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[source code]

#!/usr/bin/env python
Create an G{n,m} random graph and compute the eigenvalues.
Requires numpy and matplotlib.
import networkx as nx
import numpy.linalg
import matplotlib.pyplot as plt

n = 1000 # 1000 nodes
m = 5000 # 5000 edges
G = nx.gnm_random_graph(n,m)

L = nx.normalized_laplacian_matrix(G)
e = numpy.linalg.eigvals(L.A)
print("Largest eigenvalue:", max(e))
print("Smallest eigenvalue:", min(e))
plt.hist(e,bins=100) # histogram with 100 bins
plt.xlim(0,2)  # eigenvalues between 0 and 2