GetPageRank (SWIG)ΒΆ

GetPageRank(Graph, PRankH, C=0.85, Eps=0.0001, MaxIter=100)

Computes the PageRank score of every node in Graph. The scores are stored in PRankH.

Parameters:

  • Graph: graph (input)

    A Snap.py graph or a network.

  • PRankH: TIntFltH, a hash of int keys and float values (output)

    PageRank scores. Keys are node IDs, values are computed PageRank scores.

  • C: float (input)

    Damping factor.

  • Eps: float (input)

    Convergence difference.

  • MaxIter: int (input)

    Maximum number of iterations.

Return value:

  • None

The following example shows how to calculate PageRank scores for nodes in TNGraph, TUNGraph, and TNEANet:

import snap

Graph = snap.GenRndGnm(snap.PNGraph, 100, 1000)
PRankH = snap.TIntFltH()
snap.GetPageRank(Graph, PRankH)
for item in PRankH:
    print(item, PRankH[item])

UGraph = snap.GenRndGnm(snap.PUNGraph, 100, 1000)
PRankH = snap.TIntFltH()
snap.GetPageRank(UGraph, PRankH)
for item in PRankH:
    print(item, PRankH[item])

Network = snap.GenRndGnm(snap.PNEANet, 100, 1000)
PRankH = snap.TIntFltH()
snap.GetPageRank(Network, PRankH)
for item in PRankH:
    print(item, PRankH[item])