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High performance nearest neighbor data structures (KDTree and BallTree) and algorithms for Julia.

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Commonly called "range search" (https://en.wikipedia.org/wiki/Range_searching), but NN.jl already has `inrange` that selects points within a circle - so I call the new function `inrect`.

Currently the docstring for `knn` refers to `nn`, but not vice versa. I can make a PR, just recording it.

Running ```julia tree = KDTree(rand(2,10) nn(tree, rand(2), x->true) ``` with `julia --check-bounds=yes` (or when being run via `Pkg.test`) results in ```julia ERROR: BoundsError: attempt to access 10-element Vector{Int64} at index...

This PR has added a function `knn_threaded`. I am able to achieve several X speedup from multithreading, but a several X slowdown for small problems. This is an acceptable tradeoff...

Thanks for the great toolbox you contributed! I was trying to use it for the problem of picking particles in an image that need to have a minimum distance to...

I am pretty new to KNN, but currently, I only know to use it for classifying. So it would be most natural for this package to include a simply classifier...

Adresses https://github.com/KristofferC/NearestNeighbors.jl/issues/99

Hi! I'm currently trying to benchmark our parallel implementation of `knn` at different numbers of samples and dimensions. ```julia using BenchmarkTools: @benchmark import NearestNeighbors as NN const input_samples = Int.(exp2.(9:14))...

## Overview This PR parallelizes the construction of `BallTree` structures, achieving a __speedup of a factor of 5__ for `n = 1_000_000` points with 8 threads. The implementation uses `@spawn`...

I am trying to use this package to build neighbor lists. I am new to Julia. Can you help me in the implementation of periodic elucidation distance or add it...