Running 'testthat.R' [186s]
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: 0.35 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: 0.11 s 
     iterations: 7 
  
  A (cluster membership matrix): 
        Cl1 Cl2 Cl3
   [1,]   1   1   0
   [2,]   1   1   0
   [3,]   1   1   0
   [4,]   1   0   1
   [5,]   1   0   1
   [6,]   1   0   1
   [7,]   1   0   1
   [8,]   1   0   1
   [9,]   1   0   1
  [10,]   0   1   0
  [ 11  rows were omitted ]
  
  C (profiles in terms of components - cluster by component): 
       Comp1   Comp2
  Cl1 21.445  33.674
  Cl2 98.800   8.596
  Cl3 89.240 -17.609
  
  B' (components by variables):  
        Air.Flow Water.Temp Acid.Conc. stack.loss
  Comp1    0.491      0.178      0.852      0.033
  Comp2    0.452      0.114     -0.315      0.827
  ADPROCLUS solution 
  Setup: 
     number of clusters: 2 
     data format:  21 x 4 
     number of total starts: 6 
  Results: 
     explained variance: 0.98 
     processing time: 0.35 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: 0.35 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: 0.11 s 
     iterations: 7 
  
  A (cluster membership matrix): 
       Cl1 Cl2 Cl3
  [1,]   1   1   0
  [ 20  rows were omitted ]
  
  C (profiles in terms of components - cluster by component): 
      Comp1 Comp2
  Cl1 21.44 33.67
  [ 2  rows were omitted ]
  
  B' (components by variables):  
        Air.Flow Water.Temp Acid.Conc. stack.loss
  Comp1     0.49       0.18       0.85       0.03
  Comp2     0.45       0.11      -0.32       0.83
  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: 0.11 s 
     iterations: 7 
  
  A (cluster membership matrix): 
       Cl1 Cl2 Cl3
  [1,]   1   1   0
  [ 20  rows were omitted ]
  
  C (profiles in terms of components - cluster by component): 
      Comp1 Comp2
  Cl1 21.44 33.67
  [ 2  rows were omitted ]
  
  B' (components by variables):  
        Air.Flow Water.Temp Acid.Conc. stack.loss
  Comp1     0.49       0.18       0.85       0.03
  Comp2     0.45       0.11      -0.32       0.83
  ADPROCLUS solution 
  Setup: 
     number of clusters: 2 
     data format:  21 x 4 
     number of total starts: 6 
  Results: 
     explained variance: 0.98 
     processing time: 0.33 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 ]
  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: 0.09 s 
     iterations: 7 
  
  A (cluster membership matrix): 
       Cl1 Cl2 Cl3
  [1,]   1   1   0
  [ 20  rows were omitted ]
  
  C (profiles in terms of components - cluster by component): 
      Comp1 Comp2
  Cl1 21.44 33.67
  [ 2  rows were omitted ]
  
  B' (components by variables):  
        Air.Flow Water.Temp Acid.Conc. stack.loss
  Comp1     0.49       0.18       0.85       0.03
  Comp2     0.45       0.11      -0.32       0.83
  Cluster sizes and overlaps:
       [,1] [,2] [,3]
  [1,]   13    3   10
  [2,]    3   11    0
  [3,]   10    0   10
   (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.   :110.7   Min.   :16.06  
   Mean   :112.9   Mean   :22.11  
   Max.   :120.2   Max.   :42.27  
  Cl2 
       Comp1           Comp2       
   Min.   : 98.8   Min.   : 8.596  
   Mean   :104.6   Mean   :17.780  
   Max.   :120.2   Max.   :42.270  
  Cl3 
       Comp1           Comp2      
   Min.   :110.7   Min.   :16.06  
   Mean   :110.7   Mean   :16.06  
   Max.   :110.7   Max.   :16.06  
  ADPROCLUS solution 
  Setup: 
     number of clusters: 2 
     data format:  21 x 4 
     number of total starts: 6 
  Results: 
     explained variance: 0.98 
     processing time: 0.33 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 ]
  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: 0.33 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 ]
  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: 0.09 s 
     iterations: 7 
  
  A (cluster membership matrix): 
       Cl1 Cl2 Cl3
  [1,]   1   1   0
  [ 20  rows were omitted ]
  
  C (profiles in terms of components - cluster by component): 
      Comp1 Comp2
  Cl1 21.44 33.67
  [ 2  rows were omitted ]
  
  B' (components by variables):  
        Air.Flow Water.Temp Acid.Conc. stack.loss
  Comp1     0.49       0.18       0.85       0.03
  Comp2     0.45       0.11      -0.32       0.83
  Cluster sizes and overlaps:
       [,1] [,2] [,3]
  [1,]   13    3   10
  [2,]    3   11    0
  [3,]   10    0   10
   (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.   :110.7   Min.   :16.06  
   Mean   :112.9   Mean   :22.11  
   Max.   :120.2   Max.   :42.27  
  Cl2 
       Comp1           Comp2       
   Min.   : 98.8   Min.   : 8.596  
   Mean   :104.6   Mean   :17.780  
   Max.   :120.2   Max.   :42.270  
  Cl3 
       Comp1           Comp2      
   Min.   :110.7   Min.   :16.06  
   Mean   :110.7   Mean   :16.06  
   Max.   :110.7   Max.   :16.06  
  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: 0.09 s 
     iterations: 7 
  
  A (cluster membership matrix): 
       Cl1 Cl2 Cl3
  [1,]   1   1   0
  [ 20  rows were omitted ]
  
  C (profiles in terms of components - cluster by component): 
      Comp1 Comp2
  Cl1 21.44 33.67
  [ 2  rows were omitted ]
  
  B' (components by variables):  
        Air.Flow Water.Temp Acid.Conc. stack.loss
  Comp1     0.49       0.18       0.85       0.03
  Comp2     0.45       0.11      -0.32       0.83
  Cluster sizes and overlaps:
       [,1] [,2] [,3]
  [1,]   13    3   10
  [2,]    3   11    0
  [3,]   10    0   10
   (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.   :110.7   Min.   :16.06  
   Mean   :112.9   Mean   :22.11  
   Max.   :120.2   Max.   :42.27  
  Cl2 
       Comp1           Comp2       
   Min.   : 98.8   Min.   : 8.596  
   Mean   :104.6   Mean   :17.780  
   Max.   :120.2   Max.   :42.270  
  Cl3 
       Comp1           Comp2      
   Min.   :110.7   Min.   :16.06  
   Mean   :110.7   Mean   :16.06  
   Max.   :110.7   Max.   :16.06  
  [ FAIL 0 | WARN 0 | SKIP 0 | PASS 64 ]
  > 
  > proc.time()
     user  system elapsed 
    12.82    1.09   13.89