Update codex/formulas.py

codex/formulas.py

@@ -1,4 +1,3 @@
-# codex/formulas.py
 # Author: Liam Grinstead
 # RFT-native scoring wrapped in Formula class, restoring GVU_FORMULAS for compatibility
 
@@ -9,13 +8,6 @@ class Formula:
         self.expression = expression
 
     def evaluate(self, agent: dict) -> float:
-        """
-        RFT scoring:
-        - collapse_overlay: {'tau_eff': float, 'beta_band': float, 'operator_weights': {pair: weight}}
-        - tier: 'Tier_X'
-        - emotional_resonance: bool
-        - symbolic_operators: list[str]
-        """
         overlay = agent.get("collapse_overlay", {})
         tau_eff = overlay.get("tau_eff", 1.0)
         beta = overlay.get("beta_band", 0.5)
@@ -24,40 +16,18 @@ class Formula:
         tier_level = int(tier.split("_")[1]) if "_" in tier else 1
         resonance = 1.2 if agent.get("emotional_resonance") else 1.0
 
-        # Operator coupling magnitude with diminishing returns
         coupling_sum = sum(weights.values())
         coupling = coupling_sum / (1.0 + 0.25 * max(1, len(weights)))
 
-        # Tier drift dynamics
         drift_penalty = 0.18 * tier_level
         drift_resilience = 1.0 + 0.05 * (tier_level - 1)
 
-        # Collapse energy and coherence
         collapse_energy = tau_eff * (0.6 + 0.4 * beta) * (1.0 + 0.35 * coupling)
         coherence = exp(- (0.22 * tau_eff + 0.08 * tier_level)) * (0.9 + 0.1 * beta)
 
-        # GVU seal factor
         gvu = (collapse_energy * resonance * drift_resilience) * (0.7 + 0.6 * coherence) - drift_penalty
-
         score = max(0.0, gvu)
         return round(score, 4)
 
-
-# Restore GVU_FORMULAS so legacy imports work (e.g., falsifiability_bench.py)
 GVU_FORMULAS = {
-    # You can add more named formulas here if needed; all use Formula.evaluate() above.
-    "Formula_20": Formula("−τ_eff / (τ_c + 19/20) ⋅ P_standard ⋅ τ_eff ⋅ ℯ ⋅ |grad_R_O − grad_T_P| / GVU")
-}
-
-
-# Optional helpers retained for downstream modules that expect invariant access
-def rft_invariants(agent: dict) -> dict:
-    overlay = agent.get("collapse_overlay", {})
-    tier = agent.get("tier", "Tier_1")
-    tier_level = int(tier.split("_")[1]) if "_" in tier else 1
-    return {
-        "tau_eff": overlay.get("tau_eff", 1.0),
-        "beta_band": overlay.get("beta_band", 0.5),
-        "operator_count": len(agent.get("symbolic_operators", [])),
-        "tier_level": tier_level,
-    }
+    "Formula_20": Formula("−τ_eff / (τ_c + 19/20) ⋅ P_standard ⋅ τ_eff ⋅ ℯ