Running 'testthat.R' [54s]
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. Error: PLNfamily: main function, field access and methods (@test-plnfamily
  not a function
  1: expect_equal(models$getModel(0.1), model1) at testthat/test-plnfamily.R:46
  2: quasi_label(enquo(object), label, arg = "object")
  3: eval_bare(get_expr(quo), get_env(quo))
  4: models$getModel(0.1)
  5: self$models[[id]]$clone()
  6: copy_slice(old[[i]], new[[i]], old_new_enclosing_pairs[seq.int(i, length(old))], 
         (i == 1))
  7: makeActiveBinding(name, active_copies[[name]], new_slice$binding)
  
  
   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 30 PLN with sparse inverse covariance estimation
  	Joint optimization alternating gradient descent and graphical-lasso
  	sparsifying penalty = 7.308737 
  	sparsifying penalty = 6.750868 
  	sparsifying penalty = 6.23558 
  	sparsifying penalty = 5.759623 
  	sparsifying penalty = 5.319996 
  	sparsifying penalty = 4.913925 
  	sparsifying penalty = 4.53885 
  	sparsifying penalty = 4.192403 
  	sparsifying penalty = 3.872401 
  	sparsifying penalty = 3.576824 
  	sparsifying penalty = 3.303808 
  	sparsifying penalty = 3.051631 
  	sparsifying penalty = 2.818703 
  	sparsifying penalty = 2.603553 
  	sparsifying penalty = 2.404826 
  	sparsifying penalty = 2.221268 
  	sparsifying penalty = 2.051721 
  	sparsifying penalty = 1.895115 
  	sparsifying penalty = 1.750462 
  	sparsifying penalty = 1.616851 
  	sparsifying penalty = 1.493438 
  	sparsifying penalty = 1.379445 
  	sparsifying penalty = 1.274153 
  	sparsifying penalty = 1.176898 
  	sparsifying penalty = 1.087067 
  	sparsifying penalty = 1.004092 
  	sparsifying penalty = 0.9274503 
  	sparsifying penalty = 0.8566588 
  	sparsifying penalty = 0.7912708 
  	sparsifying penalty = 0.7308737 
   Post-treatments
   DONE!
  -- 2. Error: PLNnetwork: main function, fields access and methods (@test-plnnetw
  not a function
  1: expect_equal(getBestModel(models), getBestModel(models, "BIC")) at testthat/test-plnnetworkfamily.R:10
  2: quasi_label(enquo(object), label, arg = "object")
  3: eval_bare(get_expr(quo), get_env(quo))
  4: getBestModel(models)
  5: getBestModel.PLNnetworkfamily(models)
  6: Robject$getBestModel(match.arg(crit), stability)
  7: self$models[[id]]$clone()
  8: copy_slice(old[[i]], new[[i]], old_new_enclosing_pairs[seq.int(i, length(old))], 
         (i == 1))
  9: makeActiveBinding(name, active_copies[[name]], new_slice$binding)
  
  
  Stability Selection for PLNnetwork: 
  subsampling: +-- 3. Error: PLNnetwork computes the stability path only once. (@test-plnnetwork
  not a function
  1: stability_selection(models, subsamples = subs) at testthat/test-plnnetworkfamily.R:65
  2: Robject$stability_selection(subsamples, control, mc.cores)
  3: mclapply(subsamples, function(subsample) {
         cat("+")
         inception_ <- self$getModel(self$penalties[1])
         inception_$update(M = inception_$var_par$M[subsample, ], S = inception_$var_par$S[subsample, 
             ])
         ctrl_init <- PLN_param(list(), inception_$n, inception_$p, inception_$d)
         ctrl_init$trace <- 0
         ctrl_init$inception <- inception_
         myPLN <- PLNnetworkfamily$new(penalties = self$penalties, responses = self$responses[subsample, 
             , drop = FALSE], covariates = self$covariates[subsample, , drop = FALSE], 
             offsets = self$offsets[subsample, , drop = FALSE], model = private$model, 
             weights = self$weights[subsample], control = ctrl_init)
         ctrl_main <- PLNnetwork_param(control, inception_$n, inception_$p, inception_$d, 
             !all(self$weights == 1))
         ctrl_main$trace <- 0
         myPLN$optimize(ctrl_main)
         nets <- do.call(cbind, lapply(myPLN$models, function(model) {
             as.matrix(model$latent_network("support"))[upper.tri(diag(private$p))]
         }))
         nets
     }, mc.cores = mc.cores)
  4: lapply(X, FUN, ...)
  5: FUN(X[[i]], ...)
  6: self$getModel(self$penalties[1])
  7: self$models[[id]]$clone()
  8: copy_slice(old[[i]], new[[i]], old_new_enclosing_pairs[seq.int(i, length(old))], 
         (i == 1))
  9: makeActiveBinding(name, active_copies[[name]], new_slice$binding)
  
  
   Initialization...
   Adjusting 30 PLN with sparse inverse covariance estimation
  	Joint optimization alternating gradient descent and graphical-lasso
  	sparsifying penalty = 7.308737 
  	sparsifying penalty = 6.750868 
  	sparsifying penalty = 6.23558 
  	sparsifying penalty = 5.759623 
  	sparsifying penalty = 5.319996 
  	sparsifying penalty = 4.913925 
  	sparsifying penalty = 4.53885 
  	sparsifying penalty = 4.192403 
  	sparsifying penalty = 3.872401 
  	sparsifying penalty = 3.576824 
  	sparsifying penalty = 3.303808 
  	sparsifying penalty = 3.051631 
  	sparsifying penalty = 2.818703 
  	sparsifying penalty = 2.603553 
  	sparsifying penalty = 2.404826 
  	sparsifying penalty = 2.221268 
  	sparsifying penalty = 2.051721 
  	sparsifying penalty = 1.895115 
  	sparsifying penalty = 1.750462 
  	sparsifying penalty = 1.616851 
  	sparsifying penalty = 1.493438 
  	sparsifying penalty = 1.379445 
  	sparsifying penalty = 1.274153 
  	sparsifying penalty = 1.176898 
  	sparsifying penalty = 1.087067 
  	sparsifying penalty = 1.004092 
  	sparsifying penalty = 0.9274503 
  	sparsifying penalty = 0.8566588 
  	sparsifying penalty = 0.7912708 
  	sparsifying penalty = 0.7308737 
   Post-treatments
   DONE!
  -- 4. Error: PLNnetwork fit: check classes, getters and field access (@test-plnn
  not a function
  1: getBestModel(models) at testthat/test-plnnetworkfit.R:18
  2: getBestModel.PLNnetworkfamily(models)
  3: Robject$getBestModel(match.arg(crit), stability)
  4: self$models[[id]]$clone()
  5: copy_slice(old[[i]], new[[i]], old_new_enclosing_pairs[seq.int(i, length(old))], 
         (i == 1))
  6: makeActiveBinding(name, active_copies[[name]], new_slice$binding)
  
  	 Rank approximation = 1 
  	 Rank approximation = 2 
  	 Rank approximation = 3 
  	 Rank approximation = 4 
  	 Rank approximation = 5 
  -- 5. Error: PLNPCAfamily: main function, field access and methods (@test-plnpca
  not a function
  1: expect_is(plot(myPLN), "ggplot") at testthat/test-plnpcafamily.R:38
  2: quasi_label(enquo(object), label, arg = "object")
  3: eval_bare(get_expr(quo), get_env(quo))
  4: plot(myPLN)
  5: plot.PLNPCAfamily(myPLN)
  6: x$plot(criteria, annotate)
  7: sapply(intersect(criteria, c("BIC", "ICL")), function(crit) self$getBestModel(crit)$rank)
  8: lapply(X = X, FUN = FUN, ...)
  9: FUN(X[[i]], ...)
  10: self$getBestModel(crit)
  11: self$models[[id]]$clone()
  12: copy_slice(old[[i]], new[[i]], old_new_enclosing_pairs[seq.int(i, length(old))], 
         (i == 1))
  13: makeActiveBinding(name, active_copies[[name]], new_slice$binding)
  
  
   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!
  -- 6. Error: PLNPCA fit: check classes, getters and field access (@test-plnpcafi
  not a function
  1: getBestModel(models) at testthat/test-plnpcafit.R:15
  2: getBestModel.PLNPCAfamily(models)
  3: Robject$getBestModel(match.arg(crit))
  4: self$models[[id]]$clone()
  5: copy_slice(old[[i]], new[[i]], old_new_enclosing_pairs[seq.int(i, length(old))], 
         (i == 1))
  6: makeActiveBinding(name, active_copies[[name]], new_slice$binding)
  
  -- 7. Error: Louis-type Fisher matrices are not available for PLNPCA (@test-plnp
  not a function
  1: getBestModel(models) at testthat/test-plnpcafit.R:56
  2: getBestModel.PLNPCAfamily(models)
  3: Robject$getBestModel(match.arg(crit))
  4: self$models[[id]]$clone()
  5: copy_slice(old[[i]], new[[i]], old_new_enclosing_pairs[seq.int(i, length(old))], 
         (i == 1))
  6: makeActiveBinding(name, active_copies[[name]], new_slice$binding)
  
  -- 8. Error: plot_PCA works one axis only: (@test-plnpcafit.R#62)  -------------
  not a function
  1: getModel(models, 1) at testthat/test-plnpcafit.R:62
  2: getModel.PLNPCAfamily(models, 1)
  3: Robject$getModel(var, index)
  4: self$models[[id]]$clone()
  5: copy_slice(old[[i]], new[[i]], old_new_enclosing_pairs[seq.int(i, length(old))], 
         (i == 1))
  6: makeActiveBinding(name, active_copies[[name]], new_slice$binding)
  
  -- 9. Error: plot_PCA works for 4 or more axes: (@test-plnpcafit.R#68)  --------
  not a function
  1: getModel(models, 4) at testthat/test-plnpcafit.R:68
  2: getModel.PLNPCAfamily(models, 4)
  3: Robject$getModel(var, index)
  4: self$models[[id]]$clone()
  5: copy_slice(old[[i]], new[[i]], old_new_enclosing_pairs[seq.int(i, length(old))], 
         (i == 1))
  6: makeActiveBinding(name, active_copies[[name]], new_slice$binding)
  
  -- 10. Error: PLNPCA fit: check print message (@test-plnpcafit.R#74)  ----------
  not a function
  1: getBestModel(models) at testthat/test-plnpcafit.R:74
  2: getBestModel.PLNPCAfamily(models)
  3: Robject$getBestModel(match.arg(crit))
  4: self$models[[id]]$clone()
  5: copy_slice(old[[i]], new[[i]], old_new_enclosing_pairs[seq.int(i, length(old))], 
         (i == 1))
  6: makeActiveBinding(name, active_copies[[name]], new_slice$binding)
  
  
   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: 235 | SKIPPED: 0 | WARNINGS: 4 | FAILED: 10 ]
  1.  Error: PLNfamily: main function, field access and methods (@test-plnfamily.R#46) 
  2.  Error: PLNnetwork: main function, fields access and methods (@test-plnnetworkfamily.R#10) 
  3.  Error: PLNnetwork computes the stability path only once. (@test-plnnetworkfamily.R#65) 
  4.  Error: PLNnetwork fit: check classes, getters and field access (@test-plnnetworkfit.R#18) 
  5.  Error: PLNPCAfamily: main function, field access and methods (@test-plnpcafamily.R#38) 
  6.  Error: PLNPCA fit: check classes, getters and field access (@test-plnpcafit.R#15) 
  7.  Error: Louis-type Fisher matrices are not available for PLNPCA (@test-plnpcafit.R#56) 
  8.  Error: plot_PCA works one axis only: (@test-plnpcafit.R#62) 
  9.  Error: plot_PCA works for 4 or more axes: (@test-plnpcafit.R#68) 
  10. Error: PLNPCA fit: check print message (@test-plnpcafit.R#74) 
  
  Error: testthat unit tests failed
  Execution halted