research(rectification): angle-timing A1 — real vs shuffled and age-preserving jittered dates, 0/9 tests significant (BUG-1141)
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_017eEAG8HD3mm8gsKXgk8uU8
This commit is contained in:
Jesse_Chen
co-authored by
Claude Opus 5.5
Claude Opus 5.5
parent
f507570448
commit
915c3e829d
@@ -251,3 +251,27 @@ def stable_json(payload: Any) -> str:
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def sha256_of(path: Path) -> str:
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return hashlib.sha256(path.read_bytes()).hexdigest()
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def jittered_events(case: dict[str, Any], rng: Random) -> list[dict[str, Any]]:
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"""Second null: each event moved 1-3 years earlier or later (same precision, month/day kept),
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which keeps the age structure of real biographies; clamped to after birth and before the cutoff."""
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birth = birth_local(case).date()
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out = []
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for raw in case["events"]:
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text = str(raw.get("date") or "")
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p = str(raw.get("precision") or "")
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try:
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year = int(text[:4])
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except ValueError:
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out.append(dict(raw)); continue
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shift = rng.choice((-1, 1)) * rng.randint(1, 3)
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new_year = min(max(year + shift, birth.year + 1), EVENT_CUTOFF.year - 1)
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if p == "day" and len(text) >= 10:
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m, d = int(text[5:7]), int(text[8:10]); d = min(d, calendar.monthrange(new_year, m)[1]); new = f"{new_year:04d}-{m:02d}-{d:02d}"
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elif p == "month" and len(text) >= 7:
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new = f"{new_year:04d}-{text[5:7]}"
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else:
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new = f"{new_year:04d}"
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out.append({**raw, "date": new})
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return out
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@@ -0,0 +1,217 @@
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"""Angle-timing research runner (BUG-1141).
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A1: for each technique × orb, compare where the truth minute ranks inside its
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window when events keep their real dates versus shuffled dates. Pre-registered
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tests: TR / SP / SA × orbs 1° / 2° / 3° (9 tests), primary radius ±30, with
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±10 / ±60 reported. Score per candidate = number of events with a contact within
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the orb; truth rank = share of other window minutes scoring higher (ties half);
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0.5 = chance. Real mean rank is compared with the shuffled-date distribution.
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A2 (only for techniques significant in A1): see run_a2.
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Usage:
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PYTHONHASHSEED=0 python3 -m scripts.research.angle_timing_research --stages a1 \
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--shuffles 200 --json-out docs/research/angle_timing_a1_2026_10_01.json
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"""
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from __future__ import annotations
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import argparse
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import platform
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import sys
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import time
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from pathlib import Path
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from random import Random
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from typing import Any
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import numpy as np
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ROOT = Path(__file__).resolve().parents[2]
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if str(ROOT) not in sys.path:
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sys.path.insert(0, str(ROOT))
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from scripts.research import angle_timing_lib as at # noqa: E402
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RADII = (10, 30, 60)
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PRIMARY_RADIUS = 30
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N_TESTS = len(at.TECHNIQUES) * len(at.ORBS)
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BONFERRONI_PERCENTILE = 100.0 * (1.0 - 0.05 / N_TESTS)
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UNCORRECTED_PERCENTILE = 95.0
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def ranks_for(chart: at.CaseChart, raw_events: list[dict[str, Any]] | None) -> dict[str, dict[str, dict[str, float]]]:
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events = chart.events(raw_events)
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out: dict[str, dict[str, dict[str, float]]] = {}
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for tech in at.TECHNIQUES:
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seps = chart.separations(tech, events)
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out[tech] = {}
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for orb in at.ORBS:
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scores = at.hit_counts(seps, orb) if seps.shape[0] else np.zeros(len(chart.offsets))
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out[tech][str(orb)] = {str(r): at.truth_rank(scores, r) for r in RADII}
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return out
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def run_a1(cases: list[dict[str, Any]], shuffles: int, log) -> dict[str, Any]:
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charts = [at.CaseChart(case) for case in cases]
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real = {chart.case_id: ranks_for(chart, None) for chart in charts}
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usable = {chart.case_id: {t: int(chart.separations(t, chart.events()).shape[0]) for t in at.TECHNIQUES} for chart in charts}
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shuffled_means: dict[str, dict[str, dict[str, list[float]]]] = {
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t: {str(o): {str(r): [] for r in RADII} for o in at.ORBS} for t in at.TECHNIQUES}
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started = time.perf_counter()
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for rep in range(shuffles):
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per_case = []
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for chart in charts:
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rng = Random(f"angle-timing|{chart.case_id}|{rep}")
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per_case.append(ranks_for(chart, at.shuffled_events(chart.case, rng)))
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for t in at.TECHNIQUES:
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for o in at.ORBS:
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for r in RADII:
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shuffled_means[t][str(o)][str(r)].append(round(float(np.mean([pc[t][str(o)][str(r)] for pc in per_case])), 6))
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if (rep + 1) % 20 == 0:
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log(f"shuffle {rep + 1}/{shuffles} ({time.perf_counter() - started:.0f}s)")
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table: dict[str, Any] = {}
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for t in at.TECHNIQUES:
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table[t] = {}
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for o in at.ORBS:
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table[t][str(o)] = {}
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for r in RADII:
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real_mean = round(float(np.mean([real[cid][t][str(o)][str(r)] for cid in real])), 6)
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dist = np.array(shuffled_means[t][str(o)][str(r)])
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# percentile: share of shuffles the real dates beat (lower rank is better)
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pct = round(100.0 * float(((dist > real_mean).sum() + 0.5 * (dist == real_mean).sum()) / len(dist)), 3)
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table[t][str(o)][str(r)] = {
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"real_mean_rank": real_mean,
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"shuffle_mean": round(float(dist.mean()), 6),
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"shuffle_sd": round(float(dist.std(ddof=1)), 6) if len(dist) > 1 else 0.0,
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"shuffle_p05": round(float(np.percentile(dist, 5)), 6),
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"percentile_beaten": pct,
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"significant_uncorrected": bool(pct >= UNCORRECTED_PERCENTILE),
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"significant_bonferroni": bool(pct >= BONFERRONI_PERCENTILE),
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}
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primary = {t: {str(o): table[t][str(o)][str(PRIMARY_RADIUS)] for o in at.ORBS} for t in at.TECHNIQUES}
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significant = sorted(f"{t}@{o}" for t in at.TECHNIQUES for o in at.ORBS
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if primary[t][str(o)]["significant_bonferroni"])
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return {
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"tests": N_TESTS,
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"primary_radius": PRIMARY_RADIUS,
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"bonferroni_percentile": round(BONFERRONI_PERCENTILE, 4),
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"uncorrected_percentile": UNCORRECTED_PERCENTILE,
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"shuffles": shuffles,
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"table": table,
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"significant_primary_bonferroni": significant,
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"usable_events_per_case": usable,
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"real_per_case": real,
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"shuffled_means": shuffled_means,
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}
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def _precision_filter(raw_events: list[dict[str, Any]], precision: str) -> list[dict[str, Any]]:
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return [e for e in raw_events if str(e.get("precision")) == precision]
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def run_jitter_null(cases: list[dict[str, Any]], shuffles: int, log) -> dict[str, Any]:
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"""Second null (age-structure preserving): real ranks vs events moved ±1-3 years, all radii."""
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charts = [at.CaseChart(case) for case in cases]
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real = [ranks_for(chart, None) for chart in charts]
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dist: dict[str, dict[str, dict[str, list[float]]]] = {t: {str(o): {str(r): [] for r in RADII} for o in at.ORBS} for t in at.TECHNIQUES}
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for rep in range(shuffles):
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per = [ranks_for(c, at.jittered_events(c.case, Random(f"angle-timing-jitter|{c.case_id}|{rep}"))) for c in charts]
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for t in at.TECHNIQUES:
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for o in at.ORBS:
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for r in RADII:
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dist[t][str(o)][str(r)].append(round(float(np.mean([pc[t][str(o)][str(r)] for pc in per])), 6))
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if (rep + 1) % 10 == 0:
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log(f"jitter {rep + 1}/{shuffles}")
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table: dict[str, Any] = {}
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for t in at.TECHNIQUES:
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table[t] = {}
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for o in at.ORBS:
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table[t][str(o)] = {}
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for r in RADII:
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real_mean = round(float(np.mean([x[t][str(o)][str(r)] for x in real])), 6)
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d = np.array(dist[t][str(o)][str(r)])
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pct = round(100.0 * float(((d > real_mean).sum() + 0.5 * (d == real_mean).sum()) / len(d)), 3)
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table[t][str(o)][str(r)] = {"real_mean_rank": real_mean, "jitter_mean": round(float(d.mean()), 6),
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"percentile_beaten": pct}
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return {"shuffles": shuffles, "null": "each event moved 1-3 years earlier/later, precision kept", "table": table}
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def run_subsets(cases: list[dict[str, Any]], shuffles: int, log) -> dict[str, Any]:
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"""Robustness: real vs shuffled by event precision and by LMT era (primary radius only)."""
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charts = [at.CaseChart(case) for case in cases]
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lmt = {chart.case_id for chart in charts if chart.local.year < 1900}
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subsets: dict[str, tuple[list[at.CaseChart], str | None]] = {
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"precision=day": (charts, "day"), "precision=month": (charts, "month"), "precision=year": (charts, "year"),
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"era=lmt_before_1900": ([c for c in charts if c.case_id in lmt], None),
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"era=1900_and_later": ([c for c in charts if c.case_id not in lmt], None),
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}
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out: dict[str, Any] = {}
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for name, (members, precision) in subsets.items():
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def ranks(chart: at.CaseChart, raw: list[dict[str, Any]]):
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events = _precision_filter(raw, precision) if precision else raw
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return ranks_for(chart, events)
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real = [ranks(c, list(c.case["events"])) for c in members]
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dist: dict[str, dict[str, list[float]]] = {t: {str(o): [] for o in at.ORBS} for t in at.TECHNIQUES}
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for rep in range(shuffles):
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per = [ranks(c, at.shuffled_events(c.case, Random(f"angle-timing-sub|{name}|{c.case_id}|{rep}"))) for c in members]
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for t in at.TECHNIQUES:
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for o in at.ORBS:
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dist[t][str(o)].append(round(float(np.mean([pc[t][str(o)][str(PRIMARY_RADIUS)] for pc in per])), 6))
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out[name] = {"cases": len(members), "table": {}}
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for t in at.TECHNIQUES:
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out[name]["table"][t] = {}
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for o in at.ORBS:
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real_mean = round(float(np.mean([r[t][str(o)][str(PRIMARY_RADIUS)] for r in real])), 6)
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d = np.array(dist[t][str(o)])
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pct = round(100.0 * float(((d > real_mean).sum() + 0.5 * (d == real_mean).sum()) / len(d)), 3)
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out[name]["table"][t][str(o)] = {"real_mean_rank": real_mean, "shuffle_mean": round(float(d.mean()), 6),
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"percentile_beaten": pct}
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log(f"subset {name} done")
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return {"radius": PRIMARY_RADIUS, "shuffles": shuffles, "subsets": out,
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"note": "descriptive robustness; significance is judged only on the pre-registered A1 tests"}
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def main() -> int:
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parser = argparse.ArgumentParser()
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parser.add_argument("--stages", default="a1")
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parser.add_argument("--shuffles", type=int, default=200)
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parser.add_argument("--subset-shuffles", type=int, default=50)
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parser.add_argument("--limit", type=int, default=0)
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parser.add_argument("--json-out", required=True)
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parser.add_argument("--quiet", action="store_true")
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args = parser.parse_args()
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log = (lambda _m: None) if args.quiet else (lambda m: print(m, file=sys.stderr, flush=True))
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cases = at.load_cases()
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if args.limit:
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cases = cases[: args.limit]
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payload: dict[str, Any] = {
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"dataset": "v5",
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"holdout_sha256": at.sha256_of(at.HOLDOUT_V5),
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"case_count": len(cases),
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"zodiac": "tropical (aspects are zodiac-independent)",
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"node": "mean",
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"techniques": {
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"TR": "transit Saturn / Jupiter / mean Rahu-Ketu (+Mars for day events) to natal ASC / MC, 0/90/180",
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"SP": "secondary-progressed ASC / MC (quotidian date method, same location) to natal Sun..Saturn, 0/90/180",
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"SA": "solar-arc ASC / MC to natal Sun..Saturn, 0/90/180",
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},
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"orbs": list(at.ORBS),
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"radii": list(RADII),
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"event_cutoff": at.EVENT_CUTOFF.isoformat(),
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"python_version": platform.python_version(),
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}
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stages = {s.strip() for s in args.stages.split(",") if s.strip()}
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if "a1" in stages:
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payload["a1"] = run_a1(cases, args.shuffles, log)
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if "jitter" in stages:
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payload["jitter_null"] = run_jitter_null(cases, args.subset_shuffles, log)
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if "subsets" in stages:
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payload["subsets"] = run_subsets(cases, args.subset_shuffles, log)
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out = Path(args.json_out)
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out.parent.mkdir(parents=True, exist_ok=True)
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out.write_text(at.stable_json(payload), encoding="utf-8")
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log(f"wrote {out}")
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return 0
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if __name__ == "__main__":
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raise SystemExit(main())
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