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feat(rectification): pass ayanamsa per request

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This commit is contained in:
Jesse_Chen
2026-09-04 00:25:16 +08:00
parent 3b09bbbee0
commit 44d3d3931b
15 changed files with 135 additions and 16 deletions
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scripts/active_rectification_questions.py
+41 -4
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@@ -16,6 +16,9 @@ if str(SCRIPTS_DIR) not in sys.path:
sys.path.insert(0, str(SCRIPTS_DIR))
from active_rectification_selector import select_next_questions
from ayanamsa_utils import DEFAULT_AYANAMSA_NAME
DEFAULT_NODE_MODE = "mean"
OPTIONS = [
{"key": "A", "label": "明确有，且时间大致吻合", "score": 2},
@@ -60,7 +63,8 @@ def _candidate_scan(
lat: float | None = None,
lon: float | None = None,
tz: float | None = None,
ayanamsa: str = "raman",
ayanamsa: str = DEFAULT_AYANAMSA_NAME,
node_mode: str = DEFAULT_NODE_MODE,
) -> dict[str, Any]:
start = center - timedelta(minutes=uncertainty_minutes)
end = center + timedelta(minutes=uncertainty_minutes)
@@ -84,7 +88,14 @@ def _candidate_scan(
"cluster": cluster,
"sensitivity_flags": _sensitivity_flags(abs(offset)),
}
recast = _candidate_recast(candidate, lat=lat, lon=lon, tz=tz, ayanamsa=ayanamsa)
recast = _candidate_recast(
candidate,
lat=lat,
lon=lon,
tz=tz,
ayanamsa=ayanamsa,
node_mode=node_mode,
)
if recast:
sample.update(recast)
samples.append(sample)
@@ -106,6 +117,8 @@ def _candidate_scan(
"lat": lat,
"lon": lon,
"tz": tz,
"ayanamsa": ayanamsa,
"node_mode": node_mode,
},
uncertainty_minutes=uncertainty_minutes,
step_minutes=step_minutes,
@@ -126,6 +139,10 @@ def _candidate_scan(
"cluster_labels": ["early_candidate_cluster", "middle_candidate_cluster", "late_candidate_cluster"],
"samples": samples,
"minute_scan": minute_scan,
"calculation": {
"ayanamsa": ayanamsa,
"node_mode": node_mode,
},
"sensitivity_summary": {
"method": "minute_feature_scan_v2",
"high_value_layers": ["D2", "D4", "D9", "D10", "D24", "D30", "D60", "UL", "A7", "A10", "KP_cusp"],
@@ -152,6 +169,7 @@ def _candidate_recast(
lon: float | None,
tz: float | None,
ayanamsa: str,
node_mode: str = DEFAULT_NODE_MODE,
) -> dict[str, Any] | None:
if lat is None or lon is None or tz is None:
return None
@@ -171,6 +189,7 @@ def _candidate_recast(
"lon": lon,
"tz": tz,
"ayanamsa": ayanamsa,
"node_mode": node_mode,
})
planet_lons = {
name: data["lon"]
@@ -231,7 +250,8 @@ def build_questionnaire(
lat: float | None = None,
lon: float | None = None,
tz: float | None = None,
ayanamsa: str = "raman",
ayanamsa: str = DEFAULT_AYANAMSA_NAME,
node_mode: str = DEFAULT_NODE_MODE,
) -> dict[str, Any]:
questions = []
for qid, round_id, domain, sensitivity, window, prompt, yes_bias, no_bias in QUESTION_TEMPLATES:
@@ -270,6 +290,7 @@ def build_questionnaire(
lon=lon,
tz=tz,
ayanamsa=ayanamsa,
node_mode=node_mode,
)
selection = select_next_questions(
{"questions": questions, "candidate_scan": candidate_scan}, {}, limit=1
@@ -279,6 +300,10 @@ def build_questionnaire(
"schema_version": 1,
"candidate_scan": candidate_scan,
"selection": selection,
"calculation": {
"ayanamsa": ayanamsa,
"node_mode": node_mode,
},
"workflow": [
"candidate_time_scan",
"varga_arudha_kp_sensitivity_diff",
@@ -433,6 +458,10 @@ def score_answers(
"truth_status": "not_birth_time_truth",
"formula_unit_parity_status": "partial",
"timing_claim_status": "exploratory_unvalidated",
"calculation": questionnaire.get("calculation", {
"ayanamsa": DEFAULT_AYANAMSA_NAME,
"node_mode": DEFAULT_NODE_MODE,
}),
"answered_count": len(applied),
"candidate_cluster_rankings": rankings,
"technique_audit_table": [
@@ -494,10 +523,18 @@ def main() -> int:
parser.add_argument("--birth-time", required=True, help="Approximate local birth time, YYYY-MM-DD HH:MM")
parser.add_argument("--uncertainty-minutes", type=int, default=30)
parser.add_argument("--step-minutes", type=int, default=1)
parser.add_argument("--ayanamsa", default=DEFAULT_AYANAMSA_NAME)
parser.add_argument("--node-mode", choices=("mean", "true"), default=DEFAULT_NODE_MODE)
parser.add_argument("--answers-json", default="", help="Optional JSON object mapping question id to A/B/C/D")
parser.add_argument("--pretty", action="store_true")
args = parser.parse_args()
questionnaire = build_questionnaire(args.birth_time, args.uncertainty_minutes, args.step_minutes)
questionnaire = build_questionnaire(
args.birth_time,
args.uncertainty_minutes,
args.step_minutes,
ayanamsa=args.ayanamsa,
node_mode=args.node_mode,
)
report = score_answers(questionnaire, json.loads(args.answers_json)) if args.answers_json else questionnaire
print(json.dumps(report, ensure_ascii=False, indent=2 if args.pretty else None))
return 0