
public class SmallMemoryKDTree.KDTreeKNNQuery extends AbstractDistanceKNNQuery<O>
| Modifier and Type | Field and Description |
|---|---|
private Norm<? super O> |
norm
Norm to use.
|
distanceQuery, relationHINT_BULK, HINT_EXACT, HINT_HEAVY_USE, HINT_NO_CACHE, HINT_OPTIMIZED_ONLY, HINT_SINGLE| Constructor and Description |
|---|
SmallMemoryKDTree.KDTreeKNNQuery(DistanceQuery<O> distanceQuery,
Norm<? super O> norm)
Constructor.
|
| 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.
|
getKNNForBulkDBIDs, getKNNForDBIDprivate Norm<? super O extends NumberVector> norm
public SmallMemoryKDTree.KDTreeKNNQuery(DistanceQuery<O> distanceQuery, Norm<? super O> norm)
distanceQuery - Distance querynorm - Norm to usepublic KNNList getKNNForObject(O obj, int k)
KNNQuerygetKNNForObject in interface KNNQuery<O extends NumberVector>getKNNForObject in class AbstractDistanceKNNQuery<O extends NumberVector>obj - Query objectk - Number of neighbors requestedprivate double kdKNNSearch(int left,
int right,
int axis,
O query,
KNNHeap knns,
DoubleDBIDListIter iter,
double maxdist)
left - Subtree beginright - Subtree end (exclusive)axis - Current splitting axisquery - Query objectknns - kNN heapiter - Iterator variable (reduces memory footprint!)maxdist - Current upper bound of kNN distance.Copyright © 2015 ELKI Development Team, Lehr- und Forschungseinheit für Datenbanksysteme, Ludwig-Maximilians-Universität München. License information.