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>

tests/test_wyckoff.py

@@ -0,0 +1,117 @@
+"""威科夫引擎单测：合成震荡箱 + Spring/SOS + VP POC。"""
+from __future__ import annotations
+
+import sys
+from pathlib import Path
+
+import numpy as np
+import pandas as pd
+
+ROOT = Path(__file__).resolve().parents[1]
+sys.path.insert(0, str(ROOT))
+
+from chanlun.analysis.wyckoff import analyze_wyckoff  # noqa: E402
+
+
+def _box_df(n_box: int = 60, spring: bool = True, sos: bool = True) -> pd.DataFrame:
+	"""构造明显箱体：40~60，可选假破与上破。"""
+	rng = np.random.default_rng(7)
+	rows = []
+	t0 = pd.Timestamp("2024-06-01", tz="UTC")
+	price = 50.0
+	# 进入箱体前下跌
+	for i in range(20):
+		price -= 0.3 + rng.random() * 0.1
+		o, c = price + 0.2, price
+		h, l = max(o, c) + 0.15, min(o, c) - 0.15
+		rows.append((t0 + pd.Timedelta(minutes=5 * i), o, h, l, c, 100 + rng.random() * 20))
+	# 箱体 40-60
+	lo, hi = 40.0, 60.0
+	for i in range(n_box):
+		c = lo + (hi - lo) * (0.3 + 0.4 * rng.random())
+		o = c + rng.normal(0, 0.5)
+		h = min(hi + 0.5, max(o, c) + abs(rng.normal(0.5, 0.2)))
+		l = max(lo - 0.5, min(o, c) - abs(rng.normal(0.5, 0.2)))
+		# 触及边界
+		if i % 7 == 0:
+			h = hi - 0.1
+		if i % 7 == 3:
+			l = lo + 0.1
+		rows.append(
+			(
+				t0 + pd.Timedelta(minutes=5 * (20 + i)),
+				o,
+				h,
+				l,
+				c,
+				80 + rng.random() * 40,
+			)
+		)
+	base = 20 + n_box
+	if spring:
+		# 假破下沿
+		rows.append(
+			(
+				t0 + pd.Timedelta(minutes=5 * base),
+				42.0,
+				43.0,
+				37.0,
+				41.5,
+				90.0,
+			)
+		)
+		base += 1
+	if sos:
+		rows.append(
+			(
+				t0 + pd.Timedelta(minutes=5 * base),
+				58.0,
+				66.0,
+				57.0,
+				64.0,
+				220.0,
+			)
+		)
+		base += 1
+		# LPS 缩量回踩
+		rows.append(
+			(
+				t0 + pd.Timedelta(minutes=5 * base),
+				62.0,
+				63.0,
+				59.5,
+				61.0,
+				70.0,
+			)
+		)
+
+	df = pd.DataFrame(rows, columns=["date", "open", "high", "low", "close", "volume"])
+	return df
+
+
+def test_wyckoff_detects_range_and_events():
+	df = _box_df()
+	out = analyze_wyckoff(df, lookback=200)
+	assert out["trading_range"] is not None
+	tr = out["trading_range"]
+	assert tr["high"] > tr["low"]
+	types = {e["type"] for e in out["events"]}
+	assert "Spring" in types or "SOS" in types
+	assert out["bias"] in ("accumulation", "distribution", "unknown")
+	assert len(out["phases"]) >= 3
+
+
+def test_volume_profile_poc_on_heavy_bin():
+	# 平坦箱 + 中间价放量
+	dates = pd.date_range("2024-01-01", periods=40, freq="5min", tz="UTC")
+	rows = []
+	for i, d in enumerate(dates):
+		c = 50.0 + (i % 5) * 0.1
+		vol = 1000.0 if 49.8 <= c <= 50.2 else 10.0
+		rows.append((d, c, c + 0.2, c - 0.2, c, vol))
+	df = pd.DataFrame(rows, columns=["date", "open", "high", "low", "close", "volume"])
+	out = analyze_wyckoff(df, lookback=80, vp_bins=20)
+	vp = out["volume_profile"]
+	assert vp["poc"] is not None
+	assert vp["vah"] is not None and vp["val"] is not None
+	assert abs(vp["poc"] - 50.0) < 2.0