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 `KDTree`

of `col`

, `tree=KDTree(col)`

, and then (2) running e.g. `knn(tree, col, 3)`

over all points in `col`

.

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!