Running ‘testthat_regression_tests.R’ [208s/208s]
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 in `intI(j, n = x@Dim[2], dn[[2]], give.dn = FALSE)`: '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 in `approx(lambda, seq(lambda), sfrac)`: 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$get__smpls())
    4.     └─DoubleML:::dml_cv_predict(...)
    5.       └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
    6.         └─future.apply::future_lapply(...)
    7.           └─future.apply:::future_xapply(...)
    8.             ├─future::value(fs)
    9.             └─future:::value.list(fs)
   10.               ├─future::resolve(...)
   11.               └─future:::resolve.list(...)
   12.                 └─future:::signalConditionsASAP(obj, resignal = FALSE, pos = ii)
   13.                   └─future:::signalConditions(...)
  ── Error (test-double_ml_irm.R:32:5): Unit tests for IRM: cv_glmnet_dml1_ATTE_0 ──
  Error in `if (prod(dims) > .Machine$integer.max) stop("attempt to make a table with >= 2^31 elements")`: 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 in `if (prod(dims) > .Machine$integer.max) stop("attempt to make a table with >= 2^31 elements")`: missing value where TRUE/FALSE needed
  Backtrace:
       █
    1. ├─rlang::eval_tidy(code, args)
    2. └─double_mlirm_obj$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 in `if (nulldev == 0) stop("y is constant; gaussian glmnet fails at standardization step")`: 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 in `if (nulldev == 0) stop("y is constant; gaussian glmnet fails at standardization step")`: 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 in `if (nulldev == 0) stop("y is constant; gaussian glmnet fails at standardization step")`: 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 in `if (nulldev == 0) stop("y is constant; gaussian glmnet fails at standardization step")`: 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 in `if (nulldev == 0) stop("y is constant; gaussian glmnet fails at standardization step")`: 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 in `if (nulldev == 0) stop("y is constant; gaussian glmnet fails at standardization step")`: 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 in `if (nulldev == 0) stop("y is constant; gaussian glmnet fails at standardization step")`: 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 in `if (nulldev == 0) stop("y is constant; gaussian glmnet fails at standardization step")`: 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$get__smpls())
    4.     └─DoubleML:::dml_cv_predict(...)
    5.       └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
    6.         └─future.apply::future_lapply(...)
    7.           └─future.apply:::future_xapply(...)
    8.             ├─future::value(fs)
    9.             └─future:::value.list(fs)
   10.               ├─future::resolve(...)
   11.               └─future:::resolve.list(...)
   12.                 └─future:::signalConditionsASAP(obj, resignal = FALSE, pos = ii)
   13.                   └─future:::signalConditions(...)
  ── Error (test-double_ml_plr_loaded_mlr3learner.R:52:5): Unit tests for PLR: dml1_IV-type ──
  Error in `if (nulldev == 0) stop("y is constant; gaussian glmnet fails at standardization step")`: missing value where TRUE/FALSE needed
  Backtrace:
       █
    1. ├─rlang::eval_tidy(code, args)
    2. └─double_mlplr$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 in `if (nulldev == 0) stop("y is constant; gaussian glmnet fails at standardization step")`: 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$get__smpls())
    4.     └─DoubleML:::dml_cv_predict(...)
    5.       └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
    6.         └─future.apply::future_lapply(...)
    7.           └─future.apply:::future_xapply(...)
    8.             ├─future::value(fs)
    9.             └─future:::value.list(fs)
   10.               ├─future::resolve(...)
   11.               └─future:::resolve.list(...)
   12.                 └─future:::signalConditionsASAP(obj, resignal = FALSE, pos = ii)
   13.                   └─future:::signalConditions(...)
  ── Error (test-double_ml_plr_p_adjust.R:64:5): Unit tests for PLR: regr.cv_glmnet_dml1_partialling out_romano-wolf_TRUE ──
  Error in `if (nulldev == 0) stop("y is constant; gaussian glmnet fails at standardization step")`: missing value where TRUE/FALSE needed
  Backtrace:
       █
    1. ├─rlang::eval_tidy(code, args)
    2. └─double_mlplr_obj$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 in `if (nulldev == 0) stop("y is constant; gaussian glmnet fails at standardization step")`: 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$get__smpls())
    4.     └─DoubleML:::dml_cv_predict(...)
    5.       └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
    6.         └─future.apply::future_lapply(...)
    7.           └─future.apply:::future_xapply(...)
    8.             ├─future::value(fs)
    9.             └─future:::value.list(fs)
   10.               ├─future::resolve(...)
   11.               └─future:::resolve.list(...)
   12.                 └─future:::signalConditionsASAP(obj, resignal = FALSE, pos = ii)
   13.                   └─future:::signalConditions(...)
  ── Error (test-double_ml_plr_user_score.R:48:5): Unit tests for PLR, callable score: regr.glmnet_dml1_3_2 ──
  Error in `if (nulldev == 0) stop("y is constant; gaussian glmnet fails at standardization step")`: missing value where TRUE/FALSE needed
  Backtrace:
       █
    1. ├─rlang::eval_tidy(code, args)
    2. └─double_mlplr_obj$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 45 | SKIP 7 | PASS 331 ]
  Error: Test failures
  Execution halted