B.11: LUT-кривая уровень->маска извлечена (rmse 0.072 dB, 36 точек, 3 уровня): коллапс dual+t1kq+t1k на ОДНУ кривую x=log10(L0/res); степенной закон C~L0^p НЕ работает на 0dB (p_eff 0.19 vs 0.085) - LUT насыщающая gamma из FUN_180563440 (param_1+0x188); форма резонанса стабильна; model_lut.py канонический + roadmap B.11

2026-08-18 13:02:56 +03:00
parent 9abecb60d5
commit 32a63955f8
13 changed files with 1021 additions and 0 deletions
@@ -0,0 +1,91 @@
+#!/usr/bin/env python3
+"""verify_lut4.py — тонкая подгонка узлов LUT под все 36 точек."""
+import numpy as np
+from scipy.interpolate import PchipInterpolator
+from scipy.optimize import least_squares
+
+FS = 44100.0
+DEPTH = 0.8639736175537109
+QS = [0.1, 0.2, 0.3, 0.5, 0.7, 1.0, 1.5, 2.0, 3.0, 5.0, 10.0]
+DUAL = np.array([(10.220, 15.224), (10.219, 13.963), (10.219, 12.947),
+                 (10.219, 11.725), (10.218, 11.119), (10.216, 10.689),
+                 (10.210, 10.412), (10.203, 10.305), (10.182, 10.225),
+                 (10.113, 10.183), (9.822, 10.165)])
+FCS = [800.0, 900.0, 950.0, 1000.0, 1050.0, 1100.0, 1200.0]
+T1KQ = np.array([7.868, 8.536, 8.726, 8.788, 8.729, 8.575, 8.115])
+T1K = np.array([14.548, 15.332, 15.553, 15.626, 15.557, 15.378, 14.840])
+L_DUAL = 10 ** (-7.142 / 20)
+L_T1KQ = 10 ** (-18.063 / 20)
+L_T1K = 1.0
+TILT = {500: 1.414, 1000: 1.454, 2000: 1.795}
+Q, G = 0.900, 4.132
+
+LUTX = np.array([-0.75, -0.50, -0.25, 0.00, 0.25, 0.50, 0.574, 0.61, 0.75, 1.00])
+LUTY0 = np.array([0.4453, 0.4551, 0.4784, 0.5041, 0.5331, 0.5715, 0.5660, 0.6470, 0.6574, 0.6636])
+
+
+def res_at(ft, fc, Q, g):
+    w0 = fc * 2 * np.pi / FS
+    c, s = np.cos(w0), np.sin(w0)
+    p = (s * 0.5) / Q
+    a, a2 = p * g, p / g
+    A = [a + 1, -2 * c, 1 - a]
+    B = [a2 + 1, -2 * c, 1 - a2]
+    w = 2 * np.pi * ft / FS
+    z = np.exp(-1j * w)
+    return np.abs(2.0 * (B[0] + B[1] * z + B[2] * z * z) /
+                  (A[0] + A[1] * z + A[2] * z * z))
+
+
+def build_data():
+    xs, meas = [], []
+    for i, q in enumerate(QS):
+        for f, m in ((500, DUAL[i, 0]), (2000, DUAL[i, 1])):
+            xs.append(np.log10(L_DUAL / res_at(f, 500, q, G)))
+            meas.append(m)
+    for i, fc in enumerate(FCS):
+        r = res_at(1000, fc, 0.9999978, G)
+        xs.append(np.log10(L_T1KQ / r)); meas.append(T1KQ[i])
+        xs.append(np.log10(L_T1K / r)); meas.append(T1K[i])
+    return np.array(xs), np.array(meas)
+
+
+XS, MEAS = build_data()
+TILTS = np.array([1.414 if x < 0.35 else (1.795 if x < -0.05 else 1.454) for x in XS])
+# уточнение: tilt по тегу. пересоберём аккуратно
+def tags():
+    ts = []
+    for i, q in enumerate(QS):
+        for f in (500.0, 2000.0):
+            ts.append(TILT[f])
+    for _ in range(7):
+        ts.append(TILT[1000]); ts.append(TILT[1000])
+    return np.array(ts)
+TT = tags()
+
+
+def model(ly):
+    lut = PchipInterpolator(LUTX, ly)
+    out = []
+    for x, tilt in zip(XS, TT):
+        C = DEPTH * tilt * lut(x)
+        out.append(-20 * np.log10(max(1 - C, 1e-9)))
+    return np.array(out)
+
+
+def run():
+    r = least_squares(lambda ly: model(ly) - MEAS, LUTY0, max_nfev=30000, xtol=1e-13, ftol=1e-13)
+    ly = r.x
+    pred = model(ly)
+    rmse = np.sqrt(np.mean((pred - MEAS) ** 2))
+    print(f'LUT-knot fit rmse={rmse:.4f} dB')
+    for i, (x, m, p, t) in enumerate(zip(XS, MEAS, pred, TT)):
+        if abs(p - m) > 0.1:
+            print(f'  x={x:+.3f} tilt={t:.3f} {m:7.3f}/{p:7.3f} ({p - m:+.3f})')
+    print('knots:')
+    for xx, yy in zip(LUTX, ly):
+        print(f'  ({xx:+.3f}, {yy:.4f}),')
+
+
+if __name__ == '__main__':
+    run()