Package elki.index.preprocessed.knn

Class MetricalIndexApproximationMaterializeKNNPreprocessor<O extends NumberVector,N extends Node<E>,E extends MTreeEntry>

java.lang.Object

elki.index.preprocessed.knn.AbstractMaterializeKNNPreprocessor<O>

elki.index.preprocessed.knn.MetricalIndexApproximationMaterializeKNNPreprocessor<O,N,E>

Type Parameters:

O - the type of database objects the preprocessor can be applied to

N - the type of spatial nodes in the spatial index

E - the type of spatial entries in the spatial index

All Implemented Interfaces:

Index, KNNIndex<O>

@Title("Spatial Approximation Materialize kNN Preprocessor")
@Description("Caterializes the (approximate) k nearest neighbors of objects of a database using a spatial approximation.")
public class MetricalIndexApproximationMaterializeKNNPreprocessor<O extends NumberVector,N extends Node<E>,E extends MTreeEntry>
extends AbstractMaterializeKNNPreprocessor<O>

A preprocessor for annotation of the k nearest neighbors (and their distances) to each database object. Used for example by LOF. TODO correct handling of datastore events

Since:

0.2

Author:

Erich Schubert

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static class	MetricalIndexApproximationMaterializeKNNPreprocessor.Factory<O extends NumberVector,N extends Node<E>,E extends MTreeEntry>	The parameterizable factory.

Field Summary

Fields

Modifier and Type	Field	Description
private static Logging	LOG	Logger to use

Fields inherited from class elki.index.preprocessed.knn.AbstractMaterializeKNNPreprocessor

distance, distanceQuery, k, relation, storage

Constructor Summary

Constructors

Constructor	Description
MetricalIndexApproximationMaterializeKNNPreprocessor(Relation<O> relation, Distance<? super O> distance, int k)	Constructor

Method Summary

Modifier and Type	Method	Description
protected Logging	getLogger()	Get the classes static logger.
private MetricalIndexTree<O,N,E>	getMetricalIndex(Relation<? extends O> relation)	Do some (limited) type checking, then cast the database into a spatial database.
protected void	preprocess()	Perform the preprocessing step.

Methods inherited from class elki.index.preprocessed.knn.AbstractMaterializeKNNPreprocessor

createStorage, get, getDistanceQuery, getK, initialize, kNNByDBID, kNNByObject

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface elki.index.Index

logStatistics

Field Detail

LOG

private static final Logging LOG

Logger to use

Constructor Detail

MetricalIndexApproximationMaterializeKNNPreprocessor

public MetricalIndexApproximationMaterializeKNNPreprocessor(Relation<O> relation,
                                                            Distance<? super O> distance,
                                                            int k)

Constructor

Parameters:

relation - Relation to preprocess

distance - the distance function to use

k - query k

Method Detail

preprocess

protected void preprocess()

Description copied from class: AbstractMaterializeKNNPreprocessor

Perform the preprocessing step.

Specified by:

preprocess in class AbstractMaterializeKNNPreprocessor<O extends NumberVector>

getMetricalIndex

private MetricalIndexTree<O,N,E> getMetricalIndex(Relation<? extends O> relation)
                                                       throws java.lang.IllegalStateException

Do some (limited) type checking, then cast the database into a spatial database.

Parameters:

relation - Database

Returns:

Metrical index

Throws:

java.lang.IllegalStateException - when the cast fails.

getLogger

protected Logging getLogger()

Description copied from class: AbstractMaterializeKNNPreprocessor

Get the classes static logger.

Specified by:

getLogger in class AbstractMaterializeKNNPreprocessor<O extends NumberVector>

Returns:

Logger