I have some working python code making use of the numpy.fft package, here is a snippet:
for i in range(steps):
print i
psixvec = Ux * psixvec
psikvec = Uk * np.fft.fftn(psixvec)
psixvec = np.fft.ifftn(psikvec)
return psixvec
I tried to rewrite this code to make use of the pyfftw
package. What I came up with is the following code, which should work:
fft = fftw.builders.fftn(psix_align, auto_align_input = True, auto_contiguous = True,
overwrite_input = False, threads = 1, avoid_copy = False)
ifft = fftw.builders.ifftn(psik_align, auto_align_input = True, auto_contiguous = True,
overwrite_input = False, threads = 1, avoid_copy = False)
for i in range(steps):
psix_align[:] = Ux * psix_align
psik_align[:] = Uk * fft()
psix_align[:] = ifft()
return psix_align
The problem is, this code does not produce the same result as using the numpy.fft
package. See the attached images.
Solved. For the initialization I was using
psix_align = fftw.n_byte_align(psi0, fftw.simd_alignment, dtype='complex64')
psik_align = fftw.n_byte_align(np.zeros_like(psi0), fftw.simd_alignment, dtype='complex64')
I needed to replace complex64
with complex128
. Now I get the same result. That's probably due to the fact that the numbers involved are very small (see the 1e-11
on the z-axis).
Edit: Maybe someone can add pyfftw
to the tags of the question?