CRAN Package Check Results for Package DoubleML

Last updated on 2021-08-03 07:54:20 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 0.3.0 11.09 373.78 384.87 OK
r-devel-linux-x86_64-debian-gcc 0.3.0 10.06 266.54 276.60 OK
r-devel-linux-x86_64-fedora-clang 0.3.1 457.86 OK
r-devel-linux-x86_64-fedora-gcc 0.3.1 434.72 OK
r-devel-windows-x86_64 0.3.0 13.00 422.00 435.00 OK
r-devel-windows-x86_64-gcc10-UCRT 0.3.0 OK
r-patched-linux-x86_64 0.3.0 13.31 345.69 359.00 OK
r-patched-solaris-x86 0.3.1 387.40 ERROR
r-release-linux-x86_64 0.3.0 11.95 345.91 357.86 OK
r-release-macos-arm64 0.3.0 OK
r-release-macos-x86_64 0.3.0 OK
r-release-windows-ix86+x86_64 0.3.0 22.00 408.00 430.00 OK
r-oldrel-macos-x86_64 0.3.0 OK
r-oldrel-windows-ix86+x86_64 0.3.0 18.00 446.00 464.00 OK

Check Details

Version: 0.3.1
Check: tests
Result: ERROR
     Running ‘testthat_regression_tests.R’ [229s/274s]
    Running the tests in ‘tests/testthat_regression_tests.R’ failed.
    Complete output:
     >
     > library("testthat")
     > library("patrick")
     > library("DoubleML")
     >
     > testthat::test_check("DoubleML")
     ══ Skipped tests ═══════════════════════════════════════════════════════════════
     • On CRAN (7)
    
     ══ Failed tests ════════════════════════════════════════════════════════════════
     ── Error (test-double_ml_iivm.R:32:5): Unit tests for IIVM: cv_glmnet_dml2_LATE_0 ──
     Error: 'NA' indices are not (yet?) supported for sparse Matrices
     Backtrace:
     █
     1. ├─rlang::eval_tidy(code, args)
     2. └─DoubleML:::dml_irmiv(...) test-double_ml_iivm.R:32:4
     3. └─DoubleML:::fit_nuisance_iivm(...) helper-11-dml_iivm.R:23:4
     4. └─mlr3::resample(task_m, ml_m, resampling_m, store_models = TRUE) helper-11-dml_iivm.R:143:2
     5. └─future.apply::future_lapply(...)
     6. └─future.apply:::future_xapply(...)
     7. ├─future::value(fs)
     8. └─future:::value.list(fs)
     9. ├─future::resolve(...)
     10. └─future:::resolve.list(...)
     11. └─future:::signalConditionsASAP(obj, resignal = FALSE, pos = ii)
     12. └─future:::signalConditions(...)
     ── Error (test-double_ml_iivm_user_score.R:55:5): Unit tests for IIVM, callable score: regr.glmnet_classif.glmnet_dml2_0 ──
     Error: need at least two non-NA values to interpolate
     Backtrace:
     █
     1. ├─rlang::eval_tidy(code, args)
     2. └─double_mliivm_obj$fit() test-double_ml_iivm_user_score.R:55:4
     3. └─private$ml_nuisance_and_score_elements(private$get__smpls())
     4. └─DoubleML:::dml_cv_predict(...)
     5. └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
     6. └─future.apply::future_lapply(...)
     7. └─future.apply:::future_xapply(...)
     8. ├─future::value(fs)
     9. └─future:::value.list(fs)
     10. ├─future::resolve(...)
     11. └─future:::resolve.list(...)
     12. └─future:::signalConditionsASAP(obj, resignal = FALSE, pos = ii)
     13. └─future:::signalConditions(...)
     ── Error (test-double_ml_irm.R:32:5): Unit tests for IRM: cv_glmnet_dml1_ATTE_0 ──
     Error: missing value where TRUE/FALSE needed
     Backtrace:
     █
     1. ├─rlang::eval_tidy(code, args)
     2. └─DoubleML:::dml_irm(...) test-double_ml_irm.R:32:4
     3. └─DoubleML:::fit_nuisance_irm(...) helper-10-dml_irm.R:21:4
     4. └─mlr3::resample(task_m, ml_m, resampling_m, store_models = TRUE) helper-10-dml_irm.R:129:2
     5. └─future.apply::future_lapply(...)
     6. └─future.apply:::future_xapply(...)
     7. ├─future::value(fs)
     8. └─future:::value.list(fs)
     9. ├─future::resolve(...)
     10. └─future:::resolve.list(...)
     11. └─future:::signalConditionsASAP(obj, resignal = FALSE, pos = ii)
     12. └─future:::signalConditions(...)
     ── Error (test-double_ml_irm_user_score.R:54:5): Unit tests for IRM, callable score: regr.glmnet_classif.glmnet_dml2_0 ──
     Error: missing value where TRUE/FALSE needed
     Backtrace:
     █
     1. ├─rlang::eval_tidy(code, args)
     2. └─double_mlirm_obj$fit() test-double_ml_irm_user_score.R:54:4
     3. └─private$ml_nuisance_and_score_elements(private$get__smpls())
     4. └─DoubleML:::dml_cv_predict(...)
     5. └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
     6. └─future.apply::future_lapply(...)
     7. └─future.apply:::future_xapply(...)
     8. ├─future::value(fs)
     9. └─future:::value.list(fs)
     10. ├─future::resolve(...)
     11. └─future:::resolve.list(...)
     12. └─future:::signalConditionsASAP(obj, resignal = FALSE, pos = ii)
     13. └─future:::signalConditions(...)
     ── Error (test-double_ml_pliv.R:29:5): Unit tests for PLIV: regr.glmnet_dml1_partialling out ──
     Error: missing value where TRUE/FALSE needed
     Backtrace:
     █
     1. ├─rlang::eval_tidy(code, args)
     2. └─DoubleML:::dml_pliv(...) test-double_ml_pliv.R:29:4
     3. └─DoubleML:::fit_nuisance_pliv(...) helper-09-dml_pliv.R:20:4
     4. └─mlr3::resample(task_g, ml_g, resampling_g, store_models = TRUE) helper-09-dml_pliv.R:101:2
     5. └─future.apply::future_lapply(...)
     6. └─future.apply:::future_xapply(...)
     7. ├─future::value(fs)
     8. └─future:::value.list(fs)
     9. ├─future::resolve(...)
     10. └─future:::resolve.list(...)
     11. └─future:::signalConditionsASAP(obj, resignal = FALSE, pos = ii)
     12. └─future:::signalConditions(...)
     ── Error (test-double_ml_pliv_partial_functional_initializer.R:40:5): Unit tests for PLIV (partialX functional initialization): regr.cv_glmnet_dml2_partialling out ──
     Error: missing value where TRUE/FALSE needed
     Backtrace:
     █
     1. ├─rlang::eval_tidy(code, args)
     2. └─double_mlpliv_obj$fit() test-double_ml_pliv_partial_functional_initializer.R:40:4
     3. └─private$ml_nuisance_and_score_elements(private$get__smpls())
     4. └─private$ml_nuisance_and_score_elements_partialX(smpls, ...)
     5. └─DoubleML:::dml_cv_predict(...)
     6. └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
     7. └─future.apply::future_lapply(...)
     8. └─future.apply:::future_xapply(...)
     9. ├─future::value(fs)
     10. └─future:::value.list(fs)
     11. ├─future::resolve(...)
     12. └─future:::resolve.list(...)
     13. └─future:::signalConditionsASAP(obj, resignal = FALSE, pos = ii)
     14. └─future:::signalConditions(...)
     ── Error (test-double_ml_pliv_partial_functional_initializer.R:82:5): Unit tests for PLIV (partialZ functional initialization): regr.cv_glmnet_dml2_partialling out ──
     Error: missing value where TRUE/FALSE needed
     Backtrace:
     █
     1. ├─rlang::eval_tidy(code, args)
     2. └─double_mlpliv_partZ$fit() test-double_ml_pliv_partial_functional_initializer.R:82:4
     3. └─private$ml_nuisance_and_score_elements(private$get__smpls())
     4. └─private$ml_nuisance_and_score_elements_partialZ(smpls, ...)
     5. └─DoubleML:::dml_cv_predict(...)
     6. └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
     7. └─future.apply::future_lapply(...)
     8. └─future.apply:::future_xapply(...)
     9. ├─future::value(fs)
     10. └─future:::value.list(fs)
     11. ├─future::resolve(...)
     12. └─future:::resolve.list(...)
     13. └─future:::signalConditionsASAP(obj, resignal = FALSE, pos = ii)
     14. └─future:::signalConditions(...)
     ── Error (test-double_ml_pliv_partial_functional_initializer.R:121:5): Unit tests for PLIV (partialXZ functional initialization): regr.cv_glmnet_dml2_partialling out ──
     Error: missing value where TRUE/FALSE needed
     Backtrace:
     █
     1. ├─rlang::eval_tidy(code, args)
     2. └─double_mlpliv_partXZ$fit() test-double_ml_pliv_partial_functional_initializer.R:121:4
     3. └─private$ml_nuisance_and_score_elements(private$get__smpls())
     4. └─private$ml_nuisance_and_score_elements_partialXZ(smpls, ...)
     5. └─DoubleML:::dml_cv_predict(...)
     6. └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
     7. └─future.apply::future_lapply(...)
     8. └─future.apply:::future_xapply(...)
     9. ├─future::value(fs)
     10. └─future:::value.list(fs)
     11. ├─future::resolve(...)
     12. └─future:::resolve.list(...)
     13. └─future:::signalConditionsASAP(obj, resignal = FALSE, pos = ii)
     14. └─future:::signalConditions(...)
     ── Error (test-double_ml_pliv_user_score.R:46:5): Unit tests for PLIV, callable score: regr.glmnet_dml2 ──
     Error: missing value where TRUE/FALSE needed
     Backtrace:
     █
     1. ├─rlang::eval_tidy(code, args)
     2. └─double_mlpliv_obj$fit() test-double_ml_pliv_user_score.R:46:4
     3. └─private$ml_nuisance_and_score_elements(private$get__smpls())
     4. └─private$ml_nuisance_and_score_elements_partialX(smpls, ...)
     5. └─DoubleML:::dml_cv_predict(...)
     6. └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
     7. └─future.apply::future_lapply(...)
     8. └─future.apply:::future_xapply(...)
     9. ├─future::value(fs)
     10. └─future:::value.list(fs)
     11. ├─future::resolve(...)
     12. └─future:::resolve.list(...)
     13. └─future:::signalConditionsASAP(obj, resignal = FALSE, pos = ii)
     14. └─future:::signalConditions(...)
     ── Error (test-double_ml_plr.R:30:5): Unit tests for PLR: regr.cv_glmnet_dml2_partialling out ──
     Error: missing value where TRUE/FALSE needed
     Backtrace:
     █
     1. ├─rlang::eval_tidy(code, args)
     2. └─DoubleML:::dml_plr(...) test-double_ml_plr.R:30:4
     3. └─DoubleML:::fit_plr_single_split(...) helper-08-dml_plr.R:22:4
     4. └─DoubleML:::fit_nuisance_plr(...) helper-08-dml_plr.R:133:2
     5. └─mlr3::resample(task_g, ml_g, resampling_g, store_models = TRUE) helper-08-dml_plr.R:204:2
     6. └─future.apply::future_lapply(...)
     7. └─future.apply:::future_xapply(...)
     8. ├─future::value(fs)
     9. └─future:::value.list(fs)
     10. ├─future::resolve(...)
     11. └─future:::resolve.list(...)
     12. └─future:::signalConditionsASAP(obj, resignal = FALSE, pos = ii)
     13. └─future:::signalConditions(...)
     ── Error (test-double_ml_plr_classifier.R:35:7): Unit tests for PLR with classifier for ml_m: regr.cv_glmnet_classif.cv_glmnet_dml2_partialling out ──
     Error: missing value where TRUE/FALSE needed
     Backtrace:
     █
     1. ├─rlang::eval_tidy(code, args)
     2. └─DoubleML:::dml_plr(...) test-double_ml_plr_classifier.R:35:6
     3. └─DoubleML:::fit_plr_single_split(...) helper-08-dml_plr.R:22:4
     4. └─DoubleML:::fit_nuisance_plr(...) helper-08-dml_plr.R:133:2
     5. └─mlr3::resample(task_g, ml_g, resampling_g, store_models = TRUE) helper-08-dml_plr.R:204:2
     6. └─future.apply::future_lapply(...)
     7. └─future.apply:::future_xapply(...)
     8. ├─future::value(fs)
     9. └─future:::value.list(fs)
     10. ├─future::resolve(...)
     11. └─future:::resolve.list(...)
     12. └─future:::signalConditionsASAP(obj, resignal = FALSE, pos = ii)
     13. └─future:::signalConditions(...)
     ── Error (test-double_ml_plr_export_preds.R:31:5): Unit tests for PLR with classifier for ml_m: regr.cv_glmnet_regr.cv_glmnet_dml2_partialling out ──
     Error: missing value where TRUE/FALSE needed
     Backtrace:
     █
     1. ├─rlang::eval_tidy(code, args)
     2. └─double_mlplr_obj$fit(store_predictions = TRUE) test-double_ml_plr_export_preds.R:31:4
     3. └─private$ml_nuisance_and_score_elements(private$get__smpls())
     4. └─DoubleML:::dml_cv_predict(...)
     5. └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
     6. └─future.apply::future_lapply(...)
     7. └─future.apply:::future_xapply(...)
     8. ├─future::value(fs)
     9. └─future:::value.list(fs)
     10. ├─future::resolve(...)
     11. └─future:::resolve.list(...)
     12. └─future:::signalConditionsASAP(obj, resignal = FALSE, pos = ii)
     13. └─future:::signalConditions(...)
     ── Error (test-double_ml_plr_loaded_mlr3learner.R:52:5): Unit tests for PLR: dml1_IV-type ──
     Error: missing value where TRUE/FALSE needed
     Backtrace:
     █
     1. ├─rlang::eval_tidy(code, args)
     2. └─double_mlplr$fit() test-double_ml_plr_loaded_mlr3learner.R:52:4
     3. └─private$ml_nuisance_and_score_elements(private$get__smpls())
     4. └─DoubleML:::dml_cv_predict(...)
     5. └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
     6. └─future.apply::future_lapply(...)
     7. └─future.apply:::future_xapply(...)
     8. ├─future::value(fs)
     9. └─future:::value.list(fs)
     10. ├─future::resolve(...)
     11. └─future:::resolve.list(...)
     12. └─future:::signalConditionsASAP(obj, resignal = FALSE, pos = ii)
     13. └─future:::signalConditions(...)
     ── Error (test-double_ml_plr_nonorth.R:48:5): Unit tests for PLR: regr.cv_glmnet_dml1_function (y, d, g_hat, m_hat, smpls)
     {
     u_hat = y - g_hat
     psi_a = -1 * d * d
     psi_b = d * u_hat
     psis = list(psi_a = psi_a, psi_b = psi_b)
     return(psis)
     }_3_2 ──
     Error: missing value where TRUE/FALSE needed
     Backtrace:
     █
     1. ├─rlang::eval_tidy(code, args)
     2. └─double_mlplr_obj$fit() test-double_ml_plr_nonorth.R:48:4
     3. └─private$ml_nuisance_and_score_elements(private$get__smpls())
     4. └─DoubleML:::dml_cv_predict(...)
     5. └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
     6. └─future.apply::future_lapply(...)
     7. └─future.apply:::future_xapply(...)
     8. ├─future::value(fs)
     9. └─future:::value.list(fs)
     10. ├─future::resolve(...)
     11. └─future:::resolve.list(...)
     12. └─future:::signalConditionsASAP(obj, resignal = FALSE, pos = ii)
     13. └─future:::signalConditions(...)
     ── Error (test-double_ml_plr_p_adjust.R:64:5): Unit tests for PLR: regr.cv_glmnet_dml1_partialling out_romano-wolf_TRUE ──
     Error: missing value where TRUE/FALSE needed
     Backtrace:
     █
     1. ├─rlang::eval_tidy(code, args)
     2. └─double_mlplr_obj$fit() test-double_ml_plr_p_adjust.R:64:4
     3. └─private$ml_nuisance_and_score_elements(private$get__smpls())
     4. └─DoubleML:::dml_cv_predict(...)
     5. └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
     6. └─future.apply::future_lapply(...)
     7. └─future.apply:::future_xapply(...)
     8. ├─future::value(fs)
     9. └─future:::value.list(fs)
     10. ├─future::resolve(...)
     11. └─future:::resolve.list(...)
     12. └─future:::signalConditionsASAP(obj, resignal = FALSE, pos = ii)
     13. └─future:::signalConditions(...)
     ── Error (test-double_ml_plr_set_samples.R:47:5): PLR with external sample provision: regr.cv_glmnet_dml2_partialling out_2_1 ──
     Error: missing value where TRUE/FALSE needed
     Backtrace:
     █
     1. ├─rlang::eval_tidy(code, args)
     2. └─double_mlplr_obj$fit() test-double_ml_plr_set_samples.R:47:4
     3. └─private$ml_nuisance_and_score_elements(private$get__smpls())
     4. └─DoubleML:::dml_cv_predict(...)
     5. └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
     6. └─future.apply::future_lapply(...)
     7. └─future.apply:::future_xapply(...)
     8. ├─future::value(fs)
     9. └─future:::value.list(fs)
     10. ├─future::resolve(...)
     11. └─future:::resolve.list(...)
     12. └─future:::signalConditionsASAP(obj, resignal = FALSE, pos = ii)
     13. └─future:::signalConditions(...)
     ── Error (test-double_ml_plr_user_score.R:48:5): Unit tests for PLR, callable score: regr.glmnet_dml1_3_2 ──
     Error: missing value where TRUE/FALSE needed
     Backtrace:
     █
     1. ├─rlang::eval_tidy(code, args)
     2. └─double_mlplr_obj$fit() test-double_ml_plr_user_score.R:48:4
     3. └─private$ml_nuisance_and_score_elements(private$get__smpls())
     4. └─DoubleML:::dml_cv_predict(...)
     5. └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
     6. └─future.apply::future_lapply(...)
     7. └─future.apply:::future_xapply(...)
     8. ├─future::value(fs)
     9. └─future:::value.list(fs)
     10. ├─future::resolve(...)
     11. └─future:::resolve.list(...)
     12. └─future:::signalConditionsASAP(obj, resignal = FALSE, pos = ii)
     13. └─future:::signalConditions(...)
    
     [ FAIL 17 | WARN 0 | SKIP 7 | PASS 331 ]
     Error: Test failures
     Execution halted
Flavor: r-patched-solaris-x86