Running 'spelling.R' [0s]
  Running 'testthat.R' [6s]
Running the tests in 'tests/testthat.R' failed.
Complete output:
  > library(testthat)
  > library(missSBM)
  
  Attaching package: 'missSBM'
  
  The following objects are masked from 'package:stats':
  
      simulate, smooth
  
  The following object is masked from 'package:base':
  
      sample
  
  > 
  > test_check("missSBM")
  Tested sampling:
   - dyad
  sampling: dyad
  
   Adjusting Variational EM for Stochastic Block Model
  
  	Imputation assumes a 'dyad' network-sampling process
  
   Initialization of model with 3 blocks. 
  
   Adjusting Variational EM for Stochastic Block Model
  
  	Imputation assumes a 'covar-dyad' network-sampling process
  
   Initialization of model with 2 blocks. 
  == Failed tests ================================================================
  -- Error (test-INIT-clustering.R:19:1): (code run outside of `test_that()`) ----
  Error: no applicable method for 'isSymmetric' applied to an object of class "c('double', 'numeric')"
  Backtrace:
      x
   1. \-missSBM::observeNetwork(A_full, "dyad", psi) test-INIT-clustering.R:19:0
   2.   \-base::isSymmetric(adjacencyMatrix)
  -- Error (test-MISSSBM-fit-with-covariates.R:37:3): missSBM with covariates and dyad sampling works --
  Error: no applicable method for 'isSymmetric' applied to an object of class "c('double', 'numeric')"
  Backtrace:
      x
   1. \-missSBM::observeNetwork(...) test-MISSSBM-fit-with-covariates.R:37:2
   2.   \-base::isSymmetric(adjacencyMatrix)
  -- Error (test-MISSSBM-fit-with-covariates.R:105:3): miss SBM with covariates and node sampling works --
  Error: no applicable method for 'isSymmetric' applied to an object of class "c('double', 'numeric')"
  Backtrace:
      x
   1. \-missSBM::observeNetwork(...) test-MISSSBM-fit-with-covariates.R:105:2
   2.   \-base::isSymmetric(adjacencyMatrix)
  -- Error (test-MISSSBM-fit-without-covariate.R:38:5): missSBM-fit works and is consistent for all samplings --
  Error: no applicable method for 'isSymmetric' applied to an object of class "c('double', 'numeric')"
  Backtrace:
      x
   1. \-missSBM::observeNetwork(...) test-MISSSBM-fit-without-covariate.R:38:4
   2.   \-base::isSymmetric(adjacencyMatrix)
  -- Error (test-MISSSBM_collection.R:17:3): missSBMcollection works -------------
  Error: no applicable method for 'isSymmetric' applied to an object of class "c('double', 'numeric')"
  Backtrace:
      x
   1. \-missSBM::observeNetwork(A, "dyad", 0.5, clusters = mySBM$memberships) test-MISSSBM_collection.R:17:2
   2.   \-base::isSymmetric(adjacencyMatrix)
  -- Error (test-MISSSBM_collection.R:46:3): More smoothing tests ----------------
  Error: no applicable method for 'isSymmetric' applied to an object of class "c('double', 'numeric')"
  Backtrace:
      x
   1. \-missSBM::observeNetwork(A, "dyad", 0.5, clusters = mySBM$memberships) test-MISSSBM_collection.R:46:2
   2.   \-base::isSymmetric(adjacencyMatrix)
  -- Error (test-SAMPLING-fit-with-covariates.R:20:3): Parameter estimation in dyad-centered sampling with covariates --
  Error: no applicable method for 'isSymmetric' applied to an object of class "c('double', 'numeric')"
  Backtrace:
      x
   1. \-missSBM::observeNetwork(...) test-SAMPLING-fit-with-covariates.R:20:2
   2.   \-base::isSymmetric(adjacencyMatrix)
  -- Error (test-SAMPLING-fit-with-covariates.R:42:3): Parameter estimation in dyad-centered sampling with covariates but ignoring them --
  Error: no applicable method for 'isSymmetric' applied to an object of class "c('double', 'numeric')"
  Backtrace:
      x
   1. \-missSBM::observeNetwork(...) test-SAMPLING-fit-with-covariates.R:42:2
   2.   \-base::isSymmetric(adjacencyMatrix)
  -- Error (test-SAMPLING-fit-with-covariates.R:66:3): Parameter estimation in node-centered sampling with covariates --
  Error: no applicable method for 'isSymmetric' applied to an object of class "c('double', 'numeric')"
  Backtrace:
      x
   1. \-missSBM::observeNetwork(...) test-SAMPLING-fit-with-covariates.R:66:2
   2.   \-base::isSymmetric(adjacencyMatrix)
  -- Error (test-SAMPLING-fit-with-covariates.R:90:3): Parameter estimation in node-centered sampling with covariates but ignoring them --
  Error: no applicable method for 'isSymmetric' applied to an object of class "c('double', 'numeric')"
  Backtrace:
      x
   1. \-missSBM::observeNetwork(sbm$netMatrix, "node", 0.9, covariates = covariates_node) test-SAMPLING-fit-with-covariates.R:90:2
   2.   \-base::isSymmetric(adjacencyMatrix)
  -- Error (test-SAMPLING-fit-with-covariates.R:110:3): Parameter estimation in degree sampling --
  Error: no applicable method for 'isSymmetric' applied to an object of class "c('double', 'numeric')"
  Backtrace:
      x
   1. \-missSBM::observeNetwork(sbm$netMatrix, "degree", psi) test-SAMPLING-fit-with-covariates.R:110:2
   2.   \-base::isSymmetric(adjacencyMatrix)
  -- Error (test-SAMPLING-fit-without-covariate.R:32:5): Consistency of sampling fit --
  Error: no applicable method for 'isSymmetric' applied to an object of class "c('double', 'numeric')"
  Backtrace:
      x
   1. \-missSBM::observeNetwork(...) test-SAMPLING-fit-without-covariate.R:32:4
   2.   \-base::isSymmetric(adjacencyMatrix)
  -- Error (test-SAMPLING-sampler.R:86:3): Consistency of double-standard sampling --
  Error: non-numeric matrix extent
  Backtrace:
      x
   1. \-missSBM:::doubleStandardSampler$new(psi, A, directed) test-SAMPLING-sampler.R:86:2
   2.   \-missSBM:::initialize(...)
   3.     \-super$initialize(...)
   4.       \-base::matrix(NA, private$N, private$N)
  -- Error (test-SAMPLING-sampler.R:112:3): Consistency of degree network sampling --
  Error: 'x' must be an array of at least two dimensions
  Backtrace:
      x
   1. +-missSBM:::degreeSampler$new(psi, rowSums(A), directed) test-SAMPLING-sampler.R:112:2
   2. | \-missSBM:::initialize(...)
   3. |   \-super$initialize("degree", parameters, length(degrees), directed)
   4. \-base::rowSums(A)
  -- Error (test-SAMPLING-sampler.R:139:3): Consistency of snowball sampling -----
  Error: invalid arguments
  Backtrace:
      x
   1. \-missSBM:::snowballSampler$new(param, A, directed) test-SAMPLING-sampler.R:139:2
   2.   \-missSBM:::initialize(...)
   3.     \-stats::runif(n)
  -- Error (test-SBM-sbm-fit-with-covariates.R:29:1): (code run outside of `test_that()`) --
  Error: non-numeric matrix extent
  Backtrace:
      x
   1. \-base::matrix(NA, nrow(A), ncol(A)) test-SBM-sbm-fit-with-covariates.R:29:0
  -- Error (test-SBM-sbm-fit-without-covariate.R:18:1): (code run outside of `test_that()`) --
  Error: only matrix diagonals can be replaced
  Backtrace:
      x
   1. \-base::`diag<-`(`*tmp*`, value = 0) test-SBM-sbm-fit-without-covariate.R:18:0
  -- Error (test-TOP-LEVEL-consistency.R:21:5): check consistency against Tim's code for dyad, node, double standard and block sampling --
  Error: length(dimLabels) == 1 is not TRUE
  Backtrace:
       x
    1. \-missSBM::estimateMissSBM(...) test-TOP-LEVEL-consistency.R:21:4
    2.   \-missSBM_collection$new(...)
    3.     \-missSBM:::initialize(...)
    4.       \-parallel::mcmapply(...)
    5.         \-base::mapply(...)
    6.           \-(function (nBlock, cl0) ...
    7.             \-missSBM_fit$new(partlyObservedNet, nBlock, sampling, cl0, useCov)
    8.               \-missSBM:::initialize(...)
    9.                 \-SimpleSBM_fit_missSBM$new(private$imputedNet, clusterInit, covariates)
   10.                   \-missSBM:::initialize(...)
   11.                     \-super$initialize(...)
   12.                       \-super$initialize(...)
   13.                         \-base::stopifnot(length(dimLabels) == 1)
  -- Error (test-TOP-LEVEL-consistency.R:94:5): check consistency against Tim's code for dyad and node sampling with covariates --
  Error: length(dimLabels) == 1 is not TRUE
  Backtrace:
       x
    1. \-missSBM::estimateMissSBM(...) test-TOP-LEVEL-consistency.R:94:4
    2.   \-missSBM_collection$new(...)
    3.     \-missSBM:::initialize(...)
    4.       \-parallel::mcmapply(...)
    5.         \-base::mapply(...)
    6.           \-(function (nBlock, cl0) ...
    7.             \-missSBM_fit$new(partlyObservedNet, nBlock, sampling, cl0, useCov)
    8.               \-missSBM:::initialize(...)
    9.                 \-SimpleSBM_fit_missSBM$new(private$imputedNet, clusterInit, covariates)
   10.                   \-missSBM:::initialize(...)
   11.                     \-super$initialize(...)
   12.                       \-super$initialize(...)
   13.                         \-base::stopifnot(length(dimLabels) == 1)
  -- Error (test-TOP-LEVEL-estimate.R:16:1): (code run outside of `test_that()`) --
  Error: only matrix diagonals can be replaced
  Backtrace:
      x
   1. \-base::`diag<-`(`*tmp*`, value = 0) test-TOP-LEVEL-estimate.R:16:0
  -- Error (test-TOP-LEVEL-sampleSBM.R:27:3): Consistency of dyad-centered sampling --
  Error: no applicable method for 'isSymmetric' applied to an object of class "c('double', 'numeric')"
  Backtrace:
      x
   1. \-missSBM::observeNetwork(sbm$netMatrix, "dyad", 0.1) test-TOP-LEVEL-sampleSBM.R:27:2
   2.   \-base::isSymmetric(adjacencyMatrix)
  -- Error (test-TOP-LEVEL-sampleSBM.R:61:3): Consistency of node-centered network sampling --
  Error: no applicable method for 'isSymmetric' applied to an object of class "c('double', 'numeric')"
  Backtrace:
      x
   1. \-missSBM::observeNetwork(sbm$netMatrix, "node", 0.1) test-TOP-LEVEL-sampleSBM.R:61:2
   2.   \-base::isSymmetric(adjacencyMatrix)
  -- Error (test-TOP-LEVEL-sampleSBM.R:92:3): Consistency of block-node network sampling --
  Error: no applicable method for 'isSymmetric' applied to an object of class "c('double', 'numeric')"
  Backtrace:
      x
   1. \-missSBM::observeNetwork(...) test-TOP-LEVEL-sampleSBM.R:92:2
   2.   \-base::isSymmetric(adjacencyMatrix)
  -- Error (test-TOP-LEVEL-sampleSBM.R:110:3): Consistency of block-node network sampling --
  Error: no applicable method for 'isSymmetric' applied to an object of class "c('double', 'numeric')"
  Backtrace:
      x
   1. \-missSBM::observeNetwork(...) test-TOP-LEVEL-sampleSBM.R:110:2
   2.   \-base::isSymmetric(adjacencyMatrix)
  -- Error (test-TOP-LEVEL-sampleSBM.R:129:3): Consistency of double-standard sampling --
  Error: no applicable method for 'isSymmetric' applied to an object of class "c('double', 'numeric')"
  Backtrace:
      x
   1. \-missSBM::observeNetwork(...) test-TOP-LEVEL-sampleSBM.R:129:2
   2.   \-base::isSymmetric(adjacencyMatrix)
  -- Error (test-TOP-LEVEL-sampleSBM.R:147:3): Consistency of degree network sampling --
  Error: no applicable method for 'isSymmetric' applied to an object of class "c('double', 'numeric')"
  Backtrace:
      x
   1. \-missSBM::observeNetwork(sbm$netMatrix, "degree", c(0.01, 0.01)) test-TOP-LEVEL-sampleSBM.R:147:2
   2.   \-base::isSymmetric(adjacencyMatrix)
  -- Error (test-consistency-on-fully-observed-network.R:27:3): SimpleSBM_fit_missSBM and missSBMfit are coherent --
  Error: length(dimLabels) == 1 is not TRUE
  Backtrace:
      x
   1. \-missSBM:::SimpleSBM_fit_missSBM$new(adjacencyMatrix = A, clusterInit = cl0) test-consistency-on-fully-observed-network.R:27:2
   2.   \-missSBM:::initialize(...)
   3.     \-super$initialize(...)
   4.       \-super$initialize(...)
   5.         \-base::stopifnot(length(dimLabels) == 1)
  
  [ FAIL 27 | WARN 0 | SKIP 0 | PASS 40 ]
  Error: Test failures
  Execution halted