de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries

Class EDRDistanceFunction

java.lang.Object

de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractPrimitiveDistanceFunction<NumberVector>

de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractNumberVectorDistanceFunction

de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries.AbstractEditDistanceFunction

de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries.DTWDistanceFunction

de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries.EDRDistanceFunction

All Implemented Interfaces:

DistanceFunction<NumberVector>, NumberVectorDistanceFunction<NumberVector>, PrimitiveDistanceFunction<NumberVector>

@Title(value="Edit Distance on Real Sequence")
@Reference(authors="L. Chen and M. T. \u00d6zsu and V. Oria",
           title="Robust and fast similarity search for moving object trajectories",
           booktitle="SIGMOD \'05: Proceedings of the 2005 ACM SIGMOD international conference on Management of data",
           url="http://dx.doi.org/10.1145/1066157.1066213")
public class EDRDistanceFunction
extends DTWDistanceFunction

Edit Distance on Real Sequence distance for numerical vectors. Reference:

L. Chen and M. T. Özsu and V. Oria
Robust and fast similarity search for moving object trajectories
SIGMOD '05: Proceedings of the 2005 ACM SIGMOD international conference on Management of data

Author:

Thomas Bernecker

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	EDRDistanceFunction.Parameterizer Parameterization class.

Field Summary

Fields

Modifier and Type	Field and Description
private double	delta Delta parameter, similarity threshold for attributes.

Fields inherited from class de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries.AbstractEditDistanceFunction

bandSize

Constructor Summary

Constructors

Constructor and Description
EDRDistanceFunction(double bandSize, double delta) Constructor.

Method Summary

Methods

Modifier and Type	Method and Description
protected double	delta(double val1, double val2) Compute the delta of two values.
double	distance(NumberVector v1, NumberVector v2) Computes the distance between two given DatabaseObjects according to this distance function.
boolean	equals(Object obj)
protected void	firstRow(double[] buf, int band, NumberVector v1, NumberVector v2, int dim2) Fill the first row.

Methods inherited from class de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries.AbstractEditDistanceFunction

effectiveBandSize, getInputTypeRestriction

Methods inherited from class de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractNumberVectorDistanceFunction

dimensionality, dimensionality, dimensionality, dimensionality

Methods inherited from class de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractPrimitiveDistanceFunction

instantiate, isMetric, isSymmetric

Methods inherited from class java.lang.Object

clone, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface de.lmu.ifi.dbs.elki.distance.distancefunction.DistanceFunction

instantiate, isMetric, isSymmetric

Field Detail

delta

private final double delta

Delta parameter, similarity threshold for attributes.

Constructor Detail

EDRDistanceFunction

public EDRDistanceFunction(double bandSize,
                   double delta)

Constructor.

Parameters:

bandSize - Band size

delta - Allowed delta

Method Detail

distance

public double distance(NumberVector v1,
              NumberVector v2)

Description copied from interface: PrimitiveDistanceFunction

Computes the distance between two given DatabaseObjects according to this distance function.

Specified by:

distance in interface NumberVectorDistanceFunction<NumberVector>

Specified by:

distance in interface PrimitiveDistanceFunction<NumberVector>

Overrides:

distance in class DTWDistanceFunction

Parameters:

v1 - first DatabaseObject

v2 - second DatabaseObject

Returns:

the distance between two given DatabaseObjects according to this distance function

firstRow

protected void firstRow(double[] buf,
            int band,
            NumberVector v1,
            NumberVector v2,
            int dim2)

Description copied from class: DTWDistanceFunction

Fill the first row.

Overrides:

firstRow in class DTWDistanceFunction

Parameters:

buf - Buffer

band - Bandwidth

v1 - First vector

v2 - Second vector

dim2 - Dimensionality of second

delta

protected double delta(double val1,
           double val2)

Description copied from class: DTWDistanceFunction

Compute the delta of two values. TODO: support Euclidean, Manhattan, others?

Overrides:

delta in class DTWDistanceFunction

Parameters:

val1 - First value

val2 - Second value

Returns:

Difference

equals

public boolean equals(Object obj)

Overrides:

equals in class AbstractEditDistanceFunction