Package elki.distance.timeseries

Class EDRDistance

java.lang.Object

elki.distance.AbstractNumberVectorDistance

elki.distance.timeseries.AbstractEditDistance

elki.distance.timeseries.DTWDistance

elki.distance.timeseries.EDRDistance

All Implemented Interfaces:

Distance<NumberVector>, NumberVectorDistance<NumberVector>, PrimitiveDistance<NumberVector>

@Title("Edit Distance on Real Sequence")
@Reference(authors="L. Chen, M. T. \u00d6zsu, V. Oria",
           title="Robust and fast similarity search for moving object trajectories",
           booktitle="Proc. 2005 ACM SIGMOD Int. Conf. Management of Data",
           url="https://doi.org/10.1145/1066157.1066213",
           bibkey="DBLP:conf/sigmod/ChenOO05")
public class EDRDistance
extends DTWDistance

Edit Distance on Real Sequence distance for numerical vectors.

Reference:

L. Chen, M. T. Özsu, V. Oria
Robust and fast similarity search for moving object trajectories
Proc. 2005 ACM SIGMOD Int. Conf. Management of Data

Since:

0.2

Author:

Thomas Bernecker

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static class	EDRDistance.Par	Parameterization class.

Field Summary

Fields

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

Fields inherited from class elki.distance.timeseries.AbstractEditDistance

bandSize

Constructor Summary

Constructors

Constructor	Description
EDRDistance(double bandSize, double delta)	Constructor.

Method Summary

Modifier and Type	Method	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 vectors according to this distance function.
boolean	equals(java.lang.Object obj)
int	hashCode()

Methods inherited from class elki.distance.timeseries.DTWDistance

firstRow

Methods inherited from class elki.distance.timeseries.AbstractEditDistance

effectiveBandSize, getInputTypeRestriction

Methods inherited from class elki.distance.AbstractNumberVectorDistance

dimensionality, dimensionality, dimensionality, dimensionality, dimensionality, dimensionality, dimensionality, dimensionality

Methods inherited from class java.lang.Object

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

Methods inherited from interface elki.distance.Distance

isMetric, isSquared, isSymmetric

Methods inherited from interface elki.distance.PrimitiveDistance

instantiate

Field Detail

delta

private final double delta

Delta parameter, similarity threshold for attributes.

Constructor Detail

EDRDistance

public EDRDistance(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: NumberVectorDistance

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

Specified by:

distance in interface NumberVectorDistance<NumberVector>

Specified by:

distance in interface PrimitiveDistance<NumberVector>

Overrides:

distance in class DTWDistance

Parameters:

v1 - first vector

v2 - second vector

Returns:

the distance between two given vectors according to this distance function

delta

protected double delta(double val1,
                       double val2)

Description copied from class: DTWDistance

Compute the delta of two values.

TODO: support Euclidean, Manhattan, others?

Overrides:

delta in class DTWDistance

Parameters:

val1 - First value

val2 - Second value

Returns:

Difference

equals

public boolean equals(java.lang.Object obj)

Overrides:

equals in class AbstractEditDistance

hashCode

public int hashCode()

Overrides:

hashCode in class AbstractEditDistance