Last updated on 2025-12-24 03:51:07 CET.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 0.10.1 | 7.04 | 157.26 | 164.30 | ERROR | |
| r-devel-linux-x86_64-debian-gcc | 0.10.1 | 4.75 | 105.65 | 110.40 | ERROR | |
| r-devel-linux-x86_64-fedora-clang | 0.10.1 | 13.00 | 262.56 | 275.56 | ERROR | |
| r-devel-linux-x86_64-fedora-gcc | 0.10.1 | 13.00 | 234.43 | 247.43 | ERROR | |
| r-devel-windows-x86_64 | 0.10.1 | 9.00 | 187.00 | 196.00 | OK | |
| r-patched-linux-x86_64 | 0.10.1 | 7.06 | 241.43 | 248.49 | OK | |
| r-release-linux-x86_64 | 0.10.1 | 7.40 | 244.33 | 251.73 | OK | |
| r-release-macos-arm64 | 0.10.1 | OK | ||||
| r-release-macos-x86_64 | 0.10.1 | 4.00 | 127.00 | 131.00 | OK | |
| r-release-windows-x86_64 | 0.10.1 | 10.00 | 187.00 | 197.00 | OK | |
| r-oldrel-macos-arm64 | 0.10.1 | NOTE | ||||
| r-oldrel-macos-x86_64 | 0.10.1 | 5.00 | 139.00 | 144.00 | NOTE | |
| r-oldrel-windows-x86_64 | 0.10.1 | 13.00 | 260.00 | 273.00 | NOTE |
Version: 0.10.1
Check: examples
Result: ERROR
Running examples in ‘mlr3viz-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: autoplot.BenchmarkResult
> ### Title: Plots for Benchmark Results
> ### Aliases: autoplot.BenchmarkResult
>
> ### ** Examples
>
> if (requireNamespace("mlr3")) {
+ library(mlr3)
+ library(mlr3viz)
+
+ tasks = tsks(c("pima", "sonar"))
+ learner = lrns(c("classif.featureless", "classif.rpart"),
+ predict_type = "prob")
+ resampling = rsmps("cv")
+ object = benchmark(benchmark_grid(tasks, learner, resampling))
+
+ head(fortify(object))
+ autoplot(object)
+ autoplot(object$clone(deep = TRUE)$filter(task_ids = "pima"), type = "roc")
+ }
Loading required namespace: mlr3
INFO [04:35:40.215] [mlr3] Running benchmark with 40 resampling iterations
INFO [04:35:40.412] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 1/10)
INFO [04:35:40.480] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 2/10)
INFO [04:35:40.511] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 3/10)
INFO [04:35:40.543] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 4/10)
INFO [04:35:40.582] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 5/10)
INFO [04:35:40.611] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 6/10)
INFO [04:35:40.641] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 7/10)
INFO [04:35:40.728] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 8/10)
INFO [04:35:40.759] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 9/10)
INFO [04:35:40.791] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 10/10)
INFO [04:35:40.824] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/10)
INFO [04:35:40.890] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 2/10)
INFO [04:35:40.928] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 3/10)
INFO [04:35:40.976] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 4/10)
INFO [04:35:41.016] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 5/10)
INFO [04:35:41.055] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 6/10)
INFO [04:35:41.103] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 7/10)
INFO [04:35:41.143] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 8/10)
INFO [04:35:41.353] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 9/10)
INFO [04:35:41.394] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 10/10)
INFO [04:35:41.435] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 1/10)
INFO [04:35:41.476] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 2/10)
INFO [04:35:41.517] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 3/10)
INFO [04:35:41.551] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 4/10)
INFO [04:35:41.584] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 5/10)
INFO [04:35:41.627] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 6/10)
INFO [04:35:41.660] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 7/10)
INFO [04:35:41.693] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 8/10)
INFO [04:35:41.733] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 9/10)
INFO [04:35:41.770] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 10/10)
INFO [04:35:41.805] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 1/10)
INFO [04:35:41.862] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 2/10)
INFO [04:35:41.921] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 3/10)
INFO [04:35:41.971] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 4/10)
INFO [04:35:42.024] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 5/10)
INFO [04:35:42.077] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 6/10)
INFO [04:35:42.130] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 7/10)
INFO [04:35:42.184] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 8/10)
INFO [04:35:42.239] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 9/10)
INFO [04:35:42.301] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 10/10)
INFO [04:35:42.369] [mlr3] Finished benchmark
Error in `[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash") :
attempt access index 9/9 in VECTOR_ELT
Calls: benchmark ... initialize -> .__ResultData__initialize -> [ -> [.data.table
Execution halted
Flavor: r-devel-linux-x86_64-debian-clang
Version: 0.10.1
Check: tests
Result: ERROR
Running ‘testthat.R’ [81s/43s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("testthat")
+ library("mlr3viz")
+ test_check("mlr3viz")
+ }
Starting 2 test processes.
> test_EnsembleFSResult.R: Loading required namespace: vdiffr
Saving _problems/test_BenchmarkResult-7.R
> test_Filter.R: Loading required namespace: vdiffr
Saving _problems/test_LearnerClassif-6.R
> test_OptimInstanceSingleCrit.R: Loading required package: paradox
> test_PredictionRegr.R: `stat_bin()` using `bins = 30`. Pick better value `binwidth`.
Saving _problems/test_ResampleResult-7.R
> test_TaskClassif.R: `stat_bin()` using `bins = 30`. Pick better value `binwidth`.
> test_TaskClassif.R: `stat_bin()` using `bins = 30`. Pick better value `binwidth`.
> test_TaskClassif.R: `stat_bin()` using `bins = 30`. Pick better value `binwidth`.
> test_TaskClassif.R: `stat_bin()` using `bins = 30`. Pick better value `binwidth`.
Saving _problems/test_plot_learner_prediction-8.R
Saving _problems/test_plot_learner_prediction-41.R
Saving _problems/test_plot_learner_prediction-51.R
Saving _problems/test_TuningInstanceSingleCrit-24.R
[ FAIL 7 | WARN 51 | SKIP 20 | PASS 63 ]
══ Skipped tests (20) ══════════════════════════════════════════════════════════
• On CRAN (20): 'test_Filter.R:3:1', 'test_LearnerClassif.R:11:1',
'test_EnsembleFSResult.R:4:1', 'test_LearnerClassifRpart.R:6:1',
'test_LearnerClassifCVGlmnet.R:8:1', 'test_LearnerClasssifGlmnet.R:8:1',
'test_LearnerClustHierarchical.R:7:3', 'test_LearnerRegrCVGlmnet.R:8:1',
'test_LearnerRegr.R:1:1', 'test_LearnerRegr.R:11:1',
'test_LearnerRegr.R:21:1', 'test_LearnerRegrGlmnet.R:7:1',
'test_LearnerRegrRpart.R:6:1', 'test_PredictionClassif.R:8:1',
'test_PredictionClust.R:8:3', 'test_PredictionRegr.R:3:1',
'test_OptimInstanceSingleCrit.R:35:1', 'test_TaskClust.R:4:1',
'test_TaskRegr.R:3:1', 'test_TaskClassif.R:3:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_BenchmarkResult.R:7:1'): (code run outside of `test_that()`) ───
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(mlr3::benchmark_grid(tasks, learner, resampling)) at test_BenchmarkResult.R:7:1
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_LearnerClassif.R:6:3'): autoplot.PredictionClassif decision boundary probability ──
Error in ``[.data.table`(grid, , `:=`(".prob.response", .SD[, paste0("prob.", get("response")), with = FALSE]), by = "response")`: attempt access index 7/7 in VECTOR_ELT
Backtrace:
▆
1. ├─ggplot2::autoplot(learner, type = "prediction", task = task) at test_LearnerClassif.R:6:3
2. ├─mlr3viz:::autoplot.LearnerClassifRpart(...)
3. ├─base::NextMethod()
4. └─mlr3viz:::autoplot.LearnerClassif(...)
5. └─mlr3viz:::predict_grid(...)
6. ├─...[]
7. └─data.table:::`[.data.table`(...)
── Error ('test_ResampleResult.R:7:1'): (code run outside of `test_that()`) ────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling) at test_ResampleResult.R:7:1
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_plot_learner_prediction.R:8:3'): plot_learner_prediction.LearnerClassif ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3viz::plot_learner_prediction(learner, task, expand_range = 0.1) at test_plot_learner_prediction.R:8:3
2. └─mlr3::resample(...)
3. └─ResultData$new(data, data_extra, store_backends = store_backends)
4. └─mlr3 (local) initialize(...)
5. └─mlr3:::.__ResultData__initialize(...)
6. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
7. └─data.table:::`[.data.table`(...)
── Error ('test_plot_learner_prediction.R:41:3'): plot_learner_prediction.LearnerRegr 2d ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3viz::plot_learner_prediction(learner, task, expand_range = 0.1) at test_plot_learner_prediction.R:41:3
2. └─mlr3::resample(...)
3. └─ResultData$new(data, data_extra, store_backends = store_backends)
4. └─mlr3 (local) initialize(...)
5. └─mlr3:::.__ResultData__initialize(...)
6. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
7. └─data.table:::`[.data.table`(...)
── Error ('test_plot_learner_prediction.R:51:3'): plot_learner_prediction.LearnerRegr 1d ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3viz::plot_learner_prediction(learner, task, expand_range = 0.1) at test_plot_learner_prediction.R:51:3
2. └─mlr3::resample(...)
3. └─ResultData$new(data, data_extra, store_backends = store_backends)
4. └─mlr3 (local) initialize(...)
5. └─mlr3:::.__ResultData__initialize(...)
6. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
7. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceSingleCrit.R:24:1'): (code run outside of `test_that()`) ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance)
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
[ FAIL 7 | WARN 51 | SKIP 20 | PASS 63 ]
Deleting unused snapshots: 'BenchmarkResult/bmr-boxplot.svg',
'BenchmarkResult/bmr-holdout-ci.svg', 'BenchmarkResult/bmr-holdout-roc.svg',
'BenchmarkResult/bmr-prc.svg', 'BenchmarkResult/bmr-roc.svg',
'LearnerClassif/learner-classif-prob.svg',
'LearnerClustHierarchical/learner-clust-agnes.svg',
'LearnerClustHierarchical/learner-clust-hclust.svg',
'PredictionClust/predictionclust-pca.svg',
'PredictionClust/predictionclust-scatter.svg',
'PredictionClust/predictionclust-sil.svg',
'ResampleResult/resampleresult-boxplot.svg',
'ResampleResult/resampleresult-histogram.svg',
'ResampleResult/resampleresult-prc.svg',
'ResampleResult/resampleresult-roc.svg',
'TuningInstanceSingleCrit/tisc-incumbent.svg',
'TuningInstanceSingleCrit/tisc-marginal-01.svg',
'TuningInstanceSingleCrit/tisc-marginal-02.svg', …,
'plot_learner_prediction/learner-prediction-prob.svg', and
'plot_learner_prediction/learner-prediction-response.svg'
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-debian-clang
Version: 0.10.1
Check: examples
Result: ERROR
Running examples in ‘mlr3viz-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: autoplot.BenchmarkResult
> ### Title: Plots for Benchmark Results
> ### Aliases: autoplot.BenchmarkResult
>
> ### ** Examples
>
> if (requireNamespace("mlr3")) {
+ library(mlr3)
+ library(mlr3viz)
+
+ tasks = tsks(c("pima", "sonar"))
+ learner = lrns(c("classif.featureless", "classif.rpart"),
+ predict_type = "prob")
+ resampling = rsmps("cv")
+ object = benchmark(benchmark_grid(tasks, learner, resampling))
+
+ head(fortify(object))
+ autoplot(object)
+ autoplot(object$clone(deep = TRUE)$filter(task_ids = "pima"), type = "roc")
+ }
Loading required namespace: mlr3
INFO [17:15:47.006] [mlr3] Running benchmark with 40 resampling iterations
INFO [17:15:47.132] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 1/10)
INFO [17:15:47.229] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 2/10)
INFO [17:15:47.284] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 3/10)
INFO [17:15:47.371] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 4/10)
INFO [17:15:47.511] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 5/10)
INFO [17:15:47.556] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 6/10)
INFO [17:15:47.632] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 7/10)
INFO [17:15:47.801] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 8/10)
INFO [17:15:47.895] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 9/10)
INFO [17:15:47.972] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 10/10)
INFO [17:15:48.047] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/10)
INFO [17:15:48.104] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 2/10)
INFO [17:15:48.139] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 3/10)
INFO [17:15:48.222] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 4/10)
INFO [17:15:48.293] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 5/10)
INFO [17:15:48.342] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 6/10)
INFO [17:15:48.431] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 7/10)
INFO [17:15:48.482] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 8/10)
INFO [17:15:48.678] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 9/10)
INFO [17:15:48.703] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 10/10)
INFO [17:15:48.729] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 1/10)
INFO [17:15:48.754] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 2/10)
INFO [17:15:48.793] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 3/10)
INFO [17:15:48.834] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 4/10)
INFO [17:15:48.905] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 5/10)
INFO [17:15:48.977] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 6/10)
INFO [17:15:49.048] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 7/10)
INFO [17:15:49.125] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 8/10)
INFO [17:15:49.204] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 9/10)
INFO [17:15:49.267] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 10/10)
INFO [17:15:49.311] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 1/10)
INFO [17:15:49.357] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 2/10)
INFO [17:15:49.415] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 3/10)
INFO [17:15:49.498] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 4/10)
INFO [17:15:49.582] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 5/10)
INFO [17:15:49.673] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 6/10)
INFO [17:15:49.722] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 7/10)
INFO [17:15:49.764] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 8/10)
INFO [17:15:49.815] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 9/10)
INFO [17:15:49.875] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 10/10)
INFO [17:15:49.938] [mlr3] Finished benchmark
Error in `[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash") :
attempt access index 9/9 in VECTOR_ELT
Calls: benchmark ... initialize -> .__ResultData__initialize -> [ -> [.data.table
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 0.10.1
Check: tests
Result: ERROR
Running ‘testthat.R’ [52s/28s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("testthat")
+ library("mlr3viz")
+ test_check("mlr3viz")
+ }
Starting 2 test processes.
> test_EnsembleFSResult.R: Loading required namespace: vdiffr
Saving _problems/test_BenchmarkResult-7.R
> test_Filter.R: Loading required namespace: vdiffr
Saving _problems/test_LearnerClassif-6.R
> test_OptimInstanceSingleCrit.R: Loading required package: paradox
> test_PredictionRegr.R: `stat_bin()` using `bins = 30`. Pick better value `binwidth`.
Saving _problems/test_ResampleResult-7.R
> test_TaskClassif.R: `stat_bin()` using `bins = 30`. Pick better value `binwidth`.
> test_TaskClassif.R: `stat_bin()` using `bins = 30`. Pick better value `binwidth`.
> test_TaskClassif.R: `stat_bin()` using `bins = 30`. Pick better value `binwidth`.
> test_TaskClassif.R: `stat_bin()` using `bins = 30`. Pick better value `binwidth`.
> test_TuningInstanceSingleCrit.R: Loading required package: mlr3
Saving _problems/test_plot_learner_prediction-8.R
Saving _problems/test_plot_learner_prediction-41.R
Saving _problems/test_plot_learner_prediction-51.R
Saving _problems/test_TuningInstanceSingleCrit-24.R
[ FAIL 7 | WARN 51 | SKIP 20 | PASS 63 ]
══ Skipped tests (20) ══════════════════════════════════════════════════════════
• On CRAN (20): 'test_Filter.R:3:1', 'test_LearnerClassif.R:11:1',
'test_EnsembleFSResult.R:4:1', 'test_LearnerClassifRpart.R:6:1',
'test_LearnerClassifCVGlmnet.R:8:1', 'test_LearnerClasssifGlmnet.R:8:1',
'test_LearnerClustHierarchical.R:7:3', 'test_LearnerRegr.R:1:1',
'test_LearnerRegr.R:11:1', 'test_LearnerRegr.R:21:1',
'test_LearnerRegrCVGlmnet.R:8:1', 'test_LearnerRegrGlmnet.R:7:1',
'test_LearnerRegrRpart.R:6:1', 'test_PredictionClassif.R:8:1',
'test_PredictionClust.R:8:3', 'test_PredictionRegr.R:3:1',
'test_OptimInstanceSingleCrit.R:35:1', 'test_TaskClust.R:4:1',
'test_TaskRegr.R:3:1', 'test_TaskClassif.R:3:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_BenchmarkResult.R:7:1'): (code run outside of `test_that()`) ───
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(mlr3::benchmark_grid(tasks, learner, resampling)) at test_BenchmarkResult.R:7:1
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_LearnerClassif.R:6:3'): autoplot.PredictionClassif decision boundary probability ──
Error in ``[.data.table`(grid, , `:=`(".prob.response", .SD[, paste0("prob.", get("response")), with = FALSE]), by = "response")`: attempt access index 7/7 in VECTOR_ELT
Backtrace:
▆
1. ├─ggplot2::autoplot(learner, type = "prediction", task = task) at test_LearnerClassif.R:6:3
2. ├─mlr3viz:::autoplot.LearnerClassifRpart(...)
3. ├─base::NextMethod()
4. └─mlr3viz:::autoplot.LearnerClassif(...)
5. └─mlr3viz:::predict_grid(...)
6. ├─...[]
7. └─data.table:::`[.data.table`(...)
── Error ('test_ResampleResult.R:7:1'): (code run outside of `test_that()`) ────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling) at test_ResampleResult.R:7:1
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_plot_learner_prediction.R:8:3'): plot_learner_prediction.LearnerClassif ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3viz::plot_learner_prediction(learner, task, expand_range = 0.1) at test_plot_learner_prediction.R:8:3
2. └─mlr3::resample(...)
3. └─ResultData$new(data, data_extra, store_backends = store_backends)
4. └─mlr3 (local) initialize(...)
5. └─mlr3:::.__ResultData__initialize(...)
6. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
7. └─data.table:::`[.data.table`(...)
── Error ('test_plot_learner_prediction.R:41:3'): plot_learner_prediction.LearnerRegr 2d ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3viz::plot_learner_prediction(learner, task, expand_range = 0.1) at test_plot_learner_prediction.R:41:3
2. └─mlr3::resample(...)
3. └─ResultData$new(data, data_extra, store_backends = store_backends)
4. └─mlr3 (local) initialize(...)
5. └─mlr3:::.__ResultData__initialize(...)
6. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
7. └─data.table:::`[.data.table`(...)
── Error ('test_plot_learner_prediction.R:51:3'): plot_learner_prediction.LearnerRegr 1d ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3viz::plot_learner_prediction(learner, task, expand_range = 0.1) at test_plot_learner_prediction.R:51:3
2. └─mlr3::resample(...)
3. └─ResultData$new(data, data_extra, store_backends = store_backends)
4. └─mlr3 (local) initialize(...)
5. └─mlr3:::.__ResultData__initialize(...)
6. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
7. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceSingleCrit.R:24:1'): (code run outside of `test_that()`) ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance)
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
[ FAIL 7 | WARN 51 | SKIP 20 | PASS 63 ]
Deleting unused snapshots: 'BenchmarkResult/bmr-boxplot.svg',
'BenchmarkResult/bmr-holdout-ci.svg', 'BenchmarkResult/bmr-holdout-roc.svg',
'BenchmarkResult/bmr-prc.svg', 'BenchmarkResult/bmr-roc.svg',
'LearnerClassif/learner-classif-prob.svg',
'LearnerClustHierarchical/learner-clust-agnes.svg',
'LearnerClustHierarchical/learner-clust-hclust.svg',
'PredictionClust/predictionclust-pca.svg',
'PredictionClust/predictionclust-scatter.svg',
'PredictionClust/predictionclust-sil.svg',
'ResampleResult/resampleresult-boxplot.svg',
'ResampleResult/resampleresult-histogram.svg',
'ResampleResult/resampleresult-prc.svg',
'ResampleResult/resampleresult-roc.svg',
'TuningInstanceSingleCrit/tisc-incumbent.svg',
'TuningInstanceSingleCrit/tisc-marginal-01.svg',
'TuningInstanceSingleCrit/tisc-marginal-02.svg', …,
'plot_learner_prediction/learner-prediction-prob.svg', and
'plot_learner_prediction/learner-prediction-response.svg'
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 0.10.1
Check: examples
Result: ERROR
Running examples in ‘mlr3viz-Ex.R’ failed
The error most likely occurred in:
> ### Name: autoplot.BenchmarkResult
> ### Title: Plots for Benchmark Results
> ### Aliases: autoplot.BenchmarkResult
>
> ### ** Examples
>
> if (requireNamespace("mlr3")) {
+ library(mlr3)
+ library(mlr3viz)
+
+ tasks = tsks(c("pima", "sonar"))
+ learner = lrns(c("classif.featureless", "classif.rpart"),
+ predict_type = "prob")
+ resampling = rsmps("cv")
+ object = benchmark(benchmark_grid(tasks, learner, resampling))
+
+ head(fortify(object))
+ autoplot(object)
+ autoplot(object$clone(deep = TRUE)$filter(task_ids = "pima"), type = "roc")
+ }
Loading required namespace: mlr3
INFO [09:23:55.908] [mlr3] Running benchmark with 40 resampling iterations
INFO [09:23:56.720] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 1/10)
INFO [09:23:57.107] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 2/10)
INFO [09:23:57.441] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 3/10)
INFO [09:23:57.576] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 4/10)
INFO [09:23:58.520] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 5/10)
INFO [09:23:58.781] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 6/10)
INFO [09:23:58.969] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 7/10)
INFO [09:23:59.331] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 8/10)
INFO [09:23:59.511] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 9/10)
INFO [09:23:59.610] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 10/10)
INFO [09:23:59.731] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/10)
INFO [09:24:00.005] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 2/10)
INFO [09:24:00.150] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 3/10)
INFO [09:24:01.903] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 4/10)
INFO [09:24:02.372] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 5/10)
INFO [09:24:02.563] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 6/10)
INFO [09:24:02.769] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 7/10)
INFO [09:24:02.931] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 8/10)
INFO [09:24:03.736] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 9/10)
INFO [09:24:03.963] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 10/10)
INFO [09:24:04.197] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 1/10)
INFO [09:24:04.382] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 2/10)
INFO [09:24:04.535] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 3/10)
INFO [09:24:04.704] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 4/10)
INFO [09:24:04.872] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 5/10)
INFO [09:24:05.074] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 6/10)
INFO [09:24:05.267] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 7/10)
INFO [09:24:05.444] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 8/10)
INFO [09:24:05.625] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 9/10)
INFO [09:24:05.740] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 10/10)
INFO [09:24:05.959] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 1/10)
INFO [09:24:06.066] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 2/10)
INFO [09:24:06.169] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 3/10)
INFO [09:24:06.826] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 4/10)
INFO [09:24:06.915] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 5/10)
INFO [09:24:07.003] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 6/10)
INFO [09:24:07.506] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 7/10)
INFO [09:24:07.794] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 8/10)
INFO [09:24:08.003] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 9/10)
INFO [09:24:08.188] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 10/10)
INFO [09:24:08.496] [mlr3] Finished benchmark
Error in `[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash") :
attempt access index 9/9 in VECTOR_ELT
Calls: benchmark ... initialize -> .__ResultData__initialize -> [ -> [.data.table
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 0.10.1
Check: tests
Result: ERROR
Running ‘testthat.R’ [138s/221s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("testthat")
+ library("mlr3viz")
+ test_check("mlr3viz")
+ }
Starting 2 test processes.
> test_EnsembleFSResult.R: Loading required namespace: vdiffr
Saving _problems/test_BenchmarkResult-7.R
> test_Filter.R: Loading required namespace: vdiffr
Saving _problems/test_LearnerClassif-6.R
> test_OptimInstanceSingleCrit.R: Loading required package: paradox
> test_PredictionRegr.R: `stat_bin()` using `bins = 30`. Pick better value `binwidth`.
Saving _problems/test_ResampleResult-7.R
> test_TaskClassif.R: `stat_bin()` using `bins = 30`. Pick better value `binwidth`.
> test_TaskClassif.R: `stat_bin()` using `bins = 30`. Pick better value `binwidth`.
> test_TaskClassif.R: `stat_bin()` using `bins = 30`. Pick better value `binwidth`.
> test_TaskClassif.R: `stat_bin()` using `bins = 30`. Pick better value `binwidth`.
Saving _problems/test_TuningInstanceSingleCrit-24.R
Saving _problems/test_plot_learner_prediction-8.R
Saving _problems/test_plot_learner_prediction-41.R
Saving _problems/test_plot_learner_prediction-51.R
[ FAIL 7 | WARN 51 | SKIP 20 | PASS 63 ]
══ Skipped tests (20) ══════════════════════════════════════════════════════════
• On CRAN (20): 'test_Filter.R:3:1', 'test_LearnerClassif.R:11:1',
'test_EnsembleFSResult.R:4:1', 'test_LearnerClassifRpart.R:6:1',
'test_LearnerClassifCVGlmnet.R:8:1', 'test_LearnerClustHierarchical.R:7:3',
'test_LearnerClasssifGlmnet.R:8:1', 'test_LearnerRegrCVGlmnet.R:8:1',
'test_LearnerRegrGlmnet.R:7:1', 'test_LearnerRegr.R:1:1',
'test_LearnerRegr.R:11:1', 'test_LearnerRegr.R:21:1',
'test_LearnerRegrRpart.R:6:1', 'test_PredictionClassif.R:8:1',
'test_PredictionClust.R:8:3', 'test_PredictionRegr.R:3:1',
'test_OptimInstanceSingleCrit.R:35:1', 'test_TaskClust.R:4:1',
'test_TaskRegr.R:3:1', 'test_TaskClassif.R:3:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_BenchmarkResult.R:7:1'): (code run outside of `test_that()`) ───
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(mlr3::benchmark_grid(tasks, learner, resampling)) at test_BenchmarkResult.R:7:1
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_LearnerClassif.R:6:3'): autoplot.PredictionClassif decision boundary probability ──
Error in ``[.data.table`(grid, , `:=`(".prob.response", .SD[, paste0("prob.", get("response")), with = FALSE]), by = "response")`: attempt access index 7/7 in VECTOR_ELT
Backtrace:
▆
1. ├─ggplot2::autoplot(learner, type = "prediction", task = task) at test_LearnerClassif.R:6:3
2. ├─mlr3viz:::autoplot.LearnerClassifRpart(...)
3. ├─base::NextMethod()
4. └─mlr3viz:::autoplot.LearnerClassif(...)
5. └─mlr3viz:::predict_grid(...)
6. ├─...[]
7. └─data.table:::`[.data.table`(...)
── Error ('test_ResampleResult.R:7:1'): (code run outside of `test_that()`) ────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling) at test_ResampleResult.R:7:1
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceSingleCrit.R:24:1'): (code run outside of `test_that()`) ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance)
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_plot_learner_prediction.R:8:3'): plot_learner_prediction.LearnerClassif ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3viz::plot_learner_prediction(learner, task, expand_range = 0.1) at test_plot_learner_prediction.R:8:3
2. └─mlr3::resample(...)
3. └─ResultData$new(data, data_extra, store_backends = store_backends)
4. └─mlr3 (local) initialize(...)
5. └─mlr3:::.__ResultData__initialize(...)
6. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
7. └─data.table:::`[.data.table`(...)
── Error ('test_plot_learner_prediction.R:41:3'): plot_learner_prediction.LearnerRegr 2d ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3viz::plot_learner_prediction(learner, task, expand_range = 0.1) at test_plot_learner_prediction.R:41:3
2. └─mlr3::resample(...)
3. └─ResultData$new(data, data_extra, store_backends = store_backends)
4. └─mlr3 (local) initialize(...)
5. └─mlr3:::.__ResultData__initialize(...)
6. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
7. └─data.table:::`[.data.table`(...)
── Error ('test_plot_learner_prediction.R:51:3'): plot_learner_prediction.LearnerRegr 1d ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3viz::plot_learner_prediction(learner, task, expand_range = 0.1) at test_plot_learner_prediction.R:51:3
2. └─mlr3::resample(...)
3. └─ResultData$new(data, data_extra, store_backends = store_backends)
4. └─mlr3 (local) initialize(...)
5. └─mlr3:::.__ResultData__initialize(...)
6. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
7. └─data.table:::`[.data.table`(...)
[ FAIL 7 | WARN 51 | SKIP 20 | PASS 63 ]
Deleting unused snapshots: 'BenchmarkResult/bmr-boxplot.svg',
'BenchmarkResult/bmr-holdout-ci.svg', 'BenchmarkResult/bmr-holdout-roc.svg',
'BenchmarkResult/bmr-prc.svg', 'BenchmarkResult/bmr-roc.svg',
'LearnerClassif/learner-classif-prob.svg',
'LearnerClustHierarchical/learner-clust-agnes.svg',
'LearnerClustHierarchical/learner-clust-hclust.svg',
'PredictionClust/predictionclust-pca.svg',
'PredictionClust/predictionclust-scatter.svg',
'PredictionClust/predictionclust-sil.svg',
'ResampleResult/resampleresult-boxplot.svg',
'ResampleResult/resampleresult-histogram.svg',
'ResampleResult/resampleresult-prc.svg',
'ResampleResult/resampleresult-roc.svg',
'TuningInstanceSingleCrit/tisc-incumbent.svg',
'TuningInstanceSingleCrit/tisc-marginal-01.svg',
'TuningInstanceSingleCrit/tisc-marginal-02.svg', …,
'plot_learner_prediction/learner-prediction-prob.svg', and
'plot_learner_prediction/learner-prediction-response.svg'
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 0.10.1
Check: examples
Result: ERROR
Running examples in ‘mlr3viz-Ex.R’ failed
The error most likely occurred in:
> ### Name: autoplot.BenchmarkResult
> ### Title: Plots for Benchmark Results
> ### Aliases: autoplot.BenchmarkResult
>
> ### ** Examples
>
> if (requireNamespace("mlr3")) {
+ library(mlr3)
+ library(mlr3viz)
+
+ tasks = tsks(c("pima", "sonar"))
+ learner = lrns(c("classif.featureless", "classif.rpart"),
+ predict_type = "prob")
+ resampling = rsmps("cv")
+ object = benchmark(benchmark_grid(tasks, learner, resampling))
+
+ head(fortify(object))
+ autoplot(object)
+ autoplot(object$clone(deep = TRUE)$filter(task_ids = "pima"), type = "roc")
+ }
Loading required namespace: mlr3
INFO [02:08:29.650] [mlr3] Running benchmark with 40 resampling iterations
INFO [02:08:30.020] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 1/10)
INFO [02:08:30.149] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 2/10)
INFO [02:08:30.247] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 3/10)
INFO [02:08:30.326] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 4/10)
INFO [02:08:30.398] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 5/10)
INFO [02:08:30.471] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 6/10)
INFO [02:08:30.547] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 7/10)
INFO [02:08:30.636] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 8/10)
INFO [02:08:30.743] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 9/10)
INFO [02:08:30.789] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 10/10)
INFO [02:08:30.906] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/10)
INFO [02:08:31.001] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 2/10)
INFO [02:08:31.063] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 3/10)
INFO [02:08:31.136] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 4/10)
INFO [02:08:31.198] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 5/10)
INFO [02:08:31.262] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 6/10)
INFO [02:08:31.326] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 7/10)
INFO [02:08:31.402] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 8/10)
INFO [02:08:31.465] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 9/10)
INFO [02:08:31.531] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 10/10)
INFO [02:08:31.599] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 1/10)
INFO [02:08:31.653] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 2/10)
INFO [02:08:31.703] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 3/10)
INFO [02:08:31.747] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 4/10)
INFO [02:08:31.840] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 5/10)
INFO [02:08:31.916] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 6/10)
INFO [02:08:31.994] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 7/10)
INFO [02:08:32.077] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 8/10)
INFO [02:08:32.134] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 9/10)
INFO [02:08:32.188] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 10/10)
INFO [02:08:32.278] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 1/10)
INFO [02:08:32.380] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 2/10)
INFO [02:08:32.507] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 3/10)
INFO [02:08:32.593] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 4/10)
INFO [02:08:32.710] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 5/10)
INFO [02:08:32.814] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 6/10)
INFO [02:08:32.894] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 7/10)
INFO [02:08:32.972] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 8/10)
INFO [02:08:33.053] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 9/10)
INFO [02:08:33.137] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 10/10)
INFO [02:08:33.267] [mlr3] Finished benchmark
Error in `[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash") :
attempt access index 9/9 in VECTOR_ELT
Calls: benchmark ... initialize -> .__ResultData__initialize -> [ -> [.data.table
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc
Version: 0.10.1
Check: tests
Result: ERROR
Running ‘testthat.R’ [122s/90s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("testthat")
+ library("mlr3viz")
+ test_check("mlr3viz")
+ }
Starting 2 test processes.
Saving _problems/test_BenchmarkResult-7.R
> test_Filter.R: Loading required namespace: vdiffr
> test_EnsembleFSResult.R: Loading required namespace: vdiffr
Saving _problems/test_LearnerClassif-6.R
> test_OptimInstanceSingleCrit.R: Loading required package: paradox
> test_PredictionRegr.R: `stat_bin()` using `bins = 30`. Pick better value `binwidth`.
Saving _problems/test_ResampleResult-7.R
> test_TaskClassif.R: `stat_bin()` using `bins = 30`. Pick better value `binwidth`.
> test_TaskClassif.R: `stat_bin()` using `bins = 30`. Pick better value `binwidth`.
> test_TaskClassif.R: `stat_bin()` using `bins = 30`. Pick better value `binwidth`.
> test_TaskClassif.R: `stat_bin()` using `bins = 30`. Pick better value `binwidth`.
> test_TuningInstanceSingleCrit.R: Loading required package: paradox
Saving _problems/test_TuningInstanceSingleCrit-24.R
Saving _problems/test_plot_learner_prediction-8.R
Saving _problems/test_plot_learner_prediction-41.R
Saving _problems/test_plot_learner_prediction-51.R
[ FAIL 7 | WARN 51 | SKIP 20 | PASS 63 ]
══ Skipped tests (20) ══════════════════════════════════════════════════════════
• On CRAN (20): 'test_Filter.R:3:1', 'test_LearnerClassif.R:11:1',
'test_LearnerClassifCVGlmnet.R:8:1', 'test_EnsembleFSResult.R:4:1',
'test_LearnerClassifRpart.R:6:1', 'test_LearnerClustHierarchical.R:7:3',
'test_LearnerClasssifGlmnet.R:8:1', 'test_LearnerRegr.R:1:1',
'test_LearnerRegr.R:11:1', 'test_LearnerRegr.R:21:1',
'test_LearnerRegrGlmnet.R:7:1', 'test_LearnerRegrCVGlmnet.R:8:1',
'test_LearnerRegrRpart.R:6:1', 'test_PredictionClassif.R:8:1',
'test_PredictionClust.R:8:3', 'test_PredictionRegr.R:3:1',
'test_OptimInstanceSingleCrit.R:35:1', 'test_TaskClassif.R:3:1',
'test_TaskRegr.R:3:1', 'test_TaskClust.R:4:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_BenchmarkResult.R:7:1'): (code run outside of `test_that()`) ───
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(mlr3::benchmark_grid(tasks, learner, resampling)) at test_BenchmarkResult.R:7:1
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_LearnerClassif.R:6:3'): autoplot.PredictionClassif decision boundary probability ──
Error in ``[.data.table`(grid, , `:=`(".prob.response", .SD[, paste0("prob.", get("response")), with = FALSE]), by = "response")`: attempt access index 7/7 in VECTOR_ELT
Backtrace:
▆
1. ├─ggplot2::autoplot(learner, type = "prediction", task = task) at test_LearnerClassif.R:6:3
2. ├─mlr3viz:::autoplot.LearnerClassifRpart(...)
3. ├─base::NextMethod()
4. └─mlr3viz:::autoplot.LearnerClassif(...)
5. └─mlr3viz:::predict_grid(...)
6. ├─...[]
7. └─data.table:::`[.data.table`(...)
── Error ('test_ResampleResult.R:7:1'): (code run outside of `test_that()`) ────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling) at test_ResampleResult.R:7:1
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_TuningInstanceSingleCrit.R:24:1'): (code run outside of `test_that()`) ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance)
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_plot_learner_prediction.R:8:3'): plot_learner_prediction.LearnerClassif ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3viz::plot_learner_prediction(learner, task, expand_range = 0.1) at test_plot_learner_prediction.R:8:3
2. └─mlr3::resample(...)
3. └─ResultData$new(data, data_extra, store_backends = store_backends)
4. └─mlr3 (local) initialize(...)
5. └─mlr3:::.__ResultData__initialize(...)
6. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
7. └─data.table:::`[.data.table`(...)
── Error ('test_plot_learner_prediction.R:41:3'): plot_learner_prediction.LearnerRegr 2d ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3viz::plot_learner_prediction(learner, task, expand_range = 0.1) at test_plot_learner_prediction.R:41:3
2. └─mlr3::resample(...)
3. └─ResultData$new(data, data_extra, store_backends = store_backends)
4. └─mlr3 (local) initialize(...)
5. └─mlr3:::.__ResultData__initialize(...)
6. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
7. └─data.table:::`[.data.table`(...)
── Error ('test_plot_learner_prediction.R:51:3'): plot_learner_prediction.LearnerRegr 1d ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3viz::plot_learner_prediction(learner, task, expand_range = 0.1) at test_plot_learner_prediction.R:51:3
2. └─mlr3::resample(...)
3. └─ResultData$new(data, data_extra, store_backends = store_backends)
4. └─mlr3 (local) initialize(...)
5. └─mlr3:::.__ResultData__initialize(...)
6. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
7. └─data.table:::`[.data.table`(...)
[ FAIL 7 | WARN 51 | SKIP 20 | PASS 63 ]
Deleting unused snapshots: 'BenchmarkResult/bmr-boxplot.svg',
'BenchmarkResult/bmr-holdout-ci.svg', 'BenchmarkResult/bmr-holdout-roc.svg',
'BenchmarkResult/bmr-prc.svg', 'BenchmarkResult/bmr-roc.svg',
'LearnerClassif/learner-classif-prob.svg',
'LearnerClustHierarchical/learner-clust-agnes.svg',
'LearnerClustHierarchical/learner-clust-hclust.svg',
'PredictionClust/predictionclust-pca.svg',
'PredictionClust/predictionclust-scatter.svg',
'PredictionClust/predictionclust-sil.svg',
'ResampleResult/resampleresult-boxplot.svg',
'ResampleResult/resampleresult-histogram.svg',
'ResampleResult/resampleresult-prc.svg',
'ResampleResult/resampleresult-roc.svg',
'TuningInstanceSingleCrit/tisc-incumbent.svg',
'TuningInstanceSingleCrit/tisc-marginal-01.svg',
'TuningInstanceSingleCrit/tisc-marginal-02.svg', …,
'plot_learner_prediction/learner-prediction-prob.svg', and
'plot_learner_prediction/learner-prediction-response.svg'
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc
Version: 0.10.1
Check: package dependencies
Result: NOTE
Package suggested but not available for checking: ‘mlr3proba’
Flavors: r-oldrel-macos-arm64, r-oldrel-macos-x86_64, r-oldrel-windows-x86_64