The three neighbouring applications out of the published branch: the NLMS step size (anc), the ODE step controllers (odestep) and the relaxation factor (relax), with the six stage scripts that drive them and the five tests that cover them. They are not part of the root-finding paper and no document refers to them. stage18_bulletproof.py keeps claim A and loses claim B; tests/test_bulletproof.py loses the one test that reached into anc. Server: verify 548 OK / 0 BAD, tests x2 1205 passed (was 1240 with the three).

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>

stage18_bulletproof.py

@@ -12,15 +12,6 @@ falsi goes from 133 solved and 18799 evaluations to 193 and 8056.
     TEST: the same rule, the same driver, the same everything, with the
     stale-endpoint correction swapped for each classical fix in turn and for
     the credit projection.  Only the repair differs.
-
-CLAIM B.  In active noise control the measured step size beats Kwong-Johnston
-by 7 dB.
-    OBJECTION: Kwong-Johnston's gains are scale-dependent, and yours are the
-    published defaults run on a signal they were not scaled for.  Give it its
-    best constants and the gap will close.
-    TEST: an oracle over its (alpha, gamma) grid, chosen separately for every
-    scenario - not an achievable controller, exactly as the ITP oracle in the
-    root-finding work was not.
 """
 from __future__ import annotations
 
@@ -32,8 +23,6 @@ import numpy as np
 from scipy.optimize._tstutils import (_APS_TESTS_DICTS,
                                       _CHANDRUPATLA_TESTS_DICTS)
 
-from anc.bench import SCENARIOS, make_primary_path, make_secondary_path, run_nlms
-from anc.rules import Fixed, KwongJohnston, Measured, Rule
 from simroot.baselines import Counter, _Budget
 from simroot.pure import _Safeguard
 
@@ -162,69 +151,5 @@ def claim_a():
     return rows
 
 
-# ==========================================================================
-# CLAIM B: the measured step size against a Kwong-Johnston oracle
-# ==========================================================================
-class KJTuned(KwongJohnston):
-    def __init__(self, a, g):
-        self.A, self.G = a, g
-        self.name = f"KJ a={a:g} g={g:g}"
-        self.constants = 4
-
-
-N, SEEDS, SNRS = 8000, 6, (30.0, 15.0)
-KJ_GRID = [(a, g) for a in (0.9, 0.97, 0.99)
-           for g in (2e-4, 2e-3, 2e-2, 2e-1)]
-
-
-def anc_score(rule, scen_gen, snr, seeds=SEEDS):
-    vals = []
-    for s in range(seeds):
-        rng = np.random.default_rng(1000 + s)
-        noise = scen_gen(N, rng)
-        nr = run_nlms(noise, make_primary_path(rng), make_secondary_path(rng),
-                      rule, snr_db=snr, seed=s)
-        if math.isfinite(nr):
-            vals.append(nr)
-    return (sum(vals) / len(vals)) if vals else float("nan")
-
-
-def claim_b():
-    print("\n" + "=" * 84)
-    print("CLAIM B - the measured step size against a Kwong-Johnston ORACLE")
-    print("=" * 84)
-    print(f"the oracle is given the best of {len(KJ_GRID)} (alpha, gamma) "
-          f"pairs for every scenario\nand noise level separately - not an "
-          f"achievable controller\n")
-    print(f"{'scenario':22s}{'SNR':>6s}{'KJ default':>12s}{'KJ oracle':>12s}"
-          f"{'measured':>11s}{'fixed 0.5':>11s}")
-    print("-" * 84)
-    tot = {"kj": 0.0, "orc": 0.0, "meas": 0.0, "fix": 0.0}
-    cells = 0
-    for sname, gen in SCENARIOS:
-        for snr in SNRS:
-            kj = anc_score(KwongJohnston(), gen, snr)
-            orc = max(anc_score(KJTuned(a, g), gen, snr) for a, g in KJ_GRID)
-            meas = anc_score(Measured(), gen, snr)
-            fix = anc_score(Fixed(0.5), gen, snr)
-            tot["kj"] += kj
-            tot["orc"] += orc
-            tot["meas"] += meas
-            tot["fix"] += fix
-            cells += 1
-            print(f"{sname:22s}{snr:>6.0f}{kj:>12.2f}{orc:>12.2f}"
-                  f"{meas:>11.2f}{fix:>11.2f}", flush=True)
-    print("-" * 84)
-    print(f"{'mean':22s}{'':6s}{tot['kj'] / cells:>12.2f}"
-          f"{tot['orc'] / cells:>12.2f}{tot['meas'] / cells:>11.2f}"
-          f"{tot['fix'] / cells:>11.2f}")
-    survives = tot["meas"] > tot["orc"]
-    print(f"\n   measured {tot['meas'] / cells:.2f} dB against the oracle "
-          f"{tot['orc'] / cells:.2f} dB   => "
-          f"{'SURVIVES' if survives else 'FAILS'} the objection")
-    return survives
-
-
 if __name__ == "__main__":
     claim_a()
-    claim_b()