#kdtree and ball trees seem cool, but require full knowledge of the thing I'm searching for. What if it's 7 dimensional and I only know 4 of the values?

I feel like a "parallel kd tree" with a separate binary index on each dimension would work better here.

Reduce depth. Allow unspecified values. It'd also be a snap to create and search each dim in parallel.

This must already exist...

#computerscience #math

Randomly stumbled into #kdtree #quadtree #algorithm today and it happened to allllmost line up with a work problem I've been pondering.

My problem involves moving objects. Not just moving, but I want to query them at different points in time.

I think if I just add a time dimension (HexTrees?) it might work...? I'm not clear on the details of the actual algorithm or how this would work. #software #math

I've been using sklearns #kdtree to find intervalls contained in other intervalls by viewing intervalls as points in 2d space and finding all points within an l-infinity ball. Problem is I need to rotate and shift the ball as sklearns implemention does l-1 but not l-infinity.

Now I want to extend to boxes, viewed as points in 4d space. Any suggestions on how to do the l-infinity to l-1 transform?

#math