年运附表补上整宫、Tripataki 和特殊点公式轨迹。黄经沿用已算好的星盘，不改原有 Saham 数值。

Co-Authored-By: Grok (agent loop) Co-authored-by: Cursor <cursoragent@cursor.com>
2026-10-22 23:11:48 +08:00
parent 6b906f85c4
commit 9b2e6aa0b4
9 changed files with 560 additions and 23 deletions
@@ -166,9 +166,12 @@ SECTIONS: tuple[tuple[str, str], ...] = (
    ("Current Dasha Convergence", "当前多系统收敛"),
    ("Chara Dasha Period Durations", "Chara 大运时长"),
    ("Narayana Method Comparison", "Narayana 口径对照"),
+    ("Annual Return House Framework", "年运整宫框架"),
    ("Annual Return Calculation Contract", "年运返照计算约定"),
    ("Tajika Aspect and Yoga Candidates", "Tajika 相位与瑜伽候选"),
+    ("Tripataki Chakra Detail", "Tripataki 轮盘明细"),
    ("Annual Tajika Strength", "年度 Tajika 力量"),
+    ("Annual Saham Formula Trace", "年度特殊点公式轨迹"),
    ("Shadbala Subcomponent", "六维力量分项"),
    ("Shadbala Result", "六维力量结果"),
    ("House Components and Physical Coordinates", "宫位分量与坐标"),
@@ -202,6 +205,7 @@ SECTIONS: tuple[tuple[str, str], ...] = (
    ("Pancha Pakshi", "五鸟活动"),
    ("Natal Vivah Saham", "本命 Vivah Saham"),
    ("Natal Saham Formula Basis", "本命特殊点公式依据"),
+    ("Natal Saham Formula Trace", "本命特殊点公式轨迹"),
    ("Arudha / UL / A10", "Arudha、Upapada 与 A10"),
    ("Jaimini Calculation Details", "Jaimini 计算细节"),
    ("Graha Pada", "Graha Pada"),
@@ -225,10 +229,6 @@ SECTIONS: tuple[tuple[str, str], ...] = (
 )

 FORBIDDEN_TITLES = (
-    "Annual Return House Framework",
-    "Tripataki Chakra Detail",
-    "Annual Saham Formula Trace",
-    "Natal Saham Formula Trace",
    "Annual Chart Numeric Data",
    "Bhava Bala Relative Score Components",
    "Score Extremes",
@@ -850,6 +850,102 @@ def _narayana(packet: dict, language: str) -> str:
    ])


+def _pack_data(field: Any) -> Any:
+    if isinstance(field, dict) and "data" in field and isinstance(field.get("data"), (dict, list)):
+        return field["data"]
+    return field
+
+
+def _occupants_cell(names: Any, language: str) -> str:
+    if isinstance(names, list) and names:
+        return planet_list(names, language) or ("无" if language == "zh" else "None")
+    if isinstance(names, list):
+        return "无" if language == "zh" else "None"
+    return names if isinstance(names, str) else ("无" if language == "zh" else "None")
+
+
+def _phase_word(phase: Any, language: str) -> str | None:
+    if phase == "day":
+        return "日间" if language == "zh" else "Day"
+    if phase == "night":
+        return "夜间" if language == "zh" else "Night"
+    return None
+
+
+def _annual_houses(packet: dict, language: str) -> str:
+    pack = _first(packet, ("timing_and_predictive_systems", "annual_tajika_pack")) or {}
+    data = _pack_data(pack.get("annual_houses") if isinstance(pack, dict) else None)
+    houses = data.get("houses") if isinstance(data, dict) else None
+    rows = []
+    for item in houses or []:
+        if not isinstance(item, dict):
+            continue
+        rows.append({
+            "house": item.get("house"),
+            "sign": item.get("sign"),
+            "lord": item.get("lord"),
+            "occupant": _occupants_cell(item.get("occupants"), language),
+        })
+    return _rows_from(rows, language, [("house", "text"), ("sign", "sign"), ("lord", "planet"), ("occupant", "text")])
+
+
+def _tripataki(packet: dict, language: str) -> str:
+    pack = _first(packet, ("timing_and_predictive_systems", "annual_tajika_pack")) or {}
+    data = _pack_data(pack.get("tripataki_chakra") if isinstance(pack, dict) else None)
+    if not isinstance(data, dict):
+        return _blank(language, ["point", "sign", "degree", "longitude"])
+    placements = []
+    for item in data.get("placements") or []:
+        if isinstance(item, dict):
+            placements.append({
+                "point": item.get("body"),
+                "sign": item.get("sign"),
+                "degree": None if item.get("degree_in_sign") is None else round(float(item["degree_in_sign"]), 4),
+                "longitude": None if item.get("longitude") is None else round(float(item["longitude"]), 4),
+            })
+    vedha = []
+    for item in data.get("vedha_rows") or []:
+        if isinstance(item, dict):
+            vedha.append({
+                "target": item.get("target"),
+                "planet": item.get("available_sources") or item.get("sources"),
+                "status": item.get("status"),
+            })
+    parts = [
+        _rows_from(placements, language, [("point", "text"), ("sign", "sign"), ("degree", "text"), ("longitude", "text")]),
+        _rows_from(vedha, language, [("target", "planet"), ("planet", "planets"), ("status", "text")]),
+    ]
+    return "\n\n".join(parts)
+
+
+def _trace_table(traces: Any, language: str) -> str:
+    rows = []
+    if isinstance(traces, list):
+        for item in traces:
+            if not isinstance(item, dict):
+                continue
+            rows.append({
+                "name": item.get("name"),
+                "rule": item.get("rule"),
+                "phase": _phase_word(item.get("phase"), language),
+                "longitude": item.get("longitude"),
+            })
+    return _rows_from(rows, language, [("name", "text"), ("rule", "text"), ("phase", "text"), ("longitude", "text")])
+
+
+def _annual_saham_trace(packet: dict, language: str) -> str:
+    pack = _first(packet, ("timing_and_predictive_systems", "annual_tajika_pack")) or {}
+    sahams = _pack_data(pack.get("sahams") if isinstance(pack, dict) else None)
+    traces = sahams.get("formula_traces") if isinstance(sahams, dict) else None
+    return _trace_table(traces, language)
+
+
+def _natal_saham_trace(packet: dict, language: str) -> str:
+    module = _first(packet, ("advanced_systems", "sahams")) or {}
+    traces = module.get("formula_traces") if isinstance(module, dict) else None
+    return _trace_table(traces, language)
+
+
 def _annual(packet: dict, language: str) -> str:
    pack = _first(packet, ("timing_and_predictive_systems", "annual_tajika_pack")) or {}
    solar = pack.get("solar_return") if isinstance(pack, dict) else {}
@@ -2398,9 +2494,12 @@ _BUILDERS = {
    "Current Dasha Convergence": _convergence,
    "Chara Dasha Period Durations": _chara,
    "Narayana Method Comparison": _narayana,
-    "Annual Return Calculation Contract": _annual,
-    "Tajika Aspect and Yoga Candidates": _tajika_candidates,
-    "Annual Tajika Strength": _tajika_strength,
+        "Annual Return House Framework": _annual_houses,
+        "Annual Return Calculation Contract": _annual,
+        "Tajika Aspect and Yoga Candidates": _tajika_candidates,
+        "Tripataki Chakra Detail": _tripataki,
+        "Annual Tajika Strength": _tajika_strength,
+        "Annual Saham Formula Trace": _annual_saham_trace,
 }


@@ -2408,11 +2507,11 @@ def _chapter_sections() -> list[list[str]]:
    order = [title for title, _zh in SECTIONS]
    groups = [
        order[:14],
-        order[14:17],
-        order[17:32],
-        order[32:43],
-        order[43:59],
-        order[59:],
+        order[14:20],
+        order[20:35],
+        order[35:46],
+        order[46:63],
+        order[63:],
    ]
    return groups

@@ -2455,6 +2554,7 @@ def _render_named(packet: dict, language: str, title: str) -> str:
        "Pancha Pakshi": lambda: _missing_module(language, ["name", "value", "status"]),
        "Natal Vivah Saham": lambda: _vivah(packet, language),
        "Natal Saham Formula Basis": lambda: _saham_basis(packet, language),
+        "Natal Saham Formula Trace": lambda: _natal_saham_trace(packet, language),
        "Arudha / UL / A10": lambda: _special_points(packet, language),
        "Jaimini Calculation Details": lambda: _jaimini_details(packet, language),
        "Graha Pada": lambda: _graha_pada(packet, language),