Package elki.distance.subspace

Class SubspaceLPNormDistance

java.lang.Object

elki.distance.subspace.AbstractDimensionsSelectingDistance<NumberVector>

elki.distance.subspace.SubspaceLPNormDistance

All Implemented Interfaces:

Distance<NumberVector>, Norm<NumberVector>, NumberVectorDistance<NumberVector>, PrimitiveDistance<NumberVector>, SpatialPrimitiveDistance<NumberVector>, DimensionSelectingSubspaceDistance<NumberVector>

Direct Known Subclasses:

SubspaceEuclideanDistance, SubspaceManhattanDistance, SubspaceMaximumDistance

public class SubspaceLPNormDistance
extends AbstractDimensionsSelectingDistance<NumberVector>
implements SpatialPrimitiveDistance<NumberVector>, Norm<NumberVector>, NumberVectorDistance<NumberVector>

L_p-Norm distance function between NumberVectors only in specified dimensions.

Since:

0.1

Author:

Elke Achtert

Nested Class Summary

Nested Classes

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

Field Summary

Fields

Modifier and Type	Field	Description
private double	p	Value of p

Fields inherited from class elki.distance.subspace.AbstractDimensionsSelectingDistance

dimensions

Constructor Summary

Constructors

Constructor	Description
SubspaceLPNormDistance(double p, long[] dimensions)	Constructor.

Method Summary

Modifier and Type	Method	Description
double	distance(NumberVector v1, NumberVector v2)	Computes the distance between two given DatabaseObjects according to this distance function.
boolean	equals(java.lang.Object obj)
VectorFieldTypeInformation<? super NumberVector>	getInputTypeRestriction()	Get the input data type of the function.
double	getP()	Get the value of p.
int	hashCode()
<T extends NumberVector> SpatialPrimitiveDistanceQuery<T>	instantiate(Relation<T> database)	Instantiate with a database to get the actual distance query.
boolean	isMetric()	Is this distance function metric (satisfy the triangle inequality)
double	minDist(SpatialComparable mbr1, SpatialComparable mbr2)	Computes the distance between the two given MBRs according to this distance function.
protected double	minDistObject(SpatialComparable mbr, NumberVector v)
double	norm(NumberVector obj)	Compute the norm of object obj.

Methods inherited from class elki.distance.subspace.AbstractDimensionsSelectingDistance

getSelectedDimensions, setSelectedDimensions

Methods inherited from class java.lang.Object

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

Methods inherited from interface elki.distance.Distance

isSquared, isSymmetric

Field Detail

p

private double p

Value of p

Constructor Detail

SubspaceLPNormDistance

public SubspaceLPNormDistance(double p,
                              long[] dimensions)

Constructor.

Parameters:

dimensions - Selected dimensions

p - p value

Method Detail

getP

public double getP()

Get the value of p.

Returns:

p

distance

public double distance(NumberVector v1,
                       NumberVector v2)

Description copied from interface: PrimitiveDistance

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

Specified by:

distance in interface NumberVectorDistance<NumberVector>

Specified by:

distance in interface PrimitiveDistance<NumberVector>

Overrides:

distance in class AbstractDimensionsSelectingDistance<NumberVector>

Parameters:

v1 - first DatabaseObject

v2 - second DatabaseObject

Returns:

the distance between two given DatabaseObjects according to this distance function

minDistObject

protected double minDistObject(SpatialComparable mbr,
                               NumberVector v)

minDist

public double minDist(SpatialComparable mbr1,
                      SpatialComparable mbr2)

Description copied from interface: SpatialPrimitiveDistance

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

Specified by:

minDist in interface SpatialPrimitiveDistance<NumberVector>

Parameters:

mbr1 - the first MBR object

mbr2 - the second MBR object

Returns:

the distance between the two given MBRs according to this distance function

norm

public double norm(NumberVector obj)

Description copied from interface: Norm

Compute the norm of object obj.

Specified by:

norm in interface Norm<NumberVector>

Parameters:

obj - Object

Returns:

Norm

instantiate

public <T extends NumberVector> SpatialPrimitiveDistanceQuery<T> instantiate(Relation<T> database)

Description copied from interface: Distance

Instantiate with a database to get the actual distance query.

Specified by:

instantiate in interface Distance<NumberVector>

Specified by:

instantiate in interface PrimitiveDistance<NumberVector>

Specified by:

instantiate in interface SpatialPrimitiveDistance<NumberVector>

Parameters:

database - The representation to use

Returns:

Actual distance query.

getInputTypeRestriction

public VectorFieldTypeInformation<? super NumberVector> getInputTypeRestriction()

Description copied from interface: Distance

Get the input data type of the function.

Specified by:

getInputTypeRestriction in interface Distance<NumberVector>

Specified by:

getInputTypeRestriction in interface PrimitiveDistance<NumberVector>

Returns:

Type restriction

isMetric

public boolean isMetric()

Description copied from interface: Distance

Is this distance function metric (satisfy the triangle inequality)

Specified by:

isMetric in interface Distance<NumberVector>

Returns:

true when metric.

equals

public boolean equals(java.lang.Object obj)

Overrides:

equals in class AbstractDimensionsSelectingDistance<NumberVector>

hashCode

public int hashCode()

Overrides:

hashCode in class AbstractDimensionsSelectingDistance<NumberVector>