Running 'testthat.R' [41s]
Running the tests in 'tests/testthat.R' failed.
Complete output:
  > library(testthat)
  > library(DALEXtra)
  Loading required package: DALEX
  Welcome to DALEX (version: 1.0.1).
  Find examples and detailed introduction at: https://pbiecek.github.io/ema/
  Additional features will be available after installation of: iBreakDown, ggpubr.
  Use 'install_dependencies()' to get all suggested dependencies
  > 
  > test_check("DALEXtra")
  -- 1. Error: check group_variables function (@test_aspect_importance.R#201)  ---
  object 'tibble_update_attrs' not found
  Backtrace:
    1. DALEXtra::group_variables(...)
    3. ggplot2:::plot.ggplot(plot_group_variables(x_hc, p, draw_abline))
    5. ggplot2:::ggplot_build.ggplot(x)
    6. ggplot2:::by_layer(function(l, d) l$compute_aesthetics(d, plot))
    7. ggplot2:::f(l = layers[[i]], d = data[[i]])
    8. l$compute_aesthetics(d, plot)
    9. ggplot2:::f(..., self = self)
   10. ggplot2:::as_gg_data_frame(evaled)
   13. tibble:::as_tibble.list(x)
   14. tibble:::lst_to_tibble(x, .rows, .name_repair, col_lengths(x))
   15. tibble:::recycle_columns(x, .rows, lengths)
   16. tibble::new_tibble(x, nrow = nrow, subclass = NULL)
   17. tibble:::update_tibble_attrs(x, ...)
  
  -- 2. Error: check triplot function (@test_aspect_importance.R#290)  -----------
  object 'tibble_update_attrs' not found
  Backtrace:
    1. DALEXtra::triplot(...)
    2. DALEXtra:::triplot.default(...)
    4. gridExtra::grid.arrange(...)
    5. gridExtra::arrangeGrob(...)
    6. base::lapply(grobs[toconv], ggplot2::ggplotGrob)
    7. ggplot2:::FUN(X[[i]], ...)
   10. ggplot2:::ggplot_build.ggplot(x)
   11. layout$setup(data, plot$data, plot$plot_env)
   12. ggplot2:::f(..., self = self)
   13. self$facet$compute_layout(data, self$facet_params)
   14. ggplot2:::f(...)
   17. ggplot2::combine_vars(data, params$plot_env, vars, drop = params$drop)
   20. base::lapply(data, eval_facets, facets = vars, possible_columns = possible_columns)
   21. ggplot2:::FUN(X[[i]], ...)
   24. tibble:::as_tibble.list(vars)
   25. tibble:::lst_to_tibble(x, .rows, .name_repair, col_lengths(x))
   26. tibble:::recycle_columns(x, .rows, lengths)
   27. tibble::new_tibble(x, nrow = nrow, subclass = NULL)
   28. tibble:::update_tibble_attrs(x, ...)
  
  -- 3. Error: check triplot.explainer function (@test_aspect_importance.R#304)  -
  object 'tibble_update_attrs' not found
  Backtrace:
    1. DALEXtra::triplot(x = apartments_explainer, new_observation = apartments_num_new_observation)
    2. DALEXtra:::triplot.explainer(x = apartments_explainer, new_observation = apartments_num_new_observation)
    3. DALEXtra:::triplot.default(...)
    5. gridExtra::grid.arrange(...)
    6. gridExtra::arrangeGrob(...)
    7. base::lapply(grobs[toconv], ggplot2::ggplotGrob)
    8. ggplot2:::FUN(X[[i]], ...)
   11. ggplot2:::ggplot_build.ggplot(x)
   12. layout$setup(data, plot$data, plot$plot_env)
   13. ggplot2:::f(..., self = self)
   14. self$facet$compute_layout(data, self$facet_params)
   15. ggplot2:::f(...)
   18. ggplot2::combine_vars(data, params$plot_env, vars, drop = params$drop)
   21. base::lapply(data, eval_facets, facets = vars, possible_columns = possible_columns)
   22. ggplot2:::FUN(X[[i]], ...)
   25. tibble:::as_tibble.list(vars)
   26. tibble:::lst_to_tibble(x, .rows, .name_repair, col_lengths(x))
   27. tibble:::recycle_columns(x, .rows, lengths)
   28. tibble::new_tibble(x, nrow = nrow, subclass = NULL)
   29. tibble:::update_tibble_attrs(x, ...)
  
  Preparation of a new explainer is initiated
    -> model label       :  LM 
    -> data              :  9000  rows  6  cols 
    -> target variable   :  9000  values 
    -> data              :  A column identical to the target variable `y` has been found in the `data`.  ( [31m WARNING [39m )
    -> data              :  It is highly recommended to pass `data` without the target variable column
    -> model_info        :  package mlr , ver. 2.17.1 , task regression ( [33m default [39m ) 
    -> predict function  :  yhat.WrappedModel  will be used ( [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 
    -> data              :  A column identical to the target variable `y` has been found in the `data`.  ( [31m WARNING [39m )
    -> data              :  It is highly recommended to pass `data` without the target variable column
    -> model_info        :  package mlr , ver. 2.17.1 , task regression ( [33m default [39m ) 
    -> predict function  :  yhat.WrappedModel  will be used ( [33m default [39m )
    -> predicted values  :  numerical, min =  1971.308 , mean =  3507.76 , max =  5770.462  
    -> residual function :  difference between y and yhat ( [33m default [39m )
    -> residuals         :  numerical, min =  -708.3335 , mean =  3.763243 , max =  1285.827  
   [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 
    -> data              :  A column identical to the target variable `y` has been found in the `data`.  ( [31m WARNING [39m )
    -> data              :  It is highly recommended to pass `data` without the target variable column
    -> model_info        :  package mlr , ver. 2.17.1 , task regression ( [33m default [39m ) 
    -> predict function  :  yhat.WrappedModel  will be used ( [33m default [39m )
    -> predicted values  :  numerical, min =  2115.758 , mean =  3502.258 , max =  6055.129  
    -> residual function :  difference between y and yhat ( [33m default [39m )
    -> residuals         :  numerical, min =  -512.7577 , mean =  9.265594 , max =  778.5281  
   [32m A new explainer has been created! [39m 
  
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    |======================================================================| 100%additional arguments ignored in warning()
  Preparation of a new explainer is initiated
    -> model label       :  R6  ( [33m default [39m )
    -> data              :  2207  rows  8  cols 
    -> target variable   :  2207  values 
    -> data              :  A column identical to the target variable `y` has been found in the `data`.  ( [31m WARNING [39m )
    -> data              :  It is highly recommended to pass `data` without the target variable column
    -> model_info        :  package mlr3 , ver. 0.1.8 , task classification ( [33m default [39m ) 
    -> predict function  :  yhat.LearnerClassif  will be used ( [33m default [39m )
    -> predicted values  :  numerical, min =  0.05555556 , mean =  0.3221568 , max =  0.9267399  
    -> residual function :  difference between y and yhat ( [33m default [39m )
    -> residuals         :  numerical, min =  -0.9267399 , mean =  1.858834e-17 , max =  0.9444444  
   [32m A new explainer has been created! [39m 
  Preparation of a new explainer is initiated
    -> model label       :  R6  ( [33m default [39m )
    -> data              :  1000  rows  6  cols 
    -> target variable   :  1000  values 
    -> data              :  A column identical to the target variable `y` has been found in the `data`.  ( [31m WARNING [39m )
    -> data              :  It is highly recommended to pass `data` without the target variable column
    -> model_info        :  package mlr3 , ver. 0.1.8 , task regression ( [33m default [39m ) 
    -> predict function  :  yhat.LearnerRegr  will be used ( [33m default [39m )
    -> predicted values  :  numerical, min =  2289.664 , mean =  3487.019 , max =  5737.175  
    -> residual function :  difference between y and yhat ( [33m default [39m )
    -> residuals         :  numerical, min =  -1044.133 , mean =  4.321552e-14 , max =  1080.867  
   [32m A new explainer has been created! [39m 
  Preparation of a new explainer is initiated
    -> model label       :  WrappedModel  ( [33m default [39m )
    -> data              :  524  rows  17  cols 
    -> target variable   :  524  values 
    -> model_info        :  package mlr , ver. 2.17.1 , task classification ( [33m default [39m ) 
    -> predict function  :  yhat.WrappedModel  will be used ( [33m default [39m )
    -> predicted values  :  numerical, min =  0.4349866 , mean =  0.6677779 , max =  0.7299615  
    -> residual function :  difference between y and yhat ( [33m default [39m )
    -> residuals         :  numerical, min =  -0.7299615 , mean =  -0.3567092 , max =  0.5650134  
   [32m A new explainer has been created! [39m 
  Preparation of a new explainer is initiated
    -> model label       :  WrappedModel  ( [33m default [39m )
    -> data              :  524  rows  18  cols 
    -> target variable   :  524  values 
    -> data              :  A column identical to the target variable `y` has been found in the `data`.  ( [31m WARNING [39m )
    -> data              :  It is highly recommended to pass `data` without the target variable column
    -> model_info        :  package mlr , ver. 2.17.1 , task regression ( [33m default [39m ) 
    -> predict function  :  predict_function 
    -> predicted values  :  numerical, min =  12.77413 , mean =  18.00703 , max =  66.75339  
    -> residual function :  difference between y and yhat ( [33m default [39m )
    -> residuals         :  numerical, min =  -26.84399 , mean =  2.481275 , max =  458.6342  
   [32m A new explainer has been created! [39m 
  additional arguments ignored in warning()
  == testthat results  ===========================================================
  [ OK: 58 | SKIPPED: 11 | WARNINGS: 2 | FAILED: 3 ]
  1. Error: check group_variables function (@test_aspect_importance.R#201) 
  2. Error: check triplot function (@test_aspect_importance.R#290) 
  3. Error: check triplot.explainer function (@test_aspect_importance.R#304) 
  
  Error: testthat unit tests failed
  Execution halted