ENH: K-d tree based adjudicator for redundant points in discretized space.

[maffettone]

Expected Behavior

It is commonly needed to split space up by the resolution of the measurement/device. Binning is not a completely effective way to do this, as two neighboring points can be in different bins.

Current Behavior

Current redundant adjudicators are built off hashing approaches that will consider similar, but not identical, points in a space unique.

Possible Solution

Use https://docs.scipy.org/doc/scipy/reference/generated/scipy.spatial.KDTree.html instead of hashing.