def fastgreedy_test(graph): ''' :param graph: igraph.Graph :return: None ''' print("Fastgreedy has been started") start_time = time.time() communities = graph.community_fastgreedy() print("time : ", time.time() - start_time) modular = communities.as_clustering().modularity print('Fastgreedy modularity: ', modular) sg.write_graph_communities(communities.as_clustering().membership, "./data/vk_fastgreedy.txt")
def eigenvector_test(graph): ''' :param graph: igraph.Graph :return: None ''' print("Eigen vector has been started") start_time = time.time() communities = graph.community_leading_eigenvector(weights=None, arpack_options=None) print("time : ", time.time() - start_time) modular = communities.modularity print('Eigen vector modularity: ', modular) sg.write_graph_communities(communities.membership, "./data/lj_eigenvector.txt")
def label_propagation_test(graph): ''' :param graph: igraph.Graph :return: None ''' print("Label propagation has been started") start_time = time.time() communities = graph.community_label_propagation() print("time : ", time.time() - start_time) modular = communities.modularity print('Label propagation modularity: ', modular) sg.write_graph_communities(communities.membership, "./data/vk_label_propagation.txt")
def edge_betweenness_test(graph): ''' :param graph: igraph.Graph :return: None ''' print("Edge betweenness has been started") start_time = time.time() communities = graph.community_edge_betweenness(directed=False) print("time : ", time.time() - start_time) modular = communities.as_clustering().modularity sg.write_graph_communities(communities.as_clustering().membership, "./data/vk_edge_betweenness.txt") print('Edge betweenness modularity: ', modular)
def walktrap_test(graph): ''' :param graph: igraph.Graph :return: None ''' print("Walktrap has been started") start_time = time.time() communities = graph.community_walktrap() print("time : ", time.time() - start_time) modular = communities.as_clustering().modularity print('Walktrap modularity: ', modular) sg.write_graph_communities(communities.as_clustering().membership, "./data/vk_walktrap.txt")
def infomap_test(graph): ''' :param graph: igraph.Graph :return: None ''' print("Infomap has been started") start_time = time.time() communities = graph.community_infomap() print("time : ", time.time() - start_time) modular = communities.modularity print('Infomap modularity: ', modular) # print('Infomap: ', communities, '\n') sg.write_graph_communities(communities.membership, "./data/vk_infomap.txt")
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')