import matplotlib.pyplot as plt
from networkx import nx
z = [
98, 95, 95, 94, 92, 89, 89, 89, 87, 87, 86, 85, 85, 84, 83, 81, 80, 79, 77,
75, 71, 70, 70, 70, 69, 68, 68, 67, 65, 64, 63, 62, 61, 59, 58, 55, 54, 54,
53, 53, 53, 53, 51, 49, 47, 46, 45, 45, 45, 43, 42, 42, 41, 39, 38, 38, 37,
36, 35, 35, 35, 35, 35, 34, 33, 30, 30, 29, 28, 28, 27, 25, 23, 22, 22, 21,
19, 19, 19, 18, 17, 15, 15, 15, 13, 13, 12, 12, 12, 11, 11, 10, 10, 5, 5,
4, 4, 2, 1, 1
]
print(nx.is_graphical(z))
print("Configuration model")
G = nx.configuration_model(z) # configuration model
print(G)
degree_sequence = [d for n, d in G.degree()] # degree sequence
print("Degree sequence %s" % degree_sequence)
print("Degree histogram")
hist = {}
for d in degree_sequence:
if d in hist:
hist[d] += 1
else:
hist[d] = 1
print("degree #nodes")
for d in hist:
print('%d %d' % (d, hist[d]))
nx.draw(G)
return False
d = degree_sequence.pop(0)
if d == 0:
print("There exists a graph G with this degree sequence")
return True
if d > len(degree_sequence):
print(str(d) + " dgree is too large for sequence!")
return False
for i in range(0, d):
degree_sequence[i] -= 1
print("Popped: " + str(d))
return False
random_sequence = []
n = random.randint(0, 100)
print("the length of the degree sequence is {0}".format(n))
for x in range(n):
random_sequence.append(random.randint(0, n - 1))
print("the degree sequence is {0}".format(random_sequence))
start_time = time.time()
x = havelHakimi(random_sequence)
print("--- %s seconds ---" % (time.time() - start_time))
if x == True:
G = nx.configuration_model(random_sequence)
nx.draw(G)
plt.show()
Degree Sequence
===============
Random graph from given degree sequence.
"""
import matplotlib.pyplot as plt
from networkx import nx
# Specify seed for reproducibility
seed = 668273
z = [5, 3, 3, 3, 3, 2, 2, 2, 1, 1, 1]
print(nx.is_graphical(z))
print("Configuration model")
G = nx.configuration_model(
z, seed=seed) # configuration model, seed for reproduciblity
degree_sequence = [d for n, d in G.degree()] # degree sequence
print(f"Degree sequence {degree_sequence}")
print("Degree histogram")
hist = {}
for d in degree_sequence:
if d in hist:
hist[d] += 1
else:
hist[d] = 1
print("degree #nodes")
for d in hist:
print(f"{d:4} {hist[d]:6}")
pos = nx.spring_layout(G, seed=seed) # Seed layout for reproducibility
nx.draw(G, pos=pos)
# Copyright (C) 2004-2018 by
# Aric Hagberg <*****@*****.**>
# Dan Schult <*****@*****.**>
# Pieter Swart <*****@*****.**>
# All rights reserved.
# BSD license.
import matplotlib.pyplot as plt
from networkx import nx
z = [5, 3, 3, 3, 3, 2, 2, 2, 1, 1, 1]
print(nx.is_graphical(z))
print("Configuration model")
G = nx.configuration_model(z) # configuration model
degree_sequence = [d for n, d in G.degree()] # degree sequence
print("Degree sequence %s" % degree_sequence)
print("Degree histogram")
hist = {}
for d in degree_sequence:
if d in hist:
hist[d] += 1
else:
hist[d] = 1
print("degree #nodes")
for d in hist:
print('%d %d' % (d, hist[d]))
nx.draw(G)
plt.show()
def get_graph_based_degree_sequence(z=None, file_location="./Output/"):
if not z:
z = [5, 3, 3, 3, 3, 2, 2, 4, 1, 1, 3]
g = nx.configuration_model(z)
nx.write_pajek(g, file_location + "randomWithSequence.net")
return g
