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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) 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.type.TypeUtil;
import de.lmu.ifi.dbs.elki.data.type.VectorTypeInformation;
import de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractNumberVectorDistanceFunction;
import de.lmu.ifi.dbs.elki.utilities.documentation.Reference;
import de.lmu.ifi.dbs.elki.utilities.documentation.Title;
import de.lmu.ifi.dbs.elki.utilities.optionhandling.AbstractParameterizer;
import de.lmu.ifi.dbs.elki.utilities.optionhandling.OptionID;
import de.lmu.ifi.dbs.elki.utilities.optionhandling.constraints.CommonConstraints;
import de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.Parameterization;
import de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.DoubleParameter;
/**
* Longest Common Subsequence distance for numerical vectors.
*
* Adapted for Java, based on Matlab Code by Michalis Vlachos. Original
* Copyright Notice:
*
* BEGIN COPYRIGHT NOTICE
*
* lcsMatching code -- (c) 2002 Michalis Vlachos
* (http://www.cs.ucr.edu/~mvlachos)
*
* This code is provided as is, with no guarantees except that bugs are almost
* surely present. Published reports of research using this code (or a modified
* version) should cite the article that describes the algorithm:
*
* <p>
* M. Vlachos, M. Hadjieleftheriou, D. Gunopulos, E. Keogh:<br />
* Indexing Multi-Dimensional Time-Series with Support for Multiple Distance
* Measures<br />
* In Proc. of 9th SIGKDD, Washington, DC, 2003
* </p>
*
* Comments and bug reports are welcome. Email to mvlachos@cs.ucr.edu I would
* also appreciate hearing about how you used this code, improvements that you
* have made to it.
*
* You are free to modify, extend or distribute this code, as long as this
* copyright notice is included whole and unchanged.
*
* END COPYRIGHT NOTICE
*
*
* @author Thomas Bernecker
* @since 0.2
*/
@Title("Longest Common Subsequence distance function")
@Reference(authors = "M. Vlachos, M. Hadjieleftheriou, D. Gunopulos, E. Keogh", //
title = "Indexing Multi-Dimensional Time-Series with Support for Multiple Distance Measures", //
booktitle = "Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining", //
url = "http://dx.doi.org/10.1145/956750.956777")
public class LCSSDistanceFunction extends AbstractNumberVectorDistanceFunction {
/**
* Keeps the currently set pDelta.
*/
private double pDelta;
/**
* Keeps the currently set pEpsilon.
*/
private double pEpsilon;
/**
* Constructor.
*
* @param pDelta pDelta
* @param pEpsilon pEpsilon
*/
public LCSSDistanceFunction(double pDelta, double pEpsilon) {
super();
this.pDelta = pDelta;
this.pEpsilon = pEpsilon;
}
@Override
public double distance(NumberVector v1, NumberVector v2) {
final int dim1 = v1.getDimensionality(), dim2 = v2.getDimensionality();
if(dim1 > dim2) {
return distance(v2, v1);
}
final int delta = (int) Math.ceil(dim2 * pDelta);
// Compute value range, for scaling epsilon:
final double epsilon = getRange(v1, dim1, v2, dim2) * pEpsilon;
double[] curr = new double[dim2 + 1];
double[] next = new double[dim2 + 1];
for(int i = 0; i < dim1; i++) {
final double ai = v1.doubleValue(i);
for(int j = Math.max(0, i - delta); j <= Math.min(dim2 - 1, i + delta); j++) {
final double bj = v2.doubleValue(j);
if((bj + epsilon) >= ai && (bj - epsilon) <= ai) { // match
next[j + 1] = curr[j] + 1;
}
else if(curr[j + 1] > next[j]) { // ins
next[j + 1] = curr[j + 1];
}
else { // del
next[j + 1] = next[j];
}
}
// Swap
double[] tmp = curr;
curr = next;
next = tmp;
}
// search for maximum in the last line
double maxEntry = curr[1];
for(int i = 2; i < dim2 + 1; i++) {
maxEntry = (curr[i] > maxEntry) ? curr[i] : maxEntry;
}
final double sim = maxEntry / Math.min(dim1, dim2);
return 1. - sim;
}
public double getRange(NumberVector v1, final int dim1, NumberVector v2, final int dim2) {
double min = v1.doubleValue(0), max = min;
for(int i = 1; i < dim1; i++) {
final double v = v1.doubleValue(i);
min = (v < min) ? v : min;
max = (v > max) ? v : max;
}
for(int i = 0; i < dim2; i++) {
final double v = v2.doubleValue(i);
min = (v < min) ? v : min;
max = (v > max) ? v : max;
}
final double range = max - min;
return range;
}
@Override
public VectorTypeInformation<? super NumberVector> getInputTypeRestriction() {
return TypeUtil.NUMBER_VECTOR_VARIABLE_LENGTH;
}
@Override
public boolean equals(Object obj) {
if(obj == this) {
return true;
}
if(obj == null) {
return false;
}
if(!this.getClass().equals(obj.getClass())) {
return false;
}
return (this.pDelta == ((LCSSDistanceFunction) obj).pDelta) && (this.pEpsilon == ((LCSSDistanceFunction) obj).pEpsilon);
}
/**
* Parameterization class.
*
* @author Erich Schubert
*
* @apiviz.exclude
*/
public static class Parameterizer extends AbstractParameterizer {
/**
* PDELTA parameter
*/
public static final OptionID PDELTA_ID = new OptionID("lcss.pDelta", "the allowed deviation in x direction for LCSS alignment (positive double value, 0 <= pDelta <= 1)");
/**
* PEPSILON parameter
*/
public static final OptionID PEPSILON_ID = new OptionID("lcss.pEpsilon", "the allowed deviation in y direction for LCSS alignment (positive double value, 0 <= pEpsilon <= 1)");
/**
* Keeps the currently set pDelta.
*/
private double pDelta;
/**
* Keeps the currently set pEpsilon.
*/
private double pEpsilon;
@Override
protected void makeOptions(Parameterization config) {
super.makeOptions(config);
final DoubleParameter pDeltaP = new DoubleParameter(PDELTA_ID, 0.1)//
.addConstraint(CommonConstraints.GREATER_EQUAL_ZERO_DOUBLE)//
.addConstraint(CommonConstraints.LESS_EQUAL_ONE_DOUBLE);
if(config.grab(pDeltaP)) {
pDelta = pDeltaP.doubleValue();
}
final DoubleParameter pEpsilonP = new DoubleParameter(PEPSILON_ID, 0.05)//
.addConstraint(CommonConstraints.GREATER_EQUAL_ZERO_DOUBLE) //
.addConstraint(CommonConstraints.LESS_EQUAL_ONE_DOUBLE);
if(config.grab(pEpsilonP)) {
pEpsilon = pEpsilonP.doubleValue();
}
}
@Override
protected LCSSDistanceFunction makeInstance() {
return new LCSSDistanceFunction(pDelta, pEpsilon);
}
}
}
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