54 lines
1.5 KiB
Python
54 lines
1.5 KiB
Python
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import sys
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import numpy as np
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import scipy.signal as sig
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dummy = lambda *args, **kwargs: None
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lament = lambda *args, **kwargs: print(*args, file=sys.stderr, **kwargs)
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toLK = lambda x: -0.691 + 10*np.log10(x)
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isqrt2 = 1/np.sqrt(2)
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toQ = lambda bw: isqrt2/bw
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toA = lambda db: 10**(db/40)
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tau = 2*np.pi
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unwarp = lambda w: np.tan(w/2)
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warp = lambda w: np.arctan(w)*2
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rfft = lambda src, size: np.fft.rfft(src, size*2)
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magnitude = lambda src, size: 10*np.log10(np.abs(rfft(src, size))**2)[0:size]
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def xsp(precision=4096):
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"""create #precision log-spaced points from 20 to 20480 Hz"""
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# i opt not to use steps or linspace here,
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# as the current method is less error-prone for me.
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xs = np.arange(0,precision)/precision
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return 20*1024**xs
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def blocks(a, step, size=None):
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"""break an iterable into chunks"""
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if size is None:
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size = step
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for start in range(0, len(a), step):
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end = start + size
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if end > len(a):
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break
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yield a[start:end]
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def convolve_each(s, fir, mode=None, axis=0):
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return np.apply_along_axis(lambda s: sig.fftconvolve(s, fir, mode), axis, s)
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def count_channels(s):
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if len(s.shape) < 2:
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return 1
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return s.shape[1]
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def monoize(s):
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"""mixes an n-channel signal down to one channel.
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technically, it averages a 2D array to be 1D.
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existing mono signals are passed through unmodified."""
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channels = count_channels(s)
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if channels != 1:
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s = np.sum(s, 1)
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s /= channels
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return s
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