refactor: 缠论引擎迁入 chan/ 分层解耦，指标外置

将核心结构、指标与分析拆到 chan/{core,indicators,analysis,pipeline}；
根目录保留兼容 shim；strategies 改为从 chan 包导入；买卖点经 bsp_macd 与 MACD 接合。

Co-authored-by: Cursor <cursoragent@cursor.com>

chan/indicators/__init__.py

@@ -0,0 +1,13 @@
+"""指标外置层：不依赖笔/段/中枢，只产出按 idx 对齐的序列。"""
+
+from .config import IndicatorConfig
+from .engine import IndicatorEngine
+from .store import IndicatorStore
+from .attach import attach_indicators_for_compat
+
+__all__ = [
+    "IndicatorConfig",
+    "IndicatorEngine",
+    "IndicatorStore",
+    "attach_indicators_for_compat",
+]

chan/indicators/attach.py

@@ -0,0 +1,20 @@
+"""过渡期：把 IndicatorStore 挂到 KLU 属性上，兼容旧代码读取 klu.ema52 等。"""
+
+from __future__ import annotations
+
+from typing import Iterable
+
+from .store import IndicatorStore
+
+
+def attach_indicators_for_compat(klu_list: Iterable, store: IndicatorStore) -> None:
+    """将指标写入 KLU（deprecated：新代码应通过 store.get(idx, name) 查询）。"""
+    for klu in klu_list:
+        idx = getattr(klu, "idx", None)
+        if idx is None:
+            continue
+        row = store.row(idx)
+        if row is None:
+            continue
+        if hasattr(klu, "set_indicators"):
+            klu.set_indicators(row)

chan/indicators/config.py

@@ -0,0 +1,25 @@
+"""指标参数配置（不再散落在结构流水线内）。"""
+
+from dataclasses import dataclass, field
+from typing import List, Tuple
+
+
+@dataclass
+class IndicatorConfig:
+    macd_fast: int = 26
+    macd_slow: int = 52
+    macd_signal: int = 9
+    ema_periods: Tuple[int, ...] = (5, 7, 10, 13, 24, 26, 52, 104, 156, 208)
+    rsi_period: int = 14
+    atr_period: int = 14
+    # (period, nbdevup, nbdevdn, name_suffix)
+    bbands: List[Tuple[int, float, float, str]] = field(
+        default_factory=lambda: [
+            (365, 3.0, 3.0, "365"),
+            (120, 3.0, 3.0, "120"),
+            (20, 2.0, 2.0, "30"),
+            (20, 2.0, 2.0, "302"),
+            (26, 3.0, 3.0, "2633"),
+        ]
+    )
+    bb_middle_sma_period: int = 90

chan/indicators/engine.py

@@ -0,0 +1,74 @@
+"""从 OHLC DataFrame 计算指标，不触碰缠论结构对象。"""
+
+from __future__ import annotations
+
+from typing import Optional
+
+import talib.abstract as ta
+import pandas as pd
+
+from .config import IndicatorConfig
+from .store import IndicatorStore
+
+
+def _volume_ratio(df: pd.DataFrame, window: int = 10) -> pd.Series:
+    vol = df["volume"].astype(float)
+    ma = vol.rolling(window=window).mean()
+    ratio = vol / ma
+    return ratio.fillna(1.0)
+
+
+class IndicatorEngine:
+    def __init__(self, config: Optional[IndicatorConfig] = None):
+        self.config = config or IndicatorConfig()
+
+    def compute(self, df: pd.DataFrame, config: Optional[IndicatorConfig] = None) -> IndicatorStore:
+        cfg = config or self.config
+        out = df.copy()
+        fast, slow, period = cfg.macd_fast, cfg.macd_slow, cfg.macd_signal
+        macd = ta.MACD(out, fastperiod=fast, slowperiod=slow, signalperiod=period)
+        out["macd"] = macd["macd"]
+        out["macdsignal"] = macd["macdsignal"]
+        out["macdhist"] = macd["macdhist"]
+
+        for period_n in cfg.ema_periods:
+            out[f"ema{period_n}"] = ta.EMA(out, timeperiod=period_n)
+
+        out["rsi"] = ta.RSI(out, timeperiod=cfg.rsi_period)
+        out["atr"] = ta.ATR(out, timeperiod=cfg.atr_period)
+        out["volume_ratio"] = _volume_ratio(out)
+
+        bb_middle = ta.SMA(out, timeperiod=cfg.bb_middle_sma_period)
+        for bb_period, nbup, nbdn, suffix in cfg.bbands:
+            bb = ta.BBANDS(
+                out,
+                timeperiod=bb_period,
+                nbdevup=nbup,
+                nbdevdn=nbdn,
+                matype=0,
+            )
+            bbp = (out["close"] - bb["lowerband"]) / (bb["upperband"] - bb["lowerband"])
+            if suffix == "2633":
+                out["bb2633upper"] = bb["upperband"]
+                out["bb2633lower"] = bb["lowerband"]
+                out["bb2633middle"] = bb["middleband"]
+                out["bbp2633"] = bbp
+            elif suffix == "365":
+                out["bbup365"] = bb["upperband"]
+                out["bblow365"] = bb["lowerband"]
+                out["bbp365"] = bbp
+            elif suffix == "120":
+                out["bbup120"] = bb["upperband"]
+                out["bblow120"] = bb["lowerband"]
+                out["bbp120"] = bbp
+            elif suffix == "30":
+                out["bbup30"] = bb["upperband"]
+                out["bblow30"] = bb["lowerband"]
+                out["bbmiddle30"] = bb_middle
+                out["bbp30"] = bbp
+            elif suffix == "302":
+                out["bbup302"] = bb["upperband"]
+                out["bblow302"] = bb["lowerband"]
+                out["bbp302"] = bbp
+
+        return IndicatorStore(out)

chan/indicators/store.py

@@ -0,0 +1,41 @@
+"""按 bar idx 查询指标值。"""
+
+from __future__ import annotations
+
+from typing import Any, Dict, Optional
+
+import pandas as pd
+
+
+class IndicatorStore:
+    """以 DataFrame 列 + 行 idx 对齐的只读指标视图。"""
+
+    def __init__(self, df: pd.DataFrame):
+        self._df = df
+
+    @property
+    def dataframe(self) -> pd.DataFrame:
+        return self._df
+
+    def __len__(self) -> int:
+        return len(self._df)
+
+    def get(self, idx: int, name: str, default: Any = None) -> Any:
+        if idx < 0 or idx >= len(self._df):
+            return default
+        if name not in self._df.columns:
+            return default
+        val = self._df.iloc[idx][name]
+        if pd.isna(val):
+            return default
+        return val
+
+    def row(self, idx: int) -> Optional[Dict[str, Any]]:
+        if idx < 0 or idx >= len(self._df):
+            return None
+        return self._df.iloc[idx].to_dict()
+
+    def series(self, name: str):
+        if name not in self._df.columns:
+            return None
+        return self._df[name]