/**
* Resets the values of clusters that have been merged.
*
* @param clustering
* @param i
* @param j
*/
protected void updateScoreMatrix(Clustering clustering, int i, int j) {
int size = clustering.getNumInstances();
int[] ci = clustering.getIndicesWithLabel(i);
for (int ni = 0; ni < ci.length; ni++) {
for (int nj = 0; nj < size; nj++) if (ci[ni] != nj) scoreCache.set(ci[ni], nj, 0.0);
}
int[] cj = clustering.getIndicesWithLabel(j);
for (int ni = 0; ni < cj.length; ni++) {
for (int nj = 0; nj < size; nj++) if (cj[ni] != nj) scoreCache.set(cj[ni], nj, 0.0);
}
}
/**
* @param clustering
* @param i
* @param j
* @return The score for merging these two clusters.
*/
protected double getScore(Clustering clustering, int i, int j) {
if (scoreCache == null) scoreCache = new PairwiseMatrix(clustering.getNumInstances());
int[] ci = clustering.getIndicesWithLabel(i);
int[] cj = clustering.getIndicesWithLabel(j);
if (scoreCache.get(ci[0], cj[0]) == 0.0) {
double val =
evaluator.evaluate(
new AgglomerativeNeighbor(
clustering, ClusterUtils.copyAndMergeClusters(clustering, i, j), ci, cj));
for (int ni = 0; ni < ci.length; ni++)
for (int nj = 0; nj < cj.length; nj++) scoreCache.set(ci[ni], cj[nj], val);
}
return scoreCache.get(ci[0], cj[0]);
}
