python-math #26: feat(math): Q11 — replicate vectorz distance cancellation in legacy kmeans - #2654
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python-math #43: docs(delphi): s7 goal state + journal — mode collapse executed, battery 20/20
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…ation in legacy kmeans ## Why Quirk Q11 (`delphi/docs/CLOJURE_QUIRKS.md`): Clojure's kmeans distances go through vectorz's `matrix/distance` on ArraySubVector row views, which computes d^2 = |a|^2 + |b|^2 - 2ab; the cancellation in that formula floors true distances below ~1e-8 to EXACTLY 0.0, so near-coincident points TIE against multiple clusters and `min-key`'s last-wins tie-break merges them into the LATER cluster (the emptied cluster is dropped). Verified in-process on the vw every-vote step-57 pair (true distance 4.66e-15 → both cluster distances 0.0 → merge), via the new cache-safe diagnostic `math/dev/proj_probe.clj`, which also reproduces the recording chain bit-exactly. ## What `_euclidean` in `legacy_kmeans.py` now uses the same formula (the module runs only in clojure-legacy mode — gated by construction). numpy reproduces the 0.0 collapse bit-for-bit on the real pair. The pre-Q11 all-singletons expectation in `test_base_cluster_lineage.py` pinned Python's old difference-based distance, not Clojure — updated to the verified contract (merges only ever happen at Q11-distance 0.0). ## Testing TDD: RED on the real step-57 pair (unit + warm-start merge integration). commit-id:7ae9c688
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Why
Quirk Q11 (
delphi/docs/CLOJURE_QUIRKS.md): Clojure's kmeans distances go through vectorz'smatrix/distanceon ArraySubVector row views, which computes d^2 = |a|^2 + |b|^2 - 2ab; the cancellation in that formula floors true distances below ~1e-8 to EXACTLY 0.0, so near-coincident points TIE against multiple clusters andmin-key's last-wins tie-break merges them into the LATER cluster (the emptied cluster is dropped). Verified in-process on the vw every-vote step-57 pair (true distance 4.66e-15 → both cluster distances 0.0 → merge), via the new cache-safe diagnosticmath/dev/proj_probe.clj, which also reproduces the recording chain bit-exactly.What
_euclideaninlegacy_kmeans.pynow uses the same formula (the module runs only in clojure-legacy mode — gated by construction). numpy reproduces the 0.0 collapse bit-for-bit on the real pair. The pre-Q11 all-singletons expectation intest_base_cluster_lineage.pypinned Python's old difference-based distance, not Clojure — updated to the verified contract (merges only ever happen at Q11-distance 0.0).Testing
TDD: RED on the real step-57 pair (unit + warm-start merge integration).
commit-id:7ae9c688
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