import networkx as nx
from partA import read_graph
import matplotlib as mpl
mpl.use('Agg')
import matplotlib.pyplot as plt
G = read_graph('partA_egofb.txt')
def ASPL_task(G):
p = nx.all_pairs_shortest_path_length(G)
N = G.number_of_nodes()
APL = 0.
for v in p:
for u in p[v]:
APL += p[u][v]
APL = APL / N / (N-1)
print("Average Shortest Path Length: %f" % APL)
def CC_task(G):
CC = nx.closeness_centrality(G)
fig = plt.figure()
ax = fig.add_subplot(1,1,1)
ax.hist([CC[i] for i in CC], 20, normed=True)
fig.savefig('egofb_cc.png')
sorted_nodes = sorted(CC, key=lambda node: CC[node], reverse = True)
for i in range(10):
print(sorted_nodes[i], CC[sorted_nodes[i]])
import networkx as nx
from partA import read_graph
import matplotlib as mpl
mpl.use('Agg')
import matplotlib.pyplot as plt
G = read_graph('partA_hepth.txt')
def ASPL_task(G):
lwcc = None
MM = 0
for g in nx.weakly_connected_component_subgraphs(G):
if MM < g.number_of_nodes():
lwcc = g
MM = g.number_of_nodes()
sd = 0
sum_pairs = 0
n = 0
for node in lwcc:
x = nx.shortest_path_length(lwcc, node)
sd += sum(x[i] for i in x)
sum_pairs += (len(x) - 1)
n += 1
if n % 100 ==0:
print(n)
print(sd / n / (n-1))
print(sum_pairs)
print(n)
degree = d[node]
if degree not in distri:
distri[degree] = 0
distri[degree] += 1
degree = sorted(distri)
fraction = [distri[x] for x in degree]
return (degree, fraction)
def plot_degree_distribution(G):
(degree, fraction) = degree_distribution(G)
fig = plt.figure()
ax = fig.add_subplot(1,1,1)
ax.plot(degree, fraction, 'o')
ax.set_xscale('log')
ax.set_yscale('log')
return fig
if __name__ == '__main__':
egofb = read_graph('partA_egofb.txt')
for xmin in range(1, 30):
print('egofb:', xmin, count_alpha(egofb, xmin))
plot_degree_distribution(egofb).savefig('egofb_dd.png')
hepth = read_graph('partA_hepth.txt')
hepthu = hepth.to_undirected()
for xmin in range(1, 30):
print('hepth:', xmin, count_alpha(hepthu, xmin))
plot_degree_distribution(hepthu).savefig('hepth_dd.png')
