def test_modularity():
assert modularity(np.array([[0, 1, 0], [1, 0, 1], [0, 1, 0]])) == -0.375
assert modularity(np.array([[2, 1], [1, 0]])) == -0.125
assert modularity(
np.array([[0, 1, 1, 0, 0, 0, 0], [1, 0, 1, 0, 0, 0, 0],
[1, 1, 0, 1, 0, 0, 0], [0, 0, 1, 0, 1, 0, 1],
[0, 0, 0, 1, 0, 1, 0], [0, 0, 0, 0, 1, 0, 1],
[0, 0, 0, 1, 0, 1, 0]])) == -0.1484375
def test_modularity_graph_plus_grand():
matrix_graph = np.array([[0, 1], [1, 0]])
matrix_graph1 = np.array([[0, 0, 0], [0, 4, 0], [0, 0, 1]])
matrix_graph2 = np.array([[4, 0], [0, 1]])
matrix_graph3 = np.array([[0, 0, 2], [0, 0, 0], [2, 0, 0]])
matrix_graph4 = np.array([[0, 1, 1], [1, 0, 0], [1, 0, 0]])
assert -0.5 == modularity(matrix_graph)
assert -0.5 == modularity(matrix_graph3)
assert modularity(matrix_graph1) == modularity(matrix_graph2)
assert -0.375 == modularity(matrix_graph4)
def test_zerolization():
G = nx.Graph()
G.add_edge(0, 1, weight=1)
G.add_edge(0, 2, weight=1)
G.add_edge(1, 2, weight=1)
G.add_edge(2, 3, weight=1)
G.add_edge(3, 4, weight=1)
G.add_edge(4, 5, weight=1)
G.add_edge(5, 6, weight=1)
G.add_edge(3, 6, weight=1)
A = nx.to_numpy_matrix(G)
B = A.copy()
E = zerolize_the_be_visited(A, 0, 1)
D = compression(B, 0, 1)
assert modularity(E) == modularity(D)
def test_moudularity_with_seven_nodes():
G = nx.Graph()
G.add_edge(0, 1, weight=1)
G.add_edge(0, 2, weight=1)
G.add_edge(1, 2, weight=1)
G.add_edge(2, 3, weight=1)
G.add_edge(3, 4, weight=1)
G.add_edge(4, 5, weight=1)
G.add_edge(5, 6, weight=1)
G.add_edge(3, 6, weight=1)
A = nx.to_numpy_matrix(G)
assert -0.1484375 == modularity(A)
def test_moudularity_after_compression():
G = nx.Graph()
G.add_edge(0, 1, weight=1)
G.add_edge(0, 2, weight=1)
G.add_edge(1, 2, weight=1)
G.add_edge(2, 3, weight=1)
G.add_edge(3, 4, weight=1)
G.add_edge(4, 5, weight=1)
G.add_edge(5, 6, weight=1)
G.add_edge(3, 6, weight=1)
A = nx.to_numpy_matrix(G)
B = compression(A, 0, 1)
assert modularity(B) == -0.0546875
def louvain_test(graph):
'''
:param graph: networkx.Graph
:return: None
'''
print("Louvain has been started started")
start_time = time.time()
pa = louvain.best_partition(graph)
print("time : ", time.time() - start_time)
modular = louvain.modularity(pa, graph)
print('Louvain modularity: ', modular)
# sg.print_graph_communities(pa)
sg.write_graph_communities(pa, "./data/vk_louvain_source.txt")
print('\n')
def louvain_test(graph):
'''
:param graph: networkx.Graph
:return: None
'''
print("Louvain has been started started")
start_time = time.time()
pa = louvain.best_partition(graph)
print("time : ", time.time() - start_time)
modular = louvain.modularity(pa, graph)
print('Louvain modularity: ', modular)
# sg.print_graph_communities(pa)
sg.write_graph_communities(pa, "./data/vk_louvain_source.txt")
print('\n')
def test_modularity_graph_a_node():
matrix_graph = np.array([[0]])
assert 0 == modularity(matrix_graph)
