247 lines
7.1 KiB
Python
247 lines
7.1 KiB
Python
import numpy as np
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#from IPython.display import display
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from matplotlib.pylab import show
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from .util import *
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from .data import *
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gen_filters = lambda cascade, srate: [
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s2z(*f[1], fc=f[0], srate=srate, gain=10**(f[2]/20)) for f in cascade
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]
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from .bq import *
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from .butterworth import *
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from .sweeps import *
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from .smoothfft import *
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from .plot import *
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from .wav import *
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from .planes import *
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from .fft import *
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from .bs import *
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def analog(b, a):
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import sympy as sym
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w,s = sym.symbols('w s')
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filt_expr = sym.Poly(b, s)/sym.Poly(a, s)
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mag_expr = abs(filt_expr.subs({s: w*sym.I}))**2
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return sym.lambdify(w, mag_expr, 'numpy')
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def makemag(w0, ba, gain=0):
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f = analog(*ba)
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def magf(w):
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a = f(w/w0)
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a[0] = 1e-35
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a = np.log10(a)*10 + gain
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a[0] = a[1] # safety measure
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return a
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return magf
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def test_filter_raw(ba, fc=1000, gain=0, precision=4096):
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fig, ax = new_response(ymin=-24, ymax=24)
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xs = xsp(precision)
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ax.semilogx(xs, makemag(fc, ba, gain)(xs))
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show(fig)
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def test_filter(ff, A=toA(12), Q=toQ(1), **kwargs):
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test_filter_raw(ff(A, Q), **kwargs)
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npc = [makemag(*f) for f in cascades['raw']]
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def neonpink(xs):
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lament("neonpink(): DEPRECATED.")
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combined = np.zeros(len(xs))
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for f in npc:
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combined += f(xs)
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return combined
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def c_render(cascade, precision=4096):
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xs = xsp(precision)
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ys = np.zeros_like(xs)
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c = [makemag(*f) for f in cascade]
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for f in c:
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ys += f(xs)
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return xs, ys
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def firize(xs, ys, n=4096, srate=44100, plot=None):
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import scipy.signal as sig
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if plot:
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plot.semilogx(xs, ys, label='desired')
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xf = xs/srate*2
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yg = 10**(ys/20)
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xf = np.hstack((0, xf, 1))
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yg = np.hstack((0, yg, yg[-1]))
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b = sig.firwin2(n, xf, yg, antisymmetric=True)
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if plot:
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_, ys = sig.freqz(b, worN=xs/srate*tau)
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ys = 20*np.log10(np.abs(ys))
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plot.semilogx(xs, ys, label='FIR ({} taps)'.format(n))
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plot.legend(loc=8)
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return b
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def normalize_test(s, srate):
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# FIXME: where is fir3 defined?
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#rms_naive = np.sqrt(np.mean(s**2))
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filters3 = gen_filters(cascades['raw3'], srate)
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db_standard = BS1770_3(s, srate)
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db = BS1770_3(s, srate, filters=filters3)
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print('raw3 would be\t{:+6.2f} dB louder/quieter than RG2'.format(db_standard - db))
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db = BS1770_3(s, srate, filters=[fir3])
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print('fir3 would be\t{:+6.2f} dB louder/quieter than RG2'.format(db_standard - db))
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rms = 10**(db/20)
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return s/rms, rms
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def tilter(xs, ys, tilt):
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"""tilts a magnitude plot by some decibels, or by equalizer curve."""
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# should really just do this instead:
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# ys -= tilt(xs, 3)
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print("tilter(): DEPRECATED")
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if tilt == 'neon':
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noise = neonpink(xs)
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elif type(tilt) is str:
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noise = np.zeros(len(xs))
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c = [makemag(*f) for f in cascades[tilt]]
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for f in c:
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noise += f(xs)
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elif isinstance(tilt, int) or isinstance(tilt, float):
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noise = tilt*(np.log2(1000) - np.log2(xs))
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else:
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noise = np.zeros(xs.shape)
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return xs, ys - noise
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def tilter2(xs, tilt):
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if type(tilt) is str:
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noise = np.zeros(len(xs))
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c = [makemag(*f) for f in cascades[tilt]]
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for f in c:
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noise += f(xs)
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elif isinstance(tilt, int) or isinstance(tilt, float):
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noise = tilt*(np.log2(1000) - np.log2(xs + 1e-35))
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else:
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noise = np.zeros(xs.shape)
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return noise
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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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# this is similar to default behaviour of having no __all__ variable at all,
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# but ours ignores modules as well. this allows for `import sys` and such
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# without clobbering `from our_module import *`.
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__all__ = [o for o in locals() if type(o) != 'module' and not o.startswith('_')]
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