package de.lmu.ifi.dbs.elki.distance.similarityfunction;
/*
This file is part of ELKI:
Environment for Developing KDD-Applications Supported by Index-Structures
Copyright (C) 2012
Ludwig-Maximilians-Universität München
Lehr- und Forschungseinheit für Datenbanksysteme
ELKI Development Team
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU Affero General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU Affero General Public License for more details.
You should have received a copy of the GNU Affero General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
import java.util.Iterator;
import de.lmu.ifi.dbs.elki.database.ids.ArrayDBIDs;
import de.lmu.ifi.dbs.elki.database.ids.DBID;
import de.lmu.ifi.dbs.elki.database.ids.DBIDs;
import de.lmu.ifi.dbs.elki.database.relation.Relation;
import de.lmu.ifi.dbs.elki.distance.distancevalue.DoubleDistance;
import de.lmu.ifi.dbs.elki.index.preprocessed.snn.SharedNearestNeighborIndex;
import de.lmu.ifi.dbs.elki.index.preprocessed.snn.SharedNearestNeighborPreprocessor;
import de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.Parameterization;
/**
* SharedNearestNeighborSimilarityFunction with a pattern defined to accept
* Strings that define a non-negative Integer.
*
* @author Arthur Zimek
*
* @apiviz.has
* de.lmu.ifi.dbs.elki.index.preprocessed.snn.SharedNearestNeighborIndex
* .Factory
* @apiviz.uses Instance oneway - - «create»
*
* @param <O> object type
*/
// todo arthur comment class
public class FractionalSharedNearestNeighborSimilarityFunction<O> extends AbstractIndexBasedSimilarityFunction<O, SharedNearestNeighborIndex<O>, ArrayDBIDs, DoubleDistance> implements NormalizedSimilarityFunction<O, DoubleDistance> {
/**
* Constructor.
*
* @param indexFactory Index factory.
*/
public FractionalSharedNearestNeighborSimilarityFunction(SharedNearestNeighborIndex.Factory<O, SharedNearestNeighborIndex<O>> indexFactory) {
super(indexFactory);
}
@SuppressWarnings("unchecked")
@Override
public <T extends O> Instance<T> instantiate(Relation<T> database) {
SharedNearestNeighborIndex<O> indexi = indexFactory.instantiate((Relation<O>) database);
return (Instance<T>) new Instance<O>((Relation<O>) database, indexi);
}
/**
* Actual instance for a dataset.
*
* @author Erich Schubert
*
* @apiviz.uses SharedNearestNeighborIndex
*
* @param <T> Object type
*/
public static class Instance<T> extends AbstractIndexBasedSimilarityFunction.Instance<T, SharedNearestNeighborIndex<T>, ArrayDBIDs, DoubleDistance> {
/**
* Constructor.
*
* @param database Database
* @param preprocessor Preprocessor
*/
public Instance(Relation<T> database, SharedNearestNeighborIndex<T> preprocessor) {
super(database, preprocessor);
}
/**
* Compute the intersection size.
*
* @param neighbors1 SORTED neighbor ids of first
* @param neighbors2 SORTED neighbor ids of second
* @return Intersection size
*/
static protected int countSharedNeighbors(DBIDs neighbors1, DBIDs neighbors2) {
int intersection = 0;
Iterator<DBID> iter1 = neighbors1.iterator();
Iterator<DBID> iter2 = neighbors2.iterator();
DBID neighbors1ID = iter1.hasNext() ? iter1.next() : null;
DBID neighbors2ID = iter2.hasNext() ? iter2.next() : null;
while(neighbors1ID != null && neighbors2ID != null) {
if(neighbors1ID.equals(neighbors2ID)) {
intersection++;
neighbors1ID = iter1.hasNext() ? iter1.next() : null;
neighbors2ID = iter2.hasNext() ? iter2.next() : null;
}
else if(neighbors2ID.compareTo(neighbors1ID) > 0) {
neighbors1ID = iter1.hasNext() ? iter1.next() : null;
}
else // neighbors1ID > neighbors2ID
{
neighbors2ID = iter2.hasNext() ? iter2.next() : null;
}
}
return intersection;
}
@Override
public DoubleDistance similarity(DBID id1, DBID id2) {
DBIDs neighbors1 = index.getNearestNeighborSet(id1);
DBIDs neighbors2 = index.getNearestNeighborSet(id2);
int intersection = countSharedNeighbors(neighbors1, neighbors2);
return new DoubleDistance((double) intersection / index.getNumberOfNeighbors());
}
@Override
public DoubleDistance getDistanceFactory() {
return DoubleDistance.FACTORY;
}
}
@Override
public DoubleDistance getDistanceFactory() {
return DoubleDistance.FACTORY;
}
/**
* Parameterization class.
*
* @author Erich Schubert
*
* @apiviz.exclude
*
* @param <O> object type
*/
public static class Parameterizer<O> extends AbstractIndexBasedSimilarityFunction.Parameterizer<SharedNearestNeighborIndex.Factory<O, SharedNearestNeighborIndex<O>>> {
@Override
protected void makeOptions(Parameterization config) {
super.makeOptions(config);
configIndexFactory(config, SharedNearestNeighborIndex.Factory.class, SharedNearestNeighborPreprocessor.Factory.class);
}
@Override
protected FractionalSharedNearestNeighborSimilarityFunction<O> makeInstance() {
return new FractionalSharedNearestNeighborSimilarityFunction<O>(factory);
}
}
}