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package de.lmu.ifi.dbs.elki.math.linearalgebra.pca;
/*
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 java.util.ArrayList;
import java.util.List;
import de.lmu.ifi.dbs.elki.logging.Logging;
import de.lmu.ifi.dbs.elki.math.linearalgebra.EigenPair;
import de.lmu.ifi.dbs.elki.math.linearalgebra.SortedEigenPairs;
import de.lmu.ifi.dbs.elki.math.linearalgebra.Vector;
import de.lmu.ifi.dbs.elki.utilities.documentation.Description;
import de.lmu.ifi.dbs.elki.utilities.documentation.Title;
/**
* The NormalizingEigenPairFilter normalizes all eigenvectors s.t. <eigenvector,
* eigenvector> * eigenvalue = 1, where <,> is the standard dot product
*
* @author Simon Paradies
*/
@Title("Perecentage based Eigenpair filter")
@Description("Normalizes all eigenpairs, consisting of eigenvalue e and eigenvector v such that <v,v> * e = 1, where <,> is the standard dot product.")
public class NormalizingEigenPairFilter implements EigenPairFilter {
/**
* The logger for this class.
*/
private static final Logging logger = Logging.getLogger(NormalizingEigenPairFilter.class);
/**
* Provides a new EigenPairFilter that normalizes all eigenvectors s.t.
* eigenvalue * <eigenvector, eigenvector> = 1, where <,> is the standard dot
* product
*/
public NormalizingEigenPairFilter() {
super();
}
@Override
public FilteredEigenPairs filter(final SortedEigenPairs eigenPairs) {
// initialize strong and weak eigenpairs
// all normalized eigenpairs are regarded as strong
final List<EigenPair> strongEigenPairs = new ArrayList<EigenPair>();
final List<EigenPair> weakEigenPairs = new ArrayList<EigenPair>();
for(int i = 0; i < eigenPairs.size(); i++) {
final EigenPair eigenPair = eigenPairs.getEigenPair(i);
normalizeEigenPair(eigenPair);
strongEigenPairs.add(eigenPair);
}
if(logger.isDebugging()) {
final StringBuffer msg = new StringBuffer();
msg.append("strong EigenPairs = ").append(strongEigenPairs);
msg.append("\nweak EigenPairs = ").append(weakEigenPairs);
logger.debugFine(msg.toString());
}
return new FilteredEigenPairs(weakEigenPairs, strongEigenPairs);
}
/**
* Normalizes an eigenpair consisting of eigenvector v and eigenvalue e s.t.
* <v,v> * e = 1
*
* @param eigenPair the eigenpair to be normalized
*
*/
private void normalizeEigenPair(final EigenPair eigenPair) {
final Vector eigenvector = eigenPair.getEigenvector();
final double scaling = 1.0 / Math.sqrt(eigenPair.getEigenvalue()) * eigenvector.normF();
eigenvector.timesEquals(scaling);
}
}
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