R Under development (unstable) (2024-08-16 r87026 ucrt) -- "Unsuffered Consequences"
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> # 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
total time: 0.06 s
number of total starts: 6
Results Best Run:
explained variance: 0.976
time: 0.02 s
iterations to convergence: 2
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
total time: 0.05 s
number of total starts: 6
Results Best Run:
explained variance: 0.988
time: 0 s
iterations to convergence: 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
total time: 0.06 s
number of total starts: 6
Results Best Run:
explained variance: 0.98
time: 0.02 s
iterations to convergence: 2
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
total time: 0.06 s
number of total starts: 6
Results Best Run:
explained variance: 0.98
time: 0.02 s
iterations to convergence: 2
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
total time: 0.05 s
number of total starts: 6
Results Best Run:
explained variance: 0.99
time: 0 s
iterations to convergence: 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
total time: 0.05 s
number of total starts: 6
Results Best Run:
explained variance: 0.99
time: 0 s
iterations to convergence: 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
total time: 0.05 s
number of total starts: 6
Results Best Run:
explained variance: 0.98
time: 0.02 s
iterations to convergence: 2
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] [,3]
[1,] 21 3 0
[2,] 3 3 0
[3,] 0 0 0
(diagonal entries: number of observations in a cluster)
(off-diagonal entry [i,j]: number of observations both in cluster i and j)
(last row/column represents additional baseline cluster)
Summary statistics of approximated model variables per cluster:
Cl1
Air.Flow Water.Temp Acid.Conc. stack.loss
Min 57.44 20.22 85.83 14.00
Mean 60.43 21.10 86.29 17.52
Max 78.33 26.33 89.00 38.67
Cl2
Air.Flow Water.Temp Acid.Conc. stack.loss
Min 78.33 26.33 89 38.67
Mean 78.33 26.33 89 38.67
Max 78.33 26.33 89 38.67
Low Dimensional ADPROCLUS solution
number of clusters: 3
number of components: 2
data format: 21 x 4
total time: 0.05 s
number of total starts: 6
Results Best Run:
explained variance: 0.99
time: 0 s
iterations to convergence: 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] [,4]
[1,] 13 3 10 0
[2,] 3 11 0 0
[3,] 10 0 10 0
[4,] 0 0 0 0
(diagonal entries: number of observations in a cluster)
(off-diagonal entry [i,j]: number of observations both in cluster i and j)
(last row/column represents additional baseline cluster)
Summary statistics of approximated low dimensional components per cluster:
Cl1
Comp1 Comp2
Min 110.68 16.06
Mean 112.89 22.11
Max 120.24 42.27
Cl2
Comp1 Comp2
Min 98.80 8.60
Mean 104.65 17.78
Max 120.24 42.27
Cl3
Comp1 Comp2
Min 110.68 16.06
Mean 110.68 16.06
Max 110.68 16.06
ADPROCLUS solution
Setup:
number of clusters: 2
data format: 21 x 4
total time: 0.05 s
number of total starts: 6
Results Best Run:
explained variance: 0.98
time: 0.02 s
iterations to convergence: 2
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] [,3]
[1,] 21 3 0
[2,] 3 3 0
[3,] 0 0 0
(diagonal entries: number of observations in a cluster)
(off-diagonal entry [i,j]: number of observations both in cluster i and j)
(last row/column represents additional baseline cluster)
Summary statistics of approximated model variables per cluster:
Cl1
Air.Flow Water.Temp Acid.Conc. stack.loss
Min 57.44 20.22 85.83 14.00
Mean 60.43 21.10 86.29 17.52
Max 78.33 26.33 89.00 38.67
Cl2
Air.Flow Water.Temp Acid.Conc. stack.loss
Min 78.33 26.33 89 38.67
Mean 78.33 26.33 89 38.67
Max 78.33 26.33 89 38.67
ADPROCLUS solution
Setup:
number of clusters: 2
data format: 21 x 4
total time: 0.05 s
number of total starts: 6
Results Best Run:
explained variance: 0.98
time: 0.02 s
iterations to convergence: 2
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] [,3]
[1,] 21 3 0
[2,] 3 3 0
[3,] 0 0 0
(diagonal entries: number of observations in a cluster)
(off-diagonal entry [i,j]: number of observations both in cluster i and j)
(last row/column represents additional baseline cluster)
Summary statistics of approximated model variables per cluster:
Cl1
Air.Flow Water.Temp Acid.Conc. stack.loss
Min 57.44 20.22 85.83 14.00
Mean 60.43 21.10 86.29 17.52
Max 78.33 26.33 89.00 38.67
Cl2
Air.Flow Water.Temp Acid.Conc. stack.loss
Min 78.33 26.33 89 38.67
Mean 78.33 26.33 89 38.67
Max 78.33 26.33 89 38.67
Low Dimensional ADPROCLUS solution
number of clusters: 3
number of components: 2
data format: 21 x 4
total time: 0.05 s
number of total starts: 6
Results Best Run:
explained variance: 0.99
time: 0 s
iterations to convergence: 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] [,4]
[1,] 13 3 10 0
[2,] 3 11 0 0
[3,] 10 0 10 0
[4,] 0 0 0 0
(diagonal entries: number of observations in a cluster)
(off-diagonal entry [i,j]: number of observations both in cluster i and j)
(last row/column represents additional baseline cluster)
Summary statistics of approximated low dimensional components per cluster:
Cl1
Comp1 Comp2
Min 110.68 16.06
Mean 112.89 22.11
Max 120.24 42.27
Cl2
Comp1 Comp2
Min 98.80 8.60
Mean 104.65 17.78
Max 120.24 42.27
Cl3
Comp1 Comp2
Min 110.68 16.06
Mean 110.68 16.06
Max 110.68 16.06
Low Dimensional ADPROCLUS solution
number of clusters: 3
number of components: 2
data format: 21 x 4
total time: 0.05 s
number of total starts: 6
Results Best Run:
explained variance: 0.99
time: 0 s
iterations to convergence: 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] [,4]
[1,] 13 3 10 0
[2,] 3 11 0 0
[3,] 10 0 10 0
[4,] 0 0 0 0
(diagonal entries: number of observations in a cluster)
(off-diagonal entry [i,j]: number of observations both in cluster i and j)
(last row/column represents additional baseline cluster)
Summary statistics of approximated low dimensional components per cluster:
Cl1
Comp1 Comp2
Min 110.68 16.06
Mean 112.89 22.11
Max 120.24 42.27
Cl2
Comp1 Comp2
Min 98.80 8.60
Mean 104.65 17.78
Max 120.24 42.27
Cl3
Comp1 Comp2
Min 110.68 16.06
Mean 110.68 16.06
Max 110.68 16.06
[ FAIL 0 | WARN 0 | SKIP 0 | PASS 75 ]
>
> proc.time()
user system elapsed
8.89 0.78 9.67