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