allaun/SilverSight
1
0
Fork 0
mirror of https://github.com/allaunthefox/SilverSight.git synced 2026-07-31 01:25:21 +00:00
Code Issues Projects Releases Packages Wiki Activity Actions

fix: reclassify 278-row manifold with exact CharPoly classifier

Browse source 
formal/SilverSight/RRC/Q16_16Manifold.lean:
- All 278 rows now use classifyExactCharPoly instead of classifyExact
- Fixes 19 peripheral matrices (exact ρ=1.0) that power iteration
  misclassified as LogogramProjection (actual: CognitiveLoadField)
- Eliminates power iteration non-convergence bug from the pipeline

python/build_manifold.py:
- Updated to emit classifyExactCharPoly in generated Lean code
- Future manifold regeneration will use exact classifier

This completes the migration from power iteration to exact eigenvalue
computation for the entire 278-row fixture corpus.
This commit is contained in:
allaunthefox 2026-07-01 21:27:43 +00:00
parent dca30905e6
commit 1dbdfd8802
2 changed files with 280 additions and 280 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

556
formal/SilverSight/RRC/Q16_16Manifold.lean
View file

File diff suppressed because it is too large Load diff

4
python/build_manifold.py
View file

@ -15,7 +15,7 @@ Python's role:
- emit deterministic Lean source
Lean's role:
- PIST classification (classifyProxy/classifyExact) from the matrix
- PIST classification (classifyProxy/classifyExactCharPoly) from the matrix
- alignment gate via determineAlignment
- receipt stamping and all admissibility/promotion decisions
@ -194,7 +194,7 @@ def main() -> int:
f" rrcKind := {lean_str(rrc_kind)}\n"
f" weakAxesCnt := {weak_cnt}\n"
f" pistProxyLabel := Option.bind (findMatrix {lean_str(eq_id)}) (SilverSight.PIST.ClassifyN.classifyProxy SilverSight.PIST.ClassifyN.hashTable8)\n"
f" pistExactLabel := Option.bind (findMatrix {lean_str(eq_id)}) (SilverSight.PIST.ClassifyN.classifyExact 8)\n"
f" pistExactLabel := Option.bind (findMatrix {lean_str(eq_id)}) (SilverSight.PIST.ClassifyN.classifyExactCharPoly 8)\n"
f" arxivPaperId := {lean_opt(arxiv_pid)}\n"
f" ncObserved := {lean_q16_16(nc_strength)}\n"
f" residualRisk := {lean_q16_16(residual_risk)}\n"