Running ‘testthat.R’ [194s/349s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
  > library(testthat)
  > library(DALEXtra)
  Loading required package: DALEX
  Welcome to DALEX (version: 2.4.3).
  Find examples and detailed introduction at: http://ema.drwhy.ai/
  Additional features will be available after installation of: ggpubr.
  Use 'install_dependencies()' to get all suggested dependencies
  Anaconda not found on your computer. Conda related functionality such as create_env.R and condaenv and yml parameters from explain_scikitlearn will not be available
  > 
  > test_check("DALEXtra")
  Preparation of a new explainer is initiated
    -> model label       :  LM 
    -> data              :  9000  rows  6  cols 
    -> target variable   :  9000  values 
    -> predict function  :  yhat.WrappedModel  will be used ( [33m default [39m )
    -> predicted values  :  No value for predict function target column. ( [33m default [39m )
    -> model_info        :  package mlr , ver. 2.19.1 , task regression ( [33m default [39m ) 
    -> predicted values  :  numerical, min =  1792.597 , mean =  3506.836 , max =  6241.447  
    -> residual function :  difference between y and yhat ( [33m default [39m )
    -> residuals         :  numerical, min =  -257.2555 , mean =  4.687686 , max =  472.356  
   [32m A new explainer has been created! [39m 
  Preparation of a new explainer is initiated
    -> model label       :  RF 
    -> data              :  9000  rows  6  cols 
    -> target variable   :  9000  values 
    -> predict function  :  yhat.WrappedModel  will be used ( [33m default [39m )
    -> predicted values  :  No value for predict function target column. ( [33m default [39m )
    -> model_info        :  package mlr , ver. 2.19.1 , task regression ( [33m default [39m ) 
    -> predicted values  :  numerical, min =  1804.679 , mean =  3505.914 , max =  6249.184  
    -> residual function :  difference between y and yhat ( [33m default [39m )
    -> residuals         :  numerical, min =  -541.2998 , mean =  5.609991 , max =  741.9926  
   [32m A new explainer has been created! [39m 
  Preparation of a new explainer is initiated
    -> model label       :  GBM 
    -> data              :  9000  rows  6  cols 
    -> target variable   :  9000  values 
    -> predict function  :  yhat.WrappedModel  will be used ( [33m default [39m )
    -> predicted values  :  No value for predict function target column. ( [33m default [39m )
    -> model_info        :  package mlr , ver. 2.19.1 , task regression ( [33m default [39m ) 
    -> predicted values  :  numerical, min =  2109.59 , mean =  3504.267 , max =  6056.167  
    -> residual function :  difference between y and yhat ( [33m default [39m )
    -> residuals         :  numerical, min =  -506.59 , mean =  7.256323 , max =  708.7289  
   [32m A new explainer has been created! [39m 
  additional arguments ignored in warning()
  Preparation of a new explainer is initiated
    -> model label       :  ranger  ( [33m default [39m )
    -> data              :  2207  rows  7  cols 
    -> target variable   :  2207  values 
    -> predict function  :  yhat.ranger  will be used ( [33m default [39m )
    -> predicted values  :  No value for predict function target column. ( [33m default [39m )
    -> model_info        :  package ranger , ver. 0.14.1 , task classification ( [33m default [39m ) 
    -> predicted values  :  numerical, min =  0.01625191 , mean =  0.3222765 , max =  0.9907797  
    -> residual function :  difference between y and yhat ( [33m default [39m )
    -> residuals         :  numerical, min =  -0.780852 , mean =  -0.0001197473 , max =  0.8867573  
   [32m A new explainer has been created! [39m 
  additional arguments ignored in warning()
  [15:36:50] WARNING: src/learner.cc:767: 
  Parameters: { "prediction" } are not used.
  
  [15:36:53] WARNING: src/learner.cc:767: 
  Parameters: { "prediction" } are not used.
  
  [15:36:55] WARNING: src/learner.cc:767: 
  Parameters: { "prediction" } are not used.
  
  [ FAIL 3 | WARN 8 | SKIP 11 | PASS 51 ]
  
  ══ Skipped tests ═══════════════════════════════════════════════════════════════
  • Conda test env needed for tests (6)
  • JAVA entry needed for tests (4)
  • Test with windows (1)
  
  ══ Failed tests ════════════════════════════════════════════════════════════════
  ── Error ('test_predict_surrogate.R:39:3'): normal case ────────────────────────
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. ├─testthat::expect_is(plot(lime_johnny_d), "ggplot") at test_predict_surrogate.R:39:2
    2. │ └─testthat::quasi_label(enquo(object), label, arg = "object")
    3. │   └─rlang::eval_bare(expr, quo_get_env(quo))
    4. ├─base::plot(lime_johnny_d)
    5. └─DALEXtra:::plot.predict_surrogate_lime(lime_johnny_d)
    6.   └─lime::plot_features(x, ...)
    7.     ├─base::`[<-`(`*tmp*`, !binned_feature, "feature_weight", value = `<dbl>`)
    8.     └─tibble:::`[<-.tbl_df`(...)
    9.       └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
   10.         └─tibble:::tbl_subassign_row(xj, i, value, i_arg, value_arg, call)
   11.           ├─base::withCallingHandlers(...)
   12.           └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test_predict_surrogate.R:44:3'): faulty case ────────────────────────
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. ├─testthat::expect_is(plot(lime_johnny_d_faulty), "ggplot") at test_predict_surrogate.R:44:2
    2. │ └─testthat::quasi_label(enquo(object), label, arg = "object")
    3. │   └─rlang::eval_bare(expr, quo_get_env(quo))
    4. ├─base::plot(lime_johnny_d_faulty)
    5. └─DALEXtra:::plot.predict_surrogate_lime(lime_johnny_d_faulty)
    6.   └─lime::plot_features(x, ...)
    7.     ├─base::`[<-`(`*tmp*`, !binned_feature, "feature_weight", value = `<dbl>`)
    8.     └─tibble:::`[<-.tbl_df`(...)
    9.       └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
   10.         └─tibble:::tbl_subassign_row(xj, i, value, i_arg, value_arg, call)
   11.           ├─base::withCallingHandlers(...)
   12.           └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test_tidymodels_explain.R:54:1'): (code run outside of `test_that()`) ──
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. ├─stacks::blend_predictions(...) at test_tidymodels_explain.R:54:0
    2. │ └─preds_wf %>% ...
    3. ├─tune::tune_grid(...)
    4. ├─tune:::tune_grid.workflow(...)
    5. │ └─tune:::tune_grid_workflow(...)
    6. │   └─tune::check_parameters(...)
    7. │     ├─hardhat::extract_parameter_set_dials(wflow)
    8. │     └─workflows:::extract_parameter_set_dials.workflow(wflow)
    9. │       ├─hardhat::extract_parameter_set_dials(model)
   10. │       └─parsnip:::extract_parameter_set_dials.model_spec(model)
   11. │         ├─generics::tunable(x)
   12. │         ├─parsnip:::tunable.logistic_reg(x)
   13. │         ├─base::NextMethod()
   14. │         └─parsnip:::tunable.model_spec(x)
   15. │           └─... %>% ...
   16. ├─dplyr::mutate(...)
   17. ├─dplyr::full_join(...)
   18. └─dplyr:::full_join.data.frame(...)
   19.   └─dplyr:::join_mutate(...)
   20.     ├─base::`[<-`(`*tmp*`, new_rows, merge, value = `<tibble[,1]>`)
   21.     └─tibble:::`[<-.tbl_df`(`*tmp*`, new_rows, merge, value = `<tibble[,1]>`)
   22.       └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
   23.         └─tibble:::tbl_subassign_row(xj, i, value, i_arg, value_arg, call)
   24.           ├─base::withCallingHandlers(...)
   25.           └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  
  [ FAIL 3 | WARN 8 | SKIP 11 | PASS 51 ]
  Error: Test failures
  Execution halted