#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.
Separating 2000 points using simplex noise as the desired distance. 30 iterations. Slow. The points start in a rectangle 300 pixels away from the edge, then they are slowly pushed outwards. #CreativeCoding#naive#algorithm