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# Small-world

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 [1].

[1]

Small-world network:: https://en.wikipedia.org/wiki/Small-world_network

`random_reference`(G[, niter, connectivity, seed]) | Compute a random graph by swapping edges of a given graph.
`lattice_reference`(G[, niter, D, ...]) | Latticize the given graph by swapping edges.
`sigma`(G[, niter, nrand, seed]) | Returns the small-world coefficient (sigma) of the given graph.
`omega`(G[, niter, nrand, seed]) | Returns the small-world coefficient (omega) of a graph