Running ‘testthat.R’ [18s/27s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
  > # This file is part of the standard setup for testthat.
  > # It is recommended that you do not modify it.
  > #
  > # Where should you do additional test configuration?
  > # Learn more about the roles of various files in:
  > # * https://r-pkgs.org/testing-design.html#sec-tests-files-overview
  > # * https://testthat.r-lib.org/articles/special-files.html
  > 
  > library(testthat)
  > library(adproclus)
  > 
  > test_check("adproclus")
  ADPROCLUS solution 
  Setup: 
     number of clusters: 2 
     data format:  21 x 4 
     number of total starts: 6 
  Results: 
     explained variance: 0.976 
     processing time: 0.663 s 
     iterations: 6 
  A (cluster membership matrix): 
        Cl1 Cl2
   [1,]   1   1
   [2,]   1   1
   [3,]   1   1
   [4,]   1   0
   [5,]   1   0
   [6,]   1   0
   [7,]   1   0
   [8,]   1   0
   [9,]   1   0
  [10,]   1   0
  [ 11  rows were omitted ]
  P (profiles): 
      Air.Flow Water.Temp Acid.Conc. stack.loss
  Cl1   57.444     20.222     85.833     14.000
  Cl2   20.889      6.111      3.167     24.667
  Low Dimensional ADPROCLUS solution 
     number of clusters: 3 
     number of components:  2 
     data format:  21 x 4 
     number of total starts: 6 
  Results: 
     explained variance: 0.988 
     processing time: 0.23 s 
     iterations: 5 
  
  A (cluster membership matrix): 
        Cl1 Cl2 Cl3
   [1,]   0   1   1
   [2,]   0   1   1
   [3,]   0   1   1
   [4,]   1   1   0
   [5,]   1   1   0
   [6,]   1   1   0
   [7,]   1   1   0
   [8,]   1   1   0
   [9,]   1   1   0
  [10,]   1   0   1
  [ 11  rows were omitted ]
  
  C (profiles in terms of components - cluster by component): 
       Comp1  Comp2
  Cl1 41.186 19.293
  Cl2 70.110 -8.225
  Cl3 56.776 -3.839
  
  B' (components by variables):  
        Air.Flow Water.Temp Acid.Conc. stack.loss
  Comp1    0.585      0.200      0.751      0.231
  Comp2   -0.320     -0.067      0.511     -0.795
  ADPROCLUS solution 
  Setup: 
     number of clusters: 2 
     data format:  21 x 4 
     number of total starts: 6 
  Results: 
     explained variance: 0.98 
     processing time: 0.66 s 
     iterations: 6 
  A (cluster membership matrix): 
       Cl1 Cl2
  [1,]   1   1
  [ 20  rows were omitted ]
  P (profiles): 
      Air.Flow Water.Temp Acid.Conc. stack.loss
  Cl1    57.44      20.22      85.83         14
  [ 1  rows were omitted ]
  ADPROCLUS solution 
  Setup: 
     number of clusters: 2 
     data format:  21 x 4 
     number of total starts: 6 
  Results: 
     explained variance: 0.98 
     processing time: 0.66 s 
     iterations: 6 
  A (cluster membership matrix): 
       Cl1 Cl2
  [1,]   1   1
  [ 20  rows were omitted ]
  P (profiles): 
      Air.Flow Water.Temp Acid.Conc. stack.loss
  Cl1    57.44      20.22      85.83         14
  [ 1  rows were omitted ]
  Low Dimensional ADPROCLUS solution 
     number of clusters: 3 
     number of components:  2 
     data format:  21 x 4 
     number of total starts: 6 
  Results: 
     explained variance: 0.99 
     processing time: 0.23 s 
     iterations: 5 
  
  A (cluster membership matrix): 
       Cl1 Cl2 Cl3
  [1,]   0   1   1
  [ 20  rows were omitted ]
  
  C (profiles in terms of components - cluster by component): 
      Comp1 Comp2
  Cl1 41.19 19.29
  [ 2  rows were omitted ]
  
  B' (components by variables):  
        Air.Flow Water.Temp Acid.Conc. stack.loss
  Comp1     0.58       0.20       0.75       0.23
  Comp2    -0.32      -0.07       0.51      -0.79
  Low Dimensional ADPROCLUS solution 
     number of clusters: 3 
     number of components:  2 
     data format:  21 x 4 
     number of total starts: 6 
  Results: 
     explained variance: 0.99 
     processing time: 0.23 s 
     iterations: 5 
  
  A (cluster membership matrix): 
       Cl1 Cl2 Cl3
  [1,]   0   1   1
  [ 20  rows were omitted ]
  
  C (profiles in terms of components - cluster by component): 
      Comp1 Comp2
  Cl1 41.19 19.29
  [ 2  rows were omitted ]
  
  B' (components by variables):  
        Air.Flow Water.Temp Acid.Conc. stack.loss
  Comp1     0.58       0.20       0.75       0.23
  Comp2    -0.32      -0.07       0.51      -0.79
  ADPROCLUS solution 
  Setup: 
     number of clusters: 2 
     data format:  21 x 4 
     number of total starts: 6 
  Results: 
     explained variance: 0.98 
     processing time: 0.65 s 
     iterations: 5 
  A (cluster membership matrix): 
       Cl1 Cl2
  [1,]   0   1
  [ 20  rows were omitted ]
  P (profiles): 
      Air.Flow Water.Temp Acid.Conc. stack.loss
  Cl1    57.44      20.22      85.83         14
  [ 1  rows were omitted ]
  Cluster sizes and overlaps:
       [,1] [,2]
  [1,]   18    0
  [2,]    0    3
   (diagonal entries: number of observations in a cluster)
   (off-diagonal entry [i,j]:  number of observations both in cluster i and j)
  
  Summary statistics of model variables per cluster:
  Cl1 
      Air.Flow       Water.Temp      Acid.Conc.      stack.loss
   Min.   :57.44   Min.   :20.22   Min.   :85.83   Min.   :14  
   Mean   :57.44   Mean   :20.22   Mean   :85.83   Mean   :14  
   Max.   :57.44   Max.   :20.22   Max.   :85.83   Max.   :14  
  Cl2 
      Air.Flow       Water.Temp      Acid.Conc.   stack.loss   
   Min.   :78.33   Min.   :26.33   Min.   :89   Min.   :38.67  
   Mean   :78.33   Mean   :26.33   Mean   :89   Mean   :38.67  
   Max.   :78.33   Max.   :26.33   Max.   :89   Max.   :38.67  
  Low Dimensional ADPROCLUS solution 
     number of clusters: 3 
     number of components:  2 
     data format:  21 x 4 
     number of total starts: 6 
  Results: 
     explained variance: 0.99 
     processing time: 0.17 s 
     iterations: 3 
  
  A (cluster membership matrix): 
       Cl1 Cl2 Cl3
  [1,]   0   1   1
  [ 20  rows were omitted ]
  
  C (profiles in terms of components - cluster by component): 
      Comp1 Comp2
  Cl1 41.19 19.29
  [ 2  rows were omitted ]
  
  B' (components by variables):  
        Air.Flow Water.Temp Acid.Conc. stack.loss
  Comp1     0.58       0.20       0.75       0.23
  Comp2    -0.32      -0.07       0.51      -0.79
  Cluster sizes and overlaps:
       [,1] [,2] [,3]
  [1,]   18   10    8
  [2,]   10   13    3
  [3,]    8    3   11
   (diagonal entries: number of observations in a cluster)
   (off-diagonal entry [i,j]:  number of observations both in cluster i and j)
  
  Summary statistics of low dimensional components per cluster:
  Cl1 
       Comp1            Comp2      
   Min.   : 97.96   Min.   :11.07  
   Mean   :105.37   Mean   :13.02  
   Max.   :111.30   Max.   :15.45  
  Cl2 
       Comp1           Comp2       
   Min.   :111.3   Min.   :-12.06  
   Mean   :114.9   Mean   :  5.73  
   Max.   :126.9   Max.   : 11.07  
  Cl3 
       Comp1            Comp2        
   Min.   : 97.96   Min.   :-12.063  
   Mean   :105.85   Mean   :  7.949  
   Max.   :126.89   Max.   : 15.454  
  ADPROCLUS solution 
  Setup: 
     number of clusters: 2 
     data format:  21 x 4 
     number of total starts: 6 
  Results: 
     explained variance: 0.98 
     processing time: 0.65 s 
     iterations: 5 
  A (cluster membership matrix): 
       Cl1 Cl2
  [1,]   0   1
  [ 20  rows were omitted ]
  P (profiles): 
      Air.Flow Water.Temp Acid.Conc. stack.loss
  Cl1    57.44      20.22      85.83         14
  [ 1  rows were omitted ]
  Cluster sizes and overlaps:
       [,1] [,2]
  [1,]   18    0
  [2,]    0    3
   (diagonal entries: number of observations in a cluster)
   (off-diagonal entry [i,j]:  number of observations both in cluster i and j)
  
  Summary statistics of model variables per cluster:
  Cl1 
      Air.Flow       Water.Temp      Acid.Conc.      stack.loss
   Min.   :57.44   Min.   :20.22   Min.   :85.83   Min.   :14  
   Mean   :57.44   Mean   :20.22   Mean   :85.83   Mean   :14  
   Max.   :57.44   Max.   :20.22   Max.   :85.83   Max.   :14  
  Cl2 
      Air.Flow       Water.Temp      Acid.Conc.   stack.loss   
   Min.   :78.33   Min.   :26.33   Min.   :89   Min.   :38.67  
   Mean   :78.33   Mean   :26.33   Mean   :89   Mean   :38.67  
   Max.   :78.33   Max.   :26.33   Max.   :89   Max.   :38.67  
  ADPROCLUS solution 
  Setup: 
     number of clusters: 2 
     data format:  21 x 4 
     number of total starts: 6 
  Results: 
     explained variance: 0.98 
     processing time: 0.65 s 
     iterations: 5 
  A (cluster membership matrix): 
       Cl1 Cl2
  [1,]   0   1
  [ 20  rows were omitted ]
  P (profiles): 
      Air.Flow Water.Temp Acid.Conc. stack.loss
  Cl1    57.44      20.22      85.83         14
  [ 1  rows were omitted ]
  Cluster sizes and overlaps:
       [,1] [,2]
  [1,]   18    0
  [2,]    0    3
   (diagonal entries: number of observations in a cluster)
   (off-diagonal entry [i,j]:  number of observations both in cluster i and j)
  
  Summary statistics of model variables per cluster:
  Cl1 
      Air.Flow       Water.Temp      Acid.Conc.      stack.loss
   Min.   :57.44   Min.   :20.22   Min.   :85.83   Min.   :14  
   Mean   :57.44   Mean   :20.22   Mean   :85.83   Mean   :14  
   Max.   :57.44   Max.   :20.22   Max.   :85.83   Max.   :14  
  Cl2 
      Air.Flow       Water.Temp      Acid.Conc.   stack.loss   
   Min.   :78.33   Min.   :26.33   Min.   :89   Min.   :38.67  
   Mean   :78.33   Mean   :26.33   Mean   :89   Mean   :38.67  
   Max.   :78.33   Max.   :26.33   Max.   :89   Max.   :38.67  
  Low Dimensional ADPROCLUS solution 
     number of clusters: 3 
     number of components:  2 
     data format:  21 x 4 
     number of total starts: 6 
  Results: 
     explained variance: 0.99 
     processing time: 0.17 s 
     iterations: 3 
  
  A (cluster membership matrix): 
       Cl1 Cl2 Cl3
  [1,]   0   1   1
  [ 20  rows were omitted ]
  
  C (profiles in terms of components - cluster by component): 
      Comp1 Comp2
  Cl1 41.19 19.29
  [ 2  rows were omitted ]
  
  B' (components by variables):  
        Air.Flow Water.Temp Acid.Conc. stack.loss
  Comp1     0.58       0.20       0.75       0.23
  Comp2    -0.32      -0.07       0.51      -0.79
  Cluster sizes and overlaps:
       [,1] [,2] [,3]
  [1,]   18   10    8
  [2,]   10   13    3
  [3,]    8    3   11
   (diagonal entries: number of observations in a cluster)
   (off-diagonal entry [i,j]:  number of observations both in cluster i and j)
  
  Summary statistics of low dimensional components per cluster:
  Cl1 
       Comp1            Comp2      
   Min.   : 97.96   Min.   :11.07  
   Mean   :105.37   Mean   :13.02  
   Max.   :111.30   Max.   :15.45  
  Cl2 
       Comp1           Comp2       
   Min.   :111.3   Min.   :-12.06  
   Mean   :114.9   Mean   :  5.73  
   Max.   :126.9   Max.   : 11.07  
  Cl3 
       Comp1            Comp2        
   Min.   : 97.96   Min.   :-12.063  
   Mean   :105.85   Mean   :  7.949  
   Max.   :126.89   Max.   : 15.454  
  Low Dimensional ADPROCLUS solution 
     number of clusters: 3 
     number of components:  2 
     data format:  21 x 4 
     number of total starts: 6 
  Results: 
     explained variance: 0.99 
     processing time: 0.17 s 
     iterations: 3 
  
  A (cluster membership matrix): 
       Cl1 Cl2 Cl3
  [1,]   0   1   1
  [ 20  rows were omitted ]
  
  C (profiles in terms of components - cluster by component): 
      Comp1 Comp2
  Cl1 41.19 19.29
  [ 2  rows were omitted ]
  
  B' (components by variables):  
        Air.Flow Water.Temp Acid.Conc. stack.loss
  Comp1     0.58       0.20       0.75       0.23
  Comp2    -0.32      -0.07       0.51      -0.79
  Cluster sizes and overlaps:
       [,1] [,2] [,3]
  [1,]   18   10    8
  [2,]   10   13    3
  [3,]    8    3   11
   (diagonal entries: number of observations in a cluster)
   (off-diagonal entry [i,j]:  number of observations both in cluster i and j)
  
  Summary statistics of low dimensional components per cluster:
  Cl1 
       Comp1            Comp2      
   Min.   : 97.96   Min.   :11.07  
   Mean   :105.37   Mean   :13.02  
   Max.   :111.30   Max.   :15.45  
  Cl2 
       Comp1           Comp2       
   Min.   :111.3   Min.   :-12.06  
   Mean   :114.9   Mean   :  5.73  
   Max.   :126.9   Max.   : 11.07  
  Cl3 
       Comp1            Comp2        
   Min.   : 97.96   Min.   :-12.063  
   Mean   :105.85   Mean   :  7.949  
   Max.   :126.89   Max.   : 15.454  
  [ FAIL 2 | WARN 0 | SKIP 0 | PASS 64 ]
  
  ══ Failed tests ════════════════════════════════════════════════════════════════
  ── Failure ('test-visualize.R:7:9'): network plot, basic functionality ─────────
  Expected `plot_cluster_network(model)` to run without any conditions.
  i Actually got a <simpleError> with text:
    'list' object cannot be coerced to type 'double'
  ── Failure ('test-visualize.R:8:9'): network plot, basic functionality ─────────
  Expected `plot_cluster_network(model, title = "Test network", relative_overlap = FALSE)` to run without any errors.
  i Actually got a <simpleError> with text:
    'list' object cannot be coerced to type 'double'
  
  [ FAIL 2 | WARN 0 | SKIP 0 | PASS 64 ]
  Error: Test failures
  Execution halted