de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.query

Class GenericRStarTreeKNNQuery<O extends SpatialComparable,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.index.tree.spatial.rstarvariants.query.GenericRStarTreeKNNQuery<O,D>

All Implemented Interfaces:

DatabaseQuery, KNNQuery<O,D>

@Reference(authors="G. R. Hjaltason, H. Samet",
           title="Ranking in spatial databases",
           booktitle="Advances in Spatial Databases - 4th Symposium, SSD\'95",
           url="http://dx.doi.org/10.1007/3-540-60159-7_6")
public class GenericRStarTreeKNNQuery<O extends SpatialComparable,D extends Distance<D>>
extends AbstractDistanceKNNQuery<O,D>

Instance of a KNN query for a particular spatial index. Reference:

G. R. Hjaltason, H. Samet
Ranking in spatial databases
In: 4th Symposium on Advances in Spatial Databases, SSD'95

Field Summary

Fields

Modifier and Type	Field and Description
protected SpatialPrimitiveDistanceFunction<? super O,D>	distanceFunction Spatial primitive distance function
protected AbstractRStarTree<?,?>	tree The index to use

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
GenericRStarTreeKNNQuery(AbstractRStarTree<?,?> tree, SpatialDistanceQuery<O,D> distanceQuery) Constructor.

Method Summary

Methods

Modifier and Type	Method and Description
protected void	batchNN(AbstractRStarTreeNode<?,?> node, Map<DBID,KNNHeap<D>> knnLists) Performs a batch knn query.
protected void	doKNNQuery(O object, KNNHeap<D> knnList) Performs a k-nearest neighbor query for the given NumberVector with the given parameter k and the according distance function.
private D	expandNode(O object, KNNHeap<D> knnList, Heap<GenericDistanceSearchCandidate<D>> pq, D maxDist, int nodeID)
List<KNNResult<D>>	getKNNForBulkDBIDs(ArrayDBIDs ids, int k) Bulk query method
KNNResult<D>	getKNNForDBID(DBIDRef id, int k) Get the k nearest neighbors for a particular id.
KNNResult<D>	getKNNForObject(O obj, int k) Get the k nearest neighbors for a particular id.
protected List<DistanceEntry<D,SpatialEntry>>	getSortedEntries(AbstractRStarTreeNode<?,?> node, DBIDs ids) Sorts the entries of the specified node according to their minimum distance to the specified objects.

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

Field Detail

tree

protected final AbstractRStarTree<?,?> tree

The index to use

distanceFunction

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

Spatial primitive distance function

Constructor Detail

GenericRStarTreeKNNQuery

public GenericRStarTreeKNNQuery(AbstractRStarTree<?,?> tree,
                        SpatialDistanceQuery<O,D> distanceQuery)

Constructor.

Parameters:

tree - Index to use

distanceQuery - Distance query to use

Method Detail

doKNNQuery

protected void doKNNQuery(O object,
              KNNHeap<D> knnList)

Performs a k-nearest neighbor query for the given NumberVector with the given parameter k and the according distance function. The query result is in ascending order to the distance to the query object.

Parameters:

object - the query object

knnList - the knn list containing the result

expandNode

private D expandNode(O object,
           KNNHeap<D> knnList,
           Heap<GenericDistanceSearchCandidate<D>> pq,
           D maxDist,
           int nodeID)

batchNN

protected void batchNN(AbstractRStarTreeNode<?,?> node,
           Map<DBID,KNNHeap<D>> knnLists)

Performs a batch knn query.

Parameters:

node - the node for which the query should be performed

knnLists - a map containing the knn lists for each query objects

getSortedEntries

protected List<DistanceEntry<D,SpatialEntry>> getSortedEntries(AbstractRStarTreeNode<?,?> node,
                                                   DBIDs ids)

Sorts the entries of the specified node according to their minimum distance to the specified objects.

Parameters:

node - the node

ids - the id of the objects

Returns:

a list of the sorted entries

getKNNForObject

public KNNResult<D> 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 SpatialComparable,D extends Distance<D>>

Specified by:

getKNNForObject in class AbstractDistanceKNNQuery<O extends SpatialComparable,D extends Distance<D>>

Parameters:

obj - Query object

k - Number of neighbors requested

Returns:

neighbors

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 extends SpatialComparable,D extends Distance<D>>

Specified by:

getKNNForDBID in class AbstractDistanceKNNQuery<O extends SpatialComparable,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

Parameters:

ids - query object IDs

k - Number of neighbors requested

Returns:

neighbors