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