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

Packages that use DBID

de.lmu.ifi.dbs.elki.algorithm	Algorithms suitable as a task for the KDDTask main routine.
de.lmu.ifi.dbs.elki.algorithm.clustering	Clustering algorithms Clustering algorithms are supposed to implement the Algorithm-Interface.
de.lmu.ifi.dbs.elki.algorithm.clustering.correlation	Correlation clustering algorithms
de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.cash	Helper classes for the CASH algorithm.
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.clustering.subspace.clique	Helper classes for the CLIQUE algorithm.
de.lmu.ifi.dbs.elki.algorithm.clustering.trivial	Trivial clustering algorithms: all in one, no clusters, label clusterings These methods are mostly useful for providing a reference result in evaluation.
de.lmu.ifi.dbs.elki.algorithm.outlier	Outlier detection algorithms
de.lmu.ifi.dbs.elki.algorithm.outlier.spatial	Spatial outlier detection algorithms
de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood	Spatial outlier neighborhood classes
de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood.weighted	Weighted Neighborhood definitions.
de.lmu.ifi.dbs.elki.algorithm.statistics	Statistical analysis algorithms The algorithms in this package perform statistical analysis of the data (e.g. compute distributions, distance distributions etc.)
de.lmu.ifi.dbs.elki.application.jsmap	JavaScript based map client - server architecture.
de.lmu.ifi.dbs.elki.application.visualization	Visualization applications in ELKI.
de.lmu.ifi.dbs.elki.data.type	Data type information, also used for type restrictions.
de.lmu.ifi.dbs.elki.database	ELKI database layer - loading, storing, indexing and accessing data
de.lmu.ifi.dbs.elki.database.datastore	General data store layer API (along the lines of Map<DBID, T> - use everywhere!)
de.lmu.ifi.dbs.elki.database.datastore.memory	Memory data store implementation for ELKI.
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	Database queries - computing distances, neighbors, similarities - API and general documentation.
de.lmu.ifi.dbs.elki.database.query.distance	Prepared queries for distances.
de.lmu.ifi.dbs.elki.database.query.knn	Prepared queries for k nearest neighbor (kNN) queries.
de.lmu.ifi.dbs.elki.database.query.range	Prepared queries for ε-range queries.
de.lmu.ifi.dbs.elki.database.query.rknn	Prepared queries for reverse k nearest neighbor (rkNN) queries.
de.lmu.ifi.dbs.elki.database.query.similarity	Prepared queries for similarity functions.
de.lmu.ifi.dbs.elki.database.relation	Relations, materialized and virtual (views).
de.lmu.ifi.dbs.elki.datasource.parser	Parsers for different file formats and data types.
de.lmu.ifi.dbs.elki.distance.distancefunction	Distance functions for use within ELKI.
de.lmu.ifi.dbs.elki.distance.distancefunction.adapter	Distance functions deriving distances from e.g. similarity measures
de.lmu.ifi.dbs.elki.distance.distancefunction.correlation	Distance functions using correlations.
de.lmu.ifi.dbs.elki.distance.distancefunction.external	Distance functions using external data sources.
de.lmu.ifi.dbs.elki.distance.distancefunction.subspace	Distance functions based on subspaces.
de.lmu.ifi.dbs.elki.distance.similarityfunction	Similarity functions.
de.lmu.ifi.dbs.elki.evaluation.roc	Evaluation of rankings using ROC AUC (Receiver Operation Characteristics - Area Under Curve)
de.lmu.ifi.dbs.elki.evaluation.similaritymatrix	Render a distance matrix to visualize a clustering-distance-combination.
de.lmu.ifi.dbs.elki.index	Index structure implementations
de.lmu.ifi.dbs.elki.index.preprocessed	Index structure based on preprocessors
de.lmu.ifi.dbs.elki.index.preprocessed.knn	Indexes providing KNN and rKNN data.
de.lmu.ifi.dbs.elki.index.preprocessed.localpca	Index using a preprocessed local PCA.
de.lmu.ifi.dbs.elki.index.preprocessed.preference	Indexes storing preference vectors.
de.lmu.ifi.dbs.elki.index.preprocessed.snn	Indexes providing nearest neighbor sets
de.lmu.ifi.dbs.elki.index.preprocessed.subspaceproj	Index using a preprocessed local subspaces.
de.lmu.ifi.dbs.elki.index.tree	Tree-based index structures
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants	M-Tree and variants.
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees	Metrical index structures based on the concepts of the M-Tree supporting processing of reverse k nearest neighbor queries by using the k-nn distances of the entries.
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkapp	MkAppTree
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop	MkCoPTree
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkmax	MkMaxTree
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mktab	MkTabTree
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mtree	MTree
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.query	Classes for performing queries (knn, range, ...) on metrical trees.
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.split	Splitting strategies of nodes in an M-Tree (and variants).
de.lmu.ifi.dbs.elki.index.tree.query	Classes related to generic tree queries.
de.lmu.ifi.dbs.elki.index.tree.spatial	Tree-based index structures for spatial indexing.
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants	R*-Tree and variants.
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu	DeLiCluTree
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.rstar	RStarTree
de.lmu.ifi.dbs.elki.math.linearalgebra	Linear Algebra package provides classes and computational methods for operations on matrices.
de.lmu.ifi.dbs.elki.result	Result types, representation and handling
de.lmu.ifi.dbs.elki.result.optics	Result classes for OPTICS.
de.lmu.ifi.dbs.elki.result.outlier	Outlier result classes
de.lmu.ifi.dbs.elki.result.textwriter	Text serialization (CSV, Gnuplot, Console, ...)
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.exceptions	Exception classes and common exception messages.
de.lmu.ifi.dbs.elki.visualization.opticsplot	Code for drawing OPTICS plots
de.lmu.ifi.dbs.elki.visualization.visualizers.vis2d	Visualizers based on 2D projections.

Uses of DBID in de.lmu.ifi.dbs.elki.algorithm

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

CollectionResult<CTriple<DBID,DBID,Double>>	MaterializeDistances.run(Database database, Relation<O> relation) Iterates over all points in the database.
CollectionResult<CTriple<DBID,DBID,Double>>	MaterializeDistances.run(Database database, Relation<O> relation) Iterates over all points in the database.

Uses of DBID in de.lmu.ifi.dbs.elki.algorithm.clustering

Fields in de.lmu.ifi.dbs.elki.algorithm.clustering with type parameters of type DBID

private WritableDataStore<DBID>

SLINK.pi The values of the function Pi of the pointer representation.

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

private DBID	DeLiClu.getStartObject(Relation<NV> relation) Returns the id of the start object for the run method.
private DBID	SLINK.lastObjectInCluster(DBID id, D stopdist, DataStore<DBID> pi, DataStore<D> lambda)

Methods in de.lmu.ifi.dbs.elki.algorithm.clustering that return types with arguments of type DBID

protected List<DBID>

SNNClustering.findSNNNeighbors(SimilarityQuery<O,IntegerDistance> snnInstance, DBID queryObject) Returns the shared nearest neighbors of the specified query object in the given database.

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

int	SLINK.CompareByLambda.compare(DBID id1, DBID id2)
protected void	DBSCAN.expandCluster(Database database, RangeQuery<O,D> rangeQuery, DBID startObjectID, FiniteProgress objprog, IndefiniteProgress clusprog) DBSCAN-function expandCluster.
protected void	AbstractProjectedDBSCAN.expandCluster(LocallyWeightedDistanceFunction.Instance<V> distFunc, RangeQuery<V,DoubleDistance> rangeQuery, DBID startObjectID, FiniteProgress objprog, IndefiniteProgress clusprog) ExpandCluster function of DBSCAN.
protected void	SNNClustering.expandCluster(SimilarityQuery<O,IntegerDistance> snnInstance, DBID startObjectID, FiniteProgress objprog, IndefiniteProgress clusprog) DBSCAN-function expandCluster adapted to SNN criterion.
protected void	OPTICS.expandClusterOrder(ClusterOrderResult<D> clusterOrder, Database database, RangeQuery<O,D> rangeQuery, DBID objectID, D epsilon, FiniteProgress progress) OPTICS-function expandClusterOrder.
protected void	OPTICS.expandClusterOrderDouble(ClusterOrderResult<DoubleDistance> clusterOrder, Database database, RangeQuery<O,DoubleDistance> rangeQuery, DBID objectID, DoubleDistance epsilon, FiniteProgress progress) OPTICS-function expandClusterOrder.
protected List<DBID>	SNNClustering.findSNNNeighbors(SimilarityQuery<O,IntegerDistance> snnInstance, DBID queryObject) Returns the shared nearest neighbors of the specified query object in the given database.
double[]	EM.getProbClusterIGivenX(DBID index) Get the probabilities for a given point.
private DBID	SLINK.lastObjectInCluster(DBID id, D stopdist, DataStore<DBID> pi, DataStore<D> lambda)
private void	SLINK.step1(DBID newID) First step: Initialize P(id) = id, L(id) = infinity.
private void	SLINK.step2(DBID newID, DBIDs processedIDs, DistanceQuery<O,D> distFunc, WritableDataStore<D> m) Second step: Determine the pairwise distances from all objects in the pointer representation to the new object with the specified id.
private void	SLINK.step3(DBID newID, DBIDs processedIDs, WritableDataStore<D> m) Third step: Determine the values for P and L
private void	SLINK.step4(DBID newID, DBIDs processedIDs) Fourth step: Actualize the clusters if necessary

Method parameters in de.lmu.ifi.dbs.elki.algorithm.clustering with type arguments of type DBID

private Clustering<Model>	SLINK.extractClusters_erich(DBIDs ids, DataStore<DBID> pi, DataStore<D> lambda, int minclusters) Extract all clusters from the pi-lambda-representation.
private Clustering<DendrogramModel<D>>	SLINK.extractClusters(DBIDs ids, DataStore<DBID> pi, DataStore<D> lambda, int minclusters) Extract all clusters from the pi-lambda-representation.
private DBID	SLINK.lastObjectInCluster(DBID id, D stopdist, DataStore<DBID> pi, DataStore<D> lambda)
private Cluster<DendrogramModel<D>>	SLINK.root(Map<DBID,ModifiableDBIDs> cluster_ids, Map<DBID,D> cluster_distances, DataStore<DBID> pi, DataStore<D> lambda, ModifiableHierarchy<Cluster<DendrogramModel<D>>> hier, FiniteProgress progress)
private Cluster<DendrogramModel<D>>	SLINK.root(Map<DBID,ModifiableDBIDs> cluster_ids, Map<DBID,D> cluster_distances, DataStore<DBID> pi, DataStore<D> lambda, ModifiableHierarchy<Cluster<DendrogramModel<D>>> hier, FiniteProgress progress)
private Cluster<DendrogramModel<D>>	SLINK.root(Map<DBID,ModifiableDBIDs> cluster_ids, Map<DBID,D> cluster_distances, DataStore<DBID> pi, DataStore<D> lambda, ModifiableHierarchy<Cluster<DendrogramModel<D>>> hier, FiniteProgress progress)

Uses of DBID in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation

Constructors in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation with parameters of type DBID

ORCLUS.ORCLUSCluster(V o, DBID id, V factory)
Creates a new cluster containing the specified object o.

Uses of DBID in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.cash

Fields in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.cash with type parameters of type DBID

private Map<HyperBoundingBox,Map<DBID,Double>>	CASHIntervalSplit.f_maxima Caches maximum function values for given intervals, used for better split performance.
private Map<HyperBoundingBox,Map<DBID,Double>>	CASHIntervalSplit.f_minima Caches minimum function values for given intervals, used for better split performance.

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

Methods in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace that return types with arguments of type DBID

private Map<DBID,PROCLUS.PROCLUSCluster>	PROCLUS.assignPoints(Map<DBID,Set<Integer>> dimensions, Relation<V> database) Assigns the objects to the clusters.
private Map<DBID,Set<Integer>>	PROCLUS.findDimensions(DBIDs medoids, Relation<V> database, DistanceQuery<V,DoubleDistance> distFunc, RangeQuery<V,DoubleDistance> rangeQuery) Determines the set of correlated dimensions for each medoid in the specified medoid set.
private Map<DBID,List<DistanceResultPair<DoubleDistance>>>	PROCLUS.getLocalities(DBIDs medoids, Relation<V> database, DistanceQuery<V,DoubleDistance> distFunc, RangeQuery<V,DoubleDistance> 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.

Method parameters in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace with type arguments of type DBID

private Map<DBID,PROCLUS.PROCLUSCluster>	PROCLUS.assignPoints(Map<DBID,Set<Integer>> dimensions, Relation<V> database) Assigns the objects to the clusters.
private ModifiableDBIDs	PROCLUS.computeBadMedoids(Map<DBID,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 double	PROCLUS.evaluateClusters(Map<DBID,PROCLUS.PROCLUSCluster> clusters, Map<DBID,Set<Integer>> dimensions, Relation<V> database) Evaluates the quality of the clusters.
private double	PROCLUS.evaluateClusters(Map<DBID,PROCLUS.PROCLUSCluster> clusters, Map<DBID,Set<Integer>> dimensions, Relation<V> database) Evaluates the quality of the clusters.

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

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

boolean

CLIQUEUnit.addFeatureVector(DBID id, V vector) Adds the id of the specified feature vector to this unit, if this unit contains the feature vector.

Uses of DBID in de.lmu.ifi.dbs.elki.algorithm.clustering.trivial

Methods in de.lmu.ifi.dbs.elki.algorithm.clustering.trivial with parameters of type DBID

private void

ByLabelClustering.assign(HashMap<String,ModifiableDBIDs> labelMap, String label, DBID id) Assigns the specified id to the labelMap according to its label

Uses of DBID in de.lmu.ifi.dbs.elki.algorithm.outlier

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

private PriorityQueue<FCPair<Double,DBID>>	ABOD.calcDistsandNN(Relation<V> data, KernelMatrix kernelMatrix, int sampleSize, DBID aKey, HashMap<DBID,Double> dists)
private PriorityQueue<FCPair<Double,DBID>>	ABOD.calcDistsandRNDSample(Relation<V> data, KernelMatrix kernelMatrix, int sampleSize, DBID aKey, HashMap<DBID,Double> dists)
IterableIterator<DBID>	SOD.SODProxyScoreResult.iterDBIDs()

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

private double	ABOD.calcCos(KernelMatrix kernelMatrix, DBID aKey, DBID bKey) Compute the cosinus value between vectors aKey and bKey.
private double	ABOD.calcDenominator(KernelMatrix kernelMatrix, DBID aKey, DBID bKey, DBID cKey)
private PriorityQueue<FCPair<Double,DBID>>	ABOD.calcDistsandNN(Relation<V> data, KernelMatrix kernelMatrix, int sampleSize, DBID aKey, HashMap<DBID,Double> dists)
private PriorityQueue<FCPair<Double,DBID>>	ABOD.calcDistsandRNDSample(Relation<V> data, KernelMatrix kernelMatrix, int sampleSize, DBID aKey, HashMap<DBID,Double> dists)
private double[]	ABOD.calcFastNormalization(DBID x, HashMap<DBID,Double> dists)
private double	ABOD.calcNumerator(KernelMatrix kernelMatrix, DBID aKey, DBID bKey, DBID cKey)
void	SOD.SODProxyScoreResult.delete(DBID id)
private void	ABOD.generateExplanation(Relation<V> data, DBID key, LinkedList<DBID> expList)
Double	SOD.SODProxyScoreResult.get(DBID objID)
private double	ABOD.getAbofFilter(KernelMatrix kernelMatrix, DBID aKey, HashMap<DBID,Double> dists, double fulCounter, double counter, DBIDs neighbors)
private KNNList<DoubleDistance>	SOD.getKNN(Relation<V> database, SimilarityQuery<V,IntegerDistance> snnInstance, DBID queryObject) Provides the k nearest neighbors in terms of the shared nearest neighbor distance.
private int	ABOD.mapDBID(DBID aKey)
void	SOD.SODProxyScoreResult.set(DBID id, Double val)

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

private PriorityQueue<FCPair<Double,DBID>>	ABOD.calcDistsandNN(Relation<V> data, KernelMatrix kernelMatrix, int sampleSize, DBID aKey, HashMap<DBID,Double> dists)
private PriorityQueue<FCPair<Double,DBID>>	ABOD.calcDistsandRNDSample(Relation<V> data, KernelMatrix kernelMatrix, int sampleSize, DBID aKey, HashMap<DBID,Double> dists)
private double[]	ABOD.calcFastNormalization(DBID x, HashMap<DBID,Double> dists)
private void	ABOD.generateExplanation(Relation<V> data, DBID key, LinkedList<DBID> expList)
private double	ABOD.getAbofFilter(KernelMatrix kernelMatrix, DBID aKey, HashMap<DBID,Double> dists, double fulCounter, double counter, DBIDs neighbors)

Uses of DBID in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial

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

private Pair<DBID,Double>

CTLuGLSBackwardSearchAlgorithm.singleIteration(Relation<V> relationx, Relation<? extends NumberVector<?,?>> relationy) Run a single iteration of the GLS-SOD modeling step

Uses of DBID in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood

Methods in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood with parameters of type DBID

DBIDs	AbstractPrecomputedNeighborhood.getNeighborDBIDs(DBID reference)
DBIDs	NeighborSetPredicate.getNeighborDBIDs(DBID reference) Get the neighbors of a reference object for DBSCAN.

Uses of DBID in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood.weighted

Methods in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood.weighted that return types with arguments of type DBID

Collection<DoubleObjPair<DBID>>	UnweightedNeighborhoodAdapter.getWeightedNeighbors(DBID reference)
Collection<DoubleObjPair<DBID>>	LinearWeightedExtendedNeighborhood.getWeightedNeighbors(DBID reference)
Collection<DoubleObjPair<DBID>>	WeightedNeighborSetPredicate.getWeightedNeighbors(DBID reference) Get the neighbors of a reference object for DBSCAN.

Methods in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood.weighted with parameters of type DBID

Collection<DoubleObjPair<DBID>>	UnweightedNeighborhoodAdapter.getWeightedNeighbors(DBID reference)
Collection<DoubleObjPair<DBID>>	LinearWeightedExtendedNeighborhood.getWeightedNeighbors(DBID reference)
Collection<DoubleObjPair<DBID>>	WeightedNeighborSetPredicate.getWeightedNeighbors(DBID reference) Get the neighbors of a reference object for DBSCAN.

Uses of DBID in de.lmu.ifi.dbs.elki.algorithm.statistics

Method parameters in de.lmu.ifi.dbs.elki.algorithm.statistics with type arguments of type DBID

private void

DistanceStatisticsWithClasses.shrinkHeap(TreeSet<FCPair<Double,DBID>> hotset, int k)

Uses of DBID in de.lmu.ifi.dbs.elki.application.jsmap

Methods in de.lmu.ifi.dbs.elki.application.jsmap that return DBID

private DBID

JSONWebServer.stringToDBID(String query) Parse a string into a DBID.

Methods in de.lmu.ifi.dbs.elki.application.jsmap with parameters of type DBID

protected void

JSONWebServer.bundleToJSON(JSONBuffer re, DBID id) Serialize an object bundle to JSON.

Uses of DBID in de.lmu.ifi.dbs.elki.application.visualization

Fields in de.lmu.ifi.dbs.elki.application.visualization with type parameters of type DBID

protected HashMap<DBID,Double>

KNNExplorer.ExplorerWindow.distancecache

Methods in de.lmu.ifi.dbs.elki.application.visualization with parameters of type DBID

private Element

KNNExplorer.ExplorerWindow.plotSeries(DBID idx, int resolution) Plot a single time series.

Uses of DBID in de.lmu.ifi.dbs.elki.data.type

Fields in de.lmu.ifi.dbs.elki.data.type with type parameters of type DBID

static SimpleTypeInformation<DBID>

TypeUtil.DBID Database IDs

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

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

private void	HashmapDatabase.doDelete(DBID id) Removes the object with the specified id from this database.
void	DatabaseEventManager.fireObjectInserted(DBID insertion) Convenience method, calls fireObjectChanged(insertion, DataStoreEvent.Type.INSERT).
protected void	DatabaseEventManager.fireObjectRemoved(DBID deletion) Convenience method, calls fireObjectChanged(deletion, DataStoreEvent.Type.DELETE).
SingleObjectBundle	AbstractDatabase.getBundle(DBID id)
SingleObjectBundle	Database.getBundle(DBID id) Returns the DatabaseObject represented by the specified id.
private void	HashmapDatabase.restoreID(DBID id) Makes the given id reusable for new insertion operations.

Uses of DBID in de.lmu.ifi.dbs.elki.database.datastore

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

void	WritableDataStore.delete(DBID id) Delete the contents for a particular ID and notifies the registered listeners.
T	DataStore.get(DBID id) Retrieves an object from the storage.
int	RangeIDMap.map(DBID dbid)
int	DataStoreIDMap.map(DBID dbid) Map a DBID to a database id.
T	WritableDataStore.put(DBID id, T value) Associates the specified value with the specified id in this storage.
boolean	WritableRecordStore.remove(DBID id) Remove an object from the store, all columns.

Uses of DBID in de.lmu.ifi.dbs.elki.database.datastore.memory

Fields in de.lmu.ifi.dbs.elki.database.datastore.memory with type parameters of type DBID

private Map<DBID,Object[]>	MapRecordStore.data Storage Map
private Map<DBID,T>	MapStore.data Storage Map

Methods in de.lmu.ifi.dbs.elki.database.datastore.memory with parameters of type DBID

void	ArrayStore.delete(DBID id)
void	MapRecordStore.StorageAccessor.delete(DBID id)
void	MapStore.delete(DBID id)
void	ArrayRecordStore.StorageAccessor.delete(DBID id)
T	ArrayStore.get(DBID id)
T	MapRecordStore.StorageAccessor.get(DBID id)
T	MapStore.get(DBID id)
T	ArrayRecordStore.StorageAccessor.get(DBID id)
protected <T> T	MapRecordStore.get(DBID id, int index) Actual getter
protected <T> T	ArrayRecordStore.get(DBID id, int index) Actual getter
T	ArrayStore.put(DBID id, T value)
T	MapRecordStore.StorageAccessor.put(DBID id, T value)
T	MapStore.put(DBID id, T value)
T	ArrayRecordStore.StorageAccessor.put(DBID id, T value)
boolean	MapRecordStore.remove(DBID id)
boolean	ArrayRecordStore.remove(DBID id)
protected <T> T	MapRecordStore.set(DBID id, int index, T value) Actual setter
protected <T> T	ArrayRecordStore.set(DBID id, int index, T value) Actual setter

Constructor parameters in de.lmu.ifi.dbs.elki.database.datastore.memory with type arguments of type DBID

MapRecordStore(int rlen, Map<DBID,Object[]> data)
Constructor with existing data.

MapStore(Map<DBID,T> data)
Constructor.

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

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

static DBID	DBIDUtil.generateSingleDBID() Generate a single DBID
DBID	DBIDFactory.generateSingleDBID() Generate a single DBID
DBID	EmptyDBIDs.get(int i)
DBID	DBIDPair.getFirst() Getter for first
DBID	DBIDPair.getSecond() Getter for second element in pair
static DBID	DBIDUtil.importInteger(int id) Import an Integer DBID.
DBID	DBIDFactory.importInteger(int id) Import an integer ID

Methods in de.lmu.ifi.dbs.elki.database.ids that return types with arguments of type DBID

Collection<DBID>	EmptyDBIDs.asCollection()
Collection<DBID>	DBIDs.asCollection() Retrieve collection access to the IDs
ByteBufferSerializer<DBID>	DBIDUtil.getDBIDSerializer() Get a serializer for DBIDs
ByteBufferSerializer<DBID>	DBIDFactory.getDBIDSerializer() Get a serializer for DBIDs
ByteBufferSerializer<DBID>	DBIDUtil.getDBIDSerializerStatic() Get a serializer for DBIDs with static size
FixedSizeByteBufferSerializer<DBID>	DBIDFactory.getDBIDSerializerStatic() Get a serializer for DBIDs with static size
Class<? extends DBID>	DBIDFactory.getTypeRestriction() Get type restriction
Iterator<DBID>	EmptyDBIDs.iterator()
Iterator<DBID>	DBIDs.iterator() Retrieve Iterator access to the IDs.

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

static void	DBIDUtil.deallocateSingleDBID(DBID id) Return a single DBID for reuse.
void	DBIDFactory.deallocateSingleDBID(DBID id) Return a single DBID for reuse.
int	DBIDRange.getOffset(DBID dbid) Get offset in the array for a particular DBID.
DBIDPair	DBIDFactory.makePair(DBID first, DBID second) Make a DBID pair from two existing DBIDs.
static DBIDPair	DBIDUtil.newPair(DBID id1, DBID id2) Make a DBID pair.

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

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

DBID	MaskedDBIDs.Itr.next()
DBID	MaskedDBIDs.InvItr.next()

Methods in de.lmu.ifi.dbs.elki.database.ids.generic that return types with arguments of type DBID

Collection<DBID>	GenericTreeSetModifiableDBIDs.asCollection()
Collection<DBID>	UnmodifiableDBIDs.asCollection()
Collection<DBID>	GenericArrayModifiableDBIDs.asCollection()
Collection<DBID>	MergedDBIDs.asCollection()
Collection<DBID>	MaskedDBIDs.asCollection()
Collection<DBID>	GenericHashSetModifiableDBIDs.asCollection()
Iterator<DBID>	UnmodifiableDBIDs.iterator()
Iterator<DBID>	MergedDBIDs.iterator()
Iterator<DBID>	MaskedDBIDs.iterator()

Methods in de.lmu.ifi.dbs.elki.database.ids.generic with parameters of type DBID

boolean	MergedDBIDs.add(DBID e)
boolean	MaskedDBIDs.add(DBID e)

Method parameters in de.lmu.ifi.dbs.elki.database.ids.generic with type arguments of type DBID

boolean

MergedDBIDs.addAll(Collection<? extends DBID> c)

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

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

(package private) class

IntegerDBID Database ID object.

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

DBID	IntegerDBID.DynamicSerializer.fromByteBuffer(ByteBuffer buffer)
DBID	IntegerDBID.StaticSerializer.fromByteBuffer(ByteBuffer buffer)
DBID	ReusingDBIDFactory.generateSingleDBID()
DBID	SimpleDBIDFactory.generateSingleDBID()
DBID	TrivialDBIDFactory.generateSingleDBID()
DBID	IntegerArrayStaticDBIDs.get(int i)
DBID	IntegerDBID.get(int i)
DBID	IntegerDBIDRange.get(int i)
DBID	SimpleDBIDFactory.importInteger(int id)
DBID	TrivialDBIDFactory.importInteger(int id)
DBID	IntegerArrayStaticDBIDs.Itr.next()
DBID	IntegerDBID.Itr.next()
DBID	IntegerDBIDRange.Itr.next()

Methods in de.lmu.ifi.dbs.elki.database.ids.integer that return types with arguments of type DBID

Collection<DBID>	IntegerArrayStaticDBIDs.asCollection()
Collection<DBID>	IntegerDBID.asCollection()
Collection<DBID>	IntegerDBIDRange.asCollection()
ByteBufferSerializer<DBID>	SimpleDBIDFactory.getDBIDSerializer()
ByteBufferSerializer<DBID>	TrivialDBIDFactory.getDBIDSerializer()
FixedSizeByteBufferSerializer<DBID>	SimpleDBIDFactory.getDBIDSerializerStatic()
FixedSizeByteBufferSerializer<DBID>	TrivialDBIDFactory.getDBIDSerializerStatic()
Class<? extends DBID>	SimpleDBIDFactory.getTypeRestriction()
Class<? extends DBID>	TrivialDBIDFactory.getTypeRestriction()
Iterator<DBID>	IntegerArrayStaticDBIDs.iterator()
Iterator<DBID>	IntegerDBID.iterator()
Iterator<DBID>	IntegerDBIDRange.iterator()

Methods in de.lmu.ifi.dbs.elki.database.ids.integer with parameters of type DBID

int	IntegerDBID.compareTo(DBID o)
void	ReusingDBIDFactory.deallocateSingleDBID(DBID id)
void	SimpleDBIDFactory.deallocateSingleDBID(DBID id)
void	TrivialDBIDFactory.deallocateSingleDBID(DBID id)
int	IntegerDBID.DynamicSerializer.getByteSize(DBID object)
int	IntegerDBID.StaticSerializer.getByteSize(DBID object)
int	IntegerDBIDRange.getOffset(DBID dbid) For storage array offsets.
DBIDPair	SimpleDBIDFactory.makePair(DBID first, DBID second)
DBIDPair	TrivialDBIDFactory.makePair(DBID first, DBID second)
void	IntegerDBID.DynamicSerializer.toByteBuffer(ByteBuffer buffer, DBID object)
void	IntegerDBID.StaticSerializer.toByteBuffer(ByteBuffer buffer, DBID object)

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

Fields in de.lmu.ifi.dbs.elki.database.query declared as DBID

(package private) DBID

DoubleDistanceResultPair.id Object ID

Methods in de.lmu.ifi.dbs.elki.database.query that return DBID

DBID	DistanceResultPair.getDBID() Getter for second element in pair
DBID	DoubleDistanceResultPair.getDBID()
DBID	GenericDistanceResultPair.getDBID() Getter for second element in pair
DBID	DoubleDistanceResultPair.getSecond() Deprecated. Use DoubleDistanceResultPair.getDBID() for clearness.

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

void	DistanceResultPair.setID(DBID second) Setter for second
void	DoubleDistanceResultPair.setID(DBID id)
void	GenericDistanceResultPair.setID(DBID second) Setter for second

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

DoubleDistanceResultPair(double distance, DBID id)
Constructor.

GenericDistanceResultPair(D first, DBID second)
Canonical constructor

Uses of DBID in de.lmu.ifi.dbs.elki.database.query.distance

Methods in de.lmu.ifi.dbs.elki.database.query.distance with parameters of type DBID

D	PrimitiveDistanceQuery.distance(DBID id1, DBID id2)
D	DistanceQuery.distance(DBID id1, DBID id2) Returns the distance between the two objects specified by their object ids.
abstract D	AbstractDistanceQuery.distance(DBID id1, DBID id2) Returns the distance between the two objects specified by their object ids.
D	DBIDDistanceQuery.distance(DBID id1, DBID id2)
D	PrimitiveDistanceQuery.distance(DBID id1, O o2)
D	AbstractDatabaseDistanceQuery.distance(DBID id1, O o2)
D	DistanceQuery.distance(DBID id1, O o2) Returns the distance between the two objects specified by their object ids.
abstract D	AbstractDistanceQuery.distance(DBID id1, O o2) Returns the distance between the two objects specified by their object ids.
D	PrimitiveDistanceQuery.distance(O o1, DBID id2)
D	AbstractDatabaseDistanceQuery.distance(O o1, DBID id2)
D	DistanceQuery.distance(O o1, DBID id2) Returns the distance between the two objects specified by their object ids.
abstract D	AbstractDistanceQuery.distance(O o1, DBID id2) Returns the distance between the two objects specified by their object ids.
D	SpatialDistanceQuery.minDist(SpatialComparable mbr, DBID id) Computes the minimum distance between the given MBR and the FeatureVector object according to this distance function.
D	SpatialPrimitiveDistanceQuery.minDist(SpatialComparable mbr, DBID id)
D	PrimitiveDistanceSimilarityQuery.similarity(DBID id1, DBID id2)
D	PrimitiveDistanceSimilarityQuery.similarity(DBID id1, O o2)
D	PrimitiveDistanceSimilarityQuery.similarity(O o1, DBID id2)

Constructor parameters in de.lmu.ifi.dbs.elki.database.query.distance with type arguments of type DBID

DBIDDistanceQuery(Relation<DBID> relation, DBIDDistanceFunction<D> distanceFunction)
Constructor.

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

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

List<DistanceResultPair<D>>	KNNQuery.getKNNForDBID(DBID id, int k) Get the k nearest neighbors for a particular id.
List<DistanceResultPair<DoubleDistance>>	LinearScanRawDoubleDistanceKNNQuery.getKNNForDBID(DBID id, int k)
List<DistanceResultPair<D>>	PreprocessorKNNQuery.getKNNForDBID(DBID id, int k)
List<DistanceResultPair<D>>	LinearScanKNNQuery.getKNNForDBID(DBID id, int k)
abstract List<DistanceResultPair<D>>	AbstractDistanceKNNQuery.getKNNForDBID(DBID id, int k)
List<DistanceResultPair<D>>	LinearScanPrimitiveDistanceKNNQuery.getKNNForDBID(DBID id, int k)

Method parameters in de.lmu.ifi.dbs.elki.database.query.knn with type arguments of type DBID

void	KNNQuery.getKNNForBulkHeaps(Map<DBID,KNNHeap<D>> heaps) Bulk query method configured by a map.
void	PreprocessorKNNQuery.getKNNForBulkHeaps(Map<DBID,KNNHeap<D>> heaps)
void	LinearScanKNNQuery.getKNNForBulkHeaps(Map<DBID,KNNHeap<D>> heaps)
void	LinearScanPrimitiveDistanceKNNQuery.getKNNForBulkHeaps(Map<DBID,KNNHeap<D>> heaps)

Uses of DBID in de.lmu.ifi.dbs.elki.database.query.range

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

List<DistanceResultPair<D>>	LinearScanPrimitiveDistanceRangeQuery.getRangeForDBID(DBID id, D range)
List<DistanceResultPair<D>>	RangeQuery.getRangeForDBID(DBID id, D range) Get the nearest neighbors for a particular id in a given query range
abstract List<DistanceResultPair<D>>	AbstractDistanceRangeQuery.getRangeForDBID(DBID id, D range)
List<DistanceResultPair<D>>	LinearScanRangeQuery.getRangeForDBID(DBID id, D range)
List<DistanceResultPair<DoubleDistance>>	LinearScanRawDoubleDistanceRangeQuery.getRangeForDBID(DBID id, DoubleDistance range)

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

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

List<DistanceResultPair<D>>	LinearScanRKNNQuery.getRKNNForDBID(DBID id, int k)
List<DistanceResultPair<D>>	RKNNQuery.getRKNNForDBID(DBID id, int k) Get the reverse k nearest neighbors for a particular id.
List<DistanceResultPair<D>>	PreprocessorRKNNQuery.getRKNNForDBID(DBID id, int k)
abstract List<DistanceResultPair<D>>	AbstractRKNNQuery.getRKNNForDBID(DBID id, int k)

Uses of DBID in de.lmu.ifi.dbs.elki.database.query.similarity

Methods in de.lmu.ifi.dbs.elki.database.query.similarity with parameters of type DBID

D	SimilarityQuery.similarity(DBID id1, DBID id2) Returns the similarity between the two objects specified by their object ids.
D	PrimitiveSimilarityQuery.similarity(DBID id1, DBID id2)
abstract D	AbstractSimilarityQuery.similarity(DBID id1, DBID id2) Returns the distance between the two objects specified by their object ids.
D	SimilarityQuery.similarity(DBID id1, O o2) Returns the similarity between the two objects specified by their object ids.
D	PrimitiveSimilarityQuery.similarity(DBID id1, O o2)
abstract D	AbstractSimilarityQuery.similarity(DBID id1, O o2) Returns the distance between the two objects specified by their object ids.
D	AbstractDBIDSimilarityQuery.similarity(DBID id1, O o2)
D	SimilarityQuery.similarity(O o1, DBID id2) Returns the similarity between the two objects specified by their object ids.
D	PrimitiveSimilarityQuery.similarity(O o1, DBID id2)
abstract D	AbstractSimilarityQuery.similarity(O o1, DBID id2) Returns the distance between the two objects specified by their object ids.
D	AbstractDBIDSimilarityQuery.similarity(O o1, DBID id2)

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

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

DBID	DBIDView.get(DBID id)

Methods in de.lmu.ifi.dbs.elki.database.relation that return types with arguments of type DBID

SimpleTypeInformation<DBID>	DBIDView.getDataTypeInformation()
IterableIterator<DBID>	ConvertToStringView.iterDBIDs()
IterableIterator<DBID>	ProxyView.iterDBIDs()
IterableIterator<DBID>	MaterializedRelation.iterDBIDs()
IterableIterator<DBID>	DBIDView.iterDBIDs()
IterableIterator<DBID>	Relation.iterDBIDs() Get an iterator access to the DBIDs.

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

void	ConvertToStringView.delete(DBID id)
void	ProxyView.delete(DBID id)
void	MaterializedRelation.delete(DBID id) Delete an objects values.
void	DBIDView.delete(DBID id)
void	Relation.delete(DBID id) Delete an objects values.
String	ConvertToStringView.get(DBID id)
O	ProxyView.get(DBID id)
O	MaterializedRelation.get(DBID id)
DBID	DBIDView.get(DBID id)
O	Relation.get(DBID id) Get the representation of an object.
void	DBIDView.set(DBID id, DBID val)
void	ProxyView.set(DBID id, O val)
void	MaterializedRelation.set(DBID id, O val)
void	Relation.set(DBID id, O val) Set an object representation.
void	ConvertToStringView.set(DBID id, String val)

Uses of DBID in de.lmu.ifi.dbs.elki.datasource.parser

Methods in de.lmu.ifi.dbs.elki.datasource.parser with parameters of type DBID

boolean	NumberDistanceParser.containsKey(DBID id1, DBID id2, Map<DBIDPair,D> cache) Returns true if the specified distance cache contains a distance value for the specified ids.
private void	NumberDistanceParser.put(DBID id1, DBID id2, D distance, Map<DBIDPair,D> cache) Puts the specified distance value for the given ids to the distance cache.

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

Methods in de.lmu.ifi.dbs.elki.distance.distancefunction with type parameters of type DBID

<O extends DBID> DistanceQuery<O,D>

AbstractDBIDDistanceFunction.instantiate(Relation<O> database)

Methods in de.lmu.ifi.dbs.elki.distance.distancefunction that return types with arguments of type DBID

SimpleTypeInformation<DBID>

AbstractDBIDDistanceFunction.getInputTypeRestriction()

Methods in de.lmu.ifi.dbs.elki.distance.distancefunction with parameters of type DBID

abstract D	AbstractDBIDDistanceFunction.distance(DBID o1, DBID o2)
D	ProxyDistanceFunction.distance(DBID o1, DBID o2)
D	MinKDistance.Instance.distance(DBID id1, DBID id2)
DoubleDistance	SharedNearestNeighborJaccardDistanceFunction.Instance.distance(DBID id1, DBID id2)
D	DBIDDistanceFunction.distance(DBID id1, DBID id2) Returns the distance between the two objects specified by their object ids.
DoubleDistance	LocallyWeightedDistanceFunction.Instance.distance(DBID id1, DBID id2) Computes the distance between two given real vectors according to this distance function.
DoubleDistance	RandomStableDistanceFunction.distance(DBID o1, DBID o2)

Uses of DBID in de.lmu.ifi.dbs.elki.distance.distancefunction.adapter

Methods in de.lmu.ifi.dbs.elki.distance.distancefunction.adapter with parameters of type DBID

DoubleDistance

AbstractSimilarityAdapter.Instance.distance(DBID id1, DBID id2)

Uses of DBID in de.lmu.ifi.dbs.elki.distance.distancefunction.correlation

Methods in de.lmu.ifi.dbs.elki.distance.distancefunction.correlation with parameters of type DBID

PCACorrelationDistance	PCABasedCorrelationDistanceFunction.Instance.distance(DBID id1, DBID id2)
BitDistance	ERiCDistanceFunction.Instance.distance(DBID id1, DBID id2) Note, that the pca of o1 must have equal ore more strong eigenvectors than the pca of o2.

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

Methods in de.lmu.ifi.dbs.elki.distance.distancefunction.external with parameters of type DBID

DoubleDistance	FileBasedDoubleDistanceFunction.distance(DBID id1, DBID id2) Returns the distance between the two objects specified by their objects ids.
FloatDistance	FileBasedFloatDistanceFunction.distance(DBID id1, DBID id2) Returns the distance between the two objects specified by their objects ids.
DoubleDistance	DiskCacheBasedDoubleDistanceFunction.distance(DBID id1, DBID id2) Returns the distance between the two objects specified by their objects ids.
FloatDistance	DiskCacheBasedFloatDistanceFunction.distance(DBID id1, DBID id2) Returns the distance between the two objects specified by their objects ids.

Uses of DBID in de.lmu.ifi.dbs.elki.distance.distancefunction.subspace

Methods in de.lmu.ifi.dbs.elki.distance.distancefunction.subspace with parameters of type DBID

PreferenceVectorBasedCorrelationDistance	AbstractPreferenceVectorBasedCorrelationDistanceFunction.Instance.distance(DBID id1, DBID id2)
SubspaceDistance	SubspaceDistanceFunction.Instance.distance(DBID id1, DBID id2) Note, that the pca of o1 must have equal ore more strong eigenvectors than the pca of o2.
double	AbstractPreferenceVectorBasedCorrelationDistanceFunction.Instance.weightedDistance(DBID id1, DBID id2, BitSet weightVector) Computes the weighted distance between the two specified vectors according to the given preference vector.
double	AbstractPreferenceVectorBasedCorrelationDistanceFunction.Instance.weightedPrefereneceVectorDistance(DBID id1, DBID id2) Computes the weighted distance between the two specified data vectors according to their preference vectors.

Uses of DBID in de.lmu.ifi.dbs.elki.distance.similarityfunction

Fields in de.lmu.ifi.dbs.elki.distance.similarityfunction with type parameters of type DBID

protected Relation<? extends DBID>

AbstractDBIDSimilarityFunction.database The database we work on

Methods in de.lmu.ifi.dbs.elki.distance.similarityfunction with parameters of type DBID

D	DBIDSimilarityFunction.similarity(DBID id1, DBID id2) Computes the similarity between two given DatabaseObjects according to this similarity function.
DoubleDistance	FractionalSharedNearestNeighborSimilarityFunction.Instance.similarity(DBID id1, DBID id2)
IntegerDistance	SharedNearestNeighborSimilarityFunction.Instance.similarity(DBID id1, DBID id2)

Constructor parameters in de.lmu.ifi.dbs.elki.distance.similarityfunction with type arguments of type DBID

AbstractDBIDSimilarityFunction(Relation<? extends DBID> database)
Constructor.

Uses of DBID in de.lmu.ifi.dbs.elki.evaluation.roc

Fields in de.lmu.ifi.dbs.elki.evaluation.roc with type parameters of type DBID

private Iterator<DBID>	ROC.SimpleAdapter.iter Original Iterator
private Iterator<DBID>	ROC.OutlierScoreAdapter.iter Original Iterator

Methods in de.lmu.ifi.dbs.elki.evaluation.roc that return types with arguments of type DBID

private Iterator<DBID>	ComputeROCCurve.getDBIDIterator(IterableResult<?> ir) Wrap the uncheckable cast with the manual check.
Pair<D,DBID>	ROC.DistanceResultAdapter.next()
DoubleObjPair<DBID>	ROC.OutlierScoreAdapter.next()

Method parameters in de.lmu.ifi.dbs.elki.evaluation.roc with type arguments of type DBID

private ComputeROCCurve.ROCResult

ComputeROCCurve.computeROCResult(int size, SetDBIDs positiveids, Iterator<DBID> iter)

Constructor parameters in de.lmu.ifi.dbs.elki.evaluation.roc with type arguments of type DBID

ROC.SimpleAdapter(Iterator<DBID> iter)
Constructor

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

Methods in de.lmu.ifi.dbs.elki.evaluation.similaritymatrix that return types with arguments of type DBID

private Iterator<DBID>

ComputeSimilarityMatrixImage.getDBIDIterator(IterableResult<?> ir) Wrap the uncheckable cast with the manual check.

Method parameters in de.lmu.ifi.dbs.elki.evaluation.similaritymatrix with type arguments of type DBID

private ComputeSimilarityMatrixImage.SimilarityMatrix

ComputeSimilarityMatrixImage.computeSimilarityMatrixImage(Relation<O> relation, Iterator<DBID> iter) Compute the actual similarity image.

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

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

boolean	AbstractIndex.delete(DBID id)
boolean	Index.delete(DBID id) Deletes the specified object from this index.
void	AbstractIndex.insert(DBID id)
void	Index.insert(DBID id) Inserts the specified object into this index.

Uses of DBID in de.lmu.ifi.dbs.elki.index.preprocessed

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

P	LocalProjectionIndex.getLocalProjection(DBID objid) Get the precomputed local projection for a particular object ID.

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

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

boolean	MaterializeKNNPreprocessor.delete(DBID id)
List<DistanceResultPair<D>>	MaterializeKNNPreprocessor.get(DBID objid) Get the k nearest neighbors.
List<DistanceResultPair<D>>	MaterializeKNNAndRKNNPreprocessor.getKNN(DBID id) Returns the materialized kNNs of the specified id.
List<DistanceResultPair<D>>	MaterializeKNNAndRKNNPreprocessor.getRKNN(DBID id) Returns the materialized RkNNs of the specified id.
void	MaterializeKNNPreprocessor.insert(DBID id)

Uses of DBID in de.lmu.ifi.dbs.elki.index.preprocessed.localpca

Methods in de.lmu.ifi.dbs.elki.index.preprocessed.localpca with parameters of type DBID

PCAFilteredResult	AbstractFilteredPCAIndex.getLocalProjection(DBID objid)
PCAFilteredResult	FilteredLocalPCAIndex.getLocalProjection(DBID objid) Get the precomputed local PCA for a particular object ID.
protected abstract List<DistanceResultPair<DoubleDistance>>	AbstractFilteredPCAIndex.objectsForPCA(DBID id) Returns the objects to be considered within the PCA for the specified query object.
protected List<DistanceResultPair<DoubleDistance>>	KNNQueryFilteredPCAIndex.objectsForPCA(DBID id)
protected List<DistanceResultPair<DoubleDistance>>	RangeQueryFilteredPCAIndex.objectsForPCA(DBID id)

Uses of DBID in de.lmu.ifi.dbs.elki.index.preprocessed.preference

Methods in de.lmu.ifi.dbs.elki.index.preprocessed.preference with parameters of type DBID

private BitSet	HiSCPreferenceVectorIndex.determinePreferenceVector(Relation<V> relation, DBID id, DBIDs neighborIDs, StringBuffer msg) Determines the preference vector according to the specified neighbor ids.
BitSet	AbstractPreferenceVectorIndex.getPreferenceVector(DBID objid)
BitSet	PreferenceVectorIndex.getPreferenceVector(DBID objid) Get the precomputed preference vector for a particular object ID.

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

Methods in de.lmu.ifi.dbs.elki.index.preprocessed.snn with parameters of type DBID

TreeSetDBIDs	SharedNearestNeighborIndex.getNearestNeighborSet(DBID objid) Get the precomputed nearest neighbors
TreeSetDBIDs	SharedNearestNeighborPreprocessor.getNearestNeighborSet(DBID objid)

Uses of DBID in de.lmu.ifi.dbs.elki.index.preprocessed.subspaceproj

Methods in de.lmu.ifi.dbs.elki.index.preprocessed.subspaceproj with parameters of type DBID

protected abstract P	AbstractSubspaceProjectionIndex.computeProjection(DBID id, List<DistanceResultPair<D>> neighbors, Relation<NV> relation) This method implements the type of variance analysis to be computed for a given point.
protected SubspaceProjectionResult	PreDeConSubspaceIndex.computeProjection(DBID id, List<DistanceResultPair<D>> neighbors, Relation<V> database)
protected PCAFilteredResult	FourCSubspaceIndex.computeProjection(DBID id, List<DistanceResultPair<D>> neighbors, Relation<V> database)
P	SubspaceProjectionIndex.getLocalProjection(DBID objid) Get the precomputed local subspace for a particular object ID.
P	AbstractSubspaceProjectionIndex.getLocalProjection(DBID objid)

Uses of DBID in de.lmu.ifi.dbs.elki.index.tree

Fields in de.lmu.ifi.dbs.elki.index.tree declared as DBID

private DBID

AbstractLeafEntry.id Holds the id of the object (node or data object) represented by this entry.

Methods in de.lmu.ifi.dbs.elki.index.tree that return DBID

DBID	AbstractLeafEntry.getDBID()
DBID	LeafEntry.getDBID() Get the DBID of this leaf entry.

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

AbstractLeafEntry(DBID id)
Provides a new AbstractEntry with the specified id.

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

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

private DBID

MTreeDirectoryEntry.routingObjectID The id of routing object of this entry.

Methods in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants that return DBID

DBID	MTreeEntry.getRoutingObjectID() Returns the id of the underlying database object of this entry, if this entry is a leaf entry, the id of the routing object, otherwise.
DBID	MTreeDirectoryEntry.getRoutingObjectID() Returns the id of the routing object of this entry.
DBID	MTreeLeafEntry.getRoutingObjectID() Returns the id of the underlying data object of this entry.

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

void	AbstractMTreeNode.adjustEntry(E entry, DBID routingObjectID, D parentDistance, AbstractMTree<O,D,N,E> mTree) Adjusts the parameters of the entry representing this node (e.g. after insertion of new objects).
D	AbstractMTreeNode.coveringRadius(DBID routingObjectID, AbstractMTree<O,D,N,E> mTree) Determines and returns the covering radius of this node.
protected abstract E	AbstractMTree.createNewDirectoryEntry(N node, DBID routingObjectID, D parentDistance) Creates a new directory entry representing the specified node.
private IndexTreePath<E>	AbstractMTree.createNewRoot(N oldRoot, N newNode, DBID firstRoutingObjectID, DBID secondRoutingObjectID) Creates a new root node that points to the two specified child nodes and return the path to the new root.
protected D	AbstractMTree.distance(DBID id1, DBID id2) Returns the distance between the two specified ids.
protected D	AbstractMTree.distance(DBID id1, O o2) Returns the distance between the given object and the id.
protected void	AbstractMTree.doKNNQuery(DBID q, KNNHeap<D> knnList) Performs a k-nearest neighbor query for the given FeatureVector with the given parameter k and the according distance function.
protected List<DistanceEntry<D,E>>	AbstractMTree.getSortedEntries(N node, DBID q) Sorts the entries of the specified node according to their minimum distance to the specified object.
void	MTreeEntry.setRoutingObjectID(DBID objectID) Sets the id of the underlying database object of this entry, if this entry is a leaf entry, the id of the routing object, otherwise.
void	MTreeDirectoryEntry.setRoutingObjectID(DBID objectID) Sets the id of the routing object of this entry.
void	MTreeLeafEntry.setRoutingObjectID(DBID objectID) todo ok

Method parameters in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants with type arguments of type DBID

protected void

AbstractMTree.batchNN(N node, DBIDs ids, Map<DBID,KNNHeap<D>> knnLists) Deprecated. Change to use by-object NN lookups instead.

Constructors in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants with parameters of type DBID

MTreeDirectoryEntry(DBID objectID, D parentDistance, Integer nodeID, D coveringRadius)
Provides a new MTreeDirectoryEntry with the given parameters.

MTreeLeafEntry(DBID objectID, D parentDistance)
Provides a new MTreeLeafEntry object with the given parameters.

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

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

abstract List<DistanceResultPair<D>>

AbstractMkTree.reverseKNNQuery(DBID id, int k) Performs a reverse k-nearest neighbor query for the given object ID.

Method parameters in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees with type arguments of type DBID

protected abstract void

AbstractMkTreeUnified.kNNdistanceAdjustment(E entry, Map<DBID,KNNHeap<D>> knnLists) Performs a distance adjustment in the subtree of the specified root entry.

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

Methods in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkapp with parameters of type DBID

void	MkAppTreeNode.adjustEntry(MkAppEntry<D> entry, DBID routingObjectID, D parentDistance, AbstractMTree<O,D,MkAppTreeNode<O,D>,MkAppEntry<D>> mTree) Adjusts the parameters of the entry representing this node.
protected MkAppEntry<D>	MkAppTree.createNewDirectoryEntry(MkAppTreeNode<O,D> node, DBID routingObjectID, D parentDistance) Creates a new directory entry representing the specified node.
protected MkAppEntry<D>	MkAppTreeIndex.createNewLeafEntry(DBID id, O object, D parentDistance) Creates a new leaf entry representing the specified data object in the specified subtree.
boolean	MkAppTreeIndex.delete(DBID id) Throws an UnsupportedOperationException since deletion of objects is not yet supported by an M-Tree.
private List<DistanceResultPair<D>>	MkAppTree.doReverseKNNQuery(int k, DBID q) Performs a reverse knn query.
void	MkAppTreeIndex.insert(DBID id)
List<DistanceResultPair<D>>	MkAppTree.reverseKNNQuery(DBID id, int k) Performs a reverse k-nearest neighbor query for the given object ID.

Method parameters in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkapp with type arguments of type DBID

private void	MkAppTree.adjustApproximatedKNNDistances(MkAppEntry<D> entry, Map<DBID,KNNList<D>> knnLists) Adjusts the knn distance in the subtree of the specified root entry.
private List<D>	MkAppTree.getMeanKNNList(DBIDs ids, Map<DBID,KNNList<D>> knnLists)

Constructors in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkapp with parameters of type DBID

MkAppDirectoryEntry(DBID objectID, D parentDistance, Integer nodeID, D coveringRadius, PolynomialApproximation approximation)
Provides a new MkCoPDirectoryEntry with the given parameters.

MkAppLeafEntry(DBID objectID, D parentDistance, PolynomialApproximation approximation)
Provides a new MkAppLeafEntry with the given parameters.

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

Methods in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop with parameters of type DBID

void	MkCoPTreeNode.adjustEntry(MkCoPEntry<D> entry, DBID routingObjectID, D parentDistance, AbstractMTree<O,D,MkCoPTreeNode<O,D>,MkCoPEntry<D>> mTree)
protected MkCoPEntry<D>	MkCoPTree.createNewDirectoryEntry(MkCoPTreeNode<O,D> node, DBID routingObjectID, D parentDistance) Creates a new directory entry representing the specified node.
protected MkCoPEntry<D>	MkCoPTreeIndex.createNewLeafEntry(DBID id, O object, D parentDistance) Creates a new leaf entry representing the specified data object in the specified subtree.
boolean	MkCoPTreeIndex.delete(DBID id) Throws an UnsupportedOperationException since deletion of objects is not yet supported by an M-Tree.
private void	MkCoPTree.doReverseKNNQuery(int k, DBID q, List<DistanceResultPair<D>> result, ModifiableDBIDs candidates) Performs a reverse knn query.
void	MkCoPTreeIndex.insert(DBID id)
List<DistanceResultPair<D>>	MkCoPTree.reverseKNNQuery(DBID id, int k) Performs a reverse k-nearest neighbor query for the given object ID.

Method parameters in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop with type arguments of type DBID

private void

MkCoPTree.adjustApproximatedKNNDistances(MkCoPEntry<D> entry, Map<DBID,KNNList<D>> knnLists) Adjusts the knn distance in the subtree of the specified root entry.

Constructors in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop with parameters of type DBID

MkCoPDirectoryEntry(DBID objectID, D parentDistance, Integer nodeID, D coveringRadius, ApproximationLine conservativeApproximation)
Provides a new MkCoPDirectoryEntry with the given parameters.

MkCoPLeafEntry(DBID objectID, D parentDistance, ApproximationLine conservativeApproximation, ApproximationLine progressiveApproximation)
Provides a new MkCoPLeafEntry with the given parameters.

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

Methods in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkmax with parameters of type DBID

void	MkMaxTreeNode.adjustEntry(MkMaxEntry<D> entry, DBID routingObjectID, D parentDistance, AbstractMTree<O,D,MkMaxTreeNode<O,D>,MkMaxEntry<D>> mTree) Calls the super method and adjust additionally the k-nearest neighbor distance of this node as the maximum of the k-nearest neighbor distances of all its entries.
protected MkMaxEntry<D>	MkMaxTree.createNewDirectoryEntry(MkMaxTreeNode<O,D> node, DBID routingObjectID, D parentDistance)
protected MkMaxLeafEntry<D>	MkMaxTreeIndex.createNewLeafEntry(DBID id, O object, D parentDistance)
boolean	MkMaxTreeIndex.delete(DBID id) Throws an UnsupportedOperationException since deletion of objects is not yet supported by an M-Tree.
private void	MkMaxTree.doReverseKNNQuery(DBID q, MkMaxTreeNode<O,D> node, MkMaxEntry<D> node_entry, List<DistanceResultPair<D>> result) Performs a reverse k-nearest neighbor query in the specified subtree for the given query object with k = AbstractMkTreeUnified.k_max.
void	MkMaxTreeIndex.insert(DBID id)
List<DistanceResultPair<D>>	MkMaxTree.reverseKNNQuery(DBID id, int k) Performs a reverse k-nearest neighbor query for the given object ID.

Method parameters in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkmax with type arguments of type DBID

protected void

MkMaxTree.kNNdistanceAdjustment(MkMaxEntry<D> entry, Map<DBID,KNNHeap<D>> knnLists) Adjusts the knn distance in the subtree of the specified root entry.

Constructors in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkmax with parameters of type DBID

MkMaxDirectoryEntry(DBID objectID, D parentDistance, Integer nodeID, D coveringRadius, D knnDistance)
Provides a new MkMaxDirectoryEntry with the given parameters.

MkMaxLeafEntry(DBID objectID, D parentDistance, D knnDistance)
Provides a new MkMaxLeafEntry with the given parameters.

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

Methods in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mktab with parameters of type DBID

void	MkTabTreeNode.adjustEntry(MkTabEntry<D> entry, DBID routingObjectID, D parentDistance, AbstractMTree<O,D,MkTabTreeNode<O,D>,MkTabEntry<D>> mTree)
protected MkTabEntry<D>	MkTabTree.createNewDirectoryEntry(MkTabTreeNode<O,D> node, DBID routingObjectID, D parentDistance) Creates a new directory entry representing the specified node.
protected MkTabEntry<D>	MkTabTreeIndex.createNewLeafEntry(DBID id, O object, D parentDistance) Creates a new leaf entry representing the specified data object in the specified subtree.
boolean	MkTabTreeIndex.delete(DBID id) Throws an UnsupportedOperationException since deletion of objects is not yet supported by an M-Tree.
private void	MkTabTree.doReverseKNNQuery(int k, DBID q, MkTabEntry<D> node_entry, MkTabTreeNode<O,D> node, List<DistanceResultPair<D>> result) Performs a k-nearest neighbor query in the specified subtree for the given query object and the given parameter k.
void	MkTabTreeIndex.insert(DBID id)
List<DistanceResultPair<D>>	MkTabTree.reverseKNNQuery(DBID id, int k)

Method parameters in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mktab with type arguments of type DBID

protected void

MkTabTree.kNNdistanceAdjustment(MkTabEntry<D> entry, Map<DBID,KNNHeap<D>> knnLists)

Constructors in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mktab with parameters of type DBID

MkTabDirectoryEntry(DBID objectID, D parentDistance, Integer nodeID, D coveringRadius, List<D> knnDistances)
Provides a new MkMaxDirectoryEntry with the given parameters.

MkTabLeafEntry(DBID objectID, D parentDistance, List<D> knnDistances)
Provides a new MkMaxLeafEntry with the given parameters.

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

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

protected MTreeEntry<D>	MTree.createNewDirectoryEntry(MTreeNode<O,D> node, DBID routingObjectID, D parentDistance)
protected MTreeEntry<D>	MTreeIndex.createNewLeafEntry(DBID id, O object, D parentDistance)
boolean	MTreeIndex.delete(DBID id) Throws an UnsupportedOperationException since deletion of objects is not yet supported by an M-Tree.
void	MTreeIndex.insert(DBID id)

Uses of DBID 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 DBID

private void	MetricalIndexRangeQuery.doRangeQuery(DBID o_p, AbstractMTreeNode<O,D,?,?> node, DBID q, D r_q, List<DistanceResultPair<D>> result) Performs a range query on the specified subtree.
private void	MetricalIndexRangeQuery.doRangeQuery(DBID o_p, AbstractMTreeNode<O,D,?,?> node, O q, D r_q, List<DistanceResultPair<D>> result) Performs a range query on the specified subtree.
List<DistanceResultPair<D>>	MetricalIndexKNNQuery.getKNNForDBID(DBID id, int k)
List<DistanceResultPair<D>>	MetricalIndexRangeQuery.getRangeForDBID(DBID id, D range)
List<DistanceResultPair<D>>	MkTreeRKNNQuery.getRKNNForDBID(DBID id, int k)

Method parameters in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.query with type arguments of type DBID

void	MetricalIndexKNNQuery.getKNNForBulkHeaps(Map<DBID,KNNHeap<D>> heaps)

Uses of DBID in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.split

Fields in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.split declared as DBID

private DBID	Assignments.id1 The id of the first routing object.
private DBID	Assignments.id2 The id of the second routing object.

Methods in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.split that return DBID

DBID	Assignments.getFirstRoutingObject() Returns the id of the first routing object.
DBID	Assignments.getSecondRoutingObject() Returns the id of the second routing object.

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

(package private) Assignments<D,E>

MTreeSplit.balancedPartition(N node, DBID routingObject1, DBID routingObject2, DistanceQuery<O,D> distanceFunction) Creates a balanced partition of the entries of the specified node.

Constructors in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.split with parameters of type DBID

Assignments(DBID id1, DBID id2, D firstCoveringRadius, D secondCoveringRadius, Set<E> firstAssignments, Set<E> secondAssignments)
Provides an assignment during a split of an MTree node.

Uses of DBID in de.lmu.ifi.dbs.elki.index.tree.query

Fields in de.lmu.ifi.dbs.elki.index.tree.query declared as DBID

DBID	GenericMTreeDistanceSearchCandidate.routingObjectID The id of the routing object.

Constructors in de.lmu.ifi.dbs.elki.index.tree.query with parameters of type DBID

GenericMTreeDistanceSearchCandidate(D mindist, Integer nodeID, DBID routingObjectID)
Creates a new heap node with the specified parameters.

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

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

SpatialPointLeafEntry(DBID id, double[] values)
Constructs a new LeafEntry object with the given parameters.

SpatialPointLeafEntry(DBID id, NumberVector<?,?> vector)
Constructor from number vector

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

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

protected IndexTreePath<E>

AbstractRStarTree.findPathToObject(IndexTreePath<E> subtree, SpatialComparable mbr, DBID id) Returns the path to the leaf entry in the specified subtree that represents the data object with the specified mbr and id.

Uses of DBID in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu

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

protected DeLiCluLeafEntry	DeLiCluTreeIndex.createNewLeafEntry(DBID id) Creates a new leaf entry representing the specified data object.
boolean	DeLiCluTreeIndex.delete(DBID id) Deletes the specified object from this index.
void	DeLiCluTreeIndex.insert(DBID id) Inserts the specified real vector object into this index.
List<TreeIndexPathComponent<DeLiCluEntry>>	DeLiCluTreeIndex.setHandled(DBID id, O obj) Marks the specified object as handled and returns the path of node ids from the root to the objects's parent.

Constructors in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu with parameters of type DBID

DeLiCluLeafEntry(DBID id, NumberVector<?,?> vector)
Constructs a new LeafEntry object with the given parameters.

Uses of DBID 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 DBID

List<DistanceResultPair<DoubleDistance>>	DoubleDistanceRStarTreeKNNQuery.getKNNForDBID(DBID id, int k)
List<DistanceResultPair<D>>	GenericRStarTreeKNNQuery.getKNNForDBID(DBID id, int k)
List<DistanceResultPair<D>>	GenericRStarTreeRangeQuery.getRangeForDBID(DBID id, D range)
List<DistanceResultPair<DoubleDistance>>	DoubleDistanceRStarTreeRangeQuery.getRangeForDBID(DBID id, DoubleDistance range)

Method parameters in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.query with type arguments of type DBID

protected void	GenericRStarTreeKNNQuery.batchNN(AbstractRStarTreeNode<?,?> node, Map<DBID,KNNHeap<D>> knnLists) Performs a batch knn query.
protected void	DoubleDistanceRStarTreeKNNQuery.batchNN(AbstractRStarTreeNode<?,?> node, Map<DBID,KNNHeap<DoubleDistance>> knnLists) Performs a batch knn query.
void	GenericRStarTreeKNNQuery.getKNNForBulkHeaps(Map<DBID,KNNHeap<D>> heaps)
void	DoubleDistanceRStarTreeKNNQuery.getKNNForBulkHeaps(Map<DBID,KNNHeap<DoubleDistance>> heaps)

Uses of DBID in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rstar

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

protected SpatialPointLeafEntry	RStarTreeIndex.createNewLeafEntry(DBID id) Create a new leaf entry.
boolean	RStarTreeIndex.delete(DBID id) Deletes the specified object from this index.
void	RStarTreeIndex.insert(DBID id) Inserts the specified reel vector object into this index.

Uses of DBID in de.lmu.ifi.dbs.elki.math.linearalgebra

Method parameters in de.lmu.ifi.dbs.elki.math.linearalgebra with type arguments of type DBID

static ProjectedCentroid	ProjectedCentroid.make(BitSet dims, Relation<? extends NumberVector<?,?>> relation, Iterable<DBID> ids) Static Constructor from a relation.
static Centroid	Centroid.make(Relation<? extends NumberVector<?,?>> relation, Iterable<DBID> ids) Static constructor from an existing relation.
static CovarianceMatrix	CovarianceMatrix.make(Relation<? extends NumberVector<?,?>> relation, Iterable<DBID> ids) Static Constructor from a full relation.

Uses of DBID in de.lmu.ifi.dbs.elki.result

Methods in de.lmu.ifi.dbs.elki.result that return types with arguments of type DBID

IterableIterator<DBID>	OrderingFromDataStore.iter(DBIDs ids)
IterableIterator<DBID>	OrderingResult.iter(DBIDs ids) Sort the given ids according to this ordering and return an iterator.

Methods in de.lmu.ifi.dbs.elki.result with parameters of type DBID

int	OrderingFromDataStore.ImpliedComparator.compare(DBID id1, DBID id2)
int	OrderingFromDataStore.DerivedComparator.compare(DBID id1, DBID id2)
private StringBuffer	KMLOutputHandler.makeDescription(Collection<Relation<?>> relations, DBID id) Make an HTML description.

Uses of DBID in de.lmu.ifi.dbs.elki.result.optics

Fields in de.lmu.ifi.dbs.elki.result.optics declared as DBID

private DBID	GenericClusterOrderEntry.objectID The id of the entry.
private DBID	DoubleDistanceClusterOrderEntry.objectID The id of the entry.
private DBID	GenericClusterOrderEntry.predecessorID The id of the entry's predecessor.
private DBID	DoubleDistanceClusterOrderEntry.predecessorID The id of the entry's predecessor.

Fields in de.lmu.ifi.dbs.elki.result.optics with type parameters of type DBID

private HashMap<DBID,ClusterOrderEntry<D>>	ClusterOrderResult.map Map of object IDs to their cluster order entry
private HashMap<DBID,ClusterOrderEntry<D>>	ClusterOrderResult.ReachabilityDistanceAdapter.map Access reference.
private HashMap<DBID,ClusterOrderEntry<D>>	ClusterOrderResult.PredecessorAdapter.map Access reference.

Methods in de.lmu.ifi.dbs.elki.result.optics that return DBID

DBID	ClusterOrderResult.PredecessorAdapter.get(DBID objID)
DBID	GenericClusterOrderEntry.getID() Returns the object id of this entry.
DBID	DoubleDistanceClusterOrderEntry.getID() Returns the object id of this entry.
DBID	ClusterOrderEntry.getID() Returns the object id of this entry.
DBID	GenericClusterOrderEntry.getPredecessorID() Returns the id of the predecessor of this entry if this entry has a predecessor, null otherwise.
DBID	DoubleDistanceClusterOrderEntry.getPredecessorID() Returns the id of the predecessor of this entry if this entry has a predecessor, null otherwise.
DBID	ClusterOrderEntry.getPredecessorID() Returns the id of the predecessor of this entry if this entry has a predecessor, null otherwise.

Methods in de.lmu.ifi.dbs.elki.result.optics that return types with arguments of type DBID

SimpleTypeInformation<DBID>	ClusterOrderResult.PredecessorAdapter.getDataTypeInformation()
IterableIterator<DBID>	ClusterOrderResult.ClusterOrderAdapter.iter(DBIDs ids) Use the cluster order to sort the given collection ids.
IterableIterator<DBID>	ClusterOrderResult.ReachabilityDistanceAdapter.iterDBIDs()
IterableIterator<DBID>	ClusterOrderResult.PredecessorAdapter.iterDBIDs()

Methods in de.lmu.ifi.dbs.elki.result.optics with parameters of type DBID

void	ClusterOrderResult.add(DBID id, DBID predecessor, D reachability) Add an object to the cluster order.
void	ClusterOrderResult.ReachabilityDistanceAdapter.delete(DBID id)
void	ClusterOrderResult.PredecessorAdapter.delete(DBID id)
D	ClusterOrderResult.ReachabilityDistanceAdapter.get(DBID objID)
DBID	ClusterOrderResult.PredecessorAdapter.get(DBID objID)
void	ClusterOrderResult.ReachabilityDistanceAdapter.set(DBID id, D val)
void	ClusterOrderResult.PredecessorAdapter.set(DBID id, DBID val)

Constructors in de.lmu.ifi.dbs.elki.result.optics with parameters of type DBID

DoubleDistanceClusterOrderEntry(DBID objectID, DBID predecessorID, double reachability)
Creates a new entry in a cluster order with the specified parameters.

GenericClusterOrderEntry(DBID objectID, DBID predecessorID, D reachability)
Creates a new entry in a cluster order with the specified parameters.

Constructor parameters in de.lmu.ifi.dbs.elki.result.optics with type arguments of type DBID

ClusterOrderResult.PredecessorAdapter(HashMap<DBID,ClusterOrderEntry<D>> map, DBIDs dbids)
Constructor.

ClusterOrderResult.ReachabilityDistanceAdapter(HashMap<DBID,ClusterOrderEntry<D>> map, DBIDs dbids)
Constructor.

Uses of DBID in de.lmu.ifi.dbs.elki.result.outlier

Methods in de.lmu.ifi.dbs.elki.result.outlier that return types with arguments of type DBID

IterableIterator<DBID>

OrderingFromRelation.iter(DBIDs ids)

Methods in de.lmu.ifi.dbs.elki.result.outlier with parameters of type DBID

int	OrderingFromRelation.ImpliedComparator.compare(DBID id1, DBID id2)

Uses of DBID in de.lmu.ifi.dbs.elki.result.textwriter

Methods in de.lmu.ifi.dbs.elki.result.textwriter with parameters of type DBID

private void

TextWriter.printObject(TextWriterStream out, Database db, DBID objID, List<Relation<?>> ra)

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

Fields in de.lmu.ifi.dbs.elki.utilities with type parameters of type DBID

(package private) Iterator<DBID>

DatabaseUtil.RelationObjectIterator.iter The real iterator.

Constructor parameters in de.lmu.ifi.dbs.elki.utilities with type arguments of type DBID

DatabaseUtil.RelationObjectIterator(Iterator<DBID> iter, Relation<? extends O> database)
Full Constructor.

Uses of DBID in de.lmu.ifi.dbs.elki.utilities.datastructures.heap

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

DBID	KNNList.DBIDView.get(int i)
DBID	KNNList.DBIDItr.next()

Methods in de.lmu.ifi.dbs.elki.utilities.datastructures.heap that return types with arguments of type DBID

Collection<DBID>	KNNList.DBIDView.asCollection()
Iterator<DBID>	KNNList.DBIDView.iterator()

Methods in de.lmu.ifi.dbs.elki.utilities.datastructures.heap with parameters of type DBID

boolean

KNNHeap.add(D distance, DBID id) Add a distance-id pair to the heap unless the distance is too large.

Uses of DBID in de.lmu.ifi.dbs.elki.utilities.exceptions

Constructors in de.lmu.ifi.dbs.elki.utilities.exceptions with parameters of type DBID

ObjectNotFoundException(DBID id)
Object

Uses of DBID in de.lmu.ifi.dbs.elki.visualization.opticsplot

Fields in de.lmu.ifi.dbs.elki.visualization.opticsplot with type parameters of type DBID

private HashMap<DBID,Integer>

OPTICSColorFromClustering.idToColor The final mapping of object IDs to colors.

Uses of DBID in de.lmu.ifi.dbs.elki.visualization.visualizers.vis2d

Methods in de.lmu.ifi.dbs.elki.visualization.visualizers.vis2d with parameters of type DBID

protected Double	BubbleVisualization.getScaledForId(DBID id) Convenience method to apply scalings in the right order.
protected Element	TooltipScoreVisualization.makeTooltip(DBID id, double x, double y, double dotsize)
protected abstract Element	AbstractTooltipVisualization.makeTooltip(DBID id, double x, double y, double dotsize)
protected Element	TooltipStringVisualization.makeTooltip(DBID id, double x, double y, double dotsize)