feat: ECR-003 主站威科夫分析与图表叠层（已审）

独立 wyckoff 引擎 + 按需 include_wyckoff；主站 Lightweight 绘制区间/阶段/事件/VP。

Co-authored-by: Cursor <cursoragent@cursor.com>

chanlun/analysis/wyckoff/engine.py

@@ -0,0 +1,80 @@
+"""威科夫分析入口。"""
+from __future__ import annotations
+
+from typing import Any, Dict, Optional
+
+import pandas as pd
+
+from .events import build_phases, detect_bias_and_events
+from .range import detect_trading_range
+from .volume_profile import compute_volume_profile
+
+
+def _fmt_time(v) -> Optional[str]:
+	if v is None:
+		return None
+	if hasattr(v, "isoformat"):
+		try:
+			return v.isoformat()
+		except Exception:
+			pass
+	return str(v)
+
+
+def analyze_wyckoff(df: pd.DataFrame, lookback: int = 120, vp_bins: int = 50) -> Dict[str, Any]:
+	"""
+	对主周期 OHLCV DataFrame 做威科夫启发式分析。
+	需要列: open, high, low, close, volume；建议有 date 或 timestamp。
+	"""
+	empty = {
+		"trading_range": None,
+		"bias": "unknown",
+		"phases": [],
+		"events": [],
+		"volume_profile": {"bins": [], "poc": None, "vah": None, "val": None, "bin_count": vp_bins},
+		"volume_confirm": {"avg_volume": 0.0, "event_checks": {}},
+	}
+	if df is None or len(df) < 30:
+		return empty
+	if not all(c in df.columns for c in ("open", "high", "low", "close")):
+		return empty
+	work = df.copy()
+	if "volume" not in work.columns:
+		work["volume"] = 1.0
+
+	tr = detect_trading_range(work, lookback=lookback)
+	if tr is None:
+		return empty
+
+	bias, events, volume_confirm = detect_bias_and_events(work, tr)
+	phases = build_phases(work, tr, bias, events)
+	vp = compute_volume_profile(
+		work,
+		int(tr["abs_start_idx"]),
+		int(tr["abs_end_idx"]),
+		bin_count=vp_bins,
+	)
+
+	trading_range = {
+		"start_time": _fmt_time(tr.get("start_time")),
+		"end_time": _fmt_time(tr.get("end_time")),
+		"high": float(tr["high"]),
+		"low": float(tr["low"]),
+		"mid": float(tr["mid"]),
+		"active": bool(tr.get("active", True)),
+		"bars": int(tr.get("bars", 0)),
+	}
+	for ev in events:
+		ev["time"] = _fmt_time(ev.get("time"))
+	for ph in phases:
+		ph["start_time"] = _fmt_time(ph.get("start_time"))
+		ph["end_time"] = _fmt_time(ph.get("end_time"))
+
+	return {
+		"trading_range": trading_range,
+		"bias": bias,
+		"phases": phases,
+		"events": events,
+		"volume_profile": vp,
+		"volume_confirm": volume_confirm,
+	}