def analsys_graph(G): #print("Drawing the graph") #helpers.draw_graph(G) print("analysing the graph") print("Nodes: ", G.number_of_nodes()) print("Edges: ", G.number_of_edges()) # Draw loglog graph... #DG = G.to_directed() print("Drawing the loglog graph") helpers.plot_degseq(G, False) print('')
def analyse_directed_graph(): graph = load_graph('college', True) # helpers.draw_graph(graph) #print("Graph nodes: ", graph.number_of_nodes()) #print("Graph edges: ", graph.number_of_edges()) # already has edges from dataset... print(nx.info(graph)) analyse_strongly_connected_components(graph) # Draw loglog graph... helpers.plot_degseq(graph, False) # wait at end... input("Press Enter to Continue ...")
def main(): graph = load_graph("facebook") helpers.plot_degseq(graph, False) num_nodes = graph.number_of_nodes() x = [random.random() for i in range(num_nodes)] y = [random.random() for i in range(num_nodes)] x = np.array(x) y = np.array(y) pos = dict() for i in range(num_nodes): pos[i] = x[i], y[i] print("Graph nodes: ", graph.number_of_nodes()) print("Graph edges: ", graph.number_of_edges()) # already has edges from dataset... print("Pos nodes: ", len(pos)) # plot the graph... A = nx.adjacency_matrix(graph) graph = nx.Graph(A) print("Graph nodes after rebuild: ", graph.number_of_nodes()) print("Graph edges after rebuild: ", graph.number_of_edges()) # already has edges from dataset... # Plot the nodes only plot_graph(graph, pos, 1, False) # plot the nodes and edges plot_graph(graph, pos, 2) # reposition with the eigenvectors eigenv_pos, V = repos_with_eigs(A, num_nodes) plot_graph(graph, eigenv_pos, 3) print("Plotting spring layout") pos = nx.spring_layout(graph) plot_graph(graph, pos, 4) # Look at the clustering features = np.column_stack((V[:, 1], V[:, 2])) cluster_nodes_from_original_example(graph, features, pos, eigenv_pos) # Finally, use the columns of A directly for clustering # cluster_nodes_from_original_example(graph, A.todense(), pos, eigenv_pos) # wait at end... input("Press Enter to Continue ...")
def run_price_model_sim(): full_graph = create_price_model_graph() print_price_model_graph_as_text(full_graph) helpers.plot_degseq(full_graph, False) input("Press enter to finish.")