/**
* Compute the scores for all relevant communities for the selected node using Leung algorithm.
*
* @param u The node for which the scores computation is performed
* @complexity O(DELTA) where DELTA is is the average node degree in the network
*/
@Override
protected void communityScores(Node u) {
/*
* Reset the scores for each communities
*/
communityScores = new HashMap<Object, Double>();
/*
* Iterate over the nodes that this node "hears"
*/
for (Edge e : u.getEnteringEdgeSet()) {
Node v = e.getOpposite(u);
/*
* Update the count for this community
*/
if (v.hasAttribute(marker)) {
// Compute the neighbor node current score
Double score = (Double) v.getAttribute(marker + ".score") * Math.pow(v.getInDegree(), m);
/*
* The rest of the formula depends on the weighted status of the
* network
*/
Double weight;
if (e.hasAttribute(weightMarker))
if (e.isDirected()) {
Edge e2 = v.getEdgeToward(u.getId());
if (e2 != null && e2.hasAttribute(weightMarker))
weight =
(Double) e.getAttribute(weightMarker) + (Double) e2.getAttribute(weightMarker);
else weight = (Double) e.getAttribute(weightMarker);
} else weight = (Double) e.getAttribute(weightMarker);
else weight = 1.0;
// Update the score of the according community
if (communityScores.get(v.getAttribute(marker)) == null)
communityScores.put(v.getAttribute(marker), score * weight);
else
communityScores.put(
v.getAttribute(marker),
communityScores.get(v.getAttribute(marker)) + (score * weight));
}
}
}
/*
* (non-Javadoc)
*
* @see org.graphstream.algorithm.Algorithm#compute()
*/
@SuppressWarnings("unchecked")
public void compute() {
Node source = graph.getNode(this.source_id);
// Step 1: Initialize graph
for (Node n : graph) {
if (n == source) n.addAttribute(identifier + ".distance", 0.0);
else n.addAttribute(identifier + ".distance", Double.POSITIVE_INFINITY);
// n.addAttribute(identifier+".predecessors",(Object)null);
}
// Step 2: relax edges repeatedly
for (int i = 0; i < graph.getNodeCount(); i++) {
for (Edge e : graph.getEachEdge()) {
Node n0 = e.getNode0();
Node n1 = e.getNode1();
Double d0 = (Double) n0.getAttribute(identifier + ".distance");
Double d1 = (Double) n1.getAttribute(identifier + ".distance");
Double we = (Double) e.getAttribute(weightAttribute);
if (we == null)
throw new NumberFormatException(
"org.graphstream.algorithm.BellmanFord: Problem with attribute \""
+ weightAttribute
+ "\" on edge "
+ e);
if (d0 != null) {
if (d1 == null || d1 >= d0 + we) {
n1.addAttribute(identifier + ".distance", d0 + we);
ArrayList<Edge> predecessors =
(ArrayList<Edge>) n1.getAttribute(identifier + ".predecessors");
if (d1 != null && d1 == d0 + we) {
if (predecessors == null) {
predecessors = new ArrayList<Edge>();
}
} else {
predecessors = new ArrayList<Edge>();
}
if (!predecessors.contains(e)) {
predecessors.add(e);
}
n1.addAttribute(identifier + ".predecessors", predecessors);
}
}
}
}
// Step 3: check for negative-weight cycles
for (Edge e : graph.getEachEdge()) {
Node n0 = e.getNode0();
Node n1 = e.getNode1();
Double d0 = (Double) n0.getAttribute(identifier + ".distance");
Double d1 = (Double) n1.getAttribute(identifier + ".distance");
Double we = (Double) e.getAttribute(weightAttribute);
if (we == null) {
throw new NumberFormatException(
String.format(
"%s: Problem with attribute \"%s\" on edge \"%s\"",
BellmanFord.class.getName(), weightAttribute, e.getId()));
}
if (d1 > d0 + we) {
throw new NumberFormatException(
String.format(
"%s: Problem: negative weight, cycle detected on edge \"%s\"",
BellmanFord.class.getName(), e.getId()));
}
}
}
