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 = 7.300281 
  	sparsifying penalty = 6.743056 
  	sparsifying penalty = 6.228365 
  	sparsifying penalty = 5.752959 
  	sparsifying penalty = 5.313841 
  	sparsifying penalty = 4.90824 
  	sparsifying penalty = 4.533598 
  	sparsifying penalty = 4.187552 
  	sparsifying penalty = 3.86792 
  	sparsifying penalty = 3.572685 
  	sparsifying penalty = 3.299985 
  	sparsifying penalty = 3.0481 
  	sparsifying penalty = 2.815441 
  	sparsifying penalty = 2.600541 
  	sparsifying penalty = 2.402044 
  	sparsifying penalty = 2.218698 
  	sparsifying penalty = 2.049347 
  	sparsifying penalty = 1.892922 
  	sparsifying penalty = 1.748437 
  	sparsifying penalty = 1.61498 
  	sparsifying penalty = 1.49171 
  	sparsifying penalty = 1.377849 
  	sparsifying penalty = 1.272679 
  	sparsifying penalty = 1.175536 
  	sparsifying penalty = 1.085809 
  	sparsifying penalty = 1.00293 
  	sparsifying penalty = 0.9263771 
  	sparsifying penalty = 0.8556676 
  	sparsifying penalty = 0.7903552 
  	sparsifying penalty = 0.7300281 
   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 = 7.300281 
  	sparsifying penalty = 6.743056 
  	sparsifying penalty = 6.228365 
  	sparsifying penalty = 5.752959 
  	sparsifying penalty = 5.313841 
  	sparsifying penalty = 4.90824 
  	sparsifying penalty = 4.533598 
  	sparsifying penalty = 4.187552 
  	sparsifying penalty = 3.86792 
  	sparsifying penalty = 3.572685 
  	sparsifying penalty = 3.299985 
  	sparsifying penalty = 3.0481 
  	sparsifying penalty = 2.815441 
  	sparsifying penalty = 2.600541 
  	sparsifying penalty = 2.402044 
  	sparsifying penalty = 2.218698 
  	sparsifying penalty = 2.049347 
  	sparsifying penalty = 1.892922 
  	sparsifying penalty = 1.748437 
  	sparsifying penalty = 1.61498 
  	sparsifying penalty = 1.49171 
  	sparsifying penalty = 1.377849 
  	sparsifying penalty = 1.272679 
  	sparsifying penalty = 1.175536 
  	sparsifying penalty = 1.085809 
  	sparsifying penalty = 1.00293 
  	sparsifying penalty = 0.9263771 
  	sparsifying penalty = 0.8556676 
  	sparsifying penalty = 0.7903552 
  	sparsifying penalty = 0.7300281 
   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