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

Packages that use ArrayDBIDs

de.lmu.ifi.dbs.elki.data.model	Cluster models classes for various algorithms.
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.range	Prepared queries for ε-range queries.
de.lmu.ifi.dbs.elki.database.query.rknn	Prepared queries for reverse k nearest neighbor (rkNN) queries.
de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel	Kernel functions.
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.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.utilities	Utility and helper classes - commonly used data structures, output formatting, exceptions, ...
de.lmu.ifi.dbs.elki.utilities.datastructures.heap	Heap structures and variations such as bounded priority heaps.
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.data.model

Fields in de.lmu.ifi.dbs.elki.data.model declared as ArrayDBIDs

private ArrayDBIDs

Bicluster.rowIDs The ids of the rows included in the bicluster.

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

Bicluster(ArrayDBIDs rowIDs, int[] colIDs, Relation<V> database)
Defines a new bicluster for given parameters.

BiclusterWithInverted(ArrayDBIDs rowIDs, int[] colIDs, Relation<V> database)

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

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

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

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.

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

(package private) class

EmptyDBIDs Empty DBID collection.

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

static ArrayDBIDs

DBIDUtil.ensureArray(DBIDs ids) Ensure that the given DBIDs are array-indexable.

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

class

GenericArrayModifiableDBIDs Array-oriented implementation of a modifiable DBID collection.

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

protected ArrayDBIDs

MaskedDBIDs.data Data storage

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

MaskedDBIDs(ArrayDBIDs data, BitSet bits, boolean inverse)
Constructor.

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

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

class	IntegerArrayStaticDBIDs Static (no modifications allowed) set of Database Object IDs.
(package private) class	IntegerDBID Database ID object.
(package private) class	IntegerDBIDRange Representing a DBID range allocation

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

List<List<DistanceResultPair<D>>>	KNNQuery.getKNNForBulkDBIDs(ArrayDBIDs ids, int k) Bulk query method
List<List<DistanceResultPair<D>>>	PreprocessorKNNQuery.getKNNForBulkDBIDs(ArrayDBIDs ids, int k)
List<List<DistanceResultPair<D>>>	LinearScanKNNQuery.getKNNForBulkDBIDs(ArrayDBIDs ids, int k)
List<List<DistanceResultPair<D>>>	LinearScanPrimitiveDistanceKNNQuery.getKNNForBulkDBIDs(ArrayDBIDs ids, int k)
private void	LinearScanKNNQuery.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.range

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

List<List<DistanceResultPair<D>>>	RangeQuery.getRangeForBulkDBIDs(ArrayDBIDs ids, D range) Bulk query method
List<List<DistanceResultPair<D>>>	AbstractDistanceRangeQuery.getRangeForBulkDBIDs(ArrayDBIDs ids, D range)

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

List<List<DistanceResultPair<D>>>	LinearScanRKNNQuery.getRKNNForBulkDBIDs(ArrayDBIDs ids, int k)
List<List<DistanceResultPair<D>>>	RKNNQuery.getRKNNForBulkDBIDs(ArrayDBIDs ids, int k) Bulk query method for reverse k nearest neighbors for ids.
List<List<DistanceResultPair<D>>>	PreprocessorRKNNQuery.getRKNNForBulkDBIDs(ArrayDBIDs ids, int k)

Uses of ArrayDBIDs in de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel

Constructors in de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel with parameters of type ArrayDBIDs

KernelMatrix(PrimitiveSimilarityFunction<? super O,DoubleDistance> kernelFunction, Relation<? extends O> database, ArrayDBIDs ids)
Provides a new kernel matrix.

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

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

(package private) ArrayDBIDs

ComputeSimilarityMatrixImage.SimilarityMatrix.ids The database IDs used

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

ArrayDBIDs

ComputeSimilarityMatrixImage.SimilarityMatrix.getIDs() Get the IDs

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

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

protected ArrayDBIDs	MaterializeKNNPreprocessor.extractAndRemoveIDs(List<List<DistanceResultPair<D>>> extraxt, ArrayDBIDs 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

protected ArrayDBIDs	MaterializeKNNPreprocessor.extractAndRemoveIDs(List<List<DistanceResultPair<D>>> extraxt, ArrayDBIDs remove) Extracts and removes the DBIDs in the given collections.
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.tree.metrical.mtreevariants.query

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

List<List<DistanceResultPair<D>>>	MetricalIndexKNNQuery.getKNNForBulkDBIDs(ArrayDBIDs ids, int k)
List<List<DistanceResultPair<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

List<List<DistanceResultPair<DoubleDistance>>>	DoubleDistanceRStarTreeKNNQuery.getKNNForBulkDBIDs(ArrayDBIDs ids, int k)
List<List<DistanceResultPair<D>>>	GenericRStarTreeKNNQuery.getKNNForBulkDBIDs(ArrayDBIDs ids, int k)

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

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

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.heap

Classes in de.lmu.ifi.dbs.elki.utilities.datastructures.heap that implement ArrayDBIDs

protected static class

KNNList.DBIDView A view on the DBIDs of the result

Methods in de.lmu.ifi.dbs.elki.utilities.datastructures.heap that return ArrayDBIDs

ArrayDBIDs	KNNList.asDBIDs() View as ArrayDBIDs
static ArrayDBIDs	KNNList.asDBIDs(List<? extends DistanceResultPair<?>> list) View as ArrayDBIDs

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

private double[]

SigmoidOutlierScalingFunction.MStepLevenbergMarquardt(double a, double b, ArrayDBIDs ids, BitSet t, Relation<Double> scores) M-Step using a modified Levenberg-Marquardt method.