Running 'testthat.R' [63s/70s]
Running the tests in 'tests/testthat.R' failed.
Complete output:
  > library(testthat)
  > library(PLNmodels)
  > 
  > 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!
  -- 1. Failure: PLN fit: check classes, getters and field access (@test-plnfit.R#
  class(coef(model)) not equal to "matrix".
  Lengths differ: 2 is not 1
  
  -- 2. Failure: PLN fit: check classes, getters and field access (@test-plnfit.R#
  class(sigma(model)) not equal to "matrix".
  Lengths differ: 2 is not 1
  
  
   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!
  -- 3. Failure: PLNLDA fit: check classes, getters and field access (@test-plnlda
  class(model$group_means) not equal to "matrix".
  Lengths differ: 2 is not 1
  
  -- 4. Failure: PLNLDA fit: check classes, getters and field access (@test-plnlda
  class(sigma(model)) not equal to "matrix".
  Lengths differ: 2 is not 1
  
  
   Performing discriminant Analysis...
   DONE!
  
   Performing discriminant Analysis...
   DONE!
  
   Performing discriminant Analysis...
   DONE!
  
   Performing discriminant Analysis...
   DONE!
  
   Performing discriminant Analysis...
   DONE!
  
   Initialization...
   Adjusting 30 PLN with sparse inverse covariance estimation
  	Joint optimization alternating gradient descent and graphical-lasso
  	sparsifying penalty = 7.426214 
  	sparsifying penalty = 6.859378 
  	sparsifying penalty = 6.335807 
  	sparsifying penalty = 5.8522 
  	sparsifying penalty = 5.405507 
  	sparsifying penalty = 4.992909 
  	sparsifying penalty = 4.611805 
  	sparsifying penalty = 4.25979 
  	sparsifying penalty = 3.934644 
  	sparsifying penalty = 3.634316 
  	sparsifying penalty = 3.356911 
  	sparsifying penalty = 3.100681 
  	sparsifying penalty = 2.864009 
  	sparsifying penalty = 2.645402 
  	sparsifying penalty = 2.44348 
  	sparsifying penalty = 2.256972 
  	sparsifying penalty = 2.084699 
  	sparsifying penalty = 1.925576 
  	sparsifying penalty = 1.778598 
  	sparsifying penalty = 1.642839 
  	sparsifying penalty = 1.517443 
  	sparsifying penalty = 1.401618 
  	sparsifying penalty = 1.294633 
  	sparsifying penalty = 1.195815 
  	sparsifying penalty = 1.10454 
  	sparsifying penalty = 1.020231 
  	sparsifying penalty = 0.9423576 
  	sparsifying penalty = 0.8704283 
  	sparsifying penalty = 0.8039892 
  	sparsifying penalty = 0.7426214 
   Post-treatments
   DONE!
  	sparsifying penalty = 7.426214 
  	sparsifying penalty = 6.859378 
  	sparsifying penalty = 6.335807 
  	sparsifying penalty = 5.8522 
  	sparsifying penalty = 5.405507 
  	sparsifying penalty = 4.992909 
  	sparsifying penalty = 4.611805 
  	sparsifying penalty = 4.25979 
  	sparsifying penalty = 3.934644 
  	sparsifying penalty = 3.634316 
  	sparsifying penalty = 3.356911 
  	sparsifying penalty = 3.100681 
  	sparsifying penalty = 2.864009 
  	sparsifying penalty = 2.645402 
  	sparsifying penalty = 2.44348 
  	sparsifying penalty = 2.256972 
  	sparsifying penalty = 2.084699 
  	sparsifying penalty = 1.925576 
  	sparsifying penalty = 1.778598 
  	sparsifying penalty = 1.642839 
  	sparsifying penalty = 1.517443 
  	sparsifying penalty = 1.401618 
  	sparsifying penalty = 1.294633 
  	sparsifying penalty = 1.195815 
  	sparsifying penalty = 1.10454 
  	sparsifying penalty = 1.020231 
  	sparsifying penalty = 0.9423576 
  	sparsifying penalty = 0.8704283 
  	sparsifying penalty = 0.8039892 
  	sparsifying penalty = 0.7426214 
  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 = 7.426214 
  	sparsifying penalty = 6.859378 
  	sparsifying penalty = 6.335807 
  	sparsifying penalty = 5.8522 
  	sparsifying penalty = 5.405507 
  	sparsifying penalty = 4.992909 
  	sparsifying penalty = 4.611805 
  	sparsifying penalty = 4.25979 
  	sparsifying penalty = 3.934644 
  	sparsifying penalty = 3.634316 
  	sparsifying penalty = 3.356911 
  	sparsifying penalty = 3.100681 
  	sparsifying penalty = 2.864009 
  	sparsifying penalty = 2.645402 
  	sparsifying penalty = 2.44348 
  	sparsifying penalty = 2.256972 
  	sparsifying penalty = 2.084699 
  	sparsifying penalty = 1.925576 
  	sparsifying penalty = 1.778598 
  	sparsifying penalty = 1.642839 
  	sparsifying penalty = 1.517443 
  	sparsifying penalty = 1.401618 
  	sparsifying penalty = 1.294633 
  	sparsifying penalty = 1.195815 
  	sparsifying penalty = 1.10454 
  	sparsifying penalty = 1.020231 
  	sparsifying penalty = 0.9423576 
  	sparsifying penalty = 0.8704283 
  	sparsifying penalty = 0.8039892 
  	sparsifying penalty = 0.7426214 
   Post-treatments
   DONE!
  	 Rank approximation = 1 
  	 Rank approximation = 2 
  	 Rank approximation = 3 
  	 Rank approximation = 4 
  	 Rank approximation = 5 
   Initialization...
  
   Adjusting 5 PLN models for PCA analysis.
  	 Rank approximation = 1 
  	 Rank approximation = 2 
  	 Rank approximation = 3 
  	 Rank approximation = 4 
  	 Rank approximation = 5 
   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!
  == testthat results  ===========================================================
  [ OK: 319 | SKIPPED: 0 | WARNINGS: 4 | FAILED: 4 ]
  1. Failure: PLN fit: check classes, getters and field access (@test-plnfit.R#42) 
  2. Failure: PLN fit: check classes, getters and field access (@test-plnfit.R#43) 
  3. Failure: PLNLDA fit: check classes, getters and field access (@test-plnlda-fit.R#27) 
  4. Failure: PLNLDA fit: check classes, getters and field access (@test-plnlda-fit.R#28) 
  
  Error: testthat unit tests failed
  Execution halted