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

Packages that use ArrayModifiableDBIDs

Package	Description
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.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.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.itemsetmining	Algorithms for frequent itemset mining such as APRIORI.
de.lmu.ifi.dbs.elki.algorithm.outlier.lof	LOF family of outlier detection algorithms
de.lmu.ifi.dbs.elki.database	ELKI database layer - loading, storing, indexing and accessing data
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.distance.similarityfunction.kernel	Kernel functions.
de.lmu.ifi.dbs.elki.index.preprocessed.fastoptics	Preprocessed index used by the FastOPTICS algorithm.
de.lmu.ifi.dbs.elki.index.tree.metrical.covertree	Cover-tree variations.
de.lmu.ifi.dbs.elki.index.tree.spatial.kd	K-d-tree and variants
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.visualization.gui	Package to provide a visualization GUI
tutorial.clustering	Classes from the tutorial on implementing a custom k-means variation

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

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

Modifier and Type	Method and Description
protected ArrayModifiableDBIDs	SNNClustering.findSNNNeighbors(SimilarityQuery<O> snnInstance, DBIDRef queryObject) Returns the shared nearest neighbors of the specified query object in the given database.
static ArrayModifiableDBIDs[]	ClusteringAlgorithmUtil.partitionsFromIntegerLabels(DBIDs ids, IntegerDataStore assignment, int k) Collect clusters from their [0;k-1] integer labels.

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

Modifier and Type	Method and Description
protected int	GriDBSCAN.Instance.expandCluster(DBIDRef seed, int clusterid, WritableIntegerDataStore clusterids, ModifiableDoubleDBIDList neighbors, ArrayModifiableDBIDs activeSet, RangeQuery<V> rq, FiniteProgress pprog) Set-based expand cluster implementation.
protected void	DBSCAN.expandCluster(Relation<O> relation, RangeQuery<O> rangeQuery, DBIDRef startObjectID, ArrayModifiableDBIDs seeds, FiniteProgress objprog, IndefiniteProgress clusprog) DBSCAN-function expandCluster.
protected int	GriDBSCAN.Instance.processCorePoint(DBIDRef seed, DoubleDBIDList newneighbors, int clusterid, WritableIntegerDataStore clusterids, ArrayModifiableDBIDs activeSet) Process a single core point.
private void	DBSCAN.processNeighbors(DoubleDBIDListIter neighbor, ModifiableDBIDs currentCluster, ArrayModifiableDBIDs seeds) Process a single core point.

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

Fields in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation declared as ArrayModifiableDBIDs

Modifier and Type	Field and Description
private ArrayModifiableDBIDs	HiCO.Instance.clusterOrder Cluster order.
private ArrayModifiableDBIDs	HiCO.Instance.tmpIds Temporary ids.

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

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

Modifier and Type	Method and Description
protected int	GeneralizedDBSCAN.Instance.expandCluster(DBIDRef seed, int clusterid, WritableIntegerDataStore clusterids, T neighbors, ArrayModifiableDBIDs activeSet, FiniteProgress progress) Set-based expand cluster implementation.
protected int	GeneralizedDBSCAN.Instance.processCorePoint(DBIDRef seed, T newneighbors, int clusterid, WritableIntegerDataStore clusterids, ArrayModifiableDBIDs activeSet) Process a single core point.

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

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

Modifier and Type	Method and Description
protected static <O> void	MiniMax.initializeMatrices(MatrixParadigm mat, ArrayModifiableDBIDs prots, DistanceQuery<O> dq) Initializes the inter-cluster distance matrix of possible merges

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

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

Modifier and Type	Field and Description
protected ArrayModifiableDBIDs	AbstractCutDendrogram.Instance.cluster_leads Cluster lead objects

Method parameters in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction with type arguments of type ArrayModifiableDBIDs

Modifier and Type	Method and Description
private void	ClustersWithNoiseExtraction.Instance.mergeClusters(WritableDataStore<ArrayModifiableDBIDs> clusters, DBIDRef it, DBIDRef succ) Merge two clusters

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

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

Modifier and Type	Field and Description
(package private) ArrayModifiableDBIDs	CLARANS.Assignment.medoids Medoids

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

Modifier and Type	Method and Description
protected ArrayModifiableDBIDs	KMedoidsPAM.initialMedoids(DistanceQuery<V> distQ, DBIDs ids) Choose the initial medoids.

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

Modifier and Type	Method and Description
protected void	KMedoidsFastPAM.Instance.findBestSwaps(DBIDArrayIter m, ArrayModifiableDBIDs bestids, double[] best, double[] cost) Find the best swaps.
protected double	KMedoidsFastPAM.Instance.run(ArrayModifiableDBIDs medoids, int maxiter) Run the PAM optimization phase.
protected double	KMedoidsFastPAM1.Instance.run(ArrayModifiableDBIDs medoids, int maxiter) Run the PAM optimization phase.
protected double	KMedoidsPAM.Instance.run(ArrayModifiableDBIDs medoids, int maxiter) Run the PAM optimization phase.
protected double	KMedoidsPAMReynolds.Instance.run(ArrayModifiableDBIDs medoids, int maxiter) Run the PAM optimization phase.
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)
protected void	KMedoidsFastPAM1.Instance.updateAssignment(ArrayModifiableDBIDs medoids, DBIDArrayIter miter, DBIDRef h, int m) Update an existing cluster assignment.

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

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

Modifier and Type	Method and Description
(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.
private static void	LABInitialMeans.shuffle(ArrayModifiableDBIDs ids, int ssize, int end, java.util.Random random) Partial Fisher-Yates shuffle.

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

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

Modifier and Type	Field and Description
(package private) ArrayModifiableDBIDs	OPTICSList.Instance.candidates Current list of candidates.
protected ArrayModifiableDBIDs	GeneralizedOPTICS.Instance.candidates Current list of candidates.
(package private) ArrayModifiableDBIDs	ClusterOrder.ids Cluster order.

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

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

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

Modifier and Type	Method and Description
void	OPTICSList.Instance.findBest(ArrayModifiableDBIDs candidates, DBIDArrayMIter it, DBIDVar out) Find the minimum in the candidates array.

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

Constructor and Description
ClusterOrder(java.lang.String name, java.lang.String shortname, ArrayModifiableDBIDs ids, WritableDoubleDataStore reachability, WritableDBIDDataStore predecessor) Constructor
CorrelationClusterOrder(java.lang.String name, java.lang.String shortname, ArrayModifiableDBIDs ids, WritableDoubleDataStore reachability, WritableDBIDDataStore predecessor, WritableIntegerDataStore corrdim) Constructor.

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

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

Modifier and Type	Field and Description
private ArrayModifiableDBIDs	DiSH.Instance.clusterOrder Cluster order.
private ArrayModifiableDBIDs	HiSC.Instance.clusterOrder Cluster order.
private ArrayModifiableDBIDs	DiSH.Instance.tmpIds Temporary ids.

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

Modifier and Type	Method and Description
private it.unimi.dsi.fastutil.objects.Object2ObjectOpenCustomHashMap<long[],java.util.List<ArrayModifiableDBIDs>>	DiSH.extractClusters(Relation<V> relation, DiSH.DiSHClusterOrder clusterOrder) Extracts the clusters from the cluster order.
private Pair<long[],ArrayModifiableDBIDs>	DiSH.findParent(Relation<V> relation, Pair<long[],ArrayModifiableDBIDs> child, it.unimi.dsi.fastutil.objects.Object2ObjectMap<long[],java.util.List<ArrayModifiableDBIDs>> clustersMap) Returns the parent of the specified cluster

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

Modifier and Type	Method and Description
protected DBIDs	DOC.findNeighbors(DBIDRef q, long[] nD, ArrayModifiableDBIDs S, Relation<V> relation) Find the neighbors of point q in the given subspace
protected Cluster<SubspaceModel>	DOC.runDOC(Database database, Relation<V> relation, ArrayModifiableDBIDs S, int d, int n, int m, int r, int minClusterSize) Performs a single run of DOC, finding a single cluster.
protected Cluster<SubspaceModel>	FastDOC.runDOC(Database database, Relation<V> relation, ArrayModifiableDBIDs S, int d, int n, int m, int r, int minClusterSize) Performs a single run of FastDOC, finding a single cluster.

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

Modifier and Type	Method and Description
private void	DiSH.checkClusters(Relation<V> relation, it.unimi.dsi.fastutil.objects.Object2ObjectMap<long[],java.util.List<ArrayModifiableDBIDs>> clustersMap) Removes the clusters with size < minpts from the cluster map and adds them to their parents.
private Pair<long[],ArrayModifiableDBIDs>	DiSH.findParent(Relation<V> relation, Pair<long[],ArrayModifiableDBIDs> child, it.unimi.dsi.fastutil.objects.Object2ObjectMap<long[],java.util.List<ArrayModifiableDBIDs>> clustersMap) Returns the parent of the specified cluster
private Pair<long[],ArrayModifiableDBIDs>	DiSH.findParent(Relation<V> relation, Pair<long[],ArrayModifiableDBIDs> child, it.unimi.dsi.fastutil.objects.Object2ObjectMap<long[],java.util.List<ArrayModifiableDBIDs>> clustersMap) Returns the parent of the specified cluster
private void	DiSH.logClusterSizes(java.lang.String m, int dimensionality, it.unimi.dsi.fastutil.objects.Object2ObjectOpenCustomHashMap<long[],java.util.List<ArrayModifiableDBIDs>> clustersMap) Log cluster sizes in verbose mode.
private java.util.List<Cluster<SubspaceModel>>	DiSH.sortClusters(Relation<V> relation, it.unimi.dsi.fastutil.objects.Object2ObjectMap<long[],java.util.List<ArrayModifiableDBIDs>> clustersMap) Returns a sorted list of the clusters w.r.t. the subspace dimensionality in descending order.

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

Constructor and Description
DiSHClusterOrder(java.lang.String name, java.lang.String shortname, ArrayModifiableDBIDs ids, WritableDoubleDataStore reachability, WritableDBIDDataStore predecessor, WritableIntegerDataStore corrdim, WritableDataStore<long[]> commonPreferenceVectors) Constructor.

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

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

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.
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.

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

Methods in de.lmu.ifi.dbs.elki.algorithm.outlier.lof that return ArrayModifiableDBIDs

Modifier and Type	Method and Description
private ArrayModifiableDBIDs	OnlineLOF.LOFKNNListener.mergeIDs(java.util.List<? extends DoubleDBIDList> queryResults, DBIDs... ids) Merges the ids of the query result with the specified ids.

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

Modifier and Type	Method and Description
private void	ALOCI.ALOCIQuadTree.bulkLoad(double[] lmin, double[] lmax, java.util.List<ALOCI.Node> children, ArrayModifiableDBIDs ids, int start, int end, int dim, int level, int code) Bulk load the tree

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

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

Modifier and Type	Method and Description
static ArrayModifiableDBIDs	DatabaseUtil.getObjectsByLabelMatch(Database database, java.util.regex.Pattern name_pattern) Find object by matching their labels.

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

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

Modifier and Type	Field and Description
private ArrayModifiableDBIDs	ArrayDBIDStore.data Data array

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

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

Modifier and Type	Method and Description
ArrayModifiableDBIDs	DBIDFactory.newArray() Make a new (modifiable) array of DBIDs.
static ArrayModifiableDBIDs	DBIDUtil.newArray() Make a new (modifiable) array of DBIDs.
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.
ArrayModifiableDBIDs	DBIDFactory.newArray(int size) Make a new (modifiable) array of DBIDs.
static ArrayModifiableDBIDs	DBIDUtil.newArray(int size) Make a new (modifiable) array of DBIDs.

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

Modifier and Type	Method and Description
private static void	QuickSelectDBIDs.insertionSort(ArrayModifiableDBIDs data, java.util.Comparator<? super DBIDRef> comparator, int start, int end, DBIDArrayIter iter1, DBIDArrayIter iter2) Sort a small array using repetitive insertion sort.
static int	QuickSelectDBIDs.median(ArrayModifiableDBIDs data, java.util.Comparator<? super DBIDRef> comparator) Compute the median of an array efficiently using the QuickSelect method.
static int	QuickSelectDBIDs.median(ArrayModifiableDBIDs data, java.util.Comparator<? super DBIDRef> comparator, int begin, int end) Compute the median of an array efficiently using the QuickSelect method.
static int	QuickSelectDBIDs.quantile(ArrayModifiableDBIDs data, java.util.Comparator<? super DBIDRef> comparator, double quant) Compute the median of an array efficiently using the QuickSelect method.
static int	QuickSelectDBIDs.quantile(ArrayModifiableDBIDs data, java.util.Comparator<? super DBIDRef> comparator, int begin, int end, double quant) Compute the median of an array efficiently using the QuickSelect method.
static void	QuickSelectDBIDs.quickSelect(ArrayModifiableDBIDs data, java.util.Comparator<? super DBIDRef> comparator, int rank) QuickSelect is essentially quicksort, except that we only "sort" that half of the array that we are interested in.
static void	QuickSelectDBIDs.quickSelect(ArrayModifiableDBIDs data, java.util.Comparator<? super DBIDRef> comparator, int start, int end, int rank) QuickSelect is essentially quicksort, except that we only "sort" that half of the array that we are interested in.
static void	DBIDUtil.randomShuffle(ArrayModifiableDBIDs ids, java.util.Random random) Produce a random shuffling of the given DBID array.
static void	DBIDUtil.randomShuffle(ArrayModifiableDBIDs ids, RandomFactory rnd) Produce a random shuffling of the given DBID array.
static void	DBIDUtil.randomShuffle(ArrayModifiableDBIDs ids, java.util.Random random, int limit) Produce a random shuffling of the given DBID array.

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

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

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

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

Modifier and Type	Method and Description
ArrayModifiableDBIDs	AbstractIntegerDBIDFactory.newArray()
ArrayModifiableDBIDs	AbstractIntegerDBIDFactory.newArray(DBIDs existing)
ArrayModifiableDBIDs	AbstractIntegerDBIDFactory.newArray(int size)

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

Fields in de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel declared as ArrayModifiableDBIDs

Modifier and Type	Field and Description
(package private) ArrayModifiableDBIDs	KernelMatrix.SortedArrayMap.ids

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

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

Modifier and Type	Method and Description
int	RandomProjectedNeighborsAndDensities.splitByDistance(ArrayModifiableDBIDs ind, int begin, int end, DoubleDataStore tpro, java.util.Random rand) Split the data set by distances.
int	RandomProjectedNeighborsAndDensities.splitRandomly(ArrayModifiableDBIDs ind, int begin, int end, DoubleDataStore tpro, java.util.Random rand) Split the data set randomly.
void	RandomProjectedNeighborsAndDensities.splitupNoSort(ArrayModifiableDBIDs ind, int begin, int end, int dim, java.util.Random rand) Recursively splits entire point set until the set is below a threshold

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

Fields in de.lmu.ifi.dbs.elki.index.tree.metrical.covertree declared as ArrayModifiableDBIDs

Modifier and Type	Field and Description
(package private) ArrayModifiableDBIDs	SimplifiedCoverTree.Node.singletons Objects in this node.

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

Fields in de.lmu.ifi.dbs.elki.index.tree.spatial.kd declared as ArrayModifiableDBIDs

Modifier and Type	Field and Description
(package private) ArrayModifiableDBIDs	MinimalisticMemoryKDTree.sorted The actual "tree" as a sorted array.

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

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

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)

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

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

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

Uses of ArrayModifiableDBIDs in de.lmu.ifi.dbs.elki.visualization.gui

Fields in de.lmu.ifi.dbs.elki.visualization.gui declared as ArrayModifiableDBIDs

Modifier and Type	Field and Description
(package private) ArrayModifiableDBIDs	SelectionTableWindow.dbids The DBIDs to display

Uses of ArrayModifiableDBIDs in tutorial.clustering

Methods in tutorial.clustering that return ArrayModifiableDBIDs

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

Methods in tutorial.clustering with parameters of type ArrayModifiableDBIDs

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