Matiq
25cf786c54
- Инфраструктура: RTTI-дампы (rtti_dsp/full.json), декомпиляции DSP-классов (decomp_*.txt), Ghidra-скрипты (Dump*.java, ImportRtti*.java, Diag.java), depthcurve/curve_fits LUT. - Поведенческая модель sim_v5.py + sim.py (RMSE ~0.3dB), утилиты (measure, tt_sweep, patchparam, sweep, harness_*, verify_sim). - summary.md + roadmap.md (контракт из manual M1-M12, топология пайплайна из OCR, фазы A-C). - pipeline_ocr.txt: OCR диаграммы Appendix A (mid/side ручка, trim/mix/bypass порядок).
73 lines
2.4 KiB
Python
73 lines
2.4 KiB
Python
#!/usr/bin/env python3
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import sys, os, struct
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import numpy as np
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SR = 44100
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def read_wav(path):
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d = open(path, 'rb').read()
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i = 12
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ch = bps = None
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data_off = data_sz = None
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while i + 8 <= len(d):
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cid = d[i:i+4]; sz = struct.unpack('<I', d[i+4:i+8])[0]
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if cid == b'fmt ':
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ch = struct.unpack('<H', d[i+8:i+10])[0]
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bps = struct.unpack('<H', d[i+16:i+18])[0]
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if cid == b'data':
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data_off = i + 8; data_sz = sz
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i += 8 + sz + (sz & 1)
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raw = d[data_off:data_off+data_sz]
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if bps == 32:
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a = np.frombuffer(raw, dtype='<f4')
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e = (1, 2)[ch-1:]
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return a.reshape(-1, ch)[:, 0], ch
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if bps == 24:
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b = np.frombuffer(raw, dtype=np.uint8).reshape(-1, ch*3)
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v = b[:, 0] | (b[:,1].astype(np.int32) << 8) | (b[:,2].astype(np.int32) << 16)
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v = (v ^ (1 << 23)) - (1 << 23)
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return v / 8388608.0, ch
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a = np.frombuffer(raw, dtype='<i2')
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return a.reshape(-1, ch)[:, 0] / 32768.0, ch
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def db_spec_mono(x, nfft=16384, hop=2048, sr=SR):
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# averaged magnitude spectrum in dB
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w = np.hanning(nfft)
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frames = [x[t:t+nfft] for t in range(0, len(x)-nfft, hop)]
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if not frames: return None
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X = np.stack([np.fft.rfft(f*w) for f in frames])
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return 20*np.log10(np.abs(X).mean(0) + 1e-12), np.fft.rfftfreq(nfft, 1/sr)
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def main():
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inp = sys.argv[1]
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outs = sys.argv[2:]
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x, ch = read_wav(inp)
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bin, fr = db_spec_mono(x)
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NFFT = 16384
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# collect peaks (sines) of test tone from input
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masks = {}
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peakset = set()
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for f in range(1, len(fr)):
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if bin[f] > -120 and bin[f] == np.max(bin[max(0,f-8):f+9]):
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peakset.add(f)
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print("peaks in input (Hz):", sorted(round(fr[f]) for f in peakset if fr[f] < 18000))
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colw = 22
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hdr = f"{'Hz':>6} {'IN dB':>7}" + ''.join(f" {os.path.basename(p)[:colw]:>{colw}}" for p in outs)
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print(hdr)
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for f in sorted(peakset):
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if fr[f] < 18000:
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row = f"{fr[f]:6.0f} {bin[f]:7.1f}"
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refbase = None
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for p in outs:
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y, _ = read_wav(p)
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b, f2 = db_spec_mono(y)
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# nearest bin to fr[f]
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idx = int(round(fr[f]*(len(f2)-1)/f2[-1]))
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idx = int(np.argmin(np.abs(f2 - fr[f])))
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if p == outs[0]:
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refbase = b[idx]
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row += f" {b[idx]:{colw}.2f}"
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print(row)
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if __name__ == '__main__':
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main() |