Running ‘testthat.R’ [44s/66s]
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 = 7.326806 
  	sparsifying penalty = 6.767557 
  	sparsifying penalty = 6.250995 
  	sparsifying penalty = 5.773862 
  	sparsifying penalty = 5.333148 
  	sparsifying penalty = 4.926073 
  	sparsifying penalty = 4.55007 
  	sparsifying penalty = 4.202767 
  	sparsifying penalty = 3.881974 
  	sparsifying penalty = 3.585666 
  	sparsifying penalty = 3.311975 
  	sparsifying penalty = 3.059175 
  	sparsifying penalty = 2.825671 
  	sparsifying penalty = 2.60999 
  	sparsifying penalty = 2.410771 
  	sparsifying penalty = 2.226759 
  	sparsifying penalty = 2.056793 
  	sparsifying penalty = 1.899799 
  	sparsifying penalty = 1.754789 
  	sparsifying penalty = 1.620848 
  	sparsifying penalty = 1.49713 
  	sparsifying penalty = 1.382855 
  	sparsifying penalty = 1.277303 
  	sparsifying penalty = 1.179808 
  	sparsifying penalty = 1.089754 
  	sparsifying penalty = 1.006574 
  	sparsifying penalty = 0.929743 
  	sparsifying penalty = 0.8587766 
  	sparsifying penalty = 0.7932269 
  	sparsifying penalty = 0.7326806 
   Post-treatments
   DONE!
  	sparsifying penalty = 7.326806 
  	sparsifying penalty = 6.767557 
  	sparsifying penalty = 6.250995 
  	sparsifying penalty = 5.773862 
  	sparsifying penalty = 5.333148 
  	sparsifying penalty = 4.926073 
  	sparsifying penalty = 4.55007 
  	sparsifying penalty = 4.202767 
  	sparsifying penalty = 3.881974 
  	sparsifying penalty = 3.585666 
  	sparsifying penalty = 3.311975 
  	sparsifying penalty = 3.059175 
  	sparsifying penalty = 2.825671 
  	sparsifying penalty = 2.60999 
  	sparsifying penalty = 2.410771 
  	sparsifying penalty = 2.226759 
  	sparsifying penalty = 2.056793 
  	sparsifying penalty = 1.899799 
  	sparsifying penalty = 1.754789 
  	sparsifying penalty = 1.620848 
  	sparsifying penalty = 1.49713 
  	sparsifying penalty = 1.382855 
  	sparsifying penalty = 1.277303 
  	sparsifying penalty = 1.179808 
  	sparsifying penalty = 1.089754 
  	sparsifying penalty = 1.006574 
  	sparsifying penalty = 0.929743 
  	sparsifying penalty = 0.8587766 
  	sparsifying penalty = 0.7932269 
  	sparsifying penalty = 0.7326806 
  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 = 7.326806 
  	sparsifying penalty = 6.767557 
  	sparsifying penalty = 6.250995 
  	sparsifying penalty = 5.773862 
  	sparsifying penalty = 5.333148 
  	sparsifying penalty = 4.926073 
  	sparsifying penalty = 4.55007 
  	sparsifying penalty = 4.202767 
  	sparsifying penalty = 3.881974 
  	sparsifying penalty = 3.585666 
  	sparsifying penalty = 3.311975 
  	sparsifying penalty = 3.059175 
  	sparsifying penalty = 2.825671 
  	sparsifying penalty = 2.60999 
  	sparsifying penalty = 2.410771 
  	sparsifying penalty = 2.226759 
  	sparsifying penalty = 2.056793 
  	sparsifying penalty = 1.899799 
  	sparsifying penalty = 1.754789 
  	sparsifying penalty = 1.620848 
  	sparsifying penalty = 1.49713 
  	sparsifying penalty = 1.382855 
  	sparsifying penalty = 1.277303 
  	sparsifying penalty = 1.179808 
  	sparsifying penalty = 1.089754 
  	sparsifying penalty = 1.006574 
  	sparsifying penalty = 0.929743 
  	sparsifying penalty = 0.8587766 
  	sparsifying penalty = 0.7932269 
  	sparsifying penalty = 0.7326806 
   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: 6 | 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