def test_fftfilt_nd():
np.random.seed(123)
x = np.random.randn(2**16) + 1j * np.random.randn(2**16)
b = np.random.randn(128)
oned = fftfilt.fftfilt(b, x)
nd = fftfilt.fftfilt_nd(b, x[:, None]).squeeze()
assert np.allclose(oned, nd)
x = x.reshape((2**12, 2**4))
oned = np.zeros_like(x)
for k in range(16):
oned[:, k] = fftfilt.fftfilt(b, x[:, k])
nd = fftfilt.fftfilt_nd(b, x)
assert np.allclose(oned, nd)
def process(self,data,continuation=True, use_fft=True):
data = data.reshape((data.shape[0]//self.downsample_factor,self.downsample_factor))
if use_fft:
result = fftfilt.fftfilt_nd(self.coefficients,data)
else:
result = np.empty_like(data)
for k in range(self.downsample_factor):
result[:,k] = scipy.signal.lfilter(self.coefficients[:,k],1,data[:,k])
#result[:,k] = np.convolve(self.coefficients[:,k],data[:,k],mode='same')
return result.sum(1)
