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package de.lmu.ifi.dbs.elki.distance.distancevalue;
/*
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.regex.Pattern;
/**
* The correlation distance is a special Distance that indicates the
* dissimilarity between correlation connected objects. The correlation distance
* between two points is a pair consisting of the correlation dimension of two
* points and the euclidean distance between the two points.
*
* @author Elke Achtert
*/
public class PCACorrelationDistance extends CorrelationDistance<PCACorrelationDistance> {
/**
* The static factory instance
*/
public final static PCACorrelationDistance FACTORY = new PCACorrelationDistance();
/**
* Serial
*/
private static final long serialVersionUID = 1L;
/**
* Empty constructor for serialization purposes.
*/
public PCACorrelationDistance() {
// for serialization
}
/**
* Constructs a new CorrelationDistance object consisting of the specified
* correlation value and euclidean value.
*
* @param correlationValue the correlation dimension to be represented by the
* CorrelationDistance
* @param euclideanValue the euclidean distance to be represented by the
* CorrelationDistance
*/
public PCACorrelationDistance(int correlationValue, double euclideanValue) {
super(correlationValue, euclideanValue);
}
/**
* Provides a distance suitable to this DistanceFunction based on the given
* pattern.
*
* @param val A pattern defining a distance suitable to this
* DistanceFunction
* @return a distance suitable to this DistanceFunction based on the given
* pattern
* @throws IllegalArgumentException if the given pattern is not compatible
* with the requirements of this DistanceFunction
*/
@Override
public PCACorrelationDistance parseString(String val) throws IllegalArgumentException {
if(val.equals(INFINITY_PATTERN)) {
return infiniteDistance();
}
if(testInputPattern(val)) {
String[] values = SEPARATOR.split(val);
return new PCACorrelationDistance(Integer.parseInt(values[0]), Double.parseDouble(values[1]));
}
else {
throw new IllegalArgumentException("Given pattern \"" + val + "\" does not match required pattern \"" + requiredInputPattern() + "\"");
}
}
@Override
public Pattern getPattern() {
return CORRELATION_DISTANCE_PATTERN;
}
/**
* Provides an infinite distance.
*
* @return an infinite distance
*/
@Override
public PCACorrelationDistance infiniteDistance() {
return new PCACorrelationDistance(Integer.MAX_VALUE, Double.POSITIVE_INFINITY);
}
/**
* Provides a null distance.
*
* @return a null distance
*/
@Override
public PCACorrelationDistance nullDistance() {
return new PCACorrelationDistance(0, 0.0);
}
/**
* Provides an undefined distance.
*
* @return an undefined distance
*/
@Override
public PCACorrelationDistance undefinedDistance() {
return new PCACorrelationDistance(-1, Double.NaN);
}
@Override
public PCACorrelationDistance plus(PCACorrelationDistance distance) {
return new PCACorrelationDistance(this.correlationValue + distance.getCorrelationValue(), this.euclideanValue + distance.getEuclideanValue());
}
@Override
public PCACorrelationDistance minus(PCACorrelationDistance distance) {
return new PCACorrelationDistance(this.correlationValue - distance.getCorrelationValue(), this.euclideanValue - distance.getEuclideanValue());
}
@Override
public boolean isInfiniteDistance() {
return correlationValue == Integer.MAX_VALUE || euclideanValue == Double.POSITIVE_INFINITY;
}
@Override
public boolean isNullDistance() {
return correlationValue == 0 || euclideanValue == 0.0;
}
@Override
public boolean isUndefinedDistance() {
return correlationValue == -1 && euclideanValue == Double.NaN;
}
}
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