Package org.ddogleg.nn.alg
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Interface Summary Interface Description AxisSplitRule Selects which axis the data should be split along when given a list of variances.AxisSplitter<D> Selects which dimension the set of points should be split by, which point is used to split the lists, and splits the lists into two sets.KdTreeSearch1 Interface for searching a single tree for the nearest-neighborKdTreeSearchN Interface for searching a single tree for the N nearest-neighbors. -
Class Summary Class Description AxisSplitRuleMax Selects the axis with the largest variance to split.AxisSplitRuleRandomK Randomly selects the larger variances.AxisSplitterMedian<D> Splits the points in K-D Tree node by selecting the axis with the largest variance.ExhaustiveNeighbor Exhaustively finds the nearest-neighbor to a n-dimensional point by considering every possibility.KdTree K-D Tree is short for k-dimensional tree and is a binary tree data structure used for quickly finding the nearest-neighbor of a k-dimensional point in a set.KdTree.Node Data type for each node in the binary tree.KdTreeConstructor<D> Creates a newKD-Treefrom a list of points and (optional) associated data.KdTreeMemory Memory management for recycling KdTree data structures.KdTreeResult Storage for the results of a K-D Tree search.KdTreeSearch1Bbf Implementation ofKdTreeSearchBestBinFirstwhich searches for the single best nearest-neighbor.KdTreeSearch1Standard Standard algorithm for searching aKdTreefor the nearest-neighbor of a search.KdTreeSearchBestBinFirst Approximate search forK-D Treesusing the best-bin-first method [1] that supports multiple trees.KdTreeSearchNBbf Implementation ofKdTreeSearchBestBinFirstwhich searches for the N nearest-neighbors.KdTreeSearchNStandard Standard algorithm for searching aKdTreefor the nearest-neighbor of a search.StandardKdTreeSearch1Tests Standard tests for implemntations ofKdTreeSearch1.StandardKdTreeSearchNTests Standard tests for implementations ofKdTreeSearchN.TestAxisSplitRuleMax TestAxisSplitRuleRandomK TestAxisSplitterMedian TestExhaustiveNeighbor TestKdTree TestKdTreeConstructor TestKdTreeConstructor.DummySplitter TestKdTreeMemory TestKdTreeSearch1Bbf TestKdTreeSearch1Standard TestKdTreeSearchBestBinFirst TestKdTreeSearchNBbf TestKdTreeSearchNStandard VpTree<PointData> Vantage point tree implementation for nearest neighbor search.
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