def _istftm(self, X_hat=None, Phi_hat=None, pvoc=False, usewin=True, resamp=None):
"""
::
Inverse short-time Fourier transform magnitude. Make a signal from a |STFT| transform.
Uses phases from self.STFT if Phi_hat is None.
Inputs:
X_hat - N/2+1 magnitude STFT [None=abs(self.STFT)]
Phi_hat - N/2+1 phase STFT [None=exp(1j*angle(self.STFT))]
pvoc - whether to use phase vocoder [False]
usewin - whether to use overlap-add [False]
Returns:
x_hat - estimated signal
"""
if not self._have_stft:
return None
X_hat = P.np.abs(self.STFT) if X_hat is None else P.np.abs(X_hat)
if pvoc:
self._pvoc(X_hat, Phi_hat, pvoc)
else:
Phi_hat = P.angle(self.STFT) if Phi_hat is None else Phi_hat
self.X_hat = X_hat * P.exp( 1j * Phi_hat )
if usewin:
self.win = P.hanning(self.nfft)
self.win *= 1.0 / ((float(self.nfft)*(self.win**2).sum())/self.nhop)
else:
self.win = P.ones(self.nfft)
if resamp:
self.win = sig.resample(self.win, int(P.np.round(self.nfft * resamp)))
fp = self._check_feature_params()
self.x_hat = self._overlap_add(P.real(self.nfft * P.irfft(self.X_hat.T)), usewin=usewin, resamp=resamp)
if self.verbosity:
print "Extracted iSTFTM->self.x_hat"
return self.x_hat
def spec_env(frame, coefs):
mags = abs(frame)
N = len(mags)
ceps = pl.rfft(pl.log(mags[:N - 1]))
ceps[coefs:] = 0
mags[:N - 1] = pl.exp(pl.irfft(ceps))
return mags
def _istftm(self,
X_hat=None,
Phi_hat=None,
pvoc=False,
usewin=True,
resamp=None):
"""
::
Inverse short-time Fourier transform magnitude. Make a signal from a |STFT| transform.
Uses phases from self.STFT if Phi_hat is None.
Inputs:
X_hat - N/2+1 magnitude STFT [None=abs(self.STFT)]
Phi_hat - N/2+1 phase STFT [None=exp(1j*angle(self.STFT))]
pvoc - whether to use phase vocoder [False]
usewin - whether to use overlap-add [False]
Returns:
x_hat - estimated signal
"""
if not self._have_stft:
return None
X_hat = self.X if X_hat is None else P.np.abs(X_hat)
if pvoc:
self._pvoc(X_hat, Phi_hat, pvoc)
else:
Phi_hat = P.angle(self.STFT) if Phi_hat is None else Phi_hat
self.X_hat = X_hat * P.exp(1j * Phi_hat)
if usewin:
if self.win is None:
self.win = P.ones(
self.wfft) if self.window == 'rect' else P.np.sqrt(
P.hanning(self.wfft))
if len(self.win) != self.nfft:
self.win = P.r_[self.win, P.np.zeros(self.nfft - self.wfft)]
if len(self.win) != self.nfft:
error.BregmanError(
"features_base.Features._istftm(): assertion failed len(self.win)==self.nfft"
)
else:
self.win = P.ones(self.nfft)
if resamp:
self.win = sig.resample(self.win,
int(P.np.round(self.nfft * resamp)))
fp = self._check_feature_params()
self.x_hat = self._overlap_add(P.real(P.irfft(self.X_hat.T)),
usewin=usewin,
resamp=resamp)
if self.verbosity:
print("Extracted iSTFTM->self.x_hat")
return self.x_hat
def _icqft(self, V_hat):
"""
::
Inverse constant-Q Fourier transform. Make a signal from a constant-Q transform.
"""
if not self._have_cqft:
return False
fp = self._check_feature_params()
X_hat = pylab.array( pylab.dot(self.Q.T, V_hat) ) * pylab.exp( 1j * pylab.angle(self.STFT) )
self.x_hat = self._overlap_add( pylab.real(fp['nfft'] * pylab.irfft(X_hat.T)) )
if fp['verbosity']:
print "Extracted iCQFT->x_hat"
return True
def true_spec_env(frame, coefs, thresh):
N = len(frame)
form = pl.zeros(N)
lmags = pl.log(abs(frame[:N - 1]))
mags = lmags
go = True
while (go):
ceps = pl.rfft(lmags)
ceps[coefs:] = 0
form[:N - 1] = pl.irfft(ceps)
go = False
for i in range(0, N - 1):
if lmags[i] < form[i]: lmags[i] = form[i]
diff = mags[i] - form[i]
if diff > thresh: go = True
return pl.exp(form)
def true_spec_env(amps,coefs,thresh):
N = len(amps)
sm = 10e-15
form = pl.zeros(N)
lmags = pl.log(amps[:N-1]+sm)
mags = lmags
check = True
while(check):
ceps = pl.rfft(lmags)
ceps[coefs:] = 0
form[:N-1] = pl.irfft(ceps)
for i in range(0,N-1):
if lmags[i] < form[i]: lmags[i] = form[i]
diff = mags[i] - form[i]
if diff > thresh: check = True
else: check = False
return pl.exp(form)+sm
def _istftm(self, X_hat, Phi_hat=None):
"""
::
Inverse short-time Fourier transform magnitude. Make a signal from a |STFT| transform.
Uses phases from self.STFT if Phi_hat is None.
"""
if not self._have_stft:
return False
if Phi_hat is None:
Phi_hat = pylab.exp( 1j * pylab.angle(self.STFT))
fp = self._check_feature_params()
X_hat = X_hat * Phi_hat
self.x_hat = self._overlap_add( pylab.real(fp['nfft'] * pylab.irfft(X_hat.T)) )
if fp['verbosity']:
print "Extracted iSTFTM->self.x_hat"
return True
def _istftm(self, X_hat=None, Phi_hat=None, pvoc=False, usewin=True, resamp=None):
"""
::
Inverse short-time Fourier transform magnitude. Make a signal from a |STFT| transform.
Uses phases from self.STFT if Phi_hat is None.
Inputs:
X_hat - N/2+1 magnitude STFT [None=abs(self.STFT)]
Phi_hat - N/2+1 phase STFT [None=exp(1j*angle(self.STFT))]
pvoc - whether to use phase vocoder [False]
usewin - whether to use overlap-add [False]
Returns:
x_hat - estimated signal
"""
if not self._have_stft:
return None
X_hat = self.X if X_hat is None else P.np.abs(X_hat)
if pvoc:
self._pvoc(X_hat, Phi_hat, pvoc)
else:
Phi_hat = P.angle(self.STFT) if Phi_hat is None else Phi_hat
self.X_hat = X_hat * P.exp(1j * Phi_hat)
if usewin:
if self.win is None:
self.win = P.ones(self.wfft) if self.window == 'rect' else P.np.sqrt(
P.hanning(self.wfft))
if len(self.win) != self.nfft:
self.win = P.r_[self.win, P.np.zeros(self.nfft - self.wfft)]
if len(self.win) != self.nfft:
error.BregmanError(
"features_base.Features._istftm(): assertion failed len(self.win)==self.nfft")
else:
self.win = P.ones(self.nfft)
if resamp:
self.win = sig.resample(
self.win, int(P.np.round(self.nfft * resamp)))
fp = self._check_feature_params()
self.x_hat = self._overlap_add(
P.real(P.irfft(self.X_hat.T)), usewin=usewin, resamp=resamp)
if self.verbosity:
print("Extracted iSTFTM->self.x_hat")
return self.x_hat
def pconv(input, ir, S=1024):
N = len(ir)
L = len(input)
M = S * 2
P = int(pl.ceil(N / S))
H = pl.zeros((P, M // 2 + 1)) + 0j
X = pl.zeros((P, M // 2 + 1)) + 0j
x = pl.zeros(M)
o = pl.zeros(M)
s = pl.zeros(S)
for i in range(0, P):
p = (P - 1 - i) * S
ll = len(ir[p:p + S])
x[:ll] = ir[p:p + S]
H[i] = pl.rfft(x)
y = pl.zeros(L + N - 1)
n = S
i = 0
for p in range(0, L + N - S, S):
if p > L:
x = pl.zeros(M)
else:
if n + p > L:
n = L - p
x[n:] = pl.zeros(M - n)
x[:n] = input[p:p + n]
X[i] = pl.rfft(x)
i = (i + 1) % P
O = pl.zeros(M // 2 + 1) + 0j
for j in range(0, P):
k = (j + i) % P
O += H[j] * X[k]
o = pl.irfft(O)
y[p:p + S] = o[:S] + s
s = o[S:]
return y
def conv(input, ir):
N = len(ir)
L = len(input)
M = 2
while (M <= 2 * N - 1):
M *= 2
h = pl.zeros(M)
x = pl.zeros(M)
y = pl.zeros(L + N - 1)
h[0:N] = ir
H = pl.rfft(h)
n = N
for p in range(0, L, N):
if p + n > L:
n = L - p
x[n:] = pl.zeros(M - n)
x[0:n] = input[p:p + n]
y[p:p + 2 * n - 1] += pl.irfft(H * pl.rfft(x))[0:2 * n - 1]
return y
def istft(X, w, n):
N = len(w)
k = pl.arange(0, N / 2 + 1)
xn = pl.irfft(X * pl.exp(-2 * pl.pi * 1j * k * n / N))
return xn * w
# Return the Discrete Fourier Transform sample frequencies
logging.debug('compute the Fourier Transform sample frequencies')
freq = fftfreq(len(data), d=1.0/samprate)[range(0,npts/2+1)]
# the last element is negative, because of the symmetry, but should
# be positive
fft_values[-1] *= -1
convolved = []
for f in freq:
w = f * 2 * pi
convolved.append( response._eval_response(respaddr, w ) )
data = irfft( convolved * fft_values )
logging.debug( 'Total samples: %s ' % len(data) )
rec.trputdata( data )
response._free_response ( respaddr )
return tr
def decimate_trace( tr, newsps ):
"""
Function to correctly apply some decimation filters
"""
logging.debug('Now try to decimate the data')
pl.figure(figsize=(8, 5))
pl.subplot(211)
pl.title('waveform')
end = N
t = pl.arange(0, end) / float(sr)
pl.xlim(0, t[end - 1])
pl.ylim(-1.1, 1.1)
pl.xlabel("time (s)")
pl.plot(t, sig[0:end], 'k')
pl.subplot(212)
pl.title('spectral envelope')
x = pl.arange(0, N / 2)
bins = x * sr / N
spec = pl.fft(sig / max(sig))
mags = abs(spec / N)
logm = pl.log(mags)
ceps = pl.rfft(logm)
ceps2 = pl.zeros(len(ceps))
ceps2[0:50] = ceps[0:50]
specenv = pl.exp(pl.irfft(ceps2))
spec1 = 20 * pl.log10(mags / max(mags))
pl.ylim(-40, 1)
pl.ylabel("amp (dB)")
pl.xlabel("freq (Hz)")
pl.xlim(0, 2000)
pl.tight_layout()
pl.plot(bins[0:N / 2], spec1[0:N / 2], 'k-', linewidth=2)
pl.show()
def istft(X, w):
xn = pl.irfft(X)
return xn * w
import pylab as pl pi = pl.pi T = 1000 t = pl.arange(0, T) x = 0.51 - 0.49 * pl.cos(2 * pi * t / T) y = pl.sin(2 * pi * 10 * t / T) X = pl.rfft(y * x) pl.plot(pl.irfft(X)) pl.show()
