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Note

This documents the development version of NetworkX. Documentation for the current release can be found here.

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networkx.algorithms.smallworld.lattice_reference

lattice_reference(G, niter=1, D=None, connectivity=True, seed=None)[source]

Latticize the given graph by swapping edges.

Parameters

  • G (graph) – An undirected graph with 4 or more nodes.

  • niter (integer (optional, default=1)) – An edge is rewired approximatively niter times.

  • D (numpy.array (optional, default=None)) – Distance to the diagonal matrix.

  • connectivity (boolean (optional, default=True)) – Ensure connectivity for the latticized graph when set to True.

  • seed (integer, random_state, or None (default)) – Indicator of random number generation state. See Randomness.

Returns

G – The latticized graph.

Return type

graph

Notes

The implementation is adapted from the algorithm by Sporns et al. 1. which is inspired from the original work by Maslov and Sneppen(2002) 2.

References

1

Sporns, Olaf, and Jonathan D. Zwi. “The small world of the cerebral cortex.” Neuroinformatics 2.2 (2004): 145-162.

2

Maslov, Sergei, and Kim Sneppen. “Specificity and stability in topology of protein networks.” Science 296.5569 (2002): 910-913.