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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 static org.junit.Assert.assertEquals;
import static org.junit.Assert.assertTrue;
import java.util.ArrayList;
import java.util.List;
import java.util.Random;
import org.junit.Test;
import de.lmu.ifi.dbs.elki.JUnit4Test;
import de.lmu.ifi.dbs.elki.data.ModifiableHyperBoundingBox;
import de.lmu.ifi.dbs.elki.data.NumberVector;
import de.lmu.ifi.dbs.elki.distance.distancefunction.colorhistogram.HistogramIntersectionDistanceFunction;
import de.lmu.ifi.dbs.elki.distance.distancevalue.Distance;
import de.lmu.ifi.dbs.elki.math.linearalgebra.Vector;
/**
* Validate spatial distance functions by ensuring that mindist <= distance for
* random objects.
*
* @author Erich Schubert
*
*/
public class SpatialPrimitiveDistanceFunctionTest implements JUnit4Test {
@Test
public void testSpatialDistanceConsistency() {
final Random rnd = new Random(0);
final int dim = 7;
final int iters = 10000;
List<SpatialPrimitiveDistanceFunction<? super NumberVector<?>, ?>> dists = new ArrayList<SpatialPrimitiveDistanceFunction<? super NumberVector<?>, ?>>();
dists.add(EuclideanDistanceFunction.STATIC);
dists.add(ManhattanDistanceFunction.STATIC);
dists.add(MaximumDistanceFunction.STATIC);
dists.add(MinimumDistanceFunction.STATIC);
dists.add(new LPNormDistanceFunction(3));
dists.add(new LPNormDistanceFunction(.5));
dists.add(CanberraDistanceFunction.STATIC);
// Histogram intersection distance isn't proper for negative values
// dists.add(HistogramIntersectionDistanceFunction.STATIC);
dists.add(SquaredEuclideanDistanceFunction.STATIC);
dists.add(ArcCosineDistanceFunction.STATIC);
dists.add(CosineDistanceFunction.STATIC);
double[] d1 = new double[dim];
double[] d2 = new double[dim];
double[] d3 = new double[dim];
double[] d4 = new double[dim];
Vector v1 = new Vector(d1);
ModifiableHyperBoundingBox mbr = new ModifiableHyperBoundingBox(d2, d3);
Vector v2 = new Vector(d4);
for(int i = 0; i < iters; i++) {
for(int d = 0; d < dim; d++) {
d1[d] = (rnd.nextDouble() - .5) * 2E4;
d2[d] = (rnd.nextDouble() - .5) * 2E4;
d3[d] = (rnd.nextDouble() - .5) * 2E4;
if(d2[d] > d3[d]) {
double t = d2[d];
d2[d] = d3[d];
d3[d] = t;
}
double m = rnd.nextDouble();
d4[d] = m * d2[d] + (1 - m) * d3[d];
}
for(SpatialPrimitiveDistanceFunction<? super NumberVector<?>, ?> dis : dists) {
compareDistances(v1, mbr, v2, dis);
}
}
}
@Test
public void testSpatialDistanceConsistencyPositive() {
final Random rnd = new Random(1);
final int dim = 7;
final int iters = 10000;
List<SpatialPrimitiveDistanceFunction<? super NumberVector<?>, ?>> dists = new ArrayList<SpatialPrimitiveDistanceFunction<? super NumberVector<?>, ?>>();
dists.add(EuclideanDistanceFunction.STATIC);
dists.add(ManhattanDistanceFunction.STATIC);
dists.add(MaximumDistanceFunction.STATIC);
dists.add(MinimumDistanceFunction.STATIC);
dists.add(new LPNormDistanceFunction(3));
dists.add(new LPNormDistanceFunction(.5));
dists.add(CanberraDistanceFunction.STATIC);
dists.add(HistogramIntersectionDistanceFunction.STATIC);
dists.add(SquaredEuclideanDistanceFunction.STATIC);
dists.add(ArcCosineDistanceFunction.STATIC);
dists.add(CosineDistanceFunction.STATIC);
double[] d1 = new double[dim];
double[] d2 = new double[dim];
double[] d3 = new double[dim];
double[] d4 = new double[dim];
Vector v1 = new Vector(d1);
ModifiableHyperBoundingBox mbr = new ModifiableHyperBoundingBox(d2, d3);
Vector v2 = new Vector(d4);
for(int i = 0; i < iters; i++) {
for(int d = 0; d < dim; d++) {
d1[d] = rnd.nextDouble() * 2E4;
d2[d] = rnd.nextDouble() * 2E4;
d3[d] = rnd.nextDouble() * 2E4;
if(d2[d] > d3[d]) {
double t = d2[d];
d2[d] = d3[d];
d3[d] = t;
}
double m = rnd.nextDouble();
d4[d] = m * d2[d] + (1 - m) * d3[d];
}
for(SpatialPrimitiveDistanceFunction<? super NumberVector<?>, ?> dis : dists) {
compareDistances(v1, mbr, v2, dis);
}
}
}
protected <D extends Distance<D>> void compareDistances(Vector v1, ModifiableHyperBoundingBox mbr, Vector v2, SpatialPrimitiveDistanceFunction<? super NumberVector<?>, D> dist) {
D exact = dist.distance(v1, v2);
D mind = dist.minDist(v1, v2);
D mbrd = dist.minDist(v1, mbr);
assertEquals("Not same: " + dist.toString(), exact, mind);
assertTrue("Not smaller:" + dist.toString() + " " + mbrd + " > " + exact + " " + mbr + " " + v1, mbrd.compareTo(exact) <= 0);
}
}
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