strengthen external parity diagnostics

scripts/candidate_time_sensitivity_scan.py

@@ -39,6 +39,21 @@ def _varga_ascendant(payload: dict[str, Any], varga: str) -> str | None:
     return None
 
 
+def _all_varga_ascendants(payload: dict[str, Any]) -> dict[str, str | None]:
+    values = {varga.upper(): None for varga in _VARGAS}
+    try:
+        raw = _engine_json("varga", {**payload, "varga": "all"})
+    except subprocess.CalledProcessError:
+        return values
+    for name, chart in (raw.get("divisional_charts") or {}).items():
+        if not isinstance(chart, dict):
+            continue
+        for varga in _VARGAS:
+            if name.startswith(varga.upper() + "_"):
+                values[varga.upper()] = chart.get("ascendant")
+    return values
+
+
 def scan_candidate_times(payload: dict[str, Any], *, uncertainty_minutes: int = 30, step_minutes: int = 1) -> dict[str, Any]:
     required = ("year", "month", "day", "hour", "minute", "lat", "lon", "tz")
     missing = [key for key in required if payload.get(key) is None]
@@ -53,7 +68,7 @@ def scan_candidate_times(payload: dict[str, Any], *, uncertainty_minutes: int =
         point = {**payload, "year": moment.year, "month": moment.month, "day": moment.day, "hour": moment.hour, "minute": moment.minute}
         chart = _engine_json("chart", point)
         asc = chart.get("ascendant", {})
-        divisional = {varga.upper(): _varga_ascendant(point, varga) for varga in _VARGAS}
+        divisional = _all_varga_ascendants(point)
         rows.append({
             "time": moment.strftime("%Y-%m-%d %H:%M"),
             "offset_minutes": offset,
@@ -62,6 +77,8 @@ def scan_candidate_times(payload: dict[str, Any], *, uncertainty_minutes: int =
             "divisional_ascendants": divisional,
         })
     signatures = [tuple([row["d1_ascendant"], *row["divisional_ascendants"].values()]) for row in rows]
+    unavailable_vargas = [varga.upper() for varga in _VARGAS if all(row["divisional_ascendants"][varga.upper()] is None for row in rows)]
+    supported_vargas = [varga.lower() for varga in _VARGAS if varga.upper() not in unavailable_vargas]
     modal = Counter(signatures).most_common(1)[0][0]
     for row, signature in zip(rows, signatures):
         row["sensitivity_count"] = sum(left != right for left, right in zip(signature, modal))
@@ -69,7 +86,6 @@ def scan_candidate_times(payload: dict[str, Any], *, uncertainty_minutes: int =
             name for name, current, typical in zip(("D1", "D4", "D9", "D10", "D24", "D30"), signature, modal)
             if current != typical
         ]
-    unavailable_vargas = [varga.upper() for varga in _VARGAS if all(row["divisional_ascendants"][varga.upper()] is None for row in rows)]
     transitions = []
     for previous, current in zip(rows, rows[1:]):
         changed = [name for name in ("d1_ascendant", "divisional_ascendants") if previous[name] != current[name]]
@@ -85,6 +101,7 @@ def scan_candidate_times(payload: dict[str, Any], *, uncertainty_minutes: int =
         "step_minutes": step_minutes,
         "rows": rows,
         "transitions": transitions,
+        "supported_vargas": [varga.upper() for varga in supported_vargas],
         "unavailable_vargas": unavailable_vargas,
         "pending_layers": ["UL", "A7", "A10", "KP_cusp"],
         "boundary": "Actual local D1/Varga differences only. Unsupported Varga CLI flags are explicitly unavailable. Event answers still require an explicit event-to-candidate adjudication model before minute-level rectification.",

scripts/jyotish_api_server.py

@@ -1308,10 +1308,12 @@ class JyotishAPIHandler(BaseHTTPRequestHandler):
             elif path == '/api/rectification/questionnaire':
                 self._json(build_rectification_questionnaire(body))
             elif path == '/api/rectification/sensitivity_scan':
+                uncertainty = int(body.get('time_uncertainty_minutes') or 30)
+                step_minutes = int(body.get('step_minutes') or (5 if uncertainty > 15 else 1))
                 self._json(scan_candidate_times(
                     body,
-                    uncertainty_minutes=int(body.get('time_uncertainty_minutes') or 30),
-                    step_minutes=int(body.get('step_minutes') or 1),
+                    uncertainty_minutes=uncertainty,
+                    step_minutes=step_minutes,
                 ))
             elif path == '/api/rectification/answers':
                 questionnaire = body.get('questionnaire')

scripts/pyjhora_parity_summary.py

@@ -0,0 +1,61 @@
+#!/usr/bin/env python3
+"""Summarize reviewable PyJHora comparison matrices without overstating coverage."""
+
+from __future__ import annotations
+
+import argparse
+import csv
+import json
+from collections import Counter, defaultdict
+from pathlib import Path
+from typing import Any
+
+
+REQUIRED_FULL_PARITY = ("D1", "D9", "D10", "D2", "D4", "Vimshottari", "Shadbala", "Ashtakavarga")
+MATRIX_SECTION_MAP = {"ascendant": "D1", "planet": "D1", "dasha": "Vimshottari", "D9": "D9", "D10": "D10"}
+
+
+def summarize_matrix(path: str | Path, *, settings: dict[str, Any]) -> dict[str, Any]:
+    path = Path(path)
+    rows = list(csv.DictReader(path.open(encoding="utf-8")))
+    status_counts = Counter(str(row.get("status") or "unknown") for row in rows)
+    sections: dict[str, dict[str, int]] = defaultdict(lambda: {"total": 0, "match": 0, "mismatch": 0})
+    covered = set()
+    for row in rows:
+        section = MATRIX_SECTION_MAP.get(str(row.get("section") or ""))
+        if not section:
+            continue
+        covered.add(section)
+        sections[section]["total"] += 1
+        if row.get("status") == "match":
+            sections[section]["match"] += 1
+        elif row.get("status") == "mismatch":
+            sections[section]["mismatch"] += 1
+    missing = [field for field in REQUIRED_FULL_PARITY if field not in covered]
+    return {
+        "scope": "pyjhora_same_chart_parity_summary",
+        "matrix_path": str(path),
+        "tested": bool(rows),
+        "settings": settings,
+        "row_counts": dict(status_counts),
+        "coverage": dict(sorted(sections.items())),
+        "covered_outputs": sorted(covered),
+        "missing_required_outputs": missing,
+        "status": "partial_verified" if rows and not status_counts.get("mismatch") else "partial_mismatch",
+        "full_parity_verified": not missing and not status_counts.get("mismatch"),
+        "boundary": "Only covered outputs are compared. This summary cannot promote full parity while required outputs are absent.",
+    }
+
+
+def main() -> int:
+    parser = argparse.ArgumentParser(description=__doc__)
+    parser.add_argument("matrix")
+    parser.add_argument("--ayanamsa", default="lahiri")
+    parser.add_argument("--node-mode", default="mean", choices=["mean", "true"])
+    args = parser.parse_args()
+    print(json.dumps(summarize_matrix(args.matrix, settings={"ayanamsa": args.ayanamsa, "node_mode": args.node_mode}), ensure_ascii=False, indent=2))
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())