de.lmu.ifi.dbs.elki.distance.distancefunction
Interface DistanceFunction<O extends DatabaseObject,D extends Distance<D>>

Type Parameters:

O - the type of DatabaseObject to compute the distances in between

D - the type of Distance used by this DistanceFunction

All Superinterfaces:

MeasurementFunction<O,D>, Parameterizable

All Known Subinterfaces:

KernelFunction<O,D>, LocalPCAPreprocessorBasedDistanceFunction<O,P,D>, PreprocessorBasedDistanceFunction<O,P,D>, SpatialDistanceFunction<V,D>

All Known Implementing Classes:

AbstractCorrelationDistanceFunction, AbstractDimensionsSelectingDoubleDistanceFunction, AbstractDistanceFunction, AbstractEditDistanceFunction, AbstractKernelFunction, AbstractLocallyWeightedDistanceFunction, AbstractPreferenceVectorBasedCorrelationDistanceFunction, AbstractPreprocessorBasedDistanceFunction, ArbitraryKernelFunctionWrapper, ArcCosineDistanceFunction, CosineDistanceFunction, DimensionSelectingDistanceFunction, DimensionsSelectingEuclideanDistanceFunction, DiSHDistanceFunction, DiskCacheBasedDoubleDistanceFunction, DiskCacheBasedFloatDistanceFunction, DTWDistanceFunction, EDRDistanceFunction, ERiCDistanceFunction, ERPDistanceFunction, EuclideanDistanceFunction, FileBasedDoubleDistanceFunction, FileBasedFloatDistanceFunction, FooKernelFunction, HiSCDistanceFunction, HistogramIntersectionDistanceFunction, HSBHistogramQuadraticDistanceFunction, KernelBasedLocallyWeightedDistanceFunction, LCSSDistanceFunction, LinearKernelFunction, LocallyWeightedDistanceFunction, LPNormDistanceFunction, ManhattanDistanceFunction, MaximumDistanceFunction, MinimumDistanceFunction, PCABasedCorrelationDistanceFunction, PearsonCorrelationDistanceFunction, PolynomialKernelFunction, RGBHistogramQuadraticDistanceFunction, SimilarityAdapterAbstract, SimilarityAdapterArccos, SimilarityAdapterLinear, SimilarityAdapterLn, SquaredPearsonCorrelationDistanceFunction, SubspaceDistanceFunction, WeightedDistanceFunction

public interface DistanceFunction<O extends DatabaseObject,D extends Distance<D>>
extends MeasurementFunction<O,D>, Parameterizable

Interface DistanceFunction describes the requirements of any distance function.

Author:

Arthur Zimek

Method Summary

D	distance(Integer id1, Integer id2) Returns the distance between the two objects specified by their object ids.
D	distance(Integer id1, O o2) Returns the distance between the two specified objects.
D	distance(O o1, O o2) Computes the distance between two given DatabaseObjects according to this distance function.

Methods inherited from interface de.lmu.ifi.dbs.elki.distance.MeasurementFunction

getDistanceFactory, infiniteDistance, nullDistance, setDatabase, undefinedDistance, valueOf

Method Detail

distance

D distance(O o1,
           O o2)

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

Parameters:

o1 - first DatabaseObject

o2 - second DatabaseObject

Returns:

the distance between two given DatabaseObjects according to this distance function

distance

D distance(Integer id1,
           Integer id2)

Returns the distance between the two objects specified by their object ids.

Parameters:

id1 - first object id

id2 - second object id

Returns:

the distance between the two objects specified by their object ids

distance

D distance(Integer id1,
           O o2)

Returns the distance between the two specified objects.

Parameters:

id1 - first object id

o2 - second DatabaseObject

Returns:

the distance between the two object specified by their object ids