def add_list_to_cluster_dict(cl_id, cllist, cluster_dict):
neighbor_list = []
if cl_id not in cluster_dict:
for node in cllist:
neighbor_list = union(neighbor_list, neighbor_dict[node])
cluster_dict[cl_id] = cl(cl_id, cllist, neighbor_list)
return
def add_list_to_cluster_dict(cllist, graph, cluster_dict):
cl_id = get_id(cllist)
if cl_id not in cluster_dict:
sub_graph = graph.subgraph(cllist)
clustering_coeff = nx.average_clustering(sub_graph)
cluster_dict[cl_id] = cl(cllist, clustering_coeff)
return
def generate_cluster_dict(clusters, cluster_dict, graph):
for i in clusters:
i_int = []
neighbor_list = []
for string in i:
i_int.append(int(string))
neighbor_list = union(neighbor_list, neighbor_dict[string])
id = get_id(i_int)
if id not in cluster_dict:
cluster_dict[id] = cl(id, i, neighbor_list)
def generate_cluster_dict(clusters, cluster_dict, graph):
for i in clusters:
i_int = []
for string in i:
i_int.append(int(string))
id = get_id(i_int)
if id not in cluster_dict:
sub_graph = graph.subgraph(i_int)
clustering_coeff = nx.average_clustering(sub_graph)
cluster_dict[id] = cl(i_int, clustering_coeff)
