average_clustering¶

average_clustering(G, trials=1000)[source]¶

Estimates the average clustering coefficient of G.

The local clustering of each node in $G$ is the fraction of triangles that actually exist over all possible triangles in its neighborhood. The average clustering coefficient of a graph $G$ is the mean of local clusterings.

This function finds an approximate average clustering coefficient for G by repeating $n$ times (defined in $trials$ ) the following experiment: choose a node at random, choose two of its neighbors at random, and check if they are connected. The approximate coefficient is the fraction of triangles found over the number of trials [1].

Parameters:	G (NetworkX graph) – trials (integer) – Number of trials to perform (default 1000).
Returns:	c – Approximated average clustering coefficient.
Return type:	float

References

[1]	Schank, Thomas, and Dorothea Wagner. Approximating clustering coefficient and transitivity. Universität Karlsruhe, Fakultät für Informatik, 2004. http://www.emis.ams.org/journals/JGAA/accepted/2005/SchankWagner2005.9.2.pdf