test: fix test_ResultAssignerArchive due to upcoming changes of internal tuned values in mlr3tuning 1.3.1

Author: sumny

NEWS.md

@@ -1,5 +1,9 @@
 # mlr3mbo (development version)
 
+* chore: silence rush logger and fixed some partial matches, depend on mlr3 >= 0.22.1.
+* test: fix `test_AcqFunctionMulti`, robustify helper and loading.
+* test: fix `test_ResultAssignerArchive` due to upcoming changes of internal tuned values in mlr3tuning 1.3.1
+
 # mlr3mbo 0.2.8
 
 * docs: gracefully exit examples of `OptimizerAsyncMbo`, `OptimizerADBO`, `TunerAsyncMbo`, and `TunerADBO` if Redis is not available.
@@ -15,22 +19,22 @@
 
 # mlr3mbo 0.2.6
 
-* refactor: Extract internal tuned values in instance.
+* refactor: extract internal tuned values in instance.
 
 # mlr3mbo 0.2.5
 
-* docs: Move vignette to mlr3book.
-* feat: Add `AcqFunctionMulti` that can wrap multiple acquisition functions resulting in a multi-objective acquisition function problem.
-* feat: Support callbacks in `AcqOptimizer`.
-* feat: Allow `AcqFunctionEI` to be adjusted by epsilon to strengthen exploration.
+* docs: move vignette to mlr3book.
+* feat: add `AcqFunctionMulti` that can wrap multiple acquisition functions resulting in a multi-objective acquisition function problem.
+* feat: support callbacks in `AcqOptimizer`.
+* feat: allow `AcqFunctionEI` to be adjusted by epsilon to strengthen exploration.
 
 # mlr3mbo 0.2.4
 
-* fix: Improve runtime of `AcqOptimizer` by setting `check_values = FALSE`.
+* fix: improve runtime of `AcqOptimizer` by setting `check_values = FALSE`.
 
 # mlr3mbo 0.2.3
 
-* compatibility: Work with new bbotk and mlr3tuning version 1.0.0.
+* compatibility: work with new bbotk and mlr3tuning version 1.0.0.
 
 # mlr3mbo 0.2.2
 
@@ -70,8 +74,8 @@
 # mlr3mbo 0.1.2
 
 * refactor: adapt to mlr3tuning 0.18.0.
-* feat: Acquisition functions now assert whether surrogates match their required predict type.
-* fix: Unloading `mlr3mbo` removes optimizers and tuners from the dictionaries.
+* feat: acquisition functions now assert whether surrogates match their required predict type.
+* fix: unloading `mlr3mbo` removes optimizers and tuners from the dictionaries.
 * docs: faster examples.
 * feat: characters in surrogate regression tasks are no longer automatically converted to factors.
         `default_surrogate` now respects this and gained an appropriate pipeline step.

tests/testthat/test_ResultAssignerArchive.R

@@ -61,24 +61,24 @@ test_that("ResultAssignerArchive passes internal tuned values", {
     validate = 0.2,
     early_stopping = TRUE,
     x = to_tune(0.2, 0.3),
-    iter = to_tune(upper = 1000, internal = TRUE, aggr = function(x) 99))
+    iter = to_tune(upper = 1000L, internal = TRUE, aggr = function(x) 99L))
 
   instance = ti(
     task = tsk("pima"),
     learner = learner,
-    resampling = rsmp("cv", folds = 3),
+    resampling = rsmp("cv", folds = 3L),
     measures = msr("classif.ce"),
-    terminator = trm("evals", n_evals = 20),
+    terminator = trm("evals", n_evals = 20L),
     store_benchmark_result = TRUE
   )
   surrogate = SurrogateLearner$new(REGR_KM_DETERM)
   acq_function = AcqFunctionEI$new()
   acq_optimizer = AcqOptimizer$new(opt("random_search", batch_size = 2L), terminator = trm("evals", n_evals = 2L))
 
   tuner = tnr("mbo", result_assigner = result_assigner)
-  expect_data_table(tuner$optimize(instance), nrows = 1)
-  expect_list(instance$archive$data$internal_tuned_values, len = 20, types = "list")
-  expect_equal(instance$archive$data$internal_tuned_values[[1]], list(iter = 99))
+  expect_data_table(tuner$optimize(instance), nrows = 1L)
+  expect_list(instance$archive$data$internal_tuned_values, len = 20L, types = "list")
+  expect_equal(instance$archive$data$internal_tuned_values[[1L]]$iter, 99L)
   expect_false(instance$result_learner_param_vals$early_stopping)
-  expect_equal(instance$result_learner_param_vals$iter, 99)
+  expect_equal(instance$result_learner_param_vals$iter, 99L)
 })