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See:
Description
| Class Summary | |
|---|---|
| KdTree<T> | An efficient well-optimized kd-tree |
| KdTree.DataPoint<T> | A location point and it's value (used for storage of the tree model) |
| KdTree.Entry<T> | Stores a distance and value to output |
| KdTree.Manhattan<T> | Class for tree with Manhattan distancing |
| KdTree.ResultHeap | Class for tracking up to 'size' closest values |
| KdTree.SqrEuclid<T> | Class for tree with Unweighted Squared Euclidean distancing |
| KdTree.WeightedManhattan<T> | Class for tree with Weighted Manhattan distancing |
| KdTree.WeightedSqrEuclid<T> | Class for tree with Weighted Squared Euclidean distancing |
| Enum Summary | |
|---|---|
| KdTree.Status | Enumeration representing the status of a node during the running |
Adapted Version of Rednaxela's Kd-tree implementation.
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