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Datseris avatar Datseris commented on August 23, 2024

I've seen the source code of knn, and specifically here the "optimized version":

https://github.com/KristofferC/NearestNeighbors.jl/blob/master/src/knn.jl#L16-L26

Based on this, I wrote up a simple modified loop that goes like this:

function find_all_neighbors(vtree, vs, ns, K, w)
    k, sortres, N = maximum(K), true, length(vs)
    dists = [Vector{eltype(vs[1])}(undef, k) for _ in 1:N]
    idxs = [Vector{Int}(undef, k) for _ in 1:N]
    for i in 1:N
        # The skip predicate also skips the point itself for w ≥ 0
        skip = j -> ns[i] - w  j  ns[i] + w
        NearestNeighbors.knn_point!(vtree, vs[i], sortres, dists[i], idxs[i], skip)
    end
    return idxs
end

I think it makes sense. If anyone confirms that this indeed is the way I should do it, let me know and I can close this!

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KristofferC avatar KristofferC commented on August 23, 2024

Yeah, the skip function didn't turn out too great (I feel this always happens when you merge something you aren't 100% on heh). Something like what you do there makes sense but it is of course unfortunate that you need to use internal things like knn_point!.

from nearestneighbors.jl.

Datseris avatar Datseris commented on August 23, 2024

It's okay, it's not a big deal. True, I use something internal, but that's the reason that I wanted you to confirm. Since I am not sure about knn_point!, I wanted the expert to give the a-ok. Now all is good!

from nearestneighbors.jl.

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