84 lines
2.5 KiB
Python
84 lines
2.5 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, magnitude_x, convolve_each, monoize, count_channels
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import numpy as np
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def plotfftsmooth(s, srate, ax=None, bw=1, tilt=None, size=8192, window=0, raw=False, **kwargs):
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sm = monoize(s)
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xs_raw = magnitude_x(srate, 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 ax:
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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 plotwavinternal(sm, ss, srate, bw=1, size=8192, smoother=smoothfft2):
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xs_raw = magnitude_x(srate, size)
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ys_raw_m = averfft(sm, size=size)
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ys_raw_s = averfft(ss, size=size)
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# tilting beforehand is negligible besides lowest frequencies, but eh
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ys_raw_m -= tilter2(xs_raw, 'np2')
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ys_raw_s -= tilter2(xs_raw, 'np2s')
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if bw <= 0:
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return xs_raw, xs_raw_m, xs_raw_s
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xs, ys_m = smoother(xs_raw, ys_raw_m, bw=bw)
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xs, ys_s = smoother(xs_raw, ys_raw_s, bw=bw)
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return xs, ys_m, ys_s
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def plotwav2(fn, bw=1, size=8192, fix=False,
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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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if s.shape[1] == 2:
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ss = monoize(s*np.array((1, -1)))
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else:
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ss = np.zeros(len(s))
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xs, ys_m, ys_s = plotwavinternal(sm, ss, srate, bw, size, smoother)
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side_gain = np.average(ys_s) - np.average(ys_m)
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if fix:
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fno = fn[:-4]+"-proc.wav"
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fir_m = firize(xs, -ys_m, srate=srate)
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fir_s = firize(xs, -ys_s, srate=srate)
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smf = convolve_each(sm/8, fir_m, mode='same')
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ssf = convolve_each(ss/8, fir_s, 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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return xs, ys_m, ys_s
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def pw2(fn, label=None, bw=1/6, **kwargs):
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fno = fn[:-4]+"-proc.wav"
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xs, ys_m, ys_s = plotwav2(fn, fix=True, bw=bw, **kwargs)
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xs, ys_m, ys_s = plotwav2(fno, fix=False, bw=bw, **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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label = label or fn
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ax.semilogx(xs, ys_m + 0, label=label+' (mid)')
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ax.semilogx(xs, ys_s + 9, label=label+' (side)')
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ax.legend(loc=8)
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