de.lmu.ifi.dbs.elki.index.preprocessed.knn
Class AbstractMaterializeKNNPreprocessor<O,D extends Distance<D>>

java.lang.Object
  de.lmu.ifi.dbs.elki.index.AbstractIndex<O>
      de.lmu.ifi.dbs.elki.index.preprocessed.AbstractPreprocessorIndex<O,List<DistanceResultPair<D>>>
          de.lmu.ifi.dbs.elki.index.preprocessed.knn.AbstractMaterializeKNNPreprocessor<O,D>

Type Parameters:

O - Object type

D - Distance type

All Implemented Interfaces:

Index, KNNIndex<O>, Result

Direct Known Subclasses:

MaterializeKNNPreprocessor, MetricalIndexApproximationMaterializeKNNPreprocessor, PartitionApproximationMaterializeKNNPreprocessor, SpatialApproximationMaterializeKNNPreprocessor

public abstract class AbstractMaterializeKNNPreprocessor<O,D extends Distance<D>>
extends AbstractPreprocessorIndex<O,List<DistanceResultPair<D>>>
implements KNNIndex<O>

Abstract base class for KNN Preprocessors.

Nested Class Summary

static class

AbstractMaterializeKNNPreprocessor.Factory<O,D extends Distance<D>> The parameterizable factory.

Field Summary

protected DistanceFunction<? super O,D>	distanceFunction The distance function to be used.
protected DistanceQuery<O,D>	distanceQuery The distance query we used.
protected int	k The query k value.
protected EventListenerList	listenerList Holds the listener.

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

AbstractMaterializeKNNPreprocessor(Relation<O> relation, DistanceFunction<? super O,D> distanceFunction, int k)
Constructor.

Method Summary

D	getDistanceFactory() Get the distance factory.
DistanceQuery<O,D>	getDistanceQuery() The distance query we used.
int	getK() Get the value of 'k' supported by this preprocessor.
<S extends Distance<S>> KNNQuery<O,S>	getKNNQuery(DistanceQuery<O,S> distanceQuery, Object... hints) Get a KNN query object for the given distance query and k.
protected abstract void	preprocess() Perform the preprocessing step.

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

getLogger

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

delete, deleteAll, getLongName, getPageFileStatistics, getShortName, insert, insertAll

Methods inherited from class java.lang.Object

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

Methods inherited from interface de.lmu.ifi.dbs.elki.index.Index

delete, deleteAll, getPageFileStatistics, insert, insertAll

Methods inherited from interface de.lmu.ifi.dbs.elki.result.Result

getLongName, getShortName

Field Detail

k

protected final int k

The query k value.

distanceFunction

protected final DistanceFunction<? super O,D extends Distance<D>> distanceFunction

The distance function to be used.

distanceQuery

protected final DistanceQuery<O,D extends Distance<D>> distanceQuery

The distance query we used.

listenerList

protected final EventListenerList listenerList

Holds the listener.

Constructor Detail

AbstractMaterializeKNNPreprocessor

public AbstractMaterializeKNNPreprocessor(Relation<O> relation,
                                          DistanceFunction<? super O,D> distanceFunction,
                                          int k)

Constructor.

Parameters:

relation - Relation

distanceFunction - Distance function

k - k

Method Detail

getDistanceFactory

public D getDistanceFactory()

Get the distance factory.

Returns:

distance factory

getDistanceQuery

public DistanceQuery<O,D> getDistanceQuery()

The distance query we used.

Returns:

Distance query

getK

public int getK()

Get the value of 'k' supported by this preprocessor.

Returns:

k

preprocess

protected abstract void preprocess()

Perform the preprocessing step.

getKNNQuery

public <S extends Distance<S>> KNNQuery<O,S> getKNNQuery(DistanceQuery<O,S> distanceQuery,
                                                         Object... hints)

Description copied from interface: KNNIndex

Get a KNN query object for the given distance query and k. This function MAY return null, when the given distance is not supported!

Specified by:

getKNNQuery in interface KNNIndex<O>

Type Parameters:

S - Distance type

Parameters:

distanceQuery - Distance query

hints - Hints for the optimizer

Returns:

KNN Query object or null