#!/usr/bin/env python3 """ 大规模协同验证：18名人婚姻案例 × 5功能模块 测试: Double Transit PAC+D9, Transit LL/7L, 行星聚集, Vivah Saham, Chara Dasha """ import sys, json, os sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'scripts')) import swisseph as swe swe.set_ephe_path('') from jyotish_engine import ( compute_chart_data, cmd_double_transit_pac, cmd_transit_ll7l, cmd_planetary_congregation, cmd_vivah_saham, SIGN_LORDS, SIGNS ) from jaimini import calc_chara_dasha_with_antardasha # 18名人案例（来自 v6.1 验证脚本） CASES = [ {'name':'Nelson Mandela','birth':(1918,7,18,14.0,-33.32,26.52),'gender':'M', 'marriage1':(1944,10,5)}, {'name':'Tom Cruise','birth':(1962,7,3,19.25,43.05,-76.15),'gender':'M', 'marriage1':(1987,5,9)}, {'name':'Elon Musk','birth':(1971,6,28,5.0,-25.74,28.19),'gender':'M', 'marriage1':(2000,1,1)}, {'name':'Oprah Winfrey','birth':(1954,1,29,11.88,33.51,-88.52),'gender':'F', 'marriage1':(1986,1,1)}, {'name':'Prince Harry','birth':(1984,9,15,15.33,51.5,-0.17),'gender':'M', 'marriage1':(2018,5,19)}, {'name':'Jeff Bezos','birth':(1964,1,12,9.63,25.78,-80.19),'gender':'M', 'marriage1':(1993,1,1)}, {'name':'Priyanka Chopra','birth':(1982,7,18,10.5,23.57,87.19),'gender':'F', 'marriage1':(2018,12,1)}, {'name':'Shah Rukh Khan','birth':(1965,11,1,21.25,28.61,77.21),'gender':'M', 'marriage1':(1991,10,25)}, {'name':'Britney Spears','birth':(1981,12,2,19.92,31.17,-89.18),'gender':'F', 'marriage1':(2004,1,3)}, {'name':'Mark Zuckerberg','birth':(1984,5,14,19.67,40.71,-74.01),'gender':'M', 'marriage1':(2012,5,19)}, {'name':'Narendra Modi','birth':(1950,9,17,4.78,23.03,72.58),'gender':'M', 'marriage1':(1968,1,1)}, {'name':'Amitabh Bachchan','birth':(1942,10,11,10.5,25.43,81.85),'gender':'M', 'marriage1':(1973,6,3)}, ] def make_args(y,m,d,h,mi,lat,lon,tz,date_str,house=7): """构建 args 对象""" return type('Args', (), { 'year':y,'month':m,'day':d,'hour':h,'minute':mi, 'lat':lat,'lon':lon,'tz':tz, 'date':date_str,'house':house, 'transit_date':date_str, })() def run(): results = [] stats = {'dt':0,'p5':0,'p8':0,'pariv':0,'cong':0,'vs':0,'cd':0} total = 0 for case in CASES: y,m,d,h_utc,lat,lon = case['birth'] name = case['name'] my,mm,md_d = case['marriage1'] date_str = f"{my}-{mm:02d}-{md_d:02d}" total += 1 # 转UTC hour (假设 birth 中 h 已经是 UTC) hour_int = int(h_utc) minute_int = int((h_utc - hour_int) * 60) tz = 0 # UTC print(f"\n{'='*50}") print(f"[{total}] {name} | 婚姻: {date_str}") print(f"{'='*50}") signals = [] # 1. Double Transit PAC + D9 dt_hit = False try: dt_r = cmd_double_transit_pac(make_args(y,m,d,hour_int,minute_int,lat,lon,tz,date_str)) dt_hit = len(dt_r.get('double_transit',[])) > 0 if dt_hit: signals.append('DT') stats['dt'] += 1 dt_list = dt_r.get('double_transit',[]) layer_str = ','.join(set(l['layer'] for l in dt_list)) if dt_list else '-' dt_summary = dt_r.get('summary','') print(f" [DT PAC+D9] {'✅' if dt_hit else '❌'} layers={layer_str} {dt_summary}") except Exception as e: print(f" [DT PAC+D9] ERROR: {e}") dt_hit = False # ERROR不计为hit # 2. Transit LL/7L try: ll7l_r = cmd_transit_ll7l(make_args(y,m,d,hour_int,minute_int,lat,lon,tz,date_str)) p5 = ll7l_r['p5']['hit'] p8 = ll7l_r['p8']['hit'] pariv = ll7l_r['parivartana']['hit'] if p5: signals.append('P5'); stats['p5'] += 1 if p8: signals.append('P8'); stats['p8'] += 1 if pariv: signals.append('Pariv'); stats['pariv'] += 1 print(f" [LL/7L] P5={'✅' if p5 else '❌'} P8={'✅' if p8 else '❌'} Pariv={'✅' if pariv else '❌'}") except Exception as e: print(f" [LL/7L] ERROR: {e}") # 3. 行星聚集 try: cong_r = cmd_planetary_congregation(make_args(y,m,d,hour_int,minute_int,lat,lon,tz,date_str,7)) cong_hit = cong_r.get('hit', False) if cong_hit: signals.append('聚集'); stats['cong'] += 1 print(f" [聚集] {'✅' if cong_hit else '❌'} {cong_r.get('summary','')}") except Exception as e: print(f" [聚集] ERROR: {e}") # 4. Vivah Saham try: vs_r = cmd_vivah_saham(make_args(y,m,d,hour_int,minute_int,lat,lon,tz,date_str)) ta = vs_r.get('transit_activation', {}) vs_double = ta.get('double_activation', False) if ta else False if vs_double: signals.append('VS双星'); stats['vs'] += 1 jup = [c['type'] for c in ta.get('jupiter',[])] if ta else [] sat = [c['type'] for c in ta.get('saturn',[])] if ta else [] vs_s = vs_r.get('vivah_saham',{}) print(f" [VivahSaham] {vs_s.get('sign_cn','?')} {vs_s.get('degree_in_sign',0):.1f}° | 双星={'✅' if vs_double else '❌'} Jup={jup} Sat={sat}") except Exception as e: print(f" [VivahSaham] ERROR: {e}") # 5. Chara Dasha (Antardasha) try: chart, asc_idx, jd, aya = compute_chart_data(y,m,d,hour_int,minute_int,lat,lon,tz) if chart: p_lons = {pn: pd['degree'] for pn, pd in chart['planets'].items() if 'degree' in pd} cd = calc_chara_dasha_with_antardasha(asc_idx, p_lons, y, m) m_year, m_month = my, mm md_name = ''; ad_name = '' for md_d in cd['dasha_sequence']: s_y, s_m = map(int, md_d['start_date'].split('-')) e_y, e_m = map(int, md_d['end_date'].split('-')) if (m_year > s_y or (m_year == s_y and m_month >= s_m)) and \ (m_year < e_y or (m_year == e_y and m_month <= e_m)): md_name = f"{md_d['sign']}({md_d['lord']})" for ad in md_d.get('antardashas', []): as_y, as_m = map(int, ad['start_date'].split('-')) ae_y, ae_m = map(int, ad['end_date'].split('-')) if (m_year > as_y or (m_year == as_y and m_month >= as_m)) and \ (m_year < ae_y or (m_year == ae_y and m_month <= ae_m)): ad_name = f"{ad['sign']}({ad['lord']})" break break # 检查 MD 或 AD 是否涉及 7 宫相关 seven_sign = SIGNS[(asc_idx + 6) % 12] seven_lord = SIGN_LORDS[seven_sign] ll = SIGN_LORDS[SIGNS[asc_idx]] cd_relevant = seven_lord in md_name or ll in md_name or seven_lord in ad_name or ll in ad_name if cd_relevant: signals.append('CD'); stats['cd'] += 1 print(f" [CharaDasha] MD={md_name} AD={ad_name} | 7宫相关={'✅' if cd_relevant else '❌'}") except Exception as e: print(f" [CharaDasha] ERROR: {e}") score = len(signals) if score >= 3: verdict = '✅强' elif score == 2: verdict = '⚠️中' elif score == 1: verdict = '⚠️弱' else: verdict = '❌无' print(f" >>> 综合: {verdict} ({score}/6) 信号={signals}") results.append({ 'name': name, 'marriage': date_str, 'signals': signals, 'score': score, 'verdict': verdict, }) # 汇总 print(f"\n{'='*60}") print(f"大规模验证汇总 ({total} 案例)") print(f"{'='*60}") strong = sum(1 for r in results if r['score'] >= 3) medium = sum(1 for r in results if r['score'] == 2) weak = sum(1 for r in results if r['score'] == 1) none_c = sum(1 for r in results if r['score'] == 0) print(f"\n综合评分分布:") print(f" 强确认 (≥3信号): {strong}/{total} ({strong/total*100:.0f}%)") print(f" 中等确认 (2信号): {medium}/{total} ({medium/total*100:.0f}%)") print(f" 弱信号 (1信号): {weak}/{total} ({weak/total*100:.0f}%)") print(f" 无确认 (0信号): {none_c}/{total} ({none_c/total*100:.0f}%)") print(f"\n各功能命中率:") print(f" Double Transit PAC+D9: {stats['dt']}/{total} ({stats['dt']/total*100:.0f}%)") print(f" Transit LL/7L P5: {stats['p5']}/{total} ({stats['p5']/total*100:.0f}%)") print(f" Transit LL/7L P8: {stats['p8']}/{total} ({stats['p8']/total*100:.0f}%)") print(f" Parivartana 互换: {stats['pariv']}/{total} ({stats['pariv']/total*100:.0f}%)") print(f" 行星聚集: {stats['cong']}/{total} ({stats['cong']/total*100:.0f}%)") print(f" Vivah Saham 双星激活: {stats['vs']}/{total} ({stats['vs']/total*100:.0f}%)") print(f" Chara Dasha 7宫相关: {stats['cd']}/{total} ({stats['cd']/total*100:.0f}%)") avg_score = sum(r['score'] for r in results) / total at_least_1 = sum(1 for r in results if r['score'] >= 1) at_least_2 = sum(1 for r in results if r['score'] >= 2) print(f"\n核心指标:") print(f" 平均信号数: {avg_score:.1f}/6") print(f" ≥1信号覆盖率: {at_least_1}/{total} ({at_least_1/total*100:.0f}%)") print(f" ≥2信号覆盖率: {at_least_2}/{total} ({at_least_2/total*100:.0f}%)") # 保存 out = os.path.join(os.path.dirname(__file__), 'test-data', 'verify-large-scale-results.json') with open(out, 'w', encoding='utf-8') as f: json.dump({'results': results, 'stats': stats, 'total': total}, f, ensure_ascii=False, indent=2) print(f"\n结果已保存: {out}") if __name__ == '__main__': run()