commit 53407664e6fcf0da408a28dcb251ad8a5f763ef2 Author: wangzhiming <1115712903@qq.com> Date: Tue May 6 17:57:02 2025 +0800 上传文件至 / diff --git a/API.py b/API.py new file mode 100644 index 0000000..3992078 --- /dev/null +++ b/API.py @@ -0,0 +1,240 @@ + +import pandas as pd +import numpy as np +from datetime import datetime +from datetime import timedelta +import pymysql +from sqlalchemy import create_engine +from dateutil.relativedelta import relativedelta + + +# 在API.py开头添加 +import sys + +# 替换原来的get_user_date函数 +def get_user_date(): + if len(sys.argv) > 1: + datetime_input = sys.argv[1] + try: + return datetime.strptime(datetime_input, '%Y-%m-%d %H:%M:%S') + except ValueError: + print("日期格式不正确，请使用YYYY-MM-DD HH:MM:SS格式", file=sys.stderr) + sys.exit(1) + else: + print("没有传入日期时间参数", file=sys.stderr) + sys.exit(1) + +# 导入自定义卦象计算模块 +from guaCalc_huangjijingshi import guaCalc_huangjijingshi +from luckCalc_huangjijingshi import luckCalc_huangjijingshi + +# ========== 数据库连接配置 ========== +# 你的账号、密码、主机、端口 +username = 'cn_ainvest_db' +password = 'cn_ainvest_sd3a1' +host = 'rm-2zewagytttzk6f24xno.mysql.rds.aliyuncs.com' +port = 3306 +database = 'ai_strategy' # 这里改成你要的数据库 + +# 创建 SQLAlchemy engine +engine = create_engine(f'mysql+pymysql://{username}:{password}@{host}:{port}/{database}') + +# ========== 文件路径配置 ========== +configPath = r'C:\AI trading\config\Rey\test_reinforcement' +matlabPath = r'D:\Dropbox\Matlab\Rey\MATLAB' + +# 修改为你的 Excel 文件路径 +tempPath = r'C:\Users\24011\Documents\WeChat Files\wxid_k4ep58f81rx421\FileStorage\File\2025-04\tuigua_huangjijingshi - 副本\tuigua_huangjijingshi - 副本\皇极经世.xlsx' + +# ========== 加载 64 卦映射表 ========== +Map64Gua = pd.read_excel(tempPath, sheet_name="bagua") + +# 转换爻数据为整数 +for col in ['yao1', 'yao2', 'yao3', 'yao4', 'yao5', 'yao6']: + Map64Gua[col] = Map64Gua[col].apply(lambda x: int(x) if str(x).isdigit() else x) + +Map64GuaOmit = Map64Gua[Map64Gua['change_omit'] == 0] + +# ========== 从数据库加载 24 节气数据 ========== +def load_solar_terms(conn_params): + """通过 SQLAlchemy 连接读取 solar_terms 表""" + sqlquery = 'SELECT * FROM solar_terms' + df = pd.read_sql(sqlquery, engine) + + # 尝试将 As_Of_Date 转为 datetime，如果失败就变成 NaT + df['As_Of_Date'] = pd.to_datetime(df['As_Of_Date'], errors='coerce') + + # 过滤掉早于 1900-01-01 或转换失败的日期 + df = df[df['As_Of_Date'] >= pd.Timestamp('1900-01-01')] + df = df.dropna(subset=['As_Of_Date']) + # df['As_Of_Date'] = df['As_Of_Date'] + df = df.sort_values('As_Of_Date') + + return df + +# ========== 用户输入日期 ========== +# def get_user_date(): +# if len(sys.argv) > 1: # 命令行参数方式 +# date_input = sys.argv[1] +# else: # 标准输入方式 +# date_input = sys.stdin.read().strip() + +# try: +# year, month, day = map(int, date_input.split('-')) +# return datetime(year, month, day, 0, 0, 0) +# except ValueError: +# print("日期格式不正确，请使用YYYY-MM-DD格式", file=sys.stderr) +# sys.exit(1) +# 获取用户输入 +def get_user_date(): + # date_input = sys.stdin.read().strip() if len(sys.argv) == 1 else sys.argv[1] + if len(sys.argv) > 1: + datetime_input = sys.argv[1] + else: + print("没有传入日期时间参数", file=sys.stderr) + sys.exit(1) + try: + # 解析包含时间的日期 + return datetime.strptime(datetime_input, '%Y-%m-%d %H:%M:%S') + # # 确保日期格式为 YYYY-MM-DD + # return datetime.strptime(date_input, '%Y-%m-%d') + except ValueError: + print("日期格式不正确，请使用YYYY-MM-DD格式", file=sys.stderr) + sys.exit(1) +# 加载数据并标记重要节气 +solar_terms = load_solar_terms(engine) +important_terms = ['冬至', '雨水', '谷雨', '夏至', '处暑', '霜降'] +solar_terms['isImportant'] = solar_terms['Solar_Terms'].isin(important_terms).astype(int) +Map24Jieqi = solar_terms.copy() + +# ========== 读取CSV文件并处理每个日期的卦象 ========== +csv_path = r'C:\Users\24011\Documents\WeChat Files\wxid_k4ep58f81rx421\FileStorage\File\2025-04\tuigua_huangjijingshi - 副本\tuigua_huangjijingshi - 副本\python1\2020 - 2030年每天卦.csv' +table = pd.read_csv(csv_path) +# 获取用户输入 +kDate = get_user_date() +#print("\n计算日期:", kDate.strftime('%Y-%m-%d')) +# 计算卦象 +Gua1Hour, Gua1Day, Gua1Month, Gua1Year, GuaLuck = guaCalc_huangjijingshi( + Map64Gua, Map24Jieqi, kDate +) +# print("日卦:", Gua1Day) +import json # 导入 JSON 库 +# ========== 计算并返回 JSON 格式的结果 ========== + +# ========== 计算并返回 JSON 格式的结果 ========== + +if __name__ == "__main__": + print("=== 调试开始 ===", file=sys.stderr) # 打印到 stderr 不会干扰 stdout 的 JSON + kDate = get_user_date() + try: + Gua1Hour, Gua1Day, Gua1Month, Gua1Year, GuaLuck = guaCalc_huangjijingshi( + Map64Gua, Map24Jieqi, kDate + ) + # # 计算10年前（当前日期减10年） + # Yearpre10 = kDate.replace(year=kDate.year - 10) + # # 计算10年后（当前日期加10年） + # Yearpast10 = kDate.replace(year=kDate.year + 10) + # 或者使用relativedelta（更精确处理闰年等情况） + Yearpre10 = datetime(2010, 1, 1) + Yearpast10 = datetime(2030, 1, 1,) + + # 生成日期范围（修正end参数） + date_range = pd.date_range( + start=Yearpre10.replace(month=1, day=1), # 确保从1月1日开始 + end=Yearpast10.replace(month=1, day=1), # 确保到1月1日结束 + freq='YS' # 每年第一天 + ) + #date_range = pd.date_range(start=Yearpre10, end=Yearpast10, freq='YS') # 每年第一天 + year_gua_list = [] + for date in date_range: + _, _, _, Gua1Year, _ = guaCalc_huangjijingshi(Map64Gua, Map24Jieqi, date) + year_gua_list.append({ + 'Year': date.year, + 'Trigram': Gua1Year.trigram if hasattr(Gua1Year, 'trigram') else None, + }) + + yearGuaMap = pd.DataFrame(year_gua_list) + #========== 计算年份吉凶 ========== + LuckYear = luckCalc_huangjijingshi(Map64Gua, yearGuaMap, GuaLuck) + + # # 检查 Gua1Day 的类型并正确处理 + # if isinstance(Gua1Day, pd.DataFrame): + # # 如果是 DataFrame，提取第一行 + # day_data = Gua1Day.iloc[0] + # elif isinstance(Gua1Day, pd.Series): + # # 如果是 Series，直接使用 + # day_data = Gua1Day + # elif isinstance(Gua1Day, dict): + # # 如果是字典，直接使用 + # day_data = Gua1Day + # else: + # raise ValueError("Gua1Day 的类型不支持，必须是 DataFrame、Series 或 dict") + def format_gua_data(gua_data): + """通用格式化卦象数据的函数""" + if isinstance(gua_data, (pd.DataFrame, pd.Series)): + data = gua_data.iloc[0] if isinstance(gua_data, pd.DataFrame) else gua_data + return { + 'id': int(data.get('id', 0)), + 'trigram': str(data.get('trigram', '')), + 'yaoAll': str(data.get('yaoAll', '')), + 'yao1': int(data.get('yao1', 0)), + 'yao2': int(data.get('yao2', 0)), + 'yao3': int(data.get('yao3', 0)), + 'yao4': int(data.get('yao4', 0)), + 'yao5': int(data.get('yao5', 0)), + 'yao6': int(data.get('yao6', 0)), + 'value_2binary': int(data.get('value_2binary', 0)), + 'change_omit': int(data.get('change_omit', 0)), + 'type': str(data.get('Type', 'unknown')) + } + elif isinstance(gua_data, dict): + return gua_data + else: + return {} + + # 构建结果字典，确保所有值是 Python 原生类型 + # result = { + # 'date': kDate.strftime('%Y-%m-%d'), + # 'day_gua': { + # 'id': int(day_data.get('id', 0)), # 如果没有值，使用默认值 0 + # 'trigram': str(day_data.get('trigram', '')), # 如果没有值，使用空字符串 + # 'yaoAll': str(day_data.get('yaoAll', '')), # 如果没有值，使用空字符串 + # 'yao1': int(day_data.get('yao1', 0)), # 如果没有值，使用默认值 0 + # 'yao2': int(day_data.get('yao2', 0)), # 如果没有值，使用默认值 0 + # 'yao3': int(day_data.get('yao3', 0)), # 如果没有值，使用默认值 0 + # 'yao4': int(day_data.get('yao4', 0)), # 如果没有值，使用默认值 0 + # 'yao5': int(day_data.get('yao5', 0)), # 如果没有值，使用默认值 0 + # 'yao6': int(day_data.get('yao6', 0)), # 如果没有值，使用默认值 0 + # 'value_2binary': int(day_data.get('value_2binary', 0)), # 如果没有值，使用默认值 0 + # 'change_omit': int(day_data.get('change_omit', 0)), # 如果没有值，使用默认值 0 + # 'type': str(day_data.get('Type', 'day')) # 如果没有值，使用默认值 'day' + # } + # } + # 构建完整结果 + result = { + 'date': kDate.strftime('%Y-%m-%d'), + 'year_gua': format_gua_data(Gua1Year), + 'month_gua': format_gua_data(Gua1Month), + 'day_gua': format_gua_data(Gua1Day), + 'hour_gua': format_gua_data(Gua1Hour), + 'luck_gua': format_gua_data(GuaLuck), + 'luck_years': [ + { + 'year': row['Year'], + 'trigram': row['trigram'], + 'yaoAll': row['yaoAll'] + } for _, row in LuckYear.iterrows() + ] if isinstance(LuckYear, pd.DataFrame) else [] + } + # 在打印 JSON 前检查内容 + print("=== 要输出的 JSON 内容 ===", file=sys.stderr) + print(result, file=sys.stderr) + # 输出 JSON 格式的结果 + # print(json.dumps(result, ensure_ascii=False, indent=4)) # 添加 indent 参数更好查看格式 + print(json.dumps(result, ensure_ascii=False, indent=2)) + + except Exception as e: + import traceback + traceback.print_exc(file=sys.stderr) # 打印错误堆栈，帮助调试 + print(f"计算错误: {str(e)}", file=sys.stderr) + sys.exit(1) \ No newline at end of file diff --git a/bianyao_huangjijingshi.py b/bianyao_huangjijingshi.py new file mode 100644 index 0000000..e83fc33 --- /dev/null +++ b/bianyao_huangjijingshi.py @@ -0,0 +1,56 @@ +import pandas as pd + +def bianyao_huangjijingshi(Map64Gua: pd.DataFrame, yaoOrig: str) -> pd.DataFrame: + """ + 皇极经世：变爻计算 + 输入原爻（如 '000100'），输出所有变爻之后的卦象合集 + """ + #print("Map64Gua:",Map64Gua['yaoAll'].apply(type).value_counts()) + # 找到原始卦所在的行 + if 'yaoAll' not in Map64Gua.columns: + raise ValueError("'yaoAll' 列在 Map64Gua 中不存在，请检查数据") + + Map64Gua = Map64Gua.copy() + Map64Gua['yaoAll'] = Map64Gua['yaoAll'].astype(str).str.zfill(6).str.strip() + yaoOrig = str(yaoOrig).zfill(6).strip() + + # 找到原始卦所在的行 + matches = Map64Gua[Map64Gua['yaoAll'] == yaoOrig] + if matches.empty: + raise ValueError(f"未找到 yaoAll 为 {yaoOrig} 的卦象") + + k2 = matches.iloc[0] # 取第一行 + + # 计算原卦的二进制值 + a0 = (k2['yao1'] + k2['yao2']*2 + k2['yao3']*4 + + k2['yao4']*8 + k2['yao5']*16 + k2['yao6']*32) + + # 依次翻转每一爻，得到新卦的二进制值 + a1 = (k2['yao1'] + k2['yao2']*2 + k2['yao3']*4 + + k2['yao4']*8 + k2['yao5']*16 + (1 - k2['yao6'])*32) + + a2 = (k2['yao1'] + k2['yao2']*2 + k2['yao3']*4 + + k2['yao4']*8 + (1 - k2['yao5'])*16 + k2['yao6']*32) + + a3 = (k2['yao1'] + k2['yao2']*2 + k2['yao3']*4 + + (1 - k2['yao4'])*8 + k2['yao5']*16 + k2['yao6']*32) + + a4 = (k2['yao1'] + k2['yao2']*2 + (1 - k2['yao3'])*4 + + k2['yao4']*8 + k2['yao5']*16 + k2['yao6']*32) + + a5 = (k2['yao1'] + (1 - k2['yao2'])*2 + k2['yao3']*4 + + k2['yao4']*8 + k2['yao5']*16 + k2['yao6']*32) + + a6 = ((1 - k2['yao1']) + k2['yao2']*2 + k2['yao3']*4 + + k2['yao4']*8 + k2['yao5']*16 + k2['yao6']*32) + + # 结果列表 + result = pd.DataFrame() + + # 查找对应的卦象 + for a in [a0, a1, a2, a3, a4, a5, a6]: + row = Map64Gua[Map64Gua['value_2binary'] == a] + if not row.empty: + result = pd.concat([result, row], ignore_index=True) + + return result diff --git a/guaCalc_huangjijingshi.py b/guaCalc_huangjijingshi.py new file mode 100644 index 0000000..086136f --- /dev/null +++ b/guaCalc_huangjijingshi.py @@ -0,0 +1,99 @@ +import pandas as pd +import numpy as np +from datetime import datetime, timedelta + +def guaCalc_huangjijingshi(Map64Gua, Map24Jieqi, kDate): + """ + Calculate year, month, day, and hour gua based on Huangji Jingshi method + Args: + Map64Gua (pd.DataFrame): 64 gua mapping table + Map24Jieqi (pd.DataFrame): 24 solar terms data + kDate (datetime): Target date for calculation + Returns: + tuple: (Gua4Hour, Gua1Day, Gua1Month, Gua1Year, GuaLuck) + """ + + # Helper functions that need to be implemented separately + from bianyao_huangjijingshi import bianyao_huangjijingshi + from tuigua_huangjijingshi import tuigua_huangjijingshi + + # Bagua for 360 years + yearRef = {'trigram': '姤', 'value_2binary': '111110', 'start_year': 1744} + Gua360Year = bianyao_huangjijingshi(Map64Gua, yearRef['value_2binary']) + Gua360Year['yearStart'] = [yearRef['start_year'] + i * 60 for i in range(len(Gua360Year))] + Gua360Year['yearEnd'] = [start + 59 for start in Gua360Year['yearStart']] + + # Bagua for 60 years + kYear = kDate.year + kYearOrig = kYear + + solar_terms = Map24Jieqi + solar_terms1 = solar_terms[solar_terms['Solar_Terms'] == '冬至'] + + # Find the last winter solstice before our date + k1 = np.where((kDate - solar_terms1['As_Of_Date']) > timedelta(0))[0][-1] + kYear = (solar_terms1['As_Of_Date'].iloc[k1] + timedelta(days=90)).year + + # Find which 60-year period we're in + mask = (Gua360Year['yearStart'] <= kYear) & (Gua360Year['yearEnd'] >= kYear) + k1 = np.where(mask)[0][0] # Get first match + + a1 = Gua360Year['value_2binary'].iloc[k1] + a2 = kYear - Gua360Year['yearStart'].iloc[k1] + Gua1Year = tuigua_huangjijingshi(Map64Gua, a1, a2 + 1) + Gua1Year['Type'] = 'year' + # print(type(Gua1Year)) + # print(Gua1Year) + # Bagua for 360 days (months) + dayRef = { + 'trigram': Gua1Year['trigram'], + 'yaoAll': Gua1Year['yaoAll'], + 'start_day': 1, + 'end_day': 360 + } + + Gua365days = bianyao_huangjijingshi(Map64Gua, Gua1Year['yaoAll']) + #print("Gua365days.columns:",print(Gua365days.columns)) + # Find important solar terms + solar_termsSimple = Map24Jieqi[Map24Jieqi['isImportant'] == 1] + + # Find the last important solar term before our date + kk = np.where((kDate - solar_termsSimple['As_Of_Date']) > timedelta(0))[0][-1] + + # Find winter solstice within these terms + kk2 = np.where(solar_termsSimple['Solar_Terms'].iloc[:kk+1] == '冬至')[0][-1] + + a1 = Gua365days['value_2binary'].iloc[kk - kk2 + 1] + + Gua1Month = Gua365days.iloc[[kk - kk2 + 1]].copy() + Gua1Month['Type'] = 'month' + + # Calculate day gua + kDateMonth = solar_termsSimple['As_Of_Date'].iloc[kk] + kGap = (kDate.date() - kDateMonth.date()).days + a2 = round(kGap) + Gua1Day = tuigua_huangjijingshi(Map64Gua, a1, a2) + Gua1Day['Type'] = 'day' + + # Calculate hour gua (4-hour blocks) + Gua24Hours = bianyao_huangjijingshi(Map64Gua, Gua1Day['yaoAll']) + k1 = min(int(np.ceil(kDate.hour / 4)), len(Gua24Hours) - 1) + Gua4Hour = Gua24Hours.iloc[[k1 + 1]].copy() + Gua4Hour['Type'] = 'hour' + + # Calculate luck gua + abc = pd.concat([ + Gua1Year[['yao1', 'yao2', 'yao3', 'yao4', 'yao5', 'yao6']], + Gua1Month[['yao1', 'yao2', 'yao3', 'yao4', 'yao5', 'yao6']], + Gua1Day[['yao1', 'yao2', 'yao3', 'yao4', 'yao5', 'yao6']], + Gua4Hour[['yao1', 'yao2', 'yao3', 'yao4', 'yao5', 'yao6']] + ]) + + abc2 = np.mod(np.nansum(abc, axis=0), 2)[:6] # 确保只有6位 + abc3 = np.sum(abc2 * [1, 2, 4, 8, 16, 32]) + + k1 = np.where(Map64Gua['value_2binary'] == abc3)[0][0] + GuaLuck = Map64Gua.iloc[[k1]].copy() + GuaLuck['Type'] = 'luck' + + return Gua4Hour, Gua1Day, Gua1Month, Gua1Year, GuaLuck \ No newline at end of file diff --git a/huangjijingshi20250217.py b/huangjijingshi20250217.py new file mode 100644 index 0000000..c22a2aa --- /dev/null +++ b/huangjijingshi20250217.py @@ -0,0 +1,88 @@ +import pandas as pd +import numpy as np +from datetime import datetime +import pymysql +from sqlalchemy import create_engine + +# 导入自定义卦象计算模块 +from guaCalc_huangjijingshi import guaCalc_huangjijingshi +from luckCalc_huangjijingshi import luckCalc_huangjijingshi + +# ========== 数据库连接配置 ========== +# 你的账号、密码、主机、端口 +username = 'cn_ainvest_db' +password = 'cn_ainvest_sd3a1' +host = 'rm-2zewagytttzk6f24xno.mysql.rds.aliyuncs.com' +port = 3306 +database = 'ai_strategy' # 这里改成你要的数据库 + +# 创建 SQLAlchemy engine +engine = create_engine(f'mysql+pymysql://{username}:{password}@{host}:{port}/{database}') + +# ========== 文件路径配置 ========== +configPath = r'C:\AI trading\config\Rey\test_reinforcement' +matlabPath = r'D:\Dropbox\Matlab\Rey\MATLAB' + +# 修改为你的 Excel 文件路径 +tempPath = r'C:\Users\24011\Documents\WeChat Files\wxid_k4ep58f81rx421\FileStorage\File\2025-04\tuigua_huangjijingshi - 副本\tuigua_huangjijingshi - 副本\皇极经世.xlsx' + +# ========== 加载 64 卦映射表 ========== +Map64Gua = pd.read_excel(tempPath, sheet_name="bagua") + +# 转换爻数据为整数 +for col in ['yao1', 'yao2', 'yao3', 'yao4', 'yao5', 'yao6']: + Map64Gua[col] = Map64Gua[col].apply(lambda x: int(x) if str(x).isdigit() else x) + +Map64GuaOmit = Map64Gua[Map64Gua['change_omit'] == 0] + +# ========== 从数据库加载 24 节气数据 ========== +def load_solar_terms(conn_params): + """通过 SQLAlchemy 连接读取 solar_terms 表""" + sqlquery = 'SELECT * FROM solar_terms' + df = pd.read_sql(sqlquery, engine) + df['As_Of_Date'] = pd.to_datetime(df['As_Of_Date']) + df = df.sort_values('As_Of_Date') + return df + + +# 加载数据并标记重要节气 +solar_terms = load_solar_terms(engine) +important_terms = ['冬至', '雨水', '谷雨', '夏至', '处暑', '霜降'] +solar_terms['isImportant'] = solar_terms['Solar_Terms'].isin(important_terms).astype(int) +Map24Jieqi = solar_terms.copy() + +# ========== 示例：计算某个日期的卦象 ========== +kDate = datetime(1973, 7, 17, 17, 20, 0) +print("计算日期:", kDate) + +# 调用卦象计算函数 +Gua1Hour, Gua1Day, Gua1Month, Gua1Year, GuaLuck = guaCalc_huangjijingshi( + Map64Gua, Map24Jieqi, kDate +) + +print("年卦:", Gua1Year) +print("月卦:", Gua1Month) +print("日卦:", Gua1Day) +print("时卦:", Gua1Hour) +print("吉凶卦:", GuaLuck) + +# ========== 计算 1990-2030 每年的年卦 ========== +# 生成日期范围 +start_date = datetime(1990, 1, 1) +end_date = datetime(2030, 1, 1) +date_range = pd.date_range(start=start_date, end=end_date, freq='YS') # 每年第一天 + +year_gua_list = [] +for date in date_range: + _, _, _, Gua1Year, _ = guaCalc_huangjijingshi(Map64Gua, Map24Jieqi, date) + year_gua_list.append({ + 'Year': date.year, + 'Trigram': Gua1Year.trigram if hasattr(Gua1Year, 'trigram') else None, + }) + +yearGuaMap = pd.DataFrame(year_gua_list) + +#========== 计算年份吉凶 ========== +LuckYear = luckCalc_huangjijingshi(Map64Gua, yearGuaMap, GuaLuck) +print("\n年份吉凶计算结果:") +print(LuckYear) \ No newline at end of file diff --git a/luckCalc_huangjijingshi.py b/luckCalc_huangjijingshi.py new file mode 100644 index 0000000..b4625b5 --- /dev/null +++ b/luckCalc_huangjijingshi.py @@ -0,0 +1,51 @@ +import pandas as pd +import numpy as np + +def luckCalc_huangjijingshi(Map64Gua, yearGuaMap, GuaLuck): + """ + 计算年份吉凶卦象 + Args: + Map64Gua (pd.DataFrame): 64卦映射表，包含卦名、爻信息和二进制值 + yearGuaMap (list or pd.DataFrame): 年份卦象映射表，格式为 [年份, 卦名] + GuaLuck (pd.DataFrame): 吉凶卦象，包含6爻信息 + Returns: + pd.DataFrame: 包含年份、年卦和吉凶卦的结果表 + """ + LuckYear = [] + + # 确保 yearGuaMap 是 DataFrame（如果是列表，先转换） + if isinstance(yearGuaMap, list): + yearGuaMap = pd.DataFrame(yearGuaMap, columns=['Year', 'Trigram']) + + for i in range(len(yearGuaMap)): + kYear = yearGuaMap.iloc[i] # 当前年份和卦名 + trigram = kYear['Trigram'] + + # 找到当前卦名对应的卦象（爻信息） + k1 = Map64Gua[Map64Gua['trigram'] == trigram].index + if len(k1) == 0: + raise ValueError(f"未找到卦名 {trigram} 对应的卦象") + + # 提取当前卦的6爻和吉凶卦的6爻，合并计算 + abc = Map64Gua.loc[k1, ['yao1', 'yao2', 'yao3', 'yao4', 'yao5', 'yao6']].values + abc_luck = GuaLuck[['yao1', 'yao2', 'yao3', 'yao4', 'yao5', 'yao6']].values + abc_combined = np.vstack([abc, abc_luck]) + + # 计算新卦的二进制值（模2求和后加权） + abc2 = np.mod(np.nansum(abc_combined, axis=0), 2) + abc3 = np.sum(abc2 * [1, 2, 4, 8, 16, 32]) + + # 查找对应的新卦 + new_gua = Map64Gua[Map64Gua['value_2binary'] == abc3].iloc[0] + LuckYear.append(new_gua) + + # 合并结果 + LuckYear = pd.DataFrame(LuckYear) + LuckYear['Year'] = yearGuaMap['Year'].values + LuckYear['YearGua'] = yearGuaMap['Trigram'].values + + # 调整列顺序（年份和年卦在前） + cols = ['Year', 'YearGua'] + [c for c in LuckYear.columns if c not in ['Year', 'YearGua']] + LuckYear = LuckYear[cols] + + return LuckYear \ No newline at end of file