Running ‘testthat.R’ [30s/41s]
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: 1.046 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: 0.231 s 
     iterations: 3 
  
  A (cluster membership matrix): 
        Cl1 Cl2 Cl3
   [1,]   0   0   1
   [2,]   0   0   1
   [3,]   0   0   1
   [4,]   1   0   0
   [5,]   1   0   0
   [6,]   1   0   0
   [7,]   1   0   0
   [8,]   1   0   0
   [9,]   1   0   0
  [10,]   0   1   0
  [ 11  rows were omitted ]
  
  C (profiles in terms of components - cluster by component): 
        Comp1   Comp2
  Cl1 111.595   7.469
  Cl2  98.410  12.283
  Cl3 126.430 -16.154
  
  B' (components by variables):  
        Air.Flow Water.Temp Acid.Conc. stack.loss
  Comp1    0.574      0.198      0.767      0.205
  Comp2   -0.339     -0.074      0.487     -0.802
  ADPROCLUS solution 
  Setup: 
     number of clusters: 2 
     data format:  21 x 4 
     number of total starts: 6 
  Results: 
     explained variance: 0.98 
     processing time: 1.05 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: 1.05 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: 3 
  
  A (cluster membership matrix): 
       Cl1 Cl2 Cl3
  [1,]   0   0   1
  [ 20  rows were omitted ]
  
  C (profiles in terms of components - cluster by component): 
       Comp1 Comp2
  Cl1 111.59  7.47
  [ 2  rows were omitted ]
  
  B' (components by variables):  
        Air.Flow Water.Temp Acid.Conc. stack.loss
  Comp1     0.57       0.20       0.77       0.21
  Comp2    -0.34      -0.07       0.49      -0.80
  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: 3 
  
  A (cluster membership matrix): 
       Cl1 Cl2 Cl3
  [1,]   0   0   1
  [ 20  rows were omitted ]
  
  C (profiles in terms of components - cluster by component): 
       Comp1 Comp2
  Cl1 111.59  7.47
  [ 2  rows were omitted ]
  
  B' (components by variables):  
        Air.Flow Water.Temp Acid.Conc. stack.loss
  Comp1     0.57       0.20       0.77       0.21
  Comp2    -0.34      -0.07       0.49      -0.80
  ADPROCLUS solution 
  Setup: 
     number of clusters: 2 
     data format:  21 x 4 
     number of total starts: 6 
  Results: 
     explained variance: 0.98 
     processing time: 0.96 s 
     iterations: 5 
  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 ]
  Cluster sizes and overlaps:
       [,1] [,2]
  [1,]   21    3
  [2,]    3    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.   :14.00  
   Mean   :60.43   Mean   :21.10   Mean   :86.29   Mean   :17.52  
   Max.   :78.33   Max.   :26.33   Max.   :89.00   Max.   :38.67  
  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: 0.4 s 
     iterations: 4 
  
  A (cluster membership matrix): 
       Cl1 Cl2 Cl3
  [1,]   0   0   1
  [ 20  rows were omitted ]
  
  C (profiles in terms of components - cluster by component): 
       Comp1 Comp2
  Cl1 111.59  7.47
  [ 2  rows were omitted ]
  
  B' (components by variables):  
        Air.Flow Water.Temp Acid.Conc. stack.loss
  Comp1     0.57       0.20       0.77       0.21
  Comp2    -0.34      -0.07       0.49      -0.80
  Cluster sizes and overlaps:
       [,1] [,2] [,3]
  [1,]   10    0    0
  [2,]    0    8    0
  [3,]    0    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 low dimensional components per cluster:
  Cl1 
       Comp1           Comp2      
   Min.   :111.6   Min.   :7.469  
   Mean   :111.6   Mean   :7.469  
   Max.   :111.6   Max.   :7.469  
  Cl2 
       Comp1           Comp2      
   Min.   :98.41   Min.   :12.28  
   Mean   :98.41   Mean   :12.28  
   Max.   :98.41   Max.   :12.28  
  Cl3 
       Comp1           Comp2       
   Min.   :126.4   Min.   :-16.15  
   Mean   :126.4   Mean   :-16.15  
   Max.   :126.4   Max.   :-16.15  
  ADPROCLUS solution 
  Setup: 
     number of clusters: 2 
     data format:  21 x 4 
     number of total starts: 6 
  Results: 
     explained variance: 0.98 
     processing time: 0.96 s 
     iterations: 5 
  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 ]
  Cluster sizes and overlaps:
       [,1] [,2]
  [1,]   21    3
  [2,]    3    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.   :14.00  
   Mean   :60.43   Mean   :21.10   Mean   :86.29   Mean   :17.52  
   Max.   :78.33   Max.   :26.33   Max.   :89.00   Max.   :38.67  
  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: 0.96 s 
     iterations: 5 
  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 ]
  Cluster sizes and overlaps:
       [,1] [,2]
  [1,]   21    3
  [2,]    3    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.   :14.00  
   Mean   :60.43   Mean   :21.10   Mean   :86.29   Mean   :17.52  
   Max.   :78.33   Max.   :26.33   Max.   :89.00   Max.   :38.67  
  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: 0.4 s 
     iterations: 4 
  
  A (cluster membership matrix): 
       Cl1 Cl2 Cl3
  [1,]   0   0   1
  [ 20  rows were omitted ]
  
  C (profiles in terms of components - cluster by component): 
       Comp1 Comp2
  Cl1 111.59  7.47
  [ 2  rows were omitted ]
  
  B' (components by variables):  
        Air.Flow Water.Temp Acid.Conc. stack.loss
  Comp1     0.57       0.20       0.77       0.21
  Comp2    -0.34      -0.07       0.49      -0.80
  Cluster sizes and overlaps:
       [,1] [,2] [,3]
  [1,]   10    0    0
  [2,]    0    8    0
  [3,]    0    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 low dimensional components per cluster:
  Cl1 
       Comp1           Comp2      
   Min.   :111.6   Min.   :7.469  
   Mean   :111.6   Mean   :7.469  
   Max.   :111.6   Max.   :7.469  
  Cl2 
       Comp1           Comp2      
   Min.   :98.41   Min.   :12.28  
   Mean   :98.41   Mean   :12.28  
   Max.   :98.41   Max.   :12.28  
  Cl3 
       Comp1           Comp2       
   Min.   :126.4   Min.   :-16.15  
   Mean   :126.4   Mean   :-16.15  
   Max.   :126.4   Max.   :-16.15  
  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: 0.4 s 
     iterations: 4 
  
  A (cluster membership matrix): 
       Cl1 Cl2 Cl3
  [1,]   0   0   1
  [ 20  rows were omitted ]
  
  C (profiles in terms of components - cluster by component): 
       Comp1 Comp2
  Cl1 111.59  7.47
  [ 2  rows were omitted ]
  
  B' (components by variables):  
        Air.Flow Water.Temp Acid.Conc. stack.loss
  Comp1     0.57       0.20       0.77       0.21
  Comp2    -0.34      -0.07       0.49      -0.80
  Cluster sizes and overlaps:
       [,1] [,2] [,3]
  [1,]   10    0    0
  [2,]    0    8    0
  [3,]    0    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 low dimensional components per cluster:
  Cl1 
       Comp1           Comp2      
   Min.   :111.6   Min.   :7.469  
   Mean   :111.6   Mean   :7.469  
   Max.   :111.6   Max.   :7.469  
  Cl2 
       Comp1           Comp2      
   Min.   :98.41   Min.   :12.28  
   Mean   :98.41   Mean   :12.28  
   Max.   :98.41   Max.   :12.28  
  Cl3 
       Comp1           Comp2       
   Min.   :126.4   Min.   :-16.15  
   Mean   :126.4   Mean   :-16.15  
   Max.   :126.4   Max.   :-16.15  
  [ 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