colroles tests respect new colroles constraints

mlr-org · Sep 6, 2024 · 65d1bdc · 65d1bdc
1 parent e9210c5
commit 65d1bdc
Showing 1 changed file with 6 additions and 4 deletions.
diff --git a/tests/testthat/test_pipeop_colroles.R b/tests/testthat/test_pipeop_colroles.R
@@ -18,7 +18,8 @@ test_that("PipeOpColRoles - assertion works", {
 
 test_that("PipeOpColRoles - name checking works", {
   task = mlr_tasks$get("iris")
-  op = PipeOpColRoles$new(param_vals = list(new_role = list(Petal.Length = "name", wrong = "feature")))
+  task$cbind(data.table(rn = sprintf("%03d", 1:150)))
+  op = PipeOpColRoles$new(param_vals = list(new_role = list(rn = "name", wrong = "feature")))
   expect_error(train_pipeop(op, inputs = list(task)), regexp = "subset")
 })
 
@@ -30,15 +31,16 @@ test_that("PipeOpColRoles - changing the role of a target fails", {
 
 test_that("PipeOpColRoles - functionality works", {
   task = mlr_tasks$get("iris")
-  op = PipeOpColRoles$new(param_vals = list(new_role = list(Petal.Length = c("name", "order"), Petal.Width = character(0))))
+  task$cbind(data.table(rn = sprintf("%03d", 1:150)))
+  op = PipeOpColRoles$new(param_vals = list(new_role = list(rn = "name", Petal.Length = "order", Petal.Width = character(0))))
   train_out = train_pipeop(op, inputs = list(task))$output
   col_roles_actual = train_out$col_roles
   col_roles_expected = list(
-    feature = c("Sepal.Length", "Sepal.Width"), target = "Species", name = "Petal.Length",
+    feature = c("Sepal.Length", "Sepal.Width"), target = "Species", name = "rn",
     order = "Petal.Length", stratum = character(0), group = character(0), weight = character(0))
   if ("weights_learner" %in% names(task)) names(col_roles_expected)[names(col_roles_expected) == "weight"] = "weights_learner"
   expect_equal(train_out$col_roles[names(col_roles_expected)], col_roles_expected)
-  expect_equal(train_out$row_names$row_name, task$data(cols = "Petal.Length")[[1L]])
+  expect_equal(train_out$row_names$row_name, task$data(cols = "rn")[[1L]])
   expect_true("Petal.Width" %nin% colnames(train_out$data()))
   predict_out = predict_pipeop(op, inputs = list(task))$output
   expect_equal(train_out, predict_out)