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Diffstat (limited to 'src/de/lmu/ifi/dbs/elki/distance/distancefunction/adapter/AbstractSimilarityAdapter.java')
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1 files changed, 183 insertions, 0 deletions
diff --git a/src/de/lmu/ifi/dbs/elki/distance/distancefunction/adapter/AbstractSimilarityAdapter.java b/src/de/lmu/ifi/dbs/elki/distance/distancefunction/adapter/AbstractSimilarityAdapter.java new file mode 100644 index 00000000..d0a60c53 --- /dev/null +++ b/src/de/lmu/ifi/dbs/elki/distance/distancefunction/adapter/AbstractSimilarityAdapter.java @@ -0,0 +1,183 @@ +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) 2011 +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.DBID; +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 = OptionID.getOrCreateOptionID("adapter.similarityfunction", "Similarity function to derive the distance between database objects from."); + + /** + * Holds the similarity function. + */ + protected NormalizedSimilarityFunction<? super O, ? extends NumberDistance<?, ?>> similarityFunction; + + /** + * Constructor. + * + * @param similarityFunction Similarity function to use. + */ + public AbstractSimilarityAdapter(NormalizedSimilarityFunction<? super O, ? extends NumberDistance<?, ?>> 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(DBID id1, DBID 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 static abstract class Parameterizer<O> extends AbstractParameterizer { + /** + * Holds the similarity function. + */ + protected NormalizedSimilarityFunction<? super O, ? extends NumberDistance<?, ?>> similarityFunction = null; + + @Override + protected void makeOptions(Parameterization config) { + super.makeOptions(config); + final ObjectParameter<NormalizedSimilarityFunction<? super O, ? extends NumberDistance<?, ?>>> param = new ObjectParameter<NormalizedSimilarityFunction<? super O, ? extends NumberDistance<?, ?>>>(SIMILARITY_FUNCTION_ID, NormalizedSimilarityFunction.class, FractionalSharedNearestNeighborSimilarityFunction.class); + if(config.grab(param)) { + similarityFunction = param.instantiateClass(config); + } + } + } +}
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