Running ‘testthat.R’ [66s/82s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
  > library(testthat)
  > library(PLNmodels)
  This is packages 'PLNmodels' version 1.0.3
  Use future::plan(multicore/multisession) to speed up PLNPCA/PLNmixture/stability_selection.
  > 
  > test_check("PLNmodels")
  
   Initialization...
   Adjusting a full covariance PLN model with nlopt optimizer
   Post-treatments...
   DONE!
  
   Initialization...
   Adjusting a full covariance PLN model with nlopt optimizer
   Post-treatments...
   DONE!
  
   Initialization...
   Adjusting a full covariance PLN model with nlopt optimizer
   Post-treatments...
   DONE!
  
   Initialization...
   Adjusting a full covariance PLN model with nlopt optimizer
   Post-treatments...
   DONE!
  
   Initialization...
   Adjusting a full covariance PLN model with nlopt optimizer
   Post-treatments...
   DONE!
  
   Initialization...
   Adjusting a full covariance PLN model with nlopt optimizer
   Post-treatments...
   DONE!
  
   Initialization...
   Adjusting a full covariance PLN model with nlopt optimizer
   Post-treatments...
   DONE!
  
   Initialization...
   Adjusting a full covariance PLN model with nlopt optimizer
   Post-treatments...
   DONE!
  
   Initialization...
   Adjusting a full covariance PLN model with nlopt optimizer
   Post-treatments...
   DONE!
  
   Initialization...
   Adjusting a full covariance PLN model with nlopt optimizer
   Post-treatments...
   DONE!
  
   Initialization...
   Adjusting a full covariance PLN model with nlopt optimizer
   Post-treatments...
   DONE!
  
   Initialization...
   Adjusting a full covariance PLN model with nlopt optimizer
   Post-treatments...
   DONE!
  
   Initialization...
   Adjusting a full covariance PLN model with nlopt optimizer
   Post-treatments...
   DONE!
  
   Initialization...
   Adjusting a full covariance PLN model with nlopt optimizer
   Post-treatments...
   DONE!
  
   Initialization...
   Adjusting a full covariance PLN model with nlopt optimizer
   Post-treatments...
   DONE!
  
   Initialization...
   Adjusting a full covariance PLN model with nlopt optimizer
   Post-treatments...
   DONE!
  
   Initialization...
   Adjusting a full covariance PLN model with nlopt optimizer
   Post-treatments...
   DONE!
  
   Initialization...
   Adjusting a full covariance PLN model with nlopt optimizer
   Post-treatments...
   DONE!
  
   Initialization...
   Adjusting a full covariance PLN model with nlopt optimizer
   Post-treatments...
   DONE!
  
   Initialization...
   Adjusting a full covariance PLN model with nlopt optimizer
   Post-treatments...
   DONE!
  
   Initialization...
   Adjusting a spherical covariance PLN model with nlopt optimizer
   Post-treatments...
   DONE!
  
   Initialization...
   Adjusting a diagonal covariance PLN model with nlopt optimizer
   Post-treatments...
   DONE!
  
   Initialization...
   Adjusting a fixed covariance PLN model with nlopt optimizer
   Post-treatments...
   DONE!
  
   Performing discriminant Analysis...
   DONE!
  
   Performing discriminant Analysis...
   DONE!
  
   Initialization...
   Adjusting a full covariance PLN model with nlopt optimizer
   Post-treatments...
   DONE!
  
   Initialization...
   Adjusting a full covariance PLN model with nlopt optimizer
   Post-treatments...
   DONE!
  
   Initialization...
   Adjusting a full covariance PLN model with nlopt optimizer
   Post-treatments...
   DONE!
  
   Initialization...
   Adjusting a diagonal covariance PLN model with nlopt optimizer
   Post-treatments...
   DONE!
  
   Initialization...
   Adjusting a spherical covariance PLN model with nlopt optimizer
   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 3 PLN mixture models.
  	number of cluster = 1 
  	number of cluster = 2 
  	number of cluster = 3 
   Post-treatments
   DONE!
  
   Initialization...
  
   Adjusting 3 PLN mixture models.
  	number of cluster = 1 
  	number of cluster = 2 
  	number of cluster = 3 
   Post-treatments
   DONE!
  
   Initialization...
  
   Adjusting 3 PLN mixture models.
  	number of cluster = 1 
  	number of cluster = 2 
  	number of cluster = 3 
   Post-treatments
   DONE!
  
   Initialization...
  
   Adjusting 3 PLN mixture models.
  	number of cluster = 1 
  	number of cluster = 2 
  	number of cluster = 3 
   Post-treatments
   DONE!
  
   Initialization...
  
   Adjusting 3 PLN mixture models.
  	number of cluster = 1 
  	number of cluster = 2 
  	number of cluster = 3 
   Post-treatments
   DONE!
  
   Initialization...
  
   Adjusting 2 PLN mixture models.
  	number of cluster = 2 
  	number of cluster = 4 
  
   Smoothing PLN mixture models.
     Going backward +
                                                                                                      
     Going forward +
                                                                                                      
   Post-treatments
   DONE!
  
   Initialization...
  
   Adjusting 1 PLN mixture models.
  
   Initialization...
  
   Adjusting 3 PLN mixture models.
  	number of cluster = 1 
  	number of cluster = 2 
  	number of cluster = 3 
   Post-treatments
   DONE!
  
   Initialization...
  
   Adjusting 3 PLN mixture models.
  	number of cluster = 1 
  	number of cluster = 2 
  	number of cluster = 3 
   Post-treatments
   DONE!
  
   Initialization...
  
   Adjusting 3 PLN mixture models.
  	number of cluster = 1 
  	number of cluster = 2 
  	number of cluster = 3 
   Post-treatments
   DONE!
  
   Initialization...
   Adjusting 30 PLN with sparse inverse covariance estimation
  	Joint optimization alternating gradient descent and graphical-lasso
  	sparsifying penalty = 1.932536 
  	sparsifying penalty = 1.785027 
  	sparsifying penalty = 1.648777 
  	sparsifying penalty = 1.522928 
  	sparsifying penalty = 1.406684 
  	sparsifying penalty = 1.299313 
  	sparsifying penalty = 1.200137 
  	sparsifying penalty = 1.108532 
  	sparsifying penalty = 1.023919 
  	sparsifying penalty = 0.9457638 
  	sparsifying penalty = 0.8735745 
  	sparsifying penalty = 0.8068953 
  	sparsifying penalty = 0.7453057 
  	sparsifying penalty = 0.6884171 
  	sparsifying penalty = 0.6358708 
  	sparsifying penalty = 0.5873353 
  	sparsifying penalty = 0.5425045 
  	sparsifying penalty = 0.5010956 
  	sparsifying penalty = 0.4628474 
  	sparsifying penalty = 0.4275187 
  	sparsifying penalty = 0.3948866 
  	sparsifying penalty = 0.3647452 
  	sparsifying penalty = 0.3369045 
  	sparsifying penalty = 0.3111889 
  	sparsifying penalty = 0.2874361 
  	sparsifying penalty = 0.2654963 
  	sparsifying penalty = 0.2452312 
  	sparsifying penalty = 0.226513 
  	sparsifying penalty = 0.2092234 
  	sparsifying penalty = 0.1932536 
   Post-treatments
   DONE!
  
   *** caught segfault ***
  address 0x55f200000004, cause 'memory not mapped'
  Fatal error: *** recursive gc invocation
  
  Fatal error: *** recursive gc invocation