NeuralTracking
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Downsampling routines + tests
Necessary for proper node topological updates, it is imperative we get this right.
- [x] Finish elementary radius-based (epsilon) downsampling (based on existing grid downsampling code)
Perhaps make a version that exploits spatial hash map instead of a linear bin array. This will involve:
- [x] Write a routine that determines how many maximum points we might have per "epsilon-radius" block
- [x] Write a kernel routine for aggregating points into hash blocks
- [x] Write a kernel routine for averaging points within each block
- [x] Write a kernel routine for checking block neighbors and merging neighboring blocks' points if they are within epsilon