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