Files
sim-numerics/diag_rescore_aps.py
vvsandClaude Opus 5 1b6c626f67 Valeri's decisions (1) competitors from the library, (2) variant a. (1) Chandrupatla is scipy.optimize.elementwise.find_root, Brent is brentq, no more per-problem best_of. Our Chandrupatla stopped on a bracket twice as wide as every other method (the factor the protocol corrects for ITP); fixed (+0.5*xtol) in baselines.py and in the two copies found by grep (stage16_blend, stage19_modern) and the traced mirror, and pinned: ours == library on every problem. Regenerating sweep_full.json changed exactly three rows - chandrupatla APS 2785->2787, CHA 2423->2441, brent CHA 4099->4115 - and nothing else (diff_sweeps.py: 0 unexpected).
(2) The proposed method is again the scheduled projection (2806/3220/6026), its budget multiplier DECLARED as the one free constant: the canonical total is the same for every multiplier 1.25-4, the wide-bracket one is not. The earned projection is the constant-free variant (3568/3020/6588). What the old tables hid: problem by problem the proposed rule beats Chandrupatla on the canonical set 87/24/42, exact sign test p = 9e-5, while trailing him by 0.7% in total; on the wide-bracket set he is genuinely stronger (26 to 9, p = 0.006). Gap decomposition recomputed with the library: 244 (was 262), 160 of it on the flat families (two thirds), fun1 58 (a quarter, not a third as the abstract said).

Also corrected on the way: the 'subsumed by Chandrupatla' pin claimed he is better on the worst single problem - true only with the looser tolerance (84 against the credit rule's 83 once fixed); §8.3 still called zero slack degenerate, which Table 1a refutes; §5.2's Brent figure is our pure-Python implementation and now says so. verify_article.py 286/286, 802 tests pass twice.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
2026-09-21 10:53:00 +01:00

108 lines
5.1 KiB
Python

"""Does the canonical Alefeld-Potra-Shi set carry the same scoring artefact as fun7?
On the wide-bracket set five problems are scored unsolved for every method although every
method returns a point where f(x) = 0 exactly (diag_rescore_cha.py). Every method also
reports 153 of 154 on the canonical set, so exactly one problem there is unsolved by
everyone — this asks whether that is the same artefact, a different one, or a real failure.
Both criteria are applied to the SAME runs:
strict : |x - declared_root| <= ACC (the harness rule)
honest : strict OR f(x) == 0 (a root is a root)
and every problem that the two criteria disagree about is printed with its diagnosis.
python -u diag_rescore_aps.py
"""
from __future__ import annotations
import math
from simroot.baselines import BRENT_BASELINE, CHANDRUPATLA_BASELINE
from simroot.baselines import (best_of, bisection, brent, brent_scipy, chandrupatla,
chandrupatla_scipy, itp, toms748)
from simroot.pure import pure_root
from sweep_full import ACC, MAXFEV, XTOL, load_problems
METHODS = {
"ours (shape)": lambda f, a, b: pure_root(f, a, b, XTOL, MAXFEV, similarity="ratio",
scale="derived3", guard="safe",
prestep="slope", points="shape"),
"ours (dissimilar)": lambda f, a, b: pure_root(f, a, b, XTOL, MAXFEV, similarity="ratio",
scale="derived3", guard="safe",
prestep="slope", direction="dissimilar"),
"ours (published proj)": lambda f, a, b: pure_root(f, a, b, XTOL, MAXFEV,
similarity="ratio", scale="derived3",
guard="project"),
"chandrupatla": lambda f, a, b: CHANDRUPATLA_BASELINE(f, a, b, XTOL,
MAXFEV),
"toms748": lambda f, a, b: toms748(f, a, b, XTOL, MAXFEV),
"brent": lambda f, a, b: BRENT_BASELINE(f, a, b, XTOL, MAXFEV),
"itp": lambda f, a, b: itp(f, a, b, XTOL, MAXFEV),
"bisection": lambda f, a, b: bisection(f, a, b, XTOL, MAXFEV),
}
TINY = 2.2250738585072014e-308 # smallest normal double, for reporting only
def main():
probs = [p for p in load_problems() if p[0] == "APS"]
print(f"APS problems: {len(probs)}")
print(f"\n{'method':<22} {'strict solved/total':>22} {'honest solved/total':>22} "
f"{'disagreements':>14}")
disagree = {}
never_strict = {pid: 0 for _s, pid, *_ in probs}
for name, run in METHODS.items():
s_solved = s_total = h_solved = h_total = 0
diffs = []
for _s, pid, f, a, b, root in probs:
try:
x, n, conv = run(f, a, b)
except Exception:
x, n, conv = float("nan"), MAXFEV, False
x = float(x)
n = int(n)
fin = conv and math.isfinite(x)
strict = bool(fin and abs(x - root) <= ACC)
honest = bool(strict or (fin and f(x) == 0.0))
s_total += n if strict else MAXFEV
h_total += n if honest else MAXFEV
s_solved += int(strict)
h_solved += int(honest)
never_strict[pid] += int(strict)
if honest != strict:
diffs.append((pid, x, root, f(x), n))
disagree[name] = diffs
print(f"{name:<22} {s_solved:8d}/154 {s_total:8d} {h_solved:8d}/154 {h_total:8d} "
f"{len(diffs):14d}")
print("\nproblems where the two criteria disagree (a root found, scored a failure):")
any_diff = False
for name, diffs in disagree.items():
for pid, x, root, fx, n in diffs:
any_diff = True
print(f" {name:<22} {pid:<12} x={x:+.10g} root={root:+.10g} "
f"f(x)={fx:+.3e} after {n} evals")
if not any_diff:
print(" none — the canonical set does NOT carry the fun7 artefact")
print("\nproblems no method solved under the strict rule:")
for pid, cnt in sorted(never_strict.items(), key=lambda kv: kv[1])[:6]:
print(f" {pid:<12} solved by {cnt} of {len(METHODS)} methods")
# inspect the hardest one in the same way fun7 was inspected
worst = min(never_strict, key=lambda k: never_strict[k])
for _s, pid, f, a, b, root in probs:
if pid != worst:
continue
print(f"\ndiagnosis of {pid}: bracket [{a:.6g}, {b:.6g}] declared root {root:.10g}")
print(f" f(a)={f(a):+.6e} f(b)={f(b):+.6e} f(root)={f(root):+.6e}")
for t in (1e-12, 1e-9, 1e-6, 1e-3):
print(f" f(root+{t:g}) = {f(root + t):+.6e} f(root-{t:g}) = {f(root - t):+.6e}")
x, n, conv = METHODS["ours (dissimilar)"](f, a, b)
print(f" ours returns x={float(x):+.12g} after {n} evals, f(x)={f(float(x)):+.3e}, "
f"|x-root|={abs(float(x) - root):.3g}")
print(f" |f(x)| below smallest normal? {abs(f(float(x))) < TINY}")
if __name__ == "__main__":
main()