Uses of Class
de.lmu.ifi.dbs.elki.distance.distancevalue.DoubleDistance

Packages that use DoubleDistance

de.lmu.ifi.dbs.elki.algorithm.clustering	Clustering algorithms Clustering algorithms are supposed to implement the Algorithm-Interface.
de.lmu.ifi.dbs.elki.algorithm.clustering.correlation	Correlation clustering algorithms
de.lmu.ifi.dbs.elki.algorithm.clustering.subspace	Axis-parallel subspace clustering algorithms The clustering algorithms in this package are instances of both, projected clustering algorithms or subspace clustering algorithms according to the classical but somewhat obsolete classification schema of clustering algorithms for axis-parallel subspaces.
de.lmu.ifi.dbs.elki.algorithm.outlier	Outlier detection algorithms
de.lmu.ifi.dbs.elki.database.query	Database queries - computing distances, neighbors, similarities - API and general documentation.
de.lmu.ifi.dbs.elki.database.query.knn	Prepared queries for k nearest neighbor (kNN) queries.
de.lmu.ifi.dbs.elki.database.query.range	Prepared queries for ε-range queries.
de.lmu.ifi.dbs.elki.distance.distancefunction	Distance functions for use within ELKI.
de.lmu.ifi.dbs.elki.distance.distancefunction.adapter	Distance functions deriving distances from e.g. similarity measures
de.lmu.ifi.dbs.elki.distance.distancefunction.colorhistogram	Distance functions using correlations.
de.lmu.ifi.dbs.elki.distance.distancefunction.external	Distance functions using external data sources.
de.lmu.ifi.dbs.elki.distance.distancefunction.subspace	Distance functions based on subspaces.
de.lmu.ifi.dbs.elki.distance.distancevalue	Distance values, i.e. object storing an actual distance value along with comparison functions and value parsers.
de.lmu.ifi.dbs.elki.distance.similarityfunction	Similarity functions.
de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel	Kernel functions.
de.lmu.ifi.dbs.elki.index.preprocessed.localpca	Index using a preprocessed local PCA.
de.lmu.ifi.dbs.elki.index.preprocessed.preference	Indexes storing preference vectors.
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.query	Queries on the R-Tree family of indexes: kNN and range queries.
de.lmu.ifi.dbs.elki.math.linearalgebra.pca	Principal Component Analysis (PCA) and Eigenvector processing.
de.lmu.ifi.dbs.elki.result.optics	Result classes for OPTICS.

Uses of DoubleDistance in de.lmu.ifi.dbs.elki.algorithm.clustering

Fields in de.lmu.ifi.dbs.elki.algorithm.clustering declared as DoubleDistance

protected DoubleDistance

AbstractProjectedDBSCAN.epsilon Holds the value of AbstractProjectedDBSCAN.EPSILON_ID.

Fields in de.lmu.ifi.dbs.elki.algorithm.clustering with type parameters of type DoubleDistance

private DistanceFunction<? super V,DoubleDistance>

AbstractProjectedClustering.distanceFunction The euclidean distance function.

Methods in de.lmu.ifi.dbs.elki.algorithm.clustering that return types with arguments of type DoubleDistance

protected DistanceFunction<? super V,DoubleDistance>	AbstractProjectedClustering.getDistanceFunction() Returns the distance function.
protected DistanceQuery<V,DoubleDistance>	AbstractProjectedClustering.getDistanceQuery(Database database) Returns the distance function.

Methods in de.lmu.ifi.dbs.elki.algorithm.clustering with parameters of type DoubleDistance

protected void

OPTICS.expandClusterOrderDouble(ClusterOrderResult<DoubleDistance> clusterOrder, Database database, RangeQuery<O,DoubleDistance> rangeQuery, DBID objectID, DoubleDistance epsilon, FiniteProgress progress) OPTICS-function expandClusterOrder.

Method parameters in de.lmu.ifi.dbs.elki.algorithm.clustering with type arguments of type DoubleDistance

protected void	AbstractProjectedDBSCAN.expandCluster(LocallyWeightedDistanceFunction.Instance<V> distFunc, RangeQuery<V,DoubleDistance> rangeQuery, DBID startObjectID, FiniteProgress objprog, IndefiniteProgress clusprog) ExpandCluster function of DBSCAN.
protected void	OPTICS.expandClusterOrderDouble(ClusterOrderResult<DoubleDistance> clusterOrder, Database database, RangeQuery<O,DoubleDistance> rangeQuery, DBID objectID, DoubleDistance epsilon, FiniteProgress progress) OPTICS-function expandClusterOrder.
protected void	OPTICS.expandClusterOrderDouble(ClusterOrderResult<DoubleDistance> clusterOrder, Database database, RangeQuery<O,DoubleDistance> rangeQuery, DBID objectID, DoubleDistance epsilon, FiniteProgress progress) OPTICS-function expandClusterOrder.

Constructors in de.lmu.ifi.dbs.elki.algorithm.clustering with parameters of type DoubleDistance

AbstractProjectedDBSCAN(DoubleDistance epsilon, int minpts, LocallyWeightedDistanceFunction<V> distanceFunction, int lambda)
Constructor.

Uses of DoubleDistance in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation

Fields in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation declared as DoubleDistance

(package private) DoubleDistance

ORCLUS.ProjectedEnergy.projectedEnergy

Method parameters in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation with type arguments of type DoubleDistance

private void	ORCLUS.assign(Relation<V> database, DistanceQuery<V,DoubleDistance> distFunc, List<ORCLUS.ORCLUSCluster> clusters) Creates a partitioning of the database by assigning each object to its closest seed.
private Matrix	ORCLUS.findBasis(Relation<V> database, DistanceQuery<V,DoubleDistance> distFunc, ORCLUS.ORCLUSCluster cluster, int dim) Finds the basis of the subspace of dimensionality dim for the specified cluster.
private void	ORCLUS.merge(Relation<V> database, DistanceQuery<V,DoubleDistance> distFunc, List<ORCLUS.ORCLUSCluster> clusters, int k_new, int d_new, IndefiniteProgress cprogress) Reduces the number of seeds to k_new
private ORCLUS.ProjectedEnergy	ORCLUS.projectedEnergy(Relation<V> database, DistanceQuery<V,DoubleDistance> distFunc, ORCLUS.ORCLUSCluster c_i, ORCLUS.ORCLUSCluster c_j, int i, int j, int dim) Computes the projected energy of the specified clusters.
private ORCLUS.ORCLUSCluster	ORCLUS.union(Relation<V> database, DistanceQuery<V,DoubleDistance> distFunc, ORCLUS.ORCLUSCluster c1, ORCLUS.ORCLUSCluster c2, int dim) Returns the union of the two specified clusters.

Constructors in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation with parameters of type DoubleDistance

FourC(DoubleDistance epsilon, int minpts, LocallyWeightedDistanceFunction<V> distanceFunction, int lambda)
Constructor.

ORCLUS.ProjectedEnergy(int i, int j, ORCLUS.ORCLUSCluster cluster, DoubleDistance projectedEnergy)

Uses of DoubleDistance in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace

Fields in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace declared as DoubleDistance

private DoubleDistance	SUBCLU.epsilon Holds the value of SUBCLU.EPSILON_ID.
protected DoubleDistance	SUBCLU.Parameterizer.epsilon

Methods in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace that return DoubleDistance

private DoubleDistance

PROCLUS.manhattanSegmentalDistance(V o1, V o2, Set<Integer> dimensions) Returns the Manhattan segmental distance between o1 and o2 relative to the specified dimensions.

Methods in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace that return types with arguments of type DoubleDistance

private Map<DBID,List<DistanceResultPair<DoubleDistance>>>

PROCLUS.getLocalities(DBIDs medoids, Relation<V> database, DistanceQuery<V,DoubleDistance> distFunc, RangeQuery<V,DoubleDistance> rangeQuery) Computes the localities of the specified medoids: for each medoid m the objects in the sphere centered at m with radius minDist are determined, where minDist is the minimum distance between medoid m and any other medoid m_i.

Method parameters in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace with type arguments of type DoubleDistance

private Map<DBID,Set<Integer>>	PROCLUS.findDimensions(DBIDs medoids, Relation<V> database, DistanceQuery<V,DoubleDistance> distFunc, RangeQuery<V,DoubleDistance> rangeQuery) Determines the set of correlated dimensions for each medoid in the specified medoid set.
private Map<DBID,Set<Integer>>	PROCLUS.findDimensions(DBIDs medoids, Relation<V> database, DistanceQuery<V,DoubleDistance> distFunc, RangeQuery<V,DoubleDistance> rangeQuery) Determines the set of correlated dimensions for each medoid in the specified medoid set.
private Map<DBID,List<DistanceResultPair<DoubleDistance>>>	PROCLUS.getLocalities(DBIDs medoids, Relation<V> database, DistanceQuery<V,DoubleDistance> distFunc, RangeQuery<V,DoubleDistance> rangeQuery) Computes the localities of the specified medoids: for each medoid m the objects in the sphere centered at m with radius minDist are determined, where minDist is the minimum distance between medoid m and any other medoid m_i.
private Map<DBID,List<DistanceResultPair<DoubleDistance>>>	PROCLUS.getLocalities(DBIDs medoids, Relation<V> database, DistanceQuery<V,DoubleDistance> distFunc, RangeQuery<V,DoubleDistance> rangeQuery) Computes the localities of the specified medoids: for each medoid m the objects in the sphere centered at m with radius minDist are determined, where minDist is the minimum distance between medoid m and any other medoid m_i.
private ModifiableDBIDs	PROCLUS.greedy(DistanceQuery<V,DoubleDistance> distFunc, DBIDs sampleSet, int m, Random random) Returns a piercing set of k medoids from the specified sample set.

Constructors in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace with parameters of type DoubleDistance

PreDeCon(DoubleDistance epsilon, int minpts, LocallyWeightedDistanceFunction<V> distanceFunction, int lambda)
Constructor.

SUBCLU(AbstractDimensionsSelectingDoubleDistanceFunction<V> distanceFunction, DoubleDistance epsilon, int minpts)
Constructor.

Uses of DoubleDistance in de.lmu.ifi.dbs.elki.algorithm.outlier

Fields in de.lmu.ifi.dbs.elki.algorithm.outlier with type parameters of type DoubleDistance

private PrimitiveSimilarityFunction<? super V,DoubleDistance>	ABOD.primitiveKernelFunction Store the configured Kernel version
protected PrimitiveSimilarityFunction<V,DoubleDistance>	ABOD.Parameterizer.primitiveKernelFunction

Methods in de.lmu.ifi.dbs.elki.algorithm.outlier that return types with arguments of type DoubleDistance

private KNNList<DoubleDistance>

SOD.getKNN(Relation<V> database, SimilarityQuery<V,IntegerDistance> snnInstance, DBID queryObject) Provides the k nearest neighbors in terms of the shared nearest neighbor distance.

Constructor parameters in de.lmu.ifi.dbs.elki.algorithm.outlier with type arguments of type DoubleDistance

ABOD(int k, int sampleSize, PrimitiveSimilarityFunction<? super V,DoubleDistance> primitiveKernelFunction, DistanceFunction<V,DoubleDistance> distanceFunction)
Actual constructor, with parameters.

ABOD(int k, int sampleSize, PrimitiveSimilarityFunction<? super V,DoubleDistance> primitiveKernelFunction, DistanceFunction<V,DoubleDistance> distanceFunction)
Actual constructor, with parameters.

ABOD(int k, PrimitiveSimilarityFunction<? super V,DoubleDistance> primitiveKernelFunction, DistanceFunction<V,DoubleDistance> distanceFunction)
Actual constructor, with parameters.

ABOD(int k, PrimitiveSimilarityFunction<? super V,DoubleDistance> primitiveKernelFunction, DistanceFunction<V,DoubleDistance> distanceFunction)
Actual constructor, with parameters.

Uses of DoubleDistance in de.lmu.ifi.dbs.elki.database.query

Methods in de.lmu.ifi.dbs.elki.database.query that return DoubleDistance

DoubleDistance	DoubleDistanceResultPair.getDistance()
DoubleDistance	DoubleDistanceResultPair.getFirst() Deprecated. Use DoubleDistanceResultPair.getDoubleDistance() or DoubleDistanceResultPair.getDistance() for clearness.

Methods in de.lmu.ifi.dbs.elki.database.query with parameters of type DoubleDistance

void	DoubleDistanceResultPair.setDistance(DoubleDistance distance)

Method parameters in de.lmu.ifi.dbs.elki.database.query with type arguments of type DoubleDistance

int	DoubleDistanceResultPair.compareByDistance(DistanceResultPair<DoubleDistance> o)
int	DoubleDistanceResultPair.compareTo(DistanceResultPair<DoubleDistance> o)

Uses of DoubleDistance in de.lmu.ifi.dbs.elki.database.query.knn

Methods in de.lmu.ifi.dbs.elki.database.query.knn that return types with arguments of type DoubleDistance

List<DistanceResultPair<DoubleDistance>>	LinearScanRawDoubleDistanceKNNQuery.getKNNForDBID(DBID id, int k)
List<DistanceResultPair<DoubleDistance>>	LinearScanRawDoubleDistanceKNNQuery.getKNNForObject(O obj, int k)

Method parameters in de.lmu.ifi.dbs.elki.database.query.knn with type arguments of type DoubleDistance

protected void

LinearScanRawDoubleDistanceKNNQuery.linearScanBatchKNN(List<O> objs, List<KNNHeap<DoubleDistance>> heaps)

Constructor parameters in de.lmu.ifi.dbs.elki.database.query.knn with type arguments of type DoubleDistance

LinearScanRawDoubleDistanceKNNQuery(PrimitiveDistanceQuery<O,DoubleDistance> distanceQuery)
Constructor.

Uses of DoubleDistance in de.lmu.ifi.dbs.elki.database.query.range

Methods in de.lmu.ifi.dbs.elki.database.query.range that return types with arguments of type DoubleDistance

List<DistanceResultPair<DoubleDistance>>	LinearScanRawDoubleDistanceRangeQuery.getRangeForDBID(DBID id, DoubleDistance range)
List<DistanceResultPair<DoubleDistance>>	LinearScanRawDoubleDistanceRangeQuery.getRangeForObject(O obj, DoubleDistance range)

Methods in de.lmu.ifi.dbs.elki.database.query.range with parameters of type DoubleDistance

List<DistanceResultPair<DoubleDistance>>	LinearScanRawDoubleDistanceRangeQuery.getRangeForDBID(DBID id, DoubleDistance range)
List<DistanceResultPair<DoubleDistance>>	LinearScanRawDoubleDistanceRangeQuery.getRangeForObject(O obj, DoubleDistance range)

Constructor parameters in de.lmu.ifi.dbs.elki.database.query.range with type arguments of type DoubleDistance

LinearScanRawDoubleDistanceRangeQuery(DistanceQuery<O,DoubleDistance> distanceQuery)
Constructor.

Uses of DoubleDistance in de.lmu.ifi.dbs.elki.distance.distancefunction

Methods in de.lmu.ifi.dbs.elki.distance.distancefunction that return DoubleDistance

DoubleDistance	SquaredEuclideanDistanceFunction.centerDistance(SpatialComparable mbr1, SpatialComparable mbr2)
DoubleDistance	ManhattanDistanceFunction.centerDistance(SpatialComparable mbr1, SpatialComparable mbr2)
DoubleDistance	EuclideanDistanceFunction.centerDistance(SpatialComparable mbr1, SpatialComparable mbr2)
DoubleDistance	MaximumDistanceFunction.centerDistance(SpatialComparable mbr1, SpatialComparable mbr2)
DoubleDistance	MinimumDistanceFunction.centerDistance(SpatialComparable mbr1, SpatialComparable mbr2)
DoubleDistance	LocallyWeightedDistanceFunction.Instance.centerDistance(SpatialComparable mbr1, SpatialComparable mbr2)
DoubleDistance	SharedNearestNeighborJaccardDistanceFunction.Instance.distance(DBID id1, DBID id2)
DoubleDistance	LocallyWeightedDistanceFunction.Instance.distance(DBID id1, DBID id2) Computes the distance between two given real vectors according to this distance function.
DoubleDistance	RandomStableDistanceFunction.distance(DBID o1, DBID o2)
DoubleDistance	AbstractVectorDoubleDistanceFunction.distance(NumberVector<?,?> o1, NumberVector<?,?> o2)
DoubleDistance	LocallyWeightedDistanceFunction.Instance.distance(SpatialComparable mbr1, SpatialComparable mbr2)
DoubleDistance	AbstractVectorDoubleDistanceFunction.getDistanceFactory()
DoubleDistance	SharedNearestNeighborJaccardDistanceFunction.getDistanceFactory()
DoubleDistance	SharedNearestNeighborJaccardDistanceFunction.Instance.getDistanceFactory()
DoubleDistance	LocallyWeightedDistanceFunction.getDistanceFactory()
DoubleDistance	RandomStableDistanceFunction.getDistanceFactory()
DoubleDistance	SquaredEuclideanDistanceFunction.minDist(SpatialComparable mbr1, SpatialComparable mbr2)
DoubleDistance	ManhattanDistanceFunction.minDist(SpatialComparable mbr1, SpatialComparable mbr2)
DoubleDistance	EuclideanDistanceFunction.minDist(SpatialComparable mbr1, SpatialComparable mbr2)
DoubleDistance	MaximumDistanceFunction.minDist(SpatialComparable mbr1, SpatialComparable mbr2)
DoubleDistance	MinimumDistanceFunction.minDist(SpatialComparable mbr1, SpatialComparable mbr2)
DoubleDistance	LocallyWeightedDistanceFunction.Instance.minDistBROKEN(SpatialComparable mbr, V v)

Methods in de.lmu.ifi.dbs.elki.distance.distancefunction that return types with arguments of type DoubleDistance

<T extends NumberVector<?,?>> PrimitiveDistanceQuery<T,DoubleDistance>	AbstractCosineDistanceFunction.instantiate(Relation<T> relation)
<T extends NumberVector<?,?>> SpatialPrimitiveDistanceQuery<T,DoubleDistance>	SquaredEuclideanDistanceFunction.instantiate(Relation<T> relation)
<T extends NumberVector<?,?>> SpatialPrimitiveDistanceQuery<T,DoubleDistance>	ManhattanDistanceFunction.instantiate(Relation<T> relation)
<T extends NumberVector<?,?>> SpatialPrimitiveDistanceQuery<T,DoubleDistance>	EuclideanDistanceFunction.instantiate(Relation<T> relation)
<T extends NumberVector<?,?>> SpatialDistanceQuery<T,DoubleDistance>	MaximumDistanceFunction.instantiate(Relation<T> relation)
<T extends NumberVector<?,?>> SpatialPrimitiveDistanceQuery<T,DoubleDistance>	MinimumDistanceFunction.instantiate(Relation<T> relation)

Uses of DoubleDistance in de.lmu.ifi.dbs.elki.distance.distancefunction.adapter

Methods in de.lmu.ifi.dbs.elki.distance.distancefunction.adapter that return DoubleDistance

DoubleDistance	AbstractSimilarityAdapter.Instance.distance(DBID id1, DBID id2)
DoubleDistance	AbstractSimilarityAdapter.getDistanceFactory()
DoubleDistance	AbstractSimilarityAdapter.Instance.getDistanceFactory()

Methods in de.lmu.ifi.dbs.elki.distance.distancefunction.adapter that return types with arguments of type DoubleDistance

abstract <T extends O> DistanceQuery<T,DoubleDistance>	AbstractSimilarityAdapter.instantiate(Relation<T> database)
<T extends O> DistanceQuery<T,DoubleDistance>	SimilarityAdapterLn.instantiate(Relation<T> database)
<T extends O> DistanceQuery<T,DoubleDistance>	SimilarityAdapterLinear.instantiate(Relation<T> database)
<T extends O> DistanceQuery<T,DoubleDistance>	SimilarityAdapterArccos.instantiate(Relation<T> database)

Constructor parameters in de.lmu.ifi.dbs.elki.distance.distancefunction.adapter with type arguments of type DoubleDistance

AbstractSimilarityAdapter.Instance(Relation<O> database, DistanceFunction<? super O,DoubleDistance> parent, SimilarityQuery<? super O,? extends NumberDistance<?,?>> similarityQuery)
Constructor.

SimilarityAdapterArccos.Instance(Relation<O> database, DistanceFunction<? super O,DoubleDistance> parent, SimilarityQuery<O,? extends NumberDistance<?,?>> similarityQuery)
Constructor.

SimilarityAdapterLinear.Instance(Relation<O> database, DistanceFunction<? super O,DoubleDistance> parent, SimilarityQuery<? super O,? extends NumberDistance<?,?>> similarityQuery)
Constructor.

SimilarityAdapterLn.Instance(Relation<O> database, DistanceFunction<? super O,DoubleDistance> parent, SimilarityQuery<O,? extends NumberDistance<?,?>> similarityQuery)
Constructor.

Uses of DoubleDistance in de.lmu.ifi.dbs.elki.distance.distancefunction.colorhistogram

Methods in de.lmu.ifi.dbs.elki.distance.distancefunction.colorhistogram that return DoubleDistance

DoubleDistance	HistogramIntersectionDistanceFunction.centerDistance(SpatialComparable mbr1, SpatialComparable mbr2)
DoubleDistance	HistogramIntersectionDistanceFunction.minDist(SpatialComparable mbr1, SpatialComparable mbr2)

Methods in de.lmu.ifi.dbs.elki.distance.distancefunction.colorhistogram that return types with arguments of type DoubleDistance

<T extends NumberVector<?,?>> SpatialDistanceQuery<T,DoubleDistance>

HistogramIntersectionDistanceFunction.instantiate(Relation<T> relation)

Uses of DoubleDistance in de.lmu.ifi.dbs.elki.distance.distancefunction.external

Fields in de.lmu.ifi.dbs.elki.distance.distancefunction.external with type parameters of type DoubleDistance

private Map<DBIDPair,DoubleDistance>	FileBasedDoubleDistanceFunction.cache The distance cache
protected DistanceParser<DoubleDistance>	FileBasedDoubleDistanceFunction.Parameterizer.parser

Methods in de.lmu.ifi.dbs.elki.distance.distancefunction.external that return DoubleDistance

DoubleDistance	FileBasedDoubleDistanceFunction.distance(DBID id1, DBID id2) Returns the distance between the two objects specified by their objects ids.
DoubleDistance	DiskCacheBasedDoubleDistanceFunction.distance(DBID id1, DBID id2) Returns the distance between the two objects specified by their objects ids.
DoubleDistance	FileBasedDoubleDistanceFunction.getDistanceFactory()
DoubleDistance	DiskCacheBasedDoubleDistanceFunction.getDistanceFactory()

Method parameters in de.lmu.ifi.dbs.elki.distance.distancefunction.external with type arguments of type DoubleDistance

private void

FileBasedDoubleDistanceFunction.loadCache(DistanceParser<DoubleDistance> parser, File matrixfile)

Constructor parameters in de.lmu.ifi.dbs.elki.distance.distancefunction.external with type arguments of type DoubleDistance

FileBasedDoubleDistanceFunction(DistanceParser<DoubleDistance> parser, File matrixfile)
Constructor.

Uses of DoubleDistance in de.lmu.ifi.dbs.elki.distance.distancefunction.subspace

Methods in de.lmu.ifi.dbs.elki.distance.distancefunction.subspace that return DoubleDistance

DoubleDistance	DimensionsSelectingEuclideanDistanceFunction.centerDistance(SpatialComparable mbr1, SpatialComparable mbr2)
DoubleDistance	DimensionSelectingDistanceFunction.centerDistance(SpatialComparable mbr1, SpatialComparable mbr2)
DoubleDistance	DimensionSelectingDistanceFunction.distance(NumberVector<?,?> o1, NumberVector<?,?> o2)
DoubleDistance	AbstractDimensionsSelectingDoubleDistanceFunction.distance(V o1, V o2)
DoubleDistance	AbstractDimensionsSelectingDoubleDistanceFunction.getDistanceFactory()
DoubleDistance	DimensionSelectingDistanceFunction.getDistanceFactory()
DoubleDistance	DimensionsSelectingEuclideanDistanceFunction.minDist(SpatialComparable mbr1, SpatialComparable mbr2)
DoubleDistance	DimensionSelectingDistanceFunction.minDist(SpatialComparable mbr1, SpatialComparable mbr2)

Methods in de.lmu.ifi.dbs.elki.distance.distancefunction.subspace that return types with arguments of type DoubleDistance

<T extends NumberVector<?,?>> SpatialPrimitiveDistanceQuery<T,DoubleDistance>	DimensionsSelectingEuclideanDistanceFunction.instantiate(Relation<T> database)
<T extends NumberVector<?,?>> SpatialPrimitiveDistanceQuery<T,DoubleDistance>	DimensionSelectingDistanceFunction.instantiate(Relation<T> database)

Uses of DoubleDistance in de.lmu.ifi.dbs.elki.distance.distancevalue

Fields in de.lmu.ifi.dbs.elki.distance.distancevalue declared as DoubleDistance

static DoubleDistance

DoubleDistance.FACTORY The static factory instance

Methods in de.lmu.ifi.dbs.elki.distance.distancevalue that return DoubleDistance

DoubleDistance	DoubleDistance.fromDouble(double val)
DoubleDistance	DoubleDistance.infiniteDistance() An infinite DoubleDistance is based on Double.POSITIVE_INFINITY.
DoubleDistance	DoubleDistance.minus(DoubleDistance distance)
DoubleDistance	DoubleDistance.nullDistance() A null DoubleDistance is based on 0.
DoubleDistance	DoubleDistance.parseString(String val) As pattern is required a String defining a Double.
DoubleDistance	DoubleDistance.plus(DoubleDistance distance)
DoubleDistance	DoubleDistance.times(double lambda) Returns a new distance as the product of this distance and the given double value.
DoubleDistance	DoubleDistance.times(DoubleDistance distance) Returns a new distance as the product of this distance and the given distance.
DoubleDistance	DoubleDistance.undefinedDistance() An undefined DoubleDistance is based on Double.NaN.

Methods in de.lmu.ifi.dbs.elki.distance.distancevalue with parameters of type DoubleDistance

int	DoubleDistance.compareTo(DoubleDistance other)
DoubleDistance	DoubleDistance.minus(DoubleDistance distance)
DoubleDistance	DoubleDistance.plus(DoubleDistance distance)
DoubleDistance	DoubleDistance.times(DoubleDistance distance) Returns a new distance as the product of this distance and the given distance.

Uses of DoubleDistance in de.lmu.ifi.dbs.elki.distance.similarityfunction

Methods in de.lmu.ifi.dbs.elki.distance.similarityfunction that return DoubleDistance

DoubleDistance	FractionalSharedNearestNeighborSimilarityFunction.getDistanceFactory()
DoubleDistance	FractionalSharedNearestNeighborSimilarityFunction.Instance.getDistanceFactory()
DoubleDistance	FractionalSharedNearestNeighborSimilarityFunction.Instance.similarity(DBID id1, DBID id2)

Uses of DoubleDistance in de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel

Methods in de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel that return DoubleDistance

DoubleDistance	FooKernelFunction.distance(NumberVector<?,?> fv1, NumberVector<?,?> fv2)
DoubleDistance	PolynomialKernelFunction.distance(NumberVector<?,?> fv1, NumberVector<?,?> fv2)
DoubleDistance	LinearKernelFunction.distance(O fv1, O fv2)
DoubleDistance	FooKernelFunction.getDistanceFactory()
DoubleDistance	LinearKernelFunction.getDistanceFactory()
DoubleDistance	PolynomialKernelFunction.getDistanceFactory()
DoubleDistance	FooKernelFunction.similarity(NumberVector<?,?> o1, NumberVector<?,?> o2) Provides an experimental kernel similarity between the given two vectors.
DoubleDistance	PolynomialKernelFunction.similarity(NumberVector<?,?> o1, NumberVector<?,?> o2) Provides the linear kernel similarity between the given two vectors.
DoubleDistance	LinearKernelFunction.similarity(O o1, O o2) Provides a linear Kernel function that computes a similarity between the two feature vectors V1 and V2 definded by V1^T*V2

Methods in de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel that return types with arguments of type DoubleDistance

<T extends NumberVector<?,?>> DistanceSimilarityQuery<T,DoubleDistance>	FooKernelFunction.instantiate(Relation<T> database)
<T extends NumberVector<?,?>> DistanceSimilarityQuery<T,DoubleDistance>	PolynomialKernelFunction.instantiate(Relation<T> database)
<T extends O> DistanceSimilarityQuery<T,DoubleDistance>	LinearKernelFunction.instantiate(Relation<T> database)

Constructor parameters in de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel with type arguments of type DoubleDistance

KernelMatrix(PrimitiveSimilarityFunction<? super O,DoubleDistance> kernelFunction, Relation<? extends O> database)
Deprecated. ID mapping is not reliable!

KernelMatrix(PrimitiveSimilarityFunction<? super O,DoubleDistance> kernelFunction, Relation<? extends O> database, ArrayDBIDs ids)
Provides a new kernel matrix.

Uses of DoubleDistance in de.lmu.ifi.dbs.elki.index.preprocessed.localpca

Fields in de.lmu.ifi.dbs.elki.index.preprocessed.localpca declared as DoubleDistance

private DoubleDistance	RangeQueryFilteredPCAIndex.epsilon Query epsilon
protected DoubleDistance	RangeQueryFilteredPCAIndex.Factory.epsilon Holds the value of RangeQueryFilteredPCAIndex.Factory.EPSILON_ID.
protected DoubleDistance	RangeQueryFilteredPCAIndex.Factory.Parameterizer.epsilon

Fields in de.lmu.ifi.dbs.elki.index.preprocessed.localpca with type parameters of type DoubleDistance

private KNNQuery<NV,DoubleDistance>	KNNQueryFilteredPCAIndex.knnQuery The kNN query instance we use
protected DistanceFunction<NV,DoubleDistance>	AbstractFilteredPCAIndex.Factory.pcaDistanceFunction Holds the instance of the distance function specified by AbstractFilteredPCAIndex.Factory.PCA_DISTANCE_ID.
protected DistanceFunction<NV,DoubleDistance>	AbstractFilteredPCAIndex.Factory.Parameterizer.pcaDistanceFunction Holds the instance of the distance function specified by AbstractFilteredPCAIndex.Factory.PCA_DISTANCE_ID.
private RangeQuery<NV,DoubleDistance>	RangeQueryFilteredPCAIndex.rangeQuery The kNN query instance we use

Methods in de.lmu.ifi.dbs.elki.index.preprocessed.localpca that return types with arguments of type DoubleDistance

protected abstract List<DistanceResultPair<DoubleDistance>>	AbstractFilteredPCAIndex.objectsForPCA(DBID id) Returns the objects to be considered within the PCA for the specified query object.
protected List<DistanceResultPair<DoubleDistance>>	KNNQueryFilteredPCAIndex.objectsForPCA(DBID id)
protected List<DistanceResultPair<DoubleDistance>>	RangeQueryFilteredPCAIndex.objectsForPCA(DBID id)

Constructors in de.lmu.ifi.dbs.elki.index.preprocessed.localpca with parameters of type DoubleDistance

RangeQueryFilteredPCAIndex.Factory(DistanceFunction<V,DoubleDistance> pcaDistanceFunction, PCAFilteredRunner<V> pca, DoubleDistance epsilon)
Constructor.

RangeQueryFilteredPCAIndex(Relation<NV> database, PCAFilteredRunner<NV> pca, RangeQuery<NV,DoubleDistance> rangeQuery, DoubleDistance epsilon)
Constructor.

Constructor parameters in de.lmu.ifi.dbs.elki.index.preprocessed.localpca with type arguments of type DoubleDistance

AbstractFilteredPCAIndex.Factory(DistanceFunction<NV,DoubleDistance> pcaDistanceFunction, PCAFilteredRunner<NV> pca)
Constructor.

KNNQueryFilteredPCAIndex.Factory(DistanceFunction<V,DoubleDistance> pcaDistanceFunction, PCAFilteredRunner<V> pca, Integer k)
Constructor.

KNNQueryFilteredPCAIndex(Relation<NV> database, PCAFilteredRunner<NV> pca, KNNQuery<NV,DoubleDistance> knnQuery, int k)
Constructor.

RangeQueryFilteredPCAIndex.Factory(DistanceFunction<V,DoubleDistance> pcaDistanceFunction, PCAFilteredRunner<V> pca, DoubleDistance epsilon)
Constructor.

RangeQueryFilteredPCAIndex(Relation<NV> database, PCAFilteredRunner<NV> pca, RangeQuery<NV,DoubleDistance> rangeQuery, DoubleDistance epsilon)
Constructor.

Uses of DoubleDistance in de.lmu.ifi.dbs.elki.index.preprocessed.preference

Fields in de.lmu.ifi.dbs.elki.index.preprocessed.preference declared as DoubleDistance

static DoubleDistance	DiSHPreferenceVectorIndex.Factory.DEFAULT_EPSILON The default value for epsilon.
protected DoubleDistance[]	DiSHPreferenceVectorIndex.epsilon The epsilon value for each dimension;
protected DoubleDistance[]	DiSHPreferenceVectorIndex.Factory.epsilon The epsilon value for each dimension;
protected DoubleDistance[]	DiSHPreferenceVectorIndex.Factory.Parameterizer.epsilon The epsilon value for each dimension;

Constructors in de.lmu.ifi.dbs.elki.index.preprocessed.preference with parameters of type DoubleDistance

DiSHPreferenceVectorIndex.Factory(DoubleDistance[] epsilon, int minpts, DiSHPreferenceVectorIndex.Strategy strategy)
Constructor.

DiSHPreferenceVectorIndex(Relation<V> relation, DoubleDistance[] epsilon, int minpts, DiSHPreferenceVectorIndex.Strategy strategy)
Constructor.

Uses of DoubleDistance in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.query

Methods in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.query that return DoubleDistance

DoubleDistance

DoubleDistanceRStarTreeKNNQuery.getDistanceFactory()

Methods in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.query that return types with arguments of type DoubleDistance

protected List<DistanceResultPair<DoubleDistance>>	DoubleDistanceRStarTreeRangeQuery.doRangeQuery(O object, double epsilon) Perform the actual query process.
List<List<DistanceResultPair<DoubleDistance>>>	DoubleDistanceRStarTreeKNNQuery.getKNNForBulkDBIDs(ArrayDBIDs ids, int k)
List<DistanceResultPair<DoubleDistance>>	DoubleDistanceRStarTreeKNNQuery.getKNNForDBID(DBID id, int k)
List<DistanceResultPair<DoubleDistance>>	DoubleDistanceRStarTreeKNNQuery.getKNNForObject(O obj, int k)
List<DistanceResultPair<DoubleDistance>>	DoubleDistanceRStarTreeRangeQuery.getRangeForDBID(DBID id, DoubleDistance range)
List<DistanceResultPair<DoubleDistance>>	DoubleDistanceRStarTreeRangeQuery.getRangeForObject(O obj, DoubleDistance range)

Methods in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.query with parameters of type DoubleDistance

List<DistanceResultPair<DoubleDistance>>	DoubleDistanceRStarTreeRangeQuery.getRangeForDBID(DBID id, DoubleDistance range)
List<DistanceResultPair<DoubleDistance>>	DoubleDistanceRStarTreeRangeQuery.getRangeForObject(O obj, DoubleDistance range)

Method parameters in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.query with type arguments of type DoubleDistance

protected void	DoubleDistanceRStarTreeKNNQuery.batchNN(AbstractRStarTreeNode<?,?> node, Map<DBID,KNNHeap<DoubleDistance>> knnLists) Performs a batch knn query.
protected void	DoubleDistanceRStarTreeKNNQuery.doKNNQuery(O object, KNNHeap<DoubleDistance> knnList) Performs a k-nearest neighbor query for the given NumberVector with the given parameter k and the according distance function.
void	DoubleDistanceRStarTreeKNNQuery.getKNNForBulkHeaps(Map<DBID,KNNHeap<DoubleDistance>> heaps)

Constructor parameters in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.query with type arguments of type DoubleDistance

DoubleDistanceRStarTreeKNNQuery(AbstractRStarTree<?,?> tree, DistanceQuery<O,DoubleDistance> distanceQuery, SpatialPrimitiveDoubleDistanceFunction<? super O> distanceFunction)
Constructor.

DoubleDistanceRStarTreeRangeQuery(AbstractRStarTree<?,?> tree, DistanceQuery<O,DoubleDistance> distanceQuery, SpatialPrimitiveDoubleDistanceFunction<? super O> distanceFunction)
Constructor.

Uses of DoubleDistance in de.lmu.ifi.dbs.elki.math.linearalgebra.pca

Fields in de.lmu.ifi.dbs.elki.math.linearalgebra.pca with type parameters of type DoubleDistance

private PrimitiveDistanceFunction<? super V,DoubleDistance>

WeightedCovarianceMatrixBuilder.weightDistance Holds the distance function used for weight calculation

Uses of DoubleDistance in de.lmu.ifi.dbs.elki.result.optics

Methods in de.lmu.ifi.dbs.elki.result.optics that return DoubleDistance

DoubleDistance

DoubleDistanceClusterOrderEntry.getReachability() Returns the reachability distance of this entry

Method parameters in de.lmu.ifi.dbs.elki.result.optics with type arguments of type DoubleDistance

int	DoubleDistanceClusterOrderEntry.compareTo(ClusterOrderEntry<DoubleDistance> o)