Uses of Interface
de.lmu.ifi.dbs.elki.database.datastore.WritableDataStore

Packages that use WritableDataStore

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.
de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical
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.outlier	Outlier detection algorithms
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.index.preprocessed	Index structure based on preprocessors
de.lmu.ifi.dbs.elki.index.preprocessed.knn	Indexes providing KNN and rKNN data.
de.lmu.ifi.dbs.elki.result.optics	Result classes for OPTICS.
tutorial.clustering	Classes from the tutorial on implementing a custom k-means variation.

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

Methods in de.lmu.ifi.dbs.elki.algorithm that return WritableDataStore

Modifier and Type	Method and Description
WritableDataStore<KNNList<D>>	KNNJoin.run(Database database, Relation<V> relation) Joins in the given spatial database to each object its k-nearest neighbors.

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

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

Modifier and Type	Method and Description
static double	EM.assignProbabilitiesToInstances(Relation<? extends NumberVector<?>> relation, double[] normDistrFactor, Vector[] means, Matrix[] invCovMatr, double[] clusterWeights, WritableDataStore<double[]> probClusterIGivenX) Assigns the current probability values to the instances in the database and compute the expectation value of the current mixture of distributions.
static void	EM.recomputeCovarianceMatrices(Relation<? extends NumberVector<?>> relation, WritableDataStore<double[]> probClusterIGivenX, Vector[] means, Matrix[] covarianceMatrices, int dimensionality) Recompute the covariance matrixes.

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

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

Modifier and Type	Method and Description
private void	SLINK.step1(DBIDRef id, WritableDBIDDataStore pi, WritableDataStore<D> lambda) First step: Initialize P(id) = id, L(id) = infinity.
private void	SLINK.step2(DBIDRef id, DBIDs processedIDs, DistanceQuery<O,D> distFunc, WritableDataStore<D> m) Second step: Determine the pairwise distances from all objects in the pointer representation to the new object with the specified id.
private void	SLINK.step3(DBIDRef id, WritableDBIDDataStore pi, WritableDataStore<D> lambda, DBIDs processedIDs, WritableDataStore<D> m) Third step: Determine the values for P and L
private void	SLINK.step3(DBIDRef id, WritableDBIDDataStore pi, WritableDataStore<D> lambda, DBIDs processedIDs, WritableDataStore<D> m) Third step: Determine the values for P and L
private void	SLINK.step4(DBIDRef id, WritableDBIDDataStore pi, WritableDataStore<D> lambda, DBIDs processedIDs) Fourth step: Actualize the clusters if necessary

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

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

Modifier and Type	Method and Description
private void	P3C.assignUnassigned(Relation<V> relation, WritableDataStore<double[]> probClusterIGivenX, Vector[] means, Matrix[] invCovMatr, double[] clusterWeights, ModifiableDBIDs unassigned) Assign unassigned objects to best candidate based on shortest Mahalanobis distance.
private void	P3C.computeFuzzyMembership(Relation<V> relation, ArrayList<P3C.Signature> clusterCores, ModifiableDBIDs unassigned, WritableDataStore<double[]> probClusterIGivenX, double[] clusterWeights) Computes a fuzzy membership with the weights based on which cluster cores each data point is part of.
private ArrayList<P3C.ClusterCandidate>	P3C.hardClustering(WritableDataStore<double[]> probClusterIGivenX, List<P3C.Signature> clusterCores, DBIDs dbids) Creates a hard clustering from the specified soft membership matrix.

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

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

Modifier and Type	Method and Description
private void	DWOF.clusterData(DBIDs ids, RangeQuery<O,D> 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 WritableDataStore in de.lmu.ifi.dbs.elki.database.datastore

Subinterfaces of WritableDataStore in de.lmu.ifi.dbs.elki.database.datastore

Modifier and Type	Interface and Description
interface	WritableDBIDDataStore Data store specialized for doubles.
interface	WritableDoubleDataStore Data store specialized for doubles.
interface	WritableDoubleDistanceDataStore Data store specialized for doubles.
interface	WritableIntegerDataStore Data store specialized for doubles.

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

Modifier and Type	Method and Description
<T> WritableDataStore<T>	WritableRecordStore.getStorage(int col, Class<? super T> datatype) Get a WritableDataStore instance for a particular record column.
static <T> WritableDataStore<T>	DataStoreUtil.makeStorage(DBIDs ids, int hints, 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, Class<? super T> dataclass) Make a new storage, to associate the given ids with an object of class dataclass.

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

Classes in de.lmu.ifi.dbs.elki.database.datastore.memory that implement WritableDataStore

Modifier and Type	Class and Description
class	ArrayDBIDStore A class to answer representation queries using the stored Array.
class	ArrayDoubleDistanceStore A class to answer representation queries using the stored Array.
class	ArrayDoubleStore A class to answer representation queries using the stored Array.
class	ArrayIntegerStore A class to answer representation queries using the stored Array.
protected class	ArrayRecordStore.StorageAccessor<T> Access a single record in the given data.
class	ArrayStore<T> A class to answer representation queries using the stored Array.
class	MapIntegerDBIDDBIDStore Writable data store for double values.
class	MapIntegerDBIDDoubleDistanceStore Writable data store for double values.
class	MapIntegerDBIDDoubleStore Writable data store for double values.
class	MapIntegerDBIDIntegerStore Writable data store for double values.
protected class	MapIntegerDBIDRecordStore.StorageAccessor<T> Access a single record in the given data.
class	MapIntegerDBIDStore<T> A class to answer representation queries using a map.
protected class	MapRecordStore.StorageAccessor<T> Access a single record in the given data.
class	MapStore<T> A class to answer representation queries using a map.

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

Modifier and Type	Method and Description
<T> WritableDataStore<T>	MapIntegerDBIDRecordStore.getStorage(int col, Class<? super T> datatype)
<T> WritableDataStore<T>	ArrayRecordStore.getStorage(int col, Class<? super T> datatype)
<T> WritableDataStore<T>	MapRecordStore.getStorage(int col, Class<? super T> datatype)
<T> WritableDataStore<T>	MemoryDataStoreFactory.makeStorage(DBIDs ids, int hints, Class<? super T> dataclass)

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

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

Modifier and Type	Field and Description
protected WritableDataStore<R>	AbstractPreprocessorIndex.storage The data store.

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

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

Modifier and Type	Field and Description
private WritableDataStore<TreeSet<DistanceDBIDPair<D>>>	MaterializeKNNAndRKNNPreprocessor.materialized_RkNN Additional data storage for RkNN.

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

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

Modifier and Type	Field and Description
private WritableDataStore<ClusterOrderEntry<D>>	ClusterOrderResult.map Map of object IDs to their cluster order entry

Uses of WritableDataStore in tutorial.clustering

Methods in tutorial.clustering that return WritableDataStore

Modifier and Type	Method and Description
protected WritableDataStore<SameSizeKMeansAlgorithm.Meta>	SameSizeKMeansAlgorithm.initializeMeta(Relation<V> relation, List<? extends NumberVector<?>> means) Initialize the metadata storage.

Methods in tutorial.clustering with parameters of type WritableDataStore

Modifier and Type	Method and Description
protected ArrayModifiableDBIDs	SameSizeKMeansAlgorithm.initialAssignment(List<ModifiableDBIDs> clusters, WritableDataStore<SameSizeKMeansAlgorithm.Meta> metas, DBIDs ids)
protected List<? extends NumberVector<?>>	SameSizeKMeansAlgorithm.refineResult(Relation<V> relation, List<? extends NumberVector<?>> means, List<ModifiableDBIDs> clusters, WritableDataStore<SameSizeKMeansAlgorithm.Meta> metas, ArrayModifiableDBIDs tids) Perform k-means style iterations to improve the clustering result.
protected void	SameSizeKMeansAlgorithm.transfer(WritableDataStore<SameSizeKMeansAlgorithm.Meta> metas, SameSizeKMeansAlgorithm.Meta meta, ModifiableDBIDs src, ModifiableDBIDs dst, DBIDRef id, Integer dstnum) Transfer a single element from one cluster to another.
protected void	SameSizeKMeansAlgorithm.updateDistances(Relation<V> relation, List<? extends NumberVector<?>> means, WritableDataStore<SameSizeKMeansAlgorithm.Meta> metas, PrimitiveDoubleDistanceFunction<NumberVector<?>> df) Compute the distances of each object to all means.