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.kmeans	K-means clustering and variations.
de.lmu.ifi.dbs.elki.algorithm.outlier.meta	Meta outlier detection algorithms: external scores, score rescaling.
de.lmu.ifi.dbs.elki.database	ELKI database layer - loading, storing, indexing and accessing data
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.evaluation.similaritymatrix	Render a distance matrix to visualize a clustering-distance-combination.
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.math.dimensionsimilarity	Functions to compute the similarity of dimensions (or the interestingness of the combination).
de.lmu.ifi.dbs.elki.utilities	Utility and helper classes - commonly used data structures, output formatting, exceptions, ...
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.kmeans

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

Modifier and Type	Method and Description
protected boolean	KMedoidsPAM.assignToNearestCluster(ArrayDBIDs means, DBIDs ids, WritableDoubleDataStore second, List<? extends ModifiableDBIDs> clusters, DistanceQuery<V,D> distQ) Returns a list of clusters.
protected boolean	KMedoidsEM.assignToNearestCluster(ArrayDBIDs means, Mean[] mdist, List<? extends ModifiableDBIDs> clusters, DistanceQuery<V,D> distQ) Returns a list of clusters.
protected double	KMeansPlusPlusInitialMeans.initialWeights(double[] weights, ArrayDBIDs ids, DBID latest, DistanceQuery<? super V,D> distQ) Initialize the weight list.
protected double	KMeansPlusPlusInitialMeans.updateWeights(double[] weights, ArrayDBIDs ids, DBID latest, DistanceQuery<? super V,D> distQ) Update the weight list.
protected double	KMeansPlusPlusInitialMeans.updateWeights(double[] weights, ArrayDBIDs ids, DBID latest, PrimitiveDoubleDistanceFunction<V> distF, Relation<V> rel) Update the weight list.

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

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

Modifier and Type	Field and Description
private ArrayDBIDs	StaticArrayDatabase.ids IDs of this 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, BitSet 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.
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
class	ArrayModifiableIntegerDBIDs Class using a primitive int[] array as storage.
private class	ArrayModifiableIntegerDBIDs.Slice Slice of an array.
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<D>>	KNNQuery.getKNNForBulkDBIDs(ArrayDBIDs ids, int k) Bulk query method
List<KNNList<D>>	LinearScanPrimitiveDistanceKNNQuery.getKNNForBulkDBIDs(ArrayDBIDs ids, int k)
List<KNNList<D>>	PreprocessorKNNQuery.getKNNForBulkDBIDs(ArrayDBIDs ids, int k)
List<KNNList<D>>	LinearScanDistanceKNNQuery.getKNNForBulkDBIDs(ArrayDBIDs ids, int k)
List<? extends KNNList<D>>	AbstractDistanceKNNQuery.getKNNForBulkDBIDs(ArrayDBIDs ids, int k)
private void	LinearScanDistanceKNNQuery.linearScanBatchKNN(ArrayDBIDs ids, List<KNNHeap<D>> 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<GenericDistanceDBIDList<D>>	LinearScanRKNNQuery.getRKNNForBulkDBIDs(ArrayDBIDs ids, int k)
List<? extends DistanceDBIDList<D>>	PreprocessorRKNNQuery.getRKNNForBulkDBIDs(ArrayDBIDs ids, int k)
List<? extends DistanceDBIDList<D>>	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.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
ComputeSimilarityMatrixImage.SimilarityMatrix(RenderedImage img, Relation<?> relation, ArrayDBIDs ids) Constructor

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<D>> extraxt, DBIDs remove) Extracts and removes the DBIDs in the given collections.
protected ArrayDBIDs	MaterializeKNNAndRKNNPreprocessor.affectedRkNN(List<? extends Collection<DistanceDBIDPair<D>>> extraxt, 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
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<D>>	ProjectedIndex.ProjectedKNNQuery.getKNNForBulkDBIDs(ArrayDBIDs ids, int k)
List<? extends DistanceDBIDList<D>>	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 DistanceDBIDList<D>>	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<DoubleDistanceKNNList>	DoubleDistanceRStarTreeKNNQuery.getKNNForBulkDBIDs(ArrayDBIDs ids, int k)
List<KNNList<D>>	GenericRStarTreeKNNQuery.getKNNForBulkDBIDs(ArrayDBIDs ids, int k)

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.utilities

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

Modifier and Type	Method and Description
static <V extends NumberVector<?>> double	DatabaseUtil.quickMedian(Relation<V> relation, ArrayDBIDs ids, int dimension, int numberOfSamples) Returns the median of a data set in the given dimension by using a sampling method.

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)
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, BitSet t, Relation<Double> scores) M-Step using a modified Levenberg-Marquardt method.