mutual nearest neighbors about nearestneighbors.jl

[RainerHeintzmann]

I looked a bit more at the trees and found a solution that sort of works:

balltree = BallTree(points)
maxdist = 10.0
idxs = inrange(balltree, points, maxdist, true)

and then you need to see if a point has more than one result.
But is this the best way of solving this problem?

[RainerHeintzmann]

Maybe this is a good solution?:

"""
    nn_mutual(points)
    returns the mutual nearest neighbor distances and the index of the neares neighbor, both in matrix form.
"""
function nn_mutual(points)
    kdtree = KDTree(points)
    nns, nndist = knn(kdtree, points, 2)
    nns = [mynn[1] for mynn in nns]
    nndist = [myd[1] for myd in nndist]
    return nndist, nns
end

If so, should it maybe be part of the toolbox?

[BioTurboNick]

You might be looking for the skip argument, which allows you to specify a function to decide which points in the tree to not match.