Running ‘spelling.R’
  Running ‘testthat.R’ [163s/329s]
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 
  
   Adjusting Variational EM for Stochastic Block Model
  
  	Dyads are distributed according to a 'undirected' SBM.
  
  	Imputation assumes a 'dyad' network-sampling process
   iteration #: 2 
  
   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 
  
   Adjusting Variational EM for Stochastic Block Model
  
  	Dyads are distributed according to a 'undirected' SBM.
  
  	Imputation assumes a 'node' network-sampling process
   iteration #: 2 
  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
  double-standard
  block-node new better on mixture
   new better on mixture
   Adjusting Variational EM for Stochastic Block Model
   iteration #: 2 
   iteration #: 3 
   iteration #: 4 
   iteration #: 5 
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   iteration #: 27 
   iteration #: 28 
  
   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 
   iteration #: 6 
   iteration #: 7 
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   iteration #: 28 
  
  
   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 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  [ FAIL 17 | WARN 1 | SKIP 0 | PASS 372 ]
  
  ══ Failed tests ════════════════════════════════════════════════════════════════
  ── Failure ('test-TOP-LEVEL-consistency.R:121:5'): check consistency against Tim's code for dyad sampling with covariates ──
  `ARI_new` is not strictly more than `tol_ARI`. Difference: -0.5
  ── Failure ('test-TOP-LEVEL-consistency.R:123:5'): check consistency against Tim's code for dyad sampling with covariates ──
  `ARI_gap` is not strictly more than `tol_ARI`. Difference: -0.5
  ── Failure ('test-sbm-MAR_bernoulli-with-covariates.R:23:3'): SimpleSBM_fit 'Bernoulli' model, undirected, one covariate, dyad sampling, MAR ──
  rmse(mySBM$connectParam$mean, sampler_undirected_cov$connectParam$mean) is not strictly less than 0.075. Difference: 0.925
  ── Failure ('test-sbm-MAR_bernoulli-with-covariates.R:24:3'): SimpleSBM_fit 'Bernoulli' model, undirected, one covariate, dyad sampling, MAR ──
  ARI(mySBM$memberships, sampler_undirected_cov$memberships) is not strictly more than 0.95. Difference: -0.95
  ── Failure ('test-sbm-MAR_bernoulli-with-covariates.R:41:3'): SimpleSBM_fit 'Bernoulli' model, directed, one covariate, dyad sampling, MAR ──
  rmse(mySBM$connectParam$mean, sampler_directed_cov$connectParam$mean) is not strictly less than 0.075. Difference: 0.925
  ── Failure ('test-sbm-MAR_bernoulli-with-covariates.R:42:3'): SimpleSBM_fit 'Bernoulli' model, directed, one covariate, dyad sampling, MAR ──
  ARI(mySBM$memberships, sampler_directed_cov$memberships) is not strictly more than 0.95. Difference: -0.95
  ── Failure ('test-sbm-bernoulli-with-covariates.R:29:3'): SimpleSBM_fit 'Bernoulli' model, undirected, one covariate ──
  rmse(mySBM_missSBM$connectParam$mean, mySBM_sbm$connectParam$mean) is not strictly less than 0.05. Difference: 0.95
  ── Failure ('test-sbm-bernoulli-with-covariates.R:30:3'): SimpleSBM_fit 'Bernoulli' model, undirected, one covariate ──
  ARI(mySBM_missSBM$memberships, mySBM_sbm$memberships) is not strictly more than 0.8. Difference: -0.8
  ── Failure ('test-sbm-bernoulli-with-covariates.R:31:3'): SimpleSBM_fit 'Bernoulli' model, undirected, one covariate ──
  rmse(mySBM_missSBM$loglik, mySBM_sbm$loglik) is not strictly less than 0.01. Difference: 33.9
  ── Failure ('test-sbm-bernoulli-with-covariates.R:34:3'): SimpleSBM_fit 'Bernoulli' model, undirected, one covariate ──
  rmse(mySBM_missSBM$connectParam$mean, sampler_undirected_cov$connectParam$mean) is not strictly less than 0.1. Difference: 0.9
  ── Failure ('test-sbm-bernoulli-with-covariates.R:35:3'): SimpleSBM_fit 'Bernoulli' model, undirected, one covariate ──
  rmse(mySBM_missSBM$covarParam, sampler_undirected_cov$covarParam) is not strictly less than 0.1. Difference: 0.9
  ── Failure ('test-sbm-bernoulli-with-covariates.R:36:3'): SimpleSBM_fit 'Bernoulli' model, undirected, one covariate ──
  ARI(mySBM_missSBM$memberships, sampler_undirected_cov$memberships) is not strictly more than 0.85. Difference: -0.85
  ── Failure ('test-sbm-bernoulli-with-covariates.R:58:3'): SimpleSBM_fit 'Bernoulli' model, directed, one covariate ──
  rmse(mySBM_missSBM$connectParam$mean, mySBM_sbm$connectParam$mean) is not strictly less than 0.1. Difference: 0.9
  ── Failure ('test-sbm-bernoulli-with-covariates.R:59:3'): SimpleSBM_fit 'Bernoulli' model, directed, one covariate ──
  ARI(mySBM_missSBM$memberships, mySBM_sbm$memberships) is not strictly more than 0.8. Difference: -0.8
  ── Failure ('test-sbm-bernoulli-with-covariates.R:60:3'): SimpleSBM_fit 'Bernoulli' model, directed, one covariate ──
  rmse(mySBM_missSBM$loglik, mySBM_sbm$loglik) is not strictly less than 0.05. Difference: 34
  ── Failure ('test-sbm-bernoulli-with-covariates.R:63:3'): SimpleSBM_fit 'Bernoulli' model, directed, one covariate ──
  rmse(mySBM_missSBM$connectParam$mean, sampler_directed_cov$connectParam$mean) is not strictly less than 0.1. Difference: 0.9
  ── Failure ('test-sbm-bernoulli-with-covariates.R:64:3'): SimpleSBM_fit 'Bernoulli' model, directed, one covariate ──
  ARI(mySBM_missSBM$memberships, sampler_directed_cov$memberships) is not strictly more than 0.85. Difference: -0.85
  
  [ FAIL 17 | WARN 1 | SKIP 0 | PASS 372 ]
  Error: Test failures
  Execution halted