def testClusteringSampleSimple1Euclidean(self): bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 2, 1.0, [5, 5], True, metric=distance_metric( type_metric.EUCLIDEAN)) bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 2, 10.0, [10], True, metric=distance_metric( type_metric.EUCLIDEAN))
def testClusteringSampleSimple1Chebyshev(self): bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 2, 1.0, [5, 5], True, metric=distance_metric( type_metric.CHEBYSHEV)) bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 2, 10.0, [10], True, metric=distance_metric( type_metric.CHEBYSHEV))
def testClusteringSampleSimple1Manhattan(self): bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 2, 1.0, [5, 5], True, metric=distance_metric( type_metric.MANHATTAN)) bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 2, 10.0, [10], True, metric=distance_metric( type_metric.MANHATTAN))
def testClusteringSampleSimple1(self): bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 2, 1.0, [5, 5], True) bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 10, 1.0, [5, 5], True) bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 2, 10.0, [10], True) bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 1, 1.0, [10], True)
def testTheSamePoints1(self): bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE12, 3, 1.0, [5, 5, 5], True) bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE12, 30, 1.0, [5, 5, 5], True) bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE12, 3, 10.0, [15], True) bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE12, 1, 1.0, [15], True)
def testClusteringSampleSimple3(self): bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE3, 4, 1.0, [2, 8, 20, 30], True) bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE3, 4, 2.0, [10, 10, 10, 30], True) bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE3, 4, 10.0, [60], True)
def testClusteringSampleSimple1EuclideanSquare(self): bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 2, 1.0, [5, 5], False, metric=distance_metric( type_metric.EUCLIDEAN_SQUARE)) bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 2, 10.0, [5, 5], False, metric=distance_metric( type_metric.EUCLIDEAN_SQUARE)) bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 2, 100.0, [10], False, metric=distance_metric( type_metric.EUCLIDEAN_SQUARE))
def testThreeDimentionalPoints(self): bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE11, 2, 1.0, [10, 10], True) bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE11, 2, 10.0, [20], True)
def testOneDimentionalPoints2(self): bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE9, 2, 1.0, [10, 20], True) bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE9, 2, 10.0, [30], True)
def testOneDimentionalPoints1(self): bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE7, 2, 1.0, [10, 10], False) bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE7, 2, 10.0, [20], False)
def testClusteringSampleSimple1EuclideanSquare(self): bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 2, 1.0, [5, 5], True, metric=distance_metric(type_metric.EUCLIDEAN_SQUARE)); bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 2, 10.0, [5, 5], True, metric=distance_metric(type_metric.EUCLIDEAN_SQUARE)); bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 2, 100.0, [10], True, metric=distance_metric(type_metric.EUCLIDEAN_SQUARE));
def testProcessingWhenLibraryCoreCorrupted(self): bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 2, 1.0, [5, 5], True)
def testProcessingWhenLibraryCoreCorrupted(self): bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 2, 1.0, [5, 5], True);
def testOneDimentionalPoints2(self): bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE9, 2, 1.0, [10, 20], True); bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE9, 2, 10.0, [30], True);
def testClusteringSampleSimple3(self): bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE3, 4, 1.0, [2, 8, 20, 30], True); bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE3, 4, 2.0, [10, 10, 10, 30], True); bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE3, 4, 10.0, [60], True);
def testClusteringSampleSimple2(self): bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE2, 3, 1.0, [5, 8, 10], True); bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE2, 3, 10.0, [23], True);
def testClusteringSampleSimple1Chebyshev(self): bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 2, 1.0, [5, 5], True, metric=distance_metric(type_metric.CHEBYSHEV)); bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 2, 10.0, [10], True, metric=distance_metric(type_metric.CHEBYSHEV));
def testClusteringSampleSimple1Manhattan(self): bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 2, 1.0, [5, 5], True, metric=distance_metric(type_metric.MANHATTAN)); bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 2, 10.0, [10], True, metric=distance_metric(type_metric.MANHATTAN));
def runRemovedLibraryCoreTest(self): bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 2, 1.0, [5, 5], True)
def testTheSamePoints2(self): bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE9, 3, 1.0, [10, 20], True) bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE9, 3, 10.0, [30], True)
def testOneDimentionalPoints1(self): bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE7, 2, 1.0, [10, 10], False); bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE7, 2, 10.0, [20], False);
def testThreeDimentionalPoints(self): bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE11, 2, 1.0, [10, 10], True); bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE11, 2, 10.0, [20], True);
def testClusteringSampleSimple1(self): bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 2, 1.0, [5, 5], True); bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 10, 1.0, [5, 5], True); bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 2, 10.0, [10], True); bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 1, 1.0, [10], True);
def testTheSamePoints1(self): bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE12, 3, 1.0, [5, 5, 5], True); bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE12, 30, 1.0, [5, 5, 5], True); bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE12, 3, 10.0, [15], True); bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE12, 1, 1.0, [15], True);
def testTheSamePoints2(self): bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE9, 3, 1.0, [10, 20], True); bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE9, 3, 10.0, [30], True);
def testClusteringSampleSimple2(self): bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE2, 3, 1.0, [5, 8, 10], True) bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE2, 3, 10.0, [23], True)
def testClusteringSampleSimple1Euclidean(self): bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 2, 1.0, [5, 5], False, metric=distance_metric(type_metric.EUCLIDEAN)); bsas_test_template.clustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 2, 10.0, [10], False, metric=distance_metric(type_metric.EUCLIDEAN));