def testClusteringSampleSimple1EuclideanSquare(self): ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 1.0, 2.0, [5, 5], True, metric=distance_metric(type_metric.EUCLIDEAN_SQUARE)); ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 10.0, 20.0, [5, 5], True, metric=distance_metric(type_metric.EUCLIDEAN_SQUARE)); ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 100.0, 200.0, [10], True, metric=distance_metric(type_metric.EUCLIDEAN_SQUARE));
def testClusteringSampleSimple1Euclidean(self): ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 1.0, 2.0, [5, 5], True, metric=distance_metric(type_metric.EUCLIDEAN)); ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 10.0, 20.0, [10], True, metric=distance_metric(type_metric.EUCLIDEAN));
def testOneDimentionalPoints2(self): ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE9, 1.0, 2.0, [10, 20], False); ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE9, 10.0, 20.0, [30], False);
def testTheSamePoints1(self): ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE12, 1.0, 1.5, [5, 5, 5], False); ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE12, 0.001, 0.002, [5, 5, 5], False); ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE12, 1000, 2000, [15], False);
def testClusteringSampleSimple1Manhattan(self): ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 1.0, 2.0, [5, 5], False, metric=distance_metric(type_metric.MANHATTAN)); ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 10.0, 20.0, [10], False, metric=distance_metric(type_metric.MANHATTAN));
def testClusteringSampleSimple2(self): ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE2, 1.0, 2.0, [5, 8, 10], False); ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE2, 10.0, 20.0, [23], False);
def testOneDimentionalPoints2(self): ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE9, 1.0, 2.0, [10, 20], True) ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE9, 10.0, 20.0, [30], True)
def testClusteringSampleSimple1(self): ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 1.0, 2.0, [5, 5], False); ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 10.0, 20.0, [10], False);
def testTheSamePoints1(self): ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE12, 1.0, 1.5, [5, 5, 5], True); ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE12, 0.001, 0.002, [5, 5, 5], True); ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE12, 1000, 2000, [15], True);
def runRemovedLibraryCoreTest(self): ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 1.0, 2.0, [5, 5], True)
def testOneDimentionalPoints1(self): ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE7, 1.0, 2.0, [10, 10], True); ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE7, 10.0, 20.0, [20], True);
def testClusteringSampleSimple1Chebyshev(self): ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 1.0, 2.0, [5, 5], True, metric=distance_metric(type_metric.CHEBYSHEV)); ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 10.0, 20.0, [10], True, metric=distance_metric(type_metric.CHEBYSHEV));
def testClusteringSampleSimple1Manhattan(self): ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 1.0, 2.0, [5, 5], True, metric=distance_metric(type_metric.MANHATTAN)); ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 10.0, 20.0, [10], True, metric=distance_metric(type_metric.MANHATTAN));
def testOneDimentionalPoints1(self): ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE7, 1.0, 2.0, [10, 10], True); ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE7, 10.0, 20.0, [20], True);
def testThreeDimentionalPoints(self): ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE11, 1.0, 2.0, [10, 10], True) ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE11, 10.0, 20.0, [20], True)
def testProcessingWhenLibraryCoreCorrupted(self): ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 1.0, 2.0, [5, 5], True);
def testTheSamePoints2(self): ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE9, 1.0, 2.0, [10, 20], True) ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE9, 10.0, 20.0, [30], True)
def testClusteringSampleSimple1EuclideanSquare(self): ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 1.0, 2.0, [5, 5], False, metric=distance_metric(type_metric.EUCLIDEAN_SQUARE)); ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 10.0, 20.0, [5, 5], False, metric=distance_metric(type_metric.EUCLIDEAN_SQUARE)); ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 100.0, 200.0, [10], False, metric=distance_metric(type_metric.EUCLIDEAN_SQUARE));
def testProcessingWhenLibraryCoreCorrupted(self): ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 1.0, 2.0, [5, 5], True)
def testClusteringSampleSimple1Chebyshev(self): ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 1.0, 2.0, [5, 5], False, metric=distance_metric(type_metric.CHEBYSHEV)); ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 10.0, 20.0, [10], False, metric=distance_metric(type_metric.CHEBYSHEV));
def testClusteringSampleSimple1(self): ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 1.0, 2.0, [5, 5], True) ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 10.0, 20.0, [10], True)
def testClusteringSampleSimple3(self): ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE3, 1.0, 2.0, [10, 10, 10, 30], False); ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE3, 10.0, 20.0, [60], False);
def testClusteringSampleSimple2(self): ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE2, 1.0, 2.0, [5, 8, 10], True) ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE2, 10.0, 20.0, [23], True)
def testThreeDimentionalPoints(self): ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE11, 1.0, 2.0, [10, 10], False); ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE11, 10.0, 20.0, [20], False);
def testClusteringSampleSimple3(self): ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE3, 1.0, 2.0, [10, 10, 10, 30], True) ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE3, 10.0, 20.0, [60], True)
def testTheSamePoints2(self): ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE9, 1.0, 2.0, [10, 20], False); ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE9, 10.0, 20.0, [30], False);
def testClusteringSampleSimple1Euclidean(self): ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 1.0, 2.0, [5, 5], False, metric=distance_metric(type_metric.EUCLIDEAN)); ttsas_test.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 10.0, 20.0, [10], False, metric=distance_metric(type_metric.EUCLIDEAN));