Running ‘testthat.R’ [29s/40s]
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 = 7.326806 
  	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!
  ── 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$p))]
         }))
         nets
     }, mc.cores = mc.cores)
  4: lapply(X = X, FUN = FUN, ...)
  5: FUN(X[[i]], ...)
  6: self$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 = 7.326806 
  	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!
  ── 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