de.lmu.ifi.dbs.elki.database.query.knn

Class LinearScanPrimitiveDistanceKNNQuery<O,D extends Distance<D>>

java.lang.Object

de.lmu.ifi.dbs.elki.database.query.AbstractDataBasedQuery<O>

de.lmu.ifi.dbs.elki.database.query.knn.AbstractDistanceKNNQuery<O,D>

de.lmu.ifi.dbs.elki.database.query.knn.LinearScanKNNQuery<O,D>

de.lmu.ifi.dbs.elki.database.query.knn.LinearScanPrimitiveDistanceKNNQuery<O,D>

All Implemented Interfaces:

DatabaseQuery, KNNQuery<O,D>, LinearScanQuery

Direct Known Subclasses:

LinearScanRawDoubleDistanceKNNQuery

public class LinearScanPrimitiveDistanceKNNQuery<O,D extends Distance<D>>
extends LinearScanKNNQuery<O,D>

Instance of this query for a particular database. This is a subtle optimization: for primitive queries, it is clearly faster to retrieve the query object from the relation only once!

Field Summary

Fields inherited from class de.lmu.ifi.dbs.elki.database.query.knn.AbstractDistanceKNNQuery

distanceQuery

Fields inherited from class de.lmu.ifi.dbs.elki.database.query.AbstractDataBasedQuery

relation

Fields inherited from interface de.lmu.ifi.dbs.elki.database.query.DatabaseQuery

HINT_BULK, HINT_EXACT, HINT_HEAVY_USE, HINT_NO_CACHE, HINT_OPTIMIZED_ONLY, HINT_SINGLE

Constructor Summary

Constructors

Constructor and Description
LinearScanPrimitiveDistanceKNNQuery(PrimitiveDistanceQuery<O,D> distanceQuery) Constructor.

Method Summary

Methods

Modifier and Type	Method and Description
List<KNNResult<D>>	getKNNForBulkDBIDs(ArrayDBIDs ids, int k) Bulk query method
void	getKNNForBulkHeaps(Map<DBID,KNNHeap<D>> heaps) Bulk query method configured by a map.
KNNResult<D>	getKNNForDBID(DBIDRef id, int k) Get the k nearest neighbors for a particular id.
protected void	linearScanBatchKNN(List<O> objs, List<KNNHeap<D>> heaps) Perform a linear scan batch kNN for primitive distance functions.

Methods inherited from class de.lmu.ifi.dbs.elki.database.query.knn.LinearScanKNNQuery

getKNNForObject

Methods inherited from class de.lmu.ifi.dbs.elki.database.query.AbstractDataBasedQuery

getRelation

Methods inherited from class java.lang.Object

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

Constructor Detail

LinearScanPrimitiveDistanceKNNQuery

public LinearScanPrimitiveDistanceKNNQuery(PrimitiveDistanceQuery<O,D> distanceQuery)

Constructor.

Parameters:

distanceQuery - Distance function to use

Method Detail

linearScanBatchKNN

protected void linearScanBatchKNN(List<O> objs,
                      List<KNNHeap<D>> heaps)

Perform a linear scan batch kNN for primitive distance functions.

Parameters:

objs - Objects list

heaps - Heaps array

getKNNForDBID

public KNNResult<D> getKNNForDBID(DBIDRef id,
                         int k)

Description copied from interface: KNNQuery

Get the k nearest neighbors for a particular id.

Specified by:

getKNNForDBID in interface KNNQuery<O,D extends Distance<D>>

Overrides:

getKNNForDBID in class LinearScanKNNQuery<O,D extends Distance<D>>

Parameters:

id - query object ID

k - Number of neighbors requested

Returns:

neighbors

getKNNForBulkDBIDs

public List<KNNResult<D>> getKNNForBulkDBIDs(ArrayDBIDs ids,
                                    int k)

Description copied from interface: KNNQuery

Bulk query method

Specified by:

getKNNForBulkDBIDs in interface KNNQuery<O,D extends Distance<D>>

Overrides:

getKNNForBulkDBIDs in class LinearScanKNNQuery<O,D extends Distance<D>>

Parameters:

ids - query object IDs

k - Number of neighbors requested

Returns:

neighbors

getKNNForBulkHeaps

public void getKNNForBulkHeaps(Map<DBID,KNNHeap<D>> heaps)

Description copied from interface: KNNQuery

Bulk query method configured by a map. Warning: this API is not optimal, and might be removed soon (in fact, it is used in a single place)

Specified by:

getKNNForBulkHeaps in interface KNNQuery<O,D extends Distance<D>>

Overrides:

getKNNForBulkHeaps in class LinearScanKNNQuery<O,D extends Distance<D>>

Parameters:

heaps - Map of heaps to fill.