def compute_lpa(n_vertex, edge_list): graph, weights = tf.compute_igraph_form(n_vertex, edge_list) t = time.time() clusters = graph.community_label_propagation(weights=weights, initial=None, fixed=None) exectime = time.time() - t labels = tf.compute_labels_from_clusters(n_vertex, clusters) return labels, clusters, exectime
def compute_walktrap(n_vertex, edge_list, n_clusters, n_steps): graph, weights = tf.compute_igraph_form(n_vertex, edge_list) t = time.time() dendrogram = graph.community_walktrap(weights, n_steps) clusters = dendrogram.as_clustering(n=n_clusters) exectime = time.time() - t labels = tf.compute_labels_from_clusters(n_vertex, clusters) return labels, clusters, exectime
def compute_clauset_newman(n_vertex, edge_list, n_clusters): graph, weights = tf.compute_igraph_form(n_vertex, edge_list) t = time.time() dendrogram = graph.community_fastgreedy(weights) clusters = dendrogram.as_clustering(n=n_clusters) exectime = time.time() - t labels = tf.compute_labels_from_clusters(n_vertex, clusters) return labels, clusters, exectime
def compute_greedy_newman(n_vertex, edge_list): from agglomcluster import NewmanGreedy graph = tf.compute_networkx_form(n_vertex, edge_list) t = time.time() clst = NewmanGreedy(graph) clusters = clst.get_clusters() exectime = time.time() - t labels = tf.compute_labels_from_clusters(n_vertex, clusters) return labels, clusters, exectime