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

Class LPNormDistanceFunction

java.lang.Object

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

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

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

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

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

All Implemented Interfaces:

DistanceFunction<NumberVector<?>,DoubleDistance>, DoubleNorm<NumberVector<?>>, Norm<NumberVector<?>,DoubleDistance>, NumberVectorDistanceFunction<DoubleDistance>, PrimitiveDistanceFunction<NumberVector<?>,DoubleDistance>, PrimitiveDoubleDistanceFunction<NumberVector<?>>, SpatialPrimitiveDistanceFunction<NumberVector<?>,DoubleDistance>, SpatialPrimitiveDoubleDistanceFunction<NumberVector<?>>, Parameterizable

Direct Known Subclasses:

LPIntegerNormDistanceFunction, MaximumDistanceFunction, WeightedLPNormDistanceFunction

@Alias(value={"lp","minkowski","p","de.lmu.ifi.dbs.elki.distance.distancefunction.LPNormDistanceFunction"})
public class LPNormDistanceFunction
extends AbstractSpatialDoubleDistanceNorm

Provides a LP-Norm for FeatureVectors.

Nested Class Summary

Nested Classes

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

Field Summary

Fields

Modifier and Type	Field and Description
protected double	invp Keeps the currently set p and its inverse
protected double	p Keeps the currently set p and its inverse
static OptionID	P_ID OptionID for the "p" parameter

Constructor Summary

Constructors

Constructor and Description
LPNormDistanceFunction(double p) Constructor, internal version.

Method Summary

Methods

Modifier and Type	Method and Description
double	doubleDistance(NumberVector<?> v1, NumberVector<?> v2) Computes the distance between two given Objects according to this distance function.
double	doubleMinDist(SpatialComparable mbr1, SpatialComparable mbr2) Computes the distance between the two given MBRs according to this distance function.
double	doubleNorm(NumberVector<?> v) Compute the norm of object obj as double value.
private double	doublePreDistance(NumberVector<?> v1, NumberVector<?> v2, int start, int end, double agg) Compute unscaled distance in a range of dimensions.
private double	doublePreDistanceMBR(SpatialComparable mbr1, SpatialComparable mbr2, int start, int end, double agg) Compute unscaled distance in a range of dimensions.
private double	doublePreDistanceVM(NumberVector<?> v, SpatialComparable mbr, int start, int end, double agg) Compute unscaled distance in a range of dimensions.
private double	doublePreNorm(NumberVector<?> v, int start, int end, double agg) Compute unscaled norm in a range of dimensions.
private double	doublePreNormMBR(SpatialComparable mbr, int start, int end, double agg) Compute unscaled norm in a range of dimensions.
boolean	equals(Object obj)
SimpleTypeInformation<? super NumberVector<?>>	getInputTypeRestriction() Get the input data type of the function.
double	getP() Get the functions p parameter.
boolean	isMetric() Is this distance function metric (in particular, does it satisfy the triangle equation?)
String	toString()

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

instantiate, minDist

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

norm

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

dimensionality, dimensionality, dimensionality, dimensionality, distance, getDistanceFactory

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

isSymmetric

Methods inherited from class java.lang.Object

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

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

distance

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

getDistanceFactory, isSymmetric

Field Detail

P_ID

public static final OptionID P_ID

OptionID for the "p" parameter

p

protected double p

Keeps the currently set p and its inverse

invp

protected double invp

Keeps the currently set p and its inverse

Constructor Detail

LPNormDistanceFunction

public LPNormDistanceFunction(double p)

Constructor, internal version.

Parameters:

p - Parameter p

Method Detail

doublePreDistance

private final double doublePreDistance(NumberVector<?> v1,
                       NumberVector<?> v2,
                       int start,
                       int end,
                       double agg)

Compute unscaled distance in a range of dimensions.

Parameters:

v1 - First object

v2 - Second object

start - First dimension

end - Exclusive last dimension

agg - Current aggregate value

Returns:

Aggregated values.

doublePreDistanceVM

private final double doublePreDistanceVM(NumberVector<?> v,
                         SpatialComparable mbr,
                         int start,
                         int end,
                         double agg)

Compute unscaled distance in a range of dimensions.

Parameters:

v - First vector

mbr - Second MBR

start - First dimension

end - Exclusive last dimension

agg - Current aggregate value

Returns:

Aggregated values.

doublePreDistanceMBR

private final double doublePreDistanceMBR(SpatialComparable mbr1,
                          SpatialComparable mbr2,
                          int start,
                          int end,
                          double agg)

Compute unscaled distance in a range of dimensions.

Parameters:

mbr1 - First MBR

mbr2 - Second MBR

start - First dimension

end - Exclusive last dimension

agg - Current aggregate value

Returns:

Aggregated values.

doublePreNorm

private final double doublePreNorm(NumberVector<?> v,
                   int start,
                   int end,
                   double agg)

Compute unscaled norm in a range of dimensions.

Parameters:

v - Data object

start - First dimension

end - Exclusive last dimension

agg - Current aggregate value

Returns:

Aggregated values.

doublePreNormMBR

private final double doublePreNormMBR(SpatialComparable mbr,
                      int start,
                      int end,
                      double agg)

Compute unscaled norm in a range of dimensions.

Parameters:

mbr - Data object

start - First dimension

end - Exclusive last dimension

agg - Current aggregate value

Returns:

Aggregated values.

doubleDistance

public double doubleDistance(NumberVector<?> v1,
                    NumberVector<?> v2)

Description copied from interface: PrimitiveDoubleDistanceFunction

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

Parameters:

v1 - first Object

v2 - second Object

Returns:

the distance between two given Objects according to this distance function

doubleNorm

public double doubleNorm(NumberVector<?> v)

Description copied from interface: DoubleNorm

Compute the norm of object obj as double value.

Parameters:

v - Object

Returns:

Double

doubleMinDist

public double doubleMinDist(SpatialComparable mbr1,
                   SpatialComparable mbr2)

Description copied from interface: SpatialPrimitiveDoubleDistanceFunction

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

Parameters:

mbr1 - the first MBR object

mbr2 - the second MBR object

Returns:

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

isMetric

public boolean isMetric()

Description copied from interface: DistanceFunction

Is this distance function metric (in particular, does it satisfy the triangle equation?)

Specified by:

isMetric in interface DistanceFunction<NumberVector<?>,DoubleDistance>

Overrides:

isMetric in class AbstractPrimitiveDistanceFunction<NumberVector<?>,DoubleDistance>

Returns:

true when metric.

toString

public String toString()

Overrides:

toString in class Object

getP

public double getP()

Get the functions p parameter.

Returns:

p

equals

public boolean equals(Object obj)

Overrides:

equals in class Object

getInputTypeRestriction

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

Description copied from interface: DistanceFunction

Get the input data type of the function.

Specified by:

getInputTypeRestriction in interface DistanceFunction<NumberVector<?>,DoubleDistance>

Specified by:

getInputTypeRestriction in interface PrimitiveDistanceFunction<NumberVector<?>,DoubleDistance>

Overrides:

getInputTypeRestriction in class AbstractVectorDoubleDistanceFunction

Returns:

Type restriction