vvsandClaude Opus 5
baa93963cf
Translation limit of the analogy (f shrank, x-scale did not -> m = inf): defect + remembered + point + exp APS 2531 CHA 1972 both 4503 G2 + defect + remembered + point + exp APS 2588 CHA 1997 both 4585 G2 + contra + remembered + point + exp APS 2773 CHA 2073 both 4846 Chandrupatla APS 2787 CHA 2441 both 5228 Per problem against Chandrupatla now SIGNIFICANT ON BOTH SETS: G2+contra+rem+pt+exp APS 98/18/37 p=1.5e-7, CHA 28/3/9 p=0.0026; defect+rem+pt+exp APS 86/20/47 p=9e-4, CHA 27/3/10 p=0.0076. NOT where predicted: fun9 only -1..-3; the gain is on the flat families (x^9 177 -> 161, x^19 339 -> 167). Server regression x2: 1179 passed, 1 failed = the paper-number check. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
65 lines
2.8 KiB
Python
65 lines
2.8 KiB
Python
"""Comparative table of our wins and losses (server results only).
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Variants of the proposed rule (tent, 3-point, projection) against the library Chandrupatla,
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Brent (brentq) and TOMS748: totals per set, both sets, and per-problem wins/ties/losses with
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the sign test; then the wide-bracket set per family.
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python -u table_wins_losses.py
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"""
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from __future__ import annotations
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import json
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from analyze_extrap import h2h, sign_p
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from where_we_lose import per_family
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def load(p):
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with open(p, encoding="utf8") as fh:
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return {r["label"]: r for r in json.load(fh)}
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def main():
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full = load("sweep_full.json")
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dc = load("sweep_defcontra.json")
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op = load("sweep_orderpt.json")
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ex = load("sweep_explimit.json")
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rivals = {"Chandrupatla": full["chandrupatla"], "Brent": full["brent"],
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"TOMS748": full["toms748"]}
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ours = {
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"proposed rule": full["pure.ratio.derived3.project"],
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"+ G2 (step pattern)": dc["pure+extP.ratio.derived3.project"],
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"+ G2 + analogy entry": dc["pure+extP+flatanalog.ratio.derived3.project"],
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"+ contra + remembered analogy": dc["contra+flatanalogmem.ratio.derived3.project"],
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"+ defect + remembered analogy": dc["defect+flatanalogmem.ratio.derived3.project"],
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"+ G2 + analogy + ORDER POINT": op["pure+extP+flatanalogpt.ratio.derived3.project"],
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"+ G2 + contra + rem. + ORDER PT": op["pure+extP+contra+flatanalogmempt.ratio.derived3.project"],
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"+ defect + rem. + ORDER POINT": op["defect+flatanalogmempt.ratio.derived3.project"],
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"+ G2 + contra + rem. + pt + EXP": ex["pure+extP+contra+flatanalogmempt+exp.ratio.derived3.project"],
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"+ defect + rem. + pt + EXP": ex["defect+flatanalogmempt+exp.ratio.derived3.project"],
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}
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print("TOTALS (evaluations of f, failures charged 200)")
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print(f" {'method':<32} {'APS':>6} {'CHA':>6} {'both':>6}")
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for name, r in list(ours.items()) + list(rivals.items()):
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print(f" {name:<32} {r['APS']['total']:6d} {r['CHA']['total']:6d} "
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f"{r['APS']['total'] + r['CHA']['total']:6d}")
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print("\nPER PROBLEM, ours against each rival: wins/ties/losses (sign-test p)")
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for s in ("APS", "CHA"):
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print(f" {s}")
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for name, r in ours.items():
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cells = []
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for rn, rv in rivals.items():
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w, t, l = h2h(r, rv, s)
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cells.append(f"{rn} {w}/{t}/{l} p={sign_p(w, l):.2g}")
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print(f" {name:<32} " + " ".join(cells))
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print("\nCHA PER FAMILY (ours / Chandrupatla)")
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fams = sorted(per_family(rivals["Chandrupatla"], "CHA"))
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print(" " + " " * 32 + "".join(f"{f:>9}" for f in fams))
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for name, r in list(ours.items()) + [("Chandrupatla", rivals["Chandrupatla"])]:
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pf = per_family(r, "CHA")
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print(f" {name:<32}" + "".join(f"{pf[f]:9d}" for f in fams))
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if __name__ == "__main__":
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main()
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