Smallworld¶
Functions for estimating the smallworldness of graphs.
A small world network is characterized by a small average shortest path length, and a large clustering coefficient.
Smallworldness 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 smallworld network [1].
 1
Smallworld network:: https://en.wikipedia.org/wiki/Smallworld_network

Compute a random graph by swapping edges of a given graph. 

Latticize the given graph by swapping edges. 

Returns the smallworld coefficient (sigma) of the given graph. 

Returns the smallworld coefficient (omega) of a graph 