jackyu66gitandCursor
d3188ca83c
评分选 TR、阶段最小跨度、elements_only 门闩、Top-8 VP；无币种独立参数。 Co-authored-by: Cursor <cursoragent@cursor.com>
129 lines
3.4 KiB
Python
129 lines
3.4 KiB
Python
"""威科夫引擎单测：合成震荡箱 + Spring/SOS + VP POC（ECR-004 收紧）。"""
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from __future__ import annotations
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import sys
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from pathlib import Path
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import numpy as np
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import pandas as pd
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ROOT = Path(__file__).resolve().parents[1]
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sys.path.insert(0, str(ROOT))
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from chanlun.analysis.wyckoff import analyze_wyckoff # noqa: E402
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from chanlun.analysis.wyckoff.range import detect_trading_range # noqa: E402
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def _box_df(n_box: int = 60, spring: bool = True, sos: bool = True) -> pd.DataFrame:
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"""构造明显箱体：40~60，前 20 根下跌趋势，可选假破与上破。"""
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rng = np.random.default_rng(7)
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rows = []
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t0 = pd.Timestamp("2024-06-01", tz="UTC")
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price = 50.0
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# 进入箱体前下跌
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for i in range(20):
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price -= 0.3 + rng.random() * 0.1
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o, c = price + 0.2, price
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h, l = max(o, c) + 0.15, min(o, c) - 0.15
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rows.append((t0 + pd.Timedelta(minutes=5 * i), o, h, l, c, 100 + rng.random() * 20))
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# 箱体 40-60
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lo, hi = 40.0, 60.0
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for i in range(n_box):
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c = lo + (hi - lo) * (0.3 + 0.4 * rng.random())
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o = c + rng.normal(0, 0.5)
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h = min(hi + 0.5, max(o, c) + abs(rng.normal(0.5, 0.2)))
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l = max(lo - 0.5, min(o, c) - abs(rng.normal(0.5, 0.2)))
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if i % 7 == 0:
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h = hi - 0.1
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if i % 7 == 3:
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l = lo + 0.1
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rows.append(
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(
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t0 + pd.Timedelta(minutes=5 * (20 + i)),
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o,
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h,
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l,
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c,
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80 + rng.random() * 40,
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)
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)
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base = 20 + n_box
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if spring:
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rows.append(
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(
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t0 + pd.Timedelta(minutes=5 * base),
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42.0,
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43.0,
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37.0,
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41.5,
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90.0,
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)
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)
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base += 1
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if sos:
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rows.append(
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(
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t0 + pd.Timedelta(minutes=5 * base),
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58.0,
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66.0,
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57.0,
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64.0,
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220.0,
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)
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)
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base += 1
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rows.append(
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(
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t0 + pd.Timedelta(minutes=5 * base),
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62.0,
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63.0,
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59.5,
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61.0,
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70.0,
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)
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)
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return pd.DataFrame(rows, columns=["date", "open", "high", "low", "close", "volume"])
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def test_wyckoff_detects_range_and_events():
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df = _box_df()
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out = analyze_wyckoff(df, lookback=200)
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assert out["trading_range"] is not None
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tr = out["trading_range"]
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assert 38.0 <= tr["low"] <= 42.0
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assert 58.0 <= tr["high"] <= 62.0
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# 起点不应落入前 20 根下跌段（允许少量 overlap）
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box_start = df["date"].iloc[20]
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assert tr["start_time"] is not None
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start_ts = pd.Timestamp(tr["start_time"])
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assert start_ts >= box_start - pd.Timedelta(minutes=5 * 8)
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types = {e["type"] for e in out["events"]}
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assert "Spring" in types
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assert "SOS" in types
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assert out["bias"] in ("accumulation", "distribution", "unknown")
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assert len(out["phases"]) >= 3
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keys = [(p["start_time"], p["end_time"]) for p in out["phases"]]
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assert len(keys) == len(set(keys)), "phases must not share identical start/end"
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def test_range_scoring_skips_pretrend():
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df = _box_df(spring=False, sos=False)
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tr = detect_trading_range(df, lookback=200)
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assert tr is not None
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assert tr["abs_start_idx"] >= 12 # 不应从 bar 0 吞掉整段下跌
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def test_volume_profile_poc_on_heavy_bin():
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dates = pd.date_range("2024-01-01", periods=40, freq="5min", tz="UTC")
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rows = []
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for i, d in enumerate(dates):
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c = 50.0 + (i % 5) * 0.1
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vol = 1000.0 if 49.8 <= c <= 50.2 else 10.0
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rows.append((d, c, c + 0.2, c - 0.2, c, vol))
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df = pd.DataFrame(rows, columns=["date", "open", "high", "low", "close", "volume"])
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out = analyze_wyckoff(df, lookback=80, vp_bins=20)
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vp = out["volume_profile"]
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assert vp["poc"] is not None
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assert vp["vah"] is not None and vp["val"] is not None
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assert abs(vp["poc"] - 50.0) < 1.0
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