@Override
protected void originateCommunity(Node node) {
super.originateCommunity(node);
// Correct the original community score for the Leung algorithm
node.setAttribute(marker + ".score", 1.0);
}
private void defaultVisit(CFrame frame) {
MultiGraph graph = this.view.getGraph();
graph.getNodeSet().clear();
graph.getEdgeSet().clear();
// this.baseIRIList = new HashSet<String>();
// Получение всех элементов и формирование из них визуального части.
for (OWLNamedIndividual owlName : frame.getContent().getConcepts()) {
String label = this.model.getLabel(owlName);
if (label.equals("_EMPTY_")) {
label = owlName.getIRI().getFragment().toString();
}
Node node = graph.addNode(owlName.getIRI().toString());
node.addAttribute("OWLNamedIndividual", owlName);
node.addAttribute("ui.label", label);
if (owlName.getIRI().equals(frame.getTrgConcept().getIRI())) {
node.setAttribute("ui.class", "concept");
}
}
// Связывает все элементы линиями.
for (Branch br : frame.getContent().getBranches()) {
Node nodeSub = null;
Node nodeObj = null;
for (Node node : graph.getNodeSet()) {
if (node.getId().equals(br.getSubject().getIRI().toString())) {
nodeSub = node;
continue;
} else {
if (node.getId().equals(br.getObject().getIRI().toString())) {
nodeObj = node;
continue;
}
}
if (nodeSub != null && nodeObj != null) {
break;
}
}
// Создает элемент линия для двух node.
Edge edge = graph.addEdge(br.getBrachIndIRI().toString(), nodeSub, nodeObj, true);
String labelEdge = this.model.getAnnotationValue(br.getPrp().getIRI());
if (labelEdge.equals("_EMPTY_")) {
labelEdge = br.getPrp().getIRI().getFragment().toString();
}
edge.addAttribute("ui.label", labelEdge);
}
}
@Override
public void computeNode(Node node) {
/*
* Recall and update the node current community and previous score
*/
Object previousCommunity = node.getAttribute(marker);
Double previousScore = (Double) node.getAttribute(marker + ".score");
super.computeNode(node);
/*
* Update the node label score
*/
// Handle first iteration
if (previousCommunity == null) {
previousCommunity = node.getAttribute(marker);
previousScore = (Double) node.getAttribute(marker + ".score");
}
/*
* The node is the originator of the community and hasn't changed
* community at this iteration (or we are at the first simulation step):
* keep the maximum label score
*/
if ((node.getAttribute(marker).equals(previousCommunity)) && (previousScore.equals(1.0)))
node.setAttribute(marker + ".score", 1.0);
/*
* Otherwise search for the highest score amongst neighbors and reduce
* it by decreasing factor
*/
else {
Double maxLabelScore = Double.NEGATIVE_INFINITY;
for (Edge e : node.getEnteringEdgeSet()) {
Node v = e.getOpposite(node);
if (v.hasAttribute(marker) && v.getAttribute(marker).equals(node.getAttribute(marker))) {
if ((Double) v.getAttribute(marker + ".score") > maxLabelScore)
maxLabelScore = (Double) v.getAttribute(marker + ".score");
}
}
node.setAttribute(marker + ".score", maxLabelScore - delta);
}
}
/*
* (non-Javadoc)
*
* @see org.graphstream.algorithm.Algorithm#compute()
*/
public void compute() {
float min = Float.MAX_VALUE;
HashSet<Node> centroid = new HashSet<Node>();
for (Node node : graph.getEachNode()) {
float m = 0;
APSP.APSPInfo info = node.getAttribute(apspInfoAttribute);
if (info == null) System.err.printf("APSPInfo missing. Did you compute APSP before ?\n");
for (Node other : graph.getEachNode()) {
if (node != other) {
double d = info.getLengthTo(other.getId());
if (d < 0)
System.err.printf(
"Found a negative length value in centroid algorithm. " + "Is graph connected ?\n");
else m += d;
}
}
if (m < min) {
centroid.clear();
centroid.add(node);
min = m;
} else if (m == min) {
centroid.add(node);
}
}
for (Node node : graph.getEachNode())
node.setAttribute(
centroidAttribute, centroid.contains(node) ? isInCentroid : isNotInCentroid);
centroid.clear();
}