fix(web): 自动刷新保留 K 线视窗；威科夫与图表增量更新

自动刷新改用 tail update 与 scrollToPosition 恢复视窗，避免 setData 后跳到最右；拆分 chart_tv 模块并扩展 analyze/recent API。同步威科夫分析、pipeline 增量构建及相关策略与配置。 Co-authored-by: Cursor <cursoragent@cursor.com>
2026-08-25 22:57:43 +08:00
parent 1e60ab3bfa
commit 8ee11317d3
104 changed files with 21452 additions and 4988 deletions
@@ -0,0 +1,239 @@
+#!/usr/bin/env python3
+"""
+Negative-domain audit
+
+问题：Gate 拦掉的 Spring，是否集中死在 distribution | markdown | range（结构性错误），
+      而不是偶然删掉赚钱样本？
+
+方法（Spring 冻结，Gate=state_set）：
+  1) 跑 Baseline，取出全部 SPRING_LONG 成交
+  2) 用因果 8h market_state 标注入场时状态
+  3) 按 allow_spring 分成 kept vs blocked
+  4) 比较各域 n / PF / winrate / sum%
+
+判定：
+  - blocked 主要落在 bad domains
+  - blocked 整体 PF << kept（或明显更差）
+  - kept 域仍以 accumulation|markup 为主
+"""
+from __future__ import annotations
+
+import json
+import logging
+import sys
+from collections import defaultdict
+from pathlib import Path
+from typing import Any
+
+import numpy as np
+import pandas as pd
+
+ROOT = Path(__file__).resolve().parents[3]
+sys.path.insert(0, str(ROOT))
+sys.path.insert(0, str(ROOT / "user_data/Chan"))
+
+from engine.market_state import compute_market_state_8h  # noqa: E402
+from user_data.Chan.scripts.wyckoff_tf_grid import install_offline_markets  # noqa: E402
+
+OUT = ROOT / "user_data/Chan/scripts/wyckoff_negative_domain_audit_result.json"
+PAIR = "BTC/USDT:USDT"
+CFG = ROOT / "user_data/Chan/config/Wyckoff_BTC_V1_BASELINE.json"
+GOOD = {"accumulation", "markup"}
+BAD = {"distribution", "markdown", "range"}
+
+
+def _pf(ps: list[float]) -> float:
+	wins = [p for p in ps if p > 0]
+	losses = [-p for p in ps if p <= 0]
+	gw, gl = sum(wins), sum(losses)
+	if gl <= 0:
+		return 999.0 if gw > 0 else 0.0
+	return gw / gl
+
+
+def _stats(ps: list[float]) -> dict[str, Any]:
+	if not ps:
+		return {"n": 0, "pf": 0.0, "winrate": 0.0, "sum_pct": 0.0, "avg_pct": 0.0}
+	return {
+		"n": len(ps),
+		"pf": round(_pf(ps), 3),
+		"winrate": round(100.0 * sum(1 for p in ps if p > 0) / len(ps), 1),
+		"sum_pct": round(100.0 * float(np.sum(ps)), 2),
+		"avg_pct": round(100.0 * float(np.mean(ps)), 2),
+	}
+
+
+def run_baseline_spring_trades() -> list[dict[str, Any]]:
+	from freqtrade.configuration import Configuration
+	from freqtrade.enums import RunMode
+	from freqtrade.optimize.backtesting import Backtesting
+	from freqtrade.persistence import LocalTrade
+	import freqtrade.optimize.optimize_reports.bt_output as bt_output
+
+	bt_output.show_backtest_results = lambda *a, **k: None  # type: ignore
+	for mod in list(sys.modules):
+		if "Wyckoff_BTC" in mod:
+			del sys.modules[mod]
+
+	cfg = Configuration.from_files([str(CFG)])
+	cfg.update(
+		{
+			"strategy": "Wyckoff_BTC_V1_BASELINE",
+			"strategy_path": str(ROOT / "user_data/Chan/strategies"),
+			"timerange": "20190901-",
+			"timeframe": "1h",
+			"export": "none",
+			"runmode": RunMode.BACKTEST,
+			"datadir": ROOT / "user_data/data/binance",
+			"user_data_dir": ROOT / "user_data",
+			"enable_protections": False,
+			"fee": 0.0010,
+			"exchange": {
+				**cfg.get("exchange", {}),
+				"name": "binance",
+				"pair_whitelist": [PAIR],
+			},
+		}
+	)
+	bt = Backtesting(cfg)
+	bt.start()
+	rows = []
+	for t in LocalTrade.bt_trades:
+		tag = t.enter_tag or ""
+		if "SPRING" not in tag:
+			continue
+		rows.append(
+			{
+				"entry_date": t.open_date_utc.isoformat() if t.open_date_utc else "",
+				"exit_date": t.close_date_utc.isoformat() if t.close_date_utc else "",
+				"enter_tag": tag,
+				"profit_ratio": float(t.close_profit or 0.0),
+				"era": (
+					"2023plus"
+					if t.open_date_utc and t.open_date_utc >= pd.Timestamp("2023-01-01", tz="UTC")
+					else "pre_2023"
+				),
+			}
+		)
+	return rows
+
+
+def annotate(trades: list[dict[str, Any]]) -> list[dict[str, Any]]:
+	h8 = pd.read_feather(ROOT / "user_data/data/binance/futures/BTC_USDT_USDT-8h-futures.feather")
+	h8["date"] = pd.to_datetime(h8["date"], utc=True)
+	h8 = compute_market_state_8h(h8).set_index("date").sort_index()
+
+	out = []
+	for t in trades:
+		ed = pd.Timestamp(t["entry_date"])
+		if ed.tzinfo is None:
+			ed = ed.tz_localize("UTC")
+		idx = h8.index.get_indexer([ed], method="ffill")[0]
+		if idx < 0:
+			continue
+		row = h8.iloc[idx]
+		state = str(row["market_state"])
+		allowed = bool(row["allow_spring"])
+		rec = {
+			**t,
+			"market_state": state,
+			"allow_spring": allowed,
+			"domain": "good" if state in GOOD else ("bad" if state in BAD else "other"),
+			"accumulation_score": float(row["accumulation_score"]),
+			"markup_score": float(row["markup_score"]),
+			"distribution_score": float(row["distribution_score"]),
+			"markdown_score": float(row["markdown_score"]),
+			"range_score": float(row["range_score"]),
+		}
+		out.append(rec)
+	return out
+
+
+def bucket(rows: list[dict], key: str) -> dict[str, Any]:
+	g: dict[str, list[float]] = defaultdict(list)
+	for r in rows:
+		g[str(r[key])].append(float(r["profit_ratio"]))
+	return {k: _stats(v) for k, v in sorted(g.items(), key=lambda x: -len(x[1]))}
+
+
+def main() -> None:
+	logging.getLogger("freqtrade").setLevel(logging.ERROR)
+	install_offline_markets([PAIR])
+
+	print("===== Baseline SPRING_LONG trades =====", flush=True)
+	raw = run_baseline_spring_trades()
+	print(f"  spring trades={len(raw)}", flush=True)
+	rows = annotate(raw)
+	kept = [r for r in rows if r["allow_spring"]]
+	blocked = [r for r in rows if not r["allow_spring"]]
+
+	result: dict[str, Any] = {
+		"pair": PAIR,
+		"fee_model": "fee5bps+slip5bps",
+		"n_spring_total": len(rows),
+		"n_kept": len(kept),
+		"n_blocked": len(blocked),
+		"kept": {
+			"overall": _stats([r["profit_ratio"] for r in kept]),
+			"by_state": bucket(kept, "market_state"),
+			"by_era": bucket(kept, "era"),
+		},
+		"blocked": {
+			"overall": _stats([r["profit_ratio"] for r in blocked]),
+			"by_state": bucket(blocked, "market_state"),
+			"by_era": bucket(blocked, "era"),
+			"by_domain": bucket(blocked, "domain"),
+		},
+		"blocked_share_by_state": {},
+		"verdict": {},
+	}
+
+	# blocked 状态占比
+	if blocked:
+		for st, stt in result["blocked"]["by_state"].items():
+			result["blocked_share_by_state"][st] = round(stt["n"] / len(blocked), 3)
+
+	bad_n = sum(result["blocked"]["by_state"].get(s, {}).get("n", 0) for s in BAD)
+	blocked_bad_share = (bad_n / len(blocked)) if blocked else 0.0
+	kept_good_share = 0.0
+	if kept:
+		kg = sum(1 for r in kept if r["market_state"] in GOOD)
+		kept_good_share = kg / len(kept)
+
+	bk = result["blocked"]["overall"]
+	kp = result["kept"]["overall"]
+	result["verdict"] = {
+		"blocked_mostly_bad_domain": blocked_bad_share >= 0.8,
+		"blocked_bad_share": round(blocked_bad_share, 3),
+		"kept_mostly_good_domain": kept_good_share >= 0.95,
+		"kept_good_share": round(kept_good_share, 3),
+		"blocked_pf_worse_than_kept": bk["pf"] < kp["pf"],
+		"blocked_pf": bk["pf"],
+		"kept_pf": kp["pf"],
+		"status": (
+			"PASS"
+			if (
+				blocked_bad_share >= 0.8
+				and kept_good_share >= 0.95
+				and bk["pf"] < kp["pf"]
+			)
+			else "PARTIAL"
+			if (blocked_bad_share >= 0.7 and bk["pf"] <= kp["pf"])
+			else "FAIL"
+		),
+		"note": "PASS = Gate filters structural bad domains, not random sample deletion.",
+	}
+
+	print("\n===== KEPT (allow_spring) =====", flush=True)
+	print(json.dumps(result["kept"], indent=2, ensure_ascii=False))
+	print("\n===== BLOCKED =====", flush=True)
+	print(json.dumps(result["blocked"], indent=2, ensure_ascii=False))
+	print("\n===== Verdict =====", flush=True)
+	print(json.dumps(result["verdict"], indent=2, ensure_ascii=False))
+
+	OUT.write_text(json.dumps(result, indent=2, ensure_ascii=False))
+	print(f"\nSaved {OUT}")
+
+
+if __name__ == "__main__":
+	main()