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Diffstat (limited to 'src/de/lmu/ifi/dbs/elki/distance/distancefunction/subspace/HiSCDistanceFunction.java')
| -rw-r--r-- | src/de/lmu/ifi/dbs/elki/distance/distancefunction/subspace/HiSCDistanceFunction.java | 158 |
1 files changed, 0 insertions, 158 deletions
diff --git a/src/de/lmu/ifi/dbs/elki/distance/distancefunction/subspace/HiSCDistanceFunction.java b/src/de/lmu/ifi/dbs/elki/distance/distancefunction/subspace/HiSCDistanceFunction.java deleted file mode 100644 index a339c389..00000000 --- a/src/de/lmu/ifi/dbs/elki/distance/distancefunction/subspace/HiSCDistanceFunction.java +++ /dev/null @@ -1,158 +0,0 @@ -package de.lmu.ifi.dbs.elki.distance.distancefunction.subspace; - -/* - 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 java.util.BitSet; - -import de.lmu.ifi.dbs.elki.data.NumberVector; -import de.lmu.ifi.dbs.elki.database.relation.Relation; -import de.lmu.ifi.dbs.elki.database.relation.RelationUtil; -import de.lmu.ifi.dbs.elki.distance.distancevalue.PreferenceVectorBasedCorrelationDistance; -import de.lmu.ifi.dbs.elki.index.preprocessed.preference.HiSCPreferenceVectorIndex; -import de.lmu.ifi.dbs.elki.logging.Logging; -import de.lmu.ifi.dbs.elki.utilities.ClassGenericsUtil; -import de.lmu.ifi.dbs.elki.utilities.FormatUtil; -import de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.Parameterization; - -/** - * Distance function used in the HiSC algorithm. - * - * @author Elke Achtert - * - * @apiviz.has Instance - * - * @param <V> the type of NumberVector to compute the distances in between - */ -public class HiSCDistanceFunction<V extends NumberVector<?>> extends AbstractPreferenceVectorBasedCorrelationDistanceFunction<V, HiSCPreferenceVectorIndex<V>> { - /** - * Logger for debug. - */ - private static final Logging LOG = Logging.getLogger(HiSCDistanceFunction.class); - - /** - * Constructor. - * - * @param indexFactory HiSC index factory - * @param epsilon Epsilon value - */ - public HiSCDistanceFunction(HiSCPreferenceVectorIndex.Factory<V> indexFactory, double epsilon) { - super(indexFactory, epsilon); - } - - @Override - public <T extends V> Instance<T> instantiate(Relation<T> database) { - // We can't really avoid these warnings, due to a limitation in Java - // Generics (AFAICT) - @SuppressWarnings("unchecked") - HiSCPreferenceVectorIndex<T> indexinst = (HiSCPreferenceVectorIndex<T>) indexFactory.instantiate((Relation<V>) database); - return new Instance<>(database, indexinst, getEpsilon(), this); - } - - /** - * The actual instance bound to a particular database. - * - * @author Erich Schubert - * - * @param <V> the type of NumberVector to compute the distances in between - */ - public static class Instance<V extends NumberVector<?>> extends AbstractPreferenceVectorBasedCorrelationDistanceFunction.Instance<V, HiSCPreferenceVectorIndex<V>> { - /** - * Constructor. - * - * @param database Database - * @param index Preprocessed index - * @param epsilon Epsilon - * @param distanceFunction parent distance function - */ - public Instance(Relation<V> database, HiSCPreferenceVectorIndex<V> index, double epsilon, HiSCDistanceFunction<? super V> distanceFunction) { - super(database, index, epsilon, distanceFunction); - } - - /** - * Computes the correlation distance between the two specified vectors - * according to the specified preference vectors. - * - * @param v1 first vector - * @param v2 second vector - * @param pv1 the first preference vector - * @param pv2 the second preference vector - * @return the correlation distance between the two specified vectors - */ - @Override - public PreferenceVectorBasedCorrelationDistance correlationDistance(V v1, V v2, BitSet pv1, BitSet pv2) { - BitSet commonPreferenceVector = (BitSet) pv1.clone(); - commonPreferenceVector.and(pv2); - int dim = v1.getDimensionality(); - - // number of zero values in commonPreferenceVector - Integer subspaceDim = dim - commonPreferenceVector.cardinality(); - - // special case: v1 and v2 are in parallel subspaces - double dist1 = weightedDistance(v1, v2, pv1); - double dist2 = weightedDistance(v1, v2, pv2); - - if(Math.max(dist1, dist2) > epsilon) { - subspaceDim++; - if(LOG.isDebugging()) { - //Representation<String> rep = rep.getObjectLabelQuery(); - StringBuilder msg = new StringBuilder(); - msg.append("\ndist1 ").append(dist1); - msg.append("\ndist2 ").append(dist2); - // msg.append("\nv1 ").append(rep.get(v1.getID())); - // msg.append("\nv2 ").append(rep.get(v2.getID())); - msg.append("\nsubspaceDim ").append(subspaceDim); - msg.append("\ncommon pv ").append(FormatUtil.format(dim, commonPreferenceVector)); - LOG.debugFine(msg.toString()); - } - } - - // flip commonPreferenceVector for distance computation in common subspace - BitSet inverseCommonPreferenceVector = (BitSet) commonPreferenceVector.clone(); - inverseCommonPreferenceVector.flip(0, dim); - - return new PreferenceVectorBasedCorrelationDistance(RelationUtil.dimensionality(relation), subspaceDim, weightedDistance(v1, v2, inverseCommonPreferenceVector), commonPreferenceVector); - } - } - - /** - * Parameterization class. - * - * @author Erich Schubert - * - * @apiviz.exclude - */ - public static class Parameterizer<V extends NumberVector<?>> extends AbstractPreferenceVectorBasedCorrelationDistanceFunction.Parameterizer<HiSCPreferenceVectorIndex.Factory<V>> { - @Override - protected void makeOptions(Parameterization config) { - super.makeOptions(config); - Class<HiSCPreferenceVectorIndex.Factory<V>> cls = ClassGenericsUtil.uglyCastIntoSubclass(HiSCPreferenceVectorIndex.Factory.class); - factory = config.tryInstantiate(cls); - } - - @Override - protected HiSCDistanceFunction<V> makeInstance() { - return new HiSCDistanceFunction<>(factory, epsilon); - } - } -}
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