feat(backtest): 买卖点理由（用数据说话）+ 因子曲线 + 曲线新页面放大

用户要求：「所有买卖点详细说明买卖理由，用数据说话」「回测图上增加因子相关曲线
（买卖依据是股息率，就加股息率曲线）」「所有曲线能弹出新页面放大」。

一、买卖理由（后端产出结构化数据，前端只展示）
- 新增 `quant/trade_reasons.py`：封闭词表 + 文案构造器，组合引擎与单策略引擎共用，
  避免两个引擎对同一件事写出两种说法。理由里带**引擎当时的真实数字**：
  综合分名次/候选数/综合分/各因子原始值/持有交易日/预算与最低佣金/涨停比值等。
- 买入：按名次建仓、顺延成交、涨停未买、停牌未买、现金不足、不足最低佣金；
  卖出：跌出 TopN（含第几名掉出）、被股票池过滤（与「跌出 TopN」分开写）、
  超 Tmax 强制了结、Tmin 保护暂留、停牌/跌停顺延。
- `ActionRecord.reason` 覆盖**成交与未成交**全部买卖点（原 `reject_reason` 保留不动，
  老归档仍可读）；`Trade.entry_reason / exit_reason` 跟着成交记录走。
- 名次来自调仓日完整排名（新增 `_ranked_by_day`），拿不到名次时如实写「未给出名次」，
  绝不编造一个名次填进去。
- 未成交明细不再只写执行层原因：把「为什么选中它、当时各因子多少」一并给出。

二、因子曲线
- `FactorCurve`：每个策略因子一条曲线，值为**当日持仓按市值加权平均的原始值**
  （不做 z-score、不按方向取反，空仓日不落点、不插值、不用 0 填充），并带
  label/direction/unit 供界面说明口径；`FactorDef/FactorTemplate` 新增 `unit`
  （股息率 %、量比/接近新高 倍数、动量等 小数），11 个内置因子实例已逐一核对。
- 归档体积预算照旧按整包计量，无需改迁移。

三、界面
- 结果页新增「买卖说明」区块：全部买卖点 + 理由 + 数字标签，支持方向/成交状态/关键字
  筛选与日期排序；成交明细表加「为什么买 / 为什么卖」两列；新增「因子曲线」区块，
  每条曲线标出组合成交日，直接对照「买卖发生在什么水平」。
- 「新页面放大」：每条曲线（净值/回撤/因子/个股/月度）都能开 `/charts/{归档id}?s=...`
  整页看大图；放大页是 Server Component，数据从归档直出，URL 可分享且与归档一致。
  未归档的结果如实说明「未归档，无法放大」，不给坏链接。
- 数字格式与后端 `f"{v:.4f}"` 同规则（四舍六入五成双）：修掉 0.03125 在理由原文里
  显示 0.0312、旁边标签显示 0.0313 的不一致（17 组边界值与 Python 逐一比对一致）。
- `/factors/compose` 结果区改用同一个 `BacktestResultView`，两处口径不会再漂移。

验证：
- 新增 `tests/test_trade_reasons.py` 8 条（买入数字、跌出 TopN 名次、不在候选池、
  Tmax、Tmin 暂留、涨停未成交、因子曲线加权值、空仓不落点）；后端 510 条全过，ruff clean。
- 真实数据端到端：`/api/combos/run` 6 个月高股息组合（EXP-8EA2819B）13 个买卖点
  100% 带理由与数字，因子曲线 dividend_yield 117 点、单位 %；
  `scripts/verify_backtest_page_contract.py`（4 年、301 个买卖点、140 笔成交）扩展断言
  理由词表/名次/因子值/曲线单调性后通过。
- 浏览器实测：归档详情页与放大页 `/charts/...?s=factor:dividend_yield` 等 5 种曲线
  全部 200 渲染，截图确认表格与曲线数值正确。

backend/app/quant/trade_reasons.py

@@ -0,0 +1,404 @@
+"""买卖理由（数据化）与因子曲线的共享构造器。
+
+**为什么单独一个模块**：两套回测引擎（`combo_engine` 组合回测、`local_engine`
+单策略回测）都要回答同一个问题 ——「这一买一卖，当时的数字是多少？」。如果各写一份，
+措辞、口径、字段名迟早分叉，用户在两处看到的「理由」会互相矛盾。
+
+因此这里只放两件事：
+
+1. **封闭的原因词表 + 构造器**：每个 `code` 对应一类可判定的原因，`text` 里带关键数字，
+   `data` 里放当时的原始数值（排名 / 候选数 / 综合分 / 因子原始值 / 持有交易日 / 预算 …）。
+   引擎只允许用词表里的 code（`REASON_CODES`），避免出现「文案随手写」的漂移。
+2. **因子曲线的口径实现**：持仓股票的**权重加权平均原始值**，空仓日不落点、
+   不插值、不按方向取负（低为好的因子也原样画，方向由 `FactorCurve.direction` 说明）。
+
+数值一律「引擎当时算出来的」：前端只展示，不推算 —— 界面上不该出现看起来像真的数字。
+"""
+
+from __future__ import annotations
+
+import math
+from collections.abc import Mapping
+
+import pandas as pd
+
+from app.domain.entities.research import CurvePoint, FactorCurve, TradeReason
+from app.quant.factors import FactorDef
+
+# ---------- 封闭原因词表 ----------
+# 买入（成交）
+BUY_ENTER = "buy_enter_topn"
+BUY_DEFER_FILLED = "buy_defer_filled"
+# 买入（未成交 / 未执行）
+BUY_SKIP_LIMIT_UP = "buy_skip_limit_up"
+BUY_SKIP_HALTED = "buy_skip_halted"
+BUY_SKIP_NO_CASH = "buy_skip_no_cash"
+BUY_SKIP_MIN_COMMISSION = "buy_skip_min_commission"
+# 卖出（成交）
+SELL_DROP_TOPN = "sell_drop_topn"
+SELL_FORCE_TMAX = "sell_force_tmax"
+# 卖出（顺延 / 未成交）
+SELL_DEFER_TMIN = "sell_defer_tmin"
+SELL_DEFER_HALTED = "sell_defer_halted"
+SELL_DEFER_LIMIT_DOWN = "sell_defer_limit_down"
+
+REASON_CODES = frozenset(
+    {
+        BUY_ENTER,
+        BUY_DEFER_FILLED,
+        BUY_SKIP_LIMIT_UP,
+        BUY_SKIP_HALTED,
+        BUY_SKIP_NO_CASH,
+        BUY_SKIP_MIN_COMMISSION,
+        SELL_DROP_TOPN,
+        SELL_FORCE_TMAX,
+        SELL_DEFER_TMIN,
+        SELL_DEFER_HALTED,
+        SELL_DEFER_LIMIT_DOWN,
+    }
+)
+
+# 原因分类的中文短标签（前端筛选 / 表格上色用；改文案只改这里）
+REASON_LABELS: dict[str, str] = {
+    BUY_ENTER: "按名次建仓",
+    BUY_DEFER_FILLED: "顺延后成交",
+    BUY_SKIP_LIMIT_UP: "涨停未买",
+    BUY_SKIP_HALTED: "停牌未买",
+    BUY_SKIP_NO_CASH: "现金不足",
+    BUY_SKIP_MIN_COMMISSION: "不足最低佣金",
+    SELL_DROP_TOPN: "跌出 TopN",
+    SELL_FORCE_TMAX: "持有超 Tmax",
+    SELL_DEFER_TMIN: "Tmin 保护暂留",
+    SELL_DEFER_HALTED: "停牌未卖",
+    SELL_DEFER_LIMIT_DOWN: "跌停未卖",
+}
+
+
+def _num(v, digits: int = 6):
+    """把 numpy/pandas 数值安全地压成原生 float（NaN/inf 一律不带进理由里）。"""
+    if v is None:
+        return None
+    try:
+        f = float(v)
+    except (TypeError, ValueError):
+        return None
+    if math.isnan(f) or math.isinf(f):
+        return None
+    return round(f, digits)
+
+
+def factor_values(
+    factor_panels: Mapping[str, tuple[FactorDef, pd.DataFrame]],
+    day,
+    symbol: str,
+) -> dict[str, float]:
+    """该个股在 `day` 的各因子**原始值**（缺失因子不写进 data，不用 0 冒充）。
+
+    用交易日精确匹配：调仓日的打分与理由是同一份面板，所以这里取不到值就意味着
+    「该股当日无该因子值」，如实缺失比填 0 更可信。
+    """
+    out: dict[str, float] = {}
+    for name, (_defn, panel) in factor_panels.items():
+        if day not in panel.index or symbol not in panel.columns:
+            continue
+        v = _num(panel.at[day, symbol])
+        if v is not None:
+            out[name] = v
+    return out
+
+
+def _rank_data(
+    *,
+    rank: int | None,
+    total: int | None,
+    top_n: int | None,
+    score: float | None,
+    factors: dict[str, float] | None,
+) -> dict:
+    data: dict = {}
+    if rank is not None:
+        data["rank"] = int(rank)
+    if total is not None:
+        data["total"] = int(total)
+    if top_n is not None:
+        data["top_n"] = int(top_n)
+    if score is not None:
+        data["score"] = _num(score)
+    if factors:
+        data["factors"] = factors
+    return data
+
+
+def _rank_text(rank: int | None, total: int | None, top_n: int | None, score: float | None) -> str:
+    if rank is None:
+        return "调仓日综合分未给出名次"
+    parts = [f"综合分第 {rank}"]
+    if total:
+        parts.append(f"/{total}")
+    parts.append(" 名")
+    if top_n is not None:
+        parts.append(f"（TopN={top_n}）")
+    if score is not None:
+        parts.append(f"，综合分 {score:.4f}")
+    return "".join(parts)
+
+
+def buy_filled(
+    *,
+    rank: int | None,
+    total: int | None,
+    top_n: int | None,
+    score: float | None,
+    factors: dict[str, float] | None,
+    price: float | None,
+    budget: float | None = None,
+    deferred: bool = False,
+) -> TradeReason:
+    """买入成交的理由：名次 + 综合分 + 各因子当时的原始值 + 成交价。"""
+    head = "顺延买入成交" if deferred else "调仓日选中并建仓"
+    text = f"{head}：{_rank_text(rank, total, top_n, score)}"
+    if price is not None:
+        text += f"；成交价 {price:.2f} 元"
+    data = _rank_data(rank=rank, total=total, top_n=top_n, score=score, factors=factors)
+    if price is not None:
+        data["price"] = _num(price, 4)
+    if budget is not None:
+        data["budget"] = _num(budget, 2)
+    return TradeReason(code=BUY_DEFER_FILLED if deferred else BUY_ENTER, text=text, data=data)
+
+
+def buy_skipped(
+    code: str,
+    *,
+    rank: int | None = None,
+    total: int | None = None,
+    top_n: int | None = None,
+    score: float | None = None,
+    factors: dict[str, float] | None = None,
+    close: float | None = None,
+    prev_close: float | None = None,
+    limit_ratio: float | None = None,
+    budget: float | None = None,
+    min_commission: float | None = None,
+    not_in_pool: bool = False,
+) -> TradeReason:
+    """买入未成交 / 未执行的理由（涨停、停牌、现金不足、佣金门槛）。"""
+    if code not in REASON_CODES:
+        raise ValueError(f"未知的买入未成交原因：{code}")
+    data = _rank_data(rank=rank, total=total, top_n=top_n, score=score, factors=factors)
+    base = _rank_text(rank, total, top_n, score)
+    if code == BUY_SKIP_LIMIT_UP:
+        ratio = (
+            _num(close / prev_close, 4)
+            if close is not None and prev_close not in (None, 0)
+            else None
+        )
+        text = f"{base}，但当日涨停"
+        if ratio is not None:
+            text += f"（收盘 {close:.2f} / 前收 {prev_close:.2f} = {ratio:.3f}"
+            text += f" ≥ 涨停阈值 {limit_ratio:.3f}）" if limit_ratio else "）"
+        text += "，无法追买"
+        if ratio is not None:
+            data["close_prev_ratio"] = ratio
+        if limit_ratio is not None:
+            data["limit_ratio"] = _num(limit_ratio, 4)
+    elif code == BUY_SKIP_HALTED:
+        text = f"{base}，但当日无行情（停牌），无法买入"
+    elif code == BUY_SKIP_NO_CASH:
+        text = f"{base}，但可用现金不足，未成交"
+        if budget is not None:
+            text += f"（可用预算 {budget:.2f} 元）"
+    elif code == BUY_SKIP_MIN_COMMISSION:
+        text = f"{base}，但预算不足以覆盖最低佣金，未成交"
+        if budget is not None and min_commission is not None:
+            text += f"（预算 {budget:.2f} 元 < 最低佣金 {min_commission:.2f} 元）"
+    else:  # pragma: no cover - 上面的分支已覆盖全部代码
+        text = base
+    if close is not None:
+        data["close"] = _num(close, 4)
+    if prev_close is not None:
+        data["prev_close"] = _num(prev_close, 4)
+    if budget is not None:
+        data["budget"] = _num(budget, 2)
+    if min_commission is not None:
+        data["min_commission"] = _num(min_commission, 2)
+    if not_in_pool:
+        data["in_pool"] = False
+    return TradeReason(code=code, text=text, data=data)
+
+
+def sell_filled(
+    *,
+    code: str,
+    rank: int | None,
+    total: int | None,
+    top_n: int | None,
+    score: float | None,
+    factors: dict[str, float] | None,
+    hold_days: int,
+    tmin: int | None = None,
+    tmax: int | None = None,
+    price: float | None = None,
+    return_pct: float | None = None,
+    not_in_pool: bool = False,
+) -> TradeReason:
+    """卖出成交的理由（跌出 TopN / 持有超 Tmax），带持有交易日与当时名次。
+
+    `not_in_pool=True` 表示该股已**不在候选池**（被股票池/条件过滤，如转为 ST），
+    与「在池内但排名掉出去」是两回事，文案与 data 都分开写。
+    """
+    if code == SELL_FORCE_TMAX:
+        text = f"持有 {hold_days} 个交易日 > Tmax={tmax}，强制了结（与排名无关）"
+    else:
+        code = SELL_DROP_TOPN
+        if not_in_pool:
+            text = f"调仓日已不在候选池（被股票池/条件过滤）；持有 {hold_days} 个交易日"
+        else:
+            text = f"调仓日跌出 TopN：{_rank_text(rank, total, top_n, score)}；持有 {hold_days} 个交易日"
+        if tmin is not None:
+            text += f" ≥ Tmin={tmin}"
+    data = _rank_data(rank=rank, total=total, top_n=top_n, score=score, factors=factors)
+    data["hold_days"] = int(hold_days)
+    if not_in_pool:
+        data["in_pool"] = False
+    if tmin is not None:
+        data["tmin"] = int(tmin)
+    if tmax is not None:
+        data["tmax"] = int(tmax)
+    if price is not None:
+        text += f"；卖出价 {price:.2f} 元"
+        data["price"] = _num(price, 4)
+    if return_pct is not None:
+        data["return_pct"] = _num(return_pct, 4)
+    return TradeReason(code=code, text=text, data=data)
+
+
+def sell_deferred(
+    code: str,
+    *,
+    cause: str,
+    rank: int | None = None,
+    total: int | None = None,
+    top_n: int | None = None,
+    score: float | None = None,
+    factors: dict[str, float] | None = None,
+    hold_days: int | None = None,
+    tmin: int | None = None,
+    tmax: int | None = None,
+    close: float | None = None,
+    prev_close: float | None = None,
+    limit_ratio: float | None = None,
+    not_in_pool: bool = False,
+) -> TradeReason:
+    """卖出未成交（顺延 / 暂留）的理由：Tmin 保护 / 停牌 / 跌停。
+
+    `tmax` 有值时说明是 Tmax 强制了结被卡住，文案据此区分 —— 两者后续行为不同
+    （Tmin 保护等到满 Tmin，Tmax 每天重试且不认排名）。
+    """
+    if code not in REASON_CODES:
+        raise ValueError(f"未知的卖出顺延原因：{code}")
+    if tmax is not None:
+        head = f"持有 {hold_days} 个交易日超 Tmax={tmax}，本应强制了结"
+    elif code == SELL_DEFER_TMIN:
+        why = (
+            "调仓日已不在候选池（被股票池/条件过滤）"
+            if not_in_pool
+            else f"掉出 TopN（{_rank_text(rank, total, top_n, score)}）"
+        )
+        head = f"{why}但仅持 {hold_days} 个交易日 < Tmin={tmin}，按 Tmin 保护暂留"
+    else:
+        head = (
+            "调仓日已不在候选池（被股票池/条件过滤）"
+            if not_in_pool
+            else f"调仓日跌出 TopN（{_rank_text(rank, total, top_n, score)}）"
+        )
+    if cause == "tmin":
+        text = f"{head}，暂留至满 Tmin"
+    elif cause == "halted":
+        text = f"{head}，但当日无行情（停牌），顺延"
+    elif cause == "limit_down":
+        ratio = _num(close / prev_close, 4) if close is not None and prev_close not in (None, 0) else None
+        text = f"{head}，但当日跌停"
+        if ratio is not None:
+            text += f"（收盘 {close:.2f} / 前收 {prev_close:.2f} = {ratio:.3f}"
+            text += f" ≤ 跌停阈值 {limit_ratio:.3f}）" if limit_ratio else "）"
+        text += "，无法卖出，顺延"
+        if ratio is not None:
+            data_ratio = ratio
+            close_v, prev_v = _num(close, 4), _num(prev_close, 4)
+        else:
+            data_ratio, close_v, prev_v = None, None, None
+    else:  # pragma: no cover - 调用方只传 halted / limit_down
+        text = f"{head}，顺延"
+    data = _rank_data(rank=rank, total=total, top_n=top_n, score=score, factors=factors)
+    if not_in_pool:
+        data["in_pool"] = False
+    if hold_days is not None:
+        data["hold_days"] = int(hold_days)
+    if tmin is not None:
+        data["tmin"] = int(tmin)
+    if tmax is not None:
+        data["tmax"] = int(tmax)
+    if cause == "limit_down":
+        if data_ratio is not None:
+            data["close_prev_ratio"] = data_ratio
+            data["close"] = close_v
+            data["prev_close"] = prev_v
+        if limit_ratio is not None:
+            data["limit_ratio"] = _num(limit_ratio, 4)
+    if close is not None and "close" not in data and cause == "halted":
+        data["close"] = _num(close, 4)
+    return TradeReason(code=code, text=text, data=data)
+
+
+# ---------- 因子曲线（持仓加权平均原始值） ----------
+
+
+def weighted_average(values: Mapping[str, float], weights: Mapping[str, float]) -> float | None:
+    """权重加权平均；没有任何有效样本时返回 None（调用方据此不落点）。"""
+    total_w = 0.0
+    acc = 0.0
+    for symbol, w in weights.items():
+        v = values.get(symbol)
+        if v is None or w <= 0:
+            continue
+        acc += float(v) * float(w)
+        total_w += float(w)
+    if total_w <= 0:
+        return None
+    return acc / total_w
+
+
+def build_factor_curves(
+    factor_panels: Mapping[str, tuple[FactorDef, pd.DataFrame]],
+    weights_by_day: Mapping[object, dict[str, float]],
+) -> list[FactorCurve]:
+    """按「每日持仓权重」聚合出每个因子的曲线。
+
+    - `weights_by_day`：`{交易日: {symbol: 该股市值}}`，空仓日给空字典（不落点）；
+    - 值 = 该日持仓上该因子的权重加权平均**原始值**（不做 z-score、不按方向取负）；
+    - 曲线按因子键排序，保证同一份数据每次归档的顺序一致（便于 diff）。
+    """
+    out: list[FactorCurve] = []
+    for name in sorted(factor_panels):
+        defn, panel = factor_panels[name]
+        points: list[CurvePoint] = []
+        for day, weights in weights_by_day.items():
+            if not weights or day not in panel.index:
+                continue
+            row = panel.loc[day]
+            values = {s: _num(row.get(s)) for s in weights}
+            avg = weighted_average(values, weights)
+            if avg is None:
+                continue
+            points.append(CurvePoint(date=day.date() if hasattr(day, "date") else day, value=round(avg, 6)))
+        out.append(
+            FactorCurve(
+                name=name,
+                label=defn.display,
+                direction=defn.direction,
+                unit=defn.unit,
+                points=points,
+            )
+        )
+    return out