there seems to be some undocumented restriction on dimensions as when I work with 512x512 data things work as expected.
On 12/29/2011 09:43 AM, Torgil Svensson wrote: > Sorry, i should have looked at your image. A few test you can do is > > 1) does ifft2 give you back the original image? (allclose returned > True for a little test I did here) > 2) does scipy.fftpack.fft2 yield the same result? > > //Torgil > > > On Thu, Dec 29, 2011 at 6:32 PM, Burlen Loring<burlen.lor...@gmail.com> > wrote: >> hmmph, I used both fftn and fft2, they both produce the same result. Is >> there a restriction on the dimension of the input? power of 2 or some such? >> >> On 12/29/2011 07:21 AM, Torgil Svensson wrote: >>> This is because fft computes one-dimensional transforms (on each row). >>> Try fft2 instead. >>> >>> //Torgil >>> >>> >>> fft(a, n=None, axis=-1) >>> Compute the one-dimensional discrete Fourier Transform. >>> >>> fft2(a, s=None, axes=(-2, -1)) >>> Compute the 2-dimensional discrete Fourier Transform >>> >>> fftn(a, s=None, axes=None) >>> Compute the N-dimensional discrete Fourier Transform. >>> >>> >>> On Wed, Dec 28, 2011 at 10:05 PM, Burlen Loring<burlen.lor...@gmail.com> >>> wrote: >>>> Hi >>>> >>>> I have an image I need to do an fft on, I tried numpy.fft but results are >>>> not what I expected, and differ from matlab. >>>> >>>> My input image is a weird size, 5118x1279, I think numpy fft is not liking >>>> it. In >>>> numpy the fft appears to be computed multiple times and tiled across the >>>> output image. In other words the pattern I see in matlab fft is tiled >>>> repeatedly over numpy fft output. Any idea on what I'm doing wrong? >>>> >>>> you can see repeated pattern in the top panel of this image which also has >>>> the input in the bottom panel. >>>> http://old.nabble.com/file/p33047057/fft_uex.png fft_uex.png >>>> >>>> tx >>>> >>>> _______________________________________________ >>>> NumPy-Discussion mailing list >>>> NumPy-Discussion@scipy.org >>>> http://mail.scipy.org/mailman/listinfo/numpy-discussion >>> _______________________________________________ >>> NumPy-Discussion mailing list >>> NumPy-Discussion@scipy.org >>> http://mail.scipy.org/mailman/listinfo/numpy-discussion >> _______________________________________________ >> NumPy-Discussion mailing list >> NumPy-Discussion@scipy.org >> http://mail.scipy.org/mailman/listinfo/numpy-discussion > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
