"""! @brief Integration-tests for K-Medians 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.kmedians_templates import KmediansTestTemplates from pyclustering.cluster.kmedians import kmedians 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 type_metric, distance_metric class KmediansIntegrationTest(unittest.TestCase): def testClusterAllocationSampleSimple1Core(self): KmediansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, [[3.7, 5.5], [6.7, 7.5]], [5, 5], True) def testClusterAllocationSampleSimple1EuclideanCore(self): metric = distance_metric(type_metric.EUCLIDEAN) KmediansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, [[3.7, 5.5], [6.7, 7.5]], [5, 5], True, metric=metric) def testClusterAllocationSampleSimple1EuclideanSquareCore(self): metric = distance_metric(type_metric.EUCLIDEAN_SQUARE) KmediansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, [[3.7, 5.5], [6.7, 7.5]], [5, 5], True, metric=metric) def testClusterAllocationSampleSimple1ManhattanCore(self): metric = distance_metric(type_metric.MANHATTAN) KmediansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, [[3.7, 5.5], [6.7, 7.5]], [5, 5], True, metric=metric) def testClusterAllocationSampleSimple1ChebyshevCore(self): metric = distance_metric(type_metric.CHEBYSHEV) KmediansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, [[3.7, 5.5], [6.7, 7.5]], [5, 5], True, metric=metric) def testClusterAllocationSampleSimple1MinkowskiCore(self): metric = distance_metric(type_metric.MINKOWSKI, degree=2.0) KmediansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, [[3.7, 5.5], [6.7, 7.5]], [5, 5], True, metric=metric) def testClusterAllocationSampleSimple1UserDefinedCore(self): metric = distance_metric(type_metric.USER_DEFINED, func=distance_metric(type_metric.EUCLIDEAN)) KmediansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, [[3.7, 5.5], [6.7, 7.5]], [5, 5], True, metric=metric) def testClusterOneAllocationSampleSimple1Core(self): KmediansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, [[1.0, 2.5]], [10], True) def testClusterAllocationSampleSimple2Core(self): KmediansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE2, [[3.5, 4.8], [6.9, 7], [7.5, 0.5]], [10, 5, 8], True) def testClusterOneAllocationSampleSimple2Core(self): KmediansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE2, [[0.5, 0.2]], [23], True) def testClusterAllocationSampleSimple3Core(self): KmediansTestTemplates.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 testClusterOneAllocationSampleSimple3Core(self): KmediansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE3, [[0.2, 0.1]], [60], True) def testClusterAllocationSampleSimple5Core(self): KmediansTestTemplates.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 testClusterOneAllocationSampleSimple5Core(self): KmediansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE5, [[0.0, 0.0]], [60], True) def testClusterAllocationSample1NumpyArrayUserDefined(self): metric = distance_metric(type_metric.USER_DEFINED, func=distance_metric(type_metric.EUCLIDEAN)) input_data = numpy.array(read_sample(SIMPLE_SAMPLES.SAMPLE_SIMPLE1)) initial_centers = numpy.array([[3.7, 5.5], [6.7, 7.5]]) KmediansTestTemplates.templateLengthProcessData(input_data, initial_centers, [5, 5], True, metric=metric) def testClusterAllocationSample2NumpyArrayUserDefined(self): metric = distance_metric(type_metric.USER_DEFINED, func=distance_metric(type_metric.EUCLIDEAN_SQUARE)) input_data = numpy.array(read_sample(SIMPLE_SAMPLES.SAMPLE_SIMPLE2)) initial_centers = numpy.array([[3.5, 4.8], [6.9, 7], [7.5, 0.5]]) KmediansTestTemplates.templateLengthProcessData(input_data, initial_centers, [10, 5, 8], True, metric=metric) def testClusterAllocationSample1WrongInitialNumberCenters1Core(self): KmediansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, [[2.8, 9.5], [3.5, 6.6], [1.3, 4.0]], None, True) def testClusterAllocationSample1WrongInitialNumberCenters2Core(self): KmediansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, [[2.8, 9.5], [3.5, 6.6], [1.3, 4.0], [1.2, 4.5]], None, True) def testClusterAllocationSample2WrongInitialNumberCentersCore(self): KmediansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE2, [[3.5, 4.8], [6.9, 7], [7.5, 0.5], [7.3, 4.5], [3.1, 5.4]], None, True) def testClusterTheSameData1Core(self): KmediansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE9, [ [4.1], [7.3] ], [10, 20], True) def testClusterTheSameData2Core(self): KmediansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE12, [ [1.1, 1.0], [3.0, 3.1], [5.0, 4.9] ], [5, 5, 5], True) def testOddSize(self): # Bug issue #428 (https://github.com/annoviko/pyclustering/issues/428) data = [[59.00732, 9.748167], [59.00608, 9.749117], [59.0047, 9.749933]] KmediansTestTemplates.templateLengthProcessData(data, [[59.00732, 9.748167], [59.00608, 9.749117]], None, True, tolerance=10) def testClusterAllocationOneDimensionDataCore(self): KmediansTestTemplates.templateClusterAllocationOneDimensionData(True) def testClusterAllocationTheSameObjectsOneInitialCenterCore(self): KmediansTestTemplates.templateClusterAllocationTheSameObjects(20, 1, True) def testClusterAllocationTheSameObjectsTwoInitialCentersCore(self): KmediansTestTemplates.templateClusterAllocationTheSameObjects(15, 2, True) def testClusterAllocationTheSameObjectsThreeInitialCentersCore(self): KmediansTestTemplates.templateClusterAllocationTheSameObjects(25, 3, True) def testClusterAllocationSampleRoughMediansSimple10ByCore(self): initial_medians = [[0.0772944481804071, 0.05224990900863469], [1.6021689021213712, 1.0347579135245601], [2.3341008076636096, 1.280022869739064]] KmediansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE10, initial_medians, None, True) def testCoreInterfaceIntInputData(self): kmedians_instance = kmedians([ [1], [2], [3], [20], [21], [22] ], [ [2], [21] ], ccore=True) kmedians_instance.process() assert len(kmedians_instance.get_clusters()) == 2 @remove_library def testProcessingWhenLibraryCoreCorrupted(self): KmediansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, [[3.7, 5.5], [6.7, 7.5]], [5, 5], True) def testItermax0ByCore(self): KmediansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, [[3.7, 5.5], [6.7, 7.5]], [], True, itermax=0) def testItermax1ByCore(self): KmediansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, [[3.7, 5.5], [6.7, 7.5]], [5, 5], True, itermax=1) def testItermax10Simple01ByCore(self): KmediansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, [[3.7, 5.5], [6.7, 7.5]], [5, 5], True, itermax=10) def testItermax10Simple02ByCore(self): KmediansTestTemplates.templateLengthProcessData(SIMPLE_SAMPLES.SAMPLE_SIMPLE2, [[3.5, 4.8], [6.9, 7], [7.5, 0.5]], [10, 5, 8], True, itermax=10)