feat: P1 gap fill - Transit multi-reference + Dasa Convergence + D9 expanded
Three P1 features added to full-reading pipeline (v4.4.0 -> v4.5.0): 1. Transit Multi-Reference Analysis (transit_multi_reference) - 4 reference points: Lagna / Chandra Lagna / Arudha Lagna / Navamsa Lagna - Per-planet house calculation from each reference - Divergence detection between references - Sade Sati / Ashtama Shani checks (Chandra Lagna based) - Based on transit-multi-reference-guide.md mandatory protocol 2. Dasa Convergence 3-System Cross-Validation (dasa_convergence) - Vimshottari + Chara Dasha + Yogini Dasha convergence - Yogini Dasha engine (8-goddess 36-year cycle) - Per-domain activation detection (12 houses) - Convergence levels: L1(single) -> L3(dual) -> L4(triple) - Based on dasa-convergence-methodology.md 3. D9 Navamsa Per-Planet Dignity Expansion (d9_navamsa_expanded) - Per-planet: sign, house_in_d9, dignity, own/exalted/debilitated/MT flags - pada, lord, degree_in_sign for each planet - Full 10-planet coverage 10-case regression test: 23 modules, 0 errors across all cases
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@@ -2013,6 +2013,366 @@ def cmd_synastry(args):
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# ============================================================================
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# ============================================================================
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# Transit 多参考点分析（v4.5.0 P1补齐）
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# 基于 transit-multi-reference-guide.md 强制规范
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# 四参考点：Lagna / Chandra Lagna / Arudha Lagna / Navamsa Lagna
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# ============================================================================
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def _calc_transit_multi_reference(planets, asc_idx, asc_deg, planet_lons):
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"""
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⭐ v4.5.0: Transit多参考点分析（强制规范）
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每次Transit分析必须同时从四个参考点评估：
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1. Lagna（上升点）— 实际生活事件
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2. Chandra Lagna（月亮星座）— 心理状态、职业变动
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3. Arudha Lagna（AL）— 公众形象
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4. Navamsa Lagna（D9上升）— 灵魂层面
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"""
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# 四个参考点的星座索引
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moon_lon = planet_lons.get('Moon', 0)
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chandra_idx = int(moon_lon / 30) % 12
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# Arudha Lagna（从special_lagnas模块逻辑简化：AL = (Ascendant度数+12宫主度数)%360 对应的星座）
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twelfth_sign_idx = (asc_idx + 11) % 12
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twelfth_lord = SIGN_LORDS.get(SIGNS[twelfth_sign_idx], '')
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twelfth_lord_lon = planet_lons.get(twelfth_lord, 0)
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al_raw = (asc_deg + twelfth_lord_lon) % 360
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# AL 特殊规则：如果结果落在原始宫或第7宫，取对宫
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al_idx = int(al_raw / 30) % 12
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if al_idx == asc_idx or al_idx == (asc_idx + 6) % 12:
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al_idx = (al_idx + 7) % 12 # 取第8个 = 对宫再移一位
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# Navamsa Lagna
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d9_asc_idx = _navamsa_idx(asc_deg)
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references = {
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'Lagna': {
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'name': 'Lagna',
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'cn': '上升点',
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'sign': SIGNS[asc_idx],
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'sign_cn': SIGNS_CN[SIGNS[asc_idx]],
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'sign_idx': asc_idx,
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'priority': 'P1',
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'scope': '实际生活事件、身体健康',
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},
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'Chandra_Lagna': {
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'name': 'Chandra Lagna',
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'cn': '月亮上升',
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'sign': SIGNS[chandra_idx],
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'sign_cn': SIGNS_CN[SIGNS[chandra_idx]],
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'sign_idx': chandra_idx,
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'priority': 'P1',
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'scope': '心理状态、职业变动、情感体验',
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},
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'Arudha_Lagna': {
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'name': 'Arudha Lagna',
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'cn': '形象上升',
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'sign': SIGNS[al_idx],
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'sign_cn': SIGNS_CN[SIGNS[al_idx]],
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'sign_idx': al_idx,
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'priority': 'P2',
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'scope': '公众形象、社会认知、他人如何看待你',
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},
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'Navamsa_Lagna': {
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'name': 'Navamsa Lagna',
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'cn': '灵性上升',
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'sign': SIGNS[d9_asc_idx],
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'sign_cn': SIGNS_CN[SIGNS[d9_asc_idx]],
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'sign_idx': d9_asc_idx,
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'priority': 'P3',
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'scope': '灵魂层面的实际影响、内在真实',
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},
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}
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# 对每个外行星（Jupiter/Saturn/Rahu/Ketu），计算从四个参考点看的宫位
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OUTER_PLANETS = ['Jupiter', 'Saturn', 'Rahu', 'Ketu']
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transit_analysis = {}
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for pn in OUTER_PLANETS:
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pd = planets.get(pn, {})
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if not isinstance(pd, dict) or 'sign' not in pd:
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continue
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p_sign_idx = SIGNS.index(pd['sign']) if pd['sign'] in SIGNS else 0
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transit_analysis[pn] = {
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'sign': pd['sign'],
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'sign_cn': SIGNS_CN.get(pd['sign'], ''),
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'degree_in_sign': pd.get('degree_in_sign', pd.get('degree', 0) % 30),
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'house_from_ref': {},
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}
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for ref_name, ref_info in references.items():
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ref_idx = ref_info['sign_idx']
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house = ((p_sign_idx - ref_idx) % 12) + 1
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house_meaning = _house_theme(house)
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transit_analysis[pn]['house_from_ref'][ref_name] = {
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'house': house,
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'meaning': house_meaning,
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}
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# 差异检测：同一行星在不同参考点的宫位含义是否矛盾
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divergences = []
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for pn, pa in transit_analysis.items():
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houses = {ref: info['house'] for ref, info in pa['house_from_ref'].items()}
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unique_houses = set(houses.values())
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if len(unique_houses) > 1:
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divergences.append({
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'planet': pn,
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'houses': houses,
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'divergence': f'{pn}在四个参考点分别落在不同宫位，需综合判断',
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})
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# Sade Sati / Ashtama Shani 检测（基于Chandra Lagna）
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special_checks = {}
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saturn_sign_idx = SIGNS.index(planets.get('Saturn', {}).get('sign', 'Aries')) if isinstance(planets.get('Saturn'), dict) and planets.get('Saturn', {}).get('sign') in SIGNS else 0
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# Sade Sati: Saturn 在月亮星座或前后1宫
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sade_sati_phase = None
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if saturn_sign_idx == chandra_idx:
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sade_sati_phase = 'peak'
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elif saturn_sign_idx == (chandra_idx - 1) % 12:
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sade_sati_phase = 'rising'
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elif saturn_sign_idx == (chandra_idx + 1) % 12:
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sade_sati_phase = 'setting'
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if sade_sati_phase:
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special_checks['sade_sati'] = {
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'active': True,
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'phase': sade_sati_phase,
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'note': f'土星过境月亮{SIGNS_CN[SIGNS[chandra_idx]]}附近，Sade Sati {sade_sati_phase}期',
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}
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# Ashtama Shani: Saturn在月亮第8宫
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saturn_from_chandra = ((saturn_sign_idx - chandra_idx) % 12) + 1
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if saturn_from_chandra == 8:
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special_checks['ashtama_shani'] = {
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'active': True,
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'note': '土星过境月亮第8宫（Ashtama Shani），压力期',
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}
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return {
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'references': references,
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'transit_analysis': transit_analysis,
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'divergences': divergences,
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'divergence_count': len(divergences),
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'special_checks': special_checks,
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'protocol': 'v4.5.0 Transit多参考点强制规范：AI必须同时呈现Lagna和Chandra Lagna两个视角。任何矛盾信号必须记录并解释。',
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}
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# ============================================================================
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# Dasa Convergence 三系统交叉验证（v4.5.0 P1补齐）
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# 基于 dasa-convergence-methodology.md
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# 三系统：Vimshottari + Chara Dasha + Yogini
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# ============================================================================
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# Yogini Dasha 常量
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YOGINI_ORDER = ['Mangala', 'Pingala', 'Dhanya', 'Bhramari', 'Bhadrika', 'Ulka', 'Siddha', 'Sankata']
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YOGINI_YEARS = {'Mangala': 1, 'Pingala': 2, 'Dhanya': 3, 'Bhramari': 4, 'Bhadrika': 5, 'Ulka': 6, 'Siddha': 7, 'Sankata': 8}
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# Yogini 从月亮 Nakshatra 的第3个 Nakshatra（Dhanishta）开始计数
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YOGINI_NAK_START = 23 # Dhanishta 在 NAKSHATRA_LIST 中的索引
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def _calc_yogini_dasha(moon_lon, birthdate_str):
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"""
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计算 Yogini Dasha 时间线
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Yogini 基于 8 位女神循环，总周期 36 年
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起始点由月亮所在 Nakshatra 决定
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"""
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nak_idx = int(moon_lon / (360 / 27)) % 27
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# Yogini 起始索引 = (nak_idx - YOGINI_NAK_START) % 8
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yog_start = (nak_idx - YOGINI_NAK_START) % 8
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# 余数 = 在当前 Yogini 周期中的已过比例
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nak_in_yog = nak_idx % 8 # 在8分组的第几个
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pada = int((moon_lon % (360/27)) / (360/108)) + 1
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# 余数比例
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balance_frac = (nak_in_yog * 4 + pada - 1) / 32 # 8 Nakshatra × 4 Pada = 32 份
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balance_frac = min(balance_frac, 1.0)
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birth_date = datetime.strptime(birthdate_str, '%Y-%m-%d')
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maha_periods = []
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total_years = 0
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for i in range(8):
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idx = (yog_start + i) % 8
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name = YOGINI_ORDER[idx]
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years = YOGINI_YEARS[name]
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if i == 0:
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elapsed_years = years * balance_frac
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actual_years = years - elapsed_years
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start_offset = total_years
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maha_periods.append({
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'yogini': name,
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'full_years': years,
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'balance_years': round(actual_years, 3),
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'start_offset_years': round(start_offset, 3),
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'start_date': (birth_date + timedelta(days=round(start_offset * 365.25))).strftime('%Y-%m-%d'),
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'end_date': (birth_date + timedelta(days=round((start_offset + actual_years) * 365.25))).strftime('%Y-%m-%d'),
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'is_current_start': True,
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})
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total_years += actual_years
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else:
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start_offset = total_years
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maha_periods.append({
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'yogini': name,
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'full_years': years,
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'start_offset_years': round(start_offset, 3),
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'start_date': (birth_date + timedelta(days=round(start_offset * 365.25))).strftime('%Y-%m-%d'),
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'end_date': (birth_date + timedelta(days=round((start_offset + years) * 365.25))).strftime('%Y-%m-%d'),
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})
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total_years += years
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# 计算当前 Yogini
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today = datetime.now()
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age_days = (today - birth_date).days
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age_years = age_days / 365.25
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cycle_years = 36 # Yogini 总周期
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current_in_cycle = age_years % cycle_years
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current_yogini = None
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cumulative = 0
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for yp in maha_periods:
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dur = yp.get('balance_years', yp['full_years'])
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if cumulative <= current_in_cycle < cumulative + dur:
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current_yogini = yp
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break
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cumulative += dur
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return {
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'moon_nakshatra_idx': nak_idx,
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'yogini_start_index': yog_start,
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'total_cycle_years': 36,
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'maha_periods': maha_periods,
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'current_yogini': current_yogini,
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}
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def _calc_dasa_convergence(dasha_result, chara_dasha_result, yogini_result, planet_lons, asc_idx):
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"""
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⭐ v4.5.0: Dasa Convergence 三系统交叉验证
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Vimshottari + Chara Dasha + Yogini 三系统同时激活同一生活领域时，概率大幅提升
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"""
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# 提取各系统当前周期
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convergence_data = {'systems': {}}
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# 系统1: Vimshottari
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if isinstance(dasha_result, dict):
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current_d = dasha_result.get('current_dasha', {})
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if isinstance(current_d, dict):
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maha = current_d.get('mahadasha', current_d.get('maha'))
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antar = current_d.get('antardasha', current_d.get('antar'))
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convergence_data['systems']['vimshottari'] = {
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'maha': maha,
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'antar': antar,
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'pratyantar': current_d.get('pratyantar'),
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'basis': 'Nakshatra (Moon)',
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}
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# 系统2: Chara Dasha
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if isinstance(chara_dasha_result, dict):
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cd_maha = chara_dasha_result.get('current_maha', chara_dasha_result.get('current'))
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cd_antar = chara_dasha_result.get('current_antar')
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if isinstance(cd_maha, dict):
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cd_sign = cd_maha.get('sign', cd_maha.get('rashi'))
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elif isinstance(cd_maha, str):
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cd_sign = cd_maha
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else:
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cd_sign = None
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convergence_data['systems']['chara_dasha'] = {
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'maha_sign': cd_sign,
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'antar_sign': cd_antar.get('sign', cd_antar) if isinstance(cd_antar, dict) else cd_antar,
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'basis': 'Rashi (Sign-based)',
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}
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# 系统3: Yogini
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if isinstance(yogini_result, dict):
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cur_yog = yogini_result.get('current_yogini', {})
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convergence_data['systems']['yogini'] = {
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'yogini': cur_yog.get('yogini') if isinstance(cur_yog, dict) else None,
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'years': cur_yog.get('full_years') if isinstance(cur_yog, dict) else None,
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'basis': 'Nakshatra (8-goddess cycle)',
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}
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# 宫位主题映射
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house_themes_map = {
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1: 'self_health', 2: 'wealth_family', 3: 'communication_skill', 4: 'home_mother',
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5: 'creativity_children', 6: 'health_service', 7: 'marriage_partnership',
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8: 'transformation', 9: 'fortune_dharma', 10: 'career_status',
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11: 'gains_wishes', 12: 'loss_spirituality',
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}
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# 逐领域检测三系统激活
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domain_activations = {}
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for house, domain in house_themes_map.items():
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activations = []
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# Vimshottari: 检查大运/小运行星是否关联该宫
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vims = convergence_data['systems'].get('vimshottari', {})
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if vims:
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for level in ['maha', 'antar']:
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planet = vims.get(level)
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if planet and isinstance(planet, str):
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# 该行星是否掌管此宫？
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target_sign_idx = (asc_idx + house - 1) % 12
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target_sign = SIGNS[target_sign_idx]
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target_lord = SIGN_LORDS.get(target_sign, '')
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if planet == target_lord:
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activations.append({
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'system': 'Vimshottari',
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'level': level,
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'planet': planet,
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'reason': f'{planet}是{house}宫({target_sign})的宫主星',
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})
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# 该行星是否落在此宫？
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p_sign_idx = int(planet_lons.get(planet, 0) / 30) % 12
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p_house = ((p_sign_idx - asc_idx) % 12) + 1
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if p_house == house:
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activations.append({
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'system': 'Vimshottari',
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'level': level,
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'planet': planet,
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'reason': f'{planet}落在{house}宫',
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})
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# Chara Dasha: 检查当前星座是否关联该宫
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cd = convergence_data['systems'].get('chara_dasha', {})
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if cd and cd.get('maha_sign'):
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cd_sign = cd['maha_sign']
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if cd_sign in SIGNS:
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cd_sign_idx = SIGNS.index(cd_sign)
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cd_house_from_asc = ((cd_sign_idx - asc_idx) % 12) + 1
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if cd_house_from_asc == house:
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activations.append({
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'system': 'Chara Dasha',
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'level': 'maha',
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'sign': cd_sign,
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'reason': f'Chara大运星座{cd_sign}是{house}宫',
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})
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if activations:
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domain_activations[domain] = {
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'house': house,
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'activations': activations,
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'system_count': len(set(a['system'] for a in activations)),
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}
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# 收敛等级评估
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for domain, info in domain_activations.items():
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sc = info['system_count']
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if sc >= 3:
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info['convergence_level'] = 'L4'
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info['probability'] = '75-85%'
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info['interpretation'] = '三系统同时激活，极强信号'
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elif sc >= 2:
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info['convergence_level'] = 'L3'
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info['probability'] = '50-65%'
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info['interpretation'] = '双系统激活，强信号'
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else:
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info['convergence_level'] = 'L1'
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info['probability'] = '+15-20%'
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info['interpretation'] = '单系统激活，需Transit确认'
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# 收敛窗口（最高优先级的领域）
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top_domains = sorted(domain_activations.items(), key=lambda x: x[1]['system_count'], reverse=True)[:5]
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return {
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'systems_summary': convergence_data['systems'],
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'domain_activations': domain_activations,
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'top_convergent_domains': [(d, info['convergence_level']) for d, info in top_domains],
|
||||
'protocol': 'v4.5.0 Dasa Convergence 三系统交叉验证。收敛等级: L1(单系统)→L3(双系统)→L4(三系统)。所有预测必须标注收敛等级。',
|
||||
}
|
||||
|
||||
|
||||
def _calc_actionable_context(planets, asc_idx):
|
||||
"""⭐ v4.1.0: 计算Transit Actionable Output所需的上下文数据
|
||||
输出：宫位激活映射 + 关键行星宫位关系 → 供AI生成Actionable Output时直接引用
|
||||
@@ -2500,6 +2860,70 @@ def cmd_full_reading(args):
|
||||
except Exception as e:
|
||||
report['errors'].append(f"vivah-saham: {e}")
|
||||
|
||||
# ── Step 17: Transit 多参考点分析 (v4.5.0 P1) ──
|
||||
try:
|
||||
transit_multi = _calc_transit_multi_reference(planets, asc_idx, asc_deg, planet_lons)
|
||||
report['modules']['transit_multi_reference'] = transit_multi
|
||||
except Exception as e:
|
||||
report['errors'].append(f"transit-multi-ref: {e}")
|
||||
|
||||
# ── Step 18: Dasa Convergence 三系统交叉验证 (v4.5.0 P1) ──
|
||||
try:
|
||||
dasha_data = report['modules'].get('dasha', {})
|
||||
jaimini_data = report['modules'].get('jaimini', {})
|
||||
chara_dasha_data = jaimini_data.get('chara_dasha', {}) if isinstance(jaimini_data, dict) else {}
|
||||
birthdate_str = f"{args.year}-{args.month:02d}-{args.day:02d}"
|
||||
yogini_data = _calc_yogini_dasha(planet_lons.get('Moon', 0), birthdate_str)
|
||||
report['modules']['yogini_dasha'] = yogini_data
|
||||
convergence = _calc_dasa_convergence(dasha_data, chara_dasha_data, yogini_data, planet_lons, asc_idx)
|
||||
report['modules']['dasa_convergence'] = convergence
|
||||
except Exception as e:
|
||||
report['errors'].append(f"dasa-convergence: {e}")
|
||||
|
||||
# ── Step 19: D9 Navamsa 逐行星尊严展开 (v4.5.0 P1) ──
|
||||
try:
|
||||
varga_data = report['modules'].get('varga_full', {})
|
||||
d9_data = varga_data.get('D9_Navamsa', {}) if isinstance(varga_data, dict) else {}
|
||||
if d9_data:
|
||||
d9_expanded = {}
|
||||
for pn, pd in d9_data.items():
|
||||
if pn == '_meta' or not isinstance(pd, dict) or 'sign' not in pd:
|
||||
continue
|
||||
d9_sign = pd['sign']
|
||||
d9_deg = pd.get('degree_in_sign', pd.get('degree', 0) % 30)
|
||||
dignity = _get_dignity_level(pn, d9_sign, d9_deg)
|
||||
# D9 宫位（从D9 Asc计算）
|
||||
d9_asc_data = d9_data.get('Ascendant', {})
|
||||
d9_asc_sign_idx = SIGNS.index(d9_asc_data.get('sign', 'Aries')) if isinstance(d9_asc_data, dict) and d9_asc_data.get('sign') in SIGNS else 0
|
||||
p_sign_idx = SIGNS.index(d9_sign) if d9_sign in SIGNS else 0
|
||||
d9_house = ((p_sign_idx - d9_asc_sign_idx) % 12) + 1
|
||||
# 关系状态
|
||||
d9_sign_lord = SIGN_LORDS.get(d9_sign, '')
|
||||
is_own = (d9_sign_lord == pn)
|
||||
is_exalted = (EXALTATION.get(pn) == d9_sign)
|
||||
is_debilitated = (DEBILITATION.get(pn) == d9_sign)
|
||||
is_moola = False
|
||||
if pn in MOOLATRIKONA:
|
||||
mt_sign, mt_start, mt_end = MOOLATRIKONA[pn]
|
||||
if mt_sign == d9_sign and mt_start <= d9_deg < mt_end:
|
||||
is_moola = True
|
||||
d9_expanded[pn] = {
|
||||
'sign': d9_sign,
|
||||
'sign_cn': SIGNS_CN.get(d9_sign, ''),
|
||||
'house_in_d9': d9_house,
|
||||
'dignity': dignity,
|
||||
'is_own_sign': is_own,
|
||||
'is_exalted': is_exalted,
|
||||
'is_debilitated': is_debilitated,
|
||||
'is_moolatrikona': is_moola,
|
||||
'pada': pd.get('pada'),
|
||||
'lord': d9_sign_lord,
|
||||
'degree_in_sign': round(d9_deg, 4),
|
||||
}
|
||||
report['modules']['d9_navamsa_expanded'] = d9_expanded
|
||||
except Exception as e:
|
||||
report['errors'].append(f"d9-expanded: {e}")
|
||||
|
||||
# ── 汇总 ──
|
||||
elapsed = round(time.time() - t0, 2)
|
||||
module_count = len(report['modules'])
|
||||
@@ -2509,7 +2933,7 @@ def cmd_full_reading(args):
|
||||
'modules_computed': module_count,
|
||||
'errors': error_count,
|
||||
'status': 'complete' if error_count == 0 else f'{error_count} errors',
|
||||
'next_step': 'AI可直接基于此数据执行阶段二→三→四→五。⭐ v4.4.0: 21步全链路已就绪。新增 special_lagnas/vimsopaka/varga_extended/karaka_jh/avasthas 五个模块。modules.congregation + modules.vivah_saham + antardasha + avasthas + vimsopaka 已就绪。Transit分析时必须输出Actionable Output（时间段+行动类型+置信度），动态预测必须先检索案例。',
|
||||
'next_step': '⭐ v4.5.0: P1缺口已补齐。新增 transit_multi_reference(四参考点) + dasa_convergence(三系统交叉) + yogini_dasha + d9_navamsa_expanded(逐行星尊严展开)。AI必须使用四参考点分析Transit，Dasa预测必须标注收敛等级。',
|
||||
}
|
||||
|
||||
return report
|
||||
|
||||
Reference in New Issue
Block a user