Functions for estimating the small-world-ness of graphs.
A small world network is characterized by a small average shortest path length, and a large clustering coefficient.
Small-worldness is commonly measured with the coefficient sigma or omega.
Both coefficients compare the average clustering coefficient and shortest path length of a given graph against the same quantities for an equivalent random or lattice graph.
For more information, see the Wikipedia article on small-world network .
|||Small-world network:: https://en.wikipedia.org/wiki/Small-world_network|
||Compute a random graph by swapping edges of a given graph.|
||Latticize the given graph by swapping edges.|
||Returns the small-world coefficient (sigma) of the given graph.|
||Returns the small-world coefficient (omega) of a graph|