Last updated on 2025-12-20 13:50:23 CET.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 0.10.1 | 8.17 | 156.74 | 164.91 | ERROR | |
| r-devel-linux-x86_64-debian-gcc | 0.10.1 | 4.37 | 103.62 | 107.99 | ERROR | |
| r-devel-linux-x86_64-fedora-clang | 0.10.1 | 12.00 | 252.41 | 264.41 | ERROR | |
| r-devel-linux-x86_64-fedora-gcc | 0.10.1 | 12.00 | 234.62 | 246.62 | 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 | 251.00 | 264.00 | 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 [04:35:29.782] [mlr3] Running benchmark with 40 resampling iterations
INFO [04:35:30.057] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 1/10)
INFO [04:35:30.141] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 2/10)
INFO [04:35:30.179] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 3/10)
INFO [04:35:30.238] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 4/10)
INFO [04:35:30.311] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 5/10)
INFO [04:35:30.410] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 6/10)
INFO [04:35:30.446] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 7/10)
INFO [04:35:30.630] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 8/10)
INFO [04:35:30.664] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 9/10)
INFO [04:35:30.699] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 10/10)
INFO [04:35:30.850] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/10)
INFO [04:35:30.918] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 2/10)
INFO [04:35:30.962] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 3/10)
INFO [04:35:31.178] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 4/10)
INFO [04:35:31.243] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 5/10)
INFO [04:35:31.350] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 6/10)
INFO [04:35:31.465] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 7/10)
INFO [04:35:31.564] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 8/10)
INFO [04:35:31.962] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 9/10)
INFO [04:35:32.017] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 10/10)
INFO [04:35:32.064] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 1/10)
INFO [04:35:32.109] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 2/10)
INFO [04:35:32.161] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 3/10)
INFO [04:35:32.240] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 4/10)
INFO [04:35:32.274] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 5/10)
INFO [04:35:32.317] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 6/10)
INFO [04:35:32.351] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 7/10)
INFO [04:35:32.421] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 8/10)
INFO [04:35:32.472] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 9/10)
INFO [04:35:32.551] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 10/10)
INFO [04:35:32.585] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 1/10)
INFO [04:35:32.649] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 2/10)
INFO [04:35:32.752] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 3/10)
INFO [04:35:32.821] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 4/10)
INFO [04:35:32.890] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 5/10)
INFO [04:35:32.951] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 6/10)
INFO [04:35:33.016] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 7/10)
INFO [04:35:33.077] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 8/10)
INFO [04:35:33.139] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 9/10)
INFO [04:35:33.214] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 10/10)
INFO [04:35:33.296] [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’ [79s/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_OptimInstanceSingleCrit.R: Loading required namespace: mlr3learners
> 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_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 50 | 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_LearnerClassifCVGlmnet.R:8:1',
'test_LearnerClassifRpart.R:6:1', '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]]$hash), by = "uhash"]
7. └─data.table:::`[.data.table`(...)
[ FAIL 7 | WARN 50 | SKIP 20 | PASS 63 ]
Deleting unused snapshots: 'BenchmarkResult/bmr-boxplot.svg',
'BenchmarkResult/bmr-holdout-ci.svg', 'BenchmarkResult/bmr-holdout-roc.svg',
'BenchmarkResult/bmr-prc.svg', 'BenchmarkResult/bmr-roc.svg',
'LearnerClassif/learner-classif-prob.svg',
'LearnerClustHierarchical/learner-clust-agnes.svg',
'LearnerClustHierarchical/learner-clust-hclust.svg',
'PredictionClust/predictionclust-pca.svg',
'PredictionClust/predictionclust-scatter.svg',
'PredictionClust/predictionclust-sil.svg',
'ResampleResult/resampleresult-boxplot.svg',
'ResampleResult/resampleresult-histogram.svg',
'ResampleResult/resampleresult-prc.svg',
'ResampleResult/resampleresult-roc.svg',
'TuningInstanceSingleCrit/tisc-incumbent.svg',
'TuningInstanceSingleCrit/tisc-marginal-01.svg',
'TuningInstanceSingleCrit/tisc-marginal-02.svg', …,
'plot_learner_prediction/learner-prediction-prob.svg', and
'plot_learner_prediction/learner-prediction-response.svg'
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-debian-clang
Version: 0.10.1
Check: examples
Result: ERROR
Running examples in ‘mlr3viz-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: autoplot.BenchmarkResult
> ### Title: Plots for Benchmark Results
> ### Aliases: autoplot.BenchmarkResult
>
> ### ** Examples
>
> if (requireNamespace("mlr3")) {
+ library(mlr3)
+ library(mlr3viz)
+
+ tasks = tsks(c("pima", "sonar"))
+ learner = lrns(c("classif.featureless", "classif.rpart"),
+ predict_type = "prob")
+ resampling = rsmps("cv")
+ object = benchmark(benchmark_grid(tasks, learner, resampling))
+
+ head(fortify(object))
+ autoplot(object)
+ autoplot(object$clone(deep = TRUE)$filter(task_ids = "pima"), type = "roc")
+ }
Loading required namespace: mlr3
INFO [17:13:45.103] [mlr3] Running benchmark with 40 resampling iterations
INFO [17:13:45.217] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 1/10)
INFO [17:13:45.280] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 2/10)
INFO [17:13:45.312] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 3/10)
INFO [17:13:45.336] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 4/10)
INFO [17:13:45.363] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 5/10)
INFO [17:13:45.383] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 6/10)
INFO [17:13:45.404] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 7/10)
INFO [17:13:45.514] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 8/10)
INFO [17:13:45.576] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 9/10)
INFO [17:13:45.604] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 10/10)
INFO [17:13:45.631] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/10)
INFO [17:13:45.693] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 2/10)
INFO [17:13:45.726] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 3/10)
INFO [17:13:45.769] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 4/10)
INFO [17:13:45.802] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 5/10)
INFO [17:13:45.833] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 6/10)
INFO [17:13:45.876] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 7/10)
INFO [17:13:45.906] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 8/10)
INFO [17:13:46.100] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 9/10)
INFO [17:13:46.125] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 10/10)
INFO [17:13:46.151] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 1/10)
INFO [17:13:46.177] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 2/10)
INFO [17:13:46.204] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 3/10)
INFO [17:13:46.232] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 4/10)
INFO [17:13:46.271] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 5/10)
INFO [17:13:46.315] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 6/10)
INFO [17:13:46.341] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 7/10)
INFO [17:13:46.376] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 8/10)
INFO [17:13:46.450] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 9/10)
INFO [17:13:46.496] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 10/10)
INFO [17:13:46.522] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 1/10)
INFO [17:13:46.567] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 2/10)
INFO [17:13:46.612] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 3/10)
INFO [17:13:46.647] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 4/10)
INFO [17:13:46.684] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 5/10)
INFO [17:13:46.721] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 6/10)
INFO [17:13:46.760] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 7/10)
INFO [17:13:46.800] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 8/10)
INFO [17:13:46.840] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 9/10)
INFO [17:13:46.886] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 10/10)
INFO [17:13:46.934] [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/29s]
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_OptimInstanceSingleCrit.R: Loading required namespace: mlr3learners
> 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_TuningInstanceSingleCrit.R: Loading required package: mlr3
> 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 50 | 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_LearnerClassifCVGlmnet.R:8:1',
'test_LearnerClassifRpart.R:6:1', '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 50 | 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 [17:51:57.263] [mlr3] Running benchmark with 40 resampling iterations
INFO [17:51:57.821] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 1/10)
INFO [17:51:57.953] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 2/10)
INFO [17:51:58.076] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 3/10)
INFO [17:51:58.179] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 4/10)
INFO [17:51:58.309] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 5/10)
INFO [17:51:58.448] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 6/10)
INFO [17:51:58.507] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 7/10)
INFO [17:51:58.804] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 8/10)
INFO [17:51:58.930] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 9/10)
INFO [17:51:59.030] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 10/10)
INFO [17:51:59.192] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/10)
INFO [17:51:59.447] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 2/10)
INFO [17:51:59.647] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 3/10)
INFO [17:51:59.849] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 4/10)
INFO [17:52:00.014] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 5/10)
INFO [17:52:00.145] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 6/10)
INFO [17:52:00.297] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 7/10)
INFO [17:52:00.466] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 8/10)
INFO [17:52:00.820] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 9/10)
INFO [17:52:00.884] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 10/10)
INFO [17:52:00.993] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 1/10)
INFO [17:52:01.140] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 2/10)
INFO [17:52:01.221] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 3/10)
INFO [17:52:01.333] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 4/10)
INFO [17:52:01.479] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 5/10)
INFO [17:52:01.608] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 6/10)
INFO [17:52:01.706] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 7/10)
INFO [17:52:01.762] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 8/10)
INFO [17:52:01.841] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 9/10)
INFO [17:52:01.893] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 10/10)
INFO [17:52:02.004] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 1/10)
INFO [17:52:02.238] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 2/10)
INFO [17:52:02.496] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 3/10)
INFO [17:52:02.664] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 4/10)
INFO [17:52:02.761] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 5/10)
INFO [17:52:02.961] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 6/10)
INFO [17:52:03.170] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 7/10)
INFO [17:52:03.374] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 8/10)
INFO [17:52:03.579] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 9/10)
INFO [17:52:03.825] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 10/10)
INFO [17:52:03.987] [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’ [135s/127s]
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: paradox
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_LearnerClassifCVGlmnet.R:8:1', 'test_EnsembleFSResult.R:4:1',
'test_LearnerClassifRpart.R:6:1', 'test_LearnerClasssifGlmnet.R:8:1',
'test_LearnerClustHierarchical.R:7:3', '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_TaskClassif.R:3:1', 'test_TaskRegr.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]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
[ FAIL 7 | WARN 51 | SKIP 20 | PASS 63 ]
Deleting unused snapshots: 'BenchmarkResult/bmr-boxplot.svg',
'BenchmarkResult/bmr-holdout-ci.svg', 'BenchmarkResult/bmr-holdout-roc.svg',
'BenchmarkResult/bmr-prc.svg', 'BenchmarkResult/bmr-roc.svg',
'LearnerClassif/learner-classif-prob.svg',
'LearnerClustHierarchical/learner-clust-agnes.svg',
'LearnerClustHierarchical/learner-clust-hclust.svg',
'PredictionClust/predictionclust-pca.svg',
'PredictionClust/predictionclust-scatter.svg',
'PredictionClust/predictionclust-sil.svg',
'ResampleResult/resampleresult-boxplot.svg',
'ResampleResult/resampleresult-histogram.svg',
'ResampleResult/resampleresult-prc.svg',
'ResampleResult/resampleresult-roc.svg',
'TuningInstanceSingleCrit/tisc-incumbent.svg',
'TuningInstanceSingleCrit/tisc-marginal-01.svg',
'TuningInstanceSingleCrit/tisc-marginal-02.svg', …,
'plot_learner_prediction/learner-prediction-prob.svg', and
'plot_learner_prediction/learner-prediction-response.svg'
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 0.10.1
Check: examples
Result: ERROR
Running examples in ‘mlr3viz-Ex.R’ failed
The error most likely occurred in:
> ### Name: autoplot.BenchmarkResult
> ### Title: Plots for Benchmark Results
> ### Aliases: autoplot.BenchmarkResult
>
> ### ** Examples
>
> if (requireNamespace("mlr3")) {
+ library(mlr3)
+ library(mlr3viz)
+
+ tasks = tsks(c("pima", "sonar"))
+ learner = lrns(c("classif.featureless", "classif.rpart"),
+ predict_type = "prob")
+ resampling = rsmps("cv")
+ object = benchmark(benchmark_grid(tasks, learner, resampling))
+
+ head(fortify(object))
+ autoplot(object)
+ autoplot(object$clone(deep = TRUE)$filter(task_ids = "pima"), type = "roc")
+ }
Loading required namespace: mlr3
INFO [12:31:59.527] [mlr3] Running benchmark with 40 resampling iterations
INFO [12:31:59.933] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 1/10)
INFO [12:32:00.106] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 2/10)
INFO [12:32:00.197] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 3/10)
INFO [12:32:00.328] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 4/10)
INFO [12:32:00.477] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 5/10)
INFO [12:32:00.571] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 6/10)
INFO [12:32:00.664] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 7/10)
INFO [12:32:00.860] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 8/10)
INFO [12:32:00.907] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 9/10)
INFO [12:32:00.952] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 10/10)
INFO [12:32:01.041] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/10)
INFO [12:32:01.160] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 2/10)
INFO [12:32:01.285] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 3/10)
INFO [12:32:01.365] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 4/10)
INFO [12:32:01.513] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 5/10)
INFO [12:32:01.637] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 6/10)
INFO [12:32:01.802] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 7/10)
INFO [12:32:01.922] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 8/10)
INFO [12:32:02.520] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 9/10)
INFO [12:32:02.613] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 10/10)
INFO [12:32:02.682] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 1/10)
INFO [12:32:02.770] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 2/10)
INFO [12:32:02.847] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 3/10)
INFO [12:32:02.982] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 4/10)
INFO [12:32:03.091] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 5/10)
INFO [12:32:03.177] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 6/10)
INFO [12:32:03.324] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 7/10)
INFO [12:32:03.427] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 8/10)
INFO [12:32:03.556] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 9/10)
INFO [12:32:03.638] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 10/10)
INFO [12:32:03.783] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 1/10)
INFO [12:32:04.022] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 2/10)
INFO [12:32:04.202] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 3/10)
INFO [12:32:04.418] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 4/10)
INFO [12:32:04.603] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 5/10)
INFO [12:32:04.808] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 6/10)
INFO [12:32:04.951] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 7/10)
INFO [12:32:05.076] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 8/10)
INFO [12:32:05.254] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 9/10)
INFO [12:32:05.447] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 10/10)
INFO [12:32:05.667] [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’ [127s/112s]
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_LearnerClustHierarchical.R:7:3',
'test_LearnerClasssifGlmnet.R:8:1', '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_TaskClassif.R:3:1',
'test_TaskClust.R:4:1', 'test_TaskRegr.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-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