Generate a pseudorandom graph:

Probability density functions of the global clustering coefficient:

Generate simple undirected graphs:

Generate a set of pseudorandom graphs:

Compute probabilities and statistical properties:

In a medical study of an outbreak of influenza, each subject reported its number of potentially contagious interactions within the group. Simulate interaction networks:

Find the probability that subject 1 has interacted with subject 2:

Analyze whether a network is drawn from a degree graph distribution:

Compare the empirical and theoretical basic properties:

The empirical and theoretical global clustering coefficient:

Distribution of the number of vertices:

Distribution of the number of edges:

Distribution of the degree of a vertex:

Probability density function:

The mean of the degree of a vertex:

The sum of the degree sequence of a graph is always even:

Degree sequences with odd total degree cannot be realized as a graph:

is a degree sequence of a simple graph iff is:

Ordered degree sequence:

Reconstruct the degree sequence without the largest degree vertex:

The graphs with the same degree sequence can be non-isomorphic:

A degree sequence with distinct degrees is realized as a graph with self-loops:

Randomly colored vertices: