
public class SmallMemoryKDTree.KDTreeRangeQuery extends AbstractDistanceRangeQuery<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.KDTreeRangeQuery(DistanceQuery<O> distanceQuery,
Norm<? super O> norm)
Constructor.
|
| Modifier and Type | Method and Description |
|---|---|
void |
getRangeForObject(O obj,
double range,
ModifiableDoubleDBIDList result)
Get the neighbors for a particular object in a given query range
|
private void |
kdRangeSearch(int left,
int right,
int axis,
O query,
ModifiableDoubleDBIDList res,
DoubleDBIDListIter iter,
double radius)
Perform a kNN search on the kd-tree.
|
getRangeForDBID, getRangeForDBID, getRangeForObjectprivate Norm<? super O extends NumberVector> norm
public SmallMemoryKDTree.KDTreeRangeQuery(DistanceQuery<O> distanceQuery, Norm<? super O> norm)
distanceQuery - Distance querynorm - Norm to usepublic void getRangeForObject(O obj, double range, ModifiableDoubleDBIDList result)
RangeQueryobj - Query objectrange - Query rangeresult - Neighbors output setprivate void kdRangeSearch(int left,
int right,
int axis,
O query,
ModifiableDoubleDBIDList res,
DoubleDBIDListIter iter,
double radius)
left - Subtree beginright - Subtree end (exclusive)axis - Current splitting axisquery - Query objectres - kNN heapiter - Iterator variable (reduces memory footprint!)radius - Query radiusCopyright © 2015 ELKI Development Team, Lehr- und Forschungseinheit für Datenbanksysteme, Ludwig-Maximilians-Universität München. License information.