ParaMonte Fortran 2.0.0
Parallel Monte Carlo and Machine Learning Library
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Data Types | |
type | test_pm_clustering::TestData_type |
Modules | |
module | test_pm_clustering |
This module contains tests of the module pm_clustering. | |
Functions/Subroutines | |
subroutine | test_pm_clustering::setTest () |
subroutine | test_pm_clustering::readTestData (TestData) |
logical(LK) function | test_pm_clustering::test_runKmeans_1 () |
logical(LK) function | test_pm_clustering::test_runKmeans_2 () |
test setKmeans() by passing a fixed initial set of cluster centers to the Kmeans constructor. More... | |
logical(LK) function | test_pm_clustering::test_runKmeans_3 () |
If the optional input argument niterMax is specified, the output value for niter must not go beyond in the input value. In addition, if the specified value for niterMax has reached, the procedure must return with error stat code of 1 . More... | |
logical(LK) function | test_pm_clustering::test_runKmeans_4 () |
The function setKmeans() must function properly for reasonable optional input values of nfailMax and relTol . More... | |
logical(LK) function | test_pm_clustering::test_setKmeans_1 () |
test setKmeans() by passing a number of tries to find the more optimal Kmeans clustering. More... | |
logical(LK) function | test_pm_clustering::test_setKmeans_2 () |
The component index must be properly set by pm_clustering::setKmeans when it is given as input. More... | |
logical(LK) function | test_pm_clustering::test_setKmeans_3 () |
The component index must be properly set by pm_clustering::setKmeans when it is given as input. More... | |
logical(LK) function | test_pm_clustering::test_setKmeans_4 () |
When the pointLogVolNormed is missing, the properties of singular clusters must be correctly computed from the properties of non-singular clusters. More... | |
logical(LK) function | test_pm_clustering::test_benchmark_1 () |
Calling the Kmeans routine repeatedly should not cause any errors. This test is also used for benchmarking the performances of different implementations of the Kmeans algorithm. More... | |
Variables | |
type(test_type) | test_pm_clustering::test |
type(TestData_type) | test_pm_clustering::TestData |