Last updated on 2025-12-28 01:48:44 CET.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 0.10.0 | 33.58 | 813.83 | 847.41 | OK | |
| r-devel-linux-x86_64-debian-gcc | 0.10.0 | 23.67 | 543.08 | 566.75 | ERROR | |
| r-devel-linux-x86_64-fedora-clang | 0.10.0 | 65.00 | 1323.65 | 1388.65 | OK | |
| r-devel-linux-x86_64-fedora-gcc | 0.10.0 | 64.00 | 1321.51 | 1385.51 | OK | |
| r-devel-windows-x86_64 | 0.10.0 | 39.00 | 466.00 | 505.00 | ERROR | |
| r-patched-linux-x86_64 | 0.10.0 | 52.24 | 701.38 | 753.62 | OK | |
| r-release-linux-x86_64 | 0.10.0 | 37.46 | 743.79 | 781.25 | OK | |
| r-release-macos-arm64 | 0.10.0 | OK | ||||
| r-release-macos-x86_64 | 0.10.0 | 26.00 | 542.00 | 568.00 | OK | |
| r-release-windows-x86_64 | 0.10.0 | 37.00 | 543.00 | 580.00 | OK | |
| r-oldrel-macos-arm64 | 0.10.0 | 8.00 | 129.00 | 137.00 | ERROR | |
| r-oldrel-macos-x86_64 | 0.10.0 | 25.00 | 1323.00 | 1348.00 | ERROR | |
| r-oldrel-windows-x86_64 | 0.10.0 | 51.00 | 648.00 | 699.00 | ERROR |
Version: 0.10.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [329s/162s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("checkmate")
+ library("testthat")
+ library("mlr3")
+ library("paradox")
+ library("mlr3pipelines")
+ test_check("mlr3pipelines")
+ }
Starting 2 test processes.
> test_Graph.R: Training debug.multi with input list(input_1 = 1, input_2 = 1)
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_filter_ensemble.R: OptimInstanceSingleCrit is deprecated. Use OptimInstanceBatchSingleCrit instead.
Saving _problems/test_filter_ensemble-294.R
Saving _problems/test_filter_ensemble-307.R
> test_mlr_graphs_robustify.R: 'as(<dgCMatrix>, "dgTMatrix")' is deprecated.
> test_mlr_graphs_robustify.R: Use 'as(., "TsparseMatrix")' instead.
> test_mlr_graphs_robustify.R: See help("Deprecated") and help("Matrix-depr
> test_mlr_graphs_robustify.R: ecated").
> test_multiplicities.R:
> test_multiplicities.R: [[1]]
> test_multiplicities.R: [1] 0
> test_multiplicities.R:
> test_multiplicities.R:
> test_pipeop_blsmote.R: [1] "Borderline-SMOTE done"
> test_pipeop_blsmote.R: [1] "Borderline-SMOTE done"
> test_pipeop_blsmote.R: [1] "Borderline-SMOTE done"
> test_pipeop_blsmote.R: [1] "Borderline-SMOTE done"
> test_pipeop_isomap.R: 2025-12-27 17:21:15.449727: Isomap START
> test_pipeop_isomap.R: 2025-12-27 17:21:15.450403: constructing knn graph
> test_pipeop_isomap.R: 2025-12-27 17:21:15.459408: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-27 17:21:15.474211: Classical Scaling
> test_pipeop_isomap.R: 2025-12-27 17:21:15.514549: Isomap START
> test_pipeop_isomap.R: 2025-12-27 17:21:15.514968: constructing knn graph
> test_pipeop_isomap.R: 2025-12-27 17:21:15.520957: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-27 17:21:15.534551: Classical Scaling
> test_pipeop_isomap.R: 2025-12-27 17:21:15.554304: L-Isomap embed START
> test_pipeop_isomap.R: 2025-12-27 17:21:15.554863: constructing knn graph
> test_pipeop_isomap.R: 2025-12-27 17:21:15.565743: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-27 17:21:15.596831: embedding
> test_pipeop_isomap.R: 2025-12-27 17:21:15.597968: DONE
> test_pipeop_isomap.R: 2025-12-27 17:21:15.622575: L-Isomap embed START
> test_pipeop_isomap.R: 2025-12-27 17:21:15.622982: constructing knn graph
> test_pipeop_isomap.R: 2025-12-27 17:21:15.633685: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-27 17:21:15.663729: embedding
> test_pipeop_isomap.R: 2025-12-27 17:21:15.664781: DONE
> test_pipeop_isomap.R: 2025-12-27 17:21:15.790927: Isomap START
> test_pipeop_isomap.R: 2025-12-27 17:21:15.791316: constructing knn graph
> test_pipeop_isomap.R: 2025-12-27 17:21:15.82302: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-27 17:21:15.897911: Classical Scaling
> test_pipeop_isomap.R: 2025-12-27 17:21:15.928091: L-Isomap embed START
> test_pipeop_isomap.R: 2025-12-27 17:21:15.928732: constructing knn graph
> test_pipeop_isomap.R: 2025-12-27 17:21:15.951565: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-27 17:21:16.124808: embedding
> test_pipeop_isomap.R: 2025-12-27 17:21:16.128435: DONE
> test_pipeop_isomap.R: 2025-12-27 17:21:16.243078: Isomap START
> test_pipeop_isomap.R: 2025-12-27 17:21:16.24349: constructing knn graph
> test_pipeop_isomap.R: 2025-12-27 17:21:16.249931: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-27 17:21:16.265122: Classical Scaling
> test_pipeop_isomap.R: 2025-12-27 17:21:16.291343: L-Isomap embed START
> test_pipeop_isomap.R: 2025-12-27 17:21:16.29195: constructing knn graph
> test_pipeop_isomap.R: 2025-12-27 17:21:16.303711: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-27 17:21:16.33422: embedding
> test_pipeop_isomap.R: 2025-12-27 17:21:16.33531: DONE
> test_pipeop_isomap.R: 2025-12-27 17:21:16.437757: Isomap START
> test_pipeop_isomap.R: 2025-12-27 17:21:16.438151: constructing knn graph
> test_pipeop_isomap.R: 2025-12-27 17:21:16.443948: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-27 17:21:16.457859: Classical Scaling
> test_pipeop_isomap.R: 2025-12-27 17:21:16.491935: L-Isomap embed START
> test_pipeop_isomap.R: 2025-12-27 17:21:16.492476: constructing knn graph
> test_pipeop_isomap.R: 2025-12-27 17:21:16.503186: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-27 17:21:16.534647: embedding
> test_pipeop_isomap.R: 2025-12-27 17:21:16.535629: DONE
> test_pipeop_isomap.R: 2025-12-27 17:21:16.597995: Isomap START
> test_pipeop_isomap.R: 2025-12-27 17:21:16.598359: constructing knn graph
> test_pipeop_isomap.R: 2025-12-27 17:21:16.60424: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-27 17:21:16.618195: Classical Scaling
> test_pipeop_isomap.R: 2025-12-27 17:21:16.652202: L-Isomap embed START
> test_pipeop_isomap.R: 2025-12-27 17:21:16.652748: constructing knn graph
> test_pipeop_isomap.R: 2025-12-27 17:21:16.662844: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-27 17:21:16.694351: embedding
> test_pipeop_isomap.R: 2025-12-27 17:21:16.695387: DONE
> test_pipeop_isomap.R: 2025-12-27 17:21:16.754731: Isomap START
> test_pipeop_isomap.R: 2025-12-27 17:21:16.755148: constructing knn graph
> test_pipeop_isomap.R: 2025-12-27 17:21:16.762564: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-27 17:21:16.77637: Classical Scaling
> test_pipeop_isomap.R: 2025-12-27 17:21:16.811532: L-Isomap embed START
> test_pipeop_isomap.R: 2025-12-27 17:21:16.812068: constructing knn graph
> test_pipeop_isomap.R: 2025-12-27 17:21:16.823118: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-27 17:21:16.853851: embedding
> test_pipeop_isomap.R: 2025-12-27 17:21:16.854875: DONE
> test_pipeop_isomap.R: 2025-12-27 17:21:16.921438: Isomap START
> test_pipeop_isomap.R: 2025-12-27 17:21:16.921849: constructing knn graph
> test_pipeop_isomap.R: 2025-12-27 17:21:16.928111: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-27 17:21:16.942044: Classical Scaling
> test_pipeop_isomap.R: 2025-12-27 17:21:16.980028: L-Isomap embed START
> test_pipeop_isomap.R: 2025-12-27 17:21:16.980621: constructing knn graph
> test_pipeop_isomap.R: 2025-12-27 17:21:16.991856: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-27 17:21:17.023593: embedding
> test_pipeop_isomap.R: 2025-12-27 17:21:17.024626: DONE
> test_pipeop_isomap.R: 2025-12-27 17:21:17.092299: Isomap START
> test_pipeop_isomap.R: 2025-12-27 17:21:17.092711: constructing knn graph
> test_pipeop_isomap.R: 2025-12-27 17:21:17.098637: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-27 17:21:17.112513: Classical Scaling
> test_pipeop_isomap.R: 2025-12-27 17:21:17.179568: Isomap START
> test_pipeop_isomap.R: 2025-12-27 17:21:17.179985: constructing knn graph
> test_pipeop_isomap.R: 2025-12-27 17:21:17.199059: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-27 17:21:17.212853: Classical Scaling
> test_pipeop_isomap.R: 2025-12-27 17:21:17.232709: Isomap START
> test_pipeop_isomap.R: 2025-12-27 17:21:17.233065: constructing knn graph
> test_pipeop_isomap.R: 2025-12-27 17:21:17.238083: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-27 17:21:17.251782: Classical Scaling
> test_pipeop_nmf.R: [PipeOpNMFstate]
> test_pipeop_nmf.R: [PipeOpNMFstate]
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_textvectorizer.R: 'as(<dgCMatrix>, "dgTMatrix")' is deprecated.
> test_pipeop_textvectorizer.R: Use 'as(., "TsparseMatrix")' instead.
> test_pipeop_textvectorizer.R: See help("Deprecated") and help("Matrix-deprecated").
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R:
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_tunethreshold.R: OptimInstanceSingleCrit is deprecated. Use OptimInstanceBatchSingleCrit instead.
> test_pipeop_tunethreshold.R: OptimInstanceSingleCrit is deprecated. Use OptimInstanceBatchSingleCrit instead.
> test_pipeop_tunethreshold.R: OptimInstanceSingleCrit is deprecated. Use OptimInstanceBatchSingleCrit instead.
> test_pipeop_tunethreshold.R: OptimInstanceSingleCrit is deprecated. Use OptimInstanceBatchSingleCrit instead.
> test_pipeop_tunethreshold.R: OptimInstanceSingleCrit is deprecated. Use OptimInstanceBatchSingleCrit instead.
> test_pipeop_tunethreshold.R: OptimInstanceSingleCrit is deprecated. Use OptimInstanceBatchSingleCrit instead.
> test_pipeop_tunethreshold.R: OptimInstanceSingleCrit is deprecated. Use OptimInstanceBatchSingleCrit instead.
[ FAIL 2 | WARN 0 | SKIP 100 | PASS 13055 ]
══ Skipped tests (100) ═════════════════════════════════════════════════════════
• On CRAN (96): 'test_CnfFormula_simplify.R:6:3', 'test_CnfFormula.R:591:3',
'test_Graph.R:283:3', 'test_PipeOp.R:32:1', 'test_GraphLearner.R:5:3',
'test_GraphLearner.R:221:3', 'test_GraphLearner.R:343:3',
'test_GraphLearner.R:408:3', 'test_GraphLearner.R:571:3',
'test_dictionary.R:7:3', 'test_learner_weightedaverage.R:5:3',
'test_learner_weightedaverage.R:57:3',
'test_learner_weightedaverage.R:105:3',
'test_learner_weightedaverage.R:152:3', 'test_meta.R:39:3',
'test_mlr_graphs_branching.R:26:3', 'test_mlr_graphs_bagging.R:6:3',
'test_mlr_graphs_robustify.R:5:3', 'test_pipeop_adas.R:8:3',
'test_pipeop_blsmote.R:8:3', 'test_pipeop_branch.R:4:3',
'test_pipeop_chunk.R:4:3', 'test_pipeop_classbalancing.R:7:3',
'test_pipeop_classweights.R:10:3', 'test_pipeop_boxcox.R:7:3',
'test_pipeop_collapsefactors.R:6:3', 'test_pipeop_colapply.R:9:3',
'test_pipeop_copy.R:5:3', 'test_pipeop_colroles.R:6:3',
'test_pipeop_decode.R:14:3', 'test_pipeop_encode.R:21:3',
'test_pipeop_datefeatures.R:10:3', 'test_pipeop_encodeimpact.R:11:3',
'test_pipeop_encodepl.R:5:3', 'test_pipeop_encodepl.R:72:3',
'test_pipeop_encodelmer.R:15:3', 'test_pipeop_encodelmer.R:37:3',
'test_pipeop_encodelmer.R:80:3', 'test_pipeop_featureunion.R:9:3',
'test_pipeop_featureunion.R:134:3', 'test_pipeop_filter.R:7:3',
'test_pipeop_fixfactors.R:9:3', 'test_pipeop_histbin.R:7:3',
'test_pipeop_ica.R:7:3', 'test_pipeop_ensemble.R:6:3',
'test_pipeop_imputelearner.R:43:3', 'test_pipeop_impute.R:4:3',
'test_pipeop_isomap.R:10:3', 'test_pipeop_kernelpca.R:9:3',
'test_pipeop_learner.R:17:3', 'test_pipeop_info.R:6:3',
'test_pipeop_learnerpicvplus.R:163:3', 'test_pipeop_learnercv.R:31:3',
'test_pipeop_modelmatrix.R:7:3', 'test_pipeop_missind.R:6:3',
'test_pipeop_multiplicityexply.R:9:3', 'test_pipeop_mutate.R:9:3',
'test_pipeop_nearmiss.R:7:3', 'test_pipeop_multiplicityimply.R:9:3',
'test_pipeop_ovr.R:9:3', 'test_pipeop_ovr.R:48:3', 'test_pipeop_pca.R:8:3',
'test_pipeop_proxy.R:14:3', 'test_pipeop_quantilebin.R:5:3',
'test_pipeop_randomprojection.R:6:3', 'test_pipeop_randomresponse.R:5:3',
'test_pipeop_removeconstants.R:6:3', 'test_pipeop_renamecolumns.R:6:3',
'test_pipeop_replicate.R:9:3', 'test_pipeop_rowapply.R:6:3',
'test_pipeop_scale.R:6:3', 'test_pipeop_scale.R:10:3',
'test_pipeop_scalemaxabs.R:6:3', 'test_pipeop_scalerange.R:7:3',
'test_pipeop_select.R:9:3', 'test_pipeop_smote.R:10:3',
'test_pipeop_smotenc.R:8:3', 'test_pipeop_nmf.R:6:3',
'test_pipeop_spatialsign.R:6:3', 'test_pipeop_targetinvert.R:4:3',
'test_pipeop_targetmutate.R:5:3', 'test_pipeop_targettrafo.R:4:3',
'test_pipeop_subsample.R:6:3', 'test_pipeop_targettrafoscalerange.R:5:3',
'test_pipeop_task_preproc.R:4:3', 'test_pipeop_task_preproc.R:14:3',
'test_pipeop_tomek.R:7:3', 'test_pipeop_textvectorizer.R:37:3',
'test_pipeop_textvectorizer.R:186:3', 'test_pipeop_unbranch.R:10:3',
'test_pipeop_updatetarget.R:89:3', 'test_pipeop_vtreat.R:9:3',
'test_pipeop_yeojohnson.R:7:3', 'test_pipeop_tunethreshold.R:111:3',
'test_pipeop_tunethreshold.R:191:3', 'test_typecheck.R:188:3'
• Skipping (1): 'test_GraphLearner.R:1278:3'
• empty test (3): 'test_pipeop_isomap.R:111:1', 'test_pipeop_missind.R:101:1',
'test_ppl.R:61:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Failure ('test_filter_ensemble.R:294:3'): FilterEnsemble ignores NA scores from wrapped filters ──
Expected `all(is.nan(permutation_filter$scores[task$feature_names]))` to be TRUE.
Differences:
`actual`: FALSE
`expected`: TRUE
── Failure ('test_filter_ensemble.R:307:3'): FilterEnsemble ignores NA scores from wrapped filters ──
Expected `all.equal(object, expected, check.environment = FALSE, ...)` to be TRUE.
Differences:
`actual` is a character vector ('Mean relative difference: 0.5383785')
`expected` is a logical vector (TRUE)
Backtrace:
▆
1. └─global expect_equal(combined_scores, variance_scores * weights[["variance"]]) at test_filter_ensemble.R:307:3
2. └─testthat::expect_true(...)
[ FAIL 2 | WARN 0 | SKIP 100 | PASS 13055 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 0.10.0
Check: examples
Result: ERROR
Running examples in 'mlr3pipelines-Ex.R' failed
The error most likely occurred in:
> ### Name: mlr_graphs_stacking
> ### Title: Create A Graph to Perform Stacking.
> ### Aliases: mlr_graphs_stacking pipeline_stacking
>
> ### ** Examples
>
> ## Don't show:
> if (mlr3misc::require_namespaces("rpart", quietly = TRUE)) withAutoprint({ # examplesIf
+ ## End(Don't show)
+ library(mlr3)
+ library(mlr3learners)
+
+ base_learners = list(
+ lrn("classif.rpart", predict_type = "prob"),
+ lrn("classif.nnet", predict_type = "prob")
+ )
+ super_learner = lrn("classif.log_reg")
+
+ graph_stack = pipeline_stacking(base_learners, super_learner)
+ graph_learner = as_learner(graph_stack)
+ graph_learner$train(tsk("german_credit"))
+ ## Don't show:
+ }) # examplesIf
> library(mlr3)
> library(mlr3learners)
> base_learners = list(lrn("classif.rpart", predict_type = "prob"), lrn("classif.nnet",
+ predict_type = "prob"))
> super_learner = lrn("classif.log_reg")
> graph_stack = pipeline_stacking(base_learners, super_learner)
> graph_learner = as_learner(graph_stack)
> graph_learner$train(tsk("german_credit"))
INFO [17:12:37.279] [mlr3] Resampling 'cv' is being instantiated on task 'german_credit'
INFO [17:12:37.420] [mlr3] Applying learner 'classif.rpart' on task 'german_credit' (iter 1/3)
INFO [17:12:37.493] [mlr3] Applying learner 'classif.rpart' on task 'german_credit' (iter 2/3)
INFO [17:12:37.529] [mlr3] Applying learner 'classif.rpart' on task 'german_credit' (iter 3/3)
Error in `[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash") :
attempt access index 9/9 in VECTOR_ELT
This happened in PipeOp classif.rpart's $train()
Calls: withAutoprint ... .__ResultData__initialize -> [ -> [.data.table -> .handleSimpleError -> h
Execution halted
Flavor: r-devel-windows-x86_64
Version: 0.10.0
Check: tests
Result: ERROR
Running 'testthat.R' [171s]
Running the tests in 'tests/testthat.R' failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("checkmate")
+ library("testthat")
+ library("mlr3")
+ library("paradox")
+ library("mlr3pipelines")
+ test_check("mlr3pipelines")
+ }
Starting 2 test processes.
> test_Graph.R: Training debug.multi with input list(input_1 = 1, input_2 = 1)
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R:
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
Saving _problems/test_conversion-143.R
Saving _problems/test_conversion-165.R
> test_filter_ensemble.R: OptimInstanceSingleCrit is deprecated. Use OptimInstanceBatchSingleCrit instead.
Saving _problems/test_filter_ensemble-291.R
Saving _problems/test_filter_ensemble-447.R
Saving _problems/test_mlr_graphs_bagging-49.R
Saving _problems/test_mlr_graphs_stacking-16.R
> test_mlr_graphs_robustify.R: 'as(<dgCMatrix>, "dgTMatrix")' is deprecated.
> test_mlr_graphs_robustify.R: Use 'as(., "TsparseMatrix")' instead.
> test_mlr_graphs_robustify.R: See help("Deprecated") and help("Matrix-deprecated").
> test_multiplicities.R:
> test_multiplicities.R:
> test_multiplicities.R: [[1]]
> test_multiplicities.R: [1] 0
> test_multiplicities.R:
> test_pipeop_blsmote.R: [1] "Borderline-SMOTE done"
> test_pipeop_blsmote.R: [1] "Borderline-SMOTE done"
> test_pipeop_blsmote.R: [1] "Borderline-SMOTE done"
> test_pipeop_blsmote.R: [1] "Borderline-SMOTE done"
> test_pipeop_isomap.R: 2025-12-24 17:13:55.612832: Isomap START
> test_pipeop_isomap.R: 2025-12-24 17:13:55.613655: constructing knn graph
> test_pipeop_isomap.R: 2025-12-24 17:13:55.625629: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-24 17:13:55.645388: Classical Scaling
> test_pipeop_isomap.R: 2025-12-24 17:13:55.69406: Isomap START
> test_pipeop_isomap.R: 2025-12-24 17:13:55.694632: constructing knn graph
> test_pipeop_isomap.R: 2025-12-24 17:13:55.701462: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-24 17:13:55.717804: Classical Scaling
> test_pipeop_isomap.R: 2025-12-24 17:13:55.74954: L-Isomap embed START
> test_pipeop_isomap.R: 2025-12-24 17:13:55.750264: constructing knn graph
> test_pipeop_isomap.R: 2025-12-24 17:13:55.769375: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-24 17:13:55.814251: embedding
> test_pipeop_isomap.R: 2025-12-24 17:13:55.815744: DONE
> test_pipeop_isomap.R: 2025-12-24 17:13:55.842133: L-Isomap embed START
> test_pipeop_isomap.R: 2025-12-24 17:13:55.842642: constructing knn graph
> test_pipeop_isomap.R: 2025-12-24 17:13:55.860334: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-24 17:13:55.904064: embedding
> test_pipeop_isomap.R: 2025-12-24 17:13:55.905769: DONE
> test_pipeop_isomap.R: 2025-12-24 17:13:56.005005: Isomap START
> test_pipeop_isomap.R: 2025-12-24 17:13:56.005534: constructing knn graph
> test_pipeop_isomap.R: 2025-12-24 17:13:56.02579: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-24 17:13:56.141048: Classical Scaling
> test_pipeop_isomap.R: 2025-12-24 17:13:56.189765: L-Isomap embed START
> test_pipeop_isomap.R: 2025-12-24 17:13:56.190404: constructing knn graph
> test_pipeop_isomap.R: 2025-12-24 17:13:56.214621: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-24 17:13:56.399302: embedding
> test_pipeop_isomap.R: 2025-12-24 17:13:56.40287: DONE
> test_pipeop_isomap.R: 2025-12-24 17:13:56.538362: Isomap START
> test_pipeop_isomap.R: 2025-12-24 17:13:56.538743: constructing knn graph
> test_pipeop_isomap.R: 2025-12-24 17:13:56.543986: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-24 17:13:56.556913: Classical Scaling
> test_pipeop_isomap.R: 2025-12-24 17:13:56.587082: L-Isomap embed START
> test_pipeop_isomap.R: 2025-12-24 17:13:56.587786: constructing knn graph
> test_pipeop_isomap.R: 2025-12-24 17:13:56.60268: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-24 17:13:56.645191: embedding
> test_pipeop_isomap.R: 2025-12-24 17:13:56.646387: DONE
> test_pipeop_isomap.R: 2025-12-24 17:13:56.769397: Isomap START
> test_pipeop_isomap.R: 2025-12-24 17:13:56.769779: constructing knn graph
> test_pipeop_isomap.R: 2025-12-24 17:13:56.775735: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-24 17:13:56.790188: Classical Scaling
> test_pipeop_isomap.R: 2025-12-24 17:13:56.828514: L-Isomap embed START
> test_pipeop_isomap.R: 2025-12-24 17:13:56.829004: constructing knn graph
> test_pipeop_isomap.R: 2025-12-24 17:13:56.843064: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-24 17:13:56.881509: embedding
> test_pipeop_isomap.R: 2025-12-24 17:13:56.890602: DONE
> test_pipeop_isomap.R: 2025-12-24 17:13:56.971269: Isomap START
> test_pipeop_isomap.R: 2025-12-24 17:13:56.971823: constructing knn graph
> test_pipeop_isomap.R: 2025-12-24 17:13:56.980644: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-24 17:13:57.001431: Classical Scaling
> test_pipeop_isomap.R: 2025-12-24 17:13:57.053573: L-Isomap embed START
> test_pipeop_isomap.R: 2025-12-24 17:13:57.054248: constructing knn graph
> test_pipeop_isomap.R: 2025-12-24 17:13:57.068706: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-24 17:13:57.11281: embedding
> test_pipeop_isomap.R: 2025-12-24 17:13:57.113938: DONE
> test_pipeop_isomap.R: 2025-12-24 17:13:57.191203: Isomap START
> test_pipeop_isomap.R: 2025-12-24 17:13:57.191909: constructing knn graph
> test_pipeop_isomap.R: 2025-12-24 17:13:57.202773: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-24 17:13:57.223766: Classical Scaling
> test_pipeop_isomap.R: 2025-12-24 17:13:57.280651: L-Isomap embed START
> test_pipeop_isomap.R: 2025-12-24 17:13:57.281372: constructing knn graph
> test_pipeop_isomap.R: 2025-12-24 17:13:57.301767: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-24 17:13:57.355475: embedding
> test_pipeop_isomap.R: 2025-12-24 17:13:57.357042: DONE
> test_pipeop_isomap.R: 2025-12-24 17:13:57.448109: Isomap START
> test_pipeop_isomap.R: 2025-12-24 17:13:57.448778: constructing knn graph
> test_pipeop_isomap.R: 2025-12-24 17:13:57.459609: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-24 17:13:57.477791: Classical Scaling
> test_pipeop_isomap.R: 2025-12-24 17:13:57.535437: L-Isomap embed START
> test_pipeop_isomap.R: 2025-12-24 17:13:57.53623: constructing knn graph
> test_pipeop_isomap.R: 2025-12-24 17:13:57.556421: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-24 17:13:57.595287: embedding
> test_pipeop_isomap.R: 2025-12-24 17:13:57.59658: DONE
> test_pipeop_isomap.R: 2025-12-24 17:13:57.678123: Isomap START
> test_pipeop_isomap.R: 2025-12-24 17:13:57.678466: constructing knn graph
> test_pipeop_isomap.R: 2025-12-24 17:13:57.691609: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-24 17:13:57.708099: Classical Scaling
> test_pipeop_isomap.R: 2025-12-24 17:13:57.767787: Isomap START
> test_pipeop_isomap.R: 2025-12-24 17:13:57.768299: constructing knn graph
> test_pipeop_isomap.R: 2025-12-24 17:13:57.775576: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-24 17:13:57.788739: Classical Scaling
> test_pipeop_isomap.R: 2025-12-24 17:13:57.805722: Isomap START
> test_pipeop_isomap.R: 2025-12-24 17:13:57.806079: constructing knn graph
> test_pipeop_isomap.R: 2025-12-24 17:13:57.811284: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-24 17:13:57.824532: Classical Scaling
Saving _problems/test_pipeop_learnerpicvplus-35.R
Saving _problems/test_pipeop_learnerpicvplus-91.R
Saving _problems/test_pipeop_learnerpicvplus-116.R
Saving _problems/test_pipeop_learnerpicvplus-130.R
Saving _problems/test_pipeop_learnerpicvplus-152.R
Saving _problems/test_pipeop_learnercv-11.R
Saving _problems/test_pipeop_learnercv-100.R
Saving _problems/test_pipeop_learnercv-139.R
Saving _problems/test_pipeop_learnercv-152.R
Saving _problems/test_pipeop_learnercv-203.R
Saving _problems/test_pipeop_learnercv-250.R
Saving _problems/test_pipeop_learnercv-278.R
Saving _problems/test_pipeop_learnercv-323.R
Saving _problems/test_pipeop_learnercv-350.R
Saving _problems/test_pipeop_learnercv-387.R
Saving _problems/test_pipeop_learnercv-419.R
Saving _problems/test_pipeop_learnercv-455.R
Saving _problems/test_pipeop_learnercv-493.R
Saving _problems/test_pipeop_learnercv-516.R
Saving _problems/test_pipeop_learnercv-531.R
Saving _problems/test_pipeop_learnercv-557.R
Saving _problems/test_pipeop_learnercv-612.R
Saving _problems/test_pipeop_learnercv-628.R
Saving _problems/test_pipeop_learnercv-671.R
> test_pipeop_nmf.R: [PipeOpNMFstate]
> test_pipeop_nmf.R: [PipeOpNMFstate]
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
Saving _problems/test_pipeop_tunethreshold-7.R
Saving _problems/test_pipeop_tunethreshold-38.R
Saving _problems/test_pipeop_tunethreshold-73.R
Saving _problems/test_pipeop_tunethreshold-101.R
Saving _problems/test_pipeop_tunethreshold-260.R
Saving _problems/test_resample-13.R
Saving _problems/test_usecases-153.R
Saving _problems/test_ppl-73.R
[ FAIL 38 | WARN 2 | SKIP 98 | PASS 12316 ]
══ Skipped tests (98) ══════════════════════════════════════════════════════════
• On CRAN (95): 'test_CnfFormula_simplify.R:6:3', 'test_CnfFormula.R:591:3',
'test_Graph.R:283:3', 'test_PipeOp.R:32:1', 'test_GraphLearner.R:5:3',
'test_GraphLearner.R:221:3', 'test_GraphLearner.R:343:3',
'test_GraphLearner.R:408:3', 'test_GraphLearner.R:571:3',
'test_dictionary.R:7:3', 'test_learner_weightedaverage.R:5:3',
'test_learner_weightedaverage.R:57:3',
'test_learner_weightedaverage.R:105:3',
'test_learner_weightedaverage.R:152:3', 'test_meta.R:39:3',
'test_mlr_graphs_bagging.R:6:3', 'test_mlr_graphs_branching.R:26:3',
'test_mlr_graphs_robustify.R:5:3', 'test_pipeop_adas.R:8:3',
'test_pipeop_blsmote.R:8:3', 'test_pipeop_branch.R:4:3',
'test_pipeop_chunk.R:4:3', 'test_pipeop_classbalancing.R:7:3',
'test_pipeop_boxcox.R:7:3', 'test_pipeop_classweights.R:10:3',
'test_pipeop_collapsefactors.R:6:3', 'test_pipeop_colapply.R:9:3',
'test_pipeop_copy.R:5:3', 'test_pipeop_colroles.R:6:3',
'test_pipeop_decode.R:14:3', 'test_pipeop_encode.R:21:3',
'test_pipeop_encodeimpact.R:11:3', 'test_pipeop_datefeatures.R:10:3',
'test_pipeop_encodepl.R:5:3', 'test_pipeop_encodepl.R:72:3',
'test_pipeop_encodelmer.R:15:3', 'test_pipeop_encodelmer.R:37:3',
'test_pipeop_encodelmer.R:80:3', 'test_pipeop_featureunion.R:9:3',
'test_pipeop_featureunion.R:134:3', 'test_pipeop_filter.R:7:3',
'test_pipeop_fixfactors.R:9:3', 'test_pipeop_histbin.R:7:3',
'test_pipeop_ica.R:7:3', 'test_pipeop_ensemble.R:6:3',
'test_pipeop_imputelearner.R:43:3', 'test_pipeop_impute.R:4:3',
'test_pipeop_isomap.R:10:3', 'test_pipeop_kernelpca.R:9:3',
'test_pipeop_learner.R:17:3', 'test_pipeop_info.R:6:3',
'test_pipeop_learnerpicvplus.R:163:3', 'test_pipeop_missind.R:6:3',
'test_pipeop_modelmatrix.R:7:3', 'test_pipeop_multiplicityexply.R:9:3',
'test_pipeop_mutate.R:9:3', 'test_pipeop_nearmiss.R:7:3',
'test_pipeop_multiplicityimply.R:9:3', 'test_pipeop_ovr.R:9:3',
'test_pipeop_ovr.R:48:3', 'test_pipeop_pca.R:8:3',
'test_pipeop_proxy.R:14:3', 'test_pipeop_quantilebin.R:5:3',
'test_pipeop_randomprojection.R:6:3', 'test_pipeop_randomresponse.R:5:3',
'test_pipeop_removeconstants.R:6:3', 'test_pipeop_renamecolumns.R:6:3',
'test_pipeop_replicate.R:9:3', 'test_pipeop_rowapply.R:6:3',
'test_pipeop_scale.R:6:3', 'test_pipeop_scale.R:10:3',
'test_pipeop_scalemaxabs.R:6:3', 'test_pipeop_scalerange.R:7:3',
'test_pipeop_select.R:9:3', 'test_pipeop_smote.R:10:3',
'test_pipeop_smotenc.R:8:3', 'test_pipeop_nmf.R:6:3',
'test_pipeop_subsample.R:6:3', 'test_pipeop_targetinvert.R:4:3',
'test_pipeop_spatialsign.R:6:3', 'test_pipeop_targetmutate.R:5:3',
'test_pipeop_targettrafo.R:4:3', 'test_pipeop_targettrafoscalerange.R:5:3',
'test_pipeop_task_preproc.R:4:3', 'test_pipeop_task_preproc.R:14:3',
'test_pipeop_tomek.R:7:3', 'test_pipeop_tunethreshold.R:111:3',
'test_pipeop_tunethreshold.R:191:3', 'test_pipeop_unbranch.R:10:3',
'test_pipeop_textvectorizer.R:37:3', 'test_pipeop_textvectorizer.R:186:3',
'test_pipeop_vtreat.R:9:3', 'test_pipeop_updatetarget.R:89:3',
'test_pipeop_yeojohnson.R:7:3', 'test_typecheck.R:188:3'
• Skipping (1): 'test_GraphLearner.R:1278:3'
• empty test (2): 'test_pipeop_isomap.R:111:1', 'test_pipeop_missind.R:101:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_conversion.R:143:3'): Graph to GraphLearner ────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, glrn1, cv) at test_conversion.R:143:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_conversion.R:165:3'): PipeOp to GraphLearner ───────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, glrn1, cv) at test_conversion.R:165:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_filter_ensemble.R:291:3'): FilterEnsemble ignores NA scores from wrapped filters ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─permutation_filter$calculate(task) at test_filter_ensemble.R:291:3
2. └─mlr3filters:::.__Filter__calculate(...)
3. └─private$.calculate(task, nfeat)
4. └─mlr3filters:::.__FilterPermutation__.calculate(...)
5. └─mlr3::resample(task, self$learner, self$resampling)
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test_filter_ensemble.R:447:7'): FilterEnsemble weight search space works with bbotk ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─optimizer$optimize(instance) at test_filter_ensemble.R:463:3
2. └─bbotk:::.__OptimizerBatch__optimize(...)
3. └─bbotk::optimize_batch_default(inst, self)
4. ├─base::tryCatch(...)
5. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
6. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
7. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
8. └─get_private(optimizer)$.optimize(instance)
9. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
10. └─inst$eval_batch(design$data)
11. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
12. └─self$objective$eval_many(xss_trafoed)
13. └─bbotk:::.__Objective__eval_many(...)
14. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
15. │ └─base::eval.parent(expr, n = 1L)
16. │ └─base::eval(expr, p)
17. │ └─base::eval(expr, p)
18. └─private$.eval_many(xss = xss)
19. └─bbotk:::.__Objective__.eval_many(...)
20. └─mlr3misc::map_dtr(...)
21. ├─data.table::rbindlist(...)
22. ├─base::unname(map(.x, .f, ...))
23. └─mlr3misc::map(.x, .f, ...)
24. └─base::lapply(.x, .f, ...)
25. └─bbotk (local) FUN(X[[i]], ...)
26. └─self$eval(xs)
27. └─bbotk:::.__ObjectiveRFun__eval(...)
28. ├─mlr3misc::invoke(private$.fun, xs, .args = self$constants$values)
29. │ └─base::eval.parent(expr, n = 1L)
30. │ └─base::eval(expr, p)
31. │ └─base::eval(expr, p)
32. └─private$.fun(xs)
33. └─mlr3::resample(task, learner, resampling) at test_filter_ensemble.R:447:7
34. └─ResultData$new(data, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_graphs_bagging.R:49:3'): Bagging with replacement ──────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(tsk, GraphLearner$new(p), rsmp("holdout")) at test_mlr_graphs_bagging.R:49:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_graphs_stacking.R:16:3'): Stacking Pipeline ────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
This happened in PipeOp base.rpart's $train()
Backtrace:
▆
1. ├─graph_learner$train(tsk("iris")) at test_mlr_graphs_stacking.R:16:3
2. │ └─mlr3:::.__Learner__train(...)
3. │ └─mlr3:::learner_train(...)
4. │ └─mlr3misc::encapsulate(...)
5. │ ├─mlr3misc::invoke(...)
6. │ │ └─base::eval.parent(expr, n = 1L)
7. │ │ └─base::eval(expr, p)
8. │ │ └─base::eval(expr, p)
9. │ └─mlr3 (local) .f(learner = `<GrphLrnr>`, task = `<TskClssf>`)
10. │ └─get_private(learner)$.train(task)
11. │ └─mlr3pipelines:::.__GraphLearner__.train(...)
12. │ └─self$graph$train(task)
13. │ └─mlr3pipelines:::.__Graph__train(...)
14. │ └─mlr3pipelines:::graph_reduce(self, input, "train", single_input)
15. │ └─op[[fun]](input)
16. │ └─mlr3pipelines:::.__PipeOp__train(...)
17. │ ├─base::withCallingHandlers(...)
18. │ └─private$.train(input)
19. │ └─mlr3pipelines:::.__PipeOpTaskPreproc__.train(...)
20. │ └─private$.train_task(intask)
21. │ └─mlr3pipelines:::.__PipeOpLearnerCV__.train_task(...)
22. │ └─mlr3::resample(...)
23. │ └─ResultData$new(data, data_extra, store_backends = store_backends)
24. │ └─mlr3 (local) initialize(...)
25. │ └─mlr3:::.__ResultData__initialize(...)
26. │ ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. │ └─data.table:::`[.data.table`(...)
28. └─base::.handleSimpleError(...)
29. └─mlr3pipelines (local) h(simpleError(msg, call))
── Error ('test_pipeop_learnerpicvplus.R:35:3'): PipeOpLearnerPICVPlus - basic properties ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
This happened in PipeOp regr.featureless's $train()
Backtrace:
▆
1. ├─global train_pipeop(po, list(task)) at test_pipeop_learnerpicvplus.R:35:3
2. │ └─po$train(inputs)
3. │ └─mlr3pipelines:::.__PipeOp__train(...)
4. │ ├─base::withCallingHandlers(...)
5. │ └─private$.train(input)
6. │ └─mlr3pipelines:::.__PipeOpLearnerPICVPlus__.train(...)
7. │ └─mlr3::resample(task, private$.learner, rdesc, store_models = TRUE)
8. │ └─ResultData$new(data, data_extra, store_backends = store_backends)
9. │ └─mlr3 (local) initialize(...)
10. │ └─mlr3:::.__ResultData__initialize(...)
11. │ ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
12. │ └─data.table:::`[.data.table`(...)
13. └─base::.handleSimpleError(...)
14. └─mlr3pipelines (local) h(simpleError(msg, call))
── Error ('test_pipeop_learnerpicvplus.R:91:3'): PipeOpLearnerPICVPlus - model active binding to state ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
This happened in PipeOp regr.featureless's $train()
Backtrace:
▆
1. ├─po$train(list(task)) at test_pipeop_learnerpicvplus.R:91:3
2. │ └─mlr3pipelines:::.__PipeOp__train(...)
3. │ ├─base::withCallingHandlers(...)
4. │ └─private$.train(input)
5. │ └─mlr3pipelines:::.__PipeOpLearnerPICVPlus__.train(...)
6. │ └─mlr3::resample(task, private$.learner, rdesc, store_models = TRUE)
7. │ └─ResultData$new(data, data_extra, store_backends = store_backends)
8. │ └─mlr3 (local) initialize(...)
9. │ └─mlr3:::.__ResultData__initialize(...)
10. │ ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
11. │ └─data.table:::`[.data.table`(...)
12. └─base::.handleSimpleError(...)
13. └─mlr3pipelines (local) h(simpleError(msg, call))
── Error ('test_pipeop_learnerpicvplus.R:116:3'): PipeOpLearnerPICVPlus - integration with larger graph ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
This happened in PipeOp regr.rpart's $train()
Backtrace:
▆
1. ├─graph$train(task) at test_pipeop_learnerpicvplus.R:116:3
2. │ └─mlr3pipelines:::.__Graph__train(...)
3. │ └─mlr3pipelines:::graph_reduce(self, input, "train", single_input)
4. │ └─op[[fun]](input)
5. │ └─mlr3pipelines:::.__PipeOp__train(...)
6. │ ├─base::withCallingHandlers(...)
7. │ └─private$.train(input)
8. │ └─mlr3pipelines:::.__PipeOpLearnerPICVPlus__.train(...)
9. │ └─mlr3::resample(task, private$.learner, rdesc, store_models = TRUE)
10. │ └─ResultData$new(data, data_extra, store_backends = store_backends)
11. │ └─mlr3 (local) initialize(...)
12. │ └─mlr3:::.__ResultData__initialize(...)
13. │ ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. │ └─data.table:::`[.data.table`(...)
15. └─base::.handleSimpleError(...)
16. └─mlr3pipelines (local) h(simpleError(msg, call))
── Error ('test_pipeop_learnerpicvplus.R:130:3'): marshal ──────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
This happened in PipeOp regr.debug's $train()
Backtrace:
▆
1. ├─po$train(list(task)) at test_pipeop_learnerpicvplus.R:130:3
2. │ └─mlr3pipelines:::.__PipeOp__train(...)
3. │ ├─base::withCallingHandlers(...)
4. │ └─private$.train(input)
5. │ └─mlr3pipelines:::.__PipeOpLearnerPICVPlus__.train(...)
6. │ └─mlr3::resample(task, private$.learner, rdesc, store_models = TRUE)
7. │ └─ResultData$new(data, data_extra, store_backends = store_backends)
8. │ └─mlr3 (local) initialize(...)
9. │ └─mlr3:::.__ResultData__initialize(...)
10. │ ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
11. │ └─data.table:::`[.data.table`(...)
12. └─base::.handleSimpleError(...)
13. └─mlr3pipelines (local) h(simpleError(msg, call))
── Error ('test_pipeop_learnerpicvplus.R:152:3'): marshal multiplicity ─────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
This happened in PipeOp regr.debug's $train()
Backtrace:
▆
1. ├─po$train(list(Multiplicity(task1, task2))) at test_pipeop_learnerpicvplus.R:152:3
2. │ └─mlr3pipelines:::.__PipeOp__train(...)
3. │ └─mlr3pipelines:::evaluate_multiplicities(...)
4. │ └─mlr3misc::imap(...)
5. │ ├─stats::setNames(mapply_list(.f, list(.x, .nn), list(...)), names(.x))
6. │ └─mlr3misc:::mapply_list(.f, list(.x, .nn), list(...))
7. │ └─base::.mapply(.f, .dots, .args)
8. │ └─mlr3pipelines (local) `<fn>`(dots[[1L]][[1L]], dots[[2L]][[1L]])
9. │ └─self[[evalcall]](input)
10. │ └─mlr3pipelines:::.__PipeOp__train(...)
11. │ ├─base::withCallingHandlers(...)
12. │ └─private$.train(input)
13. │ └─mlr3pipelines:::.__PipeOpLearnerPICVPlus__.train(...)
14. │ └─mlr3::resample(task, private$.learner, rdesc, store_models = TRUE)
15. │ └─ResultData$new(data, data_extra, store_backends = store_backends)
16. │ └─mlr3 (local) initialize(...)
17. │ └─mlr3:::.__ResultData__initialize(...)
18. │ ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
19. │ └─data.table:::`[.data.table`(...)
20. └─base::.handleSimpleError(...)
21. └─mlr3pipelines (local) h(simpleError(msg, call))
── Error ('test_pipeop_learnercv.R:11:3'): PipeOpLearnerCV - basic properties ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
This happened in PipeOp classif.featureless's $train()
Backtrace:
▆
1. ├─global train_pipeop(po, list(task = task)) at test_pipeop_learnercv.R:11:3
2. │ └─po$train(inputs)
3. │ └─mlr3pipelines:::.__PipeOp__train(...)
4. │ ├─base::withCallingHandlers(...)
5. │ └─private$.train(input)
6. │ └─mlr3pipelines:::.__PipeOpTaskPreproc__.train(...)
7. │ └─private$.train_task(intask)
8. │ └─mlr3pipelines:::.__PipeOpLearnerCV__.train_task(...)
9. │ └─mlr3::resample(...)
10. │ └─ResultData$new(data, data_extra, store_backends = store_backends)
11. │ └─mlr3 (local) initialize(...)
12. │ └─mlr3:::.__ResultData__initialize(...)
13. │ ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. │ └─data.table:::`[.data.table`(...)
15. └─base::.handleSimpleError(...)
16. └─mlr3pipelines (local) h(simpleError(msg, call))
── Error ('test_pipeop_learnercv.R:100:3'): PipeOpLearnerCV - cv ensemble averages fold learners ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
This happened in PipeOp classif.rpart's $train()
Backtrace:
▆
1. ├─po$train(list(task)) at test_pipeop_learnercv.R:100:3
2. │ └─mlr3pipelines:::.__PipeOp__train(...)
3. │ ├─base::withCallingHandlers(...)
4. │ └─private$.train(input)
5. │ └─mlr3pipelines:::.__PipeOpTaskPreproc__.train(...)
6. │ └─private$.train_task(intask)
7. │ └─mlr3pipelines:::.__PipeOpLearnerCV__.train_task(...)
8. │ └─mlr3::resample(...)
9. │ └─ResultData$new(data, data_extra, store_backends = store_backends)
10. │ └─mlr3 (local) initialize(...)
11. │ └─mlr3:::.__ResultData__initialize(...)
12. │ ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
13. │ └─data.table:::`[.data.table`(...)
14. └─base::.handleSimpleError(...)
15. └─mlr3pipelines (local) h(simpleError(msg, call))
── Error ('test_pipeop_learnercv.R:139:3'): PipeOpLearnerCV - cv ensemble drops response when requested ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
This happened in PipeOp classif.rpart's $train()
Backtrace:
▆
1. ├─po$train(list(task)) at test_pipeop_learnercv.R:139:3
2. │ └─mlr3pipelines:::.__PipeOp__train(...)
3. │ ├─base::withCallingHandlers(...)
4. │ └─private$.train(input)
5. │ └─mlr3pipelines:::.__PipeOpTaskPreproc__.train(...)
6. │ └─private$.train_task(intask)
7. │ └─mlr3pipelines:::.__PipeOpLearnerCV__.train_task(...)
8. │ └─mlr3::resample(...)
9. │ └─ResultData$new(data, data_extra, store_backends = store_backends)
10. │ └─mlr3 (local) initialize(...)
11. │ └─mlr3:::.__ResultData__initialize(...)
12. │ ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
13. │ └─data.table:::`[.data.table`(...)
14. └─base::.handleSimpleError(...)
15. └─mlr3pipelines (local) h(simpleError(msg, call))
── Error ('test_pipeop_learnercv.R:152:3'): PipeOpLearnerCV - cv ensemble averages classif responses ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
This happened in PipeOp classif.rpart's $train()
Backtrace:
▆
1. ├─po$train(list(task)) at test_pipeop_learnercv.R:152:3
2. │ └─mlr3pipelines:::.__PipeOp__train(...)
3. │ ├─base::withCallingHandlers(...)
4. │ └─private$.train(input)
5. │ └─mlr3pipelines:::.__PipeOpTaskPreproc__.train(...)
6. │ └─private$.train_task(intask)
7. │ └─mlr3pipelines:::.__PipeOpLearnerCV__.train_task(...)
8. │ └─mlr3::resample(...)
9. │ └─ResultData$new(data, data_extra, store_backends = store_backends)
10. │ └─mlr3 (local) initialize(...)
11. │ └─mlr3:::.__ResultData__initialize(...)
12. │ ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
13. │ └─data.table:::`[.data.table`(...)
14. └─base::.handleSimpleError(...)
15. └─mlr3pipelines (local) h(simpleError(msg, call))
── Error ('test_pipeop_learnercv.R:203:3'): PipeOpLearnerCV - cv ensemble log prob aggregation ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
This happened in PipeOp classif.rpart's $train()
Backtrace:
▆
1. ├─po$train(list(task)) at test_pipeop_learnercv.R:203:3
2. │ └─mlr3pipelines:::.__PipeOp__train(...)
3. │ ├─base::withCallingHandlers(...)
4. │ └─private$.train(input)
5. │ └─mlr3pipelines:::.__PipeOpTaskPreproc__.train(...)
6. │ └─private$.train_task(intask)
7. │ └─mlr3pipelines:::.__PipeOpLearnerCV__.train_task(...)
8. │ └─mlr3::resample(...)
9. │ └─ResultData$new(data, data_extra, store_backends = store_backends)
10. │ └─mlr3 (local) initialize(...)
11. │ └─mlr3:::.__ResultData__initialize(...)
12. │ ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
13. │ └─data.table:::`[.data.table`(...)
14. └─base::.handleSimpleError(...)
15. └─mlr3pipelines (local) h(simpleError(msg, call))
── Error ('test_pipeop_learnercv.R:250:3'): PipeOpLearnerCV - log aggregation with zeros uses epsilon ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
This happened in PipeOp classif.featureless's $train()
Backtrace:
▆
1. ├─po$train(list(task)) at test_pipeop_learnercv.R:250:3
2. │ └─mlr3pipelines:::.__PipeOp__train(...)
3. │ ├─base::withCallingHandlers(...)
4. │ └─private$.train(input)
5. │ └─mlr3pipelines:::.__PipeOpTaskPreproc__.train(...)
6. │ └─private$.train_task(intask)
7. │ └─mlr3pipelines:::.__PipeOpLearnerCV__.train_task(...)
8. │ └─mlr3::resample(...)
9. │ └─ResultData$new(data, data_extra, store_backends = store_backends)
10. │ └─mlr3 (local) initialize(...)
11. │ └─mlr3:::.__ResultData__initialize(...)
12. │ ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
13. │ └─data.table:::`[.data.table`(...)
14. └─base::.handleSimpleError(...)
15. └─mlr3pipelines (local) h(simpleError(msg, call))
── Error ('test_pipeop_learnercv.R:278:3'): PipeOpLearnerCV - log aggregation epsilon controls shrinkage ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
This happened in PipeOp classif.featureless's $train()
Backtrace:
▆
1. ├─po$train(list(task)) at test_pipeop_learnercv.R:278:3
2. │ └─mlr3pipelines:::.__PipeOp__train(...)
3. │ ├─base::withCallingHandlers(...)
4. │ └─private$.train(input)
5. │ └─mlr3pipelines:::.__PipeOpTaskPreproc__.train(...)
6. │ └─private$.train_task(intask)
7. │ └─mlr3pipelines:::.__PipeOpLearnerCV__.train_task(...)
8. │ └─mlr3::resample(...)
9. │ └─ResultData$new(data, data_extra, store_backends = store_backends)
10. │ └─mlr3 (local) initialize(...)
11. │ └─mlr3:::.__ResultData__initialize(...)
12. │ ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
13. │ └─data.table:::`[.data.table`(...)
14. └─base::.handleSimpleError(...)
15. └─mlr3pipelines (local) h(simpleError(msg, call))
── Error ('test_pipeop_learnercv.R:323:3'): PipeOpLearnerCV - cv ensemble averages regression predictions ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
This happened in PipeOp regr.rpart's $train()
Backtrace:
▆
1. ├─po$train(list(task)) at test_pipeop_learnercv.R:323:3
2. │ └─mlr3pipelines:::.__PipeOp__train(...)
3. │ ├─base::withCallingHandlers(...)
4. │ └─private$.train(input)
5. │ └─mlr3pipelines:::.__PipeOpTaskPreproc__.train(...)
6. │ └─private$.train_task(intask)
7. │ └─mlr3pipelines:::.__PipeOpLearnerCV__.train_task(...)
8. │ └─mlr3::resample(...)
9. │ └─ResultData$new(data, data_extra, store_backends = store_backends)
10. │ └─mlr3 (local) initialize(...)
11. │ └─mlr3:::.__ResultData__initialize(...)
12. │ ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
13. │ └─data.table:::`[.data.table`(...)
14. └─base::.handleSimpleError(...)
15. └─mlr3pipelines (local) h(simpleError(msg, call))
── Error ('test_pipeop_learnercv.R:350:3'): PipeOpLearnerCV - cv ensemble handles multiplicity ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
This happened in PipeOp classif.rpart's $train()
Backtrace:
▆
1. ├─po$train(list(tasks)) at test_pipeop_learnercv.R:350:3
2. │ └─mlr3pipelines:::.__PipeOp__train(...)
3. │ └─mlr3pipelines:::evaluate_multiplicities(...)
4. │ └─mlr3misc::imap(...)
5. │ ├─stats::setNames(mapply_list(.f, list(.x, .nn), list(...)), names(.x))
6. │ └─mlr3misc:::mapply_list(.f, list(.x, .nn), list(...))
7. │ └─base::.mapply(.f, .dots, .args)
8. │ └─mlr3pipelines (local) `<fn>`(dots[[1L]][[1L]], dots[[2L]][[1L]])
9. │ └─self[[evalcall]](input)
10. │ └─mlr3pipelines:::.__PipeOp__train(...)
11. │ ├─base::withCallingHandlers(...)
12. │ └─private$.train(input)
13. │ └─mlr3pipelines:::.__PipeOpTaskPreproc__.train(...)
14. │ └─private$.train_task(intask)
15. │ └─mlr3pipelines:::.__PipeOpLearnerCV__.train_task(...)
16. │ └─mlr3::resample(...)
17. │ └─ResultData$new(data, data_extra, store_backends = store_backends)
18. │ └─mlr3 (local) initialize(...)
19. │ └─mlr3:::.__ResultData__initialize(...)
20. │ ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
21. │ └─data.table:::`[.data.table`(...)
22. └─base::.handleSimpleError(...)
23. └─mlr3pipelines (local) h(simpleError(msg, call))
── Error ('test_pipeop_learnercv.R:387:3'): PipeOpLearnerCV - learner_model returns averaged ensemble ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
This happened in PipeOp classif.rpart's $train()
Backtrace:
▆
1. ├─po$train(list(task)) at test_pipeop_learnercv.R:387:3
2. │ └─mlr3pipelines:::.__PipeOp__train(...)
3. │ ├─base::withCallingHandlers(...)
4. │ └─private$.train(input)
5. │ └─mlr3pipelines:::.__PipeOpTaskPreproc__.train(...)
6. │ └─private$.train_task(intask)
7. │ └─mlr3pipelines:::.__PipeOpLearnerCV__.train_task(...)
8. │ └─mlr3::resample(...)
9. │ └─ResultData$new(data, data_extra, store_backends = store_backends)
10. │ └─mlr3 (local) initialize(...)
11. │ └─mlr3:::.__ResultData__initialize(...)
12. │ ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
13. │ └─data.table:::`[.data.table`(...)
14. └─base::.handleSimpleError(...)
15. └─mlr3pipelines (local) h(simpleError(msg, call))
── Error ('test_pipeop_learnercv.R:419:3'): PipeOpLearnerCV - cv ensemble with predict_type = 'se' ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
This happened in PipeOp regr.lm's $train()
Backtrace:
▆
1. ├─po$train(list(task)) at test_pipeop_learnercv.R:419:3
2. │ └─mlr3pipelines:::.__PipeOp__train(...)
3. │ ├─base::withCallingHandlers(...)
4. │ └─private$.train(input)
5. │ └─mlr3pipelines:::.__PipeOpTaskPreproc__.train(...)
6. │ └─private$.train_task(intask)
7. │ └─mlr3pipelines:::.__PipeOpLearnerCV__.train_task(...)
8. │ └─mlr3::resample(...)
9. │ └─ResultData$new(data, data_extra, store_backends = store_backends)
10. │ └─mlr3 (local) initialize(...)
11. │ └─mlr3:::.__ResultData__initialize(...)
12. │ ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
13. │ └─data.table:::`[.data.table`(...)
14. └─base::.handleSimpleError(...)
15. └─mlr3pipelines (local) h(simpleError(msg, call))
── Error ('test_pipeop_learnercv.R:455:3'): PipeOpLearnerCV - within resampling ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
This happened in PipeOp classif.rpart's $train()
Backtrace:
▆
1. └─mlr3::resample(tsk("iris"), gr, rsmp("holdout")) at test_pipeop_learnercv.R:455:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_pipeop_learnercv.R:493:3'): PipeOpLearnerCV - model active binding to state ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
This happened in PipeOp classif.featureless's $train()
Backtrace:
▆
1. ├─po$train(list(task)) at test_pipeop_learnercv.R:493:3
2. │ └─mlr3pipelines:::.__PipeOp__train(...)
3. │ ├─base::withCallingHandlers(...)
4. │ └─private$.train(input)
5. │ └─mlr3pipelines:::.__PipeOpTaskPreproc__.train(...)
6. │ └─private$.train_task(intask)
7. │ └─mlr3pipelines:::.__PipeOpLearnerCV__.train_task(...)
8. │ └─mlr3::resample(...)
9. │ └─ResultData$new(data, data_extra, store_backends = store_backends)
10. │ └─mlr3 (local) initialize(...)
11. │ └─mlr3:::.__ResultData__initialize(...)
12. │ ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
13. │ └─data.table:::`[.data.table`(...)
14. └─base::.handleSimpleError(...)
15. └─mlr3pipelines (local) h(simpleError(msg, call))
── Error ('test_pipeop_learnercv.R:516:3'): predict_type ───────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
This happened in PipeOp classif.rpart's $train()
Backtrace:
▆
1. ├─global expect_equal(...) at test_pipeop_learnercv.R:516:3
2. │ ├─testthat::expect_true(...)
3. │ │ └─testthat::quasi_label(enquo(object), label)
4. │ │ └─rlang::eval_bare(expr, quo_get_env(quo))
5. │ └─base::all.equal(...)
6. ├─lcv$train(list(tsk("iris")))
7. │ └─mlr3pipelines:::.__PipeOp__train(...)
8. │ ├─base::withCallingHandlers(...)
9. │ └─private$.train(input)
10. │ └─mlr3pipelines:::.__PipeOpTaskPreproc__.train(...)
11. │ └─private$.train_task(intask)
12. │ └─mlr3pipelines:::.__PipeOpLearnerCV__.train_task(...)
13. │ └─mlr3::resample(...)
14. │ └─ResultData$new(data, data_extra, store_backends = store_backends)
15. │ └─mlr3 (local) initialize(...)
16. │ └─mlr3:::.__ResultData__initialize(...)
17. │ ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
18. │ └─data.table:::`[.data.table`(...)
19. └─base::.handleSimpleError(...)
20. └─mlr3pipelines (local) h(simpleError(msg, call))
── Error ('test_pipeop_learnercv.R:531:3'): marshal ────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
This happened in PipeOp classif.debug's $train()
Backtrace:
▆
1. ├─po_lrn$train(list(task)) at test_pipeop_learnercv.R:531:3
2. │ └─mlr3pipelines:::.__PipeOp__train(...)
3. │ ├─base::withCallingHandlers(...)
4. │ └─private$.train(input)
5. │ └─mlr3pipelines:::.__PipeOpTaskPreproc__.train(...)
6. │ └─private$.train_task(intask)
7. │ └─mlr3pipelines:::.__PipeOpLearnerCV__.train_task(...)
8. │ └─mlr3::resample(...)
9. │ └─ResultData$new(data, data_extra, store_backends = store_backends)
10. │ └─mlr3 (local) initialize(...)
11. │ └─mlr3:::.__ResultData__initialize(...)
12. │ ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
13. │ └─data.table:::`[.data.table`(...)
14. └─base::.handleSimpleError(...)
15. └─mlr3pipelines (local) h(simpleError(msg, call))
── Error ('test_pipeop_learnercv.R:557:3'): marshal multiplicity ───────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
This happened in PipeOp classif.debug's $train()
Backtrace:
▆
1. ├─po$train(list(Multiplicity(tsk("iris"), tsk("sonar")))) at test_pipeop_learnercv.R:557:3
2. │ └─mlr3pipelines:::.__PipeOp__train(...)
3. │ └─mlr3pipelines:::evaluate_multiplicities(...)
4. │ └─mlr3misc::imap(...)
5. │ ├─stats::setNames(mapply_list(.f, list(.x, .nn), list(...)), names(.x))
6. │ └─mlr3misc:::mapply_list(.f, list(.x, .nn), list(...))
7. │ └─base::.mapply(.f, .dots, .args)
8. │ └─mlr3pipelines (local) `<fn>`(dots[[1L]][[1L]], dots[[2L]][[1L]])
9. │ └─self[[evalcall]](input)
10. │ └─mlr3pipelines:::.__PipeOp__train(...)
11. │ ├─base::withCallingHandlers(...)
12. │ └─private$.train(input)
13. │ └─mlr3pipelines:::.__PipeOpTaskPreproc__.train(...)
14. │ └─private$.train_task(intask)
15. │ └─mlr3pipelines:::.__PipeOpLearnerCV__.train_task(...)
16. │ └─mlr3::resample(...)
17. │ └─ResultData$new(data, data_extra, store_backends = store_backends)
18. │ └─mlr3 (local) initialize(...)
19. │ └─mlr3:::.__ResultData__initialize(...)
20. │ ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
21. │ └─data.table:::`[.data.table`(...)
22. └─base::.handleSimpleError(...)
23. └─mlr3pipelines (local) h(simpleError(msg, call))
── Error ('test_pipeop_learnercv.R:612:3'): marshal with cv ensemble ───────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
This happened in PipeOp classif.rpart's $train()
Backtrace:
▆
1. ├─po$train(list(task)) at test_pipeop_learnercv.R:612:3
2. │ └─mlr3pipelines:::.__PipeOp__train(...)
3. │ ├─base::withCallingHandlers(...)
4. │ └─private$.train(input)
5. │ └─mlr3pipelines:::.__PipeOpTaskPreproc__.train(...)
6. │ └─private$.train_task(intask)
7. │ └─mlr3pipelines:::.__PipeOpLearnerCV__.train_task(...)
8. │ └─mlr3::resample(...)
9. │ └─ResultData$new(data, data_extra, store_backends = store_backends)
10. │ └─mlr3 (local) initialize(...)
11. │ └─mlr3:::.__ResultData__initialize(...)
12. │ ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
13. │ └─data.table:::`[.data.table`(...)
14. └─base::.handleSimpleError(...)
15. └─mlr3pipelines (local) h(simpleError(msg, call))
── Error ('test_pipeop_learnercv.R:628:3'): state class and multiplicity ───────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
This happened in PipeOp classif.debug's $train()
Backtrace:
▆
1. ├─po$train(list(Multiplicity(tsk("iris")))) at test_pipeop_learnercv.R:628:3
2. │ └─mlr3pipelines:::.__PipeOp__train(...)
3. │ └─mlr3pipelines:::evaluate_multiplicities(...)
4. │ └─mlr3misc::imap(...)
5. │ ├─stats::setNames(mapply_list(.f, list(.x, .nn), list(...)), names(.x))
6. │ └─mlr3misc:::mapply_list(.f, list(.x, .nn), list(...))
7. │ └─base::.mapply(.f, .dots, .args)
8. │ └─mlr3pipelines (local) `<fn>`(dots[[1L]][[1L]], dots[[2L]][[1L]])
9. │ └─self[[evalcall]](input)
10. │ └─mlr3pipelines:::.__PipeOp__train(...)
11. │ ├─base::withCallingHandlers(...)
12. │ └─private$.train(input)
13. │ └─mlr3pipelines:::.__PipeOpTaskPreproc__.train(...)
14. │ └─private$.train_task(intask)
15. │ └─mlr3pipelines:::.__PipeOpLearnerCV__.train_task(...)
16. │ └─mlr3::resample(...)
17. │ └─ResultData$new(data, data_extra, store_backends = store_backends)
18. │ └─mlr3 (local) initialize(...)
19. │ └─mlr3:::.__ResultData__initialize(...)
20. │ ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
21. │ └─data.table:::`[.data.table`(...)
22. └─base::.handleSimpleError(...)
23. └─mlr3pipelines (local) h(simpleError(msg, call))
── Error ('test_pipeop_learnercv.R:671:5'): PipeOpLearnerCV cv ensemble aggregates SE like PipeOpRegrAvg ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
This happened in PipeOp regr.debug's $train()
Backtrace:
▆
1. ├─po$train(list(task)) at test_pipeop_learnercv.R:671:5
2. │ └─mlr3pipelines:::.__PipeOp__train(...)
3. │ ├─base::withCallingHandlers(...)
4. │ └─private$.train(input)
5. │ └─mlr3pipelines:::.__PipeOpTaskPreproc__.train(...)
6. │ └─private$.train_task(intask)
7. │ └─mlr3pipelines:::.__PipeOpLearnerCV__.train_task(...)
8. │ └─mlr3::resample(...)
9. │ └─ResultData$new(data, data_extra, store_backends = store_backends)
10. │ └─mlr3 (local) initialize(...)
11. │ └─mlr3:::.__ResultData__initialize(...)
12. │ ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
13. │ └─data.table:::`[.data.table`(...)
14. └─base::.handleSimpleError(...)
15. └─mlr3pipelines (local) h(simpleError(msg, call))
── Error ('test_pipeop_tunethreshold.R:7:3'): threshold works for multiclass ───
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
This happened in PipeOp classif.rpart's $train()
Backtrace:
▆
1. ├─po_cv$train(list(t)) at test_pipeop_tunethreshold.R:7:3
2. │ └─mlr3pipelines:::.__PipeOp__train(...)
3. │ ├─base::withCallingHandlers(...)
4. │ └─private$.train(input)
5. │ └─mlr3pipelines:::.__PipeOpTaskPreproc__.train(...)
6. │ └─private$.train_task(intask)
7. │ └─mlr3pipelines:::.__PipeOpLearnerCV__.train_task(...)
8. │ └─mlr3::resample(...)
9. │ └─ResultData$new(data, data_extra, store_backends = store_backends)
10. │ └─mlr3 (local) initialize(...)
11. │ └─mlr3:::.__ResultData__initialize(...)
12. │ ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
13. │ └─data.table:::`[.data.table`(...)
14. └─base::.handleSimpleError(...)
15. └─mlr3pipelines (local) h(simpleError(msg, call))
── Error ('test_pipeop_tunethreshold.R:38:3'): threshold works for binary ──────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
This happened in PipeOp classif.rpart's $train()
Backtrace:
▆
1. ├─po_cv$train(list(t)) at test_pipeop_tunethreshold.R:38:3
2. │ └─mlr3pipelines:::.__PipeOp__train(...)
3. │ ├─base::withCallingHandlers(...)
4. │ └─private$.train(input)
5. │ └─mlr3pipelines:::.__PipeOpTaskPreproc__.train(...)
6. │ └─private$.train_task(intask)
7. │ └─mlr3pipelines:::.__PipeOpLearnerCV__.train_task(...)
8. │ └─mlr3::resample(...)
9. │ └─ResultData$new(data, data_extra, store_backends = store_backends)
10. │ └─mlr3 (local) initialize(...)
11. │ └─mlr3:::.__ResultData__initialize(...)
12. │ ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
13. │ └─data.table:::`[.data.table`(...)
14. └─base::.handleSimpleError(...)
15. └─mlr3pipelines (local) h(simpleError(msg, call))
── Error ('test_pipeop_tunethreshold.R:73:3'): tunethreshold graph works ───────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
This happened in PipeOp classif.rpart's $train()
Backtrace:
▆
1. ├─graph$train(tsk("pima")) at test_pipeop_tunethreshold.R:73:3
2. │ └─mlr3pipelines:::.__Graph__train(...)
3. │ └─mlr3pipelines:::graph_reduce(self, input, "train", single_input)
4. │ └─op[[fun]](input)
5. │ └─mlr3pipelines:::.__PipeOp__train(...)
6. │ ├─base::withCallingHandlers(...)
7. │ └─private$.train(input)
8. │ └─mlr3pipelines:::.__PipeOpTaskPreproc__.train(...)
9. │ └─private$.train_task(intask)
10. │ └─mlr3pipelines:::.__PipeOpLearnerCV__.train_task(...)
11. │ └─mlr3::resample(...)
12. │ └─ResultData$new(data, data_extra, store_backends = store_backends)
13. │ └─mlr3 (local) initialize(...)
14. │ └─mlr3:::.__ResultData__initialize(...)
15. │ ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. │ └─data.table:::`[.data.table`(...)
17. └─base::.handleSimpleError(...)
18. └─mlr3pipelines (local) h(simpleError(msg, call))
── Error ('test_pipeop_tunethreshold.R:101:3'): threshold works for classes that are not valid R names ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
This happened in PipeOp classif.rpart's $train()
Backtrace:
▆
1. ├─ppl$train(testtask) at test_pipeop_tunethreshold.R:101:3
2. │ └─mlr3pipelines:::.__Graph__train(...)
3. │ └─mlr3pipelines:::graph_reduce(self, input, "train", single_input)
4. │ └─op[[fun]](input)
5. │ └─mlr3pipelines:::.__PipeOp__train(...)
6. │ ├─base::withCallingHandlers(...)
7. │ └─private$.train(input)
8. │ └─mlr3pipelines:::.__PipeOpTaskPreproc__.train(...)
9. │ └─private$.train_task(intask)
10. │ └─mlr3pipelines:::.__PipeOpLearnerCV__.train_task(...)
11. │ └─mlr3::resample(...)
12. │ └─ResultData$new(data, data_extra, store_backends = store_backends)
13. │ └─mlr3 (local) initialize(...)
14. │ └─mlr3:::.__ResultData__initialize(...)
15. │ ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. │ └─data.table:::`[.data.table`(...)
17. └─base::.handleSimpleError(...)
18. └─mlr3pipelines (local) h(simpleError(msg, call))
── Error ('test_pipeop_tunethreshold.R:260:3'): threshold graph transparency ───
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
This happened in PipeOp classif.rpart's $train()
Backtrace:
▆
1. ├─lrn_prob$train(t) at test_pipeop_tunethreshold.R:260:3
2. │ └─mlr3:::.__Learner__train(...)
3. │ └─mlr3:::learner_train(...)
4. │ └─mlr3misc::encapsulate(...)
5. │ ├─mlr3misc::invoke(...)
6. │ │ └─base::eval.parent(expr, n = 1L)
7. │ │ └─base::eval(expr, p)
8. │ │ └─base::eval(expr, p)
9. │ └─mlr3 (local) .f(learner = `<GrphLrnr>`, task = `<TskClssf>`)
10. │ └─get_private(learner)$.train(task)
11. │ └─mlr3pipelines:::.__GraphLearner__.train(...)
12. │ └─self$graph$train(task)
13. │ └─mlr3pipelines:::.__Graph__train(...)
14. │ └─mlr3pipelines:::graph_reduce(self, input, "train", single_input)
15. │ └─op[[fun]](input)
16. │ └─mlr3pipelines:::.__PipeOp__train(...)
17. │ ├─base::withCallingHandlers(...)
18. │ └─private$.train(input)
19. │ └─mlr3pipelines:::.__PipeOpTaskPreproc__.train(...)
20. │ └─private$.train_task(intask)
21. │ └─mlr3pipelines:::.__PipeOpLearnerCV__.train_task(...)
22. │ └─mlr3::resample(...)
23. │ └─ResultData$new(data, data_extra, store_backends = store_backends)
24. │ └─mlr3 (local) initialize(...)
25. │ └─mlr3:::.__ResultData__initialize(...)
26. │ ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. │ └─data.table:::`[.data.table`(...)
28. └─base::.handleSimpleError(...)
29. └─mlr3pipelines (local) h(simpleError(msg, call))
── Error ('test_resample.R:13:3'): PipeOp - Resample ───────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, pp, resa) at test_resample.R:13:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_usecases.R:153:3'): stacking ───────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
This happened in PipeOp classif.rpart's $train()
Backtrace:
▆
1. ├─pipe$train(task) at test_usecases.R:153:3
2. │ └─mlr3pipelines:::.__Graph__train(...)
3. │ └─mlr3pipelines:::graph_reduce(self, input, "train", single_input)
4. │ └─op[[fun]](input)
5. │ └─mlr3pipelines:::.__PipeOp__train(...)
6. │ ├─base::withCallingHandlers(...)
7. │ └─private$.train(input)
8. │ └─mlr3pipelines:::.__PipeOpTaskPreproc__.train(...)
9. │ └─private$.train_task(intask)
10. │ └─mlr3pipelines:::.__PipeOpLearnerCV__.train_task(...)
11. │ └─mlr3::resample(...)
12. │ └─ResultData$new(data, data_extra, store_backends = store_backends)
13. │ └─mlr3 (local) initialize(...)
14. │ └─mlr3:::.__ResultData__initialize(...)
15. │ ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. │ └─data.table:::`[.data.table`(...)
17. └─base::.handleSimpleError(...)
18. └─mlr3pipelines (local) h(simpleError(msg, call))
── Error ('test_ppl.R:73:3'): mlr3book authors don't sleepwalk through life ────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
This happened in PipeOp classif.rpart.classif.rpart's $train()
Backtrace:
▆
1. └─mlr3::benchmark(benchmark_grid(tasks, learners, rsmp("cv", folds = 2))) at test_ppl.R:73:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
[ FAIL 38 | WARN 2 | SKIP 98 | PASS 12316 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-windows-x86_64
Version: 0.10.0
Check: examples
Result: ERROR
Running examples in ‘mlr3pipelines-Ex.R’ failed
The error most likely occurred in:
> ### Name: mlr_pipeops_nmf
> ### Title: Non-negative Matrix Factorization
> ### Aliases: mlr_pipeops_nmf PipeOpNMF
>
> ### ** Examples
>
> ## Don't show:
> if (mlr3misc::require_namespaces(c("NMF", "MASS"), quietly = TRUE)) withAutoprint({ # examplesIf
+ ## End(Don't show)
+ ## Don't show:
+ # NMF attaches these packages to search path on load, #929
+ lapply(c("package:Biobase", "package:BiocGenerics", "package:generics"), detach, character.only = TRUE)
+ ## End(Don't show)
+ library("mlr3")
+
+ task = tsk("iris")
+ pop = po("nmf")
+
+ task$data()
+ pop$train(list(task))[[1]]$data()
+
+ pop$state
+ ## Don't show:
+ # BiocGenerics overwrites printer for our tables mlr-org/mlr3#1112
+ # Necessary as detaching packages does not remove registered S3 methods
+ suppressWarnings(try(rm("format.list", envir = .BaseNamespaceEnv$.__S3MethodsTable__.), silent = TRUE))
+ ## End(Don't show)
+ ## Don't show:
+ }) # examplesIf
> lapply(c("package:Biobase", "package:BiocGenerics", "package:generics"),
+ detach, character.only = TRUE)
Error in FUN(X[[i]], ...) : invalid 'name' argument
Calls: withAutoprint ... withVisible -> eval -> eval -> lapply -> lapply -> FUN
Execution halted
Flavors: r-oldrel-macos-arm64, r-oldrel-macos-x86_64, r-oldrel-windows-x86_64
Version: 0.10.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [106s/52s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("checkmate")
+ library("testthat")
+ library("mlr3")
+ library("paradox")
+ library("mlr3pipelines")
+ test_check("mlr3pipelines")
+ }
Starting 2 test processes.
> test_Graph.R: Training debug.multi with input list(input_1 = 1, input_2 = 1)
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_filter_ensemble.R: OptimInstanceSingleCrit is deprecated. Use OptimInstanceBatchSingleCrit instead.
> test_mlr_graphs_robustify.R: 'as(<dgCMatrix>, "dgTMatrix")' is deprecated.
> test_mlr_graphs_robustify.R: Use 'as(., "TsparseMatrix")' instead.
> test_mlr_graphs_robustify.R: See help("Deprecated") and help("Matrix-deprecated").
> test_multiplicities.R:
> test_multiplicities.R: [[1]]
> test_multiplicities.R: [1] 0
> test_multiplicities.R:
> test_multiplicities.R:
> test_pipeop_blsmote.R: [1] "Borderline-SMOTE done"
> test_pipeop_blsmote.R: [1] "Borderline-SMOTE done"
> test_pipeop_blsmote.R: [1] "Borderline-SMOTE done"
> test_pipeop_blsmote.R: [1] "Borderline-SMOTE done"
Saving _problems/test_pipeop_datefeatures-7.R
Saving _problems/test_pipeop_datefeatures-17.R
> test_pipeop_isomap.R: 2025-12-28 10:22:43.920094: Isomap START
> test_pipeop_isomap.R: 2025-12-28 10:22:43.920355: constructing knn graph
> test_pipeop_isomap.R: 2025-12-28 10:22:43.923508: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-28 10:22:43.929656: Classical Scaling
> test_pipeop_isomap.R: 2025-12-28 10:22:43.940986: Isomap START
> test_pipeop_isomap.R: 2025-12-28 10:22:43.941117: constructing knn graph
> test_pipeop_isomap.R: 2025-12-28 10:22:43.94347: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-28 10:22:43.949845: Classical Scaling
> test_pipeop_isomap.R: 2025-12-28 10:22:43.956458: L-Isomap embed START
> test_pipeop_isomap.R: 2025-12-28 10:22:43.956624: constructing knn graph
> test_pipeop_isomap.R: 2025-12-28 10:22:43.961349: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-28 10:22:43.976455: embedding
> test_pipeop_isomap.R: 2025-12-28 10:22:43.976877: DONE
> test_pipeop_isomap.R: 2025-12-28 10:22:43.982605: L-Isomap embed START
> test_pipeop_isomap.R: 2025-12-28 10:22:43.982731: constructing knn graph
> test_pipeop_isomap.R: 2025-12-28 10:22:43.994699: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-28 10:22:44.010107: embedding
> test_pipeop_isomap.R: 2025-12-28 10:22:44.010456: DONE
> test_pipeop_isomap.R: 2025-12-28 10:22:44.031865: Isomap START
> test_pipeop_isomap.R: 2025-12-28 10:22:44.031986: constructing knn graph
> test_pipeop_isomap.R: 2025-12-28 10:22:44.036338: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-28 10:22:44.070002: Classical Scaling
> test_pipeop_isomap.R: 2025-12-28 10:22:44.078949: L-Isomap embed START
> test_pipeop_isomap.R: 2025-12-28 10:22:44.079125: constructing knn graph
> test_pipeop_isomap.R: 2025-12-28 10:22:44.087716: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-28 10:22:44.169563: embedding
> test_pipeop_isomap.R: 2025-12-28 10:22:44.170642: DONE
> test_pipeop_isomap.R: 2025-12-28 10:22:44.210089: Isomap START
> test_pipeop_isomap.R: 2025-12-28 10:22:44.210227: constructing knn graph
> test_pipeop_isomap.R: 2025-12-28 10:22:44.212385: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-28 10:22:44.21847: Classical Scaling
> test_pipeop_isomap.R: 2025-12-28 10:22:44.225438: L-Isomap embed START
> test_pipeop_isomap.R: 2025-12-28 10:22:44.225611: constructing knn graph
> test_pipeop_isomap.R: 2025-12-28 10:22:44.230285: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-28 10:22:44.245191: embedding
> test_pipeop_isomap.R: 2025-12-28 10:22:44.245565: DONE
> test_pipeop_isomap.R: 2025-12-28 10:22:44.27645: Isomap START
> test_pipeop_isomap.R: 2025-12-28 10:22:44.276585: constructing knn graph
> test_pipeop_isomap.R: 2025-12-28 10:22:44.278974: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-28 10:22:44.285077: Classical Scaling
> test_pipeop_isomap.R: 2025-12-28 10:22:44.297302: L-Isomap embed START
> test_pipeop_isomap.R: 2025-12-28 10:22:44.297513: constructing knn graph
> test_pipeop_isomap.R: 2025-12-28 10:22:44.301971: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-28 10:22:44.31716: embedding
> test_pipeop_isomap.R: 2025-12-28 10:22:44.317567: DONE
> test_pipeop_isomap.R: 2025-12-28 10:22:44.335937: Isomap START
> test_pipeop_isomap.R: 2025-12-28 10:22:44.336066: constructing knn graph
> test_pipeop_isomap.R: 2025-12-28 10:22:44.33837: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-28 10:22:44.344394: Classical Scaling
> test_pipeop_isomap.R: 2025-12-28 10:22:44.361644: L-Isomap embed START
> test_pipeop_isomap.R: 2025-12-28 10:22:44.361826: constructing knn graph
> test_pipeop_isomap.R: 2025-12-28 10:22:44.366239: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-28 10:22:44.381132: embedding
> test_pipeop_isomap.R: 2025-12-28 10:22:44.381523: DONE
> test_pipeop_isomap.R: 2025-12-28 10:22:44.39997: Isomap START
> test_pipeop_isomap.R: 2025-12-28 10:22:44.400109: constructing knn graph
> test_pipeop_isomap.R: 2025-12-28 10:22:44.402515: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-28 10:22:44.408495: Classical Scaling
> test_pipeop_isomap.R: 2025-12-28 10:22:44.419563: L-Isomap embed START
> test_pipeop_isomap.R: 2025-12-28 10:22:44.419934: constructing knn graph
> test_pipeop_isomap.R: 2025-12-28 10:22:44.42441: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-28 10:22:44.438821: embedding
> test_pipeop_isomap.R: 2025-12-28 10:22:44.439172: DONE
> test_pipeop_isomap.R: 2025-12-28 10:22:44.457931: Isomap START
> test_pipeop_isomap.R: 2025-12-28 10:22:44.458054: constructing knn graph
> test_pipeop_isomap.R: 2025-12-28 10:22:44.460514: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-28 10:22:44.466887: Classical Scaling
> test_pipeop_isomap.R: 2025-12-28 10:22:44.478286: L-Isomap embed START
> test_pipeop_isomap.R: 2025-12-28 10:22:44.478458: constructing knn graph
> test_pipeop_isomap.R: 2025-12-28 10:22:44.489137: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-28 10:22:44.504701: embedding
> test_pipeop_isomap.R: 2025-12-28 10:22:44.505133: DONE
> test_pipeop_isomap.R: 2025-12-28 10:22:44.525312: Isomap START
> test_pipeop_isomap.R: 2025-12-28 10:22:44.525435: constructing knn graph
> test_pipeop_isomap.R: 2025-12-28 10:22:44.527468: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-28 10:22:44.533532: Classical Scaling
> test_pipeop_isomap.R: 2025-12-28 10:22:44.550702: Isomap START
> test_pipeop_isomap.R: 2025-12-28 10:22:44.550821: constructing knn graph
> test_pipeop_isomap.R: 2025-12-28 10:22:44.553209: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-28 10:22:44.559196: Classical Scaling
> test_pipeop_isomap.R: 2025-12-28 10:22:44.564696: Isomap START
> test_pipeop_isomap.R: 2025-12-28 10:22:44.564816: constructing knn graph
> test_pipeop_isomap.R: 2025-12-28 10:22:44.567014: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-28 10:22:44.57294: Classical Scaling
Saving _problems/test_pipeop_nmf-45.R
Saving _problems/test_pipeop_nmf-73.R
Saving _problems/test_pipeop_nmf-93.R
Saving _problems/test_pipeop_nmf-98.R
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_textvectorizer.R: 'as(<dgCMatrix>, "dgTMatrix")' is deprecated.
> test_pipeop_textvectorizer.R: Use 'as(., "TsparseMatrix")' instead.
> test_pipeop_textvectorizer.R: See help("Deprecated") and help("Matrix-deprecated").
> test_pipeop_tunethreshold.R: OptimInstanceSingleCrit is deprecated. Use OptimInstanceBatchSingleCrit instead.
> test_pipeop_tunethreshold.R: OptimInstanceSingleCrit is deprecated. Use OptimInstanceBatchSingleCrit instead.
> test_pipeop_tunethreshold.R: OptimInstanceSingleCrit is deprecated. Use OptimInstanceBatchSingleCrit instead.
> test_pipeop_tunethreshold.R: OptimInstanceSingleCrit is deprecated. Use OptimInstanceBatchSingleCrit instead.
> test_pipeop_tunethreshold.R: OptimInstanceSingleCrit is deprecated. Use OptimInstanceBatchSingleCrit instead.
> test_pipeop_tunethreshold.R: OptimInstanceSingleCrit is deprecated. Use OptimInstanceBatchSingleCrit instead.
> test_pipeop_tunethreshold.R: OptimInstanceSingleCrit is deprecated. Use OptimInstanceBatchSingleCrit instead.
[ FAIL 6 | WARN 0 | SKIP 99 | PASS 13006 ]
══ Skipped tests (99) ══════════════════════════════════════════════════════════
• On CRAN (95): 'test_CnfFormula_simplify.R:6:3', 'test_CnfFormula.R:591:3',
'test_Graph.R:283:3', 'test_PipeOp.R:32:1', 'test_GraphLearner.R:5:3',
'test_GraphLearner.R:221:3', 'test_GraphLearner.R:343:3',
'test_GraphLearner.R:408:3', 'test_GraphLearner.R:571:3',
'test_dictionary.R:7:3', 'test_learner_weightedaverage.R:5:3',
'test_learner_weightedaverage.R:57:3',
'test_learner_weightedaverage.R:105:3',
'test_learner_weightedaverage.R:152:3', 'test_meta.R:39:3',
'test_mlr_graphs_branching.R:26:3', 'test_mlr_graphs_bagging.R:6:3',
'test_mlr_graphs_robustify.R:5:3', 'test_pipeop_adas.R:8:3',
'test_pipeop_blsmote.R:8:3', 'test_pipeop_branch.R:4:3',
'test_pipeop_chunk.R:4:3', 'test_pipeop_classbalancing.R:7:3',
'test_pipeop_boxcox.R:7:3', 'test_pipeop_classweights.R:10:3',
'test_pipeop_collapsefactors.R:6:3', 'test_pipeop_colapply.R:9:3',
'test_pipeop_copy.R:5:3', 'test_pipeop_colroles.R:6:3',
'test_pipeop_decode.R:14:3', 'test_pipeop_encode.R:21:3',
'test_pipeop_encodeimpact.R:11:3', 'test_pipeop_encodelmer.R:15:3',
'test_pipeop_encodelmer.R:37:3', 'test_pipeop_encodelmer.R:80:3',
'test_pipeop_encodepl.R:5:3', 'test_pipeop_encodepl.R:72:3',
'test_pipeop_featureunion.R:9:3', 'test_pipeop_featureunion.R:134:3',
'test_pipeop_filter.R:7:3', 'test_pipeop_fixfactors.R:9:3',
'test_pipeop_ensemble.R:6:3', 'test_pipeop_histbin.R:7:3',
'test_pipeop_ica.R:7:3', 'test_pipeop_impute.R:4:3',
'test_pipeop_imputelearner.R:43:3', 'test_pipeop_isomap.R:10:3',
'test_pipeop_kernelpca.R:9:3', 'test_pipeop_learner.R:17:3',
'test_pipeop_info.R:6:3', 'test_pipeop_learnerpicvplus.R:163:3',
'test_pipeop_missind.R:6:3', 'test_pipeop_modelmatrix.R:7:3',
'test_pipeop_multiplicityexply.R:9:3', 'test_pipeop_multiplicityimply.R:9:3',
'test_pipeop_mutate.R:9:3', 'test_pipeop_nearmiss.R:7:3',
'test_pipeop_learnercv.R:31:3', 'test_pipeop_ovr.R:9:3',
'test_pipeop_ovr.R:48:3', 'test_pipeop_pca.R:8:3',
'test_pipeop_proxy.R:14:3', 'test_pipeop_quantilebin.R:5:3',
'test_pipeop_randomprojection.R:6:3', 'test_pipeop_randomresponse.R:5:3',
'test_pipeop_nmf.R:6:3', 'test_pipeop_removeconstants.R:6:3',
'test_pipeop_renamecolumns.R:6:3', 'test_pipeop_replicate.R:9:3',
'test_pipeop_scale.R:6:3', 'test_pipeop_scale.R:10:3',
'test_pipeop_scalemaxabs.R:6:3', 'test_pipeop_scalerange.R:7:3',
'test_pipeop_select.R:9:3', 'test_pipeop_smote.R:10:3',
'test_pipeop_smotenc.R:8:3', 'test_pipeop_rowapply.R:6:3',
'test_pipeop_subsample.R:6:3', 'test_pipeop_targetinvert.R:4:3',
'test_pipeop_targetmutate.R:5:3', 'test_pipeop_targettrafo.R:4:3',
'test_pipeop_targettrafoscalerange.R:5:3', 'test_pipeop_spatialsign.R:6:3',
'test_pipeop_task_preproc.R:4:3', 'test_pipeop_task_preproc.R:14:3',
'test_pipeop_tomek.R:7:3', 'test_pipeop_textvectorizer.R:37:3',
'test_pipeop_textvectorizer.R:186:3', 'test_pipeop_unbranch.R:10:3',
'test_pipeop_updatetarget.R:89:3', 'test_pipeop_vtreat.R:9:3',
'test_pipeop_yeojohnson.R:7:3', 'test_pipeop_tunethreshold.R:111:3',
'test_pipeop_tunethreshold.R:191:3', 'test_typecheck.R:188:3'
• Skipping (1): 'test_GraphLearner.R:1278:3'
• empty test (3): 'test_pipeop_isomap.R:111:1', 'test_pipeop_missind.R:101:1',
'test_ppl.R:61:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_pipeop_datefeatures.R:7:3'): PipeOpDateFeatures - basic properties ──
Error in `seq.Date(as.Date("2020-01-31"), length.out = 150L)`: exactly two of 'to', 'by' and 'length.out' / 'along.with' must be specified
Backtrace:
▆
1. ├─base::seq(as.Date("2020-01-31"), length.out = 150L) at test_pipeop_datefeatures.R:7:3
2. └─base::seq.Date(as.Date("2020-01-31"), length.out = 150L)
── Error ('test_pipeop_datefeatures.R:17:3'): PipeOpDateFeatures - finds POSIXct column ──
Error in `seq.Date(as.Date("2020-01-31"), length.out = 150L)`: exactly two of 'to', 'by' and 'length.out' / 'along.with' must be specified
Backtrace:
▆
1. ├─base::seq(as.Date("2020-01-31"), length.out = 150L) at test_pipeop_datefeatures.R:17:3
2. └─base::seq.Date(as.Date("2020-01-31"), length.out = 150L)
── Error ('test_pipeop_nmf.R:45:3'): PipeOpNMF - does not modify search path when NMF is not loaded, fix for #929 ──
Error in `detach(package:generics)`: invalid 'name' argument
Backtrace:
▆
1. └─base::detach(package:generics) at test_pipeop_nmf.R:45:3
── Failure ('test_pipeop_nmf.R:73:3'): PipeOpNMF - does not modify search path when NMF is loaded, fix for #929 ──
Expected `all(...)` to be TRUE.
Differences:
`actual`: FALSE
`expected`: TRUE
── Failure ('test_pipeop_nmf.R:93:3'): PipeOpNMF - does not modify search path when some of NMF's dependencies are loaded, fix for #929 ──
Expected `all(paste0("package:", c("BiocGenerics", "generics")) %in% search())` to be TRUE.
Differences:
`actual`: FALSE
`expected`: TRUE
── Error ('test_pipeop_nmf.R:98:3'): PipeOpNMF - does not modify search path when some of NMF's dependencies are loaded, fix for #929 ──
Error in `FUN(X[[i]], ...)`: invalid 'name' argument
This happened in PipeOp nmf's $train()
Backtrace:
▆
1. ├─op$train(list(tsk("iris"))) at test_pipeop_nmf.R:98:3
2. │ └─mlr3pipelines:::.__PipeOp__train(...)
3. │ ├─base::withCallingHandlers(...)
4. │ └─private$.train(input)
5. │ └─mlr3pipelines:::.__PipeOpTaskPreproc__.train(...)
6. │ └─private$.train_task(intask)
7. │ └─mlr3pipelines:::.__PipeOpTaskPreproc__.train_task(...)
8. │ ├─data.table::as.data.table(...)
9. │ └─private$.train_dt(dt, task$levels(cols), task$truth())
10. │ └─mlr3pipelines:::.__PipeOpNMF__.train_dt(...)
11. │ └─mlr3misc::map(to_be_detached, detach, character.only = TRUE)
12. │ └─base::lapply(.x, .f, ...)
13. │ └─base (local) FUN(X[[i]], ...)
14. │ └─base::stop("invalid 'name' argument")
15. └─base::.handleSimpleError(...)
16. └─mlr3pipelines (local) h(simpleError(msg, call))
[ FAIL 6 | WARN 0 | SKIP 99 | PASS 13006 ]
Error:
! Test failures.
Execution halted
Flavor: r-oldrel-macos-arm64
Version: 0.10.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [326s/398s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("checkmate")
+ library("testthat")
+ library("mlr3")
+ library("paradox")
+ library("mlr3pipelines")
+ test_check("mlr3pipelines")
+ }
Starting 2 test processes.
> test_Graph.R: Training debug.multi with input list(input_1 = 1, input_2 = 1)
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_filter_ensemble.R: OptimInstanceSingleCrit is deprecated. Use OptimInstanceBatchSingleCrit instead.
> test_mlr_graphs_robustify.R: 'as(<dgCMatrix>, "dgTMatrix")' is deprecated.
> test_mlr_graphs_robustify.R: Use 'as(., "TsparseMatrix")' instead.
> test_mlr_graphs_robustify.R: See help("Deprecated") and help("Matrix-deprecated").
> test_multiplicities.R:
> test_multiplicities.R:
> test_multiplicities.R: [[1]]
> test_multiplicities.R: [1] 0
> test_multiplicities.R:
> test_pipeop_blsmote.R: [1] "Borderline-SMOTE done"
> test_pipeop_blsmote.R: [1] "Borderline-SMOTE done"
> test_pipeop_blsmote.R: [1] "Borderline-SMOTE done"
> test_pipeop_blsmote.R: [1] "Borderline-SMOTE done"
Saving _problems/test_pipeop_datefeatures-7.R
Saving _problems/test_pipeop_datefeatures-17.R
> test_pipeop_isomap.R: 2025-12-27 18:14:13.981914: Isomap START
> test_pipeop_isomap.R: 2025-12-27 18:14:13.983688: constructing knn graph
> test_pipeop_isomap.R: 2025-12-27 18:14:14.009755: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-27 18:14:14.066086: Classical Scaling
> test_pipeop_isomap.R: 2025-12-27 18:14:14.189324: Isomap START
> test_pipeop_isomap.R: 2025-12-27 18:14:14.189632: constructing knn graph
> test_pipeop_isomap.R: 2025-12-27 18:14:14.213934: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-27 18:14:14.272518: Classical Scaling
> test_pipeop_isomap.R: 2025-12-27 18:14:14.333067: L-Isomap embed START
> test_pipeop_isomap.R: 2025-12-27 18:14:14.333587: constructing knn graph
> test_pipeop_isomap.R: 2025-12-27 18:14:14.371492: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-27 18:14:14.502053: embedding
> test_pipeop_isomap.R: 2025-12-27 18:14:14.503309: DONE
> test_pipeop_isomap.R: 2025-12-27 18:14:14.581988: L-Isomap embed START
> test_pipeop_isomap.R: 2025-12-27 18:14:14.582322: constructing knn graph
> test_pipeop_isomap.R: 2025-12-27 18:14:14.641992: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-27 18:14:14.788978: embedding
> test_pipeop_isomap.R: 2025-12-27 18:14:14.792007: DONE
> test_pipeop_isomap.R: 2025-12-27 18:14:14.992145: Isomap START
> test_pipeop_isomap.R: 2025-12-27 18:14:14.992455: constructing knn graph
> test_pipeop_isomap.R: 2025-12-27 18:14:15.017466: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-27 18:14:15.289029: Classical Scaling
> test_pipeop_isomap.R: 2025-12-27 18:14:15.395499: L-Isomap embed START
> test_pipeop_isomap.R: 2025-12-27 18:14:15.39598: constructing knn graph
> test_pipeop_isomap.R: 2025-12-27 18:14:15.482678: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-27 18:14:16.03371: embedding
> test_pipeop_isomap.R: 2025-12-27 18:14:16.067034: DONE
> test_pipeop_isomap.R: 2025-12-27 18:14:16.417309: Isomap START
> test_pipeop_isomap.R: 2025-12-27 18:14:16.41763: constructing knn graph
> test_pipeop_isomap.R: 2025-12-27 18:14:16.42472: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-27 18:14:16.478978: Classical Scaling
> test_pipeop_isomap.R: 2025-12-27 18:14:16.56056: L-Isomap embed START
> test_pipeop_isomap.R: 2025-12-27 18:14:16.560981: constructing knn graph
> test_pipeop_isomap.R: 2025-12-27 18:14:16.601891: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-27 18:14:16.715261: embedding
> test_pipeop_isomap.R: 2025-12-27 18:14:16.716389: DONE
> test_pipeop_isomap.R: 2025-12-27 18:14:16.98286: Isomap START
> test_pipeop_isomap.R: 2025-12-27 18:14:16.983164: constructing knn graph
> test_pipeop_isomap.R: 2025-12-27 18:14:16.989994: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-27 18:14:17.065021: Classical Scaling
> test_pipeop_isomap.R: 2025-12-27 18:14:17.169577: L-Isomap embed START
> test_pipeop_isomap.R: 2025-12-27 18:14:17.17004: constructing knn graph
> test_pipeop_isomap.R: 2025-12-27 18:14:17.220415: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-27 18:14:17.331855: embedding
> test_pipeop_isomap.R: 2025-12-27 18:14:17.352737: DONE
> test_pipeop_isomap.R: 2025-12-27 18:14:17.503494: Isomap START
> test_pipeop_isomap.R: 2025-12-27 18:14:17.503783: constructing knn graph
> test_pipeop_isomap.R: 2025-12-27 18:14:17.530032: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-27 18:14:17.589983: Classical Scaling
> test_pipeop_isomap.R: 2025-12-27 18:14:17.701178: L-Isomap embed START
> test_pipeop_isomap.R: 2025-12-27 18:14:17.701606: constructing knn graph
> test_pipeop_isomap.R: 2025-12-27 18:14:17.748643: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-27 18:14:17.866844: embedding
> test_pipeop_isomap.R: 2025-12-27 18:14:17.867983: DONE
> test_pipeop_isomap.R: 2025-12-27 18:14:18.010992: Isomap START
> test_pipeop_isomap.R: 2025-12-27 18:14:18.011309: constructing knn graph
> test_pipeop_isomap.R: 2025-12-27 18:14:18.049413: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-27 18:14:18.095514: Classical Scaling
> test_pipeop_isomap.R: 2025-12-27 18:14:18.187243: L-Isomap embed START
> test_pipeop_isomap.R: 2025-12-27 18:14:18.187703: constructing knn graph
> test_pipeop_isomap.R: 2025-12-27 18:14:18.227869: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-27 18:14:18.324809: embedding
> test_pipeop_isomap.R: 2025-12-27 18:14:18.353311: DONE
> test_pipeop_isomap.R: 2025-12-27 18:14:18.48292: Isomap START
> test_pipeop_isomap.R: 2025-12-27 18:14:18.483212: constructing knn graph
> test_pipeop_isomap.R: 2025-12-27 18:14:18.510008: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-27 18:14:18.560628: Classical Scaling
> test_pipeop_isomap.R: 2025-12-27 18:14:18.645237: L-Isomap embed START
> test_pipeop_isomap.R: 2025-12-27 18:14:18.645709: constructing knn graph
> test_pipeop_isomap.R: 2025-12-27 18:14:18.712804: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-27 18:14:18.816938: embedding
> test_pipeop_isomap.R: 2025-12-27 18:14:18.819216: DONE
> test_pipeop_isomap.R: 2025-12-27 18:14:19.006757: Isomap START
> test_pipeop_isomap.R: 2025-12-27 18:14:19.00707: constructing knn graph
> test_pipeop_isomap.R: 2025-12-27 18:14:19.014167: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-27 18:14:19.061359: Classical Scaling
> test_pipeop_isomap.R: 2025-12-27 18:14:19.271588: Isomap START
> test_pipeop_isomap.R: 2025-12-27 18:14:19.271888: constructing knn graph
> test_pipeop_isomap.R: 2025-12-27 18:14:19.300245: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-27 18:14:19.347421: Classical Scaling
> test_pipeop_isomap.R: 2025-12-27 18:14:19.403575: Isomap START
> test_pipeop_isomap.R: 2025-12-27 18:14:19.403883: constructing knn graph
> test_pipeop_isomap.R: 2025-12-27 18:14:19.411405: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-27 18:14:19.456626: Classical Scaling
Saving _problems/test_pipeop_nmf-45.R
Saving _problems/test_pipeop_nmf-73.R
Saving _problems/test_pipeop_nmf-93.R
Saving _problems/test_pipeop_nmf-98.R
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_textvectorizer.R: 'as(<dgCMatrix>, "dgTMatrix")' is deprecated.
> test_pipeop_textvectorizer.R: Use 'as(., "TsparseMatrix")' instead.
> test_pipeop_textvectorizer.R: See help("Deprecated") and help("Matrix-deprecated").
> test_pipeop_tunethreshold.R: OptimInstanceSingleCrit is deprecated. Use OptimInstanceBatchSingleCrit instead.
> test_pipeop_tunethreshold.R: OptimInstanceSingleCrit is deprecated. Use OptimInstanceBatchSingleCrit instead.
> test_pipeop_tunethreshold.R: OptimInstanceSingleCrit is deprecated. Use OptimInstanceBatchSingleCrit instead.
> test_pipeop_tunethreshold.R: OptimInstanceSingleCrit is deprecated. Use OptimInstanceBatchSingleCrit instead.
> test_pipeop_tunethreshold.R: OptimInstanceSingleCrit is deprecated. Use OptimInstanceBatchSingleCrit instead.
> test_pipeop_tunethreshold.R: OptimInstanceSingleCrit is deprecated. Use OptimInstanceBatchSingleCrit instead.
> test_pipeop_tunethreshold.R: OptimInstanceSingleCrit is deprecated. Use OptimInstanceBatchSingleCrit instead.
[ FAIL 6 | WARN 0 | SKIP 99 | PASS 13006 ]
══ Skipped tests (99) ══════════════════════════════════════════════════════════
• On CRAN (95): 'test_CnfFormula_simplify.R:6:3', 'test_CnfFormula.R:591:3',
'test_Graph.R:283:3', 'test_PipeOp.R:32:1', 'test_GraphLearner.R:5:3',
'test_GraphLearner.R:221:3', 'test_GraphLearner.R:343:3',
'test_GraphLearner.R:408:3', 'test_GraphLearner.R:571:3',
'test_dictionary.R:7:3', 'test_learner_weightedaverage.R:5:3',
'test_learner_weightedaverage.R:57:3',
'test_learner_weightedaverage.R:105:3',
'test_learner_weightedaverage.R:152:3', 'test_meta.R:39:3',
'test_mlr_graphs_branching.R:26:3', 'test_mlr_graphs_bagging.R:6:3',
'test_mlr_graphs_robustify.R:5:3', 'test_pipeop_adas.R:8:3',
'test_pipeop_blsmote.R:8:3', 'test_pipeop_branch.R:4:3',
'test_pipeop_chunk.R:4:3', 'test_pipeop_classbalancing.R:7:3',
'test_pipeop_boxcox.R:7:3', 'test_pipeop_classweights.R:10:3',
'test_pipeop_collapsefactors.R:6:3', 'test_pipeop_colapply.R:9:3',
'test_pipeop_copy.R:5:3', 'test_pipeop_colroles.R:6:3',
'test_pipeop_decode.R:14:3', 'test_pipeop_encode.R:21:3',
'test_pipeop_encodeimpact.R:11:3', 'test_pipeop_encodepl.R:5:3',
'test_pipeop_encodepl.R:72:3', 'test_pipeop_encodelmer.R:15:3',
'test_pipeop_encodelmer.R:37:3', 'test_pipeop_encodelmer.R:80:3',
'test_pipeop_featureunion.R:9:3', 'test_pipeop_featureunion.R:134:3',
'test_pipeop_filter.R:7:3', 'test_pipeop_fixfactors.R:9:3',
'test_pipeop_histbin.R:7:3', 'test_pipeop_ica.R:7:3',
'test_pipeop_ensemble.R:6:3', 'test_pipeop_impute.R:4:3',
'test_pipeop_imputelearner.R:43:3', 'test_pipeop_isomap.R:10:3',
'test_pipeop_kernelpca.R:9:3', 'test_pipeop_learner.R:17:3',
'test_pipeop_info.R:6:3', 'test_pipeop_learnerpicvplus.R:163:3',
'test_pipeop_missind.R:6:3', 'test_pipeop_modelmatrix.R:7:3',
'test_pipeop_multiplicityexply.R:9:3', 'test_pipeop_multiplicityimply.R:9:3',
'test_pipeop_mutate.R:9:3', 'test_pipeop_nearmiss.R:7:3',
'test_pipeop_learnercv.R:31:3', 'test_pipeop_ovr.R:9:3',
'test_pipeop_ovr.R:48:3', 'test_pipeop_pca.R:8:3',
'test_pipeop_proxy.R:14:3', 'test_pipeop_nmf.R:6:3',
'test_pipeop_quantilebin.R:5:3', 'test_pipeop_randomprojection.R:6:3',
'test_pipeop_randomresponse.R:5:3', 'test_pipeop_renamecolumns.R:6:3',
'test_pipeop_removeconstants.R:6:3', 'test_pipeop_replicate.R:9:3',
'test_pipeop_scale.R:6:3', 'test_pipeop_scale.R:10:3',
'test_pipeop_scalemaxabs.R:6:3', 'test_pipeop_scalerange.R:7:3',
'test_pipeop_select.R:9:3', 'test_pipeop_smote.R:10:3',
'test_pipeop_smotenc.R:8:3', 'test_pipeop_rowapply.R:6:3',
'test_pipeop_subsample.R:6:3', 'test_pipeop_targetinvert.R:4:3',
'test_pipeop_targetmutate.R:5:3', 'test_pipeop_targettrafo.R:4:3',
'test_pipeop_targettrafoscalerange.R:5:3', 'test_pipeop_task_preproc.R:4:3',
'test_pipeop_task_preproc.R:14:3', 'test_pipeop_spatialsign.R:6:3',
'test_pipeop_tomek.R:7:3', 'test_pipeop_textvectorizer.R:37:3',
'test_pipeop_textvectorizer.R:186:3', 'test_pipeop_unbranch.R:10:3',
'test_pipeop_updatetarget.R:89:3', 'test_pipeop_vtreat.R:9:3',
'test_pipeop_yeojohnson.R:7:3', 'test_pipeop_tunethreshold.R:111:3',
'test_pipeop_tunethreshold.R:191:3', 'test_typecheck.R:188:3'
• Skipping (1): 'test_GraphLearner.R:1278:3'
• empty test (3): 'test_pipeop_isomap.R:111:1', 'test_pipeop_missind.R:101:1',
'test_ppl.R:61:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_pipeop_datefeatures.R:7:3'): PipeOpDateFeatures - basic properties ──
Error in `seq.Date(as.Date("2020-01-31"), length.out = 150L)`: exactly two of 'to', 'by' and 'length.out' / 'along.with' must be specified
Backtrace:
▆
1. ├─base::seq(as.Date("2020-01-31"), length.out = 150L) at test_pipeop_datefeatures.R:7:3
2. └─base::seq.Date(as.Date("2020-01-31"), length.out = 150L)
── Error ('test_pipeop_datefeatures.R:17:3'): PipeOpDateFeatures - finds POSIXct column ──
Error in `seq.Date(as.Date("2020-01-31"), length.out = 150L)`: exactly two of 'to', 'by' and 'length.out' / 'along.with' must be specified
Backtrace:
▆
1. ├─base::seq(as.Date("2020-01-31"), length.out = 150L) at test_pipeop_datefeatures.R:17:3
2. └─base::seq.Date(as.Date("2020-01-31"), length.out = 150L)
── Error ('test_pipeop_nmf.R:45:3'): PipeOpNMF - does not modify search path when NMF is not loaded, fix for #929 ──
Error in `detach(package:generics)`: invalid 'name' argument
Backtrace:
▆
1. └─base::detach(package:generics) at test_pipeop_nmf.R:45:3
── Failure ('test_pipeop_nmf.R:73:3'): PipeOpNMF - does not modify search path when NMF is loaded, fix for #929 ──
Expected `all(...)` to be TRUE.
Differences:
`actual`: FALSE
`expected`: TRUE
── Failure ('test_pipeop_nmf.R:93:3'): PipeOpNMF - does not modify search path when some of NMF's dependencies are loaded, fix for #929 ──
Expected `all(paste0("package:", c("BiocGenerics", "generics")) %in% search())` to be TRUE.
Differences:
`actual`: FALSE
`expected`: TRUE
── Error ('test_pipeop_nmf.R:98:3'): PipeOpNMF - does not modify search path when some of NMF's dependencies are loaded, fix for #929 ──
Error in `FUN(X[[i]], ...)`: invalid 'name' argument
This happened in PipeOp nmf's $train()
Backtrace:
▆
1. ├─op$train(list(tsk("iris"))) at test_pipeop_nmf.R:98:3
2. │ └─mlr3pipelines:::.__PipeOp__train(...)
3. │ ├─base::withCallingHandlers(...)
4. │ └─private$.train(input)
5. │ └─mlr3pipelines:::.__PipeOpTaskPreproc__.train(...)
6. │ └─private$.train_task(intask)
7. │ └─mlr3pipelines:::.__PipeOpTaskPreproc__.train_task(...)
8. │ ├─data.table::as.data.table(...)
9. │ └─private$.train_dt(dt, task$levels(cols), task$truth())
10. │ └─mlr3pipelines:::.__PipeOpNMF__.train_dt(...)
11. │ └─mlr3misc::map(to_be_detached, detach, character.only = TRUE)
12. │ └─base::lapply(.x, .f, ...)
13. │ └─base (local) FUN(X[[i]], ...)
14. │ └─base::stop("invalid 'name' argument")
15. └─base::.handleSimpleError(...)
16. └─mlr3pipelines (local) h(simpleError(msg, call))
[ FAIL 6 | WARN 0 | SKIP 99 | PASS 13006 ]
Error:
! Test failures.
Execution halted
Flavor: r-oldrel-macos-x86_64
Version: 0.10.0
Check: tests
Result: ERROR
Running 'testthat.R' [269s]
Running the tests in 'tests/testthat.R' failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("checkmate")
+ library("testthat")
+ library("mlr3")
+ library("paradox")
+ library("mlr3pipelines")
+ test_check("mlr3pipelines")
+ }
Starting 2 test processes.
> test_Graph.R: Training debug.multi with input list(input_1 = 1, input_2 = 1)
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_filter_ensemble.R: OptimInstanceSingleCrit is deprecated. Use OptimInstanceBatchSingleCrit instead.
> test_mlr_graphs_robustify.R: 'as(<dgCMatrix>, "dgTMatrix")' is deprecated.
> test_mlr_graphs_robustify.R: Use 'as(., "TsparseMatrix")' instead.
> test_mlr_graphs_robustify.R: See help("Deprecated") and help("Matrix-deprecated").
> test_multiplicities.R:
> test_multiplicities.R:
> test_multiplicities.R: [[1]]
> test_multiplicities.R: [1] 0
> test_multiplicities.R:
> test_pipeop_blsmote.R: [1] "Borderline-SMOTE done"
> test_pipeop_blsmote.R: [1] "Borderline-SMOTE done"
> test_pipeop_blsmote.R: [1] "Borderline-SMOTE done"
> test_pipeop_blsmote.R: [1] "Borderline-SMOTE done"
Saving _problems/test_pipeop_datefeatures-7.R
Saving _problems/test_pipeop_datefeatures-17.R
> test_pipeop_isomap.R: 2025-12-24 19:44:00.8847: Isomap START
> test_pipeop_isomap.R: 2025-12-24 19:44:00.885721: constructing knn graph
> test_pipeop_isomap.R: 2025-12-24 19:44:00.89953: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-24 19:44:00.922647: Classical Scaling
> test_pipeop_isomap.R: 2025-12-24 19:44:01.005968: Isomap START
> test_pipeop_isomap.R: 2025-12-24 19:44:01.006631: constructing knn graph
> test_pipeop_isomap.R: 2025-12-24 19:44:01.017267: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-24 19:44:01.039418: Classical Scaling
> test_pipeop_isomap.R: 2025-12-24 19:44:01.083344: L-Isomap embed START
> test_pipeop_isomap.R: 2025-12-24 19:44:01.084265: constructing knn graph
> test_pipeop_isomap.R: 2025-12-24 19:44:01.106502: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-24 19:44:01.160127: embedding
> test_pipeop_isomap.R: 2025-12-24 19:44:01.16247: DONE
> test_pipeop_isomap.R: 2025-12-24 19:44:01.20625: L-Isomap embed START
> test_pipeop_isomap.R: 2025-12-24 19:44:01.206883: constructing knn graph
> test_pipeop_isomap.R: 2025-12-24 19:44:01.231468: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-24 19:44:01.281787: embedding
> test_pipeop_isomap.R: 2025-12-24 19:44:01.283685: DONE
> test_pipeop_isomap.R: 2025-12-24 19:44:01.407489: Isomap START
> test_pipeop_isomap.R: 2025-12-24 19:44:01.408145: constructing knn graph
> test_pipeop_isomap.R: 2025-12-24 19:44:01.432668: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-24 19:44:01.549787: Classical Scaling
> test_pipeop_isomap.R: 2025-12-24 19:44:01.605741: L-Isomap embed START
> test_pipeop_isomap.R: 2025-12-24 19:44:01.606885: constructing knn graph
> test_pipeop_isomap.R: 2025-12-24 19:44:01.659569: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-24 19:44:01.889314: embedding
> test_pipeop_isomap.R: 2025-12-24 19:44:01.896023: DONE
> test_pipeop_isomap.R: 2025-12-24 19:44:02.164539: Isomap START
> test_pipeop_isomap.R: 2025-12-24 19:44:02.165331: constructing knn graph
> test_pipeop_isomap.R: 2025-12-24 19:44:02.173079: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-24 19:44:02.196576: Classical Scaling
> test_pipeop_isomap.R: 2025-12-24 19:44:02.248705: L-Isomap embed START
> test_pipeop_isomap.R: 2025-12-24 19:44:02.249781: constructing knn graph
> test_pipeop_isomap.R: 2025-12-24 19:44:02.270687: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-24 19:44:02.322682: embedding
> test_pipeop_isomap.R: 2025-12-24 19:44:02.324615: DONE
> test_pipeop_isomap.R: 2025-12-24 19:44:02.552554: Isomap START
> test_pipeop_isomap.R: 2025-12-24 19:44:02.553231: constructing knn graph
> test_pipeop_isomap.R: 2025-12-24 19:44:02.564091: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-24 19:44:02.585377: Classical Scaling
> test_pipeop_isomap.R: 2025-12-24 19:44:02.65997: L-Isomap embed START
> test_pipeop_isomap.R: 2025-12-24 19:44:02.661195: constructing knn graph
> test_pipeop_isomap.R: 2025-12-24 19:44:02.684129: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-24 19:44:02.736933: embedding
> test_pipeop_isomap.R: 2025-12-24 19:44:02.738703: DONE
> test_pipeop_isomap.R: 2025-12-24 19:44:02.839728: Isomap START
> test_pipeop_isomap.R: 2025-12-24 19:44:02.840493: constructing knn graph
> test_pipeop_isomap.R: 2025-12-24 19:44:02.851464: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-24 19:44:02.873809: Classical Scaling
> test_pipeop_isomap.R: 2025-12-24 19:44:02.947746: L-Isomap embed START
> test_pipeop_isomap.R: 2025-12-24 19:44:02.948878: constructing knn graph
> test_pipeop_isomap.R: 2025-12-24 19:44:02.976366: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-24 19:44:03.025596: embedding
> test_pipeop_isomap.R: 2025-12-24 19:44:03.027969: DONE
> test_pipeop_isomap.R: 2025-12-24 19:44:03.17419: Isomap START
> test_pipeop_isomap.R: 2025-12-24 19:44:03.174806: constructing knn graph
> test_pipeop_isomap.R: 2025-12-24 19:44:03.184778: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-24 19:44:03.206519: Classical Scaling
> test_pipeop_isomap.R: 2025-12-24 19:44:03.272558: L-Isomap embed START
> test_pipeop_isomap.R: 2025-12-24 19:44:03.273449: constructing knn graph
> test_pipeop_isomap.R: 2025-12-24 19:44:03.292544: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-24 19:44:03.340467: embedding
> test_pipeop_isomap.R: 2025-12-24 19:44:03.342014: DONE
> test_pipeop_isomap.R: 2025-12-24 19:44:03.456471: Isomap START
> test_pipeop_isomap.R: 2025-12-24 19:44:03.457097: constructing knn graph
> test_pipeop_isomap.R: 2025-12-24 19:44:03.467468: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-24 19:44:03.48764: Classical Scaling
> test_pipeop_isomap.R: 2025-12-24 19:44:03.561047: L-Isomap embed START
> test_pipeop_isomap.R: 2025-12-24 19:44:03.562372: constructing knn graph
> test_pipeop_isomap.R: 2025-12-24 19:44:03.583107: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-24 19:44:03.631105: embedding
> test_pipeop_isomap.R: 2025-12-24 19:44:03.632928: DONE
> test_pipeop_isomap.R: 2025-12-24 19:44:03.761525: Isomap START
> test_pipeop_isomap.R: 2025-12-24 19:44:03.762171: constructing knn graph
> test_pipeop_isomap.R: 2025-12-24 19:44:03.772532: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-24 19:44:03.794509: Classical Scaling
> test_pipeop_isomap.R: 2025-12-24 19:44:03.906476: Isomap START
> test_pipeop_isomap.R: 2025-12-24 19:44:03.90705: constructing knn graph
> test_pipeop_isomap.R: 2025-12-24 19:44:03.917833: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-24 19:44:03.939201: Classical Scaling
> test_pipeop_isomap.R: 2025-12-24 19:44:04.000915: Isomap START
> test_pipeop_isomap.R: 2025-12-24 19:44:04.001602: constructing knn graph
> test_pipeop_isomap.R: 2025-12-24 19:44:04.011507: calculating geodesic distances
> test_pipeop_isomap.R: 2025-12-24 19:44:04.034371: Classical Scaling
Saving _problems/test_pipeop_nmf-45.R
Saving _problems/test_pipeop_nmf-73.R
Saving _problems/test_pipeop_nmf-93.R
Saving _problems/test_pipeop_nmf-98.R
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_tunethreshold.R: OptimInstanceSingleCrit is deprecated. Use OptimInstanceBatchSingleCrit instead.
> test_pipeop_tunethreshold.R: OptimInstanceSingleCrit is deprecated. Use OptimInstanceBatchSingleCrit instead.
> test_pipeop_tunethreshold.R: OptimInstanceSingleCrit is deprecated. Use OptimInstanceBatchSingleCrit instead.
> test_pipeop_tunethreshold.R: OptimInstanceSingleCrit is deprecated. Use OptimInstanceBatchSingleCrit instead.
> test_pipeop_tunethreshold.R: OptimInstanceSingleCrit is deprecated. Use OptimInstanceBatchSingleCrit instead.
> test_pipeop_tunethreshold.R: OptimInstanceSingleCrit is deprecated. Use OptimInstanceBatchSingleCrit instead.
> test_pipeop_tunethreshold.R: OptimInstanceSingleCrit is deprecated. Use OptimInstanceBatchSingleCrit instead.
[ FAIL 6 | WARN 0 | SKIP 99 | PASS 13006 ]
══ Skipped tests (99) ══════════════════════════════════════════════════════════
• On CRAN (95): 'test_CnfFormula_simplify.R:6:3', 'test_CnfFormula.R:591:3',
'test_Graph.R:283:3', 'test_PipeOp.R:32:1', 'test_GraphLearner.R:5:3',
'test_GraphLearner.R:221:3', 'test_GraphLearner.R:343:3',
'test_GraphLearner.R:408:3', 'test_GraphLearner.R:571:3',
'test_dictionary.R:7:3', 'test_learner_weightedaverage.R:5:3',
'test_learner_weightedaverage.R:57:3',
'test_learner_weightedaverage.R:105:3',
'test_learner_weightedaverage.R:152:3', 'test_meta.R:39:3',
'test_mlr_graphs_branching.R:26:3', 'test_mlr_graphs_bagging.R:6:3',
'test_mlr_graphs_robustify.R:5:3', 'test_pipeop_adas.R:8:3',
'test_pipeop_blsmote.R:8:3', 'test_pipeop_branch.R:4:3',
'test_pipeop_chunk.R:4:3', 'test_pipeop_classbalancing.R:7:3',
'test_pipeop_boxcox.R:7:3', 'test_pipeop_classweights.R:10:3',
'test_pipeop_collapsefactors.R:6:3', 'test_pipeop_colapply.R:9:3',
'test_pipeop_copy.R:5:3', 'test_pipeop_colroles.R:6:3',
'test_pipeop_decode.R:14:3', 'test_pipeop_encode.R:21:3',
'test_pipeop_encodeimpact.R:11:3', 'test_pipeop_encodepl.R:5:3',
'test_pipeop_encodepl.R:72:3', 'test_pipeop_encodelmer.R:15:3',
'test_pipeop_encodelmer.R:37:3', 'test_pipeop_encodelmer.R:80:3',
'test_pipeop_featureunion.R:9:3', 'test_pipeop_featureunion.R:134:3',
'test_pipeop_filter.R:7:3', 'test_pipeop_fixfactors.R:9:3',
'test_pipeop_histbin.R:7:3', 'test_pipeop_ica.R:7:3',
'test_pipeop_ensemble.R:6:3', 'test_pipeop_impute.R:4:3',
'test_pipeop_imputelearner.R:43:3', 'test_pipeop_isomap.R:10:3',
'test_pipeop_kernelpca.R:9:3', 'test_pipeop_learner.R:17:3',
'test_pipeop_info.R:6:3', 'test_pipeop_learnerpicvplus.R:163:3',
'test_pipeop_missind.R:6:3', 'test_pipeop_modelmatrix.R:7:3',
'test_pipeop_multiplicityexply.R:9:3', 'test_pipeop_learnercv.R:31:3',
'test_pipeop_mutate.R:9:3', 'test_pipeop_nearmiss.R:7:3',
'test_pipeop_multiplicityimply.R:9:3', 'test_pipeop_ovr.R:9:3',
'test_pipeop_ovr.R:48:3', 'test_pipeop_pca.R:8:3',
'test_pipeop_proxy.R:14:3', 'test_pipeop_quantilebin.R:5:3',
'test_pipeop_randomprojection.R:6:3', 'test_pipeop_randomresponse.R:5:3',
'test_pipeop_removeconstants.R:6:3', 'test_pipeop_renamecolumns.R:6:3',
'test_pipeop_replicate.R:9:3', 'test_pipeop_rowapply.R:6:3',
'test_pipeop_scale.R:6:3', 'test_pipeop_scale.R:10:3',
'test_pipeop_scalemaxabs.R:6:3', 'test_pipeop_scalerange.R:7:3',
'test_pipeop_nmf.R:6:3', 'test_pipeop_select.R:9:3',
'test_pipeop_smote.R:10:3', 'test_pipeop_smotenc.R:8:3',
'test_pipeop_subsample.R:6:3', 'test_pipeop_targetinvert.R:4:3',
'test_pipeop_targetmutate.R:5:3', 'test_pipeop_targettrafo.R:4:3',
'test_pipeop_targettrafoscalerange.R:5:3', 'test_pipeop_task_preproc.R:4:3',
'test_pipeop_task_preproc.R:14:3', 'test_pipeop_spatialsign.R:6:3',
'test_pipeop_tomek.R:7:3', 'test_pipeop_textvectorizer.R:37:3',
'test_pipeop_textvectorizer.R:186:3', 'test_pipeop_unbranch.R:10:3',
'test_pipeop_updatetarget.R:89:3', 'test_pipeop_vtreat.R:9:3',
'test_pipeop_yeojohnson.R:7:3', 'test_pipeop_tunethreshold.R:111:3',
'test_pipeop_tunethreshold.R:191:3', 'test_typecheck.R:188:3'
• Skipping (1): 'test_GraphLearner.R:1278:3'
• empty test (3): 'test_pipeop_isomap.R:111:1', 'test_pipeop_missind.R:101:1',
'test_ppl.R:61:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_pipeop_datefeatures.R:7:3'): PipeOpDateFeatures - basic properties ──
Error in `seq.Date(as.Date("2020-01-31"), length.out = 150L)`: exactly two of 'to', 'by' and 'length.out' / 'along.with' must be specified
Backtrace:
▆
1. ├─base::seq(as.Date("2020-01-31"), length.out = 150L) at test_pipeop_datefeatures.R:7:3
2. └─base::seq.Date(as.Date("2020-01-31"), length.out = 150L)
── Error ('test_pipeop_datefeatures.R:17:3'): PipeOpDateFeatures - finds POSIXct column ──
Error in `seq.Date(as.Date("2020-01-31"), length.out = 150L)`: exactly two of 'to', 'by' and 'length.out' / 'along.with' must be specified
Backtrace:
▆
1. ├─base::seq(as.Date("2020-01-31"), length.out = 150L) at test_pipeop_datefeatures.R:17:3
2. └─base::seq.Date(as.Date("2020-01-31"), length.out = 150L)
── Error ('test_pipeop_nmf.R:45:3'): PipeOpNMF - does not modify search path when NMF is not loaded, fix for #929 ──
Error in `detach(package:generics)`: invalid 'name' argument
Backtrace:
▆
1. └─base::detach(package:generics) at test_pipeop_nmf.R:45:3
── Failure ('test_pipeop_nmf.R:73:3'): PipeOpNMF - does not modify search path when NMF is loaded, fix for #929 ──
Expected `all(...)` to be TRUE.
Differences:
`actual`: FALSE
`expected`: TRUE
── Failure ('test_pipeop_nmf.R:93:3'): PipeOpNMF - does not modify search path when some of NMF's dependencies are loaded, fix for #929 ──
Expected `all(paste0("package:", c("BiocGenerics", "generics")) %in% search())` to be TRUE.
Differences:
`actual`: FALSE
`expected`: TRUE
── Error ('test_pipeop_nmf.R:98:3'): PipeOpNMF - does not modify search path when some of NMF's dependencies are loaded, fix for #929 ──
Error in `FUN(X[[i]], ...)`: invalid 'name' argument
This happened in PipeOp nmf's $train()
Backtrace:
▆
1. ├─op$train(list(tsk("iris"))) at test_pipeop_nmf.R:98:3
2. │ └─mlr3pipelines:::.__PipeOp__train(...)
3. │ ├─base::withCallingHandlers(...)
4. │ └─private$.train(input)
5. │ └─mlr3pipelines:::.__PipeOpTaskPreproc__.train(...)
6. │ └─private$.train_task(intask)
7. │ └─mlr3pipelines:::.__PipeOpTaskPreproc__.train_task(...)
8. │ ├─data.table::as.data.table(...)
9. │ └─private$.train_dt(dt, task$levels(cols), task$truth())
10. │ └─mlr3pipelines:::.__PipeOpNMF__.train_dt(...)
11. │ └─mlr3misc::map(to_be_detached, detach, character.only = TRUE)
12. │ └─base::lapply(.x, .f, ...)
13. │ └─base (local) FUN(X[[i]], ...)
14. │ └─base::stop("invalid 'name' argument")
15. └─base::.handleSimpleError(...)
16. └─mlr3pipelines (local) h(simpleError(msg, call))
[ FAIL 6 | WARN 0 | SKIP 99 | PASS 13006 ]
Error:
! Test failures.
Execution halted
Flavor: r-oldrel-windows-x86_64
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.