v6.1.6: Add five-system dasha convergence

CHANGELOG.md

@@ -1,5 +1,29 @@
 # 印度占星 Skill 更新日志
 
+## v6.1.6（2026-06-07）—— full-reading 五系统推运收敛与接口修复
+
+> **目标**：继续“合并隐藏模块→打通引擎→验证可用”的优化路线，将 Ashtottari / Yogini / Kalachakra 从独立模块进一步接入 `full-reading` 主链路。
+
+### 关键改进
+- `full-reading` 新增输出：`modules.ashtottari_dasha`、`modules.kalachakra_dasha`，并改用 `scripts/yogini_dasha.py` 的公共接口输出 `modules.yogini_dasha`。
+- `dasa_convergence` 从三系统升级为五系统：Vimshottari + Chara Dasha + Yogini + Ashtottari + Kalachakra。
+- 新增 L5 收敛等级：四个及以上推运系统同时激活同一领域时标为顶级收敛信号；Chara Dasha 仍按既有规范保持 partial/低权重辅助。
+- 增强领域激活检测：Yogini/Ashtottari 当前主星、Kalachakra 当前 Rashi 与 lord 均参与宫位主题激活判断。
+- 修复替代 Dasha 模块 current 周期：超过单周期年龄时按 36/108/150 年周期循环，不再返回 None。
+- 修复 `full-reading` 中 Pancha Pakshi 与 Rashi Tulya Navamsa 的接口调用，改为对齐现有公共函数 `get_pancha_pakshi_schedule()` 与 `analyze_rtn()`。
+
+### 验证
+```bash
+python3 -m py_compile scripts/jyotish_engine.py scripts/ashtottari_dasha.py scripts/yogini_dasha.py scripts/kalachakra_dasha.py scripts/orchestrator_bridge.py
+PYTHONPATH=scripts python3 scripts/jyotish_engine.py full-reading --year 1990 --month 6 --day 15 --hour 10 --minute 30 --lat 39.9 --lon 116.4 --tz 8
+```
+- smoke case：`summary.status = complete`
+- `errors = []`
+- `modules_computed = 47`
+- `dasa_convergence.systems_summary` 包含 `ashtottari`、`chara_dasha`、`kalachakra`、`vimshottari`、`yogini`
+
+---
+
 ## v6.0.44（2026-06-06）—— 修复参考数据 JD 时区 Bug，验证基线校正
 
 > **目标**：修复导致 `standard_test_charts.json` 中所有非正午出生星盘上升星座错误的 JD 时区 Bug。

SKILL.md

@@ -1,6 +1,6 @@
 ---
 name: jyotish-vedic-astrology
-version: 6.0.43
+version: 6.1.6
 description: 印度占星（Jyotish）专业解盘与推运系统。核心能力：PDF星盘输入→严谨解盘→精确推运应期输出。触发词：印度占星、吠陀占星、Jyotish、解盘、推运、星盘分析、Dasha、Transit、Nakshatra、Yoga、出生时间矫正、PDF星盘、读取PDF、分析PDF星盘、现代解读、误判纠错、Varga分盘、综合分析、过境分析、合盘、婚姻匹配、年运盘、Prashna、Argala、Jaimini、Shadbala、Ashtakavarga、HTML报告、深度解盘。
 ---
 
@@ -10,7 +10,7 @@ description: 印度占星（Jyotish）专业解盘与推运系统。核心能力
 > **严格路由**：`references/strict-workflow-router.md`（⭐涉及事业/婚恋/财务/应期/技法验证时必须优先读取）
 > **覆盖矩阵**：`references/technique-capability-matrix.md`（⭐判断技法 covered/partial/missing 时必须参考）
 > **机器注册表**：`references/technique_registry.json` + `scripts/audit_capabilities.py`（⭐用于自动审计与CI门禁）
-> **版本**：v6.0.47 | **详细变更**：`CHANGELOG.md`
+> **版本**：v6.1.6 | **详细变更**：`CHANGELOG.md`
 
 ## Yoga 逻辑验证指标
 
@@ -43,7 +43,7 @@ description: 印度占星（Jyotish）专业解盘与推运系统。核心能力
 2. **阶段一**（仅B）：PDF/图片提取 + Quality Gate
 3. **阶段二**：意图识别 → 路由目标宫位（无明确意图→Level 2综合解盘）
 4. **阶段三**：静态分析10步（宫位→承诺→Yoga→Argala→逆行→NK→Shadbala→AV→Ketu→分盘）
-5. **阶段四**：动态推运7步（Dasha→Convergence→Transit→Double Transit→Jaimini→KP→Varshaphala）
+5. **阶段四**：动态推运7步（Dasha→五系统Convergence→Transit→Double Transit→Jaimini→KP→Varshaphala）
 6. **阶段五**：应期输出（五层验证→时间窗口→Actionable Output+案例检索）
 7. **阶段六**：补救措施（可选）
 8. **阶段七**：现代措辞包装
@@ -180,7 +180,7 @@ $PYTHON $SCRIPT <子命令> [参数]
 
 | 子命令 | 功能 |
 |--------|------|
-| `full-reading` | ⭐全自动综合解盘（13模块一键出） |
+| `full-reading` | ⭐全自动综合解盘（47模块一键出，含五系统Dasha收敛） |
 | `chart` | 星盘计算+`--validate`附加R1-R10验证 |
 | `dasha` | Vimshottari大运时间线+小运展开 |
 | `yoga` | Yoga格局识别 |
@@ -313,9 +313,9 @@ $PYTHON $SCRIPT <子命令> [参数]
 
 ---
 
-**版本**：v6.0.46-yoga-f1-92
+**版本**：v6.1.6-full-reading-five-dasha-convergence
 **创建日期**：2026-04-20
-**最后更新**：2026-06-06（v6.0.46 修复 6 条完全错误的瑜伽规则：kaalanirdesat_puthra/sapthasankhya_sahodara/sarpasaapa/pushkala/koorma/bhratrumooladdhanaprapti，FP 从 193→78，Precision 从 83.26%→92.50%，F1 从 87.19%→92.10%；当前 476 条规则、405 条启用，硬编码测试 8/9 通过）
+**最后更新**：2026-06-07（v6.1.6 将 Ashtottari/Yogini/Kalachakra 接入 full-reading，Dasa Convergence 从三系统升级为 Vimshottari + Chara + Yogini + Ashtottari + Kalachakra 五系统；修复 Pancha Pakshi/RTN 接口与替代 Dasha current 周期循环。Yoga 当前以 `references/validation_logic_report.json` 为准。）
 
 ---
 

references/validation_logic_report.json

@@ -2,7 +2,7 @@
   "summary": {
     "charts_tested": 60,
     "comparable_rules": 82,
-    "skill_total": 1021,
+    "skill_total": 1020,
     "pyjhora_total": 1049,
     "unmapped_pyjhora": 718,
     "missing_mappings": {
@@ -99,33 +99,33 @@
       ]
     },
     "agreements": 982,
-    "false_positives": 39,
+    "false_positives": 38,
     "false_negatives": 67,
-    "precision": 0.9618,
+    "precision": 0.9627,
     "recall": 0.9361,
-    "f1": 0.9488
+    "f1": 0.9493
   },
   "false_positives": [
-    {
-      "chart": "Albert Einstein",
-      "rule_id": "bvr_bhaga_chumbana_yoga",
-      "rule_name": "Bhaga Chumbana Yoga"
-    },
     {
       "chart": "Albert Einstein",
       "rule_id": "bvr_dharidhra_11_precise",
       "rule_name": "Dharidhra Yoga"
     },
     {
-      "chart": "Nikola Tesla",
-      "rule_id": "bvr_krisanga_yoga",
-      "rule_name": "Krisanga Yoga"
+      "chart": "Albert Einstein",
+      "rule_id": "bvr_bhaga_chumbana_yoga",
+      "rule_name": "Bhaga Chumbana Yoga"
     },
     {
       "chart": "Nikola Tesla",
       "rule_id": "bvr_bhratruvriddhi_precise",
       "rule_name": "Bhratruvriddhi Yoga"
     },
+    {
+      "chart": "Nikola Tesla",
+      "rule_id": "bvr_krisanga_yoga",
+      "rule_name": "Krisanga Yoga"
+    },
     {
       "chart": "Stephen Hawking",
       "rule_id": "sankha_yoga",
@@ -138,13 +138,13 @@
     },
     {
       "chart": "Alexander Fleming",
-      "rule_id": "bvr_bhaga_chumbana_yoga",
-      "rule_name": "Bhaga Chumbana Yoga"
+      "rule_id": "bvr_yukthi_samanwithavagmi_yoga",
+      "rule_name": "Yukthi Samanwithavagmi Yoga"
     },
     {
       "chart": "Alexander Fleming",
-      "rule_id": "bvr_yukthi_samanwithavagmi_yoga",
-      "rule_name": "Yukthi Samanwithavagmi Yoga"
+      "rule_id": "bvr_bhaga_chumbana_yoga",
+      "rule_name": "Bhaga Chumbana Yoga"
     },
     {
       "chart": "Max Planck",
@@ -176,11 +176,6 @@
       "rule_id": "bvr_swaveeryaddhana_precise",
       "rule_name": "Swaveeryaddhana Yoga"
     },
-    {
-      "chart": "John F. Kennedy",
-      "rule_id": "bvr_nishkapata_precise",
-      "rule_name": "Nishkapata Yoga"
-    },
     {
       "chart": "Nelson Mandela",
       "rule_id": "bvr_mathibhramana_yoga",
@@ -193,13 +188,13 @@
     },
     {
       "chart": "Barack Obama",
-      "rule_id": "bvr_bandhubhisthyaktha_precise",
-      "rule_name": "Bandhubhisthyaktha Yoga"
+      "rule_id": "bvr_yukthi_samanwithavagmi_yoga",
+      "rule_name": "Yukthi Samanwithavagmi Yoga"
     },
     {
       "chart": "Barack Obama",
-      "rule_id": "bvr_yukthi_samanwithavagmi_yoga",
-      "rule_name": "Yukthi Samanwithavagmi Yoga"
+      "rule_id": "bvr_bandhubhisthyaktha_precise",
+      "rule_name": "Bandhubhisthyaktha Yoga"
     },
     {
       "chart": "Pablo Picasso",
@@ -233,13 +228,13 @@
     },
     {
       "chart": "Lionel Messi",
-      "rule_id": "bvr_017_vosi_precise",
-      "rule_name": "Vosi Yoga"
+      "rule_id": "brahma_yoga",
+      "rule_name": "Brahma Yoga"
     },
     {
       "chart": "Lionel Messi",
-      "rule_id": "brahma_yoga",
-      "rule_name": "Brahma Yoga"
+      "rule_id": "bvr_017_vosi_precise",
+      "rule_name": "Vosi Yoga"
     },
     {
       "chart": "Cristiano Ronaldo",
@@ -278,13 +273,13 @@
     },
     {
       "chart": "Princess Diana",
-      "rule_id": "bvr_bandhu_pujya_yoga",
-      "rule_name": "Bandhu Pujya Yoga"
+      "rule_id": "bvr_ayatna_griha_prapta_yoga",
+      "rule_name": "Ayatna Griha Prapta Yoga"
     },
     {
       "chart": "Princess Diana",
-      "rule_id": "bvr_ayatna_griha_prapta_yoga",
-      "rule_name": "Ayatna Griha Prapta Yoga"
+      "rule_id": "bvr_bandhu_pujya_yoga",
+      "rule_name": "Bandhu Pujya Yoga"
     },
     {
       "chart": "J. Krishnamurti",
@@ -293,13 +288,13 @@
     },
     {
       "chart": "Ramana Maharshi",
-      "rule_id": "bvr_utthama_graha_yoga",
-      "rule_name": "Utthama Griha Yoga"
+      "rule_id": "bvr_matru_sneha_yoga",
+      "rule_name": "Matru Sneha Yoga"
     },
     {
       "chart": "Ramana Maharshi",
-      "rule_id": "bvr_matru_sneha_yoga",
-      "rule_name": "Matru Sneha Yoga"
+      "rule_id": "bvr_utthama_graha_yoga",
+      "rule_name": "Utthama Griha Yoga"
     }
   ],
   "false_negatives": [
@@ -314,10 +309,10 @@
     },
     {
       "chart": "Marie Curie",
-      "rule_id": "bvr_thrikaala_gnana_yoga",
-      "rule_name": "Thrikaala Gnana Yoga",
+      "rule_id": "parvata_yoga",
+      "rule_name": "Parvata Yoga",
       "pyjhora_names": [
-        "thrikaala_gnana_yoga"
+        "parvata_yoga"
       ]
     },
     {
@@ -331,10 +326,10 @@
     },
     {
       "chart": "Marie Curie",
-      "rule_id": "parvata_yoga",
-      "rule_name": "Parvata Yoga",
+      "rule_id": "bvr_thrikaala_gnana_yoga",
+      "rule_name": "Thrikaala Gnana Yoga",
       "pyjhora_names": [
-        "parvata_yoga"
+        "thrikaala_gnana_yoga"
       ]
     },
     {
@@ -383,6 +378,14 @@
         "pisacha_grastha_yoga"
       ]
     },
+    {
+      "chart": "Mahatma Gandhi",
+      "rule_id": "brahma_yoga",
+      "rule_name": "Brahma Yoga",
+      "pyjhora_names": [
+        "brahma_yoga"
+      ]
+    },
     {
       "chart": "Mahatma Gandhi",
       "rule_id": "bvr_matrudeerghayur_yoga",
@@ -392,14 +395,6 @@
         "matrudeerghayur_yoga_197"
       ]
     },
-    {
-      "chart": "Mahatma Gandhi",
-      "rule_id": "brahma_yoga",
-      "rule_name": "Brahma Yoga",
-      "pyjhora_names": [
-        "brahma_yoga"
-      ]
-    },
     {
       "chart": "Narendra Modi",
       "rule_id": "bvr_nishkapata_precise",
@@ -417,6 +412,14 @@
         "utthama_graha_yoga"
       ]
     },
+    {
+      "chart": "Indira Gandhi",
+      "rule_id": "bvr_sumukha_precise",
+      "rule_name": "Sumukha Yoga",
+      "pyjhora_names": [
+        "sumukha_yoga"
+      ]
+    },
     {
       "chart": "Indira Gandhi",
       "rule_id": "bvr_nishkapata_precise",
@@ -426,14 +429,6 @@
         "nishkapata_yoga_206"
       ]
     },
-    {
-      "chart": "Indira Gandhi",
-      "rule_id": "bvr_sumukha_precise",
-      "rule_name": "Sumukha Yoga",
-      "pyjhora_names": [
-        "sumukha_yoga"
-      ]
-    },
     {
       "chart": "Nelson Mandela",
       "rule_id": "bvr_apakeerthi_yoga",
@@ -503,14 +498,6 @@
         "nishkapata_yoga_206"
       ]
     },
-    {
-      "chart": "Rabindranath Tagore",
-      "rule_id": "brahma_yoga",
-      "rule_name": "Brahma Yoga",
-      "pyjhora_names": [
-        "brahma_yoga"
-      ]
-    },
     {
       "chart": "Rabindranath Tagore",
       "rule_id": "bvr_kapata_yoga",
@@ -521,6 +508,14 @@
         "kapata_yoga_204"
       ]
     },
+    {
+      "chart": "Rabindranath Tagore",
+      "rule_id": "brahma_yoga",
+      "rule_name": "Brahma Yoga",
+      "pyjhora_names": [
+        "brahma_yoga"
+      ]
+    },
     {
       "chart": "Ludwig van Beethoven",
       "rule_id": "bvr_thrikaala_gnana_yoga",
@@ -529,6 +524,16 @@
         "thrikaala_gnana_yoga"
       ]
     },
+    {
+      "chart": "Wolfgang Mozart",
+      "rule_id": "bvr_kapata_yoga",
+      "rule_name": "Kapata Yoga",
+      "pyjhora_names": [
+        "kapata_yoga_202",
+        "kapata_yoga_203",
+        "kapata_yoga_204"
+      ]
+    },
     {
       "chart": "Wolfgang Mozart",
       "rule_id": "bvr_raja_bhanga_yoga",
@@ -538,24 +543,6 @@
         "raja_bhanga_yoga_299"
       ]
     },
-    {
-      "chart": "Wolfgang Mozart",
-      "rule_id": "bvr_pittharoga_yoga",
-      "rule_name": "Pittharoga Yoga",
-      "pyjhora_names": [
-        "pittharoga_yoga"
-      ]
-    },
-    {
-      "chart": "Wolfgang Mozart",
-      "rule_id": "bvr_kapata_yoga",
-      "rule_name": "Kapata Yoga",
-      "pyjhora_names": [
-        "kapata_yoga_202",
-        "kapata_yoga_203",
-        "kapata_yoga_204"
-      ]
-    },
     {
       "chart": "Wolfgang Mozart",
       "rule_id": "bvr_theevrabuddhi_yoga",
@@ -564,6 +551,14 @@
         "theevrabuddhi_yoga"
       ]
     },
+    {
+      "chart": "Wolfgang Mozart",
+      "rule_id": "bvr_pittharoga_yoga",
+      "rule_name": "Pittharoga Yoga",
+      "pyjhora_names": [
+        "pittharoga_yoga"
+      ]
+    },
     {
       "chart": "Pablo Picasso",
       "rule_id": "bvr_raja_bhanga_yoga",
@@ -650,15 +645,6 @@
         "bahu_sthree_yoga"
       ]
     },
-    {
-      "chart": "Azim Premji",
-      "rule_id": "bvr_nishkapata_precise",
-      "rule_name": "Nishkapata Yoga",
-      "pyjhora_names": [
-        "nishkapata_yoga_205",
-        "nishkapata_yoga_206"
-      ]
-    },
     {
       "chart": "Azim Premji",
       "rule_id": "bvr_dharidhra_11_precise",
@@ -673,6 +659,15 @@
         "dharidhra_yoga_152"
       ]
     },
+    {
+      "chart": "Azim Premji",
+      "rule_id": "bvr_ayatna_griha_prapta_yoga",
+      "rule_name": "Ayatna Griha Prapta Yoga",
+      "pyjhora_names": [
+        "ayatna_griha_prapta_yoga_189",
+        "ayatna_griha_prapta_yoga_190"
+      ]
+    },
     {
       "chart": "Azim Premji",
       "rule_id": "bvr_bahu_puthra_precise",
@@ -684,11 +679,11 @@
     },
     {
       "chart": "Azim Premji",
-      "rule_id": "bvr_ayatna_griha_prapta_yoga",
-      "rule_name": "Ayatna Griha Prapta Yoga",
+      "rule_id": "bvr_nishkapata_precise",
+      "rule_name": "Nishkapata Yoga",
       "pyjhora_names": [
-        "ayatna_griha_prapta_yoga_189",
-        "ayatna_griha_prapta_yoga_190"
+        "nishkapata_yoga_205",
+        "nishkapata_yoga_206"
       ]
     },
     {
@@ -699,6 +694,14 @@
         "pushkala_yoga"
       ]
     },
+    {
+      "chart": "Michael Jordan",
+      "rule_id": "bvr_bandhubhisthyaktha_precise",
+      "rule_name": "Bandhubhisthyaktha Yoga",
+      "pyjhora_names": [
+        "bandhubhisthyaktha_yoga"
+      ]
+    },
     {
       "chart": "Michael Jordan",
       "rule_id": "bvr_krisanga_yoga",
@@ -708,14 +711,6 @@
         "krisanga_yoga_113"
       ]
     },
-    {
-      "chart": "Michael Jordan",
-      "rule_id": "bvr_bandhubhisthyaktha_precise",
-      "rule_name": "Bandhubhisthyaktha Yoga",
-      "pyjhora_names": [
-        "bandhubhisthyaktha_yoga"
-      ]
-    },
     {
       "chart": "Lionel Messi",
       "rule_id": "bvr_matrunasa_precise",
@@ -725,6 +720,16 @@
         "matrunasa_yoga_199"
       ]
     },
+    {
+      "chart": "Lionel Messi",
+      "rule_id": "bvr_kapata_yoga",
+      "rule_name": "Kapata Yoga",
+      "pyjhora_names": [
+        "kapata_yoga_202",
+        "kapata_yoga_203",
+        "kapata_yoga_204"
+      ]
+    },
     {
       "chart": "Lionel Messi",
       "rule_id": "bvr_dharidhra_11_precise",
@@ -748,16 +753,6 @@
         "matrudeerghayur_yoga_197"
       ]
     },
-    {
-      "chart": "Lionel Messi",
-      "rule_id": "bvr_kapata_yoga",
-      "rule_name": "Kapata Yoga",
-      "pyjhora_names": [
-        "kapata_yoga_202",
-        "kapata_yoga_203",
-        "kapata_yoga_204"
-      ]
-    },
     {
       "chart": "Cristiano Ronaldo",
       "rule_id": "bvr_matru_sneha_yoga",
@@ -815,14 +810,6 @@
         "matrudeerghayur_yoga_197"
       ]
     },
-    {
-      "chart": "Dalai Lama",
-      "rule_id": "bvr_utthama_graha_yoga",
-      "rule_name": "Utthama Griha Yoga",
-      "pyjhora_names": [
-        "utthama_graha_yoga"
-      ]
-    },
     {
       "chart": "Dalai Lama",
       "rule_id": "brahma_yoga",
@@ -831,6 +818,14 @@
         "brahma_yoga"
       ]
     },
+    {
+      "chart": "Dalai Lama",
+      "rule_id": "bvr_utthama_graha_yoga",
+      "rule_name": "Utthama Griha Yoga",
+      "pyjhora_names": [
+        "utthama_graha_yoga"
+      ]
+    },
     {
       "chart": "Pope Francis",
       "rule_id": "bvr_raja_bhanga_yoga",
@@ -873,15 +868,6 @@
         "pittharoga_yoga"
       ]
     },
-    {
-      "chart": "Paramahansa Yogananda",
-      "rule_id": "bvr_dattha_puthra_yoga",
-      "rule_name": "Dattha Puthra Yoga",
-      "pyjhora_names": [
-        "dattha_puthra_yoga_222",
-        "dattha_puthra_yoga_223"
-      ]
-    },
     {
       "chart": "Paramahansa Yogananda",
       "rule_id": "bvr_matrunasa_precise",
@@ -898,6 +884,15 @@
       "pyjhora_names": [
         "bandhubhisthyaktha_yoga"
       ]
+    },
+    {
+      "chart": "Paramahansa Yogananda",
+      "rule_id": "bvr_dattha_puthra_yoga",
+      "rule_name": "Dattha Puthra Yoga",
+      "pyjhora_names": [
+        "dattha_puthra_yoga_222",
+        "dattha_puthra_yoga_223"
+      ]
     }
   ]
 }

references/yoga_rules.json

@@ -1,7 +1,7 @@
 {
   "schema_version": "1.0",
   "description": "Yoga 规则库 - 数据驱动架构 v1.0",
-  "total_rules": 475,
+  "total_rules": 476,
   "rules": [
     {
       "id": "raja_yoga",
@@ -9295,7 +9295,7 @@
       "category": "auspicious",
       "logic": {
         "type": "custom",
-        "expr": "\n# PyJHora/BVR 205-206 Nishkapata Yoga.\nnatural_benefics = {'Jupiter', 'Venus'}\nbenefic_signs = {'Taurus', 'Gemini', 'Cancer', 'Virgo', 'Libra', 'Sagittarius', 'Pisces'}\nplanets_in_4 = occupants(4)\nhas_benefic = any(p in natural_benefics for p in planets_in_4)\nhas_strong_planet = any(exalted(p) or own(p) or moola(p) for p in planets_in_4)\nfourth_benefic_sign = house_sign(4) in benefic_signs\ny205 = has_benefic or has_strong_planet or fourth_benefic_sign\nl1 = lord(1)\ny206 = False\nif l1 in ctx.planets and house_of(l1) == 4:\n    l1_with_benefic = any(p != l1 and same_house(l1, p) for p in natural_benefics if p in ctx.planets)\n    l1_aspected_benefic = any(aspect(p, l1) for p in natural_benefics if p in ctx.planets and p != l1)\n    y206 = l1_with_benefic or l1_aspected_benefic\ny205 or y206 or vaiseshikamsa_score(lord(1)) >= 15\n",
+        "expr": "\n# PyJHora/BVR 205-206 Nishkapata Yoga.\nnatural_benefics = {'Jupiter', 'Venus'}\nbenefic_signs = {'Taurus', 'Gemini', 'Cancer', 'Virgo', 'Libra', 'Sagittarius', 'Pisces'}\nplanets_in_4 = occupants(4)\nhas_benefic = any(p in natural_benefics for p in planets_in_4)\nhas_strong_planet = any(exalted(p) or own(p) or moola(p) for p in planets_in_4)\nfourth_benefic_sign = house_sign(4) in benefic_signs\ny205 = has_benefic or has_strong_planet or fourth_benefic_sign\nl1 = lord(1)\ny206 = False\nif l1 in ctx.planets and house_of(l1) == 4:\n    l1_with_benefic = any(p != l1 and same_house(l1, p) for p in natural_benefics if p in ctx.planets)\n    l1_aspected_benefic = any(aspect(p, l1) for p in natural_benefics if p in ctx.planets and p != l1)\n    y206 = l1_with_benefic or l1_aspected_benefic\ny205 or y206 or vaiseshikamsa_score(lord(1)) >= 16\n",
         "combo_template": "第4宫有天然吉星/强星/吉性星座，或上升主入4宫且受吉星影响"
       },
       "effects": [
@@ -13634,5 +13634,5 @@
       "source_reference": "BVR-170: Malefics in 2nd + 2nd lord weak"
     }
   ],
-  "total_enabled_rules": 381
-}
+  "total_enabled_rules": 405
+}

scripts/ashtottari_dasha.py

@@ -174,17 +174,26 @@ def calculate_ashtottari_dasha(birth_info: dict) -> dict:
 
     major_periods = _build_major_periods(start_lord_idx, birth_dt)
 
-    # Determine current period
+    # Determine current period. Major periods repeat every 108 years; older natives
+    # should still return a current period instead of None after the first cycle.
     now = datetime.now()
     current_period = None
+    age_years = max((now - birth_dt).days / 365.25, 0)
+    current_in_cycle = age_years % TOTAL_CYCLE
+    cumulative = 0.0
     for p in major_periods:
-        p_start = datetime.fromisoformat(p["start_date"])
-        p_end = datetime.fromisoformat(p["end_date"])
-        if p_start <= now < p_end:
+        years = p["years"]
+        if cumulative <= current_in_cycle < cumulative + years:
+            cycle_start = birth_dt + timedelta(days=(age_years - current_in_cycle + cumulative) * 365.25)
+            cycle_end = cycle_start + timedelta(days=years * 365.25)
             current_period = p.copy()
-            current_period["elapsed_years"] = (now - p_start).days / 365.25
-            current_period["remaining_years"] = (p_end - now).days / 365.25
+            current_period["start_date"] = cycle_start.isoformat()
+            current_period["end_date"] = cycle_end.isoformat()
+            current_period["elapsed_years"] = (now - cycle_start).days / 365.25
+            current_period["remaining_years"] = (cycle_end - now).days / 365.25
+            current_period["cycle_number"] = int(age_years // TOTAL_CYCLE) + 1
             break
+        cumulative += years
 
     return {
         "applicable": True,

scripts/jyotish_engine.py

@@ -2506,9 +2506,9 @@ def _calc_transit_multi_reference(planets, asc_idx, asc_deg, planet_lons, transi
 
 
 # ============================================================================
-# Dasa Convergence 三系统交叉验证（v4.5.0 P1补齐）
+# Dasa Convergence 多系统交叉验证（v6.1.6）
 # 基于 dasa-convergence-methodology.md
-# 三系统：Vimshottari + Chara Dasha + Yogini
+# 系统：Vimshottari + Chara Dasha + Yogini + Ashtottari + Kalachakra
 # ============================================================================
 # Yogini Dasha 常量
 YOGINI_ORDER = ['Mangala', 'Pingala', 'Dhanya', 'Bhramari', 'Bhadrika', 'Ulka', 'Siddha', 'Sankata']
@@ -2589,10 +2589,11 @@ def _calc_yogini_dasha(moon_lon, birthdate_str):
     }
 
 
-def _calc_dasa_convergence(dasha_result, chara_dasha_result, yogini_result, planet_lons, asc_idx):
+def _calc_dasa_convergence(dasha_result, chara_dasha_result, yogini_result, planet_lons, asc_idx, ashtottari_result=None, kalachakra_result=None):
     """
-    ⭐ v4.5.0: Dasa Convergence 三系统交叉验证
-    Vimshottari + Chara Dasha + Yogini 三系统同时激活同一生活领域时，概率大幅提升
+    ⭐ v6.1.6: Dasa Convergence 多系统交叉验证
+    Vimshottari + Chara Dasha + Yogini + Ashtottari + Kalachakra 同时激活同一生活领域时，概率大幅提升。
+    Chara Dasha 当前仍按 skill 规范降级为 partial，只作为低权重辅助。
     """
     # 提取各系统当前周期
     convergence_data = {'systems': {}}
@@ -2628,11 +2629,33 @@ def _calc_dasa_convergence(dasha_result, chara_dasha_result, yogini_result, plan
 
     # 系统3: Yogini
     if isinstance(yogini_result, dict):
-        cur_yog = yogini_result.get('current_yogini', {})
+        cur_yog = yogini_result.get('current_yogini') or yogini_result.get('current') or {}
         convergence_data['systems']['yogini'] = {
             'yogini': cur_yog.get('yogini') if isinstance(cur_yog, dict) else None,
-            'years': cur_yog.get('full_years') if isinstance(cur_yog, dict) else None,
-            'basis': 'Nakshatra (8-goddess cycle)',
+            'planet': cur_yog.get('planet') if isinstance(cur_yog, dict) else None,
+            'years': cur_yog.get('full_years', cur_yog.get('years')) if isinstance(cur_yog, dict) else None,
+            'basis': 'Nakshatra/Lagna 36-year cycle',
+        }
+
+    # 系统4: Ashtottari Dasha（条件性）
+    if isinstance(ashtottari_result, dict):
+        cur_ash = ashtottari_result.get('current') or {}
+        convergence_data['systems']['ashtottari'] = {
+            'applicable': ashtottari_result.get('applicable', True),
+            'planet': cur_ash.get('planet') if isinstance(cur_ash, dict) else None,
+            'years': cur_ash.get('years') if isinstance(cur_ash, dict) else None,
+            'basis': 'Conditional Nakshatra/Paksha 108-year cycle',
+        }
+
+    # 系统5: Kalachakra Dasha
+    if isinstance(kalachakra_result, dict):
+        cur_kal = kalachakra_result.get('current') or {}
+        convergence_data['systems']['kalachakra'] = {
+            'mode': kalachakra_result.get('mode'),
+            'lord': cur_kal.get('lord') if isinstance(cur_kal, dict) else None,
+            'rashi': cur_kal.get('rashi') if isinstance(cur_kal, dict) else None,
+            'years': cur_kal.get('years') if isinstance(cur_kal, dict) else None,
+            'basis': 'Moon Nakshatra Pada / Rashi-year cycle',
         }
 
     # 宫位主题映射
@@ -2691,6 +2714,73 @@ def _calc_dasa_convergence(dasha_result, chara_dasha_result, yogini_result, plan
                         'reason': f'Chara大运星座{cd_sign}是{house}宫',
                     })
 
+        # Yogini / Ashtottari: 当前行星是否掌管或落入该宫
+        for system_key, system_label, planet_key in [
+            ('yogini', 'Yogini', 'planet'),
+            ('ashtottari', 'Ashtottari', 'planet'),
+        ]:
+            sys_data = convergence_data['systems'].get(system_key, {})
+            planet = sys_data.get(planet_key)
+            if not planet or not isinstance(planet, str):
+                continue
+            target_sign_idx = (asc_idx + house - 1) % 12
+            target_sign = SIGNS[target_sign_idx]
+            target_lord = SIGN_LORDS.get(target_sign, '')
+            if planet == target_lord:
+                activations.append({
+                    'system': system_label,
+                    'level': 'maha',
+                    'planet': planet,
+                    'reason': f'{system_label}当前主星{planet}是{house}宫({target_sign})的宫主星',
+                })
+            if planet in planet_lons:
+                p_sign_idx = int(planet_lons.get(planet, 0) / 30) % 12
+                p_house = ((p_sign_idx - asc_idx) % 12) + 1
+                if p_house == house:
+                    activations.append({
+                        'system': system_label,
+                        'level': 'maha',
+                        'planet': planet,
+                        'reason': f'{system_label}当前主星{planet}落在{house}宫',
+                    })
+
+        # Kalachakra: 当前 Rashi 是否关联该宫，当前 lord 是否掌管或落入该宫
+        kal = convergence_data['systems'].get('kalachakra', {})
+        if kal:
+            kal_rashi = kal.get('rashi')
+            if kal_rashi in SIGNS:
+                kal_sign_idx = SIGNS.index(kal_rashi)
+                kal_house_from_asc = ((kal_sign_idx - asc_idx) % 12) + 1
+                if kal_house_from_asc == house:
+                    activations.append({
+                        'system': 'Kalachakra',
+                        'level': 'maha_rashi',
+                        'sign': kal_rashi,
+                        'reason': f'Kalachakra当前推运星座{kal_rashi}是{house}宫',
+                    })
+            kal_lord = kal.get('lord')
+            if kal_lord and isinstance(kal_lord, str):
+                target_sign_idx = (asc_idx + house - 1) % 12
+                target_sign = SIGNS[target_sign_idx]
+                target_lord = SIGN_LORDS.get(target_sign, '')
+                if kal_lord == target_lord:
+                    activations.append({
+                        'system': 'Kalachakra',
+                        'level': 'maha_lord',
+                        'planet': kal_lord,
+                        'reason': f'Kalachakra当前主星{kal_lord}是{house}宫({target_sign})的宫主星',
+                    })
+                if kal_lord in planet_lons:
+                    p_sign_idx = int(planet_lons.get(kal_lord, 0) / 30) % 12
+                    p_house = ((p_sign_idx - asc_idx) % 12) + 1
+                    if p_house == house:
+                        activations.append({
+                            'system': 'Kalachakra',
+                            'level': 'maha_lord',
+                            'planet': kal_lord,
+                            'reason': f'Kalachakra当前主星{kal_lord}落在{house}宫',
+                        })
+
         if activations:
             domain_activations[domain] = {
                 'house': house,
@@ -2701,7 +2791,11 @@ def _calc_dasa_convergence(dasha_result, chara_dasha_result, yogini_result, plan
     # 收敛等级评估
     for domain, info in domain_activations.items():
         sc = info['system_count']
-        if sc >= 3:
+        if sc >= 4:
+            info['convergence_level'] = 'L5'
+            info['probability'] = '85-92%'
+            info['interpretation'] = '四个及以上推运系统同时激活，顶级收敛信号'
+        elif sc >= 3:
             info['convergence_level'] = 'L4'
             info['probability'] = '75-85%'
             info['interpretation'] = '三系统同时激活，极强信号'
@@ -2721,7 +2815,7 @@ def _calc_dasa_convergence(dasha_result, chara_dasha_result, yogini_result, plan
         'systems_summary': convergence_data['systems'],
         'domain_activations': domain_activations,
         '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。',
+        'protocol': 'v6.1.6 Dasa Convergence 多系统交叉验证。收敛等级: L1(单系统)→L3(双系统)→L4(三系统)→L5(四个及以上系统)。Chara Dasha 当前为 partial，所有预测仍必须由 Vimshottari/Transit/Varga 等独立层确认。',
     }
 
 
@@ -3194,36 +3288,61 @@ def cmd_full_reading(args):
 
     try:
         # Pancha Pakshi（五鸟系统，需要出生 Nakshatra）
-        # 先尝试从 nakshatra_advanced 获取出生 Nakshatra
-        nakshatra_num = None
-        if 'moon_nakshatra' in dir() or 'moon_nak' in locals():
-            pass  # 动态获取
-        # 从 planets 数据推算 Nakshatra（Moon 的度数为基准）
+        # v6.1.6: 对齐 pancha_pakshi.py 现有公共接口 get_pancha_pakshi_schedule()
         moon_deg = planet_lons.get('Moon', 0)
-        nak_num = int(moon_deg / 13.3333333) + 1
+        nak_num = int(moon_deg / (360.0 / 27)) + 1
         if nak_num > 27:
             nak_num = 27
-        from pancha_pakshi import calc_pakshi_full_analysis
-        pk_result = calc_pakshi_full_analysis(nak_num, target_weekday=0, target_period=0)
+        nak_name = NAKSHATRA_LIST[nak_num - 1][0]
+        tithi_number = int(((moon_deg - planet_lons.get('Sun', 0)) % 360) / 12) + 1
+        paksha = 'shukla' if 1 <= tithi_number <= 15 else 'krishna'
+        from pancha_pakshi import get_pancha_pakshi_schedule
+        pk_result = get_pancha_pakshi_schedule(
+            birth_nakshatra=nak_name,
+            paksha=paksha,
+            date=f"{args.year}-{args.month:02d}-{args.day:02d}",
+        )
+        pk_result['input_context'] = {
+            'moon_nakshatra_index': nak_num - 1,
+            'moon_nakshatra': nak_name,
+            'tithi_number': tithi_number,
+            'paksha': paksha,
+        }
         report['modules']['pancha_pakshi'] = pk_result
     except Exception as e:
         report['errors'].append(f"pancha-pakshi: {e}")
 
     try:
         # Rashi Tulya Navamsa（D1 与 D9 同宫对比分析）
-        from rashi_tulya_navamsa import analyze_rashi_tulya_navamsa, rashi_tulya_navamsa_summary
+        # v6.1.6: 对齐 rashi_tulya_navamsa.py 现有公共接口 analyze_rtn(chart_data)
+        from rashi_tulya_navamsa import analyze_rtn
         varga_full = report['modules'].get('varga_full', {})
         d9_data = varga_full.get('D9_Navamsa', {})
-        if d9_data and d9_data.get('planets') and d9_data.get('houses'):
-            rt_result = analyze_rashi_tulya_navamsa(
-                planets, houses,
-                d9_data['planets'], d9_data['houses']
-            )
-            rt_summary = rashi_tulya_navamsa_summary(rt_result)
-            report['modules']['rashi_tulya_navamsa'] = {
-                'analysis': rt_result,
-                'summary': rt_summary
-            }
+        if d9_data:
+            d9_planets = d9_data.get('planets') if isinstance(d9_data, dict) else None
+            if not d9_planets and isinstance(d9_data, dict):
+                d9_planets = {
+                    pn: pd for pn, pd in d9_data.items()
+                    if isinstance(pd, dict) and pn not in ('_meta', 'Ascendant') and 'sign' in pd
+                }
+            if d9_planets:
+                rt_chart = {
+                    'ascendant': chart.get('ascendant', {}),
+                    'planets': planets,
+                    'context': {'navamsa_planets': d9_planets},
+                }
+                rt_result = analyze_rtn(rt_chart)
+                report['modules']['rashi_tulya_navamsa'] = {
+                    'analysis': rt_result,
+                    'summary': {
+                        'strength_score': rt_result.get('strength_score'),
+                        'weakness_score': rt_result.get('weakness_score'),
+                        'exalted_cancelled_count': len(rt_result.get('exalted_cancelled', [])),
+                        'debilitated_cancelled_count': len(rt_result.get('debilitated_cancelled', [])),
+                    },
+                }
+            else:
+                report['modules']['rashi_tulya_navamsa'] = {'note': 'D9 planet data incomplete, skip Rashi Tulya Navamsa'}
         else:
             report['modules']['rashi_tulya_navamsa'] = {'note': 'D9 data incomplete, skip Rashi Tulya Navamsa'}
     except Exception as e:
@@ -3585,15 +3704,56 @@ def cmd_full_reading(args):
     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) ──
+    # ── Step 18: Dasa Convergence 多系统交叉验证 (v6.1.6) ──
     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)
+        moon_lon = planet_lons.get('Moon', 0)
+        moon_nakshatra_index = int(moon_lon / (360 / 27)) % 27
+        moon_pada = int((moon_lon % (360 / 27)) / (360 / 108)) + 1
+        tithi_number = int(((moon_lon - planet_lons.get('Sun', 0)) % 360) / 12) + 1
+        birth_info_for_alt_dasha = {
+            'birth_datetime': datetime(args.year, args.month, args.day, args.hour, args.minute),
+            'moon_nakshatra_index': moon_nakshatra_index,
+            'moon_pada': moon_pada,
+            'is_shukla_paksha': 1 <= tithi_number <= 15,
+            'lagna_rashi_index': asc_idx,
+        }
+
+        try:
+            from yogini_dasha import calculate_yogini_dasha
+            yogini_data = calculate_yogini_dasha(birth_info_for_alt_dasha)
+            report['modules']['yogini_dasha'] = yogini_data
+        except Exception as alt_e:
+            yogini_data = {'error': str(alt_e)}
+            report['modules']['yogini_dasha'] = yogini_data
+
+        try:
+            from ashtottari_dasha import calculate_ashtottari_dasha
+            ashtottari_data = calculate_ashtottari_dasha(birth_info_for_alt_dasha)
+            report['modules']['ashtottari_dasha'] = ashtottari_data
+        except Exception as alt_e:
+            ashtottari_data = {'error': str(alt_e)}
+            report['modules']['ashtottari_dasha'] = ashtottari_data
+
+        try:
+            from kalachakra_dasha import calculate_kalachakra_dasha
+            kalachakra_data = calculate_kalachakra_dasha(birth_info_for_alt_dasha)
+            report['modules']['kalachakra_dasha'] = kalachakra_data
+        except Exception as alt_e:
+            kalachakra_data = {'error': str(alt_e)}
+            report['modules']['kalachakra_dasha'] = kalachakra_data
+
+        convergence = _calc_dasa_convergence(
+            dasha_data,
+            chara_dasha_data,
+            yogini_data,
+            planet_lons,
+            asc_idx,
+            ashtottari_result=ashtottari_data,
+            kalachakra_result=kalachakra_data,
+        )
         report['modules']['dasa_convergence'] = convergence
     except Exception as e:
         report['errors'].append(f"dasa-convergence: {e}")
@@ -3651,7 +3811,7 @@ 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': '⭐ 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。',
+        'next_step': '⭐ v6.1.6: full-reading 已输出 transit_multi_reference(四参考点) + dasa_convergence(五系统交叉) + yogini_dasha + ashtottari_dasha + kalachakra_dasha + d9_navamsa_expanded。AI必须使用四参考点分析Transit，Dasa预测必须标注多系统收敛等级。',
     }
 
     return report

scripts/kalachakra_dasha.py

@@ -217,17 +217,26 @@ def calculate_kalachakra_dasha(birth_info: dict) -> dict:
     starting_lord = major_periods[0]["lord"] if major_periods else None
     starting_rashi = major_periods[0]["rashi"] if major_periods else None
 
-    # Determine current period
+    # Determine current period. Kalachakra cycles through the generated Rashi-year
+    # sequence repeatedly; older natives should still return a current period.
     now = datetime.now()
     current_period = None
+    age_years = max((now - birth_dt).days / 365.25, 0)
+    current_in_cycle = age_years % total_cycle if total_cycle else age_years
+    cumulative = 0.0
     for p in major_periods:
-        p_start = datetime.fromisoformat(p["start_date"])
-        p_end = datetime.fromisoformat(p["end_date"])
-        if p_start <= now < p_end:
+        years = p["years"]
+        if cumulative <= current_in_cycle < cumulative + years:
+            cycle_start = birth_dt + timedelta(days=(age_years - current_in_cycle + cumulative) * 365.25)
+            cycle_end = cycle_start + timedelta(days=years * 365.25)
             current_period = p.copy()
-            current_period["elapsed_years"] = (now - p_start).days / 365.25
-            current_period["remaining_years"] = (p_end - now).days / 365.25
+            current_period["start_date"] = cycle_start.isoformat()
+            current_period["end_date"] = cycle_end.isoformat()
+            current_period["elapsed_years"] = (now - cycle_start).days / 365.25
+            current_period["remaining_years"] = (cycle_end - now).days / 365.25
+            current_period["cycle_number"] = int(age_years // total_cycle) + 1 if total_cycle else 1
             break
+        cumulative += years
 
     return {
         "mode": mode,

scripts/yogini_dasha.py

@@ -136,17 +136,26 @@ def calculate_yogini_dasha(birth_info: dict) -> dict:
 
     major_periods = _build_major_periods(start_idx, birth_dt)
 
-    # Determine current period
+    # Determine current period. Yogini repeats every 36 years; older natives
+    # should still return a current period instead of None after the first cycle.
     now = datetime.now()
     current_period = None
+    age_years = max((now - birth_dt).days / 365.25, 0)
+    current_in_cycle = age_years % TOTAL_CYCLE
+    cumulative = 0.0
     for p in major_periods:
-        p_start = datetime.fromisoformat(p["start_date"])
-        p_end = datetime.fromisoformat(p["end_date"])
-        if p_start <= now < p_end:
+        years = p["years"]
+        if cumulative <= current_in_cycle < cumulative + years:
+            cycle_start = birth_dt + timedelta(days=(age_years - current_in_cycle + cumulative) * 365.25)
+            cycle_end = cycle_start + timedelta(days=years * 365.25)
             current_period = p.copy()
-            current_period["elapsed_years"] = (now - p_start).days / 365.25
-            current_period["remaining_years"] = (p_end - now).days / 365.25
+            current_period["start_date"] = cycle_start.isoformat()
+            current_period["end_date"] = cycle_end.isoformat()
+            current_period["elapsed_years"] = (now - cycle_start).days / 365.25
+            current_period["remaining_years"] = (cycle_end - now).days / 365.25
+            current_period["cycle_number"] = int(age_years // TOTAL_CYCLE) + 1
             break
+        cumulative += years
 
     return {
         "major": major_periods,