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API.py
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API.py
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import pandas as pd
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import numpy as np
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from datetime import datetime
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from datetime import timedelta
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import pymysql
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from sqlalchemy import create_engine
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from dateutil.relativedelta import relativedelta
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# 在API.py开头添加
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import sys
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# 替换原来的get_user_date函数
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def get_user_date():
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if len(sys.argv) > 1:
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datetime_input = sys.argv[1]
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try:
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return datetime.strptime(datetime_input, '%Y-%m-%d %H:%M:%S')
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except ValueError:
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print("日期格式不正确，请使用YYYY-MM-DD HH:MM:SS格式", file=sys.stderr)
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sys.exit(1)
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else:
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print("没有传入日期时间参数", file=sys.stderr)
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sys.exit(1)
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# 导入自定义卦象计算模块
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from guaCalc_huangjijingshi import guaCalc_huangjijingshi
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from luckCalc_huangjijingshi import luckCalc_huangjijingshi
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# ========== 数据库连接配置 ==========
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# 你的账号、密码、主机、端口
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username = 'cn_ainvest_db'
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password = 'cn_ainvest_sd3a1'
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host = 'rm-2zewagytttzk6f24xno.mysql.rds.aliyuncs.com'
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port = 3306
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database = 'ai_strategy' # 这里改成你要的数据库
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# 创建 SQLAlchemy engine
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engine = create_engine(f'mysql+pymysql://{username}:{password}@{host}:{port}/{database}')
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# ========== 文件路径配置 ==========
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configPath = r'C:\AI trading\config\Rey\test_reinforcement'
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matlabPath = r'D:\Dropbox\Matlab\Rey\MATLAB'
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# 修改为你的 Excel 文件路径
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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'
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# ========== 加载 64 卦映射表 ==========
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Map64Gua = pd.read_excel(tempPath, sheet_name="bagua")
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# 转换爻数据为整数
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for col in ['yao1', 'yao2', 'yao3', 'yao4', 'yao5', 'yao6']:
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Map64Gua[col] = Map64Gua[col].apply(lambda x: int(x) if str(x).isdigit() else x)
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Map64GuaOmit = Map64Gua[Map64Gua['change_omit'] == 0]
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# ========== 从数据库加载 24 节气数据 ==========
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def load_solar_terms(conn_params):
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"""通过 SQLAlchemy 连接读取 solar_terms 表"""
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sqlquery = 'SELECT * FROM solar_terms'
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df = pd.read_sql(sqlquery, engine)
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# 尝试将 As_Of_Date 转为 datetime，如果失败就变成 NaT
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df['As_Of_Date'] = pd.to_datetime(df['As_Of_Date'], errors='coerce')
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# 过滤掉早于 1900-01-01 或转换失败的日期
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df = df[df['As_Of_Date'] >= pd.Timestamp('1900-01-01')]
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df = df.dropna(subset=['As_Of_Date'])
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# df['As_Of_Date'] = df['As_Of_Date']
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df = df.sort_values('As_Of_Date')
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return df
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# ========== 用户输入日期 ==========
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# def get_user_date():
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# if len(sys.argv) > 1: # 命令行参数方式
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# date_input = sys.argv[1]
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# else: # 标准输入方式
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# date_input = sys.stdin.read().strip()
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# try:
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# year, month, day = map(int, date_input.split('-'))
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# return datetime(year, month, day, 0, 0, 0)
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# except ValueError:
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# print("日期格式不正确，请使用YYYY-MM-DD格式", file=sys.stderr)
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# sys.exit(1)
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# 获取用户输入
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def get_user_date():
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# date_input = sys.stdin.read().strip() if len(sys.argv) == 1 else sys.argv[1]
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if len(sys.argv) > 1:
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datetime_input = sys.argv[1]
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else:
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print("没有传入日期时间参数", file=sys.stderr)
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sys.exit(1)
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try:
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# 解析包含时间的日期
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return datetime.strptime(datetime_input, '%Y-%m-%d %H:%M:%S')
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# # 确保日期格式为 YYYY-MM-DD
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# return datetime.strptime(date_input, '%Y-%m-%d')
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except ValueError:
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print("日期格式不正确，请使用YYYY-MM-DD格式", file=sys.stderr)
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sys.exit(1)
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# 加载数据并标记重要节气
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solar_terms = load_solar_terms(engine)
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important_terms = ['冬至', '雨水', '谷雨', '夏至', '处暑', '霜降']
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solar_terms['isImportant'] = solar_terms['Solar_Terms'].isin(important_terms).astype(int)
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Map24Jieqi = solar_terms.copy()
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# ========== 读取CSV文件并处理每个日期的卦象 ==========
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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'
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table = pd.read_csv(csv_path)
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# 获取用户输入
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kDate = get_user_date()
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#print("\n计算日期:", kDate.strftime('%Y-%m-%d'))
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# 计算卦象
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Gua1Hour, Gua1Day, Gua1Month, Gua1Year, GuaLuck = guaCalc_huangjijingshi(
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Map64Gua, Map24Jieqi, kDate
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)
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# print("日卦:", Gua1Day)
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import json # 导入 JSON 库
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# ========== 计算并返回 JSON 格式的结果 ==========
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# ========== 计算并返回 JSON 格式的结果 ==========
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if __name__ == "__main__":
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print("=== 调试开始 ===", file=sys.stderr) # 打印到 stderr 不会干扰 stdout 的 JSON
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kDate = get_user_date()
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try:
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Gua1Hour, Gua1Day, Gua1Month, Gua1Year, GuaLuck = guaCalc_huangjijingshi(
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Map64Gua, Map24Jieqi, kDate
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)
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# # 计算10年前（当前日期减10年）
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# Yearpre10 = kDate.replace(year=kDate.year - 10)
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# # 计算10年后（当前日期加10年）
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# Yearpast10 = kDate.replace(year=kDate.year + 10)
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# 或者使用relativedelta（更精确处理闰年等情况）
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Yearpre10 = datetime(2010, 1, 1)
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Yearpast10 = datetime(2030, 1, 1,)
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# 生成日期范围（修正end参数）
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date_range = pd.date_range(
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start=Yearpre10.replace(month=1, day=1), # 确保从1月1日开始
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end=Yearpast10.replace(month=1, day=1), # 确保到1月1日结束
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freq='YS' # 每年第一天
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)
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#date_range = pd.date_range(start=Yearpre10, end=Yearpast10, freq='YS') # 每年第一天
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year_gua_list = []
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for date in date_range:
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_, _, _, Gua1Year, _ = guaCalc_huangjijingshi(Map64Gua, Map24Jieqi, date)
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year_gua_list.append({
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'Year': date.year,
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'Trigram': Gua1Year.trigram if hasattr(Gua1Year, 'trigram') else None,
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})
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yearGuaMap = pd.DataFrame(year_gua_list)
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#========== 计算年份吉凶 ==========
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LuckYear = luckCalc_huangjijingshi(Map64Gua, yearGuaMap, GuaLuck)
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# # 检查 Gua1Day 的类型并正确处理
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# if isinstance(Gua1Day, pd.DataFrame):
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# # 如果是 DataFrame，提取第一行
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# day_data = Gua1Day.iloc[0]
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# elif isinstance(Gua1Day, pd.Series):
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# # 如果是 Series，直接使用
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# day_data = Gua1Day
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# elif isinstance(Gua1Day, dict):
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# # 如果是字典，直接使用
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# day_data = Gua1Day
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# else:
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# raise ValueError("Gua1Day 的类型不支持，必须是 DataFrame、Series 或 dict")
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def format_gua_data(gua_data):
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"""通用格式化卦象数据的函数"""
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if isinstance(gua_data, (pd.DataFrame, pd.Series)):
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data = gua_data.iloc[0] if isinstance(gua_data, pd.DataFrame) else gua_data
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return {
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'id': int(data.get('id', 0)),
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'trigram': str(data.get('trigram', '')),
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'yaoAll': str(data.get('yaoAll', '')),
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'yao1': int(data.get('yao1', 0)),
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'yao2': int(data.get('yao2', 0)),
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'yao3': int(data.get('yao3', 0)),
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'yao4': int(data.get('yao4', 0)),
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'yao5': int(data.get('yao5', 0)),
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'yao6': int(data.get('yao6', 0)),
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'value_2binary': int(data.get('value_2binary', 0)),
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'change_omit': int(data.get('change_omit', 0)),
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'type': str(data.get('Type', 'unknown'))
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}
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elif isinstance(gua_data, dict):
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return gua_data
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else:
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return {}
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# 构建结果字典，确保所有值是 Python 原生类型
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# result = {
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# 'date': kDate.strftime('%Y-%m-%d'),
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# 'day_gua': {
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# 'id': int(day_data.get('id', 0)), # 如果没有值，使用默认值 0
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# 'trigram': str(day_data.get('trigram', '')), # 如果没有值，使用空字符串
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# 'yaoAll': str(day_data.get('yaoAll', '')), # 如果没有值，使用空字符串
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# 'yao1': int(day_data.get('yao1', 0)), # 如果没有值，使用默认值 0
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# 'yao2': int(day_data.get('yao2', 0)), # 如果没有值，使用默认值 0
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# 'yao3': int(day_data.get('yao3', 0)), # 如果没有值，使用默认值 0
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# 'yao4': int(day_data.get('yao4', 0)), # 如果没有值，使用默认值 0
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# 'yao5': int(day_data.get('yao5', 0)), # 如果没有值，使用默认值 0
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# 'yao6': int(day_data.get('yao6', 0)), # 如果没有值，使用默认值 0
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# 'value_2binary': int(day_data.get('value_2binary', 0)), # 如果没有值，使用默认值 0
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# 'change_omit': int(day_data.get('change_omit', 0)), # 如果没有值，使用默认值 0
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# 'type': str(day_data.get('Type', 'day')) # 如果没有值，使用默认值 'day'
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# }
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# }
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# 构建完整结果
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result = {
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'date': kDate.strftime('%Y-%m-%d'),
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'year_gua': format_gua_data(Gua1Year),
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'month_gua': format_gua_data(Gua1Month),
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'day_gua': format_gua_data(Gua1Day),
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'hour_gua': format_gua_data(Gua1Hour),
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'luck_gua': format_gua_data(GuaLuck),
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'luck_years': [
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{
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'year': row['Year'],
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'trigram': row['trigram'],
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'yaoAll': row['yaoAll']
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} for _, row in LuckYear.iterrows()
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] if isinstance(LuckYear, pd.DataFrame) else []
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}
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# 在打印 JSON 前检查内容
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print("=== 要输出的 JSON 内容 ===", file=sys.stderr)
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print(result, file=sys.stderr)
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# 输出 JSON 格式的结果
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# print(json.dumps(result, ensure_ascii=False, indent=4)) # 添加 indent 参数更好查看格式
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print(json.dumps(result, ensure_ascii=False, indent=2))
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except Exception as e:
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import traceback
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traceback.print_exc(file=sys.stderr) # 打印错误堆栈，帮助调试
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print(f"计算错误: {str(e)}", file=sys.stderr)
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sys.exit(1)
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56
bianyao_huangjijingshi.py
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56
bianyao_huangjijingshi.py
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import pandas as pd
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def bianyao_huangjijingshi(Map64Gua: pd.DataFrame, yaoOrig: str) -> pd.DataFrame:
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"""
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皇极经世：变爻计算
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输入原爻（如 '000100'），输出所有变爻之后的卦象合集
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"""
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#print("Map64Gua:",Map64Gua['yaoAll'].apply(type).value_counts())
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# 找到原始卦所在的行
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if 'yaoAll' not in Map64Gua.columns:
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raise ValueError("'yaoAll' 列在 Map64Gua 中不存在，请检查数据")
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Map64Gua = Map64Gua.copy()
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Map64Gua['yaoAll'] = Map64Gua['yaoAll'].astype(str).str.zfill(6).str.strip()
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yaoOrig = str(yaoOrig).zfill(6).strip()
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# 找到原始卦所在的行
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matches = Map64Gua[Map64Gua['yaoAll'] == yaoOrig]
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if matches.empty:
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raise ValueError(f"未找到 yaoAll 为 {yaoOrig} 的卦象")
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k2 = matches.iloc[0] # 取第一行
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# 计算原卦的二进制值
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a0 = (k2['yao1'] + k2['yao2']*2 + k2['yao3']*4 +
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k2['yao4']*8 + k2['yao5']*16 + k2['yao6']*32)
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# 依次翻转每一爻，得到新卦的二进制值
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a1 = (k2['yao1'] + k2['yao2']*2 + k2['yao3']*4 +
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k2['yao4']*8 + k2['yao5']*16 + (1 - k2['yao6'])*32)
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a2 = (k2['yao1'] + k2['yao2']*2 + k2['yao3']*4 +
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k2['yao4']*8 + (1 - k2['yao5'])*16 + k2['yao6']*32)
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a3 = (k2['yao1'] + k2['yao2']*2 + k2['yao3']*4 +
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(1 - k2['yao4'])*8 + k2['yao5']*16 + k2['yao6']*32)
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a4 = (k2['yao1'] + k2['yao2']*2 + (1 - k2['yao3'])*4 +
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k2['yao4']*8 + k2['yao5']*16 + k2['yao6']*32)
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a5 = (k2['yao1'] + (1 - k2['yao2'])*2 + k2['yao3']*4 +
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k2['yao4']*8 + k2['yao5']*16 + k2['yao6']*32)
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a6 = ((1 - k2['yao1']) + k2['yao2']*2 + k2['yao3']*4 +
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k2['yao4']*8 + k2['yao5']*16 + k2['yao6']*32)
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# 结果列表
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result = pd.DataFrame()
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# 查找对应的卦象
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for a in [a0, a1, a2, a3, a4, a5, a6]:
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row = Map64Gua[Map64Gua['value_2binary'] == a]
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if not row.empty:
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result = pd.concat([result, row], ignore_index=True)
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return result
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99
guaCalc_huangjijingshi.py
Normal file
99
guaCalc_huangjijingshi.py
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import pandas as pd
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import numpy as np
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from datetime import datetime, timedelta
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def guaCalc_huangjijingshi(Map64Gua, Map24Jieqi, kDate):
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"""
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Calculate year, month, day, and hour gua based on Huangji Jingshi method
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Args:
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Map64Gua (pd.DataFrame): 64 gua mapping table
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Map24Jieqi (pd.DataFrame): 24 solar terms data
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kDate (datetime): Target date for calculation
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Returns:
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tuple: (Gua4Hour, Gua1Day, Gua1Month, Gua1Year, GuaLuck)
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"""
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# Helper functions that need to be implemented separately
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from bianyao_huangjijingshi import bianyao_huangjijingshi
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from tuigua_huangjijingshi import tuigua_huangjijingshi
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# Bagua for 360 years
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yearRef = {'trigram': '姤', 'value_2binary': '111110', 'start_year': 1744}
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Gua360Year = bianyao_huangjijingshi(Map64Gua, yearRef['value_2binary'])
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Gua360Year['yearStart'] = [yearRef['start_year'] + i * 60 for i in range(len(Gua360Year))]
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Gua360Year['yearEnd'] = [start + 59 for start in Gua360Year['yearStart']]
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# Bagua for 60 years
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kYear = kDate.year
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kYearOrig = kYear
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solar_terms = Map24Jieqi
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solar_terms1 = solar_terms[solar_terms['Solar_Terms'] == '冬至']
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# Find the last winter solstice before our date
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k1 = np.where((kDate - solar_terms1['As_Of_Date']) > timedelta(0))[0][-1]
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kYear = (solar_terms1['As_Of_Date'].iloc[k1] + timedelta(days=90)).year
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# Find which 60-year period we're in
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mask = (Gua360Year['yearStart'] <= kYear) & (Gua360Year['yearEnd'] >= kYear)
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k1 = np.where(mask)[0][0] # Get first match
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a1 = Gua360Year['value_2binary'].iloc[k1]
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a2 = kYear - Gua360Year['yearStart'].iloc[k1]
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Gua1Year = tuigua_huangjijingshi(Map64Gua, a1, a2 + 1)
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Gua1Year['Type'] = 'year'
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# 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
|
||||
88
huangjijingshi20250217.py
Normal file
88
huangjijingshi20250217.py
Normal file
@ -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)
|
||||
51
luckCalc_huangjijingshi.py
Normal file
51
luckCalc_huangjijingshi.py
Normal file
@ -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
|
||||
Loading…
x
Reference in New Issue
Block a user