GetBetweennessCentr

GetBetweennessCentr(Graph, NIdBtwH, EdgeBtwH, NodeFrac=1.0)

Computes (approximate) Node and Edge Betweenness Centrality based on a sample of NodeFrac nodes.

Parameters:

• Graph: undirected graph (input)

  A Snap.py undirected graph.

• NIdBtwH: TIntFltH, a hash table with int keys and float values (output)

  Hash table mapping node ids to their corresponding betweenness centrality values.

• EdgeBtwH: TIntPrFltH, a hash table with int pair keys and float values (output)

  Hash table mapping edges (provided as pairs of node ids) to their corresponding betweenness centrality values.

• NodeFrac: float (input)

  Quality of the approximation. NodeFrac=1.0 gives exact betweenness values.

Return Value:

• None

See “A Faster Algorithm for Betweenness Centrality”, Ulrik Brandes, Journal of Mathematical Sociology, 2001, and “Centrality Estimation in Large Networks”, Urlik Brandes and Christian Pich, 2006 for more details.

The following example shows how to calculate Betweenness Centrality scores for nodes and edges in TUNGraph:

import snap

UGraph = snap.GenRndGnm(snap.PUNGraph, 100, 1000)
Nodes = snap.TIntFltH()
Edges = snap.TIntPrFltH()
snap.GetBetweennessCentr(UGraph, Nodes, Edges, 1.0)

for node in Nodes:
    print "node: %d centrality: %f" % (node, Nodes[node])

for edge in Edges:
    print "edge: (%d, %d) centrality: %f" % (edge.GetVal1(), edge.GetVal2(), Edges[edge])