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

Type Parameters:

D - the type of Distance used as measurement for comparing database objects

O - the type of DatabaseObject for which a measurement is provided for comparison

All Known Subinterfaces:

DistanceFunction<O,D>, KernelFunction<O,D>, LocalPCAPreprocessorBasedDistanceFunction<O,P,D>, NormalizedSimilarityFunction<O,D>, PreprocessorBasedDistanceFunction<O,P,D>, PreprocessorBasedMeasurementFunction<O,P,D>, SimilarityFunction<O,D>, SpatialDistanceFunction<V,D>

All Known Implementing Classes:

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

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

Interface Measurement describes the requirements of any measurement function (e.g. distance function or similarity function), that provides a measurement for comparing database objects.

Author:

Elke Achtert

Method Summary

D	getDistanceFactory() Method to get the distance functions factory.
D	infiniteDistance() Provides an infinite distance.
D	nullDistance() Provides a null distance.
void	setDatabase(Database<O> database) Set the database that holds the associations for the DatabaseObject for which the measurements should be computed.
D	undefinedDistance() Provides an undefined distance.
D	valueOf(String val) Parse a string value into a distance

Method Detail

setDatabase

void setDatabase(Database<O> database)

Set the database that holds the associations for the DatabaseObject for which the measurements should be computed.

Parameters:

database - the database to be set

getDistanceFactory

D getDistanceFactory()

Method to get the distance functions factory.

Returns:

Factory for distance objects

infiniteDistance

D infiniteDistance()

Provides an infinite distance.

Returns:

an infinite distance

nullDistance

D nullDistance()

Provides a null distance.

Returns:

a null distance

undefinedDistance

D undefinedDistance()

Provides an undefined distance.

Returns:

an undefined distance

valueOf

D valueOf(String val)
                              throws IllegalArgumentException

Parse a string value into a distance

Parameters:

val - input string

Returns:

parsed value

Throws:

IllegalArgumentException - on parsing error