Jesse_ChenandClaude Opus 5.5
4ed2e55627
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_017eEAG8HD3mm8gsKXgk8uU8
42 lines
2.2 KiB
Python
42 lines
2.2 KiB
Python
"""Positive control for the angle-timing A1 pipeline (Claude acceptance 2026-10-01).
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Plants three day-precision events per case on dates when transit Saturn sits within
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0.15 deg of the TRUE natal ascendant, then ranks the truth minute with the same
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ranks_for() used by A1. A working pipeline must rank it near 0; moving the same
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dates by whole years must return it to chance (~0.5).
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PYTHONHASHSEED=0 python3 scripts/research/angle_timing_positive_control.py
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"""
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import sys, statistics, random
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from datetime import date, timedelta
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sys.path.insert(0, ".")
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import swisseph as swe
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from scripts.research import angle_timing_lib as at
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from scripts.research.angle_timing_research import ranks_for
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cases = at.load_cases()
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res = {"real": [], "planted": [], "planted_shuffled_years": []}
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rng = random.Random(7)
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for case in cases:
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ch = at.CaseChart(case)
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asc_truth = float(ch.asc[at.RADIUS_MAX])
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# find Saturn conjunction dates with the TRUE natal ascendant (tropical, both sides)
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d = ch.local.date() + timedelta(days=400); hits = []
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prev = None
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while d < date(2026, 9, 1) and len(hits) < 3:
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jd = swe.julday(d.year, d.month, d.day, 12.0)
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s = float(at.aspect_sep(__import__("numpy").array([asc_truth]), at.planet_lon(jd, swe.SATURN))[0])
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if s < 0.15 and (not hits or (d - hits[-1]).days > 200): hits.append(d)
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d += timedelta(days=2)
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if not hits:
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continue
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planted = [{"id": f"p{i}", "domain": "career", "precision": "day", "date": h.isoformat()} for i, h in enumerate(hits)]
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# same dates moved by random whole years (keeps precision, breaks the alignment)
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moved = [{**e, "date": (date.fromisoformat(e["date"]) + timedelta(days=365 * rng.choice([-3, -2, 2, 3]))).isoformat()} for e in planted]
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moved = [e for e in moved if ch.local.date() < date.fromisoformat(e["date"]) < date(2026, 9, 1)]
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for key, evs in (("planted", planted), ("planted_shuffled_years", moved)):
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r = ranks_for(ch, evs)
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res[key].append(r["TR"]["1.0"]["30"])
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res["real"].append(ranks_for(ch, None)["TR"]["1.0"]["30"])
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for k, v in res.items():
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print(f"{k:24s} n={len(v):2d} mean truth rank (TR, 1°, ±30) = {statistics.mean(v):.3f} share with rank<0.15: {sum(1 for x in v if x < 0.15)/len(v):.2f}")
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