复盘对账后两处口径修正：结论表只取不晚于数据日的最新行（历史重建防前视）；复盘名单加观察档等权；关注环节表补未动环节的成员数与领涨者（不限档位表内）
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
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zlt
parent
769aa59e68
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22
plan.py
22
plan.py
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@ -75,8 +75,8 @@ def _names() -> dict:
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def _evidence(ds: str):
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"""每股最强一条传导证据：主题、源数、已动比例；另返回涉及的行情快照日。"""
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tr = db.read_pg(
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"SELECT ts_code, target, n_sources, moved_ratio, mkt_trade_date "
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"FROM v_factor_transmission WHERE scan_date = %s", (ds,))
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"SELECT ts_code, target, n_sources, moved_ratio, mkt_trade_date, "
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"members_total, moved FROM v_factor_transmission WHERE scan_date = %s", (ds,))
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if tr.empty:
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return {}, set()
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tr["k"] = tr["ts_code"].map(common.to_prefix)
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@ -84,7 +84,10 @@ def _evidence(ds: str):
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tr["moved_ratio"] = pd.to_numeric(tr["moved_ratio"], errors="coerce").fillna(0)
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tr["strength"] = tr["n_sources"] * (1.0 - tr["moved_ratio"])
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tr = tr.sort_values("strength", ascending=False).drop_duplicates("k")
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ev = {r.k: (str(r.target), int(r.n_sources), float(r.moved_ratio))
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# 元组前三项是既有口径（多处按下标取），第四、五项是环节的成员数与已动数（关注环节表用）
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ev = {r.k: (str(r.target), int(r.n_sources), float(r.moved_ratio),
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None if pd.isna(r.members_total) else int(r.members_total),
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None if pd.isna(r.moved) else int(r.moved))
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for r in tr.itertuples()}
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days = {str(x) for x in tr["mkt_trade_date"].dropna().unique()}
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return ev, days
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@ -161,17 +164,22 @@ def _assemble_cards(ds: str, codes: list, ev: dict, upside: pd.Series,
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if cards.get(k, {}).get("verdict") == card.VERDICT_CANDIDATE:
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s["candidates"] += 1
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for e in ev.values(): # 只有未动名单的环节也是"被指向"，列入但无已启动
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segs.setdefault(e[0], {"segment": e[0], "n_sources": e[1], "chain_fit": None,
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"members_total": None, "moved": None,
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"started": [], "candidates": 0, "leader": None})
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s = segs.setdefault(e[0], {"segment": e[0], "n_sources": e[1], "chain_fit": None,
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"members_total": None, "moved": None,
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"started": [], "candidates": 0, "leader": None})
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if s["members_total"] is None and len(e) > 4:
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s["members_total"], s["moved"] = e[3], e[4]
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for s in segs.values():
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best, best_pct = None, None
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for k in s["started"]:
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p = cards.get(k, {}).get("pct0")
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# 领涨者按行情视图找，不限于档位表里的票：被指向且已启动但不在主榜与观察档的
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# （无覆盖且不在赛道、或被风险闸挡）也要显示，这是"定位对不对"的读数
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p = (daily.get(k) or {}).get("pct0")
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if p is not None and (best_pct is None or p > best_pct):
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best, best_pct = k, p
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s["leader"] = {"code": best, "pct0": best_pct} if best else None
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s["started_count"] = len(s["started"])
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s["started_in_tiers"] = sum(1 for k in s["started"] if k in cards)
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ordered = sorted(segs.values(), key=lambda s: (-s["candidates"], -(s["n_sources"] or 0),
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-(s["chain_fit"] or 0), s["segment"]))
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return cards, ordered
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@ -183,6 +183,7 @@ def run(since: str, until: str | None, horizons: tuple, start: str, out_dir: str
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full = data.get("_full") or {}
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main_rows, obs_rows = full.get("main", []), full.get("observe", [])
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main_codes = [r["code"] for r in main_rows]
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obs_codes = [r["code"] for r in obs_rows]
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tier_of = {r["code"]: r.get("tier") for r in main_rows}
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verdict_of = {r["code"]: r.get("verdict") for r in main_rows + obs_rows}
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seg_codes = sorted({r["code"] for r in main_rows + obs_rows if r.get("evidence")})
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@ -212,7 +213,8 @@ def run(since: str, until: str | None, horizons: tuple, start: str, out_dir: str
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if reg and reg.get("weak_day") is not None else "无标签")
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lists = {
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"生产名单": prod, "候选单": cands, "关注单": watch, "环节名单": seg_codes,
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"主榜等权": main_codes, "全池等权": list(ret.dropna().index),
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"主榜等权": main_codes, "观察档等权": obs_codes,
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"全池等权": list(ret.dropna().index),
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}
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for name, codes in lists.items():
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s = summarize(ret, codes, base_all, base_main)
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@ -93,13 +93,18 @@ def night_conclusions(codes, ds: str) -> dict[str, dict]:
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codes = sorted({common.to_prefix(str(c).strip()) for c in codes if c})
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if not codes:
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return {}
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# 只取不晚于数据日 ds 的结论行：生产上 ds 就是数据日，与"取最新一行"等价；
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# 复盘重建历史日时这一条防前视（否则历史日会读到今天的吸筹状态）。
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# trade_date 是整数 YYYYMMDD（数据源盘点 §1a），直接比大小。
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ds_int = int(ds.replace("-", "")) if ds else 99999999
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try:
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marks = ",".join(["%s"] * len(codes))
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df = db.read_mysql(
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"pms",
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f"SELECT stock_code, trade_date, signal_type, support_level, pressure_level, "
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f"raw_logic_json FROM strategy_daily_results WHERE stock_code IN ({marks})",
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tuple(codes))
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f"raw_logic_json FROM strategy_daily_results "
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f"WHERE stock_code IN ({marks}) AND trade_date <= %s",
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tuple(codes) + (ds_int,))
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except Exception as e: # noqa: BLE001
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print(f" （决策系统结论表读取失败，吸筹确认线与坏信号风险整体缺席: {e!r}）")
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return {}
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