CRAN Package Check Results for Package mlr3proba

Last updated on 2020-09-22 12:55:21 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 0.2.1 64.65 161.01 225.66 ERROR
r-devel-linux-x86_64-debian-gcc 0.2.1 52.20 124.17 176.37 ERROR
r-devel-linux-x86_64-fedora-clang 0.2.1 314.05 ERROR
r-devel-linux-x86_64-fedora-gcc 0.2.1 284.28 ERROR
r-devel-windows-ix86+x86_64 0.2.1 125.00 230.00 355.00 ERROR
r-patched-linux-x86_64 0.2.1 57.44 151.42 208.86 ERROR
r-patched-solaris-x86 0.2.1 345.20 ERROR
r-release-linux-x86_64 0.2.1 56.44 154.10 210.54 ERROR
r-release-macos-x86_64 0.2.1 OK
r-release-windows-ix86+x86_64 0.2.1 129.00 444.00 573.00 OK
r-oldrel-macos-x86_64 0.2.1 OK
r-oldrel-windows-ix86+x86_64 0.2.1 81.00 196.00 277.00 ERROR

Check Details

Version: 0.2.1
Check: examples
Result: ERROR
    Running examples in 'mlr3proba-Ex.R' failed
    The error most likely occurred in:
    
    > base::assign(".ptime", proc.time(), pos = "CheckExEnv")
    > ### Name: PredictionDens
    > ### Title: Prediction Object for Density
    > ### Aliases: PredictionDens
    >
    > ### ** Examples
    >
    > library(mlr3)
    > task = mlr_tasks$get("precip")
    > learner = mlr_learners$get("dens.hist")
    > p = learner$train(task)$predict(task)
    Error in UseMethod("check_prediction_data") :
     no applicable method for 'check_prediction_data' applied to an object of class "list"
    Calls: <Anonymous> ... .__Learner__predict -> as_prediction -> check_prediction_data
    Execution halted
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-patched-linux-x86_64, r-release-linux-x86_64

Version: 0.2.1
Check: tests
Result: ERROR
     Running 'testthat.R' [32s/37s]
    Running the tests in 'tests/testthat.R' failed.
    Complete output:
     > library(testthat)
     > library(checkmate) # for more expect_*() functions
     > library(mlr3proba)
     >
     > test_check("mlr3proba")
     -- 1. Failure: Construction (@test_PredictionDens.R#8) ------------------------
     Check on data.table::as.data.table(p) isn't true.
     Must have exactly 0 rows, but has 70 rows
    
     -- 2. Error: Internally constructed Prediction (@test_PredictionDens.R#12) ----
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     -- 3. Error: c (@test_PredictionDens.R#20) ------------------------------------
     Assertion on 'li' failed: May only contain the following types: {PredictionData}, but element 1 has type 'list'.
     Backtrace:
     1. rr$predictions()
     2. mlr3:::.__ResampleResult__predictions(...)
     3. mlr3:::as_predictions(self$data$prediction, predict_sets)
     4. mlr3misc::map(...)
     5. base::lapply(.x, .f, ...)
     6. mlr3:::FUN(X[[i]], ...)
     7. checkmate::assert_list(li, "PredictionData")
     8. checkmate::makeAssertion(x, res, .var.name, add)
     9. checkmate:::mstop(...)
    
     -- 4. Failure: Construction (@test_PredictionSurv.R#5) ------------------------
     Check on data.table::as.data.table(p) isn't true.
     Must have exactly 0 rows, but has 20 rows
    
     -- 5. Error: Internally constructed Prediction (@test_PredictionSurv.R#10) ----
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     -- 6. Error: c (@test_PredictionSurv.R#20) ------------------------------------
     Assertion on 'li' failed: May only contain the following types: {PredictionData}, but element 1 has type 'list'.
     Backtrace:
     1. rr$predictions()
     2. mlr3:::.__ResampleResult__predictions(...)
     3. mlr3:::as_predictions(self$data$prediction, predict_sets)
     4. mlr3misc::map(...)
     5. base::lapply(.x, .f, ...)
     6. mlr3:::FUN(X[[i]], ...)
     7. checkmate::assert_list(li, "PredictionData")
     8. checkmate::makeAssertion(x, res, .var.name, add)
     9. checkmate:::mstop(...)
    
     -- 7. Failure: autotest (@test_mlr_learners_density_hist.R#6) -----------------
     `result` isn't true.
     [predict()] learner 'dens.hist:pdf' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     -- 8. Failure: autotest (@test_mlr_learners_density_kde.R#6) ------------------
     `result` isn't true.
     [predict()] learner 'dens.kde:pdf' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     -- 9. Error: pdf (@test_mlr_learners_density_kde.R#18) ------------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. testthat::expect_equal(...)
     4. lrn$predict(task_test)
     5. mlr3:::.__Learner__predict(...)
     7. mlr3::check_prediction_data(pdata)
    
     -- 10. Error: bw (@test_mlr_learners_density_kde.R#32) ------------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. testthat::expect_equal(...)
     4. lrn$predict(task_test)
     5. mlr3:::.__Learner__predict(...)
     7. mlr3::check_prediction_data(pdata)
    
     -- 11. Failure: autotest (@test_mlr_learners_surv_coxph.R#8) ------------------
     `result` isn't true.
     [predict()] learner 'surv.coxph:distr' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     -- 12. Failure: weights (@test_mlr_learners_surv_coxph.R#14) ------------------
     `learner$train(task)` did not produce any warnings.
    
     -- 13. Failure: autotest (@test_mlr_learners_surv_kaplan.R#5) -----------------
     `result` isn't true.
     [predict()] learner 'surv.kaplan:crank' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     -- 14. Failure: autotest (@test_mlr_learners_surv_rpart.R#5) ------------------
     `result` isn't true.
     [predict()] learner 'surv.rpart:crank' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     -- 15. Error: (unknown) (@test_mlr_measures.R#4) ------------------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. learner$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     -- 16. Error: mlr_measures (@test_mlr_measures_dens.R#14) ---------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. mlr_learners$get("dens.hist")$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     -- 17. Error: crankcompositor (@test_pipelines.R#10) --------------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pipe$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     -- 18. Error: distrcompositor (@test_pipelines.R#21) --------------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pipe$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     -- 19. Error: survaverager (@test_pipelines.R#35) -----------------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pipe$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     -- 20. Error: survbagging (@test_pipelines.R#45) ------------------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pipe$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     -- 21. Error: PipeOpCrankCompositor - estimate (@test_pipeop_crankcompositor.R#1
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. gr$predict(task)
     2. mlr3pipelines:::.__Graph__predict(...)
     3. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     4. op[[fun]](input)
     5. mlr3pipelines:::.__PipeOp__predict(...)
     6. private$.predict(input)
     7. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     8. private$.learner$predict(task)
     9. mlr3:::.__Learner__predict(...)
     11. mlr3::check_prediction_data(pdata)
    
     -- 22. Error: no params (@test_pipeop_crankcompositor.R#18) -------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. po$predict(list(lrn("surv.kaplan")$train(task)$predict(task)))
     7. lrn("surv.kaplan")$train(task)$predict(task)
     8. mlr3:::.__Learner__predict(...)
     10. mlr3::check_prediction_data(pdata)
    
     -- 23. Error: response (@test_pipeop_crankcompositor.R#26) --------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. po$predict(list(lrn("surv.kaplan")$train(task)$predict(task)))
     7. lrn("surv.kaplan")$train(task)$predict(task)
     8. mlr3:::.__Learner__predict(...)
     10. mlr3::check_prediction_data(pdata)
    
     -- 24. Error: overwrite crank (@test_pipeop_crankcompositor.R#40) -------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pl$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     -- 25. Error: overwrite response (@test_pipeop_crankcompositor.R#56) ----------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn("surv.kaplan")$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     -- 26. Error: PipeOpDistrCompositor - overwrite = FALSE (@test_pipeop_distrcompo
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. testthat::expect_equal(...)
     4. gr$predict(task)
     5. mlr3pipelines:::.__Graph__predict(...)
     6. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     7. op[[fun]](input)
     8. mlr3pipelines:::.__PipeOp__predict(...)
     9. private$.predict(input)
     10. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     11. private$.learner$predict(task)
     12. mlr3:::.__Learner__predict(...)
     14. mlr3::check_prediction_data(pdata)
    
     -- 27. Error: PipeOpDistrCompositor - overwrite = TRUE (@test_pipeop_distrcompos
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. gr$predict(task)
     2. mlr3pipelines:::.__Graph__predict(...)
     3. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     4. op[[fun]](input)
     5. mlr3pipelines:::.__PipeOp__predict(...)
     6. private$.predict(input)
     7. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     8. private$.learner$predict(task)
     9. mlr3:::.__Learner__predict(...)
     11. mlr3::check_prediction_data(pdata)
    
     -- 28. Error: no params (@test_pipeop_distrcompositor.R#29) -------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn("surv.kaplan")$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     -- 29. Error: (unknown) (@test_pipeop_survavg.R#7) ----------------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn("surv.kaplan")$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     -- 30. Error: single-step (@test_single_step.R#10) ----------------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. learner$predict_newdata(task = train_task, newdata = newdata)
     2. mlr3:::.__Learner__predict_newdata(...)
     3. self$predict(task$rbind(newdata))
     4. mlr3:::.__Learner__predict(...)
     6. mlr3::check_prediction_data(pdata)
    
     == testthat results ===========================================================
     [ OK: 609 | SKIPPED: 2 | WARNINGS: 0 | FAILED: 30 ]
     1. Failure: Construction (@test_PredictionDens.R#8)
     2. Error: Internally constructed Prediction (@test_PredictionDens.R#12)
     3. Error: c (@test_PredictionDens.R#20)
     4. Failure: Construction (@test_PredictionSurv.R#5)
     5. Error: Internally constructed Prediction (@test_PredictionSurv.R#10)
     6. Error: c (@test_PredictionSurv.R#20)
     7. Failure: autotest (@test_mlr_learners_density_hist.R#6)
     8. Failure: autotest (@test_mlr_learners_density_kde.R#6)
     9. Error: pdf (@test_mlr_learners_density_kde.R#18)
     1. ...
    
     Error: testthat unit tests failed
     Execution halted
Flavor: r-devel-linux-x86_64-debian-clang

Version: 0.2.1
Check: re-building of vignette outputs
Result: WARN
    Error(s) in re-building vignettes:
     ...
    --- re-building 'density.Rmd' using rmarkdown
    Quitting from lines 54-74 (density.Rmd)
    Error: processing vignette 'density.Rmd' failed with diagnostics:
    no applicable method for 'check_prediction_data' applied to an object of class "list"
    --- failed re-building 'density.Rmd'
    
    SUMMARY: processing the following file failed:
     'density.Rmd'
    
    Error: Vignette re-building failed.
    Execution halted
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-patched-linux-x86_64, r-release-linux-x86_64

Version: 0.2.1
Check: tests
Result: ERROR
     Running ‘testthat.R’ [22s/37s]
    Running the tests in ‘tests/testthat.R’ failed.
    Complete output:
     > library(testthat)
     > library(checkmate) # for more expect_*() functions
     > library(mlr3proba)
     >
     > test_check("mlr3proba")
     ── 1. Failure: Construction (@test_PredictionDens.R#8) ────────────────────────
     Check on data.table::as.data.table(p) isn't true.
     Must have exactly 0 rows, but has 70 rows
    
     ── 2. Error: Internally constructed Prediction (@test_PredictionDens.R#12) ────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     ── 3. Error: c (@test_PredictionDens.R#20) ────────────────────────────────────
     Assertion on 'li' failed: May only contain the following types: {PredictionData}, but element 1 has type 'list'.
     Backtrace:
     1. rr$predictions()
     2. mlr3:::.__ResampleResult__predictions(...)
     3. mlr3:::as_predictions(self$data$prediction, predict_sets)
     4. mlr3misc::map(...)
     5. base::lapply(.x, .f, ...)
     6. mlr3:::FUN(X[[i]], ...)
     7. checkmate::assert_list(li, "PredictionData")
     8. checkmate::makeAssertion(x, res, .var.name, add)
     9. checkmate:::mstop(...)
    
     ── 4. Failure: Construction (@test_PredictionSurv.R#5) ────────────────────────
     Check on data.table::as.data.table(p) isn't true.
     Must have exactly 0 rows, but has 20 rows
    
     ── 5. Error: Internally constructed Prediction (@test_PredictionSurv.R#10) ────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     ── 6. Error: c (@test_PredictionSurv.R#20) ────────────────────────────────────
     Assertion on 'li' failed: May only contain the following types: {PredictionData}, but element 1 has type 'list'.
     Backtrace:
     1. rr$predictions()
     2. mlr3:::.__ResampleResult__predictions(...)
     3. mlr3:::as_predictions(self$data$prediction, predict_sets)
     4. mlr3misc::map(...)
     5. base::lapply(.x, .f, ...)
     6. mlr3:::FUN(X[[i]], ...)
     7. checkmate::assert_list(li, "PredictionData")
     8. checkmate::makeAssertion(x, res, .var.name, add)
     9. checkmate:::mstop(...)
    
     ── 7. Failure: autotest (@test_mlr_learners_density_hist.R#6) ─────────────────
     `result` isn't true.
     [predict()] learner 'dens.hist:pdf' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     ── 8. Failure: autotest (@test_mlr_learners_density_kde.R#6) ──────────────────
     `result` isn't true.
     [predict()] learner 'dens.kde:pdf' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     ── 9. Error: pdf (@test_mlr_learners_density_kde.R#18) ────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. testthat::expect_equal(...)
     4. lrn$predict(task_test)
     5. mlr3:::.__Learner__predict(...)
     7. mlr3::check_prediction_data(pdata)
    
     ── 10. Error: bw (@test_mlr_learners_density_kde.R#32) ────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. testthat::expect_equal(...)
     4. lrn$predict(task_test)
     5. mlr3:::.__Learner__predict(...)
     7. mlr3::check_prediction_data(pdata)
    
     ── 11. Failure: autotest (@test_mlr_learners_surv_coxph.R#8) ──────────────────
     `result` isn't true.
     [predict()] learner 'surv.coxph:distr' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     ── 12. Failure: weights (@test_mlr_learners_surv_coxph.R#14) ──────────────────
     `learner$train(task)` did not produce any warnings.
    
     ── 13. Failure: autotest (@test_mlr_learners_surv_kaplan.R#5) ─────────────────
     `result` isn't true.
     [predict()] learner 'surv.kaplan:crank' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     ── 14. Failure: autotest (@test_mlr_learners_surv_rpart.R#5) ──────────────────
     `result` isn't true.
     [predict()] learner 'surv.rpart:crank' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     ── 15. Error: (unknown) (@test_mlr_measures.R#4) ──────────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. learner$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     ── 16. Error: mlr_measures (@test_mlr_measures_dens.R#14) ─────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. mlr_learners$get("dens.hist")$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     ── 17. Error: crankcompositor (@test_pipelines.R#10) ──────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pipe$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     ── 18. Error: distrcompositor (@test_pipelines.R#21) ──────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pipe$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     ── 19. Error: survaverager (@test_pipelines.R#35) ─────────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pipe$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     ── 20. Error: survbagging (@test_pipelines.R#45) ──────────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pipe$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     ── 21. Error: PipeOpCrankCompositor - estimate (@test_pipeop_crankcompositor.R#1
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. gr$predict(task)
     2. mlr3pipelines:::.__Graph__predict(...)
     3. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     4. op[[fun]](input)
     5. mlr3pipelines:::.__PipeOp__predict(...)
     6. private$.predict(input)
     7. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     8. private$.learner$predict(task)
     9. mlr3:::.__Learner__predict(...)
     11. mlr3::check_prediction_data(pdata)
    
     ── 22. Error: no params (@test_pipeop_crankcompositor.R#18) ───────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. po$predict(list(lrn("surv.kaplan")$train(task)$predict(task)))
     7. lrn("surv.kaplan")$train(task)$predict(task)
     8. mlr3:::.__Learner__predict(...)
     10. mlr3::check_prediction_data(pdata)
    
     ── 23. Error: response (@test_pipeop_crankcompositor.R#26) ────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. po$predict(list(lrn("surv.kaplan")$train(task)$predict(task)))
     7. lrn("surv.kaplan")$train(task)$predict(task)
     8. mlr3:::.__Learner__predict(...)
     10. mlr3::check_prediction_data(pdata)
    
     ── 24. Error: overwrite crank (@test_pipeop_crankcompositor.R#40) ─────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pl$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     ── 25. Error: overwrite response (@test_pipeop_crankcompositor.R#56) ──────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn("surv.kaplan")$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     ── 26. Error: PipeOpDistrCompositor - overwrite = FALSE (@test_pipeop_distrcompo
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. testthat::expect_equal(...)
     4. gr$predict(task)
     5. mlr3pipelines:::.__Graph__predict(...)
     6. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     7. op[[fun]](input)
     8. mlr3pipelines:::.__PipeOp__predict(...)
     9. private$.predict(input)
     10. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     11. private$.learner$predict(task)
     12. mlr3:::.__Learner__predict(...)
     14. mlr3::check_prediction_data(pdata)
    
     ── 27. Error: PipeOpDistrCompositor - overwrite = TRUE (@test_pipeop_distrcompos
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. gr$predict(task)
     2. mlr3pipelines:::.__Graph__predict(...)
     3. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     4. op[[fun]](input)
     5. mlr3pipelines:::.__PipeOp__predict(...)
     6. private$.predict(input)
     7. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     8. private$.learner$predict(task)
     9. mlr3:::.__Learner__predict(...)
     11. mlr3::check_prediction_data(pdata)
    
     ── 28. Error: no params (@test_pipeop_distrcompositor.R#29) ───────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn("surv.kaplan")$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     ── 29. Error: (unknown) (@test_pipeop_survavg.R#7) ────────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn("surv.kaplan")$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     ── 30. Error: single-step (@test_single_step.R#10) ────────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. learner$predict_newdata(task = train_task, newdata = newdata)
     2. mlr3:::.__Learner__predict_newdata(...)
     3. self$predict(task$rbind(newdata))
     4. mlr3:::.__Learner__predict(...)
     6. mlr3::check_prediction_data(pdata)
    
     ══ testthat results ═══════════════════════════════════════════════════════════
     [ OK: 609 | SKIPPED: 2 | WARNINGS: 0 | FAILED: 30 ]
     1. Failure: Construction (@test_PredictionDens.R#8)
     2. Error: Internally constructed Prediction (@test_PredictionDens.R#12)
     3. Error: c (@test_PredictionDens.R#20)
     4. Failure: Construction (@test_PredictionSurv.R#5)
     5. Error: Internally constructed Prediction (@test_PredictionSurv.R#10)
     6. Error: c (@test_PredictionSurv.R#20)
     7. Failure: autotest (@test_mlr_learners_density_hist.R#6)
     8. Failure: autotest (@test_mlr_learners_density_kde.R#6)
     9. Error: pdf (@test_mlr_learners_density_kde.R#18)
     1. ...
    
     Error: testthat unit tests failed
     Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc

Version: 0.2.1
Check: package dependencies
Result: NOTE
    Suggests orphaned package: ‘bibtex’
Flavor: r-devel-linux-x86_64-fedora-clang

Version: 0.2.1
Check: Rd cross-references
Result: NOTE
    Undeclared package ‘bujar’ in Rd xrefs
Flavor: r-devel-linux-x86_64-fedora-clang

Version: 0.2.1
Check: examples
Result: ERROR
    Running examples in ‘mlr3proba-Ex.R’ failed
    The error most likely occurred in:
    
    > ### Name: PredictionDens
    > ### Title: Prediction Object for Density
    > ### Aliases: PredictionDens
    >
    > ### ** Examples
    >
    > library(mlr3)
    > task = mlr_tasks$get("precip")
    > learner = mlr_learners$get("dens.hist")
    > p = learner$train(task)$predict(task)
    Error in UseMethod("check_prediction_data") :
     no applicable method for 'check_prediction_data' applied to an object of class "list"
    Calls: <Anonymous> ... .__Learner__predict -> as_prediction -> check_prediction_data
    Execution halted
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-patched-solaris-x86

Version: 0.2.1
Check: tests
Result: ERROR
     Running ‘testthat.R’ [40s/59s]
    Running the tests in ‘tests/testthat.R’ failed.
    Complete output:
     > library(testthat)
     > library(checkmate) # for more expect_*() functions
     > library(mlr3proba)
     >
     > test_check("mlr3proba")
     ── 1. Failure: Construction (@test_PredictionDens.R#8) ────────────────────────
     Check on data.table::as.data.table(p) isn't true.
     Must have exactly 0 rows, but has 70 rows
    
     ── 2. Error: Internally constructed Prediction (@test_PredictionDens.R#12) ────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     ── 3. Error: c (@test_PredictionDens.R#20) ────────────────────────────────────
     Assertion on 'li' failed: May only contain the following types: {PredictionData}, but element 1 has type 'list'.
     Backtrace:
     1. rr$predictions()
     2. mlr3:::.__ResampleResult__predictions(...)
     3. mlr3:::as_predictions(self$data$prediction, predict_sets)
     4. mlr3misc::map(...)
     5. base::lapply(.x, .f, ...)
     6. mlr3:::FUN(X[[i]], ...)
     7. checkmate::assert_list(li, "PredictionData")
     8. checkmate::makeAssertion(x, res, .var.name, add)
     9. checkmate:::mstop(...)
    
     ── 4. Failure: Construction (@test_PredictionSurv.R#5) ────────────────────────
     Check on data.table::as.data.table(p) isn't true.
     Must have exactly 0 rows, but has 20 rows
    
     ── 5. Error: Internally constructed Prediction (@test_PredictionSurv.R#10) ────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     ── 6. Error: c (@test_PredictionSurv.R#20) ────────────────────────────────────
     Assertion on 'li' failed: May only contain the following types: {PredictionData}, but element 1 has type 'list'.
     Backtrace:
     1. rr$predictions()
     2. mlr3:::.__ResampleResult__predictions(...)
     3. mlr3:::as_predictions(self$data$prediction, predict_sets)
     4. mlr3misc::map(...)
     5. base::lapply(.x, .f, ...)
     6. mlr3:::FUN(X[[i]], ...)
     7. checkmate::assert_list(li, "PredictionData")
     8. checkmate::makeAssertion(x, res, .var.name, add)
     9. checkmate:::mstop(...)
    
     ── 7. Failure: autotest (@test_mlr_learners_density_hist.R#6) ─────────────────
     `result` isn't true.
     [predict()] learner 'dens.hist:pdf' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     ── 8. Failure: autotest (@test_mlr_learners_density_kde.R#6) ──────────────────
     `result` isn't true.
     [predict()] learner 'dens.kde:pdf' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     ── 9. Error: pdf (@test_mlr_learners_density_kde.R#18) ────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. testthat::expect_equal(...)
     4. lrn$predict(task_test)
     5. mlr3:::.__Learner__predict(...)
     7. mlr3::check_prediction_data(pdata)
    
     ── 10. Error: bw (@test_mlr_learners_density_kde.R#32) ────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. testthat::expect_equal(...)
     4. lrn$predict(task_test)
     5. mlr3:::.__Learner__predict(...)
     7. mlr3::check_prediction_data(pdata)
    
     ── 11. Failure: autotest (@test_mlr_learners_surv_coxph.R#8) ──────────────────
     `result` isn't true.
     [predict()] learner 'surv.coxph:distr' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     ── 12. Failure: weights (@test_mlr_learners_surv_coxph.R#14) ──────────────────
     `learner$train(task)` did not produce any warnings.
    
     ── 13. Failure: autotest (@test_mlr_learners_surv_kaplan.R#5) ─────────────────
     `result` isn't true.
     [predict()] learner 'surv.kaplan:crank' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     ── 14. Failure: autotest (@test_mlr_learners_surv_rpart.R#5) ──────────────────
     `result` isn't true.
     [predict()] learner 'surv.rpart:crank' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     ── 15. Error: (unknown) (@test_mlr_measures.R#4) ──────────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. learner$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     ── 16. Error: mlr_measures (@test_mlr_measures_dens.R#14) ─────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. mlr_learners$get("dens.hist")$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     ── 17. Error: crankcompositor (@test_pipelines.R#10) ──────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pipe$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     ── 18. Error: distrcompositor (@test_pipelines.R#21) ──────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pipe$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     ── 19. Error: survaverager (@test_pipelines.R#35) ─────────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pipe$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     ── 20. Error: survbagging (@test_pipelines.R#45) ──────────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pipe$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     ── 21. Error: PipeOpCrankCompositor - estimate (@test_pipeop_crankcompositor.R#1
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. gr$predict(task)
     2. mlr3pipelines:::.__Graph__predict(...)
     3. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     4. op[[fun]](input)
     5. mlr3pipelines:::.__PipeOp__predict(...)
     6. private$.predict(input)
     7. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     8. private$.learner$predict(task)
     9. mlr3:::.__Learner__predict(...)
     11. mlr3::check_prediction_data(pdata)
    
     ── 22. Error: no params (@test_pipeop_crankcompositor.R#18) ───────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. po$predict(list(lrn("surv.kaplan")$train(task)$predict(task)))
     7. lrn("surv.kaplan")$train(task)$predict(task)
     8. mlr3:::.__Learner__predict(...)
     10. mlr3::check_prediction_data(pdata)
    
     ── 23. Error: response (@test_pipeop_crankcompositor.R#26) ────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. po$predict(list(lrn("surv.kaplan")$train(task)$predict(task)))
     7. lrn("surv.kaplan")$train(task)$predict(task)
     8. mlr3:::.__Learner__predict(...)
     10. mlr3::check_prediction_data(pdata)
    
     ── 24. Error: overwrite crank (@test_pipeop_crankcompositor.R#40) ─────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pl$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     ── 25. Error: overwrite response (@test_pipeop_crankcompositor.R#56) ──────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn("surv.kaplan")$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     ── 26. Error: PipeOpDistrCompositor - overwrite = FALSE (@test_pipeop_distrcompo
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. testthat::expect_equal(...)
     4. gr$predict(task)
     5. mlr3pipelines:::.__Graph__predict(...)
     6. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     7. op[[fun]](input)
     8. mlr3pipelines:::.__PipeOp__predict(...)
     9. private$.predict(input)
     10. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     11. private$.learner$predict(task)
     12. mlr3:::.__Learner__predict(...)
     14. mlr3::check_prediction_data(pdata)
    
     ── 27. Error: PipeOpDistrCompositor - overwrite = TRUE (@test_pipeop_distrcompos
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. gr$predict(task)
     2. mlr3pipelines:::.__Graph__predict(...)
     3. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     4. op[[fun]](input)
     5. mlr3pipelines:::.__PipeOp__predict(...)
     6. private$.predict(input)
     7. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     8. private$.learner$predict(task)
     9. mlr3:::.__Learner__predict(...)
     11. mlr3::check_prediction_data(pdata)
    
     ── 28. Error: no params (@test_pipeop_distrcompositor.R#29) ───────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn("surv.kaplan")$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     ── 29. Error: (unknown) (@test_pipeop_survavg.R#7) ────────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn("surv.kaplan")$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     ── 30. Error: single-step (@test_single_step.R#10) ────────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. learner$predict_newdata(task = train_task, newdata = newdata)
     2. mlr3:::.__Learner__predict_newdata(...)
     3. self$predict(task$rbind(newdata))
     4. mlr3:::.__Learner__predict(...)
     6. mlr3::check_prediction_data(pdata)
    
     ══ testthat results ═══════════════════════════════════════════════════════════
     [ OK: 609 | SKIPPED: 2 | WARNINGS: 0 | FAILED: 30 ]
     1. Failure: Construction (@test_PredictionDens.R#8)
     2. Error: Internally constructed Prediction (@test_PredictionDens.R#12)
     3. Error: c (@test_PredictionDens.R#20)
     4. Failure: Construction (@test_PredictionSurv.R#5)
     5. Error: Internally constructed Prediction (@test_PredictionSurv.R#10)
     6. Error: c (@test_PredictionSurv.R#20)
     7. Failure: autotest (@test_mlr_learners_density_hist.R#6)
     8. Failure: autotest (@test_mlr_learners_density_kde.R#6)
     9. Error: pdf (@test_mlr_learners_density_kde.R#18)
     1. ...
    
     Error: testthat unit tests failed
     Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang

Version: 0.2.1
Check: re-building of vignette outputs
Result: WARN
    Error(s) in re-building vignettes:
    --- re-building ‘density.Rmd’ using rmarkdown
    Quitting from lines 54-74 (density.Rmd)
    Error: processing vignette 'density.Rmd' failed with diagnostics:
    no applicable method for 'check_prediction_data' applied to an object of class "list"
    --- failed re-building ‘density.Rmd’
    
    SUMMARY: processing the following file failed:
     ‘density.Rmd’
    
    Error: Vignette re-building failed.
    Execution halted
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-ix86+x86_64, r-oldrel-windows-ix86+x86_64

Version: 0.2.1
Check: tests
Result: ERROR
     Running ‘testthat.R’ [35s/41s]
    Running the tests in ‘tests/testthat.R’ failed.
    Complete output:
     > library(testthat)
     > library(checkmate) # for more expect_*() functions
     > library(mlr3proba)
     >
     > test_check("mlr3proba")
     ── 1. Failure: Construction (@test_PredictionDens.R#8) ────────────────────────
     Check on data.table::as.data.table(p) isn't true.
     Must have exactly 0 rows, but has 70 rows
    
     ── 2. Error: Internally constructed Prediction (@test_PredictionDens.R#12) ────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     ── 3. Error: c (@test_PredictionDens.R#20) ────────────────────────────────────
     Assertion on 'li' failed: May only contain the following types: {PredictionData}, but element 1 has type 'list'.
     Backtrace:
     1. rr$predictions()
     2. mlr3:::.__ResampleResult__predictions(...)
     3. mlr3:::as_predictions(self$data$prediction, predict_sets)
     4. mlr3misc::map(...)
     5. base::lapply(.x, .f, ...)
     6. mlr3:::FUN(X[[i]], ...)
     7. checkmate::assert_list(li, "PredictionData")
     8. checkmate::makeAssertion(x, res, .var.name, add)
     9. checkmate:::mstop(...)
    
     ── 4. Failure: Construction (@test_PredictionSurv.R#5) ────────────────────────
     Check on data.table::as.data.table(p) isn't true.
     Must have exactly 0 rows, but has 20 rows
    
     ── 5. Error: Internally constructed Prediction (@test_PredictionSurv.R#10) ────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     ── 6. Error: c (@test_PredictionSurv.R#20) ────────────────────────────────────
     Assertion on 'li' failed: May only contain the following types: {PredictionData}, but element 1 has type 'list'.
     Backtrace:
     1. rr$predictions()
     2. mlr3:::.__ResampleResult__predictions(...)
     3. mlr3:::as_predictions(self$data$prediction, predict_sets)
     4. mlr3misc::map(...)
     5. base::lapply(.x, .f, ...)
     6. mlr3:::FUN(X[[i]], ...)
     7. checkmate::assert_list(li, "PredictionData")
     8. checkmate::makeAssertion(x, res, .var.name, add)
     9. checkmate:::mstop(...)
    
     ── 7. Failure: autotest (@test_mlr_learners_density_hist.R#6) ─────────────────
     `result` isn't true.
     [predict()] learner 'dens.hist:pdf' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     ── 8. Failure: autotest (@test_mlr_learners_density_kde.R#6) ──────────────────
     `result` isn't true.
     [predict()] learner 'dens.kde:pdf' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     ── 9. Error: pdf (@test_mlr_learners_density_kde.R#18) ────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. testthat::expect_equal(...)
     4. lrn$predict(task_test)
     5. mlr3:::.__Learner__predict(...)
     7. mlr3::check_prediction_data(pdata)
    
     ── 10. Error: bw (@test_mlr_learners_density_kde.R#32) ────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. testthat::expect_equal(...)
     4. lrn$predict(task_test)
     5. mlr3:::.__Learner__predict(...)
     7. mlr3::check_prediction_data(pdata)
    
     ── 11. Failure: autotest (@test_mlr_learners_surv_coxph.R#8) ──────────────────
     `result` isn't true.
     [predict()] learner 'surv.coxph:distr' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     ── 12. Failure: weights (@test_mlr_learners_surv_coxph.R#14) ──────────────────
     `learner$train(task)` did not produce any warnings.
    
     ── 13. Failure: autotest (@test_mlr_learners_surv_kaplan.R#5) ─────────────────
     `result` isn't true.
     [predict()] learner 'surv.kaplan:crank' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     ── 14. Failure: autotest (@test_mlr_learners_surv_rpart.R#5) ──────────────────
     `result` isn't true.
     [predict()] learner 'surv.rpart:crank' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     ── 15. Error: (unknown) (@test_mlr_measures.R#4) ──────────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. learner$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     ── 16. Error: mlr_measures (@test_mlr_measures_dens.R#14) ─────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. mlr_learners$get("dens.hist")$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     ── 17. Error: crankcompositor (@test_pipelines.R#10) ──────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pipe$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     ── 18. Error: distrcompositor (@test_pipelines.R#21) ──────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pipe$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     ── 19. Error: survaverager (@test_pipelines.R#35) ─────────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pipe$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     ── 20. Error: survbagging (@test_pipelines.R#45) ──────────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pipe$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     ── 21. Error: PipeOpCrankCompositor - estimate (@test_pipeop_crankcompositor.R#1
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. gr$predict(task)
     2. mlr3pipelines:::.__Graph__predict(...)
     3. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     4. op[[fun]](input)
     5. mlr3pipelines:::.__PipeOp__predict(...)
     6. private$.predict(input)
     7. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     8. private$.learner$predict(task)
     9. mlr3:::.__Learner__predict(...)
     11. mlr3::check_prediction_data(pdata)
    
     ── 22. Error: no params (@test_pipeop_crankcompositor.R#18) ───────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. po$predict(list(lrn("surv.kaplan")$train(task)$predict(task)))
     7. lrn("surv.kaplan")$train(task)$predict(task)
     8. mlr3:::.__Learner__predict(...)
     10. mlr3::check_prediction_data(pdata)
    
     ── 23. Error: response (@test_pipeop_crankcompositor.R#26) ────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. po$predict(list(lrn("surv.kaplan")$train(task)$predict(task)))
     7. lrn("surv.kaplan")$train(task)$predict(task)
     8. mlr3:::.__Learner__predict(...)
     10. mlr3::check_prediction_data(pdata)
    
     ── 24. Error: overwrite crank (@test_pipeop_crankcompositor.R#40) ─────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pl$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     ── 25. Error: overwrite response (@test_pipeop_crankcompositor.R#56) ──────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn("surv.kaplan")$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     ── 26. Error: PipeOpDistrCompositor - overwrite = FALSE (@test_pipeop_distrcompo
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. testthat::expect_equal(...)
     4. gr$predict(task)
     5. mlr3pipelines:::.__Graph__predict(...)
     6. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     7. op[[fun]](input)
     8. mlr3pipelines:::.__PipeOp__predict(...)
     9. private$.predict(input)
     10. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     11. private$.learner$predict(task)
     12. mlr3:::.__Learner__predict(...)
     14. mlr3::check_prediction_data(pdata)
    
     ── 27. Error: PipeOpDistrCompositor - overwrite = TRUE (@test_pipeop_distrcompos
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. gr$predict(task)
     2. mlr3pipelines:::.__Graph__predict(...)
     3. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     4. op[[fun]](input)
     5. mlr3pipelines:::.__PipeOp__predict(...)
     6. private$.predict(input)
     7. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     8. private$.learner$predict(task)
     9. mlr3:::.__Learner__predict(...)
     11. mlr3::check_prediction_data(pdata)
    
     ── 28. Error: no params (@test_pipeop_distrcompositor.R#29) ───────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn("surv.kaplan")$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     ── 29. Error: (unknown) (@test_pipeop_survavg.R#7) ────────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn("surv.kaplan")$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     ── 30. Error: single-step (@test_single_step.R#10) ────────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. learner$predict_newdata(task = train_task, newdata = newdata)
     2. mlr3:::.__Learner__predict_newdata(...)
     3. self$predict(task$rbind(newdata))
     4. mlr3:::.__Learner__predict(...)
     6. mlr3::check_prediction_data(pdata)
    
     ══ testthat results ═══════════════════════════════════════════════════════════
     [ OK: 609 | SKIPPED: 2 | WARNINGS: 0 | FAILED: 30 ]
     1. Failure: Construction (@test_PredictionDens.R#8)
     2. Error: Internally constructed Prediction (@test_PredictionDens.R#12)
     3. Error: c (@test_PredictionDens.R#20)
     4. Failure: Construction (@test_PredictionSurv.R#5)
     5. Error: Internally constructed Prediction (@test_PredictionSurv.R#10)
     6. Error: c (@test_PredictionSurv.R#20)
     7. Failure: autotest (@test_mlr_learners_density_hist.R#6)
     8. Failure: autotest (@test_mlr_learners_density_kde.R#6)
     9. Error: pdf (@test_mlr_learners_density_kde.R#18)
     1. ...
    
     Error: testthat unit tests failed
     Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc

Version: 0.2.1
Check: running examples for arch ‘i386’
Result: ERROR
    Running examples in 'mlr3proba-Ex.R' failed
    The error most likely occurred in:
    
    > ### Name: PredictionDens
    > ### Title: Prediction Object for Density
    > ### Aliases: PredictionDens
    >
    > ### ** Examples
    >
    > library(mlr3)
    > task = mlr_tasks$get("precip")
    > learner = mlr_learners$get("dens.hist")
    > p = learner$train(task)$predict(task)
    Error in UseMethod("check_prediction_data") :
     no applicable method for 'check_prediction_data' applied to an object of class "list"
    Calls: <Anonymous> ... .__Learner__predict -> as_prediction -> check_prediction_data
    Execution halted
Flavors: r-devel-windows-ix86+x86_64, r-oldrel-windows-ix86+x86_64

Version: 0.2.1
Check: running examples for arch ‘x64’
Result: ERROR
    Running examples in 'mlr3proba-Ex.R' failed
    The error most likely occurred in:
    
    > ### Name: PredictionDens
    > ### Title: Prediction Object for Density
    > ### Aliases: PredictionDens
    >
    > ### ** Examples
    >
    > library(mlr3)
    > task = mlr_tasks$get("precip")
    > learner = mlr_learners$get("dens.hist")
    > p = learner$train(task)$predict(task)
    Error in UseMethod("check_prediction_data") :
     no applicable method for 'check_prediction_data' applied to an object of class "list"
    Calls: <Anonymous> ... .__Learner__predict -> as_prediction -> check_prediction_data
    Execution halted
Flavors: r-devel-windows-ix86+x86_64, r-oldrel-windows-ix86+x86_64

Version: 0.2.1
Check: running tests for arch ‘i386’
Result: ERROR
     Running 'testthat.R' [25s]
    Running the tests in 'tests/testthat.R' failed.
    Complete output:
     > library(testthat)
     > library(checkmate) # for more expect_*() functions
     > library(mlr3proba)
     >
     > test_check("mlr3proba")
     -- 1. Failure: Construction (@test_PredictionDens.R#8) ------------------------
     Check on data.table::as.data.table(p) isn't true.
     Must have exactly 0 rows, but has 70 rows
    
     -- 2. Error: Internally constructed Prediction (@test_PredictionDens.R#12) ----
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     -- 3. Error: c (@test_PredictionDens.R#20) ------------------------------------
     Assertion on 'li' failed: May only contain the following types: {PredictionData}, but element 1 has type 'list'.
     Backtrace:
     1. rr$predictions()
     2. mlr3:::.__ResampleResult__predictions(...)
     3. mlr3:::as_predictions(self$data$prediction, predict_sets)
     4. mlr3misc::map(...)
     5. base::lapply(.x, .f, ...)
     6. mlr3:::FUN(X[[i]], ...)
     7. checkmate::assert_list(li, "PredictionData")
     8. checkmate::makeAssertion(x, res, .var.name, add)
     9. checkmate:::mstop(...)
    
     -- 4. Failure: Construction (@test_PredictionSurv.R#5) ------------------------
     Check on data.table::as.data.table(p) isn't true.
     Must have exactly 0 rows, but has 20 rows
    
     -- 5. Error: Internally constructed Prediction (@test_PredictionSurv.R#10) ----
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     -- 6. Error: c (@test_PredictionSurv.R#20) ------------------------------------
     Assertion on 'li' failed: May only contain the following types: {PredictionData}, but element 1 has type 'list'.
     Backtrace:
     1. rr$predictions()
     2. mlr3:::.__ResampleResult__predictions(...)
     3. mlr3:::as_predictions(self$data$prediction, predict_sets)
     4. mlr3misc::map(...)
     5. base::lapply(.x, .f, ...)
     6. mlr3:::FUN(X[[i]], ...)
     7. checkmate::assert_list(li, "PredictionData")
     8. checkmate::makeAssertion(x, res, .var.name, add)
     9. checkmate:::mstop(...)
    
     -- 7. Failure: autotest (@test_mlr_learners_density_hist.R#6) -----------------
     `result` isn't true.
     [predict()] learner 'dens.hist:pdf' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     -- 8. Failure: autotest (@test_mlr_learners_density_kde.R#6) ------------------
     `result` isn't true.
     [predict()] learner 'dens.kde:pdf' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     -- 9. Error: pdf (@test_mlr_learners_density_kde.R#18) ------------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. testthat::expect_equal(...)
     4. lrn$predict(task_test)
     5. mlr3:::.__Learner__predict(...)
     7. mlr3::check_prediction_data(pdata)
    
     -- 10. Error: bw (@test_mlr_learners_density_kde.R#32) ------------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. testthat::expect_equal(...)
     4. lrn$predict(task_test)
     5. mlr3:::.__Learner__predict(...)
     7. mlr3::check_prediction_data(pdata)
    
     -- 11. Failure: autotest (@test_mlr_learners_surv_coxph.R#8) ------------------
     `result` isn't true.
     [predict()] learner 'surv.coxph:distr' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     -- 12. Failure: weights (@test_mlr_learners_surv_coxph.R#14) ------------------
     `learner$train(task)` did not produce any warnings.
    
     -- 13. Failure: autotest (@test_mlr_learners_surv_kaplan.R#5) -----------------
     `result` isn't true.
     [predict()] learner 'surv.kaplan:crank' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     -- 14. Failure: autotest (@test_mlr_learners_surv_rpart.R#5) ------------------
     `result` isn't true.
     [predict()] learner 'surv.rpart:crank' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     -- 15. Error: (unknown) (@test_mlr_measures.R#4) ------------------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. learner$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     -- 16. Error: mlr_measures (@test_mlr_measures_dens.R#14) ---------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. mlr_learners$get("dens.hist")$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     -- 17. Error: crankcompositor (@test_pipelines.R#10) --------------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pipe$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     -- 18. Error: distrcompositor (@test_pipelines.R#21) --------------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pipe$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     -- 19. Error: survaverager (@test_pipelines.R#35) -----------------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pipe$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     -- 20. Error: survbagging (@test_pipelines.R#45) ------------------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pipe$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     -- 21. Error: PipeOpCrankCompositor - estimate (@test_pipeop_crankcompositor.R#1
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. gr$predict(task)
     2. mlr3pipelines:::.__Graph__predict(...)
     3. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     4. op[[fun]](input)
     5. mlr3pipelines:::.__PipeOp__predict(...)
     6. private$.predict(input)
     7. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     8. private$.learner$predict(task)
     9. mlr3:::.__Learner__predict(...)
     11. mlr3::check_prediction_data(pdata)
    
     -- 22. Error: no params (@test_pipeop_crankcompositor.R#18) -------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. po$predict(list(lrn("surv.kaplan")$train(task)$predict(task)))
     7. lrn("surv.kaplan")$train(task)$predict(task)
     8. mlr3:::.__Learner__predict(...)
     10. mlr3::check_prediction_data(pdata)
    
     -- 23. Error: response (@test_pipeop_crankcompositor.R#26) --------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. po$predict(list(lrn("surv.kaplan")$train(task)$predict(task)))
     7. lrn("surv.kaplan")$train(task)$predict(task)
     8. mlr3:::.__Learner__predict(...)
     10. mlr3::check_prediction_data(pdata)
    
     -- 24. Error: overwrite crank (@test_pipeop_crankcompositor.R#40) -------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pl$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     -- 25. Error: overwrite response (@test_pipeop_crankcompositor.R#56) ----------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn("surv.kaplan")$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     -- 26. Error: PipeOpDistrCompositor - overwrite = FALSE (@test_pipeop_distrcompo
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. testthat::expect_equal(...)
     4. gr$predict(task)
     5. mlr3pipelines:::.__Graph__predict(...)
     6. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     7. op[[fun]](input)
     8. mlr3pipelines:::.__PipeOp__predict(...)
     9. private$.predict(input)
     10. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     11. private$.learner$predict(task)
     12. mlr3:::.__Learner__predict(...)
     14. mlr3::check_prediction_data(pdata)
    
     -- 27. Error: PipeOpDistrCompositor - overwrite = TRUE (@test_pipeop_distrcompos
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. gr$predict(task)
     2. mlr3pipelines:::.__Graph__predict(...)
     3. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     4. op[[fun]](input)
     5. mlr3pipelines:::.__PipeOp__predict(...)
     6. private$.predict(input)
     7. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     8. private$.learner$predict(task)
     9. mlr3:::.__Learner__predict(...)
     11. mlr3::check_prediction_data(pdata)
    
     -- 28. Error: no params (@test_pipeop_distrcompositor.R#29) -------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn("surv.kaplan")$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     -- 29. Error: (unknown) (@test_pipeop_survavg.R#7) ----------------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn("surv.kaplan")$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     -- 30. Error: single-step (@test_single_step.R#10) ----------------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. learner$predict_newdata(task = train_task, newdata = newdata)
     2. mlr3:::.__Learner__predict_newdata(...)
     3. self$predict(task$rbind(newdata))
     4. mlr3:::.__Learner__predict(...)
     6. mlr3::check_prediction_data(pdata)
    
     == testthat results ===========================================================
     [ OK: 609 | SKIPPED: 2 | WARNINGS: 0 | FAILED: 30 ]
     1. Failure: Construction (@test_PredictionDens.R#8)
     2. Error: Internally constructed Prediction (@test_PredictionDens.R#12)
     3. Error: c (@test_PredictionDens.R#20)
     4. Failure: Construction (@test_PredictionSurv.R#5)
     5. Error: Internally constructed Prediction (@test_PredictionSurv.R#10)
     6. Error: c (@test_PredictionSurv.R#20)
     7. Failure: autotest (@test_mlr_learners_density_hist.R#6)
     8. Failure: autotest (@test_mlr_learners_density_kde.R#6)
     9. Error: pdf (@test_mlr_learners_density_kde.R#18)
     1. ...
    
     Error: testthat unit tests failed
     Execution halted
Flavor: r-devel-windows-ix86+x86_64

Version: 0.2.1
Check: running tests for arch ‘x64’
Result: ERROR
     Running 'testthat.R' [27s]
    Running the tests in 'tests/testthat.R' failed.
    Complete output:
     > library(testthat)
     > library(checkmate) # for more expect_*() functions
     > library(mlr3proba)
     >
     > test_check("mlr3proba")
     -- 1. Failure: Construction (@test_PredictionDens.R#8) ------------------------
     Check on data.table::as.data.table(p) isn't true.
     Must have exactly 0 rows, but has 70 rows
    
     -- 2. Error: Internally constructed Prediction (@test_PredictionDens.R#12) ----
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     -- 3. Error: c (@test_PredictionDens.R#20) ------------------------------------
     Assertion on 'li' failed: May only contain the following types: {PredictionData}, but element 1 has type 'list'.
     Backtrace:
     1. rr$predictions()
     2. mlr3:::.__ResampleResult__predictions(...)
     3. mlr3:::as_predictions(self$data$prediction, predict_sets)
     4. mlr3misc::map(...)
     5. base::lapply(.x, .f, ...)
     6. mlr3:::FUN(X[[i]], ...)
     7. checkmate::assert_list(li, "PredictionData")
     8. checkmate::makeAssertion(x, res, .var.name, add)
     9. checkmate:::mstop(...)
    
     -- 4. Failure: Construction (@test_PredictionSurv.R#5) ------------------------
     Check on data.table::as.data.table(p) isn't true.
     Must have exactly 0 rows, but has 20 rows
    
     -- 5. Error: Internally constructed Prediction (@test_PredictionSurv.R#10) ----
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     -- 6. Error: c (@test_PredictionSurv.R#20) ------------------------------------
     Assertion on 'li' failed: May only contain the following types: {PredictionData}, but element 1 has type 'list'.
     Backtrace:
     1. rr$predictions()
     2. mlr3:::.__ResampleResult__predictions(...)
     3. mlr3:::as_predictions(self$data$prediction, predict_sets)
     4. mlr3misc::map(...)
     5. base::lapply(.x, .f, ...)
     6. mlr3:::FUN(X[[i]], ...)
     7. checkmate::assert_list(li, "PredictionData")
     8. checkmate::makeAssertion(x, res, .var.name, add)
     9. checkmate:::mstop(...)
    
     -- 7. Failure: autotest (@test_mlr_learners_density_hist.R#6) -----------------
     `result` isn't true.
     [predict()] learner 'dens.hist:pdf' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     -- 8. Failure: autotest (@test_mlr_learners_density_kde.R#6) ------------------
     `result` isn't true.
     [predict()] learner 'dens.kde:pdf' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     -- 9. Error: pdf (@test_mlr_learners_density_kde.R#18) ------------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. testthat::expect_equal(...)
     4. lrn$predict(task_test)
     5. mlr3:::.__Learner__predict(...)
     7. mlr3::check_prediction_data(pdata)
    
     -- 10. Error: bw (@test_mlr_learners_density_kde.R#32) ------------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. testthat::expect_equal(...)
     4. lrn$predict(task_test)
     5. mlr3:::.__Learner__predict(...)
     7. mlr3::check_prediction_data(pdata)
    
     -- 11. Failure: autotest (@test_mlr_learners_surv_coxph.R#8) ------------------
     `result` isn't true.
     [predict()] learner 'surv.coxph:distr' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     -- 12. Failure: weights (@test_mlr_learners_surv_coxph.R#14) ------------------
     `learner$train(task)` did not produce any warnings.
    
     -- 13. Failure: autotest (@test_mlr_learners_surv_kaplan.R#5) -----------------
     `result` isn't true.
     [predict()] learner 'surv.kaplan:crank' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     -- 14. Failure: autotest (@test_mlr_learners_surv_rpart.R#5) ------------------
     `result` isn't true.
     [predict()] learner 'surv.rpart:crank' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     -- 15. Error: (unknown) (@test_mlr_measures.R#4) ------------------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. learner$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     -- 16. Error: mlr_measures (@test_mlr_measures_dens.R#14) ---------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. mlr_learners$get("dens.hist")$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     -- 17. Error: crankcompositor (@test_pipelines.R#10) --------------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pipe$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     -- 18. Error: distrcompositor (@test_pipelines.R#21) --------------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pipe$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     -- 19. Error: survaverager (@test_pipelines.R#35) -----------------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pipe$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     -- 20. Error: survbagging (@test_pipelines.R#45) ------------------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pipe$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     -- 21. Error: PipeOpCrankCompositor - estimate (@test_pipeop_crankcompositor.R#1
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. gr$predict(task)
     2. mlr3pipelines:::.__Graph__predict(...)
     3. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     4. op[[fun]](input)
     5. mlr3pipelines:::.__PipeOp__predict(...)
     6. private$.predict(input)
     7. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     8. private$.learner$predict(task)
     9. mlr3:::.__Learner__predict(...)
     11. mlr3::check_prediction_data(pdata)
    
     -- 22. Error: no params (@test_pipeop_crankcompositor.R#18) -------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. po$predict(list(lrn("surv.kaplan")$train(task)$predict(task)))
     7. lrn("surv.kaplan")$train(task)$predict(task)
     8. mlr3:::.__Learner__predict(...)
     10. mlr3::check_prediction_data(pdata)
    
     -- 23. Error: response (@test_pipeop_crankcompositor.R#26) --------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. po$predict(list(lrn("surv.kaplan")$train(task)$predict(task)))
     7. lrn("surv.kaplan")$train(task)$predict(task)
     8. mlr3:::.__Learner__predict(...)
     10. mlr3::check_prediction_data(pdata)
    
     -- 24. Error: overwrite crank (@test_pipeop_crankcompositor.R#40) -------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pl$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     -- 25. Error: overwrite response (@test_pipeop_crankcompositor.R#56) ----------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn("surv.kaplan")$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     -- 26. Error: PipeOpDistrCompositor - overwrite = FALSE (@test_pipeop_distrcompo
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. testthat::expect_equal(...)
     4. gr$predict(task)
     5. mlr3pipelines:::.__Graph__predict(...)
     6. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     7. op[[fun]](input)
     8. mlr3pipelines:::.__PipeOp__predict(...)
     9. private$.predict(input)
     10. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     11. private$.learner$predict(task)
     12. mlr3:::.__Learner__predict(...)
     14. mlr3::check_prediction_data(pdata)
    
     -- 27. Error: PipeOpDistrCompositor - overwrite = TRUE (@test_pipeop_distrcompos
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. gr$predict(task)
     2. mlr3pipelines:::.__Graph__predict(...)
     3. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     4. op[[fun]](input)
     5. mlr3pipelines:::.__PipeOp__predict(...)
     6. private$.predict(input)
     7. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     8. private$.learner$predict(task)
     9. mlr3:::.__Learner__predict(...)
     11. mlr3::check_prediction_data(pdata)
    
     -- 28. Error: no params (@test_pipeop_distrcompositor.R#29) -------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn("surv.kaplan")$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     -- 29. Error: (unknown) (@test_pipeop_survavg.R#7) ----------------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn("surv.kaplan")$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     -- 30. Error: single-step (@test_single_step.R#10) ----------------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. learner$predict_newdata(task = train_task, newdata = newdata)
     2. mlr3:::.__Learner__predict_newdata(...)
     3. self$predict(task$rbind(newdata))
     4. mlr3:::.__Learner__predict(...)
     6. mlr3::check_prediction_data(pdata)
    
     == testthat results ===========================================================
     [ OK: 609 | SKIPPED: 2 | WARNINGS: 0 | FAILED: 30 ]
     1. Failure: Construction (@test_PredictionDens.R#8)
     2. Error: Internally constructed Prediction (@test_PredictionDens.R#12)
     3. Error: c (@test_PredictionDens.R#20)
     4. Failure: Construction (@test_PredictionSurv.R#5)
     5. Error: Internally constructed Prediction (@test_PredictionSurv.R#10)
     6. Error: c (@test_PredictionSurv.R#20)
     7. Failure: autotest (@test_mlr_learners_density_hist.R#6)
     8. Failure: autotest (@test_mlr_learners_density_kde.R#6)
     9. Error: pdf (@test_mlr_learners_density_kde.R#18)
     1. ...
    
     Error: testthat unit tests failed
     Execution halted
Flavor: r-devel-windows-ix86+x86_64

Version: 0.2.1
Check: tests
Result: ERROR
     Running ‘testthat.R’ [29s/31s]
    Running the tests in ‘tests/testthat.R’ failed.
    Complete output:
     > library(testthat)
     > library(checkmate) # for more expect_*() functions
     > library(mlr3proba)
     >
     > test_check("mlr3proba")
     ── 1. Failure: Construction (@test_PredictionDens.R#8) ────────────────────────
     Check on data.table::as.data.table(p) isn't true.
     Must have exactly 0 rows, but has 70 rows
    
     ── 2. Error: Internally constructed Prediction (@test_PredictionDens.R#12) ────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     ── 3. Error: c (@test_PredictionDens.R#20) ────────────────────────────────────
     Assertion on 'li' failed: May only contain the following types: {PredictionData}, but element 1 has type 'list'.
     Backtrace:
     1. rr$predictions()
     2. mlr3:::.__ResampleResult__predictions(...)
     3. mlr3:::as_predictions(self$data$prediction, predict_sets)
     4. mlr3misc::map(...)
     5. base::lapply(.x, .f, ...)
     6. mlr3:::FUN(X[[i]], ...)
     7. checkmate::assert_list(li, "PredictionData")
     8. checkmate::makeAssertion(x, res, .var.name, add)
     9. checkmate:::mstop(...)
    
     ── 4. Failure: Construction (@test_PredictionSurv.R#5) ────────────────────────
     Check on data.table::as.data.table(p) isn't true.
     Must have exactly 0 rows, but has 20 rows
    
     ── 5. Error: Internally constructed Prediction (@test_PredictionSurv.R#10) ────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     ── 6. Error: c (@test_PredictionSurv.R#20) ────────────────────────────────────
     Assertion on 'li' failed: May only contain the following types: {PredictionData}, but element 1 has type 'list'.
     Backtrace:
     1. rr$predictions()
     2. mlr3:::.__ResampleResult__predictions(...)
     3. mlr3:::as_predictions(self$data$prediction, predict_sets)
     4. mlr3misc::map(...)
     5. base::lapply(.x, .f, ...)
     6. mlr3:::FUN(X[[i]], ...)
     7. checkmate::assert_list(li, "PredictionData")
     8. checkmate::makeAssertion(x, res, .var.name, add)
     9. checkmate:::mstop(...)
    
     ── 7. Failure: autotest (@test_mlr_learners_density_hist.R#6) ─────────────────
     `result` isn't true.
     [predict()] learner 'dens.hist:pdf' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     ── 8. Failure: autotest (@test_mlr_learners_density_kde.R#6) ──────────────────
     `result` isn't true.
     [predict()] learner 'dens.kde:pdf' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     ── 9. Error: pdf (@test_mlr_learners_density_kde.R#18) ────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. testthat::expect_equal(...)
     4. lrn$predict(task_test)
     5. mlr3:::.__Learner__predict(...)
     7. mlr3::check_prediction_data(pdata)
    
     ── 10. Error: bw (@test_mlr_learners_density_kde.R#32) ────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. testthat::expect_equal(...)
     4. lrn$predict(task_test)
     5. mlr3:::.__Learner__predict(...)
     7. mlr3::check_prediction_data(pdata)
    
     ── 11. Failure: autotest (@test_mlr_learners_surv_coxph.R#8) ──────────────────
     `result` isn't true.
     [predict()] learner 'surv.coxph:distr' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     ── 12. Failure: weights (@test_mlr_learners_surv_coxph.R#14) ──────────────────
     `learner$train(task)` did not produce any warnings.
    
     ── 13. Failure: autotest (@test_mlr_learners_surv_kaplan.R#5) ─────────────────
     `result` isn't true.
     [predict()] learner 'surv.kaplan:crank' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     ── 14. Failure: autotest (@test_mlr_learners_surv_rpart.R#5) ──────────────────
     `result` isn't true.
     [predict()] learner 'surv.rpart:crank' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     ── 15. Error: (unknown) (@test_mlr_measures.R#4) ──────────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. learner$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     ── 16. Error: mlr_measures (@test_mlr_measures_dens.R#14) ─────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. mlr_learners$get("dens.hist")$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     ── 17. Error: crankcompositor (@test_pipelines.R#10) ──────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pipe$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     ── 18. Error: distrcompositor (@test_pipelines.R#21) ──────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pipe$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     ── 19. Error: survaverager (@test_pipelines.R#35) ─────────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pipe$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     ── 20. Error: survbagging (@test_pipelines.R#45) ──────────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pipe$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     ── 21. Error: PipeOpCrankCompositor - estimate (@test_pipeop_crankcompositor.R#1
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. gr$predict(task)
     2. mlr3pipelines:::.__Graph__predict(...)
     3. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     4. op[[fun]](input)
     5. mlr3pipelines:::.__PipeOp__predict(...)
     6. private$.predict(input)
     7. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     8. private$.learner$predict(task)
     9. mlr3:::.__Learner__predict(...)
     11. mlr3::check_prediction_data(pdata)
    
     ── 22. Error: no params (@test_pipeop_crankcompositor.R#18) ───────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. po$predict(list(lrn("surv.kaplan")$train(task)$predict(task)))
     7. lrn("surv.kaplan")$train(task)$predict(task)
     8. mlr3:::.__Learner__predict(...)
     10. mlr3::check_prediction_data(pdata)
    
     ── 23. Error: response (@test_pipeop_crankcompositor.R#26) ────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. po$predict(list(lrn("surv.kaplan")$train(task)$predict(task)))
     7. lrn("surv.kaplan")$train(task)$predict(task)
     8. mlr3:::.__Learner__predict(...)
     10. mlr3::check_prediction_data(pdata)
    
     ── 24. Error: overwrite crank (@test_pipeop_crankcompositor.R#40) ─────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pl$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     ── 25. Error: overwrite response (@test_pipeop_crankcompositor.R#56) ──────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn("surv.kaplan")$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     ── 26. Error: PipeOpDistrCompositor - overwrite = FALSE (@test_pipeop_distrcompo
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. testthat::expect_equal(...)
     4. gr$predict(task)
     5. mlr3pipelines:::.__Graph__predict(...)
     6. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     7. op[[fun]](input)
     8. mlr3pipelines:::.__PipeOp__predict(...)
     9. private$.predict(input)
     10. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     11. private$.learner$predict(task)
     12. mlr3:::.__Learner__predict(...)
     14. mlr3::check_prediction_data(pdata)
    
     ── 27. Error: PipeOpDistrCompositor - overwrite = TRUE (@test_pipeop_distrcompos
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. gr$predict(task)
     2. mlr3pipelines:::.__Graph__predict(...)
     3. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     4. op[[fun]](input)
     5. mlr3pipelines:::.__PipeOp__predict(...)
     6. private$.predict(input)
     7. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     8. private$.learner$predict(task)
     9. mlr3:::.__Learner__predict(...)
     11. mlr3::check_prediction_data(pdata)
    
     ── 28. Error: no params (@test_pipeop_distrcompositor.R#29) ───────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn("surv.kaplan")$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     ── 29. Error: (unknown) (@test_pipeop_survavg.R#7) ────────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn("surv.kaplan")$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     ── 30. Error: single-step (@test_single_step.R#10) ────────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. learner$predict_newdata(task = train_task, newdata = newdata)
     2. mlr3:::.__Learner__predict_newdata(...)
     3. self$predict(task$rbind(newdata))
     4. mlr3:::.__Learner__predict(...)
     6. mlr3::check_prediction_data(pdata)
    
     ══ testthat results ═══════════════════════════════════════════════════════════
     [ OK: 609 | SKIPPED: 2 | WARNINGS: 0 | FAILED: 30 ]
     1. Failure: Construction (@test_PredictionDens.R#8)
     2. Error: Internally constructed Prediction (@test_PredictionDens.R#12)
     3. Error: c (@test_PredictionDens.R#20)
     4. Failure: Construction (@test_PredictionSurv.R#5)
     5. Error: Internally constructed Prediction (@test_PredictionSurv.R#10)
     6. Error: c (@test_PredictionSurv.R#20)
     7. Failure: autotest (@test_mlr_learners_density_hist.R#6)
     8. Failure: autotest (@test_mlr_learners_density_kde.R#6)
     9. Error: pdf (@test_mlr_learners_density_kde.R#18)
     1. ...
    
     Error: testthat unit tests failed
     Execution halted
Flavor: r-patched-linux-x86_64

Version: 0.2.1
Check: tests
Result: ERROR
     Running ‘testthat.R’ [38s/39s]
    Running the tests in ‘tests/testthat.R’ failed.
    Complete output:
     > library(testthat)
     > library(checkmate) # for more expect_*() functions
     > library(mlr3proba)
     >
     > test_check("mlr3proba")
     ── 1. Failure: Construction (@test_PredictionDens.R#8) ────────────────────────
     Check on data.table::as.data.table(p) isn't true.
     Must have exactly 0 rows, but has 70 rows
    
     ── 2. Error: Internally constructed Prediction (@test_PredictionDens.R#12) ────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     ── 3. Error: c (@test_PredictionDens.R#20) ────────────────────────────────────
     Assertion on 'li' failed: May only contain the following types: {PredictionData}, but element 1 has type 'list'.
     Backtrace:
     1. rr$predictions()
     2. mlr3:::.__ResampleResult__predictions(...)
     3. mlr3:::as_predictions(self$data$prediction, predict_sets)
     4. mlr3misc::map(...)
     5. base::lapply(.x, .f, ...)
     6. mlr3:::FUN(X[[i]], ...)
     7. checkmate::assert_list(li, "PredictionData")
     8. checkmate::makeAssertion(x, res, .var.name, add)
     9. checkmate:::mstop(...)
    
     ── 4. Failure: Construction (@test_PredictionSurv.R#5) ────────────────────────
     Check on data.table::as.data.table(p) isn't true.
     Must have exactly 0 rows, but has 20 rows
    
     ── 5. Error: Internally constructed Prediction (@test_PredictionSurv.R#10) ────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     ── 6. Error: c (@test_PredictionSurv.R#20) ────────────────────────────────────
     Assertion on 'li' failed: May only contain the following types: {PredictionData}, but element 1 has type 'list'.
     Backtrace:
     1. rr$predictions()
     2. mlr3:::.__ResampleResult__predictions(...)
     3. mlr3:::as_predictions(self$data$prediction, predict_sets)
     4. mlr3misc::map(...)
     5. base::lapply(.x, .f, ...)
     6. mlr3:::FUN(X[[i]], ...)
     7. checkmate::assert_list(li, "PredictionData")
     8. checkmate::makeAssertion(x, res, .var.name, add)
     9. checkmate:::mstop(...)
    
     ── 7. Failure: autotest (@test_mlr_learners_density_hist.R#6) ─────────────────
     `result` isn't true.
     [predict()] learner 'dens.hist:pdf' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     ── 8. Failure: autotest (@test_mlr_learners_density_kde.R#6) ──────────────────
     `result` isn't true.
     [predict()] learner 'dens.kde:pdf' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     ── 9. Error: pdf (@test_mlr_learners_density_kde.R#18) ────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. testthat::expect_equal(...)
     4. lrn$predict(task_test)
     5. mlr3:::.__Learner__predict(...)
     7. mlr3::check_prediction_data(pdata)
    
     ── 10. Error: bw (@test_mlr_learners_density_kde.R#32) ────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. testthat::expect_equal(...)
     4. lrn$predict(task_test)
     5. mlr3:::.__Learner__predict(...)
     7. mlr3::check_prediction_data(pdata)
    
     ── 11. Failure: autotest (@test_mlr_learners_surv_coxph.R#8) ──────────────────
     `result` isn't true.
     [predict()] learner 'surv.coxph:distr' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     ── 12. Failure: weights (@test_mlr_learners_surv_coxph.R#14) ──────────────────
     `learner$train(task)` did not produce any warnings.
    
     ── 13. Failure: autotest (@test_mlr_learners_surv_kaplan.R#5) ─────────────────
     `result` isn't true.
     [predict()] learner 'surv.kaplan:crank' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     ── 14. Failure: autotest (@test_mlr_learners_surv_rpart.R#5) ──────────────────
     `result` isn't true.
     [predict()] learner 'surv.rpart:crank' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     ── 15. Error: (unknown) (@test_mlr_measures.R#4) ──────────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. learner$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     ── 16. Error: mlr_measures (@test_mlr_measures_dens.R#14) ─────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. mlr_learners$get("dens.hist")$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     ── 17. Error: crankcompositor (@test_pipelines.R#10) ──────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pipe$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     ── 18. Error: distrcompositor (@test_pipelines.R#21) ──────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pipe$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     ── 19. Error: survaverager (@test_pipelines.R#35) ─────────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pipe$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     ── 20. Error: survbagging (@test_pipelines.R#45) ──────────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pipe$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     ── 21. Error: PipeOpCrankCompositor - estimate (@test_pipeop_crankcompositor.R#1
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. gr$predict(task)
     2. mlr3pipelines:::.__Graph__predict(...)
     3. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     4. op[[fun]](input)
     5. mlr3pipelines:::.__PipeOp__predict(...)
     6. private$.predict(input)
     7. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     8. private$.learner$predict(task)
     9. mlr3:::.__Learner__predict(...)
     11. mlr3::check_prediction_data(pdata)
    
     ── 22. Error: no params (@test_pipeop_crankcompositor.R#18) ───────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. po$predict(list(lrn("surv.kaplan")$train(task)$predict(task)))
     7. lrn("surv.kaplan")$train(task)$predict(task)
     8. mlr3:::.__Learner__predict(...)
     10. mlr3::check_prediction_data(pdata)
    
     ── 23. Error: response (@test_pipeop_crankcompositor.R#26) ────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. po$predict(list(lrn("surv.kaplan")$train(task)$predict(task)))
     7. lrn("surv.kaplan")$train(task)$predict(task)
     8. mlr3:::.__Learner__predict(...)
     10. mlr3::check_prediction_data(pdata)
    
     ── 24. Error: overwrite crank (@test_pipeop_crankcompositor.R#40) ─────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pl$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     ── 25. Error: overwrite response (@test_pipeop_crankcompositor.R#56) ──────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn("surv.kaplan")$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     ── 26. Error: PipeOpDistrCompositor - overwrite = FALSE (@test_pipeop_distrcompo
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. testthat::expect_equal(...)
     4. gr$predict(task)
     5. mlr3pipelines:::.__Graph__predict(...)
     6. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     7. op[[fun]](input)
     8. mlr3pipelines:::.__PipeOp__predict(...)
     9. private$.predict(input)
     10. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     11. private$.learner$predict(task)
     12. mlr3:::.__Learner__predict(...)
     14. mlr3::check_prediction_data(pdata)
    
     ── 27. Error: PipeOpDistrCompositor - overwrite = TRUE (@test_pipeop_distrcompos
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. gr$predict(task)
     2. mlr3pipelines:::.__Graph__predict(...)
     3. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     4. op[[fun]](input)
     5. mlr3pipelines:::.__PipeOp__predict(...)
     6. private$.predict(input)
     7. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     8. private$.learner$predict(task)
     9. mlr3:::.__Learner__predict(...)
     11. mlr3::check_prediction_data(pdata)
    
     ── 28. Error: no params (@test_pipeop_distrcompositor.R#29) ───────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn("surv.kaplan")$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     ── 29. Error: (unknown) (@test_pipeop_survavg.R#7) ────────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn("surv.kaplan")$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     ── 30. Error: single-step (@test_single_step.R#10) ────────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. learner$predict_newdata(task = train_task, newdata = newdata)
     2. mlr3:::.__Learner__predict_newdata(...)
     3. self$predict(task$rbind(newdata))
     4. mlr3:::.__Learner__predict(...)
     6. mlr3::check_prediction_data(pdata)
    
     ══ testthat results ═══════════════════════════════════════════════════════════
     [ OK: 609 | SKIPPED: 2 | WARNINGS: 0 | FAILED: 30 ]
     1. Failure: Construction (@test_PredictionDens.R#8)
     2. Error: Internally constructed Prediction (@test_PredictionDens.R#12)
     3. Error: c (@test_PredictionDens.R#20)
     4. Failure: Construction (@test_PredictionSurv.R#5)
     5. Error: Internally constructed Prediction (@test_PredictionSurv.R#10)
     6. Error: c (@test_PredictionSurv.R#20)
     7. Failure: autotest (@test_mlr_learners_density_hist.R#6)
     8. Failure: autotest (@test_mlr_learners_density_kde.R#6)
     9. Error: pdf (@test_mlr_learners_density_kde.R#18)
     1. ...
    
     Error: testthat unit tests failed
     Execution halted
Flavor: r-patched-solaris-x86

Version: 0.2.1
Check: re-building of vignette outputs
Result: WARN
    Error(s) in re-building vignettes:
     ...
    --- re-building ‘density.Rmd’ using rmarkdown
    Warning in engine$weave(file, quiet = quiet, encoding = enc) :
     Pandoc (>= 1.12.3) and/or pandoc-citeproc not available. Falling back to R Markdown v1.
    Quitting from lines 54-74 (density.Rmd)
    Error: processing vignette 'density.Rmd' failed with diagnostics:
    no applicable method for 'check_prediction_data' applied to an object of class "list"
    --- failed re-building ‘density.Rmd’
    
    SUMMARY: processing the following file failed:
     ‘density.Rmd’
    
    Error: Vignette re-building failed.
    Execution halted
Flavor: r-patched-solaris-x86

Version: 0.2.1
Check: tests
Result: ERROR
     Running ‘testthat.R’ [30s/33s]
    Running the tests in ‘tests/testthat.R’ failed.
    Complete output:
     > library(testthat)
     > library(checkmate) # for more expect_*() functions
     > library(mlr3proba)
     >
     > test_check("mlr3proba")
     ── 1. Failure: Construction (@test_PredictionDens.R#8) ────────────────────────
     Check on data.table::as.data.table(p) isn't true.
     Must have exactly 0 rows, but has 70 rows
    
     ── 2. Error: Internally constructed Prediction (@test_PredictionDens.R#12) ────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     ── 3. Error: c (@test_PredictionDens.R#20) ────────────────────────────────────
     Assertion on 'li' failed: May only contain the following types: {PredictionData}, but element 1 has type 'list'.
     Backtrace:
     1. rr$predictions()
     2. mlr3:::.__ResampleResult__predictions(...)
     3. mlr3:::as_predictions(self$data$prediction, predict_sets)
     4. mlr3misc::map(...)
     5. base::lapply(.x, .f, ...)
     6. mlr3:::FUN(X[[i]], ...)
     7. checkmate::assert_list(li, "PredictionData")
     8. checkmate::makeAssertion(x, res, .var.name, add)
     9. checkmate:::mstop(...)
    
     ── 4. Failure: Construction (@test_PredictionSurv.R#5) ────────────────────────
     Check on data.table::as.data.table(p) isn't true.
     Must have exactly 0 rows, but has 20 rows
    
     ── 5. Error: Internally constructed Prediction (@test_PredictionSurv.R#10) ────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     ── 6. Error: c (@test_PredictionSurv.R#20) ────────────────────────────────────
     Assertion on 'li' failed: May only contain the following types: {PredictionData}, but element 1 has type 'list'.
     Backtrace:
     1. rr$predictions()
     2. mlr3:::.__ResampleResult__predictions(...)
     3. mlr3:::as_predictions(self$data$prediction, predict_sets)
     4. mlr3misc::map(...)
     5. base::lapply(.x, .f, ...)
     6. mlr3:::FUN(X[[i]], ...)
     7. checkmate::assert_list(li, "PredictionData")
     8. checkmate::makeAssertion(x, res, .var.name, add)
     9. checkmate:::mstop(...)
    
     ── 7. Failure: autotest (@test_mlr_learners_density_hist.R#6) ─────────────────
     `result` isn't true.
     [predict()] learner 'dens.hist:pdf' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     ── 8. Failure: autotest (@test_mlr_learners_density_kde.R#6) ──────────────────
     `result` isn't true.
     [predict()] learner 'dens.kde:pdf' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     ── 9. Error: pdf (@test_mlr_learners_density_kde.R#18) ────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. testthat::expect_equal(...)
     4. lrn$predict(task_test)
     5. mlr3:::.__Learner__predict(...)
     7. mlr3::check_prediction_data(pdata)
    
     ── 10. Error: bw (@test_mlr_learners_density_kde.R#32) ────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. testthat::expect_equal(...)
     4. lrn$predict(task_test)
     5. mlr3:::.__Learner__predict(...)
     7. mlr3::check_prediction_data(pdata)
    
     ── 11. Failure: autotest (@test_mlr_learners_surv_coxph.R#8) ──────────────────
     `result` isn't true.
     [predict()] learner 'surv.coxph:distr' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     ── 12. Failure: weights (@test_mlr_learners_surv_coxph.R#14) ──────────────────
     `learner$train(task)` did not produce any warnings.
    
     ── 13. Failure: autotest (@test_mlr_learners_surv_kaplan.R#5) ─────────────────
     `result` isn't true.
     [predict()] learner 'surv.kaplan:crank' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     ── 14. Failure: autotest (@test_mlr_learners_surv_rpart.R#5) ──────────────────
     `result` isn't true.
     [predict()] learner 'surv.rpart:crank' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     ── 15. Error: (unknown) (@test_mlr_measures.R#4) ──────────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. learner$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     ── 16. Error: mlr_measures (@test_mlr_measures_dens.R#14) ─────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. mlr_learners$get("dens.hist")$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     ── 17. Error: crankcompositor (@test_pipelines.R#10) ──────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pipe$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     ── 18. Error: distrcompositor (@test_pipelines.R#21) ──────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pipe$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     ── 19. Error: survaverager (@test_pipelines.R#35) ─────────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pipe$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     ── 20. Error: survbagging (@test_pipelines.R#45) ──────────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pipe$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     ── 21. Error: PipeOpCrankCompositor - estimate (@test_pipeop_crankcompositor.R#1
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. gr$predict(task)
     2. mlr3pipelines:::.__Graph__predict(...)
     3. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     4. op[[fun]](input)
     5. mlr3pipelines:::.__PipeOp__predict(...)
     6. private$.predict(input)
     7. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     8. private$.learner$predict(task)
     9. mlr3:::.__Learner__predict(...)
     11. mlr3::check_prediction_data(pdata)
    
     ── 22. Error: no params (@test_pipeop_crankcompositor.R#18) ───────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. po$predict(list(lrn("surv.kaplan")$train(task)$predict(task)))
     7. lrn("surv.kaplan")$train(task)$predict(task)
     8. mlr3:::.__Learner__predict(...)
     10. mlr3::check_prediction_data(pdata)
    
     ── 23. Error: response (@test_pipeop_crankcompositor.R#26) ────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. po$predict(list(lrn("surv.kaplan")$train(task)$predict(task)))
     7. lrn("surv.kaplan")$train(task)$predict(task)
     8. mlr3:::.__Learner__predict(...)
     10. mlr3::check_prediction_data(pdata)
    
     ── 24. Error: overwrite crank (@test_pipeop_crankcompositor.R#40) ─────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pl$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     ── 25. Error: overwrite response (@test_pipeop_crankcompositor.R#56) ──────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn("surv.kaplan")$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     ── 26. Error: PipeOpDistrCompositor - overwrite = FALSE (@test_pipeop_distrcompo
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. testthat::expect_equal(...)
     4. gr$predict(task)
     5. mlr3pipelines:::.__Graph__predict(...)
     6. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     7. op[[fun]](input)
     8. mlr3pipelines:::.__PipeOp__predict(...)
     9. private$.predict(input)
     10. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     11. private$.learner$predict(task)
     12. mlr3:::.__Learner__predict(...)
     14. mlr3::check_prediction_data(pdata)
    
     ── 27. Error: PipeOpDistrCompositor - overwrite = TRUE (@test_pipeop_distrcompos
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. gr$predict(task)
     2. mlr3pipelines:::.__Graph__predict(...)
     3. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     4. op[[fun]](input)
     5. mlr3pipelines:::.__PipeOp__predict(...)
     6. private$.predict(input)
     7. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     8. private$.learner$predict(task)
     9. mlr3:::.__Learner__predict(...)
     11. mlr3::check_prediction_data(pdata)
    
     ── 28. Error: no params (@test_pipeop_distrcompositor.R#29) ───────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn("surv.kaplan")$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     ── 29. Error: (unknown) (@test_pipeop_survavg.R#7) ────────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn("surv.kaplan")$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     ── 30. Error: single-step (@test_single_step.R#10) ────────────────────────────
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. learner$predict_newdata(task = train_task, newdata = newdata)
     2. mlr3:::.__Learner__predict_newdata(...)
     3. self$predict(task$rbind(newdata))
     4. mlr3:::.__Learner__predict(...)
     6. mlr3::check_prediction_data(pdata)
    
     ══ testthat results ═══════════════════════════════════════════════════════════
     [ OK: 609 | SKIPPED: 2 | WARNINGS: 0 | FAILED: 30 ]
     1. Failure: Construction (@test_PredictionDens.R#8)
     2. Error: Internally constructed Prediction (@test_PredictionDens.R#12)
     3. Error: c (@test_PredictionDens.R#20)
     4. Failure: Construction (@test_PredictionSurv.R#5)
     5. Error: Internally constructed Prediction (@test_PredictionSurv.R#10)
     6. Error: c (@test_PredictionSurv.R#20)
     7. Failure: autotest (@test_mlr_learners_density_hist.R#6)
     8. Failure: autotest (@test_mlr_learners_density_kde.R#6)
     9. Error: pdf (@test_mlr_learners_density_kde.R#18)
     1. ...
    
     Error: testthat unit tests failed
     Execution halted
Flavor: r-release-linux-x86_64

Version: 0.2.1
Check: running tests for arch ‘i386’
Result: ERROR
     Running 'testthat.R' [20s]
    Running the tests in 'tests/testthat.R' failed.
    Complete output:
     > library(testthat)
     > library(checkmate) # for more expect_*() functions
     > library(mlr3proba)
     >
     > test_check("mlr3proba")
     -- 1. Failure: Construction (@test_PredictionDens.R#8) ------------------------
     Check on data.table::as.data.table(p) isn't true.
     Must have exactly 0 rows, but has 70 rows
    
     -- 2. Error: Internally constructed Prediction (@test_PredictionDens.R#12) ----
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     -- 3. Error: c (@test_PredictionDens.R#20) ------------------------------------
     Assertion on 'li' failed: May only contain the following types: {PredictionData}, but element 1 has type 'list'.
     Backtrace:
     1. rr$predictions()
     2. mlr3:::.__ResampleResult__predictions(...)
     3. mlr3:::as_predictions(self$data$prediction, predict_sets)
     4. mlr3misc::map(...)
     5. base::lapply(.x, .f, ...)
     6. mlr3:::FUN(X[[i]], ...)
     7. checkmate::assert_list(li, "PredictionData")
     8. checkmate::makeAssertion(x, res, .var.name, add)
     9. checkmate:::mstop(...)
    
     -- 4. Failure: Construction (@test_PredictionSurv.R#5) ------------------------
     Check on data.table::as.data.table(p) isn't true.
     Must have exactly 0 rows, but has 20 rows
    
     -- 5. Error: Internally constructed Prediction (@test_PredictionSurv.R#10) ----
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     -- 6. Error: c (@test_PredictionSurv.R#20) ------------------------------------
     Assertion on 'li' failed: May only contain the following types: {PredictionData}, but element 1 has type 'list'.
     Backtrace:
     1. rr$predictions()
     2. mlr3:::.__ResampleResult__predictions(...)
     3. mlr3:::as_predictions(self$data$prediction, predict_sets)
     4. mlr3misc::map(...)
     5. base::lapply(.x, .f, ...)
     6. mlr3:::FUN(X[[i]], ...)
     7. checkmate::assert_list(li, "PredictionData")
     8. checkmate::makeAssertion(x, res, .var.name, add)
     9. checkmate:::mstop(...)
    
     -- 7. Failure: autotest (@test_mlr_learners_density_hist.R#6) -----------------
     `result` isn't true.
     [predict()] learner 'dens.hist:pdf' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     -- 8. Failure: autotest (@test_mlr_learners_density_kde.R#6) ------------------
     `result` isn't true.
     [predict()] learner 'dens.kde:pdf' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     -- 9. Error: pdf (@test_mlr_learners_density_kde.R#18) ------------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. testthat::expect_equal(...)
     4. lrn$predict(task_test)
     5. mlr3:::.__Learner__predict(...)
     7. mlr3::check_prediction_data(pdata)
    
     -- 10. Error: bw (@test_mlr_learners_density_kde.R#32) ------------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. testthat::expect_equal(...)
     4. lrn$predict(task_test)
     5. mlr3:::.__Learner__predict(...)
     7. mlr3::check_prediction_data(pdata)
    
     -- 11. Failure: autotest (@test_mlr_learners_surv_coxph.R#8) ------------------
     `result` isn't true.
     [predict()] learner 'surv.coxph:distr' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     -- 12. Failure: weights (@test_mlr_learners_surv_coxph.R#14) ------------------
     `learner$train(task)` did not produce any warnings.
    
     -- 13. Failure: autotest (@test_mlr_learners_surv_kaplan.R#5) -----------------
     `result` isn't true.
     [predict()] learner 'surv.kaplan:crank' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     -- 14. Failure: autotest (@test_mlr_learners_surv_rpart.R#5) ------------------
     `result` isn't true.
     [predict()] learner 'surv.rpart:crank' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     -- 15. Error: (unknown) (@test_mlr_measures.R#4) ------------------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. learner$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     -- 16. Error: mlr_measures (@test_mlr_measures_dens.R#14) ---------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. mlr_learners$get("dens.hist")$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     -- 17. Error: crankcompositor (@test_pipelines.R#10) --------------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pipe$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     -- 18. Error: distrcompositor (@test_pipelines.R#21) --------------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pipe$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     -- 19. Error: survaverager (@test_pipelines.R#35) -----------------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pipe$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     -- 20. Error: survbagging (@test_pipelines.R#45) ------------------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pipe$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     -- 21. Error: PipeOpCrankCompositor - estimate (@test_pipeop_crankcompositor.R#1
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. gr$predict(task)
     2. mlr3pipelines:::.__Graph__predict(...)
     3. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     4. op[[fun]](input)
     5. mlr3pipelines:::.__PipeOp__predict(...)
     6. private$.predict(input)
     7. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     8. private$.learner$predict(task)
     9. mlr3:::.__Learner__predict(...)
     11. mlr3::check_prediction_data(pdata)
    
     -- 22. Error: no params (@test_pipeop_crankcompositor.R#18) -------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. po$predict(list(lrn("surv.kaplan")$train(task)$predict(task)))
     7. lrn("surv.kaplan")$train(task)$predict(task)
     8. mlr3:::.__Learner__predict(...)
     10. mlr3::check_prediction_data(pdata)
    
     -- 23. Error: response (@test_pipeop_crankcompositor.R#26) --------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. po$predict(list(lrn("surv.kaplan")$train(task)$predict(task)))
     7. lrn("surv.kaplan")$train(task)$predict(task)
     8. mlr3:::.__Learner__predict(...)
     10. mlr3::check_prediction_data(pdata)
    
     -- 24. Error: overwrite crank (@test_pipeop_crankcompositor.R#40) -------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pl$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     -- 25. Error: overwrite response (@test_pipeop_crankcompositor.R#56) ----------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn("surv.kaplan")$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     -- 26. Error: PipeOpDistrCompositor - overwrite = FALSE (@test_pipeop_distrcompo
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. testthat::expect_equal(...)
     4. gr$predict(task)
     5. mlr3pipelines:::.__Graph__predict(...)
     6. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     7. op[[fun]](input)
     8. mlr3pipelines:::.__PipeOp__predict(...)
     9. private$.predict(input)
     10. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     11. private$.learner$predict(task)
     12. mlr3:::.__Learner__predict(...)
     14. mlr3::check_prediction_data(pdata)
    
     -- 27. Error: PipeOpDistrCompositor - overwrite = TRUE (@test_pipeop_distrcompos
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. gr$predict(task)
     2. mlr3pipelines:::.__Graph__predict(...)
     3. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     4. op[[fun]](input)
     5. mlr3pipelines:::.__PipeOp__predict(...)
     6. private$.predict(input)
     7. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     8. private$.learner$predict(task)
     9. mlr3:::.__Learner__predict(...)
     11. mlr3::check_prediction_data(pdata)
    
     -- 28. Error: no params (@test_pipeop_distrcompositor.R#29) -------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn("surv.kaplan")$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     -- 29. Error: (unknown) (@test_pipeop_survavg.R#7) ----------------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn("surv.kaplan")$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     -- 30. Error: single-step (@test_single_step.R#10) ----------------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. learner$predict_newdata(task = train_task, newdata = newdata)
     2. mlr3:::.__Learner__predict_newdata(...)
     3. self$predict(task$rbind(newdata))
     4. mlr3:::.__Learner__predict(...)
     6. mlr3::check_prediction_data(pdata)
    
     == testthat results ===========================================================
     [ OK: 609 | SKIPPED: 2 | WARNINGS: 0 | FAILED: 30 ]
     1. Failure: Construction (@test_PredictionDens.R#8)
     2. Error: Internally constructed Prediction (@test_PredictionDens.R#12)
     3. Error: c (@test_PredictionDens.R#20)
     4. Failure: Construction (@test_PredictionSurv.R#5)
     5. Error: Internally constructed Prediction (@test_PredictionSurv.R#10)
     6. Error: c (@test_PredictionSurv.R#20)
     7. Failure: autotest (@test_mlr_learners_density_hist.R#6)
     8. Failure: autotest (@test_mlr_learners_density_kde.R#6)
     9. Error: pdf (@test_mlr_learners_density_kde.R#18)
     1. ...
    
     Error: testthat unit tests failed
     Execution halted
Flavor: r-oldrel-windows-ix86+x86_64

Version: 0.2.1
Check: running tests for arch ‘x64’
Result: ERROR
     Running 'testthat.R' [20s]
    Running the tests in 'tests/testthat.R' failed.
    Complete output:
     > library(testthat)
     > library(checkmate) # for more expect_*() functions
     > library(mlr3proba)
     >
     > test_check("mlr3proba")
     -- 1. Failure: Construction (@test_PredictionDens.R#8) ------------------------
     Check on data.table::as.data.table(p) isn't true.
     Must have exactly 0 rows, but has 70 rows
    
     -- 2. Error: Internally constructed Prediction (@test_PredictionDens.R#12) ----
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     -- 3. Error: c (@test_PredictionDens.R#20) ------------------------------------
     Assertion on 'li' failed: May only contain the following types: {PredictionData}, but element 1 has type 'list'.
     Backtrace:
     1. rr$predictions()
     2. mlr3:::.__ResampleResult__predictions(...)
     3. mlr3:::as_predictions(self$data$prediction, predict_sets)
     4. mlr3misc::map(...)
     5. base::lapply(.x, .f, ...)
     6. mlr3:::FUN(X[[i]], ...)
     7. checkmate::assert_list(li, "PredictionData")
     8. checkmate::makeAssertion(x, res, .var.name, add)
     9. checkmate:::mstop(...)
    
     -- 4. Failure: Construction (@test_PredictionSurv.R#5) ------------------------
     Check on data.table::as.data.table(p) isn't true.
     Must have exactly 0 rows, but has 20 rows
    
     -- 5. Error: Internally constructed Prediction (@test_PredictionSurv.R#10) ----
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     -- 6. Error: c (@test_PredictionSurv.R#20) ------------------------------------
     Assertion on 'li' failed: May only contain the following types: {PredictionData}, but element 1 has type 'list'.
     Backtrace:
     1. rr$predictions()
     2. mlr3:::.__ResampleResult__predictions(...)
     3. mlr3:::as_predictions(self$data$prediction, predict_sets)
     4. mlr3misc::map(...)
     5. base::lapply(.x, .f, ...)
     6. mlr3:::FUN(X[[i]], ...)
     7. checkmate::assert_list(li, "PredictionData")
     8. checkmate::makeAssertion(x, res, .var.name, add)
     9. checkmate:::mstop(...)
    
     -- 7. Failure: autotest (@test_mlr_learners_density_hist.R#6) -----------------
     `result` isn't true.
     [predict()] learner 'dens.hist:pdf' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     -- 8. Failure: autotest (@test_mlr_learners_density_kde.R#6) ------------------
     `result` isn't true.
     [predict()] learner 'dens.kde:pdf' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     -- 9. Error: pdf (@test_mlr_learners_density_kde.R#18) ------------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. testthat::expect_equal(...)
     4. lrn$predict(task_test)
     5. mlr3:::.__Learner__predict(...)
     7. mlr3::check_prediction_data(pdata)
    
     -- 10. Error: bw (@test_mlr_learners_density_kde.R#32) ------------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. testthat::expect_equal(...)
     4. lrn$predict(task_test)
     5. mlr3:::.__Learner__predict(...)
     7. mlr3::check_prediction_data(pdata)
    
     -- 11. Failure: autotest (@test_mlr_learners_surv_coxph.R#8) ------------------
     `result` isn't true.
     [predict()] learner 'surv.coxph:distr' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     -- 12. Failure: weights (@test_mlr_learners_surv_coxph.R#14) ------------------
     `learner$train(task)` did not produce any warnings.
    
     -- 13. Failure: autotest (@test_mlr_learners_surv_kaplan.R#5) -----------------
     `result` isn't true.
     [predict()] learner 'surv.kaplan:crank' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     -- 14. Failure: autotest (@test_mlr_learners_surv_rpart.R#5) ------------------
     `result` isn't true.
     [predict()] learner 'surv.rpart:crank' on task 'feat_single_logical' failed: Must inherit from class 'Prediction', but has class 'try-error'
    
     -- 15. Error: (unknown) (@test_mlr_measures.R#4) ------------------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. learner$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     -- 16. Error: mlr_measures (@test_mlr_measures_dens.R#14) ---------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. mlr_learners$get("dens.hist")$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     -- 17. Error: crankcompositor (@test_pipelines.R#10) --------------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pipe$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     -- 18. Error: distrcompositor (@test_pipelines.R#21) --------------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pipe$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     -- 19. Error: survaverager (@test_pipelines.R#35) -----------------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pipe$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     -- 20. Error: survbagging (@test_pipelines.R#45) ------------------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pipe$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     -- 21. Error: PipeOpCrankCompositor - estimate (@test_pipeop_crankcompositor.R#1
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. gr$predict(task)
     2. mlr3pipelines:::.__Graph__predict(...)
     3. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     4. op[[fun]](input)
     5. mlr3pipelines:::.__PipeOp__predict(...)
     6. private$.predict(input)
     7. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     8. private$.learner$predict(task)
     9. mlr3:::.__Learner__predict(...)
     11. mlr3::check_prediction_data(pdata)
    
     -- 22. Error: no params (@test_pipeop_crankcompositor.R#18) -------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. po$predict(list(lrn("surv.kaplan")$train(task)$predict(task)))
     7. lrn("surv.kaplan")$train(task)$predict(task)
     8. mlr3:::.__Learner__predict(...)
     10. mlr3::check_prediction_data(pdata)
    
     -- 23. Error: response (@test_pipeop_crankcompositor.R#26) --------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. po$predict(list(lrn("surv.kaplan")$train(task)$predict(task)))
     7. lrn("surv.kaplan")$train(task)$predict(task)
     8. mlr3:::.__Learner__predict(...)
     10. mlr3::check_prediction_data(pdata)
    
     -- 24. Error: overwrite crank (@test_pipeop_crankcompositor.R#40) -------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. pl$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     3. mlr3:::learner_predict(self, task, row_ids)
     4. mlr3misc::encapsulate(...)
     9. mlr3:::.f(task = <environment>, learner = <environment>)
     10. get_private(learner)$.predict(task)
     11. mlr3pipelines:::.__GraphLearner__.predict(...)
     12. self$graph$predict(task)
     13. mlr3pipelines:::.__Graph__predict(...)
     14. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     15. op[[fun]](input)
     16. mlr3pipelines:::.__PipeOp__predict(...)
     17. private$.predict(input)
     18. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     19. private$.learner$predict(task)
     20. mlr3:::.__Learner__predict(...)
     22. mlr3::check_prediction_data(pdata)
    
     -- 25. Error: overwrite response (@test_pipeop_crankcompositor.R#56) ----------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn("surv.kaplan")$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     -- 26. Error: PipeOpDistrCompositor - overwrite = FALSE (@test_pipeop_distrcompo
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. testthat::expect_equal(...)
     4. gr$predict(task)
     5. mlr3pipelines:::.__Graph__predict(...)
     6. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     7. op[[fun]](input)
     8. mlr3pipelines:::.__PipeOp__predict(...)
     9. private$.predict(input)
     10. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     11. private$.learner$predict(task)
     12. mlr3:::.__Learner__predict(...)
     14. mlr3::check_prediction_data(pdata)
    
     -- 27. Error: PipeOpDistrCompositor - overwrite = TRUE (@test_pipeop_distrcompos
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. gr$predict(task)
     2. mlr3pipelines:::.__Graph__predict(...)
     3. mlr3pipelines:::graph_reduce(self, input, "predict", single_input)
     4. op[[fun]](input)
     5. mlr3pipelines:::.__PipeOp__predict(...)
     6. private$.predict(input)
     7. mlr3pipelines:::.__PipeOpLearner__.predict(...)
     8. private$.learner$predict(task)
     9. mlr3:::.__Learner__predict(...)
     11. mlr3::check_prediction_data(pdata)
    
     -- 28. Error: no params (@test_pipeop_distrcompositor.R#29) -------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn("surv.kaplan")$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     -- 29. Error: (unknown) (@test_pipeop_survavg.R#7) ----------------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. lrn("surv.kaplan")$train(task)$predict(task)
     2. mlr3:::.__Learner__predict(...)
     4. mlr3::check_prediction_data(pdata)
    
     -- 30. Error: single-step (@test_single_step.R#10) ----------------------------
     no applicable method for 'check_prediction_data' applied to an object of class "list"
     Backtrace:
     1. learner$predict_newdata(task = train_task, newdata = newdata)
     2. mlr3:::.__Learner__predict_newdata(...)
     3. self$predict(task$rbind(newdata))
     4. mlr3:::.__Learner__predict(...)
     6. mlr3::check_prediction_data(pdata)
    
     == testthat results ===========================================================
     [ OK: 609 | SKIPPED: 2 | WARNINGS: 0 | FAILED: 30 ]
     1. Failure: Construction (@test_PredictionDens.R#8)
     2. Error: Internally constructed Prediction (@test_PredictionDens.R#12)
     3. Error: c (@test_PredictionDens.R#20)
     4. Failure: Construction (@test_PredictionSurv.R#5)
     5. Error: Internally constructed Prediction (@test_PredictionSurv.R#10)
     6. Error: c (@test_PredictionSurv.R#20)
     7. Failure: autotest (@test_mlr_learners_density_hist.R#6)
     8. Failure: autotest (@test_mlr_learners_density_kde.R#6)
     9. Error: pdf (@test_mlr_learners_density_kde.R#18)
     1. ...
    
     Error: testthat unit tests failed
     Execution halted
Flavor: r-oldrel-windows-ix86+x86_64