Uses of Interface
elki.database.query.distance.DistanceQuery
-
Packages that use DistanceQuery Package Description elki.algorithm.statistics Statistical analysis algorithms.elki.clustering.hierarchical Hierarchical agglomerative clustering (HAC).elki.clustering.kmeans.initialization Initialization strategies for k-means.elki.clustering.kmedoids K-medoids clustering (PAM).elki.clustering.kmedoids.initialization elki.clustering.optics OPTICS family of clustering algorithms.elki.clustering.silhouette Silhouette clustering algorithms.elki.clustering.subspace Axis-parallel subspace clustering algorithms.elki.database.query Database queries - computing distances, neighbors, similarities - API and general documentation.elki.database.query.distance Prepared queries for distances.elki.database.query.knn Prepared queries for k nearest neighbor (kNN) queries.elki.database.query.range Prepared queries for ε-range queries, that return all objects within the radius ε.elki.database.query.rknn Prepared queries for reverse k nearest neighbor (rkNN) queries.elki.distance Distance functions for use within ELKI.elki.distance.adapter Distance functions deriving distances from, e.g., similarity measures.elki.distance.external Distance functions using external data sources.elki.evaluation.clustering.internal Internal evaluation measures for clusterings.elki.index Index structure implementations.elki.index.distancematrix Precomputed distance matrix.elki.index.idistance iDistance is a distance based indexing technique, using a reference points embedding.elki.index.invertedlist Indexes using inverted lists.elki.index.laesa Linear Approximating and Eliminating Search Algorithm (LAESA).elki.index.lsh Locality Sensitive Hashing.elki.index.preprocessed.knn Indexes providing KNN and rKNN data.elki.index.projected Projected indexes for data.elki.index.tree.metrical.covertree Cover-tree variations.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.elki.index.tree.metrical.mtreevariants.mktrees.mkapp elki.index.tree.metrical.mtreevariants.mktrees.mkcop elki.index.tree.metrical.mtreevariants.mktrees.mkmax elki.index.tree.metrical.mtreevariants.mktrees.mktab elki.index.tree.metrical.mtreevariants.mtree elki.index.tree.metrical.mtreevariants.query Classes for performing queries (knn, range, ...) on metrical trees.elki.index.tree.metrical.vptree elki.index.tree.spatial.kd K-d-tree and variants.elki.index.tree.spatial.rstarvariants.deliclu elki.index.tree.spatial.rstarvariants.flat elki.index.tree.spatial.rstarvariants.rdknn elki.index.tree.spatial.rstarvariants.rstar elki.index.vafile Vector Approximation File.elki.math.statistics.intrinsicdimensionality Methods for estimating the intrinsic dimensionality.elki.outlier Outlier detection algorithms.elki.outlier.distance Distance-based outlier detection algorithms, such as DBOutlier and kNN.elki.outlier.intrinsic Outlier detection algorithms based on intrinsic dimensionality.elki.outlier.lof LOF family of outlier detection algorithms.elki.projection Data projections (see also preprocessing filters for basic projections). -
-
Uses of DistanceQuery in elki.algorithm.statistics
Methods in elki.algorithm.statistics with parameters of type DistanceQuery Modifier and Type Method 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> distance)
Compute the exact maximum and minimum.private DoubleMinMax
DistanceStatisticsWithClasses. sampleMinMax(Relation<O> relation, DistanceQuery<O> distance)
Estimate minimum and maximum via sampling. -
Uses of DistanceQuery in elki.clustering.hierarchical
Fields in elki.clustering.hierarchical declared as DistanceQuery Modifier and Type Field Description private DistanceQuery<?>
AbstractHDBSCAN.HDBSCANAdapter. distq
Distance query for exact distances.protected DistanceQuery<?>
HACAM.Instance. dq
Distance queryprotected DistanceQuery<?>
MedoidLinkage.Instance. dq
Distance queryprotected DistanceQuery<?>
MiniMax.Instance. dq
Distance query functionMethods in elki.clustering.hierarchical with parameters of type DistanceQuery Modifier and Type Method Description private static double
HACAM.Instance. distanceSum(DistanceQuery<?> dq, DBIDIter i, DBIDs cy, double distsum, double minDistSum)
Find the maximum distance of one object to a set.private static double
MiniMax.Instance. findMax(DistanceQuery<?> dq, DBIDIter i, DBIDs cy, double maxDist, double minMaxDist)
Find the maximum distance of one object to a set.private static double
MedoidLinkage.Instance. findMedoid(DistanceQuery<?> dq, DBIDs c, DBIDArrayMIter prototype)
Find the prototypes.private static double
HACAM.Instance. findPrototype(DistanceQuery<?> dq, DBIDs cx, DBIDs cy, DBIDVar prototype, double minDistSum)
Find the prototypes.private static double
MiniMax.Instance. findPrototype(DistanceQuery<?> dq, DBIDs cx, DBIDs cy, DBIDVar prototype, double minMaxDist)
Find the prototypes.private static double
HACAM.Instance. findPrototypeSingleton(DistanceQuery<?> dq, DBIDs cx, DBIDRef cy, DBIDVar prototype)
Find the prototypes.private static double
MiniMax.Instance. findPrototypeSingleton(DistanceQuery<?> dq, DBIDs cx, DBIDRef cy, DBIDVar prototype)
Find the prototypes.protected static ClusterDistanceMatrix
AGNES. initializeDistanceMatrix(ArrayDBIDs ids, DistanceQuery<?> dq, Linkage linkage)
Initialize a distance matrix.protected static <O> ClusterDistanceMatrix
MiniMax. initializeMatrices(ArrayDBIDs ids, ArrayModifiableDBIDs prots, DistanceQuery<O> dq)
Initializes the inter-cluster distance matrix of possible mergesClusterPrototypeMergeHistory
HACAM.Instance. run(ArrayDBIDs ids, ClusterDistanceMatrix mat, ClusterMergeHistoryBuilder builder, DistanceQuery<?> dq, DBIDArrayMIter prots)
Run HACAM linkageClusterPrototypeMergeHistory
MedoidLinkage.Instance. run(ArrayDBIDs ids, ClusterDistanceMatrix mat, ClusterMergeHistoryBuilder builder, DistanceQuery<?> dq)
Run medoid linkageClusterPrototypeMergeHistory
MiniMax.Instance. run(ArrayDBIDs ids, ClusterDistanceMatrix mat, ClusterMergeHistoryBuilder builder, DistanceQuery<?> dq, DBIDArrayMIter prots)
ClusterPrototypeMergeHistory
MiniMaxAnderberg.Instance. run(ArrayDBIDs ids, ClusterDistanceMatrix mat, ClusterMergeHistoryBuilder builder, DistanceQuery<?> dq, DBIDArrayMIter prots)
ClusterPrototypeMergeHistory
MiniMaxNNChain.Instance. run(ArrayDBIDs ids, ClusterDistanceMatrix mat, ClusterMergeHistoryBuilder builder, DistanceQuery<?> dq, DBIDArrayMIter prots)
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.Constructors in elki.clustering.hierarchical with parameters of type DistanceQuery Constructor Description HDBSCANAdapter(ArrayDBIDs ids, DoubleDataStore coredists, DistanceQuery<?> distq)
Constructor. -
Uses of DistanceQuery in elki.clustering.kmeans.initialization
Fields in elki.clustering.kmeans.initialization declared as DistanceQuery Modifier and Type Field Description (package private) DistanceQuery<?>
KMeansPlusPlus.MedoidsInstance. distQ
Distance queryMethods in elki.clustering.kmeans.initialization with parameters of type DistanceQuery Modifier and Type Method Description DBIDs
FarthestPoints. chooseInitialMedoids(int k, DBIDs ids, DistanceQuery<? super O> distQ)
DBIDs
FarthestSumPoints. chooseInitialMedoids(int k, DBIDs ids, DistanceQuery<? super O> distQ)
DBIDs
FirstK. chooseInitialMedoids(int k, DBIDs ids, DistanceQuery<? super O> distance)
DBIDs
KMeansPlusPlus. chooseInitialMedoids(int k, DBIDs ids, DistanceQuery<? super O> distQ)
DBIDs
RandomlyChosen. chooseInitialMedoids(int k, DBIDs ids, DistanceQuery<? super O> distance)
Constructors in elki.clustering.kmeans.initialization with parameters of type DistanceQuery Constructor Description MedoidsInstance(DBIDs ids, DistanceQuery<?> distQ, RandomFactory rnd)
-
Uses of DistanceQuery in elki.clustering.kmedoids
Classes in elki.clustering.kmedoids that implement DistanceQuery Modifier and Type Class Description protected static class
CLARA.CachedDistanceQuery<V>
Cached distance query.Fields in elki.clustering.kmedoids declared as DistanceQuery Modifier and Type Field Description (package private) DistanceQuery<?>
CLARANS.Assignment. distQ
Distance function to use.(package private) DistanceQuery<?>
PAM.Instance. distQ
Distance function to use.(package private) DistanceQuery<?>
SingleAssignmentKMedoids.Instance. distQ
Distance function to use.(package private) DistanceQuery<V>
CLARA.CachedDistanceQuery. inner
Inner distance queryMethods in elki.clustering.kmedoids with parameters of type DistanceQuery Modifier and Type Method Description protected static double
CLARA. assignRemainingToNearestCluster(ArrayDBIDs means, DBIDs ids, DBIDs rids, WritableIntegerDataStore assignment, DistanceQuery<?> distQ)
Returns a list of clusters.protected ArrayModifiableDBIDs
PAM. initialMedoids(DistanceQuery<? super O> distQ, DBIDs ids, int k)
Choose the initial medoids.Clustering<MedoidModel>
AlternatingKMedoids. run(Relation<O> relation, int k, DistanceQuery<? super O> distQ)
Clustering<MedoidModel>
CLARA. run(Relation<V> relation, int k, DistanceQuery<? super V> distQ)
Clustering<MedoidModel>
CLARANS. run(Relation<O> relation, int k, DistanceQuery<? super O> distQ)
Clustering<MedoidModel>
EagerPAM. run(Relation<O> relation, int k, DistanceQuery<? super O> distQ)
Clustering<MedoidModel>
FastCLARA. run(Relation<V> relation, int k, DistanceQuery<? super V> distQ)
Clustering<MedoidModel>
FasterCLARA. run(Relation<O> relation, int k, DistanceQuery<? super O> distQ)
Clustering<MedoidModel>
FasterPAM. run(Relation<O> relation, int k, DistanceQuery<? super O> distQ)
Clustering<MedoidModel>
FastPAM. run(Relation<O> relation, int k, DistanceQuery<? super O> distQ)
Clustering<MedoidModel>
FastPAM1. run(Relation<O> relation, int k, DistanceQuery<? super O> distQ)
Clustering<MedoidModel>
KMedoidsClustering. run(Relation<O> relation, int k, DistanceQuery<? super O> distQ)
Run k-medoids clustering with a given distance query.
Not a very elegant API, but needed for some types of nested k-medoids.Clustering<MedoidModel>
PAM. run(Relation<O> relation, int k, DistanceQuery<? super O> distQ)
Clustering<MedoidModel>
ReynoldsPAM. run(Relation<O> relation, int k, DistanceQuery<? super O> distQ)
Clustering<MedoidModel>
SingleAssignmentKMedoids. run(Relation<O> relation, int k, DistanceQuery<? super O> distQ)
Constructors in elki.clustering.kmedoids with parameters of type DistanceQuery Constructor 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, double fasttol)
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)
Constructor. -
Uses of DistanceQuery in elki.clustering.kmedoids.initialization
Methods in elki.clustering.kmedoids.initialization with parameters of type DistanceQuery Modifier and Type Method Description static double
AlternateRefinement. assignToNearestCluster(DBIDArrayIter miter, DBIDs ids, DistanceQuery<?> distQ, WritableIntegerDataStore assignment, double[] cost)
Compute the initial cluster assignment.DBIDs
AlternateRefinement. chooseInitialMedoids(int k, DBIDs ids, DistanceQuery<? super O> distQ)
DBIDs
BUILD. chooseInitialMedoids(int k, DBIDs ids, DistanceQuery<? super O> distQ)
DBIDs
GreedyG. chooseInitialMedoids(int k, DBIDs ids, DistanceQuery<? super O> distQ)
DBIDs
KMedoidsInitialization. chooseInitialMedoids(int k, DBIDs ids, DistanceQuery<? super O> distance)
Choose initial meansDBIDs
KMedoidsKMedoidsInitialization. chooseInitialMedoids(int k, DBIDs ids, DistanceQuery<? super O> distance)
DBIDs
LAB. chooseInitialMedoids(int k, DBIDs ids, DistanceQuery<? super O> distQ)
DBIDs
ParkJun. chooseInitialMedoids(int k, DBIDs ids, DistanceQuery<? super O> distQ)
static boolean
AlternateRefinement. findMedoid(DBIDs ids, DistanceQuery<?> distQ, IntegerDataStore assignment, int j, DBIDArrayMIter miter, double[] cost)
Find the best medoid of a given fixed set.static double
GreedyG. findMedoid(DBIDs ids, DistanceQuery<?> distQ, int j, DBIDArrayMIter miter, double bestm, WritableDoubleDataStore temp, WritableDoubleDataStore tempbest, WritableDoubleDataStore mindist)
Find the best medoid of a given fixed set.protected static double
LAB. getMinDist(DBIDArrayIter j, DistanceQuery<?> distQ, DBIDArrayIter mi, WritableDoubleDataStore mindist)
Get the minimum distance to previous medoids. -
Uses of DistanceQuery in elki.clustering.optics
Methods in elki.clustering.optics with parameters of type DistanceQuery Modifier and Type Method 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 elki.clustering.silhouette
Fields in elki.clustering.silhouette declared as DistanceQuery Modifier and Type Field Description protected DistanceQuery<?>
FastMSC.Instance. distQ
Distance function to use.protected DistanceQuery<?>
FastMSC.Instance2. distQ
Distance function to use.(package private) DistanceQuery<?>
PAMSIL.Instance. distQ
Distance function to use.Methods in elki.clustering.silhouette with parameters of type DistanceQuery Modifier and Type Method Description Clustering<MedoidModel>
FasterMSC. run(Relation<O> relation, int k, DistanceQuery<? super O> distQ)
Clustering<MedoidModel>
FastMSC. run(Relation<O> relation, int k, DistanceQuery<? super O> distQ)
Clustering<MedoidModel>
PAMMEDSIL. run(Relation<O> relation, int k, DistanceQuery<? super O> distQ)
Clustering<MedoidModel>
PAMSIL. run(Relation<O> relation, int k, DistanceQuery<? super O> distQ)
Constructors in elki.clustering.silhouette with parameters of type DistanceQuery Constructor Description 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)
Constructor.Instance2(DistanceQuery<?> distQ, DBIDs ids, WritableIntegerDataStore assignment)
Constructor.Instance2(DistanceQuery<?> distQ, DBIDs ids, WritableIntegerDataStore assignment)
Constructor. -
Uses of DistanceQuery in elki.clustering.subspace
Methods in elki.clustering.subspace with parameters of type DistanceQuery Modifier and Type Method Description private long[][]
PROCLUS. findDimensions(ArrayDBIDs medoids, Relation<? extends NumberVector> relation, DistanceQuery<? extends NumberVector> distance, RangeSearcher<DBIDRef> rangeQuery)
Determines the set of correlated dimensions for each medoid in the specified medoid set.private DataStore<DBIDs>
PROCLUS. getLocalities(DBIDs medoids, DistanceQuery<? extends NumberVector> distance, RangeSearcher<DBIDRef> 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<? extends NumberVector> distance, DBIDs sampleSet, int m, java.util.Random random)
Returns a piercing set of k medoids from the specified sample set. -
Uses of DistanceQuery in elki.database.query
Subinterfaces of DistanceQuery in elki.database.query Modifier and Type Interface Description interface
DistanceSimilarityQuery<O>
Interface that is a combination of distance and a similarity function.Fields in elki.database.query declared as DistanceQuery Modifier and Type Field Description private DistanceQuery<O>
QueryBuilder. distQuery
Bound distance to queryMethods in elki.database.query that return DistanceQuery Modifier and Type Method Description DistanceQuery<O>
QueryBuilder. distanceQuery()
Build a distance query.<O> DistanceQuery<O>
EmpiricalQueryOptimizer. getDistanceQuery(Relation<? extends O> relation, Distance<? super O> distance, int flags)
default <O> DistanceQuery<O>
QueryOptimizer. getDistanceQuery(Relation<? extends O> relation, Distance<? super O> distanceFunction, int flags)
Optimize a distance query for this relation.Methods in elki.database.query with parameters of type DistanceQuery Modifier and Type Method Description <O> KNNSearcher<DBIDRef>
EmpiricalQueryOptimizer. kNNByDBID(Relation<? extends O> relation, DistanceQuery<O> distanceQuery, int maxk, int flags)
default <O> KNNSearcher<DBIDRef>
QueryOptimizer. kNNByDBID(Relation<? extends O> relation, DistanceQuery<O> distanceQuery, int maxk, int flags)
Optimize a kNN query for this relation.<O> KNNSearcher<O>
EmpiricalQueryOptimizer. kNNByObject(Relation<? extends O> relation, DistanceQuery<O> distanceQuery, int maxk, int flags)
default <O> KNNSearcher<O>
QueryOptimizer. kNNByObject(Relation<? extends O> relation, DistanceQuery<O> distanceQuery, int maxk, int flags)
Optimize a kNN query for this relation.private <O> KNNIndex<O>
EmpiricalQueryOptimizer. makeKnnPreprocessor(Relation<? extends O> relation, DistanceQuery<O> distanceQuery, int maxk, int flags)
Make a knn preprocessor.<O> PrioritySearcher<DBIDRef>
EmpiricalQueryOptimizer. priorityByDBID(Relation<? extends O> relation, DistanceQuery<O> distanceQuery, double maxrange, int flags)
default <O> PrioritySearcher<DBIDRef>
QueryOptimizer. priorityByDBID(Relation<? extends O> relation, DistanceQuery<O> distanceQuery, double maxrange, int flags)
Optimize a distance priority search for this relation.<O> PrioritySearcher<O>
EmpiricalQueryOptimizer. priorityByObject(Relation<? extends O> relation, DistanceQuery<O> distanceQuery, double maxrange, int flags)
default <O> PrioritySearcher<O>
QueryOptimizer. priorityByObject(Relation<? extends O> relation, DistanceQuery<O> distanceQuery, double maxrange, int flags)
Optimize a distance priority search for this relation.<O> RangeSearcher<DBIDRef>
EmpiricalQueryOptimizer. rangeByDBID(Relation<? extends O> relation, DistanceQuery<O> distanceQuery, double maxrange, int flags)
default <O> RangeSearcher<DBIDRef>
QueryOptimizer. rangeByDBID(Relation<? extends O> relation, DistanceQuery<O> distanceQuery, double maxrange, int flags)
Optimize a range query for this relation.<O> RangeSearcher<O>
EmpiricalQueryOptimizer. rangeByObject(Relation<? extends O> relation, DistanceQuery<O> distanceQuery, double maxrange, int flags)
default <O> RangeSearcher<O>
QueryOptimizer. rangeByObject(Relation<? extends O> relation, DistanceQuery<O> distanceQuery, double maxrange, int flags)
Optimize a range query for this relation.default <O> RKNNSearcher<DBIDRef>
QueryOptimizer. rkNNByDBID(Relation<? extends O> relation, DistanceQuery<O> distanceQuery, int maxk, int flags)
Optimize a reverse nearest neighbors query for this relation.default <O> RKNNSearcher<O>
QueryOptimizer. rkNNByObject(Relation<? extends O> relation, DistanceQuery<O> distanceQuery, int maxk, int flags)
Optimize a reverse nearest neighbors query for this relation.Constructors in elki.database.query with parameters of type DistanceQuery Constructor Description QueryBuilder(DistanceQuery<? super O> distQuery)
Constructor. -
Uses of DistanceQuery in elki.database.query.distance
Subinterfaces of DistanceQuery in elki.database.query.distance Modifier and Type Interface 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 elki.database.query.distance that implement DistanceQuery Modifier and Type Class Description class
DBIDDistanceQuery
Run a distance query based on DBIDsclass
DBIDRangeDistanceQuery
Run a distance query based on DBIDRangesclass
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 functionsclass
SpatialPrimitiveDistanceSimilarityQuery<O extends SpatialComparable>
Combination query class, to allow combined implementations of spatial distances and similarities.Fields in elki.database.query.distance declared as DistanceQuery Modifier and Type Field Description protected DistanceQuery<O>
LinearScanEuclideanPrioritySearcher. distanceQuery
Distance to use.protected DistanceQuery<O>
LinearScanPrioritySearcher. distanceQuery
Distance to use.Constructors in elki.database.query.distance with parameters of type DistanceQuery Constructor Description ByDBID(DistanceQuery<O> distanceQuery)
Constructor.ByDBID(DistanceQuery<O> distanceQuery)
Constructor.ByObject(DistanceQuery<O> distanceQuery)
Constructor.ByObject(DistanceQuery<O> distanceQuery)
Constructor.LinearScanEuclideanPrioritySearcher(DistanceQuery<O> distanceQuery)
Constructor.LinearScanPrioritySearcher(DistanceQuery<O> distanceQuery)
Constructor. -
Uses of DistanceQuery in elki.database.query.knn
Fields in elki.database.query.knn declared as DistanceQuery Modifier and Type Field Description private DistanceQuery<O>
LinearScanKNNByDBID. distanceQuery
Hold the distance function to be used.private DistanceQuery<O>
LinearScanKNNByObject. distanceQuery
Hold the distance function to be used.Constructors in elki.database.query.knn with parameters of type DistanceQuery Constructor Description LinearScanKNNByDBID(DistanceQuery<O> distanceQuery)
Constructor.LinearScanKNNByObject(DistanceQuery<O> distanceQuery)
Constructor. -
Uses of DistanceQuery in elki.database.query.range
Fields in elki.database.query.range declared as DistanceQuery Modifier and Type Field Description private DistanceQuery<O>
LinearScanDistanceRangeByDBID. distanceQuery
Distance to use.private DistanceQuery<O>
LinearScanDistanceRangeByObject. distanceQuery
Distance to use.Constructors in elki.database.query.range with parameters of type DistanceQuery Constructor Description LinearScanDistanceRangeByDBID(DistanceQuery<O> distanceQuery)
Constructor.LinearScanDistanceRangeByObject(DistanceQuery<O> distanceQuery)
Constructor.LinearScanEuclideanRangeByObject(DistanceQuery<O> distanceQuery)
Constructor. -
Uses of DistanceQuery in elki.database.query.rknn
Fields in elki.database.query.rknn declared as DistanceQuery Modifier and Type Field Description private DistanceQuery<O>
LinearScanRKNNByDBID. distanceQuery
Hold the distance function to be used.private DistanceQuery<O>
LinearScanRKNNByObject. distanceQuery
Hold the distance function to be used.Constructors in elki.database.query.rknn with parameters of type DistanceQuery Constructor Description LinearScanRKNNByDBID(DistanceQuery<O> distanceQuery, KNNSearcher<DBIDRef> knnQuery)
Constructor.LinearScanRKNNByObject(DistanceQuery<O> distanceQuery, KNNSearcher<DBIDRef> knnQuery)
Constructor. -
Uses of DistanceQuery in elki.distance
Subinterfaces of DistanceQuery in elki.distance Modifier and Type Interface Description static interface
IndexBasedDistance.Instance<T,I extends Index>
Instance interface for Index based distance functions.Classes in elki.distance that implement DistanceQuery Modifier and Type Class Description static class
AbstractDatabaseDistance.Instance<O>
The actual instance bound to a particular database.static class
AbstractIndexBasedDistance.Instance<O,I extends Index,F extends Distance<? super O>>
The actual instance bound to a particular database.static class
SharedNearestNeighborJaccardDistance.Instance<T>
Actual instance for a dataset.Methods in elki.distance that return DistanceQuery Modifier and Type Method Description <O extends DBID>
DistanceQuery<O>AbstractDBIDRangeDistance. instantiate(Relation<O> database)
<T extends O>
DistanceQuery<T>Distance. instantiate(Relation<T> relation)
Instantiate with a database to get the actual distance query.default <T extends O>
DistanceQuery<T>PrimitiveDistance. instantiate(Relation<T> relation)
<T extends DBID>
DistanceQuery<T>RandomStableDistance. instantiate(Relation<T> relation)
-
Uses of DistanceQuery in elki.distance.adapter
Classes in elki.distance.adapter that implement DistanceQuery Modifier and Type Class Description static class
AbstractSimilarityAdapter.Instance<O>
Inner proxy class for SNN distance function.static class
ArccosSimilarityAdapter.Instance<O>
Distance function instancestatic class
LinearSimilarityAdapter.Instance<O>
Distance function instancestatic class
LnSimilarityAdapter.Instance<O>
Distance function instanceMethods in elki.distance.adapter that return DistanceQuery Modifier and Type Method Description abstract <T extends O>
DistanceQuery<T>AbstractSimilarityAdapter. instantiate(Relation<T> database)
<T extends O>
DistanceQuery<T>ArccosSimilarityAdapter. instantiate(Relation<T> database)
<T extends O>
DistanceQuery<T>LinearSimilarityAdapter. instantiate(Relation<T> database)
<T extends O>
DistanceQuery<T>LnSimilarityAdapter. instantiate(Relation<T> database)
-
Uses of DistanceQuery in elki.distance.external
Methods in elki.distance.external that return DistanceQuery Modifier and Type Method Description <O extends DBID>
DistanceQuery<O>FileBasedSparseDoubleDistance. instantiate(Relation<O> relation)
<O extends DBID>
DistanceQuery<O>FileBasedSparseFloatDistance. instantiate(Relation<O> relation)
-
Uses of DistanceQuery in elki.evaluation.clustering.internal
Methods in elki.evaluation.clustering.internal with parameters of type DistanceQuery Modifier and Type Method Description double
CIndex. evaluateClustering(Relation<? extends O> rel, DistanceQuery<O> dq, Clustering<?> c)
Evaluate a single clustering.double
Silhouette. evaluateClustering(Relation<O> rel, DistanceQuery<O> dq, Clustering<?> c)
Evaluate a single clustering.protected double
CIndex. processCluster(Cluster<?> cluster, java.util.List<? extends Cluster<?>> clusters, int i, DistanceQuery<O> dq, DoubleHeap maxDists, DoubleHeap minDists, int w)
protected void
CIndex. processSingleton(Cluster<?> cluster, Relation<? extends O> rel, DistanceQuery<O> dq, DoubleHeap maxDists, DoubleHeap minDists, int w)
-
Uses of DistanceQuery in elki.index
Fields in elki.index declared as DistanceQuery Modifier and Type Field Description protected DistanceQuery<O>
AbstractRefiningIndex.AbstractRefiningQuery. distanceQuery
Distance query.Methods in elki.index that return DistanceQuery Modifier and Type Method Description DistanceQuery<O>
DistanceIndex. getDistanceQuery(Distance<? super O> distanceFunction)
Get a KNN query object for the given distance query and k.Methods in elki.index with parameters of type DistanceQuery Modifier and Type Method Description default KNNSearcher<DBIDRef>
KNNIndex. kNNByDBID(DistanceQuery<O> distanceQuery, int maxk, int flags)
Get a KNN query object for the given distance query and k.default KNNSearcher<O>
DistancePriorityIndex. kNNByObject(DistanceQuery<O> distanceQuery, int maxk, int flags)
KNNSearcher<O>
KNNIndex. kNNByObject(DistanceQuery<O> distanceQuery, int maxk, int flags)
Get a KNN query object for the given distance query and k.default PrioritySearcher<DBIDRef>
DistancePriorityIndex. priorityByDBID(DistanceQuery<O> distanceQuery, double maxrange, int flags)
Get a priority search object.PrioritySearcher<O>
DistancePriorityIndex. priorityByObject(DistanceQuery<O> distanceQuery, double maxrange, int flags)
Get a priority search object.default RangeSearcher<DBIDRef>
RangeIndex. rangeByDBID(DistanceQuery<O> distanceQuery, double maxrange, int flags)
Get a range query object for the given distance query and k.default RangeSearcher<O>
DistancePriorityIndex. rangeByObject(DistanceQuery<O> distanceQuery, double maxrange, int flags)
RangeSearcher<O>
RangeIndex. rangeByObject(DistanceQuery<O> distanceQuery, double maxrange, int flags)
Get a range query object for the given distance query and k.RKNNSearcher<DBIDRef>
RKNNIndex. rkNNByDBID(DistanceQuery<O> distanceQuery, int maxk, int flags)
Get a RKNN query object for the given distance query and k.RKNNSearcher<O>
RKNNIndex. rkNNByObject(DistanceQuery<O> distanceQuery, int maxk, int flags)
Get a RKNN query object for the given distance query and k.Constructors in elki.index with parameters of type DistanceQuery Constructor Description AbstractRefiningQuery(DistanceQuery<O> distanceQuery)
Constructor. -
Uses of DistanceQuery in elki.index.distancematrix
Classes in elki.index.distancematrix that implement DistanceQuery Modifier and Type Class Description class
PrecomputedDistanceMatrix.PrecomputedDistanceQuery
Distance query using the precomputed matrix.Methods in elki.index.distancematrix that return DistanceQuery Modifier and Type Method Description DistanceQuery<O>
PrecomputedDistanceMatrix. getDistanceQuery(Distance<? super O> distanceFunction)
Methods in elki.index.distancematrix with parameters of type DistanceQuery Modifier and Type Method Description KNNSearcher<DBIDRef>
PrecomputedDistanceMatrix. kNNByDBID(DistanceQuery<O> distanceQuery, int maxk, int flags)
KNNSearcher<O>
PrecomputedDistanceMatrix. kNNByObject(DistanceQuery<O> distanceQuery, int maxk, int flags)
PrioritySearcher<DBIDRef>
PrecomputedDistanceMatrix. priorityByDBID(DistanceQuery<O> distanceQuery, double maxrange, int flags)
PrioritySearcher<O>
PrecomputedDistanceMatrix. priorityByObject(DistanceQuery<O> distanceQuery, double maxrange, int flags)
RangeSearcher<DBIDRef>
PrecomputedDistanceMatrix. rangeByDBID(DistanceQuery<O> distanceQuery, double maxrange, int flags)
RangeSearcher<O>
PrecomputedDistanceMatrix. rangeByObject(DistanceQuery<O> distanceQuery, double maxrange, int flags)
-
Uses of DistanceQuery in elki.index.idistance
Fields in elki.index.idistance declared as DistanceQuery Modifier and Type Field Description private DistanceQuery<O>
InMemoryIDistanceIndex. distanceQuery
Distance query.Methods in elki.index.idistance with parameters of type DistanceQuery Modifier and Type Method Description KNNSearcher<O>
InMemoryIDistanceIndex. kNNByObject(DistanceQuery<O> distanceQuery, int maxk, int flags)
RangeSearcher<O>
InMemoryIDistanceIndex. rangeByObject(DistanceQuery<O> distanceQuery, double maxradius, int flags)
protected static <O> DoubleIntPair[]
InMemoryIDistanceIndex. rankReferencePoints(DistanceQuery<O> distanceQuery, O obj, ArrayDBIDs referencepoints)
Sort the reference points by distance to the query objectConstructors in elki.index.idistance with parameters of type DistanceQuery Constructor Description IDistanceKNNSearcher(DistanceQuery<O> distanceQuery)
Constructor.IDistanceRangeSearcher(DistanceQuery<O> distanceQuery)
Constructor.InMemoryIDistanceIndex(Relation<O> relation, DistanceQuery<O> distance, KMedoidsInitialization<O> initialization, int numref)
Constructor. -
Uses of DistanceQuery in elki.index.invertedlist
Methods in elki.index.invertedlist with parameters of type DistanceQuery Modifier and Type Method Description KNNSearcher<V>
InMemoryInvertedIndex. kNNByObject(DistanceQuery<V> distanceQuery, int maxk, int flags)
RangeSearcher<V>
InMemoryInvertedIndex. rangeByObject(DistanceQuery<V> distanceQuery, double maxradius, int flags)
-
Uses of DistanceQuery in elki.index.laesa
Fields in elki.index.laesa declared as DistanceQuery Modifier and Type Field Description (package private) DistanceQuery<? super O>
LAESA. distq
Distance query, bound to the relationMethods in elki.index.laesa with parameters of type DistanceQuery Modifier and Type Method Description KNNSearcher<DBIDRef>
LAESA. kNNByDBID(DistanceQuery<O> distanceQuery, int maxk, int flags)
KNNSearcher<O>
LAESA. kNNByObject(DistanceQuery<O> distanceQuery, int maxk, int flags)
RangeSearcher<DBIDRef>
LAESA. rangeByDBID(DistanceQuery<O> distanceQuery, double maxrange, int flags)
RangeSearcher<O>
LAESA. rangeByObject(DistanceQuery<O> distanceQuery, double maxrange, int flags)
-
Uses of DistanceQuery in elki.index.lsh
Methods in elki.index.lsh with parameters of type DistanceQuery Modifier and Type Method Description KNNSearcher<V>
InMemoryLSHIndex.Instance. kNNByObject(DistanceQuery<V> distanceQuery, int maxk, int flags)
RangeSearcher<V>
InMemoryLSHIndex.Instance. rangeByObject(DistanceQuery<V> distanceQuery, double maxradius, int flags)
Constructors in elki.index.lsh with parameters of type DistanceQuery Constructor Description LSHKNNQuery(DistanceQuery<V> distanceQuery)
Constructor.LSHRangeQuery(DistanceQuery<V> distanceQuery)
Constructor. -
Uses of DistanceQuery in elki.index.preprocessed.knn
Fields in elki.index.preprocessed.knn declared as DistanceQuery Modifier and Type Field 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 refinementMethods in elki.index.preprocessed.knn that return DistanceQuery Modifier and Type Method Description DistanceQuery<O>
AbstractMaterializeKNNPreprocessor. getDistanceQuery()
The distance query we used.Methods in elki.index.preprocessed.knn with parameters of type DistanceQuery Modifier and Type Method Description PreprocessorKNNQuery
AbstractMaterializeKNNPreprocessor. kNNByDBID(DistanceQuery<O> distQ, int maxk, int flags)
KNNSearcher<DBIDRef>
NaiveProjectedKNNPreprocessor. kNNByDBID(DistanceQuery<O> distanceQuery, int maxk, int flags)
KNNSearcher<DBIDRef>
SpacefillingKNNPreprocessor. kNNByDBID(DistanceQuery<O> distanceQuery, int maxk, int flags)
KNNSearcher<O>
AbstractMaterializeKNNPreprocessor. kNNByObject(DistanceQuery<O> distanceQuery, int maxk, int flags)
Deprecated.not possibleKNNSearcher<O>
NaiveProjectedKNNPreprocessor. kNNByObject(DistanceQuery<O> distanceQuery, int maxk, int flags)
KNNSearcher<O>
NNDescent. kNNByObject(DistanceQuery<O> distanceQuery, int maxk, int flags)
KNNSearcher<O>
SpacefillingKNNPreprocessor. kNNByObject(DistanceQuery<O> distanceQuery, int maxk, int flags)
KNNSearcher<O>
SpacefillingMaterializeKNNPreprocessor. kNNByObject(DistanceQuery<O> distQ, int maxk, int flags)
RKNNSearcher<DBIDRef>
MaterializeKNNAndRKNNPreprocessor. rkNNByDBID(DistanceQuery<O> distanceQuery, int maxk, int flags)
RKNNSearcher<O>
MaterializeKNNAndRKNNPreprocessor. rkNNByObject(DistanceQuery<O> distanceQuery, int maxk, int flags)
Constructors in elki.index.preprocessed.knn with parameters of type DistanceQuery Constructor Description AbstractMaterializeKNNPreprocessor(Relation<O> relation, DistanceQuery<O> distanceQuery, int k)
Constructor.MaterializeKNNPreprocessor(Relation<O> relation, DistanceQuery<O> distanceQuery, int k, boolean noopt)
Constructor with preprocessing step.NaiveProjectedKNNQuery(DistanceQuery<O> distanceQuery)
Constructor.SpaceFillingKNNQuery(DistanceQuery<O> distanceQuery)
Constructor. -
Uses of DistanceQuery in elki.index.projected
Fields in elki.index.projected declared as DistanceQuery Modifier and Type Field Description protected DistanceQuery<O>
ProjectedIndex.ProjectedRangeByDBID. distanceQuery
Hold the distance function to be used.protected DistanceQuery<O>
ProjectedIndex.ProjectedRangeByObject. distanceQuery
Hold the distance function to be used.(package private) DistanceQuery<O>
ProjectedIndex.ProjectedKNNByDBID. distq
Distance query for refinement.(package private) DistanceQuery<O>
ProjectedIndex.ProjectedKNNByObject. distq
Distance query for refinement.(package private) DistanceQuery<O>
ProjectedIndex.ProjectedRKNNByDBID. distq
Distance query for refinement.(package private) DistanceQuery<O>
ProjectedIndex.ProjectedRKNNByObject. distq
Distance query for refinement.Methods in elki.index.projected with parameters of type DistanceQuery Modifier and Type Method Description KNNSearcher<DBIDRef>
ProjectedIndex. kNNByDBID(DistanceQuery<O> distanceQuery, int maxk, int flags)
KNNSearcher<O>
LatLngAsECEFIndex. kNNByObject(DistanceQuery<O> distanceQuery, int maxk, int flags)
KNNSearcher<O>
LngLatAsECEFIndex. kNNByObject(DistanceQuery<O> distanceQuery, int maxk, int flags)
KNNSearcher<O>
ProjectedIndex. kNNByObject(DistanceQuery<O> distanceQuery, int maxk, int flags)
RangeSearcher<DBIDRef>
ProjectedIndex. rangeByDBID(DistanceQuery<O> distanceQuery, double maxradius, int flags)
RangeSearcher<O>
LatLngAsECEFIndex. rangeByObject(DistanceQuery<O> distanceQuery, double maxradius, int flags)
RangeSearcher<O>
LngLatAsECEFIndex. rangeByObject(DistanceQuery<O> distanceQuery, double maxradius, int flags)
RangeSearcher<O>
ProjectedIndex. rangeByObject(DistanceQuery<O> distanceQuery, double maxradius, int flags)
RKNNSearcher<DBIDRef>
ProjectedIndex. rkNNByDBID(DistanceQuery<O> distanceQuery, int maxk, int flags)
RKNNSearcher<O>
LatLngAsECEFIndex. rkNNByObject(DistanceQuery<O> distanceQuery, int maxk, int flags)
RKNNSearcher<O>
LngLatAsECEFIndex. rkNNByObject(DistanceQuery<O> distanceQuery, int maxk, int flags)
RKNNSearcher<O>
ProjectedIndex. rkNNByObject(DistanceQuery<O> distanceQuery, int maxk, int flags)
Constructors in elki.index.projected with parameters of type DistanceQuery Constructor Description ProjectedKNNByDBID(DistanceQuery<O> distanceQuery, KNNSearcher<I> inner)
Constructor.ProjectedKNNByObject(DistanceQuery<O> distanceQuery, KNNSearcher<I> inner)
Constructor.ProjectedRangeByDBID(DistanceQuery<O> distanceQuery, RangeSearcher<I> inner)
Constructor.ProjectedRangeByObject(DistanceQuery<O> distanceQuery, RangeSearcher<I> inner)
Constructor.ProjectedRKNNByDBID(DistanceQuery<O> distanceQuery, RKNNSearcher<I> inner)
Constructor.ProjectedRKNNByObject(DistanceQuery<O> distanceQuery, RKNNSearcher<I> inner)
Constructor. -
Uses of DistanceQuery in elki.index.tree.metrical.covertree
Fields in elki.index.tree.metrical.covertree declared as DistanceQuery Modifier and Type Field Description private DistanceQuery<O>
AbstractCoverTree. distanceQuery
Distance query, on the data relation.Methods in elki.index.tree.metrical.covertree with parameters of type DistanceQuery Modifier and Type Method Description KNNSearcher<DBIDRef>
CoverTree. kNNByDBID(DistanceQuery<O> distanceQuery, int maxk, int flags)
KNNSearcher<DBIDRef>
SimplifiedCoverTree. kNNByDBID(DistanceQuery<O> distanceQuery, int maxk, int flags)
KNNSearcher<O>
CoverTree. kNNByObject(DistanceQuery<O> distanceQuery, int maxk, int flags)
KNNSearcher<O>
SimplifiedCoverTree. kNNByObject(DistanceQuery<O> distanceQuery, int maxk, int flags)
PrioritySearcher<DBIDRef>
CoverTree. priorityByDBID(DistanceQuery<O> distanceQuery, double maxradius, int flags)
PrioritySearcher<DBIDRef>
SimplifiedCoverTree. priorityByDBID(DistanceQuery<O> distanceQuery, double maxradius, int flags)
PrioritySearcher<O>
CoverTree. priorityByObject(DistanceQuery<O> distanceQuery, double maxradius, int flags)
PrioritySearcher<O>
SimplifiedCoverTree. priorityByObject(DistanceQuery<O> distanceQuery, double maxradius, int flags)
RangeSearcher<DBIDRef>
CoverTree. rangeByDBID(DistanceQuery<O> distanceQuery, double maxradius, int flags)
RangeSearcher<DBIDRef>
SimplifiedCoverTree. rangeByDBID(DistanceQuery<O> distanceQuery, double maxradius, int flags)
RangeSearcher<O>
CoverTree. rangeByObject(DistanceQuery<O> distanceQuery, double maxradius, int flags)
RangeSearcher<O>
SimplifiedCoverTree. rangeByObject(DistanceQuery<O> distanceQuery, double maxradius, int flags)
-
Uses of DistanceQuery in elki.index.tree.metrical.mtreevariants.mktrees
Fields in elki.index.tree.metrical.mtreevariants.mktrees declared as DistanceQuery Modifier and Type Field Description private DistanceQuery<O>
AbstractMkTree. distanceQuery
Distance query to use. -
Uses of DistanceQuery in elki.index.tree.metrical.mtreevariants.mktrees.mkapp
Methods in elki.index.tree.metrical.mtreevariants.mktrees.mkapp with parameters of type DistanceQuery Modifier and Type Method Description KNNSearcher<DBIDRef>
MkAppTreeIndex. kNNByDBID(DistanceQuery<O> distanceQuery, int maxk, int flags)
KNNSearcher<O>
MkAppTreeIndex. kNNByObject(DistanceQuery<O> distanceQuery, int maxk, int flags)
RangeSearcher<DBIDRef>
MkAppTreeIndex. rangeByDBID(DistanceQuery<O> distanceQuery, double maxradius, int flags)
RangeSearcher<O>
MkAppTreeIndex. rangeByObject(DistanceQuery<O> distanceQuery, double maxradius, int flags)
RKNNSearcher<DBIDRef>
MkAppTreeIndex. rkNNByDBID(DistanceQuery<O> distanceQuery, int maxk, int flags)
RKNNSearcher<O>
MkAppTreeIndex. rkNNByObject(DistanceQuery<O> distanceQuery, int maxk, int flags)
-
Uses of DistanceQuery in elki.index.tree.metrical.mtreevariants.mktrees.mkcop
Methods in elki.index.tree.metrical.mtreevariants.mktrees.mkcop with parameters of type DistanceQuery Modifier and Type Method Description KNNSearcher<DBIDRef>
MkCoPTreeIndex. kNNByDBID(DistanceQuery<O> distanceQuery, int maxk, int flags)
KNNSearcher<O>
MkCoPTreeIndex. kNNByObject(DistanceQuery<O> distanceQuery, int maxk, int flags)
RangeSearcher<DBIDRef>
MkCoPTreeIndex. rangeByDBID(DistanceQuery<O> distanceQuery, double maxradius, int flags)
RangeSearcher<O>
MkCoPTreeIndex. rangeByObject(DistanceQuery<O> distanceQuery, double maxrange, int flags)
RKNNSearcher<DBIDRef>
MkCoPTreeIndex. rkNNByDBID(DistanceQuery<O> distanceQuery, int maxk, int flags)
RKNNSearcher<O>
MkCoPTreeIndex. rkNNByObject(DistanceQuery<O> distanceQuery, int maxk, int flags)
-
Uses of DistanceQuery in elki.index.tree.metrical.mtreevariants.mktrees.mkmax
Methods in elki.index.tree.metrical.mtreevariants.mktrees.mkmax with parameters of type DistanceQuery Modifier and Type Method Description KNNSearcher<DBIDRef>
MkMaxTreeIndex. kNNByDBID(DistanceQuery<O> distanceQuery, int maxk, int flags)
KNNSearcher<O>
MkMaxTreeIndex. kNNByObject(DistanceQuery<O> distanceQuery, int maxk, int flags)
RangeSearcher<DBIDRef>
MkMaxTreeIndex. rangeByDBID(DistanceQuery<O> distanceQuery, double maxradius, int flags)
RangeSearcher<O>
MkMaxTreeIndex. rangeByObject(DistanceQuery<O> distanceQuery, double maxrange, int flags)
RKNNSearcher<DBIDRef>
MkMaxTreeIndex. rkNNByDBID(DistanceQuery<O> distanceQuery, int maxk, int flags)
RKNNSearcher<O>
MkMaxTreeIndex. rkNNByObject(DistanceQuery<O> distanceQuery, int maxk, int flags)
-
Uses of DistanceQuery in elki.index.tree.metrical.mtreevariants.mktrees.mktab
Methods in elki.index.tree.metrical.mtreevariants.mktrees.mktab with parameters of type DistanceQuery Modifier and Type Method Description KNNSearcher<DBIDRef>
MkTabTreeIndex. kNNByDBID(DistanceQuery<O> distanceQuery, int maxk, int flags)
KNNSearcher<O>
MkTabTreeIndex. kNNByObject(DistanceQuery<O> distanceQuery, int maxk, int flags)
RangeSearcher<DBIDRef>
MkTabTreeIndex. rangeByDBID(DistanceQuery<O> distanceQuery, double maxradius, int flags)
RangeSearcher<O>
MkTabTreeIndex. rangeByObject(DistanceQuery<O> distanceQuery, double maxrange, int flags)
RKNNSearcher<DBIDRef>
MkTabTreeIndex. rkNNByDBID(DistanceQuery<O> distanceQuery, int maxk, int flags)
RKNNSearcher<O>
MkTabTreeIndex. rkNNByObject(DistanceQuery<O> distanceQuery, int maxk, int flags)
-
Uses of DistanceQuery in elki.index.tree.metrical.mtreevariants.mtree
Fields in elki.index.tree.metrical.mtreevariants.mtree declared as DistanceQuery Modifier and Type Field Description protected DistanceQuery<O>
MTreeIndex. distanceQuery
The distance query.Methods in elki.index.tree.metrical.mtreevariants.mtree with parameters of type DistanceQuery Modifier and Type Method Description KNNSearcher<DBIDRef>
MTreeIndex. kNNByDBID(DistanceQuery<O> distanceQuery, int maxk, int flags)
KNNSearcher<O>
MTreeIndex. kNNByObject(DistanceQuery<O> distanceQuery, int maxk, int flags)
RangeSearcher<DBIDRef>
MTreeIndex. rangeByDBID(DistanceQuery<O> distanceQuery, double maxradius, int flags)
RangeSearcher<O>
MTreeIndex. rangeByObject(DistanceQuery<O> distanceQuery, double maxrange, int flags)
-
Uses of DistanceQuery in elki.index.tree.metrical.mtreevariants.query
Fields in elki.index.tree.metrical.mtreevariants.query declared as DistanceQuery Modifier and Type Field Description protected DistanceQuery<O>
MkTreeRKNNQuery. distanceQuery
Distance queryprotected DistanceQuery<O>
MTreeKNNByDBID. distanceQuery
Hold the distance function to be used.protected DistanceQuery<O>
MTreeKNNByObject. distanceQuery
Hold the distance function to be used.protected DistanceQuery<O>
MTreeRangeByDBID. distanceQuery
Hold the distance function to be used.protected DistanceQuery<O>
MTreeRangeByObject. distanceQuery
Hold the distance function to be used.Constructors in elki.index.tree.metrical.mtreevariants.query with parameters of type DistanceQuery Constructor Description MkTreeRKNNQuery(AbstractMkTree<O,?,?,?> index, DistanceQuery<O> distanceQuery)
Constructor.MTreeKNNByDBID(AbstractMTree<O,?,?,?> index, DistanceQuery<O> distanceQuery)
Constructor.MTreeKNNByObject(AbstractMTree<O,?,?,?> index, DistanceQuery<O> distanceQuery)
Constructor.MTreeRangeByDBID(AbstractMTree<O,?,?,?> index, DistanceQuery<O> distanceQuery)
Constructor.MTreeRangeByObject(AbstractMTree<O,?,?,?> index, DistanceQuery<O> distanceQuery)
Constructor. -
Uses of DistanceQuery in elki.index.tree.metrical.vptree
Fields in elki.index.tree.metrical.vptree declared as DistanceQuery Modifier and Type Field Description (package private) DistanceQuery<O>
GNAT. distQuery
Actual distance query on the Dataprivate DistanceQuery<O>
VPTree. distQuery
Actual distance query on the DataMethods in elki.index.tree.metrical.vptree with parameters of type DistanceQuery Modifier and Type Method Description KNNSearcher<DBIDRef>
GNAT. kNNByDBID(DistanceQuery<O> distanceQuery, int maxk, int flags)
KNNSearcher<DBIDRef>
VPTree. kNNByDBID(DistanceQuery<O> distanceQuery, int maxk, int flags)
KNNSearcher<O>
GNAT. kNNByObject(DistanceQuery<O> distanceQuery, int maxk, int flags)
KNNSearcher<O>
VPTree. kNNByObject(DistanceQuery<O> distanceQuery, int maxk, int flags)
PrioritySearcher<DBIDRef>
GNAT. priorityByDBID(DistanceQuery<O> distanceQuery, double maxrange, int flags)
PrioritySearcher<DBIDRef>
VPTree. priorityByDBID(DistanceQuery<O> distanceQuery, double maxrange, int flags)
PrioritySearcher<O>
GNAT. priorityByObject(DistanceQuery<O> distanceQuery, double maxrange, int flags)
PrioritySearcher<O>
VPTree. priorityByObject(DistanceQuery<O> distanceQuery, double maxrange, int flags)
RangeSearcher<DBIDRef>
GNAT. rangeByDBID(DistanceQuery<O> distanceQuery, double maxrange, int flags)
RangeSearcher<DBIDRef>
VPTree. rangeByDBID(DistanceQuery<O> distanceQuery, double maxrange, int flags)
RangeSearcher<O>
GNAT. rangeByObject(DistanceQuery<O> distanceQuery, double maxrange, int flags)
RangeSearcher<O>
VPTree. rangeByObject(DistanceQuery<O> distanceQuery, double maxrange, int flags)
-
Uses of DistanceQuery in elki.index.tree.spatial.kd
Methods in elki.index.tree.spatial.kd with parameters of type DistanceQuery Modifier and Type Method Description KNNSearcher<O>
MemoryKDTree. kNNByObject(DistanceQuery<O> distanceQuery, int maxk, int flags)
KNNSearcher<O>
MinimalisticMemoryKDTree. kNNByObject(DistanceQuery<O> distanceQuery, int maxk, int flags)
KNNSearcher<O>
SmallMemoryKDTree. kNNByObject(DistanceQuery<O> distanceQuery, int maxk, int flags)
PrioritySearcher<O>
MemoryKDTree. priorityByObject(DistanceQuery<O> distanceQuery, double maxrange, int flags)
PrioritySearcher<O>
MinimalisticMemoryKDTree. priorityByObject(DistanceQuery<O> distanceQuery, double maxrange, int flags)
PrioritySearcher<O>
SmallMemoryKDTree. priorityByObject(DistanceQuery<O> distanceQuery, double maxrange, int flags)
RangeSearcher<O>
MemoryKDTree. rangeByObject(DistanceQuery<O> distanceQuery, double maxrange, int flags)
RangeSearcher<O>
MinimalisticMemoryKDTree. rangeByObject(DistanceQuery<O> distanceQuery, double maxradius, int flags)
RangeSearcher<O>
SmallMemoryKDTree. rangeByObject(DistanceQuery<O> distanceQuery, double maxrange, int flags)
-
Uses of DistanceQuery in elki.index.tree.spatial.rstarvariants.deliclu
Methods in elki.index.tree.spatial.rstarvariants.deliclu with parameters of type DistanceQuery Modifier and Type Method Description KNNSearcher<O>
DeLiCluTreeIndex. kNNByObject(DistanceQuery<O> distanceQuery, int maxk, int flags)
PrioritySearcher<O>
DeLiCluTreeIndex. priorityByObject(DistanceQuery<O> distanceQuery, double maxradius, int flags)
RangeSearcher<O>
DeLiCluTreeIndex. rangeByObject(DistanceQuery<O> distanceQuery, double maxradius, int flags)
-
Uses of DistanceQuery in elki.index.tree.spatial.rstarvariants.flat
Methods in elki.index.tree.spatial.rstarvariants.flat with parameters of type DistanceQuery Modifier and Type Method Description KNNSearcher<O>
FlatRStarTreeIndex. kNNByObject(DistanceQuery<O> distanceQuery, int maxk, int flags)
PrioritySearcher<O>
FlatRStarTreeIndex. priorityByObject(DistanceQuery<O> distanceQuery, double maxradius, int flags)
RangeSearcher<O>
FlatRStarTreeIndex. rangeByObject(DistanceQuery<O> distanceQuery, double maxradius, int flags)
-
Uses of DistanceQuery in elki.index.tree.spatial.rstarvariants.rdknn
Methods in elki.index.tree.spatial.rstarvariants.rdknn with parameters of type DistanceQuery Modifier and Type Method Description KNNSearcher<O>
RdKNNTree. kNNByObject(DistanceQuery<O> distanceQuery, int maxk, int flags)
PrioritySearcher<O>
RdKNNTree. priorityByObject(DistanceQuery<O> distanceQuery, double maxradius, int flags)
RangeSearcher<O>
RdKNNTree. rangeByObject(DistanceQuery<O> distanceQuery, double maxradius, int flags)
RKNNSearcher<DBIDRef>
RdKNNTree. rkNNByDBID(DistanceQuery<O> distanceQuery, int maxk, int flags)
RKNNSearcher<O>
RdKNNTree. rkNNByObject(DistanceQuery<O> distanceQuery, int maxk, int flags)
-
Uses of DistanceQuery in elki.index.tree.spatial.rstarvariants.rstar
Methods in elki.index.tree.spatial.rstarvariants.rstar with parameters of type DistanceQuery Modifier and Type Method Description KNNSearcher<O>
RStarTreeIndex. kNNByObject(DistanceQuery<O> distanceQuery, int maxk, int flags)
PrioritySearcher<O>
RStarTreeIndex. priorityByObject(DistanceQuery<O> distanceQuery, double maxradius, int flags)
RangeSearcher<O>
RStarTreeIndex. rangeByObject(DistanceQuery<O> distanceQuery, double maxradius, int flags)
-
Uses of DistanceQuery in elki.index.vafile
Methods in elki.index.vafile with parameters of type DistanceQuery Modifier and Type Method Description KNNSearcher<V>
PartialVAFile. kNNByObject(DistanceQuery<V> distanceQuery, int maxk, int flags)
KNNSearcher<V>
VAFile. kNNByObject(DistanceQuery<V> distanceQuery, int maxk, int flags)
RangeSearcher<V>
PartialVAFile. rangeByObject(DistanceQuery<V> distanceQuery, double maxradius, int flags)
RangeSearcher<V>
VAFile. rangeByObject(DistanceQuery<V> distanceQuery, double maxradius, int flags)
Constructors in elki.index.vafile with parameters of type DistanceQuery Constructor 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. -
Uses of DistanceQuery in elki.math.statistics.intrinsicdimensionality
Methods in elki.math.statistics.intrinsicdimensionality with parameters of type DistanceQuery Modifier and Type Method Description protected double
RABIDEstimator. computeABID(DistanceQuery<?> distq, KNNList knn, boolean bias)
Estimate intrinsic dimensionality (both variants).double
ABIDEstimator. estimate(KNNSearcher<DBIDRef> knnq, DistanceQuery<?> distq, DBIDRef cur, int k)
double
ALIDEstimator. estimate(KNNSearcher<DBIDRef> knnq, DistanceQuery<?> distq, DBIDRef cur, int k)
double
ALIDEstimator. estimate(RangeSearcher<DBIDRef> rnq, DistanceQuery<?> distq, DBIDRef cur, double range)
default double
DistanceBasedIntrinsicDimensionalityEstimator. estimate(KNNSearcher<DBIDRef> knnq, DistanceQuery<? extends java.lang.Object> distq, DBIDRef cur, int k)
default double
DistanceBasedIntrinsicDimensionalityEstimator. estimate(RangeSearcher<DBIDRef> rnq, DistanceQuery<? extends java.lang.Object> distq, DBIDRef cur, double range)
double
IntrinsicDimensionalityEstimator. estimate(KNNSearcher<DBIDRef> knnq, DistanceQuery<? extends O> distq, DBIDRef cur, int k)
Estimate from a Reference Point, a KNNSearcher and the neighborhood size k.double
IntrinsicDimensionalityEstimator. estimate(RangeSearcher<DBIDRef> rnq, DistanceQuery<? extends O> distq, DBIDRef cur, double range)
Estimate from a distance list.double
LPCAEstimator. estimate(KNNSearcher<DBIDRef> knnq, DistanceQuery<? extends NumberVector> distq, DBIDRef cur, int k)
double
LPCAEstimator. estimate(RangeSearcher<DBIDRef> rnq, DistanceQuery<? extends NumberVector> distq, DBIDRef cur, double range)
double
RABIDEstimator. estimate(KNNSearcher<DBIDRef> knnq, DistanceQuery<?> distq, DBIDRef cur, int k)
double
TightLIDEstimator. estimate(KNNSearcher<DBIDRef> knnq, DistanceQuery<? extends java.lang.Object> distq, DBIDRef cur, int k)
double
TightLIDEstimator. estimate(RangeSearcher<DBIDRef> rnq, DistanceQuery<? extends java.lang.Object> distq, DBIDRef cur, double range)
-
Uses of DistanceQuery in elki.outlier
Methods in elki.outlier with parameters of type DistanceQuery Modifier and Type Method Description private void
DWOF. initializeRadii(DBIDs ids, KNNSearcher<DBIDRef> 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 elki.outlier.distance
Fields in elki.outlier.distance declared as DistanceQuery Modifier and Type Field Description private DistanceQuery<O>
HilOut. distq
Distance query -
Uses of DistanceQuery in elki.outlier.intrinsic
Methods in elki.outlier.intrinsic with parameters of type DistanceQuery Modifier and Type Method Description protected DoubleDataStore
IDOS. computeIDs(DBIDs ids, KNNSearcher<DBIDRef> knnQ, DistanceQuery<O> distQ)
Computes all IDs -
Uses of DistanceQuery in elki.outlier.lof
Methods in elki.outlier.lof with parameters of type DistanceQuery Modifier and Type Method Description protected void
COF. computeAverageChainingDistances(KNNSearcher<DBIDRef> 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 elki.projection
Methods in elki.projection with parameters of type DistanceQuery Modifier and Type Method Description protected double[][]
GaussianAffinityMatrixBuilder. buildDistanceMatrix(ArrayDBIDs ids, DistanceQuery<?> dq)
Build a distance matrix of squared distances.
-