Uses of Interface
elki.database.datastore.WritableDoubleDataStore

Packages that use WritableDoubleDataStore

Package	Description
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.em	Expectation-Maximization clustering algorithm for Gaussian Mixture Modeling (GMM).
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.kmeans.initialization	Initialization strategies for k-means.
elki.clustering.kmeans.spherical	Spherical k-means clustering and variations.
elki.clustering.kmedoids	K-medoids clustering (PAM).
elki.clustering.kmedoids.initialization
elki.clustering.optics	OPTICS family of clustering algorithms.
elki.clustering.silhouette	Silhouette clustering algorithms.
elki.clustering.subspace	Axis-parallel subspace clustering algorithms.
elki.database.datastore	General data store layer API (along the lines of Map<DBID, T> - use everywhere!)
elki.database.datastore.memory	Memory data store implementation for ELKI.
elki.index.invertedlist	Indexes using inverted lists.
elki.outlier	Outlier detection algorithms.
elki.outlier.anglebased	Angle-based outlier detection algorithms.
elki.outlier.clustering	Clustering based outlier detection.
elki.outlier.distance	Distance-based outlier detection algorithms, such as DBOutlier and kNN.
elki.outlier.intrinsic	Outlier detection algorithms based on intrinsic dimensionality.
elki.outlier.lof	LOF family of outlier detection algorithms.
elki.parallel.processor	Processor API of ELKI, and some essential shared processors.
elki.visualization.style	Style management for ELKI visualizations.

Uses of WritableDoubleDataStore in elki.clustering.correlation

Fields in elki.clustering.correlation declared as WritableDoubleDataStore

Modifier and Type	Field	Description
private WritableDoubleDataStore	HiCO.Instance.tmpDistance	Temporary storage of distances.

Uses of WritableDoubleDataStore in elki.clustering.correlation.cash

Fields in elki.clustering.correlation.cash with type parameters of type WritableDoubleDataStore

Modifier and Type	Field	Description
private java.util.Map<HyperBoundingBox,WritableDoubleDataStore>	CASHIntervalSplit.f_maxima	Caches maximum function values for given intervals, used for better split performance.
private java.util.Map<HyperBoundingBox,WritableDoubleDataStore>	CASHIntervalSplit.f_minima	Caches minimum function values for given intervals, used for better split performance.

Uses of WritableDoubleDataStore in elki.clustering.dbscan

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

Modifier and Type	Method	Description
private void	LSDBC.fillDensities(KNNSearcher<DBIDRef> knnq, DBIDs ids, WritableDoubleDataStore dens)	Collect all densities into an array for sorting.
private boolean	LSDBC.isLocalMaximum(double kdist, DBIDs neighbors, WritableDoubleDataStore kdists)	Test if a point is a local density maximum.

Uses of WritableDoubleDataStore in elki.clustering.em

Methods in elki.clustering.em with parameters of type WritableDoubleDataStore

Modifier and Type	Method	Description
static <O> double	EM.assignProbabilitiesToInstances(Relation<? extends O> relation, java.util.List<? extends EMClusterModel<? super O,?>> models, WritableDataStore<double[]> probClusterIGivenX, WritableDoubleDataStore loglikelihoods)	Assigns the current probability values to the instances in the database and compute the expectation value of the current mixture of distributions.

Uses of WritableDoubleDataStore in elki.clustering.hierarchical

Methods in elki.clustering.hierarchical that return WritableDoubleDataStore

Modifier and Type	Method	Description
protected WritableDoubleDataStore	AbstractHDBSCAN.computeCoreDists(DBIDs ids, KNNSearcher<DBIDRef> knnQ, int minPts)	Compute the core distances for all objects.

Methods in elki.clustering.hierarchical with parameters of type WritableDoubleDataStore

Modifier and Type	Method	Description
private void	CLINK.clinkstep3(DBIDArrayIter i, int n, WritableDBIDDataStore pi, WritableDoubleDataStore lambda, WritableDoubleDataStore m)	Third step: Determine the values for P and L
private void	CLINK.clinkstep4567(DBIDRef id, ArrayDBIDs ids, DBIDArrayIter it, int n, WritableDBIDDataStore pi, WritableDoubleDataStore lambda, WritableDoubleDataStore m)	Fourth to seventh step of CLINK: find best insertion
private void	CLINK.clinkstep8(DBIDRef id, DBIDArrayIter it, int n, WritableDBIDDataStore pi, WritableDoubleDataStore lambda)	Update hierarchy.
ClusterDensityMergeHistory	ClusterMergeHistoryBuilder.complete(WritableDoubleDataStore coredists)	Build a result with additional coredists information.
protected void	CLINK.process(DBIDRef id, ArrayDBIDs ids, DBIDArrayIter it, int n, WritableDBIDDataStore pi, WritableDoubleDataStore lambda, WritableDoubleDataStore m)	CLINK main loop, based on the SLINK main loop.
protected void	SLINK.process(DBIDRef id, ArrayDBIDs ids, DBIDArrayIter it, int n, WritableDBIDDataStore pi, WritableDoubleDataStore lambda, WritableDoubleDataStore m)	SLINK main loop.
private void	SLINK.slinkstep3(DBIDRef id, DBIDArrayIter it, int n, WritableDBIDDataStore pi, WritableDoubleDataStore lambda, WritableDoubleDataStore m)	Third step: Determine the values for P and L
private void	SLINK.slinkstep4(DBIDRef id, DBIDArrayIter it, int n, WritableDBIDDataStore pi, WritableDoubleDataStore lambda)	Fourth step: Actualize the clusters if necessary
private void	SLINK.step2(DBIDRef id, DBIDArrayIter it, int n, DistanceQuery<? super O> distQuery, 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.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	SLINK.step2primitive(DBIDRef id, DBIDArrayIter it, int n, Relation<? extends O> relation, PrimitiveDistance<? super O> distance, 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

Uses of WritableDoubleDataStore in elki.clustering.hierarchical.extraction

Methods in elki.clustering.hierarchical.extraction with parameters of type WritableDoubleDataStore

Modifier and Type	Method	Description
private double	HDBSCANHierarchyExtraction.Instance.collectChildren(HDBSCANHierarchyExtraction.TempCluster temp, Clustering<DendrogramModel> clustering, WritableDoubleDataStore glosh, HDBSCANHierarchyExtraction.TempCluster cur, Cluster<DendrogramModel> clus, boolean flatten)	Recursive flattening of clusters.
private double	HDBSCANHierarchyExtraction.Instance.finalizeCluster(HDBSCANHierarchyExtraction.TempCluster temp, Clustering<DendrogramModel> clustering, WritableDoubleDataStore glosh, Cluster<DendrogramModel> parent, boolean flatten)	Make the cluster for the given object

Uses of WritableDoubleDataStore in elki.clustering.kmeans

Fields in elki.clustering.kmeans declared as WritableDoubleDataStore

Modifier and Type	Field	Description
(package private) WritableDoubleDataStore	HamerlyKMeans.Instance.lower	Lower bounds
(package private) WritableDoubleDataStore	HartiganWongKMeans.Instance.r1s	The value [NC(L1) * D(I,L1)^2] / [NC(L1) -1] will be remembered and will remain the same for Point I until cluster L1 is updated.
(package private) WritableDoubleDataStore	HamerlyKMeans.Instance.upper	Upper bounds
(package private) WritableDoubleDataStore	SimplifiedElkanKMeans.Instance.upper	Upper bounds
(package private) WritableDoubleDataStore	YinYangKMeans.Instance.upper	Upper bound

Uses of WritableDoubleDataStore in elki.clustering.kmeans.initialization

Fields in elki.clustering.kmeans.initialization declared as WritableDoubleDataStore

Modifier and Type	Field	Description
protected WritableDoubleDataStore	KMC2.Instance.weights	Weights
protected WritableDoubleDataStore	KMeansPlusPlus.Instance.weights	Weights
protected WritableDoubleDataStore	SphericalKMeansPlusPlus.Instance.weights	Weights

Uses of WritableDoubleDataStore in elki.clustering.kmeans.spherical

Fields in elki.clustering.kmeans.spherical declared as WritableDoubleDataStore

Modifier and Type	Field	Description
(package private) WritableDoubleDataStore	EuclideanSphericalHamerlyKMeans.Instance.lower	Lower bounds
(package private) WritableDoubleDataStore	SphericalHamerlyKMeans.Instance.lsim	Similarity lower bound.
(package private) WritableDoubleDataStore	SphericalSimplifiedElkanKMeans.Instance.lsim	Similarity lower bound.
(package private) WritableDoubleDataStore	SphericalSimplifiedHamerlyKMeans.Instance.lsim	Similarity lower bound.
(package private) WritableDoubleDataStore	EuclideanSphericalHamerlyKMeans.Instance.upper	Upper bounds
(package private) WritableDoubleDataStore	EuclideanSphericalSimplifiedElkanKMeans.Instance.upper	Upper bounds
(package private) WritableDoubleDataStore	SphericalHamerlyKMeans.Instance.usim	Similarity upper bound.
(package private) WritableDoubleDataStore	SphericalSimplifiedHamerlyKMeans.Instance.usim	Similarity upper bound.

Uses of WritableDoubleDataStore in elki.clustering.kmedoids

Fields in elki.clustering.kmedoids declared as WritableDoubleDataStore

Modifier and Type	Field	Description
(package private) WritableDoubleDataStore	CLARANS.Assignment.nearest	Distance to the nearest medoid of each point.
(package private) WritableDoubleDataStore	PAM.Instance.nearest	Distance to the nearest medoid of each point.
(package private) WritableDoubleDataStore	CLARANS.Assignment.second	Distance to the second nearest medoid.
(package private) WritableDoubleDataStore	PAM.Instance.second	Distance to the second nearest medoid.

Methods in elki.clustering.kmedoids with parameters of type WritableDoubleDataStore

Modifier and Type	Method	Description
protected double	ReynoldsPAM.Instance.computeReassignmentCost(DBIDRef h, WritableDoubleDataStore tnearest)	Compute the reassignment cost, for all medoids in one pass.
protected double	ReynoldsPAM.Instance.computeRemovalCost(int i, WritableDoubleDataStore tnearest)	Compute the cost of removing a medoid just once.

Uses of WritableDoubleDataStore in elki.clustering.kmedoids.initialization

Methods in elki.clustering.kmedoids.initialization with parameters of type WritableDoubleDataStore

Modifier and Type	Method	Description
static double	GreedyG.findMedoid(DBIDs ids, DistanceQuery<?> distQ, int j, DBIDArrayMIter miter, double bestm, WritableDoubleDataStore temp, WritableDoubleDataStore tempbest, WritableDoubleDataStore mindist)	Find the best medoid of a given fixed set.
protected static double	LAB.getMinDist(DBIDArrayIter j, DistanceQuery<?> distQ, DBIDArrayIter mi, WritableDoubleDataStore mindist)	Get the minimum distance to previous medoids.

Uses of WritableDoubleDataStore in elki.clustering.optics

Fields in elki.clustering.optics declared as WritableDoubleDataStore

Modifier and Type	Field	Description
(package private) WritableDoubleDataStore	ClusterOrder.reachability	Reachability storage.
protected WritableDoubleDataStore	GeneralizedOPTICS.Instance.reachability	Reachability storage.
(package private) WritableDoubleDataStore	OPTICSList.Instance.reachability	Reachability storage.
(package private) WritableDoubleDataStore	FastOPTICS.reachDist	Result: reachability distances

Constructors in elki.clustering.optics with parameters of type WritableDoubleDataStore

Constructor	Description
ClusterOrder(ArrayModifiableDBIDs ids, WritableDoubleDataStore reachability, WritableDBIDDataStore predecessor)	Constructor
CorrelationClusterOrder(ArrayModifiableDBIDs ids, WritableDoubleDataStore reachability, WritableDBIDDataStore predecessor, WritableIntegerDataStore corrdim)	Constructor.

Uses of WritableDoubleDataStore in elki.clustering.silhouette

Fields in elki.clustering.silhouette declared as WritableDoubleDataStore

Modifier and Type	Field	Description
protected WritableDoubleDataStore	FastMSC.Instance2.dm0	Distances to the first medoid.
protected WritableDoubleDataStore	FastMSC.Instance2.dm1	Distances to the second medoid.
(package private) WritableDoubleDataStore	PAMSIL.Instance.silhouettes	Store the per-point silhouette scores for plotting.

Uses of WritableDoubleDataStore in elki.clustering.subspace

Fields in elki.clustering.subspace declared as WritableDoubleDataStore

Modifier and Type	Field	Description
private WritableDoubleDataStore	DiSH.Instance.tmpDistance	Temporary storage of distances.

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

Constructor	Description
DiSHClusterOrder(ArrayModifiableDBIDs ids, WritableDoubleDataStore reachability, WritableDBIDDataStore predecessor, WritableIntegerDataStore corrdim, WritableDataStore<long[]> commonPreferenceVectors)	Constructor.

Uses of WritableDoubleDataStore in elki.database.datastore

Methods in elki.database.datastore that return WritableDoubleDataStore

Modifier and Type	Method	Description
WritableDoubleDataStore	DataStoreFactory.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, double def)	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.
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.

Uses of WritableDoubleDataStore in elki.database.datastore.memory

Classes in elki.database.datastore.memory that implement WritableDoubleDataStore

Modifier and Type	Class	Description
class	ArrayDoubleStore	A class to answer representation queries using the stored Array.
class	MapIntegerDBIDDoubleStore	Writable data store for double values.

Methods in elki.database.datastore.memory that return WritableDoubleDataStore

Modifier and Type	Method	Description
WritableDoubleDataStore	MemoryDataStoreFactory.makeDoubleStorage(DBIDs ids, int hints)
WritableDoubleDataStore	MemoryDataStoreFactory.makeDoubleStorage(DBIDs ids, int hints, double def)

Uses of WritableDoubleDataStore in elki.index.invertedlist

Fields in elki.index.invertedlist declared as WritableDoubleDataStore

Modifier and Type	Field	Description
protected WritableDoubleDataStore	InMemoryInvertedIndex.length	Length storage.

Methods in elki.index.invertedlist with parameters of type WritableDoubleDataStore

Modifier and Type	Method	Description
private double	InMemoryInvertedIndex.naiveQuery(V obj, WritableDoubleDataStore scores, HashSetModifiableDBIDs cands)	Query the most similar objects, abstract version.
private double	InMemoryInvertedIndex.naiveQueryDense(NumberVector obj, WritableDoubleDataStore scores, HashSetModifiableDBIDs cands)	Query the most similar objects, dense version.
private double	InMemoryInvertedIndex.naiveQuerySparse(SparseNumberVector obj, WritableDoubleDataStore scores, HashSetModifiableDBIDs cands)	Query the most similar objects, sparse version.

Uses of WritableDoubleDataStore in elki.outlier

Methods in elki.outlier with parameters of type WritableDoubleDataStore

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 void	DWOF.initializeRadii(DBIDs ids, KNNSearcher<DBIDRef> 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)

Uses of WritableDoubleDataStore in elki.outlier.anglebased

Methods in elki.outlier.anglebased with parameters of type WritableDoubleDataStore

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

Uses of WritableDoubleDataStore in elki.outlier.clustering

Methods in elki.outlier.clustering with parameters of type WritableDoubleDataStore

Modifier and Type	Method	Description
private void	CBLOF.computeCBLOFs(Relation<O> relation, WritableDoubleDataStore cblofs, DoubleMinMax cblofMinMax, java.util.List<? extends Cluster<MeanModel>> largeClusters, java.util.List<? extends Cluster<MeanModel>> smallClusters)	Compute the CBLOF scores for all the data.
private void	KMeansOutlierDetection.distanceScoring(Clustering<?> c, Relation<O> relation, NumberVectorDistance<? super O> distfunc, WritableDoubleDataStore scores, DoubleMinMax mm)	Simple distance-based scoring function.
private void	KMeansOutlierDetection.singletonsScoring(Clustering<?> c, Relation<O> relation, NumberVectorDistance<? super O> distfunc, WritableDoubleDataStore scores, DoubleMinMax mm)	Distance-based scoring that takes singletons into account.
private void	CBLOF.storeCBLOFScore(WritableDoubleDataStore cblofs, DoubleMinMax cblofMinMax, double cblof, DBIDIter iter)
private void	KMeansOutlierDetection.varianceScoring(Clustering<?> c, Relation<O> relation, NumberVectorDistance<? super O> distfunc, WritableDoubleDataStore scores, DoubleMinMax mm)	Variance-based scoring function.

Uses of WritableDoubleDataStore in elki.outlier.distance

Methods in elki.outlier.distance with parameters of type WritableDoubleDataStore

Modifier and Type	Method	Description
static void	SOS.nominateNeighbors(DBIDIter ignore, DBIDArrayIter di, double[] p, double norm, WritableDoubleDataStore scores)	Vote for neighbors not being outliers.
protected void	ReferenceBasedOutlierDetection.updateDensities(WritableDoubleDataStore rbod_score, DoubleDBIDList referenceDists)	Update the density estimates for each object.

Uses of WritableDoubleDataStore in elki.outlier.intrinsic

Methods in elki.outlier.intrinsic with parameters of type WritableDoubleDataStore

Modifier and Type	Method	Description
static void	ISOS.nominateNeighbors(DBIDIter ignore, DBIDArrayIter di, double[] p, double norm, WritableDoubleDataStore scores)	Vote for neighbors not being outliers.
static DoubleMinMax	ISOS.transformScores(WritableDoubleDataStore scores, DBIDs ids, double logPerp, double phi)	Transform scores

Uses of WritableDoubleDataStore in elki.outlier.lof

Fields in elki.outlier.lof declared as WritableDoubleDataStore

Modifier and Type	Field	Description
private WritableDoubleDataStore	FlexibleLOF.LOFResult.lofs	The LOF values of the objects.
private WritableDoubleDataStore	FlexibleLOF.LOFResult.lrds	The LRD values of the objects.

Methods in elki.outlier.lof that return WritableDoubleDataStore

Modifier and Type	Method	Description
WritableDoubleDataStore	FlexibleLOF.LOFResult.getLofs()	Get the LOF data store.
WritableDoubleDataStore	FlexibleLOF.LOFResult.getLrds()	Get the LRD data store.

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

Modifier and Type	Method	Description
protected void	COF.computeAverageChainingDistances(KNNSearcher<DBIDRef> 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(KNNSearcher<DBIDRef> knnq, DBIDs ids, DoubleDataStore acds, WritableDoubleDataStore cofs, DoubleMinMax cofminmax)	Compute Connectivity outlier factors.
protected void	INFLO.computeINFLO(Relation<O> relation, ModifiableDBIDs pruned, KNNSearcher<DBIDRef> knnq, WritableDataStore<ModifiableDBIDs> rNNminuskNNs, WritableDoubleDataStore inflos, DoubleMinMax inflominmax)	Compute the final INFLO scores.
protected void	FlexibleLOF.computeLOFs(KNNSearcher<DBIDRef> knnq, DBIDs ids, DoubleDataStore lrds, WritableDoubleDataStore lofs, DoubleMinMax lofminmax)	Computes the Local outlier factor (LOF) of the specified objects.
private void	LOF.computeLOFScores(KNNSearcher<DBIDRef> knnq, DBIDs ids, DoubleDataStore lrds, WritableDoubleDataStore lofs, DoubleMinMax lofminmax)	Compute local outlier factors.
protected void	FlexibleLOF.computeLRDs(KNNSearcher<DBIDRef> knnq, DBIDs ids, WritableDoubleDataStore lrds)	Computes the local reachability density (LRD) of the specified objects.
private void	LOF.computeLRDs(KNNSearcher<DBIDRef> knnq, DBIDs ids, WritableDoubleDataStore lrds)	Compute local reachability distances.
protected void	KDEOS.computeOutlierScores(KNNSearcher<DBIDRef> knnq, DBIDs ids, WritableDataStore<double[]> densities, WritableDoubleDataStore kdeos, DoubleMinMax minmax)	Compute the final KDEOS scores.
protected void	LoOP.computePDists(Relation<O> relation, KNNSearcher<DBIDRef> knn, WritableDoubleDataStore pdists)	Compute the probabilistic distances used by LoOP.
protected double	LoOP.computePLOFs(Relation<O> relation, KNNSearcher<DBIDRef> knn, WritableDoubleDataStore pdists, WritableDoubleDataStore plofs)	Compute the LOF values, using the pdist distances.
private void	SimplifiedLOF.computeSimplifiedLOFs(DBIDs ids, KNNSearcher<DBIDRef> knnq, WritableDoubleDataStore slrds, WritableDoubleDataStore lofs, DoubleMinMax lofminmax)	Compute the simplified LOF factors.
private void	SimplifiedLOF.computeSimplifiedLRDs(DBIDs ids, KNNSearcher<DBIDRef> knnq, WritableDoubleDataStore lrds)	Compute the simplified reachability densities.
private void	VarianceOfVolume.computeVolumes(KNNSearcher<DBIDRef> knnq, int dim, DBIDs ids, WritableDoubleDataStore vols)	Compute volumes
private void	VarianceOfVolume.computeVOVs(KNNSearcher<DBIDRef> knnq, DBIDs ids, DoubleDataStore vols, WritableDoubleDataStore vovs, DoubleMinMax vovminmax)	Compute variance of volumes.

Constructors in elki.outlier.lof with parameters of type WritableDoubleDataStore

Constructor	Description
LOFResult(OutlierResult result, KNNSearcher<DBIDRef> kNNRefer, KNNSearcher<DBIDRef> kNNReach, WritableDoubleDataStore lrds, WritableDoubleDataStore lofs)	Encapsulates information generated during a run of the FlexibleLOF algorithm.

Uses of WritableDoubleDataStore in elki.parallel.processor

Fields in elki.parallel.processor declared as WritableDoubleDataStore

Modifier and Type	Field	Description
(package private) WritableDoubleDataStore	WriteDoubleDataStoreProcessor.store	Store to write to

Constructors in elki.parallel.processor with parameters of type WritableDoubleDataStore

Constructor	Description
WriteDoubleDataStoreProcessor(WritableDoubleDataStore store)	Constructor.

Uses of WritableDoubleDataStore in elki.visualization.style

Fields in elki.visualization.style declared as WritableDoubleDataStore

Modifier and Type	Field	Description
(package private) WritableDoubleDataStore	ClusterStylingPolicy.intensities	Maps an ID to its best assignment value.