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

Class AbstractMaterializeKNNPreprocessor<O,D extends Distance<D>,T extends KNNResult<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<O,D,T>

Type Parameters:

O - Object type

D - Distance type

All Implemented Interfaces:

Index, KNNIndex<O>, Result

Direct Known Subclasses:

KNNJoinMaterializeKNNPreprocessor, MaterializeKNNPreprocessor, MetricalIndexApproximationMaterializeKNNPreprocessor, PartitionApproximationMaterializeKNNPreprocessor, RandomSampleKNNPreprocessor, SpatialApproximationMaterializeKNNPreprocessor

public abstract class AbstractMaterializeKNNPreprocessor<O,D extends Distance<D>,T extends KNNResult<D>>
extends AbstractPreprocessorIndex<O,T>
implements KNNIndex<O>

Abstract base class for KNN Preprocessors.

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	AbstractMaterializeKNNPreprocessor.Factory<O,D extends Distance<D>,T extends KNNResult<D>> The parameterizable factory.

Field Summary

Fields

Modifier and Type	Field and Description
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.

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

Method Summary

Methods

Modifier and Type	Method and Description
(package private) void	createStorage() Create the default storage.
KNNResult<D>	get(DBIDRef id) Get the k nearest neighbors.
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.
void	insertAll(DBIDs ids) Inserts the specified objects into this index.
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

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

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.

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.

get

public KNNResult<D> get(DBIDRef id)

Get the k nearest neighbors.

Parameters:

id - Object ID

Returns:

Neighbors

createStorage

void createStorage()

Create the default storage.

insertAll

public void insertAll(DBIDs ids)

Description copied from interface: Index

Inserts the specified objects into this index. If a bulk load mode is implemented, the objects are inserted in one bulk.

Specified by:

insertAll in interface Index

Overrides:

insertAll in class AbstractIndex<O>

Parameters:

ids - the objects to be inserted

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