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

Packages that use DistanceQuery

Package	Description
de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical	Hierarchical agglomerative clustering (HAC).
de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans	K-means clustering and variations
de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization	Initialization strategies for k-means.
de.lmu.ifi.dbs.elki.algorithm.clustering.optics	OPTICS family of 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.outlier.distance	Distance-based outlier detection algorithms, such as DBOutlier and kNN.
de.lmu.ifi.dbs.elki.algorithm.outlier.lof	LOF family of outlier detection algorithms
de.lmu.ifi.dbs.elki.algorithm.projection	Data projections (see also preprocessing filters for basic projections).
de.lmu.ifi.dbs.elki.algorithm.statistics	Statistical analysis algorithms.
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 Introduction The database query API is designed around the concept of prepared statements.
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, that return all objects within the radius ε
de.lmu.ifi.dbs.elki.database.query.rknn	Prepared queries for reverse k nearest neighbor (rkNN) queries
de.lmu.ifi.dbs.elki.database.relation	Relations, materialized and virtual (views)
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.external	Distance functions using external data sources
de.lmu.ifi.dbs.elki.evaluation.clustering.internal	Internal evaluation measures for clusterings.
de.lmu.ifi.dbs.elki.index	Index structure implementations
de.lmu.ifi.dbs.elki.index.distancematrix	Precomputed distance matrix.
de.lmu.ifi.dbs.elki.index.idistance	iDistance is a distance based indexing technique, using a reference points embedding.
de.lmu.ifi.dbs.elki.index.invertedlist	Indexes using inverted lists.
de.lmu.ifi.dbs.elki.index.lsh	Locality Sensitive Hashing
de.lmu.ifi.dbs.elki.index.preprocessed.knn	Indexes providing KNN and rKNN data.
de.lmu.ifi.dbs.elki.index.projected	Projected indexes for data
de.lmu.ifi.dbs.elki.index.tree.metrical.covertree	Cover-tree variations.
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.spatial.kd	K-d-tree and variants
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu	DeLiCluTree
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.flat	FlatRStarTree
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn	RdKNNTree
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rstar	RStarTree
de.lmu.ifi.dbs.elki.index.vafile	Vector Approximation File

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

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

Modifier and Type	Field and Description
private DistanceQuery<?>	AbstractHDBSCAN.HDBSCANAdapter.distq Distance query for exact distances.

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

Modifier and Type	Method and Description
private static double	MiniMax.findMax(DistanceQuery<?> dq, DBIDIter i, DBIDs cy, double maxDist, double minMaxDist) Find the maximum distance of one object to a set.
protected static int	MiniMax.findMerge(int end, MatrixParadigm mat, DBIDArrayMIter prots, PointerHierarchyRepresentationBuilder builder, it.unimi.dsi.fastutil.ints.Int2ObjectOpenHashMap<ModifiableDBIDs> clusters, DistanceQuery<?> dq) Find the best merge.
protected int	MiniMaxAnderberg.findMerge(int size, MatrixParadigm mat, DBIDArrayMIter prots, PointerHierarchyRepresentationBuilder builder, it.unimi.dsi.fastutil.ints.Int2ObjectOpenHashMap<ModifiableDBIDs> clusters, double[] bestd, int[] besti, DistanceQuery<O> dq) Perform the next merge step.
private static double	MiniMax.findPrototype(DistanceQuery<?> dq, DBIDs cx, DBIDs cy, DBIDVar prototype, double minMaxDist) Find the prototypes.
private static double	MiniMax.findPrototypeSingleton(DistanceQuery<?> dq, DBIDs cx, DBIDRef cy, DBIDVar prototype) Find the prototypes.
protected static void	AGNES.initializeDistanceMatrix(MatrixParadigm mat, DistanceQuery<?> dq, Linkage linkage) Initialize a distance matrix.
protected static <O> void	MiniMax.initializeMatrices(MatrixParadigm mat, ArrayModifiableDBIDs prots, DistanceQuery<O> dq) Initializes the inter-cluster distance matrix of possible merges
MatrixParadigm	MatrixParadigm.initializeWithDistances(DistanceQuery<?> dq) Initialize a distance matrix.
protected static void	MiniMax.merge(int size, MatrixParadigm mat, DBIDArrayMIter prots, PointerHierarchyRepresentationBuilder builder, it.unimi.dsi.fastutil.ints.Int2ObjectOpenHashMap<ModifiableDBIDs> clusters, DistanceQuery<?> dq, int x, int y) Merges two clusters given by x, y, their points with smallest IDs, and y to keep
protected void	MiniMaxAnderberg.merge(int size, MatrixParadigm mat, DBIDArrayMIter prots, PointerHierarchyRepresentationBuilder builder, it.unimi.dsi.fastutil.ints.Int2ObjectOpenHashMap<ModifiableDBIDs> clusters, DistanceQuery<O> dq, double[] bestd, int[] besti, int x, int y) Execute the cluster merge
private void	MiniMaxNNChain.nnChainCore(MatrixParadigm mat, DBIDArrayMIter prots, DistanceQuery<O> dq, PointerHierarchyRepresentationBuilder builder, it.unimi.dsi.fastutil.ints.Int2ObjectOpenHashMap<ModifiableDBIDs> clusters) Uses NNChain as in "Modern hierarchical, agglomerative clustering algorithms" by Daniel Müllner
private void	SLINK.step2(DBIDRef id, DBIDArrayIter it, int n, DistanceQuery<? super O> distQuery, WritableDoubleDataStore m) Second step: Determine the pairwise distances from all objects in the pointer representation to the new object with the specified id.
private void	SLINKHDBSCANLinearMemory.step2(DBIDRef id, DBIDs processedIDs, DistanceQuery<? super O> distQuery, DoubleDataStore coredists, WritableDoubleDataStore m) Second step: Determine the pairwise distances from all objects in the pointer representation to the new object with the specified id.
protected static void	MiniMax.updateEntry(MatrixParadigm mat, DBIDArrayMIter prots, it.unimi.dsi.fastutil.ints.Int2ObjectOpenHashMap<ModifiableDBIDs> clusters, DistanceQuery<?> dq, int x, int y) Update entry at x,y for distance matrix distances
private void	MiniMaxAnderberg.updateMatrices(int size, MatrixParadigm mat, DBIDArrayMIter prots, PointerHierarchyRepresentationBuilder builder, it.unimi.dsi.fastutil.ints.Int2ObjectOpenHashMap<ModifiableDBIDs> clusters, DistanceQuery<O> dq, double[] bestd, int[] besti, int x, int y) Update the entries of the matrices that contain a distance to y, the newly merged cluster.
protected static <O> void	MiniMax.updateMatrices(int size, MatrixParadigm mat, DBIDArrayMIter prots, PointerHierarchyRepresentationBuilder builder, it.unimi.dsi.fastutil.ints.Int2ObjectOpenHashMap<ModifiableDBIDs> clusters, DistanceQuery<O> dq, int c) Update the entries of the matrices that contain a distance to c, the newly merged cluster.

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

Constructor and Description
HDBSCANAdapter(ArrayDBIDs ids, DoubleDataStore coredists, DistanceQuery<?> distq) Constructor.

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

Classes in de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans that implement DistanceQuery

Modifier and Type	Class and Description
(package private) static class	CLARA.CachedDistanceQuery<V> Cached distance query.

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

Modifier and Type	Field and Description
(package private) DistanceQuery<?>	KMedoidsPAM.Instance.distQ Distance function to use.
(package private) DistanceQuery<?>	CLARANS.Assignment.distQ Distance function to use.
(package private) DistanceQuery<V>	CLARA.CachedDistanceQuery.inner Inner distance query

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

Modifier and Type	Method and Description
(package private) static double	CLARA.assignRemainingToNearestCluster(ArrayDBIDs means, DBIDs ids, DBIDs rids, WritableIntegerDataStore assignment, DistanceQuery<?> distQ) Returns a list of clusters.
protected double	KMedoidsPark.assignToNearestCluster(DBIDArrayIter miter, double[] dsum, java.util.List<? extends ModifiableDBIDs> clusters, DistanceQuery<V> distQ) Returns a list of clusters.
protected ArrayModifiableDBIDs	KMedoidsPAM.initialMedoids(DistanceQuery<V> distQ, DBIDs ids) Choose the initial medoids.
protected void	KMedoidsFastPAM.run(DistanceQuery<V> distQ, DBIDs ids, ArrayModifiableDBIDs medoids, WritableIntegerDataStore assignment)
protected void	KMedoidsFastPAM1.run(DistanceQuery<V> distQ, DBIDs ids, ArrayModifiableDBIDs medoids, WritableIntegerDataStore assignment)
protected void	KMedoidsPAM.run(DistanceQuery<V> distQ, DBIDs ids, ArrayModifiableDBIDs medoids, WritableIntegerDataStore assignment) Run the main algorithm.
protected void	KMedoidsPAMReynolds.run(DistanceQuery<V> distQ, DBIDs ids, ArrayModifiableDBIDs medoids, WritableIntegerDataStore assignment)

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

Constructor and Description
Assignment(DistanceQuery<?> distQ, DBIDs ids, int k) Constructor.
Assignment(DistanceQuery<?> distQ, DBIDs ids, int k) Constructor.
CachedDistanceQuery(DistanceQuery<V> inner, int size) Constructor.
Instance(DistanceQuery<?> distQ, DBIDs ids, WritableIntegerDataStore assignment) Constructor.
Instance(DistanceQuery<?> distQ, DBIDs ids, WritableIntegerDataStore assignment) Constructor.
Instance(DistanceQuery<?> distQ, DBIDs ids, WritableIntegerDataStore assignment) Constructor.
Instance(DistanceQuery<?> distQ, DBIDs ids, WritableIntegerDataStore assignment, double fasttol) Constructor.

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

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

Modifier and Type	Method and Description
DBIDs	PAMInitialMeans.chooseInitialMedoids(int k, DBIDs ids, DistanceQuery<? super O> distQ)
DBIDs	FirstKInitialMeans.chooseInitialMedoids(int k, DBIDs ids, DistanceQuery<? super O> distanceFunction)
DBIDs	FarthestPointsInitialMeans.chooseInitialMedoids(int k, DBIDs ids, DistanceQuery<? super O> distQ)
DBIDs	ParkInitialMeans.chooseInitialMedoids(int k, DBIDs ids, DistanceQuery<? super O> distQ)
DBIDs	FarthestSumPointsInitialMeans.chooseInitialMedoids(int k, DBIDs ids, DistanceQuery<? super O> distQ)
DBIDs	LABInitialMeans.chooseInitialMedoids(int k, DBIDs ids, DistanceQuery<? super O> distQ)
DBIDs	KMeansPlusPlusInitialMeans.chooseInitialMedoids(int k, DBIDs ids, DistanceQuery<? super O> distQ)
DBIDs	RandomlyChosenInitialMeans.chooseInitialMedoids(int k, DBIDs ids, DistanceQuery<? super O> distanceFunction)
DBIDs	KMedoidsInitialization.chooseInitialMedoids(int k, DBIDs ids, DistanceQuery<? super V> distanceFunction) Choose initial means
(package private) static void	KMeansPlusPlusInitialMeans.chooseRemaining(DBIDs ids, DistanceQuery<?> distQ, int k, ArrayModifiableDBIDs means, WritableDoubleDataStore weights, double weightsum, java.util.Random random) Choose remaining means, weighted by distance.
(package private) static void	KMeansPlusPlusInitialMeans.chooseRemaining(Relation<? extends NumberVector> relation, DBIDs ids, DistanceQuery<NumberVector> distQ, int k, java.util.List<NumberVector> means, WritableDoubleDataStore weights, double weightsum, java.util.Random random) Choose remaining means, weighted by distance.
protected static double	LABInitialMeans.getMinDist(DBIDArrayIter j, DistanceQuery<?> distQ, DBIDArrayIter mi, WritableDoubleDataStore mindist) Get the minimum distance to previous medoids.
(package private) static double	KMeansPlusPlusInitialMeans.initialWeights(WritableDoubleDataStore weights, DBIDs ids, DBIDRef latest, DistanceQuery<?> distQ) Initialize the weight list.
(package private) static double	KMeansPlusPlusInitialMeans.initialWeights(WritableDoubleDataStore weights, DBIDs ids, NumberVector first, DistanceQuery<? super NumberVector> distQ) Initialize the weight list.
protected static <T> double	OstrovskyInitialMeans.initialWeights(WritableDoubleDataStore weights, Relation<? extends T> relation, DBIDs ids, T first, T second, DistanceQuery<? super T> distQ) Initialize the weight list.
private static double	KMeansPlusPlusInitialMeans.updateWeights(WritableDoubleDataStore weights, DBIDs ids, DBIDRef latest, DistanceQuery<?> distQ) Update the weight list.
private static double	KMeansPlusPlusInitialMeans.updateWeights(WritableDoubleDataStore weights, DBIDs ids, NumberVector latest, DistanceQuery<? super NumberVector> distQ) Update the weight list.

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

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

Modifier and Type	Method and Description
protected void	FastOPTICS.expandClusterOrder(DBID ipt, ClusterOrder order, DistanceQuery<V> dq, FiniteProgress prog) OPTICS algorithm for processing a point, but with different density estimates

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

Modifier and Type	Method and Description
private long[][]	PROCLUS.findDimensions(ArrayDBIDs medoids, Relation<V> database, DistanceQuery<V> distFunc, RangeQuery<V> rangeQuery) Determines the set of correlated dimensions for each medoid in the specified medoid set.
private DataStore<DBIDs>	PROCLUS.getLocalities(DBIDs medoids, DistanceQuery<V> distFunc, RangeQuery<V> 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 ArrayDBIDs	PROCLUS.greedy(DistanceQuery<V> distFunc, DBIDs sampleSet, int m, java.util.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

Modifier and Type	Method and Description
private void	DWOF.initializeRadii(DBIDs ids, KNNQuery<O> knnq, DistanceQuery<O> distFunc, WritableDoubleDataStore radii) This method prepares a container for the radii of the objects and initializes radii according to the equation: initialRadii of a certain object = (absoluteMinDist of all objects) * (avgDist of the object) / (minAvgDist of all objects)

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

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

Modifier and Type	Field and Description
private DistanceQuery<O>	HilOut.distq Distance query

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

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

Modifier and Type	Method and Description
protected void	COF.computeAverageChainingDistances(KNNQuery<O> knnq, DistanceQuery<O> dq, DBIDs ids, WritableDoubleDataStore acds) Computes the average chaining distance, the average length of a path through the given set of points to each target.

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

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

Modifier and Type	Method and Description
protected double[][]	GaussianAffinityMatrixBuilder.buildDistanceMatrix(ArrayDBIDs ids, DistanceQuery<?> dq) Build a distance matrix of squared distances.

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

Modifier and Type	Method and Description
private void	EvaluateRetrievalPerformance.computeDistances(ModifiableDoubleDBIDList nlist, DBIDIter query, DistanceQuery<O> distQuery, Relation<O> relation) Compute the distances to the neighbor objects.
private DoubleMinMax	DistanceStatisticsWithClasses.exactMinMax(Relation<O> relation, DistanceQuery<O> distFunc) Compute the exact maximum and minimum.
private DoubleMinMax	DistanceStatisticsWithClasses.sampleMinMax(Relation<O> relation, DistanceQuery<O> distFunc) Estimate minimum and maximum via sampling.

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

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

Modifier and Type	Method and Description
static <O> DistanceQuery<O>	QueryUtil.getDistanceQuery(Database database, DistanceFunction<? super O> distanceFunction, java.lang.Object... hints) Get a distance query for a given distance function, automatically choosing a relation.
<O> DistanceQuery<O>	Database.getDistanceQuery(Relation<O> relation, DistanceFunction<? super O> distanceFunction, java.lang.Object... hints) Get the distance query for a particular distance function.
<O> DistanceQuery<O>	AbstractDatabase.getDistanceQuery(Relation<O> objQuery, DistanceFunction<? super O> distanceFunction, java.lang.Object... hints)
static <O> DistanceQuery<O>	DatabaseUtil.precomputedDistanceQuery(Database database, Relation<O> relation, DistanceFunction<? super O> distf, Logging log) Get (or create) a precomputed distance query for the database.

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

Modifier and Type	Method and Description
<O> KNNQuery<O>	Database.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints) Get a KNN query object for the given distance query.
<O> KNNQuery<O>	AbstractDatabase.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)
static <O> KNNQuery<O>	QueryUtil.getLinearScanKNNQuery(DistanceQuery<O> distanceQuery) Get a linear scan query for the given distance query.
static <O> RangeQuery<O>	QueryUtil.getLinearScanRangeQuery(DistanceQuery<O> distanceQuery) Get a linear scan query for the given distance query.
<O> RangeQuery<O>	Database.getRangeQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints) Get a range query object for the given distance query for radius-based neighbor search.
<O> RangeQuery<O>	AbstractDatabase.getRangeQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)
<O> RKNNQuery<O>	Database.getRKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints) Get a rKNN query object for the given distance query.
<O> RKNNQuery<O>	AbstractDatabase.getRKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)
static <O> KNNQuery<O>	DatabaseUtil.precomputedKNNQuery(Database database, Relation<O> relation, DistanceQuery<O> dq, int k) Get (or create) a precomputed kNN query for the database.

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

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

Modifier and Type	Interface and Description
interface	DistanceSimilarityQuery<O> 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

Modifier and Type	Interface and Description
interface	DatabaseDistanceQuery<O> Run a database query in a database context.
interface	SpatialDistanceQuery<V extends SpatialComparable> Query interface for spatial distance queries.

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

Modifier and Type	Class and Description
class	DBIDDistanceQuery Run a distance query based on DBIDs
class	DBIDRangeDistanceQuery Run a distance query based on DBIDRanges
class	PrimitiveDistanceQuery<O> Run a database query in a database context.
class	PrimitiveDistanceSimilarityQuery<O> Combination query class, for convenience.
class	SpatialPrimitiveDistanceQuery<V extends SpatialComparable> Distance query for spatial distance functions
class	SpatialPrimitiveDistanceSimilarityQuery<O extends SpatialComparable> Combination query class, to allow combined implementations of spatial distances and similarities.

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

Modifier and Type	Field and Description
protected DistanceQuery<O>	AbstractDistanceKNNQuery.distanceQuery Hold the distance function to be used.

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

Constructor and Description
AbstractDistanceKNNQuery(DistanceQuery<O> distanceQuery) Constructor.
LinearScanDistanceKNNQuery(DistanceQuery<O> 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

Modifier and Type	Field and Description
protected DistanceQuery<O>	AbstractDistanceRangeQuery.distanceQuery Hold the distance function to be used.

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

Constructor and Description
AbstractDistanceRangeQuery(DistanceQuery<O> distanceQuery) Constructor.
LinearScanDistanceRangeQuery(DistanceQuery<O> 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

Modifier and Type	Field and Description
protected DistanceQuery<O>	AbstractRKNNQuery.distanceQuery Hold the distance function to be used.

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

Constructor and Description
AbstractRKNNQuery(DistanceQuery<O> distanceQuery) Constructor.
LinearScanRKNNQuery(DistanceQuery<O> distanceQuery, KNNQuery<O> knnQuery, java.lang.Integer maxk) Constructor.

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

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

Modifier and Type	Method and Description
DistanceQuery<O>	Relation.getDistanceQuery(DistanceFunction<? super O> distanceFunction, java.lang.Object... hints) Get the distance query for a particular distance function.
DistanceQuery<O>	AbstractRelation.getDistanceQuery(DistanceFunction<? super O> distanceFunction, java.lang.Object... hints)

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

Modifier and Type	Method and Description
KNNQuery<O>	Relation.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints) Get a KNN query object for the given distance query.
KNNQuery<O>	AbstractRelation.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)
RangeQuery<O>	Relation.getRangeQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints) Get a range query object for the given distance query.
RangeQuery<O>	AbstractRelation.getRangeQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)
RKNNQuery<O>	Relation.getRKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints) Get a rKNN query object for the given distance query.
RKNNQuery<O>	AbstractRelation.getRKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)

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

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

Modifier and Type	Interface and Description
static interface	IndexBasedDistanceFunction.Instance<T,I extends Index> Instance interface for Index based distance functions.

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

Modifier and Type	Class and Description
static class	AbstractDatabaseDistanceFunction.Instance<O> The actual instance bound to a particular database.
static class	AbstractIndexBasedDistanceFunction.Instance<O,I extends Index,F extends DistanceFunction<? super O>> The actual instance bound to a particular database.
static class	SharedNearestNeighborJaccardDistanceFunction.Instance<T> Actual instance for a dataset.

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

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

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

Modifier and Type	Class and Description
static class	AbstractSimilarityAdapter.Instance<O> Inner proxy class for SNN distance function.
static class	ArccosSimilarityAdapter.Instance<O> Distance function instance
static class	LinearAdapterLinear.Instance<O> Distance function instance
static class	LnSimilarityAdapter.Instance<O> Distance function instance

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

Modifier and Type	Method and Description
abstract <T extends O> DistanceQuery<T>	AbstractSimilarityAdapter.instantiate(Relation<T> database)
<T extends O> DistanceQuery<T>	LnSimilarityAdapter.instantiate(Relation<T> database)
<T extends O> DistanceQuery<T>	ArccosSimilarityAdapter.instantiate(Relation<T> database)
<T extends O> DistanceQuery<T>	LinearAdapterLinear.instantiate(Relation<T> database)

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

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

Modifier and Type	Method and Description
<O extends DBID> DistanceQuery<O>	FileBasedSparseFloatDistanceFunction.instantiate(Relation<O> relation)
<O extends DBID> DistanceQuery<O>	FileBasedSparseDoubleDistanceFunction.instantiate(Relation<O> relation)

Uses of DistanceQuery in de.lmu.ifi.dbs.elki.evaluation.clustering.internal

Methods in de.lmu.ifi.dbs.elki.evaluation.clustering.internal with parameters of type DistanceQuery

Modifier and Type	Method and Description
double	EvaluateCIndex.evaluateClustering(Database db, Relation<? extends O> rel, DistanceQuery<O> dq, Clustering<?> c) Evaluate a single clustering.
double	EvaluateSilhouette.evaluateClustering(Database db, Relation<O> rel, DistanceQuery<O> dq, Clustering<?> c) Evaluate a single clustering.
protected double	EvaluateCIndex.processCluster(Cluster<?> cluster, java.util.List<? extends Cluster<?>> clusters, int i, DistanceQuery<O> dq, DoubleHeap maxDists, DoubleHeap minDists, int w)
protected void	EvaluateCIndex.processSingleton(Cluster<?> cluster, Relation<? extends O> rel, DistanceQuery<O> dq, DoubleHeap maxDists, DoubleHeap minDists, int w)

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

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

Modifier and Type	Method and Description
DistanceQuery<O>	DistanceIndex.getDistanceQuery(DistanceFunction<? super O> distanceFunction, java.lang.Object... hints) Get a KNN query object for the given distance query and k.

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

Modifier and Type	Method and Description
KNNQuery<O>	KNNIndex.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints) Get a KNN query object for the given distance query and k.
RangeQuery<O>	RangeIndex.getRangeQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints) Get a range query object for the given distance query and k.
RKNNQuery<O>	RKNNIndex.getRKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints) Get a KNN query object for the given distance query and k.

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

Constructor and Description
AbstractKNNQuery(DistanceQuery<O> distanceQuery) Constructor.
AbstractRangeQuery(DistanceQuery<O> distanceQuery) Constructor.

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

Classes in de.lmu.ifi.dbs.elki.index.distancematrix that implement DistanceQuery

Modifier and Type	Class and Description
private class	PrecomputedDistanceMatrix.PrecomputedDistanceQuery Distance query using the precomputed matrix.

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

Modifier and Type	Field and Description
protected DistanceQuery<O>	PrecomputedDistanceMatrix.distanceQuery Nested distance query.

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

Modifier and Type	Method and Description
DistanceQuery<O>	PrecomputedDistanceMatrix.getDistanceQuery(DistanceFunction<? super O> distanceFunction, java.lang.Object... hints)

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

Modifier and Type	Method and Description
KNNQuery<O>	PrecomputedDistanceMatrix.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)
RangeQuery<O>	PrecomputedDistanceMatrix.getRangeQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)

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

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

Modifier and Type	Field and Description
private DistanceQuery<O>	InMemoryIDistanceIndex.distanceQuery Distance query.

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

Modifier and Type	Method and Description
KNNQuery<O>	InMemoryIDistanceIndex.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)
RangeQuery<O>	InMemoryIDistanceIndex.getRangeQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)
protected static <O> DoubleIntPair[]	InMemoryIDistanceIndex.rankReferencePoints(DistanceQuery<O> distanceQuery, O obj, ArrayDBIDs referencepoints) Sort the reference points by distance to the query object

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

Constructor and Description
IDistanceKNNQuery(DistanceQuery<O> distanceQuery) Constructor.
IDistanceRangeQuery(DistanceQuery<O> distanceQuery) Constructor.
InMemoryIDistanceIndex(Relation<O> relation, DistanceQuery<O> distance, KMedoidsInitialization<O> initialization, int numref) Constructor.

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

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

Modifier and Type	Method and Description
KNNQuery<V>	InMemoryInvertedIndex.getKNNQuery(DistanceQuery<V> distanceQuery, java.lang.Object... hints)
RangeQuery<V>	InMemoryInvertedIndex.getRangeQuery(DistanceQuery<V> distanceQuery, java.lang.Object... hints)

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

Constructor and Description
ArcCosineKNNQuery(DistanceQuery<V> distanceQuery) Constructor.
ArcCosineRangeQuery(DistanceQuery<V> distanceQuery) Constructor.
CosineKNNQuery(DistanceQuery<V> distanceQuery) Constructor.
CosineRangeQuery(DistanceQuery<V> distanceQuery) Constructor.

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

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

Modifier and Type	Method and Description
KNNQuery<V>	InMemoryLSHIndex.Instance.getKNNQuery(DistanceQuery<V> distanceQuery, java.lang.Object... hints)
RangeQuery<V>	InMemoryLSHIndex.Instance.getRangeQuery(DistanceQuery<V> distanceQuery, java.lang.Object... hints)

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

Constructor and Description
LSHKNNQuery(DistanceQuery<V> distanceQuery) Constructor.
LSHRangeQuery(DistanceQuery<V> distanceQuery) Constructor.

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

Modifier and Type	Field and Description
protected DistanceQuery<O>	AbstractMaterializeKNNPreprocessor.distanceQuery The distance query we used.
(package private) DistanceQuery<O>	NaiveProjectedKNNPreprocessor.NaiveProjectedKNNQuery.distq Distance query to use for refinement
(package private) DistanceQuery<O>	SpacefillingKNNPreprocessor.SpaceFillingKNNQuery.distq Distance query to use for refinement

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

Modifier and Type	Method and Description
DistanceQuery<O>	AbstractMaterializeKNNPreprocessor.getDistanceQuery() The distance query we used.

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

Modifier and Type	Method and Description
KNNQuery<O>	NNDescent.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)
KNNQuery<O>	NaiveProjectedKNNPreprocessor.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)
KNNQuery<O>	SpacefillingMaterializeKNNPreprocessor.getKNNQuery(DistanceQuery<O> distQ, java.lang.Object... hints)
KNNQuery<O>	SpacefillingKNNPreprocessor.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)
KNNQuery<O>	AbstractMaterializeKNNPreprocessor.getKNNQuery(DistanceQuery<O> distQ, java.lang.Object... hints)
RKNNQuery<O>	MaterializeKNNAndRKNNPreprocessor.getRKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)

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

Constructor and Description
NaiveProjectedKNNQuery(DistanceQuery<O> distanceQuery) Constructor.
SpaceFillingKNNQuery(DistanceQuery<O> distanceQuery) Constructor.

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

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

Modifier and Type	Field and Description
(package private) DistanceQuery<O>	ProjectedIndex.ProjectedKNNQuery.distq Distance query for refinement.
(package private) DistanceQuery<O>	ProjectedIndex.ProjectedRKNNQuery.distq Distance query for refinement.

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

Modifier and Type	Method and Description
KNNQuery<O>	LatLngAsECEFIndex.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)
KNNQuery<O>	LngLatAsECEFIndex.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)
KNNQuery<O>	ProjectedIndex.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)
RangeQuery<O>	LatLngAsECEFIndex.getRangeQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)
RangeQuery<O>	LngLatAsECEFIndex.getRangeQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)
RangeQuery<O>	ProjectedIndex.getRangeQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)
RKNNQuery<O>	LatLngAsECEFIndex.getRKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)
RKNNQuery<O>	LngLatAsECEFIndex.getRKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)
RKNNQuery<O>	ProjectedIndex.getRKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)

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

Constructor and Description
ProjectedKNNQuery(DistanceQuery<O> distanceQuery, KNNQuery<I> inner) Constructor.
ProjectedRangeQuery(DistanceQuery<O> distanceQuery, RangeQuery<I> inner) Constructor.
ProjectedRKNNQuery(DistanceQuery<O> distanceQuery, RKNNQuery<I> inner) Constructor.

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

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

Modifier and Type	Field and Description
private DistanceQuery<O>	AbstractCoverTree.distanceQuery Distance query, on the data relation.

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

Modifier and Type	Method and Description
KNNQuery<O>	CoverTree.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)
KNNQuery<O>	SimplifiedCoverTree.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)
RangeQuery<O>	CoverTree.getRangeQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)
RangeQuery<O>	SimplifiedCoverTree.getRangeQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)

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

Constructor and Description
CoverTreeKNNQuery(DistanceQuery<O> distanceQuery) Constructor.
CoverTreeKNNQuery(DistanceQuery<O> distanceQuery) Constructor.
CoverTreeRangeQuery(DistanceQuery<O> distanceQuery) Constructor.
CoverTreeRangeQuery(DistanceQuery<O> distanceQuery) Constructor.

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

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

Modifier and Type	Field and Description
private DistanceQuery<O>	AbstractMkTree.distanceQuery Distance query to use.

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

Modifier and Type	Method and Description
KNNQuery<O>	MkAppTreeIndex.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)
RangeQuery<O>	MkAppTreeIndex.getRangeQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)
RKNNQuery<O>	MkAppTreeIndex.getRKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)

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

Modifier and Type	Method and Description
KNNQuery<O>	MkCoPTreeIndex.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)
RangeQuery<O>	MkCoPTreeIndex.getRangeQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)
RKNNQuery<O>	MkCoPTreeIndex.getRKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)

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

Modifier and Type	Method and Description
KNNQuery<O>	MkMaxTreeIndex.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)
RangeQuery<O>	MkMaxTreeIndex.getRangeQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)
RKNNQuery<O>	MkMaxTreeIndex.getRKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)

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

Modifier and Type	Method and Description
KNNQuery<O>	MkTabTreeIndex.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)
RangeQuery<O>	MkTabTreeIndex.getRangeQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)
RKNNQuery<O>	MkTabTreeIndex.getRKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)

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

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

Modifier and Type	Field and Description
protected DistanceQuery<O>	MTreeIndex.distanceQuery The distance query.

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

Modifier and Type	Method and Description
KNNQuery<O>	MTreeIndex.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)
RangeQuery<O>	MTreeIndex.getRangeQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)

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

Constructor and Description
MkTreeRKNNQuery(AbstractMkTree<O,?,?,?> index, DistanceQuery<O> distanceQuery) Constructor.
MTreeKNNQuery(AbstractMTree<O,?,?,?> index, DistanceQuery<O> distanceQuery) Constructor.
MTreeRangeQuery(AbstractMTree<O,?,?,?> index, DistanceQuery<O> distanceQuery) Constructor.

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

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

Modifier and Type	Method and Description
KNNQuery<O>	MinimalisticMemoryKDTree.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)
KNNQuery<O>	SmallMemoryKDTree.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)
RangeQuery<O>	MinimalisticMemoryKDTree.getRangeQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)
RangeQuery<O>	SmallMemoryKDTree.getRangeQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)

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

Constructor and Description
KDTreeKNNQuery(DistanceQuery<O> distanceQuery, Norm<? super O> norm) Constructor.
KDTreeKNNQuery(DistanceQuery<O> distanceQuery, Norm<? super O> norm) Constructor.
KDTreeRangeQuery(DistanceQuery<O> distanceQuery, Norm<? super O> norm) Constructor.
KDTreeRangeQuery(DistanceQuery<O> distanceQuery, Norm<? super O> norm) Constructor.

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

Modifier and Type	Method and Description
KNNQuery<O>	DeLiCluTreeIndex.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)
RangeQuery<O>	DeLiCluTreeIndex.getRangeQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)

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

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

Modifier and Type	Method and Description
KNNQuery<O>	FlatRStarTreeIndex.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)
RangeQuery<O>	FlatRStarTreeIndex.getRangeQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)

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

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

Modifier and Type	Method and Description
KNNQuery<O>	RdKNNTree.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)
RangeQuery<O>	RdKNNTree.getRangeQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)
RKNNQuery<O>	RdKNNTree.getRKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)

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

Modifier and Type	Method and Description
KNNQuery<O>	RStarTreeIndex.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)
RangeQuery<O>	RStarTreeIndex.getRangeQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)

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

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

Modifier and Type	Method and Description
KNNQuery<V>	PartialVAFile.getKNNQuery(DistanceQuery<V> distanceQuery, java.lang.Object... hints)
KNNQuery<V>	VAFile.getKNNQuery(DistanceQuery<V> distanceQuery, java.lang.Object... hints)
RangeQuery<V>	PartialVAFile.getRangeQuery(DistanceQuery<V> distanceQuery, java.lang.Object... hints)
RangeQuery<V>	VAFile.getRangeQuery(DistanceQuery<V> distanceQuery, java.lang.Object... hints)

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

Constructor and Description
PartialVAFileKNNQuery(DistanceQuery<V> ddq, double p, long[] subspace) Constructor.
PartialVAFileRangeQuery(DistanceQuery<V> ddq, double p, long[] subspace) Constructor.
VAFileKNNQuery(DistanceQuery<V> distanceQuery, double p) Constructor.
VAFileRangeQuery(DistanceQuery<V> distanceQuery, double p) Constructor.