Last updated on 2025-12-28 03:51:27 CET.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 1.0.2 | 15.45 | 379.09 | 394.54 | OK | |
| r-devel-linux-x86_64-debian-gcc | 1.0.2 | 9.32 | 267.93 | 277.25 | OK | |
| r-devel-linux-x86_64-fedora-clang | 1.0.2 | 27.00 | 622.49 | 649.49 | OK | |
| r-devel-linux-x86_64-fedora-gcc | 1.0.2 | 25.00 | 611.56 | 636.56 | OK | |
| r-devel-windows-x86_64 | 1.0.2 | 15.00 | 140.00 | 155.00 | ERROR | |
| r-patched-linux-x86_64 | 1.0.2 | 14.80 | 332.03 | 346.83 | OK | |
| r-release-linux-x86_64 | 1.0.2 | 14.02 | 341.37 | 355.39 | OK | |
| r-release-macos-arm64 | 1.0.2 | OK | ||||
| r-release-macos-x86_64 | 1.0.2 | 9.00 | 358.00 | 367.00 | OK | |
| r-release-windows-x86_64 | 1.0.2 | 15.00 | 352.00 | 367.00 | OK | |
| r-oldrel-macos-arm64 | 1.0.2 | OK | ||||
| r-oldrel-macos-x86_64 | 1.0.2 | 9.00 | 354.00 | 363.00 | OK | |
| r-oldrel-windows-x86_64 | 1.0.2 | 22.00 | 442.00 | 464.00 | OK |
Version: 1.0.2
Check: tests
Result: ERROR
Running 'testthat_regression_tests.R' [40s]
Running the tests in 'tests/testthat_regression_tests.R' failed.
Complete output:
> library("testthat")
> library("patrick")
> library("DoubleML")
>
> testthat::test_check("DoubleML")
Saving _problems/test-double_ml_cluster_not_implemented-13.R
Saving _problems/test-double_ml_iivm-39.R
Saving _problems/test-double_ml_iivm_binary_outcome-40.R
Saving _problems/test-double_ml_iivm_parameter_passing-52.R
Saving _problems/test-double_ml_iivm_parameter_passing-140.R
Saving _problems/test-double_ml_iivm_parameter_passing-227.R
Saving _problems/test-double_ml_iivm_parameter_passing-304.R
Saving _problems/test-double_ml_iivm_trim-38.R
Saving _problems/test-double_ml_iivm_tuning-76.R
Saving _problems/test-double_ml_iivm_user_score-55.R
Saving _problems/test-double_ml_irm-36.R
Saving _problems/test-double_ml_irm_binary_outcome-40.R
Saving _problems/test-double_ml_irm_loaded_mlr3learner-73.R
Saving _problems/test-double_ml_irm_parameter_passing-50.R
Saving _problems/test-double_ml_irm_parameter_passing-127.R
Saving _problems/test-double_ml_irm_parameter_passing-127.R
Saving _problems/test-double_ml_irm_parameter_passing-198.R
Saving _problems/test-double_ml_irm_parameter_passing-260.R
Saving _problems/test-double_ml_irm_trim-37.R
Saving _problems/test-double_ml_irm_tuning-76.R
Saving _problems/test-double_ml_irm_user_score-54.R
Saving _problems/test-double_ml_pliv-36.R
Saving _problems/test-double_ml_pliv_exception_handling-47.R
Saving _problems/test-double_ml_pliv_one_way_cluster-56.R
Saving _problems/test-double_ml_pliv_parameter_passing-54.R
Saving _problems/test-double_ml_pliv_parameter_passing-150.R
Saving _problems/test-double_ml_pliv_parameter_passing-240.R
Saving _problems/test-double_ml_pliv_parameter_passing-321.R
Saving _problems/test-double_ml_pliv_partial_functional_initializer-40.R
Saving _problems/test-double_ml_pliv_partial_functional_initializer-82.R
Saving _problems/test-double_ml_pliv_partial_functional_initializer-121.R
Saving _problems/test-double_ml_pliv_partial_functional_initializer_IVtype-41.R
Saving _problems/test-double_ml_pliv_tuning-98.R
Saving _problems/test-double_ml_pliv_tuning-188.R
Saving _problems/test-double_ml_pliv_two_way_cluster-50.R
Saving _problems/test-double_ml_pliv_user_score-66.R
Saving _problems/test-double_ml_plr-36.R
Saving _problems/test-double_ml_plr_classifier-50.R
Saving _problems/test-double_ml_plr_classifier-130.R
Saving _problems/test-double_ml_plr_classifier-143.R
Saving _problems/test-double_ml_plr_exception_handling-116.R
Saving _problems/test-double_ml_plr_exception_handling-177.R
Saving _problems/test-double_ml_plr_export_preds-49.R
Saving _problems/test-double_ml_plr_loaded_mlr3learner-66.R
Saving _problems/test-double_ml_plr_multitreat-43.R
Saving _problems/test-double_ml_plr_nocrossfit-58.R
Saving _problems/test-double_ml_plr_nocrossfit-58.R
Saving _problems/test-double_ml_plr_nonorth-74.R
Saving _problems/test-double_ml_plr_p_adjust-69.R
Saving _problems/test-double_ml_plr_parameter_passing-57.R
Saving _problems/test-double_ml_plr_parameter_passing-160.R
Saving _problems/test-double_ml_plr_parameter_passing-264.R
Saving _problems/test-double_ml_plr_parameter_passing-353.R
Saving _problems/test-double_ml_plr_rep_cross_fit-44.R
Saving _problems/test-double_ml_plr_set_samples-53.R
Saving _problems/test-double_ml_plr_tuning-95.R
Saving _problems/test-double_ml_plr_tuning-95.R
Saving _problems/test-double_ml_plr_user_score-48.R
Saving _problems/test-double_ml_print-12.R
Saving _problems/test-double_ml_ssm_mar-36.R
Saving _problems/test-double_ml_ssm_nonignorable-36.R
Saving _problems/test-double_ml_ssm_tuning-75.R
Saving _problems/test-double_ml_ssm_tuning-75.R
[ FAIL 63 | WARN 0 | SKIP 7 | PASS 296 ]
══ Skipped tests (7) ═══════════════════════════════════════════════════════════
• On CRAN (7): 'test-double_ml_datasets.R:15:1',
'test-double_ml_pliv_multi_z_parameter_passing.R:7:1',
'test-double_ml_pliv_partial_x.R:5:1',
'test-double_ml_pliv_partial_xz.R:7:1',
'test-double_ml_pliv_partial_xz_parameter_passing.R:5:1',
'test-double_ml_pliv_partial_z.R:5:1',
'test-double_ml_pliv_partial_z_parameter_passing.R:5:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test-double_ml_cluster_not_implemented.R:13:3'): Not yet implemented cluster features ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─dml_pliv_cluster$fit() at test-double_ml_cluster_not_implemented.R:13:3
2. └─private$nuisance_est(private$get__smpls())
3. └─private$nuisance_est_partialX(smpls, ...)
4. └─DoubleML:::dml_cv_predict(...)
5. └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_iivm.R:32:5'): Unit tests for IIVM: rpart_dml2_LATE_1e-05 ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─DoubleML:::dml_irmiv(...) at test-double_ml_iivm.R:32:5
3. └─DoubleML:::fit_nuisance_iivm(...) at ./helper-11-dml_iivm.R:23:5
4. └─mlr3::resample(task_m, ml_m, resampling_m, store_models = TRUE) at ./helper-11-dml_iivm.R:145:3
5. └─ResultData$new(data, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_iivm_binary_outcome.R:32:5'): Unit tests for IIVM: log_reg_dml2_LATE_0.025 ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─DoubleML:::dml_irmiv(...) at test-double_ml_iivm_binary_outcome.R:32:5
3. └─DoubleML:::fit_nuisance_iivm(...) at ./helper-11-dml_iivm.R:23:5
4. └─mlr3::resample(task_m, ml_m, resampling_m, store_models = TRUE) at ./helper-11-dml_iivm.R:145:3
5. └─ResultData$new(data, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_iivm_parameter_passing.R:41:5'): Unit tests for parameter passing of IIVM (oop vs fun): rpart_dml2_LATE_1e-05 ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─DoubleML:::dml_irmiv(...) at test-double_ml_iivm_parameter_passing.R:41:5
3. └─DoubleML:::fit_nuisance_iivm(...) at ./helper-11-dml_iivm.R:23:5
4. └─mlr3::resample(task_m, ml_m, resampling_m, store_models = TRUE) at ./helper-11-dml_iivm.R:145:3
5. └─ResultData$new(data, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_iivm_parameter_passing.R:129:5'): Unit tests for parameter passing of IIVM (no cross-fitting) rpart_dml1_LATE_1e-05 ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─DoubleML:::dml_irmiv(...) at test-double_ml_iivm_parameter_passing.R:129:5
3. └─DoubleML:::fit_nuisance_iivm(...) at ./helper-11-dml_iivm.R:23:5
4. └─mlr3::resample(task_m, ml_m, resampling_m, store_models = TRUE) at ./helper-11-dml_iivm.R:145:3
5. └─ResultData$new(data, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_iivm_parameter_passing.R:227:5'): Unit tests for parameter passing of IIVM (fold-wise vs global) rpart_dml2_LATE_1e-05 ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─dml_iivm_obj$fit() at test-double_ml_iivm_parameter_passing.R:227:5
3. └─private$nuisance_est(private$get__smpls())
4. └─DoubleML:::dml_cv_predict(...)
5. └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_iivm_parameter_passing.R:304:5'): Unit tests for parameter passing of IIVM (default vs explicit) rpart_dml2_LATE_1e-05 ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─dml_iivm_default$fit() at test-double_ml_iivm_parameter_passing.R:304:5
3. └─private$nuisance_est(private$get__smpls())
4. └─DoubleML:::dml_cv_predict(...)
5. └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_iivm_trim.R:31:5'): Unit tests for IIVM: rpart_dml2_LATE_truncate_0.05 ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─DoubleML:::dml_irmiv(...) at test-double_ml_iivm_trim.R:31:5
3. └─DoubleML:::fit_nuisance_iivm(...) at ./helper-11-dml_iivm.R:23:5
4. └─mlr3::resample(task_m, ml_m, resampling_m, store_models = TRUE) at ./helper-11-dml_iivm.R:145:3
5. └─ResultData$new(data, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_iivm_tuning.R:76:5'): Unit tests for tuning of IIVM: rpart_dml2_LATE_TRUE_TRUE_1_FALSE ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─double_mliivm_obj_tuned$tune(...) at test-double_ml_iivm_tuning.R:76:5
3. └─private$nuisance_tuning(...)
4. └─DoubleML:::dml_tune(...)
5. └─base::lapply(...)
6. └─DoubleML (local) FUN(X[[i]], ...)
7. └─DoubleML:::tune_instance(tune_settings$tuner, x)
8. └─tuner$optimize(tuning_instance)
9. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
10. └─private$.optimizer$optimize(inst)
11. └─bbotk:::.__OptimizerBatch__optimize(...)
12. └─bbotk::optimize_batch_default(inst, self)
13. ├─base::tryCatch(...)
14. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
15. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
16. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
17. └─get_private(optimizer)$.optimize(instance)
18. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
19. └─inst$eval_batch(design$data)
20. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
21. └─self$objective$eval_many(xss_trafoed)
22. └─bbotk:::.__Objective__eval_many(...)
23. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
24. │ └─base::eval.parent(expr, n = 1L)
25. │ └─base::eval(expr, p)
26. │ └─base::eval(expr, p)
27. └─private$.eval_many(xss = xss, resampling = `<list>`)
28. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
29. └─mlr3::benchmark(...)
30. └─ResultData$new(grid, data_extra, store_backends = store_backends)
31. └─mlr3 (local) initialize(...)
32. └─mlr3:::.__ResultData__initialize(...)
33. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
34. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_iivm_user_score.R:55:5'): Unit tests for IIVM, callable score: regr.rpart_classif.rpart_dml2_0 ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─double_mliivm_obj$fit() at test-double_ml_iivm_user_score.R:55:5
3. └─private$nuisance_est(private$get__smpls())
4. └─DoubleML:::dml_cv_predict(...)
5. └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_irm.R:32:5'): Unit tests for IRM: rpart_dml1_ATTE_0 ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─DoubleML:::dml_irm(...) at test-double_ml_irm.R:32:5
3. └─DoubleML:::fit_nuisance_irm(...) at ./helper-10-dml_irm.R:21:5
4. └─mlr3::resample(task_m, ml_m, resampling_m, store_models = TRUE) at ./helper-10-dml_irm.R:138:3
5. └─ResultData$new(data, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_irm_binary_outcome.R:35:5'): Unit tests for IRM: rpart_dml1_ATTE_0 ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─DoubleML:::dml_irm(...) at test-double_ml_irm_binary_outcome.R:35:5
3. └─DoubleML:::fit_nuisance_irm(...) at ./helper-10-dml_irm.R:21:5
4. └─mlr3::resample(task_m, ml_m, resampling_m, store_models = TRUE) at ./helper-10-dml_irm.R:138:3
5. └─ResultData$new(data, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_irm_loaded_mlr3learner.R:73:5'): Unit tests for IRM: dml1_ATTE_0 ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─double_mlirm$fit() at test-double_ml_irm_loaded_mlr3learner.R:73:5
3. └─private$nuisance_est(private$get__smpls())
4. └─DoubleML:::dml_cv_predict(...)
5. └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_irm_parameter_passing.R:41:5'): Unit tests for parameter passing of IRM (oop vs fun): rpart_dml2_ATE_1e-05 ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─DoubleML:::dml_irm(...) at test-double_ml_irm_parameter_passing.R:41:5
3. └─DoubleML:::fit_nuisance_irm(...) at ./helper-10-dml_irm.R:21:5
4. └─mlr3::resample(task_m, ml_m, resampling_m, store_models = TRUE) at ./helper-10-dml_irm.R:138:3
5. └─ResultData$new(data, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_irm_parameter_passing.R:118:5'): Unit tests for parameter passing of IRM (no cross-fitting) rpart_dml1_ATE_1e-05 ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─DoubleML:::dml_irm(...) at test-double_ml_irm_parameter_passing.R:118:5
3. └─DoubleML:::fit_nuisance_irm(...) at ./helper-10-dml_irm.R:21:5
4. └─mlr3::resample(task_m, ml_m, resampling_m, store_models = TRUE) at ./helper-10-dml_irm.R:138:3
5. └─ResultData$new(data, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_irm_parameter_passing.R:118:5'): Unit tests for parameter passing of IRM (no cross-fitting) rpart_dml1_ATTE_1e-05 ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─DoubleML:::dml_irm(...) at test-double_ml_irm_parameter_passing.R:118:5
3. └─DoubleML:::fit_nuisance_irm(...) at ./helper-10-dml_irm.R:21:5
4. └─mlr3::resample(task_m, ml_m, resampling_m, store_models = TRUE) at ./helper-10-dml_irm.R:138:3
5. └─ResultData$new(data, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_irm_parameter_passing.R:198:5'): Unit tests for parameter passing of IRM (fold-wise vs global) rpart_dml2_ATE_1e-05 ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─double_mlirm_obj$fit() at test-double_ml_irm_parameter_passing.R:198:5
3. └─private$nuisance_est(private$get__smpls())
4. └─DoubleML:::dml_cv_predict(...)
5. └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_irm_parameter_passing.R:260:5'): Unit tests for parameter passing of IRM (default vs explicit) rpart_dml2_ATE_1e-05 ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─dml_irm_default$fit() at test-double_ml_irm_parameter_passing.R:260:5
3. └─private$nuisance_est(private$get__smpls())
4. └─DoubleML:::dml_cv_predict(...)
5. └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_irm_trim.R:31:5'): Unit tests for IRM: rpart_dml2_ATTE_truncate_0.05 ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─DoubleML:::dml_irm(...) at test-double_ml_irm_trim.R:31:5
3. └─DoubleML:::fit_nuisance_irm(...) at ./helper-10-dml_irm.R:21:5
4. └─mlr3::resample(task_m, ml_m, resampling_m, store_models = TRUE) at ./helper-10-dml_irm.R:138:3
5. └─ResultData$new(data, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_irm_tuning.R:76:5'): Unit tests for tuning of PLR: rpart_dml2_ATE_FALSE_1 ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─double_mlirm_obj_tuned$tune(...) at test-double_ml_irm_tuning.R:76:5
3. └─private$nuisance_tuning(...)
4. └─DoubleML:::dml_tune(...)
5. └─base::lapply(...)
6. └─DoubleML (local) FUN(X[[i]], ...)
7. └─DoubleML:::tune_instance(tune_settings$tuner, x)
8. └─tuner$optimize(tuning_instance)
9. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
10. └─private$.optimizer$optimize(inst)
11. └─bbotk:::.__OptimizerBatch__optimize(...)
12. └─bbotk::optimize_batch_default(inst, self)
13. ├─base::tryCatch(...)
14. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
15. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
16. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
17. └─get_private(optimizer)$.optimize(instance)
18. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
19. └─inst$eval_batch(g$data[inds])
20. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
21. └─self$objective$eval_many(xss_trafoed)
22. └─bbotk:::.__Objective__eval_many(...)
23. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
24. │ └─base::eval.parent(expr, n = 1L)
25. │ └─base::eval(expr, p)
26. │ └─base::eval(expr, p)
27. └─private$.eval_many(xss = xss, resampling = `<list>`)
28. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
29. └─mlr3::benchmark(...)
30. └─ResultData$new(grid, data_extra, store_backends = store_backends)
31. └─mlr3 (local) initialize(...)
32. └─mlr3:::.__ResultData__initialize(...)
33. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
34. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_irm_user_score.R:54:5'): Unit tests for IRM, callable score: regr.rpart_classif.rpart_dml2_1e-05 ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─double_mlirm_obj$fit() at test-double_ml_irm_user_score.R:54:5
3. └─private$nuisance_est(private$get__smpls())
4. └─DoubleML:::dml_cv_predict(...)
5. └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_pliv.R:29:5'): Unit tests for PLIV: regr.lm_dml1_partialling out ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─DoubleML:::dml_pliv(...) at test-double_ml_pliv.R:29:5
3. └─DoubleML:::fit_nuisance_pliv(...) at ./helper-09-dml_pliv.R:22:5
4. └─mlr3::resample(task_l, ml_l, resampling_l, store_models = TRUE) at ./helper-09-dml_pliv.R:114:3
5. └─ResultData$new(data, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_pliv_exception_handling.R:46:3'): Unit tests for deprecation warnings of PLIV ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─testthat::expect_warning(dml_obj$tune(par_grids), regexp = msg) at test-double_ml_pliv_exception_handling.R:46:3
2. │ └─testthat:::quasi_capture(...)
3. │ ├─testthat (local) .capture(...)
4. │ │ └─base::withCallingHandlers(...)
5. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
6. └─dml_obj$tune(par_grids)
7. └─super$tune(param_set, tune_settings, tune_on_folds)
8. └─private$nuisance_tuning(...)
9. └─private$nuisance_tuning_partialX(...)
10. └─DoubleML:::dml_tune(...)
11. └─base::lapply(...)
12. └─DoubleML (local) FUN(X[[i]], ...)
13. └─DoubleML:::tune_instance(tune_settings$tuner, x)
14. └─tuner$optimize(tuning_instance)
15. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
16. └─private$.optimizer$optimize(inst)
17. └─bbotk:::.__OptimizerBatch__optimize(...)
18. └─bbotk::optimize_batch_default(inst, self)
19. ├─base::tryCatch(...)
20. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
21. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
22. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
23. └─get_private(optimizer)$.optimize(instance)
24. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
25. └─inst$eval_batch(g$data[inds])
26. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
27. └─self$objective$eval_many(xss_trafoed)
28. └─bbotk:::.__Objective__eval_many(...)
29. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
30. │ └─base::eval.parent(expr, n = 1L)
31. │ └─base::eval(expr, p)
32. │ └─base::eval(expr, p)
33. └─private$.eval_many(xss = xss, resampling = `<list>`)
34. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
35. └─mlr3::benchmark(...)
36. └─ResultData$new(grid, data_extra, store_backends = store_backends)
37. └─mlr3 (local) initialize(...)
38. └─mlr3:::.__ResultData__initialize(...)
39. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
40. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_pliv_one_way_cluster.R:56:5'): Unit tests for PLIV with one-way clustering: regr.lm_dml1_partialling out ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─double_mlpliv_obj$fit() at test-double_ml_pliv_one_way_cluster.R:56:5
3. └─private$nuisance_est(private$get__smpls())
4. └─private$nuisance_est_partialX(smpls, ...)
5. └─DoubleML:::dml_cv_predict(...)
6. └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
7. └─ResultData$new(data, data_extra, store_backends = store_backends)
8. └─mlr3 (local) initialize(...)
9. └─mlr3:::.__ResultData__initialize(...)
10. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
11. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_pliv_parameter_passing.R:43:5'): Unit tests for parameter passing of PLIV (oop vs fun): regr.rpart_dml2_partialling out ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─DoubleML:::dml_pliv(...) at test-double_ml_pliv_parameter_passing.R:43:5
3. └─DoubleML:::fit_nuisance_pliv(...) at ./helper-09-dml_pliv.R:22:5
4. └─mlr3::resample(task_l, ml_l, resampling_l, store_models = TRUE) at ./helper-09-dml_pliv.R:114:3
5. └─ResultData$new(data, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_pliv_parameter_passing.R:138:5'): Unit tests for parameter passing of PLIV (no cross-fitting) regr.rpart_dml1_partialling out ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─DoubleML:::dml_pliv(...) at test-double_ml_pliv_parameter_passing.R:138:5
3. └─DoubleML:::fit_nuisance_pliv(...) at ./helper-09-dml_pliv.R:22:5
4. └─mlr3::resample(task_l, ml_l, resampling_l, store_models = TRUE) at ./helper-09-dml_pliv.R:114:3
5. └─ResultData$new(data, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_pliv_parameter_passing.R:240:5'): Unit tests for parameter passing of PLIV (fold-wise vs global) regr.rpart_dml2_partialling out ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─dml_pliv_obj$fit() at test-double_ml_pliv_parameter_passing.R:240:5
3. └─private$nuisance_est(private$get__smpls())
4. └─private$nuisance_est_partialX(smpls, ...)
5. └─DoubleML:::dml_cv_predict(...)
6. └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
7. └─ResultData$new(data, data_extra, store_backends = store_backends)
8. └─mlr3 (local) initialize(...)
9. └─mlr3:::.__ResultData__initialize(...)
10. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
11. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_pliv_parameter_passing.R:321:5'): Unit tests for parameter passing of PLIV (default vs explicit) regr.rpart_dml2_partialling out ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─dml_pliv_default$fit() at test-double_ml_pliv_parameter_passing.R:321:5
3. └─private$nuisance_est(private$get__smpls())
4. └─private$nuisance_est_partialX(smpls, ...)
5. └─DoubleML:::dml_cv_predict(...)
6. └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
7. └─ResultData$new(data, data_extra, store_backends = store_backends)
8. └─mlr3 (local) initialize(...)
9. └─mlr3:::.__ResultData__initialize(...)
10. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
11. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_pliv_partial_functional_initializer.R:40:5'): Unit tests for PLIV (partialX functional initialization): regr.lm_dml2_partialling out ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─double_mlpliv_obj$fit() at test-double_ml_pliv_partial_functional_initializer.R:40:5
3. └─private$nuisance_est(private$get__smpls())
4. └─private$nuisance_est_partialX(smpls, ...)
5. └─DoubleML:::dml_cv_predict(...)
6. └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
7. └─ResultData$new(data, data_extra, store_backends = store_backends)
8. └─mlr3 (local) initialize(...)
9. └─mlr3:::.__ResultData__initialize(...)
10. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
11. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_pliv_partial_functional_initializer.R:82:5'): Unit tests for PLIV (partialZ functional initialization): regr.lm_dml2_partialling out ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─double_mlpliv_partZ$fit() at test-double_ml_pliv_partial_functional_initializer.R:82:5
3. └─private$nuisance_est(private$get__smpls())
4. └─private$nuisance_est_partialZ(smpls, ...)
5. └─DoubleML:::dml_cv_predict(...)
6. └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
7. └─ResultData$new(data, data_extra, store_backends = store_backends)
8. └─mlr3 (local) initialize(...)
9. └─mlr3:::.__ResultData__initialize(...)
10. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
11. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_pliv_partial_functional_initializer.R:121:5'): Unit tests for PLIV (partialXZ functional initialization): regr.lm_dml2_partialling out ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─double_mlpliv_partXZ$fit() at test-double_ml_pliv_partial_functional_initializer.R:121:5
3. └─private$nuisance_est(private$get__smpls())
4. └─private$nuisance_est_partialXZ(smpls, ...)
5. └─DoubleML:::dml_cv_predict(...)
6. └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
7. └─ResultData$new(data, data_extra, store_backends = store_backends)
8. └─mlr3 (local) initialize(...)
9. └─mlr3:::.__ResultData__initialize(...)
10. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
11. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_pliv_partial_functional_initializer_IVtype.R:41:5'): Unit tests for PLIV (partialX functional initialization): regr.lm_dml2_IV-type ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─double_mlpliv_obj$fit() at test-double_ml_pliv_partial_functional_initializer_IVtype.R:41:5
3. └─private$nuisance_est(private$get__smpls())
4. └─private$nuisance_est_partialX(smpls, ...)
5. └─DoubleML:::dml_cv_predict(...)
6. └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
7. └─ResultData$new(data, data_extra, store_backends = store_backends)
8. └─mlr3 (local) initialize(...)
9. └─mlr3:::.__ResultData__initialize(...)
10. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
11. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_pliv_tuning.R:98:5'): Unit tests for tuning of PLIV dml2_partialling out_1_FALSE ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─double_mlpliv_obj_tuned$tune(...) at test-double_ml_pliv_tuning.R:98:5
3. └─super$tune(param_set, tune_settings, tune_on_folds)
4. └─private$nuisance_tuning(...)
5. └─private$nuisance_tuning_partialX(...)
6. └─DoubleML:::dml_tune(...)
7. └─base::lapply(...)
8. └─DoubleML (local) FUN(X[[i]], ...)
9. └─DoubleML:::tune_instance(tune_settings$tuner, x)
10. └─tuner$optimize(tuning_instance)
11. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
12. └─private$.optimizer$optimize(inst)
13. └─bbotk:::.__OptimizerBatch__optimize(...)
14. └─bbotk::optimize_batch_default(inst, self)
15. ├─base::tryCatch(...)
16. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
17. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
18. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
19. └─get_private(optimizer)$.optimize(instance)
20. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
21. └─inst$eval_batch(g$data[inds])
22. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
23. └─self$objective$eval_many(xss_trafoed)
24. └─bbotk:::.__Objective__eval_many(...)
25. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
26. │ └─base::eval.parent(expr, n = 1L)
27. │ └─base::eval(expr, p)
28. │ └─base::eval(expr, p)
29. └─private$.eval_many(xss = xss, resampling = `<list>`)
30. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
31. └─mlr3::benchmark(...)
32. └─ResultData$new(grid, data_extra, store_backends = store_backends)
33. └─mlr3 (local) initialize(...)
34. └─mlr3:::.__ResultData__initialize(...)
35. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
36. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_pliv_tuning.R:188:5'): Unit tests for tuning of PLIV (multiple Z) dml2_partialling out_1_FALSE ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─double_mlpliv_obj_tuned$tune(...) at test-double_ml_pliv_tuning.R:188:5
3. └─super$tune(param_set, tune_settings, tune_on_folds)
4. └─private$nuisance_tuning(...)
5. └─private$nuisance_tuning_partialX(...)
6. └─DoubleML:::dml_tune(...)
7. └─base::lapply(...)
8. └─DoubleML (local) FUN(X[[i]], ...)
9. └─DoubleML:::tune_instance(tune_settings$tuner, x)
10. └─tuner$optimize(tuning_instance)
11. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
12. └─private$.optimizer$optimize(inst)
13. └─bbotk:::.__OptimizerBatch__optimize(...)
14. └─bbotk::optimize_batch_default(inst, self)
15. ├─base::tryCatch(...)
16. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
17. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
18. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
19. └─get_private(optimizer)$.optimize(instance)
20. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
21. └─inst$eval_batch(g$data[inds])
22. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
23. └─self$objective$eval_many(xss_trafoed)
24. └─bbotk:::.__Objective__eval_many(...)
25. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
26. │ └─base::eval.parent(expr, n = 1L)
27. │ └─base::eval(expr, p)
28. │ └─base::eval(expr, p)
29. └─private$.eval_many(xss = xss, resampling = `<list>`)
30. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
31. └─mlr3::benchmark(...)
32. └─ResultData$new(grid, data_extra, store_backends = store_backends)
33. └─mlr3 (local) initialize(...)
34. └─mlr3:::.__ResultData__initialize(...)
35. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
36. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_pliv_two_way_cluster.R:50:5'): Unit tests for PLIV with two-way clustering: regr.lm_dml1_partialling out ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─double_mlpliv_obj$fit() at test-double_ml_pliv_two_way_cluster.R:50:5
3. └─private$nuisance_est(private$get__smpls())
4. └─private$nuisance_est_partialX(smpls, ...)
5. └─DoubleML:::dml_cv_predict(...)
6. └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
7. └─ResultData$new(data, data_extra, store_backends = store_backends)
8. └─mlr3 (local) initialize(...)
9. └─mlr3:::.__ResultData__initialize(...)
10. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
11. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_pliv_user_score.R:66:5'): Unit tests for PLIV, callable score: regr.lm_dml2_partialling out ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─double_mlpliv_obj$fit() at test-double_ml_pliv_user_score.R:66:5
3. └─private$nuisance_est(private$get__smpls())
4. └─private$nuisance_est_partialX(smpls, ...)
5. └─DoubleML:::dml_cv_predict(...)
6. └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
7. └─ResultData$new(data, data_extra, store_backends = store_backends)
8. └─mlr3 (local) initialize(...)
9. └─mlr3:::.__ResultData__initialize(...)
10. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
11. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_plr.R:30:5'): Unit tests for PLR: regr.lm_dml2_partialling out ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─DoubleML:::dml_plr(...) at test-double_ml_plr.R:30:5
3. └─DoubleML:::fit_plr_single_split(...) at ./helper-08-dml_plr.R:22:5
4. └─DoubleML:::fit_nuisance_plr(...) at ./helper-08-dml_plr.R:141:3
5. └─mlr3::resample(task_l, ml_l, resampling_l, store_models = TRUE) at ./helper-08-dml_plr.R:225:3
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_plr_classifier.R:44:7'): Unit tests for PLR with classifier for ml_m: regr.rpart_classif.rpart_regr.rpart_dml2_partialling out ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─DoubleML:::dml_plr(...) at test-double_ml_plr_classifier.R:44:7
3. └─DoubleML:::fit_plr_single_split(...) at ./helper-08-dml_plr.R:22:5
4. └─DoubleML:::fit_nuisance_plr(...) at ./helper-08-dml_plr.R:141:3
5. └─mlr3::resample(task_l, ml_l, resampling_l, store_models = TRUE) at ./helper-08-dml_plr.R:225:3
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Failure ('test-double_ml_plr_classifier.R:129:3'): Unit tests for exception handling of PLR with classifier for ml_m: ──
`double_mlplr_obj$fit()` threw an error with unexpected message.
Expected match: "Assertion on 'levels\\(data\\[\\[target\\]\\])' failed: .* set \\{'0','1'\\}"
Actual message: "attempt access index 9/9 in VECTOR_ELT"
Backtrace:
▆
1. ├─testthat::expect_error(double_mlplr_obj$fit(), regexp = msg) at test-double_ml_plr_classifier.R:129:3
2. │ └─testthat:::quasi_capture(...)
3. │ ├─testthat (local) .capture(...)
4. │ │ └─base::withCallingHandlers(...)
5. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
6. └─double_mlplr_obj$fit()
7. └─private$nuisance_est(private$get__smpls())
8. └─DoubleML:::dml_cv_predict(...)
9. └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
10. └─ResultData$new(data, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Failure ('test-double_ml_plr_classifier.R:142:3'): Unit tests for exception handling of PLR with classifier for ml_m: ──
`double_mlplr_obj$fit()` threw an error with unexpected message.
Expected match: "Assertion on 'levels\\(data\\[\\[target\\]\\])' failed: .* set \\{'0','1'\\}"
Actual message: "attempt access index 9/9 in VECTOR_ELT"
Backtrace:
▆
1. ├─testthat::expect_error(double_mlplr_obj$fit(), regexp = msg) at test-double_ml_plr_classifier.R:142:3
2. │ └─testthat:::quasi_capture(...)
3. │ ├─testthat (local) .capture(...)
4. │ │ └─base::withCallingHandlers(...)
5. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
6. └─double_mlplr_obj$fit()
7. └─private$nuisance_est(private$get__smpls())
8. └─DoubleML:::dml_cv_predict(...)
9. └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
10. └─ResultData$new(data, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_plr_exception_handling.R:116:7'): Unit tests for exception handling of PLR: regr.lm_dml1_IV-type_FALSE_4_1_TRUE ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─double_mlplr_obj$fit() at test-double_ml_plr_exception_handling.R:116:7
3. └─private$nuisance_est(private$get__smpls())
4. └─DoubleML:::dml_cv_predict(...)
5. └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_plr_exception_handling.R:176:3'): Unit tests for deprecation warnings of PLR ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─testthat::expect_warning(dml_obj$tune(par_grids), regexp = msg) at test-double_ml_plr_exception_handling.R:176:3
2. │ └─testthat:::quasi_capture(...)
3. │ ├─testthat (local) .capture(...)
4. │ │ └─base::withCallingHandlers(...)
5. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
6. └─dml_obj$tune(par_grids)
7. └─super$tune(param_set, tune_settings, tune_on_folds)
8. └─private$nuisance_tuning(...)
9. └─DoubleML:::dml_tune(...)
10. └─base::lapply(...)
11. └─DoubleML (local) FUN(X[[i]], ...)
12. └─DoubleML:::tune_instance(tune_settings$tuner, x)
13. └─tuner$optimize(tuning_instance)
14. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
15. └─private$.optimizer$optimize(inst)
16. └─bbotk:::.__OptimizerBatch__optimize(...)
17. └─bbotk::optimize_batch_default(inst, self)
18. ├─base::tryCatch(...)
19. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
20. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
21. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
22. └─get_private(optimizer)$.optimize(instance)
23. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
24. └─inst$eval_batch(g$data[inds])
25. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
26. └─self$objective$eval_many(xss_trafoed)
27. └─bbotk:::.__Objective__eval_many(...)
28. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
29. │ └─base::eval.parent(expr, n = 1L)
30. │ └─base::eval(expr, p)
31. │ └─base::eval(expr, p)
32. └─private$.eval_many(xss = xss, resampling = `<list>`)
33. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
34. └─mlr3::benchmark(...)
35. └─ResultData$new(grid, data_extra, store_backends = store_backends)
36. └─mlr3 (local) initialize(...)
37. └─mlr3:::.__ResultData__initialize(...)
38. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
39. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_plr_export_preds.R:49:5'): Unit tests for for the export of predictions: regr.rpart_regr.rpart_regr.rpart_dml2_partialling out ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─double_mlplr_obj$fit(store_predictions = TRUE, store_models = TRUE) at test-double_ml_plr_export_preds.R:49:5
3. └─private$nuisance_est(private$get__smpls())
4. └─DoubleML:::dml_cv_predict(...)
5. └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_plr_loaded_mlr3learner.R:66:5'): Unit tests for PLR: dml1_IV-type ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─double_mlplr$fit() at test-double_ml_plr_loaded_mlr3learner.R:66:5
3. └─private$nuisance_est(private$get__smpls())
4. └─DoubleML:::dml_cv_predict(...)
5. └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_plr_multitreat.R:37:5'): Unit tests for PLR: regr.lm_dml2_partialling out ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─DoubleML:::dml_plr_multitreat(...) at test-double_ml_plr_multitreat.R:37:5
3. └─DoubleML:::fit_plr_single_split(...) at ./helper-08-dml_plr.R:89:7
4. └─DoubleML:::fit_nuisance_plr(...) at ./helper-08-dml_plr.R:141:3
5. └─mlr3::resample(task_l, ml_l, resampling_l, store_models = TRUE) at ./helper-08-dml_plr.R:225:3
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_plr_nocrossfit.R:51:5'): Unit tests for PLR: regr.lm_dml2_partialling out_FALSE_1 ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─DoubleML:::dml_plr(...) at test-double_ml_plr_nocrossfit.R:51:5
3. └─DoubleML:::fit_plr_single_split(...) at ./helper-08-dml_plr.R:22:5
4. └─DoubleML:::fit_nuisance_plr(...) at ./helper-08-dml_plr.R:141:3
5. └─mlr3::resample(task_l, ml_l, resampling_l, store_models = TRUE) at ./helper-08-dml_plr.R:225:3
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_plr_nocrossfit.R:51:5'): Unit tests for PLR: regr.lm_dml2_partialling out_FALSE_2 ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─DoubleML:::dml_plr(...) at test-double_ml_plr_nocrossfit.R:51:5
3. └─DoubleML:::fit_plr_single_split(...) at ./helper-08-dml_plr.R:22:5
4. └─DoubleML:::fit_nuisance_plr(...) at ./helper-08-dml_plr.R:141:3
5. └─mlr3::resample(task_l, ml_l, resampling_l, store_models = TRUE) at ./helper-08-dml_plr.R:225:3
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_plr_nonorth.R:74:5'): Unit tests for PLR: regr.lm_dml1_non_orth_score_w_g_3_2 ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─double_mlplr_obj$fit() at test-double_ml_plr_nonorth.R:74:5
3. └─private$nuisance_est(private$get__smpls())
4. └─DoubleML:::dml_cv_predict(...)
5. └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_plr_p_adjust.R:69:5'): Unit tests for PLR: regr.rpart_dml1_partialling out_romano-wolf_TRUE ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─double_mlplr_obj$fit() at test-double_ml_plr_p_adjust.R:69:5
3. └─private$nuisance_est(private$get__smpls())
4. └─DoubleML:::dml_cv_predict(...)
5. └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_plr_parameter_passing.R:48:5'): Unit tests for parameter passing of PLR (oop vs fun) regr.rpart_dml2_partialling out ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─DoubleML:::dml_plr_multitreat(...) at test-double_ml_plr_parameter_passing.R:48:5
3. └─DoubleML:::fit_plr_single_split(...) at ./helper-08-dml_plr.R:89:7
4. └─DoubleML:::fit_nuisance_plr(...) at ./helper-08-dml_plr.R:141:3
5. └─mlr3::resample(task_l, ml_l, resampling_l, store_models = TRUE) at ./helper-08-dml_plr.R:225:3
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_plr_parameter_passing.R:150:5'): Unit tests for parameter passing of PLR (no cross-fitting) regr.rpart_dml1_partialling out ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─DoubleML:::dml_plr_multitreat(...) at test-double_ml_plr_parameter_passing.R:150:5
3. └─DoubleML:::fit_plr_single_split(...) at ./helper-08-dml_plr.R:89:7
4. └─DoubleML:::fit_nuisance_plr(...) at ./helper-08-dml_plr.R:141:3
5. └─mlr3::resample(task_l, ml_l, resampling_l, store_models = TRUE) at ./helper-08-dml_plr.R:225:3
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_plr_parameter_passing.R:264:5'): Unit tests for parameter passing of PLR (fold-wise vs global) regr.rpart_dml2_partialling out ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─double_mlplr_obj$fit() at test-double_ml_plr_parameter_passing.R:264:5
3. └─private$nuisance_est(private$get__smpls())
4. └─DoubleML:::dml_cv_predict(...)
5. └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_plr_parameter_passing.R:353:5'): Unit tests for parameter passing of PLR (default vs explicit) regr.rpart_dml2_partialling out ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─dml_plr_default$fit() at test-double_ml_plr_parameter_passing.R:353:5
3. └─private$nuisance_est(private$get__smpls())
4. └─DoubleML:::dml_cv_predict(...)
5. └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_plr_rep_cross_fit.R:38:5'): Unit tests for PLR: regr.lm_dml1_partialling out_5 ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─DoubleML:::dml_plr(...) at test-double_ml_plr_rep_cross_fit.R:38:5
3. └─DoubleML:::fit_plr_single_split(...) at ./helper-08-dml_plr.R:22:5
4. └─DoubleML:::fit_nuisance_plr(...) at ./helper-08-dml_plr.R:141:3
5. └─mlr3::resample(task_l, ml_l, resampling_l, store_models = TRUE) at ./helper-08-dml_plr.R:225:3
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_plr_set_samples.R:53:5'): PLR with external sample provision: regr.rpart_dml2_partialling out_2_1 ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─double_mlplr_obj$fit() at test-double_ml_plr_set_samples.R:53:5
3. └─private$nuisance_est(private$get__smpls())
4. └─DoubleML:::dml_cv_predict(...)
5. └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_plr_tuning.R:95:5'): Unit tests for tuning of PLR: regr.rpart_regr.rpart_dml2_partialling out_1_FALSE ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─double_mlplr_obj_tuned$tune(...) at test-double_ml_plr_tuning.R:95:5
3. └─super$tune(param_set, tune_settings, tune_on_folds)
4. └─private$nuisance_tuning(...)
5. └─DoubleML:::dml_tune(...)
6. └─base::lapply(...)
7. └─DoubleML (local) FUN(X[[i]], ...)
8. └─DoubleML:::tune_instance(tune_settings$tuner, x)
9. └─tuner$optimize(tuning_instance)
10. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
11. └─private$.optimizer$optimize(inst)
12. └─bbotk:::.__OptimizerBatch__optimize(...)
13. └─bbotk::optimize_batch_default(inst, self)
14. ├─base::tryCatch(...)
15. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
16. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
17. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
18. └─get_private(optimizer)$.optimize(instance)
19. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
20. └─inst$eval_batch(g$data[inds])
21. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
22. └─self$objective$eval_many(xss_trafoed)
23. └─bbotk:::.__Objective__eval_many(...)
24. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
25. │ └─base::eval.parent(expr, n = 1L)
26. │ └─base::eval(expr, p)
27. │ └─base::eval(expr, p)
28. └─private$.eval_many(xss = xss, resampling = `<list>`)
29. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
30. └─mlr3::benchmark(...)
31. └─ResultData$new(grid, data_extra, store_backends = store_backends)
32. └─mlr3 (local) initialize(...)
33. └─mlr3:::.__ResultData__initialize(...)
34. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
35. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_plr_tuning.R:95:5'): Unit tests for tuning of PLR: regr.rpart_regr.rpart_dml2_partialling out_1_TRUE ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─double_mlplr_obj_tuned$tune(...) at test-double_ml_plr_tuning.R:95:5
3. └─super$tune(param_set, tune_settings, tune_on_folds)
4. └─private$nuisance_tuning(...)
5. └─DoubleML:::dml_tune(...)
6. └─base::lapply(...)
7. └─DoubleML (local) FUN(X[[i]], ...)
8. └─DoubleML:::tune_instance(tune_settings$tuner, x)
9. └─tuner$optimize(tuning_instance)
10. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
11. └─private$.optimizer$optimize(inst)
12. └─bbotk:::.__OptimizerBatch__optimize(...)
13. └─bbotk::optimize_batch_default(inst, self)
14. ├─base::tryCatch(...)
15. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
16. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
17. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
18. └─get_private(optimizer)$.optimize(instance)
19. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
20. └─inst$eval_batch(g$data[inds])
21. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
22. └─self$objective$eval_many(xss_trafoed)
23. └─bbotk:::.__Objective__eval_many(...)
24. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
25. │ └─base::eval.parent(expr, n = 1L)
26. │ └─base::eval(expr, p)
27. │ └─base::eval(expr, p)
28. └─private$.eval_many(xss = xss, resampling = `<list>`)
29. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
30. └─mlr3::benchmark(...)
31. └─ResultData$new(grid, data_extra, store_backends = store_backends)
32. └─mlr3 (local) initialize(...)
33. └─mlr3:::.__ResultData__initialize(...)
34. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
35. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_plr_user_score.R:48:5'): Unit tests for PLR, callable score: regr.lm_dml1_3_2 ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─double_mlplr_obj$fit() at test-double_ml_plr_user_score.R:48:5
3. └─private$nuisance_est(private$get__smpls())
4. └─DoubleML:::dml_cv_predict(...)
5. └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_print.R:12:1'): (code run outside of `test_that()`) ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─dml_plr$fit() at test-double_ml_print.R:12:1
2. └─private$nuisance_est(private$get__smpls())
3. └─DoubleML:::dml_cv_predict(...)
4. └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
5. └─ResultData$new(data, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_ssm_mar.R:32:5'): Unit tests for SSM, missing-at-random: cv_glmnet_dml1_missing-at-random_0 ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─DoubleML:::dml_ssm(...) at test-double_ml_ssm_mar.R:32:5
3. └─DoubleML:::fit_nuisance_ssm(...) at ./helper-17-dml_ssm.R:22:5
4. └─mlr3::resample(task_pi, ml_pi, resampling_pi, store_models = TRUE) at ./helper-17-dml_ssm.R:147:5
5. └─ResultData$new(data, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_ssm_nonignorable.R:32:5'): Unit tests for SSM, nonignorable nonresponse: cv_glmnet_dml1_nonignorable_0 ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─DoubleML:::dml_ssm(...) at test-double_ml_ssm_nonignorable.R:32:5
3. └─DoubleML:::fit_nuisance_ssm(...) at ./helper-17-dml_ssm.R:22:5
4. └─mlr3::resample(...) at ./helper-17-dml_ssm.R:239:7
5. └─ResultData$new(data, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_ssm_tuning.R:75:5'): Unit tests for tuning of SSM: rpart_dml2_missing-at-random_1_FALSE ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─double_mlssm_obj_tuned$tune(...) at test-double_ml_ssm_tuning.R:75:5
3. └─super$tune(param_set, tune_settings, tune_on_folds)
4. └─private$nuisance_tuning(...)
5. └─DoubleML:::dml_tune(...)
6. └─base::lapply(...)
7. └─DoubleML (local) FUN(X[[i]], ...)
8. └─DoubleML:::tune_instance(tune_settings$tuner, x)
9. └─tuner$optimize(tuning_instance)
10. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
11. └─private$.optimizer$optimize(inst)
12. └─bbotk:::.__OptimizerBatch__optimize(...)
13. └─bbotk::optimize_batch_default(inst, self)
14. ├─base::tryCatch(...)
15. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
16. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
17. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
18. └─get_private(optimizer)$.optimize(instance)
19. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
20. └─inst$eval_batch(design$data)
21. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
22. └─self$objective$eval_many(xss_trafoed)
23. └─bbotk:::.__Objective__eval_many(...)
24. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
25. │ └─base::eval.parent(expr, n = 1L)
26. │ └─base::eval(expr, p)
27. │ └─base::eval(expr, p)
28. └─private$.eval_many(xss = xss, resampling = `<list>`)
29. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
30. └─mlr3::benchmark(...)
31. └─ResultData$new(grid, data_extra, store_backends = store_backends)
32. └─mlr3 (local) initialize(...)
33. └─mlr3:::.__ResultData__initialize(...)
34. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
35. └─data.table:::`[.data.table`(...)
── Error ('test-double_ml_ssm_tuning.R:75:5'): Unit tests for tuning of SSM: rpart_dml2_nonignorable_1_FALSE ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─rlang::eval_tidy(code, test_args)
2. └─double_mlssm_obj_tuned$tune(...) at test-double_ml_ssm_tuning.R:75:5
3. └─super$tune(param_set, tune_settings, tune_on_folds)
4. └─private$nuisance_tuning(...)
5. └─DoubleML:::dml_tune(...)
6. └─base::lapply(...)
7. └─DoubleML (local) FUN(X[[i]], ...)
8. └─DoubleML:::tune_instance(tune_settings$tuner, x)
9. └─tuner$optimize(tuning_instance)
10. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
11. └─private$.optimizer$optimize(inst)
12. └─bbotk:::.__OptimizerBatch__optimize(...)
13. └─bbotk::optimize_batch_default(inst, self)
14. ├─base::tryCatch(...)
15. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
16. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
17. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
18. └─get_private(optimizer)$.optimize(instance)
19. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
20. └─inst$eval_batch(design$data)
21. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
22. └─self$objective$eval_many(xss_trafoed)
23. └─bbotk:::.__Objective__eval_many(...)
24. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
25. │ └─base::eval.parent(expr, n = 1L)
26. │ └─base::eval(expr, p)
27. │ └─base::eval(expr, p)
28. └─private$.eval_many(xss = xss, resampling = `<list>`)
29. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
30. └─mlr3::benchmark(...)
31. └─ResultData$new(grid, data_extra, store_backends = store_backends)
32. └─mlr3 (local) initialize(...)
33. └─mlr3:::.__ResultData__initialize(...)
34. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
35. └─data.table:::`[.data.table`(...)
[ FAIL 63 | WARN 0 | SKIP 7 | PASS 296 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-windows-x86_64
Version: 1.0.2
Check: re-building of vignette outputs
Result: ERROR
Error(s) in re-building vignettes:
--- re-building 'Introduction_to_DoubleML.Rmd' using rmarkdown
--- finished re-building 'Introduction_to_DoubleML.Rmd'
--- re-building 'getstarted.Rmd' using rmarkdown
Quitting from getstarted.Rmd:124-133 [unnamed-chunk-6]
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
<error/rlang_error>
Error in `[.data.table`:
! attempt access index 9/9 in VECTOR_ELT
---
Backtrace:
▆
1. └─obj_dml_plr_bonus$fit()
2. └─private$nuisance_est(private$get__smpls())
3. └─DoubleML:::dml_cv_predict(...)
4. └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
5. └─ResultData$new(data, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Error: processing vignette 'getstarted.Rmd' failed with diagnostics:
attempt access index 9/9 in VECTOR_ELT
--- failed re-building 'getstarted.Rmd'
--- re-building 'install.Rmd' using rmarkdown
--- finished re-building 'install.Rmd'
SUMMARY: processing the following file failed:
'getstarted.Rmd'
Error: Vignette re-building failed.
Execution halted
Flavor: r-devel-windows-x86_64
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