edu.uci.ics.jung.algorithms.scoring
Class EigenvectorCentrality<V,E>
java.lang.Object
edu.uci.ics.jung.algorithms.scoring.AbstractIterativeScorer<V,E,S>
edu.uci.ics.jung.algorithms.scoring.AbstractIterativeScorerWithPriors<V,E,Double>
edu.uci.ics.jung.algorithms.scoring.PageRankWithPriors<V,E>
edu.uci.ics.jung.algorithms.scoring.PageRank<V,E>
edu.uci.ics.jung.algorithms.scoring.EigenvectorCentrality<V,E>
- All Implemented Interfaces:
- VertexScorer<V,Double>, IterativeContext
public class EigenvectorCentrality<V,E>
- extends PageRank<V,E>
Calculates eigenvector centrality for each vertex in the graph.
The 'eigenvector centrality' for a vertex is defined as the fraction of
time that a random walk(er) will spend at that vertex over an infinite
time horizon.
Assumes that the graph is strongly connected.
Methods inherited from class edu.uci.ics.jung.algorithms.scoring.AbstractIterativeScorer |
acceptDisconnectedGraph, done, evaluate, getAdjustedIncidentCount, getCurrentValue, getEdgeWeight, getEdgeWeights, getIterations, getMaxIterations, getOutputValue, getTolerance, getVertexScore, isDisconnectedGraphOK, setCurrentValue, setEdgeWeights, setHyperedgesAreSelfLoops, setMaxIterations, setOutputValue, setTolerance, step, swapOutputForCurrent, updateMaxDelta |
Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
EigenvectorCentrality
public EigenvectorCentrality(Hypergraph<V,E> graph,
org.apache.commons.collections15.Transformer<E,? extends Number> edge_weights)
- Creates an instance with the specified graph and edge weights.
The outgoing edge weights for each edge must sum to 1.
(See
UniformDegreeWeight
for one way to handle this for
undirected graphs.)
- Parameters:
graph
- the graph for which the centrality is to be calculatededge_weights
- the edge weights
EigenvectorCentrality
public EigenvectorCentrality(Hypergraph<V,E> graph)
- Creates an instance with the specified graph and default edge weights.
(Default edge weights:
UniformDegreeWeight
.)
- Parameters:
graph
- the graph for which the centrality is to be calculated.
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