Running ‘testthat.R’ [12s/17s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
  > library(testthat)
  > test_check("Cyclops")
  Loading required package: Cyclops
  Sorting outcomes by stratumId and rowId
  Sorting covariates by covariateId, stratumId, and rowId
  Sorting outcomes by stratumId and rowId
  Sorting covariates by covariateId, stratumId and rowId
  Sorting outcomes by stratumId and rowId
  Sorting covariates by covariateId, stratumId, and rowId
  Sorting outcomes by stratumId, time (descending), y, and rowId
  Sorting covariates by covariateId, stratumId, time (descending), y, and rowId
  Sorting outcomes by stratumId, time (descending), y and rowId
  Sorting covariates by covariateId, stratumId, time (descending), y, and rowId
  Sorting outcomes by stratumId, time (descending), y, and rowId
  Sorting covariates by covariateId, stratumId, time (descending), y, and rowId
  Sorting outcomes by stratumId, time (descending), y and rowId
  Sorting covariates by covariateId, stratumId, time (descending), y, and rowId
  Sparseness = 76.245 %
  Sorting covariates by covariateId, stratumId and rowId
  Sorting covariates by covariateId, stratumId, and rowId
  Sorting outcomes by stratumId, time (descending), y, and rowId
  Sorting covariates by covariateId, stratumId, time (descending), y, and rowId
  Sorting outcomes by stratumId, time (descending), y and rowId
  Sorting covariates by covariateId, stratumId, time (descending), y, and rowId
  Sparseness = 75.76 %
  Sorting covariates by covariateId, rowId
  Sorting covariates by covariateId and rowId
  Sparseness = 99.012 %
  Sorting covariates by covariateId and rowId
  ── 1. Failure: Separable covariates in logistic regression (@test-largeBernoulli
  `coef(fit)` did not throw an error.
  
  ── 2. Failure: Separable covariates in logistic regression (@test-largeBernoulli
  coef(ecFit)[separability] not equivalent to 0.
  Lengths differ: 0 is not 1
  
  ── 3. Failure: Separable covariates in logistic regression (@test-largeBernoulli
  is.na(coef(nsFit)[7]) isn't true.
  
  Sparseness = 99.012 %
  Sorting outcomes by stratumId, time (descending), y and rowId
  Sorting covariates by covariateId, stratumId, time (descending), y, and rowId
  Sparseness = 76.145 %
  Sorting covariates by covariateId and rowId
  Sparseness = 75.035 %
  Sorting covariates by covariateId and rowId
  Sparseness = 75.5 %
  Sorting covariates by covariateId and rowId
  Sparseness = 76.95 %
  Sorting covariates by covariateId and rowId
  Sparseness = 99.012 %
  Sorting outcomes by stratumId, time (descending), y and rowId
  Sorting covariates by covariateId, stratumId, time (descending), y, and rowId
  Sparseness = 98.0118 %
  Sorting covariates by covariateId and rowId
  Using cross-validation selector type byRow
  Performing 10-fold cross-validation [seed = 123] with data partitions of sizes 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000
  Using 1 thread(s)
  Starting var = 0.1
  Running at Laplace(4.47214) None  Grid-point #1 at 0.1 	Fold #1 Rep #1 pred log like = -506.649
  Running at Laplace(4.47214) None  Grid-point #1 at 0.1 	Fold #2 Rep #1 pred log like = -488.019
  Running at Laplace(4.47214) None  Grid-point #1 at 0.1 	Fold #3 Rep #1 pred log like = -468.301
  Running at Laplace(4.47214) None  Grid-point #1 at 0.1 	Fold #4 Rep #1 pred log like = -457.075
  Running at Laplace(4.47214) None  Grid-point #1 at 0.1 	Fold #5 Rep #1 pred log like = -486.668
  Running at Laplace(4.47214) None  Grid-point #1 at 0.1 	Fold #6 Rep #1 pred log like = -481.722
  Running at Laplace(4.47214) None  Grid-point #1 at 0.1 	Fold #7 Rep #1 pred log like = -523.012
  Running at Laplace(4.47214) None  Grid-point #1 at 0.1 	Fold #8 Rep #1 pred log like = -478.147
  Running at Laplace(4.47214) None  Grid-point #1 at 0.1 	Fold #9 Rep #1 pred log like = -535.522
  Running at Laplace(4.47214) None  Grid-point #1 at 0.1 	Fold #10 Rep #1 pred log like = -522.17
  AvgPred = -494.728 with stdev = 24.5549
  Completed at 0.1
  Next point at 1 with value 0 and continue = 1
  search[ 0.1 ] = -494.728(24.5549)
  
  Running at Laplace(1.41421) None  Grid-point #2 at 1 	Fold #1 Rep #1 pred log like = -506.416
  Running at Laplace(1.41421) None  Grid-point #2 at 1 	Fold #2 Rep #1 pred log like = -491.745
  Running at Laplace(1.41421) None  Grid-point #2 at 1 	Fold #3 Rep #1 pred log like = -471.182
  Running at Laplace(1.41421) None  Grid-point #2 at 1 	Fold #4 Rep #1 pred log like = -459.531
  Running at Laplace(1.41421) None  Grid-point #2 at 1 	Fold #5 Rep #1 pred log like = -490.299
  Running at Laplace(1.41421) None  Grid-point #2 at 1 	Fold #6 Rep #1 pred log like = -484.243
  Running at Laplace(1.41421) None  Grid-point #2 at 1 	Fold #7 Rep #1 pred log like = -528.388
  Running at Laplace(1.41421) None  Grid-point #2 at 1 	Fold #8 Rep #1 pred log like = -481.737
  Running at Laplace(1.41421) None  Grid-point #2 at 1 	Fold #9 Rep #1 pred log like = -537.224
  Running at Laplace(1.41421) None  Grid-point #2 at 1 	Fold #10 Rep #1 pred log like = -523.871
  AvgPred = -497.464 with stdev = 24.3935
  Completed at 1
  Next point at 0.01 with value 0 and continue = 1
  search[ 0.1 ] = -494.728(24.5549)
  search[ 1 ] = -497.464(24.3935)
  
  Running at Laplace(14.1421) None  Grid-point #3 at 0.01 	Fold #1 Rep #1 pred log like = -507.689
  Running at Laplace(14.1421) None  Grid-point #3 at 0.01 	Fold #2 Rep #1 pred log like = -487.469
  Running at Laplace(14.1421) None  Grid-point #3 at 0.01 	Fold #3 Rep #1 pred log like = -468.406
  Running at Laplace(14.1421) None  Grid-point #3 at 0.01 	Fold #4 Rep #1 pred log like = -457.267
  Running at Laplace(14.1421) None  Grid-point #3 at 0.01 	Fold #5 Rep #1 pred log like = -486.379
  Running at Laplace(14.1421) None  Grid-point #3 at 0.01 	Fold #6 Rep #1 pred log like = -482.372
  Running at Laplace(14.1421) None  Grid-point #3 at 0.01 	Fold #7 Rep #1 pred log like = -519.134
  Running at Laplace(14.1421) None  Grid-point #3 at 0.01 	Fold #8 Rep #1 pred log like = -475.33
  Running at Laplace(14.1421) None  Grid-point #3 at 0.01 	Fold #9 Rep #1 pred log like = -535.713
  Running at Laplace(14.1421) None  Grid-point #3 at 0.01 	Fold #10 Rep #1 pred log like = -520.314
  AvgPred = -494.007 with stdev = 24.1668
  Completed at 0.01
  Next point at 0.001 with value 0 and continue = 1
  search[ 0.01 ] = -494.007(24.1668)
  search[ 0.1 ] = -494.728(24.5549)
  search[ 1 ] = -497.464(24.3935)
  
  Running at Laplace(44.7214) None  Grid-point #4 at 0.001 	Fold #1 Rep #1 pred log like = -511.696
  Running at Laplace(44.7214) None  Grid-point #4 at 0.001 	Fold #2 Rep #1 pred log like = -493.423
  Running at Laplace(44.7214) None  Grid-point #4 at 0.001 	Fold #3 Rep #1 pred log like = -474.024
  Running at Laplace(44.7214) None  Grid-point #4 at 0.001 	Fold #4 Rep #1 pred log like = -458.982
  Running at Laplace(44.7214) None  Grid-point #4 at 0.001 	Fold #5 Rep #1 pred log like = -490.634
  Running at Laplace(44.7214) None  Grid-point #4 at 0.001 	Fold #6 Rep #1 pred log like = -487.851
  Running at Laplace(44.7214) None  Grid-point #4 at 0.001 	Fold #7 Rep #1 pred log like = -520.214
  Running at Laplace(44.7214) None  Grid-point #4 at 0.001 	Fold #8 Rep #1 pred log like = -476.777
  Running at Laplace(44.7214) None  Grid-point #4 at 0.001 	Fold #9 Rep #1 pred log like = -538.855
  Running at Laplace(44.7214) None  Grid-point #4 at 0.001 	Fold #10 Rep #1 pred log like = -523.065
  AvgPred = -497.552 with stdev = 23.8793
  Completed at 0.001
  Next point at 0.0305978 with value -493.972 and continue = 0
  search[ 0.001 ] = -497.552(23.8793)
  search[ 0.01 ] = -494.007(24.1668)
  search[ 0.1 ] = -494.728(24.5549)
  search[ 1 ] = -497.464(24.3935)
  
  
  Maximum predicted log likelihood (-493.972) estimated at:
  	0.0305978 (variance)
  	8.08481 (lambda)
  
  Fitting model at optimal hyperparameter
  Using prior: Laplace(8.08481) None 
  ── 4. Failure: Logistic regression with cross-validation (@test-weighted_cv.R#26
  coef(fit)[1] not equal to -0.99.
  1/1 mismatches
  [1] -1.44 - -0.99 == -0.446
  
  Using cross-validation selector type byRow
  Performing 10-fold cross-validation [seed = 1551541861] with data partitions of sizes 1 1 1 1 1 1 1 1 1 0
  Using 1 thread(s)
  Starting var = 0.333333 (default)
  Running at Laplace(2.44949) None  Grid-point #1 at 0.333333 	Fold #1 Rep #1 pred log like = -15.8476
  Running at Laplace(2.44949) None  Grid-point #1 at 0.333333 	Fold #2 Rep #1 pred log like = -7.51911
  Running at Laplace(2.44949) None  Grid-point #1 at 0.333333 	Fold #3 Rep #1 pred log like = -2.77056
  Running at Laplace(2.44949) None  Grid-point #1 at 0.333333 	Fold #4 Rep #1 pred log like = -14.1377
  Running at Laplace(2.44949) None  Grid-point #1 at 0.333333 	Fold #5 Rep #1 pred log like = -9.40993
  Running at Laplace(2.44949) None  Grid-point #1 at 0.333333 	Fold #6 Rep #1 pred log like = -4.84215
  Running at Laplace(2.44949) None  Grid-point #1 at 0.333333 	Fold #7 Rep #1 pred log like = -5.31322
  Running at Laplace(2.44949) None  Grid-point #1 at 0.333333 	Fold #8 Rep #1 pred log like = -2.95369
  Running at Laplace(2.44949) None  Grid-point #1 at 0.333333 	Fold #9 Rep #1 pred log like = -2.20943
  Running at Laplace(2.44949) None  Grid-point #1 at 0.333333 	Fold #10 Rep #1 pred log like = 0
  AvgPred = -6.50034 with stdev = 4.96507
  Completed at 0.333333
  Next point at 3.33333 with value 0 and continue = 1
  search[ 0.333333 ] = -6.50034(4.96507)
  
  Running at Laplace(0.774597) None  Grid-point #2 at 3.33333 	Fold #1 Rep #1 pred log like = -15.7841
  Running at Laplace(0.774597) None  Grid-point #2 at 3.33333 	Fold #2 Rep #1 pred log like = -9.67073
  Running at Laplace(0.774597) None  Grid-point #2 at 3.33333 	Fold #3 Rep #1 pred log like = -3.50408
  Running at Laplace(0.774597) None  Grid-point #2 at 3.33333 	Fold #4 Rep #1 pred log like = -16.7879
  Running at Laplace(0.774597) None  Grid-point #2 at 3.33333 	Fold #5 Rep #1 pred log like = -9.85821
  Running at Laplace(0.774597) None  Grid-point #2 at 3.33333 	Fold #6 Rep #1 pred log like = -4.90173
  Running at Laplace(0.774597) None  Grid-point #2 at 3.33333 	Fold #7 Rep #1 pred log like = -5.39944
  Running at Laplace(0.774597) None  Grid-point #2 at 3.33333 	Fold #8 Rep #1 pred log like = -3.1064
  Running at Laplace(0.774597) None  Grid-point #2 at 3.33333 	Fold #9 Rep #1 pred log like = -2.20787
  Running at Laplace(0.774597) None  Grid-point #2 at 3.33333 	Fold #10 Rep #1 pred log like = 0
  AvgPred = -7.12204 with stdev = 5.4261
  Completed at 3.33333
  Next point at 0.0333333 with value 0 and continue = 1
  search[ 0.333333 ] = -6.50034(4.96507)
  search[ 3.33333 ] = -7.12204(5.4261)
  
  Running at Laplace(7.74597) None  Grid-point #3 at 0.0333333 	Fold #1 Rep #1 pred log like = -17.2486
  Running at Laplace(7.74597) None  Grid-point #3 at 0.0333333 	Fold #2 Rep #1 pred log like = -6.4016
  Running at Laplace(7.74597) None  Grid-point #3 at 0.0333333 	Fold #3 Rep #1 pred log like = -2.38933
  Running at Laplace(7.74597) None  Grid-point #3 at 0.0333333 	Fold #4 Rep #1 pred log like = -8.5641
  Running at Laplace(7.74597) None  Grid-point #3 at 0.0333333 	Fold #5 Rep #1 pred log like = -8.2011
  Running at Laplace(7.74597) None  Grid-point #3 at 0.0333333 	Fold #6 Rep #1 pred log like = -5.03777
  Running at Laplace(7.74597) None  Grid-point #3 at 0.0333333 	Fold #7 Rep #1 pred log like = -4.23476
  Running at Laplace(7.74597) None  Grid-point #3 at 0.0333333 	Fold #8 Rep #1 pred log like = -2.83786
  Running at Laplace(7.74597) None  Grid-point #3 at 0.0333333 	Fold #9 Rep #1 pred log like = -2.22488
  Running at Laplace(7.74597) None  Grid-point #3 at 0.0333333 	Fold #10 Rep #1 pred log like = 0
  AvgPred = -5.714 with stdev = 4.63275
  Completed at 0.0333333
  Next point at 0.00333333 with value 0 and continue = 1
  search[ 0.0333333 ] = -5.714(4.63275)
  search[ 0.333333 ] = -6.50034(4.96507)
  search[ 3.33333 ] = -7.12204(5.4261)
  
  Running at Laplace(24.4949) None  Grid-point #4 at 0.00333333 	Fold #1 Rep #1 pred log like = -17.9197
  Running at Laplace(24.4949) None  Grid-point #4 at 0.00333333 	Fold #2 Rep #1 pred log like = -4.82178
  Running at Laplace(24.4949) None  Grid-point #4 at 0.00333333 	Fold #3 Rep #1 pred log like = -2.40093
  Running at Laplace(24.4949) None  Grid-point #4 at 0.00333333 	Fold #4 Rep #1 pred log like = -8.76107
  Running at Laplace(24.4949) None  Grid-point #4 at 0.00333333 	Fold #5 Rep #1 pred log like = -10.0062
  Running at Laplace(24.4949) None  Grid-point #4 at 0.00333333 	Fold #6 Rep #1 pred log like = -5.61869
  Running at Laplace(24.4949) None  Grid-point #4 at 0.00333333 	Fold #7 Rep #1 pred log like = -3.17614
  Running at Laplace(24.4949) None  Grid-point #4 at 0.00333333 	Fold #8 Rep #1 pred log like = -2.43581
  Running at Laplace(24.4949) None  Grid-point #4 at 0.00333333 	Fold #9 Rep #1 pred log like = -2.59079
  Running at Laplace(24.4949) None  Grid-point #4 at 0.00333333 	Fold #10 Rep #1 pred log like = 0
  AvgPred = -5.77311 with stdev = 4.9802
  Completed at 0.00333333
  Next point at 0.0042315 with value -5.71926 and continue = 0
  search[ 0.00333333 ] = -5.77311(4.9802)
  search[ 0.0333333 ] = -5.714(4.63275)
  search[ 0.333333 ] = -6.50034(4.96507)
  search[ 3.33333 ] = -7.12204(5.4261)
  
  
  Maximum predicted log likelihood (-5.71926) estimated at:
  	0.0042315 (variance)
  	21.7404 (lambda)
  
  Fitting model at optimal hyperparameter
  Using prior: Laplace(21.7404) None 
  Sparseness = 99.09 %
  Sorting covariates by covariateId and rowId
  ══ testthat results  ═══════════════════════════════════════════════════════════
  OK: 249 SKIPPED: 11 FAILED: 4
  1. Failure: Separable covariates in logistic regression (@test-largeBernoulli.R#43) 
  2. Failure: Separable covariates in logistic regression (@test-largeBernoulli.R#62) 
  3. Failure: Separable covariates in logistic regression (@test-largeBernoulli.R#67) 
  4. Failure: Logistic regression with cross-validation (@test-weighted_cv.R#26) 
  
  Error: testthat unit tests failed
  Execution halted