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

Class HammingDistanceFunction

java.lang.Object

de.lmu.ifi.dbs.elki.distance.distancefunction.set.AbstractSetDistanceFunction<FeatureVector<?>>

de.lmu.ifi.dbs.elki.distance.distancefunction.set.HammingDistanceFunction

All Implemented Interfaces:

DistanceFunction<FeatureVector<?>>, NumberVectorDistanceFunction<FeatureVector<?>>, PrimitiveDistanceFunction<FeatureVector<?>>

@Reference(authors="R. W. Hamming",
           title="Error detecting and error correcting codes",
           booktitle="Bell System technical journal, 29(2)",
           url="https://doi.org/10.1002/j.1538-7305.1950.tb00463.x",
           bibkey="doi:10.1002/j.1538-7305.1950.tb00463.x")
public class HammingDistanceFunction
extends AbstractSetDistanceFunction<FeatureVector<?>>
implements NumberVectorDistanceFunction<FeatureVector<?>>

Computes the Hamming distance of arbitrary vectors - i.e. counting, on how many places they differ.

Reference:

R. W. Hamming
Error detecting and error correcting codes
Bell System technical journal, 29(2)

TODO: add a sparse (but not binary) optimized version?

Since:

0.7.0

Author:

Erich Schubert

Nested Class Summary

Nested Classes

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

Field Summary

Fields

Modifier and Type	Field and Description
static HammingDistanceFunction	STATIC Static instance.

Fields inherited from class de.lmu.ifi.dbs.elki.distance.distancefunction.set.AbstractSetDistanceFunction

DOUBLE_NULL, INTEGER_NULL, STRING_NULL

Constructor Summary

Constructors

Constructor and Description
HammingDistanceFunction()

Method Summary

Modifier and Type	Method and Description
double	distance(FeatureVector<?> o1, FeatureVector<?> o2) Computes the distance between two given DatabaseObjects according to this distance function.
double	distance(NumberVector o1, NumberVector o2) Computes the distance between two given vectors according to this distance function.
boolean	equals(java.lang.Object obj)
SimpleTypeInformation<? super FeatureVector<?>>	getInputTypeRestriction() Get the input data type of the function.
private double	hammingDistanceNumberVector(NumberVector o1, NumberVector o2) Version for number vectors.
int	hashCode()
boolean	isMetric() Is this distance function metric (satisfy the triangle inequality)

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

isNull

Methods inherited from class java.lang.Object

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

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

instantiate

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

isSquared, isSymmetric

Field Detail

STATIC

public static final HammingDistanceFunction STATIC

Static instance.

Constructor Detail

HammingDistanceFunction

public HammingDistanceFunction()

Method Detail

isMetric

public boolean isMetric()

Description copied from interface: DistanceFunction

Is this distance function metric (satisfy the triangle inequality)

Specified by:

isMetric in interface DistanceFunction<FeatureVector<?>>

Returns:

true when metric.

distance

public double distance(FeatureVector<?> o1,
                       FeatureVector<?> o2)

Description copied from interface: PrimitiveDistanceFunction

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

Specified by:

distance in interface PrimitiveDistanceFunction<FeatureVector<?>>

Parameters:

o1 - first DatabaseObject

o2 - second DatabaseObject

Returns:

the distance between two given DatabaseObjects according to this distance function

distance

public double distance(NumberVector o1,
                       NumberVector o2)

Description copied from interface: NumberVectorDistanceFunction

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

Specified by:

distance in interface NumberVectorDistanceFunction<FeatureVector<?>>

Parameters:

o1 - first vector

o2 - second vector

Returns:

the distance between two given vectors according to this distance function

hammingDistanceNumberVector

private double hammingDistanceNumberVector(NumberVector o1,
                                           NumberVector o2)

Version for number vectors.

Parameters:

o1 - First vector

o2 - Second vector

Returns:

hamming distance

getInputTypeRestriction

public SimpleTypeInformation<? super FeatureVector<?>> getInputTypeRestriction()

Description copied from interface: DistanceFunction

Get the input data type of the function.

Specified by:

getInputTypeRestriction in interface DistanceFunction<FeatureVector<?>>

Specified by:

getInputTypeRestriction in interface PrimitiveDistanceFunction<FeatureVector<?>>

Returns:

Type restriction

equals

public boolean equals(java.lang.Object obj)

Overrides:

equals in class java.lang.Object

hashCode

public int hashCode()

Overrides:

hashCode in class java.lang.Object