def ifftvec(vec):
"""
performs a fft on a vector with 3 components in the last index position
This is a wrapper for ifft and ifftn
"""
try:
from anfft import ifft, ifftn
fft_type = 1
except:
# print "Could not import anfft, importing scipy instead."
#Update 9/18/2013 -- numpy with mkl is way faster than scipy
import mkl
mkl.set_num_threads(8)
from numpy.fft import ifft, ifftn
fft_type = 0
if force_gpu:
fft_type = 2 #set gpu fft's manually -- not sure what a automatic way would look like
from numpy import float32, real, array, empty, complex64
if vec.ndim > 2:
if vec.shape[0] == 3:
# "Vector": first index has size 3 so fft the other columns
if fft_type==1:
return array([ifftn(i,measure=True) for i in vec]).astype(float32)
# result = empty(vec.shape, dtype=float32)
# result[0] = real(ifftn(vec[0], measure=True)).astype(float32)
# result[1] = real(ifftn(vec[1], measure=True)).astype(float32)
# result[2] = real(ifftn(vec[2], measure=True)).astype(float32)
# return result
elif fft_type==0:
return ifftn(vec, axes=range(1,vec.ndim)).astype(float32)
elif fft_type==2:
# return array([gpu_ifft(i) for i in vec]).astype(float32)
result = empty(vec.shape, dtype=float32)
result[0] = gpu_ifft(vec[0].copy()).astype(float32)
result[1] = gpu_ifft(vec[1].copy()).astype(float32)
result[2] = gpu_ifft(vec[2].copy()).astype(float32)
return result
else: # "Scalar", fft the whole thing
if fft_type==1:
return ifftn(vec,measure=True).astype(float32)
elif fft_type==0:
return ifftn(vec).astype(float32)
elif fft_type==2:
return gpu_ifft(vec.copy()).astype(float32)
elif vec.ndim == 1: #Not a vector, so use fft
if fft_type==1:
return ifft(vec,measure = True).astype(float32)
elif fft_type==0:
return ifft(vec).astype(float32)
elif fft_type==2:
return gpu_ifft(vec).astype(float32)
else:
#0th index is 3, so its a vector
#return fft(vec, axis=1).astype(complex64)
return array([ifft(i) for i in vec]).astype(float32)
t1 = time.time()
for i in range(Ntest):
b2 = scifft.fft(a0)
a1 = scifft.ifft(b2)
t1b = time.time()
print(np.sum(a1))
t2 = time.time()
for i in range(Ntest):
b3 = anfft.fft(a0)
a2 = anfft.ifft(b3)
t2b = time.time()
print(np.sum(a2))
t3 = time.time()
# create a forward and backward fft plan
a = fftw3.create_aligned_array(a0.shape, np.complex128, 16)
b = fftw3.create_aligned_array(a0.shape, np.complex128, 16)
c = fftw3.create_aligned_array(a0.shape, np.complex128, 16)
a[:] = a0
ft3fft = fftw3.Plan(a, b, direction="forward", flags=["measure"])
ft3ifft = fftw3.Plan(b, c, direction="backward", flags=["measure"])
t1 = time.time()
for i in range(Ntest):
b2 = scifft.fft(a0)
a1 = scifft.ifft(b2)
t1b = time.time()
print np.sum(a1)
t2 = time.time()
for i in range(Ntest):
b3 = anfft.fft(a0)
a2 = anfft.ifft(b3)
t2b = time.time()
print np.sum(a2)
t3 = time.time()
# create a forward and backward fft plan
a = fftw3.create_aligned_array(a0.shape, np.complex128, 16)
b = fftw3.create_aligned_array(a0.shape, np.complex128, 16)
c = fftw3.create_aligned_array(a0.shape, np.complex128, 16)
a[:] = a0
ft3fft = fftw3.Plan(a, b, direction='forward', flags=['measure'])
ft3ifft = fftw3.Plan(b, c, direction='backward', flags=['measure'])
#rate2,sig2 = wavfile.read('balloon.wav')
#m = sig2.shape[0]
#sig1 = sp.append(sig1,sp.zeros((m,2)),axis = 0)
#sig2 = sp.append(sig2,sp.zeros((sig1.shape[0] - m,2)),axis = 0)
#f1 = anfft.fft(sig1.T).T
#f2 = anfft.fft(sig2.T).T
#out = anfft.ifft((f1*f2).T).T
#out = sp.real(out)
#scaled = sp.int16(out/sp.absolute(out).max() * 32767)
#wavfile.write('test.wav',44100,scaled)
#==============================================================================
# PROBLEM 4
#==============================================================================
#samplerate = 22050
#noise = sp.int16(sp.random.randint(-32767,32767,samplerate*10)) # Create 10 seconds of mono white noise
#wavfile.write('white_noise.wav',22050,noise)
#f = anfft.fft(sp.float32(noise))
#plt.plot(sp.absolute(f))
#plt.show()
#==============================================================================
# PROBLEM 5
#==============================================================================
rate, sig = wavfile.read('tada.wav')
sig = sp.float32(sig)
noise = sp.float32(sp.random.randint(-32767,32767,sig.shape))
out = anfft.ifft(anfft.fft(sig.T)*anfft.fft(noise.T)).T
out = sp.real(out)
out = sp.int16(out/sp.absolute(out).max() * 32767)
wavfile.write('white-conv.wav',rate,out)