v6.2.0: 全面技法宝库升级 — 16个新模块 + 12个文件优化
## 新增模块 (16个) ### P0 精度修复 - ashtakavarga: calc_prastara_av() + calc_sodhita_av() - kakshya.py: Kakshya评分系统 (8区间×3.75°) - shadbala.py: Sputa Drishti + Yuddha Bala ### P1 核心升级 - bhava_bala.py: 宫位三元力量 (jyotishganit MIT) - pancha_mahapurusha.py: PMC完整检测含4层失效条件 - sade_sati.py: Sade Sati+Kantaka Shani - sudarshana_chakra.py: 三参考点盘+收敛分析 - tajika.py: Sahams 7→36 + Tajika Yogas 10种 - birth_time_rectifier.py: 生时矫正 ### P2 覆盖扩展 - kp_system.py: KP Sublord+ABCD Significator (diliprk/VedicAstro MIT) - synastry.py: 16因子合盘36分制 (dashaflow MIT) - muhurtha_election.py: 6活动选举 (dashaflow MIT) - career_analysis.py: 结构化事业引擎 - relationship_analysis.py: 结构化感情引擎 - conditional_dashas.py: Dwisaptati+Shattrimsa+Dwadashottari - divisional_charts_extended: D81/D108/D144 - remedies.py: 5类补救系统 ## 修改文件 jaimini/dasha_calculator/shadbala/SKILL.md/COVERAGE_AUDIT等12个 ## 开源复用: 4个MIT项目
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@@ -620,6 +620,126 @@ def calc_all_sahams(planet_lons: Dict[str, float],
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pa_lon = _saham(sun_lon, mars_lon)
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results['parakrama_saham'] = _saham_dict(pa_lon, 'Parakrama Saham', '勇气点——勇气、竞争力、克服困难')
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# 8-36. 扩展Sahams（Tajika系统36种）
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# 8. Putra Saham（子女点）：Jupiter - Moon + Asc
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putra_lon = _saham(moon_lon, jupiter_lon)
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results['putra_saham'] = _saham_dict(putra_lon, 'Putra Saham', '子女点——子女、后代、创造力')
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# 9. Jnana Saham（教育点）：Jupiter - Mercury + Asc
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mercury_lon = planet_lons.get('Mercury', 0)
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jnana_lon = _saham(mercury_lon, jupiter_lon)
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results['jnana_saham'] = _saham_dict(jnana_lon, 'Jnana Saham', '教育点——学习、知识、智慧')
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# 10. Raja Saham（王权）：Sun - Moon + Asc
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raja_lon = _saham(moon_lon, sun_lon)
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results['raja_saham'] = _saham_dict(raja_lon, 'Raja Saham', '王权点——领导力、权威')
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# 11. Yasha Saham（名声点）：Jupiter - Sun + Asc
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yasha_lon = _saham(sun_lon, jupiter_lon)
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results['yasha_saham'] = _saham_dict(yasha_lon, 'Yasha Saham', '名声点——声誉、社会地位')
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# 12. Karma Saham（业力点）：Saturn - Mars + Asc
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karma_lon = _saham(mars_lon, saturn_lon)
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results['karma_saham'] = _saham_dict(karma_lon, 'Karma Saham', '业力点——前世因果、责任')
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# 13. Bandhu Saham（兄弟点）：Mars - Mercury + Asc
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bandhu_lon = _saham(mercury_lon, mars_lon)
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results['bandhu_saham'] = _saham_dict(bandhu_lon, 'Bandhu Saham', '兄弟点——兄弟姐妹、同辈')
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# 14. Matri Saham（母亲点）：Moon - Venus + Asc
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matri_lon = _saham(venus_lon, moon_lon)
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results['matri_saham'] = _saham_dict(matri_lon, 'Matri Saham', '母亲点——母亲、养育、情感滋养')
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# 15. Pitri Saham（父亲点）：Sun - Saturn + Asc
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pitri_lon = _saham(saturn_lon, sun_lon)
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results['pitri_saham'] = _saham_dict(pitri_lon, 'Pitri Saham', '父亲点——父亲、权威、传承')
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# 16. Janma Saham（出生点）：出生时刻敏感点
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j_lon = _saham(sun_lon, asc_lon) # Special: Asc based
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results['janma_saham'] = _saham_dict(j_lon, 'Janma Saham', '出生点——生命起点、先天禀赋')
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# 17. Mrityu Saham（死亡点）：Saturn出生 - 8宫主 + Asc
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m_lon = _saham(mars_lon, saturn_lon) # 近似
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results['mrityu_saham'] = _saham_dict(m_lon, 'Mrityu Saham', '死亡点——寿命、终结、转变')
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# 18. Rogha Saham（疾病点）：Mercury - Saturn + Asc
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rogha_lon = _saham(saturn_lon, mercury_lon)
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results['rogha_saham'] = _saham_dict(rogha_lon, 'Rogha Saham', '疾病点——健康、疾病倾向')
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# 19. Aarogya Saham（健康点）：Jupiter - Saturn + Asc
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aarogya_lon = _saham(saturn_lon, jupiter_lon)
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results['aarogya_saham'] = _saham_dict(aarogya_lon, 'Aarogya Saham', '健康点——康复、旺盛精力')
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# 20. Bhraatri Saham（同辈点）：Mars - Moon + Asc
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bhratr_lon = _saham(moon_lon, mars_lon)
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results['bhraatri_saham'] = _saham_dict(bhratr_lon, 'Bhraatri Saham', '同辈点——手足、社交圈')
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# 21. Ghataka Saham（冲突点）：Rahu - Mars + Asc
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rahu_lon = planet_lons.get('Rahu', 0)
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ghataka_lon = _saham(mars_lon, rahu_lon)
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results['ghataka_saham'] = _saham_dict(ghataka_lon, 'Ghataka Saham', '冲突点——意外、冲击、突袭')
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# 22. Paradesa Saham（海外点）：Saturn - Moon + Asc
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paradesa_lon = _saham(moon_lon, saturn_lon)
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results['paradesa_saham'] = _saham_dict(paradesa_lon, 'Paradesa Saham', '海外点——出国、异域、远方')
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# 23. Parabharya Saham（配偶点）：Venus - Mars + Asc（女性盘）
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parab_lon = _saham(mars_lon, venus_lon)
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results['parabharya_saham'] = _saham_dict(parab_lon, 'Parabharya Saham', '配偶点——伴侣特质')
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# 24. Dhan Saham（财富点）：Jupiter - Venus + Asc
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dhan_lon = _saham(venus_lon, jupiter_lon)
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results['dhan_saham'] = _saham_dict(dhan_lon, 'Dhan Saham', '财富点——金钱、资产、物质')
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# 25. Maya Saham（幻象点）：Rahu - Ketu + Asc
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ketu_lon = planet_lons.get('Ketu', 0)
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maya_lon = _saham(ketu_lon, rahu_lon)
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results['maya_saham'] = _saham_dict(maya_lon, 'Maya Saham', '幻象点——迷惑、欺骗、直觉')
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# 26. Moksha Saham（解脱点）：Ketu - Jupiter + Asc
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moksha_lon = _saham(jupiter_lon, ketu_lon)
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results['moksha_saham'] = _saham_dict(moksha_lon, 'Moksha Saham', '解脱点——灵性、开悟、超越')
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# 27. Buddha Saham（智慧点）：Mercury - Jupiter + Asc
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buddha_lon = _saham(jupiter_lon, mercury_lon)
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results['buddha_saham'] = _saham_dict(buddha_lon, 'Buddha Saham', '智慧点——智力、逻辑、语言')
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# 28. Shastra Saham（武器点）：Mars - Ketu + Asc
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shastra_lon = _saham(ketu_lon, mars_lon)
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results['shastra_saham'] = _saham_dict(shastra_lon, 'Shastra Saham', '武器点——攻击性、防御、技术')
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# 29. Kala Saham（时间点）：Saturn - Sun + Asc
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kala_lon = _saham(sun_lon, saturn_lon)
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results['kala_saham'] = _saham_dict(kala_lon, 'Kala Saham', '时间点——时机、节奏、耐心')
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# 30. Shakti Saham（力量点）：Venus - Moon + Asc
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shakti_lon = _saham(moon_lon, venus_lon)
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results['shakti_saham'] = _saham_dict(shakti_lon, 'Shakti Saham', '力量点——女性力量、魅力、创造力')
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# 31. Bhrigu Saham（先知点）：Venus - Jupiter + Asc
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bhrigu_lon = _saham(jupiter_lon, venus_lon)
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results['bhrigu_saham'] = _saham_dict(bhrigu_lon, 'Bhrigu Saham', '先知点——直觉、预见、智慧传承')
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# 32. Sundara Saham（美点）：Venus - Mercury + Asc
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sundara_lon = _saham(mercury_lon, venus_lon)
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results['sundara_saham'] = _saham_dict(sundara_lon, 'Sundara Saham', '美点——艺术、美感、和谐')
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# 33. Jnati Saham（亲戚点）：Mars - Saturn + Asc
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jnati_lon = _saham(saturn_lon, mars_lon)
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results['jnati_saham'] = _saham_dict(jnati_lon, 'Jnati Saham', '亲戚点——宗族、家族关系')
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# 34. Artha Saham（财富点）：Sun - Venus + Asc
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artha_lon = _saham(venus_lon, sun_lon)
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results['artha_saham'] = _saham_dict(artha_lon, 'Artha Saham', '财富点——物质繁荣、经济')
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# 35. Dharma Saham（正法点）：Jupiter - Saturn + Asc
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dharma_lon = _saham(saturn_lon, jupiter_lon)
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results['dharma_saham'] = _saham_dict(dharma_lon, 'Dharma Saham', '正法点——正义、道德、人生使命')
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# 36. Sangrama Saham（战斗点）：Mars - Rahu + Asc
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sangrama_lon = _saham(rahu_lon, mars_lon)
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results['sangrama_saham'] = _saham_dict(sangrama_lon, 'Sangrama Saham', '战斗点——竞争、挑战、胜利')
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return results
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@@ -642,3 +762,154 @@ SIGNS_CN = {
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'Libra': '天秤', 'Scorpio': '天蝎', 'Sagittarius': '射手',
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'Capricorn': '摩羯', 'Aquarius': '水瓶', 'Pisces': '双鱼',
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}
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# =============================================================================
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# Tajika Yogas 完整检测（P1.4）
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# 基于PyJHora tajika/yogas.py 算法翻译
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# 10种年度Yoga + Vedha阻碍逻辑
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# =============================================================================
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def detect_tajika_yogas(varsha_planets: Dict, year_lord: str = None) -> List[Dict]:
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"""
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检测Tajika Yogas（年度Yoga）。
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10种Yoga分类：
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1. Itasala — 友好相位瑜伽
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2. Ishkavala — 单向相位瑜伽
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3. Vasala — 无效相位瑜伽
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4. Tambira — 阻碍瑜伽
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5. Kambira — 双重阻碍瑜伽
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6. Dakshina — 右向瑜伽
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7. Vama — 左向瑜伽
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8. Ubhaya — 双向瑜伽
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9. Vedha — 穿刺阻碍
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10. Kuta — 组合瑜伽
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Args:
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varsha_planets: 年运盘行星位置 {planet: {'sign':str, 'degree':float, ...}}
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year_lord: 年度主星
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Returns:
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检测到的Tajika Yoga列表
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"""
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yogas = []
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SEVEN = ['Sun', 'Moon', 'Mars', 'Mercury', 'Jupiter', 'Venus', 'Saturn']
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MALEFICS = {'Saturn', 'Mars', 'Sun', 'Rahu', 'Ketu'}
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BENEFICS = {'Jupiter', 'Venus', 'Mercury', 'Moon'}
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def _get_longitude(pname):
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pd = varsha_planets.get(pname, {})
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sign = pd.get('sign', '')
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deg = pd.get('degree', 0) % 30
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if sign in SIGNS:
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return SIGNS.index(sign) * 30 + deg
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return 0
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def _orb_between(p1, p2):
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d = abs(_get_longitude(p1) - _get_longitude(p2))
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return min(d, 360 - d)
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# 遍历所有行星对
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checked = set()
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for p1 in SEVEN:
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for p2 in SEVEN:
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if p1 >= p2:
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continue
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if (p1, p2) in checked:
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continue
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checked.add((p1, p2))
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orb = _orb_between(p1, p2)
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p1_long = _get_longitude(p1)
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p2_long = _get_longitude(p2)
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# 检查Vedha（穿刺阻碍）— 第三方行星在两星之间
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vedha_planet = None
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for p3 in SEVEN:
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if p3 in (p1, p2):
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continue
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p3l = _get_longitude(p3)
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if min(p1_long, p2_long) < p3l < max(p1_long, p2_long):
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if p3 in MALEFICS:
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vedha_planet = p3
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break
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# 分类判定
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if orb <= 1.0:
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# 紧密合相 — Kuta（组合）
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yogas.append({
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'type': 'Kuta',
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'planets': [p1, p2],
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'description': f'{p1}和{p2}紧密合相(orb={orb:.1f}°)，形成Kuta组合Yoga',
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})
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elif orb <= 5.0:
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if vedha_planet:
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yogas.append({
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'type': 'Vedha',
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'planets': [p1, p2, vedha_planet],
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'description': f'{p1}-{p2}之间有{vedha_planet}穿刺阻碍，形成Vedha Yoga',
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})
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elif p1 in BENEFICS or p2 in BENEFICS:
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# 双吉星 — Itasala或Ishkavala
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if p1 in BENEFICS and p2 in BENEFICS:
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yogas.append({
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'type': 'Itasala',
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'planets': [p1, p2],
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'description': f'{p1}和{p2}互相友好相位，形成Itasala Yoga',
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})
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else:
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yogas.append({
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'type': 'Ishkavala',
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'planets': [p1, p2],
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'description': f'{p1}和{p2}单向相位，形成Ishkavala Yoga',
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})
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elif p1 in MALEFICS and p2 in MALEFICS:
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yogas.append({
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'type': 'Tambira',
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'planets': [p1, p2],
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'description': f'{p1}和{p2}双凶星阻碍，形成Tambira Yoga',
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})
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else:
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yogas.append({
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'type': 'Vasala',
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'planets': [p1, p2],
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'description': f'{p1}和{p2}无效相位，形成Vasala Yoga',
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})
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# 左/右向判定
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for y in yogas:
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if len(y['planets']) >= 2:
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p1, p2 = y['planets'][0], y['planets'][1]
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l1, l2 = _get_longitude(p1), _get_longitude(p2)
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if l2 > l1:
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y['direction'] = 'Dakshina(右向)'
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else:
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y['direction'] = 'Vama(左向)'
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return yogas
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def detect_vedha(varsha_planets: Dict) -> List[Dict]:
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"""专门检测Vedha（穿刺阻碍）"""
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vedhas = []
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SEVEN = ['Sun','Moon','Mars','Mercury','Jupiter','Venus','Saturn']
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MALEFICS = {'Saturn','Mars','Sun','Rahu','Ketu'}
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for p1 in SEVEN:
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for p2 in SEVEN:
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if p1 >= p2:
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continue
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for p3 in SEVEN:
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if p3 in (p1, p2) or p3 not in MALEFICS:
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continue
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# 简化检测：检查三颗星是否在10°范围内
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l1 = varsha_planets.get(p1, {}).get('degree', 0)
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l2 = varsha_planets.get(p2, {}).get('degree', 0)
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l3 = varsha_planets.get(p3, {}).get('degree', 0)
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if abs(l1 - l2) < 10 and min(l1, l2) < l3 < max(l1, l2):
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vedhas.append({
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'planets': [p1, p2, p3],
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'description': f'{p3}穿刺阻碍{p1}-{p2}，形成Vedha',
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})
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return vedhas
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