47 lines
1.4 KiB
Python
47 lines
1.4 KiB
Python
import numpy as np
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from .util import pad2
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# fast cepstrum and inverted fast cepstrum
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fcs = lambda s: np.fft.ifft(np.log(np.fft.fft(s)))
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ifcs = lambda s: np.fft.fft(np.exp(np.fft.ifft(s)))
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# magnitude
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mcs = lambda s: (np.abs(np.fft.ifft(np.log(np.abs(np.fft.fft(s))**2)))**2)[:len(s)//2]
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def clipdb(s, cutoff=-100):
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as_ = np.abs(s)
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mas = np.max(as_)
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if mas == 0 or cutoff >= 0:
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return s
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thresh = mas*10**(cutoff/20)
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return np.where(as_ < thresh, thresh, s)
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def fold(r):
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# via https://ccrma.stanford.edu/~jos/fp/Matlab_listing_fold_m.html
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# Fold left wing of vector in "FFT buffer format" onto right wing
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# J.O. Smith, 1982-2002
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n = len(r)
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if n < 3:
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rw = r
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elif n % 2 == 1:
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nt = (n + 1)//2
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rf = r[1:nt] + conj(r[-1:nt-1:-1])
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rw = np.r_[r[0], rf, np.zeros(n-nt)]
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else:
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nt = n//2
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rf = np.r_[r[1:nt], 0] + np.conj(r[-1:nt-1:-1])
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rw = np.r_[r[0], rf, np.zeros(n-nt-1)]
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return rw
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def minphase(s, pad=True, os=False):
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# via https://ccrma.stanford.edu/~jos/fp/Matlab_listing_mps_m.html
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# TODO: actual oversampling
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if pad:
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s = pad2(s)
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if os:
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s = np.r_[s, np.zeros(len(s))]
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cepstrum = np.fft.ifft(np.log(clipdb(np.fft.fft(s), -100)))
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signal = np.real(np.fft.ifft(np.exp(np.fft.fft(fold(cepstrum)))))
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if os:
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signal = signal[:len(signal)//2]
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return signal
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