de.lmu.ifi.dbs.elki.index.preprocessed.knn

Class KNNJoinMaterializeKNNPreprocessor<V extends NumberVector<?>,D extends Distance<D>>

java.lang.Object

de.lmu.ifi.dbs.elki.index.AbstractIndex<O>

de.lmu.ifi.dbs.elki.index.preprocessed.AbstractPreprocessorIndex<O,T>

de.lmu.ifi.dbs.elki.index.preprocessed.knn.AbstractMaterializeKNNPreprocessor<V,D,KNNList<D>>

de.lmu.ifi.dbs.elki.index.preprocessed.knn.KNNJoinMaterializeKNNPreprocessor<V,D>

Type Parameters:

V - vector type

D - distance type

All Implemented Interfaces:

Index, KNNIndex<V>, Result

public class KNNJoinMaterializeKNNPreprocessor<V extends NumberVector<?>,D extends Distance<D>>
extends AbstractMaterializeKNNPreprocessor<V,D,KNNList<D>>

Class to materialize the kNN using a spatial join on an R-tree.

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	KNNJoinMaterializeKNNPreprocessor.Factory<O extends NumberVector<?>,D extends Distance<D>> The parameterizable factory.

Field Summary

Fields

Modifier and Type	Field and Description
private static Logging	LOG Logging class.

Fields inherited from class de.lmu.ifi.dbs.elki.index.preprocessed.knn.AbstractMaterializeKNNPreprocessor

distanceFunction, distanceQuery, k

Fields inherited from class de.lmu.ifi.dbs.elki.index.preprocessed.AbstractPreprocessorIndex

storage

Fields inherited from class de.lmu.ifi.dbs.elki.index.AbstractIndex

relation

Constructor Summary

Constructors

Constructor and Description
KNNJoinMaterializeKNNPreprocessor(Relation<V> relation, DistanceFunction<? super V,D> distanceFunction, int k) Constructor.

Method Summary

Methods

Modifier and Type	Method and Description
protected Logging	getLogger() Get the classes static logger.
String	getLongName() A "pretty" name for the result, for use in titles, captions and menus.
String	getShortName() A short name for the result, useful for file names.
void	logStatistics() Send statistics to the logger, if enabled.
protected void	preprocess() Perform the preprocessing step.

Methods inherited from class de.lmu.ifi.dbs.elki.index.preprocessed.knn.AbstractMaterializeKNNPreprocessor

createStorage, get, getDistanceFactory, getDistanceQuery, getK, getKNNQuery, initialize

Methods inherited from class java.lang.Object

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

Field Detail

LOG

private static final Logging LOG

Logging class.

Constructor Detail

KNNJoinMaterializeKNNPreprocessor

public KNNJoinMaterializeKNNPreprocessor(Relation<V> relation,
                                 DistanceFunction<? super V,D> distanceFunction,
                                 int k)

Constructor.

Parameters:

relation - Relation to index

distanceFunction - Distance function

k - k

Method Detail

preprocess

protected void preprocess()

Description copied from class: AbstractMaterializeKNNPreprocessor

Perform the preprocessing step.

Specified by:

preprocess in class AbstractMaterializeKNNPreprocessor<V extends NumberVector<?>,D extends Distance<D>,KNNList<D extends Distance<D>>>

getLogger

protected Logging getLogger()

Description copied from class: AbstractPreprocessorIndex

Get the classes static logger.

Specified by:

getLogger in class AbstractPreprocessorIndex<V extends NumberVector<?>,KNNList<D extends Distance<D>>>

Returns:

Logger

getLongName

public String getLongName()

Description copied from interface: Result

A "pretty" name for the result, for use in titles, captions and menus.

Specified by:

getLongName in interface Result

Specified by:

getLongName in class AbstractIndex<V extends NumberVector<?>>

Returns:

result name

getShortName

public String getShortName()

Description copied from interface: Result

A short name for the result, useful for file names.

Specified by:

getShortName in interface Result

Specified by:

getShortName in class AbstractIndex<V extends NumberVector<?>>

Returns:

result name

logStatistics

public void logStatistics()

Description copied from interface: Index

Send statistics to the logger, if enabled. Note: you must have set the logging level appropriately before initializing the index! Otherwise, the index might not have collected the desired statistics.