diff --git a/R-package/tests/testthat/test_basic.R b/R-package/tests/testthat/test_basic.R index 3efa9a21777b..cbbb37e440cd 100644 --- a/R-package/tests/testthat/test_basic.R +++ b/R-package/tests/testthat/test_basic.R @@ -394,7 +394,7 @@ test_that("CVBooster$reset_parameter() works as expected", { , nrounds = 3L , nfold = n_folds ) - expect_is(cv_bst, "lgb.CVBooster") + expect_true(methods::is(cv_bst, "lgb.CVBooster")) expect_length(cv_bst$boosters, n_folds) for (bst in cv_bst$boosters) { expect_equal(bst[["booster"]]$params[["num_leaves"]], 7L) @@ -467,7 +467,7 @@ test_that("lightgbm.cv() gives the correct best_score and best_iter for a metric , num_leaves = 5L ) ) - expect_is(cv_bst, "lgb.CVBooster") + expect_true(methods::is(cv_bst, "lgb.CVBooster")) expect_named( cv_bst$record_evals , c("start_iter", "valid") @@ -505,7 +505,7 @@ test_that("lgb.cv() fit on linearly-relatead data improves when using linear lea , params = params , nfold = 5L ) - expect_is(cv_bst, "lgb.CVBooster") + expect_true(methods::is(cv_bst, "lgb.CVBooster")) dtrain <- .new_dataset() cv_bst_linear <- lgb.cv( @@ -514,7 +514,7 @@ test_that("lgb.cv() fit on linearly-relatead data improves when using linear lea , params = utils::modifyList(params, list(linear_tree = TRUE)) , nfold = 5L ) - expect_is(cv_bst_linear, "lgb.CVBooster") + expect_true(methods::is(cv_bst_linear, "lgb.CVBooster")) expect_true(cv_bst_linear$best_score < cv_bst$best_score) }) @@ -549,7 +549,7 @@ test_that("lgb.cv() respects showsd argument", { evals_showsd[["eval"]] , evals_no_showsd[["eval"]] ) - expect_is(evals_showsd[["eval_err"]], "list") + expect_true(methods::is(evals_showsd[["eval_err"]], "list")) expect_equal(length(evals_showsd[["eval_err"]]), nrounds) expect_identical(evals_no_showsd[["eval_err"]], list()) }) diff --git a/R-package/tests/testthat/test_dataset.R b/R-package/tests/testthat/test_dataset.R index 2fc41b28e2d2..6994bf3847b3 100644 --- a/R-package/tests/testthat/test_dataset.R +++ b/R-package/tests/testthat/test_dataset.R @@ -148,7 +148,10 @@ test_that("Dataset$set_reference() updates categorical_feature, colnames, and pr dtest$set_reference(dtrain) # after setting reference to dtrain, those attributes should have dtrain's values - expect_is(dtest$.__enclos_env__$private$predictor, "lgb.Predictor") + expect_true(methods::is( + dtest$.__enclos_env__$private$predictor + , "lgb.Predictor" + )) expect_identical( dtest$.__enclos_env__$private$predictor$.__enclos_env__$private$handle , dtrain$.__enclos_env__$private$predictor$.__enclos_env__$private$handle @@ -199,7 +202,7 @@ test_that("lgb.Dataset: Dataset should be able to construct from matrix and retu , lightgbm:::lgb.params2str(params = list()) , ref_handle ) - expect_is(handle, "externalptr") + expect_true(methods::is(handle, "externalptr")) expect_false(is.null(handle)) .Call(LGBM_DatasetFree_R, handle) handle <- NULL @@ -411,7 +414,7 @@ test_that("lgb.Dataset: should be able to run lgb.cv() immediately after using l , data = dtest_read_in ) - expect_is(bst, "lgb.CVBooster") + expect_true(methods::is(bst, "lgb.CVBooster")) }) test_that("lgb.Dataset: should be able to use and retrieve long feature names", { diff --git a/R-package/tests/testthat/test_learning_to_rank.R b/R-package/tests/testthat/test_learning_to_rank.R index 8a313d21065e..b560f30dcde7 100644 --- a/R-package/tests/testthat/test_learning_to_rank.R +++ b/R-package/tests/testthat/test_learning_to_rank.R @@ -94,7 +94,7 @@ test_that("learning-to-rank with lgb.cv() works as expected", { , nrounds = nrounds , nfold = nfold ) - expect_is(cv_bst, "lgb.CVBooster") + expect_true(methods::is(cv_bst, "lgb.CVBooster")) expect_equal(length(cv_bst$boosters), nfold) # "valid" should contain results for each metric diff --git a/R-package/tests/testthat/test_lgb.convert_with_rules.R b/R-package/tests/testthat/test_lgb.convert_with_rules.R index 546ab9663f4f..cf75fa542475 100644 --- a/R-package/tests/testthat/test_lgb.convert_with_rules.R +++ b/R-package/tests/testthat/test_lgb.convert_with_rules.R @@ -37,7 +37,7 @@ test_that("lgb.convert_with_rules() should work correctly for a dataset with onl expect_identical(converted_dataset[["col2"]], c(1L, 1L, 2L)) # rules should be returned and correct rules <- conversion_result$rules - expect_is(rules, "list") + expect_true(methods::is(rules, "list")) expect_length(rules, ncol(input_data)) expect_identical(rules[["col1"]], c("a" = 1L, "b" = 2L, "c" = 3L)) expect_identical(rules[["col2"]], c("green" = 1L, "red" = 2L)) @@ -62,7 +62,7 @@ test_that("lgb.convert_with_rules() should work correctly for a dataset with onl expect_identical(converted_dataset[["col2"]], c(1L, 1L, 2L)) # rules should be returned and correct rules <- conversion_result$rules - expect_is(rules, "list") + expect_true(methods::is(rules, "list")) expect_length(rules, ncol(input_data)) expect_identical(rules[["col1"]], c("a" = 1L, "b" = 2L, "c" = 3L)) expect_identical(rules[["col2"]], c("green" = 1L, "red" = 2L)) @@ -106,7 +106,7 @@ test_that("lgb.convert_with_rules() should work correctly for a dataset with num expect_identical(converted_dataset[["factor_col"]], c(1L, 1L, 2L)) # rules should be returned and correct rules <- conversion_result$rules - expect_is(rules, "list") + expect_true(methods::is(rules, "list")) expect_length(rules, 2L) expect_identical(rules[["character_col"]], c("a" = 1L, "b" = 2L, "c" = 3L)) expect_identical(rules[["factor_col"]], c("n" = 1L, "y" = 2L)) @@ -164,7 +164,7 @@ test_that("lgb.convert_with_rules() should convert missing values to the expecte # rules should be returned and correct rules <- conversion_result$rules - expect_is(rules, "list") + expect_true(methods::is(rules, "list")) expect_length(rules, 3L) expect_identical(rules[["character_col"]], c("a" = 1L, "c" = 2L)) expect_identical(rules[["factor_col"]], c("n" = 1L, "y" = 2L))