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package de.lmu.ifi.dbs.elki.distance.distancefunction.adapter;
/*
This file is part of ELKI:
Environment for Developing KDD-Applications Supported by Index-Structures
Copyright (C) 2013
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 de.lmu.ifi.dbs.elki.data.type.TypeInformation;
import de.lmu.ifi.dbs.elki.database.ids.DBIDRef;
import de.lmu.ifi.dbs.elki.database.query.distance.DistanceQuery;
import de.lmu.ifi.dbs.elki.database.query.similarity.SimilarityQuery;
import de.lmu.ifi.dbs.elki.database.relation.Relation;
import de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractDatabaseDistanceFunction;
import de.lmu.ifi.dbs.elki.distance.distancefunction.DistanceFunction;
import de.lmu.ifi.dbs.elki.distance.distancevalue.DoubleDistance;
import de.lmu.ifi.dbs.elki.distance.distancevalue.NumberDistance;
import de.lmu.ifi.dbs.elki.distance.similarityfunction.FractionalSharedNearestNeighborSimilarityFunction;
import de.lmu.ifi.dbs.elki.distance.similarityfunction.NormalizedSimilarityFunction;
import de.lmu.ifi.dbs.elki.utilities.optionhandling.AbstractParameterizer;
import de.lmu.ifi.dbs.elki.utilities.optionhandling.OptionID;
import de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.Parameterization;
import de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.ObjectParameter;
/**
* Adapter from a normalized similarity function to a distance function.
*
* Note: The derived distance function will usually not satisfy the triangle
* equation.
*
* @author Erich Schubert
*
* @apiviz.has Instance
*
* @param <O> object class to process
*/
public abstract class AbstractSimilarityAdapter<O> extends AbstractDatabaseDistanceFunction<O, DoubleDistance> {
/**
* Parameter to specify the similarity function to derive the distance between
* database objects from. Must extend
* {@link de.lmu.ifi.dbs.elki.distance.similarityfunction.NormalizedSimilarityFunction}
* .
* <p>
* Key: {@code -adapter.similarityfunction}
* </p>
* <p>
* Default value:
* {@link de.lmu.ifi.dbs.elki.distance.similarityfunction.FractionalSharedNearestNeighborSimilarityFunction}
* </p>
*/
public static final OptionID SIMILARITY_FUNCTION_ID = new OptionID("adapter.similarityfunction", "Similarity function to derive the distance between database objects from.");
/**
* Holds the similarity function.
*/
protected NormalizedSimilarityFunction<? super O> similarityFunction;
/**
* Constructor.
*
* @param similarityFunction Similarity function to use.
*/
public AbstractSimilarityAdapter(NormalizedSimilarityFunction<? super O> similarityFunction) {
super();
this.similarityFunction = similarityFunction;
}
@Override
public TypeInformation getInputTypeRestriction() {
return similarityFunction.getInputTypeRestriction();
}
@Override
public boolean isSymmetric() {
return similarityFunction.isSymmetric();
}
@Override
public DoubleDistance getDistanceFactory() {
return DoubleDistance.FACTORY;
}
@Override
abstract public <T extends O> DistanceQuery<T, DoubleDistance> instantiate(Relation<T> database);
@Override
public boolean equals(Object obj) {
if (obj == null) {
return false;
}
// Same subclass
if (!this.getClass().equals(obj.getClass())) {
return false;
}
// Same similarity function
AbstractSimilarityAdapter<?> other = (AbstractSimilarityAdapter<?>) obj;
return other.similarityFunction.equals(other.similarityFunction);
}
/**
* Inner proxy class for SNN distance function.
*
* @author Erich Schubert
*
* @param <O> Object type
*/
public abstract static class Instance<O> extends AbstractDatabaseDistanceFunction.Instance<O, DoubleDistance> {
/**
* The similarity query we use.
*/
private SimilarityQuery<? super O, ? extends NumberDistance<?, ?>> similarityQuery;
/**
* Constructor.
*
* @param database Database to use
* @param parent Parent distance function
* @param similarityQuery Similarity query
*/
public Instance(Relation<O> database, DistanceFunction<? super O, DoubleDistance> parent, SimilarityQuery<? super O, ? extends NumberDistance<?, ?>> similarityQuery) {
super(database, parent);
this.similarityQuery = similarityQuery;
}
/**
* Transformation function.
*
* @param similarity Similarity value
* @return Distance value
*/
public abstract double transform(double similarity);
@Override
public DoubleDistance distance(DBIDRef id1, DBIDRef id2) {
final NumberDistance<?, ?> sim = similarityQuery.similarity(id1, id2);
return new DoubleDistance(transform(sim.doubleValue()));
}
@Override
public DoubleDistance getDistanceFactory() {
return DoubleDistance.FACTORY;
}
}
/**
* Parameterization class.
*
* @author Erich Schubert
*
* @apiviz.exclude
*/
public abstract static class Parameterizer<O> extends AbstractParameterizer {
/**
* Holds the similarity function.
*/
protected NormalizedSimilarityFunction<? super O> similarityFunction = null;
@Override
protected void makeOptions(Parameterization config) {
super.makeOptions(config);
final ObjectParameter<NormalizedSimilarityFunction<? super O>> param = new ObjectParameter<>(SIMILARITY_FUNCTION_ID, NormalizedSimilarityFunction.class, FractionalSharedNearestNeighborSimilarityFunction.class);
if (config.grab(param)) {
similarityFunction = param.instantiateClass(config);
}
}
}
}
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