Running ‘testthat.R’ [10s/11s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
  > # This file is part of the standard setup for testthat.
  > # It is recommended that you do not modify it.
  > #
  > # Where should you do additional test configuration?
  > # Learn more about the roles of various files in:
  > # * https://r-pkgs.org/tests.html
  > # * https://testthat.r-lib.org/reference/test_package.html#special-files
  > 
  > Sys.setenv("OMP_THREAD_LIMIT" = 2)
  > Sys.setenv("Ncpu" = 2)
  > 
  > library(testthat)
  > library(mlsurvlrnrs)
  > 
  > test_check("mlsurvlrnrs")
  
  CV fold: Fold1
  Parameter 'ncores' is ignored for learner 'LearnerSurvCoxPHCox'.
  
  CV fold: Fold2
  Parameter 'ncores' is ignored for learner 'LearnerSurvCoxPHCox'.
  
  CV fold: Fold3
  Parameter 'ncores' is ignored for learner 'LearnerSurvCoxPHCox'.
  
  CV fold: Fold1
  Saving _problems/test-surv_glmnet_cox-99.R
  
  CV fold: Fold1
  
  Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
  ... reducing initialization grid to 10 rows.
  Saving _problems/test-surv_ranger_cox-110.R
  
  CV fold: Fold1
  
  Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
  ... reducing initialization grid to 10 rows.
  Saving _problems/test-surv_rpart_cox-108.R
  
  CV fold: Fold1
  
  Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
  ... reducing initialization grid to 10 rows.
  Saving _problems/test-surv_xgboost_aft-121.R
  
  CV fold: Fold1
  
  CV fold: Fold2
  
  CV fold: Fold3
  
  CV fold: Fold1
  
  Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
  ... reducing initialization grid to 10 rows.
  Saving _problems/test-surv_xgboost_cox-118.R
  
  CV fold: Fold1
  
  CV fold: Fold2
  
  CV fold: Fold3
  [ FAIL 5 | WARN 0 | SKIP 1 | PASS 9 ]
  
  ══ Skipped tests (1) ═══════════════════════════════════════════════════════════
  • On CRAN (1): 'test-lints.R:10:5'
  
  ══ Failed tests ════════════════════════════════════════════════════════════════
  ── Error ('test-surv_glmnet_cox.R:99:5'): test nested cv, grid - surv_glmnet_cox ──
  Error: Package "ParBayesianOptimization" must be installed to use 'strategy = "bayesian"'.
  Backtrace:
       ▆
    1. └─surv_glmnet_cox_optimizer$execute() at test-surv_glmnet_cox.R:99:5
    2.   └─mlexperiments:::.run_cv(self = self, private = private)
    3.     └─mlexperiments:::.fold_looper(self, private)
    4.       ├─base::do.call(private$cv_run_model, run_args)
    5.       └─mlexperiments (local) `<fn>`(train_index = `<int>`, fold_train = `<list>`, fold_test = `<list>`)
    6.         ├─base::do.call(.cv_run_nested_model, args)
    7.         └─mlexperiments (local) `<fn>`(...)
    8.           └─hparam_tuner$execute(k = self$k_tuning)
    9.             └─private$select_optimizer(self, private)
   10.               └─BayesianOptimizer$new(...)
   11.                 └─mlexperiments (local) initialize(...)
  ── Error ('test-surv_ranger_cox.R:110:5'): test nested cv, bayesian - surv_ranger_cox ──
  Error: Package "ParBayesianOptimization" must be installed to use 'strategy = "bayesian"'.
  Backtrace:
       ▆
    1. └─surv_ranger_cox_optimizer$execute() at test-surv_ranger_cox.R:110:5
    2.   └─mlexperiments:::.run_cv(self = self, private = private)
    3.     └─mlexperiments:::.fold_looper(self, private)
    4.       ├─base::do.call(private$cv_run_model, run_args)
    5.       └─mlexperiments (local) `<fn>`(train_index = `<int>`, fold_train = `<list>`, fold_test = `<list>`)
    6.         ├─base::do.call(.cv_run_nested_model, args)
    7.         └─mlexperiments (local) `<fn>`(...)
    8.           └─hparam_tuner$execute(k = self$k_tuning)
    9.             └─private$select_optimizer(self, private)
   10.               └─BayesianOptimizer$new(...)
   11.                 └─mlexperiments (local) initialize(...)
  ── Error ('test-surv_rpart_cox.R:108:5'): test nested cv, bayesian - surv_rpart_cox ──
  Error: Package "ParBayesianOptimization" must be installed to use 'strategy = "bayesian"'.
  Backtrace:
       ▆
    1. └─surv_rpart_cox_optimizer$execute() at test-surv_rpart_cox.R:108:5
    2.   └─mlexperiments:::.run_cv(self = self, private = private)
    3.     └─mlexperiments:::.fold_looper(self, private)
    4.       ├─base::do.call(private$cv_run_model, run_args)
    5.       └─mlexperiments (local) `<fn>`(train_index = `<int>`, fold_train = `<list>`, fold_test = `<list>`)
    6.         ├─base::do.call(.cv_run_nested_model, args)
    7.         └─mlexperiments (local) `<fn>`(...)
    8.           └─hparam_tuner$execute(k = self$k_tuning)
    9.             └─private$select_optimizer(self, private)
   10.               └─BayesianOptimizer$new(...)
   11.                 └─mlexperiments (local) initialize(...)
  ── Error ('test-surv_xgboost_aft.R:121:3'): test nested cv, bayesian - surv_xgboost_aft ──
  Error: Package "ParBayesianOptimization" must be installed to use 'strategy = "bayesian"'.
  Backtrace:
       ▆
    1. └─surv_xgboost_aft_optimizer$execute() at test-surv_xgboost_aft.R:121:3
    2.   └─mlexperiments:::.run_cv(self = self, private = private)
    3.     └─mlexperiments:::.fold_looper(self, private)
    4.       ├─base::do.call(private$cv_run_model, run_args)
    5.       └─mlexperiments (local) `<fn>`(train_index = `<int>`, fold_train = `<list>`, fold_test = `<list>`)
    6.         ├─base::do.call(.cv_run_nested_model, args)
    7.         └─mlexperiments (local) `<fn>`(...)
    8.           └─hparam_tuner$execute(k = self$k_tuning)
    9.             └─private$select_optimizer(self, private)
   10.               └─BayesianOptimizer$new(...)
   11.                 └─mlexperiments (local) initialize(...)
  ── Error ('test-surv_xgboost_cox.R:118:3'): test nested cv, bayesian - surv_xgboost_cox ──
  Error: Package "ParBayesianOptimization" must be installed to use 'strategy = "bayesian"'.
  Backtrace:
       ▆
    1. └─surv_xgboost_cox_optimizer$execute() at test-surv_xgboost_cox.R:118:3
    2.   └─mlexperiments:::.run_cv(self = self, private = private)
    3.     └─mlexperiments:::.fold_looper(self, private)
    4.       ├─base::do.call(private$cv_run_model, run_args)
    5.       └─mlexperiments (local) `<fn>`(train_index = `<int>`, fold_train = `<list>`, fold_test = `<list>`)
    6.         ├─base::do.call(.cv_run_nested_model, args)
    7.         └─mlexperiments (local) `<fn>`(...)
    8.           └─hparam_tuner$execute(k = self$k_tuning)
    9.             └─private$select_optimizer(self, private)
   10.               └─BayesianOptimizer$new(...)
   11.                 └─mlexperiments (local) initialize(...)
  
  [ FAIL 5 | WARN 0 | SKIP 1 | PASS 9 ]
  Error:
  ! Test failures.
  Execution halted