feat: 全链路引擎整合 - 新功能接入解盘/预测管线
核心修复： - cmd_full_reading 新增 Step 15(行星聚集) + Step 16(Vivah Saham) - cmd_full_reading Step 6 Chara Dasha 升级为带 Antardasha 版本 - event_prediction_model.py v5.0 完全重写三层验证法: - 第一层: 接入 congregation + vivah_saham + ashtakavarga - 第二层: 接入 Vimshottari MD/AD + Chara Dasha + Antardasha - 第三层: 接入 Double Transit PAC+D9 + LL/7L + Saham 过境激活 - 新增 _calc_planetary_congregation / _calc_vivah_saham 内部函数 - 新增 _house_theme 宫位领域映射 - 预测结果增加置信度分级(高/中/低)和时间窗
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@@ -596,6 +596,116 @@ def _navamsa_idx(lon):
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return (el_starts[si % 4] + ni) % 12
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def _calc_planetary_congregation(planets: Dict, asc_idx: int) -> Dict:
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"""
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本命盘行星聚集检测（供 cmd_full_reading 调用）
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检测 3+ 行星同宫的聚集效应，返回聚集宫位、行星列表、影响领域
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"""
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houses = {}
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for pn, pd in planets.items():
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if not isinstance(pd, dict) or 'sign' not in pd:
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continue
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if pn in ['Rahu', 'Ketu']:
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continue # Rahu/Ketu 不计入聚集
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si = SIGNS.index(pd['sign']) if pd['sign'] in SIGNS else 0
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h = ((si - asc_idx) % 12) + 1
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houses.setdefault(h, []).append(pn)
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congregations = []
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for h, plist in houses.items():
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if len(plist) >= 3:
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h_sign = SIGNS[(asc_idx + h - 1) % 12]
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# 判断影响领域
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impact = _house_theme(h)
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# 判断聚集力量（有无吉星/凶星）
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benefics = [p for p in plist if p in ['Jupiter', 'Venus', 'Mercury', 'Moon']]
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malefics = [p for p in plist if p in ['Saturn', 'Mars', 'Sun', 'Rahu']]
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strength = 'strong' if len(benefics) > len(malefics) else 'mixed'
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if len(malefics) >= 3:
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strength = 'malefic_heavy'
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congregations.append({
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'house': h,
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'sign': h_sign,
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'planets': plist,
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'count': len(plist),
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'benefics': benefics,
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'malefics': malefics,
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'strength': strength,
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'impact': impact,
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'description': f'{",".join(plist)} 聚集于{h}宫({h_sign})',
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})
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return {
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'congregations': congregations,
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'total': len(congregations),
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'note': '3+ 行星同宫为显著聚集，影响该宫主题领域',
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}
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def _house_theme(house: int) -> List[str]:
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"""返回宫位影响领域"""
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themes = {
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1: ['自我', '健康', '性格'],
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2: ['财富', '家庭', '言语'],
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3: ['沟通', '旅行', '兄弟'],
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4: ['母亲', '房产', '情感'],
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5: ['子女', '投资', '创意'],
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6: ['疾病', '敌人', '债务'],
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7: ['婚姻', '合作', '伴侣'],
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8: ['转型', '意外', '遗产'],
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9: ['命运', '父亲', '灵性'],
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10: ['事业', '声望', '成就'],
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11: ['收益', '社交', '愿望'],
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12: ['损失', '外迁', '解脱'],
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}
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return themes.get(house, ['未知'])
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def _calc_vivah_saham(planets: Dict, asc_deg: float) -> Dict:
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"""
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计算本命 Vivah Saham 婚姻敏感点（供 cmd_full_reading 调用）
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公式: Saham = (Venus_lon - Saturn_lon + Asc_deg) % 360
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"""
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venus_lon = planets.get('Venus', {}).get('degree', 0)
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saturn_lon = planets.get('Saturn', {}).get('degree', 0)
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if venus_lon == 0 or saturn_lon == 0:
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return {'error': '缺少金星或土星数据', 'saham': None}
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sahams_lon = (venus_lon - saturn_lon + asc_deg) % 360
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sahams_sign = SIGNS[int(sahams_lon / 30) % 12]
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sahams_deg_in_sign = sahams_lon % 30
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sahams_si = int(sahams_lon / 30) % 12
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# 检查哪些本命行星与 Saham 同宫/合相
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conjuncts = []
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for pn, pd in planets.items():
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if pn in ['Rahu', 'Ketu']:
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continue
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if not isinstance(pd, dict) or 'degree' not in pd:
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continue
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p_lon = pd['degree']
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diff = abs(p_lon - sahams_lon) % 360
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if diff > 180:
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diff = 360 - diff
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if diff <= 5:
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conjuncts.append({'planet': pn, 'diff_deg': round(diff, 2)})
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# 从 Saham 位置反推婚姻相关宫位
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asc_si = int(asc_deg / 30) % 12
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sahams_house = ((sahams_si - asc_si) % 12) + 1
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return {
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'saham_lon': round(sahams_lon, 4),
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'saham_sign': sahams_sign,
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'saham_deg_in_sign': round(sahams_deg_in_sign, 2),
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'saham_house': sahams_house,
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'formula': f'Venus({venus_lon:.2f}°) - Saturn({saturn_lon:.2f}°) + Asc({asc_deg:.2f}°)',
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'natal_conjuncts': conjuncts,
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'marriage_relevance': 'high' if sahams_house in [7, 1, 5, 9] else 'moderate',
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'note': 'Vivah Saham 是度数级婚姻敏感点，Transit 木星/土星过境此点时触发婚姻事件窗',
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}
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def _check_pac(planet_name, planet_lon, target_lon, asc_idx):
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"""PAC检查: Position(同宫)/Aspect(相位)/Conjunction(合相<=10度)"""
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results = []
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@@ -1971,13 +2081,15 @@ def cmd_full_reading(args):
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# ── Step 6: Jaimini系统 ──
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try:
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from jaimini import calc_chara_karaka_7, calc_chara_karaka_8, calc_chara_dasha, calc_karakamsha
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from jaimini import calc_chara_karaka_7, calc_chara_karaka_8, calc_chara_dasha, calc_karakamsha, calc_chara_dasha_with_antardasha
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from varga import calc_varga
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jaimini_result = {}
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jaimini_result['chara_karaka_7'] = calc_chara_karaka_7(planet_degs)
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jaimini_result['chara_karaka_8'] = calc_chara_karaka_8(planet_degs)
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jaimini_result['chara_dasha'] = calc_chara_dasha(asc_idx, planet_lons, args.year, args.month)
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# 使用带 Antardasha 子周期的 Chara Dasha（v4.3.0）
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jaimini_result['chara_dasha'] = calc_chara_dasha_with_antardasha(asc_idx, planet_lons, args.year, args.month)
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jaimini_result['has_antardasha'] = True
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# Karakamsha（用AK灵魂星，非DK配偶星）
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# ⚠️ 2026-05-03修正：此前错误使用DK，现已修正为AK
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@@ -2079,6 +2191,20 @@ def cmd_full_reading(args):
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except Exception as e:
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report['errors'].append(f"actionable-context: {e}")
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# ── Step 15: Planetary Congregation 行星聚集 (v4.3.0) ──
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try:
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congregation = _calc_planetary_congregation(planets, asc_idx)
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report['modules']['congregation'] = congregation
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except Exception as e:
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report['errors'].append(f"congregation: {e}")
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# ── Step 16: Vivah Saham 婚姻敏感点 (v4.3.0) ──
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try:
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sahams = _calc_vivah_saham(planets, asc_deg)
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report['modules']['vivah_saham'] = sahams
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except Exception as e:
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report['errors'].append(f"vivah-saham: {e}")
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# ── 汇总 ──
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elapsed = round(time.time() - t0, 2)
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module_count = len(report['modules'])
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@@ -2088,7 +2214,7 @@ def cmd_full_reading(args):
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'modules_computed': module_count,
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'errors': error_count,
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'status': 'complete' if error_count == 0 else f'{error_count} errors',
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'next_step': 'AI可直接基于此数据执行阶段二→三→四→五。⭐ v4.1.0: modules.actionable_context 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。',
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'next_step': 'AI可直接基于此数据执行阶段二→三→四→五。⭐ v4.3.0: modules.congregation + modules.vivah_saham + antardasha已就绪，全链路分析包含行星聚集、婚姻敏感点、Chara子周期。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。',
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}
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return report
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