Uses of Interface
de.lmu.ifi.dbs.elki.database.query.distance.DistanceQuery

Packages that use DistanceQuery

de.lmu.ifi.dbs.elki.algorithm	Algorithms suitable as a task for the KDDTask main routine.
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.algorithm.statistics	Statistical analysis algorithms The algorithms in this package perform statistical analysis of the data (e.g. compute distributions, distance distributions etc.)
de.lmu.ifi.dbs.elki.application.visualization	Visualization applications in ELKI.
de.lmu.ifi.dbs.elki.database	ELKI database layer - loading, storing, indexing and accessing data
de.lmu.ifi.dbs.elki.database.query	Database queries - computing distances, neighbors, similarities - API and general documentation.
de.lmu.ifi.dbs.elki.database.query.distance	Prepared queries for distances.
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.database.query.rknn	Prepared queries for reverse k nearest neighbor (rkNN) 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.correlation	Distance functions using correlations.
de.lmu.ifi.dbs.elki.distance.distancefunction.subspace	Distance functions based on subspaces.
de.lmu.ifi.dbs.elki.index	Index structure implementations
de.lmu.ifi.dbs.elki.index.preprocessed.knn	Indexes providing KNN and rKNN data.
de.lmu.ifi.dbs.elki.index.tree.metrical	Tree-based index structures for metrical vector spaces.
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants	M-Tree and variants.
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees	Metrical index structures based on the concepts of the M-Tree supporting processing of reverse k nearest neighbor queries by using the k-nn distances of the entries.
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkapp	MkAppTree
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop	MkCoPTree
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkmax	MkMaxTree
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mktab	MkTabTree
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mtree	MTree
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.query	Classes for performing queries (knn, range, ...) on metrical trees.
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.split	Splitting strategies of nodes in an M-Tree (and variants).
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu	DeLiCluTree
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.index.tree.spatial.rstarvariants.rstar	RStarTree

Uses of DistanceQuery in de.lmu.ifi.dbs.elki.algorithm

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

private D

KNNJoin.processDataPages(DistanceQuery<V,D> distQ, N pr, N ps, WritableDataStore<KNNHeap<D>> knnLists, D pr_knn_distance) Processes the two data pages pr and ps and determines the k-nearest neighbors of pr in ps.

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

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

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 DistanceQuery

private void

SLINK.step2(DBID newID, DBIDs processedIDs, DistanceQuery<O,D> distFunc, WritableDataStore<D> m) Second step: Determine the pairwise distances from all objects in the pointer representation to the new object with the specified id.

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

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

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 void	ERiC.buildHierarchy(SortedMap<Integer,List<Cluster<CorrelationModel<V>>>> clusterMap, DistanceQuery<V,IntegerDistance> query)
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.
ClusteringAlgorithm<Clustering<Model>>	COPAC.getPartitionAlgorithm(DistanceQuery<V,D> query) Returns the partition algorithm.
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 Clustering<Model>	COPAC.runPartitionAlgorithm(Relation<V> relation, Map<Integer,DBIDs> partitionMap, DistanceQuery<V,D> query) Runs the partition algorithm and creates the result.
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.

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

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

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 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.

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

Methods in de.lmu.ifi.dbs.elki.algorithm.outlier with parameters of type DistanceQuery

protected List<DistanceResultPair<D>>	ReferenceBasedOutlierDetection.computeDistanceVector(V refPoint, Relation<V> database, DistanceQuery<V,D> distFunc) Computes for each object the distance to one reference point.
protected DataStore<Double>	DBOutlierDetection.computeOutlierScores(Database database, DistanceQuery<O,D> distFunc, D neighborhoodSize)
protected abstract DataStore<Double>	AbstractDBOutlier.computeOutlierScores(Database database, DistanceQuery<O,D> distFunc, D d) computes an outlier score for each object of the database.
protected DataStore<Double>	DBOutlierScore.computeOutlierScores(Database database, DistanceQuery<O,D> distFunc, D d)

Uses of DistanceQuery in de.lmu.ifi.dbs.elki.algorithm.statistics

Methods in de.lmu.ifi.dbs.elki.algorithm.statistics with parameters of type DistanceQuery

private DoubleMinMax	DistanceStatisticsWithClasses.exactMinMax(Relation<O> database, DistanceQuery<O,D> distFunc)
private DoubleMinMax	DistanceStatisticsWithClasses.sampleMinMax(Relation<O> database, DistanceQuery<O,D> distFunc)

Uses of DistanceQuery in de.lmu.ifi.dbs.elki.application.visualization

Fields in de.lmu.ifi.dbs.elki.application.visualization declared as DistanceQuery

private DistanceQuery<O,D>

KNNExplorer.ExplorerWindow.distanceQuery Holds the instance of the distance function specified by KNNExplorer.DISTANCE_FUNCTION_ID.

Methods in de.lmu.ifi.dbs.elki.application.visualization with parameters of type DistanceQuery

void	KNNExplorer.ExplorerWindow.run(Database db, DistanceQuery<O,D> distanceQuery) Process the given Database and distance function.

Uses of DistanceQuery in de.lmu.ifi.dbs.elki.database

Methods in de.lmu.ifi.dbs.elki.database that return DistanceQuery

static <O,D extends Distance<D>> DistanceQuery<O,D>	QueryUtil.getDistanceQuery(Database database, DistanceFunction<? super O,D> distanceFunction, Object... hints) Get a distance query for a given distance function, automatically choosing a relation.
<O,D extends Distance<D>> DistanceQuery<O,D>	AbstractDatabase.getDistanceQuery(Relation<O> objQuery, DistanceFunction<? super O,D> distanceFunction, Object... hints)
<O,D extends Distance<D>> DistanceQuery<O,D>	Database.getDistanceQuery(Relation<O> relation, DistanceFunction<? super O,D> distanceFunction, Object... hints) Get the distance query for a particular distance function.

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

<O,D extends Distance<D>> KNNQuery<O,D>	AbstractDatabase.getKNNQuery(DistanceQuery<O,D> distanceQuery, Object... hints)
<O,D extends Distance<D>> KNNQuery<O,D>	Database.getKNNQuery(DistanceQuery<O,D> distanceQuery, Object... hints) Get a KNN query object for the given distance query.
static <O,D extends Distance<D>> KNNQuery<O,D>	QueryUtil.getLinearScanKNNQuery(DistanceQuery<O,D> distanceQuery) Get a linear scan query for the given distance query.
static <O,D extends Distance<D>> RangeQuery<O,D>	QueryUtil.getLinearScanRangeQuery(DistanceQuery<O,D> distanceQuery) Get a linear scan query for the given distance query.
<O,D extends Distance<D>> RangeQuery<O,D>	AbstractDatabase.getRangeQuery(DistanceQuery<O,D> distanceQuery, Object... hints)
<O,D extends Distance<D>> RangeQuery<O,D>	Database.getRangeQuery(DistanceQuery<O,D> distanceQuery, Object... hints) Get a range query object for the given distance query.
<O,D extends Distance<D>> RKNNQuery<O,D>	AbstractDatabase.getRKNNQuery(DistanceQuery<O,D> distanceQuery, Object... hints)
<O,D extends Distance<D>> RKNNQuery<O,D>	Database.getRKNNQuery(DistanceQuery<O,D> distanceQuery, Object... hints) Get a rKNN query object for the given distance query.

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

Subinterfaces of DistanceQuery in de.lmu.ifi.dbs.elki.database.query

interface

DistanceSimilarityQuery<O,D extends Distance<D>> Interface that is a combination of distance and a similarity function.

Uses of DistanceQuery in de.lmu.ifi.dbs.elki.database.query.distance

Subinterfaces of DistanceQuery in de.lmu.ifi.dbs.elki.database.query.distance

interface

SpatialDistanceQuery<V extends SpatialComparable,D extends Distance<D>> Query interface for spatial distance queries.

Classes in de.lmu.ifi.dbs.elki.database.query.distance that implement DistanceQuery

class	AbstractDatabaseDistanceQuery<O,D extends Distance<D>> Run a database query in a database context.
class	AbstractDistanceQuery<O,D extends Distance<D>> A distance query serves as adapter layer for database and primitive distances.
class	DBIDDistanceQuery<D extends Distance<D>> Run a distance query based on DBIDs
class	PrimitiveDistanceQuery<O,D extends Distance<D>> Run a database query in a database context.
class	PrimitiveDistanceSimilarityQuery<O,D extends Distance<D>> Combination query class, for convenience.
class	SpatialPrimitiveDistanceQuery<V extends SpatialComparable,D extends Distance<D>> Distance query for spatial distance functions

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

Fields in de.lmu.ifi.dbs.elki.database.query.knn declared as DistanceQuery

protected DistanceQuery<O,D>

AbstractDistanceKNNQuery.distanceQuery Hold the distance function to be used.

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

DistanceQuery<O,D>	KNNQuery.getDistanceQuery() Get the distance query for this function.
DistanceQuery<O,D>	PreprocessorKNNQuery.getDistanceQuery()
DistanceQuery<O,D>	AbstractDistanceKNNQuery.getDistanceQuery()

Constructors in de.lmu.ifi.dbs.elki.database.query.knn with parameters of type DistanceQuery

AbstractDistanceKNNQuery(DistanceQuery<O,D> distanceQuery)
Constructor.

LinearScanKNNQuery(DistanceQuery<O,D> distanceQuery)
Constructor.

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

Fields in de.lmu.ifi.dbs.elki.database.query.range declared as DistanceQuery

protected DistanceQuery<O,D>

AbstractDistanceRangeQuery.distanceQuery Hold the distance function to be used.

Constructors in de.lmu.ifi.dbs.elki.database.query.range with parameters of type DistanceQuery

AbstractDistanceRangeQuery(DistanceQuery<O,D> distanceQuery)
Constructor.

LinearScanRangeQuery(DistanceQuery<O,D> distanceQuery)
Constructor.

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

Uses of DistanceQuery in de.lmu.ifi.dbs.elki.database.query.rknn

Fields in de.lmu.ifi.dbs.elki.database.query.rknn declared as DistanceQuery

protected DistanceQuery<O,D>

AbstractRKNNQuery.distanceQuery Hold the distance function to be used.

Constructors in de.lmu.ifi.dbs.elki.database.query.rknn with parameters of type DistanceQuery

AbstractRKNNQuery(DistanceQuery<O,D> distanceQuery)
Constructor.

LinearScanRKNNQuery(DistanceQuery<O,D> distanceQuery, KNNQuery<O,D> knnQuery, Integer maxk)
Constructor.

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

Subinterfaces of DistanceQuery in de.lmu.ifi.dbs.elki.distance.distancefunction

static interface	FilteredLocalPCABasedDistanceFunction.Instance<T extends NumberVector<?,?>,I extends Index,D extends Distance<D>> Instance produced by the distance function.
static interface	IndexBasedDistanceFunction.Instance<T,I extends Index,D extends Distance<D>> Instance interface for Index based distance functions.

Classes in de.lmu.ifi.dbs.elki.distance.distancefunction that implement DistanceQuery

static class	AbstractDatabaseDistanceFunction.Instance<O,D extends Distance<D>> The actual instance bound to a particular database.
static class	AbstractIndexBasedDistanceFunction.Instance<O,I extends Index,D extends Distance<D>,F extends DistanceFunction<? super O,D>> The actual instance bound to a particular database.
static class	LocallyWeightedDistanceFunction.Instance<V extends NumberVector<?,?>> Instance of this distance for a particular database.
class	MinKDistance.Instance<T extends O> Instance for an actual database.
static class	SharedNearestNeighborJaccardDistanceFunction.Instance<T> Actual instance for a dataset.

Fields in de.lmu.ifi.dbs.elki.distance.distancefunction declared as DistanceQuery

(package private) DistanceQuery<O,D>

ProxyDistanceFunction.inner Distance query

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

DistanceQuery<O,D>	ProxyDistanceFunction.getDistanceQuery() Get the inner query
<O extends DBID> DistanceQuery<O,D>	AbstractDBIDDistanceFunction.instantiate(Relation<O> database)
<T extends O> DistanceQuery<T,D>	DistanceFunction.instantiate(Relation<T> relation) Instantiate with a database to get the actual distance query.
<T extends O> DistanceQuery<T,D>	MinKDistance.instantiate(Relation<T> relation)
<T extends O> DistanceQuery<T,D>	AbstractPrimitiveDistanceFunction.instantiate(Relation<T> relation) Instantiate with a database to get the actual distance query.

Methods in de.lmu.ifi.dbs.elki.distance.distancefunction with parameters of type DistanceQuery

static <O,D extends Distance<D>> ProxyDistanceFunction<O,D>	ProxyDistanceFunction.proxy(DistanceQuery<O,D> inner) Static method version.
void	ProxyDistanceFunction.setDistanceQuery(DistanceQuery<O,D> inner)

Constructors in de.lmu.ifi.dbs.elki.distance.distancefunction with parameters of type DistanceQuery

ProxyDistanceFunction(DistanceQuery<O,D> inner)
Constructor

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

Classes in de.lmu.ifi.dbs.elki.distance.distancefunction.adapter that implement DistanceQuery

static class	AbstractSimilarityAdapter.Instance<O> Inner proxy class for SNN distance function.
static class	SimilarityAdapterArccos.Instance<O> Distance function instance
static class	SimilarityAdapterLinear.Instance<O> Distance function instance
static class	SimilarityAdapterLn.Instance<O> Distance function instance

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

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)

Uses of DistanceQuery in de.lmu.ifi.dbs.elki.distance.distancefunction.correlation

Classes in de.lmu.ifi.dbs.elki.distance.distancefunction.correlation that implement DistanceQuery

static class	ERiCDistanceFunction.Instance<V extends NumberVector<?,?>> The actual instance bound to a particular database.
static class	PCABasedCorrelationDistanceFunction.Instance<V extends NumberVector<?,?>> The actual instance bound to a particular database.

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

Classes in de.lmu.ifi.dbs.elki.distance.distancefunction.subspace that implement DistanceQuery

static class	AbstractPreferenceVectorBasedCorrelationDistanceFunction.Instance<V extends NumberVector<?,?>,P extends PreferenceVectorIndex<V>> Instance to compute the distances on an actual database.
static class	DiSHDistanceFunction.Instance<V extends NumberVector<?,?>> The actual instance bound to a particular database.
static class	HiSCDistanceFunction.Instance<V extends NumberVector<?,?>> The actual instance bound to a particular database.
static class	SubspaceDistanceFunction.Instance<V extends NumberVector<?,?>> The actual instance bound to a particular database.

Uses of DistanceQuery in de.lmu.ifi.dbs.elki.index

Methods in de.lmu.ifi.dbs.elki.index with parameters of type DistanceQuery

<D extends Distance<D>> KNNQuery<O,D>	KNNIndex.getKNNQuery(DistanceQuery<O,D> distanceQuery, Object... hints) Get a KNN query object for the given distance query and k.
<D extends Distance<D>> RangeQuery<O,D>	RangeIndex.getRangeQuery(DistanceQuery<O,D> distanceQuery, Object... hints) Get a range query object for the given distance query and k.
<D extends Distance<D>> RKNNQuery<O,D>	RKNNIndex.getRKNNQuery(DistanceQuery<O,D> distanceQuery, Object... hints) Get a KNN query object for the given distance query and k.

Uses of DistanceQuery in de.lmu.ifi.dbs.elki.index.preprocessed.knn

Fields in de.lmu.ifi.dbs.elki.index.preprocessed.knn declared as DistanceQuery

protected DistanceQuery<O,D>

AbstractMaterializeKNNPreprocessor.distanceQuery The distance query we used.

Methods in de.lmu.ifi.dbs.elki.index.preprocessed.knn that return DistanceQuery

DistanceQuery<O,D>

AbstractMaterializeKNNPreprocessor.getDistanceQuery() The distance query we used.

Methods in de.lmu.ifi.dbs.elki.index.preprocessed.knn with parameters of type DistanceQuery

<S extends Distance<S>> KNNQuery<O,S>	AbstractMaterializeKNNPreprocessor.getKNNQuery(DistanceQuery<O,S> distanceQuery, Object... hints)
<S extends Distance<S>> RKNNQuery<O,S>	MaterializeKNNAndRKNNPreprocessor.getRKNNQuery(DistanceQuery<O,S> distanceQuery, Object... hints)

Uses of DistanceQuery in de.lmu.ifi.dbs.elki.index.tree.metrical

Methods in de.lmu.ifi.dbs.elki.index.tree.metrical that return DistanceQuery

abstract DistanceQuery<O,D>

MetricalIndexTree.getDistanceQuery() Returns the distance function of this metrical index.

Uses of DistanceQuery in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants

Fields in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants declared as DistanceQuery

protected DistanceQuery<O,D>

AbstractMTree.distanceQuery The distance query

Methods in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants that return DistanceQuery

DistanceQuery<O,D>

AbstractMTree.getDistanceQuery()

Constructors in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants with parameters of type DistanceQuery

AbstractMTree(PageFile<N> pagefile, DistanceQuery<O,D> distanceQuery, DistanceFunction<O,D> distanceFunction)
Constructor.

Uses of DistanceQuery in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees

Constructors in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees with parameters of type DistanceQuery

AbstractMkTree(PageFile<N> pagefile, DistanceQuery<O,D> distanceQuery, DistanceFunction<O,D> distanceFunction)
Constructor.

AbstractMkTreeUnified(PageFile<N> pagefile, DistanceQuery<O,D> distanceQuery, DistanceFunction<O,D> distanceFunction, int k_max)
Constructor.

Uses of DistanceQuery in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkapp

Methods in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkapp with parameters of type DistanceQuery

<S extends Distance<S>> KNNQuery<O,S>	MkAppTreeIndex.getKNNQuery(DistanceQuery<O,S> distanceQuery, Object... hints)
<S extends Distance<S>> RangeQuery<O,S>	MkAppTreeIndex.getRangeQuery(DistanceQuery<O,S> distanceQuery, Object... hints)
<S extends Distance<S>> RKNNQuery<O,S>	MkAppTreeIndex.getRKNNQuery(DistanceQuery<O,S> distanceQuery, Object... hints)

Constructors in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkapp with parameters of type DistanceQuery

MkAppTree(PageFile<MkAppTreeNode<O,D>> pageFile, DistanceQuery<O,D> distanceQuery, DistanceFunction<O,D> distanceFunction, int k_max, int p, boolean log)
Constructor.

MkAppTreeIndex(Relation<O> relation, PageFile<MkAppTreeNode<O,D>> pageFile, DistanceQuery<O,D> distanceQuery, DistanceFunction<O,D> distanceFunction, int k_max, int p, boolean log)
Constructor.

Uses of DistanceQuery in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop

Methods in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop with parameters of type DistanceQuery

<O> D	MkCoPDirectoryEntry.approximateConservativeKnnDistance(int k, DistanceQuery<O,D> distanceFunction) Returns the conservative approximated knn distance of the entry.
<O> D	MkCoPEntry.approximateConservativeKnnDistance(int k, DistanceQuery<O,D> distanceFunction) Returns the conservative approximated knn distance of the entry.
<O> D	MkCoPLeafEntry.approximateConservativeKnnDistance(int k, DistanceQuery<O,D> distanceFunction) Returns the conservative approximated knn distance of the entry.
<O> D	MkCoPLeafEntry.approximateProgressiveKnnDistance(int k, DistanceQuery<O,D> distanceFunction) Returns the progressive approximated knn distance of the entry.
<O,D extends NumberDistance<D,?>> D	ApproximationLine.getApproximatedKnnDistance(int k, DistanceQuery<O,D> distanceFunction) Returns the approximated knn-distance at the specified k.
<S extends Distance<S>> KNNQuery<O,S>	MkCoPTreeIndex.getKNNQuery(DistanceQuery<O,S> distanceQuery, Object... hints)
<S extends Distance<S>> RangeQuery<O,S>	MkCoPTreeIndex.getRangeQuery(DistanceQuery<O,S> distanceQuery, Object... hints)
<S extends Distance<S>> RKNNQuery<O,S>	MkCoPTreeIndex.getRKNNQuery(DistanceQuery<O,S> distanceQuery, Object... hints)

Constructors in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop with parameters of type DistanceQuery

MkCoPTree(PageFile<MkCoPTreeNode<O,D>> pagefile, DistanceQuery<O,D> distanceQuery, DistanceFunction<O,D> distanceFunction, int k_max)
Constructor.

MkCoPTreeIndex(Relation<O> relation, PageFile<MkCoPTreeNode<O,D>> pageFile, DistanceQuery<O,D> distanceQuery, DistanceFunction<O,D> distanceFunction, int k_max)
Constructor.

Uses of DistanceQuery in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkmax

Methods in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkmax with parameters of type DistanceQuery

<S extends Distance<S>> KNNQuery<O,S>	MkMaxTreeIndex.getKNNQuery(DistanceQuery<O,S> distanceQuery, Object... hints)
<S extends Distance<S>> RangeQuery<O,S>	MkMaxTreeIndex.getRangeQuery(DistanceQuery<O,S> distanceQuery, Object... hints)
<S extends Distance<S>> RKNNQuery<O,S>	MkMaxTreeIndex.getRKNNQuery(DistanceQuery<O,S> distanceQuery, Object... hints)
protected D	MkMaxTreeNode.kNNDistance(DistanceQuery<O,D> distanceFunction) Determines and returns the k-nearest neighbor distance of this node as the maximum of the k-nearest neighbor distances of all entries.

Constructors in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkmax with parameters of type DistanceQuery

MkMaxTree(PageFile<MkMaxTreeNode<O,D>> pagefile, DistanceQuery<O,D> distanceQuery, DistanceFunction<O,D> distanceFunction, int k_max)
Constructor.

MkMaxTreeIndex(Relation<O> relation, PageFile<MkMaxTreeNode<O,D>> pagefile, DistanceQuery<O,D> distanceQuery, DistanceFunction<O,D> distanceFunction, int k_max)
Constructor.

Uses of DistanceQuery in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mktab

Methods in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mktab with parameters of type DistanceQuery

<S extends Distance<S>> KNNQuery<O,S>	MkTabTreeIndex.getKNNQuery(DistanceQuery<O,S> distanceQuery, Object... hints)
<S extends Distance<S>> RangeQuery<O,S>	MkTabTreeIndex.getRangeQuery(DistanceQuery<O,S> distanceQuery, Object... hints)
<S extends Distance<S>> RKNNQuery<O,S>	MkTabTreeIndex.getRKNNQuery(DistanceQuery<O,S> distanceQuery, Object... hints)
protected List<D>	MkTabTreeNode.kNNDistances(DistanceQuery<O,D> distanceFunction) Determines and returns the knn distance of this node as the maximum knn distance of all entries.

Constructors in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mktab with parameters of type DistanceQuery

MkTabTree(PageFile<MkTabTreeNode<O,D>> pagefile, DistanceQuery<O,D> distanceQuery, DistanceFunction<O,D> distanceFunction, int k_max)
Constructor.

MkTabTreeIndex(Relation<O> relation, PageFile<MkTabTreeNode<O,D>> pagefile, DistanceQuery<O,D> distanceQuery, DistanceFunction<O,D> distanceFunction, int k_max)
Constructor.

Uses of DistanceQuery in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mtree

Methods in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mtree with parameters of type DistanceQuery

<S extends Distance<S>> KNNQuery<O,S>	MTreeIndex.getKNNQuery(DistanceQuery<O,S> distanceQuery, Object... hints)
<S extends Distance<S>> RangeQuery<O,S>	MTreeIndex.getRangeQuery(DistanceQuery<O,S> distanceQuery, Object... hints)

Constructors in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mtree with parameters of type DistanceQuery

MTree(PageFile<MTreeNode<O,D>> pagefile, DistanceQuery<O,D> distanceQuery, DistanceFunction<O,D> distanceFunction)
Constructor.

MTreeIndex(Relation<O> relation, PageFile<MTreeNode<O,D>> pagefile, DistanceQuery<O,D> distanceQuery, DistanceFunction<O,D> distanceFunction)
Constructor.

Uses of DistanceQuery in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.query

Constructors in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.query with parameters of type DistanceQuery

MetricalIndexKNNQuery(AbstractMTree<O,D,?,?> index, DistanceQuery<O,D> distanceQuery)
Constructor.

MetricalIndexRangeQuery(AbstractMTree<O,D,?,?> index, DistanceQuery<O,D> distanceQuery)
Constructor.

MkTreeRKNNQuery(AbstractMkTree<O,D,?,?> index, DistanceQuery<O,D> distanceQuery)
Constructor.

Uses of DistanceQuery in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.split

Methods in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.split with parameters of type DistanceQuery

(package private) Assignments<D,E>	MTreeSplit.balancedPartition(N node, DBID routingObject1, DBID routingObject2, DistanceQuery<O,D> distanceFunction) Creates a balanced partition of the entries of the specified node.
private void	MLBDistSplit.promote(N node, DistanceQuery<O,D> distanceFunction) Selects the second object of the specified node to be promoted and stored into the parent node and partitions the entries according to the M_LB_DIST strategy.
private void	MRadSplit.promote(N node, DistanceQuery<O,D> distanceFunction) Selects two objects of the specified node to be promoted and stored into the parent node.

Constructors in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.split with parameters of type DistanceQuery

MLBDistSplit(N node, DistanceQuery<O,D> distanceFunction)
Creates a new split object.

MRadSplit(N node, DistanceQuery<O,D> distanceFunction)
Creates a new split object.

Uses of DistanceQuery in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu

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

<D extends Distance<D>> KNNQuery<O,D>	DeLiCluTreeIndex.getKNNQuery(DistanceQuery<O,D> distanceQuery, Object... hints)
<D extends Distance<D>> RangeQuery<O,D>	DeLiCluTreeIndex.getRangeQuery(DistanceQuery<O,D> distanceQuery, Object... hints)

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

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

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 DistanceQuery in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rstar

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

<D extends Distance<D>> KNNQuery<O,D>	RStarTreeIndex.getKNNQuery(DistanceQuery<O,D> distanceQuery, Object... hints)
<D extends Distance<D>> RangeQuery<O,D>	RStarTreeIndex.getRangeQuery(DistanceQuery<O,D> distanceQuery, Object... hints)