sync: import research boundary evidence packets
This commit is contained in:
732642856
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#!/usr/bin/env python3
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from __future__ import annotations
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import hashlib
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import json
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import re
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from dataclasses import dataclass
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from pathlib import Path
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ROOT = Path(__file__).resolve().parents[1]
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OUTPUT = ROOT / "references/oracle/full_technique_invocation_matrix_2026_07_22.json"
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SCAN_ROOTS = {
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"skill": ["SKILL.md", "skills"],
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"api": ["mcp_server.py", "scripts/jyotish_api_server.py", "scripts"],
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"ui": ["jyotish-app"],
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"scripts": ["scripts"],
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"references": ["references"],
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"tests": ["tests"],
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}
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SKIP_PARTS = {
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".git",
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"__pycache__",
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"node_modules",
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"dist",
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"build",
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".pytest_cache",
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".mypy_cache",
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}
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MAX_SCAN_BYTES = 1_000_000
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@dataclass(frozen=True)
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class Technique:
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technique_id: str
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label: str
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domain: str
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aliases: tuple[str, ...]
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p_batch: str
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first_batch: bool = False
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TECHNIQUES: tuple[Technique, ...] = (
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Technique("ul_arudha_upapada", "UL / Upapada Lagna", "arudha_rectification", ("UL", "Upapada", "upapada"), "P0", True),
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Technique("a7_arudha_relationship", "A7 Arudha", "arudha_rectification", ("A7", "arudha a7", "darapada"), "P0", True),
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Technique("a10_arudha_career", "A10 Arudha", "arudha_rectification", ("A10", "arudha a10", "rajyapada"), "P0", True),
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Technique("kp_exact_cusp", "KP exact cusp", "kp_precision_timing", ("KP cusp", "house cusp", "exact cusp", "cusp longitude"), "P0", True),
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Technique("kp_star_sub_sub", "KP star / sub / sub-sub", "kp_precision_timing", ("star lord", "sub lord", "sub-sub", "sub sub", "KP star"), "P0", True),
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Technique("kp_significator", "KP significator table", "kp_precision_timing", ("significator", "KP significator"), "P1", True),
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Technique("kp_ruling_planets", "KP ruling planets", "kp_precision_timing", ("ruling planets", "RP", "KP ruling"), "P1", True),
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Technique("shadbala", "Shadbala total", "strength", ("Shadbala", "Ṣaḍbala", "Sadbal"), "P0", True),
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Technique("shadbala_chesta", "Shadbala Chesta Bala", "strength", ("Chesta", "ceṣṭā", "mean-motion", "Seeghrochcha"), "P0", True),
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Technique("shadbala_sthana", "Shadbala Sthana Bala", "strength", ("Sthana", "Uccha", "Saptavargaja", "Ojayugma", "Kendradi", "Drekkana"), "P0", True),
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Technique("shadbala_dig", "Shadbala Dig Bala", "strength", ("Dig Bala", "Digbala"), "P1"),
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Technique("shadbala_drik", "Shadbala Drik Bala", "strength", ("Drik Bala", "aspect strength"), "P1"),
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Technique("shadbala_kala", "Shadbala Kala Bala", "strength", ("Kala Bala", "Natonnata", "Paksha", "Tribhaga", "Abda", "Masa", "Vara", "Hora"), "P1"),
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Technique("naisargika_bala", "Naisargika Bala", "strength", ("Naisargika", "natural strength"), "P1"),
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Technique("ashtakavarga_bav", "Ashtakavarga BAV", "ashtakavarga", ("BAV", "Bhinnashtakavarga", "Bhinnashtaka"), "P1"),
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Technique("ashtakavarga_sav", "Ashtakavarga SAV", "ashtakavarga", ("SAV", "Sarvashtakavarga", "Sarvashtaka"), "P1"),
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Technique("ashtakavarga_kakshya", "Ashtakavarga Kakshya", "ashtakavarga", ("Kakshya", "kakshya transit"), "P1"),
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Technique("muhurta", "Muhurta full scoring", "muhurta", ("Muhurta", "Electional", "择日"), "P0", True),
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Technique("tarabala", "Tarabala", "muhurta", ("Tarabala", "Tara Bala"), "P0", True),
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Technique("chandrabala", "Chandrabala", "muhurta", ("Chandrabala", "Chandra Bala"), "P0", True),
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Technique("rahu_kalam", "Rahu Kalam", "muhurta", ("Rahu Kalam", "Rahu Kala", "Rāhukāla"), "P0", True),
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Technique("yamaganda", "Yamaganda", "muhurta", ("Yamaganda", "Yama Gandam", "Yamakanda"), "P1"),
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Technique("gulika_kalam", "Gulika Kalam", "muhurta", ("Gulika Kalam", "Gulikai", "Mandi Kalam"), "P1"),
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Technique("abhijit_muhurta", "Abhijit Muhurta", "muhurta", ("Abhijit", "Abhijit Muhurta"), "P0", True),
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Technique("panchaka", "Panchaka", "muhurta", ("Panchaka",), "P1"),
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Technique("vyatipata_vaidhriti", "Vyatipata / Vaidhriti", "muhurta", ("Vyatipata", "Vaidhriti"), "P1"),
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Technique("sankranti_gate", "Sankranti gate", "muhurta", ("Sankranti", "Saṅkrānti"), "P1"),
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Technique("prashna", "Prashna chart", "horary", ("Prashna", "Horary", "question chart"), "P0", True),
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Technique("sphuta", "Sphuta set", "horary", ("Sphuta", "Trisphuta", "Catusphuta", "Panchasphuta"), "P0", True),
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Technique("gulika", "Gulika / Mandi", "horary", ("Gulika", "Mandi"), "P0", True),
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Technique("saham", "Saham lots", "horary_annual", ("Saham", "Sahams", "Arabic parts"), "P0", True),
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Technique("tajika", "Tajika / Varshaphala", "annual", ("Tajika", "Varshaphala", "annual chart"), "P0", True),
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Technique("muntha", "Muntha", "annual", ("Muntha",), "P1"),
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Technique("mudda_dasha", "Mudda Dasha", "annual", ("Mudda", "Mudda Dasha"), "P1"),
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Technique("vimshottari", "Vimshottari Dasha", "dasha", ("Vimshottari",), "P1"),
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Technique("narayana_dasha", "Narayana Dasha", "dasha", ("Narayana",), "P1"),
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Technique("chara_dasha", "Chara Dasha", "dasha", ("Chara Dasha",), "P2"),
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Technique("functional_benefic_malefic", "Functional Benefic / Malefic", "interpretation_gate", ("Functional Benefic", "Functional Malefic", "功能性吉凶"), "P0"),
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Technique("mevg", "MEVG / real-case calibration", "interpretation_gate", ("MEVG", "Real Case Calibration", "Global Web Evidence"), "P0"),
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Technique("birth_time_rectification", "Birth-time rectification", "rectification", ("birth-time rectification", "生时校正", "rectification"), "P0"),
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Technique("timing_holdout", "Timing negative holdout", "timing", ("holdout", "negative controls", "blind ranking", "负样本"), "P0"),
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Technique("d1_rasi", "D1 Rasi", "varga", ("D1", "Rasi", "Rāśi"), "P1"),
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Technique("d2_hora", "D2 Hora", "varga", ("D2", "Hora"), "P1"),
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Technique("d3_drekkana", "D3 Drekkana", "varga", ("D3", "Drekkana", "Decanate"), "P1"),
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Technique("d4_chaturthamsha", "D4 Chaturthamsha", "varga", ("D4", "Chaturthamsha"), "P1"),
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Technique("d7_saptamsha", "D7 Saptamsha", "varga", ("D7", "Saptamsha"), "P1"),
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Technique("d9_navamsa", "D9 Navamsa", "varga", ("D9", "Navamsa"), "P1"),
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Technique("d10_dasamsha", "D10 Dasamsha", "varga", ("D10", "Dasamsha"), "P1"),
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Technique("d12_dwadashamsha", "D12 Dwadashamsha", "varga", ("D12", "Dwadashamsha"), "P2"),
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Technique("d24_chaturvimshamsha", "D24 Chaturvimshamsha", "varga", ("D24", "Chaturvimshamsha", "Siddhamsa"), "P2"),
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Technique("d30_trimsamsha", "D30 Trimsamsha", "varga", ("D30", "Trimsamsha"), "P2"),
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Technique("d60_shashtiamsha", "D60 Shashtiamsha", "varga", ("D60", "Shashtiamsha"), "P1"),
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Technique("darakaraka", "Darakaraka", "relationship", ("Darakaraka", "DK"), "P1"),
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Technique("ashtakoota", "Ashtakoota matching", "relationship", ("Ashtakoota", "Koota", "Guna Milan"), "P1"),
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Technique("mangal_dosha", "Mangal Dosha", "relationship", ("Mangal Dosha", "Kuja Dosha"), "P1"),
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Technique("relationship_combinations", "Relationship rule-family combinations", "relationship", ("relationship combinations", "marriage combinations", "合盘"), "P1"),
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Technique("conception_adhana_niseka", "Adhana / Niseka conception chart", "conception", ("Adhana", "Niseka", "conception chart"), "P2"),
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Technique("argala", "Argala", "interpretation", ("Argala",), "P2"),
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Technique("yoga", "Yoga rules", "interpretation", ("Yoga", "Raja Yoga", "Dhana Yoga"), "P1"),
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)
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def _iter_files(paths: list[str]) -> list[Path]:
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files: list[Path] = []
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for rel in paths:
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base = ROOT / rel
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if not base.exists():
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continue
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if base.is_file():
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files.append(base)
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continue
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for path in base.rglob("*"):
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if path.is_file() and not (set(path.parts) & SKIP_PARTS):
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if path.suffix.lower() in {".py", ".js", ".ts", ".jsx", ".tsx", ".json", ".md", ".txt"}:
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files.append(path)
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return sorted(set(files))
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def _read_layer(files: list[Path]) -> tuple[list[tuple[str, str]], list[str]]:
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indexed: list[tuple[str, str]] = []
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skipped: list[str] = []
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for path in files:
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try:
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if path.stat().st_size > MAX_SCAN_BYTES:
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skipped.append(str(path.relative_to(ROOT)))
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continue
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text = path.read_text(encoding="utf-8", errors="ignore").lower()
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except OSError:
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continue
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indexed.append((str(path.relative_to(ROOT)), text))
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return indexed, skipped
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def _count_hits(indexed_files: list[tuple[str, str]], aliases: tuple[str, ...]) -> tuple[int, list[str]]:
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patterns = []
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for alias in aliases:
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escaped = re.escape(alias.lower())
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if re.fullmatch(r"[a-z0-9]+", alias.lower()) and len(alias) <= 4:
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patterns.append(re.compile(rf"(?<![a-z0-9]){escaped}(?![a-z0-9])"))
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else:
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patterns.append(re.compile(escaped))
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hit_files: list[str] = []
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total = 0
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for rel, text in indexed_files:
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count = sum(len(pattern.findall(text)) for pattern in patterns)
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if count:
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total += count
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hit_files.append(rel)
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return total, hit_files[:12]
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def _state_from_hits(count: int, layer: str) -> str:
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if count <= 0:
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return "missing"
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if layer in {"references", "tests"}:
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return "present"
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if count <= 2:
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return "thin"
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return "present"
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def _claim_status(tech: Technique, layer_states: dict[str, str]) -> str:
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refs = layer_states["references"] != "missing"
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code = layer_states["scripts"] != "missing" or layer_states["api"] != "missing"
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ui = layer_states["ui"] != "missing"
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tests = layer_states["tests"] != "missing"
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if tech.technique_id in {
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"kp_exact_cusp",
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"kp_star_sub_sub",
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"timing_holdout",
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"saham",
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"tajika",
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"gulika",
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"sphuta",
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"prashna",
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}:
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return "blocked_or_observation_only"
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if tech.technique_id in {"shadbala_chesta", "shadbala_sthana", "muhurta"}:
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return "component_partial"
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if refs and code and tests and ui:
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return "invoked_with_boundary"
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if refs and (code or tests):
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return "evidence_present_not_fully_invoked"
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if refs:
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return "reference_only"
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return "gap_candidate"
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def _missing_integration(layer_states: dict[str, str]) -> list[str]:
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missing = []
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for key in ("skill", "api", "ui", "scripts", "tests"):
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if layer_states[key] == "missing":
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missing.append(key)
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return missing
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def _priority_score(tech: Technique, layer_states: dict[str, str], claim_status: str) -> int:
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score = {"P0": 300, "P1": 200, "P2": 100}[tech.p_batch]
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if tech.first_batch:
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score += 80
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if layer_states["references"] != "missing":
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score += 40
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if layer_states["scripts"] != "missing" or layer_states["tests"] != "missing":
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score += 25
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if layer_states["api"] == "missing":
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score += 12
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if layer_states["ui"] == "missing":
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score += 10
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if claim_status in {"blocked_or_observation_only", "component_partial", "evidence_present_not_fully_invoked"}:
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score += 20
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return score
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def build_matrix() -> dict:
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files_by_layer = {layer: _iter_files(paths) for layer, paths in SCAN_ROOTS.items()}
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indexed_by_layer = {}
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skipped_by_layer = {}
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for layer, files in files_by_layer.items():
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indexed_by_layer[layer], skipped_by_layer[layer] = _read_layer(files)
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rows = []
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for tech in TECHNIQUES:
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layer_hits = {}
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layer_samples = {}
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layer_states = {}
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for layer, indexed_files in indexed_by_layer.items():
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count, samples = _count_hits(indexed_files, tech.aliases)
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layer_hits[layer] = count
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layer_samples[layer] = samples
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layer_states[layer] = _state_from_hits(count, layer)
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claim_status = _claim_status(tech, layer_states)
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missing = _missing_integration(layer_states)
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has_material = layer_states["references"] != "missing" or layer_states["tests"] != "missing" or layer_states["scripts"] != "missing"
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uninvoked = has_material and ("api" in missing or "ui" in missing or "skill" in missing)
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rows.append(
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{
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"technique_id": tech.technique_id,
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"label": tech.label,
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"domain": tech.domain,
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"priority_batch": tech.p_batch,
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"first_batch_requested": tech.first_batch,
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"layer_states": layer_states,
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"hit_counts": layer_hits,
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"sample_files": layer_samples,
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"has_material": has_material,
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"has_material_but_not_fully_invoked": uninvoked,
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"missing_integration": missing,
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"claim_status": claim_status,
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"commercial_sync_policy": "sync_observation_or_boundary_contract_only"
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if claim_status in {"blocked_or_observation_only", "component_partial"}
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else "sync_when_invocation_and_claim_gate_are_explicit",
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"claim_boundary": _claim_boundary(tech, claim_status),
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"priority_score": _priority_score(tech, layer_states, claim_status),
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}
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)
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top50 = sorted(
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[row for row in rows if row["has_material_but_not_fully_invoked"]],
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key=lambda row: (-row["priority_score"], row["technique_id"]),
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)[:50]
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first_batch_ids = {
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"ul_arudha_upapada",
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"a7_arudha_relationship",
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"a10_arudha_career",
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"kp_exact_cusp",
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"kp_star_sub_sub",
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"kp_significator",
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"kp_ruling_planets",
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"shadbala_chesta",
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"shadbala_sthana",
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"muhurta",
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"tarabala",
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"chandrabala",
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"rahu_kalam",
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"abhijit_muhurta",
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"prashna",
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"sphuta",
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"gulika",
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"saham",
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"tajika",
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}
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migration_batches = {
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"P0_first_batch_requested": [
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row for row in rows if row["technique_id"] in first_batch_ids and row["priority_batch"] == "P0"
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],
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"P1_first_batch_requested": [
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row for row in rows if row["technique_id"] in first_batch_ids and row["priority_batch"] == "P1"
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],
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"P2_deferred": [row for row in rows if row["priority_batch"] == "P2"],
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}
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return {
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"scope": "full_technique_invocation_matrix",
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"created_at": "2026-07-22",
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"claim_status": "planning_and_invocation_audit",
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"production_tuning_allowed": False,
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"truth_matrix_allowed": False,
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"boundary": "Automated static invocation scan across skill/API/UI/scripts/references/tests. Hit presence is not numeric oracle closure or predictive validation.",
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"scan_roots": SCAN_ROOTS,
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"scan_limits": {
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"max_file_bytes": MAX_SCAN_BYTES,
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"skipped_large_files_by_layer": skipped_by_layer,
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},
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"summary": {
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"technique_count": len(rows),
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"first_batch_count": sum(1 for row in rows if row["first_batch_requested"]),
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"material_but_not_fully_invoked_count": sum(1 for row in rows if row["has_material_but_not_fully_invoked"]),
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"top50_count": len(top50),
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"p0_count": sum(1 for row in rows if row["priority_batch"] == "P0"),
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"p1_count": sum(1 for row in rows if row["priority_batch"] == "P1"),
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"p2_count": sum(1 for row in rows if row["priority_batch"] == "P2"),
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},
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"first_batch_execution_queue": [
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row for row in rows if row["first_batch_requested"] and row["priority_batch"] in {"P0", "P1"}
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],
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"migration_batches": migration_batches,
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"top50_material_not_invoked": top50,
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"rows": rows,
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"content_hash": "",
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}
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def _claim_boundary(tech: Technique, claim_status: str) -> str:
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if tech.technique_id.startswith("kp_"):
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return "KP runtime/probes may be displayed as observation; exact cusp/star-sub-sub needs public numeric worked example before verified timing use."
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if tech.technique_id.startswith("shadbala"):
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return "Shadbala must show component-level unit/formula/method-variant status; no absolute Virupa truth upgrade until component arbitration closes."
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if tech.domain == "muhurta":
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return "Muhurta factors may be shown as observations/scoring inputs; no final election verdict until worked examples validate the scoring matrix."
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if tech.technique_id in {"prashna", "sphuta", "gulika", "saham", "tajika"}:
|
||||
return "Horary/annual numeric packets require public input contract plus expected numeric fields; otherwise observation/queue only."
|
||||
if tech.technique_id == "timing_holdout":
|
||||
return "Exact month/day and rectification claims require frozen positive/negative labels and blind ranking."
|
||||
if claim_status == "reference_only":
|
||||
return "Reference exists but runtime invocation is not proven."
|
||||
return "Use only with explicit source, settings, and claim boundary."
|
||||
|
||||
|
||||
def main() -> None:
|
||||
packet = build_matrix()
|
||||
without_hash = dict(packet)
|
||||
without_hash["content_hash"] = ""
|
||||
digest = hashlib.sha256(json.dumps(without_hash, ensure_ascii=False, sort_keys=True).encode("utf-8")).hexdigest()
|
||||
packet["content_hash"] = digest
|
||||
OUTPUT.write_text(json.dumps(packet, ensure_ascii=False, indent=2) + "\n", encoding="utf-8")
|
||||
print(json.dumps({"path": str(OUTPUT.relative_to(ROOT)), "sha256": digest, "summary": packet["summary"]}, ensure_ascii=False, indent=2))
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
Reference in New Issue
Block a user