Matiq
b4d75f4d22
- Implemented exact ln/exp2 infrastructure (log2_ln.hpp/cpp) - Parameterized VLAW α/β/c by (fc, q, sens) configuration - Implemented real RFFT for FIR construction - Fixed VLAW parameterization for dual group (3.455 → 0.764 dB) - Added detector cascade 529c60 (Haar smoothing, magnitude, peak processing) - TOTAL error: 0.870 dB (vs bridge baseline 1.594 dB) Results: - t1kq: 0.618 dB (bridge: 0.226 dB) - t1k: 0.938 dB (bridge: 1.801 dB) ✓ better - al: 0.727 dB (bridge: 0.638 dB) - res: 0.284 dB (bridge: 0.628 dB) ✓ better - dual: 0.764 dB (bridge: 0.726 dB) - comb: 3.000 dB (bridge: 10.149 dB) ✓ better
113 lines
3.5 KiB
Python
113 lines
3.5 KiB
Python
#!/usr/bin/env python3
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"""
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Quick VLAW parameter grid search - test fewer combos per case.
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"""
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import numpy as np
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import os
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import sys
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import subprocess
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import json
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sys.path.insert(0, '/home/m/re-tools/scripts')
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import corpus
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corpus.RB = '/home/m/re-tools/dsp/build/render48k'
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with open('scripts/baseline_bridge.json') as f:
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REF_ERRORS = json.load(f)
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def structural_cases():
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out = []
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for name, inp, args, ref, f in corpus.build_cases():
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joined = [','.join(args)] if len(args) == 3 else args
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out.append((name, inp, joined, ref, f))
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return out
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def run_vlaw(inp, args, alpha, beta, c, delta):
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out = f'/tmp/vlaw_{alpha}_{beta}_{c}_{delta}_{os.path.basename(inp)}.wav'
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env = {
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**os.environ,
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'RT_VLAW': '1',
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'RT_VLAW_ALPHA': str(alpha),
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'RT_VLAW_BETA': str(beta),
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'RT_VLAW_C': str(c),
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'RT_VLAW_DELTA': str(delta),
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'RT_SYN': '1', 'RT_NOWARP': '1', 'RT_NOIIR3': '1', 'RT_IIR12': '0',
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}
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subprocess.run([corpus.RB, inp, out] + args, capture_output=True, env=env, cwd='/home/m/re-tools')
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return out
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def eval_error(out, ref, f):
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if not os.path.exists(out) or os.path.getsize(out) == 0:
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return None
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ref_sig = corpus.load_mono(ref)
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out_sig = corpus.load_mono(out)
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min_len = min(len(ref_sig), len(out_sig))
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ref_sig = ref_sig[-min_len:]
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out_sig = out_sig[-min_len:]
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ref_ta = corpus.ta(ref_sig, f)
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out_ta = corpus.ta(out_sig, f)
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return corpus.db(out_ta / ref_ta)
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def group_key(name):
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return name.split('_')[0]
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all_cases = structural_cases()
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groups = {}
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for name, inp, args, ref, f in all_cases:
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g = group_key(name)
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groups.setdefault(g, []).append((name, inp, args, ref, f))
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# Pick one case per group
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rep_cases = {}
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for g in ['t1kq', 't1k', 'al', 'res', 'dual']:
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if g in groups:
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# Pick middle-ish case
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cases = groups[g]
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rep_cases[g] = cases[len(cases)//2]
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print("Representative cases:")
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for g, (name, inp, args, ref, f) in rep_cases.items():
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print(f" {g}: {name}")
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# Test a small grid around dual params
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dual_params = (3.2193, 0.4927, 0.5423, 6.9177)
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print("\n=== Grid search per group ===")
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results = {}
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for g, (name, inp, args, ref, f) in rep_cases.items():
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print(f"\n--- {g} ({name}) ---")
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best = None
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best_err = float('inf')
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# Coarse grid
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alphas = np.linspace(1.0, 5.0, 5)
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betas = np.linspace(0.2, 0.8, 5)
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cs = np.linspace(-0.5, 2.0, 5)
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deltas = np.linspace(0.0, 12.0, 5)
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for alpha in alphas:
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for beta in betas:
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for c in cs:
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for delta in deltas:
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out = run_vlaw(inp, args, alpha, beta, c, delta)
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err = eval_error(out, ref, f)
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if err is not None and abs(err) < best_err:
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best_err = abs(err)
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best = (alpha, beta, c, delta, err)
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print(f' {name}: α={alpha:.3f}, β={beta:.3f}, c={c:.3f}, Δ={delta:.3f} => {err:.3f} dB')
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if best:
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results[g] = best[:4]
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print(f' BEST {g}: α={best[0]:.4f}, β={best[1]:.4f}, c={best[2]:.4f}, Δ={best[3]:.4f} => {best[4]:.3f} dB')
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print("\n=== SUMMARY ===")
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for g, (a, b, c, d) in results.items():
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print(f'{g}: α={a:.4f}, β={b:.4f}, c={c:.4f}, Δ={d:.4f}')
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with open('/tmp/opencode/vlaw_params.json', 'w') as f:
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json.dump({g: {'alpha': a, 'beta': b, 'c': c, 'delta': d}
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for g, (a, b, c, d) in results.items()}, f, indent=2)
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print('\nSaved to /tmp/opencode/vlaw_params.json') |