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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) 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.Arrays;
import de.lmu.ifi.dbs.elki.data.NumberVector;
/**
* Weighted version of the Euclidean distance function.
*
* @author Erich Schubert
*/
// TODO: make parameterizable; add optimized variants
public class WeightedLPNormDistanceFunction extends LPNormDistanceFunction {
/**
* Weight array
*/
protected double[] weights;
/**
* Constructor.
*
* @param p p value
* @param weights Weight vector
*/
public WeightedLPNormDistanceFunction(double p, double[] weights) {
super(p);
this.weights = weights;
}
@Override
public double doubleDistance(NumberVector<?, ?> v1, NumberVector<?, ?> v2) {
final int dim = weights.length;
if(dim != v1.getDimensionality()) {
throw new IllegalArgumentException("Dimensionality of FeatureVector doesn't match weights!");
}
if(dim != v2.getDimensionality()) {
throw new IllegalArgumentException("Dimensionality of FeatureVector doesn't match weights!");
}
final double p = getP();
double sqrDist = 0;
for(int i = 1; i <= dim; i++) {
final double delta = Math.abs(v1.doubleValue(i) - v2.doubleValue(i));
sqrDist += Math.pow(delta, p) * weights[i - 1];
}
return Math.pow(sqrDist, 1.0 / p);
}
@Override
public boolean equals(Object obj) {
if(this == obj) {
return true;
}
if(obj == null) {
return false;
}
if(!(obj instanceof WeightedLPNormDistanceFunction)) {
if(obj instanceof LPNormDistanceFunction && super.equals(obj)) {
for(double d : weights) {
if(d != 1.0) {
return false;
}
}
return true;
}
return false;
}
WeightedLPNormDistanceFunction other = (WeightedLPNormDistanceFunction) obj;
return Arrays.equals(this.weights, other.weights);
}
}
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