From dc201905f69ac3b1d1c283fe04e24a15eded0cda Mon Sep 17 00:00:00 2001
From: zlt <zlt@zlt.com>
Date: Thu, 30 Jul 2026 12:55:24 +0800
Subject: [PATCH] =?UTF-8?q?plan=20v2:=20=E6=AF=8F=E4=B8=BB=E9=A2=98?=
 =?UTF-8?q?=E9=99=90=E9=A2=9D(=E9=BB=98=E8=AE=A45,=20=E9=98=B2=E5=8D=95?=
 =?UTF-8?q?=E6=9D=BF=E5=9D=97=E5=88=B7=E5=B1=8F)=20+=20=E9=A2=84=E6=9C=9F?=
 =?UTF-8?q?=E7=A9=BA=E9=97=B4=E5=88=97=E7=8E=B0=E7=AE=97=E5=85=9C=E5=BA=95?=
 =?UTF-8?q?=20=EF=BC=88=E5=BD=93=E6=97=A5=20upside=20=E8=A1=A8=E5=9C=A8=20?=
 =?UTF-8?q?18:40=20=E5=BB=BA=E8=A1=A8=E6=97=B6=E8=A1=8C=E6=83=85=E6=9C=AA?=
 =?UTF-8?q?=E5=88=B0=E3=80=81=E5=B8=B8=E4=B8=BA=E7=A9=BA=E2=80=94=E2=80=94?=
 =?UTF-8?q?=E8=AF=BB=E8=A1=A8=E6=94=B9=E4=B8=BA=E7=A9=BA=E5=88=99=E7=8E=B0?=
 =?UTF-8?q?=E7=AE=97=EF=BC=89?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 plan.py | 44 ++++++++++++++++++++++++++++++++++++++------
 run.py  |  4 +++-
 2 files changed, 41 insertions(+), 7 deletions(-)

diff --git a/plan.py b/plan.py
index c2c89f4..d83a933 100644
--- a/plan.py
+++ b/plan.py
@@ -94,7 +94,27 @@ def _num(v) -> str:
     return "—" if v is None or pd.isna(v) else f"{v:.2f}"
 
 
-def generate(date: str | None = None, top: int = 20, obs_top: int = 10) -> str:
+def _pick(ranked: pd.Series, ev: dict, top: int, theme_cap: int):
+    """按分数从高到低取 top 条；每个传导主题最多 theme_cap 条（0=不设限）。
+
+    为什么设限：传导目标是环节级，同环节全体成员共享同一条证据，不设限时
+    榜单会被三四个环节刷屏——20 个名额实际只是 4 注。限额后变成
+    "多条线索 × 每条线索取最冷最便宜的几只"，被挤掉的仍在完整档位表里。"""
+    out, cnt = [], {}
+    for k, s in ranked.items():
+        e = ev.get(k)
+        theme = e[0] if e else "（无传导）"
+        if theme_cap and cnt.get(theme, 0) >= theme_cap:
+            continue
+        cnt[theme] = cnt.get(theme, 0) + 1
+        out.append((k, s))
+        if len(out) >= top:
+            break
+    return out
+
+
+def generate(date: str | None = None, top: int = 20, obs_top: int = 10,
+             theme_cap: int = 5) -> str:
     ds = date or _latest_date("t_factor_akg_score")
     if not ds:
         raise SystemExit("t_factor_akg_score 还没有数据——先 build akg_score。")
@@ -103,6 +123,15 @@ def generate(date: str | None = None, top: int = 20, obs_top: int = 10) -> str:
     if score.empty or gate.empty:
         raise SystemExit(f"{ds} 缺 akg_score / akg_gate——先 build 该日再出计划。")
     upside = _factor("t_factor_akg_upside", ds)
+    if upside.empty:
+        # 晚间 18:40 建当日 upside 表时行情源（~19:50 发布）还没到，当日表常为空。
+        # 这里现算兜底：此刻库里已有晚到的当日价，as-of 口径不变（consensus<=当日）。
+        import factors
+        df_up = factors.build_upside(ds, ds)
+        if df_up is not None and not df_up.empty:
+            x = df_up.copy()
+            x["k"] = x["stock_code"].map(common.to_prefix)
+            upside = x.groupby("k")["factor_value"].max().astype(float)
     hd = _latest_date("t_factor_akg_heat", ds)
     heat = _factor("t_factor_akg_heat", hd) if hd else pd.Series(dtype=float)
     names = _names()
@@ -119,23 +148,26 @@ def generate(date: str | None = None, top: int = 20, obs_top: int = 10) -> str:
                  f"\"谁已经动了\"看的是上个交易日收盘；拍点方案定版前均如此）。")
     L.append("")
 
-    L.append(f"## 主榜 Top {min(top, len(main))}（有券商预期、目标价不低于现价）")
+    cap_txt = f"，每主题限额 {theme_cap}" if theme_cap else ""
+    main_rows = _pick(main, ev, top, theme_cap)
+    L.append(f"## 主榜 Top {len(main_rows)}（有券商预期、目标价不低于现价{cap_txt}）")
     L.append("")
     L.append("| # | 代码 | 名称 | 总分 | 档位 | 传导证据 | 热度 | 预期空间 |")
     L.append("|---|------|------|------|------|----------|------|----------|")
-    for i, (k, s) in enumerate(main.head(top).items(), 1):
+    for i, (k, s) in enumerate(main_rows, 1):
         e = ev.get(k)
         etxt = f"{e[0]}（{e[1]} 源，已动 {e[2]:.0%}）" if e else "—"
         L.append(f"| {i} | {k} | {names.get(k, '—')} | {s:.1f} | {_tier_label(s)} "
                  f"| {etxt} | {_num(heat.get(k))} | {_pct(upside.get(k))} |")
     L.append("")
 
-    L.append(f"## 观察档 Top {min(obs_top, len(obs))}"
-             f"（无券商预期、但在传导链上——没有估值锚，置信度低）")
+    obs_rows = _pick(obs, ev, obs_top, theme_cap)
+    L.append(f"## 观察档 Top {len(obs_rows)}"
+             f"（无券商预期、但在传导链上——没有估值锚，置信度低{cap_txt}）")
     L.append("")
     L.append("| # | 代码 | 名称 | 分 | 传导证据 | 热度 |")
     L.append("|---|------|------|----|----------|------|")
-    for i, (k, s) in enumerate(obs.head(obs_top).items(), 1):
+    for i, (k, s) in enumerate(obs_rows, 1):
         e = ev.get(k)
         etxt = f"{e[0]}（{e[1]} 源，已动 {e[2]:.0%}）" if e else "—"
         L.append(f"| {i} | {k} | {names.get(k, '—')} | {s:.1f} "
diff --git a/run.py b/run.py
index 3769d60..6de2126 100644
--- a/run.py
+++ b/run.py
@@ -145,6 +145,8 @@ def main():
     pl.add_argument("--date", help="默认取 score 表最新日")
     pl.add_argument("--top", type=int, default=20, help="主榜条数")
     pl.add_argument("--obs-top", type=int, default=10, help="观察档条数")
+    pl.add_argument("--theme-cap", type=int, default=5,
+                    help="每个传导主题最多几条（防单板块刷屏；0=不设限）")
     p = sub.add_parser("probe")
     p.add_argument("--section", choices=["all", "pools", "price", "upside", "corr"],
                    default="all",
@@ -178,7 +180,7 @@ def main():
         cmd_register()
     elif a.cmd == "plan":
         import plan
-        plan.generate(a.date, a.top, a.obs_top)
+        plan.generate(a.date, a.top, a.obs_top, a.theme_cap)
     elif a.cmd == "tracks":
         import tracks
         tracks.coverage_report()