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

Class SparseLPNormDistanceFunction

java.lang.Object

de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.SparseLPNormDistanceFunction

All Implemented Interfaces:

DistanceFunction<SparseNumberVector>, Norm<SparseNumberVector>, PrimitiveDistanceFunction<SparseNumberVector>

Direct Known Subclasses:

SparseEuclideanDistanceFunction, SparseManhattanDistanceFunction, SparseMaximumDistanceFunction

@Alias(value="de.lmu.ifi.dbs.elki.distance.distancefunction.SparseLPNormDistanceFunction")
public class SparseLPNormDistanceFunction
extends java.lang.Object
implements PrimitiveDistanceFunction<SparseNumberVector>, Norm<SparseNumberVector>

L_p-Norm, optimized for SparseNumberVectors.

The L_p distance is defined as: \[ L_p(\vec{x},\vec{y}) := \left(\sum\nolimits_i (x_i-y_i)\right)^{1/p} \]

Since:

0.5.0

Author:

Erich Schubert

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	SparseLPNormDistanceFunction.Parameterizer Parameterizer

Field Summary

Fields

Modifier and Type	Field and Description
private double	invp P parameter and its inverse.
private double	p P parameter and its inverse.

Constructor Summary

Constructors

Constructor and Description
SparseLPNormDistanceFunction(double p) Constructor.

Method Summary

Modifier and Type	Method and Description
double	distance(SparseNumberVector v1, SparseNumberVector v2) Computes the distance between two given DatabaseObjects according to this distance function.
SimpleTypeInformation<? super SparseNumberVector>	getInputTypeRestriction() Get the input data type of the function.
boolean	isMetric() Is this distance function metric (satisfy the triangle inequality)
double	norm(SparseNumberVector v1) Compute the norm of object obj.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, 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

p

private double p

P parameter and its inverse.

invp

private double invp

P parameter and its inverse.

Constructor Detail

SparseLPNormDistanceFunction

public SparseLPNormDistanceFunction(double p)

Constructor.

Method Detail

distance

public double distance(SparseNumberVector v1,
                       SparseNumberVector v2)

Description copied from interface: PrimitiveDistanceFunction

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

Specified by:

distance in interface PrimitiveDistanceFunction<SparseNumberVector>

Parameters:

v1 - first DatabaseObject

v2 - second DatabaseObject

Returns:

the distance between two given DatabaseObjects according to this distance function

norm

public double norm(SparseNumberVector v1)

Description copied from interface: Norm

Compute the norm of object obj.

Specified by:

norm in interface Norm<SparseNumberVector>

Parameters:

v1 - Object

Returns:

Norm

getInputTypeRestriction

public SimpleTypeInformation<? super SparseNumberVector> getInputTypeRestriction()

Description copied from interface: DistanceFunction

Get the input data type of the function.

Specified by:

getInputTypeRestriction in interface DistanceFunction<SparseNumberVector>

Specified by:

getInputTypeRestriction in interface PrimitiveDistanceFunction<SparseNumberVector>

Returns:

Type restriction

isMetric

public boolean isMetric()

Description copied from interface: DistanceFunction

Is this distance function metric (satisfy the triangle inequality)

Specified by:

isMetric in interface DistanceFunction<SparseNumberVector>

Returns:

true when metric.