51 lines
2.0 KiB
Python
51 lines
2.0 KiB
Python
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import pandas as pd
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import numpy as np
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def luckCalc_huangjijingshi(Map64Gua, yearGuaMap, GuaLuck):
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"""
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计算年份吉凶卦象
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Args:
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Map64Gua (pd.DataFrame): 64卦映射表，包含卦名、爻信息和二进制值
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yearGuaMap (list or pd.DataFrame): 年份卦象映射表，格式为 [年份, 卦名]
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GuaLuck (pd.DataFrame): 吉凶卦象，包含6爻信息
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Returns:
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pd.DataFrame: 包含年份、年卦和吉凶卦的结果表
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"""
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LuckYear = []
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# 确保 yearGuaMap 是 DataFrame（如果是列表，先转换）
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if isinstance(yearGuaMap, list):
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yearGuaMap = pd.DataFrame(yearGuaMap, columns=['Year', 'Trigram'])
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for i in range(len(yearGuaMap)):
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kYear = yearGuaMap.iloc[i] # 当前年份和卦名
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trigram = kYear['Trigram']
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# 找到当前卦名对应的卦象（爻信息）
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k1 = Map64Gua[Map64Gua['trigram'] == trigram].index
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if len(k1) == 0:
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raise ValueError(f"未找到卦名 {trigram} 对应的卦象")
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# 提取当前卦的6爻和吉凶卦的6爻，合并计算
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abc = Map64Gua.loc[k1, ['yao1', 'yao2', 'yao3', 'yao4', 'yao5', 'yao6']].values
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abc_luck = GuaLuck[['yao1', 'yao2', 'yao3', 'yao4', 'yao5', 'yao6']].values
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abc_combined = np.vstack([abc, abc_luck])
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# 计算新卦的二进制值（模2求和后加权）
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abc2 = np.mod(np.nansum(abc_combined, axis=0), 2)
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abc3 = np.sum(abc2 * [1, 2, 4, 8, 16, 32])
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# 查找对应的新卦
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new_gua = Map64Gua[Map64Gua['value_2binary'] == abc3].iloc[0]
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LuckYear.append(new_gua)
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# 合并结果
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LuckYear = pd.DataFrame(LuckYear)
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LuckYear['Year'] = yearGuaMap['Year'].values
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LuckYear['YearGua'] = yearGuaMap['Trigram'].values
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# 调整列顺序（年份和年卦在前）
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cols = ['Year', 'YearGua'] + [c for c in LuckYear.columns if c not in ['Year', 'YearGua']]
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LuckYear = LuckYear[cols]
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return LuckYear
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