732642856
427 lines
18 KiB
Python
427 lines
18 KiB
Python
#!/usr/bin/env python3
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"""
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逻辑正确性验证框架 v2
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对比 Skill 引擎和 PyJhora 对60张名人星盘的 Yoga 检测结果
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"""
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import json, sys, os
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from pathlib import Path
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# ==== 路径 ====
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PROJECT_DIR = Path(__file__).resolve().parents[1]
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SKILL_DIR = str(PROJECT_DIR)
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RULES_PATH = os.path.join(SKILL_DIR, 'references', 'yoga_rules.json')
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from yoga_engine import YogaEngine
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# CROSS_NAME_MAP: PyJhora Yoga名 → Skill rule_id
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# 复用 validate_comprehensive.py 中的映射（简化版，只保留核心映射）
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# ---- 从 validate_comprehensive.py 内联的映射逻辑 ----
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PYJHORA_VARIANTS = {
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# Dharidhra variants
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'dharidhra_yoga_144': 'bvr_dharidhra_precise',
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'dharidhra_yoga_147': 'bvr_dharidhra_precise',
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'dharidhra_yoga_148': 'bvr_dharidhra_precise',
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'dharidhra_yoga_149': 'bvr_dharidhra_precise',
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'dharidhra_yoga_150': 'bvr_dharidhra_precise',
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'dharidhra_yoga_151': 'bvr_dharidhra_precise',
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'dharidhra_yoga_152': 'bvr_dharidhra_precise',
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# Dehasthoulya variants
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'dehasthoulya_yoga_114': 'bvr_dehasthoulya_yoga',
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'dehasthoulya_yoga_115': 'bvr_dehasthoulya_yoga',
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'dehasthoulya_yoga_116': 'bvr_dehasthoulya_yoga',
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# Mathibhramana variants
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'mathibhramana_yoga_291': 'bvr_mathibhramana_yoga',
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'mathibhramana_yoga_292': 'bvr_mathibhramana_yoga',
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'mathibhramana_yoga_293': 'bvr_mathibhramana_yoga',
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'mathibhramana_yoga_294': 'bvr_mathibhramana_yoga',
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'mathibhramana_yoga_variation': 'bvr_mathibhramana_yoga',
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# Krisanga variants
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'krisanga_yoga_112': 'bvr_krisanga_yoga',
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'krisanga_yoga_113': 'bvr_krisanga_yoga',
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# Kaalanirdesat variants
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'kaalanirdesat_puthra_yoga_227': 'bvr_kaalanirdesat_puthra_yoga',
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'kaalanirdesat_puthra_yoga_228': 'bvr_kaalanirdesat_puthra_yoga',
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'kaalanirdesat_puthranaasa_yoga_230': 'bvr_kaalanirdesat_puthranaasa_yoga',
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# Matrunasa variants
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'matrunasa_yoga_198': 'bvr_matrunasa_precise',
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'matrunasa_yoga_199': 'bvr_matrunasa_precise',
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# Matrudeerghayur variants
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'matrudeerghayur_yoga_196': 'bvr_matrudeerghayur_yoga',
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'matrudeerghayur_yoga_197': 'bvr_matrudeerghayur_yoga',
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# Nishkapata variants
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'nishkapata_yoga_205': 'bvr_nishkapata_precise',
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'nishkapata_yoga_206': 'bvr_nishkapata_precise',
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# Bahu puthra variants
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'bahu_puthra_yoga_220': 'bvr_bahu_puthra_precise',
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'bahu_puthra_yoga_221': 'bvr_bahu_puthra_precise',
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# Bandhu pujya variants
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'bandhu_pujya_yoga_193': 'bvr_bandhu_pujya_yoga',
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'bandhu_pujya_yoga_194': 'bvr_bandhu_pujya_yoga',
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# Ayatna griha prapta variants
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'ayatna_griha_prapta_yoga_189': 'bvr_ayatna_griha_prapta_yoga',
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'ayatna_griha_prapta_yoga_190': 'bvr_ayatna_griha_prapta_yoga',
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# Grihanasa variants
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'grihanasa_yoga_191': 'bvr_grihanasa_yoga',
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'grihanasa_yoga_192': 'bvr_grihanasa_yoga',
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# Dattha puthra variants
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'dattha_puthra_yoga_222': 'bvr_dattha_puthra_yoga',
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'dattha_puthra_yoga_223': 'bvr_dattha_puthra_yoga',
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# Kushtaroga variants
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'kushtaroga_yoga_268': 'bvr_kushtaroga_yoga',
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# Sarpasaapa variants
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'sarpasaapa_yoga_212': 'bvr_sarpasaapa_yoga',
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'sarpasaapa_yoga_213': 'bvr_sarpasaapa_yoga',
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# Raja bhanga variants
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'raja_bhanga_yoga_298': 'bvr_raja_bhanga_yoga',
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'raja_bhanga_yoga_299': 'bvr_raja_bhanga_yoga',
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# Andha variants
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'andha_yoga_288': 'bvr_andha_yoga',
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'andha_yoga_289': 'bvr_andha_yoga',
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# Vahana variants
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'vahana_yoga_209': 'bvr_vahana_yoga',
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'vahana_yoga_210': 'bvr_vahana_yoga',
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# Kapata family
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'kapata_yoga_202': 'bvr_kapata_yoga',
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'kapata_yoga_203': 'bvr_kapata_yoga',
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'kapata_yoga_204': 'bvr_kapata_yoga',
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'pisacha_grastha_yoga': 'bvr_pisacha_grastha_yoga',
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'kaalanirdesat_puthranaasa_yoga_229': 'bvr_kaalanirdesat_puthranaasa_yoga',
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'dwadasa_sahodara_yoga': 'bvr_dwadasa_sahodara_yoga',
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'sapthasankhya_sahodara_yoga': 'bvr_sapthasankhya_sahodara_yoga',
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'karma_malika_yoga': 'bvr_karma_malika_precise',
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'ardha_chandra_yoga': 'bvr_ardha_chandra_yoga',
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# Kalanidhi variants
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'kalaanidhi_yoga': 'bvr_kalaanidhi_yoga',
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'kalanidhi_yoga': 'bvr_kalaanidhi_yoga',
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# Soola/Sula
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'soola_yoga': 'bvr_soola_yoga',
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'sula_yoga': 'bvr_soola_yoga',
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# Kedara
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'kedara_yoga': 'bvr_kedaara_yoga',
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# Kaahala/Kahala are distinct PyJHora functions:
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# - kaahala_yoga: L4 and Jupiter in mutual quadrants + strong L1
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# - kahala_yoga: L4 and L9 in mutual kendras + strong L1
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'kaahala_yoga': 'bvr_kaahala_yoga',
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'kahala_yoga': 'kahala_yoga',
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# Direct mappings for common yogas
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'vosi_yoga': 'bvr_vosi_precise',
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'sunaphaa_yoga': 'bvr_sunaphaa_precise',
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'amala_yoga': 'bvr_amala_precise',
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'anaphaa_yoga': 'bvr_anaphaa_precise',
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'sareera_soukhya_yoga': 'bvr_sareera_soukhya_precise',
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'rogagrastha_yoga': 'bvr_rogagrastha_precise',
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'sada_sanchara_yoga': 'bvr_sada_sanchara_precise',
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'swaveeryaddhana_yoga': 'bvr_swaveeryaddhana_precise',
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'anthya_vayasi_dhana_yoga': 'bvr_anthya_vayasi_dhana_yoga',
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'matrumooladdhana_yoga': 'bvr_matrumooladdhana_yoga',
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'yuddha_praveena_yoga': 'bvr_yuddha_praveena_yoga',
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'bandhubhisthyaktha_yoga': 'bvr_bandhubhisthyaktha_precise',
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'sraddhannabhuktha_yoga': 'bvr_sraddhannabhuktha_precise',
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'bhratruvriddhi_yoga': 'bvr_bhratruvriddhi_precise',
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'sodaranasa_yoga': 'bvr_sodaranasa_yoga',
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'dehapushti_yoga': 'bvr_dehapushti_yoga',
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'mridanga_yoga': 'bvr_mridanga_yoga',
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'bheri_yoga': 'bvr_bheri_yoga',
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'pushkala_yoga': 'bvr_pushkala_yoga',
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'parakrama_yoga': 'bvr_parakrama_yoga',
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'lakshmi_yoga': 'bvr_lakshmi_yoga',
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'adhi_yoga': 'bvr_adhi_yoga',
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'brahma_yoga': 'bvr_brahma_yoga',
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'bhandhana_yoga': 'bvr_bhandhana_yoga',
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'harihara_brahma_yoga': 'bvr_harihara_brahma_yoga',
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'hara_yoga': 'bvr_hara_yoga',
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'hari_yoga': 'bvr_hari_yoga',
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'madhya_vayasi_dhana_yoga': 'bvr_madhya_vayasi_dhana_yoga',
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'balya_dhana_yoga': 'bvr_balya_dhana_yoga',
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'go_yoga': 'bvr_go_yoga',
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'sara_yoga': 'bvr_sara_yoga',
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'ishu_yoga': 'bvr_ishu_yoga',
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'kshayaroga_yoga': 'bvr_kshayaroga_yoga',
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'kalatramooladdhana_yoga': 'bvr_kalatramooladdhana_yoga',
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'vishnu_yoga': 'bvr_vishnu_yoga',
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'vichitra_saudha_prakara_yoga': 'bvr_vichitra_saudha_prakara_yoga',
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'jananatpurvam_pitru_marana_yoga': 'bvr_jananatpurvam_pitru_marana_yoga',
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'bhratrumooladdhanaprapti_yoga': 'bvr_bhratrumooladdhanaprapti_yoga',
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'thrikaala_gnana_yoga': 'bvr_thrikaala_gnana_yoga',
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'yuddhatpaschaddrudha_yoga': 'bvr_yuddhatpaschaddrudha_yoga',
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'yuddhatpoorvadridhachitta_yoga': 'bvr_yuddhatpoorvadridhachitta_yoga',
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'dhurmarana_yoga': 'bvr_dhurmarana_yoga',
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'theevrabuddhi_yoga': 'bvr_theevrabuddhi_yoga',
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'vaatharoga_yoga': 'bvr_vaatharoga_yoga',
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'amaranantha_dhana_yoga': 'bvr_amaranantha_dhana_yoga',
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'pittharoga_yoga': 'bvr_pittharoga_yoga',
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'sarpasaapa_yoga': 'bvr_sarpasaapa_yoga',
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'parannabhojana_yoga': 'bvr_parannabhojana_yoga',
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'veenaa_yoga': 'bvr_veenaa_yoga',
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'duradhara_yoga': 'bvr_duradhara_yoga',
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'annadana_yoga': 'bvr_annadana_yoga',
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'yukthi_samanwithavagmi_yoga_154': 'bvr_yukthi_samanwithavagmi_yoga',
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'nipuna_yoga': 'bvr_nipuna_yoga',
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'surya_budha_yoga': 'bvr_nipuna_yoga',
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'parvata_yoga': 'bvr_parvata_yoga',
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'hamsa_yoga': 'bvr_hamsa_yoga',
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'ruchaka_yoga': 'bvr_ruchaka_yoga',
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'bhadra_yoga': 'bvr_bhadra_yoga',
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'chatussagara_yoga': 'bvr_chatussagara_yoga',
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'sarpa_yoga': 'bvr_sarpa_yoga',
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'kemadruma_yoga': 'bvr_kemadruma_yoga',
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'sankha_yoga': 'bvr_sankha_yoga',
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'sumukha_yoga': 'bvr_sumukha_yoga',
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'ubhayachara_yoga': 'bvr_ubhayachara_yoga',
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'sasa_yoga': 'bvr_sasa_yoga',
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'matsya_yoga': 'bvr_matsya_yoga',
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'koorma_yoga': 'bvr_koorma_yoga',
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'naukaa_yoga': 'bvr_naukaa_yoga',
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'vihaga_yoga': 'bvr_vihaga_yoga',
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'yuga_yoga': 'bvr_yuga_yoga',
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'gola_yoga': 'bvr_gola_yoga',
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# Fix previously unmapped
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'matru_sneha_yoga': 'bvr_matru_sneha_yoga',
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'eka_puthra_yoga': 'bvr_eka_puthra_precise',
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'guru_mangala_yoga': 'bvr_103_guru_mangala_yoga',
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'vanchana_chora_bheethi_yoga': 'bvr_vanchana_chora_bheethi_yoga',
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'bahu_sthree_yoga': 'bvr_bahu_sthree_yoga',
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'dama_yoga': 'bvr_dama_yoga',
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'utthama_graha_yoga': 'bvr_utthama_graha_yoga',
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'chandra_mangala_yoga': 'bvr_105_chandra_mangala_yoga',
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'bhaga_chumbana_yoga': 'bvr_bhaga_chumbana_yoga',
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'yuddha_marana_yoga': 'bvr_yuddha_marana_yoga',
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'andha_yoga': 'bvr_andha_yoga',
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'matru_satrutwa_yoga': 'bvr_matru_satrutwa_yoga',
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'apakeerthi_yoga': 'bvr_apakeerthi_yoga',
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}
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RULE_ID_ALIASES = {
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# Historical/numbered rule ids in yoga_rules.json
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'bvr_vosi_precise': 'bvr_017_vosi_precise',
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'bvr_sunaphaa_precise': 'bvr_002_sunapha_precise',
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'bvr_anaphaa_precise': 'bvr_003_anapha_precise',
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'bvr_duradhara_yoga': 'bvr_004_duradhara_precise',
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'bvr_ubhayachara_yoga': 'bvr_018_ubhayachara_precise',
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'bvr_dharidhra_precise': 'bvr_dharidhra_11_precise',
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'bvr_sara_yoga': 'bvr_072_sara',
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'bvr_ishu_yoga': 'bvr_072_ishu',
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'bvr_naukaa_yoga': 'bvr_075_naukaa_precise',
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'bvr_vihaga_yoga': 'vihaga_nabhasa',
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'bvr_veenaa_yoga': 'veena_yoga',
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'bvr_sumukha_yoga': 'bvr_sumukha_precise',
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}
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def canonical_rule_id(rule_id, valid_rule_ids):
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"""Map historical validation ids to actual enabled yoga_rules.json ids."""
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if not rule_id:
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return None
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if rule_id in valid_rule_ids:
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return rule_id
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alias = RULE_ID_ALIASES.get(rule_id)
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if alias in valid_rule_ids:
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return alias
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if rule_id.startswith('bvr_'):
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without_bvr = rule_id[4:]
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candidates = [without_bvr]
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if without_bvr.endswith('_precise'):
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base = without_bvr[:-8]
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candidates.extend([base, f'{base}_yoga'])
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for candidate in candidates:
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if candidate in valid_rule_ids:
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return candidate
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return None
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def extract_skill_rule_ids(skill_results):
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"""Extract comparable rule ids while ignoring algorithmic Yoga rows."""
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ids = set()
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for row in skill_results:
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if not isinstance(row, dict):
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continue
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rule_id = row.get('rule_id') or row.get('id')
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if isinstance(rule_id, str) and rule_id:
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ids.add(rule_id)
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return ids
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# ---- 内联结束 ----
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def main():
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# 1. 加载位置数据。固定使用 skill 内部 references，避免从其他 cwd 运行时读写错目录。
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planet_positions_path = os.path.join(SKILL_DIR, 'references', 'planet_positions_60.json')
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standard_charts_path = os.path.join(SKILL_DIR, 'references', 'standard_test_charts.json')
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report_path = os.path.join(SKILL_DIR, 'references', 'validation_logic_report.json')
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with open(planet_positions_path) as f:
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pos_data = json.load(f)
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# 2. 加载 PyJhora Yoga 结果
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with open(standard_charts_path) as f:
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pyj_data = json.load(f)
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# 构建 name -> pyjhora yoga list 映射
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pyj_charts = {c['name']: c for c in pyj_data['charts']}
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# 3. 加载 Skill 引擎
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engine = YogaEngine(RULES_PATH)
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# 构建 rule_id -> rule_name 映射
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rule_id_to_name = {r['id']: r['name'] for r in engine.rules}
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# 以及 name -> rule_id 反向映射（用于去重匹配）
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name_to_rule_ids = {}
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for r in engine.rules:
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name = r['name']
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name_to_rule_ids.setdefault(name, []).append(r['id'])
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valid_rule_ids = set(rule_id_to_name.keys())
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# 建立"可对比规则集"：仅保留真实存在且启用的 Skill rule_id，避免历史 ID 别名造成 60/60 假性 FN。
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variant_to_rule_id = {}
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missing_mappings = {}
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for py_name, raw_id in PYJHORA_VARIANTS.items():
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canonical = canonical_rule_id(raw_id, valid_rule_ids)
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if canonical:
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variant_to_rule_id[py_name] = canonical
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else:
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missing_mappings.setdefault(raw_id, []).append(py_name)
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comparable_rule_ids = set(variant_to_rule_id.values())
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print(f"可对比规则数量: {len(comparable_rule_ids)}")
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if missing_mappings:
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print(f"暂不可对比映射数量: {len(missing_mappings)}")
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# 统计（只统计可对比规则）
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total_skill_comp = 0 # Skill在可对比规则集中的检测数
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total_pyj_comp = 0 # PyJhora能映射到可对比规则的检测数
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total_agreements = 0
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total_false_positives = 0
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total_false_negatives = 0
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total_unmapped_pyj = 0
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fp_details = [] # Skill说有，PyJhora说没有（都在可对比集内）
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fn_details = [] # PyJhora说有，Skill说没有（都在可对比集内）
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for chart in pos_data['charts']:
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name = chart['name']
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planets = chart['planets']
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ascendant = chart['ascendant']
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# 从 standard_test_charts.json 取完整 context（含 D9/Navamsa/Upagraha 数据）
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pyj_chart = pyj_charts.get(name)
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if not pyj_chart:
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print(f" WARNING: {name} not in PyJhora data")
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continue
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context = pyj_chart.get('context', {})
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# Skill 引擎检测（使用含 D9 的完整 context）
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skill_results = engine.detect(planets, ascendant, context=context)
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skill_yoga_ids = extract_skill_rule_ids(skill_results)
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skill_comp = skill_yoga_ids & comparable_rule_ids # 只保留可对比的
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total_skill_comp += len(skill_comp)
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pyj_yoga_names = set(pyj_chart.get('expected_yogas', []))
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# 将 PyJhora Yoga名映射到 Skill rule_id
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pyj_mapped_ids = set()
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unmapped = 0
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for pyj_name in pyj_yoga_names:
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mapped = variant_to_rule_id.get(pyj_name)
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if not mapped:
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norm = pyj_name.lower().strip()
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mapped = variant_to_rule_id.get(norm)
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if mapped:
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pyj_mapped_ids.add(mapped)
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else:
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unmapped += 1
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total_unmapped_pyj += unmapped
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|
pyj_comp = pyj_mapped_ids & comparable_rule_ids
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|
total_pyj_comp += len(pyj_comp)
|
|
|
|
# 对比（只对比可对比规则集）
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|
agreements = skill_comp & pyj_comp
|
|
false_positives = skill_comp - pyj_comp # Skill说有，PyJhora说没有
|
|
false_negatives = pyj_comp - skill_comp # PyJhora说有，Skill说没有
|
|
|
|
total_agreements += len(agreements)
|
|
total_false_positives += len(false_positives)
|
|
total_false_negatives += len(false_negatives)
|
|
|
|
if false_positives:
|
|
for rid in sorted(false_positives):
|
|
fp_details.append({
|
|
'chart': name,
|
|
'rule_id': rid,
|
|
'rule_name': rule_id_to_name.get(rid, '?'),
|
|
})
|
|
if false_negatives:
|
|
for rid in sorted(false_negatives):
|
|
orig_names = sorted(pn for pn, sid in variant_to_rule_id.items() if sid == rid)
|
|
fn_details.append({
|
|
'chart': name,
|
|
'rule_id': rid,
|
|
'rule_name': rule_id_to_name.get(rid, '?'),
|
|
'external_benchmark_names': orig_names,
|
|
})
|
|
|
|
# ==== 输出报告 ====
|
|
print("=" * 70)
|
|
print("Skill vs PyJhora 逻辑正确性验证报告（仅可对比规则）")
|
|
print("=" * 70)
|
|
print(f"测试星盘数量: 60")
|
|
print(f"可对比规则集大小: {len(comparable_rule_ids)}")
|
|
print(f"PyJhora未映射Yoga: {total_unmapped_pyj}")
|
|
print()
|
|
print(f"Skill 可对比检测总数: {total_skill_comp}")
|
|
print(f"PyJhora 可对比检测总数: {total_pyj_comp}")
|
|
print(f"一致 (Agreements): {total_agreements}")
|
|
print(f"False Positives (Skill过宽): {total_false_positives}")
|
|
print(f"False Negatives (Skill过严): {total_false_negatives}")
|
|
print()
|
|
|
|
precision = total_agreements / total_skill_comp if total_skill_comp else 0
|
|
recall = total_agreements / total_pyj_comp if total_pyj_comp else 0
|
|
f1 = 2 * precision * recall / (precision + recall) if (precision + recall) else 0
|
|
|
|
print(f"Precision (准确率): {precision:.2%}")
|
|
print(f"Recall (召回率): {recall:.2%}")
|
|
print(f"F1 Score: {f1:.2%}")
|
|
print()
|
|
|
|
# 按规则汇总 FP
|
|
if fp_details:
|
|
from collections import Counter
|
|
fp_by_rule = Counter((d['rule_id'], d['rule_name']) for d in fp_details)
|
|
print("--- False Positives 最多的规则 (Top 20) ---")
|
|
for (rid, rname), count in fp_by_rule.most_common(20):
|
|
print(f" {count:2d} 次: {rid} ({rname})")
|
|
print()
|
|
|
|
# 按规则汇总 FN
|
|
if fn_details:
|
|
from collections import Counter
|
|
fn_by_rule = Counter((d['rule_id'], d['rule_name']) for d in fn_details)
|
|
print("--- False Negatives 最多的规则 (Top 20) ---")
|
|
for (rid, rname), count in fn_by_rule.most_common(20):
|
|
print(f" {count:2d} 次: {rid} ({rname})")
|
|
print()
|
|
|
|
# 保存详细报告
|
|
report = {
|
|
"summary": {
|
|
"charts_tested": 60,
|
|
"comparable_rules": len(comparable_rule_ids),
|
|
"skill_total": total_skill_comp,
|
|
"external_benchmark_total": total_pyj_comp,
|
|
"unmapped_external_benchmark": total_unmapped_pyj,
|
|
"missing_mappings": {k: v for k, v in sorted(missing_mappings.items())},
|
|
"agreements": total_agreements,
|
|
"false_positives": total_false_positives,
|
|
"false_negatives": total_false_negatives,
|
|
"precision": round(precision, 4),
|
|
"recall": round(recall, 4),
|
|
"f1": round(f1, 4),
|
|
},
|
|
"false_positives": sorted(fp_details, key=lambda row: (row["chart"], row["rule_id"])),
|
|
"false_negatives": sorted(fn_details, key=lambda row: (row["chart"], row["rule_id"])),
|
|
}
|
|
with open(report_path, 'w') as f:
|
|
json.dump(report, f, indent=2, ensure_ascii=False)
|
|
print(f"详细报告已保存至: {report_path}")
|
|
|
|
|
|
if __name__ == "__main__":
|
|
main()
|