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

Packages that use DBIDs

Package	Description
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.gdbscan	Generalized DBSCAN Generalized DBSCAN is an abstraction of the original DBSCAN idea, that allows the use of arbitrary "neighborhood" and "core point" predicates.
de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical	Hierarchical agglomerative clustering (HAC).
de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.birch	BIRCH clustering.
de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction	Extraction of partitional clusterings from hierarchical results.
de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans	K-means clustering and variations
de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization	Initialization strategies for k-means.
de.lmu.ifi.dbs.elki.algorithm.clustering.optics	OPTICS family of clustering algorithms.
de.lmu.ifi.dbs.elki.algorithm.clustering.subspace	Axis-parallel subspace clustering algorithms The clustering algorithms in this package are instances of both, projected clustering algorithms or subspace clustering algorithms according to the classical but somewhat obsolete classification schema of clustering algorithms for axis-parallel subspaces.
de.lmu.ifi.dbs.elki.algorithm.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.clustering.uncertain	Clustering algorithms for uncertain data.
de.lmu.ifi.dbs.elki.algorithm.itemsetmining	Algorithms for frequent itemset mining such as APRIORI.
de.lmu.ifi.dbs.elki.algorithm.outlier	Outlier detection algorithms
de.lmu.ifi.dbs.elki.algorithm.outlier.anglebased	Angle-based outlier detection algorithms.
de.lmu.ifi.dbs.elki.algorithm.outlier.intrinsic	Outlier detection algorithms based on intrinsic dimensionality.
de.lmu.ifi.dbs.elki.algorithm.outlier.lof	LOF family of outlier detection algorithms
de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood	Spatial outlier neighborhood classes
de.lmu.ifi.dbs.elki.algorithm.outlier.subspace	Subspace outlier detection methods Methods that detect outliers in subspaces (projections) of the data set.
de.lmu.ifi.dbs.elki.application.greedyensemble	Greedy ensembles for outlier detection.
de.lmu.ifi.dbs.elki.data	Basic classes for different data types, database object types and label types
de.lmu.ifi.dbs.elki.data.model	Cluster models classes for various algorithms
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.integer	Integer-based DBID implementation -- do not use directly - always use DBIDUtil.
de.lmu.ifi.dbs.elki.database.relation	Relations, materialized and virtual (views)
de.lmu.ifi.dbs.elki.distance.distancefunction	Distance functions for use within ELKI.
de.lmu.ifi.dbs.elki.distance.similarityfunction	Similarity functions
de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel	Kernel functions.
de.lmu.ifi.dbs.elki.evaluation.clustering.pairsegments	Pair-segment analysis of multiple clusterings
de.lmu.ifi.dbs.elki.evaluation.outlier	Evaluate an outlier score using a misclassification based cost model
de.lmu.ifi.dbs.elki.evaluation.scores	Evaluation of rankings and scorings
de.lmu.ifi.dbs.elki.evaluation.scores.adapter	Adapter classes for ranking and scoring measures.
de.lmu.ifi.dbs.elki.index	Index structure implementations
de.lmu.ifi.dbs.elki.index.lsh	Locality Sensitive Hashing
de.lmu.ifi.dbs.elki.index.preprocessed.fastoptics	Preprocessed index used by the FastOPTICS algorithm.
de.lmu.ifi.dbs.elki.index.preprocessed.knn	Indexes providing KNN and rKNN data.
de.lmu.ifi.dbs.elki.index.preprocessed.preference	Indexes storing preference vectors
de.lmu.ifi.dbs.elki.index.tree.metrical.covertree	Cover-tree variations.
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.mkmax	MkMaxTree
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mtree	MTree
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu	DeLiCluTree
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.flat	FlatRStarTree
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.query	Queries on the R-Tree family of indexes: kNN and range queries
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn	RdKNNTree
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rstar	RStarTree
de.lmu.ifi.dbs.elki.math.linearalgebra	The linear algebra package provides classes and computational methods for operations on matrices and vectors.
de.lmu.ifi.dbs.elki.math.linearalgebra.pca	Principal Component Analysis (PCA) and Eigenvector processing
de.lmu.ifi.dbs.elki.math.spacefillingcurves	Space filling curves
de.lmu.ifi.dbs.elki.parallel	Parallel processing core for ELKI.
de.lmu.ifi.dbs.elki.result	Result types, representation and handling
de.lmu.ifi.dbs.elki.result.outlier	Outlier result classes
de.lmu.ifi.dbs.elki.utilities.datastructures.unionfind	Union-find data structures.
de.lmu.ifi.dbs.elki.visualization.style	Style management for ELKI visualizations
de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection	Visualizers for object selection based on 2D projections
tutorial.clustering	Classes from the tutorial on implementing a custom k-means variation

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

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

Modifier and Type	Method and Description
CorrelationAnalysisSolution<V>	DependencyDerivator.generateModel(Relation<V> db, DBIDs ids) Runs the pca on the given set of IDs.
CorrelationAnalysisSolution<V>	DependencyDerivator.generateModel(Relation<V> relation, DBIDs ids, double[] centroid) Runs the pca on the given set of IDs and for the given centroid.
WritableDataStore<KNNList>	KNNJoin.run(Relation<V> relation, DBIDs ids) Inner run method.
WritableDataStore<KNNList>	KNNJoin.run(SpatialIndexTree<N,E> index, DBIDs ids) Inner run method.

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

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

Modifier and Type	Method and Description
static ArrayModifiableDBIDs[]	ClusteringAlgorithmUtil.partitionsFromIntegerLabels(DBIDs ids, IntegerDataStore assignment, int k) Collect clusters from their [0;k-1] integer labels.

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

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

Modifier and Type	Method and Description
private MaterializedRelation<ParameterizationFunction>	CASH.buildDB(int dim, double[][] basis, DBIDs ids, Relation<ParameterizationFunction> relation) Builds a dim-1 dimensional database where the objects are projected into the specified subspace.
private Database	CASH.buildDerivatorDB(Relation<ParameterizationFunction> relation, DBIDs ids) Builds a database for the derivator consisting of the ids in the specified interval.
private LMCLUS.Separation	LMCLUS.findSeparation(Relation<NumberVector> relation, DBIDs currentids, int dimension, java.util.Random r) This method samples a number of linear manifolds an tries to determine which the one with the best cluster is.
private void	CASH.initHeap(ObjectHeap<CASHInterval> heap, Relation<ParameterizationFunction> relation, int dim, DBIDs ids) Initializes the heap with the root intervals.
private LinearEquationSystem	CASH.runDerivator(Relation<ParameterizationFunction> relation, int dimensionality, DBIDs ids) Runs the derivator on the specified interval and assigns all points having a distance less then the standard deviation of the derivator model to the model to this model.

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

Methods in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.cash with parameters of type DBIDs

Modifier and Type	Method and Description
ModifiableDBIDs	CASHIntervalSplit.determineIDs(DBIDs superSetIDs, HyperBoundingBox interval, double d_min, double d_max) Determines the ids belonging to the given interval, i.e. the parameterization functions falling within the interval.
void	CASHInterval.removeIDs(DBIDs ids2) Removes the specified ids from this interval.

Uses of DBIDs in de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan

Classes in de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan that implement DBIDs

Modifier and Type	Class and Description
static class	COPACNeighborPredicate.COPACModel Model used by COPAC for core point property.

Fields in de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan declared as DBIDs

Modifier and Type	Field and Description
protected DBIDs	EpsilonNeighborPredicate.Instance.ids DBIDs to process
protected DBIDs	SimilarityNeighborPredicate.Instance.ids DBIDs to process
protected DBIDs	AbstractRangeQueryNeighborPredicate.Instance.ids DBIDs to process

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

Modifier and Type	Method and Description
DBIDs	EpsilonNeighborPredicate.Instance.getIDs()
DBIDs	SimilarityNeighborPredicate.Instance.getIDs()
DBIDs	NeighborPredicate.Instance.getIDs() Get the IDs the predicate is defined for.
DBIDs	AbstractRangeQueryNeighborPredicate.Instance.getIDs()
DBIDs	ERiCNeighborPredicate.Instance.getNeighbors(DBIDRef reference)

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

Modifier and Type	Method and Description
SimpleTypeInformation<DBIDs>	ERiCNeighborPredicate.getOutputType()

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

Modifier and Type	Method and Description
protected int	LSDBC.expandCluster(int clusterid, WritableIntegerDataStore clusterids, KNNQuery<O> knnq, DBIDs neighbors, double maxkdist, FiniteProgress progress) Set-based expand cluster implementation.
private void	LSDBC.fillDensities(KNNQuery<O> knnq, DBIDs ids, WritableDoubleDataStore dens) Collect all densities into an array for sorting.
boolean	MinPtsCorePredicate.Instance.isCorePoint(DBIDRef point, DBIDs neighbors)
private boolean	LSDBC.isLocalMaximum(double kdist, DBIDs neighbors, WritableDoubleDataStore kdists) Test if a point is a local density maximum.
DBIDIter	ERiCNeighborPredicate.Instance.iterDBIDs(DBIDs neighbors)

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

Modifier and Type	Method and Description
boolean	MinPtsCorePredicate.acceptsType(SimpleTypeInformation<? extends DBIDs> type)

Constructors in de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan with parameters of type DBIDs

Constructor and Description
Instance(DBIDs ids, DataStore<COPACNeighborPredicate.COPACModel> storage) Constructor.
Instance(DBIDs ids, DataStore<M> storage) Constructor.
Instance(DBIDs ids, DataStore<PCAFilteredResult> storage, Relation<? extends NumberVector> relation) Constructor.
Instance(DBIDs ids, DataStore<PreDeConNeighborPredicate.PreDeConModel> storage) Constructor.
Instance(DBIDs ids, DataStore<PreDeConNeighborPredicate.PreDeConModel> storage) Constructor.
Instance(double epsilon, RangeQuery<?> rq, DBIDs ids) Constructor.
Instance(double epsilon, RangeQuery<?> rq, DBIDs ids) Constructor.

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

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

Modifier and Type	Field and Description
(package private) DBIDs	PointerHierarchyRepresentationResult.ids The DBIDs in this result.
protected DBIDs	PointerHierarchyRepresentationBuilder.ids The DBIDs in this result.

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

Modifier and Type	Method and Description
DBIDs	PointerHierarchyRepresentationResult.getDBIDs() Get the clustered DBIDs.

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

Modifier and Type	Method and Description
protected WritableDoubleDataStore	AbstractHDBSCAN.computeCoreDists(DBIDs ids, KNNQuery<O> knnQ, int minPts) Compute the core distances for all objects.
private WritableIntegerDataStore	PointerHierarchyRepresentationResult.computeSubtreeSizes(DBIDs order) Compute the size of all subtrees.
private static double	MiniMax.findMax(DistanceQuery<?> dq, DBIDIter i, DBIDs cy, double maxDist, double minMaxDist) Find the maximum distance of one object to a set.
DBID	PointerPrototypeHierarchyRepresentationResult.findPrototype(DBIDs members) Extract the prototype of a given cluster.
private static double	MiniMax.findPrototype(DistanceQuery<?> dq, DBIDs cx, DBIDs cy, DBIDVar prototype, double minMaxDist) Find the prototypes.
private static double	MiniMax.findPrototypeSingleton(DistanceQuery<?> dq, DBIDs cx, DBIDRef cy, DBIDVar prototype) Find the prototypes.
private void	SLINKHDBSCANLinearMemory.step2(DBIDRef id, DBIDs processedIDs, DistanceQuery<? super O> distQuery, DoubleDataStore coredists, WritableDoubleDataStore m) Second step: Determine the pairwise distances from all objects in the pointer representation to the new object with the specified id.
private void	SLINKHDBSCANLinearMemory.step3(DBIDRef id, WritableDBIDDataStore pi, WritableDoubleDataStore lambda, DBIDs processedIDs, WritableDoubleDataStore m) Third step: Determine the values for P and L
private void	SLINKHDBSCANLinearMemory.step4(DBIDRef id, WritableDBIDDataStore pi, WritableDoubleDataStore lambda, DBIDs processedIDs) Fourth step: Actualize the clusters if necessary

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

Constructor and Description
MatrixParadigm(DBIDs ids) Constructor.
PointerDensityHierarchyRepresentationResult(DBIDs ids, DBIDDataStore parent, DoubleDataStore parentDistance, boolean isSquared, DoubleDataStore coreDistance) Constructor.
PointerHierarchyRepresentationBuilder(DBIDs ids, boolean isSquared) Constructor.
PointerHierarchyRepresentationResult(DBIDs ids, DBIDDataStore parent, DoubleDataStore parentDistance, boolean isSquared) Constructor.
PointerHierarchyRepresentationResult(DBIDs ids, DBIDDataStore parent, DoubleDataStore parentDistance, boolean isSquared, IntegerDataStore mergeOrder) Constructor.
PointerPrototypeHierarchyRepresentationResult(DBIDs ids, DBIDDataStore parent, DoubleDataStore parentDistance, boolean isSquared, DBIDDataStore prototypes) Constructor.
PointerPrototypeHierarchyRepresentationResult(DBIDs ids, DBIDDataStore parent, DoubleDataStore parentDistance, boolean isSquared, IntegerDataStore mergeOrder, DBIDDataStore prototypes) Constructor.

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

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

Modifier and Type	Method and Description
CFTree	CFTree.Factory.newTree(DBIDs ids, Relation<? extends NumberVector> relation) Make a new tree.

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

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

Modifier and Type	Method and Description
void	SimplifiedHierarchyExtraction.TempCluster.addDBIDs(DBIDs ids) Add new objects to the cluster.
protected Cluster<DendrogramModel>	SimplifiedHierarchyExtraction.Instance.makeCluster(DBIDRef lead, double depth, DBIDs members) Make the cluster for the given object
protected Cluster<DendrogramModel>	AbstractCutDendrogram.Instance.makeCluster(DBIDRef lead, double depth, DBIDs members) Make the cluster for the given object

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

Fields in de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans declared as DBIDs

Modifier and Type	Field and Description
(package private) DBIDs	KMedoidsPAM.Instance.ids Ids to process.
(package private) DBIDs	CLARANS.Assignment.ids Ids to process.

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

Modifier and Type	Method and Description
(package private) static DBIDs	CLARA.randomSample(DBIDs ids, int samplesize, java.util.Random rnd, DBIDs previous) Draw a random sample of the desired size.

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

Modifier and Type	Method and Description
(package private) static double	CLARA.assignRemainingToNearestCluster(ArrayDBIDs means, DBIDs ids, DBIDs rids, WritableIntegerDataStore assignment, DistanceQuery<?> distQ) Returns a list of clusters.
protected ArrayModifiableDBIDs	KMedoidsPAM.initialMedoids(DistanceQuery<V> distQ, DBIDs ids) Choose the initial medoids.
(package private) static DBIDs	CLARA.randomSample(DBIDs ids, int samplesize, java.util.Random rnd, DBIDs previous) Draw a random sample of the desired size.
protected void	KMedoidsFastPAM.run(DistanceQuery<V> distQ, DBIDs ids, ArrayModifiableDBIDs medoids, WritableIntegerDataStore assignment)
protected void	KMedoidsFastPAM1.run(DistanceQuery<V> distQ, DBIDs ids, ArrayModifiableDBIDs medoids, WritableIntegerDataStore assignment)
protected void	KMedoidsPAM.run(DistanceQuery<V> distQ, DBIDs ids, ArrayModifiableDBIDs medoids, WritableIntegerDataStore assignment) Run the main algorithm.
protected void	KMedoidsPAMReynolds.run(DistanceQuery<V> distQ, DBIDs ids, ArrayModifiableDBIDs medoids, WritableIntegerDataStore assignment)

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

Modifier and Type	Method and Description
private static double[][]	AbstractKMeans.denseMeans(java.util.List<? extends DBIDs> clusters, double[][] means, Relation<? extends NumberVector> relation) Returns the mean vectors of the given clusters in the given database.
protected static double[][]	AbstractKMeans.means(java.util.List<? extends DBIDs> clusters, double[][] means, Relation<? extends NumberVector> relation) Returns the mean vectors of the given clusters in the given database.
protected double[][]	KMediansLloyd.Instance.medians(java.util.List<? extends DBIDs> clusters, double[][] medians, Relation<? extends NumberVector> relation) Returns the median vectors of the given clusters in the given database.
private static double[][]	AbstractKMeans.sparseMeans(java.util.List<? extends DBIDs> clusters, double[][] means, Relation<? extends SparseNumberVector> relation) Returns the mean vectors of the given clusters in the given database.

Constructors in de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans with parameters of type DBIDs

Constructor and Description
Assignment(DistanceQuery<?> distQ, DBIDs ids, int k) Constructor.
Assignment(DistanceQuery<?> distQ, DBIDs ids, int k) Constructor.
Instance(DistanceQuery<?> distQ, DBIDs ids, WritableIntegerDataStore assignment) Constructor.
Instance(DistanceQuery<?> distQ, DBIDs ids, WritableIntegerDataStore assignment) Constructor.
Instance(DistanceQuery<?> distQ, DBIDs ids, WritableIntegerDataStore assignment) Constructor.
Instance(DistanceQuery<?> distQ, DBIDs ids, WritableIntegerDataStore assignment, double fasttol) Constructor.

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

Methods in de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization that return DBIDs

Modifier and Type	Method and Description
DBIDs	PAMInitialMeans.chooseInitialMedoids(int k, DBIDs ids, DistanceQuery<? super O> distQ)
DBIDs	FirstKInitialMeans.chooseInitialMedoids(int k, DBIDs ids, DistanceQuery<? super O> distanceFunction)
DBIDs	FarthestPointsInitialMeans.chooseInitialMedoids(int k, DBIDs ids, DistanceQuery<? super O> distQ)
DBIDs	ParkInitialMeans.chooseInitialMedoids(int k, DBIDs ids, DistanceQuery<? super O> distQ)
DBIDs	FarthestSumPointsInitialMeans.chooseInitialMedoids(int k, DBIDs ids, DistanceQuery<? super O> distQ)
DBIDs	LABInitialMeans.chooseInitialMedoids(int k, DBIDs ids, DistanceQuery<? super O> distQ)
DBIDs	KMeansPlusPlusInitialMeans.chooseInitialMedoids(int k, DBIDs ids, DistanceQuery<? super O> distQ)
DBIDs	RandomlyChosenInitialMeans.chooseInitialMedoids(int k, DBIDs ids, DistanceQuery<? super O> distanceFunction)
DBIDs	KMedoidsInitialization.chooseInitialMedoids(int k, DBIDs ids, DistanceQuery<? super V> distanceFunction) Choose initial means

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

Modifier and Type	Method and Description
DBIDs	PAMInitialMeans.chooseInitialMedoids(int k, DBIDs ids, DistanceQuery<? super O> distQ)
DBIDs	FirstKInitialMeans.chooseInitialMedoids(int k, DBIDs ids, DistanceQuery<? super O> distanceFunction)
DBIDs	FarthestPointsInitialMeans.chooseInitialMedoids(int k, DBIDs ids, DistanceQuery<? super O> distQ)
DBIDs	ParkInitialMeans.chooseInitialMedoids(int k, DBIDs ids, DistanceQuery<? super O> distQ)
DBIDs	FarthestSumPointsInitialMeans.chooseInitialMedoids(int k, DBIDs ids, DistanceQuery<? super O> distQ)
DBIDs	LABInitialMeans.chooseInitialMedoids(int k, DBIDs ids, DistanceQuery<? super O> distQ)
DBIDs	KMeansPlusPlusInitialMeans.chooseInitialMedoids(int k, DBIDs ids, DistanceQuery<? super O> distQ)
DBIDs	RandomlyChosenInitialMeans.chooseInitialMedoids(int k, DBIDs ids, DistanceQuery<? super O> distanceFunction)
DBIDs	KMedoidsInitialization.chooseInitialMedoids(int k, DBIDs ids, DistanceQuery<? super V> distanceFunction) Choose initial means
(package private) static void	KMeansPlusPlusInitialMeans.chooseRemaining(DBIDs ids, DistanceQuery<?> distQ, int k, ArrayModifiableDBIDs means, WritableDoubleDataStore weights, double weightsum, java.util.Random random) Choose remaining means, weighted by distance.
(package private) static void	KMeansPlusPlusInitialMeans.chooseRemaining(Relation<? extends NumberVector> relation, DBIDs ids, DistanceQuery<NumberVector> distQ, int k, java.util.List<NumberVector> means, WritableDoubleDataStore weights, double weightsum, java.util.Random random) Choose remaining means, weighted by distance.
(package private) static double	KMeansPlusPlusInitialMeans.initialWeights(WritableDoubleDataStore weights, DBIDs ids, DBIDRef latest, DistanceQuery<?> distQ) Initialize the weight list.
(package private) static double	KMeansPlusPlusInitialMeans.initialWeights(WritableDoubleDataStore weights, DBIDs ids, NumberVector first, DistanceQuery<? super NumberVector> distQ) Initialize the weight list.
protected static <T> double	OstrovskyInitialMeans.initialWeights(WritableDoubleDataStore weights, Relation<? extends T> relation, DBIDs ids, T first, T second, DistanceQuery<? super T> distQ) Initialize the weight list.
private static double	KMeansPlusPlusInitialMeans.updateWeights(WritableDoubleDataStore weights, DBIDs ids, DBIDRef latest, DistanceQuery<?> distQ) Update the weight list.
private static double	KMeansPlusPlusInitialMeans.updateWeights(WritableDoubleDataStore weights, DBIDs ids, NumberVector latest, DistanceQuery<? super NumberVector> distQ) Update the weight list.

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

Fields in de.lmu.ifi.dbs.elki.algorithm.clustering.optics declared as DBIDs

Modifier and Type	Field and Description
(package private) DBIDs	OPTICSList.Instance.ids IDs to process.
(package private) DBIDs	GeneralizedOPTICS.Instance.ids IDs to process.
private DBIDs	OPTICSHeap.Instance.ids IDs to process.

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

Modifier and Type	Field and Description
(package private) DataStore<? extends DBIDs>	FastOPTICS.neighs neighbors of a point

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

Modifier and Type	Method and Description
ArrayModifiableDBIDs	ClusterOrder.order(DBIDs ids) Use the cluster order to sort the given collection ids.

Constructors in de.lmu.ifi.dbs.elki.algorithm.clustering.optics with parameters of type DBIDs

Constructor and Description
ClusterOrder(DBIDs ids, java.lang.String name, java.lang.String shortname) Constructor

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

Fields in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace declared as DBIDs

Modifier and Type	Field and Description
(package private) DBIDs	P3C.Signature.ids Object ids.

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

Modifier and Type	Method and Description
private DBIDs	PROCLUS.computeBadMedoids(ArrayDBIDs m_current, java.util.ArrayList<PROCLUS.PROCLUSCluster> clusters, int threshold) Computes the bad medoids, where the medoid of a cluster with less than the specified threshold of objects is bad.
protected DBIDs	DOC.findNeighbors(DBIDRef q, long[] nD, ArrayModifiableDBIDs S, Relation<V> relation) Find the neighbors of point q in the given subspace

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

Modifier and Type	Method and Description
private DataStore<DBIDs>	PROCLUS.getLocalities(DBIDs medoids, DistanceQuery<V> distFunc, RangeQuery<V> 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.

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

Modifier and Type	Method and Description
private double	PROCLUS.avgDistance(double[] centroid, DBIDs objectIDs, Relation<V> database, int dimension) Computes the average distance of the objects to the centroid along the specified dimension.
private ArrayDBIDs	PROCLUS.computeM_current(DBIDs m, DBIDs m_best, DBIDs m_bad, java.util.Random random) Computes the set of medoids in current iteration.
protected boolean	DOC.dimensionIsRelevant(int dimension, Relation<V> relation, DBIDs points) Utility method to test if a given dimension is relevant as determined via a set of reference points (i.e. if the variance along the attribute is lower than the threshold).
private DataStore<DBIDs>	PROCLUS.getLocalities(DBIDs medoids, DistanceQuery<V> distFunc, RangeQuery<V> rangeQuery) Computes the localities of the specified medoids: for each medoid m the objects in the sphere centered at m with radius minDist are determined, where minDist is the minimum distance between medoid m and any other medoid m_i.
private ArrayDBIDs	PROCLUS.greedy(DistanceQuery<V> distFunc, DBIDs sampleSet, int m, java.util.Random random) Returns a piercing set of k medoids from the specified sample set.
private java.util.ArrayList<P3C.ClusterCandidate>	P3C.hardClustering(WritableDataStore<double[]> probClusterIGivenX, java.util.List<P3C.Signature> clusterCores, DBIDs dbids) Creates a hard clustering from the specified soft membership matrix.
private ArrayDBIDs	PROCLUS.initialSet(DBIDs sampleSet, int k, java.util.Random random) Returns a set of k elements from the specified sample set.
protected Cluster<SubspaceModel>	DOC.makeCluster(Relation<V> relation, DBIDs C, long[] D) Utility method to create a subspace cluster from a list of DBIDs and the relevant attributes.
private java.util.List<Cluster<Model>>	SUBCLU.runDBSCAN(Relation<V> relation, DBIDs ids, Subspace subspace) Runs the DBSCAN algorithm on the specified partition of the database in the given subspace.
protected HashSetModifiableDBIDs	P3C.unionDBIDs(DBIDs[] parts, int start, int end) Compute the union of multiple DBID sets.

Constructors in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace with parameters of type DBIDs

Constructor and Description
Signature(int[] spec, DBIDs ids) Constructor.

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

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

Modifier and Type	Method and Description
DBIDs	CLIQUEUnit.getIds() Returns the ids of the feature vectors this unit contains.

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

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

Modifier and Type	Method and Description
private java.util.HashMap<java.lang.String,DBIDs>	ByLabelClustering.multipleAssignment(Relation<?> data) Assigns the objects of the database to multiple clusters according to their labels.
private java.util.HashMap<java.lang.String,DBIDs>	ByLabelClustering.singleAssignment(Relation<?> data) Assigns the objects of the database to single clusters according to their labels.

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

Modifier and Type	Method and Description
private void	ByLabelHierarchicalClustering.assign(java.util.HashMap<java.lang.String,DBIDs> labelMap, java.lang.String label, DBIDRef id) Assigns the specified id to the labelMap according to its label
private void	ByLabelClustering.assign(java.util.HashMap<java.lang.String,DBIDs> labelMap, java.lang.String label, DBIDRef id) Assigns the specified id to the labelMap according to its label

Uses of DBIDs in de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain

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

Modifier and Type	Method and Description
DBIDs	FDBSCANNeighborPredicate.Instance.getIDs()
DBIDs	FDBSCANNeighborPredicate.Instance.getNeighbors(DBIDRef reference)

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

Modifier and Type	Method and Description
SimpleTypeInformation<DBIDs>	FDBSCANNeighborPredicate.getOutputType()

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

Modifier and Type	Method and Description
DBIDIter	FDBSCANNeighborPredicate.Instance.iterDBIDs(DBIDs neighbors)
protected Clustering<?>	RepresentativeUncertainClustering.runClusteringAlgorithm(ResultHierarchy hierarchy, Result parent, DBIDs ids, DataStore<DoubleVector> store, int dim, java.lang.String title) Run a clustering algorithm on a single instance.
protected C	CenterOfMassMetaClustering.runClusteringAlgorithm(ResultHierarchy hierarchy, Result parent, DBIDs ids, DataStore<DoubleVector> store, int dim, java.lang.String title) Run a clustering algorithm on a single instance.

Uses of DBIDs in de.lmu.ifi.dbs.elki.algorithm.itemsetmining

Methods in de.lmu.ifi.dbs.elki.algorithm.itemsetmining that return DBIDs

Modifier and Type	Method and Description
private DBIDs[]	Eclat.buildIndex(Relation<BitVector> relation, int dim, int minsupp)
private DBIDs	Eclat.mergeJoin(DBIDs first, DBIDs second)

Methods in de.lmu.ifi.dbs.elki.algorithm.itemsetmining with parameters of type DBIDs

Modifier and Type	Method and Description
protected java.util.List<SparseItemset>	APRIORI.buildFrequentTwoItemsets(java.util.List<OneItemset> oneitems, Relation<BitVector> relation, int dim, int needed, DBIDs ids, ArrayModifiableDBIDs survivors) Build the 2-itemsets.
private void	Eclat.extractItemsets(DBIDs[] idx, int start, int minsupp, java.util.List<Itemset> solution)
private void	Eclat.extractItemsets(DBIDs iset, DBIDs[] idx, int[] buf, int depth, int start, int minsupp, java.util.List<Itemset> solution)
private void	Eclat.extractItemsets(DBIDs iset, DBIDs[] idx, int[] buf, int depth, int start, int minsupp, java.util.List<Itemset> solution)
protected java.util.List<? extends Itemset>	APRIORI.frequentItemsets(java.util.List<? extends Itemset> candidates, Relation<BitVector> relation, int needed, DBIDs ids, ArrayModifiableDBIDs survivors, int length) Returns the frequent BitSets out of the given BitSets with respect to the given database.
protected java.util.List<SparseItemset>	APRIORI.frequentItemsetsSparse(java.util.List<SparseItemset> candidates, Relation<BitVector> relation, int needed, DBIDs ids, ArrayModifiableDBIDs survivors, int length) Returns the frequent BitSets out of the given BitSets with respect to the given database.
private DBIDs	Eclat.mergeJoin(DBIDs first, DBIDs second)

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

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

Modifier and Type	Method and Description
private void	DWOF.clusterData(DBIDs ids, RangeQuery<O> rnnQuery, WritableDoubleDataStore radii, WritableDataStore<ModifiableDBIDs> labels) This method applies a density based clustering algorithm.
private static void	COP.computeCentroid(double[] centroid, Relation<? extends NumberVector> relation, DBIDs ids) Recompute the centroid of a set.
private void	DWOF.initializeRadii(DBIDs ids, KNNQuery<O> knnq, DistanceQuery<O> distFunc, WritableDoubleDataStore radii) This method prepares a container for the radii of the objects and initializes radii according to the equation: initialRadii of a certain object = (absoluteMinDist of all objects) * (avgDist of the object) / (minAvgDist of all objects)
private double	GaussianUniformMixture.loglikelihoodAnomalous(DBIDs anomalousObjs) Loglikelihood anomalous objects.
private double	GaussianUniformMixture.loglikelihoodNormal(DBIDs objids, SetDBIDs anomalous, CovarianceMatrix builder, Relation<V> relation) Computes the loglikelihood of all normal objects.
private int	DWOF.updateSizes(DBIDs ids, WritableDataStore<ModifiableDBIDs> labels, WritableIntegerDataStore newSizes) This method updates each object's cluster size after the clustering step.

Uses of DBIDs in de.lmu.ifi.dbs.elki.algorithm.outlier.anglebased

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

Modifier and Type	Method and Description
private void	FastABOD.fastABOD(Database db, Relation<V> relation, DBIDs ids, WritableDoubleDataStore abodvalues, DoubleMinMax minmaxabod) Full kernel-based version.
private boolean	FastABOD.kNNABOD(Database db, Relation<V> relation, DBIDs ids, WritableDoubleDataStore abodvalues, DoubleMinMax minmaxabod) Simpler kNN based, can use more indexing.

Uses of DBIDs in de.lmu.ifi.dbs.elki.algorithm.outlier.intrinsic

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

Modifier and Type	Method and Description
protected DoubleDataStore	IDOS.computeIDOS(DBIDs ids, KNNQuery<O> knnQ, DoubleDataStore intDims, DoubleMinMax idosminmax) Computes all IDOS scores.
protected DoubleDataStore	IDOS.computeIDs(DBIDs ids, KNNQuery<O> knnQ) Computes all IDs
static DoubleMinMax	ISOS.transformScores(WritableDoubleDataStore scores, DBIDs ids, double logPerp, double phi) Transform scores

Uses of DBIDs in de.lmu.ifi.dbs.elki.algorithm.outlier.lof

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

Modifier and Type	Method and Description
protected void	COF.computeAverageChainingDistances(KNNQuery<O> knnq, DistanceQuery<O> dq, DBIDs ids, WritableDoubleDataStore acds) Computes the average chaining distance, the average length of a path through the given set of points to each target.
private void	COF.computeCOFScores(KNNQuery<O> knnq, DBIDs ids, DoubleDataStore acds, WritableDoubleDataStore cofs, DoubleMinMax cofminmax) Compute Connectivity outlier factors.
protected void	FlexibleLOF.computeLOFs(KNNQuery<O> knnq, DBIDs ids, DoubleDataStore lrds, WritableDoubleDataStore lofs, DoubleMinMax lofminmax) Computes the Local outlier factor (LOF) of the specified objects.
private void	LOF.computeLOFScores(KNNQuery<O> knnq, DBIDs ids, DoubleDataStore lrds, WritableDoubleDataStore lofs, DoubleMinMax lofminmax) Compute local outlier factors.
private void	LOF.computeLRDs(KNNQuery<O> knnq, DBIDs ids, WritableDoubleDataStore lrds) Compute local reachability distances.
protected void	FlexibleLOF.computeLRDs(KNNQuery<O> knnq, DBIDs ids, WritableDoubleDataStore lrds) Computes the local reachability density (LRD) of the specified objects.
protected void	KDEOS.computeOutlierScores(KNNQuery<O> knnq, DBIDs ids, WritableDataStore<double[]> densities, WritableDoubleDataStore kdeos, DoubleMinMax minmax) Compute the final KDEOS scores.
private void	SimplifiedLOF.computeSimplifiedLOFs(DBIDs ids, KNNQuery<O> knnq, WritableDoubleDataStore slrds, WritableDoubleDataStore lofs, DoubleMinMax lofminmax) Compute the simplified LOF factors.
private void	SimplifiedLOF.computeSimplifiedLRDs(DBIDs ids, KNNQuery<O> knnq, WritableDoubleDataStore lrds) Compute the simplified reachability densities.
private void	VarianceOfVolume.computeVolumes(KNNQuery<O> knnq, int dim, DBIDs ids, WritableDoubleDataStore vols) Compute volumes
private void	VarianceOfVolume.computeVOVs(KNNQuery<O> knnq, DBIDs ids, DoubleDataStore vols, WritableDoubleDataStore vovs, DoubleMinMax vovminmax) Compute variance of volumes.
protected FlexibleLOF.LOFResult<O>	FlexibleLOF.doRunInTime(DBIDs ids, KNNQuery<O> kNNRefer, KNNQuery<O> kNNReach, StepProgress stepprog) Performs the Generalized LOF_SCORE algorithm on the given database and returns a FlexibleLOF.LOFResult encapsulating information that may be needed by an OnlineLOF algorithm.
protected void	KDEOS.estimateDensities(Relation<O> rel, KNNQuery<O> knnq, DBIDs ids, WritableDataStore<double[]> densities) Perform the kernel density estimation step.
private void	OnlineLOF.LOFKNNListener.kNNsInserted(DBIDs insertions, DBIDs updates1, DBIDs updates2, FlexibleLOF.LOFResult<O> lofResult) Invoked after kNNs have been inserted and updated, updates the result.
private void	OnlineLOF.LOFKNNListener.kNNsRemoved(DBIDs deletions, DBIDs updates1, DBIDs updates2, FlexibleLOF.LOFResult<O> lofResult) Invoked after kNNs have been removed and updated, updates the result.
private ArrayModifiableDBIDs	OnlineLOF.LOFKNNListener.mergeIDs(java.util.List<? extends DoubleDBIDList> queryResults, DBIDs... ids) Merges the ids of the query result with the specified ids.
protected void	LOCI.precomputeInterestingRadii(DBIDs ids, RangeQuery<O> rangeQuery, WritableDataStore<LOCI.DoubleIntArrayList> interestingDistances) Preprocessing step: determine the radii of interest for each point.
private void	OnlineLOF.LOFKNNListener.recomputeLOFs(DBIDs ids, FlexibleLOF.LOFResult<O> lofResult) Recomputes the lofs of the specified ids.

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

Fields in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood with type parameters of type DBIDs

Modifier and Type	Field and Description
protected DataStore<DBIDs>	AbstractPrecomputedNeighborhood.store The data

Methods in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood that return DBIDs

Modifier and Type	Method and Description
DBIDs	AbstractPrecomputedNeighborhood.getNeighborDBIDs(DBIDRef reference)
DBIDs	NeighborSetPredicate.getNeighborDBIDs(DBIDRef reference) Get the neighbors of a reference object for DBSCAN.

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

Modifier and Type	Method and Description
private DataStore<DBIDs>	ExtendedNeighborhood.Factory.extendNeighborhood(Database database, Relation<? extends O> relation) Method to load the external neighbors.
private DataStore<DBIDs>	ExternalNeighborhood.Factory.loadNeighbors(Database database, Relation<?> relation) Method to load the external neighbors.

Constructor parameters in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood with type arguments of type DBIDs

Constructor and Description
AbstractPrecomputedNeighborhood(DataStore<DBIDs> store) Constructor.
ExtendedNeighborhood(DataStore<DBIDs> store) Constructor.
ExternalNeighborhood(DataStore<DBIDs> store) Constructor.
PrecomputedKNearestNeighborNeighborhood(DataStore<DBIDs> store) Constructor.

Uses of DBIDs in de.lmu.ifi.dbs.elki.algorithm.outlier.subspace

Fields in de.lmu.ifi.dbs.elki.algorithm.outlier.subspace with type parameters of type DBIDs

Modifier and Type	Field and Description
(package private) java.util.ArrayList<java.util.ArrayList<DBIDs>>	AggarwalYuEvolutionary.EvolutionarySearch.ranges Database ranges.

Methods in de.lmu.ifi.dbs.elki.algorithm.outlier.subspace that return DBIDs

Modifier and Type	Method and Description
protected DBIDs	AbstractAggarwalYuOutlier.computeSubspace(int[] subspace, java.util.ArrayList<java.util.ArrayList<DBIDs>> ranges) Method to get the ids in the given subspace.
protected DBIDs	AbstractAggarwalYuOutlier.computeSubspaceForGene(short[] gene, java.util.ArrayList<java.util.ArrayList<DBIDs>> ranges) Get the DBIDs in the current subspace.
private DBIDs	SOD.getNearestNeighbors(Relation<V> relation, SimilarityQuery<V> simQ, DBIDRef queryObject) Get the k nearest neighbors in terms of the shared nearest neighbor distance.

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

Modifier and Type	Method and Description
protected java.util.ArrayList<java.util.ArrayList<DBIDs>>	AbstractAggarwalYuOutlier.buildRanges(Relation<V> relation) Grid discretization of the data: Each attribute of data is divided into phi equi-depth ranges.

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

Modifier and Type	Method and Description
private static double[]	SOD.computePerDimensionVariances(Relation<? extends NumberVector> relation, double[] center, DBIDs neighborhood) Compute the per-dimension variances for the given neighborhood and center.
private DoubleDBIDList	OUTRES.initialRange(DBIDRef obj, DBIDs cands, PrimitiveDistanceFunction<? super NumberVector> df, double eps, OUTRES.KernelDensityEstimator kernel, ModifiableDoubleDBIDList n) Initial range query.
double	OUTRES.outresScore(int s, long[] subspace, DBIDRef id, OUTRES.KernelDensityEstimator kernel, DBIDs cands) Main loop of OUTRES.

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

Modifier and Type	Method and Description
protected DBIDs	AbstractAggarwalYuOutlier.computeSubspace(int[] subspace, java.util.ArrayList<java.util.ArrayList<DBIDs>> ranges) Method to get the ids in the given subspace.
protected DBIDs	AbstractAggarwalYuOutlier.computeSubspaceForGene(short[] gene, java.util.ArrayList<java.util.ArrayList<DBIDs>> ranges) Get the DBIDs in the current subspace.

Constructor parameters in de.lmu.ifi.dbs.elki.algorithm.outlier.subspace with type arguments of type DBIDs

Constructor and Description
EvolutionarySearch(Relation<V> relation, java.util.ArrayList<java.util.ArrayList<DBIDs>> ranges, int m, java.util.Random random) Constructor.

Uses of DBIDs in de.lmu.ifi.dbs.elki.application.greedyensemble

Methods in de.lmu.ifi.dbs.elki.application.greedyensemble with parameters of type DBIDs

Modifier and Type	Method and Description
static Relation<NumberVector>	GreedyEnsembleExperiment.applyPrescaling(ScalingFunction scaling, Relation<NumberVector> relation, DBIDs skip) Prescale each vector (except when in skip) with the given scaling function.
(package private) void	ComputeKNNOutlierScores.writeResult(java.io.PrintStream out, DBIDs ids, OutlierResult result, ScalingFunction scaling, java.lang.String label) Write a single output line.

Uses of DBIDs in de.lmu.ifi.dbs.elki.data

Fields in de.lmu.ifi.dbs.elki.data declared as DBIDs

Modifier and Type	Field and Description
private DBIDs	Cluster.ids Cluster data.

Methods in de.lmu.ifi.dbs.elki.data that return DBIDs

Modifier and Type	Method and Description
DBIDs	Cluster.getIDs() Access group object

Methods in de.lmu.ifi.dbs.elki.data with parameters of type DBIDs

Modifier and Type	Method and Description
void	Cluster.setIDs(DBIDs g) Access group object

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

Constructor and Description
Cluster(DBIDs ids) Constructor without hierarchy information and name and model
Cluster(DBIDs ids, boolean noise) Constructor without hierarchy information and name and model
Cluster(DBIDs ids, boolean noise, M model) Constructor without hierarchy information and name
Cluster(DBIDs ids, M model) Constructor without hierarchy information and name
Cluster(java.lang.String name, DBIDs ids) Constructor without hierarchy information and model
Cluster(java.lang.String name, DBIDs ids, boolean noise) Constructor without hierarchy information and model
Cluster(java.lang.String name, DBIDs ids, boolean noise, M model) Full constructor
Cluster(java.lang.String name, DBIDs ids, M model) Constructor without hierarchy information.

Uses of DBIDs in de.lmu.ifi.dbs.elki.data.model

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

Modifier and Type	Field and Description
(package private) DBIDs	CoreObjectsModel.core Objects that are part of the cluster core.
private DBIDs	BiclusterWithInversionsModel.invertedRows The ids of inverted rows.

Methods in de.lmu.ifi.dbs.elki.data.model that return DBIDs

Modifier and Type	Method and Description
DBIDs	CoreObjectsModel.getCoreObjects() Get the core object IDs.
DBIDs	BiclusterWithInversionsModel.getInvertedRows() Provides a copy of the inverted column IDs.

Methods in de.lmu.ifi.dbs.elki.data.model with parameters of type DBIDs

Modifier and Type	Method and Description
static NumberVector	ModelUtil.getPrototypeOrCentroid(Model model, Relation<? extends NumberVector> relation, DBIDs ids) Get the representative vector for a cluster model, or compute the centroid.
static <V extends NumberVector> V	ModelUtil.getPrototypeOrCentroid(Model model, Relation<? extends V> relation, DBIDs ids, NumberVector.Factory<V> factory) Get the representative vector for a cluster model, or compute the centroid.
void	BiclusterWithInversionsModel.setInvertedRows(DBIDs invertedRows) Sets the ids of the inverted rows.

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

Constructor and Description
BiclusterWithInversionsModel(int[] colIDs, DBIDs invertedRows)
CoreObjectsModel(DBIDs core) Constructor.

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

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

Modifier and Type	Field and Description
static SimpleTypeInformation<DBIDs>	TypeUtil.DBIDS Database ID lists (but not single DBIDs).

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

Methods in de.lmu.ifi.dbs.elki.database that return DBIDs

Modifier and Type	Method and Description
DBIDs	UpdatableDatabase.insert(ObjectBundle objpackages) Inserts the given object(s) and their associations into the database.
DBIDs	HashmapDatabase.insert(ObjectBundle objpackages)

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

Modifier and Type	Method and Description
ObjectBundle	UpdatableDatabase.delete(DBIDs ids) Removes and returns the specified objects with the given ids from the database.
MultipleObjectsBundle	HashmapDatabase.delete(DBIDs ids) Removes the objects from the database (by calling HashmapDatabase.doDelete(DBIDRef) for each object) and indexes and fires a deletion event.
private void	DatabaseEventManager.fireObjectsChanged(DBIDs objects, DatabaseEventManager.Type type) Handles a DataStoreEvent with the specified type.
void	DatabaseEventManager.fireObjectsInserted(DBIDs insertions) Event when new objects are inserted.
protected void	DatabaseEventManager.fireObjectsRemoved(DBIDs deletions) Event when objects were removed / deleted.
void	DatabaseEventManager.fireObjectsUpdated(DBIDs updates) Event when objects have changed / were updated.
void	ProxyDatabase.setDBIDs(DBIDs ids) Set the DBIDs to use.

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

Constructor and Description
ProxyDatabase(DBIDs ids) Constructor.
ProxyDatabase(DBIDs ids, Database database) Constructor, proxying all relations of an existing database.
ProxyDatabase(DBIDs ids, java.lang.Iterable<Relation<?>> relations) Constructor.
ProxyDatabase(DBIDs ids, Relation<?>... relations) Constructor.

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

Fields in de.lmu.ifi.dbs.elki.database.datastore declared as DBIDs

Modifier and Type	Field and Description
private DBIDs	DataStoreEvent.inserts Insertions.
private DBIDs	DataStoreEvent.removals Removals.
private DBIDs	DataStoreEvent.updates Updates.

Methods in de.lmu.ifi.dbs.elki.database.datastore that return DBIDs

Modifier and Type	Method and Description
DBIDs	DataStoreEvent.getInserts() Get the inserted objects.
DBIDs	DataStoreEvent.getRemovals() Get the removed objects.
DBIDs	DataStoreEvent.getUpdates() Get the updates objects.

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

Modifier and Type	Method and Description
static DataStoreEvent	DataStoreEvent.insertionEvent(DBIDs inserts) Insertion event.
static WritableDBIDDataStore	DataStoreUtil.makeDBIDStorage(DBIDs ids, int hints) Make a new storage, to associate the given ids with an object of class dataclass.
WritableDBIDDataStore	DataStoreFactory.makeDBIDStorage(DBIDs ids, int hints) Make a new storage, to associate the given ids with an object of class dataclass.
static WritableDoubleDataStore	DataStoreUtil.makeDoubleStorage(DBIDs ids, int hints) Make a new storage, to associate the given ids with an object of class dataclass.
WritableDoubleDataStore	DataStoreFactory.makeDoubleStorage(DBIDs ids, int hints) Make a new storage, to associate the given ids with an object of class dataclass.
static WritableDoubleDataStore	DataStoreUtil.makeDoubleStorage(DBIDs ids, int hints, double def) Make a new storage, to associate the given ids with an object of class dataclass.
WritableDoubleDataStore	DataStoreFactory.makeDoubleStorage(DBIDs ids, int hints, double def) Make a new storage, to associate the given ids with an object of class dataclass.
static WritableIntegerDataStore	DataStoreUtil.makeIntegerStorage(DBIDs ids, int hints) Make a new storage, to associate the given ids with an object of class dataclass.
WritableIntegerDataStore	DataStoreFactory.makeIntegerStorage(DBIDs ids, int hints) Make a new storage, to associate the given ids with an object of class dataclass.
static WritableIntegerDataStore	DataStoreUtil.makeIntegerStorage(DBIDs ids, int hints, int def) Make a new storage, to associate the given ids with an object of class dataclass.
WritableIntegerDataStore	DataStoreFactory.makeIntegerStorage(DBIDs ids, int hints, int def) Make a new storage, to associate the given ids with an object of class dataclass.
static WritableRecordStore	DataStoreUtil.makeRecordStorage(DBIDs ids, int hints, java.lang.Class<?>... dataclasses) Make a new record storage, to associate the given ids with an object of class dataclass.
WritableRecordStore	DataStoreFactory.makeRecordStorage(DBIDs ids, int hints, java.lang.Class<?>... dataclasses) Make a new record storage, to associate the given ids with an object of class dataclass.
static <T> WritableDataStore<T>	DataStoreUtil.makeStorage(DBIDs ids, int hints, java.lang.Class<? super T> dataclass) Make a new storage, to associate the given ids with an object of class dataclass.
<T> WritableDataStore<T>	DataStoreFactory.makeStorage(DBIDs ids, int hints, java.lang.Class<? super T> dataclass) Make a new storage, to associate the given ids with an object of class dataclass.
static DataStoreEvent	DataStoreEvent.removalEvent(DBIDs removals) Removal event.
static DataStoreEvent	DataStoreEvent.updateEvent(DBIDs updates) Update event.

Constructors in de.lmu.ifi.dbs.elki.database.datastore with parameters of type DBIDs

Constructor and Description
DataStoreEvent(DBIDs inserts, DBIDs removals, DBIDs updates) Constructor.

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

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

Modifier and Type	Method and Description
WritableDBIDDataStore	MemoryDataStoreFactory.makeDBIDStorage(DBIDs ids, int hints)
WritableDoubleDataStore	MemoryDataStoreFactory.makeDoubleStorage(DBIDs ids, int hints)
WritableDoubleDataStore	MemoryDataStoreFactory.makeDoubleStorage(DBIDs ids, int hints, double def)
WritableIntegerDataStore	MemoryDataStoreFactory.makeIntegerStorage(DBIDs ids, int hints)
WritableIntegerDataStore	MemoryDataStoreFactory.makeIntegerStorage(DBIDs ids, int hints, int def)
WritableRecordStore	MemoryDataStoreFactory.makeRecordStorage(DBIDs ids, int hints, java.lang.Class<?>... dataclasses)
<T> WritableDataStore<T>	MemoryDataStoreFactory.makeStorage(DBIDs ids, int hints, java.lang.Class<? super T> dataclass)

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

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

Modifier and Type	Interface and Description
interface	ArrayDBIDs Interface for array based DBIDs.
interface	ArrayModifiableDBIDs Array-oriented implementation of a modifiable DBID collection.
interface	ArrayStaticDBIDs Unmodifiable, indexed DBIDs.
interface	DBID Database ID object.
interface	DBIDPair Immutable pair of two DBIDs, more memory efficient than two DBIDs.
interface	DBIDRange Static DBID range.
interface	DBIDVar (Persistent) variable storing a DBID reference.
interface	DoubleDBIDList Collection of double values associated with objects.
interface	HashSetDBIDs Hash-organized DBIDs
interface	HashSetModifiableDBIDs Set-oriented implementation of a modifiable DBID collection.
interface	KNNList Interface for kNN results.
interface	ModifiableDBIDs Interface for a generic modifiable DBID collection.
interface	ModifiableDoubleDBIDList Modifiable API for Distance-DBID results
interface	SetDBIDs Interface for DBIDs that support fast "set" operations, in particular "contains" lookups.
interface	StaticDBIDs Unmodifiable DBIDs.

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

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

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

Modifier and Type	Method and Description
static DBIDs	DBIDUtil.randomSample(DBIDs ids, double rate, java.util.Random random) Produce a random sample of the given DBIDs.
static DBIDs	DBIDUtil.randomSample(DBIDs ids, double rate, RandomFactory random) Produce a random sample of the given DBIDs.

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

Modifier and Type	Method and Description
boolean	ModifiableDBIDs.addDBIDs(DBIDs ids) Add DBIDs to collection.
static DBIDRange	DBIDUtil.assertRange(DBIDs ids) Assert that the presented ids constitute a continuous DBIDRange.
static ModifiableDBIDs	DBIDUtil.difference(DBIDs ids1, DBIDs ids2) Returns the difference of the two specified collection of IDs.
static ArrayDBIDs	DBIDUtil.ensureArray(DBIDs ids) Ensure that the given DBIDs are array-indexable.
static ModifiableDBIDs	DBIDUtil.ensureModifiable(DBIDs ids) Ensure modifiable.
static SetDBIDs	DBIDUtil.ensureSet(DBIDs ids) Ensure that the given DBIDs support fast "contains" operations.
private static ModifiableDBIDs	DBIDUtil.internalIntersection(DBIDs first, DBIDs second) Compute the set intersection of two sets.
private static int	DBIDUtil.internalIntersectionSize(DBIDs first, DBIDs second) Compute the set intersection size of two sets.
static ModifiableDBIDs	DBIDUtil.intersection(DBIDs first, DBIDs second) Compute the set intersection of two sets.
static int	DBIDUtil.intersectionSize(DBIDs first, DBIDs second) Compute the set intersection size of two sets.
StaticDBIDs	DBIDFactory.makeUnmodifiable(DBIDs existing) Make DBIDs immutable.
static StaticDBIDs	DBIDUtil.makeUnmodifiable(DBIDs existing) Wrap an existing DBIDs collection to be unmodifiable.
ArrayModifiableDBIDs	DBIDFactory.newArray(DBIDs existing) Make a new (modifiable) array of DBIDs.
static ArrayModifiableDBIDs	DBIDUtil.newArray(DBIDs existing) Make a new (modifiable) array of DBIDs.
HashSetModifiableDBIDs	DBIDFactory.newHashSet(DBIDs existing) Make a new (modifiable) hash set of DBIDs.
static HashSetModifiableDBIDs	DBIDUtil.newHashSet(DBIDs existing) Make a new (modifiable) hash set of DBIDs.
static DBIDs	DBIDUtil.randomSample(DBIDs ids, double rate, java.util.Random random) Produce a random sample of the given DBIDs.
static DBIDs	DBIDUtil.randomSample(DBIDs ids, double rate, RandomFactory random) Produce a random sample of the given DBIDs.
static ModifiableDBIDs	DBIDUtil.randomSample(DBIDs source, int k, int seed) Produce a random sample of the given DBIDs.
static ModifiableDBIDs	DBIDUtil.randomSample(DBIDs source, int k, java.lang.Long seed) Produce a random sample of the given DBIDs.
static ModifiableDBIDs	DBIDUtil.randomSample(DBIDs source, int k, java.util.Random random) Produce a random sample of the given DBIDs.
static ModifiableDBIDs	DBIDUtil.randomSample(DBIDs source, int k, RandomFactory rnd) Produce a random sample of the given DBIDs.
static DBIDVar	DBIDUtil.randomSample(DBIDs ids, java.util.Random random) Draw a single random sample.
static DBIDVar	DBIDUtil.randomSample(DBIDs ids, RandomFactory random) Draw a single random sample.
static ModifiableDBIDs	DBIDUtil.randomSampleExcept(DBIDs source, DBIDRef except, int k, java.util.Random random) Produce a random sample of the given DBIDs.
static ModifiableDBIDs	DBIDUtil.randomSampleExcept(DBIDs source, DBIDRef except, int k, RandomFactory rnd) Produce a random sample of the given DBIDs.
static ArrayDBIDs[]	DBIDUtil.randomSplit(DBIDs oids, int p, java.util.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.
boolean	ModifiableDBIDs.removeDBIDs(DBIDs ids) Remove DBIDs from collection.
boolean	HashSetModifiableDBIDs.retainAll(DBIDs set) Retain all elements that also are in the second set.
static void	DBIDUtil.symmetricIntersection(DBIDs first, DBIDs second, HashSetModifiableDBIDs firstonly, HashSetModifiableDBIDs intersection, HashSetModifiableDBIDs secondonly) Compute the set symmetric intersection of two sets.
static java.lang.String	DBIDUtil.toString(DBIDs ids) Format a DBID as string.
static ModifiableDBIDs	DBIDUtil.union(DBIDs ids1, DBIDs ids2) Returns the union of the two specified collection of IDs.

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

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

Modifier and Type	Interface and Description
(package private) interface	DoubleIntegerDBIDList Interface to store double distance, integer DBID results.
interface	IntegerArrayDBIDs Trivial combination interface.
(package private) interface	IntegerArrayStaticDBIDs Combination of ArrayStaticDBIDs and IntegerDBIDs.
interface	IntegerDBIDKNNList Combination interface for KNNList and IntegerDBIDs.
interface	IntegerDBIDs Integer DBID collection.

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

Modifier and Type	Class and Description
(package private) class	ArrayModifiableIntegerDBIDs Class using a primitive int[] array as storage.
private class	ArrayModifiableIntegerDBIDs.Slice Slice of an array.
(package private) class	ArrayStaticIntegerDBIDs Static (no modifications allowed) set of Database Object IDs.
private class	ArrayStaticIntegerDBIDs.Slice Slice of an array.
(package private) class	DoubleIntegerDBIDArrayList Class to store double distance, integer DBID results.
(package private) class	DoubleIntegerDBIDKNNList kNN list, but without automatic sorting.
class	DoubleIntegerDBIDSubList Sublist of an existing result to contain only some of the elements.
(package private) class	FastutilIntOpenHashSetModifiableDBIDs Implementation using Fastutil IntSet.
(package private) class	IntegerDBID Database ID object.
class	IntegerDBIDKNNSubList Sublist of an existing result to contain only the first k elements.
(package private) class	IntegerDBIDPair DBID pair using two ints for storage.
private class	IntegerDBIDPair.Slice Slice of an array.
(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.
class	UnmodifiableIntegerDBIDs Unmodifiable wrapper for DBIDs.

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

Modifier and Type	Method and Description
boolean	FastutilIntOpenHashSetModifiableDBIDs.addDBIDs(DBIDs ids)
boolean	ArrayModifiableIntegerDBIDs.addDBIDs(DBIDs ids)
StaticDBIDs	AbstractIntegerDBIDFactory.makeUnmodifiable(DBIDs existing)
ArrayModifiableDBIDs	AbstractIntegerDBIDFactory.newArray(DBIDs existing)
HashSetModifiableDBIDs	AbstractIntegerDBIDFactory.newHashSet(DBIDs existing)
boolean	FastutilIntOpenHashSetModifiableDBIDs.removeDBIDs(DBIDs ids)
boolean	ArrayModifiableIntegerDBIDs.removeDBIDs(DBIDs ids)
boolean	FastutilIntOpenHashSetModifiableDBIDs.retainAll(DBIDs set)

Constructors in de.lmu.ifi.dbs.elki.database.ids.integer with parameters of type DBIDs

Constructor and Description
ArrayModifiableIntegerDBIDs(DBIDs existing) Constructor.
FastutilIntOpenHashSetModifiableDBIDs(DBIDs existing) Constructor.

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

Fields in de.lmu.ifi.dbs.elki.database.relation declared as DBIDs

Modifier and Type	Field and Description
private DBIDs	DBIDView.ids The ids object
private DBIDs	ProxyView.idview The DBIDs we contain

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

Modifier and Type	Method and Description
DBIDs	Relation.getDBIDs() Get the IDs the query is defined for.
DBIDs	DBIDView.getDBIDs()
DBIDs	ProjectedView.getDBIDs()
DBIDs	ProxyView.getDBIDs()
DBIDs	ConvertToStringView.getDBIDs()

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

Modifier and Type	Method and Description
void	DBIDView.setDBIDs(DBIDs ids) Set the DBIDs of the view.
void	ProxyView.setDBIDs(DBIDs ids) Set the DBIDs to use.

Constructors in de.lmu.ifi.dbs.elki.database.relation with parameters of type DBIDs

Constructor and Description
DBIDView(DBIDs ids) Constructor.
MaterializedDoubleRelation(DBIDs ids) Constructor.
MaterializedDoubleRelation(DBIDs ids, java.lang.String name) Constructor.
MaterializedDoubleRelation(DBIDs ids, java.lang.String name, DoubleDataStore content) Constructor.
MaterializedDoubleRelation(java.lang.String name, java.lang.String shortname, DoubleDataStore content, DBIDs ids) Constructor.
MaterializedRelation(SimpleTypeInformation<O> type, DBIDs ids) Constructor.
MaterializedRelation(SimpleTypeInformation<O> type, DBIDs ids, java.lang.String name) Constructor.
MaterializedRelation(SimpleTypeInformation<O> type, DBIDs ids, java.lang.String name, DataStore<O> content) Constructor.
MaterializedRelation(java.lang.String name, java.lang.String shortname, SimpleTypeInformation<O> type, DataStore<O> content, DBIDs ids) Constructor.
ProxyView(DBIDs idview, Relation<O> inner) Constructor.

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

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

Modifier and Type	Method and Description
protected static double	SharedNearestNeighborJaccardDistanceFunction.Instance.jaccardCoefficient(DBIDs neighbors1, DBIDs neighbors2) Compute the Jaccard coefficient

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

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

Modifier and Type	Method and Description
protected static int	FractionalSharedNearestNeighborSimilarityFunction.Instance.countSharedNeighbors(DBIDs neighbors1, DBIDs neighbors2) Compute the intersection size.
protected static int	SharedNearestNeighborSimilarityFunction.countSharedNeighbors(DBIDs neighbors1, DBIDs neighbors2) Compute the intersection size

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

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

Constructor and Description
KernelMatrix(PrimitiveSimilarityFunction<? super O> kernelFunction, Relation<? extends O> relation, DBIDs ids) Provides a new kernel matrix.
KernelMatrix(SimilarityQuery<? super O> kernelFunction, Relation<? extends O> relation, DBIDs ids) Provides a new kernel matrix.
SortedArrayMap(DBIDs ids)

Uses of DBIDs in de.lmu.ifi.dbs.elki.evaluation.clustering.pairsegments

Fields in de.lmu.ifi.dbs.elki.evaluation.clustering.pairsegments declared as DBIDs

Modifier and Type	Field and Description
protected DBIDs	Segment.objIDs IDs in segment, for object segments.

Methods in de.lmu.ifi.dbs.elki.evaluation.clustering.pairsegments that return DBIDs

Modifier and Type	Method and Description
DBIDs	Segment.getDBIDs() Get the DBIDs of objects contained in this segment.

Methods in de.lmu.ifi.dbs.elki.evaluation.clustering.pairsegments with parameters of type DBIDs

Modifier and Type	Method and Description
private void	Segments.makeOrUpdateSegment(int[] path, DBIDs ids, int pairsize)

Uses of DBIDs in de.lmu.ifi.dbs.elki.evaluation.outlier

Methods in de.lmu.ifi.dbs.elki.evaluation.outlier with parameters of type DBIDs

Modifier and Type	Method and Description
private XYCurve	OutlierPrecisionAtKCurve.computePrecisionResult(int size, SetDBIDs positiveids, DBIDs order)
private OutlierROCCurve.ROCResult	OutlierROCCurve.computeROCResult(SetDBIDs positiveids, DBIDs order)
protected JudgeOutlierScores.ScoreResult	JudgeOutlierScores.computeScore(DBIDs ids, DBIDs outlierIds, OutlierResult or) Evaluate a single outlier score result.
private EvaluationResult	OutlierRankingEvaluation.evaluateOrderingResult(int size, SetDBIDs positiveids, DBIDs order)

Uses of DBIDs in de.lmu.ifi.dbs.elki.evaluation.scores

Methods in de.lmu.ifi.dbs.elki.evaluation.scores with parameters of type DBIDs

Modifier and Type	Method and Description
default double	ScoreEvaluation.evaluate(DBIDs ids, DoubleDBIDList nei) Evaluate given a list of positives and a scoring.

Uses of DBIDs in de.lmu.ifi.dbs.elki.evaluation.scores.adapter

Fields in de.lmu.ifi.dbs.elki.evaluation.scores.adapter declared as DBIDs

Modifier and Type	Field and Description
private DBIDs	DBIDsTest.set DBID set.

Constructors in de.lmu.ifi.dbs.elki.evaluation.scores.adapter with parameters of type DBIDs

Constructor and Description
DBIDsTest(DBIDs set) Constructor.

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

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

Modifier and Type	Method and Description
void	DynamicIndex.deleteAll(DBIDs ids) Deletes the specified objects from this index.
void	DynamicIndex.insertAll(DBIDs ids) Inserts the specified objects into this index.

Uses of DBIDs in de.lmu.ifi.dbs.elki.index.lsh

Fields in de.lmu.ifi.dbs.elki.index.lsh with type parameters of type DBIDs

Modifier and Type	Field and Description
(package private) java.util.ArrayList<it.unimi.dsi.fastutil.ints.Int2ObjectOpenHashMap<DBIDs>>	InMemoryLSHIndex.Instance.hashtables The actual table

Methods in de.lmu.ifi.dbs.elki.index.lsh that return DBIDs

Modifier and Type	Method and Description
protected DBIDs	InMemoryLSHIndex.Instance.getCandidates(V obj) Get the candidates: points which have at least one hash bucket in common.

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

Methods in de.lmu.ifi.dbs.elki.index.preprocessed.fastoptics that return types with arguments of type DBIDs

Modifier and Type	Method and Description
DataStore<? extends DBIDs>	RandomProjectedNeighborsAndDensities.getNeighs() Compute list of neighbors for each point from sets resulting from projection

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

Modifier and Type	Method and Description
void	RandomProjectedNeighborsAndDensities.computeSetsBounds(Relation<V> points, int minSplitSize, DBIDs ptList) Create random projections, project points and put points into sets of size about minSplitSize/2

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

Fields in de.lmu.ifi.dbs.elki.index.preprocessed.knn declared as DBIDs

Modifier and Type	Field and Description
private DBIDs	KNNChangeEvent.objects The ids of the kNNs that were inserted or deleted due to the insertion or removals of objects.
private DBIDs	KNNChangeEvent.updates The ids of the kNNs that were updated due to the insertion or removals of objects.

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

Modifier and Type	Method and Description
DBIDs	KNNChangeEvent.getObjects() Returns the ids of the removed or inserted kNNs (according to the type of this event).
DBIDs	KNNChangeEvent.getUpdates() Returns the ids of kNNs which have been changed due to the removals or insertions.

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

Modifier and Type	Method and Description
protected ArrayDBIDs	MaterializeKNNAndRKNNPreprocessor.affectedkNN(java.util.List<? extends KNNList> extract, DBIDs remove) Extracts and removes the DBIDs in the given collections.
protected ArrayDBIDs	MaterializeKNNAndRKNNPreprocessor.affectedRkNN(java.util.List<? extends java.util.Collection<DoubleDBIDPair>> extract, DBIDs remove) Extracts and removes the DBIDs in the given collections.
private void	NNDescent.clearAll(DBIDs ids, WritableDataStore<HashSetModifiableDBIDs> sets) Clear (but reuse) all sets in the given storage.
void	MaterializeKNNPreprocessor.deleteAll(DBIDs ids)
protected void	MaterializeKNNPreprocessor.fireKNNsInserted(DBIDs insertions, DBIDs updates) Informs all registered KNNListener that new kNNs have been inserted and as a result some kNNs have been changed.
protected void	MaterializeKNNPreprocessor.fireKNNsRemoved(DBIDs removals, DBIDs updates) Informs all registered KNNListener that existing kNNs have been removed and as a result some kNNs have been changed.
void	MaterializeKNNPreprocessor.insertAll(DBIDs ids)
protected void	MaterializeKNNPreprocessor.objectsInserted(DBIDs ids) Called after new objects have been inserted, updates the materialized neighborhood.
protected void	MaterializeKNNAndRKNNPreprocessor.objectsInserted(DBIDs ids)
protected void	MaterializeKNNPreprocessor.objectsRemoved(DBIDs ids) Called after objects have been removed, updates the materialized neighborhood.
protected void	MaterializeKNNAndRKNNPreprocessor.objectsRemoved(DBIDs ids)
private int	NNDescent.sampleNew(DBIDs ids, WritableDataStore<HashSetModifiableDBIDs> sampleNewNeighbors, WritableDataStore<HashSetModifiableDBIDs> newNeighborHash, int items) samples newNeighbors for every object
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.

Constructors in de.lmu.ifi.dbs.elki.index.preprocessed.knn with parameters of type DBIDs

Constructor and Description
KNNChangeEvent(java.lang.Object source, KNNChangeEvent.Type type, DBIDs objects, DBIDs updates) Used to create an event when kNNs of some objects have been changed.

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

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

Modifier and Type	Method and Description
private long[]	HiSCPreferenceVectorIndex.determinePreferenceVector(Relation<V> relation, DBIDRef id, DBIDs neighborIDs) Determines the preference vector according to the specified neighbor ids.

Uses of DBIDs in de.lmu.ifi.dbs.elki.index.tree.metrical.covertree

Methods in de.lmu.ifi.dbs.elki.index.tree.metrical.covertree with parameters of type DBIDs

Modifier and Type	Method and Description
void	CoverTree.bulkLoad(DBIDs ids) Bulk-load the index.
void	SimplifiedCoverTree.bulkLoad(DBIDs ids) Bulk-load the index.

Uses of DBIDs 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 DBIDs

Modifier and Type	Method and Description
protected java.util.Map<DBID,KNNList>	AbstractMkTree.batchNN(N node, DBIDs ids, int kmax) Deprecated. Change to use by-object NN lookups instead.

Uses of DBIDs 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 DBIDs

Modifier and Type	Method and Description
private double[]	MkAppTree.getMeanKNNList(DBIDs ids, java.util.Map<DBID,KNNList> knnLists)

Uses of DBIDs 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 DBIDs

Modifier and Type	Method and Description
void	MkMaxTreeIndex.deleteAll(DBIDs ids) Throws an UnsupportedOperationException since deletion of objects is not yet supported by an M-Tree.
void	MkMaxTreeIndex.insertAll(DBIDs ids)

Uses of DBIDs 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 DBIDs

Modifier and Type	Method and Description
void	MTreeIndex.deleteAll(DBIDs ids) Throws an UnsupportedOperationException since deletion of objects is not yet supported by an M-Tree.
void	MTreeIndex.insertAll(DBIDs ids)

Uses of DBIDs 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 DBIDs

Modifier and Type	Method and Description
void	DeLiCluTreeIndex.deleteAll(DBIDs ids)
void	DeLiCluTreeIndex.insertAll(DBIDs ids) Inserts the specified objects into this index.

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

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

Modifier and Type	Method and Description
void	FlatRStarTreeIndex.deleteAll(DBIDs ids)
void	FlatRStarTreeIndex.insertAll(DBIDs ids) Inserts the specified objects into this index.

Uses of DBIDs 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 DBIDs

Modifier and Type	Method and Description
protected java.util.List<RStarTreeKNNQuery.DoubleDistanceEntry>	RStarTreeKNNQuery.getSortedEntries(AbstractRStarTreeNode<?,?> node, DBIDs ids) Sorts the entries of the specified node according to their minimum distance to the specified objects.

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

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

Modifier and Type	Method and Description
java.util.List<ModifiableDoubleDBIDList>	RdKNNTree.bulkReverseKNNQueryForID(DBIDs ids, int k, SpatialPrimitiveDistanceFunction<? super O> distanceFunction, KNNQuery<O> knnQuery)
void	RdKNNTree.deleteAll(DBIDs ids)
private void	RdKNNTree.doBulkReverseKNN(RdKNNNode node, DBIDs ids, java.util.Map<DBID,ModifiableDoubleDBIDList> result) Performs a bulk reverse knn query in the specified subtree.
void	RdKNNTree.insertAll(DBIDs ids) Inserts the specified objects into this index.

Uses of DBIDs 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 DBIDs

Modifier and Type	Method and Description
void	RStarTreeIndex.deleteAll(DBIDs ids)
void	RStarTreeIndex.insertAll(DBIDs ids) Inserts the specified objects into this index.

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

Methods in de.lmu.ifi.dbs.elki.math.linearalgebra with parameters of type DBIDs

Modifier and Type	Method and Description
static ProjectedCentroid	ProjectedCentroid.make(long[] dims, Relation<? extends NumberVector> relation, DBIDs ids) Static Constructor from a relation.
static Centroid	Centroid.make(Relation<? extends NumberVector> relation, DBIDs ids) Static constructor from an existing relation.
static CovarianceMatrix	CovarianceMatrix.make(Relation<? extends NumberVector> relation, DBIDs ids) Static Constructor from a full relation.

Uses of DBIDs in de.lmu.ifi.dbs.elki.math.linearalgebra.pca

Methods in de.lmu.ifi.dbs.elki.math.linearalgebra.pca with parameters of type DBIDs

Modifier and Type	Method and Description
double[][]	WeightedCovarianceMatrixBuilder.processIds(DBIDs ids, Relation<? extends NumberVector> relation) Weighted Covariance Matrix for a set of IDs.
PCAResult	AutotuningPCA.processIds(DBIDs ids, Relation<? extends NumberVector> database)
double[][]	StandardCovarianceMatrixBuilder.processIds(DBIDs ids, Relation<? extends NumberVector> database) Compute Covariance Matrix for a collection of database IDs.
double[][]	CovarianceMatrixBuilder.processIds(DBIDs ids, Relation<? extends NumberVector> database) Compute Covariance Matrix for a collection of database IDs.
PCAResult	PCARunner.processIds(DBIDs ids, Relation<? extends NumberVector> database) Run PCA on a collection of database IDs.
double[][]	RANSACCovarianceMatrixBuilder.processIds(DBIDs ids, Relation<? extends NumberVector> relation)

Uses of DBIDs in de.lmu.ifi.dbs.elki.math.spacefillingcurves

Constructors in de.lmu.ifi.dbs.elki.math.spacefillingcurves with parameters of type DBIDs

Constructor and Description
ZCurveTransformer(Relation<? extends NumberVector> relation, DBIDs ids) Constructor.

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

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

Modifier and Type	Field and Description
private DBIDs	SingleThreadedExecutor.SingleThreadedRunner.ids Array IDs to process

Methods in de.lmu.ifi.dbs.elki.parallel with parameters of type DBIDs

Modifier and Type	Method and Description
static void	ParallelExecutor.run(DBIDs ids, Processor... procs) Run a task on all available CPUs.
static void	SingleThreadedExecutor.run(DBIDs ids, Processor... procs) Run a task on a single thread.

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

Constructor and Description
SingleThreadedRunner(DBIDs ids, Processor[] procs) Constructor.

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

Fields in de.lmu.ifi.dbs.elki.result declared as DBIDs

Modifier and Type	Field and Description
protected DBIDs	OrderingFromDataStore.ids Database IDs
(package private) DBIDs	SamplingResult.sample The actual selection
private DBIDs	DBIDSelection.selectedIds Selected IDs

Methods in de.lmu.ifi.dbs.elki.result that return DBIDs

Modifier and Type	Method and Description
DBIDs	OrderingResult.getDBIDs() Get the full set of DBIDs this ordering is defined for.
DBIDs	OrderingFromDataStore.getDBIDs()
DBIDs	SamplingResult.getSample()
DBIDs	DBIDSelection.getSelectedIds() Getter for the selected IDs

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

Modifier and Type	Method and Description
ArrayModifiableDBIDs	OrderingResult.order(DBIDs ids) Sort the given ids according to this ordering and return an iterator.
ArrayModifiableDBIDs	OrderingFromDataStore.order(DBIDs ids)
void	SamplingResult.setSample(DBIDs sample) Note: trigger a resultchanged event!

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

Constructor and Description
DBIDSelection(DBIDs selectedIds) Constructor with new object IDs.
OrderingFromDataStore(java.lang.String name, java.lang.String shortname, DBIDs ids, DataStore<? extends T> map) Minimal Constructor
OrderingFromDataStore(java.lang.String name, java.lang.String shortname, DBIDs ids, DataStore<? extends T> map, boolean descending) Constructor without comparator
OrderingFromDataStore(java.lang.String name, java.lang.String shortname, DBIDs ids, DataStore<? extends T> map, java.util.Comparator<T> comparator, boolean descending) Constructor with comparator
RangeSelection(DBIDs selectedIds) Constructor.
RangeSelection(DBIDs selection, ModifiableHyperBoundingBox ranges) Constructor.

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

Methods in de.lmu.ifi.dbs.elki.result.outlier that return DBIDs

Modifier and Type	Method and Description
DBIDs	OrderingFromRelation.getDBIDs()

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

Modifier and Type	Method and Description
ArrayModifiableDBIDs	OrderingFromRelation.order(DBIDs ids)

Uses of DBIDs in de.lmu.ifi.dbs.elki.utilities.datastructures.unionfind

Methods in de.lmu.ifi.dbs.elki.utilities.datastructures.unionfind that return DBIDs

Modifier and Type	Method and Description
DBIDs	WeightedQuickUnionRangeDBIDs.getRoots()
DBIDs	UnionFind.getRoots() Collect all component root elements.
DBIDs	WeightedQuickUnionStaticDBIDs.getRoots()

Uses of DBIDs in de.lmu.ifi.dbs.elki.visualization.style

Fields in de.lmu.ifi.dbs.elki.visualization.style with type parameters of type DBIDs

Modifier and Type	Field and Description
(package private) java.util.ArrayList<DBIDs>	ClusterStylingPolicy.ids Object IDs

Uses of DBIDs in de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection

Methods in de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection with parameters of type DBIDs

Modifier and Type	Method and Description
private void	MoveObjectsToolVisualization.Instance.updateDB(DBIDs dbids, double[] movingVector) Updates the objects with the given DBIDs It will be moved depending on the given Vector

Uses of DBIDs in tutorial.clustering

Methods in tutorial.clustering with parameters of type DBIDs

Modifier and Type	Method and Description
protected ArrayModifiableDBIDs	SameSizeKMeansAlgorithm.initialAssignment(java.util.List<ModifiableDBIDs> clusters, WritableDataStore<SameSizeKMeansAlgorithm.Meta> metas, DBIDs ids)