Running ‘spelling.R’ [0s/1s]
  Running ‘testthat.R’ [125s/151s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
  > library(testthat)
  > library(missSBM)
  > 
  > test_check("missSBM")
  
   Adjusting Variational EM for Stochastic Block Model
  
  	Dyads are distributed according to a 'undirected' SBM.
  
  	Imputation assumes a 'covar-dyad' network-sampling process
   iteration #: 2 
   iteration #: 3 
  
   Adjusting Variational EM for Stochastic Block Model
  
  	Dyads are distributed according to a 'undirected' SBM.
  
  	Imputation assumes a 'dyad' network-sampling process
   iteration #: 2 
   iteration #: 3 
  
   Adjusting Variational EM for Stochastic Block Model
  
  	Dyads are distributed according to a 'undirected' SBM.
  
  	Imputation assumes a 'covar-node' network-sampling process
   iteration #: 2 
   iteration #: 3 
   iteration #: 4 
   iteration #: 5 
  
   Adjusting Variational EM for Stochastic Block Model
  
  	Dyads are distributed according to a 'undirected' SBM.
  
  	Imputation assumes a 'node' network-sampling process
   iteration #: 2 
   iteration #: 3 
   iteration #: 4 
   iteration #: 5 
  Tested sampling:
   - dyad
   - node
   - double-standard
   - block-node
   - block-dyad
  
   Adjusting Variational EM for Stochastic Block Model
  
  	Imputation assumes a 'dyad' network-sampling process
  
   Initialization of 3 model(s). 
  Tested sampling:
   - dyad
   - node
   - double-standard
   - block-node
   - block-dyadTested sampling:
   - dyad
   - node
   - double-standard
   - block-node
   - block-dyad
  sampling: dyad new better on connectivity
  node new better on mixture new better on connectivity
  double-standard new better on mixture
  block-node
  
   Adjusting Variational EM for Stochastic Block Model
   iteration #: 2 
  
   Adjusting Variational EM for Stochastic Block Model
  
  	Dyads are distributed according to a 'undirected' SBM.
  
  	Imputation assumes a 'node' network-sampling process
   iteration #: 2 
  
  
   Adjusting Variational EM for Stochastic Block Model
  
  	Imputation assumes a 'node' network-sampling process
  
   Initialization of 1 model(s). 
   Performing VEM inference
   	Model with 3 blocks.
  
  
  
  
  
  
  
  
  
  
  
  
  
  
   Adjusting Variational EM for Stochastic Block Model
   iteration #: 2 
   iteration #: 3 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  ══ Failed tests ════════════════════════════════════════════════════════════════
  ── Failure (test-MISSSBM-fit-with-covariates.R:124:3): miss SBM with covariates and node sampling works ──
  aricode::ARI(missSBM$fittedSBM$memberships, sampler_undirected_cov_node$memberships) is not strictly more than `tol_ARI`. Difference: -0.334
  ── Failure (test-MISSSBM-fit-with-covariates.R:147:3): miss SBM with covariates and node sampling works ──
  error(...) is not strictly less than `tol_truth`. Difference: 0.147
  ── Failure (test-MISSSBM-fit-with-covariates.R:154:3): miss SBM with covariates and node sampling works ──
  aricode::ARI(missSBM$fittedSBM$memberships, sampler_undirected_cov_node$memberships) is not strictly more than `tol_ARI`. Difference: -0.16
  
  [ FAIL 3 | WARN 1 | SKIP 0 | PASS 435 ]
  Error: Test failures
  Execution halted