KdTree, for efficient search in K-dimensional point clouds. https://github.com/ijt/kdtree

Latest on Hackage:0.2.1

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BSD3 licensed by Issac Trotts
This is a simple library for k-d trees in Haskell, based on the algorithms
at http://en.wikipedia.org/wiki/K-d_tree.

It enables efficient searching through collections of points in O(log N) time
for randomly distributed points, using the nearestNeighbor function.

Here is an example of an interactive session using this module:

[ ~/haskell/KdTree ] ghci
GHCi, version 7.0.3: http://www.haskell.org/ghc/ :? for help
Prelude> :m Data.Trees.KdTree
Prelude Data.Trees.KdTree> import Test.QuickCheck
Prelude Data.Trees.KdTree Test.QuickCheck> points <- sample' arbitrary :: IO [Point3d]
Prelude Data.Trees.KdTree Test.QuickCheck> let tree = fromList points
Prelude Data.Trees.KdTree Test.QuickCheck> nearestNeighbor tree (head points)
Just (Point3d {p3x = 0.0, p3y = 0.0, p3z = 0.0})
Prelude Data.Trees.KdTree Test.QuickCheck> head points
Point3d {p3x = 0.0, p3y = 0.0, p3z = 0.0}

Depends on:
Used by 1 package:
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