Uses of Interface
de.lmu.ifi.dbs.elki.database.ids.ArrayDBIDs

Packages that use ArrayDBIDs

Package	Description
de.lmu.ifi.dbs.elki.algorithm.clustering.affinitypropagation	Affinity Propagation (AP) clustering.
de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering	Biclustering algorithms.
de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical	Hierarchical agglomerative clustering (HAC).
de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction	Extraction of partitional clusterings from hierarchical results.
de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans	K-means clustering and variations.
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.meta	Meta outlier detection algorithms: external scores, score rescaling.
de.lmu.ifi.dbs.elki.database.ids	Database object identification and ID group handling API.
de.lmu.ifi.dbs.elki.database.ids.generic	Database object identification and ID group handling - generic implementations.
de.lmu.ifi.dbs.elki.database.ids.integer	Integer-based DBID implementation -- do not use directly - always use DBIDUtil.
de.lmu.ifi.dbs.elki.database.query.knn	Prepared queries for k nearest neighbor (kNN) queries.
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.datasource.bundle	Object bundles - exchange container for multi-represented objects.
de.lmu.ifi.dbs.elki.evaluation.similaritymatrix	Render a distance matrix to visualize a clustering-distance-combination.
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.preprocessed.fastoptics	Preprocessed index used by the FastOPTICS algorithm.
de.lmu.ifi.dbs.elki.index.preprocessed.knn	Indexes providing KNN and rKNN data.
de.lmu.ifi.dbs.elki.index.preprocessed.snn	Indexes providing nearest neighbor sets
de.lmu.ifi.dbs.elki.index.projected	Projected indexes for data.
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.rstarvariants.query	Queries on the R-Tree family of indexes: kNN and range queries.
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn	RdKNNTree
de.lmu.ifi.dbs.elki.math.dimensionsimilarity	Functions to compute the similarity of dimensions (or the interestingness of the combination).
de.lmu.ifi.dbs.elki.parallel	Parallel processing core for ELKI.
de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike	Common API for accessing objects that are "array-like", including lists, numerical vectors, database vectors and arrays.
de.lmu.ifi.dbs.elki.utilities.scaling.outlier	Scaling of Outlier scores, that require a statistical analysis of the occurring values

Uses of ArrayDBIDs in de.lmu.ifi.dbs.elki.algorithm.clustering.affinitypropagation

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

Modifier and Type	Method and Description
double[][]	DistanceBasedInitializationWithMedian.getSimilarityMatrix(Database db, Relation<O> relation, ArrayDBIDs ids)
double[][]	AffinityPropagationInitialization.getSimilarityMatrix(Database db, Relation<O> relation, ArrayDBIDs ids) Compute the initial similarity matrix.
double[][]	SimilarityBasedInitializationWithMedian.getSimilarityMatrix(Database db, Relation<O> relation, ArrayDBIDs ids)

Uses of ArrayDBIDs in de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering

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

Modifier and Type	Field and Description
protected ArrayDBIDs	AbstractBiclustering.rowIDs The row ids corresponding to the currently set AbstractBiclustering.relation.

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

Modifier and Type	Method and Description
protected ArrayDBIDs	AbstractBiclustering.rowsBitsetToIDs(BitSet rows) Convert a bitset into integer row ids.
protected ArrayDBIDs	AbstractBiclustering.rowsBitsetToIDs(long[] rows) Convert a bitset into integer row ids.

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

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

Modifier and Type	Field and Description
private ArrayDBIDs	AbstractHDBSCAN.HDBSCANAdapter.ids IDs to process.

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

Modifier and Type	Method and Description
private void	CLINK.clinkstep4567(DBIDRef id, ArrayDBIDs ids, DBIDArrayIter it, int n, WritableDBIDDataStore pi, WritableDoubleDataStore lambda, WritableDoubleDataStore m) Fourth to seventh step of CLINK: find best insertion
protected void	AbstractHDBSCAN.convertToPointerRepresentation(ArrayDBIDs ids, DoubleLongHeap heap, WritableDBIDDataStore pi, WritableDoubleDataStore lambda) Convert spanning tree to a pointer representation.
double	AbstractHDBSCAN.HDBSCANAdapter.distance(ArrayDBIDs data, int ip, int iq)
protected void	SLINK.process(DBIDRef id, ArrayDBIDs ids, DBIDArrayIter it, int n, WritableDBIDDataStore pi, WritableDoubleDataStore lambda, WritableDoubleDataStore m) SLINK main loop.
protected void	CLINK.process(DBIDRef id, ArrayDBIDs ids, DBIDArrayIter it, int n, WritableDBIDDataStore pi, WritableDoubleDataStore lambda, WritableDoubleDataStore m) CLINK main loop, based on the SLINK main loop.
int	AbstractHDBSCAN.HDBSCANAdapter.size(ArrayDBIDs data)

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

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

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

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

Modifier and Type	Method and Description
private int	ExtractFlatClusteringFromHierarchy.findSplit(ArrayDBIDs order, DBIDArrayIter it, DoubleDataStore lambda) Find the splitting point in the ordered DBIDs list.

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

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

Modifier and Type	Method and Description
protected double	CLARA.assignRemainingToNearestCluster(ArrayDBIDs means, DBIDs ids, DBIDs rids, WritableIntegerDataStore assignment, DistanceQuery<V> distQ) Returns a list of clusters.
protected double	KMedoidsPAM.assignToNearestCluster(ArrayDBIDs means, DBIDs ids, WritableDoubleDataStore nearest, WritableDoubleDataStore second, WritableIntegerDataStore assignment, DistanceQuery<V> distQ) Returns a list of clusters.
protected boolean	KMedoidsEM.assignToNearestCluster(ArrayDBIDs means, Mean[] mdist, List<? extends ModifiableDBIDs> clusters, DistanceQuery<V> distQ) Returns a list of clusters.

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

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

Modifier and Type	Method and Description
ArrayDBIDs	ClusterOrder.getDBIDs()

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

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

Modifier and Type	Method and Description
private ArrayDBIDs	PROCLUS.computeM_current(DBIDs m, DBIDs m_best, DBIDs m_bad, Random random) Computes the set of medoids in current iteration.
private ArrayDBIDs	PROCLUS.greedy(DistanceQuery<V> distFunc, DBIDs sampleSet, int m, Random random) Returns a piercing set of k medoids from the specified sample set.
private ArrayDBIDs	PROCLUS.initialSet(DBIDs sampleSet, int k, Random random) Returns a set of k elements from the specified sample set.

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

Modifier and Type	Method and Description
private ArrayList<PROCLUS.PROCLUSCluster>	PROCLUS.assignPoints(ArrayDBIDs m_current, long[][] dimensions, Relation<V> database) Assigns the objects to the clusters.
private DBIDs	PROCLUS.computeBadMedoids(ArrayDBIDs m_current, ArrayList<PROCLUS.PROCLUSCluster> clusters, int threshold) Computes the bad medoids, where the medoid of a cluster with less than the specified threshold of objects is bad.
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.

Uses of ArrayDBIDs in de.lmu.ifi.dbs.elki.algorithm.outlier.meta

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

Modifier and Type	Method and Description
private ArrayList<ArrayDBIDs>	HiCS.buildOneDimIndexes(Relation<? extends NumberVector> relation) Calculates "index structures" for every attribute, i.e. sorts a ModifiableArray of every DBID in the database for every dimension and stores them in a list

Method parameters in de.lmu.ifi.dbs.elki.algorithm.outlier.meta with type arguments of type ArrayDBIDs

Modifier and Type	Method and Description
private void	HiCS.calculateContrast(Relation<? extends NumberVector> relation, HiCS.HiCSSubspace subspace, ArrayList<ArrayDBIDs> subspaceIndex, Random random) Calculates the actual contrast of a given subspace.
private Set<HiCS.HiCSSubspace>	HiCS.calculateSubspaces(Relation<? extends NumberVector> relation, ArrayList<ArrayDBIDs> subspaceIndex, Random random) Identifies high contrast subspaces in a given full-dimensional database.

Uses of ArrayDBIDs in de.lmu.ifi.dbs.elki.database.ids

Subinterfaces of ArrayDBIDs in de.lmu.ifi.dbs.elki.database.ids

Modifier and Type	Interface and Description
interface	ArrayModifiableDBIDs Array-oriented implementation of a modifiable DBID collection.
interface	ArrayStaticDBIDs Unmodifiable, indexed DBIDs.
interface	DBID Database ID object.
interface	DBIDRange Static DBID range.
interface	DBIDVar (Persistent) variable storing a DBID reference.

Classes in de.lmu.ifi.dbs.elki.database.ids that implement ArrayDBIDs

Modifier and Type	Class and Description
class	EmptyDBIDs Empty DBID collection.

Methods in de.lmu.ifi.dbs.elki.database.ids that return ArrayDBIDs

Modifier and Type	Method and Description
static ArrayDBIDs	DBIDUtil.ensureArray(DBIDs ids) Ensure that the given DBIDs are array-indexable.
static ArrayDBIDs[]	DBIDUtil.randomSplit(DBIDs oids, int p, Random random) Randomly split IDs into p partitions of almost-equal size.
static ArrayDBIDs[]	DBIDUtil.randomSplit(DBIDs ids, int p, RandomFactory rnd) Randomly split IDs into p partitions of almost-equal size.
ArrayDBIDs	EmptyDBIDs.slice(int begin, int end)
ArrayDBIDs	ArrayDBIDs.slice(int begin, int end) Slice a subarray (as view, not copy!)

Uses of ArrayDBIDs in de.lmu.ifi.dbs.elki.database.ids.generic

Classes in de.lmu.ifi.dbs.elki.database.ids.generic that implement ArrayDBIDs

Modifier and Type	Class and Description
class	UnmodifiableArrayDBIDs Unmodifiable wrapper for DBIDs.

Fields in de.lmu.ifi.dbs.elki.database.ids.generic declared as ArrayDBIDs

Modifier and Type	Field and Description
protected ArrayDBIDs	MaskedDBIDs.data Data storage.
private ArrayDBIDs	UnmodifiableArrayDBIDs.inner The DBIDs we wrap.

Methods in de.lmu.ifi.dbs.elki.database.ids.generic that return ArrayDBIDs

Modifier and Type	Method and Description
ArrayDBIDs	UnmodifiableArrayDBIDs.slice(int begin, int end)

Constructors in de.lmu.ifi.dbs.elki.database.ids.generic with parameters of type ArrayDBIDs

Constructor and Description
MaskedDBIDs(ArrayDBIDs data, long[] bits, boolean inverse) Constructor.
UnmodifiableArrayDBIDs(ArrayDBIDs inner) Constructor.

Uses of ArrayDBIDs in de.lmu.ifi.dbs.elki.database.ids.integer

Subinterfaces of ArrayDBIDs in de.lmu.ifi.dbs.elki.database.ids.integer

Modifier and Type	Interface and Description
interface	IntegerArrayDBIDs Trivial combination interface.
(package private) interface	IntegerArrayStaticDBIDs Combination of ArrayStaticDBIDs and IntegerDBIDs.

Classes in de.lmu.ifi.dbs.elki.database.ids.integer that implement ArrayDBIDs

Modifier and Type	Class and Description
(package private) class	ArrayModifiableIntegerDBIDs Class using a primitive int[] array as storage.
private class	ArrayModifiableIntegerDBIDs.Slice Slice of an array.
(package private) class	ArrayStaticIntegerDBIDs Static (no modifications allowed) set of Database Object IDs.
private class	ArrayStaticIntegerDBIDs.Slice Slice of an array.
(package private) class	IntegerDBID Database ID object.
(package private) class	IntegerDBIDRange Representing a DBID range allocation.
(package private) class	IntegerDBIDVar Variable for storing a single DBID reference.
class	UnmodifiableIntegerArrayDBIDs Unmodifiable wrapper for DBIDs.

Methods in de.lmu.ifi.dbs.elki.database.ids.integer that return ArrayDBIDs

Modifier and Type	Method and Description
ArrayDBIDs	IntegerDBID.slice(int begin, int end)
ArrayDBIDs	IntegerDBIDVar.slice(int begin, int end)
ArrayDBIDs	IntegerDBIDRange.slice(int begin, int end)

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

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

Modifier and Type	Method and Description
List<? extends KNNList>	KNNQuery.getKNNForBulkDBIDs(ArrayDBIDs ids, int k) Bulk query method
List<KNNList>	LinearScanPrimitiveDistanceKNNQuery.getKNNForBulkDBIDs(ArrayDBIDs ids, int k)
List<KNNList>	PreprocessorKNNQuery.getKNNForBulkDBIDs(ArrayDBIDs ids, int k)
List<KNNList>	LinearScanEuclideanDistanceKNNQuery.getKNNForBulkDBIDs(ArrayDBIDs ids, int k)
List<KNNList>	LinearScanDistanceKNNQuery.getKNNForBulkDBIDs(ArrayDBIDs ids, int k)
List<? extends KNNList>	AbstractDistanceKNNQuery.getKNNForBulkDBIDs(ArrayDBIDs ids, int k)
private void	LinearScanDistanceKNNQuery.linearScanBatchKNN(ArrayDBIDs ids, List<KNNHeap> heaps) Linear batch knn for arbitrary distance functions.

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

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

Modifier and Type	Method and Description
List<? extends DoubleDBIDList>	LinearScanRKNNQuery.getRKNNForBulkDBIDs(ArrayDBIDs ids, int k)
List<? extends DoubleDBIDList>	PreprocessorRKNNQuery.getRKNNForBulkDBIDs(ArrayDBIDs ids, int k)
List<? extends DoubleDBIDList>	RKNNQuery.getRKNNForBulkDBIDs(ArrayDBIDs ids, int k) Bulk query method for reverse k nearest neighbors for ids.

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

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

Modifier and Type	Method and Description
static double[][]	RelationUtil.relationAsMatrix(Relation<? extends NumberVector> relation, ArrayDBIDs ids) Copy a relation into a double matrix.

Uses of ArrayDBIDs in de.lmu.ifi.dbs.elki.datasource.bundle

Fields in de.lmu.ifi.dbs.elki.datasource.bundle declared as ArrayDBIDs

Modifier and Type	Field and Description
private ArrayDBIDs	MultipleObjectsBundle.ids DBIDs for these objects, but may be null.

Methods in de.lmu.ifi.dbs.elki.datasource.bundle that return ArrayDBIDs

Modifier and Type	Method and Description
ArrayDBIDs	MultipleObjectsBundle.getDBIDs() Get the DBIDs, may be null.

Methods in de.lmu.ifi.dbs.elki.datasource.bundle with parameters of type ArrayDBIDs

Modifier and Type	Method and Description
void	MultipleObjectsBundle.setDBIDs(ArrayDBIDs ids) Set the DBID range for this bundle.

Uses of ArrayDBIDs in de.lmu.ifi.dbs.elki.evaluation.similaritymatrix

Fields in de.lmu.ifi.dbs.elki.evaluation.similaritymatrix declared as ArrayDBIDs

Modifier and Type	Field and Description
(package private) ArrayDBIDs	ComputeSimilarityMatrixImage.SimilarityMatrix.ids The database IDs used

Methods in de.lmu.ifi.dbs.elki.evaluation.similaritymatrix that return ArrayDBIDs

Modifier and Type	Method and Description
ArrayDBIDs	ComputeSimilarityMatrixImage.SimilarityMatrix.getIDs() Get the IDs

Constructors in de.lmu.ifi.dbs.elki.evaluation.similaritymatrix with parameters of type ArrayDBIDs

Constructor and Description
SimilarityMatrix(RenderedImage img, Relation<?> relation, ArrayDBIDs ids) Constructor

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

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

Modifier and Type	Field and Description
private ArrayDBIDs	InMemoryIDistanceIndex.referencepoints Reference points.

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

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

Uses of ArrayDBIDs in de.lmu.ifi.dbs.elki.index.preprocessed.fastoptics

Fields in de.lmu.ifi.dbs.elki.index.preprocessed.fastoptics with type parameters of type ArrayDBIDs

Modifier and Type	Field and Description
(package private) ArrayList<ArrayDBIDs>	RandomProjectedNeighborssAndDensities.splitsets sets that resulted from recursive split of entire point set

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

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

Modifier and Type	Method and Description
protected ArrayDBIDs	MaterializeKNNAndRKNNPreprocessor.affectedkNN(List<? extends KNNList> extract, DBIDs remove) Extracts and removes the DBIDs in the given collections.
protected ArrayDBIDs	MaterializeKNNAndRKNNPreprocessor.affectedRkNN(List<? extends Collection<DoubleDBIDPair>> extract, DBIDs remove) Extracts and removes the DBIDs in the given collections.
private ArrayDBIDs	MaterializeKNNPreprocessor.updateKNNsAfterDeletion(DBIDs ids) Updates the kNNs of the RkNNs of the specified ids.
private ArrayDBIDs	MaterializeKNNPreprocessor.updateKNNsAfterInsertion(DBIDs ids) Updates the kNNs of the RkNNs of the specified ids.
private ArrayDBIDs	MaterializeKNNAndRKNNPreprocessor.updateKNNsAndRkNNs(DBIDs ids) Updates the kNNs and RkNNs after insertion of the specified ids.

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

Modifier and Type	Method and Description
List<KNNList>	SpacefillingKNNPreprocessor.SpaceFillingKNNQuery.getKNNForBulkDBIDs(ArrayDBIDs ids, int k)
List<KNNList>	NaiveProjectedKNNPreprocessor.NaiveProjectedKNNQuery.getKNNForBulkDBIDs(ArrayDBIDs ids, int k)
private void	MaterializeKNNAndRKNNPreprocessor.materializeKNNAndRKNNs(ArrayDBIDs ids, FiniteProgress progress) Materializes the kNNs and RkNNs of the specified object IDs.

Uses of ArrayDBIDs in de.lmu.ifi.dbs.elki.index.preprocessed.snn

Methods in de.lmu.ifi.dbs.elki.index.preprocessed.snn that return ArrayDBIDs

Modifier and Type	Method and Description
ArrayDBIDs	SharedNearestNeighborIndex.getNearestNeighborSet(DBIDRef id) Get the precomputed nearest neighbors
ArrayDBIDs	SharedNearestNeighborPreprocessor.getNearestNeighborSet(DBIDRef objid)

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

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

Modifier and Type	Method and Description
List<? extends KNNList>	ProjectedIndex.ProjectedKNNQuery.getKNNForBulkDBIDs(ArrayDBIDs ids, int k)
List<? extends DoubleDBIDList>	ProjectedIndex.ProjectedRKNNQuery.getRKNNForBulkDBIDs(ArrayDBIDs ids, int k)

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

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

Modifier and Type	Method and Description
List<? extends DoubleDBIDList>	MkTreeRKNNQuery.getRKNNForBulkDBIDs(ArrayDBIDs ids, int k)

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

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

Modifier and Type	Method and Description
List<KNNList>	EuclideanRStarTreeKNNQuery.getKNNForBulkDBIDs(ArrayDBIDs ids, int k)
List<KNNList>	RStarTreeKNNQuery.getKNNForBulkDBIDs(ArrayDBIDs ids, int k)

Uses of ArrayDBIDs 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 ArrayDBIDs

Modifier and Type	Method and Description
private void	RdKNNTree.adjustKNNDistance(RdKNNEntry entry, ArrayDBIDs ids, List<? extends KNNList> knnLists) Adjusts the knn distance in the subtree of the specified root entry.

Uses of ArrayDBIDs in de.lmu.ifi.dbs.elki.math.dimensionsimilarity

Methods in de.lmu.ifi.dbs.elki.math.dimensionsimilarity that return types with arguments of type ArrayDBIDs

Modifier and Type	Method and Description
private ArrayList<ArrayDBIDs>	HiCSDimensionSimilarity.buildOneDimIndexes(Relation<? extends NumberVector> relation, DBIDs ids, DimensionSimilarityMatrix matrix) Calculates "index structures" for every attribute, i.e. sorts a ModifiableArray of every DBID in the database for every dimension and stores them in a list

Methods in de.lmu.ifi.dbs.elki.math.dimensionsimilarity with parameters of type ArrayDBIDs

Modifier and Type	Method and Description
private double	HiCSDimensionSimilarity.calculateContrast(Relation<? extends NumberVector> relation, DBIDs subset, ArrayDBIDs subspaceIndex1, ArrayDBIDs subspaceIndex2, int dim1, int dim2, Random random) Calculates the actual contrast of a given subspace

Uses of ArrayDBIDs in de.lmu.ifi.dbs.elki.parallel

Fields in de.lmu.ifi.dbs.elki.parallel declared as ArrayDBIDs

Modifier and Type	Field and Description
private ArrayDBIDs	ParallelExecutor.BlockArrayRunner.ids Array IDs to process

Methods in de.lmu.ifi.dbs.elki.parallel that return ArrayDBIDs

Modifier and Type	Method and Description
ArrayDBIDs	ParallelExecutor.BlockArrayRunner.call()

Constructors in de.lmu.ifi.dbs.elki.parallel with parameters of type ArrayDBIDs

Constructor and Description
BlockArrayRunner(ArrayDBIDs ids, int start, int end, Processor[] procs) Constructor.

Uses of ArrayDBIDs in de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike

Methods in de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike with parameters of type ArrayDBIDs

Modifier and Type	Method and Description
DBID	ArrayDBIDsAdapter.get(ArrayDBIDs array, int off) Deprecated.
int	ArrayDBIDsAdapter.size(ArrayDBIDs array)

Uses of ArrayDBIDs in de.lmu.ifi.dbs.elki.utilities.scaling.outlier

Methods in de.lmu.ifi.dbs.elki.utilities.scaling.outlier with parameters of type ArrayDBIDs

Modifier and Type	Method and Description
private double[]	SigmoidOutlierScalingFunction.MStepLevenbergMarquardt(double a, double b, ArrayDBIDs ids, long[] t, DoubleRelation scores) M-Step using a modified Levenberg-Marquardt method.