# Finite-Splitting Directional Attention MVP

Run:

```bash
/home/maxwelhelp/main/bin/python3 finite_splitting_attention.py
```

The script writes `results.json` and prints:

- exact geometric lacunarity-ratio verification;
- exact binary M-adic tree leaf/path split counts;
- dense 32-direction line responses;
- a proxy-guided top-2 sparse target approximation;
- random top-2 comparison;
- directional target-sample reduction and approximation error.

Important interpretation: the prototype uses a radius-1 line response as a routing proxy and a radius-2 response as the expensive target. The proxy currently evaluates all directions, so the 16x reduction is only in expensive target directional samples, not demonstrated end-to-end latency. In addition, with `M=2`, 32 distinct leaves require at least `ceil(log2(32))=5` splitting vertices on a route; the requested `N=3` and `K=32` are incompatible for a full binary tree unless a larger branching factor or fewer leaves is used.