feat: 新增 ChanMacro 宏观 regime 检测模块

ChanMacro/validation/reporter.py

@@ -0,0 +1,120 @@
+"""
+validation/reporter.py — Aggregates all validation reports into a unified summary.
+
+Used by: python main.py validate
+"""
+
+from datetime import date as Date
+from typing import Optional
+import logging
+
+from .factor_validator import FactorValidator, FactorReport
+from .regime_validator import RegimeValidator, RegimeReport
+from .transition_validator import TransitionValidator, TransitionReport
+
+logger = logging.getLogger(__name__)
+
+
+class ValidationReporter:
+    """
+    Orchestrates full validation pipeline:
+
+    1. Factor validation (IC, ICIR, Hit Ratio) for each factor
+    2. Regime validation (MI, KL, ANOVA) for each factor
+    3. Transition validation (stability, flip rate)
+    """
+
+    def __init__(self, db_path: Optional[str] = None):
+        from config import config
+        self.db_path = db_path or config.db_path
+        self.factor_validator = FactorValidator(self.db_path)
+        self.regime_validator = RegimeValidator(self.db_path)
+        self.transition_validator = TransitionValidator(self.db_path)
+
+    def run_all(self) -> str:
+        """Run all validations and return a formatted report string."""
+        lines = []
+        lines.append("=" * 70)
+        lines.append(f"  ChanMacro Validation Report — {Date.today()}")
+        lines.append("=" * 70)
+
+        # ── Factor Validation ──────────────────────────
+        lines.append("")
+        lines.append("─" * 50)
+        lines.append("  FACTOR VALIDATION (Predictive Power)")
+        lines.append("─" * 50)
+
+        factor_queries = {
+            "Price Structure": "SELECT date, score FROM ohlcv_daily WHERE ema20 IS NOT NULL",
+            "Breadth": """
+                SELECT bd.date,
+                    (bd.advance_top50*1.0/(bd.advance_top50+bd.decline_top50+1)*100*0.30
+                     + bd.above_ema20_top50*1.0/50*100*0.35
+                     + bd.new_highs_20d_top50*1.0/50*100*0.20
+                     + 50*0.15) as score
+                FROM breadth_daily bd
+            """,
+        }
+
+        factor_reports: list[FactorReport] = []
+        for name, query in factor_queries.items():
+            try:
+                report = self.factor_validator.validate_from_db(name, query)
+                factor_reports.append(report)
+                lines.append(report.summary())
+                lines.append("")
+            except Exception as e:
+                logger.warning(f"Factor validation failed for {name}: {e}")
+
+        # ── Regime Validation ──────────────────────────
+        lines.append("─" * 50)
+        lines.append("  REGIME VALIDATION (Regime Separation)")
+        lines.append("─" * 50)
+
+        regime_reports: list[RegimeReport] = []
+        for name, query in factor_queries.items():
+            try:
+                report = self.regime_validator.validate_from_db(name, query)
+                regime_reports.append(report)
+                lines.append(report.summary())
+                lines.append("")
+            except Exception as e:
+                logger.warning(f"Regime validation failed for {name}: {e}")
+
+        # ── Transition Validation ──────────────────────
+        lines.append("─" * 50)
+        lines.append("  TRANSITION VALIDATION (Regime Stability)")
+        lines.append("─" * 50)
+
+        try:
+            t_report = self.transition_validator.validate_from_db()
+            lines.append(t_report.summary())
+        except Exception as e:
+            logger.warning(f"Transition validation failed: {e}")
+
+        # ── Summary ────────────────────────────────────
+        lines.append("")
+        lines.append("=" * 70)
+        lines.append("  SUMMARY")
+        lines.append("=" * 70)
+
+        # Factor ranking by IC
+        if factor_reports:
+            ranked = sorted(factor_reports, key=lambda r: abs(r.ic_mean), reverse=True)
+            lines.append("  Factor Ranking (by |IC|):")
+            for i, r in enumerate(ranked):
+                tag = "★★★" if abs(r.ic_mean) > 0.05 else "★★" if abs(r.ic_mean) > 0.03 else "★"
+                lines.append(f"    {i+1}. {r.factor_name:20s} IC={r.ic_mean:+.4f} {tag}  {r.conclusion}")
+
+        # Regime factor ranking
+        if regime_reports:
+            ranked_r = sorted(regime_reports, key=lambda r: r.separation_score, reverse=True)
+            lines.append("")
+            lines.append("  Regime Factor Ranking (by Separation Score):")
+            for i, r in enumerate(ranked_r):
+                lines.append(f"    {i+1}. {r.factor_name:20s} Score={r.separation_score:.2f}  {r.conclusion}")
+
+        lines.append("")
+        lines.append("=" * 70)
+
+        return "\n".join(lines)