fix(rectification): fold D24 into education refine and score family D3

Window scan now drives d5_refine when D24 changes, family events use D3, and pada/Hora/Ghati are display-only. New cases bind Skill 10.0.7 without unique-minute confirmation.

Co-authored-by: Cursor <cursoragent@cursor.com>

scripts/active_rectification_event_engine.py

@@ -12,6 +12,7 @@ import hashlib
 import json
 import sys
 from datetime import date, datetime, time, timedelta
+from functools import lru_cache
 from pathlib import Path
 from collections.abc import Sequence
 from typing import Any, Final, assert_never
@@ -39,7 +40,10 @@ import functional_benefics  # noqa: E402
 import jaimini  # noqa: E402
 import shadbala  # noqa: E402
 import narayana_dasha  # noqa: E402
+import saham_daynight  # noqa: E402
+import special_lagnas  # noqa: E402
 import varga  # noqa: E402
+from scripts.rectification.refinement_packet import NAKSHATRA_SPAN  # noqa: E402
 
 AYANAMSA: Final = "lahiri"
 NODE_MODE: Final = "mean"
@@ -53,8 +57,8 @@ DOMAIN_CONFIG: Final[dict[EventDomain, DomainConfig]] = {
     "career": (("D10",), (10,)),
     "finance": (("D2", "D11"), (2, 11)),
     "health_pressure": (("D30",), (6, 8, 12)),
-    # 六亲: D12 parents, D7 children/spouse detail, plus D1 houses 3/4/5/9.
-    "family": (("D12", "D7"), (3, 4, 5, 9)),
+    # 六亲: D12 parents, D7 children/spouse detail, D3 siblings, plus D1 houses 3/4/5/9.
+    "family": (("D12", "D7", "D3"), (3, 4, 5, 9)),
     # Dated appearance/marks: D1 lagna / 1st house only. Not a primary formula.
     "appearance": ((), (1,)),
 }
@@ -340,6 +344,49 @@ def _arudha_sign(arudha_padas: dict, key: str) -> int | None:
     return int(sign_index) if isinstance(sign_index, int) and 0 <= sign_index <= 11 else None
 
 
+def _pada_index(longitude: float) -> int:
+    return int((float(longitude) % 360.0) / (NAKSHATRA_SPAN / 4.0)) % 108
+
+
+@lru_cache(maxsize=64)
+def _sunrise_local_naive(date_iso: str, lat: float, lon: float, tz: float) -> datetime | None:
+    """Real sunrise only. Polar or unavailable locations omit Hora/Ghati; never invent 06:00."""
+    try:
+        import swisseph as swe
+        noon = datetime.fromisoformat(f"{date_iso}T12:00:00")
+        row = saham_daynight.determine_daytime(noon, lat=lat, lon=lon, tz=tz)
+        year, month, day, ut_hours = swe.revjul(float(row["sunrise_jd_ut"]))
+        return datetime(int(year), int(month), int(day)) + timedelta(hours=float(ut_hours) + float(tz))
+    except (saham_daynight.SahamDayNightError, TypeError, ValueError, OverflowError, OSError):
+        return None
+
+
+def _fine_minute_indices(
+    *,
+    ascendant_longitude: float,
+    candidate_at: datetime,
+    lat: float,
+    lon: float,
+    tz: float,
+) -> dict[str, int]:
+    indices: dict[str, int] = {"pada_index": _pada_index(ascendant_longitude)}
+    sunrise = _sunrise_local_naive(candidate_at.date().isoformat(), lat, lon, tz)
+    if sunrise is None:
+        return indices
+    calculator = special_lagnas.SpecialLagnasCalculator()
+    wrapped = float(ascendant_longitude) % 360.0
+    try:
+        hora = calculator.calculate_hora_lagna(wrapped, 0.0, candidate_at, sunrise)
+        ghati = calculator.calculate_ghati_lagna(wrapped, candidate_at, sunrise)
+        hora_degree = float(hora["degree"])
+        ghati_degree = float(ghati["degree"])
+    except (TypeError, ValueError, KeyError, OverflowError):
+        return indices
+    indices["hora_sign_index"] = int(hora_degree // 30.0) % 12
+    indices["ghati_sign_index"] = int(ghati_degree // 30.0) % 12
+    return indices
+
+
 def build_candidate_static_context(
     request: RectificationEventRequest,
     candidate_at: datetime,
@@ -369,12 +416,12 @@ def build_candidate_static_context(
     charts = varga.calc_all_vargas(
         planet_longitudes,
         ascendant_longitude,
-        divisions=[2, 4, 5, 7, 9, 10, 12, 24, 30],
+        divisions=[2, 3, 4, 5, 7, 9, 10, 12, 24, 30],
     )
     d11_chart = _d11_chart(planet_longitudes, ascendant_longitude)
     varga_charts = {
         prefix: d11_chart if prefix == "D11" else _varga_chart(charts, prefix)
-        for prefix in ("D2", "D4", "D5", "D7", "D9", "D10", "D11", "D12", "D24", "D30")
+        for prefix in ("D2", "D3", "D4", "D5", "D7", "D9", "D10", "D11", "D12", "D24", "D30")
     }
     available_layers = ["D1"]
     blocked_layers = ["KP_cusps"]
@@ -417,6 +464,13 @@ def build_candidate_static_context(
         "time": candidate_at.strftime("%H:%M"),
         "ascendant_degree": ascendant_longitude,
         "ascendant_sign_index": ascendant_index,
+        **_fine_minute_indices(
+            ascendant_longitude=ascendant_longitude,
+            candidate_at=candidate_at,
+            lat=float(request["lat"]),
+            lon=float(request["lon"]),
+            tz=float(request["tz"]),
+        ),
         "varga_ascendants": varga_ascendants,
         "arudha_signs": arudha_signs,
         "available_layers": sorted(set(available_layers)),

scripts/rectification/decision_policy.py

@@ -52,6 +52,7 @@ _AUDIT_LABELS = {
     "d2-hora": ("D2 财帛分盘", "本轮已对照财帛主题。"),
     "d4-chaturthamsha": ("D4 迁移分盘", "本轮已对照居所或迁移。"),
     "d5-panchamsha": ("D5 成就分盘", "本轮已对照学业或被委以责任的变化。"),
+    "d3-drekkana": ("D3 兄弟分盘", "本轮已对照兄弟姐妹主题。"),
     "d7-saptamsha": ("D7 子女分盘", "本轮已对照子女或伴侣细节。"),
     "d9-navamsa": ("D9 婚姻分盘", "本轮已对照关系主题，未给类型标签。"),
     "d10-dashamsa": ("D10 事业分盘", "本轮已对照事业主题，未给类型标签。"),

scripts/rectification/refinement_packet.py

@@ -121,25 +121,38 @@ _LAYER_LABEL = {
     "d5": "D5",
     "d7": "D7",
     "d12": "D12",
+    "d24": "D24",
+    "pada": "Nakshatra pada",
+    "hora": "Hora Lagna",
+    "ghati": "Ghati Lagna",
 }
 
 
+def _scan_layer_value(feature: dict[str, Any], layer: str) -> int | None:
+    vargas = feature.get("varga_ascendants") if isinstance(feature.get("varga_ascendants"), dict) else {}
+    raw = {
+        "d1": feature.get("ascendant_sign_index"),
+        "d9": vargas.get("D9"),
+        "d10": vargas.get("D10"),
+        "d4": vargas.get("D4"),
+        "d5": vargas.get("D5"),
+        "d7": vargas.get("D7"),
+        "d12": vargas.get("D12"),
+        "d24": vargas.get("D24"),
+        "pada": feature.get("pada_index"),
+        "hora": feature.get("hora_sign_index"),
+        "ghati": feature.get("ghati_sign_index"),
+    }.get(layer)
+    return raw if isinstance(raw, int) else None
+
+
 def window_scan(built: dict[str, Any]) -> dict[str, Any]:
-    """D1/D9/D10/D4/D5/D7/D12 diversity plus change minutes. Indices only; never sign names."""
+    """D1/D9/D10/D4/D5/D7/D12/D24 plus display-only pada/Hora/Ghati. Indices only; never sign names."""
     counts: dict[str, set[int]] = {layer: set() for layer in _LAYER_LABEL}
     transitions: list[dict[str, Any]] = []
     previous: dict[str, int | None] | None = None
     for feature in _features(built):
-        vargas = feature.get("varga_ascendants") if isinstance(feature.get("varga_ascendants"), dict) else {}
-        current = {
-            "d1": feature.get("ascendant_sign_index") if isinstance(feature.get("ascendant_sign_index"), int) else None,
-            "d9": vargas.get("D9") if isinstance(vargas.get("D9"), int) else None,
-            "d10": vargas.get("D10") if isinstance(vargas.get("D10"), int) else None,
-            "d4": vargas.get("D4") if isinstance(vargas.get("D4"), int) else None,
-            "d5": vargas.get("D5") if isinstance(vargas.get("D5"), int) else None,
-            "d7": vargas.get("D7") if isinstance(vargas.get("D7"), int) else None,
-            "d12": vargas.get("D12") if isinstance(vargas.get("D12"), int) else None,
-        }
+        current = {layer: _scan_layer_value(feature, layer) for layer in _LAYER_LABEL}
         for layer, bucket in counts.items():
             value = current[layer]
             if isinstance(value, int):
@@ -156,26 +169,16 @@ def window_scan(built: dict[str, Any]) -> dict[str, Any]:
                         "user_meaning": f"{label} 在 {time} 发生变化",
                     })
         previous = current
-    return {
+    payload: dict[str, Any] = {
         "scanned": True,
         "confirmation_allowed": False,
         "unique_minute_claim": False,
-        "d1_lagna_count": len(counts["d1"]),
-        "d9_lagna_count": len(counts["d9"]),
-        "d10_lagna_count": len(counts["d10"]),
-        "d4_lagna_count": len(counts["d4"]),
-        "d5_lagna_count": len(counts["d5"]),
-        "d7_lagna_count": len(counts["d7"]),
-        "d12_lagna_count": len(counts["d12"]),
-        "d1_candidates_differ": len(counts["d1"]) > 1,
-        "d9_candidates_differ": len(counts["d9"]) > 1,
-        "d10_candidates_differ": len(counts["d10"]) > 1,
-        "d4_candidates_differ": len(counts["d4"]) > 1,
-        "d5_candidates_differ": len(counts["d5"]) > 1,
-        "d7_candidates_differ": len(counts["d7"]) > 1,
-        "d12_candidates_differ": len(counts["d12"]) > 1,
         "transitions": transitions,
     }
+    for layer in _LAYER_LABEL:
+        payload[f"{layer}_lagna_count" if layer.startswith("d") else f"{layer}_count"] = len(counts[layer])
+        payload[f"{layer}_candidates_differ"] = len(counts[layer]) > 1
+    return payload
 
 
 def event_dasha_ledger(
@@ -376,9 +379,9 @@ def precision_stage(scan: dict[str, Any], event_count: int) -> dict[str, Any]:
     elif scan.get("d4_candidates_differ"):
         current = "d4_refine"
         meaning = "事业盘已较稳，居所盘仍会换升。可再补一件记得时间的搬家或住处变化。"
-    elif scan.get("d5_candidates_differ"):
+    elif scan.get("d5_candidates_differ") or scan.get("d24_candidates_differ"):
         current = "d5_refine"
-        meaning = "居所盘已较稳，成就盘仍会换升。可再补一件记得时间的学业、考试或被委以责任的变化；不要贴类型标签。"
+        meaning = "居所盘已较稳，成就盘或学业盘仍会换升。可再补一件记得时间的学业、考试或被委以责任的变化；不要贴类型标签。"
     else:
         current = "ready_to_adopt"
         meaning = "核心分盘已不再换升。可以采用代表性时间看盘，也可以再补主题经历。"

scripts/rectification/scoring_service.py

@@ -12,7 +12,7 @@ from scripts.active_rectification_event_engine import compute_candidate_static_c
 from scripts.active_rectification_events import CandidateScoreRow
 from scripts.rectification.contracts import LifeEvent, RectificationRequest, is_scoreable_event
 
-ALGORITHM_VERSION = "rectification-v5-matrix-scoring-4"
+ALGORITHM_VERSION = "rectification-v5-matrix-scoring-5"
 INPUT_CONTRACT_VERSION = "rectification-calculation-spec-v4"
 PRECISION_WEIGHTS = {
     "day": 1.0,
@@ -184,7 +184,7 @@ def public_technique_layers(domain: str, rule_ids: Sequence[str]) -> list[str]:
     if domain == "career":
         layers.update({"d1-rashi", "d10-dashamsa"})
     elif domain == "family":
-        layers.update({"d1-rashi", "d12-dwadashamsha", "d7-saptamsha"})
+        layers.update({"d1-rashi", "d12-dwadashamsha", "d7-saptamsha", "d3-drekkana"})
     elif domain == "education":
         layers.update({"d1-rashi", "d24-chaturvimshamsha", "d5-panchamsha"})
     elif domain == "relocation":

scripts/rectification_technique_contract.py

@@ -80,7 +80,7 @@ def build_rectification_technique_contract(
     return {
         "schema_version": 2,
         "calculation_status": "not_started" if event_count == 0 else "evaluated",
-        "used_divisional_charts": ["D2", "D4", "D5", "D7", "D9", "D10", "D11", "D12", "D24", "D30"],
+        "used_divisional_charts": ["D2", "D3", "D4", "D5", "D7", "D9", "D10", "D11", "D12", "D24", "D30"],
         "used_arudha": ["A7", "UL", "A10"],
         "dasha_tracks": ["vimshottari_md_ad_pd", "narayana_md_ad"],
         "missing_layers": reported_missing_layers,