Uses of Interface
elki.database.ids.ModifiableDBIDs

Packages that use ModifiableDBIDs

Package	Description
elki.algorithm.statistics	Statistical analysis algorithms.
elki.clustering	Clustering algorithms.
elki.clustering.affinitypropagation	Affinity Propagation (AP) clustering.
elki.clustering.correlation	Correlation clustering algorithms.
elki.clustering.correlation.cash	Helper classes for the CASH algorithm.
elki.clustering.dbscan	DBSCAN and its generalizations.
elki.clustering.hierarchical	Hierarchical agglomerative clustering (HAC).
elki.clustering.hierarchical.extraction	Extraction of partitional clusterings from hierarchical results.
elki.clustering.kmeans	K-means clustering and variations.
elki.clustering.optics	OPTICS family of clustering algorithms.
elki.clustering.subspace	Axis-parallel subspace clustering algorithms.
elki.clustering.subspace.clique	Helper classes for the CLIQUE algorithm.
elki.clustering.uncertain	Clustering algorithms for uncertain data.
elki.database.ids	Database object identification and ID group handling API.
elki.database.ids.integer	Integer-based DBID implementation -- do not use directly - always use DBIDUtil.
elki.index.tree.metrical.mtreevariants.mktrees.mkapp	MkAppTree.
elki.index.tree.metrical.mtreevariants.mktrees.mkcop	MkCoPTree.
elki.outlier	Outlier detection algorithms.
elki.outlier.lof	LOF family of outlier detection algorithms.
elki.visualization.visualizers.pairsegments	Visualizers for inspecting cluster differences using pair counting segments.
tutorial.clustering	Classes from the tutorial on implementing a custom k-means variation.

Uses of ModifiableDBIDs in elki.algorithm.statistics

Methods in elki.algorithm.statistics with parameters of type ModifiableDBIDs

Modifier and Type	Method	Description
private void	EvaluateRetrievalPerformance.findMatches(ModifiableDBIDs posn, Relation<?> lrelation, java.lang.Object label)	Find all matching objects.

Uses of ModifiableDBIDs in elki.clustering

Fields in elki.clustering declared as ModifiableDBIDs

Modifier and Type	Field	Description
protected ModifiableDBIDs	SNNClustering.noise	Holds a set of noise.
protected ModifiableDBIDs	SNNClustering.processedIDs	Holds a set of processed ids.

Fields in elki.clustering with type parameters of type ModifiableDBIDs

Modifier and Type	Field	Description
protected java.util.List<ModifiableDBIDs>	SNNClustering.resultList	Holds a list of clusters found.

Uses of ModifiableDBIDs in elki.clustering.affinitypropagation

Methods in elki.clustering.affinitypropagation that return types with arguments of type ModifiableDBIDs

Modifier and Type	Method	Description
private it.unimi.dsi.fastutil.ints.Int2ObjectOpenHashMap<ModifiableDBIDs>	AffinityPropagation.makeClusterMap(ArrayDBIDs ids, int[] assignment)	Build an int to DBIDs lookup for the clusters.

Uses of ModifiableDBIDs in elki.clustering.correlation

Fields in elki.clustering.correlation declared as ModifiableDBIDs

Modifier and Type	Field	Description
(package private) ModifiableDBIDs	ORCLUS.ORCLUSCluster.objectIDs	The ids of the objects belonging to this cluster.
private ModifiableDBIDs	CASH.processedIDs	Holds a set of processed ids.

Methods in elki.clustering.correlation with parameters of type ModifiableDBIDs

Modifier and Type	Method	Description
private double[][]	CASH.runDerivator(Relation<ParameterizationFunction> relation, int dim, CASHInterval interval, ModifiableDBIDs outids)	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 ModifiableDBIDs in elki.clustering.correlation.cash

Fields in elki.clustering.correlation.cash declared as ModifiableDBIDs

Modifier and Type	Field	Description
private ModifiableDBIDs	CASHInterval.ids	Holds the ids of the objects associated with this interval.

Methods in elki.clustering.correlation.cash that return ModifiableDBIDs

Modifier and Type	Method	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.
ModifiableDBIDs	CASHInterval.getIDs()	Returns the set of ids of the objects associated with this interval.

Constructors in elki.clustering.correlation.cash with parameters of type ModifiableDBIDs

Constructor	Description
CASHInterval(double[] min, double[] max, CASHIntervalSplit split, ModifiableDBIDs ids, int maxSplitDimension, int level, double d_min, double d_max)	Provides a unique interval represented by its id, a hyper bounding box and a set of objects ids associated with this interval.

Uses of ModifiableDBIDs in elki.clustering.dbscan

Fields in elki.clustering.dbscan declared as ModifiableDBIDs

Modifier and Type	Field	Description
protected ModifiableDBIDs	DBSCAN.Instance.noise	Holds a set of noise.
protected ModifiableDBIDs	DBSCAN.Instance.processedIDs	Holds a set of processed ids.

Fields in elki.clustering.dbscan with type parameters of type ModifiableDBIDs

Modifier and Type	Field	Description
(package private) it.unimi.dsi.fastutil.longs.Long2ObjectOpenHashMap<ModifiableDBIDs>	GriDBSCAN.Instance.grid	Data grid partitioning.
protected java.util.List<ModifiableDBIDs>	DBSCAN.Instance.resultList	Holds a list of clusters found.

Methods in elki.clustering.dbscan with parameters of type ModifiableDBIDs

Modifier and Type	Method	Description
protected void	GriDBSCAN.Instance.mergeClusterInformation(ModifiableDBIDs cellids, WritableIntegerDataStore temporary, WritableDataStore<Assignment> clusterids)	Merge cluster information.
private void	DBSCAN.Instance.processNeighbors(DoubleDBIDList neighbors, ModifiableDBIDs currentCluster, ArrayModifiableDBIDs seeds)	Process a single core point.

Uses of ModifiableDBIDs in elki.clustering.hierarchical

Fields in elki.clustering.hierarchical with type parameters of type ModifiableDBIDs

Modifier and Type	Field	Description
protected it.unimi.dsi.fastutil.ints.Int2ObjectOpenHashMap<ModifiableDBIDs>	HACAM.Instance.clusters	Cluster to members map
protected it.unimi.dsi.fastutil.ints.Int2ObjectOpenHashMap<ModifiableDBIDs>	MedoidLinkage.Instance.clusters	Cluster to members map
protected it.unimi.dsi.fastutil.ints.Int2ObjectOpenHashMap<ModifiableDBIDs>	MiniMax.Instance.clusters	Map to cluster members

Uses of ModifiableDBIDs in elki.clustering.hierarchical.extraction

Fields in elki.clustering.hierarchical.extraction declared as ModifiableDBIDs

Modifier and Type	Field	Description
protected ModifiableDBIDs	HDBSCANHierarchyExtraction.TempCluster.members	New ids, not yet in child clusters.
protected ModifiableDBIDs	SimplifiedHierarchyExtraction.TempCluster.newids	New ids, not yet in child clusters.

Fields in elki.clustering.hierarchical.extraction with type parameters of type ModifiableDBIDs

Modifier and Type	Field	Description
protected java.util.ArrayList<ModifiableDBIDs>	AbstractCutDendrogram.Instance.clusterMembers	Collected cluster members

Uses of ModifiableDBIDs in elki.clustering.kmeans

Fields in elki.clustering.kmeans with type parameters of type ModifiableDBIDs

Modifier and Type	Field	Description
protected java.util.List<ModifiableDBIDs>	AbstractKMeans.Instance.clusters	Store the elements per cluster.

Uses of ModifiableDBIDs in elki.clustering.optics

Fields in elki.clustering.optics declared as ModifiableDBIDs

Modifier and Type	Field	Description
(package private) ModifiableDBIDs	FastOPTICS.processed	processed points
protected ModifiableDBIDs	GeneralizedOPTICS.Instance.processedIDs	Holds a set of processed ids.
private ModifiableDBIDs	OPTICSHeap.Instance.processedIDs	Holds a set of processed ids.
(package private) ModifiableDBIDs	OPTICSList.Instance.processedIDs	Holds a set of processed ids.

Uses of ModifiableDBIDs in elki.clustering.subspace

Fields in elki.clustering.subspace declared as ModifiableDBIDs

Modifier and Type	Field	Description
ModifiableDBIDs	P3C.ClusterCandidate.ids	Objects contained in cluster.
(package private) ModifiableDBIDs	PROCLUS.PROCLUSCluster.objectIDs	The ids of the objects belonging to this cluster.

Methods in elki.clustering.subspace that return types with arguments of type ModifiableDBIDs

Modifier and Type	Method	Description
private java.util.List<Pair<Subspace,ModifiableDBIDs>>	CLIQUE.determineClusters(java.util.List<CLIQUESubspace> denseSubspaces)	Determines the clusters in the specified dense subspaces.

Methods in elki.clustering.subspace with parameters of type ModifiableDBIDs

Modifier and Type	Method	Description
private void	P3C.assignUnassigned(Relation<? extends NumberVector> relation, WritableDataStore<double[]> probClusterIGivenX, java.util.List<MultivariateGaussianModel> models, ModifiableDBIDs unassigned)	Assign unassigned objects to best candidate based on shortest Mahalanobis distance.
private void	P3C.computeFuzzyMembership(Relation<? extends NumberVector> relation, java.util.ArrayList<P3C.Signature> clusterCores, ModifiableDBIDs unassigned, WritableDataStore<double[]> probClusterIGivenX, java.util.List<MultivariateGaussianModel> models, int dim)	Computes a fuzzy membership with the weights based on which cluster cores each data point is part of.
private long[]	DiSH.Instance.determinePreferenceVector(ModifiableDBIDs[] neighborIDs, java.lang.StringBuilder msg)	Determines the preference vector according to the specified neighbor ids.
private long[]	DiSH.Instance.determinePreferenceVectorByApriori(ModifiableDBIDs[] neighborIDs, java.lang.StringBuilder msg)	Determines the preference vector with the apriori strategy.
private long[]	DiSH.Instance.determinePreferenceVectorByMaxIntersection(ModifiableDBIDs[] neighborIDs, java.lang.StringBuilder msg)	Determines the preference vector with the max intersection strategy.
private void	P3C.findOutliers(Relation<? extends NumberVector> relation, java.util.List<MultivariateGaussianModel> models, java.util.ArrayList<P3C.ClusterCandidate> clusterCandidates, ModifiableDBIDs noise)	Performs outlier detection by testing the Mahalanobis distance of each point in a cluster against the critical value of the ChiSquared distribution with as many degrees of freedom as the cluster has relevant attributes.
private int	DiSH.Instance.maxIntersection(java.util.Map<java.lang.Integer,ModifiableDBIDs> candidates, ModifiableDBIDs set)	Returns the index of the set having the maximum intersection set with the specified set contained in the specified map.

Method parameters in elki.clustering.subspace with type arguments of type ModifiableDBIDs

Modifier and Type	Method	Description
private int	DiSH.Instance.max(java.util.Map<java.lang.Integer,ModifiableDBIDs> candidates)	Returns the set with the maximum size contained in the specified map.
private int	DiSH.Instance.maxIntersection(java.util.Map<java.lang.Integer,ModifiableDBIDs> candidates, ModifiableDBIDs set)	Returns the index of the set having the maximum intersection set with the specified set contained in the specified map.

Constructors in elki.clustering.subspace with parameters of type ModifiableDBIDs

Constructor	Description
PROCLUSCluster(ModifiableDBIDs objectIDs, long[] dimensions, double[] centroid)	Constructor.

Uses of ModifiableDBIDs in elki.clustering.subspace.clique

Fields in elki.clustering.subspace.clique declared as ModifiableDBIDs

Modifier and Type	Field	Description
private ModifiableDBIDs	CLIQUEUnit.ids	The ids of the feature vectors this unit contains.

Methods in elki.clustering.subspace.clique that return types with arguments of type ModifiableDBIDs

Modifier and Type	Method	Description
java.util.List<Pair<Subspace,ModifiableDBIDs>>	CLIQUESubspace.determineClusters()	Determines all clusters in this subspace by performing a depth-first search algorithm to find connected dense units.

Methods in elki.clustering.subspace.clique with parameters of type ModifiableDBIDs

Modifier and Type	Method	Description
void	CLIQUESubspace.dfs(CLIQUEUnit unit, ModifiableDBIDs cluster, CLIQUESubspace model)	Depth-first search algorithm to find connected dense units in this subspace that build a cluster.

Constructors in elki.clustering.subspace.clique with parameters of type ModifiableDBIDs

Constructor	Description
CLIQUEUnit(CLIQUEUnit prefix, int newdim, double min, double max, ModifiableDBIDs ids)	Creates a new k-dimensional unit for the given intervals.

Uses of ModifiableDBIDs in elki.clustering.uncertain

Method parameters in elki.clustering.uncertain with type arguments of type ModifiableDBIDs

Modifier and Type	Method	Description
protected java.util.List<double[]>	UKMeans.means(java.util.List<? extends ModifiableDBIDs> clusters, java.util.List<double[]> means, Relation<DiscreteUncertainObject> database)	Returns the mean vectors of the given clusters in the given database.
protected boolean	UKMeans.updateAssignment(DBIDIter iditer, java.util.List<? extends ModifiableDBIDs> clusters, WritableIntegerDataStore assignment, int newA)	Update the cluster assignment.

Uses of ModifiableDBIDs in elki.database.ids

Subinterfaces of ModifiableDBIDs in elki.database.ids

Modifier and Type	Interface	Description
interface	ArrayModifiableDBIDs	Array-oriented implementation of a modifiable DBID collection.
interface	HashSetModifiableDBIDs	Set-oriented implementation of a modifiable DBID collection.

Methods in elki.database.ids with type parameters of type ModifiableDBIDs

Modifier and Type	Method	Description
default <T extends ModifiableDBIDs> T	DBIDIter.addTo(T collection)	Add all remaining elements of an iterator to an existing collection.

Methods in elki.database.ids that return ModifiableDBIDs

Modifier and Type	Method	Description
ModifiableDBIDs	ModifiableDBIDs.clear()	Clear this collection.
static ModifiableDBIDs	DBIDUtil.difference(DBIDs ids1, DBIDs ids2)	Returns the difference of the two specified collection of IDs.
static ModifiableDBIDs	DBIDUtil.ensureModifiable(DBIDs ids)	Ensure modifiable.
private static ModifiableDBIDs	DBIDUtil.internalIntersection(DBIDs first, DBIDs second)	Compute the set intersection of two sets.
static ModifiableDBIDs	DBIDUtil.intersection(DBIDs first, DBIDs second)	Compute the set intersection of two sets.
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, RandomFactory rnd)	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.randomSampleExcept(DBIDs source, DBIDRef except, int k, RandomFactory rnd)	Produce a random sample of the given DBIDs.
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.union(DBIDs ids1, DBIDs ids2)	Returns the union of the two specified collection of IDs.

Uses of ModifiableDBIDs in elki.database.ids.integer

Classes in elki.database.ids.integer that implement ModifiableDBIDs

Modifier and Type	Class	Description
(package private) class	ArrayModifiableIntegerDBIDs	Class using a primitive int[] array as storage.
(package private) class	FastutilIntOpenHashSetModifiableDBIDs	Implementation using Fastutil IntSet.

Uses of ModifiableDBIDs in elki.index.tree.metrical.mtreevariants.mktrees.mkapp

Methods in elki.index.tree.metrical.mtreevariants.mktrees.mkapp with parameters of type ModifiableDBIDs

Modifier and Type	Method	Description
private void	MkAppTree.leafEntryIDs(MkAppTreeNode<O> node, ModifiableDBIDs result)	Determines the ids of the leaf entries stored in the specified subtree.

Uses of ModifiableDBIDs in elki.index.tree.metrical.mtreevariants.mktrees.mkcop

Methods in elki.index.tree.metrical.mtreevariants.mktrees.mkcop with parameters of type ModifiableDBIDs

Modifier and Type	Method	Description
private void	MkCoPTree.doReverseKNNQuery(int k, DBIDRef q, ModifiableDoubleDBIDList result, ModifiableDBIDs candidates)	Performs a reverse knn query.

Uses of ModifiableDBIDs in elki.outlier

Method parameters in elki.outlier with type arguments of type ModifiableDBIDs

Modifier and Type	Method	Description
private void	DWOF.clusterData(DBIDs ids, RangeSearcher<DBIDRef> rnnQuery, WritableDoubleDataStore radii, WritableDataStore<ModifiableDBIDs> labels)	This method applies a density based clustering algorithm.
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 ModifiableDBIDs in elki.outlier.lof

Methods in elki.outlier.lof with parameters of type ModifiableDBIDs

Modifier and Type	Method	Description
protected void	INFLO.computeINFLO(Relation<O> relation, ModifiableDBIDs pruned, KNNSearcher<DBIDRef> knnq, WritableDataStore<ModifiableDBIDs> rNNminuskNNs, WritableDoubleDataStore inflos, DoubleMinMax inflominmax)	Compute the final INFLO scores.
private void	INFLO.computeNeighborhoods(Relation<O> relation, DataStore<SetDBIDs> knns, ModifiableDBIDs pruned, WritableDataStore<ModifiableDBIDs> rNNminuskNNs)	Compute the reverse kNN minus the kNN.

Method parameters in elki.outlier.lof with type arguments of type ModifiableDBIDs

Modifier and Type	Method	Description
protected void	INFLO.computeINFLO(Relation<O> relation, ModifiableDBIDs pruned, KNNSearcher<DBIDRef> knnq, WritableDataStore<ModifiableDBIDs> rNNminuskNNs, WritableDoubleDataStore inflos, DoubleMinMax inflominmax)	Compute the final INFLO scores.
private void	INFLO.computeNeighborhoods(Relation<O> relation, DataStore<SetDBIDs> knns, ModifiableDBIDs pruned, WritableDataStore<ModifiableDBIDs> rNNminuskNNs)	Compute the reverse kNN minus the kNN.

Uses of ModifiableDBIDs in elki.visualization.visualizers.pairsegments

Fields in elki.visualization.visualizers.pairsegments declared as ModifiableDBIDs

Modifier and Type	Field	Description
protected ModifiableDBIDs	SegmentsStylingPolicy.unselectedObjects	Not selected IDs that will be drawn in default colors.

Uses of ModifiableDBIDs in tutorial.clustering

Methods in tutorial.clustering with parameters of type ModifiableDBIDs

Modifier and Type	Method	Description
protected void	SameSizeKMeans.transfer(WritableDataStore<SameSizeKMeans.Meta> metas, SameSizeKMeans.Meta meta, ModifiableDBIDs src, ModifiableDBIDs dst, DBIDRef id, int dstnum)	Transfer a single element from one cluster to another.

Method parameters in tutorial.clustering with type arguments of type ModifiableDBIDs

Modifier and Type	Method	Description
protected ArrayModifiableDBIDs	SameSizeKMeans.initialAssignment(java.util.List<ModifiableDBIDs> clusters, WritableDataStore<SameSizeKMeans.Meta> metas, DBIDs ids)
protected double[][]	SameSizeKMeans.refineResult(Relation<V> relation, double[][] means, java.util.List<ModifiableDBIDs> clusters, WritableDataStore<SameSizeKMeans.Meta> metas, ArrayModifiableDBIDs tids)	Perform k-means style iterations to improve the clustering result.