"""! @brief Integration-tests for K-Means algorithm. @authors Andrei Novikov (pyclustering@yandex.ru) @date 2014-2020 @copyright BSD-3-Clause """ import unittest import numpy import matplotlib matplotlib.use('Agg') from pyclustering.cluster.tests.kmeans_templates import KmeansTestTemplates from pyclustering.cluster.kmeans import kmeans from pyclustering.samples.definitions import SIMPLE_SAMPLES from pyclustering.core.tests import remove_library from pyclustering.utils import read_sample from pyclustering.utils.metric import distance_metric, type_metric class KmeansIntegrationTest(unittest.TestCase): def testClusterAllocationSampleSimple1ByCore(self): KmeansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, [[3.7, 5.5], [6.7, 7.5]], [5, 5], True) def testClusterOneAllocationSampleSimple1ByCore(self): KmeansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, [[1.0, 2.5]], [10], True) def testClusterAllocationSampleSimple1EuclideanByCore(self): metric = distance_metric(type_metric.EUCLIDEAN) KmeansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, [[3.7, 5.5], [6.7, 7.5]], [5, 5], True, metric=metric) def testClusterAllocationSampleSimple1EuclideanSquareByCore(self): metric = distance_metric(type_metric.EUCLIDEAN_SQUARE) KmeansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, [[3.7, 5.5], [6.7, 7.5]], [5, 5], True, metric=metric) def testClusterAllocationSampleSimple1ManhattanByCore(self): metric = distance_metric(type_metric.MANHATTAN) KmeansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, [[3.7, 5.5], [6.7, 7.5]], [5, 5], True, metric=metric) def testClusterAllocationSampleSimple1ChebyshevByCore(self): metric = distance_metric(type_metric.CHEBYSHEV) KmeansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, [[3.7, 5.5], [6.7, 7.5]], [5, 5], True, metric=metric) def testClusterAllocationSampleSimple1Minkowski01ByCore(self): metric = distance_metric(type_metric.MINKOWSKI, degree=2) KmeansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, [[3.7, 5.5], [6.7, 7.5]], [5, 5], True, metric=metric) def testClusterAllocationSampleSimple1Minkowski02ByCore(self): metric = distance_metric(type_metric.MINKOWSKI, degree=4) KmeansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, [[3.7, 5.5], [6.7, 7.5]], [5, 5], True, metric=metric) def testClusterAllocationSampleSimple1UserDefinedByCore(self): metric = distance_metric(type_metric.USER_DEFINED, func=distance_metric(type_metric.EUCLIDEAN)) KmeansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, [[3.7, 5.5], [6.7, 7.5]], [5, 5], True, metric=metric) def testClusterAllocationSampleSimple1UserDefinedNumPyByCore(self): data = numpy.array(read_sample(SIMPLE_SAMPLES.SAMPLE_SIMPLE1)) centers = numpy.array([[3.7, 5.5], [6.7, 7.5]]) metric = distance_metric(type_metric.USER_DEFINED, func=distance_metric(type_metric.EUCLIDEAN)) KmeansTestTemplates.templateLengthProcessData(data, centers, [5, 5], True, metric=metric) def testClusterAllocationSampleSimple1Canberra(self): metric = distance_metric(type_metric.CANBERRA) KmeansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, [[3.7, 5.5], [6.7, 7.5]], [5, 5], True, metric=metric) def testClusterAllocationSampleSimple1ChiSquare(self): metric = distance_metric(type_metric.CHI_SQUARE) KmeansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, [[3.7, 5.5], [6.7, 7.5]], [5, 5], True, metric=metric) def testClusterAllocationSampleSimple2ByCore(self): KmeansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE2, [[3.5, 4.8], [6.9, 7], [7.5, 0.5]], [10, 5, 8], True) def testClusterOneAllocationSampleSimple2ByCore(self): KmeansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE2, [[0.5, 0.2]], [23], True) def testClusterAllocationSampleSimple2UserDefinedByCore(self): metric = distance_metric(type_metric.USER_DEFINED, func=distance_metric(type_metric.EUCLIDEAN)) KmeansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE2, [[3.5, 4.8], [6.9, 7], [7.5, 0.5]], [10, 5, 8], True, metric=metric) def testClusterAllocationSampleSimple2UserDefinedNumPyByCore(self): data = numpy.array(read_sample(SIMPLE_SAMPLES.SAMPLE_SIMPLE2)) centers = numpy.array([[3.5, 4.8], [6.9, 7], [7.5, 0.5]]) metric = distance_metric(type_metric.USER_DEFINED, func=distance_metric(type_metric.EUCLIDEAN)) KmeansTestTemplates.templateLengthProcessData(data, centers, [10, 5, 8], True, metric=metric) def testClusterAllocationSampleSimple3ByCore(self): KmeansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE3, [[0.2, 0.1], [4.0, 1.0], [2.0, 2.0], [2.3, 3.9]], [10, 10, 10, 30], True) def testClusterOneAllocationSampleSimple3ByCore(self): KmeansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE3, [[0.2, 0.1]], [60], True) def testClusterAllocationSampleSimple4ByCore(self): KmeansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE4, [[1.5, 0.0], [1.5, 2.0], [1.5, 4.0], [1.5, 6.0], [1.5, 8.0]], [15, 15, 15, 15, 15], True) def testClusterOneAllocationSampleSimple4ByCore(self): KmeansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE4, [[2.0, 5.0]], [75], True) def testClusterAllocationSampleSimple5ByCore(self): KmeansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE5, [[0.0, 1.0], [0.0, 0.0], [1.0, 1.0], [1.0, 0.0]], [15, 15, 15, 15], True) def testClusterOneAllocationSampleSimple5ByCore(self): KmeansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE5, [[0.0, 0.0]], [60], True) def testClusterAllocationSampleSimple5Canberra(self): metric = distance_metric(type_metric.CANBERRA) KmeansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE5, [[0.0, 1.0], [0.0, 0.0], [1.0, 1.0], [1.0, 0.0]], [30, 30], True, metric=metric) def testClusterAllocationSampleSimple5ChiSquare(self): metric = distance_metric(type_metric.CHI_SQUARE) KmeansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE5, [[3.4, 2.6], [3.4, -3.2], [-3.4, -3.4], [-3.1, 3.3]], [15, 15, 15, 15], True, metric=metric) def testClusterOneDimensionSampleSimple7ByCore(self): KmeansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE7, [[-3.0], [2.0]], [10, 10], True) def testClusterOneDimensionSampleSimple8ByCore(self): KmeansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE8, [[-4.0], [3.1], [6.1], [12.0]], [15, 30, 20, 80], True) def testWrongNumberOfCentersSimpleSample1ByCore(self): KmeansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, [[2.0, 4.5], [3.3, 6.5], [5.0, 7.8]], None, True) def testWrongNumberOfCentersSimpleSample2ByCore(self): KmeansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE2, [[1.3, 1.5], [5.2, 8.5], [5.0, 7.8], [11.0, -3.0]], None, True) def testTheSameData1ByCore(self): KmeansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE9, [ [4.0], [8.0] ], [10, 20], True) def testTheSameData2ByCore(self): KmeansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE12, [ [1.0, 1.0], [2.5, 2.5], [4.0, 4.0] ], [5, 5, 5], True) def testClusterAllocationOneDimensionDataByCore(self): KmeansTestTemplates.templateClusterAllocationOneDimensionData(True) def testEncoderProcedureSampleSimple4ByCore(self): KmeansTestTemplates.templateEncoderProcedures(SIMPLE_SAMPLES.SAMPLE_SIMPLE4, [[1.5, 0.0], [1.5, 2.0], [1.5, 4.0], [1.5, 6.0], [1.5, 8.0]], 5, True) def testCoreInterfaceIntInputData(self): kmeans_instance = kmeans([ [1], [2], [3], [20], [21], [22] ], [ [2], [21] ], 0.025, True) kmeans_instance.process() assert len(kmeans_instance.get_clusters()) == 2 def testObserveSampleSimple1ByCore(self): KmeansTestTemplates.templateCollectEvolution(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, [[3.5, 5.6], [6.8, 7.4]], [5, 5], True) def testObserveSampleSimple1OneClusterByCore(self): KmeansTestTemplates.templateCollectEvolution(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, [[3.3, 5.4]], [10], True) def testObserveSampleSimple2ByCore(self): KmeansTestTemplates.templateCollectEvolution(SIMPLE_SAMPLES.SAMPLE_SIMPLE2, [[3.4, 4.9], [6.8, 7.1], [7.6, 0.4]], [10, 5, 8], True) def testItermax0ByCore(self): KmeansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, [[3.7, 5.5], [6.7, 7.5]], [], True, itermax=0) def testItermax1ByCore(self): KmeansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, [[3.7, 5.5], [6.7, 7.5]], [5, 5], True, itermax=1) def testItermax10Simple01ByCore(self): KmeansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, [[3.7, 5.5], [6.7, 7.5]], [5, 5], True, itermax=10) def testItermax10Simple02ByCore(self): KmeansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE2, [[3.5, 4.8], [6.9, 7], [7.5, 0.5]], [10, 5, 8], True, itermax=10) def testShowResultsSampleSimple01(self): KmeansTestTemplates.templateShowClusteringResultNoFailure(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, [[3.5, 5.6], [6.8, 7.4]], True) def testShowResultsSampleSimple02(self): KmeansTestTemplates.templateShowClusteringResultNoFailure(SIMPLE_SAMPLES.SAMPLE_SIMPLE2, [[3.4, 4.9], [6.8, 7.1], [7.6, 0.4]], True) def testShowResultsOneDimensionalData(self): KmeansTestTemplates.templateShowClusteringResultNoFailure(SIMPLE_SAMPLES.SAMPLE_SIMPLE8, [[-2.0], [3.0], [6.0], [12.0]], True) def testShowResultsThreeDimensionalData(self): KmeansTestTemplates.templateShowClusteringResultNoFailure(SIMPLE_SAMPLES.SAMPLE_SIMPLE11, [[1.0, 0.6, 0.8], [4.1, 4.2, 4.3]], True) def testAnimateResultsSampleSimple01(self): KmeansTestTemplates.templateAnimateClusteringResultNoFailure(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, [[3.5, 5.6], [6.8, 7.4]], True) def testAnimateResultsSampleSimple02(self): KmeansTestTemplates.templateAnimateClusteringResultNoFailure(SIMPLE_SAMPLES.SAMPLE_SIMPLE2, [[3.4, 4.9], [6.8, 7.1], [7.6, 0.4]], True) def testAnimateResultsOneDimensionalData(self): KmeansTestTemplates.templateAnimateClusteringResultNoFailure(SIMPLE_SAMPLES.SAMPLE_SIMPLE8, [[-2.0], [3.0], [6.0], [12.0]], True) def testAnimateResultsThreeDimensionalData(self): KmeansTestTemplates.templateAnimateClusteringResultNoFailure(SIMPLE_SAMPLES.SAMPLE_SIMPLE11, [[1.0, 0.6, 0.8], [4.1, 4.2, 4.3]], True) @remove_library def testProcessingWhenLibraryCoreCorrupted(self): KmeansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, [[3.7, 5.5], [6.7, 7.5]], [5, 5], True)