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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) 2015
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.spatial.SpatialComparable;
import de.lmu.ifi.dbs.elki.utilities.BitsUtil;
/**
* Euclidean distance function between {@link NumberVector}s only in specified
* dimensions.
*
* @author Elke Achtert
*/
public class SubspaceEuclideanDistanceFunction extends SubspaceLPNormDistanceFunction {
/**
* Constructor.
*
* @param dimensions Selected dimensions
*/
public SubspaceEuclideanDistanceFunction(long[] dimensions) {
super(2.0, dimensions);
}
/**
* Constructor.
*
* @param v1 first feature vector
* @param v2 second feature vector
* @return the Euclidean distance between two given feature vectors in the
* selected dimensions
*/
@Override
public double distance(NumberVector v1, NumberVector v2) {
if(v1.getDimensionality() != v2.getDimensionality()) {
throw new IllegalArgumentException("Different dimensionality of FeatureVectors\n " + "first argument: " + v1 + "\n " + "second argument: " + v2);
}
double sqrDist = 0;
for(int d = BitsUtil.nextSetBit(dimensions, 0); d >= 0; d = BitsUtil.nextSetBit(dimensions, d + 1)) {
final double delta = v1.doubleValue(d) - v2.doubleValue(d);
sqrDist += delta * delta;
}
return Math.sqrt(sqrDist);
}
@Override
protected double minDistObject(SpatialComparable mbr, NumberVector v) {
if(mbr.getDimensionality() != v.getDimensionality()) {
throw new IllegalArgumentException("Different dimensionality of objects\n " + "first argument: " + mbr.toString() + "\n " + "second argument: " + v.toString());
}
double sqrDist = 0;
for(int d = BitsUtil.nextSetBit(dimensions, 0); d >= 0; d = BitsUtil.nextSetBit(dimensions, d + 1)) {
final double delta;
final double value = v.doubleValue(d);
final double omin = mbr.getMin(d);
if(value < omin) {
delta = omin - value;
}
else {
final double omax = mbr.getMax(d);
if(value > omax) {
delta = value - omax;
}
else {
continue;
}
}
sqrDist += delta * delta;
}
return Math.sqrt(sqrDist);
}
@Override
public double minDist(SpatialComparable mbr1, SpatialComparable mbr2) {
if(mbr1.getDimensionality() != mbr2.getDimensionality()) {
throw new IllegalArgumentException("Different dimensionality of objects\n " + "first argument: " + mbr1.toString() + "\n " + "second argument: " + mbr2.toString());
}
double sqrDist = 0;
for(int d = BitsUtil.nextSetBit(dimensions, 0); d >= 0; d = BitsUtil.nextSetBit(dimensions, d + 1)) {
final double delta;
final double max1 = mbr1.getMax(d);
final double min2 = mbr2.getMin(d);
if(max1 < min2) {
delta = min2 - max1;
}
else {
final double min1 = mbr1.getMin(d);
final double max2 = mbr2.getMax(d);
if(min1 > max2) {
delta = min1 - max2;
}
else { // The mbrs intersect!
continue;
}
}
sqrDist += delta * delta;
}
return Math.sqrt(sqrDist);
}
@Override
public double norm(NumberVector obj) {
double sqrDist = 0;
for(int d = BitsUtil.nextSetBit(dimensions, 0); d >= 0; d = BitsUtil.nextSetBit(dimensions, d + 1)) {
final double delta = obj.doubleValue(d);
sqrDist += delta * delta;
}
return Math.sqrt(sqrDist);
}
/**
* Parameterization class.
*
* @author Erich Schubert
*
* @apiviz.exclude
*/
public static class Parameterizer extends AbstractDimensionsSelectingDistanceFunction.Parameterizer {
@Override
protected SubspaceEuclideanDistanceFunction makeInstance() {
return new SubspaceEuclideanDistanceFunction(dimensions);
}
}
}
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