Running ‘testthat.R’ [103s/103s]
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 = 7.436075 
  	sparsifying penalty = 6.868485 
  	sparsifying penalty = 6.34422 
  	sparsifying penalty = 5.859971 
  	sparsifying penalty = 5.412684 
  	sparsifying penalty = 4.999539 
  	sparsifying penalty = 4.617928 
  	sparsifying penalty = 4.265446 
  	sparsifying penalty = 3.939868 
  	sparsifying penalty = 3.639141 
  	sparsifying penalty = 3.361369 
  	sparsifying penalty = 3.104798 
  	sparsifying penalty = 2.867812 
  	sparsifying penalty = 2.648914 
  	sparsifying penalty = 2.446725 
  	sparsifying penalty = 2.259968 
  	sparsifying penalty = 2.087467 
  	sparsifying penalty = 1.928132 
  	sparsifying penalty = 1.78096 
  	sparsifying penalty = 1.645021 
  	sparsifying penalty = 1.519458 
  	sparsifying penalty = 1.403479 
  	sparsifying penalty = 1.296352 
  	sparsifying penalty = 1.197403 
  	sparsifying penalty = 1.106006 
  	sparsifying penalty = 1.021586 
  	sparsifying penalty = 0.9436089 
  	sparsifying penalty = 0.871584 
  	sparsifying penalty = 0.8050567 
  	sparsifying penalty = 0.7436075 
   Post-treatments
   DONE!
  	sparsifying penalty = 7.436075 
  	sparsifying penalty = 6.868485 
  	sparsifying penalty = 6.34422 
  	sparsifying penalty = 5.859971 
  	sparsifying penalty = 5.412684 
  	sparsifying penalty = 4.999539 
  	sparsifying penalty = 4.617928 
  	sparsifying penalty = 4.265446 
  	sparsifying penalty = 3.939868 
  	sparsifying penalty = 3.639141 
  	sparsifying penalty = 3.361369 
  	sparsifying penalty = 3.104798 
  	sparsifying penalty = 2.867812 
  	sparsifying penalty = 2.648914 
  	sparsifying penalty = 2.446725 
  	sparsifying penalty = 2.259968 
  	sparsifying penalty = 2.087467 
  	sparsifying penalty = 1.928132 
  	sparsifying penalty = 1.78096 
  	sparsifying penalty = 1.645021 
  	sparsifying penalty = 1.519458 
  	sparsifying penalty = 1.403479 
  	sparsifying penalty = 1.296352 
  	sparsifying penalty = 1.197403 
  	sparsifying penalty = 1.106006 
  	sparsifying penalty = 1.021586 
  	sparsifying penalty = 0.9436089 
  	sparsifying penalty = 0.871584 
  	sparsifying penalty = 0.8050567 
  	sparsifying penalty = 0.7436075 
  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 = 7.436075 
  	sparsifying penalty = 6.868485 
  	sparsifying penalty = 6.34422 
  	sparsifying penalty = 5.859971 
  	sparsifying penalty = 5.412684 
  	sparsifying penalty = 4.999539 
  	sparsifying penalty = 4.617928 
  	sparsifying penalty = 4.265446 
  	sparsifying penalty = 3.939868 
  	sparsifying penalty = 3.639141 
  	sparsifying penalty = 3.361369 
  	sparsifying penalty = 3.104798 
  	sparsifying penalty = 2.867812 
  	sparsifying penalty = 2.648914 
  	sparsifying penalty = 2.446725 
  	sparsifying penalty = 2.259968 
  	sparsifying penalty = 2.087467 
  	sparsifying penalty = 1.928132 
  	sparsifying penalty = 1.78096 
  	sparsifying penalty = 1.645021 
  	sparsifying penalty = 1.519458 
  	sparsifying penalty = 1.403479 
  	sparsifying penalty = 1.296352 
  	sparsifying penalty = 1.197403 
  	sparsifying penalty = 1.106006 
  	sparsifying penalty = 1.021586 
  	sparsifying penalty = 0.9436089 
  	sparsifying penalty = 0.871584 
  	sparsifying penalty = 0.8050567 
  	sparsifying penalty = 0.7436075 
   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 = 7.436075 
  	sparsifying penalty = 6.868485 
  	sparsifying penalty = 6.34422 
  	sparsifying penalty = 5.859971 
  	sparsifying penalty = 5.412684 
  	sparsifying penalty = 4.999539 
  	sparsifying penalty = 4.617928 
  	sparsifying penalty = 4.265446 
  	sparsifying penalty = 3.939868 
  	sparsifying penalty = 3.639141 
  	sparsifying penalty = 3.361369 
  	sparsifying penalty = 3.104798 
  	sparsifying penalty = 2.867812 
  	sparsifying penalty = 2.648914 
  	sparsifying penalty = 2.446725 
  	sparsifying penalty = 2.259968 
  	sparsifying penalty = 2.087467 
  	sparsifying penalty = 1.928132 
  	sparsifying penalty = 1.78096 
  	sparsifying penalty = 1.645021 
  	sparsifying penalty = 1.519458 
  	sparsifying penalty = 1.403479 
  	sparsifying penalty = 1.296352 
  	sparsifying penalty = 1.197403 
  	sparsifying penalty = 1.106006 
  	sparsifying penalty = 1.021586 
  	sparsifying penalty = 0.9436089 
  	sparsifying penalty = 0.871584 
  	sparsifying penalty = 0.8050567 
  	sparsifying penalty = 0.7436075 
   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: 0.01707108')
  `expected` is a logical vector (TRUE)
  
  [ FAIL 1 | WARN 43 | SKIP 0 | PASS 670 ]
  Error: Test failures
  Execution halted