Qionk/a-share-quant

1"""2A股涨跌停限制检测与预测修正3"""4 5import numpy as np6 7 8def detect_price_limit_pct(stock_code: str, stock_name: str = "") -> float:9    """10    根据股票代码和名称检测涨跌停比例。11    返回: 涨跌幅限制百分比（如 0.10 = 10%），无法识别返回 None12    """13    code = str(stock_code).strip()14 15    # ST / *ST 股票 (5%)16    if stock_name and ("ST" in stock_name.upper()):17        return 0.0518 19    if code.startswith("688"):20        return 0.20  # 科创板 STAR Market21    if code.startswith("300") or code.startswith("301") or code.startswith("302"):22        return 0.20  # 创业板 ChiNext/GEM23    if code.startswith("60") or code.startswith("00"):24        return 0.10  # 沪深主板25    if code.startswith("83") or code.startswith("87") or code.startswith("43"):26        return 0.30  # 北交所/新三板 BSE/NEEQ27 28    return None29 30 31def get_board_name(stock_code: str) -> str:32    """获取板块名称（含涨跌幅信息）"""33    code = str(stock_code).strip()34    if code.startswith("688"):35        return "科创板 (±20%)"36    if code.startswith("300") or code.startswith("301") or code.startswith("302"):37        return "创业板/GEM (±20%)"38    if code.startswith("60"):39        return "沪市主板 (±10%)"40    if code.startswith("00"):41        return "深市主板 (±10%)"42    if code.startswith("83") or code.startswith("87") or code.startswith("43"):43        return "北交所/新三板 (±30%)"44    return "未知板块"45 46 47def apply_price_limits(predictions, last_close: float, limit_pct: float):48    """49    将预测价格裁剪到涨跌停范围内。50    predictions: ensemble_predict() 返回的 dict51    返回: 裁剪后的 dict52    """53    if limit_pct is None:54        return predictions55 56    upper = last_close * (1 + limit_pct)57    lower = last_close * (1 - limit_pct)58 59    result = predictions.copy()60    for key in ["predicted_close", "confidence_lower", "confidence_upper"]:61        if key in result and result[key] is not None and len(result[key]) > 0:62            arr = result[key] if isinstance(result[key], np.ndarray) else np.array(result[key])63            result[key] = np.clip(arr, lower, upper)64 65    if "model_predictions" in result and result["model_predictions"]:66        for k, v in result["model_predictions"].items():67            arr = v if isinstance(v, np.ndarray) else np.array(v)68            result["model_predictions"][k] = np.clip(arr, lower, upper)69 70    return result