def nsgtf_sl(f_slices,g,wins,nn,M=None,real=False,reducedform=0,measurefft=False):
M = chkM(M,g)
fft = fftp(measure=measurefft)
ifft = ifftp(measure=measurefft)
if real:
assert 0 <= reducedform <= 2
sl = slice(reducedform,len(g)//2+1-reducedform)
else:
sl = slice(0,None)
maxLg = max(int(ceil(float(len(gii))/mii))*mii for mii,gii in izip(M[sl],g[sl]))
temp0 = None
loopparams = []
for mii,gii,win_range in izip(M[sl],g[sl],wins[sl]):
Lg = len(gii)
col = int(ceil(float(Lg)/mii))
assert col*mii >= Lg
gi1 = gii[:(Lg+1)//2]
gi2 = gii[-(Lg//2):]
p = (mii,gii,gi1,gi2,win_range,Lg,col)
loopparams.append(p)
if True or T is None:
def loop(temp0):
c = [] # Initialization of the result
# The actual transform
# TODO: stuff loop into theano
for mii,gii,gi1,gi2,win_range,Lg,col in loopparams:
# Lg = len(gii)
# if the number of time channels is too small (mii < Lg), aliasing is introduced
# wrap around and sum up in the end (below)
# col = int(ceil(float(Lg)/mii)) # normally col == 1
# assert col*mii >= Lg
temp = temp0[:col*mii]
# original version
# t = ft[win_range]*N.fft.fftshift(N.conj(gii))
# temp[:(Lg+1)//2] = t[Lg//2:] # if mii is odd, this is of length mii-mii//2
# temp[-(Lg//2):] = t[:Lg//2] # if mii is odd, this is of length mii//2
# modified version to avoid superfluous memory allocation
t1 = temp[:(Lg+1)//2]
t1[:] = gi1 # if mii is odd, this is of length mii-mii//2
t2 = temp[-(Lg//2):]
t2[:] = gi2 # if mii is odd, this is of length mii//2
ftw = ft[win_range]
t2 *= ftw[:Lg//2]
t1 *= ftw[Lg//2:]
# (wh1a,wh1b),(wh2a,wh2b) = win_range
# t2[:wh1a.stop-wh1a.start] *= ft[wh1a]
# t2[wh1a.stop-wh1a.start:] *= ft[wh1b]
# t1[:wh2a.stop-wh2a.start] *= ft[wh2a]
# t1[wh2a.stop-wh2a.start:] *= ft[wh2b]
temp[(Lg+1)//2:-(Lg//2)] = 0 # clear gap (if any)
if col > 1:
temp = N.sum(temp.reshape((mii,-1)),axis=1)
else:
temp = temp.copy()
c.append(temp)
return c
else:
raise RuntimeError("Theano support not implemented yet")
for f in f_slices:
Ls = len(f)
# some preparation
ft = fft(f)
if temp0 is None:
# pre-allocate buffer (delayed because of dtype)
temp0 = N.empty(maxLg,dtype=ft.dtype)
# A small amount of zero-padding might be needed (e.g. for scale frames)
if nn > Ls:
ft = N.concatenate((ft,N.zeros(nn-Ls,dtype=ft.dtype)))
# The actual transform
c = loop(temp0)
yield map(ifft,c) # TODO: if matrixform, perform "2D" FFT along one axis
def nsgtf_sl(f_slices,
g,
wins,
nn,
M=None,
real=False,
reducedform=0,
measurefft=False):
M = chkM(M, g)
fft = fftp(measure=measurefft)
ifft = ifftp(measure=measurefft)
if real:
assert 0 <= reducedform <= 2
sl = slice(reducedform, len(g) // 2 + 1 - reducedform)
else:
sl = slice(0, None)
maxLg = max(
int(ceil(float(len(gii)) / mii)) * mii
for mii, gii in izip(M[sl], g[sl]))
temp0 = None
loopparams = []
for mii, gii, win_range in izip(M[sl], g[sl], wins[sl]):
Lg = len(gii)
col = int(ceil(float(Lg) / mii))
assert col * mii >= Lg
gi1 = gii[:(Lg + 1) // 2]
gi2 = gii[-(Lg // 2):]
p = (mii, gii, gi1, gi2, win_range, Lg, col)
loopparams.append(p)
if True or T is None:
def loop(temp0):
c = [] # Initialization of the result
# The actual transform
# TODO: stuff loop into theano
for mii, gii, gi1, gi2, win_range, Lg, col in loopparams:
# Lg = len(gii)
# if the number of time channels is too small (mii < Lg), aliasing is introduced
# wrap around and sum up in the end (below)
# col = int(ceil(float(Lg)/mii)) # normally col == 1
# assert col*mii >= Lg
temp = temp0[:col * mii]
# original version
# t = ft[win_range]*N.fft.fftshift(N.conj(gii))
# temp[:(Lg+1)//2] = t[Lg//2:] # if mii is odd, this is of length mii-mii//2
# temp[-(Lg//2):] = t[:Lg//2] # if mii is odd, this is of length mii//2
# modified version to avoid superfluous memory allocation
t1 = temp[:(Lg + 1) // 2]
t1[:] = gi1 # if mii is odd, this is of length mii-mii//2
t2 = temp[-(Lg // 2):]
t2[:] = gi2 # if mii is odd, this is of length mii//2
ftw = ft[win_range]
t2 *= ftw[:Lg // 2]
t1 *= ftw[Lg // 2:]
# (wh1a,wh1b),(wh2a,wh2b) = win_range
# t2[:wh1a.stop-wh1a.start] *= ft[wh1a]
# t2[wh1a.stop-wh1a.start:] *= ft[wh1b]
# t1[:wh2a.stop-wh2a.start] *= ft[wh2a]
# t1[wh2a.stop-wh2a.start:] *= ft[wh2b]
temp[(Lg + 1) // 2:-(Lg // 2)] = 0 # clear gap (if any)
if col > 1:
temp = N.sum(temp.reshape((mii, -1)), axis=1)
else:
temp = temp.copy()
c.append(temp)
return c
else:
raise RuntimeError("Theano support not implemented yet")
for f in f_slices:
Ls = len(f)
# some preparation
ft = fft(f)
if temp0 is None:
# pre-allocate buffer (delayed because of dtype)
temp0 = N.empty(maxLg, dtype=ft.dtype)
# A small amount of zero-padding might be needed (e.g. for scale frames)
if nn > Ls:
ft = N.concatenate((ft, N.zeros(nn - Ls, dtype=ft.dtype)))
# The actual transform
c = loop(temp0)
yield map(ifft,
c) # TODO: if matrixform, perform "2D" FFT along one axis
def nsigtf_sl(cseq,gd,wins,nn,Ls=None,real=False,reducedform=0,measurefft=False):
cseq = iter(cseq)
fft = fftp(measure=measurefft)
ifft = irfftp(measure=measurefft) if real else ifftp(measure=measurefft)
if real:
ln = len(gd)//2+1-reducedform*2
fftsymm = lambda c: N.hstack((c[0],c[-1:0:-1])).conj()
if reducedform:
# no coefficients for f=0 and f=fs/2
symm = lambda fc: chain(fc,imap(fftsymm,fc[::-1]))
sl = lambda x: chain(x[reducedform:len(gd)//2+1-reducedform],x[len(gd)//2+reducedform:len(gd)+1-reducedform])
else:
symm = lambda fc: chain(fc,imap(fftsymm,fc[-2:0:-1]))
sl = lambda x: x
else:
ln = len(gd)
symm = lambda fc: fc
sl = lambda x: x
maxLg = max(len(gdii) for gdii in sl(gd))
# get first slice
c0 = cseq.next()
fr = N.empty(nn,dtype=c0[0].dtype) # Initialize output
temp0 = N.empty(maxLg,dtype=fr.dtype) # pre-allocation
loopparams = []
for gdii,win_range in izip(sl(gd),sl(wins)):
Lg = len(gdii)
temp = temp0[:Lg]
wr1 = win_range[:(Lg)//2]
wr2 = win_range[-((Lg+1)//2):]
# wr1,wr2 = win_range
sl1 = slice(None,(Lg+1)//2)
sl2 = slice(-(Lg//2),None)
p = (gdii,wr1,wr2,sl1,sl2,temp)
loopparams.append(p)
if True or T is None:
def loop(fr,fc):
# The overlap-add procedure including multiplication with the synthesis windows
# TODO: stuff loop into theano
for t,(gdii,wr1,wr2,sl1,sl2,temp) in izip(symm(fc),loopparams):
t1 = temp[sl1]
t2 = temp[sl2]
t1[:] = t[sl1]
t2[:] = t[sl2]
temp *= gdii
temp *= len(t)
fr[wr1] += t2
fr[wr2] += t1
# wr1a,wr1b = wr1
# fr[wr1a] += t2[:wr1a.stop-wr1a.start]
# fr[wr1b] += t2[wr1a.stop-wr1a.start:]
# wr2a,wr2b = wr2
# fr[wr2a] += t1[:wr2a.stop-wr2a.start]
# fr[wr2b] += t1[wr2a.stop-wr2a.start:]
else:
raise RuntimeError("Theano support not implemented yet")
for c in chain((c0,),cseq):
assert len(c) == ln
fr[:] = 0.
fc = map(fft,c) # do transforms on coefficients - TODO: for matrixform we could do a FFT on the whole matrix along one axis
# The overlap-add procedure including multiplication with the synthesis windows
loop(fr,fc)
ftr = fr[:nn//2+1] if real else fr
sig = ifft(ftr,outn=nn)
sig = sig[:Ls] # Truncate the signal to original length (if given)
yield sig
def nsigtf_sl(cseq,
gd,
wins,
nn,
Ls=None,
real=False,
reducedform=0,
measurefft=False):
cseq = iter(cseq)
fft = fftp(measure=measurefft)
ifft = irfftp(measure=measurefft) if real else ifftp(measure=measurefft)
if real:
ln = len(gd) // 2 + 1 - reducedform * 2
fftsymm = lambda c: N.hstack((c[0], c[-1:0:-1])).conj()
if reducedform:
# no coefficients for f=0 and f=fs/2
symm = lambda fc: chain(fc, imap(fftsymm, fc[::-1]))
sl = lambda x: chain(
x[reducedform:len(gd) // 2 + 1 - reducedform], x[len(
gd) // 2 + reducedform:len(gd) + 1 - reducedform])
else:
symm = lambda fc: chain(fc, imap(fftsymm, fc[-2:0:-1]))
sl = lambda x: x
else:
ln = len(gd)
symm = lambda fc: fc
sl = lambda x: x
maxLg = max(len(gdii) for gdii in sl(gd))
# get first slice
c0 = cseq.next()
fr = N.empty(nn, dtype=c0[0].dtype) # Initialize output
temp0 = N.empty(maxLg, dtype=fr.dtype) # pre-allocation
loopparams = []
for gdii, win_range in izip(sl(gd), sl(wins)):
Lg = len(gdii)
temp = temp0[:Lg]
wr1 = win_range[:(Lg) // 2]
wr2 = win_range[-((Lg + 1) // 2):]
# wr1,wr2 = win_range
sl1 = slice(None, (Lg + 1) // 2)
sl2 = slice(-(Lg // 2), None)
p = (gdii, wr1, wr2, sl1, sl2, temp)
loopparams.append(p)
if True or T is None:
def loop(fr, fc):
# The overlap-add procedure including multiplication with the synthesis windows
# TODO: stuff loop into theano
for t, (gdii, wr1, wr2, sl1, sl2,
temp) in izip(symm(fc), loopparams):
t1 = temp[sl1]
t2 = temp[sl2]
t1[:] = t[sl1]
t2[:] = t[sl2]
temp *= gdii
temp *= len(t)
fr[wr1] += t2
fr[wr2] += t1
# wr1a,wr1b = wr1
# fr[wr1a] += t2[:wr1a.stop-wr1a.start]
# fr[wr1b] += t2[wr1a.stop-wr1a.start:]
# wr2a,wr2b = wr2
# fr[wr2a] += t1[:wr2a.stop-wr2a.start]
# fr[wr2b] += t1[wr2a.stop-wr2a.start:]
else:
raise RuntimeError("Theano support not implemented yet")
for c in chain((c0, ), cseq):
assert len(c) == ln
fr[:] = 0.
fc = map(
fft, c
) # do transforms on coefficients - TODO: for matrixform we could do a FFT on the whole matrix along one axis
# The overlap-add procedure including multiplication with the synthesis windows
loop(fr, fc)
ftr = fr[:nn // 2 + 1] if real else fr
sig = ifft(ftr, outn=nn)
sig = sig[:Ls] # Truncate the signal to original length (if given)
yield sig
