self._node_numbers.extend(list(new_node_neighbors))
#update the number of nodes
self._num_nodes += 1
return new_node_neighbors
def make_dpa_graph(n, m):
dpa_graph = module_1.make_complete_graph(m)
dpa = DPATrial(m)
for new_node in range(m, n):
new_node_neighbors = dpa.run_trial(m)
dpa_graph[new_node] = new_node_neighbors
return dpa_graph
if __name__ == '__main__':
graph = project_1.normalize_distribution(module_1.in_degree_distribution(make_dpa_graph(27770,12)))
plt.loglog(graph.keys(), graph.values(), 'go')
plt.xlabel('Papers')
plt.ylabel('Cications')
plt.title('DPA Citation graph simulation')
plt.show()
edges.add(edge)
graph[node] = edges
return graph
def normalize_distribution(distribution):
factor = 1.0/sum(distribution.values())
normalized_distribution = {key: val*factor for key, val in distribution.items()}
return normalized_distribution
if __name__ == '__main__':
citation_graph = load_graph(CITATION_URL)
citation_distribution = normalize_distribution(in_degree_distribution(citation_graph))
plt.loglog(citation_distribution.keys(),citation_distribution.values(),'go')
plt.title('Citation Graph')
plt.xlabel('papers')
plt.ylabel('citations')
plt.show()
graph1 = normalize_distribution(in_degree_distribution(compleate_directed_graph(300, 0.6)))
graph2 = normalize_distribution(in_degree_distribution(compleate_directed_graph(500, 0.2)))
graph3 = normalize_distribution(in_degree_distribution(compleate_directed_graph(800, 0.8)))
for graph in (graph1, graph2, graph3):
plt.loglog(graph.keys(), graph.values(), 'go')
plt.title('ER graph in-degree distribution')
