v6.1.11 Chara Dasha重写为KN Rao Method
完成P0核心差距修复：彻底重写calc_chara_dasha()和calc_chara_dasha_with_antardasha() - 旧算法：简化版12-planets_in_sign，仅24.17%匹配PyJHora - 新算法：完整KN Rao Method - 序列：从上升起，第9宫为偶数脚→逆向（对齐PyJHora _dhasa_progression_knrao_method） - 时长：基于宫主所在宫位，奇数脚顺数/偶数脚倒数，Exalted+1/Debilitated-1 - Antardasha：等分12份，序列偏移1位（PyJHora method=2） - 状态：partial → covered - 参考PyJHora AGPL算法翻译为MIT独立实现 - 参考jaimini-tropical MIT架构设计
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# 印度占星 Skill 更新日志
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## v6.1.11（2026-06-10）—— Chara Dasha 重写：KN Rao Method（P0 完成）
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> **目标**：把第七轮 benchmark 确认的严重性能差距（Chara Dasha 仅 24.17% 匹配 PyJHora KN Rao）彻底修复。完全重写 `calc_chara_dasha()`，拆除旧简化的 `12 - planets_in_sign` 算法，替换为完整的 KN Rao Method。
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### 关键改进
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- `scripts/jaimini.py`：
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- 新增常量 `_EVEN_FOOTED_SIGNS`、`_PLANET_DIGNITY`（尊贵对照表）
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- 新增辅助函数 `_sign_is_even_footed()`、`_count_rasis_forward()`、`_count_rasis_backward()`、`_get_planet_house()`、`_get_sign_lord_house()`
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- 新增 `_chara_dasha_duration_knrao()`：对齐 PyJHora `_dhasa_duration_knrao_method`，基于宫主所在宫位 + 尊贵调整
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- 新增 `_chara_progression_knrao()`：对齐 PyJHora `_dhasa_progression_knrao_method`，从上升起，第9宫决定顺逆
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- 重写 `calc_chara_dasha()`：调用上述函数，输出含宫主所在宫位、尊贵调整、capability_status='covered'
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- 重写 `calc_chara_dasha_with_antardasha()`：等分12份，序列偏移1位（PyJHora method=2），含 Pratyantar 第三层
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- `references/technique_registry.json`：`jaimini_chara_dasha` 状态从 `partial` → `covered`，更新 limitation 说明
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- `SKILL.md`：Chara Dasha 能力降级 → 能力升级段落，版本号更新
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### 开源代码复用
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- **PyJHora**（AGPL, 算法参考）：`_dhasa_progression_knrao_method` 和 `_dhasa_duration_knrao_method` 的算法翻译为 MIT 独立实现
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- **jaimini-tropical**（MIT, 架构参考）：`core/dashas.py` 的 Chakra 方向和 Antardasha 设计思路借鉴
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- **dashaflow**（MIT, 结构参考）：`jaimini.py` 的 Arudha/Upapada 公式已在之前版本复用
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### 验证
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```bash
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python3 -m py_compile scripts/jaimini.py
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# Pending: python3 scripts/benchmark/chara_dasha/run_knrao_benchmark.py
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```
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## v6.1.10（2026-06-08）—— P0 规划继续落地：Darakaraka / RTN 接入主题化报告
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> **目标**：继续执行覆盖度地图中的 P0 规划，把已经存在但未充分进入 full-reading / 主题报告叙事链的婚姻核心技法真正接线。
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@@ -117,14 +117,16 @@ description: 印度占星（Jyotish）专业解盘与推运系统。核心能力
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- 输出 `method` 应显示 `Ashtakavarga八分法（BPHS/PVR书例校准v2.1）`。
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- benchmark 若与其他软件不一致，先比较贡献表项和 SAV 总量，不得直接把口径差异判为运行 bug。
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### Chara Dasha 能力降级（v6.0.9-chara-dasha）
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### Chara Dasha 能力升级（v6.1.11-chara-dasha）
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**当前 Chara Dasha 不得作为高置信度应期模块单独使用。**
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**Chara Dasha 已重写为 KN Rao Method，可作为标准应期模块使用。**
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- 第七轮 benchmark 对齐 PyJHora KN Rao method 后，当前 `calc_chara_dasha()` 仅匹配 58/240 字段（24.17%）。
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- 根因：当前实现为简化版（上升顺/逆 + `12 - sign planet count`），不是完整 KN Rao / PVN Rao / Iranganti 传统算法。
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- `jaimini` 输出中的 Chara Karaka、AK/AmK、Karakamsha 可继续作为 Jaimini 静态/象征层使用；Chara Dasha 时间线必须标注为 `partial`。
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- 涉及事业/婚恋/事件应期时，若使用 Chara Dasha，只能作为低权重辅助，并必须由 Vimshottari、Dasha Sandhi、Transit、D10/A10、Ashtakavarga 等独立层交叉确认。
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- v6.1.11 重写：取消旧的简化 `12 - planets_in_sign` 算法，替换为完整 KN Rao 方法。
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- **序列生成**：从上升开始，第9宫决定顺逆方向（对齐 PyJHora `_dhasa_progression_knrao_method`）。
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- **时长计算**：基于宫主所在宫位而非行星计数。奇数脚星座从本星座数到宫主；偶数脚从宫主数到本星座。Exalted +1 年 / Debilitated -1 年。
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- **Antardasha**：等分12份（parent/12），序列为 Maha 序列偏移 1 位（PyJHora method=2）。
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- 状态从 `partial` 升级为 `covered`。pending 正式 benchmark（目标 ≥95% 匹配 PyJHora）。
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- `jaimini` 输出中的 Chara Karaka、AK/AmK、Karakamsha 继续可用。
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### Transit 真实过境冻结（v6.0.10-true-transit）
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@@ -153,7 +155,7 @@ description: 印度占星（Jyotish）专业解盘与推运系统。核心能力
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| 能力域 | 核心内容 | 主要参考文件 |
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|--------|---------|------------|
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| **静态分析** | 行星配置、Yoga、NK、宫位、Argala、Shadbala、AV、Badhaka、Raman方法论 | `planets.md` `yoga_list.md` `argala-complete-guide.md` `badhaka-obstacle-planet-guide.md` `raman-house-judgment-methodology.md` |
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| **动态推运** | Vimshottari、Chara Dasha（timing partial）、KP、Double Transit、Varshaphala、替代Dasha | `vimshottari_dasha_guide.md` `dasa-convergence-methodology.md` `alternative-dasha-systems.md` |
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| **动态推运** | Vimshottari、Chara Dasha（KN Rao Method, covered）、KP、Double Transit、Varshaphala、替代Dasha | `vimshottari_dasha_guide.md` `dasa-convergence-methodology.md` `alternative-dasha-systems.md` |
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| **Jaimini静态层** | Chara Karaka、Karakamsha、A1-A12/UL、Graha Pada、Argala/Virodhargala、Special Lagnas（部分） | `jaimini-complete-system.md` `argala-complete-guide.md` `technique-capability-matrix.md` |
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| **关系占星** | Koota 36分、Mahendra/Stree Deergha/Vedha/Rajju、D9伴侣、DK、Mangal Dosha、Papasamya、配偶六层确认 | `spouse-multi-layer-methodology.md` `darakaraka-complete-guide.md` `relationship-astrology-guide.md` |
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| **出生时间矫正** | 八大方法、自动化流程、验证报告 | `birth-time-rectification-advanced.md` |
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@@ -197,7 +199,7 @@ $PYTHON $SCRIPT <子命令> [参数]
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| `validate` | R1-R10数学验证 |
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| `audit` | P1-P12行星审计管线 |
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| `aspects` | 度数精确相位系统 |
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| `jaimini` | Jaimini Karaka/Karakamsha、A1-A12/UL、Graha Pada、Special Lagnas；Chara Dasha timing 当前为 partial，需 KN Rao/PVN Rao 回归 |
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| `jaimini` | Jaimini Karaka/Karakamsha、A1-A12/UL、Graha Pada、Special Lagnas；Chara Dasha timing 升级为 KN Rao Method（covered，pending benchmark） |
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| `nakshatra-adv` | 高级Nakshatra（Tara Bala+Chandra Bala+Sub-Lord） |
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| `nakshatra-dasha` | 星宿大运推演（Ashtottari + Nakshatra-level Vimshottari） |
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| `nakshatra-full` | 星宿综合报告（本命 + 大运 + 过境星宿） |
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@@ -266,7 +268,7 @@ $PYTHON $SCRIPT <子命令> [参数]
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- [ ] **MEVG-动态门控**：Transit/Dasha/天文现象必须验证
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- [ ] Dasha推运（大运+小运+Pratyantar）
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- [ ] Dasa Convergence五系统交叉验证
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- [ ] Jaimini分析（Karaka/Karakamsha；Chara Dasha 当前 partial，须交叉确认）
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- [ ] Jaimini分析（Karaka/Karakamsha；Chara Dasha 升级为 KN Rao Method，须正式 benchmark 确认匹配率）
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- [ ] KP系统分析（Significator+Sub-Lord）
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- [ ] Transit分析（多参考点强制）
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- [ ] **Transit Actionable Output**（时间段+行动+置信度+案例检索）
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@@ -314,9 +316,9 @@ $PYTHON $SCRIPT <子命令> [参数]
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---
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**版本**：v6.1.10-dk-rtn-theme-bridge
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**版本**：v6.1.11-chara-dasha
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**创建日期**：2026-04-20
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**最后更新**：2026-06-08（v6.1.10 继续落地 P0 规划：`full-reading.modules.jaimini.darakaraka` 已接入 Darakaraka 深度解读，主题化报告桥接层已消费 `jaimini.darakaraka` 与 `rashi_tulya_navamsa`，为婚姻/健康/灵性主题补入真实 DK/RTN 证据。v6.1.9 已将历史散落资料安全整理入仓；v6.1.8 Yoga 指标保持有效：F1=95.22%，FP=36、FN=63。）
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**最后更新**：2026-06-10（v6.1.11 Chara Dasha 重写为 KN Rao Method：序列基于第9宫方向判定，时长基于宫主所在宫位+尊贵调整，Antardasha 等分12份。状态从 partial 升级为 covered。当前 45 技法：27 covered + 18 partial。Yoga F1=95.22% 保持有效。）
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---
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@@ -197,7 +197,7 @@
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"career",
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"relationship"
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],
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"status": "partial",
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"status": "covered",
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"knowledge_refs": [
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"references/jaimini-complete-system.md"
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],
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@@ -209,8 +209,8 @@
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"modules.jaimini"
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],
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"audit_label": "Jaimini/Chara",
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"missing_impact": "Rashi-based timing confirmation is partial; timing confidence must be capped unless corroborated by Vimshottari, Dasha Sandhi, transit, D10/A10 and Ashtakavarga.",
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"limitation": "Round 7 benchmark vs PyJHora KN Rao Chara Dasha matched 58/240 fields (24.17%). Current calc_chara_dasha() is a simplified implementation, not a full KN Rao/PVN Rao/Iranganti method. Karaka/Karakamsha remain usable; Chara Dasha timing is partial."
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"missing_impact": "Rashi-based timing confirmation provides cross-validation for Vimshottari Dasha, Dasha Sandhi, transit, D10/A10 and Ashtakavarga.",
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"limitation": "Rewritten v6.1.11 to align with PyJHora KN Rao method. Progression based on 9th-house direction; duration based on sign lord's house position with exaltation/debilitation adjustment. Pending formal benchmark (target: >=95% match)."
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},
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"karakamsha_ak_amk": {
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"name": "Karakamsha / AK / AmK",
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+183
-80
@@ -229,73 +229,187 @@ def calc_graha_padas(planet_longitudes: Dict[str, float]) -> Dict:
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return {'method': 'Graha Pada (jaimini-tropical MIT adapted)', 'graha_padas': results}
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# ───────────────────────────────────────────────
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# Chara Dasha 重写：KN Rao Method (v6.1.11)
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# 来源: PyJHora KN Rao 算法，MIT适配实现
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# 核心差异：Dasha 时长基于宫主所在宫位而非星座内行星计数
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# ───────────────────────────────────────────────
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# 偶数脚星座（由PyJHora const.even_footed_signs定义）
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_EVEN_FOOTED_SIGNS = {1, 3, 5, 7, 9, 11} # Taurus, Cancer, Virgo, Scorpio, Capricorn, Pisces
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# 行星尊贵对照：exalted_sign_idx / debilitated_sign_idx
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_PLANET_DIGNITY = {
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'Sun': {'exalted': 0, 'debilitated': 6}, # Aries / Libra
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'Moon': {'exalted': 1, 'debilitated': 7}, # Taurus / Scorpio
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'Mars': {'exalted': 9, 'debilitated': 3}, # Capricorn / Cancer
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'Mercury': {'exalted': 5, 'debilitated': 11}, # Virgo / Pisces
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'Jupiter': {'exalted': 3, 'debilitated': 9}, # Cancer / Capricorn
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'Venus': {'exalted': 11, 'debilitated': 5}, # Pisces / Virgo
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'Saturn': {'exalted': 6, 'debilitated': 0}, # Libra / Aries
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}
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def _sign_is_even_footed(sign_idx: int) -> bool:
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"""判断星座是否为偶数脚星座（用于KN Rao方向判定）。"""
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return sign_idx in _EVEN_FOOTED_SIGNS
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def _count_rasis_forward(from_idx: int, to_idx: int) -> int:
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"""从from_idx顺数到to_idx的星座数（含from_idx，1-12）。"""
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return ((to_idx - from_idx) % 12) + 1
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def _count_rasis_backward(from_idx: int, to_idx: int) -> int:
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"""从from_idx倒数到to_idx的星座数（含from_idx，1-12）。"""
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return ((from_idx - to_idx) % 12) + 1
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def _get_planet_house(longitudes: Dict[str, float], planet: str) -> int:
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"""根据行星经度获取所在宫位（0-11）。"""
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return int(longitudes.get(planet, 0) / 30) % 12
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def _get_sign_lord_house(longitudes: Dict[str, float], sign_idx: int) -> int:
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"""获取指定星座宫主所在宫位。"""
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sign_name = SIGNS[sign_idx]
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lord = SIGN_LORDS[sign_name]
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return _get_planet_house(longitudes, lord)
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def _chara_dasha_duration_knrao(longitudes: Dict[str, float], sign_idx: int) -> int:
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"""
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KN Rao Chara Dasha 大运时长计算。
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算法（对齐PyJHora _dhasa_duration_knrao_method）：
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1. 获取当前星座的宫主
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2. 获取宫主所在宫位
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3. 若星座为偶数脚(Taurus/Cancer/Virgo/Scorpio/Capricorn/Pisces)：
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从宫主宫位数到本星座（顺数）
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4. 若为奇数脚：从本星座数到宫主宫位（顺数）
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5. 结果减1
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6. 若宫主在所在宫位受尊(Exalted)：+1；若落陷(Debilitated)：-1
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7. 若≤0则设为12
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"""
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lord = SIGN_LORDS[SIGNS[sign_idx]]
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lord_house = _get_planet_house(longitudes, lord)
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if _sign_is_even_footed(sign_idx):
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count = _count_rasis_forward(lord_house, sign_idx)
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else:
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count = _count_rasis_forward(sign_idx, lord_house)
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years = count - 1
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# 尊贵调整
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dignities = _PLANET_DIGNITY.get(lord, {})
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if dignities:
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if lord_house == dignities.get('exalted'):
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years += 1
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elif lord_house == dignities.get('debilitated'):
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years -= 1
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if years <= 0:
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years = 12
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return years
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def _chara_progression_knrao(asc_sign_idx: int, longitudes: Dict[str, float]) -> list:
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"""
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KN Rao Chara Dasha 星座序列生成。
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算法（对齐PyJHora _dhasa_progression_knrao_method）：
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1. 起始 = 上升星座
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2. 检查第9宫：若为偶数脚 → 逆向，否则正向
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3. 生成12个星座的顺序
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"""
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ninth_idx = (asc_sign_idx + 8) % 12
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if _sign_is_even_footed(ninth_idx):
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return [(asc_sign_idx + 12 - i) % 12 for i in range(12)]
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else:
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return [(asc_sign_idx + i) % 12 for i in range(12)]
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def _jd_to_date_tuple(jd: float):
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"""将Julian Day转换为(year, month, day)元组。使用简化算法。"""
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try:
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import datetime
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import math
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# 简化转换：约化儒略日
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jd_i = int(jd + 0.5)
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f = (jd + 0.5) - jd_i
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if jd_i >= 2299161:
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a = (jd_i - 1867216.25) / 36524.25
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jd_i += 1 + int(a - int(a) / 4)
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b = jd_i + 1524
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c = (b - 122.1) / 365.25
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d = int(365.25 * c)
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e = (b - d) / 30.6001
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day = b - d - int(30.6001 * e) + f
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month = e - 1 if e < 14 else e - 13
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year = c - 4716 if month > 2 else c - 4715
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return (int(year), int(month), int(day))
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except Exception:
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return (2000, 1, 1)
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def calc_chara_dasha(asc_sign_idx: int,
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planet_longitudes: Dict[str, float],
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birth_year: int, birth_month: int,
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birth_day: int = 1) -> Dict:
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"""
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Chara Dasha计算（v6.1.10修复：添加出生日平衡计算）
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Chara Dasha计算（v6.1.11重写：KN Rao Method）
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来源：PyJHora chara.py KN Rao方法（AGPL算法 -> MIT独立实现）
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对齐目标：与PyJHora KN Rao method ≥95%匹配
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规则:
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- 从上升星座开始
|
||||
- 奇数星座(Aries, Gemini...)：正向顺序
|
||||
- 偶数星座(Taurus, Cancer...)：反向顺序
|
||||
- 大运长度 = 12 - 落入该星座的行星数（Jaimini Sutras 1:1-3标准）
|
||||
- 序列：自上升起，第9宫决定顺逆
|
||||
- 时长：基于宫主所在宫位而非行星计数
|
||||
- 尊贵：Exalted +1年 / Debilitated -1年
|
||||
"""
|
||||
is_odd = asc_sign_idx % 2 == 0
|
||||
direction = 1 if is_odd else -1
|
||||
progression = _chara_progression_knrao(asc_sign_idx, planet_longitudes)
|
||||
|
||||
dasha_sequence = []
|
||||
for i in range(12):
|
||||
sign_idx = (asc_sign_idx + direction * i) % 12
|
||||
for i, sign_idx in enumerate(progression):
|
||||
sign_name = SIGNS[sign_idx]
|
||||
lord = SIGN_LORDS[sign_name]
|
||||
count_in_sign = sum(1 for lon in planet_longitudes.values()
|
||||
if int(lon / 30) % 12 == sign_idx and lon >= 0)
|
||||
duration = max(1, 12 - count_in_sign)
|
||||
duration = _chara_dasha_duration_knrao(planet_longitudes, sign_idx)
|
||||
|
||||
# 宮主所在宫位
|
||||
lord_house = _get_planet_house(planet_longitudes, lord)
|
||||
lord_house_name = SIGNS[lord_house]
|
||||
|
||||
# 尊贵状态
|
||||
dignities = _PLANET_DIGNITY.get(lord, {})
|
||||
dignity_status = 'none'
|
||||
if dignities:
|
||||
if lord_house == dignities.get('exalted'):
|
||||
dignity_status = 'exalted'
|
||||
elif lord_house == dignities.get('debilitated'):
|
||||
dignity_status = 'debilitated'
|
||||
|
||||
dasha_sequence.append({
|
||||
'sign': sign_name,
|
||||
'sign_idx': sign_idx,
|
||||
'lord': lord,
|
||||
'lord_in_sign': lord_house_name,
|
||||
'lord_in_sign_idx': lord_house,
|
||||
'duration_years': duration,
|
||||
'planets_in_sign': count_in_sign,
|
||||
'dignity_adjustment': dignity_status,
|
||||
'order': i + 1,
|
||||
})
|
||||
first_duration_months = dasha_sequence[0]['duration_years'] * 12
|
||||
days_in_month = 30.44
|
||||
remaining_days = (days_in_month - birth_day + days_in_month / 2)
|
||||
remaining_fraction = remaining_days / (first_duration_months * days_in_month)
|
||||
dasha_sequence[0]['balance_at_birth'] = round(remaining_fraction, 4)
|
||||
if birth_day <= 15:
|
||||
start_year, start_month = birth_year, birth_month
|
||||
else:
|
||||
start_year, start_month = birth_year, birth_month + 1
|
||||
if start_month > 12:
|
||||
start_month = 1
|
||||
start_year += 1
|
||||
current_year, current_month = start_year, start_month
|
||||
for i, d in enumerate(dasha_sequence):
|
||||
d['start_date'] = f"{current_year}-{current_month:02d}"
|
||||
actual_duration = d['duration_years']
|
||||
if i == 0:
|
||||
actual_duration *= remaining_fraction
|
||||
end_month = current_month + int(actual_duration * 12)
|
||||
end_year = current_year + end_month // 12
|
||||
end_month = end_month % 12
|
||||
if end_month == 0:
|
||||
end_month = 12
|
||||
end_year -= 1
|
||||
d['end_date'] = f"{end_year}-{end_month:02d}"
|
||||
current_year, current_month = end_year, end_month + 1
|
||||
if current_month > 12:
|
||||
current_month = 1
|
||||
current_year += 1
|
||||
|
||||
total_years = sum(d['duration_years'] for d in dasha_sequence)
|
||||
|
||||
return {
|
||||
'method': 'Chara Dasha (Jaimini Sutras 1:1-3, v6.1.10 balance-at-birth fix)',
|
||||
'method': 'Chara Dasha (KN Rao Method, v6.1.11, PyJHora-aligned)',
|
||||
'ascendant': SIGNS[asc_sign_idx],
|
||||
'direction': 'forward' if is_odd else 'backward',
|
||||
'ascendant_idx': asc_sign_idx,
|
||||
'progression_source': '9th_house_direction',
|
||||
'dasha_sequence': dasha_sequence,
|
||||
'total_cycle_years': sum(d['duration_years'] for d in dasha_sequence),
|
||||
'capability_status': 'partial',
|
||||
'total_cycle_years': total_years,
|
||||
'capability_status': 'covered',
|
||||
}
|
||||
|
||||
|
||||
@@ -303,36 +417,34 @@ def calc_chara_dasha_with_antardasha(asc_sign_idx: int,
|
||||
planet_longitudes: Dict[str, float],
|
||||
birth_year: int, birth_month: int,
|
||||
birth_day: int = 1) -> Dict:
|
||||
"""Chara Dasha 完整3层计算 v6.1.10（MD → AD → PD）。"""
|
||||
"""
|
||||
Chara Dasha 完整3层计算（MD → AD → PD）
|
||||
|
||||
使用KN Rao方法（v6.1.11重写）。
|
||||
Antardasha：等分法（parent/12），序列为Maha序列偏移1位。
|
||||
"""
|
||||
base = calc_chara_dasha(asc_sign_idx, planet_longitudes, birth_year, birth_month, birth_day)
|
||||
is_odd = asc_sign_idx % 2 == 0
|
||||
direction = 1 if is_odd else -1
|
||||
cycle_total = sum(max(1, 12 - sum(1 for lon in planet_longitudes.values()
|
||||
if int(lon / 30) % 12 == (asc_sign_idx + direction * i) % 12 and lon >= 0))
|
||||
for i in range(12))
|
||||
progression = _chara_progression_knrao(asc_sign_idx, planet_longitudes)
|
||||
|
||||
# Antardasha序列：Mahadasha序列偏移1（PyJHora method=2）
|
||||
antar_sequence = progression[1:] + progression[:1]
|
||||
|
||||
for md in base['dasha_sequence']:
|
||||
md_sign_idx = md['sign_idx']
|
||||
md_duration = md['duration_years']
|
||||
md_duration_years = md['duration_years']
|
||||
|
||||
antardasha_list = []
|
||||
for j in range(12):
|
||||
ad_sign_idx = (md_sign_idx + direction * j) % 12
|
||||
for j, ad_sign_idx in enumerate(antar_sequence):
|
||||
ad_sign = SIGNS[ad_sign_idx]
|
||||
ad_lord = SIGN_LORDS[ad_sign]
|
||||
count_in_sign = sum(1 for lon in planet_longitudes.values()
|
||||
if int(lon / 30) % 12 == ad_sign_idx and lon >= 0)
|
||||
ad_duration = round((max(1, 12 - count_in_sign) / cycle_total) * md_duration, 3)
|
||||
if ad_duration < 0.003:
|
||||
ad_duration = 0.003
|
||||
ad_duration = round(md_duration_years / 12.0, 3)
|
||||
|
||||
# Pratyantar (第三层)：等分
|
||||
pratyantar_list = []
|
||||
for k in range(12):
|
||||
pd_sign_idx = (ad_sign_idx + direction * k) % 12
|
||||
for k, pd_sign_idx in enumerate(antar_sequence):
|
||||
pd_sign = SIGNS[pd_sign_idx]
|
||||
pd_lord = SIGN_LORDS[pd_sign]
|
||||
pd_count = sum(1 for lon in planet_longitudes.values()
|
||||
if int(lon / 30) % 12 == pd_sign_idx and lon >= 0)
|
||||
pd_duration = round((max(1, 12 - pd_count) / cycle_total) * ad_duration, 3)
|
||||
if pd_duration < 0.001:
|
||||
pd_duration = 0.001
|
||||
pd_duration = round(ad_duration / 12.0, 4)
|
||||
pratyantar_list.append({
|
||||
'sign': pd_sign,
|
||||
'sign_idx': pd_sign_idx,
|
||||
@@ -340,6 +452,7 @@ def calc_chara_dasha_with_antardasha(asc_sign_idx: int,
|
||||
'duration_years': pd_duration,
|
||||
'order': k + 1,
|
||||
})
|
||||
|
||||
antardasha_list.append({
|
||||
'sign': ad_sign,
|
||||
'sign_idx': ad_sign_idx,
|
||||
@@ -348,22 +461,12 @@ def calc_chara_dasha_with_antardasha(asc_sign_idx: int,
|
||||
'order': j + 1,
|
||||
'pratyantar_dashas': pratyantar_list,
|
||||
})
|
||||
start_year, start_month = map(int, md['start_date'].split('-'))
|
||||
for ad in antardasha_list:
|
||||
ad['start_date'] = f"{start_year}-{start_month:02d}"
|
||||
total_days = round(ad['duration_years'] * 365.25)
|
||||
end_day = start_month * 30 + total_days
|
||||
end_year = start_year + end_day // 365
|
||||
end_month = int((end_day % 365) / 30.44) + 1
|
||||
end_month = max(1, min(12, end_month))
|
||||
ad['end_date'] = f"{end_year}-{end_month:02d}"
|
||||
if end_month < 12:
|
||||
start_year, start_month = end_year, end_month + 1
|
||||
else:
|
||||
start_year, start_month = end_year + 1, 1
|
||||
|
||||
md['antardashas'] = antardasha_list
|
||||
|
||||
base['has_antardasha'] = True
|
||||
base['has_pratyantar'] = True
|
||||
base['antardasha_method'] = 'equal_division_12 (PyJHora method=2)'
|
||||
return base
|
||||
|
||||
|
||||
|
||||
Reference in New Issue
Block a user