GenSmallWorld (SWIG)

GenSmallWorld(Nodes, NodeOutDeg, RewireProb, Rnd=TRnd)

Generates and returns a random small-world graph using the Watts-Strogatz model. We assume a circle where each node creates links to NodeOutDeg other nodes.

Parameters:

  • Nodes: int (input)

    The number of nodes desired.

  • NodeOutDeg: int (input)

    The out degree of each node desired. Since the generated graph is undirected, the out degree for each node, on average, will be twice this value.

  • RewireProb: float (input)

    Represents the probability that an edge will be rewired.

  • Rnd: TRnd (input)

    Random number generator.

Return value:

  • undirected graph

    A Snap.py undirected graph generated with the Watts-Strogatz model.

See: Collective dynamics of ‘small-world’ networks. Watts and Strogatz. URL: http://research.yahoo.com/files/w_s_NATURE_0.pdf

The following example shows how to generate a small-world graph for various values of RewireProb:

import snap

Rnd = snap.TRnd(1,0)
UGraph1 = snap.GenSmallWorld(10, 3, 0, Rnd)
for EI in UGraph1.Edges():
    print("edge: (%d, %d)" % (EI.GetSrcNId(), EI.GetDstNId()))

UGraph2 = snap.GenSmallWorld(10, 3, 0.7, Rnd)
for EI in UGraph2.Edges():
    print("edge: (%d, %d)" % (EI.GetSrcNId(), EI.GetDstNId()))