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

Interface PrimitiveDistanceFunction<O,D extends Distance<?>>

Type Parameters:

O - input object type

D - distance result type

All Superinterfaces:

DistanceFunction<O,D>, Parameterizable

All Known Subinterfaces:

DoubleNorm<O>, NumberVectorDistanceFunction<D>, PrimitiveDoubleDistanceFunction<O>, SpatialPrimitiveDistanceFunction<V,D>, SpatialPrimitiveDoubleDistanceFunction<V>

All Known Implementing Classes:

AbstractDimensionsSelectingDoubleDistanceFunction, AbstractEditDistanceFunction, AbstractPrimitiveDistanceFunction, AbstractSpatialDoubleDistanceFunction, AbstractSpatialDoubleDistanceNorm, AbstractVectorDoubleDistanceFunction, AbstractVectorDoubleDistanceNorm, ArcCosineDistanceFunction, BrayCurtisDistanceFunction, CanberraDistanceFunction, ChiSquaredDistanceFunction, ClarkDistanceFunction, CosineDistanceFunction, DimensionSelectingDistanceFunction, DimensionSelectingLatLngDistanceFunction, DTWDistanceFunction, EDRDistanceFunction, ERPDistanceFunction, EuclideanDistanceFunction, HistogramIntersectionDistanceFunction, HistogramMatchDistanceFunction, HSBHistogramQuadraticDistanceFunction, JaccardPrimitiveSimilarityFunction, JeffreyDivergenceDistanceFunction, JensenShannonDivergenceDistanceFunction, KolmogorovSmirnovDistanceFunction, Kulczynski1DistanceFunction, KullbackLeiblerDivergenceAsymmetricDistanceFunction, KullbackLeiblerDivergenceReverseAsymmetricDistanceFunction, LatLngDistanceFunction, LCSSDistanceFunction, LevenshteinDistanceFunction, LinearKernelFunction, LngLatDistanceFunction, LorentzianDistanceFunction, LPIntegerNormDistanceFunction, LPNormDistanceFunction, ManhattanDistanceFunction, MaximumDistanceFunction, MinimumDistanceFunction, MultiLPNorm, NormalizedLevenshteinDistanceFunction, PearsonCorrelationDistanceFunction, PolynomialKernelFunction, RGBHistogramQuadraticDistanceFunction, SparseEuclideanDistanceFunction, SparseLPNormDistanceFunction, SparseManhattanDistanceFunction, SparseMaximumDistanceFunction, SqrtJensenShannonDivergenceDistanceFunction, SquaredEuclideanDistanceFunction, SquaredPearsonCorrelationDistanceFunction, SubspaceEuclideanDistanceFunction, SubspaceLPNormDistanceFunction, SubspaceManhattanDistanceFunction, SubspaceMaximumDistanceFunction, TutorialDistanceFunction, WeightedCanberraDistanceFunction, WeightedDistanceFunction, WeightedEuclideanDistanceFunction, WeightedLPNormDistanceFunction, WeightedManhattanDistanceFunction, WeightedMaximumDistanceFunction, WeightedPearsonCorrelationDistanceFunction, WeightedSquaredEuclideanDistanceFunction, WeightedSquaredPearsonCorrelationDistanceFunction

public interface PrimitiveDistanceFunction<O,D extends Distance<?>>
extends DistanceFunction<O,D>

Primitive distance function that is defined on some kind of object.

Method Summary

Methods

Modifier and Type	Method and Description
D	distance(O o1, O o2) Computes the distance between two given DatabaseObjects according to this distance function.
SimpleTypeInformation<? super O>	getInputTypeRestriction() Get the input data type of the function.

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

getDistanceFactory, instantiate, isMetric, isSymmetric

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

getInputTypeRestriction

SimpleTypeInformation<? super O> getInputTypeRestriction()

Description copied from interface: DistanceFunction

Get the input data type of the function.

Specified by:

getInputTypeRestriction in interface DistanceFunction<O,D extends Distance<?>>

Returns:

Type restriction