Running 'testthat.R' [118s/134s]
Running the tests in 'tests/testthat.R' failed.
Complete output:
  > library(testthat)
  > library(PLNmodels)
  This is packages 'PLNmodels' version 0.11.4
  Use future::plan(multicore/multisession) to speed up PLNPCA/PLNmixture/stability_selection.
  > 
  > test_check("PLNmodels")
  
   Initialization...
   Adjusting a PLN model with full covariance model
   Post-treatments...
   DONE!
  
   Initialization...
   Adjusting a PLN model with full covariance model
   Post-treatments...
   DONE!
  
   Initialization...
   Adjusting a PLN model with full covariance model
   Post-treatments...
   DONE!
  
   Initialization...
   Adjusting a PLN model with full covariance model
   Post-treatments...
   DONE!
  
   Initialization...
   Adjusting a PLN model with full covariance model
   Post-treatments...
   DONE!
  
   Initialization...
   Adjusting a PLN model with full covariance model
   Post-treatments...
   DONE!
  
   Initialization...
   Adjusting a PLN model with full covariance model
   Post-treatments...
   DONE!
  
   Initialization...
   Adjusting a PLN model with full covariance model
   Post-treatments...
   DONE!
  
   Initialization...
   Adjusting a PLN model with full covariance model
   Post-treatments...
   DONE!
  
   Initialization...
   Adjusting a PLN model with full covariance model
   Post-treatments...
   DONE!
  
   Initialization...
   Adjusting a PLN model with full covariance model
   Post-treatments...
   DONE!
  
   Initialization...
   Adjusting a PLN model with full covariance model
   Post-treatments...
   DONE!
  
   Initialization...
   Adjusting a PLN model with full covariance model
   Post-treatments...
   DONE!
  
   Initialization...
   Adjusting a PLN model with full covariance model
   Post-treatments...
   DONE!
  
   Initialization...
   Adjusting a PLN model with full covariance model
   Post-treatments...
   DONE!
  
   Initialization...
   Adjusting a PLN model with full covariance model
   Post-treatments...
   DONE!
  
   Initialization...
   Adjusting a PLN model with full covariance model
   Post-treatments...
   DONE!
  
   Initialization...
   Adjusting a PLN model with full covariance model
   Post-treatments...
   DONE!
  
   Initialization...
   Adjusting a PLN model with full covariance model
   Post-treatments...
   DONE!
  
   Initialization...
   Adjusting a PLN model with diagonal covariance model
   Post-treatments...
   DONE!
  
   Initialization...
   Adjusting a PLN model with spherical covariance model
   Post-treatments...
   DONE!
  
   Performing discriminant Analysis...
   DONE!
  
   Performing discriminant Analysis...
   DONE!
  
   Performing discriminant Analysis...
   DONE!
  
   Performing discriminant Analysis...
   DONE!
  
   Performing discriminant Analysis...
   DONE!
  
   Performing discriminant Analysis...
   DONE!
  
   Performing discriminant Analysis...
   DONE!
  
   Initialization...
  
   Adjusting 5 PLN mixture models.
  	number of cluster = 1 
  	number of cluster = 2 
  	number of cluster = 3 
  	number of cluster = 4 
  	number of cluster = 5 
  
   Smoothing PLN mixture models.
  
   Post-treatments
   DONE!
  
   Initialization...
  
   Adjusting 5 PLN mixture models.
  	number of cluster = 1 
  	number of cluster = 2 
  	number of cluster = 3 
  	number of cluster = 4 
  	number of cluster = 5 
  
   Smoothing PLN mixture models.
  
   Post-treatments
   DONE!
  
   Initialization...
  
   Adjusting 5 PLN mixture models.
  	number of cluster = 1 
  	number of cluster = 2 
  	number of cluster = 3 
  	number of cluster = 4 
  	number of cluster = 5 
  
   Smoothing PLN mixture models.
     Going backward ++++
                                                                                                      
     Going forward ++++
                                                                                                      
     Going backward ++++
                                                                                                      
     Going forward ++++
                                                                                                      
   Post-treatments
   DONE!
  
   Initialization...
  
   Adjusting 5 PLN mixture models.
  	number of cluster = 1 
  	number of cluster = 2 
  	number of cluster = 3 
  	number of cluster = 4 
  	number of cluster = 5 
  
   Smoothing PLN mixture models.
  
   Post-treatments
   DONE!
  
   Initialization...
  
   Adjusting 5 PLN mixture models.
  	number of cluster = 1 
  	number of cluster = 2 
  	number of cluster = 3 
  	number of cluster = 4 
  	number of cluster = 5 
  
   Smoothing PLN mixture models.
  
   Post-treatments
   DONE!
  
   Initialization...
  
   Adjusting 1 PLN mixture models.
  
   Initialization...
  
   Adjusting 5 PLN mixture models.
  	number of cluster = 1 
  	number of cluster = 2 
  	number of cluster = 3 
  	number of cluster = 4 
  	number of cluster = 5 
  
   Smoothing PLN mixture models.
     Going backward ++++
                                                                                                      
     Going forward ++++
                                                                                                      
   Post-treatments
   DONE!
  
   Initialization...
  
   Adjusting 5 PLN mixture models.
  	number of cluster = 1 
  	number of cluster = 2 
  	number of cluster = 3 
  	number of cluster = 4 
  	number of cluster = 5 
  
   Smoothing PLN mixture models.
  
   Post-treatments
   DONE!
  
   Initialization...
  
   Adjusting 5 PLN mixture models.
  	number of cluster = 1 
  	number of cluster = 2 
  	number of cluster = 3 
  	number of cluster = 4 
  	number of cluster = 5 
  
   Smoothing PLN mixture models.
  
   Post-treatments
   DONE!
  
   Initialization...
   Adjusting 30 PLN with sparse inverse covariance estimation
  	Joint optimization alternating gradient descent and graphical-lasso
  	sparsifying penalty = 6.816502 
  	sparsifying penalty = 6.296205 
  	sparsifying penalty = 5.815621 
  	sparsifying penalty = 5.371719 
  	sparsifying penalty = 4.961701 
  	sparsifying penalty = 4.582978 
  	sparsifying penalty = 4.233164 
  	sparsifying penalty = 3.91005 
  	sparsifying penalty = 3.611599 
  	sparsifying penalty = 3.335929 
  	sparsifying penalty = 3.0813 
  	sparsifying penalty = 2.846107 
  	sparsifying penalty = 2.628866 
  	sparsifying penalty = 2.428207 
  	sparsifying penalty = 2.242864 
  	sparsifying penalty = 2.071668 
  	sparsifying penalty = 1.91354 
  	sparsifying penalty = 1.767481 
  	sparsifying penalty = 1.63257 
  	sparsifying penalty = 1.507958 
  	sparsifying penalty = 1.392857 
  	sparsifying penalty = 1.286541 
  	sparsifying penalty = 1.188341 
  	sparsifying penalty = 1.097636 
  	sparsifying penalty = 1.013854 
  	sparsifying penalty = 0.9364673 
  	sparsifying penalty = 0.8649876 
  	sparsifying penalty = 0.7989638 
  	sparsifying penalty = 0.7379796 
  	sparsifying penalty = 0.6816502 
   Post-treatments
   DONE!
  	sparsifying penalty = 6.816502 
  	sparsifying penalty = 6.296205 
  	sparsifying penalty = 5.815621 
  	sparsifying penalty = 5.371719 
  	sparsifying penalty = 4.961701 
  	sparsifying penalty = 4.582978 
  	sparsifying penalty = 4.233164 
  	sparsifying penalty = 3.91005 
  	sparsifying penalty = 3.611599 
  	sparsifying penalty = 3.335929 
  	sparsifying penalty = 3.0813 
  	sparsifying penalty = 2.846107 
  	sparsifying penalty = 2.628866 
  	sparsifying penalty = 2.428207 
  	sparsifying penalty = 2.242864 
  	sparsifying penalty = 2.071668 
  	sparsifying penalty = 1.91354 
  	sparsifying penalty = 1.767481 
  	sparsifying penalty = 1.63257 
  	sparsifying penalty = 1.507958 
  	sparsifying penalty = 1.392857 
  	sparsifying penalty = 1.286541 
  	sparsifying penalty = 1.188341 
  	sparsifying penalty = 1.097636 
  	sparsifying penalty = 1.013854 
  	sparsifying penalty = 0.9364673 
  	sparsifying penalty = 0.8649876 
  	sparsifying penalty = 0.7989638 
  	sparsifying penalty = 0.7379796 
  	sparsifying penalty = 0.6816502 
  Stability Selection for PLNnetwork: 
  subsampling: ++
  Stability Selection for PLNnetwork: 
  subsampling: ++
   Initialization...
   Adjusting 30 PLN with sparse inverse covariance estimation
  	Joint optimization alternating gradient descent and graphical-lasso
  	sparsifying penalty = 6.816502 
  	sparsifying penalty = 6.296205 
  	sparsifying penalty = 5.815621 
  	sparsifying penalty = 5.371719 
  	sparsifying penalty = 4.961701 
  	sparsifying penalty = 4.582978 
  	sparsifying penalty = 4.233164 
  	sparsifying penalty = 3.91005 
  	sparsifying penalty = 3.611599 
  	sparsifying penalty = 3.335929 
  	sparsifying penalty = 3.0813 
  	sparsifying penalty = 2.846107 
  	sparsifying penalty = 2.628866 
  	sparsifying penalty = 2.428207 
  	sparsifying penalty = 2.242864 
  	sparsifying penalty = 2.071668 
  	sparsifying penalty = 1.91354 
  	sparsifying penalty = 1.767481 
  	sparsifying penalty = 1.63257 
  	sparsifying penalty = 1.507958 
  	sparsifying penalty = 1.392857 
  	sparsifying penalty = 1.286541 
  	sparsifying penalty = 1.188341 
  	sparsifying penalty = 1.097636 
  	sparsifying penalty = 1.013854 
  	sparsifying penalty = 0.9364673 
  	sparsifying penalty = 0.8649876 
  	sparsifying penalty = 0.7989638 
  	sparsifying penalty = 0.7379796 
  	sparsifying penalty = 0.6816502 
   Post-treatments
   DONE!
  
  Stability Selection for PLNnetwork: 
  subsampling: ++
   Initialization...
   Adjusting 30 PLN with sparse inverse covariance estimation
  	Joint optimization alternating gradient descent and graphical-lasso
  	sparsifying penalty = 6.816502 
  	sparsifying penalty = 6.296205 
  	sparsifying penalty = 5.815621 
  	sparsifying penalty = 5.371719 
  	sparsifying penalty = 4.961701 
  	sparsifying penalty = 4.582978 
  	sparsifying penalty = 4.233164 
  	sparsifying penalty = 3.91005 
  	sparsifying penalty = 3.611599 
  	sparsifying penalty = 3.335929 
  	sparsifying penalty = 3.0813 
  	sparsifying penalty = 2.846107 
  	sparsifying penalty = 2.628866 
  	sparsifying penalty = 2.428207 
  	sparsifying penalty = 2.242864 
  	sparsifying penalty = 2.071668 
  	sparsifying penalty = 1.91354 
  	sparsifying penalty = 1.767481 
  	sparsifying penalty = 1.63257 
  	sparsifying penalty = 1.507958 
  	sparsifying penalty = 1.392857 
  	sparsifying penalty = 1.286541 
  	sparsifying penalty = 1.188341 
  	sparsifying penalty = 1.097636 
  	sparsifying penalty = 1.013854 
  	sparsifying penalty = 0.9364673 
  	sparsifying penalty = 0.8649876 
  	sparsifying penalty = 0.7989638 
  	sparsifying penalty = 0.7379796 
  	sparsifying penalty = 0.6816502 
   Post-treatments
   DONE!
  	 Rank approximation = 1 
  	 Rank approximation = 5 
  	 Rank approximation = 2 
  	 Rank approximation = 3 
  	 Rank approximation = 4 
   Initialization...
  
   Adjusting 5 PLN models for PCA analysis.
  	 Rank approximation = 2 
  	 Rank approximation = 5 
  	 Rank approximation = 1 
  	 Rank approximation = 3 
  	 Rank approximation = 4 
   Post-treatments
   DONE!
  
   Initialization...
   Adjusting a PLN model with full covariance model
   Post-treatments...
   DONE!
  
   Initialization...
   Adjusting a PLN model with full covariance model
   Post-treatments...
   DONE!
  == Failed tests ================================================================
  -- Failure (test-pln.R:174:3): PLN: Check that all univariate PLN models are equivalent with the multivariate diagonal case --
  all.equal(...) is not TRUE
  
  `actual` is a character vector ('Mean scaled difference: 0.04463325')
  `expected` is a logical vector (TRUE)
  
  [ FAIL 1 | WARN 43 | SKIP 0 | PASS 670 ]
  Error: Test failures
  Execution halted