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

Interface PrimitiveDistanceFunction<O>

Type Parameters:

O - input object type

All Superinterfaces:

DistanceFunction<O>

All Known Subinterfaces:

ClusteringDistanceSimilarityFunction, Norm<O>, NumberVectorDistanceFunction<O>, SpatialPrimitiveDistanceFunction<V>, WeightedNumberVectorDistanceFunction<V>

All Known Implementing Classes:

AbsolutePearsonCorrelationDistanceFunction, AbsoluteUncenteredCorrelationDistanceFunction, AbstractDimensionsSelectingDistanceFunction, AbstractEditDistanceFunction, AbstractNumberVectorDistanceFunction, AbstractSetDistanceFunction, ArcCosineDistanceFunction, ArcCosineUnitlengthDistanceFunction, BrayCurtisDistanceFunction, CanberraDistanceFunction, ChiDistanceFunction, ChiSquaredDistanceFunction, ClarkDistanceFunction, ClusteringAdjustedRandIndexSimilarityFunction, ClusteringBCubedF1SimilarityFunction, ClusteringFowlkesMallowsSimilarityFunction, ClusteringRandIndexSimilarityFunction, ClusterIntersectionSimilarityFunction, ClusterJaccardSimilarityFunction, CosineDistanceFunction, CosineUnitlengthDistanceFunction, DerivativeDTWDistanceFunction, DimensionSelectingLatLngDistanceFunction, DTWDistanceFunction, EDRDistanceFunction, ERPDistanceFunction, EuclideanDistanceFunction, FisherRaoDistanceFunction, HammingDistanceFunction, HellingerDistanceFunction, HistogramIntersectionDistanceFunction, HistogramMatchDistanceFunction, HSBHistogramQuadraticDistanceFunction, JaccardSimilarityDistanceFunction, JeffreyDivergenceDistanceFunction, JensenShannonDivergenceDistanceFunction, KolmogorovSmirnovDistanceFunction, Kulczynski1SimilarityFunction, KullbackLeiblerDivergenceAsymmetricDistanceFunction, KullbackLeiblerDivergenceReverseAsymmetricDistanceFunction, LatLngDistanceFunction, LCSSDistanceFunction, LevenshteinDistanceFunction, LinearKernelFunction, LngLatDistanceFunction, LPIntegerNormDistanceFunction, LPNormDistanceFunction, MahalanobisDistanceFunction, ManhattanDistanceFunction, MatrixWeightedQuadraticDistanceFunction, MaximumDistanceFunction, MinimumDistanceFunction, MultiLPNorm, NormalizedLevenshteinDistanceFunction, OnedimensionalDistanceFunction, PearsonCorrelationDistanceFunction, PolynomialKernelFunction, RGBHistogramQuadraticDistanceFunction, SparseEuclideanDistanceFunction, SparseLPNormDistanceFunction, SparseManhattanDistanceFunction, SparseMaximumDistanceFunction, SparseSquaredEuclideanDistanceFunction, SqrtJensenShannonDivergenceDistanceFunction, SquaredEuclideanDistanceFunction, SquaredPearsonCorrelationDistanceFunction, SquaredUncenteredCorrelationDistanceFunction, SubspaceEuclideanDistanceFunction, SubspaceLPNormDistanceFunction, SubspaceManhattanDistanceFunction, SubspaceMaximumDistanceFunction, TriangularDiscriminationDistanceFunction, TriangularDistanceFunction, TutorialDistanceFunction, UncenteredCorrelationDistanceFunction, WeightedCanberraDistanceFunction, WeightedEuclideanDistanceFunction, WeightedLPNormDistanceFunction, WeightedManhattanDistanceFunction, WeightedMaximumDistanceFunction, WeightedPearsonCorrelationDistanceFunction, WeightedSquaredEuclideanDistanceFunction, WeightedSquaredPearsonCorrelationDistanceFunction

public interface PrimitiveDistanceFunction<O>
extends DistanceFunction<O>

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

Since:

0.4.0

Author:

Erich Schubert

Method Summary

Modifier and Type	Method and Description
double	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.
default <T extends O> DistanceQuery<T>	instantiate(Relation<T> relation) Instantiate with a database to get the actual distance query.

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

isMetric, isSquared, isSymmetric

Method Detail

distance

double 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>

Returns:

Type restriction

instantiate

default <T extends O> DistanceQuery<T> instantiate(Relation<T> relation)

Description copied from interface: DistanceFunction

Instantiate with a database to get the actual distance query.

Specified by:

instantiate in interface DistanceFunction<O>

Parameters:

relation - The representation to use

Returns:

Actual distance query.