126 lines
3.6 KiB
Python
126 lines
3.6 KiB
Python
# this is a bunch of crap that should really be reduced to one or two functions
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from . import wav_read, normalize, averfft, tilter2, smoothfft2, firize
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from . import new_response, show, convolve_each, monoize, count_channels
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import numpy as np
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def plotwavsmooth(fn, ax, tilt=None, bw=1, size=8192, raw=False, fix=False, smoother=smoothfft2, **kwargs):
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s, srate = wav_read(fn)
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s, rms = normalize(s, srate)
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sm = monoize(s)
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ss = monoize(s*np.array((1, -1)))
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xs_raw = np.arange(0, srate/2, srate/2/size)
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ys_raw = averfft(sm, size=size)
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# tilting beforehand is negligible besides lowest frequencies, but eh
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if tilt is not None:
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ys_raw -= tilter2(xs_raw, tilt)
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xs, ys = smoother(xs_raw, ys_raw, bw=bw)
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if not 'label' in kwargs:
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kwargs['label'] = fn
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if raw:
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ax.semilogx(xs_raw, ys_raw, **kwargs)
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ax.semilogx(xs, ys, **kwargs)
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if not fix: return
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fno = fn[:-4]+"-proc.wav"
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fir = firize(xs, -ys, srate=srate)
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sf = convolve_each(s/8, fir, mode='same')
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import ewave
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with ewave.open(fno, 'w', sampling_rate=srate, nchannels=count_channels(sf)) as f:
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f.write(sf)
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print('wrote '+fno)
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def plotfftsmooth(s, srate, ax, bw=1, tilt=None, size=8192, window=0, raw=False, **kwargs):
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sm = monoize(s)
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xs_raw = np.arange(0, srate/2, srate/2/size)
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ys_raw = averfft(sm, size=size, mode=window)
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ys_raw -= tilter2(xs_raw, tilt)
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xs, ys = smoothfft(xs_raw, ys_raw, bw=bw)
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if raw: ax.semilogx(xs_raw, ys_raw, **kwargs)
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ax.semilogx(xs, ys, **kwargs)
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return xs, ys
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def plotwav2(fn, ax, bw=1, size=8192, raw=False, fix=False,
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smoother=smoothfft2, side_compensate=9, **kwargs):
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s, srate = wav_read(fn)
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s, rms = normalize(s, srate)
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sm = monoize(s)
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ss = monoize(s*np.array((1, -1)))
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xs_raw = np.arange(0, srate/2, srate/2/size)
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ys_raw = averfft(sm, size=size)
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ys_raw_side = averfft(ss, size=size)
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# tilting beforehand is negligible besides lowest frequencies, but eh
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ys_raw -= tilter2(xs_raw, 'np2')
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ys_raw_side -= tilter2(xs_raw, 'np2s')
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xs, ys = smoother(xs_raw, ys_raw, bw=bw)
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xs, ys_side = smoother(xs_raw, ys_raw_side, bw=bw)
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if not 'label' in kwargs:
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kwargs['label'] = fn
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if raw:
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ax.semilogx(xs_raw, ys_raw, **kwargs)
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ax.semilogx(xs_raw, ys_raw_side + side_compensate, **kwargs)
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ax.semilogx(xs, ys, **kwargs)
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ax.semilogx(xs, ys_side + side_compensate, **kwargs)
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side_gain = np.average(ys_raw_side) - np.average(ys_raw)
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print("side gain:", side_gain)
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if not fix: return
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fno = fn[:-4]+"-proc.wav"
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fir = firize(xs, -ys, srate=srate)
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smf = convolve_each(sm/8, fir, mode='same')
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fir = firize(xs, -ys_side, srate=srate)
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ssf = convolve_each(ss/8, fir, mode='same')
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ssf *= 10**(side_gain/20)
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sf = np.array((smf + ssf, smf - ssf)).T
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import ewave
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with ewave.open(fno, 'w', sampling_rate=srate, nchannels=count_channels(sf)) as f:
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f.write(sf)
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print('wrote '+fno)
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def pw(fn, ax, **kwargs):
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plotwavsmooth(fn, ax, tilt='np2', bw=1/6, **kwargs)
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def pwc(fn, **kwargs):
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fig, ax = new_response(-18, 18)
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ax.set_title('averaged magnitudes of normalized songs with tilt and smoothing')
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pw(fn, ax, fix=True, **kwargs)
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fno = fn[:-4]+"-proc.wav"
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pw(fno, ax, fix=False, **kwargs)
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ax.legend(loc=8)
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show(fig)
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def pw2(fn, **kwargs):
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fig, ax = new_response(-18, 18)
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ax.set_title('averaged magnitudes of normalized songs with tilt and smoothing')
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plotwav2(fn, ax, fix=True, bw=1/6, **kwargs)
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fno = fn[:-4]+"-proc.wav"
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plotwav2(fno, ax, fix=False, bw=1/6, **kwargs)
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ax.legend(loc=8)
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show(fig)
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