GetAnf (SWIG)ΒΆ

GetAnf(Graph, SrcNId, DistNbrsV, MxDist, IsDir, NApprox=32)

Approximate neighborhood function of a node. Prints the (approximate) number of nodes reachable from SrcNId in less than MxDist hops.

Parameters:

  • Graph: graph (input)

    A Snap.py graph or a network.

  • SrcNId: int (input)

    The node id for the starting node.

  • DistNbrsV: TIntFltKdV, a vector of (integer, float) pairs (output)

    Maps between the distance H (in hops) and the number of nodes reachable in <= H hops.

  • MxDist: int (input)

    Maximum number of hops the algorithm spreads from SrcNId.

  • IsDir: bool (input)

    Indicates whether the edges should be considered directed or undirected.

  • Napprox: int (input)

    Quality of approximation. See the ANF paper. Should be a multiple of 8.

Return value:

  • None

The ANF paper: http://www.cs.cmu.edu/~christos/PUBLICATIONS/kdd02-anf.pdf

The following example shows how to use GetAnf() with TNGraph, TUNGraph, and TNEANet:

import snap

Graph = snap.GenRndGnm(snap.PNGraph, 100, 1000)
SrcNId = 0
DistNbrsV = snap.TIntFltKdV()
snap.GetAnf(Graph, SrcNId, DistNbrsV, 3, False, 32)
for item in DistNbrsV:
    print(item.Dat())

UGraph = snap.GenRndGnm(snap.PUNGraph, 100, 1000)
SrcNId = 0
DistNbrsV = snap.TIntFltKdV()
snap.GetAnf(UGraph, SrcNId, DistNbrsV, 3, False, 32)
for item in DistNbrsV:
    print(item.Dat())

Network = snap.GenRndGnm(snap.PNEANet, 100, 1000)
SrcNId = 0
DistNbrsV = snap.TIntFltKdV()
snap.GetAnf(Network, SrcNId, DistNbrsV, 3, False, 32)
for item in DistNbrsV:
    print(item.Dat())