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package de.lmu.ifi.dbs.elki.distance.distancefunction;
/*
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 de.lmu.ifi.dbs.elki.data.NumberVector;
import de.lmu.ifi.dbs.elki.data.type.VectorFieldTypeInformation;
import de.lmu.ifi.dbs.elki.math.MathUtil;
import de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix;
import de.lmu.ifi.dbs.elki.math.linearalgebra.Vector;
/**
* Provides the Weighted distance for feature vectors.
*
* @author Elke Achtert
*/
// TODO: Factory with parameterizable weight matrix?
public class WeightedDistanceFunction extends AbstractVectorDoubleDistanceFunction {
/**
* The weight matrix.
*/
protected Matrix weightMatrix;
/**
* Provides the Weighted distance for feature vectors.
*
* @param weightMatrix weight matrix
*/
public WeightedDistanceFunction(Matrix weightMatrix) {
super();
this.weightMatrix = weightMatrix;
assert (weightMatrix.getColumnDimensionality() == weightMatrix.getRowDimensionality());
}
/**
* Provides the Weighted distance for feature vectors.
*
* @return the Weighted distance between the given two vectors
*/
@Override
public double doubleDistance(NumberVector<?> o1, NumberVector<?> o2) {
assert (o1.getDimensionality() == o2.getDimensionality()) : "Different dimensionality of FeatureVectors" + "\n first argument: " + o1.toString() + "\n second argument: " + o2.toString();
Vector o1_minus_o2 = o1.getColumnVector().minusEquals(o2.getColumnVector());
return MathUtil.mahalanobisDistance(weightMatrix, o1_minus_o2);
}
@Override
public VectorFieldTypeInformation<? super NumberVector<?>> getInputTypeRestriction() {
return new VectorFieldTypeInformation<NumberVector<?>>(NumberVector.class, weightMatrix.getColumnDimensionality());
}
}
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