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

Class LinearScanPrimitiveDistanceKNNQuery<O>

java.lang.Object

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

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

All Implemented Interfaces:

DatabaseQuery, KNNQuery<O>, LinearScanQuery

Direct Known Subclasses:

LinearScanEuclideanDistanceKNNQuery

public class LinearScanPrimitiveDistanceKNNQuery<O>
extends AbstractDistanceKNNQuery<O>
implements LinearScanQuery

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!

Author:

Erich Schubert

Field Summary

Fields

Modifier and Type	Field and Description
private PrimitiveDistanceFunction<? super O>	rawdist Unboxed distance function.

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

distanceQuery, 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> distanceQuery) Constructor.

Method Summary

Methods

Modifier and Type	Method and Description
List<KNNList>	getKNNForBulkDBIDs(ArrayDBIDs ids, int k) Bulk query method
KNNList	getKNNForDBID(DBIDRef id, int k) Get the k nearest neighbors for a particular id.
KNNList	getKNNForObject(O obj, int k) Get the k nearest neighbors for a particular id.
private KNNHeap	linearScan(Relation<? extends O> relation, DBIDIter iter, O obj, KNNHeap heap) Main loop of the linear scan.
protected void	linearScanBatchKNN(List<O> objs, List<KNNHeap> heaps) Perform a linear scan batch kNN for primitive distance functions.

Methods inherited from class java.lang.Object

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

Field Detail

rawdist

private PrimitiveDistanceFunction<? super O> rawdist

Unboxed distance function.

Constructor Detail

LinearScanPrimitiveDistanceKNNQuery

public LinearScanPrimitiveDistanceKNNQuery(PrimitiveDistanceQuery<O> distanceQuery)

Constructor.

Parameters:

distanceQuery - Distance function to use

Method Detail

getKNNForDBID

public KNNList 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>

Overrides:

getKNNForDBID in class AbstractDistanceKNNQuery<O>

Parameters:

id - query object ID

k - Number of neighbors requested

Returns:

neighbors

getKNNForObject

public KNNList getKNNForObject(O obj,
                      int k)

Description copied from interface: KNNQuery

Get the k nearest neighbors for a particular id.

Specified by:

getKNNForObject in interface KNNQuery<O>

Specified by:

getKNNForObject in class AbstractDistanceKNNQuery<O>

Parameters:

obj - Query object

k - Number of neighbors requested

Returns:

neighbors

linearScan

private KNNHeap linearScan(Relation<? extends O> relation,
                 DBIDIter iter,
                 O obj,
                 KNNHeap heap)

Main loop of the linear scan.

Parameters:

relation - Data relation

iter - ID iterator

obj - Query object

heap - Output heap

Returns:

Heap

getKNNForBulkDBIDs

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

Description copied from interface: KNNQuery

Bulk query method

Specified by:

getKNNForBulkDBIDs in interface KNNQuery<O>

Overrides:

getKNNForBulkDBIDs in class AbstractDistanceKNNQuery<O>

Parameters:

ids - query object IDs

k - Number of neighbors requested

Returns:

neighbors

linearScanBatchKNN

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

Perform a linear scan batch kNN for primitive distance functions.

Parameters:

objs - Objects list

heaps - Heaps array