vvsandClaude Opus 5
862feaff86
Point 1. The base step's order is Muller's 1.839, not 2: the derivative of the parabola through
the last three points errs by f'''/6 (x_n - x_{n-1})(x_n - x_{n-2}) = O(e_{n-1} e_{n-2}).
order_high_precision.py (3000 digits, to 1e-2900): 1.840 on cos x - x, e^x - 2, x^3 - x - 2,
sin x - 1/2; 2.000 only on x^2 - 2; two-point 1.618. The double-precision medians (2.000, 1.94)
are removed from the text.
Point 3. Every protocol number is re-scored under the criterion of section 9 - a sign change
within 1e-6 or f(x) == 0. rescore_uniform.py re-runs all 2779 distinct configurations of the 25
protocol sweeps on APS and CHA (the runs did not keep x) -> sweep_uniform.json, same row format;
it reproduces the APS/CHA lines of Table 10 exactly (built-in check). verify_article.py,
audit_similarity_places.py and the gap diagnostics read the re-scored data; the multiplier and
endowment measurements score by the same criterion. Table 7 (two criteria side by side) is gone;
7.3 now explains why the criterion is a sign change. Consequences stated in the text: the base
rule 2634 / 2357 against Chandrupatla 2595 / 1505 (1.5% behind on APS, no longer "level"); A'
2259 / 1074 (12.9% and 28.6% below Chandrupatla); the defect reading 2351 is second to the
shape reading 2337, not the record; the remembered analogy is level with no regime (2633 vs
2634) under this criterion; Table 9a's range is 19% to 425%.
Point 8. report_sweep.head_to_head counts every problem, failures charged (it counted only the
problems both methods solved, which is why Table 8 rows summed to 153 and 40). Family-level
comparisons added (A' vs Chandrupatla 8/1/6 of 15 and 7/0/2 of 9 families, not significant), and
an independence paragraph in section 9.
Point 11. sweep_itp.py: ITP (recommended constants and per-problem oracle) on all six corpora ->
Table 10; behind A' on every corpus, 0 bound violations.
Points 7, 9, 10 and the internals: the 2x bound is ours, not the rivals' promise; the law
predicts the group order only; "outside the proven bracket" explained (narrowest bracket of all
observed signs); 7.4's fun1 paragraph corrected (five costs under safe; the unguarded numbers
belong to fun1.4, fun1.5 and to fun3.1, fun5.1 separately); Table 1's last cell; the corpus-4
composition and odd multiplicities stated, also in the abstract.
build_tex.py: pdflatex output decoded with errors="replace" (a UTF-8 character cut by TeX's log
wrap crashed the build). Table 10 column widths rebalanced.
Checks: verify_article on the server 500 OK / 0 BAD (467 existing with the new values, 33 new);
regression x2 on the server 1232 passed, 0 failed; PDF 28 pages, 0 errors, 0 undefined, 0 overfull.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
49 lines
2.2 KiB
Python
49 lines
2.2 KiB
Python
"""Revision point 3: the diagnosis scripts that verify_article.py runs score a run by the
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paper's single criterion (a sign change within 1e-6 or f(x) == 0), and the audit of the
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similarity places reads the re-scored sweeps. Exact anchors, counted, or nothing is written.
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python -u apply_diag_uniform.py
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"""
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from __future__ import annotations
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EDITS = {
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"diag_model_order.py": [
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(" if c and math.isfinite(float(x)) and abs(float(x) - r) <= ACC:",
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" if c and solved(f, float(x)):", 1),
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(" if not (conv and abs(float(x) - r) <= ACC):",
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" if not (conv and solved(f, float(x))):", 1),
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("XTOL, MAXFEV, ACC = 1e-12, 200, 1e-6",
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"XTOL, MAXFEV, ACC = 1e-12, 200, 1e-6\n"
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"# success = the paper's single criterion since 2026-09-22 (revision point 3)\n"
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"from corpus_roots_jl import solved # noqa: E402", 1),
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],
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"diag_model_order_checks.py": [
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(" if not (conv and abs(float(x) - r) <= ACC):",
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" if not (conv and solved(f, float(x))):", 1),
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("from diag_model_order import ACC, MAXFEV, OURS, XTOL, ch_cost, iqi",
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"from diag_model_order import ACC, MAXFEV, OURS, XTOL, ch_cost, iqi, solved", 1),
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],
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"diag_flat_detectable.py": [
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(" if not (conv and abs(float(x) - r) <= ACC):",
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" if not (conv and solved(f, float(x))):", 1),
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("from diag_model_order import ACC, MAXFEV, OURS, XTOL",
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"from diag_model_order import ACC, MAXFEV, OURS, XTOL, solved", 1),
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],
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"audit_similarity_places.py": [
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("def load(path):\n with open(path, encoding=\"utf8\") as fh:\n return json.load(fh)\n",
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"def load(path):\n \"\"\"The sweep re-scored under the paper's single criterion (sweep_uniform.json).\"\"\"\n"
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" from rescore_uniform import load_uniform\n return load_uniform(path)\n", 1),
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],
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}
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new = {}
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for path, edits in EDITS.items():
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src = open(path, encoding="utf8").read()
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for old, rep, count in edits:
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assert src.count(old) == count, (path, old[:60], src.count(old))
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src = src.replace(old, rep)
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new[path] = src
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for path, src in new.items():
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open(path, "w", encoding="utf8").write(src)
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print("edited", ", ".join(new))
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