@Override
public boolean contains(DBIDRef o) {
for (DBIDIter iter = iter(); iter.valid(); iter.advance()) {
if (DBIDUtil.equal(iter, o)) {
return true;
}
}
return false;
}
/**
* Run the ODIN algorithm
*
* @param database Database to run on.
* @param relation Relation to process.
* @return ODIN outlier result.
*/
public OutlierResult run(Database database, Relation<O> relation) {
// Get the query functions:
DistanceQuery<O> dq = database.getDistanceQuery(relation, getDistanceFunction());
KNNQuery<O> knnq = database.getKNNQuery(dq, k);
// Get the objects to process, and a data storage for counting and output:
DBIDs ids = relation.getDBIDs();
WritableDoubleDataStore scores =
DataStoreUtil.makeDoubleStorage(ids, DataStoreFactory.HINT_DB, 0.);
double inc = 1. / (k - 1);
double min = Double.POSITIVE_INFINITY, max = 0.0;
// Process all objects
for (DBIDIter iter = ids.iter(); iter.valid(); iter.advance()) {
// Find the nearest neighbors (using an index, if available!)
DBIDs neighbors = knnq.getKNNForDBID(iter, k);
// For each neighbor, except ourselves, increase the in-degree:
for (DBIDIter nei = neighbors.iter(); nei.valid(); nei.advance()) {
if (DBIDUtil.equal(iter, nei)) {
continue;
}
final double value = scores.doubleValue(nei) + inc;
if (value < min) {
min = value;
}
if (value > max) {
max = value;
}
scores.put(nei, value);
}
}
// Wrap the result and add metadata.
OutlierScoreMeta meta = new InvertedOutlierScoreMeta(min, max, 0., inc * (ids.size() - 1), 1);
DoubleRelation rel = new MaterializedDoubleRelation("ODIN In-Degree", "odin", scores, ids);
return new OutlierResult(meta, rel);
}
