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 +1,240 @@
+#!/usr/bin/env python3
+"""
+Gate v1.1 冻结前小范围稳健性确认（不改 Spring / 不调 soft-score）
+
+在 Baseline SPRING_LONG 全集上：
+  - 按年份、era 切片
+  - 看 blocked 是否仍主要来自 distribution
+  - kept vs blocked 的 PF 关系是否稳定
+
+range 只作观察桶，不改交易规则。
+"""
+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
+
+AUDIT = ROOT / "user_data/Chan/scripts/wyckoff_negative_domain_audit_result.json"
+OUT = ROOT / "user_data/Chan/scripts/wyckoff_gate_robustness_slices_result.json"
+PAIR = "BTC/USDT:USDT"
+CFG = ROOT / "user_data/Chan/config/Wyckoff_BTC_V1_BASELINE.json"
+
+
+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, "sum_pct": 0.0, "winrate": 0.0}
+	return {
+		"n": len(ps),
+		"pf": round(_pf(ps), 3),
+		"sum_pct": round(100.0 * float(np.sum(ps)), 2),
+		"winrate": round(100.0 * sum(1 for p in ps if p > 0) / len(ps), 1),
+	}
+
+
+def load_annotated_springs() -> list[dict[str, Any]]:
+	"""复用 audit 逻辑，产出逐笔 annotated SPRING。"""
+	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()
+
+	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()
+
+	rows = []
+	for t in LocalTrade.bt_trades:
+		if "SPRING" not in (t.enter_tag or ""):
+			continue
+		ed = pd.Timestamp(t.open_date_utc)
+		if ed.tzinfo is None:
+			ed = ed.tz_localize("UTC")
+		idx = h8.index.get_indexer([ed], method="ffill")[0]
+		if idx < 0:
+			continue
+		st = h8.iloc[idx]
+		state = str(st["market_state"])
+		rows.append(
+			{
+				"entry_date": ed.isoformat(),
+				"year": str(ed.year),
+				"era": "2023plus" if ed >= pd.Timestamp("2023-01-01", tz="UTC") else "pre_2023",
+				"market_state": state,
+				"allow_spring": bool(st["allow_spring"]),
+				"profit_ratio": float(t.close_profit or 0.0),
+			}
+		)
+	return rows
+
+
+def slice_report(rows: list[dict], key: str) -> dict[str, Any]:
+	out: dict[str, Any] = {}
+	groups: dict[str, list[dict]] = defaultdict(list)
+	for r in rows:
+		groups[str(r[key])].append(r)
+	for k, rs in sorted(groups.items()):
+		kept = [x for x in rs if x["allow_spring"]]
+		blocked = [x for x in rs if not x["allow_spring"]]
+		b_by_state: dict[str, list[float]] = defaultdict(list)
+		for x in blocked:
+			b_by_state[x["market_state"]].append(x["profit_ratio"])
+		blocked_states = {s: _stats(ps) for s, ps in b_by_state.items()}
+		dist_n = blocked_states.get("distribution", {}).get("n", 0)
+		blocked_n = len(blocked)
+		out[k] = {
+			"n_total": len(rs),
+			"kept": _stats([x["profit_ratio"] for x in kept]),
+			"blocked": _stats([x["profit_ratio"] for x in blocked]),
+			"blocked_by_state": blocked_states,
+			"blocked_distribution_share": round(dist_n / blocked_n, 3) if blocked_n else None,
+			"blocked_all_bad": (
+				all(s in ("distribution", "markdown", "range") for s in blocked_states)
+				if blocked_n
+				else True
+			),
+		}
+	return out
+
+
+def main() -> None:
+	logging.getLogger("freqtrade").setLevel(logging.ERROR)
+	install_offline_markets([PAIR])
+
+	print("===== Annotate SPRING_LONG =====", flush=True)
+	rows = load_annotated_springs()
+	print(f"  n={len(rows)}", flush=True)
+
+	by_year = slice_report(rows, "year")
+	by_era = slice_report(rows, "era")
+
+	# 稳定性：有 blocked 的切片里，distribution 是否为第一大来源
+	dist_primary = []
+	for label, block in {**{f"year:{k}": v for k, v in by_year.items()}, **{f"era:{k}": v for k, v in by_era.items()}}.items():
+		bn = block["blocked"]["n"]
+		if bn < 2:
+			continue
+		states = block["blocked_by_state"]
+		top = max(states.items(), key=lambda x: x[1]["n"])[0] if states else None
+		dist_primary.append(
+			{
+				"slice": label,
+				"blocked_n": bn,
+				"top_blocked_state": top,
+				"distribution_share": block["blocked_distribution_share"],
+				"blocked_pf": block["blocked"]["pf"],
+				"kept_pf": block["kept"]["pf"],
+			}
+		)
+
+	n_slices = len(dist_primary)
+	n_dist_top = sum(1 for x in dist_primary if x["top_blocked_state"] == "distribution")
+	n_dist_ge_50 = sum(
+		1 for x in dist_primary if (x["distribution_share"] or 0) >= 0.5
+	)
+
+	result = {
+		"n_spring": len(rows),
+		"by_year": by_year,
+		"by_era": by_era,
+		"slice_summaries": dist_primary,
+		"range_observation_only": {
+			"note": "range 不作交易规则；仅观察 blocked 中的占比与 PF",
+			"blocked_range_global": _stats(
+				[r["profit_ratio"] for r in rows if (not r["allow_spring"] and r["market_state"] == "range")]
+			),
+		},
+		"verdict": {
+			"slices_with_blocked_ge_2": n_slices,
+			"distribution_is_top_blocked_state": n_dist_top,
+			"distribution_share_ge_50pct_slices": n_dist_ge_50,
+			"distribution_attribution_stable": (
+				n_slices > 0 and (n_dist_top / n_slices) >= 0.6
+			),
+			"status": (
+				"PASS"
+				if n_slices > 0 and (n_dist_top / n_slices) >= 0.6
+				else "PARTIAL"
+				if n_dist_ge_50 >= max(1, n_slices // 2)
+				else "FAIL"
+			),
+			"note": "PASS = across year/era slices, blocked mass still led by distribution.",
+		},
+	}
+
+	print("\n===== By year (blocked focus) =====", flush=True)
+	for y, b in by_year.items():
+		print(
+			f"  {y}: total={b['n_total']} kept_pf={b['kept']['pf']} "
+			f"blocked_n={b['blocked']['n']} blocked_pf={b['blocked']['pf']} "
+			f"dist_share={b['blocked_distribution_share']} states={list(b['blocked_by_state'])}",
+			flush=True,
+		)
+	print("\n===== By era =====", flush=True)
+	for e, b in by_era.items():
+		print(
+			f"  {e}: total={b['n_total']} kept_pf={b['kept']['pf']} "
+			f"blocked_n={b['blocked']['n']} blocked_pf={b['blocked']['pf']} "
+			f"dist_share={b['blocked_distribution_share']} states={list(b['blocked_by_state'])}",
+			flush=True,
+		)
+	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()