def test_modularity_1(self):
measure_list = MeasureParser.list_measures()
A = np.array([[0, 1, 1], [1, 0, 0], [1, 0, 0]])
graph = GraphBU(A, measure_list[GraphBU], 'zero', 'max')
MeasureModularity.compute_measure(graph)
self.assertAlmostEqual(
graph.measure_dict[MeasureModularity]['modularity'], 0, places=4)
def test_bd_2(self):
measure_list = MeasureParser.list_measures()
A = np.array([[0, 1, 1, 1, 0, 1, 0, 0, 0, 1],
[0, 1, 0, 0, 0, 1, 0, 0, 1, 0],
[0, 0, 0, 1, 0, 0, 0, 1, 1, 0],
[1, 0, 1, 0, 1, 0, 1, 1, 1, 0],
[1, 1, 0, 0, 1, 1, 0, 1, 1, 1],
[1, 0, 1, 1, 1, 0, 0, 0, 0, 0],
[1, 1, 0, 0, 1, 1, 0, 1, 1, 1],
[0, 1, 0, 1, 1, 1, 0, 1, 1, 0],
[0, 1, 1, 0, 1, 1, 1, 0, 1, 0],
[1, 0, 1, 0, 1, 1, 0, 1, 1, 0]])
graph = GraphBD(A, measure_list[GraphBD], 'zero')
self.assertAlmostEqual(graph.get_measure(MeasureAssortativity,
'assortativity_out_in'),
-0.0840,
places=4)
self.assertAlmostEqual(graph.get_measure(MeasureAssortativity,
'assortativity_in_out'),
-0.0420,
places=4)
self.assertAlmostEqual(graph.get_measure(MeasureAssortativity,
'assortativity_out_out'),
-0.0810,
places=4)
self.assertAlmostEqual(graph.get_measure(MeasureAssortativity,
'assortativity_in_in'),
-0.1476,
places=4)
def test_graphBU_disconnected(self):
measure_list = MeasureParser.list_measures()
A = np.array([[0, 1, 1, 0], [1, 0, 0, 0], [1, 0, 0, 0], [0, 0, 0, 0]])
graph = GraphBU(A, measure_list[GraphBU], 'zero', 'max')
true_distance = [[0.0, 1.0, 1.0, np.inf], [1.0, 0.0, 2.0, np.inf],
[1.0, 2.0, 0.0, np.inf],
[np.inf, np.inf, np.inf, 0.0]]
self.assertSequenceEqual(graph.D.tolist(), true_distance)
def test_bd(self):
measure_list = MeasureParser.list_measures()
A = np.array([[0, 1, 1], [1, 0, 0], [1, 0, 0]])
graph = GraphBD(A, measure_list[GraphBD], 'zero')
betweenness = [2, 0, 0]
self.assertSequenceEqual(
graph.get_measure(MeasureBetweenness, 'betweenness').tolist(),
betweenness)
def test_graphBD_large(self):
measure_list = MeasureParser.list_measures()
A = np.array([[0, 1, 0, 0, 0], [0, 0, 1, 0, 0], [0, 0, 0, 1, 1],
[0, 0, 1, 0, 0], [1, 0, 0, 0, 0]])
graph = GraphBD(A, measure_list[GraphBU], 'zero')
true_distance = [[0.0, 1.0, 2.0, 3.0, 3.0], [3.0, 0.0, 1.0, 2.0, 2.0],
[2.0, 3.0, 0.0, 1.0, 1.0], [3.0, 4.0, 1.0, 0.0, 2.0],
[1.0, 2.0, 3.0, 4.0, 0.0]]
self.assertSequenceEqual(graph.D.tolist(), true_distance)
def test_graphBU(self):
measure_list = MeasureParser.list_measures()
A = np.array([[0, 1, 0, 0, 0], [0, 0, 1, 0, 0], [0, 0, 0, 1, 1],
[0, 0, 1, 0, 0], [1, 0, 0, 0, 0]])
graph = GraphBU(A, measure_list[GraphBU], 'zero', 'max')
eccentricity = [3, 2, 2, 3, 2]
self.assertSequenceEqual(
graph.get_measure(MeasureEccentricity, 'eccentricity').tolist(),
eccentricity)
def test_graphBU(self):
measure_list = MeasureParser.list_measures()
A = np.array([[1, 0, 1, 1, 1], [0, 1, 1, 0, 1], [1, 0, 1, 1, 1],
[0, 0, 0, 0, 0], [0, 1, 1, 0, 1]])
graph = GraphBU(A, measure_list[GraphBU], 'zero', 'max')
true_path_length = [1.25, 1.5, 1.0, 1.5, 1.25]
self.assertSequenceEqual(
graph.get_measure(MeasurePathLength, 'path_length').tolist(),
true_path_length)
def test_wu(self):
measure_list = MeasureParser.list_measures()
A = np.array([[3.2, 3.14, 2.7, 0.01, 0.0], [3.2, 2.7, 3.14, 6.7, -75],
[13, 0.0, 1.2, 5.7, -0.01],
[5.5, 8.2, 0.3, 0.0005, -0.5], [1, 0.0, 345, 8.7, -2]])
graph = GraphWU(A, measure_list[GraphWU], 'zero', 'max')
self.assertAlmostEqual(
graph.get_measure(MeasureAssortativity, 'assortativity'),
-0.166126077)
def test_bu(self):
measure_list = MeasureParser.list_measures()
A = np.array([[1, 1, 0, 1], [1, 0, 1, 1], [1, 0, 1, 1], [0, 0, 0, 0]])
graph = GraphBU(A, measure_list[GraphBU], 'zero', 'max')
MeasureGlobalEfficiency.compute_measure(graph)
global_efficiency = [1, 1, 1, 1]
test_utility = TestUtility()
test_utility.assertSequenceAlmostEqual(
graph.measure_dict[MeasureGlobalEfficiency]
['global_efficiency'].tolist(), global_efficiency, 4)
def test_graphWU(self):
measure_list = MeasureParser.list_measures()
A = np.array([[3.2, 3.14, 2.7, 0.01, 0.0],
[3.2, 2.7, 3.14, 6.7, 75],
[13, 0.0, 1.2, 5.7, 0.01],
[5.5, 8.2, 0.3, 0.0005, 0.5],
[1, 0.0, 345, 8.7, 2]])
graph = GraphWU(A, measure_list[GraphWU], 'zero', 'max')
path_length = [0.1079, 0.0612, 0.0535, 0.1341, 0.0527]
self.assertSequenceAlmostEqual(graph.get_measure(MeasurePathLength, 'path_length'), path_length, places = 4)
def test_graphWU(self):
measure_list = MeasureParser.list_measures()
A = np.array([[3.2, 3.14, 2.7, 0.01, 0.0], [3.2, 2.7, 3.14, 6.7, 75],
[13, 0.0, 1.2, 5.7, 0.01], [5.5, 8.2, 0.3, 0.0005, 0.5],
[1, 0.0, 345, 8.7, 2]])
graph = GraphWU(A, measure_list[GraphWU], 'null', 'max')
eccentricity = [0.1818, 0.1220, 0.1178, 0.1818, 0.1149]
self.assertSequenceAlmostEqual(graph.get_measure(
MeasureEccentricity, 'eccentricity'),
eccentricity,
places=4)
def test_graphWD(self):
measure_list = MeasureParser.list_measures()
A = np.array([[0.0, 3.14, 2.7, 0.01, 0.0], [3.2, 0.0, 3.14, 6.7, 75],
[13, 0.0, 0.0, 5.7, 0.01], [5.5, 8.2, 0.3, 0.0, 0.5],
[1, 0.0, 345, 8.7, 0.0]])
graph = GraphWD(A, measure_list[GraphWD], 'abs')
eccentricity = [0.4467, 0.3185, 0.3347, 0.4467, 0.3318]
self.assertSequenceAlmostEqual(graph.get_measure(
MeasureEccentricity, 'eccentricity'),
eccentricity,
places=4)
def test_graphWD(self):
measure_list = MeasureParser.list_measures()
A = np.array([[0.0, 0.1, 0.5, 0.4, 0.0], [0.8, 0.0, 0.0, 0.0, 0.0],
[0.5, 0.2, 0.0, 0.4, 0.0], [0.8, 0.1, 0.0, 0.0, 0.0],
[0.0, 0.0, 0.0, 0.0, 0.0]])
true_distance = [[0.0, 7.0, 2.0, 2.5, np.inf],
[1.25, 0.0, 3.25, 3.75, np.inf],
[2.0, 5.0, 0.0, 2.5, np.inf],
[1.25, 8.25, 3.25, 0.0, np.inf],
[np.inf, np.inf, np.inf, np.inf, 0]]
graph = GraphWD(A, measure_list[GraphWD], 'zero')
self.assertSequenceEqual(graph.D.tolist(), true_distance)
def test_graphWU(self):
measure_list = MeasureParser.list_measures()
A = np.array([[0.0, 0.1, 0.5, 0.4, 0.0], [0.1, 0.0, 0.2, 0.5, 0.0],
[0.5, 0.2, 0.0, 0.4, 0.0], [0.4, 0.5, 0.4, 0.0, 0.0],
[0.0, 0.0, 0.0, 0.0, 0.0]])
true_distance = [[0.0, 4.5, 2.0, 2.5, np.inf],
[4.5, 0.0, 4.5, 2.0, np.inf],
[2.0, 4.5, 0.0, 2.5, np.inf],
[2.5, 2.0, 2.5, 0.0, np.inf],
[np.inf, np.inf, np.inf, np.inf, 0]]
graph = GraphWU(A, measure_list[GraphWU], 'zero', 'min')
self.assertSequenceEqual(graph.D.tolist(), true_distance)
def test_wu(self):
measure_list = MeasureParser.list_measures()
A = np.array([[0, 0.1, 0.2, 0.1, 0, 0, 0, 0],
[0, 0, 0.5, 0, 0.1, 0, 0, 0], [0, 0, 0, 0, 0.2, 0, 0, 0],
[0, 0, 0.5, 0, 0.1, 0, 0, 0],
[0, 0, 0, 0, 0, 0.1, 0.5, 0], [0, 0, 0, 0, 0, 0, 0, 0.2],
[0, 0, 0, 0, 0, 0, 0, 0.8], [0, 0, 0, 0, 0, 0, 0, 0]])
graph = GraphWU(A, measure_list[GraphWU], 'zero')
betweenness = [0, 0, 30, 0, 24, 0, 20, 12]
self.assertSequenceEqual(
graph.get_measure(MeasureBetweenness, 'betweenness').tolist(),
betweenness)
def test_graphBD(self):
measure_list = MeasureParser.list_measures()
A = np.array([[0, 1, 0, 1, 0, 0, 0, 0], [0, 0, 1, 0, 1, 0, 0, 0],
[1, 0, 0, 0, 1, 0, 0, 0], [0, 0, 1, 0, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 1, 1, 0], [0, 0, 0, 0, 0, 0, 0, 1],
[0, 0, 0, 0, 0, 0, 0, 1], [0, 0, 0, 0, 0, 0, 0, 0]])
graph_bd = GraphBD(A, measure_list[GraphBD], 'zero')
MeasureCluster.compute_measure(graph_bd)
for i in range(len(A[0])):
self.assertAlmostEqual(
graph_bd.measure_dict[MeasureCluster]['cluster'].tolist()[i],
[1.0000, 0.5000, 0.5000, 0.5000, 0, 0, 0, 0][i],
places=4)
def test_graphBU(self):
measure_list = MeasureParser.list_measures()
A = np.array([[0, 1, 1, 1, 0, 0, 0, 0], [0, 0, 1, 0, 1, 0, 0, 0],
[0, 0, 0, 0, 1, 0, 0, 0], [0, 0, 1, 0, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 1, 1, 0], [0, 0, 0, 0, 0, 0, 0, 1],
[0, 0, 0, 0, 0, 0, 0, 1], [0, 0, 0, 0, 0, 0, 0, 0]])
graph_bu = GraphBU(A, measure_list[GraphBU], 'zero', 'max')
MeasureCluster.compute_measure(graph_bu)
for i in range(len(A[0])):
self.assertAlmostEqual(
graph_bu.measure_dict[MeasureCluster]['cluster'].tolist()[i],
[0.6667, 0.6667, 0.6667, 0.6667, 0.2000, 0, 0, 0][i],
places=4)
def test_bu(self):
measure_list = MeasureParser.list_measures()
A = np.array([[0, 1, 1, 1, 0, 0, 0, 0], [0, 0, 1, 0, 1, 0, 0, 0],
[0, 0, 0, 0, 1, 0, 0, 0], [0, 0, 1, 0, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 1, 1, 0], [0, 0, 0, 0, 0, 0, 0, 1],
[0, 0, 0, 0, 0, 0, 0, 1], [0, 0, 0, 0, 0, 0, 0, 0]])
graph = GraphBU(A, measure_list[GraphBU], 'zero')
betweenness = [
0.6667, 2.6667, 3.3333, 2.6667, 25.6667, 5.0000, 5.0000, 1.0000
]
self.assertSequenceAlmostEqual(graph.get_measure(
MeasureBetweenness, 'betweenness'),
betweenness,
places=4)
def test_graphWD(self):
measure_list = MeasureParser.list_measures()
A = np.array([[3.2, 3.14, 2.7, 0.01, 0.0],
[3.2, 2.7, 3.14, 6.7, 75],
[13, 0.0, 1.2, 5.7, 0.01],
[5.5, 8.2, 0.3, 0.0005, 0.5],
[1, 0.0, 345, 8.7, 2]])
graph = GraphWD(A, measure_list[GraphWD], 'zero')
path_length = [0.2329, 0.1532, 0.1691, 0.1803, 0.1532]
in_path_length = [0.1079, 0.2437, 0.1230, 0.2164, 0.1978]
out_path_length = [0.3579, 0.0627, 0.2151, 0.1443, 0.1086]
self.assertSequenceAlmostEqual(graph.get_measure(MeasurePathLength, 'path_length'), path_length, places = 4)
self.assertSequenceAlmostEqual(graph.get_measure(MeasurePathLength, 'in_path_length'), in_path_length, places = 4)
self.assertSequenceAlmostEqual(graph.get_measure(MeasurePathLength, 'out_path_length'), out_path_length, places = 4)
def test_wu(self):
measure_list = MeasureParser.list_measures()
A = np.array([[0.7577, 0.7060, 0.8235, 0.4387, 0.4898],
[0.7431, 0.0318, 0.6948, 0.3816, 0.4456],
[0.3922, 0.2769, 0.3171, 0.7655, 0.6463],
[0.6555, 0.0462, 0.9502, 0.7952, 0.7094],
[0.1712, 0.0971, 0.0344, 0.1869, 0.7547]])
graph = GraphWU(A, measure_list[GraphWU], 'zero', 'max')
MeasureGlobalEfficiency.compute_measure(graph)
global_efficiency = [0.6780, 0.5712, 0.7787, 0.6791, 0.5728]
test_utility = TestUtility()
test_utility.assertSequenceAlmostEqual(
graph.measure_dict[MeasureGlobalEfficiency]
['global_efficiency'].tolist(), global_efficiency, 4)
def test_graphWU(self):
measure_list = MeasureParser.list_measures()
A = np.array([[0, 0.1, 0.2, 0.1, 0, 0, 0, 0],
[0, 0, 0.5, 0, 0.1, 0, 0, 0], [0, 0, 0, 0, 0.2, 0, 0, 0],
[0, 0, 0.5, 0, 0.1, 0, 0, 0],
[0, 0, 0, 0, 0, 0.1, 0.5, 0], [0, 0, 0, 0, 0, 0, 0, 0.2],
[0, 0, 0, 0, 0, 0, 0, 0.8], [0, 0, 0, 0, 0, 0, 0, 0]])
graph_wu = GraphWU(A, measure_list[GraphWU], 'zero', 'max')
MeasureCluster.compute_measure(graph_wu)
for i in range(len(A[0])):
self.assertAlmostEqual(
graph_wu.measure_dict[MeasureCluster]['cluster'].tolist()[i],
[0.1436, 0.1436, 0.1436, 0.1436, 0.0431, 0, 0, 0][i],
places=4)
