@Override
public void processNewResult(ResultHierarchy hier, Result newResult) {
// We may just have added this result.
if (newResult instanceof Clustering && isReferenceResult((Clustering<?>) newResult)) {
return;
}
Database db = ResultUtil.findDatabase(hier);
List<Clustering<?>> crs = ResultUtil.getClusteringResults(newResult);
if (crs == null || crs.size() < 1) {
return;
}
// Compute the reference clustering
Clustering<?> refc = null;
// Try to find an existing reference clustering (globally)
{
Collection<Clustering<?>> cs = ResultUtil.filterResults(hier, db, Clustering.class);
for (Clustering<?> test : cs) {
if (isReferenceResult(test)) {
refc = test;
break;
}
}
}
// Try to find an existing reference clustering (locally)
if (refc == null) {
Collection<Clustering<?>> cs = ResultUtil.filterResults(hier, newResult, Clustering.class);
for (Clustering<?> test : cs) {
if (isReferenceResult(test)) {
refc = test;
break;
}
}
}
if (refc == null) {
LOG.debug("Generating a new reference clustering.");
Result refres = referencealg.run(db);
List<Clustering<?>> refcrs = ResultUtil.getClusteringResults(refres);
if (refcrs.size() == 0) {
LOG.warning("Reference algorithm did not return a clustering result!");
return;
}
if (refcrs.size() > 1) {
LOG.warning("Reference algorithm returned more than one result!");
}
refc = refcrs.get(0);
} else {
LOG.debug("Using existing clustering: " + refc.getLongName() + " " + refc.getShortName());
}
for (Clustering<?> c : crs) {
if (c == refc) {
continue;
}
evaluteResult(db, c, refc);
}
}
@Override
public void processNewResult(ResultHierarchy hier, Result result) {
List<Clustering<?>> crs = ResultUtil.getClusteringResults(result);
if (crs.size() < 1) {
return;
}
Database db = ResultUtil.findDatabase(hier);
Relation<? extends NumberVector> rel = db.getRelation(this.distance.getInputTypeRestriction());
for (Clustering<?> c : crs) {
evaluateClustering(db, rel, c);
}
}
@Override
public void processNewResult(ResultHierarchy hier, Result result) {
List<Clustering<?>> crs = ResultUtil.getClusteringResults(result);
if (crs.size() < 1) {
return;
}
Database db = ResultUtil.findDatabase(hier);
Relation<O> rel = db.getRelation(distance.getInputTypeRestriction());
DistanceQuery<O> dq = db.getDistanceQuery(rel, distance);
for (Clustering<?> c : crs) {
evaluateClustering(db, rel, dq, c);
}
}