fix: 策略库「重跑到今天」补齐组合分析 — 多策略组合级WF/一条龙/AI解读

策略库（/strategies）多策略组合卡片此前只有主回测：本轮把 v1.31.0
的组合分析链路延伸到多策略组合（N 策略 × 各自原标的）：

- walkforward：组合 WF 泛化为槽位模型（_ComboSlot/_ComboWalkForwardBase），
  PortfolioWalkForwardEngine 行为不变；新增 MultiStrategyWalkForwardEngine
  （N 个策略各跑各自原标的，key 形如 label@symbol），复用切窗语义与
  WalkForwardResult 结构（前端 WalkForwardPanel 直接渲染）
- benchmark：新增 evaluate_multi 一条龙（MultiStrategyEngine 回测 + 多策略
  组合 WF + 逐槽位三段体检多数口径聚合 + 综合评分 + 组合评级 + 各槽位标的
  等权买入持有基准对比），报告结构与单标的 evaluate_strategy 同构
- Web：新增 POST /backtest/multi-strategy/wf/run/async 与
  /backtest/multi-strategy/evaluate/run/async；多策略组合回测响应附带
  grade/score（与单标的/多标的组合响应同构）
- 前端 StrategiesView：组合结果区新增「WF 样本外验证 / 一条龙评估 / AI 解读」
  按钮与同构面板（按需触发，复用最近一次组合回测的 items/cash）；
  绩效指标表补齐 v1.28 深度 6 项（SQN/最大连胜连亏/Ulcer/VaR/CVaR）；
  aiPrompt 新增 multi 模式（策略明细语境 + 槽位表现段）
- 测试：多策略 WF 引擎 3 例、evaluate_multi 3 例、新端点 Web 级 2 例、
  aiPrompt multi 模式 1 例（pytest 1611 绿、node --test 5/5、E2E 9/9）

tests/unit/test_backtest_fitness_benchmark.py

@@ -251,3 +251,59 @@ def test_evaluate_portfolio_serializable():
     )
     text = json.dumps(report, default=str)
     assert "excess_return" in text
+
+
+# ── evaluate_multi（v1.31.1：多策略组合一条龙）────────────────────────────────
+def _slots_for_multi() -> list[Any]:
+    from easy_tdx.backtest.multi_strategy_engine import StrategySlot
+
+    return [
+        StrategySlot(
+            label="动量", symbol="SZ:000001", strategy=_CycleTrader(), df=_df(400, drift=0.002)
+        ),
+        StrategySlot(
+            label="反转", symbol="SH:600000", strategy=_CycleTrader(), df=_df(400, drift=0.003)
+        ),
+    ]
+
+
+def test_evaluate_multi_full_report_structure():
+    """多策略组合一条龙报告与 evaluate_portfolio 同构（前端面板可复用）。"""
+    from easy_tdx.backtest.benchmark import evaluate_multi
+
+    report = evaluate_multi(_slots_for_multi(), total_cash=500_000)
+    for key in ("performance", "score", "grade", "walkforward", "fitness", "benchmark", "config"):
+        assert key in report
+    assert "sqn" in report["performance"]
+    assert "max_consecutive_losses" in report["performance"]
+    assert report["performance"]["total_stocks"] == 2
+    assert 0 <= report["score"]["total"] <= 100
+    assert report["score"]["wf_provided"] is True
+    assert report["grade"]["grade"] in ("S", "A", "B", "C", "D")
+    assert report["grade"]["scenario"] == "portfolio"
+    assert len(report["walkforward"]["windows"]) > 0
+    assert report["fitness"]["total_checks"] == 8
+    assert "只标的通过" in report["fitness"]["checks"][0]["detail"]
+    assert "buy_hold" in report["benchmark"]
+    assert report["config"]["slots"] == ["动量@SZ:000001", "反转@SH:600000"]
+
+
+def test_evaluate_multi_buy_hold_excess_near_zero():
+    """各槽位换成买入持有后，组合收益 ≈ 等权买入持有基准（excess 近 0）。"""
+    from easy_tdx.backtest.benchmark import evaluate_multi
+    from easy_tdx.backtest.multi_strategy_engine import StrategySlot
+
+    bh_slots = [
+        StrategySlot(label=s.label, symbol=s.symbol, strategy=_BuyFirstBar(), df=s.df)
+        for s in _slots_for_multi()
+    ]
+    report = evaluate_multi(bh_slots, total_cash=500_000)
+    assert abs(report["benchmark"]["excess_return"]) < 0.05
+
+
+def test_evaluate_multi_serializable():
+    from easy_tdx.backtest.benchmark import evaluate_multi
+
+    report = evaluate_multi(_slots_for_multi(), total_cash=500_000, n_windows=3)
+    text = json.dumps(report, default=str)
+    assert "excess_return" in text

tests/unit/test_portfolio_walkforward.py

@@ -3,6 +3,7 @@
 from __future__ import annotations
 
 import json
+from typing import Any
 
 import numpy as np
 import pandas as pd
@@ -131,3 +132,53 @@ class TestPortfolioWalkForward:
             strategy=PeriodicStrategy, stocks=_stocks(), n_windows=0
         ).run()
         assert wf.n_windows == 2
+
+
+# ── MultiStrategyWalkForwardEngine（v1.31.1：多策略组合槽位 WF）───────────────
+def _slots() -> list[Any]:
+    from easy_tdx.backtest.multi_strategy_engine import StrategySlot
+
+    return [
+        StrategySlot(
+            label="双均线交叉",
+            symbol="SH:601088",
+            strategy=PeriodicStrategy(),
+            df=_make_df(400, seed=42),
+        ),
+        StrategySlot(
+            label="RSI反转",
+            symbol="SZ:000001",
+            strategy=PeriodicStrategy(),
+            df=_make_df(400, seed=99),
+        ),
+    ]
+
+
+def test_multi_strategy_wf_basic_structure() -> None:
+    from easy_tdx.backtest.walkforward import MultiStrategyWalkForwardEngine
+
+    wf = MultiStrategyWalkForwardEngine(strategies=_slots(), n_windows=4, total_cash=200_000).run()
+    assert len(wf.windows) == 4
+    assert wf.total_trades > 0
+    assert wf.total_trades == sum(w.total_trades for w in wf.windows)
+    # 窗口时间升序
+    starts = [pd.Timestamp(w.start) for w in wf.windows]
+    assert starts == sorted(starts)
+
+
+def test_multi_strategy_wf_matches_portfolio_structure() -> None:
+    """与 PortfolioWalkForwardEngine 输出同构（前端面板可复用）。"""
+    from easy_tdx.backtest.walkforward import MultiStrategyWalkForwardEngine
+
+    wf = MultiStrategyWalkForwardEngine(strategies=_slots(), n_windows=3).run()
+    d = wf.to_dict()
+    json.dumps(d)
+    assert "sqn" in d["windows"][0]["performance"]
+    assert "max_consecutive_wins" in d["windows"][0]["performance"]
+
+
+def test_multi_strategy_wf_empty_slots() -> None:
+    from easy_tdx.backtest.walkforward import MultiStrategyWalkForwardEngine
+
+    wf = MultiStrategyWalkForwardEngine(strategies=[], n_windows=3).run()
+    assert wf.windows == []

tests/unit/test_web_backtest.py

@@ -11,6 +11,7 @@
 from __future__ import annotations
 
 import time
+from typing import Any
 
 import numpy as np
 import pandas as pd
@@ -1196,3 +1197,171 @@ def test_portfolio_evaluate_endpoint(client, monkeypatch):
     assert report["grade"]["scenario"] == "portfolio"
     assert report["fitness"]["total_checks"] == 8
     assert report["config"]["stocks"] == ["SZ000001", "SH600519"]
+
+
+# ── 多策略组合级 WF / 一条龙评估端点（v1.31.1）────────────────────────────────
+def _fake_multi_slots(n: int = 400):
+    """构造 _fetch_multi_strategy_bars 的 mock 替身（两槽位合成行情）。"""
+    import pandas as pd
+
+    from easy_tdx.backtest.multi_strategy_engine import StrategySlot
+
+    async def fake_fetch(client_arg, items):  # noqa: ANN001
+        slots = []
+        for item in items:
+            mkt, code = item.symbol.split(":")
+            close = 10 + np.cumsum(np.random.randn(n) * 0.3 + 0.02)
+            df = pd.DataFrame(
+                {
+                    "datetime": pd.date_range("2023-01-02", periods=n, freq="B"),
+                    "open": close - 0.1,
+                    "high": close + 0.2,
+                    "low": close - 0.2,
+                    "close": close,
+                    "vol": np.full(n, 5000.0),
+                    "amount": close * 5000,
+                }
+            )
+            slots.append(
+                StrategySlot(label=item.strategy, symbol=item.symbol, strategy=None, df=df)
+            )
+        return slots
+
+    return fake_fetch
+
+
+def _multi_request() -> dict[str, Any]:
+    from datetime import date as _date
+
+    start = f"{_date.today().year - 3}-01-02"
+    return {
+        "items": [
+            {
+                "strategy": "ma_cross",
+                "strategy_label": "双均线交叉",
+                "params": {"fast": 5, "slow": 20},
+                "symbol": "SH:601088",
+                "category": "DAY",
+                "start_date": start,
+            },
+            {
+                "strategy": "macd",
+                "strategy_label": "MACD 金叉",
+                "params": {},
+                "symbol": "SZ:000001",
+                "category": "DAY",
+                "start_date": start,
+            },
+        ],
+        "cash": 200000,
+    }
+
+
+def test_multi_strategy_wf_endpoint(client, monkeypatch):
+    """POST /backtest/multi-strategy/wf/run/async 端到端（mock 取数 + 真实引擎）。
+
+    StrategySlot 由取数阶段绑定策略实例（_build 时替换 mock 的 None），
+    这里用 router 内的真实 _fetch_multi_strategy_bars 不可行（需 client），
+    故 fake_fetch 直接构造策略实例。
+    """
+    import pandas as pd
+
+    import easy_tdx.web.routers.backtest as bt_router
+    from easy_tdx.backtest.multi_strategy_engine import StrategySlot
+    from easy_tdx.backtest.strategies import get_registry
+
+    async def fake_fetch(client_arg, items):  # noqa: ANN001
+        registry = get_registry()
+        slots = []
+        for item in items:
+            entry = registry.get(item.strategy)
+            strategy = entry.build(item.params)
+            close = 10 + np.cumsum(np.random.randn(400) * 0.3 + 0.02)
+            df = pd.DataFrame(
+                {
+                    "datetime": pd.date_range("2023-01-02", periods=400, freq="B"),
+                    "open": close - 0.1,
+                    "high": close + 0.2,
+                    "low": close - 0.2,
+                    "close": close,
+                    "vol": np.full(400, 5000.0),
+                    "amount": close * 5000,
+                }
+            )
+            slots.append(
+                StrategySlot(
+                    label=item.strategy_label or item.strategy,
+                    symbol=item.symbol,
+                    strategy=strategy,
+                    df=df,
+                )
+            )
+        return slots
+
+    monkeypatch.setattr(bt_router, "_fetch_multi_strategy_bars", fake_fetch)
+
+    resp = client.post(
+        "/api/v1/backtest/multi-strategy/wf/run/async?n_windows=3",
+        json=_multi_request(),
+    )
+    assert resp.status_code == 202, resp.text
+    final = _wait_task(client, resp.json()["task_id"])
+    assert final["status"] == "done", final
+    wf = final["result"]["walkforward"]
+    assert wf["n_windows"] == 3
+    assert len(wf["windows"]) == 3
+    assert "consistency" in wf
+    assert "sqn" in wf["windows"][0]["performance"]
+
+
+def test_multi_strategy_evaluate_endpoint(client, monkeypatch):
+    """POST /backtest/multi-strategy/evaluate/run/async 端到端。"""
+    import pandas as pd
+
+    import easy_tdx.web.routers.backtest as bt_router
+    from easy_tdx.backtest.multi_strategy_engine import StrategySlot
+    from easy_tdx.backtest.strategies import get_registry
+
+    async def fake_fetch(client_arg, items):  # noqa: ANN001
+        registry = get_registry()
+        slots = []
+        for item in items:
+            entry = registry.get(item.strategy)
+            strategy = entry.build(item.params)
+            close = 10 + np.cumsum(np.random.randn(400) * 0.3 + 0.02)
+            df = pd.DataFrame(
+                {
+                    "datetime": pd.date_range("2023-01-02", periods=400, freq="B"),
+                    "open": close - 0.1,
+                    "high": close + 0.2,
+                    "low": close - 0.2,
+                    "close": close,
+                    "vol": np.full(400, 5000.0),
+                    "amount": close * 5000,
+                }
+            )
+            slots.append(
+                StrategySlot(
+                    label=item.strategy_label or item.strategy,
+                    symbol=item.symbol,
+                    strategy=strategy,
+                    df=df,
+                )
+            )
+        return slots
+
+    monkeypatch.setattr(bt_router, "_fetch_multi_strategy_bars", fake_fetch)
+
+    resp = client.post(
+        "/api/v1/backtest/multi-strategy/evaluate/run/async",
+        json=_multi_request(),
+    )
+    assert resp.status_code == 202, resp.text
+    final = _wait_task(client, resp.json()["task_id"])
+    assert final["status"] == "done", final
+    report = final["result"]
+    for key in ("performance", "score", "grade", "walkforward", "fitness", "benchmark", "config"):
+        assert key in report
+    assert report["grade"]["scenario"] == "portfolio"
+    assert report["fitness"]["total_checks"] == 8
+    assert report["config"]["slots"] == ["双均线交叉@SH:601088", "MACD 金叉@SZ:000001"]