_names)) ) }) test_that("set_levels", { task = tsk("penguins") new_lvls = c("male", "female", "missing") task$set_levels(list(sex = new_lvls)) tab = task$col_info[list("sex")] expect_equal(tab$levels[[1]], new_lvls) expect_equal(tab$fix_factor_levels[[1]], TRUE) expect_equal(levels(task$data(1)$sex), new_lvls) expect_equal(levels(head(task)$sex), new_lvls) new_lvls = c("female", "nothing") task$set_levels(list(sex = new_lvls)) tab = task$col_info[list("sex")] expect_equal(tab$levels[[1]], new_lvls) expect_equal(tab$fix_factor_levels[[1]], TRUE) expect_equal(as.integer(task$data(1)$sex), NA_integer_) expect_equal(as.integer(head(task, 1)$sex), NA_integer_) expect_equal(levels(task$data(1)$sex), new_lvls) expect_equal(levels(head(task, 1)$sex), new_lvls) }) test_that("special chars in feature names (#697)", { prev = options(mlr3.allow_utf8_names = FALSE) on.exit(options(prev)) expect_error( TaskRegr$new("test", data.table(`%^` = 1:3, t = 3:1), target = "t"), "comply" ) options(mlr3.allow_utf8_names = TRUE) expect_error( TaskRegr$new("test", data.table(`%asd` = 1:3, t = 3:1), target = "t") , "special character" ) }) test_that("head/tail", { task = tsk("iris") expect_data_table(head(task, n = 3), nrows = 3) expect_data_table(head(task, n = -3), nrows = task$nrow - 3) expect_data_table(tail(task, n = 3), nrows = 3) expect_data_table(tail(task, n = -3), nrows = task$nrow - 3) expect_data_table(head(task, n = Inf), nrows = 150) expect_data_table(tail(task, n = Inf), nrows = 150) expect_data_table(head(task, n = -Inf), nrows = 0) expect_data_table(tail(task, n = -Inf), nrows = 0) }) test_that("Roles get printed (#877)", { task = tsk("iris") task$col_roles$weight = "Petal.Width" expect_output(print(task), "Weights: Petal.Width") })