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Algorithm Development Kit 1.0 |
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java.lang.Objectalgs.model.kdtree.KDFactory
public class KDFactory
Produces a KD-tree from a given input set using recursive median approach.
Note that we take care to construct the associated Hypercube
regions with each
node to ensure the integrity of the regions; without these regions being properly
set, there is no way to "drain" the children of a subtree when a query wholly
contains a subtree's region.
Constructor Summary | |
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KDFactory()
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Method Summary | |
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static KDTree |
generate(IMultiPoint[] points)
Generate a KDTree from the given array of points. |
static KDTree |
generate(IPoint[] points)
Generate a KDTree from the given array of IPoints. |
Methods inherited from class java.lang.Object |
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clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Constructor Detail |
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public KDFactory()
Method Detail |
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public static KDTree generate(IMultiPoint[] points)
If points is null, then return null since the dimensionality is unknown.
All points must have the same dimensionality, otherwise strange behavior may occur. Also, this method is not re-entrant, since the comparators array is regenerated upon each invocation, thus we mark the method as 'synchronized'.
points
- points which are to be used as source to generate KDTree.public static KDTree generate(IPoint[] points)
points
-
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