[Numpy-discussion] second 2d fft gives the same result as fft+ifft

Béla MIHALIK bela.mihalik@gmail....
Wed Jun 10 10:53:31 CDT 2009


I made the transformations with scipy. It works with complex numbers.
The results are here:

http://server6.theimagehosting.com/image.php?img=second_fourier_scipy.png

Also i asked it from others... as i understand now: the second fourier
transformation of a function always gives back the mirror of the function
itself.
I didn't know it :-)

thanks,
   bela


2009/6/9 David Goldsmith <d_l_goldsmith@yahoo.com>

>
> Sorry, I meant:
>
>      Im(iFT(FT(f))) = Im(FT^2(f)), Re(iFT(FT(f))) != Re(FT^2(f))
>
> DG
>
> --- On Tue, 6/9/09, David Goldsmith <d_l_goldsmith@yahoo.com> wrote:
>
> > From: David Goldsmith <d_l_goldsmith@yahoo.com>
> > Subject: Re: [Numpy-discussion] second 2d fft gives the same result as
> fft+ifft
> > To: "Discussion of Numerical Python" <numpy-discussion@scipy.org>
> > Date: Tuesday, June 9, 2009, 11:01 AM
> >
> > --- On Tue, 6/9/09, Matthieu Brucher <matthieu.brucher@gmail.com>
> > wrote:
> >
> > > Hi,
> > >
> > > Is it really ?
> > > You only show the imaginary part of the FFT, so you
> > can't
> > > be sure of
> > > what you are saying.
> >
> > Indeed, is there not a "label" for a function f which
> > satisfies
> >
> >      Im(iFFT(f)) = Im(FFT^2(f)),
> > Re(iFFT(f)) != Re(FFT^2(f))?
> >
> > (And similarly if Im and Re roles are reversed.)
> > Seems like the class of such functions (if any exist) might
> > have some interesting properties...
> >
> > DG
> >
> > > Don't forget that the only difference between FFT and
> > iFFT
> > > is (besides
> > > of teh scaling factor) a minus sign in the exponent.
> > >
> > > Matthieu
> > >
> > > 2009/6/9 bela <bela.mihalik@gmail.com>:
> > > >
> > > > I tried to calculate the second fourier
> > transformation
> > > of an image with the
> > > > following code below:
> > > >
> > > >
> > >
> > ---------------------------------------------------------------
> > > > import pylab
> > > > import numpy
> > > >
> > > > ### Create a simple image
> > > >
> > > > fx = numpy.zeros( 128**2
> > ).reshape(128,128).astype(
> > > numpy.float )
> > > >
> > > > for i in xrange(8):
> > > >        for j in xrange(8):
> > > >                fx[i*8+16][j*8+16] = 1.0
> > > >
> > > > ### Fourier Transformations
> > > >
> > > > Ffx = numpy.copy( numpy.fft.fft2( fx ).real )
> > # 1st
> > > fourier
> > > > FFfx = numpy.copy( numpy.fft.fft2( Ffx ).real )
> >  #
> > > 2nd fourier
> > > > IFfx = numpy.copy( numpy.fft.ifft2( Ffx ).real )
> >   #
> > > inverse fourier
> > > >
> > > > ### Display result
> > > >
> > > > pylab.figure( 1, figsize=(8,8), dpi=125 )
> > > >
> > > > pylab.subplot(221)
> > > > pylab.imshow( fx, cmap=pylab.cm.gray )
> > > > pylab.colorbar()
> > > > pylab.title( "fx" )
> > > >
> > > > pylab.subplot(222)
> > > > pylab.imshow( Ffx, cmap=pylab.cm.gray )
> > > > pylab.colorbar()
> > > > pylab.title( "Ffx" )
> > > >
> > > > pylab.subplot(223)
> > > > pylab.imshow( FFfx, cmap=pylab.cm.gray )
> > > > pylab.colorbar()
> > > > pylab.title( "FFfx" )
> > > >
> > > > pylab.subplot(224)
> > > > pylab.imshow( IFfx, cmap=pylab.cm.gray )
> > > > pylab.colorbar()
> > > > pylab.title( "IFfx" )
> > > >
> > > > pylab.show()
> > > >
> > >
> > ---------------------------------------------------------------
> > > >
> > > > On my computer FFfx is the same as IFfx..... but
> > why?
> > > >
> > > > I uploaded a screenshot about my result here:
> > > > http://server6.theimagehosting.com/image.php?img=second_fourier.png
> > > >
> > > > Bela
> > > >
> > > >
> > > > --
> > > > View this message in context:
> http://www.nabble.com/second-2d-fft-gives-the-same-result-as-fft%2Bifft-tp23945026p23945026.html
> > > > Sent from the Numpy-discussion mailing list
> > archive at
> > > Nabble.com.
> > > >
> > > > _______________________________________________
> > > > Numpy-discussion mailing list
> > > > Numpy-discussion@scipy.org
> > > > http://mail.scipy.org/mailman/listinfo/numpy-discussion
> > > >
> > >
> > >
> > >
> > > --
> > > Information System Engineer, Ph.D.
> > > Website: http://matthieu-brucher.developpez.com/
> > > Blogs: http://matt.eifelle.com and http://blog.developpez.com/?blog=92
> > > LinkedIn: http://www.linkedin.com/in/matthieubrucher
> > > _______________________________________________
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> > >
> >
> >
> >
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