From e17098248fbac377f422955917572f79b3684277 Mon Sep 17 00:00:00 2001 From: Claude Date: Wed, 4 Nov 2026 16:53:31 +0800 Subject: [PATCH 1/2] fix(benchmark): pass the ayanamsa to both sides in the Chara, transit and node-mode compares (BUG-1569) Same failure as 74169e1b: run_chara_dasha_compare, run_chara_dasha_knrao, run_transit_true_compare and run_node_mode_compare hard-coded Lahiri on the PyJHora / Swiss side while the engine default is Raman, or never checked the canonical baseline's ayanamsa. Each now takes --ayanamsa (the Chara ones also --node-mode), passes it to both sides, and refuses a baseline or engine output built differently. The Chara and transit compares pointed at a non-existent benchmarks/scripts/ path; fixed. run_skill_baseline.py main gained --ayanamsa / --node-mode. Raman rerun (19 charts): Chara MD signs 228/228, years 225/228; K.N. Rao on shared positions 117/120; transit 646/646; Swiss mean node 152/152. Co-Authored-By: Claude Opus 5.5 Claude-Session: https://claude.ai/code/session_01DbBXoyeZrYn6ryNcSe5Y2Y --- .../scripts/run_chara_dasha_compare.py | 34 +++++--- .../jyotish/scripts/run_chara_dasha_knrao.py | 19 ++++- .../jyotish/scripts/run_node_mode_compare.py | 34 +++++--- .../jyotish/scripts/run_skill_baseline.py | 9 ++- .../scripts/run_transit_true_compare.py | 41 ++++++---- ...st_benchmark_ayanamsa_plumbing_20261104.py | 79 +++++++++++++++++++ 6 files changed, 179 insertions(+), 37 deletions(-) create mode 100644 tests/test_benchmark_ayanamsa_plumbing_20261104.py diff --git a/benchmarks/jyotish/scripts/run_chara_dasha_compare.py b/benchmarks/jyotish/scripts/run_chara_dasha_compare.py index 088b5ec3..b105e06a 100644 --- a/benchmarks/jyotish/scripts/run_chara_dasha_compare.py +++ b/benchmarks/jyotish/scripts/run_chara_dasha_compare.py @@ -10,6 +10,7 @@ PyJHora's KN Rao Chara Dasha over fictional/public smoke samples. This script is intended to identify whether the local module is production-grade or only a placeholder workflow component. """ +import argparse import csv import json import sys @@ -23,7 +24,7 @@ OUT = ROOT / 'outputs' CANON = OUT / 'canonical' REPORT = OUT / 'jyotish_benchmark_round7_chara_dasha_compare.md' MATRIX = OUT / 'chara_dasha_comparison_matrix.csv' -SKILL_SCRIPTS = Path(__file__).resolve().parents[2] / 'scripts' +SKILL_SCRIPTS = Path(__file__).resolve().parents[3] / 'scripts' PYJHORA_SITE = Path(__import__('os').environ.get('PYJHORA_SITE', '')) PYJHORA_COMPAT = ROOT / 'scripts/pyjhora_compat' @@ -71,7 +72,7 @@ def local_chara(sample, c): return [{'order': x['order'], 'sign': x['sign'], 'duration_years': float(x['duration_years'])} for x in d['dasha_sequence']] -def pyjhora_chara(sample): +def pyjhora_chara(sample, *, ayanamsa='lahiri', node_mode='mean'): if str(PYJHORA_COMPAT) not in sys.path: sys.path.insert(0, str(PYJHORA_COMPAT)) if str(PYJHORA_SITE) not in sys.path: @@ -80,8 +81,12 @@ def pyjhora_chara(sample): from jhora import const from jhora.panchanga import drik from jhora.horoscope.dhasa.raasi import chara - const._DEFAULT_AYANAMSA_MODE = 'LAHIRI' - drik.set_ayanamsa_mode('LAHIRI') + # Both sides use the requested ayanamsa and node mode; the engine default + # is Raman and PyJHora's is TRUE_PUSHYA (2026-11-04 audit H). + const._DEFAULT_AYANAMSA_MODE = ayanamsa.upper() + drik.set_ayanamsa_mode(ayanamsa.upper()) + const.set_node_mode(node_mode == 'true') + drik.set_planet_list(set_rahu_ketu_as_true_nodes=(node_mode == 'true')) b = sample['birth'] dob = (b['year'], b['month'], b['day']) tob = (b['hour'], b['minute'], 0) @@ -120,7 +125,7 @@ def summarize(rows, prefix=None): return total, match, total - match, match / total if total else 0.0 -def write_report(rows, per_sample): +def write_report(rows, per_sample, *, ayanamsa='lahiri', sample_count=None): lines = [] lines.append('# Jyotish benchmark 第七轮：Chara Dasha / Jaimini 时间线对标') lines.append('') @@ -130,7 +135,8 @@ def write_report(rows, per_sample): lines.append('') lines.append('- 验证当前 skill `scripts/jaimini.py` 的 Chara Dasha 是否可作为正式计算模块使用。') lines.append('- 对标对象：PyJHora `raasi/chara.py` 的 KN Rao method（PyJHora 默认 `CHARA_TYPE_DEFAULT = KN_RAO`）。') - lines.append('- 样本仍为10个公开/虚构 smoke case，不包含用户个人资料。') + lines.append(f'- 样本：{sample_count if sample_count is not None else len(per_sample)} 个公开 / 虚构样本，不包含用户个人资料。') + lines.append(f'- 口径：两边都用 {ayanamsa.capitalize()}、平均交点；本地行星位置取自同口径的 canonical 基线。') lines.append('') lines.append('## 2. 总体结果') lines.append('') @@ -161,15 +167,25 @@ def write_report(rows, per_sample): return '\n'.join(lines) -def main(): +def main(argv=None): + parser = argparse.ArgumentParser(description='Compare the local K.N. Rao Chara Dasha against PyJHora.') + parser.add_argument('--ayanamsa', choices=['lahiri', 'raman'], default='lahiri', + help='Ayanamsa for both sides; the canonical baseline must have been built with the same one.') + parser.add_argument('--node-mode', choices=['mean', 'true'], default='mean') + args = parser.parse_args(argv) + sys.path.insert(0, str(Path(__file__).resolve().parent)) + from run_pyjhora_compare import baseline_settings_error samples = json.loads(DATA.read_text()) rows = [] per_sample = [] for sample in samples: sid = sample['id'] c = canon(sid) + settings_error = baseline_settings_error(c, ayanamsa=args.ayanamsa, node_mode=args.node_mode) + if settings_error: + parser.error(f'{sid}: {settings_error}; rebuild with run_skill_baseline.py --ayanamsa {args.ayanamsa}') local = local_chara(sample, c) - pyj = pyjhora_chara(sample) + pyj = pyjhora_chara(sample, ayanamsa=args.ayanamsa, node_mode=args.node_mode) sign_match = 0 duration_match = 0 for i in range(12): @@ -191,7 +207,7 @@ def main(): writer = csv.DictWriter(f, fieldnames=list(rows[0].keys())) writer.writeheader() writer.writerows(rows) - REPORT.write_text(write_report(rows, per_sample)) + REPORT.write_text(write_report(rows, per_sample, ayanamsa=args.ayanamsa, sample_count=len(samples))) print(json.dumps({'report': str(REPORT), 'matrix': str(MATRIX), 'rows': len(rows)}, ensure_ascii=False, indent=2)) diff --git a/benchmarks/jyotish/scripts/run_chara_dasha_knrao.py b/benchmarks/jyotish/scripts/run_chara_dasha_knrao.py index 0722d244..f152f49e 100644 --- a/benchmarks/jyotish/scripts/run_chara_dasha_knrao.py +++ b/benchmarks/jyotish/scripts/run_chara_dasha_knrao.py @@ -8,6 +8,7 @@ Chara Dasha KN Rao Benchmark v1.1 依赖: pip install jhora numpy """ +import argparse import sys, json, os # 添加scripts路径 @@ -44,7 +45,15 @@ PLANET_NAMES = { } -def run_benchmark(): +def run_benchmark(ayanamsa='lahiri', node_mode='mean'): + # Shared positions come from PyJHora, so the ayanamsa does not change the + # algorithm comparison, but it decides which sign each planet is in; set + # it explicitly instead of inheriting PyJHora's TRUE_PUSHYA default + # (2026-11-04 audit H). + const._DEFAULT_AYANAMSA_MODE = ayanamsa.upper() + drik.set_ayanamsa_mode(ayanamsa.upper()) + const.set_node_mode(node_mode == 'true') + drik.set_planet_list(set_rahu_ketu_as_true_nodes=(node_mode == 'true')) total_sign = 0; sign_match = 0 total_dur = 0; dur_match = 0 detail_lines = [] @@ -154,6 +163,8 @@ def run_benchmark(): result = { "version": "v6.1.11", "benchmark": "chara_dasha_kn_rao", + "ayanamsa": ayanamsa, + "node_mode": node_mode, "total_sign_match": sign_match, "total_dur_match": dur_match, "total_sign": total_sign, @@ -169,4 +180,8 @@ def run_benchmark(): if __name__ == "__main__": - run_benchmark() + _parser = argparse.ArgumentParser(description="K.N. Rao Chara Dasha: local helpers vs PyJHora on shared PyJHora positions.") + _parser.add_argument("--ayanamsa", choices=["lahiri", "raman"], default="lahiri") + _parser.add_argument("--node-mode", choices=["mean", "true"], default="mean") + _args = _parser.parse_args() + run_benchmark(_args.ayanamsa, _args.node_mode) diff --git a/benchmarks/jyotish/scripts/run_node_mode_compare.py b/benchmarks/jyotish/scripts/run_node_mode_compare.py index 8df0a491..fe967a8d 100644 --- a/benchmarks/jyotish/scripts/run_node_mode_compare.py +++ b/benchmarks/jyotish/scripts/run_node_mode_compare.py @@ -8,6 +8,7 @@ Compares local Jyotish skill canonical output against Swiss Ephemeris Mean/True Node and PyJHora's default rasi_chart node mode. Samples are fictional/public smoke cases. """ +import argparse import csv import json import math @@ -33,6 +34,9 @@ NAKSHATRAS = [ 'Mula','Purva Ashadha','Uttara Ashadha','Shravana','Dhanishta','Shatabhisha','Purva Bhadrapada','Uttara Bhadrapada','Revati' ] PYJHORA_PLANET_ID = {7: 'Rahu', 8: 'Ketu'} +# Both sides get the ayanamsa explicitly; the canonical baseline must have been +# built with the same one (2026-11-04 audit H). +SIDEREAL_MODES = {'lahiri': swe.SIDM_LAHIRI, 'raman': swe.SIDM_RAMAN} def norm(deg): @@ -73,9 +77,9 @@ def point_from_lon(lon): } -def swiss_nodes(sample, node_pid): +def swiss_nodes(sample, node_pid, ayanamsa='lahiri'): jd = julian_day_utc(sample['birth']) - swe.set_sid_mode(swe.SIDM_LAHIRI, 0, 0) + swe.set_sid_mode(SIDEREAL_MODES[ayanamsa], 0, 0) flags = swe.FLG_SWIEPH | swe.FLG_SIDEREAL | swe.FLG_SPEED res, _ = swe.calc_ut(jd, node_pid, flags) rahu = point_from_lon(res[0]) @@ -104,7 +108,7 @@ def patch_swisseph_for_pyjhora(): return swe -def pyjhora_default_nodes(sample): +def pyjhora_default_nodes(sample, ayanamsa='lahiri'): # PyJHora is used only as an external benchmark. Do not vendor/copy its code into the skill. if str(PYJHORA_COMPAT) not in sys.path: sys.path.insert(0, str(PYJHORA_COMPAT)) @@ -114,8 +118,8 @@ def pyjhora_default_nodes(sample): from jhora import utils, const from jhora.panchanga import drik from jhora.horoscope.chart import charts - const._DEFAULT_AYANAMSA_MODE = 'LAHIRI' - drik.set_ayanamsa_mode('LAHIRI') + const._DEFAULT_AYANAMSA_MODE = ayanamsa.upper() + drik.set_ayanamsa_mode(ayanamsa.upper()) # Note: charts.rasi_chart -> drik.dhasavarga() defaults to set_rahu_ketu_as_true_nodes=True. b = sample['birth'] jd = utils.julian_day_number((b['year'], b['month'], b['day']), (b['hour'], b['minute'], 0)) @@ -186,7 +190,7 @@ def write_report(rows): lines.append('') lines.append('- 解释第三轮 PyJHora 对比中 Rahu/Ketu 大量差异的根因。') lines.append('- 对比当前 skill canonical baseline 与 Swiss Ephemeris Mean Node、Swiss Ephemeris True Node、PyJHora rasi_chart 默认输出。') - lines.append('- 样本仍为10个公开/虚构 smoke case，不包含用户个人资料。') + lines.append('- 样本：公开 / 虚构样本，不包含用户个人资料；岁差两边显式传入。') lines.append('') lines.append('## 2. 总体结果') lines.append('') @@ -223,16 +227,26 @@ def write_report(rows): return '\n'.join(lines) -def main(): +def main(argv=None): + parser = argparse.ArgumentParser(description='Arbitrate the local Rahu / Ketu against Swiss mean / true node and PyJHora.') + parser.add_argument('--ayanamsa', choices=sorted(SIDEREAL_MODES), default='lahiri', + help='Ayanamsa for every side; the canonical baseline must have been built with the same one.') + args = parser.parse_args(argv) + sys.path.insert(0, str(Path(__file__).resolve().parent)) + from run_pyjhora_compare import baseline_settings_error samples = json.loads(DATA.read_text()) rows = [] for sample in samples: sample_id = sample['id'] + canonical = json.loads((CANON / f'{sample_id}.canonical.json').read_text()) + settings_error = baseline_settings_error(canonical, ayanamsa=args.ayanamsa, node_mode='mean') + if settings_error: + parser.error(f'{sample_id}: {settings_error}; rebuild with run_skill_baseline.py --ayanamsa {args.ayanamsa}') local = local_nodes(sample_id) targets = { - 'swiss_mean_node': swiss_nodes(sample, swe.MEAN_NODE), - 'swiss_true_node': swiss_nodes(sample, swe.TRUE_NODE), - 'pyjhora_default_rasi': pyjhora_default_nodes(sample), + 'swiss_mean_node': swiss_nodes(sample, swe.MEAN_NODE, args.ayanamsa), + 'swiss_true_node': swiss_nodes(sample, swe.TRUE_NODE, args.ayanamsa), + 'pyjhora_default_rasi': pyjhora_default_nodes(sample, args.ayanamsa), } for target_name, target_nodes in targets.items(): for body in ['Rahu', 'Ketu']: diff --git a/benchmarks/jyotish/scripts/run_skill_baseline.py b/benchmarks/jyotish/scripts/run_skill_baseline.py index a2731af5..64cb18ff 100644 --- a/benchmarks/jyotish/scripts/run_skill_baseline.py +++ b/benchmarks/jyotish/scripts/run_skill_baseline.py @@ -235,12 +235,17 @@ def write_report(samples, results): return report -def main(): +def main(argv=None): + import argparse + parser = argparse.ArgumentParser(description='Build the local canonical baselines for the benchmark samples.') + parser.add_argument('--ayanamsa', choices=['lahiri', 'raman'], default=DEFAULT_AYANAMSA) + parser.add_argument('--node-mode', choices=['mean', 'true'], default=DEFAULT_NODE_MODE) + args = parser.parse_args(argv) OUT.mkdir(parents=True, exist_ok=True) RAW.mkdir(parents=True, exist_ok=True) CANON.mkdir(parents=True, exist_ok=True) samples = json.loads(DATA.read_text()) - results = [run_sample(sample) for sample in samples] + results = [run_sample(sample, ayanamsa=args.ayanamsa, node_mode=args.node_mode) for sample in samples] summary = {'total': len(results), 'ok': sum(1 for r in results if r.get('ok')), 'results': [{'id': r['id'], 'ok': r.get('ok'), 'error': r.get('error')} for r in results]} (OUT / 'run_summary.json').write_text(json.dumps(summary, ensure_ascii=False, indent=2)) rows = flatten_rows(results) diff --git a/benchmarks/jyotish/scripts/run_transit_true_compare.py b/benchmarks/jyotish/scripts/run_transit_true_compare.py index faee699e..28bfa513 100644 --- a/benchmarks/jyotish/scripts/run_transit_true_compare.py +++ b/benchmarks/jyotish/scripts/run_transit_true_compare.py @@ -3,6 +3,7 @@ # or JYOTISH_SKILL_SCRIPT is provided. Raw output directories are generated locally # and are intentionally not committed. #!/usr/bin/env python3 +import argparse import csv import json import subprocess @@ -13,7 +14,7 @@ from pathlib import Path import swisseph as swe ROOT = Path(__file__).resolve().parents[1] -SKILL_SCRIPT = Path(__file__).resolve().parents[2] / 'scripts' / 'jyotish_engine.py' +SKILL_SCRIPT = Path(__file__).resolve().parents[3] / 'scripts' / 'jyotish_engine.py' PYTHON = Path(sys.executable) DATA = ROOT / 'data/benchmark_samples.json' OUT = ROOT / 'outputs' @@ -31,6 +32,10 @@ PLANETS = { 'Rahu': swe.MEAN_NODE, } SIGNS = ['Aries','Taurus','Gemini','Cancer','Leo','Virgo','Libra','Scorpio','Sagittarius','Capricorn','Aquarius','Pisces'] +# Both sides get the ayanamsa explicitly: the engine default is Raman, and this +# script used to compare an engine-default full reading with Lahiri Swiss +# positions (2026-11-04 audit H). +SIDEREAL_MODES = {'lahiri': swe.SIDM_LAHIRI, 'raman': swe.SIDM_RAMAN} def normalize(deg): @@ -53,9 +58,9 @@ def julian_day_for_transit(date_str, tz): return swe.julday(utc_dt.year, utc_dt.month, utc_dt.day, hour, swe.GREG_CAL) -def calc_swiss_transit(date_str, tz): +def calc_swiss_transit(date_str, tz, ayanamsa='lahiri'): jd = julian_day_for_transit(date_str, tz) - swe.set_sid_mode(swe.SIDM_LAHIRI, 0, 0) + swe.set_sid_mode(SIDEREAL_MODES[ayanamsa], 0, 0) flags = swe.FLG_SWIEPH | swe.FLG_SIDEREAL | swe.FLG_SPEED planets = {} for name, pid in PLANETS.items(): @@ -75,10 +80,10 @@ def calc_swiss_transit(date_str, tz): 'degree_in_sign': round(degree_in_sign(ketu_lon), 6), 'retrograde': planets['Rahu']['retrograde'], } - return {'julian_day_ut': jd, 'planets': planets, 'parameters': {'ayanamsa': 'Lahiri', 'node': 'Mean Node'}} + return {'julian_day_ut': jd, 'planets': planets, 'parameters': {'ayanamsa': ayanamsa, 'node': 'Mean Node'}} -def run_full_reading(sample): +def run_full_reading(sample, ayanamsa='lahiri'): birth = sample['birth'] transit_date = sample.get('today', '2026-06-03') cmd = [ @@ -94,6 +99,7 @@ def run_full_reading(sample): '--today', transit_date, '--transit-date', transit_date, '--node-mode', 'mean', + '--ayanamsa', ayanamsa, ] proc = subprocess.run(cmd, text=True, capture_output=True) raw_path = RAW / f"{sample['id']}.transit_full_reading.json" @@ -105,13 +111,16 @@ def run_full_reading(sample): return data -def compare_sample(sample): +def compare_sample(sample, ayanamsa='lahiri'): transit_date = sample.get('today', '2026-06-03') - data = run_full_reading(sample) + data = run_full_reading(sample, ayanamsa) + reported = str((data.get('birth_info') or {}).get('ayanamsa_name') or '').lower() + if reported and reported != ayanamsa: + raise RuntimeError(f"{sample['id']}: engine reported ayanamsa {reported}, comparison asked for {ayanamsa}") modules = data.get('modules', {}) local_transit = modules.get('transit_positions', {}) local_multi = modules.get('transit_multi_reference', {}) - swiss = calc_swiss_transit(transit_date, sample['birth']['tz']) + swiss = calc_swiss_transit(transit_date, sample['birth']['tz'], ayanamsa) (TRANSIT_OUT / f"{sample['id']}.swiss_transit.json").write_text(json.dumps(swiss, ensure_ascii=False, indent=2)) rows = [] @@ -184,7 +193,7 @@ def compare_sample(sample): return rows -def write_report(rows): +def write_report(rows, *, ayanamsa='lahiri', sample_count=None): total = len(rows) matches = sum(1 for r in rows if r['status'] == 'match') mismatches = [r for r in rows if r['status'] == 'mismatch'] @@ -202,8 +211,8 @@ def write_report(rows): lines.append('## 1. 范围') lines.append('') lines.append('- 对比对象：full-reading.modules.transit_positions / transit_multi_reference vs 直接调用 Swiss Ephemeris。') - lines.append('- 样本：10个公开/虚构 smoke case，不包含真实用户个人资料。') - lines.append('- 配置：Sidereal Lahiri，Mean Node，transit date 使用样本 today 字段。') + lines.append(f'- 样本：{sample_count} 个公开 / 虚构样本，不包含真实用户个人资料。') + lines.append(f'- 配置：Sidereal {ayanamsa.capitalize()}（两边显式传入），Mean Node，transit date 使用样本 today 字段。') lines.append('- 重点：确认 full-reading 的多参考点 Transit 不再使用 natal positions fallback，而是使用真实过境行星位置。') lines.append('') lines.append('## 2. 总体结果') @@ -240,20 +249,24 @@ def write_report(rows): return report -def main(): +def main(argv=None): + parser = argparse.ArgumentParser(description='Compare full-reading transit positions with Swiss Ephemeris.') + parser.add_argument('--ayanamsa', choices=sorted(SIDEREAL_MODES), default='lahiri', + help='Ayanamsa passed to both the engine and the Swiss Ephemeris side.') + args = parser.parse_args(argv) OUT.mkdir(parents=True, exist_ok=True) RAW.mkdir(parents=True, exist_ok=True) TRANSIT_OUT.mkdir(parents=True, exist_ok=True) samples = json.loads(DATA.read_text()) all_rows = [] for sample in samples: - all_rows.extend(compare_sample(sample)) + all_rows.extend(compare_sample(sample, args.ayanamsa)) csv_path = OUT / 'transit_true_comparison_matrix.csv' with csv_path.open('w', newline='') as f: writer = csv.DictWriter(f, fieldnames=['sample_id','body','field','local_skill','swiss_direct','delta','status']) writer.writeheader() writer.writerows(all_rows) - report = write_report(all_rows) + report = write_report(all_rows, ayanamsa=args.ayanamsa, sample_count=len(samples)) print(json.dumps({ 'rows': len(all_rows), 'matches': sum(1 for r in all_rows if r['status'] == 'match'), diff --git a/tests/test_benchmark_ayanamsa_plumbing_20261104.py b/tests/test_benchmark_ayanamsa_plumbing_20261104.py new file mode 100644 index 00000000..75096ffa --- /dev/null +++ b/tests/test_benchmark_ayanamsa_plumbing_20261104.py @@ -0,0 +1,79 @@ +"""BUG-1569: the Chara, transit and node-mode benchmark scripts pass the ayanamsa +to both sides and refuse a canonical baseline built with another one. + +Same failure as 74169e1b: one side hard-coded Lahiri while the engine default +is Raman, so a 1.446 degree ayanamsa gap read as an algorithm difference. +""" + +from __future__ import annotations + +import json +from pathlib import Path + +import pytest +import swisseph as swe + +ROOT = Path(__file__).resolve().parents[1] +SCRIPTS = ROOT / "benchmarks" / "jyotish" / "scripts" + + +@pytest.mark.parametrize("name", [ + "run_chara_dasha_compare.py", "run_chara_dasha_knrao.py", + "run_transit_true_compare.py", "run_node_mode_compare.py", +]) +def test_no_script_hard_codes_lahiri_and_each_takes_the_ayanamsa(name): + source = (SCRIPTS / name).read_text(encoding="utf-8") + assert "set_ayanamsa_mode('LAHIRI')" not in source + assert "SIDM_LAHIRI, 0, 0" not in source + assert "--ayanamsa" in source + + +def test_engine_paths_point_at_the_repository_scripts(): + from benchmarks.jyotish.scripts import run_chara_dasha_compare, run_transit_true_compare + + assert (run_chara_dasha_compare.SKILL_SCRIPTS / "jaimini.py").is_file() + assert run_transit_true_compare.SKILL_SCRIPT.is_file() + + +def test_transit_compare_passes_the_ayanamsa_to_engine_and_swiss(monkeypatch, tmp_path): + from benchmarks.jyotish.scripts import run_transit_true_compare as rtc + + seen = {} + + class Done: + returncode = 0 + stdout = json.dumps({"birth_info": {"ayanamsa_name": "raman"}, "modules": {}}) + stderr = "" + + def fake_run(cmd, **kwargs): + seen["cmd"] = cmd + return Done() + + monkeypatch.setattr(rtc, "RAW", tmp_path) + monkeypatch.setattr(rtc.subprocess, "run", fake_run) + sample = {"id": "fixture", "today": "2026-11-04", + "birth": {"year": 2000, "month": 1, "day": 1, "hour": 0, "minute": 0, "lat": 0, "lon": 0, "tz": 0}} + rtc.run_full_reading(sample, "raman") + assert seen["cmd"][seen["cmd"].index("--ayanamsa") + 1] == "raman" + raman = rtc.calc_swiss_transit("2026-11-04", 0, "raman")["planets"]["Saturn"]["longitude"] + lahiri = rtc.calc_swiss_transit("2026-11-04", 0, "lahiri")["planets"]["Saturn"]["longitude"] + assert 1.3 < (raman - lahiri) % 360 < 1.6 + monkeypatch.setattr(rtc, "TRANSIT_OUT", tmp_path) + with pytest.raises(RuntimeError, match="ayanamsa"): + rtc.compare_sample(sample, "lahiri") + + +@pytest.mark.parametrize("module_name", ["run_chara_dasha_compare", "run_node_mode_compare"]) +def test_canonical_baseline_from_another_ayanamsa_is_refused(module_name, monkeypatch, tmp_path): + import importlib + + module = importlib.import_module(f"benchmarks.jyotish.scripts.{module_name}") + canon = tmp_path / "canonical" + canon.mkdir() + (canon / "fixture.canonical.json").write_text(json.dumps({"parameters": {"ayanamsa": "raman", "node_mode": "mean"}})) + data = tmp_path / "samples.json" + data.write_text(json.dumps([{"id": "fixture", "label": "x", "birth": {}}])) + monkeypatch.setattr(module, "CANON", canon) + monkeypatch.setattr(module, "DATA", data) + with pytest.raises(SystemExit): + module.main(["--ayanamsa", "lahiri"]) From 5f234c315b928d85a294db6fcc9ce35024e9dc20 Mon Sep 17 00:00:00 2001 From: Claude Date: Wed, 4 Nov 2026 16:53:31 +0800 Subject: [PATCH 2/2] fix(jyotish): Chara co-lord and antardasha, night time-segment points, pre-sunrise weekday; re-freeze as audit_h (BUG-1565..1568) Data audit wave 2 (H) against PyJHora 4.8.6 and Swiss Ephemeris, 19 charts, Raman and Lahiri passed explicitly to both sides. - BUG-1566 (jaimini.py): the K.N. Rao Chara Scorpio / Aquarius lord read both co-lords' dignity in the dasha sign itself, so Scorpio was always Ketu and Aquarius always Saturn. Now one lord in the sign gives way to the other (K.N. Rao; Rath p.43 (c); PyJHora); otherwise compared where each stands (companions, Jupiter / Mercury / dispositor, dignity, modality, degrees). MD years vs PyJHora 212/228 -> 225/228 (Raman), 226/228 (Lahiri). - BUG-1567 (jaimini.py): K.N. Rao antardashas now run each MD's own direction with the MD sign last (pp.35-36); book order 19/228 -> 228/228. - BUG-1565 (gulika.py): Wednesday-Saturday night share table started one lord early; Maandi and the four other time-segment points 79/114 -> 114/114 against an independent Swiss computation. Gulika unchanged (19/19). - BUG-1568 (jyotish_engine.py): natal Panchanga vara / hora used the civil date; a birth before sunrise belongs to the previous weekday (15/19 -> 19/19 vs PyJHora drik.vaara). Narayana (legacy and Rath), transits, sunrise and day/night: no defect; the second-cycle rule matches PyJHora's. Variants are listed in BUG_HISTORY. jaimini.py is in the frozen identity: per ERR-110, new records frozen and replayed as audit_h_2026_11_04; contract, freshness test and frontend gate test rotated. Versus moon_paksha_2026_11_04: sealed 20/20 and reported offset 900/900 identical, metrics and summary unchanged. Chara sections of two frontend fixtures and the rashi-dasha PyJHora fixture's native rows updated. Co-Authored-By: Claude Opus 5.5 Claude-Session: https://claude.ai/code/session_01DbBXoyeZrYn6ryNcSe5Y2Y --- CHANGELOG.md | 8 + docs/BUG_HISTORY.md | 77 + docs/research/pre_work_error_ledger.md | 1 + ...rted_offset_audit_h_2026_11_04.freeze.json | 118 + .../reported_offset_audit_h_2026_11_04.json | 42510 ++++++++++++++++ ...ldout_rerun_audit_h_2026_11_04.freeze.json | 116 + ...aled_holdout_rerun_audit_h_2026_11_04.json | 1941 + ...a-zero-year-1985-08-03-beijing.golden.json | 2 +- .../tests/fixtures/chart-view-golden.json | 1008 +- .../rectification-confirmation-gate.test.ts | 8 +- .../rectification_sealed_holdout.v1.json | 258 +- scripts/gulika.py | 10 +- scripts/jaimini.py | 144 +- scripts/jyotish_engine.py | 7 +- scripts/research/reported_offset_sweep.py | 7 +- scripts/research/sealed_holdout_rerun.py | 7 +- .../rashi_dasha_pyjhora_20261008.json | 9 +- tests/test_audit_h_dasha_sky_20261104.py | 199 + tests/test_chara_dasha_board_lord.py | 18 +- tests/test_rashi_dashas_native.py | 3 + .../test_sealed_holdout_contract_freshness.py | 5 + 21 files changed, 45755 insertions(+), 701 deletions(-) create mode 100644 docs/research/reported_offset_audit_h_2026_11_04.freeze.json create mode 100644 docs/research/reported_offset_audit_h_2026_11_04.json create mode 100644 docs/research/sealed_holdout_rerun_audit_h_2026_11_04.freeze.json create mode 100644 docs/research/sealed_holdout_rerun_audit_h_2026_11_04.json create mode 100644 tests/test_audit_h_dasha_sky_20261104.py diff --git a/CHANGELOG.md b/CHANGELOG.md index 9abae0a4..f239e8da 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,5 +1,13 @@ # 印度占星 Skill 更新日志 +## 2026-11-04 — 数据核对 H：Chara Dasha 双主星与小运、时段点夜段、日出前出生的星期 + +- K.N. Rao Chara Dasha 的天蝎 / 水瓶宫主以前与盘面无关（天蝎总是计都、水瓶总是土星），现在一主在本宫取另一主，两主都在外按所在星座比强弱；天蝎、水瓶两段的年数与其后各段起止可能变化（例：布什公开盘天蝎 13 → 9 年，乔布斯水瓶 5 → 1 年），与 PyJHora 的年数一致率 93% → 99%（BUG-1566）。 +- K.N. Rao Chara 的小运按 K.N. Rao 原书：每个大运按自己的顺逆，从下一星座起，本运星座排最后；以前除第一运外都不对（BUG-1567）。 +- 星盘页特殊点层的 Maandi、Kaala、Mrityu、Artha Praharaka、Yama Ghantaka：周三到周六夜里出生的盘以前落在错的时段，已改正；Gulika 不变（BUG-1565）。 +- 完整解读 / 报告里的出生星期（vara）和时主：日出前出生按前一天算（BUG-1568）。 +- 对照脚本两边都显式传岁差（BUG-1569）。Narayana、行运、日出与外部引擎核对后未发现缺陷，流派差异列给占星师。生时校正结果不变。Skill 版本不变；没有数据库变更。 + ## 2026-11-04 — Shadbala：月亮的盈亏力不再重复计入 - 六力里月亮的盈亏力（Paksha）以前被算了四倍（时力里乘 2，动力又取乘 2 后的值），现按 BPHS（Santhanam 译本）27.10–11 + 27.18：时力里不乘 2，动力等于盈亏力，合计两倍。月亮的六力总分、Ishta / Kashta 和「最强星」可能变化（例：奥巴马公开盘最强星由月亮变为太阳），其他六颗星不变；结果里 `method_variants.moon_paksha` 写明口径（BUG-1557）。生时校正结果不变。Skill 版本不变；没有数据库变更。 diff --git a/docs/BUG_HISTORY.md b/docs/BUG_HISTORY.md index 060e2d78..f48bace7 100644 --- a/docs/BUG_HISTORY.md +++ b/docs/BUG_HISTORY.md @@ -21364,3 +21364,80 @@ - 关联记录：BUG-1540（VISIBLE VOICE 合并）。 - 复发自：无 - 修复版本：分支 `codex/login-rectify-loading-1103`，待合并。 + +## BUG-1565 | 时段点夜段分配表周三到周六整体错一格：Maandi 和 Gulika 不在同一个土星段，Kaala 等四点落在别的星段 + +- 状态：resolved（引擎 + 回归测试；未部署） +- 首次发现 / 最近更新：2026-11-04（数据核对 H：19 张对照盘逐张用 Swiss Ephemeris 独立重算八分段）/ 2026-11-04 +- 影响面：`scripts/gulika.py` `NIGHT_RULERS`，经 `_temporal_upagraha` 影响 `calculate_upagrahas` 的 Maandi、Kaala、Mrityu、Artha_Praharaka、Yama_Ghantaka：星盘页特殊点层（`chart_view_points/api.py`）、完整解读的 upagraha 包（`_build_natal_foundation_modules`）。Gulika 本身走 `SATURN_PART_START`，本来就对，不受影响。 +- 现象：19 张盘里 7 张夜生盘（乔布斯周四夜、奥巴马 / 泰勒 / 洛杉矶周五夜、琵雅芙 / 伦敦周六夜、齐达内周四夜）这五个点全部偏一段（几度到几十度）；例：乔布斯（Raman）Maandi 射手 26.93°，应为射手 3.35°，与 Gulika（天蝎 22.80°，同一土星段的起点）不在同一段。 +- 触发条件：出生在周三、周四、周五、周六的夜段（日落到次日日出；按开启该段的日落所在日期算星期）。 +- 根因：夜段八分的第一段应由「当天星期主数起第五位」的行星主管（周六夜从水星起），表里周三到周六四行都从前一位起（周六夜从火星起）。白天表与 `SATURN_PART_START` 是对的，夜段表手写时错位，两张表没有互相校验。 +- 修复：改正 `NIGHT_RULERS` 的周三到周六四行，与 PyJHora `const.night_rulers` 同表；注释写明规则。 +- 验证：`tests/test_audit_h_dasha_sky_20261104.py`：七天白天 / 夜段第一段与「星期主 / 第五位」一致、土星所在段与 `SATURN_PART_START` 一致；乔布斯、泰勒、伦敦三张周四到周六夜生盘五个时段点与独立 Swiss 计算差 ≤ 0.01°，Maandi 的段位 = Gulika 段位 + 1/16。修复后 19 张盘 × 2 种岁差 114/114 与独立计算一致（修复前 79/114）。`test_gulika*.py` 通过。 +- 未改（口径，列给占星师）：PyJHora 的八段循环把「无主段」放在土星段之后，BPHS 读法是第八段无主；Gulika / Maandi 两种读法相同，Kaala 等四点在 114 项里有 42 项不同。PyJHora 4.8.6 `upagraha_longitude` 夜段用次日日出作起点、以「日落与次日日出钟点差」作夜长，夜生盘 Gulika 与本仓差 128–177°，夜段不能作对照。 +- 防复发：上述测试锁两张表互相一致。 +- 关联记录：BUG-1388（夜段终点用真实次日日出）、BUG-513。 +- 复发自：无 +- 修复版本：分支 `codex/audit-dasha-sky-20261104`（未推送）。 + +## BUG-1566 | K.N. Rao Chara Dasha 天蝎 / 水瓶的宫主一律取计都 / 土星：按大运星座本身比尊贵，没有「一主在本宫取另一主」 + +- 状态：resolved（引擎 + 回归测试；未部署） +- 首次发现 / 最近更新：2026-11-04（数据核对 H：19 张盘 × Raman / Lahiri 与 PyJHora 4.8.6 `chara` KN_RAO 逐段对照）/ 2026-11-04 +- 影响面：`scripts/jaimini.py` `_resolve_chara_dasha_lord`、`_jaimini_stronger_planet`（新增 `_co_lord_strength`、`_rasi_drishti`）；连带 `calc_chara_dasha` / `calc_chara_dasha_with_antardasha` 天蝎、水瓶两段的宫主、年数与其后各段起止：咨询 `modules.chara_dasha`（数据卡 Chara 当前运）、`/api/dasha/chara` 与星盘页 Chara 宫主标注（issue #163）、完整解读 Jaimini、报告 Rashi 大运章 Chara 表。Narayana（两条时间轴）不用这两个函数，不受影响。 +- 现象：19 张盘每种岁差 228 段里 16 段年数与 PyJHora 不同，全部在天蝎、水瓶。布什公开盘计都在天蝎、火星在狮子，天蝎给 13 年（PyJHora 9）；泰勒水瓶 1 年（PyJHora 11）；乔布斯水瓶 5 年（PyJHora 1）。 +- 触发条件：盘中有天蝎或水瓶大运（每张盘都有），且计都 / 土星不是按规则该取的那一颗。 +- 根因：`_jaimini_stronger_planet` 用大运星座（天蝎 / 水瓶）本身判断两颗主星的尊贵，与它们实际所在星座无关：天蝎里计都「入旺」永远胜火星，水瓶里土星「本宫」永远胜罗睺，结果与盘面无关；也没有「一主在本宫、另一主在外，取在外者」这条（K.N. Rao《Predicting through Jaimini's Chara Dasha》；Rath《Narayana Dasa》p.43 (c)；PyJHora basic rule；`references/prashna-complete-guide.md` 双主星第 1 条）。函数注释说「基于 PyJHora _stronger_planet_new」，实际没有照它的次序。 +- 修复：一主在本宫、另一主在外，取在外者；两主都在外，按各自所在星座比：① 同宫星数多者；② 木星 / 水星 / 定位星同宫或星座相照者多；③ 所在星座尊贵（旺 > 本宫 > 其他 > 落）；④ 双体 > 固定 > 活动；⑤ 星座内度数大者；最后天然力量。次序与 PyJHora、Rath p.43 (d)、prashna 指南一致。两主都在本宫仍按比较结果（年数都是 12），未改。 +- 验证：`tests/test_audit_h_dasha_sky_20261104.py`（布什、泰勒、乔布斯三张公开盘两种岁差的天蝎 / 水瓶年数等于 PyJHora 参照值，只存数字；一主在本宫取另一主；两主都在外时随盘面翻转）；`tests/test_chara_dasha_board_lord.py` 一条按「原值 / 新值 / 原因」改写（计都在天蝎、火星在天秤：原值 计都 / 天蝎，新值 火星 / 天秤），另加一例火星在天蝎时取计都。修复后与 PyJHora 年数 225/228（Raman）、226/228（Lahiri），剩余差异均为 PyJHora 自己的取法：把上升算作同宫星（东京盘天蝎、齐达内 Raman 水瓶），尊贵一步只认入旺、第二颗星的入旺判断写成和自己比（伦敦盘天蝎）。K.N. Rao 书中越南女士例（1958，Lahiri）前 5 段星座与年数（含水瓶 3 年）与原书一致。前端金样 `chart-view-golden.json`、`chara-zero-year-1985-08-03-beijing.golden.json` 的 Chara 段按同一张盘的经度用修复后的引擎重采（前者天蝎宫主计都 8 年 → 火星 4 年，两份的小运次序随 BUG-1567 变），先用改前代码重算与原金样逐字节相同，确认输入一致；读它们的前端测试 256 条通过。咨询数据卡两份大金样（`consult-evidence-card-golden.json`、`consult-biography-backtest-golden.json`）里的 `chara_dasha` 仍是旧引擎采样（乔布斯天蝎宫主计都、水瓶 5 年），未重采，下次整体重采时更新。`tests/test_rashi_dashas_native.py` 的 PyJHora 4.8.7 对照（乔布斯、奥巴马、爱因斯坦）三盘 Chara 年数改前各差一段，改后与 PyJHora 逐段相同，fixture 的 `native.chara.years` 与 `diff_steps` 按「原值 / 新值 / 原因」更新（PyJHora 行未动）。 +- 冻结身份（ERR-110）：`jaimini.py` 在生时校正冻结身份里（校正只用 `calc_arudha_padas`，未改）。与 BUG-1567 一起按 ERR-110 改 FREEZE / REPORT 常量后用各脚本 `--freeze` 新建记录并回放，标签 `audit_h_2026_11_04`（`docs/research/sealed_holdout_rerun_audit_h_2026_11_04.{freeze.json,json}`、`docs/research/reported_offset_audit_h_2026_11_04.{freeze.json,json}`），合同 `references/rectification_sealed_holdout.v1.json` 按 moon_paksha 先例轮换，旧记录逐字节保留。与 `moon_paksha_2026_11_04` 逐条逐字段比：密封 20 条全部相同、`metrics` 不变；报时窗口 900 条全部相同、`summary` 不变（只有冻结身份哈希与路径不同）；相对 09-20 历史报告的 changed_trial_count 仍为 8 / 581。符合预期：校正打分只调 `jaimini.calc_arudha_padas`，Chara Dasha 不进打分。 +- 防复发：上述测试；同名「动态判定」函数要用盘面上的位置，不能用被判定的星座代入。 +- 关联记录：BUG-1567（同轮 Chara 小运）、BUG-1218 / BUG-1227（Narayana Rath 版双主星，p.43）、issue #163。 +- 复发自：无 +- 修复版本：分支 `codex/audit-dasha-sky-20261104`（未推送）。 + +## BUG-1567 | K.N. Rao Chara Dasha 小运：每个大运都沿用上升序右移一位，只有第一运对 + +- 状态：resolved（引擎 + 回归测试；未部署） +- 首次发现 / 最近更新：2026-10-08 已在 `docs/tasks/PROGRESS-rashi-dashas-native-20261008.md` 记为与书不符、未改 `jaimini.py`；2026-11-04 数据核对 H 按书逐运核对后修复。 +- 影响面：`scripts/jaimini.py` `calc_chara_dasha_with_antardasha`（`profile="kn_rao"`）的 `antardashas` 与其下 `pratyantar_dashas` 次序：报告 Rashi 大运章 Chara 表的子运（`rashi_dashas_native._chara`）、`/api/dasha/chara`、完整解读 Jaimini 的 Chara 子运。Goel 三个档案不变。 +- 现象：19 张盘 × 12 运，只有每张盘的第一运（19/228）符合书中规则。K.N. Rao 书中越南女士例（pdf pp.51–52）摩羯大运第一小运是射手，本仓给白羊。 +- 触发条件：任何盘的第二运起。 +- 根因：子运序列写成「全盘大运序右移一位」（注释称 PyJHora method=2；PyJHora 实为不移位、并注明「逻辑未实现」）。K.N. Rao《Predicting through Jaimini's Chara Dasha》印页 35–36：每个大运按它自己的顺逆（其第 9 宫若为偶足则逆行），从下一星座起，本运星座排最后。 +- 修复：`kn_rao` 档案每运单独起序：第 9 宫偶足则逆行，否则顺行，从下一星座起，第 12 段为本运星座；`antardasha_method` 写明口径。其余档案保持原序并注明「未找到出处，沿用」。 +- 验证：`tests/test_audit_h_dasha_sky_20261104.py`：每运末段为本运星座、方向按其第 9 宫；天蝎大运次序等于原书 pdf pp.49–50 金样（天秤 … 天蝎）；越南女士例 5 段大运与原书一致、摩羯首个小运为射手；Goel 档案次序不变。修复后 228/228 符合书中规则（修复前 19/228）。PyJHora 的 KN_RAO 子运是全盘大运序不移位（0/57），不作参照。 +- 冻结身份（ERR-110）：与 BUG-1566 同一次重冻，见 BUG-1566。 +- 防复发：上述测试与书中金样。 +- 关联记录：BUG-1566。 +- 复发自：无 +- 修复版本：分支 `codex/audit-dasha-sky-20261104`（未推送）。 + +## BUG-1568 | 出生 Panchanga 的星期（vara）和时主（hora）按公历日：日出前出生算成当天 + +- 状态：resolved（引擎 + 回归测试；未部署） +- 首次发现 / 最近更新：2026-11-04（数据核对 H：19 张盘与 PyJHora `drik.vaara`、本仓 Shadbala 的星期对照）/ 2026-11-04 +- 影响面：`scripts/jyotish_engine.py` `_build_natal_foundation_modules` 的 `panchanga.raw.vara` 与 `hora`：完整解读 `modules.panchanga`、报告「基础资料表」与 parity 章出生 Panchanga、读这两项的地方。Shadbala 的星期 / 时主本来就按日出算，不受影响；星盘页出生历法的「星期」是公历星期，未改（列给产品）。 +- 现象：19 张盘 4 张日出前出生（德里测试盘、泰勒、琵雅芙、齐达内）vara 写成公历当天，时主随之错：泰勒（1932-02-27 周六 02:30 伦敦）写周六，应为周五，时主应为火星。 +- 触发条件：出生在午夜后、当天日出前。 +- 根因：时主小时数从最近一次日出算（前一天的日出），星期却取出生的公历日期。吠陀日从日出到日出（PyJHora `vedic_weekday`、本仓 `shadbala._calendar_lords` 都是这样），两者混用。 +- 修复：星期取「开始计时的那次日出」所在的公历日期。日出口径（apparent）不变。 +- 验证：`tests/test_audit_h_dasha_sky_20261104.py`：泰勒 vara 周五、第 20 个时、时主火星；布什（日出后）仍为周六。19 张盘 vara 与 PyJHora 吠陀星期 19/19（修复前 15/19）；与 Shadbala 时主一致 16/19，余 3 张（卡罗、布什、齐达内）差在日出口径（Panchanga 用 apparent、Shadbala 用 Hindu，差 4–6 分钟，恰好跨整点），列给占星师。 +- 防复发：上述测试。 +- 关联记录：BUG-1388（日出口径分用）、BUG-1546（PyJHora 时主公式错，不作参照）。 +- 复发自：无 +- 修复版本：分支 `codex/audit-dasha-sky-20261104`（未推送）。 + +## BUG-1569 | 四个对照脚本一边写死 Lahiri、一边吃引擎默认（Raman）或不查基线口径；两个脚本引擎路径指错 + +- 状态：resolved（工具 + 回归测试；不涉及线上） +- 首次发现 / 最近更新：2026-11-04（数据核对 H，按同日 74169e1b 的做法逐个检查）/ 2026-11-04 +- 影响面：`benchmarks/jyotish/scripts/run_chara_dasha_compare.py`、`run_chara_dasha_knrao.py`、`run_transit_true_compare.py`、`run_node_mode_compare.py`、`run_skill_baseline.py`（`main`）。只影响对照报告，不影响产品输出。 +- 现象：引擎默认岁差改为 Raman 后，这几份对照会把 1.446° 的岁差差当成算法差；`run_chara_dasha_compare.py` 与 `run_transit_true_compare.py` 的引擎路径指到不存在的 `benchmarks/scripts/`，直接跑不起来。 +- 根因：PyJHora / Swiss 一侧写死 `LAHIRI` / `SIDM_LAHIRI`，引擎一侧不传 `--ayanamsa`，canonical 基线的口径也不核对；`parents[2]` 应为 `parents[3]`。 +- 修复：四个脚本都加 `--ayanamsa`（Chara 两个另加 `--node-mode`），两边显式传入；读 canonical 基线的两个脚本用 `run_pyjhora_compare.baseline_settings_error` 拒绝口径不符的基线；Transit 脚本核对引擎回报的岁差；路径改正；`run_skill_baseline.py` 命令行加 `--ayanamsa / --node-mode`。 +- 验证：`tests/test_benchmark_ayanamsa_plumbing_20261104.py`；用 Raman 重建 19 张 canonical 基线后重跑：Chara 对照 MD 星座 228/228、年数 225/228（BUG-1566 后）；K.N. Rao 共享位置对照 Raman 年数 117/120、Lahiri 118/120；Transit 646/646（含 19 张盘 171 项度数、逆行、多参考点星座）；节点对照 Swiss 平均交点 152/152、真交点与 PyJHora 默认各 100/152（口径差，预期）。用 Lahiri 对 Raman 基线跑 Chara 对照，脚本拒绝并提示重建。 +- 防复发：上述测试；新写对照脚本两边都要显式传岁差与交点，并核对基线口径。 +- 关联记录：74169e1b（`run_skill_baseline.py`、`run_pyjhora_compare.py` 同类修正）。 +- 复发自：无 +- 修复版本：分支 `codex/audit-dasha-sky-20261104`（未推送）。 diff --git a/docs/research/pre_work_error_ledger.md b/docs/research/pre_work_error_ledger.md index cbaba7f1..b1115455 100644 --- a/docs/research/pre_work_error_ledger.md +++ b/docs/research/pre_work_error_ledger.md @@ -18,6 +18,7 @@ Purpose: read this file before substantial project work. It exists to stop repea - BUG-1556（worktree `/workspace/wt-vim`，分支 `codex/vimshottari-second-cycle-20261104`）：Vimshottari 过 120 年变空已修，改在冻结身份之外（`chart_dasha/birth_moment.py` 的 `next_cycle_mahadashas`，`cmd_dasha` 与星盘 / 咨询共用），`dasha_analyzer.py`、`domain_calculation_service.py` 未动，无需重冻。`pre_work_check.py` exit 0；Python quick 门一次通过。注意：`_compute_chart_sync` 里 Vimshottari 算了两次，后一次（原 `utcnow()`）才是返回的 `dasha`，改参照日要两处都改；`test_chart_dasha_birth_moment_20261028.py` 里有 1879 年等老盘，以前只因两边都只排一轮才相等。 - 数据卡宫行加 Ashtakavarga 强 / 中 / 弱（worktree `/workspace/wt-card-av`，`codex/card-ashtakavarga-20261104`）：`pre_work_check.py` 第一次 exit 1（`fragment_scan` 90 s、`focused_tests` 45 s 超时，当时同机在建 worktree、跑卡片导出），机器空下来重跑 pass、六项全部 ok。分档沿用星盘页 `savBand`（≥ 28 强、25–27 中、≤ 24 弱），来源写在 `SAV_BAND_SOURCE`。注意：事业卡的 `sav_by_house`、财富 / 综合卡的 `ashtakavarga` 块本来就把原始与净化后的 SAV 点数给了模型，本单没动。 - BUG-1557 月亮 Paksha 口径（worktree `/workspace/wt-moon`，`codex/moon-paksha-bphs-20261104`）：`pre_work_check.py` exit 0、六项全部 ok。精确路径 Kala 里月亮 ×2（Raman）加 Chesta = Paksha（BPHS 27.18）同时用、Chesta 又取 ×2 后的值，总分 4P；改为 BPHS-Santhanam（不乘 2，Chesta = Paksha），`method_variants.moon_paksha` 标口径。`shadbala.py` 在冻结身份里，按 ERR-110 重冻为 `moon_paksha_2026_11_04`：密封 20 条、报时 900 条与 `data_audit_2026_11_04` 全同。教训：两家来源各自「×2」「Chesta = Paksha」都对，拼在一起就错；引进一条古典规则时先看同一来源怎么处理相邻分量。Shadbala 相关测试改前改后失败清单一致（同上 10 条 + 其他既有 12 条）；Python quick 门一次通过。 +- 数据核对 H（worktree `/workspace/wt-h`，`codex/audit-dasha-sky-20261104`）：`pre_work_check.py` exit 0、六项全部 ok。Narayana / Chara / 行运 / 日出 / Gulika 两种岁差各 19 张盘对 PyJHora 与 Swiss 直算：行运 190/190、Hindu 日出与 PyJHora 0 秒、Narayana Rath 版差异全是流派（起运宫、双主星、水星处女），第二轮规则与 PyJHora 同；修 BUG-1565（夜段时段点表错一格）、BUG-1566 / 1567（K.N. Rao Chara 双主星、小运次序）、BUG-1568（日出前出生的星期）、BUG-1569（四个对照脚本岁差）。`jaimini.py` 在冻结身份里，按 ERR-110 重冻为 `audit_h_2026_11_04`：密封 20 条、报时 900 条与 `moon_paksha_2026_11_04` 全同。教训：① PyJHora 4.8.6 夜生的 Gulika / 时段点算法本身错（以次日日出为起点、钟点差作夜长），夜生盘不能拿它作对照，要用 Swiss 独立重算；② 一个函数名叫「动态判定」不等于真按盘面判定，对照时先看结果是否随盘面变；③ 同机多会话同时跑报时回放与全量测试，相关测试 91 个文件跑了一个多小时，比对改前改后要用同一时段的两个 worktree 并行跑。`test_narayana_rath_book_tables.py::test_rath_profile_is_display_only` 在未改动的基线上就失败（`scripts/annual_service/package.py` 导入 `narayana_rath`）。 ## 2026-11-03 · 输入框单行起步（方案 2，worktree `/workspace/wt-composer`） diff --git a/docs/research/reported_offset_audit_h_2026_11_04.freeze.json b/docs/research/reported_offset_audit_h_2026_11_04.freeze.json new file mode 100644 index 00000000..142bd69e --- /dev/null +++ b/docs/research/reported_offset_audit_h_2026_11_04.freeze.json @@ -0,0 +1,118 @@ +{ + "record_version": "reported-offset-native-candidate-date-v3", + "frozen_at_utc": "2026-11-04T08:34:36.741288+00:00", + "ayanamsa": "raman", + "node_mode": 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dx":7,"lord":"Mars","duration_years":0.0069,"order":3},{"sign":"Sagittarius","sign_idx":8,"lord":"Jupiter","duration_years":0.0069,"order":4},{"sign":"Capricorn","sign_idx":9,"lord":"Saturn","duration_years":0.0069,"order":5},{"sign":"Aquarius","sign_idx":10,"lord":"Saturn","duration_years":0.0069,"order":6},{"sign":"Pisces","sign_idx":11,"lord":"Jupiter","duration_years":0.0069,"order":7},{"sign":"Aries","sign_idx":0,"lord":"Mars","duration_years":0.0069,"order":8},{"sign":"Taurus","sign_idx":1,"lord":"Venus","duration_years":0.0069,"order":9},{"sign":"Gemini","sign_idx":2,"lord":"Mercury","duration_years":0.0069,"order":10},{"sign":"Cancer","sign_idx":3,"lord":"Moon","duration_years":0.0069,"order":11},{"sign":"Leo","sign_idx":4,"lord":"Sun","duration_years":0.0069,"order":12}]},{"sign":"Leo","sign_idx":4,"lord":"Sun","duration_years":0.083,"order":12,"pratyantar_dashas":[{"sign":"Virgo","sign_idx":5,"lord":"Mercury","duration_years":0.0069,"order":1},{"sign":"Libra","sign_idx":6,"lord":"Venus","duration_years":0.0069,"order":2},{"sign":"Scorpio","sign_idx":7,"lord":"Mars","duration_years":0.0069,"order":3},{"sign":"Sagittarius","sign_idx":8,"lord":"Jupiter","duration_years":0.0069,"order":4},{"sign":"Capricorn","sign_idx":9,"lord":"Saturn","duration_years":0.0069,"order":5},{"sign":"Aquarius","sign_idx":10,"lord":"Saturn","duration_years":0.0069,"order":6},{"sign":"Pisces","sign_idx":11,"lord":"Jupiter","duration_years":0.0069,"order":7},{"sign":"Aries","sign_idx":0,"lord":"Mars","duration_years":0.0069,"order":8},{"sign":"Taurus","sign_idx":1,"lord":"Venus","duration_years":0.0069,"order":9},{"sign":"Gemini","sign_idx":2,"lord":"Mercury","duration_years":0.0069,"order":10},{"sign":"Cancer","sign_idx":3,"lord":"Moon","duration_years":0.0069,"order":11},{"sign":"Leo","sign_idx":4,"lord":"Sun","duration_years":0.0069,"order":12}]}]}],"total_cycle_years":41,"capability_status":"covered","has_antardasha":true,"has_pratyantar":true,"antardasha_method":"equal_division_12; kn_rao: own direction per mahadasha sign, mahadasha sign last (K.N. Rao pp.35-36)"}},"alias_of":"jaimini"}} diff --git a/frontend/tests/fixtures/chart-view-golden.json b/frontend/tests/fixtures/chart-view-golden.json index a1dfc734..1a82b2fb 100644 --- a/frontend/tests/fixtures/chart-view-golden.json +++ b/frontend/tests/fixtures/chart-view-golden.json @@ -1,5 +1,5 @@ { - "sourceCommand": "anaconda python: domain_calculation_service.compute_chart + compute_vimshottari_timeline; divisional_charts_extended.DivisionalChartsCalculator; jaimini.calc_chara_dasha_with_antardasha (pratyantar_dashas stripped; unused by the page); western_chart_engine.build_tropical_natal_chart. Fictional 1990-06-15 12:00 Beijing 39.9042N 116.4074E tz+8 Raman mean node. D40/D45/D60 appended 2026-09-28 from the same chart.planets[*].lon and ascendant.lon via DivisionalChartsCalculator._calculate_single_varga (recompute of D9/D10/D30 from those inputs equals the stored ones). 2026-10-03 (BUG-1202): varga_full.result[*].planets[*].dignity_level from scripts/varga_dignity.annotate_varga_dignity on the stored positions. 2026-10-15 (BUG-1352): chart.ascendant nakshatra, nakshatra_pada and nakshatra_lord are the fields returned by JyotishAPIHandler._compute_chart_sync for this birth (tests/test_api_chart_ascendant_nakshatra.py); they are not filled in by hand.", + "sourceCommand": "anaconda python: domain_calculation_service.compute_chart + compute_vimshottari_timeline; divisional_charts_extended.DivisionalChartsCalculator; jaimini.calc_chara_dasha_with_antardasha (pratyantar_dashas stripped; unused by the page); western_chart_engine.build_tropical_natal_chart. Fictional 1990-06-15 12:00 Beijing 39.9042N 116.4074E tz+8 Raman mean node. D40/D45/D60 appended 2026-09-28 from the same chart.planets[*].lon and ascendant.lon via DivisionalChartsCalculator._calculate_single_varga (recompute of D9/D10/D30 from those inputs equals the stored ones). 2026-10-03 (BUG-1202): varga_full.result[*].planets[*].dignity_level from scripts/varga_dignity.annotate_varga_dignity on the stored positions. 2026-10-15 (BUG-1352): chart.ascendant nakshatra, nakshatra_pada and nakshatra_lord are the fields returned by JyotishAPIHandler._compute_chart_sync for this birth (tests/test_api_chart_ascendant_nakshatra.py); they are not filled in by hand. 2026-11-04 (BUG-1566 / BUG-1567): chara.result.chara_dasha recomputed with jaimini.calc_chara_dasha_with_antardasha from the same chart.planets[*].lon and ascendant.lon (Scorpio lord Mars, 4 years; K.N. Rao antardasha order).", "chart": { "success": true, "birth": { @@ -2723,88 +2723,88 @@ "dignity_adjustment": "none", "order": 2, "antardashas": [ - { - "sign": "Virgo", - "sign_idx": 5, - "lord": "Mercury", - "duration_years": 0.333, - "order": 1 - }, { "sign": "Libra", "sign_idx": 6, "lord": "Venus", "duration_years": 0.333, - "order": 2 + "order": 1 }, { "sign": "Scorpio", "sign_idx": 7, "lord": "Mars", "duration_years": 0.333, - "order": 3 + "order": 2 }, { "sign": "Sagittarius", "sign_idx": 8, "lord": "Jupiter", "duration_years": 0.333, - "order": 4 + "order": 3 }, { "sign": "Capricorn", "sign_idx": 9, "lord": "Saturn", "duration_years": 0.333, - "order": 5 + "order": 4 }, { "sign": "Aquarius", "sign_idx": 10, "lord": "Saturn", "duration_years": 0.333, - "order": 6 + "order": 5 }, { "sign": "Pisces", "sign_idx": 11, "lord": "Jupiter", "duration_years": 0.333, - "order": 7 + "order": 6 }, { "sign": "Aries", "sign_idx": 0, "lord": "Mars", "duration_years": 0.333, - "order": 8 + "order": 7 }, { "sign": "Taurus", "sign_idx": 1, "lord": "Venus", "duration_years": 0.333, - "order": 9 + "order": 8 }, { "sign": "Gemini", "sign_idx": 2, "lord": "Mercury", "duration_years": 0.333, - "order": 10 + "order": 9 }, { "sign": "Cancer", "sign_idx": 3, "lord": "Moon", "duration_years": 0.333, - "order": 11 + "order": 10 }, { "sign": "Leo", "sign_idx": 4, "lord": "Sun", "duration_years": 0.333, + "order": 11 + }, + { + "sign": "Virgo", + "sign_idx": 5, + "lord": "Mercury", + "duration_years": 0.333, "order": 12 } ] @@ -2819,88 +2819,88 @@ "dignity_adjustment": "none", "order": 3, "antardashas": [ - { - "sign": "Virgo", - "sign_idx": 5, - "lord": "Mercury", - "duration_years": 0.5, - "order": 1 - }, - { - "sign": "Libra", - "sign_idx": 6, - "lord": "Venus", - "duration_years": 0.5, - "order": 2 - }, { "sign": "Scorpio", "sign_idx": 7, "lord": "Mars", "duration_years": 0.5, - "order": 3 + "order": 1 }, { "sign": "Sagittarius", "sign_idx": 8, "lord": "Jupiter", "duration_years": 0.5, - "order": 4 + "order": 2 }, { "sign": "Capricorn", "sign_idx": 9, "lord": "Saturn", "duration_years": 0.5, - "order": 5 + "order": 3 }, { "sign": "Aquarius", "sign_idx": 10, "lord": "Saturn", "duration_years": 0.5, - "order": 6 + "order": 4 }, { "sign": "Pisces", "sign_idx": 11, "lord": "Jupiter", "duration_years": 0.5, - "order": 7 + "order": 5 }, { "sign": "Aries", "sign_idx": 0, "lord": "Mars", "duration_years": 0.5, - "order": 8 + "order": 6 }, { "sign": "Taurus", "sign_idx": 1, "lord": "Venus", "duration_years": 0.5, - "order": 9 + "order": 7 }, { "sign": "Gemini", "sign_idx": 2, "lord": "Mercury", "duration_years": 0.5, - "order": 10 + "order": 8 }, { "sign": "Cancer", "sign_idx": 3, "lord": "Moon", "duration_years": 0.5, - "order": 11 + "order": 9 }, { "sign": "Leo", "sign_idx": 4, "lord": "Sun", "duration_years": 0.5, + "order": 10 + }, + { + "sign": "Virgo", + "sign_idx": 5, + "lord": "Mercury", + "duration_years": 0.5, + "order": 11 + }, + { + "sign": "Libra", + "sign_idx": 6, + "lord": "Venus", + "duration_years": 0.5, "order": 12 } ] @@ -2908,95 +2908,95 @@ { "sign": "Scorpio", "sign_idx": 7, - "lord": "Ketu", - "lord_in_sign": "Cancer", - "lord_in_sign_idx": 3, - "duration_years": 8, + "lord": "Mars", + "lord_in_sign": "Pisces", + "lord_in_sign_idx": 11, + "duration_years": 4, "dignity_adjustment": "none", "order": 4, "antardashas": [ - { - "sign": "Virgo", - "sign_idx": 5, - "lord": "Mercury", - "duration_years": 0.667, - "order": 1 - }, { "sign": "Libra", "sign_idx": 6, "lord": "Venus", - "duration_years": 0.667, - "order": 2 + "duration_years": 0.333, + "order": 1 }, { - "sign": "Scorpio", - "sign_idx": 7, - "lord": "Mars", - "duration_years": 0.667, - "order": 3 - }, - { - "sign": "Sagittarius", - "sign_idx": 8, - "lord": "Jupiter", - "duration_years": 0.667, - "order": 4 - }, - { - "sign": "Capricorn", - "sign_idx": 9, - "lord": "Saturn", - "duration_years": 0.667, - "order": 5 - }, - { - "sign": "Aquarius", - "sign_idx": 10, - "lord": "Saturn", - "duration_years": 0.667, - "order": 6 - }, - { - "sign": "Pisces", - "sign_idx": 11, - "lord": "Jupiter", - "duration_years": 0.667, - "order": 7 - }, - { - "sign": "Aries", - "sign_idx": 0, - "lord": "Mars", - "duration_years": 0.667, - "order": 8 - }, - { - "sign": "Taurus", - "sign_idx": 1, - "lord": "Venus", - "duration_years": 0.667, - "order": 9 - }, - { - "sign": "Gemini", - "sign_idx": 2, + "sign": "Virgo", + "sign_idx": 5, "lord": "Mercury", - "duration_years": 0.667, - "order": 10 - }, - { - "sign": "Cancer", - "sign_idx": 3, - "lord": "Moon", - "duration_years": 0.667, - "order": 11 + "duration_years": 0.333, + "order": 2 }, { "sign": "Leo", "sign_idx": 4, "lord": "Sun", - "duration_years": 0.667, + "duration_years": 0.333, + "order": 3 + }, + { + "sign": "Cancer", + "sign_idx": 3, + "lord": "Moon", + "duration_years": 0.333, + "order": 4 + }, + { + "sign": "Gemini", + "sign_idx": 2, + "lord": "Mercury", + "duration_years": 0.333, + "order": 5 + }, + { + "sign": "Taurus", + "sign_idx": 1, + "lord": "Venus", + "duration_years": 0.333, + "order": 6 + }, + { + "sign": "Aries", + "sign_idx": 0, + "lord": "Mars", + "duration_years": 0.333, + "order": 7 + }, + { + "sign": "Pisces", + "sign_idx": 11, + "lord": "Jupiter", + "duration_years": 0.333, + "order": 8 + }, + { + "sign": "Aquarius", + "sign_idx": 10, + "lord": "Saturn", + "duration_years": 0.333, + "order": 9 + }, + { + "sign": "Capricorn", + "sign_idx": 9, + "lord": "Saturn", + "duration_years": 0.333, + "order": 10 + }, + { + "sign": "Sagittarius", + "sign_idx": 8, + "lord": "Jupiter", + "duration_years": 0.333, + "order": 11 + }, + { + "sign": "Scorpio", + "sign_idx": 7, + "lord": "Mars", + "duration_years": 0.333, "order": 12 } ] @@ -3012,9 +3012,9 @@ "order": 5, "antardashas": [ { - "sign": "Virgo", - "sign_idx": 5, - "lord": "Mercury", + "sign": "Scorpio", + "sign_idx": 7, + "lord": "Mars", "duration_years": 0.5, "order": 1 }, @@ -3026,37 +3026,37 @@ "order": 2 }, { - "sign": "Scorpio", - "sign_idx": 7, - "lord": "Mars", + "sign": "Virgo", + "sign_idx": 5, + "lord": "Mercury", "duration_years": 0.5, "order": 3 }, { - "sign": "Sagittarius", - "sign_idx": 8, - "lord": "Jupiter", + "sign": "Leo", + "sign_idx": 4, + "lord": "Sun", "duration_years": 0.5, "order": 4 }, { - "sign": "Capricorn", - "sign_idx": 9, - "lord": "Saturn", + "sign": "Cancer", + "sign_idx": 3, + "lord": "Moon", "duration_years": 0.5, "order": 5 }, { - "sign": "Aquarius", - "sign_idx": 10, - "lord": "Saturn", + "sign": "Gemini", + "sign_idx": 2, + "lord": "Mercury", "duration_years": 0.5, "order": 6 }, { - "sign": "Pisces", - "sign_idx": 11, - "lord": "Jupiter", + "sign": "Taurus", + "sign_idx": 1, + "lord": "Venus", "duration_years": 0.5, "order": 7 }, @@ -3068,30 +3068,30 @@ "order": 8 }, { - "sign": "Taurus", - "sign_idx": 1, - "lord": "Venus", + "sign": "Pisces", + "sign_idx": 11, + "lord": "Jupiter", "duration_years": 0.5, "order": 9 }, { - "sign": "Gemini", - "sign_idx": 2, - "lord": "Mercury", + "sign": "Aquarius", + "sign_idx": 10, + "lord": "Saturn", "duration_years": 0.5, "order": 10 }, { - "sign": "Cancer", - "sign_idx": 3, - "lord": "Moon", + "sign": "Capricorn", + "sign_idx": 9, + "lord": "Saturn", "duration_years": 0.5, "order": 11 }, { - "sign": "Leo", - "sign_idx": 4, - "lord": "Sun", + "sign": "Sagittarius", + "sign_idx": 8, + "lord": "Jupiter", "duration_years": 0.5, "order": 12 } @@ -3108,86 +3108,86 @@ "order": 6, "antardashas": [ { - "sign": "Virgo", - "sign_idx": 5, - "lord": "Mercury", + "sign": "Sagittarius", + "sign_idx": 8, + "lord": "Jupiter", "duration_years": 1.0, "order": 1 }, - { - "sign": "Libra", - "sign_idx": 6, - "lord": "Venus", - "duration_years": 1.0, - "order": 2 - }, { "sign": "Scorpio", "sign_idx": 7, "lord": "Mars", "duration_years": 1.0, + "order": 2 + }, + { + "sign": "Libra", + "sign_idx": 6, + "lord": "Venus", + "duration_years": 1.0, "order": 3 }, { - "sign": "Sagittarius", - "sign_idx": 8, - "lord": "Jupiter", + "sign": "Virgo", + "sign_idx": 5, + "lord": "Mercury", "duration_years": 1.0, "order": 4 }, { - "sign": "Capricorn", - "sign_idx": 9, - "lord": "Saturn", + "sign": "Leo", + "sign_idx": 4, + "lord": "Sun", "duration_years": 1.0, "order": 5 }, - { - "sign": "Aquarius", - "sign_idx": 10, - "lord": "Saturn", - "duration_years": 1.0, - "order": 6 - }, - { - "sign": "Pisces", - "sign_idx": 11, - "lord": "Jupiter", - "duration_years": 1.0, - "order": 7 - }, - { - "sign": "Aries", - "sign_idx": 0, - "lord": "Mars", - "duration_years": 1.0, - "order": 8 - }, - { - "sign": "Taurus", - "sign_idx": 1, - "lord": "Venus", - "duration_years": 1.0, - "order": 9 - }, - { - "sign": "Gemini", - "sign_idx": 2, - "lord": "Mercury", - "duration_years": 1.0, - "order": 10 - }, { "sign": "Cancer", "sign_idx": 3, "lord": "Moon", "duration_years": 1.0, + "order": 6 + }, + { + "sign": "Gemini", + "sign_idx": 2, + "lord": "Mercury", + "duration_years": 1.0, + "order": 7 + }, + { + "sign": "Taurus", + "sign_idx": 1, + "lord": "Venus", + "duration_years": 1.0, + "order": 8 + }, + { + "sign": "Aries", + "sign_idx": 0, + "lord": "Mars", + "duration_years": 1.0, + "order": 9 + }, + { + "sign": "Pisces", + "sign_idx": 11, + "lord": "Jupiter", + "duration_years": 1.0, + "order": 10 + }, + { + "sign": "Aquarius", + "sign_idx": 10, + "lord": "Saturn", + "duration_years": 1.0, "order": 11 }, { - "sign": "Leo", - "sign_idx": 4, - "lord": "Sun", + "sign": "Capricorn", + "sign_idx": 9, + "lord": "Saturn", "duration_years": 1.0, "order": 12 } @@ -3203,88 +3203,88 @@ "dignity_adjustment": "none", "order": 7, "antardashas": [ - { - "sign": "Virgo", - "sign_idx": 5, - "lord": "Mercury", - "duration_years": 0.083, - "order": 1 - }, - { - "sign": "Libra", - "sign_idx": 6, - "lord": "Venus", - "duration_years": 0.083, - "order": 2 - }, - { - "sign": "Scorpio", - "sign_idx": 7, - "lord": "Mars", - "duration_years": 0.083, - "order": 3 - }, - { - "sign": "Sagittarius", - "sign_idx": 8, - "lord": "Jupiter", - "duration_years": 0.083, - "order": 4 - }, - { - "sign": "Capricorn", - "sign_idx": 9, - "lord": "Saturn", - "duration_years": 0.083, - "order": 5 - }, - { - "sign": "Aquarius", - "sign_idx": 10, - "lord": "Saturn", - "duration_years": 0.083, - "order": 6 - }, { "sign": "Pisces", "sign_idx": 11, "lord": "Jupiter", "duration_years": 0.083, - "order": 7 + "order": 1 }, { "sign": "Aries", "sign_idx": 0, "lord": "Mars", "duration_years": 0.083, - "order": 8 + "order": 2 }, { "sign": "Taurus", "sign_idx": 1, "lord": "Venus", "duration_years": 0.083, - "order": 9 + "order": 3 }, { "sign": "Gemini", "sign_idx": 2, "lord": "Mercury", "duration_years": 0.083, - "order": 10 + "order": 4 }, { "sign": "Cancer", "sign_idx": 3, "lord": "Moon", "duration_years": 0.083, - "order": 11 + "order": 5 }, { "sign": "Leo", "sign_idx": 4, "lord": "Sun", "duration_years": 0.083, + "order": 6 + }, + { + "sign": "Virgo", + "sign_idx": 5, + "lord": "Mercury", + "duration_years": 0.083, + "order": 7 + }, + { + "sign": "Libra", + "sign_idx": 6, + "lord": "Venus", + "duration_years": 0.083, + "order": 8 + }, + { + "sign": "Scorpio", + "sign_idx": 7, + "lord": "Mars", + "duration_years": 0.083, + "order": 9 + }, + { + "sign": "Sagittarius", + "sign_idx": 8, + "lord": "Jupiter", + "duration_years": 0.083, + "order": 10 + }, + { + "sign": "Capricorn", + "sign_idx": 9, + "lord": "Saturn", + "duration_years": 0.083, + "order": 11 + }, + { + "sign": "Aquarius", + "sign_idx": 10, + "lord": "Saturn", + "duration_years": 0.083, "order": 12 } ] @@ -3299,88 +3299,88 @@ "dignity_adjustment": "none", "order": 8, "antardashas": [ - { - "sign": "Virgo", - "sign_idx": 5, - "lord": "Mercury", - "duration_years": 0.75, - "order": 1 - }, - { - "sign": "Libra", - "sign_idx": 6, - "lord": "Venus", - "duration_years": 0.75, - "order": 2 - }, - { - "sign": "Scorpio", - "sign_idx": 7, - "lord": "Mars", - "duration_years": 0.75, - "order": 3 - }, - { - "sign": "Sagittarius", - "sign_idx": 8, - "lord": "Jupiter", - "duration_years": 0.75, - "order": 4 - }, - { - "sign": "Capricorn", - "sign_idx": 9, - "lord": "Saturn", - "duration_years": 0.75, - "order": 5 - }, - { - "sign": "Aquarius", - "sign_idx": 10, - "lord": "Saturn", - "duration_years": 0.75, - "order": 6 - }, - { - "sign": "Pisces", - "sign_idx": 11, - "lord": "Jupiter", - "duration_years": 0.75, - "order": 7 - }, { "sign": "Aries", "sign_idx": 0, "lord": "Mars", "duration_years": 0.75, - "order": 8 + "order": 1 }, { "sign": "Taurus", "sign_idx": 1, "lord": "Venus", "duration_years": 0.75, - "order": 9 + "order": 2 }, { "sign": "Gemini", "sign_idx": 2, "lord": "Mercury", "duration_years": 0.75, - "order": 10 + "order": 3 }, { "sign": "Cancer", "sign_idx": 3, "lord": "Moon", "duration_years": 0.75, - "order": 11 + "order": 4 }, { "sign": "Leo", "sign_idx": 4, "lord": "Sun", "duration_years": 0.75, + "order": 5 + }, + { + "sign": "Virgo", + "sign_idx": 5, + "lord": "Mercury", + "duration_years": 0.75, + "order": 6 + }, + { + "sign": "Libra", + "sign_idx": 6, + "lord": "Venus", + "duration_years": 0.75, + "order": 7 + }, + { + "sign": "Scorpio", + "sign_idx": 7, + "lord": "Mars", + "duration_years": 0.75, + "order": 8 + }, + { + "sign": "Sagittarius", + "sign_idx": 8, + "lord": "Jupiter", + "duration_years": 0.75, + "order": 9 + }, + { + "sign": "Capricorn", + "sign_idx": 9, + "lord": "Saturn", + "duration_years": 0.75, + "order": 10 + }, + { + "sign": "Aquarius", + "sign_idx": 10, + "lord": "Saturn", + "duration_years": 0.75, + "order": 11 + }, + { + "sign": "Pisces", + "sign_idx": 11, + "lord": "Jupiter", + "duration_years": 0.75, "order": 12 } ] @@ -3395,88 +3395,88 @@ "dignity_adjustment": "none", "order": 9, "antardashas": [ - { - "sign": "Virgo", - "sign_idx": 5, - "lord": "Mercury", - "duration_years": 0.917, - "order": 1 - }, - { - "sign": "Libra", - "sign_idx": 6, - "lord": "Venus", - "duration_years": 0.917, - "order": 2 - }, - { - "sign": "Scorpio", - "sign_idx": 7, - "lord": "Mars", - "duration_years": 0.917, - "order": 3 - }, - { - "sign": "Sagittarius", - "sign_idx": 8, - "lord": "Jupiter", - "duration_years": 0.917, - "order": 4 - }, - { - "sign": "Capricorn", - "sign_idx": 9, - "lord": "Saturn", - "duration_years": 0.917, - "order": 5 - }, - { - "sign": "Aquarius", - "sign_idx": 10, - "lord": "Saturn", - "duration_years": 0.917, - "order": 6 - }, - { - "sign": "Pisces", - "sign_idx": 11, - "lord": "Jupiter", - "duration_years": 0.917, - "order": 7 - }, - { - "sign": "Aries", - "sign_idx": 0, - "lord": "Mars", - "duration_years": 0.917, - "order": 8 - }, { "sign": "Taurus", "sign_idx": 1, "lord": "Venus", "duration_years": 0.917, - "order": 9 + "order": 1 }, { "sign": "Gemini", "sign_idx": 2, "lord": "Mercury", "duration_years": 0.917, - "order": 10 + "order": 2 }, { "sign": "Cancer", "sign_idx": 3, "lord": "Moon", "duration_years": 0.917, - "order": 11 + "order": 3 }, { "sign": "Leo", "sign_idx": 4, "lord": "Sun", "duration_years": 0.917, + "order": 4 + }, + { + "sign": "Virgo", + "sign_idx": 5, + "lord": "Mercury", + "duration_years": 0.917, + "order": 5 + }, + { + "sign": "Libra", + "sign_idx": 6, + "lord": "Venus", + "duration_years": 0.917, + "order": 6 + }, + { + "sign": "Scorpio", + "sign_idx": 7, + "lord": "Mars", + "duration_years": 0.917, + "order": 7 + }, + { + "sign": "Sagittarius", + "sign_idx": 8, + "lord": "Jupiter", + "duration_years": 0.917, + "order": 8 + }, + { + "sign": "Capricorn", + "sign_idx": 9, + "lord": "Saturn", + "duration_years": 0.917, + "order": 9 + }, + { + "sign": "Aquarius", + "sign_idx": 10, + "lord": "Saturn", + "duration_years": 0.917, + "order": 10 + }, + { + "sign": "Pisces", + "sign_idx": 11, + "lord": "Jupiter", + "duration_years": 0.917, + "order": 11 + }, + { + "sign": "Aries", + "sign_idx": 0, + "lord": "Mars", + "duration_years": 0.917, "order": 12 } ] @@ -3492,86 +3492,86 @@ "order": 10, "antardashas": [ { - "sign": "Virgo", - "sign_idx": 5, - "lord": "Mercury", - "duration_years": 0.917, - "order": 1 - }, - { - "sign": "Libra", - "sign_idx": 6, - "lord": "Venus", - "duration_years": 0.917, - "order": 2 - }, - { - "sign": "Scorpio", - "sign_idx": 7, + "sign": "Aries", + "sign_idx": 0, "lord": "Mars", "duration_years": 0.917, - "order": 3 - }, - { - "sign": "Sagittarius", - "sign_idx": 8, - "lord": "Jupiter", - "duration_years": 0.917, - "order": 4 - }, - { - "sign": "Capricorn", - "sign_idx": 9, - "lord": "Saturn", - "duration_years": 0.917, - "order": 5 - }, - { - "sign": "Aquarius", - "sign_idx": 10, - "lord": "Saturn", - "duration_years": 0.917, - "order": 6 + "order": 1 }, { "sign": "Pisces", "sign_idx": 11, "lord": "Jupiter", "duration_years": 0.917, + "order": 2 + }, + { + "sign": "Aquarius", + "sign_idx": 10, + "lord": "Saturn", + "duration_years": 0.917, + "order": 3 + }, + { + "sign": "Capricorn", + "sign_idx": 9, + "lord": "Saturn", + "duration_years": 0.917, + "order": 4 + }, + { + "sign": "Sagittarius", + "sign_idx": 8, + "lord": "Jupiter", + "duration_years": 0.917, + "order": 5 + }, + { + "sign": "Scorpio", + "sign_idx": 7, + "lord": "Mars", + "duration_years": 0.917, + "order": 6 + }, + { + "sign": "Libra", + "sign_idx": 6, + "lord": "Venus", + "duration_years": 0.917, "order": 7 }, { - "sign": "Aries", - "sign_idx": 0, - "lord": "Mars", + "sign": "Virgo", + "sign_idx": 5, + "lord": "Mercury", "duration_years": 0.917, "order": 8 }, { - "sign": "Taurus", - "sign_idx": 1, - "lord": "Venus", + "sign": "Leo", + "sign_idx": 4, + "lord": "Sun", "duration_years": 0.917, "order": 9 }, - { - "sign": "Gemini", - "sign_idx": 2, - "lord": "Mercury", - "duration_years": 0.917, - "order": 10 - }, { "sign": "Cancer", "sign_idx": 3, "lord": "Moon", "duration_years": 0.917, + "order": 10 + }, + { + "sign": "Gemini", + "sign_idx": 2, + "lord": "Mercury", + "duration_years": 0.917, "order": 11 }, { - "sign": "Leo", - "sign_idx": 4, - "lord": "Sun", + "sign": "Taurus", + "sign_idx": 1, + "lord": "Venus", "duration_years": 0.917, "order": 12 } @@ -3588,30 +3588,30 @@ "order": 11, "antardashas": [ { - "sign": "Virgo", - "sign_idx": 5, - "lord": "Mercury", + "sign": "Taurus", + "sign_idx": 1, + "lord": "Venus", "duration_years": 0.917, "order": 1 }, { - "sign": "Libra", - "sign_idx": 6, - "lord": "Venus", + "sign": "Aries", + "sign_idx": 0, + "lord": "Mars", "duration_years": 0.917, "order": 2 }, { - "sign": "Scorpio", - "sign_idx": 7, - "lord": "Mars", + "sign": "Pisces", + "sign_idx": 11, + "lord": "Jupiter", "duration_years": 0.917, "order": 3 }, { - "sign": "Sagittarius", - "sign_idx": 8, - "lord": "Jupiter", + "sign": "Aquarius", + "sign_idx": 10, + "lord": "Saturn", "duration_years": 0.917, "order": 4 }, @@ -3623,37 +3623,37 @@ "order": 5 }, { - "sign": "Aquarius", - "sign_idx": 10, - "lord": "Saturn", + "sign": "Sagittarius", + "sign_idx": 8, + "lord": "Jupiter", "duration_years": 0.917, "order": 6 }, { - "sign": "Pisces", - "sign_idx": 11, - "lord": "Jupiter", + "sign": "Scorpio", + "sign_idx": 7, + "lord": "Mars", "duration_years": 0.917, "order": 7 }, { - "sign": "Aries", - "sign_idx": 0, - "lord": "Mars", + "sign": "Libra", + "sign_idx": 6, + "lord": "Venus", "duration_years": 0.917, "order": 8 }, { - "sign": "Taurus", - "sign_idx": 1, - "lord": "Venus", + "sign": "Virgo", + "sign_idx": 5, + "lord": "Mercury", "duration_years": 0.917, "order": 9 }, { - "sign": "Gemini", - "sign_idx": 2, - "lord": "Mercury", + "sign": "Leo", + "sign_idx": 4, + "lord": "Sun", "duration_years": 0.917, "order": 10 }, @@ -3665,9 +3665,9 @@ "order": 11 }, { - "sign": "Leo", - "sign_idx": 4, - "lord": "Sun", + "sign": "Gemini", + "sign_idx": 2, + "lord": "Mercury", "duration_years": 0.917, "order": 12 } @@ -3684,97 +3684,97 @@ "order": 12, "antardashas": [ { - "sign": "Virgo", - "sign_idx": 5, + "sign": "Gemini", + "sign_idx": 2, "lord": "Mercury", "duration_years": 0.417, "order": 1 }, - { - "sign": "Libra", - "sign_idx": 6, - "lord": "Venus", - "duration_years": 0.417, - "order": 2 - }, - { - "sign": "Scorpio", - "sign_idx": 7, - "lord": "Mars", - "duration_years": 0.417, - "order": 3 - }, - { - "sign": "Sagittarius", - "sign_idx": 8, - "lord": "Jupiter", - "duration_years": 0.417, - "order": 4 - }, - { - "sign": "Capricorn", - "sign_idx": 9, - "lord": "Saturn", - "duration_years": 0.417, - "order": 5 - }, - { - "sign": "Aquarius", - "sign_idx": 10, - "lord": "Saturn", - "duration_years": 0.417, - "order": 6 - }, - { - "sign": "Pisces", - "sign_idx": 11, - "lord": "Jupiter", - "duration_years": 0.417, - "order": 7 - }, - { - "sign": "Aries", - "sign_idx": 0, - "lord": "Mars", - "duration_years": 0.417, - "order": 8 - }, { "sign": "Taurus", "sign_idx": 1, "lord": "Venus", "duration_years": 0.417, + "order": 2 + }, + { + "sign": "Aries", + "sign_idx": 0, + "lord": "Mars", + "duration_years": 0.417, + "order": 3 + }, + { + "sign": "Pisces", + "sign_idx": 11, + "lord": "Jupiter", + "duration_years": 0.417, + "order": 4 + }, + { + "sign": "Aquarius", + "sign_idx": 10, + "lord": "Saturn", + "duration_years": 0.417, + "order": 5 + }, + { + "sign": "Capricorn", + "sign_idx": 9, + "lord": "Saturn", + "duration_years": 0.417, + "order": 6 + }, + { + "sign": "Sagittarius", + "sign_idx": 8, + "lord": "Jupiter", + "duration_years": 0.417, + "order": 7 + }, + { + "sign": "Scorpio", + "sign_idx": 7, + "lord": "Mars", + "duration_years": 0.417, + "order": 8 + }, + { + "sign": "Libra", + "sign_idx": 6, + "lord": "Venus", + "duration_years": 0.417, "order": 9 }, { - "sign": "Gemini", - "sign_idx": 2, + "sign": "Virgo", + "sign_idx": 5, "lord": "Mercury", "duration_years": 0.417, "order": 10 }, - { - "sign": "Cancer", - "sign_idx": 3, - "lord": "Moon", - "duration_years": 0.417, - "order": 11 - }, { "sign": "Leo", "sign_idx": 4, "lord": "Sun", "duration_years": 0.417, + "order": 11 + }, + { + "sign": "Cancer", + "sign_idx": 3, + "lord": "Moon", + "duration_years": 0.417, "order": 12 } ] } ], - "total_cycle_years": 86, + "total_cycle_years": 82, "capability_status": "covered", "has_antardasha": true, "has_pratyantar": true, - "antardasha_method": "equal_division_12 (PyJHora method=2)" + "antardasha_method": "equal_division_12; kn_rao: own direction per mahadasha sign, mahadasha sign last (K.N. Rao pp.35-36)" } } }, diff --git a/frontend/tests/rectification-confirmation-gate.test.ts b/frontend/tests/rectification-confirmation-gate.test.ts index f6cf7918..d3e510d8 100644 --- a/frontend/tests/rectification-confirmation-gate.test.ts +++ b/frontend/tests/rectification-confirmation-gate.test.ts @@ -123,8 +123,11 @@ const diagnosticReport = JSON.parse(readFileSync( // 原值(14)：docs/research/sealed_holdout_rerun_data_audit_2026_11_04.json // 新值(14)：docs/research/sealed_holdout_rerun_moon_paksha_2026_11_04.json // 原因(14)：BUG-1557 月亮 Paksha 口径改了冻结身份里的 shadbala.py，20 条回放不变，ERR-110 另存新记录。确认门行为与阈值不变。 +// 原值(15)：docs/research/sealed_holdout_rerun_moon_paksha_2026_11_04.json +// 新值(15)：docs/research/sealed_holdout_rerun_audit_h_2026_11_04.json +// 原因(15)：数据核对 H 的 BUG-1566 / BUG-1567（Chara Dasha 双主星与小运次序）改了冻结身份里的 jaimini.py，20 条回放不变，ERR-110 另存新记录。确认门行为与阈值不变。 const currentTreeRerun = JSON.parse(readFileSync( - new URL("../../docs/research/sealed_holdout_rerun_moon_paksha_2026_11_04.json", import.meta.url), + new URL("../../docs/research/sealed_holdout_rerun_audit_h_2026_11_04.json", import.meta.url), "utf8", )) as { frozen_record: { implementation_sha256: string }; @@ -276,9 +279,10 @@ test("sealed holdout aggregates match the v3 report and still block confirmation // 原值(11)：…upstream_sync9b_2026_10_28.json / 新值(11)：…d60_mapping_2026_10_29.json / 原因(11)：BUG-1500 修正 D60 映射，输出不变，ERR-110 另存新记录。 // 原值(12)：…d60_mapping_2026_10_29.json / 新值(12)：…data_audit_2026_11_04.json / 原因(12)：BUG-1545 / BUG-1546 改了冻结身份文件，输出不变，ERR-110 另存新记录。 // 原值(13)：…data_audit_2026_11_04.json / 新值(13)：…moon_paksha_2026_11_04.json / 原因(13)：BUG-1557 改了冻结身份里的 shadbala.py，输出不变，ERR-110 另存新记录。 + // 原值(14)：…moon_paksha_2026_11_04.json / 新值(14)：…audit_h_2026_11_04.json / 原因(14)：BUG-1566 / BUG-1567 改了冻结身份里的 jaimini.py，输出不变，ERR-110 另存新记录。 assert.equal( productHoldout.current_tree_scorer.source_report, - "docs/research/sealed_holdout_rerun_moon_paksha_2026_11_04.json", + "docs/research/sealed_holdout_rerun_audit_h_2026_11_04.json", ); assert.equal(currentTreeRerun.official_valid_independent_blind, false); assert.equal(productHoldout.current_tree_scorer.matches_metrics_scorer, false); diff --git a/references/rectification_sealed_holdout.v1.json b/references/rectification_sealed_holdout.v1.json index 2f4d04f5..17739011 100644 --- a/references/rectification_sealed_holdout.v1.json +++ b/references/rectification_sealed_holdout.v1.json @@ -24,7 +24,7 @@ "evaluated_on": "2026-07-21" }, "current_tree_scorer": { - "implementation_sha256": "19ce36a9938928f345928fc44792eb70e6b71945aa5ab2a08a942b214cf0b085", + "implementation_sha256": "a6a60f59f7405496453000abef6f9f3074aa8d31c2a4dc9a8f18c6d812837168", "extended_identity": { "historical_artifacts_manifest_sha256": "6102a26a840be207b5858b3a4c0509274468ae9071e86d308cbbac7371d6864e", "production_scoring_files": [ @@ -52,7 +52,7 @@ "scripts/shadbala.py", "scripts/varga.py" ], - "production_scoring_sha256": "9857465d8305d0ccdcedff12c4c0bc572d4a12eea7e348fa4fc1b38e4f244fcf", + "production_scoring_sha256": "e20ff44f33b57db60bb6661ac235bd9f81425ced3fa632e7ea4b31f48b41237e", "research_files": [ "scripts/research/reported_offset_sweep.py", "scripts/research/cluster_width_lib.py", @@ -62,7 +62,7 @@ "scripts/minute_rectification_fact_blind_eval_v4.py", "scripts/minute_rectification_holdout_validator.py" ], - "research_implementation_sha256": "8747a78a8b7a3fee0542423978adab11cee3e98880065ce13ef243f9488e5de9", + "research_implementation_sha256": "25d970c09cb4d6a71e90c05d9580be5b81a63cbc338cc7cd4bf768a8aa45efd9", "file_sha256": { "scripts/active_rectification_event_engine.py": "dced0b398ad90bdec59c743a55ffe01613306127c17a1e44c8c9cfb569c57841", "scripts/active_rectification_events.py": "03e333ccf1103caf685dfe50fe890ab1793e945037085f50ce834a4a3b232222", @@ -71,7 +71,7 @@ "scripts/divisional_charts_extended.py": "e9820e80f14fddc86ab5495d11455d16c2d3c9502a9a242fcf9efc41186e0d11", "scripts/domain_calculation_service.py": "66923a2bc69daf65c965d2973c4b9234edbec5147909eaf3609b6b377ce3c7ca", "scripts/functional_benefics.py": "cbaac3b8c09b97f8724b5300e9a402cbf77089af6c7db8788550d40fd35ac57b", - "scripts/jaimini.py": "6b88658da5404da9b136686d92a04be462d61a39da6e8de4255021e2ed2d1173", + "scripts/jaimini.py": "706d20dcff89079063fd1857a36f19419604ef81c80227921c7a2ced60011ac9", "scripts/minute_rectification_blind_eval.py": "07aa30d8bad3278669495d5fea8be937aaf6367c8af980ff4f2fe9aa84ccc6ff", "scripts/minute_rectification_fact_blind_eval_v4.py": "bdf460e3467208e8b87345c5beb2128f3e22de7eeffd68f72b281b3ad9affc92", "scripts/minute_rectification_fact_ranker_v4.py": "f1a0d8d2482cd754d2e7f253a9606b0373519435a2bf58cfc3753e2b9ae0fb76", @@ -90,8 +90,8 @@ "scripts/rectification/scoring_service.py": "fa056fa30d9e6ffa4b75295fc49c793e35b26ebeca64ca843d26c8abef3050f2", "scripts/research/cluster_width_lib.py": "1d8f2ffa7795d62069deebb2de8e16749317037d4ed3f24a2c0092676e5cfcc6", "scripts/research/probe_supply_after_six.py": "098a5b4398d6f8d996917d809c2fc922ad64031d3b70660f8ef7c876aba92438", - "scripts/research/reported_offset_sweep.py": "1c7183e77f442b8c6b46761ff8a833b6c27b7841999426c72556237f45df1343", - "scripts/research/sealed_holdout_rerun.py": "957b824b7579c4f52681c85d7964fc802f8179470c93917cded63c7fe6c2769d", + "scripts/research/reported_offset_sweep.py": "13c29205f5315383a4d4af04b4c69a244d8f175158beb20f3d9e47b62fd2683f", + "scripts/research/sealed_holdout_rerun.py": "2a4dfd27bb8b78d90d81f2b534091a1f82f748bc873e9943609256774a4313bc", "scripts/shadbala.py": "352a9dd91c9be6dd7a294b1dc24c62173e8f08db5fc36c453dc5dcd7e0fd62d7", "scripts/varga.py": "1bca389e4f36d293a755de175163c3f39b42bab5831cb6f7828830899f9f177e" }, @@ -100,7 +100,7 @@ "matches_metrics_scorer": false, "official_eval_implementation_hash_matches": false, "official_eval_trial_count": 0, - "source_report": "docs/research/sealed_holdout_rerun_moon_paksha_2026_11_04.json", + "source_report": "docs/research/sealed_holdout_rerun_audit_h_2026_11_04.json", "fixed_protocol_rerun_trial_count": 20, "fixed_protocol_rerun_hash_matches": true, "metrics": { @@ -113,6 +113,106 @@ } }, "current_tree_fixed_protocol_rerun": { + "evaluated_on": "2026-11-04", + "report_path": "docs/research/sealed_holdout_rerun_audit_h_2026_11_04.json", + "freeze_record_path": "docs/research/sealed_holdout_rerun_audit_h_2026_11_04.freeze.json", + "implementation_sha256": "a6a60f59f7405496453000abef6f9f3074aa8d31c2a4dc9a8f18c6d812837168", + "extended_identity": { + "historical_artifacts_manifest_sha256": "6102a26a840be207b5858b3a4c0509274468ae9071e86d308cbbac7371d6864e", + "production_scoring_files": [ + "scripts/active_rectification_event_engine.py", + "scripts/active_rectification_events.py", + "scripts/ashtakavarga.py", + "scripts/dasha_analyzer.py", + "scripts/divisional_charts_extended.py", + "scripts/domain_calculation_service.py", + "scripts/functional_benefics.py", + "scripts/jaimini.py", + "scripts/minute_rectification_fact_ranker_v4.py", + "scripts/minute_rectification_feature_facts_v4.py", + "scripts/narayana_dasha.py", + "scripts/rectification/api_service.py", + "scripts/rectification/candidate_contrast.py", + "scripts/rectification/candidate_window.py", + "scripts/rectification/case_holdout.py", + "scripts/rectification/contracts.py", + "scripts/rectification/dasha_transition_proximity.py", + "scripts/rectification/decision_policy.py", + "scripts/rectification/event_probes.py", + "scripts/rectification/refinement_packet.py", + "scripts/rectification/scoring_service.py", + "scripts/shadbala.py", + "scripts/varga.py" + ], + "production_scoring_sha256": "e20ff44f33b57db60bb6661ac235bd9f81425ced3fa632e7ea4b31f48b41237e", + "research_files": [ + "scripts/research/reported_offset_sweep.py", + "scripts/research/cluster_width_lib.py", + "scripts/research/probe_supply_after_six.py", + "scripts/research/sealed_holdout_rerun.py", + "scripts/minute_rectification_blind_eval.py", + "scripts/minute_rectification_fact_blind_eval_v4.py", + "scripts/minute_rectification_holdout_validator.py" + ], + "research_implementation_sha256": "25d970c09cb4d6a71e90c05d9580be5b81a63cbc338cc7cd4bf768a8aa45efd9", + "file_sha256": { + "scripts/active_rectification_event_engine.py": "dced0b398ad90bdec59c743a55ffe01613306127c17a1e44c8c9cfb569c57841", + "scripts/active_rectification_events.py": "03e333ccf1103caf685dfe50fe890ab1793e945037085f50ce834a4a3b232222", + "scripts/ashtakavarga.py": "c524da3f54b2ed9c080b78b33854854a0ca3d5d79b7e536bb1c3bc2be3e02852", + "scripts/dasha_analyzer.py": "3949b96813217fe624899856afec9f0b787c4cb0fea3a9a0d961990dbd11943a", + "scripts/divisional_charts_extended.py": "e9820e80f14fddc86ab5495d11455d16c2d3c9502a9a242fcf9efc41186e0d11", + "scripts/domain_calculation_service.py": "66923a2bc69daf65c965d2973c4b9234edbec5147909eaf3609b6b377ce3c7ca", + "scripts/functional_benefics.py": "cbaac3b8c09b97f8724b5300e9a402cbf77089af6c7db8788550d40fd35ac57b", + 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"must_not_claim_as_release_metrics": true, + "must_not_use_for_tuning": true, + "verified_minute_claim_allowed": false, + "metric_gates_passed": false, + "events_per_case": 3, + "boundary": "Previously exposed v3 shadow fixed-protocol rerun after data audit H (ERR-110, BUG-1566, BUG-1567). Trials and metrics match the 2026-11-04 moon_paksha report on every field. Versus the 2026-09-20 historical report, changed_trial_count stays 8. Not a release metric. Prior reports and freezes preserved byte-for-byte.", + "report_sha256": "d8371b2b1a034d7fd0f481c27416f9411304b8d77c0adddacc8d0477cd74e7fe", + "freeze_record_sha256": "b6fb92641c582a6998b09f49785cff7314b42993c96fe083ae904478e47347e5", + "replay_started_at_utc": "2026-11-04T08:34:34.311638+00:00", + "replay_finished_at_utc": "2026-11-04T08:34:36.590266+00:00", + "previous_fixed_protocol_rerun": { + "report_path": "docs/research/sealed_holdout_rerun_moon_paksha_2026_11_04.json", + "freeze_record_path": "docs/research/sealed_holdout_rerun_moon_paksha_2026_11_04.freeze.json", + "superseded_reason": "Data audit H, BUG-1566 / BUG-1567 (scripts/jaimini.py: K.N. Rao Chara Dasha Scorpio / Aquarius co-lord and antardasha order) changed a frozen identity file. Rectification scoring reads only jaimini.calc_arudha_padas, which did not change. Output is unchanged, so ERR-110 stored a new record. Prior moon_paksha report and freeze preserved byte-for-byte." + } + }, + "previous_fixed_protocol_rerun": { "evaluated_on": "2026-11-04", "report_path": "docs/research/sealed_holdout_rerun_moon_paksha_2026_11_04.json", "freeze_record_path": "docs/research/sealed_holdout_rerun_moon_paksha_2026_11_04.freeze.json", @@ -212,106 +312,6 @@ "superseded_reason": "BUG-1557 (scripts/shadbala.py: the Moon's Paksha is no longer doubled; convention bphs_santhanam_27_10_11_chesta_27_18) changed a frozen identity file. Output is unchanged. Rectification scoring reads only Sthana, Drik and Naisargika, so ERR-110 stored a new record. 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Trials and metrics match the 2026-10-29 d60_mapping report on every field. Versus the 2026-09-20 historical report, changed_trial_count stays 8. Not a release metric. Prior reports and freezes preserved byte-for-byte.", - "report_sha256": "2dce02cc332e1cbcc8d7a3168725d0d6d0d4c9bf34c550d0ea263b5dfa0e844f", - "freeze_record_sha256": "99c3be9638418bff7241dd53f17c06b2780e309c0450d1445de5e496ca3919ec", - "replay_started_at_utc": "2026-11-04T04:44:54.299954+00:00", - "replay_finished_at_utc": "2026-11-04T04:44:56.382187+00:00", - "previous_fixed_protocol_rerun": { - "report_path": "docs/research/sealed_holdout_rerun_d60_mapping_2026_10_29.json", - "freeze_record_path": "docs/research/sealed_holdout_rerun_d60_mapping_2026_10_29.freeze.json", - "superseded_reason": "The data-audit fixes BUG-1545 (scripts/narayana_dasha.py, scripts/active_rectification_event_engine.py) and BUG-1546 (scripts/shadbala.py) changed frozen identity files. Output is unchanged, so ERR-110 stored a new record. Prior d60_mapping report and freeze preserved byte-for-byte." - } - }, "current_tree_unfrozen_diagnostic": { "is_blind_evaluation": false, "results_already_seen": true, @@ -330,6 +330,28 @@ "verified_minute_claim_allowed": false }, "current_tree_reported_offset_replay": { + "report_path": "docs/research/reported_offset_audit_h_2026_11_04.json", + "report_sha256": "42a87ac29bbd18a2bc4bf62794e53e3c39e078841beb253a54375e5b668bbba2", + "freeze_record_path": "docs/research/reported_offset_audit_h_2026_11_04.freeze.json", + "freeze_record_sha256": "bccffb8212e9513f43dea69ee25d115b3bedd34f39ab1d27722041292047c93c", + "scope": "reported_offset_sensitivity_not_product_accuracy", + "trial_count": 900, + "official_valid_independent_blind": false, + "official_blind_trial_count": 0, + "must_not_use_for_tuning": true, + "must_not_claim_as_release_metrics": true, + "replay_started_at_utc": "2026-11-04T08:34:40.821345+00:00", + "replay_finished_at_utc": "2026-11-04T08:37:31.907880+00:00", + "boundary": "Previously exposed reported-offset sensitivity after data audit H (ERR-110, BUG-1566, BUG-1567). Summary and all 900 trials match the 2026-11-04 moon_paksha report on every field. Versus the 2026-09-20 historical report, changed_trial_count stays 581 of 900. Not a release metric. No tuning. Prior reports and freezes preserved byte-for-byte.", + "previous_reported_offset_replay": { + "report_path": "docs/research/reported_offset_moon_paksha_2026_11_04.json", + "report_sha256": "f0b602a0477d5913d4befcdf888f3687062c3e62e0b11e6ea3bc69303f0f02cb", + "freeze_record_path": "docs/research/reported_offset_moon_paksha_2026_11_04.freeze.json", + "freeze_record_sha256": "9728da404c736a85179dfbbd62ac551550ff8590494f4da62df874cac5ffbd49", + "superseded_reason": "Data audit H, BUG-1566 / BUG-1567 (scripts/jaimini.py: K.N. Rao Chara Dasha Scorpio / Aquarius co-lord and antardasha order) changed a frozen identity file. Rectification scoring reads only jaimini.calc_arudha_padas, which did not change. Summary and all 900 trials are unchanged, so ERR-110 stored a new record. Prior moon_paksha report and freeze preserved byte-for-byte." + } + }, + "previous_reported_offset_replay": { "report_path": "docs/research/reported_offset_moon_paksha_2026_11_04.json", "report_sha256": "f0b602a0477d5913d4befcdf888f3687062c3e62e0b11e6ea3bc69303f0f02cb", "freeze_record_path": "docs/research/reported_offset_moon_paksha_2026_11_04.freeze.json", @@ -350,27 +372,5 @@ "freeze_record_sha256": "389995d59467aac0270c1395200126c9065340c8177362566bd816f8c4ef9321", "superseded_reason": "BUG-1557 (scripts/shadbala.py: the Moon's Paksha is no longer doubled; convention bphs_santhanam_27_10_11_chesta_27_18) changed a frozen identity file. Summary and all 900 trials are unchanged. Rectification scoring reads only Sthana, Drik and Naisargika, so ERR-110 stored a new record. Prior data_audit report and freeze preserved byte-for-byte." } - }, - "previous_reported_offset_replay": { - "report_path": "docs/research/reported_offset_data_audit_2026_11_04.json", - "report_sha256": "227498db6488da6f4841c14ea063abcd3b788a069f8e61bb3c384b8bcee55f94", - "freeze_record_path": "docs/research/reported_offset_data_audit_2026_11_04.freeze.json", - "freeze_record_sha256": "389995d59467aac0270c1395200126c9065340c8177362566bd816f8c4ef9321", - "scope": "reported_offset_sensitivity_not_product_accuracy", - "trial_count": 900, - "official_valid_independent_blind": false, - "official_blind_trial_count": 0, - "must_not_use_for_tuning": true, - "must_not_claim_as_release_metrics": true, - "replay_started_at_utc": "2026-11-04T04:44:56.483403+00:00", - "replay_finished_at_utc": "2026-11-04T04:47:27.195146+00:00", - "boundary": "Previously exposed reported-offset sensitivity after the data-audit engine fixes (ERR-110, BUG-1545, BUG-1546). Summary matches the 2026-10-29 d60_mapping report. 898 of 900 trials match on every field; 2 trials (case_ordinal 6, radius 60, offsets -30 and -20) changed true_rank only (76 to 67 and 80 to 77), traced to the BUG-1545 Narayana second cycle. Versus the 2026-09-20 historical report, changed_trial_count stays 581 of 900. Not a release metric. No tuning. Prior reports and freezes preserved byte-for-byte.", - "previous_reported_offset_replay": { - "report_path": "docs/research/reported_offset_d60_mapping_2026_10_29.json", - "report_sha256": "f40157139733552dbefdfc999f95458de75594cd511df0e5377d606e27559f0d", - "freeze_record_path": "docs/research/reported_offset_d60_mapping_2026_10_29.freeze.json", - "freeze_record_sha256": "20e7684bc6c7356a421c2c20517c153279561f810cd15d77f260c9915352aed9", - "superseded_reason": "The data-audit fixes BUG-1545 (scripts/narayana_dasha.py, scripts/active_rectification_event_engine.py) and BUG-1546 (scripts/shadbala.py) changed frozen identity files. Summary is unchanged and 2 of 900 trials changed true_rank only (BUG-1545), so ERR-110 stored a new record. Prior d60_mapping report and freeze preserved byte-for-byte." - } } } diff --git a/scripts/gulika.py b/scripts/gulika.py index bd3634b5..1277b878 100644 --- a/scripts/gulika.py +++ b/scripts/gulika.py @@ -43,7 +43,13 @@ SATURN_PART_START = { # Planet indices follow the local seven-graha ordering: Sun through Saturn. # Each row assigns the eight daylight/nighttime shares for a weekday where -# Python's datetime.weekday() is Monday=0. +# Python's datetime.weekday() is Monday=0. The day starts with the weekday +# lord, the night with the lord of the fifth weekday counted from it; the +# shares then run round the eight-slot cycle Sun..Saturn, lordless (PyJHora +# const.day_rulers / night_rulers). Saturn's share in every row equals +# SATURN_PART_START. The Wednesday-Saturday night rows used to start one lord +# early (Saturday night with Mars instead of Mercury), so Maandi and the four +# other time-segment points sat in the wrong share on those nights (BUG-1565). DAY_RULERS = ( (1, 2, 3, 4, 5, 6, -1, 0), (2, 3, 4, 5, 6, -1, 0, 1), @@ -56,10 +62,10 @@ DAY_RULERS = ( NIGHT_RULERS = ( (5, 6, -1, 0, 1, 2, 3, 4), (6, -1, 0, 1, 2, 3, 4, 5), - (-1, 0, 1, 2, 3, 4, 5, 6), (0, 1, 2, 3, 4, 5, 6, -1), (1, 2, 3, 4, 5, 6, -1, 0), (2, 3, 4, 5, 6, -1, 0, 1), + (3, 4, 5, 6, -1, 0, 1, 2), (4, 5, 6, -1, 0, 1, 2, 3), ) TEMPORAL_UPAGRAHAS = { diff --git a/scripts/jaimini.py b/scripts/jaimini.py index e6fb909a..111e5bca 100644 --- a/scripts/jaimini.py +++ b/scripts/jaimini.py @@ -361,38 +361,66 @@ def _jaimini_planet_dignity_level(planet: str, sign_idx: int) -> int: return 3 +_CO_LORD_GRAHAS = ('Sun', 'Moon', 'Mars', 'Mercury', 'Jupiter', 'Venus', 'Saturn', 'Rahu', 'Ketu') + + +def _rasi_drishti(source_sign_idx: int, target_sign_idx: int) -> bool: + """Jaimini sign aspect: movable -> fixed (not the next), fixed -> movable + (not the previous), dual -> the other duals.""" + if source_sign_idx in (0, 3, 6, 9): + return target_sign_idx in (1, 4, 7, 10) and target_sign_idx != (source_sign_idx + 1) % 12 + if source_sign_idx in (1, 4, 7, 10): + return target_sign_idx in (0, 3, 6, 9) and target_sign_idx != (source_sign_idx - 1) % 12 + return target_sign_idx in (2, 5, 8, 11) and target_sign_idx != source_sign_idx + + +def _co_lord_strength(longitudes: Dict[str, float], planet: str) -> Tuple[int, int, int, int, float]: + """Strength key of one Scorpio / Aquarius co-lord where it stands (BUG-1566). + + Same order as PyJHora `house._stronger_planet_new`, Rath (Narayana Dasa + p.43 (d)) and references/prashna-complete-guide.md (dual lords): + 1. more other bodies in its sign; + 2. more of Jupiter, Mercury and its dispositor in or aspecting (Rasi + Drishti) its sign; + 3. dignity in the sign it occupies (exalted > own > other > debilitated); + 4. dual > fixed > movable sign; + 5. more degrees in the sign. + """ + sign_idx = _get_planet_house(longitudes, planet) + companions = sum( + 1 for other in _CO_LORD_GRAHAS + if other != planet and other in longitudes and _get_planet_house(longitudes, other) == sign_idx + ) + dispositor = SIGN_LORDS[SIGNS[sign_idx]] + support = 0 + for role in ('Jupiter', 'Mercury', dispositor): + if role not in longitudes: + continue + role_sign = _get_planet_house(longitudes, role) + if role_sign == sign_idx or _rasi_drishti(role_sign, sign_idx): + support += 1 + dignity = _jaimini_planet_dignity_level(planet, sign_idx) + modality = 2 if sign_idx % 3 == 2 else 1 if sign_idx % 3 == 1 else 0 + return companions, support, dignity, modality, float(longitudes[planet]) % 30 + + def _jaimini_stronger_planet(longitudes: Dict[str, float], planet_a: str, planet_b: str, sign_idx: int) -> str: """ - 动态比较两颗行星在指定星座的力量，返回较强者。 - 基于PyJHora _stronger_planet_new 算法翻译。 + Stronger of two co-lords of ``sign_idx``, judged where each one stands. - 比较层次： - 1. 尊严层级: exalted(6) > own(5) > friendly(4) > neutral(3) > enemy(2) > debilitated(1) - 2. 同层级：比较行星经度位置（度数更靠近星座中心更强） - 3. 仍相同：比较Naisargika Bala（天然力量） + Before BUG-1566 this compared both planets' dignity *in ``sign_idx``* + (the dasha sign) rather than in the signs they occupy, so Scorpio always + went to Ketu (exalted there) and Aquarius always to Saturn (own sign), + whatever the chart. Now: `_co_lord_strength` levels 1-5, then the + natural-strength order as a last tie-break. """ - level_a = _jaimini_planet_dignity_level(planet_a, sign_idx) - level_b = _jaimini_planet_dignity_level(planet_b, sign_idx) - - if level_a > level_b: + key_a = _co_lord_strength(longitudes, planet_a) + key_b = _co_lord_strength(longitudes, planet_b) + if key_a > key_b: return planet_a - if level_b > level_a: + if key_b > key_a: return planet_b - - # 同层级：比较行星在星座中的位置（更靠近星座中心度数=15°更强） - deg_a = longitudes.get(planet_a, 0) % 30 - deg_b = longitudes.get(planet_b, 0) % 30 - - center_diff_a = abs(deg_a - 15) - center_diff_b = abs(deg_b - 15) - - if center_diff_a < center_diff_b: - return planet_a - if center_diff_b < center_diff_a: - return planet_b - - # 完全平局：使用Naisargika Bala决断 naisargika_order = ['Sun', 'Moon', 'Venus', 'Jupiter', 'Mercury', 'Mars', 'Saturn'] idx_a = naisargika_order.index(planet_a) if planet_a in naisargika_order else 99 idx_b = naisargika_order.index(planet_b) if planet_b in naisargika_order else 99 @@ -401,32 +429,33 @@ def _jaimini_stronger_planet(longitudes: Dict[str, float], planet_a: str, def _resolve_chara_dasha_lord(longitudes, sign_idx): """ - 解析Chara Dasha宫主。v6.1.13: 实现动态共主判定。 + 解析Chara Dasha宫主（天蝎：火星 / 计都；水瓶：土星 / 罗睺）。 - Aquarius (sign 10): 比较 Saturn vs Rahu - Scorpio (sign 7): 比较 Mars vs Ketu + BUG-1566: one co-lord in the sign itself and the other elsewhere -> the + one elsewhere (K.N. Rao, Predicting through Jaimini's Chara Dasha; Rath, + Narayana Dasa p.43 (c); PyJHora basic rule; prashna guide rule 1). + Otherwise the stronger by `_jaimini_stronger_planet`, judged where each + planet stands. Both in the sign keep the stronger-planet result (the + count is 12 either way). 其他星座: 使用传统宫主 """ sign_name = SIGNS[sign_idx] traditional_lord = SIGN_LORDS.get(sign_name, '') - - # Aquarius: Saturn vs Rahu 共主判定 - if sign_idx == 10: # Aquarius - saturn_present = 'Saturn' in longitudes and longitudes['Saturn'] >= 0 - rahu_present = 'Rahu' in longitudes and longitudes['Rahu'] >= 0 - if saturn_present and rahu_present: - return _jaimini_stronger_planet(longitudes, 'Saturn', 'Rahu', sign_idx) - return 'Saturn' if saturn_present else 'Rahu' - - # Scorpio: Mars vs Ketu 共主判定 - if sign_idx == 7: # Scorpio - mars_present = 'Mars' in longitudes and longitudes['Mars'] >= 0 - ketu_present = 'Ketu' in longitudes and longitudes['Ketu'] >= 0 - if mars_present and ketu_present: - return _jaimini_stronger_planet(longitudes, 'Mars', 'Ketu', sign_idx) - return 'Mars' if mars_present else 'Ketu' - - return traditional_lord + pair = {10: ('Saturn', 'Rahu'), 7: ('Mars', 'Ketu')}.get(sign_idx) + if pair is None: + return traditional_lord + first, second = pair + first_present = first in longitudes and longitudes[first] >= 0 + second_present = second in longitudes and longitudes[second] >= 0 + if not (first_present and second_present): + return first if first_present else second + first_in = _get_planet_house(longitudes, first) == sign_idx + second_in = _get_planet_house(longitudes, second) == sign_idx + if first_in and not second_in: + return second + if second_in and not first_in: + return first + return _jaimini_stronger_planet(longitudes, first, second, sign_idx) def _sign_is_even_footed(sign_idx: int) -> bool: @@ -707,8 +736,21 @@ def calc_chara_dasha_with_antardasha(asc_sign_idx: int, antar_sequence = [(md_sign_idx + 12 - i) % 12 for i in range(12)] else: antar_sequence = [(md_sign_idx + i) % 12 for i in range(12)] + elif profile == "kn_rao": + # K.N. Rao, Predicting through Jaimini's Chara Dasha, printed + # pp.35-36: each mahadasha sign runs its own direction (reverse + # when the 9th from it is even-footed) and its own sign comes + # last. The book's Scorpio MD (pp.49-50) runs Libra .. Scorpio and + # its Capricorn MD (pp.51-52) opens with Sagittarius (golden rows + # in references/oracle/chara_narayana_book_golden_cases_2026_08_28.json). + # Before BUG-1567 every MD reused the lagna order shifted by one, + # which matches the book only for the first MD. + if _sign_is_even_footed((md_sign_idx + 8) % 12): + antar_sequence = [(md_sign_idx - i) % 12 for i in range(1, 13)] + else: + antar_sequence = [(md_sign_idx + i) % 12 for i in range(1, 13)] else: - # Antardasha序列：Mahadasha序列偏移1（PyJHora method=2） + # Antardasha序列：Mahadasha序列偏移1（Goel 两档未找到出处，沿用旧序） antar_sequence = progression[1:] + progression[:1] antardasha_list = [] @@ -744,7 +786,13 @@ def calc_chara_dasha_with_antardasha(asc_sign_idx: int, base['has_antardasha'] = True base['has_pratyantar'] = True - base['antardasha_method'] = 'equal_division_12 (PyJHora method=2)' + base['antardasha_method'] = ( + 'equal_division_12; kn_rao: own direction per mahadasha sign, mahadasha sign last (K.N. Rao pp.35-36)' + if profile == 'kn_rao' else + 'equal_division_12; goel_shastri_method2: mahadasha sign first, its own direction' + if profile == 'goel_shastri_method2' else + 'equal_division_12; lagna order shifted by one (unsourced, unchanged)' + ) return base diff --git a/scripts/jyotish_engine.py b/scripts/jyotish_engine.py index 54caee8a..9fc569a5 100644 --- a/scripts/jyotish_engine.py +++ b/scripts/jyotish_engine.py @@ -15283,8 +15283,13 @@ def _build_natal_foundation_modules(args, planet_lons, *, asc_lon=None, jd=None) hours_from_sunrise = (daynight["julian_day_ut"] - daynight["sunrise_jd_ut"]) * 24 if hours_from_sunrise < 0: hours_from_sunrise += 24 + # The Vedic day (vara) runs sunrise to sunrise: a birth before sunrise + # belongs to the previous weekday, and its hora counts from that + # day's sunrise (BUG-1568). The weekday is the civil date of the + # sunrise the hours are counted from, not the birth's civil date. # muhurta.py uses Sunday=0 while datetime.weekday() uses Monday=0. - weekday = (birth_dt.weekday() + 1) % 7 + sy, sm, sd, _ = swe.revjul(daynight["sunrise_jd_ut"] + float(args.tz) / 24.0) + weekday = (datetime(int(sy), int(sm), int(sd)).weekday() + 1) % 7 panchanga = calc_panchanga( float(planet_lons["Sun"]), float(planet_lons["Moon"]), diff --git a/scripts/research/reported_offset_sweep.py b/scripts/research/reported_offset_sweep.py index 3dbe5bac..ebe307cf 100644 --- a/scripts/research/reported_offset_sweep.py +++ b/scripts/research/reported_offset_sweep.py @@ -42,8 +42,11 @@ MINUTE_STEP = 1 # 原值: docs/research/reported_offset_data_audit_2026_11_04.{freeze.json,json} # 新值: docs/research/reported_offset_moon_paksha_2026_11_04.{freeze.json,json} # 原因: BUG-1557 月亮 Paksha 口径（scripts/shadbala.py）改了冻结身份文件，ERR-110 另存新记录 -FREEZE = ROOT / "docs/research/reported_offset_moon_paksha_2026_11_04.freeze.json" -REPORT = ROOT / "docs/research/reported_offset_moon_paksha_2026_11_04.json" +# 原值: docs/research/reported_offset_moon_paksha_2026_11_04.{freeze.json,json} +# 新值: docs/research/reported_offset_audit_h_2026_11_04.{freeze.json,json} +# 原因: 数据核对 H 的 BUG-1566 / BUG-1567（scripts/jaimini.py，Chara Dasha 双主星与小运次序）改了冻结身份文件，ERR-110 另存新记录 +FREEZE = ROOT / "docs/research/reported_offset_audit_h_2026_11_04.freeze.json" +REPORT = ROOT / "docs/research/reported_offset_audit_h_2026_11_04.json" LEGACY_REPORT = ROOT / "docs/research/reported_offset_2026_09_20.json" diff --git a/scripts/research/sealed_holdout_rerun.py b/scripts/research/sealed_holdout_rerun.py index 07a941f6..75ba85f2 100644 --- a/scripts/research/sealed_holdout_rerun.py +++ b/scripts/research/sealed_holdout_rerun.py @@ -39,8 +39,11 @@ DATASET = ROOT / "references/real_case_calibration/minute_rectification_holdout_ # 原值: docs/research/sealed_holdout_rerun_data_audit_2026_11_04.{freeze.json,json} # 新值: docs/research/sealed_holdout_rerun_moon_paksha_2026_11_04.{freeze.json,json} # 原因: BUG-1557 月亮 Paksha 口径（scripts/shadbala.py）改了冻结身份文件，ERR-110 另存新记录 -FREEZE = ROOT / "docs/research/sealed_holdout_rerun_moon_paksha_2026_11_04.freeze.json" -REPORT = ROOT / "docs/research/sealed_holdout_rerun_moon_paksha_2026_11_04.json" +# 原值: docs/research/sealed_holdout_rerun_moon_paksha_2026_11_04.{freeze.json,json} +# 新值: docs/research/sealed_holdout_rerun_audit_h_2026_11_04.{freeze.json,json} +# 原因: 数据核对 H 的 BUG-1566 / BUG-1567（scripts/jaimini.py，Chara Dasha 双主星与小运次序）改了冻结身份文件，ERR-110 另存新记录 +FREEZE = ROOT / "docs/research/sealed_holdout_rerun_audit_h_2026_11_04.freeze.json" +REPORT = ROOT / "docs/research/sealed_holdout_rerun_audit_h_2026_11_04.json" LEGACY_REPORT = ROOT / "docs/research/sealed_holdout_rerun_2026_09_20.json" ARCHIVE = ROOT / "docs/research/history/rectification_pre_cross_midnight_2026_09_20" PRODUCTION_FILES = [ diff --git a/tests/fixtures/rashi_dasha_pyjhora_20261008.json b/tests/fixtures/rashi_dasha_pyjhora_20261008.json index b142d915..1de98efe 100644 --- a/tests/fixtures/rashi_dasha_pyjhora_20261008.json +++ b/tests/fixtures/rashi_dasha_pyjhora_20261008.json @@ -619,7 +619,7 @@ 6, 6, 4, - 5, + 1, 9, 12, 7, @@ -658,7 +658,6 @@ "subperiod" ], "chara": [ - "years", "subperiod" ] } @@ -1274,7 +1273,7 @@ "years": [ 12, 0, - 3, + 9, 8, 2, 1, @@ -1318,7 +1317,6 @@ "subperiod" ], "chara": [ - "years", "subperiod" ] } @@ -1963,7 +1961,7 @@ 11, 10, 2, - 8, + 3, 6, 5, 5, @@ -2001,7 +1999,6 @@ "subperiod" ], "chara": [ - "years", "subperiod" ] } diff --git a/tests/test_audit_h_dasha_sky_20261104.py b/tests/test_audit_h_dasha_sky_20261104.py new file mode 100644 index 00000000..921a914f --- /dev/null +++ b/tests/test_audit_h_dasha_sky_20261104.py @@ -0,0 +1,199 @@ +"""Data audit wave 2 (H), 2026-11-04: Chara Dasha, time-segment points and the +birth weekday, checked against PyJHora 4.8.6, Swiss Ephemeris and the books. + +External reference values are stored as plain numbers (PyJHora is AGPL and is +not imported here). Public charts are Rodden AA figures already in +benchmarks/jyotish/data/benchmark_samples.json. +""" + +from __future__ import annotations + +import json +from datetime import datetime +from pathlib import Path +from types import SimpleNamespace + +import pytest +import swisseph as swe + +from scripts import gulika, jaimini +from scripts.jyotish_engine import _build_natal_foundation_modules, compute_chart_data + +ROOT = Path(__file__).resolve().parents[1] +GRAHAS = ("Sun", "Moon", "Mars", "Mercury", "Jupiter", "Venus", "Saturn", "Rahu", "Ketu") + + +def _chart(year, month, day, hour, minute, lat, lon, tz, ayanamsa="raman"): + chart, asc_idx, jd, _ = compute_chart_data(year, month, day, hour, minute, lat, lon, tz, + node_mode="mean", ayanamsa_name=ayanamsa) + return asc_idx, {name: chart["planets"][name]["degree_raw"] for name in GRAHAS}, jd + + +BUSH = (1946, 7, 6, 7, 26, 41.3, -72.9333, -4.0) +TAYLOR = (1932, 2, 27, 2, 30, 51.5, -0.1667, 0.0) +JOBS = (1955, 2, 24, 19, 15, 37.7749, -122.4194, -8.0) +TOKYO = (1964, 10, 10, 12, 0, 35.6762, 139.6503, 9.0) + + +# ── BUG-1566: Scorpio / Aquarius co-lord in K.N. Rao Chara Dasha ───────────── + +@pytest.mark.parametrize("ayanamsa", ["raman", "lahiri"]) +@pytest.mark.parametrize("birth, scorpio, aquarius", [ + # PyJHora 4.8.6 chara KN_RAO, same ayanamsa, mean node (numbers only). + (BUSH, 9, 7), # Ketu in Scorpio, Mars in Leo -> Mars (was Ketu, 13 years) + (TAYLOR, 3, 11), # both outside: Mars wins Scorpio, Rahu wins Aquarius (were 10 / 1) + (JOBS, 6, 1), # Aquarius goes to Rahu (was Saturn, 5 years) +]) +def test_co_lord_years_match_pyjhora_kn_rao(ayanamsa, birth, scorpio, aquarius): + asc_idx, lons, _ = _chart(*birth, ayanamsa=ayanamsa) + years = {row["sign"]: row["duration_years"] for row in + jaimini.calc_chara_dasha(asc_idx, lons, birth[0], birth[1], birth[2])["dasha_sequence"]} + assert years["Scorpio"] == scorpio + assert years["Aquarius"] == aquarius + + +def test_a_co_lord_sitting_in_the_sign_gives_way_to_the_one_outside(): + # K.N. Rao; Rath, Narayana Dasa p.43 (c); references/prashna-complete-guide.md. + base = {"Sun": 15.0, "Moon": 75.0, "Mercury": 40.0, "Jupiter": 100.0, "Venus": 160.0} + assert jaimini._resolve_chara_dasha_lord({**base, "Mars": 215.0, "Ketu": 45.0, "Rahu": 225.0, "Saturn": 5.0}, 7) == "Ketu" + assert jaimini._resolve_chara_dasha_lord({**base, "Mars": 190.0, "Ketu": 225.0, "Rahu": 45.0, "Saturn": 5.0}, 7) == "Mars" + assert jaimini._resolve_chara_dasha_lord({**base, "Mars": 0.0, "Ketu": 100.0, "Rahu": 280.0, "Saturn": 310.0}, 10) == "Rahu" + asc_idx, lons, _ = _chart(*TOKYO) + assert int(lons["Saturn"] // 30) == 10 # Saturn in Aquarius + assert jaimini._resolve_chara_dasha_lord(lons, 10) == "Rahu" + + +def test_co_lord_choice_depends_on_where_the_planets_stand(): + # Before BUG-1566 dignity was read in Scorpio itself, so Ketu won every + # chart; with both lords outside, moving them must be able to flip it. + base = {"Sun": 15.0, "Moon": 75.0, "Mercury": 40.0, "Jupiter": 100.0, "Venus": 160.0, "Saturn": 5.0} + mars_exalted = {**base, "Mars": 285.0, "Ketu": 130.0, "Rahu": 310.0} # Mars in Capricorn, alone + ketu_crowded = {**base, "Mars": 250.0, "Ketu": 105.0, "Rahu": 285.0} # Ketu in Cancer with Jupiter + assert jaimini._resolve_chara_dasha_lord(mars_exalted, 7) == "Mars" + assert jaimini._resolve_chara_dasha_lord(ketu_crowded, 7) == "Ketu" + + +# ── BUG-1567: K.N. Rao Chara antardasha order ─────────────────────────────── + +def _golden(case_id): + data = json.loads((ROOT / "references/oracle/chara_narayana_book_golden_cases_2026_08_28.json").read_text()) + return next(case for case in data["golden_cases"] if case["case_id"] == case_id) + + +def test_every_mahadasha_runs_its_own_direction_and_ends_on_itself(): + asc_idx, lons, _ = _chart(*JOBS) + result = jaimini.calc_chara_dasha_with_antardasha(asc_idx, lons, 1955, 2, 24) + for md in result["dasha_sequence"]: + order = [ad["sign_idx"] for ad in md["antardashas"]] + assert order[-1] == md["sign_idx"] + step = -1 if ((md["sign_idx"] + 8) % 12) in jaimini._EVEN_FOOTED_SIGNS else 1 + assert order == [(md["sign_idx"] + step * i) % 12 for i in range(1, 13)] + + +def test_scorpio_mahadasha_matches_the_book_order(): + # K.N. Rao, Predicting through Jaimini's Chara Dasha, pdf pp.49-50. + expected = _golden("rao_chara_male_1949_scorpio_ad")["profile_assertions"]["subperiod_order"] + asc_idx, lons, _ = _chart(*JOBS) + result = jaimini.calc_chara_dasha_with_antardasha(asc_idx, lons, 1955, 2, 24) + scorpio = next(md for md in result["dasha_sequence"] if md["sign"] == "Scorpio") + assert [ad["sign"] for ad in scorpio["antardashas"]] == expected + + +def test_vietnamese_lady_replays_the_book_mahadashas_and_first_capricorn_antardasha(): + # K.N. Rao, pdf pp.51-52: 1958-01-19 14:45 Hanoi; Lahiri as in the book. + asc_idx, lons, _ = _chart(1958, 1, 19, 14, 45, 21.03, 105.85, 7.0, ayanamsa="lahiri") + result = jaimini.calc_chara_dasha_with_antardasha(asc_idx, lons, 1958, 1, 19) + rows = [(md["sign"], md["duration_years"]) for md in result["dasha_sequence"][:5]] + book = [(row["sign"], row["duration_years"]) for row in _golden("rao_chara_vietnamese_lady_1958_capricorn_ad")["period_rows"] if row["level"] == "MD"] + assert rows == book + capricorn = next(md for md in result["dasha_sequence"] if md["sign"] == "Capricorn") + assert capricorn["antardashas"][0]["sign"] == "Sagittarius" + + +def test_goel_profiles_keep_their_antardasha_order(): + asc_idx, lons, _ = _chart(*JOBS) + progression = jaimini._chara_progression_profile(asc_idx, lons, profile="goel_lagna_start") + result = jaimini.calc_chara_dasha_with_antardasha(asc_idx, lons, 1955, 2, 24, profile="goel_lagna_start") + for md in result["dasha_sequence"]: + assert [ad["sign_idx"] for ad in md["antardashas"]] == progression[1:] + progression[:1] + + +# ── BUG-1565: night shares of the time-segment points ─────────────────────── + +def test_night_and_day_share_tables_follow_the_weekday_rule(): + for weekday in range(7): # Monday=0 + sunday_based = (weekday + 1) % 7 + assert gulika.DAY_RULERS[weekday][0] == sunday_based + assert gulika.NIGHT_RULERS[weekday][0] == (sunday_based + 4) % 7 # lord of the 5th weekday + assert gulika.DAY_RULERS[weekday].index(6) == gulika.SATURN_PART_START[weekday]["day"] + assert gulika.NIGHT_RULERS[weekday].index(6) == gulika.SATURN_PART_START[weekday]["night"] + + +def _independent_point(moment, lat, lon, tz, planet, middle, ayanamsa="raman"): + flags = swe.FLG_SWIEPH | swe.FLG_TRUEPOS + geo = (lon, lat, 0.0) + + def event(after, kind): + return swe.rise_trans(after, swe.SUN, kind | swe.BIT_HINDU_RISING, geo, flags=flags)[1][0] + + jd = swe.julday(moment.year, moment.month, moment.day, moment.hour + moment.minute / 60 - tz) + midnight = swe.julday(moment.year, moment.month, moment.day, -tz) + rise = event(midnight, swe.CALC_RISE) + if rise > jd: + midnight -= 1.0 + rise = event(midnight, swe.CALC_RISE) + sunset, next_rise = event(midnight, swe.CALC_SET), event(midnight + 1.0, swe.CALC_RISE) + day = rise <= jd < sunset + start, end = (rise, sunset) if day else (sunset, next_rise) + y, m, d, _ = swe.revjul(start + tz / 24) + sunday_based = (datetime(y, m, d).weekday() + 1) % 7 + first = sunday_based if day else (sunday_based + 4) % 7 + cycle = [0, 1, 2, 3, 4, 5, 6, -1] + order = [cycle[(cycle.index(first) + i) % 8] for i in range(8)] + fraction = (order.index(planet) + (0.5 if middle else 0.0)) / 8 + from scripts.ayanamsa_utils import temporary_ayanamsa + with temporary_ayanamsa(ayanamsa, swe): + return swe.houses_ex(start + (end - start) * fraction, lat, lon, b"P", swe.FLG_SWIEPH | swe.FLG_SIDEREAL)[1][0] % 360 + + +@pytest.mark.parametrize("birth", [JOBS, TAYLOR, (1970, 3, 21, 18, 15, 51.5074, -0.1278, 0.0)]) +def test_thursday_to_saturday_night_points_sit_in_the_right_share(birth): + # Jobs: Thursday night; Taylor: Friday night (before Saturday's sunrise); + # London smoke chart: Saturday night. + moment = datetime(*birth[:5]) + lat, lon, tz = birth[5], birth[6], birth[7] + sun = _chart(*birth)[1]["Sun"] + raw = gulika.calculate_upagrahas(moment, lat=lat, lon=lon, tz=tz, sun_longitude=sun, ayanamsa="raman")["raw"] + assert raw["Maandi"]["period"] == "night" + for name, (planet, part) in gulika.TEMPORAL_UPAGRAHAS.items(): + expected = _independent_point(moment, lat, lon, tz, planet, part == "middle") + assert raw[name]["longitude"] == pytest.approx(expected, abs=0.01), name + # Maandi is the middle of the same Saturn share whose start is Gulika. + single = gulika.calculate_gulika(moment, lat=lat, lon=lon, tz=tz, ayanamsa="raman") + assert raw["Maandi"]["segment_fraction"] == pytest.approx(single["segment_fraction"] + 1 / 16) + + +# ── BUG-1568: birth weekday (vara) and hora before sunrise ────────────────── + +def _panchanga(birth): + year, month, day, hour, minute, lat, lon, tz = birth + _, lons, jd = _chart(*birth) + args = SimpleNamespace(year=year, month=month, day=day, hour=hour, minute=minute, second=0, + lat=lat, lon=lon, tz=tz, ayanamsa="raman", node_mode="mean", position_mode="legacy") + return _build_natal_foundation_modules(args, lons, jd=jd)["panchanga"]["raw"] + + +def test_a_birth_before_sunrise_belongs_to_the_previous_weekday(): + # Taylor: Saturday 1932-02-27 02:30 civil, before sunrise -> Friday + # (PyJHora drik.vaara, the Shadbala path in this repo, Panchanga practice). + raw = _panchanga(TAYLOR) + assert raw["vara"]["vara"] == "Friday" + # Hora counts from Friday's sunrise: about 19.5 hours in -> the 20th hora, + # Friday's sequence Venus, Mercury, Moon, Saturn, Jupiter, Mars, Sun, ... -> Mars. + assert raw["hora"]["hora_num"] == 20 + assert raw["hora"]["hora_lord"] == "Mars" + + +def test_a_daytime_birth_keeps_its_civil_weekday(): + raw = _panchanga(BUSH) # Saturday morning after sunrise + assert raw["vara"]["vara"] == "Saturday" diff --git a/tests/test_chara_dasha_board_lord.py b/tests/test_chara_dasha_board_lord.py index 2bf23a7d..0f65d37e 100644 --- a/tests/test_chara_dasha_board_lord.py +++ b/tests/test_chara_dasha_board_lord.py @@ -17,8 +17,9 @@ from jaimini import ( # noqa: E402 calc_chara_dasha_with_antardasha, ) -# Scorpio: Ketu (exalted there in this table) outranks Mars, so the engine picks Ketu. -# Aquarius: Saturn owns it and outranks Rahu, so the engine keeps Saturn. +# Scorpio: Ketu sits in Scorpio and Mars in Libra, so the lord outside, Mars, +# counts (BUG-1566; before, Ketu always won Scorpio because its dignity was +# read in Scorpio itself). Aquarius: Rahu sits in Aquarius, so Saturn counts. LONGITUDES = { "Sun": 15.0, "Moon": 75.0, @@ -47,8 +48,17 @@ def test_every_mahadasha_row_names_its_lord_and_the_sign_it_sits_in(): def test_co_lord_signs_carry_the_engine_choice_not_the_traditional_lord(): + # Was Scorpio -> Ketu / Scorpio (原值); now Mars / Libra (新值): the co-lord + # sitting in the sign gives way to the one outside it (BUG-1566). rows = _rows() - assert rows["Scorpio"]["lord"] == "Ketu" - assert rows["Scorpio"]["lord_in_sign"] == "Scorpio" + assert rows["Scorpio"]["lord"] == "Mars" + assert rows["Scorpio"]["lord_in_sign"] == "Libra" assert rows["Aquarius"]["lord"] == "Saturn" assert rows["Aquarius"]["lord_in_sign"] == "Aries" + # Mars in Scorpio, Ketu in Taurus: the row carries Ketu, not the + # traditional lord. + moved = {**LONGITUDES, "Mars": 215.0, "Ketu": 45.0, "Rahu": 225.0} + result = calc_chara_dasha_with_antardasha(0, moved, 1990, 6) + scorpio = next(row for row in result["dasha_sequence"] if row["sign"] == "Scorpio") + assert scorpio["lord"] == "Ketu" + assert scorpio["lord_in_sign"] == "Taurus" diff --git a/tests/test_rashi_dashas_native.py b/tests/test_rashi_dashas_native.py index f81b8441..c85375ee 100644 --- a/tests/test_rashi_dashas_native.py +++ b/tests/test_rashi_dashas_native.py @@ -285,6 +285,9 @@ def test_pyjhora_fixture_diffs_stay_on_the_recorded_steps() -> None: # 原值：niryaana_shoola 的 native 行与 Shoola 一样，从上升或第七宫起、每段 9 年，并带子运差异。 # 新值：同一键改为 PVR 主运的星座和年数；diff_steps 按新表相对 PyJHora 重记。 # 原因：产品 2026-10-18 改口径。PyJHora 对照行没有重跑，只改我们自己的期望。 + # 原值：乔布斯 / 奥巴马 / 爱因斯坦三盘 native.chara 年数各有一段（水瓶或天蝎）与 PyJHora 不同，diff_steps 含 years。 + # 新值：三盘 Chara 年数与 PyJHora 4.8.7 对照行逐段相同，diff_steps 只剩 subperiod。 + # 原因：BUG-1566 天蝎 / 水瓶双主星按盘面判定（一主在本宫取另一主）。PyJHora 对照行未重跑。 payload = json.loads(FIXTURE.read_text(encoding="utf-8")) assert payload["pyjhora_version"] == "4.8.7" assert payload["generator_python_has_pyjhora"] is True diff --git a/tests/test_sealed_holdout_contract_freshness.py b/tests/test_sealed_holdout_contract_freshness.py index f51e6131..cf53d435 100644 --- a/tests/test_sealed_holdout_contract_freshness.py +++ b/tests/test_sealed_holdout_contract_freshness.py @@ -73,6 +73,11 @@ IDENTITY_FORBIDDEN_PREFIXES = ( # 原因: BUG-1557 月亮 Paksha 口径改了冻结身份里的 shadbala.py，ERR-110 另存新记录 "docs/research/sealed_holdout_rerun_moon_paksha_2026_11_04", "docs/research/reported_offset_moon_paksha_2026_11_04", + # 原值: 排除到 moon_paksha_2026_11_04 + # 新值: 再排除 audit_h_2026_11_04 两份冻结路径（追加，不替换上面的） + # 原因: 数据核对 H 的 BUG-1566 / BUG-1567 改了冻结身份里的 jaimini.py，ERR-110 另存新记录 + "docs/research/sealed_holdout_rerun_audit_h_2026_11_04", + "docs/research/reported_offset_audit_h_2026_11_04", "docs/research/history/", "artifacts/", )