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.
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Small-world network:: https://en.wikipedia.org/wiki/Small-world_network
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Compute a random graph by swapping edges of a given graph. |
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Latticize the given graph by swapping edges. |
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Returns the small-world coefficient (sigma) of the given graph. |
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Returns the small-world coefficient (omega) of a graph |