test_that("lgb.params2str() works as expected for empty lists", { out_str <- lgb.params2str( params = list() ) expect_identical(class(out_str), "character") expect_equal(out_str, "") }) test_that("lgb.params2str() works as expected for a key in params with multiple different-length elements", { metrics <- c("a", "ab", "abc", "abcdefg") params <- list( objective = "magic" , metric = metrics , nrounds = 10L , learning_rate = 0.0000001 ) out_str <- lgb.params2str( params = params ) expect_identical(class(out_str), "character") expect_identical( out_str , "objective=magic metric=a,ab,abc,abcdefg nrounds=10 learning_rate=0.0000001" ) }) test_that("lgb.params2str() passes through duplicated params", { out_str <- lgb.params2str( params = list( objective = "regression" , bagging_fraction = 0.8 , bagging_fraction = 0.5 # nolint: duplicate_argument ) ) expect_equal(out_str, "objective=regression bagging_fraction=0.8 bagging_fraction=0.5") }) test_that("lgb.check.eval works as expected with no metric", { params <- lgb.check.eval( params = list(device = "cpu") , eval = "binary_error" ) expect_named(params, c("device", "metric")) expect_identical(params[["metric"]], list("binary_error")) }) test_that("lgb.check.eval adds eval to metric in params", { params <- lgb.check.eval( params = list(metric = "auc") , eval = "binary_error" ) expect_named(params, "metric") expect_identical(params[["metric"]], list("auc", "binary_error")) }) test_that("lgb.check.eval adds eval to metric in params if two evaluation names are provided", { params <- lgb.check.eval( params = list(metric = "auc") , eval = c("binary_error", "binary_logloss") ) expect_named(params, "metric") expect_identical(params[["metric"]], list("auc", "binary_error", "binary_logloss")) }) test_that("lgb.check.eval adds eval to metric in params if a list is provided", { params <- lgb.check.eval( params = list(metric = "auc") , eval = list("binary_error", "binary_logloss") ) expect_named(params, "metric") expect_identical(params[["metric"]], list("auc", "binary_error", "binary_logloss")) }) test_that("lgb.check.eval drops duplicate metrics and preserves order", { params <- lgb.check.eval( params = list(metric = "l1") , eval = list("l2", "rmse", "l1", "rmse") ) expect_named(params, "metric") expect_identical(params[["metric"]], list("l1", "l2", "rmse")) }) test_that("lgb.check.wrapper_param() uses passed-in keyword arg if no alias found in params", { kwarg_val <- sample(seq_len(100L), size = 1L) params <- lgb.check.wrapper_param( main_param_name = "num_iterations" , params = list() , alternative_kwarg_value = kwarg_val ) expect_equal(params[["num_iterations"]], kwarg_val) }) test_that("lgb.check.wrapper_param() prefers main parameter to alias and keyword arg", { num_iterations <- sample(seq_len(100L), size = 1L) kwarg_val <- sample(seq_len(100L), size = 1L) params <- lgb.check.wrapper_param( main_param_name = "num_iterations" , params = list( num_iterations = num_iterations , num_tree = sample(seq_len(100L), size = 1L) , n_estimators = sample(seq_len(100L), size = 1L) ) , alternative_kwarg_value = kwarg_val ) expect_equal(params[["num_iterations"]], num_iterations) # aliases should be removed expect_identical(params, list(num_iterations = num_iterations)) }) test_that("lgb.check.wrapper_param() prefers alias to keyword arg", { n_estimators <- sample(seq_len(100L), size = 1L) num_tree <- sample(seq_len(100L), size = 1L) kwarg_val <- sample(seq_len(100L), size = 1L) params <- lgb.check.wrapper_param( main_param_name = "num_iterations" , params = list( num_tree = num_tree , n_estimators = n_estimators ) , alternative_kwarg_value = kwarg_val ) expect_equal(params[["num_iterations"]], num_tree) expect_identical(params, list(num_iterations = num_tree)) # switching the order should switch which one is chosen params2 <- lgb.check.wrapper_param( main_param_name = "num_iterations" , params = list( n_estimators = n_estimators , num_tree = num_tree ) , alternative_kwarg_value = kwarg_val ) expect_equal(params2[["num_iterations"]], n_estimators) expect_identical(params2, list(num_iterations = n_estimators)) })