Using NearestNeighbor.jl I can find which points within a collection
col are closest to a (different) given point or set of points. What I need is slightly different. I would like to compute the points p_i in
col that are within a certain distance of each point p_j, also in
col. I suspect this is an “easier” problem, hence the question below.
I can currently get what I want by (1) building a
tree=KDTree(col), and then (2) running e.g.
knn(tree, col, 3) over all points in
It turns out that step (1) is typically ~ six times faster than (2) for me, and I suspect all the information I need is already contained in
tree. So the question: is it possible to obtain the n nearest neighbors for each point in a collection without invoking
knn, just from the data inside the
KDTree of that collection?
[Please complain if the question is not clear. Also let me know if it should be posted elsewhere]
I take the liberty of pinging @kristoffer.carlsson, the author of NearestNeighbors.jl, I hope that’s ok!