GenRndPowerLaw (SWIG)ΒΆ

GenRndPowerLaw(Nodes, PowerExp, ConfModel=True, Rnd=TRnd)

Generates a random scale-free graph with power-law degree distribution with exponent PowerExp. The method uses either the Configuration model (fast but the result is approximate) or the Edge Rewiring method (slow but exact).

Parameters:

  • Nodes: int (input)

    Number of nodes.

  • PowerExp: float (input)

    Power exponent, which must be greater than 1.

  • ConfModel: bool (input)

    Whether the method uses the Configuration model.

  • Rnd: TRnd (input)

    Random number generator.

Return value:

  • undirected graph

    A Snap.py undirected, random, scale-free graph.

The following example shows how to create PUNGraph with this function:

import snap

UGraph1 = snap.GenRndPowerLaw (9, 10)
for NI in UGraph1.Nodes():
    print("node: %d, out-degree %d, in-degree %d" % (NI.GetId(), NI.GetOutDeg(), NI.GetInDeg()))

UGraph2 = snap.GenRndPowerLaw (5, 2, False)
for NI in UGraph2.Nodes():
    print("node: %d, out-degree %d, in-degree %d" % (NI.GetId(), NI.GetOutDeg(), NI.GetInDeg()))