signal_aggregator + engine: drop write-only counters and unreachable branches (no behaviour change)

- SignalAggregator.pb_funnel / cp_funnel and the 19 _reject() ticks inside
  _try_m5_pullback / _try_chart_pattern: class-level rejection counters nothing
  in the repo reads. Every gate keeps its early return; only the counter bump
  before it is gone.
- _TP_QUALITY_SCALE: the "B"/"C" entries and the 0.75 default could never be
  selected — the XAU ATR generator is only called for A+/A. The lookup is now
  a direct index so a violated invariant fails loudly instead of scaling silently.
- engine._classify_regime no longer takes the unused DataFrame argument, and the
  structure S/R branch tests the 5-minute frame only (M1 is never a primary).

Parity: 12-month M5 and H1 books regenerated byte-identical
(md5 a28fed4becd056466c26d6a947e1a0e5 / d20405ef64f069770c258bb9bed1ac90).
Suite: 461 passed, 0 failed.

Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_0156YhogLytzj9P2iH1skGbL

engine.py

@@ -153,7 +153,7 @@ class TechnicalEngine:
         if "candlestick" not in disabled: self._detect_candlestick_patterns(df, result)
 
         # ── Classify market regime ─────────────────────────────────
-        self._classify_regime(df, result)
+        self._classify_regime(result)
 
         # ── Regime-aware RSI reinterpretation ──────────────────────
         if self.config.rsi_mode == "regime_aware" and "rsi" not in disabled:
@@ -873,7 +873,7 @@ class TechnicalEngine:
     def _compute_structure_sr(self, df: pd.DataFrame, result: TechnicalAnalysis):
         """Detect swing high/low structure levels for S/R and trade setup."""
         base_lookback = self.config.swing_sr_lookback
-        if result.timeframe in ("1min", "5min"):
+        if result.timeframe == "5min":
             base_lookback = max(base_lookback, 120)
         lookback = min(base_lookback, len(df) - 1)
         if lookback < 10:
@@ -1096,7 +1096,7 @@ class TechnicalEngine:
             confidence=conf, description=desc, weight=rsi_ind.weight,
         )
 
-    def _classify_regime(self, df: pd.DataFrame, result: TechnicalAnalysis):
+    def _classify_regime(self, result: TechnicalAnalysis):
         """Classify the market regime (trending vs ranging vs transitioning)."""
         adx_sig = result.indicators.get("adx")
         ema_sig = result.indicators.get("ema_trend")