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package de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries;
/*
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.distance.distancevalue.DoubleDistance;
import de.lmu.ifi.dbs.elki.utilities.documentation.Reference;
import de.lmu.ifi.dbs.elki.utilities.documentation.Title;
/**
* Provides the Dynamic Time Warping distance for FeatureVectors.
*
* @author Thomas Bernecker
*/
@Title("Dynamic Time Warping Distance Function")
@Reference(authors = "Berndt, D. and Clifford, J.", title = "Using dynamic time warping to find patterns in time series", booktitle = "AAAI-94 Workshop on Knowledge Discovery in Databases, 1994", url = "http://www.aaai.org/Papers/Workshops/1994/WS-94-03/WS94-03-031.pdf")
public class DTWDistanceFunction extends AbstractEditDistanceFunction {
/**
* Constructor.
*
* @param bandSize Band size
*/
public DTWDistanceFunction(double bandSize) {
super(bandSize);
}
/**
* Provides the Dynamic Time Warping distance between the given two vectors.
*
* @return the Dynamic Time Warping distance between the given two vectors as
* an instance of {@link DoubleDistance DoubleDistance}.
*/
@Override
public double doubleDistance(NumberVector<?, ?> v1, NumberVector<?, ?> v2) {
// Current and previous columns of the matrix
double[] curr = new double[v2.getDimensionality()];
double[] prev = new double[v2.getDimensionality()];
// size of edit distance band
int band = (int) Math.ceil(v2.getDimensionality() * bandSize);
// bandsize is the maximum allowed distance to the diagonal
// System.out.println("len1: " + features1.length + ", len2: " +
// features2.length + ", band: " + band);
for(int i = 0; i < v1.getDimensionality(); i++) {
// Swap current and prev arrays. We'll just overwrite the new curr.
{
double[] temp = prev;
prev = curr;
curr = temp;
}
int l = i - (band + 1);
if(l < 0) {
l = 0;
}
int r = i + (band + 1);
if(r > (v2.getDimensionality() - 1)) {
r = (v2.getDimensionality() - 1);
}
for(int j = l; j <= r; j++) {
if(Math.abs(i - j) <= band) {
double val1 = v1.doubleValue(i + 1);
double val2 = v2.doubleValue(j + 1);
double diff = (val1 - val2);
// Formally: diff = Math.sqrt(diff * diff);
double cost = diff * diff;
if((i + j) != 0) {
if((i == 0) || ((j != 0) && ((prev[j - 1] > curr[j - 1]) && (curr[j - 1] < prev[j])))) {
// del
cost += curr[j - 1];
}
else if((j == 0) || ((i != 0) && ((prev[j - 1] > prev[j]) && (prev[j] < curr[j - 1])))) {
// ins
cost += prev[j];
}
else {
// match
cost += prev[j - 1];
}
}
curr[j] = cost;
}
else {
curr[j] = Double.POSITIVE_INFINITY; // outside band
}
}
}
return Math.sqrt(curr[v2.getDimensionality() - 1]);
}
/**
* Parameterization class.
*
* @author Erich Schubert
*
* @apiviz.exclude
*/
public static class Parameterizer extends AbstractEditDistanceFunction.Parameterizer {
@Override
protected DTWDistanceFunction makeInstance() {
return new DTWDistanceFunction(bandSize);
}
}
}
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