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.")