de.lmu.ifi.dbs.elki.index.tree.spatial.kd

Class SmallMemoryKDTree.KDTreeKNNQuery

java.lang.Object

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

de.lmu.ifi.dbs.elki.index.tree.spatial.kd.SmallMemoryKDTree.KDTreeKNNQuery

All Implemented Interfaces:

DatabaseQuery, KNNQuery<O>

Enclosing class:

SmallMemoryKDTree<O extends NumberVector>

public class SmallMemoryKDTree.KDTreeKNNQuery
extends AbstractDistanceKNNQuery<O>

kNN query for the k-d-tree.

Author:

Erich Schubert

Field Summary

Fields

Modifier and Type	Field and Description
private Norm<? super O>	norm Norm to use.

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
KDTreeKNNQuery(DistanceQuery<O> distanceQuery, Norm<? super O> norm) Constructor.

Method Summary

Modifier and Type	Method and Description
KNNList	getKNNForObject(O obj, int k) Get the k nearest neighbors for a particular id.
private double	kdKNNSearch(int left, int right, int axis, O query, KNNHeap knns, DoubleDBIDListIter iter, double maxdist) Perform a kNN search on the kd-tree.

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

getKNNForBulkDBIDs, getKNNForDBID

Methods inherited from class java.lang.Object

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

Field Detail

norm

private Norm<? super O extends NumberVector> norm

Norm to use.

Constructor Detail

KDTreeKNNQuery

public KDTreeKNNQuery(DistanceQuery<O> distanceQuery,
                      Norm<? super O> norm)

Constructor.

Parameters:

distanceQuery - Distance query

norm - Norm to use

Method Detail

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 extends NumberVector>

Specified by:

getKNNForObject in class AbstractDistanceKNNQuery<O extends NumberVector>

Parameters:

obj - Query object

k - Number of neighbors requested

Returns:

neighbors

kdKNNSearch

private double kdKNNSearch(int left,
                           int right,
                           int axis,
                           O query,
                           KNNHeap knns,
                           DoubleDBIDListIter iter,
                           double maxdist)

Perform a kNN search on the kd-tree.

Parameters:

left - Subtree begin

right - Subtree end (exclusive)

axis - Current splitting axis

query - Query object

knns - kNN heap

iter - Iterator variable (reduces memory footprint!)

maxdist - Current upper bound of kNN distance.

Returns:

New upper bound of kNN distance.